NETWORK RELATIONS AND STARTUPS APRIL 2013

Transkript

1 NETWORK RELATIONS AND STARTUPS - Bridging the muddy waters between Effectuation and Entrepreneurship Theory APRIL 2013 MASTER THESIS Lasse Grosen Jensen Brian Langarica Nielsen MSc in Management of Innovation & Business Development Supervisor: Nicolaj Højer Nielsen Department of Marketing Number of pages: 120 Character count:

2 ABSTRACT Early-stage ventures are characterised by their limited resources (Stinchcombe, 1965; Baum, 1996) and acting in an environment characterised by Knightian Uncertainty (Knight, 1921). To accommodate for their limited resources, research has shown that engaging with network relations can provide valuable resources for a startup. Only to a limited degree has research empirically shed light on further qualifying what resources the early-stage entrepreneurs seek externally. We also lack academic knowledge on how entrepreneurs engage with their network relations. Hence, this research paper focused on the network relations of early-stage startups, in relation to what resources they provide, and how these relationships have been engaged. Research on network types and the reasoning for engaging represent two different strings of literature. Therefore, these were initially assessed individually, as to allow for an in-depth understanding of the related concepts. The main objective of the project was to explore the link between these strings of literature, namely the network types with the reasoning for engaging. We collected empirical data in several rounds of interviews from four case companies within the industry of Information and Communication Technology (ICT). This led to interesting findings, both within the individual analysis of network types and reasons for engaging, respectively, but also for the link between these. For exploring network types, this paper adopted a typology by Lechner and Dowling (2003). The typology has empirical strength in its direct association of the four network types with relation to resources. We found that the early-stage startups mainly engaged in network relations that provided marketing and reputational resources, while also engaging in technology relations. Investigating the reasoning for startup s relation engagement, this paper applied the four principles of effectuation, an emerging entrepreneurship theory (Sarasvathy, 2001, 2008). As the principles have not previously been applied for the purpose of investigating the reasoning for engaging in relationships, this study was a first attempt. This led to interesting findings, as all four principles were represented in our findings. Linking the two theoretical concepts, it was found that the framework could be explanatory. The empirical findings, however, gave rise to a discussion, as there were pronounced limitations within the framework. Namely, some interesting findings were not captured in the framework. This thesis nonetheless contributed to the field with a first attempt to operationalize the effectuation principles, in relation to network types. The findings furthermore lead to interesting reflections for the limitation of the framework, serving as important insights for future research. 1

3 TABLE OF CENTENT ABSTRACT... 1 TABLE OF CENTENT... 2 LIST OF TABLES INTRODUCTION Introduction Delimitations Outline METHODOLOGY Philosophy of Science Research Method Research Design Definitions Empirical Data Evaluation of the Research Process LITERATURE REVIEW The Life Cycle of the Entrepreneurial Venture A Typology of Network Relations Defining and Exploring the Typology Effectuation Theory CONCEPTUAL FRAMEWORK Introduction Types of Network Relations Principles for Engaging Linking Network Relations and Effectual Principles ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Introduction Tradeshift Echo.it Billy s Billing Opeepl Cross Case Analysis

4 6. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Introduction Tradeshift Echo.it Echo.it Main Findings Billy s Billing Opeepl Opeepl Main Findings Cross Case Analysis ANALYSIS PART 3 NETWORK RELATIONS AND PRINCIPLES FOR ENGAGING Introduction Reputational Network Relations Marketing Network Relations Co-opetition Network Relations Technology Network Relations DISCUSSION Introduction Types of Networks Principles of Effectuation Limitations of the Study CONCLUSION Field of Study Types of Network Relations Principles for Engaging Linking Network Types and Principles for Engaging REFERENCES APPENDIX Appendix Overview

5 LIST OF TABLES Table 1. Outline of the study...10 Table 2. Case Companies...21 Table 3. Overview of literature on life cycle stages, limited to early stage startups...27 Table 4. Typologies of network relations of the entrepreneurial venture...31 Table 5. Effectuation principles as origins and strategic conditions...54 Table 6. Network relations of Tradeshift, according to type...69 Table 7. Network relations of Echo.it, according to type...74 Table 8. Network relations of Billy's Billing, according to type...78 Table 9. Network relations of Opeepl, according to type...82 Table 10. Overview of network relations of all case companies...83 Table 11. Network relations of Tradeshift, according to reasoning for engaging...91 Table 12. Network relations of Echo.it, according to reasoning for engaging...95 Table 13. Network relations of Billy's Billing, according to reasoning for engaging...98 Table 14. Network relations of Opeepl, according to reasoning for engaging Table 15. Reasoning for engaging in network relations, across cases

6 1. INTRODUCTION Introduction Research Question Setting The Scene Delimitations Outline This chapter provides an introduction into the overarching topic, leading up to the field of research and the purpose of the thesis. We present the main research question and sub-questions that explain our approach. We construct the scope of the study through delimitation. Finally, we present a model depicting the structure of the paper. 5

7 1.1. Introduction Entrepreneurship has gained momentum and recognition as an important driver of our economy, ever since it was recognized by Schumpeter (1921), when he called entrepreneurship the fourth driver of the economy. Our knowledge within the field of entrepreneurship has significantly improved as research within the field gained momentum in the early 1990s. However, we are still lacking an academic understanding of the central elements which could potentially guide entrepreneurs to make better decisions. The focus of this study is to provide insights into the field which could further develop our understanding of the entrepreneurial decision making process and critical factors of entrepreneurial success. Startups are characterized by three key elements. First, startups face a high degree of uncertainty known as Knightian Uncertainty, which entails that for startup companies the future is not merely unknown, but essentially unknowable (Knight, 1934). Second, a startup is also characterized by its lack of resources - time, money, etc. - termed the liability of smallness (Stinchcombe, 1965), and third, a lack of reputation in the market, termed the liability of newness (Baum, 1996). These elements constitute challenges which startups particularly face in the early stages of the startup. Hence, relying solely on internal resources will most likely lead to recurring bottleneck issues. To address these fundamental issues of entrepreneurship, it has been argued that engaging in cooperative behavior can be a method to acquire the specific resources that startups need (Dickson, Weaver, and Hoy, 2006). Basing one s resource needs on external networks can be considered an alternative model of organization for the startup (Richardson, 1972), as it is based on inter-organizational activities (Nohria 1992). In this context, a broad consensus has emerged within entrepreneurship research that networks play a key role in successful firm emergence by functioning as potentially valuable providers of resources (Aldrich and Reese, 1993; Ostgaard and Birley, 1994; Hansen, 1995; Stuart Hoang and Hybels, 1999; Hite and Hesterly, 2001; Jensen and Koenig, 2002). Empirical research underpins this point, showing that networking can improve growth and success in small firms (Chell and Baines, 2000; Huggins, 2000; Jarillo, 1988, 1989). These startup network relations can take many forms, ranging from weak ties to strong ties (Granovetter, 1973), implying a range of relations that all address startups diverse resource needs. Engaging in network relations necessitates that a startup devote internal resources, in order to reap the benefits of the relationship. As network commitments take up resources from the startup, it also limits the quantity of relations a startup can maintain and the resource allocation for each relation. Startups are characterized by their limited resources (Stinchcombe, 1965), and thus engaging in network commitments INTRODUCTION Introduction 6

8 is considered a strategic decision: it entails how the startup manages its own resources. This strategy might both be implicit or explicit. As startups apply resources by engaging in external relationships, it becomes important to be aware of which type of resources the relationships brings to the startup in order to make the most of the potential of each network relation. Furthermore, research has shown that the resource needs for startups change over time, why an important consideration, is what resources are needed at what developmental stage of the venture (Butler and Hansen, 1991; Lechner and Dowling, 2003; Lechner et al., 2006). We therefore argue that entrepreneurs should enter external relations with a strategic focus, as to not waste valuable internal resources. This implies that the startup should prioritize its network commitments in relation to its specific resource needs. Since limited knowledge exists about the specific kind of relations exploited by startups (Lechner et al, 2006), we find this research topic interesting to explore further. We assume that behind every network relation engaged lies a decision making process, whether explicit or implicit. Research within this field is highly limited, which is an obstacle in terms of building on existing knowledge, but also a great opportunity for further exploring the field. We therefore set out to understand what decision making factors are evident to explain startups engagement with external relation, to further grasp the underlying mechanisms of startups, which is a central element of entrepreneurship research (Sarasvathy and Dew, 2005) Research Question The essential element we will explore within the boundaries outlined above is to find patterns in the startups type of relations and the principles which the startup bases their network engagement relations on. Attempting to understand these underlying mechanisms, or principles, for how startups engage in their relations could provide valuable insights for future research within the field. This implies studying both which network relations startups engage in, and furthermore, how they do so. This has led us to explore the following research question: How do early-stage Danish SaaS startups engage in the network types they do? To answer this research question, we divide this study into three parts. First, related to the network types, we will investigate what network relations startups engage in. Second, we will apply relevant entrepreneurship literature, to provide possible explanatory factors for how network relations are engaged. Third, we will combine the first and second part, as to seek to answer if there are relations between the network types and reasoning for engaging. INTRODUCTION Introduction 7

9 Setting the Scene To answer this research question and, we conducted a multiple case study based on several interviews with four aspiring early-stage Danish startups. These startups all operate within the information and communications technology (ICT) industry, and more specifically, the sub-industry known as Software-as-a- Service (SaaS). SaaS companies are characterized by providing an internet-based service where the customer interacts with a type of fully automated software. This thesis is built on assumptions, entailing that under conditions of uncertainty, entrepreneurs adopt a decision logic that is different to that explicated by a traditional, more rational model of entrepreneurship (called causation in Sarasvathy s writings) (Fisher, 2012: 1024). This is the belief that serves as a basis for the emerging effectuation theory (Sarasvathy, 2001, 2008). At its core, effectuation theory differentiates prediction and control, arguing that early-stage startups are characterized by Knightian Uncertainty (Knight, 1934), whereby they should emphasize control rather than prediction. Hence, the theory is a logic of how entrepreneurs make decisions particular for early-stage startups, which is also the focus of this study. The essence of the effectual logic has been described with four principles (Fisher, 2012), and contrasts causal reasoning (Sarasvathy, 2001). These factors apply broadly in the decision situations faced by an entrepreneur. In this study, they will be studied in relation to the decision making of engaging in external relations. To our knowledge, effectuation theory remains the only theory which argues for specific principles on which expert entrepreneurs base their decisions. The framework developed in this thesis is an attempt to further develop our understanding of how startups engage in network relations, in light of the effectuation theory, and to study the relation between effectual factors and types of network relations. Within effectuation theory, it has been argued that precisely the network relations of the startup, is the most important resource to exploit (Sarasvathy, 2008). This underpins earlier research (eg. Stuart Hoang and Hybels, 1999; Hite and Hesterly, 2001). We are of the belief that this study can serve as a first step toward a more strategic approach to how entrepreneurs can utilize their limited resources optimally, for engaging in external relationships. By focusing on what resources relationships bring to the startup, we intend to bring building blocks to effectuation theory, by bridging it with existing theoretical constructs of network theory. This visional approach, we hope, can serve to operationalize effectuation, which until now is argued not to be a toolbox (Sarasvathy, 2008). We recognize that effectuation theory has not yet been established as a main theoretical view, unlike traditional views such as the Resource-Based View (Wernerfelt, 1984; Barney, 1991), The Relational View (Dyer and Singh, 1998) and Transaction Cost Economics (Williamson, 1975). However, as an emerging INTRODUCTION Introduction 8

10 theoretical construct, effectuation theory is still in a nascent developmental phase (Perry et al, 2012). We acknowledge the youth of effectuation. Despite its youth we find the view highly interesting, as it represents a paradigmatic shift in the way that we understand entrepreneurship (Perry et al, 2012: 838). In section 3.4.3, effectuation theory as an emerging theory is further discussed Delimitations The purpose of this section is to narrow down the scope of inquiry of the research question. This study does not look into network structure of the entrepreneur or the startup, but focus on dyadic relations from an egocentric perspective. Hence, we adopt the definition of Lechner et al. (2006: 515), focusing on value-added networks that go beyond exclusively economic relationships. In this study of network relationships, we have chosen to concentrate the efforts within the Danish SaaS industry, which narrows down the field of inquiry. We refer to the section on industry selection (2.3.5) for the reasoning behind this choice. The findings can be argued only to be applicable to this industry. However, as the SaaS industry is a subdivision of the broader ICT (Information Communication and Technology) it can be implied that the findings will have some degree of relevance in a broader perspective. As all case companies, and employees, are based in Copenhagen, the geographic scope of this thesis is limited to the context of Denmark. While we do have a focus on the resources which the partnerships contribute with to the startup it is not a focal point of study in this thesis. We merely identify and accept empirical findings signifying which value adding resources the external relationships contribute with. Hence we have no intention of including contributions from the Resource Based View discussing their ability to create competitive advantages (Penrose, 1959; Barney, 1991) which also excludes the Relational View (Dyer and Singh, 1998). In order to maintain a clear cut focus we also limit ourselves to investigate the early-stage of ventures life cycle, which is further discussed and defined in section 3.1. INTRODUCTION Delimitations 9

11 1.3. Outline The following figure depicts the approach taken in the current study. Table 1. Outline of the study Research question Methodology Philosophy of Science Research Design Empirical Approach Theoretical Point of Departure Conceptual Framework Types of Network Relations Effectual Principles as Explanatory for Engagement Linking Network Types and Reasons for Engagement Tradeshift Echo.IT Billy s Billing Opeepl Analysis Diskussion Conclusion Source: Own development INTRODUCTION Outline 10

12 2. METHODOLOGY Philosophy of Science Research Method Research Design Definitions Empirical Data Evaluation of the Research Process In this chapter, we first introduce the philosophical foundation for the thesis. The research method and design are explained and we discuss the empirical data selection. The chapter also conducts an evaluation of the research process. 11

13 2.1. Philosophy of Science The discussion of theory of science is of great importance in the creation of academic literature in many cases while in the current study, we believe the discussion is important as one of our main objectives is to bridge two different bodies of knowledge which are based on different assumptions. We are aware of the potential issues which such an approach can lead to, as noted by Kaplan (1964). It can be problematic to borrow from different theories if the understanding of the theoretical roots are not clear, which can have negative impact on future research. If we failed to state our standpoint, it could lead to misunderstandings and impede the quality of this study. Beneath, we will provide a short description of the theoretical foundations upon which this study is built. The two relevant sets of assumptions are the rational decision process in contrast with Knightian Uncertainty (Knight, 1921). The rational decision making process is a foundation for much classic and contemporary entrepreneurship literature (Gaglio and Katz, 2001; Shane, 2003; Venkataraman, 2003). This includes entrepreneurship network theory which is part of the analytical framework of the current study. The reason for this connection is found due to the adoption of neo-classical economic theory into entrepreneurship as an academic field, which is also based on rational decision making (Perry et al, 2012). Rational decision making theory is occupied with finding the one right solution to a given problem through a staged process of evaluating alternatives based on sufficient data until the optimal one is found (Dawson, 1986; Minkes, 1987). It requires that goals and preferences are known when information is widely available (Simon, 1979). Causal reasoning, which is argued to be the inverse of effectual reasoning, draws clear parallels to rational decision making (Sarasvathy, 2008). Effectuation theory is, by contrast, occupied with maneuvering in conditions of Knightian Uncertainty (Knight, 1921) which do not offer an arena where the assumptions underlying a rational decision making process is present. Knight (1921) distinguished between uncertainty and risk, arguing that risk is measurable while uncertainty is not. Uncertainty, therefore, represents a state of reality where the rational decision mechanisms are set out of order, calling for novel approaches, which effectuation contributes to (Sarasvathy, 2008). In social sciences, there is a range of approaches instrumental for the understanding and perception of the world and reality. Within these views are different rule sets dictating how the construction of knowledge is supposed to occur. Positivism is one of the most recognized and distinguishable ideas of how social sciences shall be conducted. It is believed that the social world can be said to exist externally of reality, meaning that reality METHODOLOGY Philosophy of Science 12

14 can be observed isolated from human interaction, thus calling for objective methods of research (Easterby- Smith, Thorpe and Jackson, 2008). The positivist perspective seeks to develop precise measures that will find dimensions of reality sought. In other words, it is thought that already existing fixed relationships are evident and can be identified. Positivism is mainly related to into entrepreneurship literature regarding opportunities as existing, ready for discovery. Effectuation, which figures as the main theoretical framework of this paper, takes the opposite position by assuming that opportunities are created. It is instead coherent with a pragmatic epistemological view (Sarasvathy, 2008). Pragmatism is largely indefinable (Papini, 1927), yet there is some consensus around it. Pragmatism is concerned about how things work, while the objective of getting insight in a cosmic reality is less important. In general terms, applying a pragmatic approach to this study implies that our goal is not to discover a monolithic idea of truth, but instead to verify a certain analytical framework in order to better understand the mechanisms underlying the commitment to network relations. Therefore, it can also be said that the choice of applying two different bodies of knowledge to study a certain field of entrepreneurship according to their immediate fit, rather than respecting underlying assumptions, is a pragmatic action. Hence, in this study we apply a pragmatic view. We do not dedicate ourselves to any particular epistemology, but instead place ourselves in a continuum, where we use what works to study our research question. The literature strings applied are based on diverging assumptions, but we will still test the applicability. This both with the goal of shedding light over the complex nature of external relations of companies and humans in a business perspective. Thus, we also argue that different assumptions underlying the theory utilized in this paper are not our main focus. We recognize them, but we do not necessarily take them into consideration in the subsequent sections Research Method Qualitative Research Method We adopted a qualitative research approach, which is appropriate for this study that explores the social phenomena of egocentric network relations in startups, and the underlying principles of why and how the relations are engaged. Adopting a qualitative research approach implies a focus on the "... objective analysis of subjective meaning" (Erickson, 1986). The qualitative research methods are characterized by their focus on exploring and subsequently explaining the world through observation and by appreciating social actors experiences. In the light of the research question, exploring an under-researched area of METHODOLOGY Research Method 13

15 social phenomena, the explorative and flexible nature of qualitative research has proved to be appropriate and efficient (Eisenhardt, 1989; Ghauri and Gronhaug; 2002). Underpinning this, it has been shown that qualitative research has contributed to a better understanding of issues, which have remained unclear through quantitative research (Eriksson and Kovalainen, 2008) Multiple Case Study Research Design The central purpose of this paper is to shed light on egocentric network relations, and to take initial steps in developing a theory across existing entrepreneurship bodies of knowledge. The methodological approach is based on a multiple case study. For this purpose, we adopted the methodological framework of Eisenhardt (1989), which provides a comprehensive explanation of the process. The application of a research design of multiple case studies is adequate for our purpose, as the aim is to investigate a contemporary phenomenon in depth and within its real life context, especially when the boundaries between the phenomenon and context are not clearly evident (Yin, 2003: 13). Though the qualitative method has been dismissed by critics within social sciences who question the rigor of the approach, case studies as a research method have become widely accepted (Eisenhardt, 1989; Lee, 1989; Miles and Huberman, 1994; Yin, 1994, 2003). By investigating social phenomena, the case study method has particular strength in its ability to explain the presumed causal links in real-life interventions that are too complex for the survey or experimental strategies (Yin, 2003). Furthermore, by applying a case study method, the reasoning behind decisions can be illuminated (Yin, 2003). This is a central point, as we are empirically shedding light on the strategic reasoning for the case companies to engage with their network commitments. It is recommended by Eisenhardt (1989) that 4-10 cases are included in a multiple case study, and that all the cases have the same importance. This paper uses four in-depth cases as the empirical grounds for the research, meeting the requirements set by Eisenhardt (1989). Each case is based on in-depth desk research, interviews and company visits. When building theory, the results from the empirical investigations should be verifiable (Eisenhardt, 1989), which is why we base our propositions on existing knowledge within the field. We believe this enhances the verifiability of our findings Research Design Operationalization of Theory Conducting a multiple case study, the theory development prior to the collection of any case study data is an essential step in doing case studies ( ) a good case study investigator should make the effort to develop the theoretical framework (Yin, 2003: 29). We review existing literature within the relevant METHODOLOGY Research Design 14

16 entrepreneurship lines of study, as to provide a solid theoretical background. After reviewing the relevant literature strings, we condense this into an analytical framework, with the goal of making propositions of how the two lines of study can be linked. In other words, we conceptually outline the possible links for behavior of the entrepreneurs and the network types they engage with. This framework provides a basis for grasping our research question, laying the foundation for analyzing the empirical data (Yin, 2003), and understanding new findings (Eisenhardt, 1989) Matching Data and Theoretical Constructs In part two and three of the analysis, we seek to match the data of each case study relation to the data of the startups reasoning for engaging in the relation. The strength of this fit is also assessed, and we adopt the approach taken by Fisher (2012), where the method is used for assessing whether entrepreneurs apply different theoretical methods for their decision making. This method implies, that if a network relation and a factor for engaging in the relation were found to be strong, it is marked with in the relevant tables. A relation was found to be strong, if 1) the case study data showed clear evidence of a match between the reasoning of the entrepreneur and the factors of the theory, and 2) if the case study data was not likely to be contested by anyone else reading the transcript, and as such, the case study data was clear (Fisher, 2012). If the evidence required some interpretation, meaning that it was not as strong, it would be marked with. The differentiation among strong or weak is further qualified for the individual principles, in the conceptual framework. This approach is relevant, as startups can fulfill the factors outlined in theory to different degrees, which is captured in this method Individual Case Analysis The overall idea is to become intimately familiar with each case as a stand-alone entity. This process allows the unique patterns of each case to emerge before investigators push to generalize patterns across cases (Eisenhardt, 1989: 540). We adopted such a strategy in a two-step approach. The analysis is structured into two parts. For both parts, each case is analyzed separately, allowing for the unique patterns of each case to emerge before investigators push to generalize patterns across cases (Eisenhardt, 1989: 540). In the first analysis part, we described each case company, which allows for an understanding of the services offered by the company and its history Cross-case Analysis The last chapter of each part of the analysis is dedicated to cross-case search for patterns: One tactic is to select categories or dimensions, and then look for within-group similarities coupled with intergroup METHODOLOGY Research Design 15

17 differences. Dimensions can be suggested by the research problem or by existing literature, or the researcher can simply choose some dimensions (Eisenhardt, 1989: 540). The search patterns are based on existing literature within categories (network types) and dimensions (reasoning for engagement), to look for within-group similarities. The third part of the analysis is based on the conceptual propositions, which is a cross-case analysis, exploring whether there are links across these two research strings analyzed. Thus, the analysis contains both exploratory and explanatory elements Selection of Industry To limit the scope, and to also ensure a focused case study research, this thesis looks into a specific industry: Danish-based Software as a Service (SaaS) startups. Our reasoning for this choice will be discussed below. The SaaS industry is a sub-industry of the Information and Communications Technology (ICT) industry, wherein there is a significant boom of startups (Economist, 2011). The industry growth within the SaaS industry is also evident: In Western Europe, SaaS revenue is forecast to surpass USD 3.2 billion in 2012, up from USD 2.7 billion in 2011 (Gartner, 2012a 1 ). Also on a longer term, the growth perspectives are significant: Software as a service is forecast to have a 17.2 % compound annual growth rate through 2015 for enterprise application markets (Gartner, 2012b). Furthermore, ICT services represent a large part of the service sector in the Nordic countries, compared to other OECD countries (Näringsdepartementet, 2010). The scope of the industry, the prospects of further growth within the industry, and the significant relevance in a Danish context, stresses why it is interesting to explore SaaS startups. Limiting our empirical scope of research to one industry also limits the generalizability of the study to other industries. There might be industry-specific contextual factors which influence the case companies decision making. To potentially overcome this, it would have been interesting to further qualify the industry selection with characteristics of the SaaS industry, and importantly, research the relevance of engaging in network commitments for startups within the SaaS industry. To the knowledge of the authors, however, there is no relevant research on the topic. This is why we adhere to the general knowledge on the importance of exploiting relations for entrepreneurs in general Selection of Cases Four cases were selected. They were chosen according to the purposive theoretical sampling approach, which is one of 16 purposive sampling strategies outlined by Patton (2002). The rationale of applying such a 1 The final information for 2012 is not yet available from Gartner. METHODOLOGY Research Design 16

18 sampling strategy lies in its ability to select information-rich cases for gaining in-depth insight to a phenomenon. As the purpose of this study has been to gain insights into network relations of early stage SaaS startups, the developmental stage of the startups was essential. It was sought after on the basis of theory within this field, to commit case companies which had reached the same developmental stage. The further characterization is defined in chapter 3.1. In accordance with the definitions of this chapter, we were seeking ventures which were finalizing stage 1, as the focus of this study is early-stage startups (Lechner and Dowling, 2003). This severely limited the scope of possible case companies within the SaaS industry, but it was important since entrepreneurs in later stage ventures may have difficulty recalling events in the early stages of their startup Definitions Entrepreneurs in SaaS Startups ICT startups are characterized by being started by a team of entrepreneurs, rather than by one entrepreneur (Littunen, 2000). It is argued that this is because such ventures involve the combination of diverse competences (Lechler and Gemuenden, 1999; Vesper, 1990).This has implications for the theoretical and analytical approach, as much entrepreneurship research is centered on the entrepreneur, rather than the firm as an entity. This thesis uses the startup as a whole as the unit of analysis, though importantly, acknowledging that the startup is comprised of the founding entrepreneurs, and thus not as a distinct entity. Hence, we recognize that decisions are performed by individuals, not firms, but will mainly we will have the startup as the unit of analysis, as the complexity of distinguishing among the founders is out of the scope of this thesis. Research has emphasized how founders and the firms are inseparable for a startup, supporting such an approach (Dollinger, 1985; Begley and Boyd, 1986) Network Relations This study has egocentric network relations as a focus. This entails looking at the relationship of one focal actor with other actors (Wassermann and Faust, 1994; Johannisson, 1998)., which is at a key point of the current study. This implies that this study will not look at the network - understood as all the relations of the startup - and how the startup positions itself within that network (Burt, 1992), but rather focus on the individual relations, also referred to as ties. Such ties can take a variety of forms, ranging from social interaction to a highly strategic partnership. The current study investigates the ties which were present at the time of the interviews conducted. METHODOLOGY Definitions 17

19 Synonyms We use the terms startup, venture, company and firm identically throughout this thesis. Relating to the relations of the ventures, we use the terms network relations, network ties and external relations interchangeably. This is mainly to allow for a more nuanced language throughout the project Empirical Data Primary Data One of the challenges related to research within the field of entrepreneurship, namely with a focus on the initial phase and stages, is the scarcity of information. In regards of all four case companies under study, the information is rather limited as much has yet to be formalized, related to the early stage of the ventures. Thus, in our qualitative study of their network relations, we have relied primarily on case interviews Case Interview Methods As the primary data source, we conducted interviews with the founders of our four case companies. Our main criteria for selecting the interviewees were those with the most knowledge on the firm s external relations. In three of the cases, we spoke to the CEO, while in the last case we spoke with a CSO. Personal interviews were chosen as they render possible open-ended communication while allowing for guidance and focus on the underlying topics of interest. This approach was suitable for our qualitative research which relied on retrospective reasoning, memories, and to a certain degree, subjective interpretations of the interviewees. It could occur that some of the interviewees answers might be reconsidered when the interviewer questioned them or rephrased the question, enabling the interviewer to receive more reasonable answers (Freeman, 2007). A semi-structured approach was chosen as the primary interview method. The semi-structured approach allows for open inquiry and enables the interviewees to freely express stories while the interviewer keeps the agenda in focus (Eriksson and Kovalainen, 2008). In all four cases, we conducted two, one hour-long personal interviews. We had specific agendas for each of the two interviews which were based on relevant theory and structured with an interview guide based on topics which we wished to have covered. The interview guide is found in appendix 5. METHODOLOGY Empirical Data 18

20 Additionally, follow up phone-calls were conducted in some cases in order to clarify elements of the interviews which we felt had not been covered sufficiently. Two days before the first round of interviews, the interviewees were asked to consider which external relationships they had engaged in. We also provided them with a broad definition of resources and partnerships, which we look into (appendix 6). This was done in order to save time in the actual interview while also giving the interviewee a chance to reflect on the subject. It was decided to divide our questions in the two interview rounds to allow for focusing the topics in detail. The first interview of the two in each company was dedicated to getting an overview of the types of networks ties engaged in. The second interview was devoted to shedding light on the underlying reasoning for engaging in the relations discovered. While the first interview round featured both closed and open-ended questions, the second interview round was dominated by open-ended questions. In both rounds, we were cautious not to reveal theoretical definitions about typologies, stages, principles, in order not to contaminate the answers. This was especially important in the second interview round, focusing on how the case companies engaged in the partnerships. This question calls for open ended questions since evidence is sought for in their answers that could legitimize the use of effectual/causal reasoning as explanations for partnership engagement. During the interviews, the approach suggested by Eisenhardt and Bourgeois (1988) of letting one interviewer control all the questions while the other would take notes and record observations was adopted. This enabled the interviews to fulfill our goal of obtaining good information. It enabled the passive interviewer to observe the interview from a distance, and consider the quality of the answers from the interviewee and rephrase questions if it was obvious that the questions were misunderstood. The interviews were all conducted in Danish due to mutual agreement between the interviewees and interviewers. The important passages from the interviews used for quotation in the analysis were translated into English Secondary Data As argued initially, public and internal information of the early stage startups is limited. It can be implied that startups do not have large amounts of formalized data which external researchers access. Instead, much of the knowledge is internalized, which personal interviews could appropriately tap into. However, this also implies that this study was highly reliant on the interviews which has negatively influenced our ability to triangulate our empirical data. METHODOLOGY Empirical Data 19

21 A range of articles, however, were available through the article database Infomedia, while blog posts and similar information was found through thorough online search. These were valuable as they provided us with a good understanding of the services offered by the case companies. Sources are listed in the reference list. In some cases there was information about the partnerships on the webpage which the interviewee did not mention himself. We also encountered that the interviewees encouraged us to look through specific sections of the webpages to find useful information where we might not have looked otherwise. On the blogs which are part of the some of the case companies webpages, we found information about partnerships and got insight on how they were used for promotional reasons Interview Data Analysis As stated above, two rounds of interviews were conducted which have been partially transcribed. All unnecessary passages were skipped. The transcriptions are found in appendix The focus of the first interview round was to map an understanding of which kind of partnerships the case companies engaged in. We attempted to identify this for each company in order to obtain an overview of occurring network ties. In the following analysis, these network ties were then categorized in correlation with the selected theory. The second interview was focused on revealing some of the underlying reasoning for becoming involved in the respective network ties that we found in the first interview round. Subsequently, the discovered typologies were plotted on a model with the purpose of providing overview for the reader. As qualitative data is very rich and often somewhat ambiguous, it is important to apply methods which serve to reduce its complexity. A widely used method for doing so is coding. Coding involves identifying topics in the transcribed interviews to achieve an overview. it is formulated into the following three procedures: a) noticing relevant phenomena, (b) collecting examples of those phenomena and (c) analyzing those phenomena in order to find commonalities, differences, patterns and structures (Coffey and Atkinson 1996: 29). Each interview was analyzed and compared based on the respective theory which the questions behind it were built upon. Therefore each topic found through coding was based on the conceptual framework developed. METHODOLOGY Empirical Data 20

22 The following table provides an overview of the four case companies. Table 2. Case Companies Company Interviewee Position Legal Creation Employees, April 2013 Date of interviews Tradeshift Mikkel Hippe Brun CSO 2009 N/A Int.1 7/1/13 Int.2 26/2/13 Echo.IT Stefan K. Madsen CEO Int.1 22/1/13 Int.2 2/2/13 Billy s Billing Toke Kruse CEO Int.1 11/1/13 Int.2 26/2/13 Opeepl Morten Korch- Haahr CEO Int.1 28/1/13 Int.2 4/3/13 Source: Own development 2.6. Evaluation of the Research Process Ensuring validity and reliability are central factors when conducting qualitative research (Yin, 2003). By focusing on constructing validity, internal validity, external validity and reliability of a study, it can be determined if our qualitative research has been undertaken in a scientifically rigorous and defensible approach (Yin, 2003) Methodology In this paper, we adhere to an abductive research approach, which entails a mix of both deduction and induction. As we base our study on existing knowledge within the field, the empirical findings related to these constructs are deductive, as we are testing theories. When this study takes the step further to bridge these theories, it becomes an inductive method, which implies theory building from our case studies in accordance with Eisenhardt (1989). In line with our discussion of the philosophy of science, we incorporate methods from different epistemological orientations, which have been encouraged as one should attempt to mix methods to some extent, because it provides more perspectives on the phenomena being investigated (Easterby-Smith et al., 2008: 71). METHODOLOGY Evaluation of the Research Process 21

23 Construct Validity Based on extant literature, this study has formulated an extensive framework which provides operational measures to identify given phenomenon in the empirical settings. According to Yin (2003), this is an important process towards establishing construct validity, as it provides an operational set to identify the dynamics of a phenomenon Internal Validity To ensure the internal validity, Both Yin (2003) and Eisenhardt (1989) have proposed the concept of pattern matching, where empirically based patterns are compared with predicted ones, defined prior to data collection. As described in the chapter on research design (2.3), our interviews with case companies was based on theoretical insights, which provided us with categories and dimensions that allowed for cross-case patterns searching. By basing our research on such pattern matching principles, the results of this study are believed to strengthen the internal validity of this study (Yin, 2003) External Validity The external validity refers to the extent the study can be generalized to other contexts, implying different cases, other industries or other cultural settings. It is a common concern that cases provides little basis for generalization: the mode of generalization is analytic generalization, in which a previously developed theory is used as a template with which to compare the empirical results of the case study. If two or more cases are shown to support the same theory, replication may be claimed (Yin, 2003: 33). As stated by Eisenhardt (1989), a central strength of the case study theory building is how the process is intimately tied with evidence that it is very likely that the resultant theory will be consistent with empirical observation (Eisenhardt, 1989: 547). Case study theory building is also a bottom-up approach, which poses the risk that the empirical findings describe a very idiosyncratic phenomenon, hampering the generalizeability of the study (Eisenhardt, 1989). By relying on extant literature, we seek to overcome this weakness of the case study approach, and hence ensure the external validity of this study. In line with these insights, this paper seeks to explore connections of existing entrepreneurship theories, focusing on network relations, whereby initial steps for new entrepreneurship theory insights may be developed. METHODOLOGY Evaluation of the Research Process 22

24 By applying a multiple case study design instead of a single case study design, we have sought to enhance the external validity because of the comparability strength between the cases. This enhances the replication logic, which has been applied in consistence with the guidelines of Yin (2003) Reliability The reliability relates to the repeatability and consistency of the study, which should be present, such that other researchers can conduct a repetition of the study to provide the same results (Yin, 2003). In conducting qualitative research within startups, we saw that the case companies did not have written documents, but rather an internalized knowledge of strategy and processes. Exploring past events and reasoning for engaging with network relations, we were dependent on entrepreneur s hindsight and their own interpretation and memory. Hence, the subjects are prone to information-processing biases (Eisenhardt, 1989; Kahneman and Tversky, 1973). Focusing on early stage startups, we have sought to include case companies which are in an early developmental stage, where the decisions to be recalled by the entrepreneurs, were made within a recallable time span. As described earlier, to ensure the reliability of the study, interview guides were created for both interview rounds (see appendix 5). Before submitting this thesis, all interviewees read their relevant sections, allowing them to clarify statements and correct possible errors. In being transparent and explicit in our approach to this study, we introduced our assumptions and an indepth view of the theory upon which we further build. The sources of qualitative data and the empirical data are disclosed, and we sought to explain all steps of how results are reached. This further ensures the ability to replicate the current study and reach the same conclusions. METHODOLOGY Evaluation of the Research Process 23

25 3. LITERATURE REVIEW The Life Cycle of the Entrepreneurial Venture A Typology Of Network Relations Exploring The Typology Effectuation Theory The following chapter starts with a discussion of new startups development through stages related to our study. Next, the startups engagement with external network ties is discussed. We then adopt the most promising typology for the further analysis. The effectuation theory, set as the overarching framework for our inquiry, is presented in relation to how it can help us better understand how entrepreneurs engage in network relations. The aim of the section is to provide a thorough insight into the theoretical framework, upon which the analysis is built. 24

26 3.1. The Life Cycle of the Entrepreneurial Venture In the following section, we cover findings from literature that explains the early stages through which the new venture develops. For this purpose, we assess a selection of the most cited studies that involve a life cycle approach where the development is explained by shifts in the firm s required resources (Sullivan and Ford, 2013; Smith and Lohrke, 2008; Leung, 2003). It is an attempt to narrow down and specify the scope of the current study. It will provide the reader with a sense of which dynamics define the life cycle stage of the ventures under study. As mentioned in the research question, we focus on the early stages of startup development. It seems indisputable that there is a co-evolutionary aspect to how firms and networks evolve (Koza and Lewin, 1998). Thus, we adapt the view that all new ventures go through a set of development stages. A general characteristic in the field of network theory is that scholars have not managed to reach consensus on the understanding of neither what drives the development of networks (Jack et al, 2010), nor who drives it (Hoang and Antoncic, 2003). The need for resources in the early-stage startups change quickly, and the stages that the new firms go through represent different challenges, such as goals, resource needs and resource acquisition challenges (Hite and Hesterly, 2001; Reese and Aldrich, 1995). In every stage, the new firm must overcome their resource acquisition challenges to increase the likelihood of survival (Bhide, 1999; Churchill and Lewis, 1983) which can be obtained through the exploitation of different network ties (Lechner and Dowling, 2003) Laying the Foundation for a Framework of Scope of Time As the typology by Lechner and Dowling (2003) is central to this thesis (see section 3.2), it is also relevant to assess the four stages which these typologies are divided into. These remain broad in scope, compared to other literature within in the topic, and will briefly be introduced here. Lechner and Dowling (2003) state that stage 1 includes fast-growing startups with a low degree of market appreciation. Their liability of smallness and newness is evident (Stinchcombe, 1965; Baum, 1996) and thus the use of the startups social and reputational networks are important due to their capability to create future options and create legitimacy. In stage 2, firms have become established and have begun to generate ample sales. Also in stage 2, the companies are considering and actually working towards an initial public offering (IPO) for the following year and have often been funded by venture capital at this point. The most important networks are here argued to be marketing and co-opetition networks which they engage with in order to overcome the challenges of obtaining stable sales. Stage 3 contains companies LITERATURE REVIEW The Life Cycle of the Entrepreneurial Venture 25

27 which were already in due diligence process for reaching IPO. The firms have here gained a significant network and a central position in the network. The company has now obtained the authority to offer other companies reputation. Technology networks become useful in order to further develop the software which is central to the startup. Stage 4 entails that the startup is now focusing on culling old redundant ties, in order to add new ties; the startup has moved pass IPO. The relationships have begun taking another form and have become more structured. In the light of the stages above, our focus in the current study is covered by Stage 1. An examination of subsequent stages is out of the scope of this study. Hence, we argue that in order to focus the current thesis, a more detailed picture of the mechanisms in Stage 1 is needed in order to describe the early stage of the startup in more detail. Thus, we incorporate relevant theory to further develop our understanding of stage Defining the Scope of Time In general, what characterizes the reviewed literature is that the elements which are explanatory of the stages are quite homogenous. The stages range from the early idea phase, where the startup is not legally established and basically testing an idea in a close social network, to the point where the startup is actively steering towards growth and profit. LITERATURE REVIEW The Life Cycle of the Entrepreneurial Venture 26

28 Table 3. Overview of literature on life cycle stages, limited to early stage startups Authors LECHNER AND DOWLIN G(2003) Overview of life cycle stage for early stage startups Stage 1 -Fast growing startup -Low degree of market appreciation -Liability of smallness/newness evident LARSON AND STARR (1993) Focusing on the Essential Dyads -Motivated to engage in extended exchange relationships to obtain resources - Encounter new connections and evaluate - Move from social networks to business network - Needed resources explicit and identified Converting Dyadic Ties to Socio- Economic Exchanges -One dimensional relationships change into multi dimensional, - Quid pro quo and trial and driven - Establishment of mutually beneficial goals and org interdependence Layering the Exchanges -Moving towards multi layered networks ties -Increase in complexity -Tighter integration in dyad HITE AND HESTERL Y(2001) Emergence -Legal creation of firm, - Goal is to survive, - Periode is equivocal, liability of newness/smallness - Identity based networks - Path dependent Early growth -Clear strat. Decision to pursue growth, -Stronger legitimacy and resources, -In need of extensive ressources, -Cohensive networks - Intentional management Butler and Hansen (1991) entreprenurial phase Business Startup Phase Ongoing Business Phase -Size of social network important, -strength of ties determine quality info -Big networks likely to provide information which disconfirms existing knowledge - More focused network, social network new individuals and organisation with direct business links, selecting suppliers, raising capital, org structure, fir Business is startedm interest in growth and profit, aware of smallness/newness, mutal dependency between network participants, strategic network reduce smallness/newness Source: Own development, based on the papers As the focus of this paper is not the initial idea phase, we will set off at the point of the new firm development. This can be explained with what Hite and Hesterly (2001) called Emergence or the Entrepreneurial Phase (Butler and Hansen, 1991), whereas Larson and Starr named it Focusing on the Essential Dyads (Larson and Starr, 1993). The similarities which these stages share are depicted in the table above. In respect of the terminology of Lechner and Dowling (2003), we argue that these would all fit under Stage 1, though it can be argued that LITERATURE REVIEW The Life Cycle of the Entrepreneurial Venture 27

29 the initial stages are a bit preliminary for Stage 1 due to the missing high growth aspect. Within the focus of the current study, however, it is necessary to include these. Hite and Hesterly (2001) clearly define the emergence stage, namely as the legal creation of the firm. It is generally implied that the development of the networks tend to start from identity based networks (Hite and Hesterly, 2001), which are based on previously established connections. Butler and Hansen (1991) argue that the size and diversity of the social network is an important factor in this stage, as it can lead to diverse information which can be useful to challenge existing knowledge. This also implies the extended use of social ties in the initial stages. Larson and Starr (1993) argue that an initial shift from social to business network is also seen at this point. The use of previously established ties continues into the next phase as well, which then is challenged by the startups limits caused by the extended need for different types of information and tangible resources in the Business Startup Phase (Butler and Hansen, 1991). The Business Startup Phase entails tasks like raising capital, selecting organizational structure, and selecting suppliers. This creates a shift in the need of resources compared to the Entrepreneurial Phase, calling for a more focused and strategically chosen type of network. The Converting Dyadic Ties to Socio-Economic Exchanges (Larson and Starr, 1993) explains how the needs are met by transforming one-dimensional ties into multi-dimensional relationships, meaning the partnerships develop more functions. As an example, the social tie may add a business perspective to it, like an old friend with a legal background, who initially provided the startup with informal legal advice, becomes the startup s official lawyer (Larson and Starr, 1993). To finish setting the scope of research, we will continue to the Early Growth Stage discussed in Hite and Hesterly (2001). This, together with the Ongoing Business Phase (Butler and Hansen, 1991) and the Layering the Exchanges (Larson and Starr, 1993) it is argued that the awareness of liability of smallness becomes more explicit. The need for extensive resources forces the new venture to pursue partnerships with companies outside of the entrepreneurs social network, thus moving towards a more strategic network through external ties. More business functions and activities are enrolled in the exchange activities and the multiple layers lead to a more complex network structure, fostering tighter integration between the actors in the dyad. The added layers forge dyads to shift from interpersonal connections to interorganizational ones (Larson and Starr, 1993). This is exemplified as by a social tie evolving from a tie between two social entities to a tie between two organisations. The scope of this thesis ends, as it is defined under the Early Growth Stage (Hite and Hesterly, 2001). This is when the focal company takes the purposeful decision to pursue growth. LITERATURE REVIEW The Life Cycle of the Entrepreneurial Venture 28

30 3.2. A Typology of Network Relations This section will discuss and develop the part of the framework concerning the types of entrepreneurial networks in which entrepreneurs engage. By reviewing existing literature, we intend to discuss different conceptual approaches to network typologies. Based on this discussion, we will propose a typology which provides the intended insights for the current study Structure of the Section Starting with a short introduction to the subject of network typologies, the next section will present a figure which summarizes existing typologies of entrepreneurial network relations. The relevance of the typologies will thereafter be related and discussed according to the aim of the study. The discussion will focus on the relevant typology and how we can develop this directed towards our empirical research. As will be argued in the section, our findings necessitate a further discussion of social networks as a network type, as well as a further exploration of the typology Why a Typology? Prior literature suggest that network relations of startups still remains an area where much research is to be conducted (Hoang and Antoncic, 2003; Slotte-Kock and Coviello, 2010), where the network relations of the startup still largely remains a black box. By working with a typology, researchers and entrepreneurs alike can acquire an instrument which allows a differentiation among the network relations. Such a differentiation provides a language for further discussing the relations, which is a step towards a better understanding of which network relations startups engage in. It is important to underline that typologies in the literature are closely linked to the development of the startup, and researchers have linked the typologies closely to the stages of the startup. This entails that a separation of those two elements, as seen in this thesis, can be difficult because of the mutual relationship. Though, to provide a deep insight into both elements, it is found that a separate review of the elements enables us to go more into depth with each element. Due to their mutual relationship, however, we have found it necessary to accept overlapping elements amongst the two sections Different Approaches to Typologies In defining different types of startup network relations, the literature takes different approaches to investigating the phenomenon (Slotte-Kock and Coviello, 2010). To provide a solid background for investigating network relations empirically, we conducted a thorough literature search for frameworks which distinguish different types of networks. Five different approaches to typologies were identified in the literature. The approaches are distinguished by a different focus in their approach to defining network LITERATURE REVIEW A Typology of Network Relations 29

31 types (Slotte-Kock and Coviello, 2010). This calls for a review of such approaches, in order to discuss and qualify the approach taken in this thesis. Furthermore, it serves as a transparent insight to the work towards adopting a typology for this study. The table below depicts the five typologies of entrepreneurial networks, and their definition of each network category, which are examined further in the following section. The table includes the author(s), the purpose of the paper, and the definition of network relations types. LITERATURE REVIEW A Typology of Network Relations 30

32 Table 4. Typologies of network relations of the entrepreneurial venture Author(s) Purpose Network relations typology Butler and Hansen (1991) Donckels and Lambrecht (1995) Littunen (2000) Hite and Hesterly (2001) Lechner and Dowling (2003); Lechner et al. (2006)... examines the roles and evolution of networks, and their impact on the initial and ongoing success of the entrepreneurial venture. The authors develop a conceptual model with four types of networks, and a dimension of whether the network is direct or indirect. The framework is a classic within the literature, and has been adopted from earlier research within the topic. Network relations of startup in relation with the development of the young firm. A typology of functionally different networks, referred to as the Relational Mix. Based on case study research of German tech startups. Social Business Strategic The social network is given as the social network of the entrepreneur, and is not specified any further by Butler and Hansen (1991).... should reflect links to individuals and organizations that directly serve the more immediate needs of the new business (Butler and Hansen, 1991: 4). The business network is a hybrid, which contains both social connections known before the venture was established and new, business-related contacts. Social Communication Business Moral... affective network relations, (which, red.) are maintained with family, friends and acquaintances (Donckels and Lambrecht, 1995: 274). Entitles emotional bond among relationships. Informal... organizations and individuals with which the small firm has non-trading links that inform its business activities, such as external consultants, the family and other entrepreneurs (Ibid.) Exchange networks, where the core is the trading partners of the firm. Business networks are further divided into three sub-groups. Formal The strategic networks entails mutual dependence, and are often engaged with competitors, from which production knowledge or reputation can be shared. The... entrepreneur becomes aware of the strategic aspects of success and their firm's vulnerability with respect to larger competitors (Ibid.).... the entrepreneur feels morally obliged to do everything possible for his partners (relatives and fellow entrepreneurs) in the network (Ibid.).... personal relationships, family and business contacts (Littunen, 2000: 62).... venture capitalists, banks, accountants, creditors, lawyers and trade associations (Ibid.). Identity-based Who the ties are-matters more than the specific economic functions or resources that this tie can provide to a firm (Hite and Hesterly, 2001: 278) Calculative providing greater resource availability and mitigating more environmental uncertainty (Ibid.) 1991) Social Reputational Marketing Co-opetition Technology Relationships with other firms based on strong personal relationships with individuals such as friends, relatives, longstanding colleagues that became friends before foundation, and so forth (Ibid.). partner firms that are market leaders, or highly regarded firms or individuals, and where one of the main objectives in entering into this relationship is to increase the entrepreneurial firm s credibility (Ibid.). Relationships that allow for the flow of market information through distinct relationships with other individuals / firms (Ibid.). Relationships with direct competitors (Ibid.). Alliances involving joint technology development or innovation projects (Ibid.). Source: Own development, based on the papers

33 Discussion The figure above provides an overview of how it, in different ways, can be attempted to box the relations of a startup. Across the typologies, a main commonality is the presence of a network type which contains social ties of the entrepreneurs in a startup. This is reflected as social relations (Butler and Hansen, 1991; Donckels and Lambrecht, 1995; Lechner and Dowling, 2003; Lechner et al. 2006), informal relations (Littunen, 2000) and identity-based relations (Hite and Hesterly, 2001). Literature on startups network relations have consistently argued that entrepreneurs rely heavily on their social relations in the very early stages of a startup: Clearly, broad agreement exists about the importance of networks for emerging firms (Hite and Hesterly, 2001: 275). Hence, the exploitation of one s close network in the early stages of a venture is reflected in the typologies. As also argued in the section on stages (3.1), the company s new relations move towards business relations, entailing that there is, most often, no prior social relation (Dollinger, 1985; Green and Brown, 1997). This is also reflected in the typologies, as either business or strategic relations (Butler and Hansen, 1991), business relations (Donckels and Lambrecht, 1995), formal relations (Littunen, 2000), calculative relations, (Hite and Hesterly, 2001) or reputational, marketing, co-opetition or technology relations (Lechner and Dowling, 2003; Lechner et al. 2006). Throughout the typologies, the line dividing the network types can be blurry. For example, how well should an entrepreneur personally know a venture capitalist, before she is an informal, rather than a formal (Littunen, 2000) relation? In the typologies which have more than two categories, relations can fall into several of these categories. For example, in the case of Lechner and Dowlings (2003) typology, a relation can both serve as marketing and a reputational relation. This highlights the inherent complexity of network research, and further enhances the complexity of working with a typology. The division of the typologies is also an expression of the close links these have to the development phase of the venture, which is a connection emphasized in all the papers examined. The typologies tend to put much emphasis on the origin of entrepreneurs network relations, mainly differentiating among social and business relations. The main objective of applying a typology in our study is not to discover from where the relations emerged, but rather to determine what resources specific relations bring to the venture. For example, whether a network is characterized by being identity-based or calculative (Hite and Hesterly, 2001), does not inform us about what resources the relationship brings to the startup. This LITERATURE REVIEW A Typology of Network Relations 32

34 limits the applicability of the typologies which are based on two categories, principally differentiating among social and business relations. Taking such an approach, we find a group of papers consisting of Butler and Hansen (1991), Littunen (2000) and Hite and Hesterly (2001).These all represent a typology categorization which focus on whether a network relation is social, informal or identity-based rather than business/strategic, formal or calculative. For this reason, we do not proceed with these papers. In a second group, we find Lechner and Dowling (2003) and Donckels and Lambrecht (1995). The typologies from these papers also shed light on whether a relationship has emerged from a social relationship, but the typologies go a step further. Besides social relations, the network types are characterised by shedding light on more network types than the typologies in the first group of papers. Donckels and Lambrecht (1995) distinguish four network types: social, communication, business and moral networks. This typology sheds light on the types of social bonds the entrepreneur exploits and their implications. Even though this typology sheds a more nuanced light on the relations of the firm, as it encompasses more network types, the typology does not sufficiently provide insights to what resources each network type brings to the venture (Hoang and Antoncic, 2003). Rather, it mainly provides an extended, and thus more nuanced typology, than is the case of the papers examined above. Thus, this approach is not found appropriate for the current study. Lechner and Dowlings (2003) typology - the Relational Mix - is distinct, as it emphasizes a focus on the resources which each network type offers in the different stages of the startup. Thus, the empirical use of the Relational Mix emphasizes which resources each network type provides. For example, if a startup has engaged in a reputational network relation, the startup has prioritized resources to draw on another firm's reputation and become regarded as more trustworthy by external entities. By providing five network types, the typology can possibly give a nuanced view of a venture s network relations. Slotte-Kock and Coviello (2010) describe it as putting emphasis on the functions of the networks in different developmental stages. They also highlight that this research area lacks further insights (Slotte-Kock and Coviello, 2010). LITERATURE REVIEW A Typology of Network Relations 33

35 A critique of the typology is the lack of empirical validation. A thorough forward-citing search method was conducted, to search for additional research based on the typology, yet did not result in further publications 2. The above section and the following discussion have provided a broad understanding of what typologies entail and how they differ. It is found that the typology by Lechner and Dowling (2003), further developed by Lechner et al. (2006), the Relational Mix, is best suited for our purpose, as it highlights the resources of the network relations. The Relational Mix framework, however, does have limitations which will be discussed in the next section Adopting and Adapting a Framework The typology development by Lechner and Dowling (2003) was conducted as case study research in a tech cluster context in Germany. This further qualifies the relevance of this typology in light of developing a model directed towards SaaS startups, which are also technology companies. In 2006, Lechner et al. performed a quantitative follow-up study, providing insights on which network types matter and when (Slotte-Kock and Coviello, 2010). We find it relevant to discuss two elements of their typology. First, in relation to the earlier discussion, the typology has a category of social networks (Lechner and Dowling, 2003). The typology emphasizes focusing on the resources of the relations, but we find that social relations can be questioned as a type of relation, which sheds light on resources. This will be further discussed in the subsequent section. Second, as has been emphasized earlier, it is found that network types are seldom a well defined entity. This can lead to incorrect understandings of the network types, which should be avoided. This is also the case for the Relational Mix, which is why a discussion will be initiated to attempt to address and alleviate the problem of the blurry lines associated with current typologies. This discussion is to be found in section To further exclude the possibility that the typology has been further validated or developed, a co-author of both articles was contacted (Christian Lechner, Senior Professor, ESC Toulouse), and he confirmed that he was not aware of any further publications on the Relational Mix. LITERATURE REVIEW A Typology of Network Relations 34

36 Social Networks Social networks are strong personal ties such as family and friends (Lechner et al., 2006: 517). Such ties can help entrepreneurs avoid opportunism and uncertainty through trust, predictability, and voice (Lechner et al., 2006: 520). Entrepreneurship research has shown how social networks may be the most critical strategic resource for the startup entrepreneurs (Dubini and Aldrich, 1991; Ostgaard and Birley, 1994; Johannisson, 1995, 1998, 2000; Lipparini and Sobrero, 1997; Aldrich, 1999; Ardichvili et al., 2003). However, we find that social networks are not a relevant network category in our use of the Relational Mix framework. Focusing on the content of the startups network relations, the conceptual framework for relationship types in this thesis do not focus on whether a relation emerged via a social or a business relation, which is a common differentiating factor within the literature (Slotte-Kock and Coviello, 2010). By not having such a distinction as a main focus, it contrasts with much entrepreneurial network theory (Jack, 2010; Slotte- Kock and Coviello, 2010). The importance of the relationship origins are acknowledged, but a distinction of whether a relationship is social does not reveal what resources that relation brings to the venture, which is a main building block of the typology framework. The typology by Lechner and Dowling (2003), which is adopted for the conceptual framework, has been praised for its ability to distinguish functionally different networks (Slotte-Kock and Coviello, 2010). Of the five network categories, however, social networks cannot be described as a network type which can be distinguished from the others in the Relational Mix, by the resources it brings to the startup. Startups social network relations in Lecher et al s (2006) typology described as relationships with other firms based on strong personal relationships with individuals such as friends, relatives, long-standing colleagues that became friends before foundation, and so forth (Lechner et al., 2006: 515). Hence, the startup s social network is not characterized by bringing a specific type of resources to a startup, but is a way to approach external resources. We therefore argue that social networks should not be part of the typology adopted, as it does not shed light on a specific type of resources. It is important to underline that we recognize the significance of social networks. As research has shown, a startup relies heavily on its social networks when seeking out new relations (Gulati, Nohria, and Zaheer, 2000). However, based on the above argument, this thesis perceives social networks as a construct similar to business networks, and these are seen as underlying factors of how network relations come into being. This is to be further discussed in the section on principles, which discusses underlying mechanisms for engaging in relationships under the notion of means (section 3.4). Thus we argue that the Relational Mix proposed by LITERATURE REVIEW A Typology of Network Relations 35

37 Lechner et al. (2006) is re-structured accordingly for the sake of relevance of the current study, entailing that social networks will not be considered as a network category, but rather embraced by the remaining four network categories. These will be further explored in the following section Defining and Exploring the Typology This section further explores and discusses the network types in the adopted typology to provide a more holistic perspective (Lechner and Dowling, 2003; Lechner et al., 2006). The intention is not to modify the already existing definitions, but rather explore and limit their definition by drawing on existing literature. This will provide a more well-defined typology for the conceptual framework, which should also serve as initial building block for further research within the field. Due to the focus of this thesis, the choice of using the typologies by Lechner and Dowling (2003) can be subject to critique as we are aware that two of the four types of networks are argued not to figure in the time scope we study. However, we do also expect that even though the findings of Lechner et al (2006) show this, it is also noted that it is not unusual to encounter all the relation types in earlier stages than suggested Reputational Networks The study by Lechner and Dowling (2003), found that most of the examined sample firms; Developed a system for overcoming both quantitative and qualitative constraints for future ties: they seek new and highly visible partners partners that can give a start-up the reputation it could not otherwise achieve in the market at that point (Lechner and Dowling, 2003:13). Such partnerships are also called reputational networks. They are defined as ties with other firms where the entrepreneur estimated the main reason for engaging in the relationship was of a reputation gaining character (Lechner et al., 2006). The reputational partner may consist of everything from well-renowned customers, suppliers to investors, and even competitors, as long as they are able to provide value to the startup through the affiliation between the two. This type of network is also called a weak tie (Granovetter, 1973), as the parties are not thoroughly embedded into each other (Lechner and Dowling, 2003) Research on Reputational Networks Larson (1992) has suggested that social networks and reputation were pre-conditions for economic exchange. In this light, relationships with other firms can have important reputational or signaling effects (Stuart et al., 1999; Gulati and Higgins, 2003; Deeds et al.,2004) LITERATURE REVIEW Defining and Exploring the Typology 36

38 To enter into reputational relationships, entrepreneurial firms must be able to offer attractive resources (Eisenhardt and Schoonhoven, 1996). As the quality of a young company cannot be assessed directly due to the lack of information and no or little history to look back at, stakeholders (e.g. investors, customers, partners, media, potential employees) wanting to evaluate the firm and the resources it can offer before engagement, must rely on other signs of quality. This means that partners and customers may be reluctant in working together with or buying the service or products offered by the young firm. Stuart, Hoang and Hybels (1999) found how the perception of value of early-stage companies can be influenced positively by interorganizational relationships in which that company engages. Partnerships with larger established companies reduce uncertainty and generate viability in the eyes of other stakeholders. Exploiting reputational networks is a gateway to subsequent network-building as the companies engaged will gain access to each other's networks. The increased perception of reputation gives rise to additional relationships, even ones which were out of the question beforehand. The bridging effect of the added reputation is an important factor for the early stage startup (Rothaermel and Deeds, 2001). Reputational networks are found to have a positive impact on firm growth as well (Lee et al, 2001) while reducing time-to-ipo (Stuart et al, 1999) and other time performance targets set within the startup Marketing Networks Marketing networks are defined as... relationships with other firms that enable the central firm to gain better market information for the requirements of new products, to reach new markets or to gain new clients (Lechner and Dowling, 2003: 14). These networks rely on an informal approach to marketing, which can be distinguished from marketing research, which is the formal gathering of market information. It is argued that the informal information gathering from external network sources are more important than an internal marketing planning function (Brush, 1992; Malecki and Poehling, 1999). Lechner et al ( 2006) found strong support for this argument in their empirical research, stating that marketing networks had a positive impact on sales Research on Marketing Information Networks Research within this string of literature has centered on marketing planning within established companies. These studies mainly show a positive relationship between the formal marketing planning and firm performance, but the usefulness of such planning tools were questioned in terms of the usability for smaller companies, which favor personal networks and an informal approach in their environmental scanning (Brush, 1992; Lechner et al, 2006). LITERATURE REVIEW Defining and Exploring the Typology 37

39 Like reputational networks, the marketing information networks encompass a broad spectrum of the startups network. Marketing networks are most often entered with existing business relations - like customers, suppliers or other network partners - as these are often the gateway to market information on entering new markets or product development (Lechner et al, 2006). For example, a foreign client in a B2B-relationship may help the startup expand to the client s market. Hence, marketing networks become important channels for information which leads to strategic decisions on the startups approach to marketing and product development. Marketing networks address the liability of newness by incorporating networks for marketing purposes. As the internal marketing capabilities of the company grow with the company s general growth, the firm will rely less on these marketing networks as the formalised internal resources take over these processes (Lechner and Dowling, 2003). When a startup engages with a new customer or supplier, the relationship is based on a transaction. Only over time can relationships with such partners develop, as they gain a stake in the survival of the startup (Bhidé, 2000). For example, customers can become - to a varying degree - dependent on the product or service delivered by the startup, as it especially in a B2B setting becomes a part of the company s own offering. Suppliers are interested in their customers growth, as an increasing sale for the startup will also entail an increased sale for the supplier. For both examples, the network relation has an interest in the startup s survival, which is why they have an incentive to provide relevant market information to the startup, or even assist in penetrating new markets. Customers are also highlighted as a source for market information and hence, product development (Von Hippel, 1978) Co-opetition Networks Success in today's business world consequently requires firms to develop, manage and assess complex coopetitive relationships (Abdallah and Wadhwa, 2009: 2). Co-opetition is defined as a simultaneous cooperation and competition between firms (Brandenburger and Nalebuff, 1996). The underlying logic is that companies perform better when they simultaneously engage in competition and cooperation (Abdallah and Wadhwa, 2009). Thus, this network type comprises relationships with direct competitors, which is a horizontal partnership. In the explanation of this network type, Lechner and Dowling (2003) and Lechner et al (2006) argue that co-opetition networks are a deliberate strategy. This can be contrasted with marketing networks, which are more often overlapping with other network types. The authors LITERATURE REVIEW Defining and Exploring the Typology 38

40 also argue that this type of partnership is an important source of flexibility and growth for the entrepreneurial firm Research on Co-opetition Networks Co-opetition networks are two distinct research strings that propose opposite strategies, namely competition and cooperation, which come together. Within these classic research perspectives, competition has a focus on rent appropriation strategies, while cooperation focus on collective strategies for rent generation (Eikebrokk and Olsen, 2005). The following quote captures the essence of co-opetition: Creating value, a bigger pie, is fundamentally a cooperative activity involving customers and suppliers that a company can t accomplish alone. On the other hand, the act of dividing up the pie is fundamentally competitive. A company has to keep its eyes on both balls and creating and capturing at the same time. We have chosen to call this co-opetition because it combines competition and cooperation (Brandenburger and Nalebuff, 1997). Research within co-opetition networks is a relatively young research string, as the term was not coined until the early 1990s. Research on the topic did not take off until 1996 with the book Co-opetition by Brandenburger and Nalebuff (1996). Since then, scholars have expanded the view on co-opetition networks, but this string of research is still in its infancy (Abdallah and Wadhwa, 2009; Eikebrokk and Olsen, 2005). Co-opetition networks should be engaged as competitors will often struggle with similar issues across organisational boundaries, as they compete in the same markets and their technologies are often complementary (Gnyawali and Park, 2009). This makes their resources and capabilities relevant for one another, why much can often be learned across the boundaries of the organisational lines. The perspective of collectively making the pie bigger, also probes challenges. It becomes important for companies engaging in a contradicting logic of interaction to balance the interests of all partners in such a relationship (Zineldin, 2004; Eikebrokk and Olsen, 2005; Bengtsson et al, 2010). Three elements are highlighted which are found to be of relevance for the entrepreneurial firm when engaging in co-opetition relationships. First, co-opetition networks arguably reduce uncertainty (Gnyawali and Park, 2009), as the entrepreneurial companies engage in a common goal towards a common market. When cooperating, the entrepreneurial firms stand stronger against larger incumbents. Choi (2005) argues that this combination of resources gives each company a competitive edge not available to companies which are not a part of the partnership. LITERATURE REVIEW Defining and Exploring the Typology 39

41 Second, another cooperation benefit when working with a competitor is a reduction in the time span of R&D (Gnyawali and Park, 2009). The overlapping knowledge of partners would constitute a high degree of absorptive capacity (Cohen and Levinthal, 1990), enabling the transfer of knowledge without the constraints of learning about new technologies, markets or other relevant elements. This enables the small companies to develop faster in collaboration, which is an important parameter in a fast-moving market. Third, also related to R&D, the entrepreneurial firms which pool together resources are likely to gain economies of scale, which in turn enables them to better compete against larger competitors (Gnyawali and Park, 2009) Technology Networks The technology networks are defined as a network type which is mainly engaged in on later stages of the venture, primarily stage four, but initially in stage three, as framed by Lechner et al. (2006). As mentioned, these later stages are not the focus of this thesis, but it is still relevant to review this network type, as some ventures might engage in such networks, and thus we will complete the circle of networks with the technology networks. The cooperative technology networks are defined as... relationships with other firms in order to jointly develop technology for the creation of innovation (Lechner et al, 2006: 524). Further specified, these networks... are relationships with other firms that allow firms the access to and the creation of new (technological) knowledge (Lechner and Dowling, 2003: 14). It entails such networks as joint research and/or development projects, licensing, and cross-licensing. These partnerships can be both vertical and horizontal Research on Technology Networks Initially, startups mainly exploit the technology base on which they were founded. However, in later stages, the startup will strive for the continuous development of their technology, which is often sought to do in collaboration with other firms. This provides a platform for the development of new technology, which is of relevance for both companies technology portfolio. Such partnerships have been shown to foster alliance formation and lead to a higher innovation rate (Kelley and Rice, 2002). A main requirement for a technology collaboration to be successful, is the existence of absorptive capacity in both companies (Cohen and Levinthal, 1990). This entails the ability to absorb the knowledge from the counterpart, which entails that there is a certain understanding of the technology. It has gained widespread acceptance within the literature, that the existence of absorptive capacity is a prerequisite for a successful LITERATURE REVIEW Defining and Exploring the Typology 40

42 mutual technology partnership. Another prerequisite for technology networks in order to create new knowledge, strong ties and socialization processes are required (Johannisson, 1998). There are three reasons why startups refrain from technology networks in the first two stages of the venture, which later become the most important network type in the third stage. First, the startup lacks the necessary reputation, which legitimates close technology collaboration with another company (Eisenhardt and Schoonhoven, 1996). Second, the lack of time and resources in the startup impedes it from engaging in such a network, as it demands many resources of each company for a fruitful outcome (Ahuja, 2000). As these resources are missing in the initial stages, technology partnerships are postponed until later stages, but initialized before the maturity of the firm. This point also impedes the number of such partnerships that a firm can engage in, as extensive time and resources are demanded. Third, it has been argued that startups initially exploit their own technology base, which also explains the postponement of this network type, as the startup needs further technology development only at a later phase (Lechner and Dowling, 2003). LITERATURE REVIEW Defining and Exploring the Typology 41

43 3.4. Effectuation Theory By applying effectuation theory, the intention is to further develop the framework which began with the model on typologies and stages of the entrepreneurial firm. As the model can help in the mapping of the startups use of networks, the effectuation theory will add an analytical layer, attempting to answer the how question, which is a central part of this study. This section will engage in a discussion on how effectuation theory can shed light on the rationale behind the startups choice of engaging in the specific network relations they have. Effectuation is a good point of departure to address this question, as the theory is based on how expert entrepreneurs think (Sarasvathy, 2001) and can therefore be assessed as a best practice framework for our study. As effectuation is a relatively new concept in academia, the rather complex notion of effectuation will be presented in the light of how entrepreneurship theory has developed over the years. This is to be followed by a solid introduction to the concepts that underlie effectuation, with a focus on the link to external relations. Lastly, it will be discussed how the principles of effectuation are seen in relation to external relations The Field of Entrepreneurship and Effectuation Theory To grasp how effectuation theory differs from existing entrepreneurship literature, a brief introduction to this string of literature and how it has developed, will be presented. It has been argued that entrepreneurship is about understanding the drivers of entrepreneurial performance (Sarasvathy and Dew, 2005). The search for such predictive variables in entrepreneurial survival has even been described as the holy grail of entrepreneurship research (Sarasvathy and Dew, 2005). This statement also entails, that entrepreneurship research is a rather young string of literature, and there are still many drivers of entrepreneurship which are not well understood (Slotte-Kock and Coviello, 2010). The academics that rushed into the entrepreneurial field of research when the discipline took off as a separate academic area in the 1970s and 1980s mainly came from management studies. This explains why their theoretical background came from the study of large corporations (Landström et al., 2012). This implied that theories were mainly based on neoclassical economics, which emphasizes rational decision-making models (Perry et al, 2012). An example of this is Drucker (1998), who argue that most entrepreneurial opportunities are discovered through a purposeful search process. This resulted in a series of management theories being adapted to entrepreneurship research (Perry et al, 2012). As the assumptions of neoclassical economics have prevailed in entrepreneurship research, most researchers assumed that entrepreneurial individuals engage in rational goal-driven behavior (e.g. Bird, 1989). This view is LITERATURE REVIEW Effectuation Theory 42

44 supported by Landström et al. (2012), who in the article Entrepreneurship: Exploring the Knowledge Base reviews the academic literature on entrepreneurship, its changing themes over years and the most influential contributors and articles. Landström et al (2012) argue that entrepreneurship research: is still based on some fairly old theoretical frameworks imported from mainstream disciplines, although during the last decade we have seen the emergence of a number of new field-specific concepts and theories (Landström et al, 2012: 1154). The statement stresses how the field only recently has started the development of more field-specific notions on how we can understand the drivers of entrepreneurship. One such emerging strategy is the concept of effectuation, which has gained a significant stronghold since it was first presented in 2001 by professor Saras D. Sarasvathy. It has been argued that the effectuation theory represents a paradigmatic shift in the way that we understand entrepreneurship (Perry et al, 2012). Emphasizing that entrepreneurs behave differently than traditional managers, the effectuation theory shakes up established entrepreneurship research. Effectuation is formulated as a general theory, or grand theory of entrepreneurship, as it has the intention of explaining the drivers of entrepreneurial performance, earlier referred to as the holy grail of entrepreneurship research (Sarasvathy and Dew, 2005). Perry et al. (2012: 857) explain that the effectuation theory has captured the imagination of researchers because it identifies and questions basic assumptions of how individuals think and behave when starting businesses An Introduction to Effectuation Theory Effectuation theory intends to take on the challenging task of explaining the drivers of entrepreneurship. The theoretical focus is on new venture creation, and Chandler et al. (2011: 380) states that the effectuation process may be viewed as a series of experiments to identify a business model that works. Thus, it can be seen as a way to create opportunities, rather than discover opportunities. At its core, the theory distinguishes between the notion of effectuation and causation as two modes of reasoning (Sarasvathy, 2001). Causal reasoning is related to classic management theory and planned strategy approach (Chandler et al, 2011). Here, focus is on an end-goal, and utilizing the most optimal means under the circumstances to achieve that end-goal. This is consistent with what most business schools teach students, and how most larger corporations work for the majority of their work; a project is initialized from an overall strategy plan of the company, a project plan with a detailed timeline and actions are set up, and this plan is then executed by employees. LITERATURE REVIEW Effectuation Theory 43

45 Effectuation emphasizes that entrepreneurs start with a general idea of aspiration, and then utilize the resources they have at hand. The resources are referred to as who you are, what you know and whom you know (Sarasvathy, 2001). The goal is not set in stone and by remaining flexible, taking advantage of environmental contingencies when they arise, and learning on the way, effectuation questions the causationbased model of entrepreneurship. Effectual reasoning is rooted in Knightian Uncertainty (Knight, 1921), and emergent planning strategy (Chandler et al, 2011). Joseph Schumpeter (1934) and his work on adaptive processes has similarities to what would become effectuation theory. It has even been stated that The effectual entrepreneur... comes closest to describing what Schumpeter had in mind (Endres and Woods, 2010). Also, the effectuation theory has a significant grounding in exploration and exploitation, which was introduced by March (1991). As concrete examples can often lead to a more comprehensive understanding, we chose to retell the example of the chef which we have encountered in various effectuation articles, which highlights the different modes of reasoning behind causal and effectual thinking. Sarasvathy (2001) explains how there are two approaches a chef can take to the task of creating a meal. Either she have decided upon a recipe from the beginning (causal reasoning), and simply need to buy all the ingredients and follow the recipe from buying the ingredient on to the list to create the meal according to the recipe. The other is the process of looking at what she has at hand in the kitchen (effectual reasoning), and imagine what meals can be done with these elements, and cook accordingly The Formation of Effectuation Theory In the light of the theory not being an established theory, this section will briefly address and discuss the legitimacy of the effectuation theory, in light of its development. The first article referring to effectuation was published in 1998 by Sarasvathy, Simon and Lave. Though, it was not until Sarasvathy in 2001 published the article Causation and effectuation: Toward a theoretical shift from economic inevitability to entrepreneurial contingency, that effectuation theory was properly defined. This article was empirically based on 27 expert entrepreneurs, based on several criteria, and by applying verbal protocol analysis, Sarasvathy derived the foundation for effectuation theory. LITERATURE REVIEW Effectuation Theory 44

46 In 2012, a review (Perry et al, 2012) of the string of literature on effectuation theory found 29 articles 3 with effectuation as a main topic. The review finds that effectuation theory has just moved into an intermediate stage of development, coming from a nascent theoretical position. Among other variables, the authors base this on a comparison of the number of articles within the subject, compared to how other theoretical concepts have evolved over time. We find this review helpful, as it gives insights into how effectuation can be perceived, in terms of its legitimacy as a central entrepreneurship theory. As it is developing with a similar trend as has earlier been the case for such theoretical concepts as the Resource-Based View (Wernerfelt, 1984) 4, we see no further reasons for questioning the validity of the effectuation theory, in terms of its evolutionary development to date Effectual Logic Sarasvathy (2001a) found that entrepreneurs are not fond of prediction, like market prediction. Instead, the expert entrepreneurs believe that... to the extent that we can control the future, we do not need to predict it (Sarasvathy, 2001: 252). They use techniques which minimize the use of prediction and allow them to shape the future. Some researchers criticize effectuation of the overconfident attempts to control the future (Ye, Fitzsimmons and Douglas, 2008), but according to Sarasvathy, the approach should be seen as an illustration of how entrepreneurs see opportunities and prepare to reshape those opportunities as they develop. The study (Sarasvathy, 2001) also finds that entrepreneurs are highly optimistic, as earlier studies suggested (Cooper et al, 1988; Lowe and Ziedonis, 2006; Hmieleski and Baron, 2009). This leads to another factor of effectual thinking, which is an entreprenuers ability to thrive on contingency: Unlike causal reasoning that comes to life through careful planning and subsequent execution, effectual reasoning lives and breathes execution (Sarasvathy, 2001b: 3). It is noted that, Under conditions of true uncertainty (Knight, 1921), unique circumstances make it impossible to draw statistical inferences (Geh, 2011), further explaining the use of effectuation in the early stages of the firm development. 3 The search criteria of Perry et al. (2012: 839): To identify the effectuation literature, we searched for mentions of effectuation in article titles and abstracts and we read each of the articles that have cited Sarasvathy (2001). After discarding articles that referred tangentially to effectuation, we developed a list of 29 articles in which effectuation was a main topic. 4 Eg. the Resource-Based View was introduced in 1984 (Wernerfelt), but it was not until 13 years later that the theoretical concept achieved a level where 10 resoruce-based view articles was written on the subject within one year. LITERATURE REVIEW Effectuation Theory 45

47 Causal Logic Causal reasoning is rooted in classic management theory, where planning, analysis and prediction are amongst the key words. Causation is similar to planned strategy approaches (Ansoff, 1988; Brews and Hunt, 1999; Mintzberg, 1978). For example, Sarasvathy found that corporate managers often believe that to the extent they can predict the future, they can control it (Sarasvathy, 2001). It is important to emphasize that effectual thinking is not an overly better strategy than causal thinking. It depends on the context and which mode of reasoning should be applied. However, as the topic of the effectuation theory is entrepreneurship, where it is argued that effectual thinking has an advantage over causal thinking, it can seem like this mode of thinking has an advantage. Sarasvathy makes a good example of this with the explanation that "effectual logic is like 1st & 2nd gear - You need them to start your business but eventually you shift away from effectual logic" (Sarasvathy, 2001b: 1). Furthermore, causal thinking is useful in domains where pre-existent goals, predictive rationality and environmental selection are the primary factors influencing outcomes (Sarasvathy, 2001) Applying Effectuation Empirically Earlier studies (Dew et al, 2009; Chandler et al, 2011; Fisher, 2012) have investigated the decision-making processes of startup ventures in relation to whether an effectual or causational reasoning was applied for taking decisions in the company. The framework developed in these earlier studies have been the point of departure for developing a conceptual framework for investigating what underlying considerations have lead to the startups engaging in network relations. As such, we build our framework on already well-developed and tested frameworks. As these earlier studies have mainly looked into effectuation and causation reasoning in an overall perspective of the decisions of the startup, we must adapt those approaches to solely focus on decisions concerning network relations Four Principles of Effectuation Reasoning Sarasvathy (2001) identified four sub-constructs, which are the principles that form the core of a rudimentary theory of effectuation (Sarasvathy, 2001: 252). It is explained how each element relates to the engagement of partnerships for the startup. These constructs will serve as explanatory factors of why network relations were engaged. LITERATURE REVIEW Effectuation Theory 46

48 Strategic Alliances Establishing alliances with external partners is a central element in the logic behind effectuation, as it is an important part of to the extent we can control the future, we do not need to predict it (Sarasvathy, 2001: 252). In the entrepreneur s efforts to control the future with the goal of maneuvering through high uncertainty, partnerships make the entrepreneur less dependent on the need to predict the future (Sarasvathy, 2001). Strategic alliances can be formed with customers, suppliers, competitors or any other strategic partner, while a strategic alliance does not necessarily continue in the form of an external entity, but can also develop into an internal partnership where ownership is offered. By obtaining pre-commitments from partners early on in the life of the venture, entrepreneurs reduce uncertainty, as responsibility is distributed among partners. Also, as risk is spread amongst multiple partners, the potential loss is constrained, making the venture start-up more affordable for the entrepreneur (Chandler et al, 2011), forging a clear overlap with the other heuristics of effectuation. Every new member who is engaged in the network adds to the pool of resources and competences controlled by the startup. The co-creational aspect is seen as a negotiation taking place through the development of the startup. While these negotiations are argued not to entail how much equity each shall control, they instead regard forming the shape of the market/company. In the context of classical network theory The idea of strategic alliances, takes departure in uncertainty as a central condition, rather than opportunism which is often linked to rational decision making theory. Under uncertainty, docility which is defined as the ability to be persuaded by others, is argued to be more useful than acting by the assumptions of opportunism or altruism (Simon, 1993). Effectuation (Sarasvathy, 2001) and docility are coupled to form a logic of precommitments. The focal company is able to engage external relations into the co-creational process, taking advantage of the ability to persuade others. Thus, the idea of the pre-commitments is a reaction to the assumptions undergirding network theory based on classical economic theory (Sarasvathy and Dew, 2003; Williamson, 1975). It is found that under conditions of Knightian Uncertainty the assumption of opportunism might not always be relevant due to the low degree of clarity regarding motivation, potential and goals which is often evident under Knightian Uncertainty (Knight, 1921).Though clearly representing an aspect of human behavior, studies show LITERATURE REVIEW Effectuation Theory 47

49 that human beings are not purely opportunistic, nor altruistic which can be seen as opposite extremes, but rather a mixture of both (Rabin, 1998). It is therefore argued how the notion of strategic alliances could be beneficial to attempt to diverge from the traditional views of network development as prediction of own motives and others motives is to a large degree impossible in the early stages of the startup. Hence, theorizing on the base of assumptions of opportunism and the antidote of trust which are broadly discussed subjects in network theory, is to some extent regarded as superfluous following the strategic alliance logic. Strategic Alliances and Network Relations The notion of strategic alliances under the concept of effectuation is a way of utilizing the possibilities of cooperation. In the end this is supposed to heighten the chances of the startup to succeed. Thus, we believe it can contribute with valuable insights for the purpose of answering our research question. Strategic alliance implies that the early stage startup involves different external relations to model the startup. Thus, it can be expected that some partnerships have had a clear influence in that sense. Therefore we find it interesting to study to what extent that has materialized in practice. It can be implied that all the relationships which are revealed in our field study carry along elements of a strategic alliances. We will only involve the most effectual network distinct partnerships and we will rate our findings as weak or strong attempt in an attempt to show to what degree a certain partnership has engaged in co-creational activities with the partnership. The current study will not include the notion of docility as the ability to persuade external relations is not the focus of this study as we expect it will require more rigorous psychological studies Means Means entail that entrepreneurs start with the resources they already have at hand (Sarasvathy, 2008). There are three categories of means: identity, knowledge base and social networks (Sarasvathy, 2001; 2008). These are often referred to as who I am, what I know and whom I know (Sarasvathy, 2001). The implications of each of those elements will now be examined. The field of basing strategic decisions on one s identity is an under-researched area. Identity, in this context, consists of preferences for particular processes or ways of living and deciding (Sarasvathy, 2008: 79). Exemplifying this, a macho identity could lead to the search for revenge, whereas a Christian identity could lead to forgiveness of the same person (Sarasvathy, 2008). One could argue that identity is not well suited as a reasoning strategy, but the following quote argues for how identity can minimize the complexity of decisions LITERATURE REVIEW Effectuation Theory 48

50 faced by startups in the entrepreneurial environment: using identity-based decision criteria frees entrepreneurs from having to order their preferences for specific consequences of their choice and allows them to take decisive action even in the face of Knightian uncertainty (Sarasvathy, 2008: 79). In regards to the entrepreneurs knowledge base, the importance of exploiting prior knowledge has already been shown to be of importance for entrepreneurs by extant research (Shane, 2000; Wiklund and Shephard, 2003). Prior knowledge relates to the entrepreneurs education, training, expertise and experience (Sarasvathy, 2001b). The social network of the startup has been shown to be of high importance in the early phases of a ventures development (Hite and Hesterly, 2001; Uzzi, 1997). This notion was also discussed in section 3.1. In the effectuation perspective, the social network is understood as both the personal social network and the professional personal network of the entrepreneur (Sarasvathy, 2001b). Notably, when social networks are seen as an embedded part of the principle of means, it implies that the entrepreneur s social network has become a reasoning mode for engaging with these relations. For example, an entrepreneur can decide to engage with a social network relation to co-create a technology development, which is then mainly based on their former relationship. It should be noted that within means, the social network of a startup involves the social relations of all the founders of the startup. With these means as a point of departure, effectuation argues that the expert entrepreneur most often starts off with a small business and execution rules over planning (Sarasvathy, 2001b). The set of means an entrepreneur has at hand changes over time, as strategic partnerships are formed and the venture changes. Also, the approach allow goals to emerge and change, and as means under ones control are exploited, it is an ongoing process of exploration (March, 1991). This principle contrasts with focusing on a given goal, which would prescribe careful planning and subsequent execution, entailing a causal reasoning approach (Fisher, 2012). Instead, the entrepreneur exerts control over the means at hand. This impedes the necessity of forecasting future events. Means and Network Relations Engaging in network relations, the notion of means is seen as a central principle, which can possibly explain the background for some network commitments. In the light of this study s focus on network relations, we find that the notion of one s social network, is the most central element of means, which can also be LITERATURE REVIEW Effectuation Theory 49

51 operationalized. We therefore delimit this study not to integrate identity based and knowledge based decisions as a part of the means principle, in the operationalization of the principle Affordable Loss The affordable loss principle seeks to explain how entrepreneurs find ways to reach a market with minimum expenditure of resources such as time, effort and money (Sarasvathy, 2001b: 5). It can be defined as a principle that involves decision makers estimating what they might be able to put at risk and examining what they are willing to lose in order to follow a particular course of action (Dew et al, 2009: 110). Rather than using expected return to calculate the needed investment amount, affordable loss emphasizes taking departure in what is already available and making a commitment with these elements (Sarasvathy, 2008). It is argued that entrepreneurs find information about the potential downside of a venture more salient than information about the potential upside of the venture (Sarasvathy, 2001; 2008; Dew et al, 2009). This should be seen in relation to the environment in which the entrepreneur act, as this is characterized by true uncertainty (Knight, 1921), which makes it near impossible to predict outcomes of the emerging venture. In the creative process of shaping a company, it is argued in line with Knight (1921) that we cannot normatively prescribe what we ought to invest because the upside is virtually unknowable (Dew et al, 2009: 108). Supporting such a view, studies have also documented how expert entrepreneurs reject predictive data on market opportunities, such as market research on new product ideas (Dew et al, 2009: 112). Also, it should be mentioned that studies also suggest that entrepreneurs may overestimatethe upside potential because of overconfidence and optimism (Camerer and Lovallo, 1999; Cassar, 2008; Casson, 2005). The affordable loss principle attempts to lower the startups resource investments in most aspects of the new venture (Dew et al, 2009). At the extreme, some ventures are launched with almost zero resources, as the entrepreneur attempts to minimize the downside losses, while accepting the risk a new venture inevitably involves (Dew et al, 2009). The decision maker therefore estimates what can be put at risk, and also what he is willing to lose, to follow a strategic direction (Dew et al, 2009). The principle is firmly grounded in behavioral theory (bounded cognition and psychology) about human reasoning (Dew et al, 2009: 109; see eg. Kahneman and Tversky, 1973). This also implies that decisions are not necessarily based on an evaluation of economic returns, but rather a much more complex process for decisions are implied (Sarasvathy, 2008; Dew et al, 2009). The notion of affordable loss is put in contrast to the normative, expected returns reasoning. Expected returns relate to causal logic, where different scenarios are laid out, and the one with the highest expected return, LITERATURE REVIEW Effectuation Theory 50

52 would be selected and followed. Such an approach is based on neoclassical investment theory (NCIT) and real options reasoning (ROR) (Dixit and Pindyk, 1994; McMullen and Shepherd, 2006; Wennberg, Folta, and Delmar, 2006; Lee, Peng, and Barney, 2007). These approaches represent the expected utility model, which has been criticized by behavioral economists (Dew et al, 2009). Where the affordable loss principle focus on the downside, as the upside is seen as unknowable, the expected return approach weighs both upside and downside equally (Dew et al, 2009). In terms of the processed information, the two reasoning modes also take different approaches. Models based on expected returns are based on an exogenous view, where the decision is based on information about factors which are outside the decision makers control. In contrast, the affordable loss principle is based on an endogenous view, where the decision is based on internal, and wellknown factors, which relates to what the entrepreneur already know (Dew et al, 2009). As opposed to models based on the expected utility approach, the affordable loss principle lacks empirical verification, as it has mainly been observed as a heuristic induced from studies of entrepreneurial expertise (Dew et al, 2009). Affordable Loss and Network Relations Engaging in network relations for early stage startups, the upside is often unpredictable (Knight, 1921). This is why the affordable loss principle can be expected to be applied for taking such decisions. For an early stage startup engaging in partnerships, the affordable loss principle implies that for evaluating the viability of a partnership, the entrepreneur will seek out and engage in relationships which have the least resource costs. By focusing on and minimizing the downside, the potential loss of engaging in a partnership is reduced, allowing the startup to engage with different networks simultaneously. This will be in line with an effectual line of thought, which predetermines how much loss is affordable and focuses on experimenting with as many strategies as possible (Sarasvathy, 2001: 252) Leverage Contingencies Leveraging contingencies is the idea of turning unexpected changes in the environment into something positive. This principle is concerned with the entrepreneur following an effectual logic that tends to remain flexible in regards of external events influencing the startup. When contingent opportunities emerge, expert entrepreneurs will see how they can leverage from this contingency. Therefore, contingencies can alter a current business model in different degrees, depending on how the entrepreneur interprets the contingency and consequently changes elements in her business model. LITERATURE REVIEW Effectuation Theory 51

53 Sarasvathy (2001: 252) argues that, in light of this principle, the need for prediction is greatly reduced. As the entrepreneur sees contingencies as possibilities that can foster a strong business, and as contingencies are defined by being unpredictable, the need for prediction is also reduced. In causal logic a great amount of energy is put into predicting the future, which achievement goals are then defined from. Most external occurrences with the potential of disturbing that picture would be sought to be minimized and avoided as much as possible. In causal reasoning, pre-existing knowledge and prediction would be urged (Sarasvathy, 2001b). While leveraging contingencies can be very beneficial at times, it should also be stated that it can be problematic to continuously react on external changes for the startup. One could imagine that continuously reacting to new possibilities might create an entity with a lack of focus which can impede the formation of the actual startup. This problem is also evident in situations where entrepreneurs become overconfident as an illusion of control might arise (Ye, Fitzsimmons and Douglas, 2008; Langer and Alberson 1983; Schwenk, 1988; Simon et al, 2000) implying that the entrepreneur might be overly reliant on own skills in situations where more uncertain factors as chance actually might be a more realistic reason. This bias might lead to underestimating the risk of choices which can have devastating impact. Leverage Contingencies and Network Relations Engaging in network relations, will in some cases be on the background of contingencies. Therefore the relevance of leveraging contingencies is clearly important when asking why a given partnership is initiated. The ability to leverage contingencies is interesting for networks as it can give some valuable information about the degree of randomness through which the observed partnerships are engaged. The ability to leverage contingencies signifies the startups flexibility and ability to react on externalities Applicability of the Effectuation Principles When studying the four effectual principles, it becomes evident that they do not contribute with insight into the mechanisms of partnerships on the same level. In the following we will suggest a simple categorization dividing up the effectual principles into two categories, and thereby avoid forcing them into the same box. We do not question that the effectual principles clearly support each other, overlap and serve to explain a mindset which is evident in the thought processes of expert entrepreneurs. Though there are no prior examples of subcategorizing the four principles in the literature for any purpose, we believe this is a necessary step in order for them to serve as a clearer framework for further analysis, at least in regards of the current study. Therefore, LITERATURE REVIEW Effectuation Theory 52

54 acknowledging that the heuristics take different perspectives on network relations and therefore have different additions to the overarching story, we will subcategorize them beneath. We suggest one group which we name origins and another, which we name strategic conditions. In the first category we have placed means and leverage contingencies. They are both explanatory to how the partnerships emerged, in the sense that they signify what mindset led to the opportunity for an engagement. They take the perspective of two broad explanations representing an effectual method of attaining network relationships. Engaging in network relationships, following the notion of leverage contingencies signifies the situations where external events e.g dinners, conferences, sports etc. suddenly throws off an opportunity for an engagement. Means, on the other hand, are pre-established personal ties which are exploited (Sarasvathy, 2008). The two overlap in the sense that leverage contingencies can be said to be a flexibility or agility mindset which serves the startup to take advantage of occurring externalities, while these externalities can rise through preestablished ties. An example could be a social relation who has been promoted to a position where she can make decisions in the company she works, which could benefit the startup. In the second category, strategic conditions we argue to fit affordable loss and strategic alliances together. These two serve as conditions which are sought to be respected and achieved when engaging in relations, and opposite Origins, these do not explain a method or preference suggesting which overarching possibilities are exploited for the emergence of engaging with external partners Causal Reasoning Causation is based on the inverse of effectuation: Causal models begin with an effect to be created (Sarasvathy, 2008: 16) and Causal logic help us choose; effectual logics help us construct (Sarasvathy, 2008: 73). In opposition to the principles which have been stated as underpinning the effectual reasoning, such specific principles have not been developed for assessing the causational mode of reasoning. In the following we therefore identify causational elements, such that causation, like effectuation principles, can explain engagement in network relations. We also argue that the causal approach can be seen in line with the strategic conditions above for the sake of this study. Causation entails having a clear and consistent vision for where the startup wanted to end up with the network relationship (Chandler et al, 2011; Fisher, 2012). It is the notion of assessing a potential relationship for what long run opportunities it might bring, and select the relationship which is believed to provide the best return LITERATURE REVIEW Effectuation Theory 53

55 (Chandler et al, 2011). The startup thus believes that it can predict the future, as the future is seen as a reflection of the past. This makes a planned strategy approach (eg. Porter, 1980; Schoemaker, 2002; Ansoff, 1988; Brews and Hunt, 1999; Mintzberg, 1978). These pre-selected, strategic end goals are set by the startup alone, and therefore do not involve the network partner in this process. Moreover, the strategic planning can also imply writing a project plan for the network relationship, which specifies how the relationship is to be developed (Fisher, 2012). This process involves the network partner, with whom specific strategic milestones are laid out to be achieved. The importance of causal reasoning is neither degraded compared to effectual reasoning in theory, nor for the purpose of this study, but it is found to be more appropriate to emphasize effectual reasoning for the early developmental stages of a venture (Sarasvathy, 2008). Thus, causal reasoning will not figure in the propositions which are argued for in subsequent sections. Due to the fact that this thesis is not based on empirical data which has been gathered from expert entrepreneurs which alike effectuation, we argue that the necessity of involving causation as an explanatory factor is evident. As it, like affordable loss and strategic alliances signifies an approach to engage in external relations, rather than an opportunity, it is placed under the category of strategic conditions for the purpose of clarity. A table summarizing the above discussion is found below. Table 5. Effectuation principles as origins and strategic conditions Origins Means Leverage Contingencies Strategic conditions Affordable Loss Strategic Alliances Causational Reasoning Source: Own development LITERATURE REVIEW Effectuation Theory 54

56 4. CONCEPTUAL FRAMEWORK Introduction Types of Network Relations Principles for Engaging Linking Network Relations and Effectual Principles This chapter introduces our theoretical framework, which is based on the literature review in the previous section. The section is divided into three parts, serving as the structure for the subsequent analysis. First, we assess what we expect to find empirically for the case companies networks types engagement. Second, we operationalize the effectual principles, and set out expectations about what explanatory abilities we expect. Third, we propose how we might see links between the engaged network types and the principles for their engagement. 55

57 4.1. Introduction In this section we will propose how we expect startups to behave, when investigating which networks they engage in, and how they do so. Thus, this section serves as a transition from the conceptual theory review into empirically testing our framework. The section is separated into three parts. This allows the analysis part one and two to first assess the individual theoretical constructs, before these are linked in the third part of the analysis. Hence, the sub sequential analysis is structured according to the conceptual framework presented below Types of Network Relations In section 3.2, we have sought to argue for the benefits of involving the Relational mix (Lechner et al, 2006) in the current study. In the literature review, we found the Relational mix to be a valuable framework for identifying network relations engaged by startups. As it is argued by Lechner et al (2006), the sequential development of startups resource needs leads to an evolvement in the use of egocentric network ties. This extended need of resources entails moving from reputational networks towards relations requiring a higher degree of effort to exploit; marketing relations and especially co-opetition and technology network relations (Lechner and Dowling, 2003). These relations can provide additional resources. The shift happens over the period of stage 1 through stage 4 (Lechner and Dowling, 2003). However, it is argued that in stage 1, reputational network ties are still dominant. As reputational networks are not considered a high involvement relation, the shift is thus argued not to materialize within stage 1. The sequential transformation in the characteristics of engaging in relationships is not unique to the Relational mix, as similar findings are also evident in the other articles which the Relational mix has been compared with in this thesis. However, as explained in section (3.1) the shift which is proposed by this literature is already seen within what we have defined as stage 1. Hence, we expect that reputational network relations are strongly represented, other more resource craving network types than reputational, are also to be found in Stage Principles for Engaging As the framework is not specifically developed for the purpose of determining the behavior of startups in relation to network relations, we are aware that there can be limitations to the explanatory effects of this framework. Below are our propositions for the second part of the outlined analysis. 56

58 Means Considering the early stage of the ventures, the literature suggests that more emphasis is on the existing network relations, entailing both social and professional relations (Hite and Hesterly, 2001; Uzzi, 1997), which is termed means by the effectuation principles. The social relations are people related to the entrepreneurs who exist in a social network. They are already trusted and their skills are well known (Sarasvathy, 2001b). To exploit such relations is arguably a main source of a startup s external relations (Hite and Hesterly, 2001; Uzzi, 1997), and is within this framework seen as the origin of a relation. Therefore, it is expected that case companies, to a high degree, will exploit their means in their pursuit of network relations. This entails exploiting relations who have origins within their already existing network when the company was founded. We interpret means as strongly present, marked, if the relationship had evolved from an existing relationship of the startup, such as customers, suppliers, etc. For a weak association ( ) to be present, the relationship was initiated with a social or professional relation, outside the existing relations of the firm Leverage contingencies Startups are in general characterized by acting in an environment which is by definition unpredictable (Knight, 1921), which is only signified by the early stage of the case companies. This entails that few elements have been set in stone, which would also entail the external network relations which have been engaged. Exploiting external contingencies (Sarasvathy, 2008) can take many forms. Taking into consideration the young nature of the companies, we argue that it is highly likely that the case companies have applied this principle for engaging with external relations. This would imply that origins of a relation are based on leveraging contingencies. If the contingency is not clearly external we perceive the link to be weak ( ). For example, if a startup had directly pursued a partnership, which an externality then suddenly enabled and thus was leveraged by the startup, we believe it entails strategic elements which is not a clear leverage contingency origin. If data showed a clear leveraging of a contingency, leading to a sudden new relationship, it is perceived as strong ( ) Affordable loss The early stage case ventures most often have very limited resources, as they are characterized by the liability of smallness (Stinchcombe, 1965) and newness (Baum, 1996). When engaging with external relations, they would therefore be expected to reduce the resource investment and hence focus on the downside, rather than the upside (Dew et al, 2009). Often, the economic resources of a startup are limited, which is why we argue that the case companies apply the principle of affordable loss as to minimize the economic downside of entering into a relationship. 57

59 This principle is marked as weak ( ), if affordable loss was interpreted as one among more factors for the strategic conditions of engaging. A strong interpretation ( ) indicates a primary focus on this principle, when the relation was engaged Strategic Alliances By engaging in a strategic alliance, the close partnership entails that by co-operation, two or more companies can leverage more resources than on their own. It should be noted that this principle can be interpreted to different degrees, in terms of how close a collaboration should be, in order to have this principle present. We argue that too broad a definition would easily entail all relations of the startups, as long as they provide input, which would degenerate the applicability of including the principle, as it would not provide any value to the analysis. Hence, relationships should be close and entail considerable co-creation for this principle to be present. In general, Strategic alliance partnerships would be expected to be present, as the co-creation with other companies, provides a significant resource input for the startups (Sarasvathy, 2001). The strategic alliance principle is marked as strong ( ), if there was a significant, and very close collaboration, implying strong mutual benefits for both partners. If it is observed that there, to some degree is a strong engagement, but it is not judged to be as strong as other observations the relation is marked as weak ( ) Causation Causal reasoning, as presented in section 3.4.5, is expected to be present. In the overall management of a venture, most firms would be expected to be planning and laying out options to choose from to some degree, which resembles a causal reasoning approach (e.g. Porter, 1980; Ansoff, 1988). By this, we would also expect that the ventures approach relations in this manner. Specifically, startups could be expected to demonstrate a causal logic approach when co-operating with incumbent firms, as these are characterised by causal reasoning (Sarasvathy, 2008). Causation is rather broad in scope, and it is not the intention of the current study to distinguish the causal reasoning approach into subgroups. It is included to try to gain a more complete picture of entrepreneurs reasoning. If we find that the observed startup has strategically chosen, planned how to approach and then contacted specific relations, it is interpreted as a strong evidence ( ) for causation. If the startup has been obligated 58

60 by the external partner to engage in comprehensive contractual agreement, goal setting etc., while not itself actively assessing the relationship strategically, causation is interpreted as weak ( ) Linking Network Relations and Effectual Principles This section will seek to bridge the theoretical streams of literature, which represent theoretically-based assumptions of our expectations of how the reasoning elements (Sarasvathy, 2001) are linked to the types of network relations (Lechner and Dowling, 2003). We emphasize that, to the knowledge of the authors, there has been no earlier attempts to link the two theoretical constructs. The conceptual framework represents propositions which are chosen as they represent the strongest possible links. Thus, we do not propose how all four network types can be linked to all four principles, but rather we outline the links which are most likely, according to the knowledge within the field Reputational Relations - Means Literature suggests that reputational relations are pre-conditions for economic exchange (Larson, 1992), which is why the relationship with other firms can be an important reputational or signaling effect (Stuart et al., 1999; Gulati and Higgins, 2003; Deeds et al.,2004). This can assist a startup to overcome the liability of newness (Stinchcombe, 1965), and increase firm performance (Larson, 1992; Gulati and Higgins, 2003; Roberts and Dowling, 2002). Possible reputational relationships, however, may still be reluctant to engage with the startup, as economic exchange with entrepreneurial firms are perceived to be risky (Bhide, 2000). The above proves somewhat contradictory, as it highlights the importance of engaging in a reputational relationship for a startup. It also shows why incumbent companies may be reluctant to co-operate with an early stage venture, making it difficult to attract the very same reputational relations for the startup. We emphasize that it is the new venture which is lacking reputational resources, which makes incumbent firms reluctant to engage with the startup. However, the entrepreneurs of the startup often possess a reputation by themselves, often because of earlier work experience, which can be leveraged for the benefit of the venture. Research shows that social relations of the entrepreneur are often more prone to engage in a relation, as they base this on an existing trust-relation, which have been shown to impede opportunism and uncertainty (Lechner et al, 2006). By exploiting their social and professional network, the entrepreneurs can engage with relations who are associated with other organizations which can in turn become associated with the startup. We propose that reputational relations originate from means as the main principle, implying that the startup draws upon individual strong ties (Granovetter, 1973) of their social networks, which have led to reputational relations, and hence reputational resources. 59

61 Marketing Relations Affordable Loss Engaging in a marketing relationship implies that the external relation directly commits resources for the startup. This can vary from providing valuable information, to committing more tangible resources for the startup. Hence, marketing relations is a way to obtain external resources related to marketing activities, as to accommodate for the limited internal resources (Stinchcombe, 1965). To minimize the resource needs of engaging, but still exploiting the possible external marketing resources, it is found likely that the startup would emphasize the downside, which implies minimizing the risk of engaging. We therefore propose that the marketing relationships are likely to be engaged on conditions which resemble the affordable loss principle. This implies that the startup has a focus on the downside, and invests a minimum of resources, as to minimize the risk of engaging, but still exploiting the external marketing resources (Dew et al, 2009) Co-opetition Relations Strategic Alliance Engaging in network partnerships with competitors is a possibility the startup can exploit in order to reduce uncertainty, enhance R&D and innovation and reach economies of scale (Sarasvathy, 2008; Kelly and Rice, 2002; Gnyawali and Park, 2009). These all hamper the effect of the liability of smallness (Baum, 1996) and newness (Stinchcombe, 1965). In the event where competitors engage in an alliance, it is often because they share some relationship which - whether it being technology, customers, other partners - can be combined and in conjunction extend their businesses. In other words, it creates a bigger pie (Brandenburger and Nalebuff, 1997). Co-opetition network ties require a higher degree of engagement (Lechner and Dowling, 2003) and therefore depend on a strong mutual engagement. The goal of co-creating a bigger pie instead of competing for the existing market shares is closely related to the idea of the strategic alliance principle, and the similarities are evident. Referring to the section on strategic alliances, though the principle of strategic alliances and that of co-opetition stem from different theoretical background, it is noted how both implicitly attempt to overcome whatever element of opportunism there might be present in the relationship, which is a clear obstacle when engaging in partnerships with competitors (Loebecke, Van Fenema, Powell, 1999; Gnyawali and Park, 2009; Sarasvathy and Dew, 2005). The notion of strategic alliances requires strong engagement ( Sarasvathy and Dew, 2005), which is also the case for co-opetition (Lechner and Dowling, 206). Thus, it is expected that the startup will actively seek to engage the partners to contribute with a lot of effort. We therefore expect that strategic alliance is the central principle which will be found in cases of co-opetition network ties. 60

62 Technology Relations Strategic Alliance and Affordable Loss When engaging in a technology network, the arrangement is quite similar to that of partnering with a competitor (Lechner et al, 2006). The focal firm seeks to further develop their technology in collaboration with the partner while the engagement often leads to innovative technologies which both parties can benefit from. It therefore resembles co-opetition in the sense that a high degree of engagement is necessary, as superficial collaboration impedes the value output in this sense (Johannisson, 1998). In the subsection, Defining and Adapting a Framework (2.3.5) we found that technology networks are not likely to be developed in the early stages (Lechner and Dowling, 2003). However, due to the need of resources which is evident for startups in the stage we study, we argue that some degree of external collaboration in relation to developing the startups software will emerge. We therefore suggest, that if our empirical studies are to reveal that these types of ties are established, it can be implied that the affordable loss principle is part of the explanation. This means that the startups have, to some degree, assessed through available information what the possible downside of the partnership would be, and engaged in the partnerships only if the downside was perceived as low. In the nature of co-creating technology with an external partner lies also an element of pre-commitment between the respective partners. Co-developing new technological features, which both parties can benefit from, clearly resembles the tight collaboration between the entities as explained in the principle of strategic alliances (Sarasvathy and Dew, 2005). Hence, it is expected that if technology networks are engaged in, they are so on behalf of the strategic alliance principle, due to the high degree of engagement this would require. Moreover, they are engaged with, only if the downside is low, signifying that the principle of affordable loss is also evident. 61

63 5. ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Introduction Tradeshift Echo.it Billy s Billing Opeepl Cross Case Analysis The first part of the analysis focuses on which network relations the case companies engaged with. The approach is an individual case study where relations are categorized within our chosen typology framework. A concluding section will provide a cross-case analysis. 62

64 5.1. Introduction This part provides insights to which external relations each case company engaged with since the venture s legal creation. Each relation is related to one or more of the four network types, which is related to what resource(s), according to the case company, the relation brings to the startup. As such, for each relation, it will be justified why we find it related to the chosen network category. An important notion to the analysis is that what is described took place when the relationship was established for the first time. For each network type, the respective relations are listed in chronological order, beginning with the earliest relation Tradeshift Case Description Legally established in 2009, Tradeshift is a cloud-based platform targeting the business-to-business segment where all business interactions can be carried out. Starting out with e-invoicing services, the company has expanded their product to include other business interactions between companies. The vision is to become the biggest platform for all business interactions (Tradeshift Blog, 2013). Tradeshift s competitive advantage is their ability to reach a 100 per cent e-invoicing solution from the start, and their ability to engage the suppliers in the industry. The business model is built such that larger companies pay for the service, while smaller businesses can use the basic services for free. This is a central reason for why Tradeshift has been able to secure a high adoption rate amongst suppliers of larger companies. In relation to the other case companies, Tradeshift is furthest down the road in terms of growth. We therefore restrict our focus to the network engagements which the company had engaged in primo This to align the developmental stage of the company to the other case companies. Tradeshift is founded by CEO Christian Lanng, CSO Mikkel Hippe Brun, and CTO Gert Sylvest, who all had careers in the international B2B trade industry, prior to founding Tradeshift. They brought their reputation to the company which created leverage (Int. 1, Tradeshift). Combined, they had a great network which was beneficial in establishing Tradeshift as a market player. Since their foundation, and even prior to it, the founding team adopted a strategy of making Tradeshift active in public discussions of technology s advantages in making worldwide business more efficient. Tradeshift ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Introduction 63

65 always countered the opinion of the establishment, which brought a lot of publicity and support their way (Int. 1, Tradeshift) Reputational Network Relations The founding team of Tradeshift had already established a name through working in industries related to Tradeshift. This helped them along the way, but based on the interviews it can be implied that it was not enough to progress and therefore they pursued more reputational partnerships. The reputational networks take different forms, from ties with other individuals, to ties with large organisations. Tradeshift used reputational networks in the following ways. First of all the resources were obtained which might not have been accessible without reputational ties. Moreover, reputational networks were used for advertisement reasons when approaching other stakeholders while the relations were also stated on the webpages for legitimacy reasons. In relation to the latter, these stories were also often pushed to medias for them to makes stories Morten Lund When the founders of Tradeshift decided to legally establish the company, one of the first network ties they engaged with was Morten Lund. Morten Lund is an iconic Danish entrepreneur and venture capitalist most famous for his involvement in Skype and ZYB. Morten Lund quickly contributed to Tradeshift in a reputational sense. Through his network, he attempted to recruit developers for the project. As Morten Lund was a relatively famous name in the tech startup scene, he has a range of followers who do not hesitate to respond to his requests. In this case, Twitter was the platform which enabled the contact between Morten and the developers. Through his very association with the startup, IT development teams were formed in three different continents with only compensation being in the form of equity. Moreover, Morten Lund also has good relations with investors as he has made many people very wealthy over time... So if Morten says, I have an interesting company, I think you should take a look at it.. And all the venture people, he could just call them and say, I am in London Monday, I want to present to you a new company then they clear up their calendar (Int. 1, Tradeshift). In regards of customer acqusitions the founders of Tradeshifts own names were more beneficial. ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Tradeshift 64

66 So Morten has done a lot of good for us especially in regards to investors, but in regards of customers, our own names carried more weight than Morten s, because we had this street credibility in our field. So we didn t exploit Morten in that sense (Int. 1, Tradeshift) Jon Bosak Jon Bosak is an American IT specialist who has co-developed XML, and initiated coding language standard called UBL. He was approached by Tradeshift in order to partner up in the early stages of Tradeshift. Jon Bosak is a well-known and respected personality within certain circles of interest for Tradeshift. Tradeshift actively engaged in public debates relevant for their industry, where they often criticized the established solutions 5. Jon Bosak was instrumental in creating a platform from where Tradeshift could criticize incumbents, as UBL was an open source standardized language which the startup would leverage as part of their service. The rest of the market was rather fragmented impeding efficient trade. We have sought the arenas for fights, and then we got into them Every time a new proposal came from incumbents or political organs we have always strongly disagreed (Int. 2, Tradeshift) PayPal PayPal was also one of the first connections into which we got insight. PayPal were the first to invest money in Tradeshift. They got a seat in the board and equity in Tradeshift. PayPal is a transnational online payment service which amongst other things ensures that there is actually money available to transfer in a buyer-seller transaction. Partnering up with PayPal involved Tradeshift to integrate their services up against PayPals existing solution meaning that Tradeshifts software would be digitally interconnected with that of PayPals. In such, Tradeshifts product becomes an extra service which PayPal offers to their own customers. Due to the size of PayPal, this partnership had a strong signaling effect for Tradeshift. The CEO reckons: We got an investment from PayPal. And that was really a seal of approval.. When you are to go out and offer a solution to a big company, then they ll say, will you also be around in two months? Do I dare to tide my company to a startup company who doesn t earn decent money? So that means [that you can tell them], well, PayPal invested in us, so you can sleep good at night (Int. 1, Tradeshift). In practice, the engagement with PayPal was actively used in two profound ways, namely for engaging with media, and simply naming the partnership. A small Danish provocateur 6 had partnered up with the large 5 This is further analyzed under the Reputational network type, Media. 6 More on this later (where) ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Tradeshift 65

67 American PayPal, which created hype and drew the attention from media. This led to articles in the famed technology-oriented startup media TechCrunch 7, creating an international awareness about Tradeshift. The second use was for their own webpage. Partnering with PayPal was used in reputational sense as Tradeshift actively advertised with the partnerships on their webpage, both through blog posts but also as a static element on visible parts of the webpage TDC TDC is one of the biggest Danish companies and also meets the criteria of the strategy of approaching C20 index companies. Tradeshift thus saw TDC as an interesting prospect. The engagement between Tradeshift and TDC ensured strong signaling value for TS. The founders of the startup often named this partnership when interacting with media or other public organs. The following citation signifies the use of TDC in their external communication when approaching potential customers and other stakeholders: If you have an agreement with TDC, then you can go out on the market and say, we already have TDC as customers etcetera and you need that first customer who is willing to take a risk with a young company and then benefit from VIP treatment (Int. 2, Tradeshift) Additionally it was found that TDC, like other reputational partnerships, were listed as customers on Tradeshift s webpage to gain leverage and thereby ease the road to new customers, partners etc Media Media was to a high degree leveraged in conjunction with the mentioned partnerships above. When new partnerships were engaged, Tradeshift would approach relevant news media, to engage in a story on the subject. Their provocative and disruptive behavior within the industry was instrumental in gaining publicity for Tradeshift in the media. This was exploited to expose the Tradeshift name and gain reputation. Over time, Tradeshift has built relationships with specific journalists, which are considered reputational relationships Marketing Network Relations Tradeshift utilized the nature of their service to get information or utilize reputation which provided openings to new customers and markets. 7 ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Tradeshift 66

68 It can be implied that the large companies which Tradeshift has partnered with - PayPal and TDC - have had an influence on opening up new markets and customers PayPal PayPal also took position as a marketing tie which had a unspecified, but positive effect in regards of acquiring new customers and stepping into new markets. This is reasoned by the fact that Tradeshift integrated their solution up against the PayPal software and were therefore allowed to get access to the supply chain which PayPal is a part of. The nature of Tradeshifts products entails that it makes sense for customers and partners to try to integrate their own supply chain to use Tradeshifts service and therefore Marketing networks characteristics can show up every time Tradeshift gets a customer onboard. Part of for example engaging in the agreement with PayPal is to get access to and market our service in their network. That s when an investor can be strategic, and open up new markets for you. And about our customers, I do not know if I would call them a marketing network, but we are a network company. The value of Tradeshift rises as [we get customers and can onboard their supply chain] (Int. 1, Tradeshift). Moreover, through contractual agreements, Tradeshift ensures that the large companies also continue to be marketing networks. There is a clear strategic initiative towards tapping into their supply chain. Our contracts have also had some clauses which read, that if we are not allowed to onboard the suppliers in their network, then we have to be compensated for that. Especially in the beginning, if we had given them a very sharp [competitive]price where we would say that, we can only give it to this price, if you also promise us to go out to your suppliers and promote Tradeshift as the solution you have chosen (Int. 1, Tradeshift) TDC The engagement with TDC, which is also categorized as a reputational tie, also served as a marketing network tie. The reason is that Tradeshift used TDC, being a customer, to give feedback on their product. Tradeshift utilized that to further develop their service. They helped us mature our platform They have been easy going when we made mistakes (Int. 2, Tradeshift). Thus, it can be argued that this feedback is valuable in developing their solutions which Tradeshift can incorporate to better suit future large customers Technology Network Relations Tradeshift used different kinds of technology networks for in order to of developing initial versions of the software, while later on also for further development of the IT system ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Tradeshift 67

69 External Developers From the initial steps of the development of Tradeshift, external developers were engaged to construct the software architecture of the startups platform. Though the founders of Tradeshift already had developers capabilities inhouse, they sought for additional resources externally in order to fulfill the task. Morten Lund, through his reputation in the international startup community persuade external developers to join the Tradeshift team to develop the platform. These external developers were instrumental in creating first prototypes of Tradeshift, but were later replaced with internal developers. Moreover, as they were remained external to the startup, these external relationships are regarded technology network tie Jon Bosak In the early stages of the history of Tradeshift, the founders allied themselves with John Bosak for the reason that they saw value in the new language standard technology he was working on, namely, UBL. Jon Bosak was funded by Tradeshift to pursue his vision of making UBL a standard language, just like XML. Bosak can be said to be a technology relation as he co-developed UBL, getting input from Tradeshift. The language was useful as it provided a central building block of the Tradeshift software product, and it would have the potential to spread virally to customers, and their customers: His [Jon Bosak] vision was that the standard could get spread virally like XML and be used all over (Int. 2, Tradeshift). In the end Tradeshift and Jon Bosak work towards building a universal IT language which could disrupt the existing fragmented incumbents which Tradeshift would be recognized for.however, due to political reasons and competition, the language has yet to reach the expected viral effect. The cooperation regarding developing XML is hence seen as a technology network tie Software Development and Design Companies (Names not displayed) Also early on in the lifespan of Tradeshift, partnerships were engaged with IT development companies, which according to the CSO, were among the best in Denmark. Together with in-house developers 8, they made the Tradeshift service more professional. The design development company professionally created the whole identity for Tradeshift, entailing videos and other design related tasks. Since these companies received equity, and as a consequence were paid a lower wage, we see them as partners rather than mere suppliers. 8 Obtained through Morten Lund ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Tradeshift 68

70 Tradeshift Main Findings The following table provides an overview of these relations, with a summary of what the core of the relation involves, and what network categories were found adequate for each relationship. The table lists the relations chronologically, according to when they were engaged. Table 6. Network relations of Tradeshift, according to type Tradeshift relations External developers Morten Lund Jon Bosak IT/Design development Purpose Development of prototypes Legitimacy and access to developers in early stages Legitimacy and development of important coding language Software development X X Marketing PayPal Legitimacy and access to customers X X TDC Legitimacy and product feedback X X Media Legitimacy through media coverage X Source: Own development Reputational Coopetition Technolo gy X X X Tradeshift, having reached a more mature stage than the remaining case companies, is also one of the most diverse in regards of network ties. It is clear however, that the two main typologies which have been engaged in are reputational and marketing network ties. Surprisingly, many technology network ties were found in this case Echo.it Case Description The mission of Echo.it is to... use web-based technology to promote desirable behavior and create better data-points for implementing corporate strategies and reach targets in organizations (Int. 1, Echo.it). The company provides an internetbased service for companies, where employees can share their actions or echos with colleagues. Colleagues can get inspired from others work and like or comment on posts. The concept is inspired by social media platforms, such as Facebook. The goal is to unify the company culture and let colleagues inspire each other with great ideas, creating more engaged employees. As the CEO Stefan Madsen states, It can prompt sharing of behavior that wouldn't normally be shared (Arcticstartup.com, ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Echo.it 69

71 2012). The platform is built on gamification-elements, which is the platform engagement driver. Users are awarded badges for their actions, also called echos, which receive many likes. The platform provides access to data which management would otherwise not be able to quantify. The statistical module shows the management if company targets are met, and they can award departments rewards for meeting certain goals which were set on the platform. The company was founded in They have received business angel funding twice. The company has two founders: Stefan K. Madsen and Ida Adler Olsen. Asides from the founders, the company employed three other employees as of April Reputational Network Relations The reputational relations provide Echo.it with established names, which they state on their website, and in personal meetings with other stakeholders. Echo.it showed that they are highly aware of the importance of their reputational relationships as a startup DSB The partnership with DSB, which is the biggest train operator in Denmark, has been strategically important in reputational building, from an early stage of the venture s development. The relationship with DSB is unique for the company, as they have only engaged in one partnership, where a customer was acting as a pilot tester of the ventures service offering. The partnership with DSB was established in the very early stages of Echo.it. In early 2011, DSB agreed to be the first company to implement Echo.it into the department of S-Tog, based on a six-month free license. Echo.it could then also use them as a reference, and they were to publicly tell about it (Int. 1, Echo.it). The product was well-received within DSB, as DSB was able to promote a series of positive news articles which ran in national news, local news, and online media. DSB had a strong interest in promoting positive stories about themselves, which was helpful for Echo.it as it led to free publicity where Echo.it was associated with a major player. As the project leader within DSB put it: There's a little pioneering spirit in this, and there are some companies that now have become interested in learning more about the way we have done it (Jonas Bladt Hansen, project leader, DSB S-Tog in Computerworld, 2012, freely translated). In this regard, DSB was acting as an important reputational partner in order to gain new customers. DSB was Echo.it s first company relation which resembled a reputational aspect. The CEO emphasized how the youth and lack of other reputational relations made this first relation with DSB more difficult to close: That s ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Echo.it 70

72 why it took really long time for us with DSB, because we had to become accepted by ourselves. That s difficult! (Int. 1, Echo.it) Large Consultancies Echo.it has relations with three consultancy companies: Bro Kommunikation, Hill & Knowlton and Quadric. These relationships are engaged as marketing relationships, and as such mainly engaged to provide market information and actively promote sales. This will also be further explained within the category of marketing network relations. According to the CEO of Echo.it, they often serve as reputational relationships as an extra advantage of the relationship (Int. 1, Echo.it). They are reputational because they are well-established companies, which have great influence on the legitimacy of Echo.it for other potential stakeholders. More specifically, when the first relationship with Bro Kommunikation was engaged, it became easier to convince the other consultancies to come aboard. Echo.it could refer back to their already existing relationship with a related company IBM Partnering with IBM was a leap for Echo.it, as IBM represents one of the Big Four software companies. As the CEO explains (Int. 1, Echo.it), he refers to the Big Four as IBM, Microsoft, Oracle and SAP. These all are multinational companies, accounting for a large part of the software market, and are well-established names within the software industry. An association with these will influence the reputation of a software startup. Since IBM is a well-known name, with a wide industry perspective, this reputational relationship was leveraged on different levels and platforms Other Stakeholders Echo.it engages in several semi-structured network relationships with students, researchers and bloggers. These relationships lead, for example, to the use of Echo.it in research articles by Ph.D. students and a discussion of the company on blog posts. According to the CEO, this is an important step in gaining legitimacy as a startup: It counts a lot more than you think (Int. 1, Echo.it). He mainly relates this to how the company becomes more established if others publish material about Echo.it. This is important for the company when they are researched by possible buyers, for example (Int. 1, Opeepl) Marketing Network Relations Marketing network ties are a great part of Echo.it s network ties. Mainly, these serve as strategic sales partnerships, but they go beyond the mere economic relationship. Echo.it also engages with industry experts to gain knowledge on the industry development. ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Echo.it 71

73 Rasmus Aaen Rasmus Aaen was a main person behind the company SuccessFactors, which has similarities with Echo.it. SuccessFactors is a SaaS company and to some degree offers a similar product as Echo.it. Rasmus Aaen is no longer part of SuccesFactors, but has engaged with Echo.it on an informal level to provide general industry insights: Rasmus Aaen has been critical to our start he managed to make us see things, which we were not aware of (Int. 1, Echo.it). By providing highly valuable market information, Aaen has been instrumental in the development of Echo.it in the very early stage Large Consultancies The dominant network ties within marketing networks are three partnerships with large consultancy companies which operate within strategic communication. These partnerships are all characterized by a similar setup and will be discussed altogether. The first of these relations to emerge was with Bro Kommunikation. The main purpose of the partnership was to provide Bro Kommunikation with the Echo.it platform, as a part of the portfolio of Bro Kommunikation, they use when they approach their customers. This model was successful fairly quickly. Echo.it was thus interested when Hill & Knowlton later approached them to engage on similar terms. Quadric was approached proactively by Echo.it. As the setup is similar for all three partnerships, they can be cross-compared. These partnerships were engaged as a sales channel, but are seen as more than a mere exchange partnership, as they provide other resources for the startup. The consultancies have engaged with Echo.it in the further development of the platform, as they have provided valuable inputs from their direct contact with customers. The consultancies are aware of their respective clients needs, meaning that these marketing ties provide Echo.it with valuable information for product and market development: Regarding the partners, they know much more about when they [clients of the partner of Echo.it] are ready for the product than we do (Int. 1, Echo.it). The consultancies have played a central role in the early stage of Echo.it s development as a solid sales channel. They also provide valuable inputs for the further development of the Echo.it platform. CEO of Echo.it sums it up in the following: and that s why partnerships are brilliant for startups especially regarding the big organizations it can be very difficult to become accepted as partner So it can be a good idea sometimes with these partnerships, as they are already certified to do business with their customers (Int. 1, Echo.it). ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Echo.it 72

74 Independent Consultants Resembling a similar setup as with the larger consultancies, Echo.it has also engaged with the independent consultants of Klaus Lund and Sarah Gregersen. According to the CEO, these consultants are experienced personalities within the field, and enjoy benefits which are not available to Echo.it: They have experience and an existing trust-relation with senior members in the companies within their fields, which make it a lot easier (Int. 1, Echo.it). Similar to the larger consultancies, this enables the consultants to present Echo.it to possible customers, helping Echo.it overcome any reputational issues they experienced in their very early stages when promoting their product themselves Co-opetition Network Relations Echo.it has no relationships with competitors. This category will not be represented in the further analysis of Echo.it s network types Technology Network Relations Sortedam Ventures To develop the software for the product, Echo.it partnered up with the technology company Sortedam Ventures, which specializes in developing IT for startups. Together, they have developed and further refined the Echo.it platform. This makes Sortedam Ventures a central partner of the startup Echo.it Main Findings The above have highlighted ten external relations in which Echo.it engages. The following table provides an overview of these relations, with a summary of what the core of the relation involves, and what network categories were found adequate for each relationship. The table lists the relations chronologically, according to when they were engaged. ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Echo.it 73

75 Table 7. Network relations of Echo.it, according to type Sortedam Ventures DSB Technology development First customer, pilot-testing of platform X Marketing Rasmus Aaen General industry insights X Bro Kommunikation Strategic sales partnership X X Klaus Lund Strategic sales partnership X Sarah Gregersen Strategic sales partnership X Ph.Ds, bloggers External publishing on Echo.it X Quadric Strategic sales partnership X X IBM Joining IBM Partnership Programme X Hill & Knowlton Strategic sales partnership X X Echo.it relations Purpose Reputational Coopetition Technolo gy X Source: Own development With the exception of one technology partnership, Echo.it has only engaged in marketing and reputational relationships. In many cases, these overlapped; the marketing relations often provided a reputational function as well Billy s Billing Case Description Billy s Billing offers an online small business accounting software, which seeks to make accounting as accessible as possible through user-friendly software using non-complicated language. The software allows you to do a range of functions which are necessary when running a business, like managing bills, accounts receivable, balance, result, VAT results, etcetera. The startup was legally established at the end of 2010 by the founding partners Toke Kruse and Sebastian Seilund. The company has since experienced substantial growth and currently has 10 employees. In the beginning of 2012, the founding team decided to move to San Francisco to further scale the company, as the circumstances for investment in Denmark were found inferior. The headquarters of Billy s Billing is now located in San Francisco. ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Billy s Billing 74

76 The CEO Toke Kruse has been very active in various medias, and holds positions in various startup advisory boards while also appearing as expert blogger in the Danish startup community, Amino.dk Reputational Network Relations The approach of Billy s Billing was a bit untraditional compared to the other case companies. The only type of reputational tie they approach was the media. They nevertheless put a lot of emphasis into this which also seems to have made an impact as they are often seen in the Danish media News Media Three different media outlets were identified as reputational network ties which Billy s Billing approached for the sake of obtaining legitimacy. These were namely TV2, Børsen and Berlingske - some of the biggest media outlets in Denmark. While the former is a television channel, the two latter are major Danish newspapers. Moreover, Billy s Billing partnered up with various blogs, on same terms as the other outlets. It seems reasonable to describe these in general terms in the section as the value gained through these outlets is very similar. In general, the Danish news media have played a central role of legitimizing Billy s Billing s product and have very much been the reason why the CEO has put that much emphasis on developing this network. The CEO already had experience with utilizing media in order to gain recognition and it was therefore a natural path to continue. Moreover Billy s Billing partnered up with a PR agent in order to consult on the process towards exploiting the media. As media exposure can take a negative turn due to misunderstandings between journalists and story providers and for other communicational reasons, it can be a double-edged sword. However the CEO of BB has had a series of positive outcomes from contacting and engaging media in their stories. They provide you with a lot of legitimacy. And if you are in TV2 people think it is impossible to get in. I don t know who told you that in school... But people really take notice [when you get into TV2] (Int. 1, Billy s Billing) Billy s Billing has generally strategically assessed the different outlets as they have waited for the right moment where their stories would be relevant. In the case of Berlingske, the following quote exemplifies that: I just wrote them because I could see I had a story which could fit in with what they were writing about (Int. 2, Billy s Billing) Marketing Network Relations Billy s Billing had clear goals of approaching other service suppliers to partner up with, whose customers who could potentially see value in a cloud-based auditing application, which could complement the service they ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Billy s Billing 75

77 already use. The approach is captured in the following citation: I also know that from other startups, that as soon as you take the leap and start integrating up against other companies products, and get access to their customers you really take a big jump! [red. It has a positive impact] (Int. 1, Billy s Billing) Danløn Danløn is a wage management service provider, who has a large customer base in mainly Denmark. The CEO of Billy s Billing saw that Danløn could potentially benefit from providing Billy s Billing s service to their own customers and was also an obvious target due to their large customer base. Unfortunately, Billy s Billing has yet to reap the full potential of this partnership, which is largely due to Danløn s unwilling ability to cooperate. The reason can be found in the following: So in the beginning we experienced they didn t think it [a partnership with Billy s Billing] was that interesting because we didn t have that many customers I can see that they had difficulties in understanding that if we coupled our program to theirs, their program would get better, and therefore they will be able to gain more customers themselves. They had the classical understanding that, okay if you come with if you are to reap the benefits of our customers, and that I would if we integrate, then we also want something from you (Int. 2, Billy s Billing). This partnership, it is argued, can be categorized under the marketing network category as the alliance with Danløn potentially opens up for all the customers they have as Billy s Billings service will be bundled into Danløns. However, as seen in other cases the partnership did not lead to the expected value, as it was argued that Danløn could simply not see the value proposition in the partnership for themselves Webshop Platforms The web platforms could not be specifically named in the interview for secrecy reasons. One platform was compared to Shopify, which is an american SaaS company offering, cheap and user friendly solution for companies who want to set up an online shop (Int. 1, Billy s Billing). Their customer bases are attractive in the sense that their services, which is a cloud based web shop solutions, could benefit from complementary products which Billy s Billing offers. Though the partnership has not fully developed, like in the case of Danløn, the webshop platform has functioned as a marketing network tie providing Billy s Billing with access to potential customers. Hence, it is categorized as a marketing network relation. ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Billy s Billing 76

78 Technology Network Relations SEO Company One of the partnerships which have been more difficult to categorize is the one with a traditional search engine optimizing (SEO) service company. The partnership developed from merely being a supplier-buyer partnership to one where the supplier had so close connections to the focal startup that, It is almost as if they were employed by us (Int. 2, Billy s Billing). Though it is not argued that the fitting is perfect, it is decided that the SEO-company belongs under the technology networks. The company is supporting Billy s Billing in co-developing a technical aspect of running the startup, which seems to be a rather important know-how for the startup: We do so [engage in the partnership] because I see it as an important value to have internally in the company (Int. 2, Billy s Billing). There is also a degree of co-development which the following citation signifies: It s a little funny partnership, because normally you would just outsource and say, okay now - SEO optimize What we have done is that we have hired them as consultants, but they took it a step further and build our internal SEO team and work together on that... That is more than they would normally do... They optimize our business on behalf of our interests (Int. 2, Billy s Billing) Billy s Billing Main Findings The following table provides an overview of these relations, with a summary of what the core of the relation involves, and what network categories were found adequate for each relationship. The table lists the relations chronologically, according to when they were engaged. ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Billy s Billing 77

79 Table 8. Network relations of Billy's Billing, according to type Billy s Billing relations Purpose Børsen Creating legitimacy and hype X Tv2 Creating legitimacy and hype X Danløn Webshop hosting Strategic sales partnership and platform feedback for development Strategic sales partnership and platform feedback for development Marketing X X Reputational Coopetition Technolo gy SEO company Develop internal technology skills X Source: Own development To sum up, the resources which seem to be sought for by Billy s Billing, shows a common picture which is also seen in the remaining case companies. Reputational and marketing network ties figured as dominant. Billy s Billing seemed to be more proactive in regards of the media why it can be signified that reputational resources had been important. Moreover it was seen how two partnerships with larger established companies did not add the value which was hoped Opeepl Case Description Opeepl is a mobile-based analysis company that delivers data via surveys. The surveys are sent by text messages to consumers, and answers are with the Opeepl platform customers within an hour. The short response time is a main competitive advantage of Opeepl, together with the relatively low prices of the surveys, starting at 700 DKK. The concept is described as: We want to be the market analysis answer to Google Adwords (Markedføring Online, 2013, freely translated). The technological platform has been build in-house, and is a pure SaaS solution. Customers can send questions and receive answers without any involvement from Opeepl. In order to complete this setup, Opeepl have teamed up with a company which operates an SMS-gateway (Coolsms) and a company which have the panelists to answer the questions (Yougov). According to Opeepl, no other company has the same functionality as the Opeepl technology. Opeepl believe that their product is well suited for the small- and medium-sized businesses: We see an enormous potential in the SMV segment the companies which today are not doing market analysis because of the costs and resources associated with them (Markedsføring Online, 2013, freely translated). Opeepl has provided large companies with fast feedback on ideas or other relevant strategic considerations, where ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Opeepl 78

80 customer opinions are important. Companies such as Carlsberg and McDonalds have used their service (Markedsføring Online, 2013). The company was founded in 2009 by three co-founders; two technical founders and one business founder. Initially, the company was run in their spare time, until the CEO, Morten Korch-Haahr went full time in early 2012 to further drive business development and sales. In early 2013, the company closed their first round of financing (Børsen, 2013) Reputational Network Relations For Opeepl, the reputational relations are mainly used by presenting them on the website to provide legitimacy to the product (Int. 1, Opeepl). This is done by highlighting cases on the website, and explaining that a wellrenowed analysis company is in charge of the panelists, which provide the data for the customers Yougov Yougov is a Nordic analysis and consultancy company, which specialize in market and stakeholder analysis, and has an extensive panel (Yougov.dk, 2013) 9. The partnership with Yougov played an important role for Opeepl, as the startup leveraged Yougov s reputation in terms of the reliability and trustworthiness of the panel when approaching stakeholders: When we use Yougov, it provides some validity (Int. 1, Opeepl). Different from the major companies, Yougov mainly provides legitimacy for the panel, as it is a well-known brand and among the 25 largest research institutes globally (Int.1, Opeepl) Major Customers Opeepl very explicitly leverage their major customers as reputational networks, by quoting them on the front page of their website alongside their logo. There is a section of cases on the Opeepl website, where each case of these reputational ties are further explained 10. The CEO of Opeepl explained that the explicit use is intended to establish trust with potential customers, as the reliability of their panel can largely be a trust-element. The CEO of Opeepl explained the importance of the major customers as reputational networks: these provide much value, because we can use them as a reference on the website (Int. 1, Opeepl). Specifically, it emphasized that if potential customers can see that established companies such as Carlsberg and McDonalds are using the platform, that credibility is reflected on Opeepl (Int. 1, Opeepl). 9 As of 2013, Yougov has a panel of persons within the Nordic countries (Yougov.dk, 2013). 10 See cases at ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Opeepl 79

81 Go Aften Danmark A minor partnership has been set up with the TV program Go Aften Danmark, where Opeepl gain some publicity, some validity, and they gain some cheap analysis (Int. 1, Opeepl). Opeepl is mentioned as the source of the data, when Go Aften Danmark uses their service, providing a marketing function for Opeepl. Opeepl have leveraged this by showing short film clips on the website from Go Aften Danmark, thus showcasing how their service is used by a nationally known TV station Marketing Network Relations The marketing network ties of Opeepl range from important industry information from individuals, to closer sales partnerships with a major company. The all provide valuable resources for Opeepl MetroXpress The partnership with MetroXpress was the first partnership for Opeepl, and the first attempt for Opeepl to approach a main concern, which was having access to a panel which could provide data for the venture s market analysis. The partnership entailed that MetroXpress would print advertisements for Opeepl, which invited the readers to join the Opeepl panel. The advertisements were free of charge for Opeepl, and would be printed when MetroXpress had unsold ad spots. In exchange for the advertisements, MetroXpress would get a cut of the revenue generated on the basis of the established panel. By these means, Opeepl intended to build their own panel for market analysis. In 2010, Opeepl realized that their partnership with MetroXpress was not sustainable for two reasons. First, the speed of gaining panelists were not sufficient in order to build a solid panel for Opeepls purpose. Second, and importantly, the representativeness, and hence the quality of the panel recruited through MetroXpress was not satisfactory in order for Opeepl to be able to deliver the quality of market analysis needed for their customers. This led to a termination of the partnership with MetroXpress in We define MetroXpress as a marketing relation of Opeepl. MetroXpress played an important role in Opeepl s way to the market Coolsms The company Coolsms delivers IT-infrastructure in terms of an SMS-gateway to handle mobile text messages for larger groups of people. This provides the link between the software developed by Opeepl and the panelists of Yougov, and is as such, an economic exchange as a normal supplier. Coolsms is primarily a service supplier ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Opeepl 80

82 for Opeepl, but the CEO of Opeepl emphasized that Coolsms had engaged in the further development of the Opeepl software. This is why it is seen as more than a mere exchange relationship. Coolsms have provided Opeepl with market information about the possibilities with text messages, how they can leverage smartphones for their services, and also specific input for new customer development (Int. 1, Opeepl). Hence, both parties have gained more than a simple exchange of payment for a service in the relationship Yougov The partnership with Yougov can be divided into two different elements. First, Opeepl can leverage the panel of Yougov when performing market analysis for customers, which is part of the SaaS solution of Opeepl, why it runs 100 percent automatically. The agreement entails that Yougov gets a cut for each panelist which Opeepl uses for market analysis. Second, the Opeepl software has become a part of the sales portfolio of Yougov, when they approach their customers. The CEO of Opeepl explains: First and foremost Yougov use our system, on their panel simply a white label supplier of software They use our system, and have to sell it then also. And then we charge money for it (Int. 1, Opeepl). Yougov constitutes a highly important strategic partnership for Opeepl, as the core product of the market analysis is based on the panel to which Yougov provides access. Underlining the partnership as a marketing relation of Opeepl, it clearly provides access to new customers and markets through the white label version of the product. By partnering up with Yougov, Opeepl leverages the resources of an incumbent company, instead of using many internal resources on building their own panel. This was the initial approach with the earlier partnership with MetroXpress Per Møller A highly influential relation of Opeepl is Per Møller. As an investor, Per Møller has provided Opeepl with extensive insights into business aspects of running a startup: He can challenge us and give inputs to what to do next (Int. 1, Opeepl). He invested in the company in February 2013 (Børsen, 2013) Co-opetition Network Relations Opeepl does not engage with any competitors. This category will therefore not be represented in the further analysis of the network types of Opeepl. A remark about their take on competitors is still appropriate. The market for market analysis is dominated by incumbent companies, which have full-service market research offerings, mainly based on consultancy services. As Opeepl does not offer consultancy services, but only the ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Opeepl 81

83 raw data, the CEO concludes: We don t really see them as competitors, we see it as we are creating a new market (Int. 1, Opeepl). It should be implied how such a view is in line with the effectual thinking of to the extent that we can control the future, we do not need to predict it (Sarasvathy, 2008: 91), as Opeepl sees themselves creating a new market within market analysis for their product Technology Network Relations Opeepl has no technology relationships. This category will therefore not be represented in the further analysis of the network types Network Relations of Opeepl Main Findings The above highlighted six external relations for Opeepl. The following table provides an overview of these relations, with a summary of what the core of the relation involves, and what network categories were found adequate for each relationship. The table lists the relations chronologically, according to when they were engaged. Table 9. Network relations of Opeepl, according to type Opeepl relations Purpose Marketing MetroXpress Panel recruitment through newspaper ads X Yougov Coolsms Major customers Go Aften Danmark Per Møller Source: Own development Providing panelists, selling white-label solution SMS-gateway, technical feedback and market information Proof of concept, market information and valuable references Close media partner for getting publicity and using as a reference Investor providing market insights and network X X X X X X X Reputational Coopetition Technolo gy The relationships of Opeepl centered around reputational and marketing relationships, whereas co-opetition and technology relations are non-existing. For Opeepl, the partnership with Yougov is critical and highly central for the company, which was highlighted in both interviews with the CEO of Opeepl. Only one relationship, namely that of Go Aften Danmark, has been engaged with a main purpose unrelated to the marketing category. In addition, the reputational relations are Yougov and major customers, where the reputational aspect is an extra benefit to the core of the relationship. ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Cross Case Analysis 82

84 OPEEPL ECHO.IT TRADESHIFT April Cross Case Analysis Our research which is looking into the case company network relations has revealed some interesting findings. Overall, it seems as if the typology proposed by Lecher et al (2006) is actually rather accurate in functioning as an umbrella for capturing and defining different networks which early stage startups engage in - though with a few surprises. Nevertheless, it was often encountered that the network ties which we found empirically would overlap several of the categories of the Relational mix leaves room for subjective judgment. This is a challenge when comparing to qualitative empirical data. Considering stage 1 as described by Lechner et al (2006) which is the focus of this research, it is found that both reputational network ties and marketing network ties are predominant. We also observed a number of technology network ties. The figure below summarizes the findings from each case, in relation to the network types. The table lists the relations chronologically, according to when they were engaged. Table 10. Overview of network relations of all case companies Startup Relation Reputational Marketing Co-opetition Technology External developers X Morten Lund X Jon Bosak X X IT/Design X PayPal X X TDC X X Media X Sortedam Ventures X DSB X Rasmus Aaen X Bro Kommunikation X X Klaus Lund X Sarah Gregersen X Ph.Ds, bloggers X Quadric X X IBM X Hill & Knowlton X X MetroXpress X Yougov X X Coolsms X ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Cross Case Analysis 83

85 BILLY S BILLING April 2013 Major customers X X Go Aften Danmark X Per Møller X Børsen X Tv2 X Danløn X Webshop service X SEO Source: Own development X Reputational Network Relations The affiliation with external entities with a more well-renowned and established image than that of the startup itself is a widely used method in our case companies and also prescribed as by Lechner and Dowling (2003). In all cases there were found large companies which the case companies had engaged with to gain reputational resources. Moreover, there were also examples that the reputational tie was actually a single person who had gained popularity and respect, which the startups could benefit from. The reputational network ties were often announced on their websites, while the startups also often mentioned their names when speaking to journalists. Moreover they were also often named when approaching new customers Marketing network relations When taking our expectations into account, it was surprising to observe the large number of engaged marketing ties. Engaging in marketing network ties involved that the case companies searched the market for other companies with services which their own service could integrate as a complementary product. Through that, there was a possibility that the startup could get access to that company s own supply chain. These partnerships were often perceived, at least from the startup s view, as win-win situations. Both companies would benefit from each other and potentially satisfy and serve more customers. In other situations, marketing network relations were engaged with as customers, in the sense that they merely sold the startups service as part of their own service. Moreover, it was also observed how other network relations were engaged with external individuals and customers who merely contributed with market information. We saw examples of both large and smaller companies, as well as individuals involved as important marketing networks ties. While the larger companies were often those which the startup either integrated or pursued for network access, the smaller companies and individuals were providers of market information and applying the startups service as part of their own. ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Cross Case Analysis 84

86 Thus, marketing networks either actively sold the startup s product to third parties, or marketing network ties agreed to market the startup s product to their own supply chain. We also encountered that other relationships were merely providers of information which was useful to the startup in terms of, for example, customer acquisition. Hence, in all three cases these network ties led to new customers or information enabling better assessment of specific customers or markets Technology Network Relations We found some examples of technology network relations which, according to Lechner and Dowling (2003), would not be expected to be found within the time-frame relevant to this study. These findings were therefore surprising. The technology network ties were in most cases external relations that cooperated with the startup in order to develop the startups software. Technology relationships helped to further develop the product for two of the case companies, where they played an instrumental role in providing technological resources. The codevelopment often initiated early in the life of the startup Co-opetition Network Relations As also found by Lechner and Dowling (2003) and Lechner et al (2006), co-opetition networks were not evident in our empirical data. Hence, we will not go further into co-opetition network relations in the subsequent sections of this study Summing up The current analysis showed clear evidence acknowledging the expectation that, in the scope of time we study, the case companies would to a large degree engage in reputational and marketing network relations, while to some degree, technology networks were also found in the empirical data. As the Relational mix is defined in terms of the resources which the different categories contributed with, we found that the ties which were engaged in contributed in the following ways: Legitimacy from reputational ties was clearly obtained. New customers and market information were obtained through marketing ties The startups software was further developed through technology ties ANALYSIS PART 1 TYPES OF NETWORK RELATIONS Cross Case Analysis 85

87 6. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Introduction Tradeshift Echo.it Billy s Billing Cross Case Analysis The second part of the analysis focuses on explaining how the company engaged in their network relations. We study each case individually and argue how the effectual principles are explanatory factors to the engagement approach. The section concludes with a cross-case analysis. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Cross Case Analysis 86

88 6.1. Introduction This section goes beyond the relationship and looks into the reasoning for engaging in these relations. With the framework laid out, this encompasses both origins and strategic conditions for the relationship as possible explanatory factors. If any elements go beyond the capabilities of this framework, these will of course also be presented, as to show a complete picture of the factors. For each case company, relevant inputs from the firm s view on external stakeholders engagement, will briefly be introduced Tradeshift External Developers As mentioned in the Reputational section about Morten Lund, external IT developers were involved from a very early stage to develop the software needed utilizing Morten Lunds network. Through the use of online social networks he persuaded developers to apply for a position in Tradeshift and work for free, only paid with equity. He sent out tweets to his followers, where he asked if someone wanted to work for free on a new and interesting project, against stock in the business. And that there was I think we got 200 applicants. And within a week we had three development teams up and running with 4-5 developers on each team. One in Peru, one in Sri Lanka, one in Aalborg. (Int. 1, Tradeshift). As all these developers were not paid but rather offered equity for their service minimizing the downside, we believe this is a strong case of affordable loss. Moreover as the external developers had an important role, together with the remaining developers, of co-developing the core software for Tradeshift s we find it evidential that a high degree of engagement was necessary implying a strong degree of the strategic alliance mindset Pay Pal Tradeshift had early on in the company s lifetime taken upon them the strategy to be loud on criticizing incumbent solutions and thereby defining their own company as a reaction to the established. At one event, the CEO of Tradeshift made a presentation to a banking industry event with the provocative headline, Why banks will fail. Representatives from PayPal attended this conference and noticed the opposing style of which Christian Lanng (CEO, Tradeshift) had shown on scene and had awakened their interest. Paypal representatives approached Christian in a break, and not long after the first coffee meeting was set up: As an example, we would probably not have met PayPal as we did, had Christian not stood up and made his presentation called Why Banks Fail ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Introduction 87

89 He stands up and gives that presentation at a banking conference! And if you don t have the guts to stand up and do that, you won t get the jumps which you will need. That was a defining moment for the partnership with PayPal (*23,53, Int. 2, Tradeshift). The quote above signifies that there was a strong relation between the principle of utilizing sudden opportunities arising and the engagement in the partnership between Tradeshift and PayPal. The background for the establishment of the partnership can be characterized as involving the leverage contingencies principle as it was induced by a chance. Another principle which was clear is that of affordable loss which we find strong. Equity was given to PayPal as compensation for investment and for opening up for Tradeshift to engage with PayPals customers which stands opposed to other methods of customer acquisition we judge the downside to be comparably low. Moreover, as the alternative for an investment would be that Tradeshift had to borrow this capital from a bank or other lenders which most likely would entail debt, we judge the act of trading equity in for investment is a minimization of the downside as well. As with many of the other partnerships, the approach to engaging with PayPal also entailed causal elements. When getting involved in a company of this size, there is a due diligence process where both parties study each other and the partnership in order to make a contract which both can be satisfied with. However, the contracts are not focused much on the future, but more rooted in the present, as noted by the CEO of Tradeshift. You cannot plan much more than 5-6 months out in the future. You got to have [more focus] on what is just around the corner than what is further out [in time] (Int. 2, Tradeshift *31.40 ). Also what Tradeshift experienced was that the plans and visions which were actually made became irrelevant; what happens is that the persons you had relationships with disappear out of the organisation, and suddenly nobody knows what it was all about (Int. 2, Tradeshift). However as Tradeshift had not themselves assessed PayPal before, we perceive the causal element to be weak Hence we observed that both leverage contingencies and affordable Loss serve as explanatory factors, while causal reasoning was also part a represented principle. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Tradeshift 88

90 TDC TDC was the first of the strategically assesses C20 index 11 to showed an interest in using Tradeshifts product. Entailed in the position as customer also were elements of partnership, as described in analytical part 1. Principles were found to be activated in regards of this partnership. Through already established relations, it was possible through a couple of links, to reach the right people with decision making power in TDC and thereby established the partnership. Therefore, one of the weak underlying mechanisms for this partnership is means, in the sense that Tradeshift utilized already established ties to make their way into the organisation. Means is not perceived as strong as the link did not lead directly to the engagement It can be implied that Tradeshift used TDC to test their system to get rid of all the unexpected errors that might be in a product like the one Tradeshift offers: They almost got it free in the beginning and that was for being able to use them for references and that they would do reference calls with new customers et cetera (Int. 2, Tradeshift). The partnership probably inhibited Tradeshift from many errors (Int. 2, Tradeshift) had they just pursued various customers from the beginning without eliminating process errors as happened here. In that sense it can be implied that affordable loss is playing a central strong part of the reason as well As with most other partnerships, where one party is an established player on the market, causal elements are seen here. The degree of clearness was high regarding what partnership the engagement should entail (Int 2, Tradeshift). Moreover, it was revealed that the pursuit of c20-index companies was a strategy which was agreed upon amongst the founders of Tradeshift implying a causal element. Thus we argue that the causal elements were strongly represented Software Development and Design Companies Two clear principles were evident in the case of these partnerships. These partnerships are bundled into one category as the approaches were similar to the degree that differentiating between them is irrelevant. Tradeshift already had connections in the companies established through working together with them earlier under other endeavors. These connections were utilized to get in talks with the companies, which all are amongst the best at what they do in Denmark. Therefore the interviews showed a strong influence of the means principle. 11 Largest group of public companies in Denmark ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Tradeshift 89

91 The process of the already established connections to convince the board in the respective companies and the later contractual construction was rather causal in itself. Strategies were written down and negotiations and renegotiations were performed to continuously have both sides satisfied with the partnership. Elements of the causal approach is therefore also evident. Moreover, Tradeshift had a strategy dictating that only the best software- and design companies were good enough. This further adds evidence to a causal approach which we therefore argue is strong. These partnerships were also based on a strong affordable loss principle. No money was transferred between the two, but rather service hours from the partners credited with equity in Tradeshift allowing Tradeshift to get high quality material from the very beginning without having to put down great amounts of cash Morten Lund Morten Lund had a great impact on Tradeshift, and the establishment of this connection can very much be contributed the Leverage Contingency principle. The founders of Tradeshift being long time Twitter followers of Morten Lund one day saw Morten Lund post as questions which gave a natural chance for the Tradeshift founders to help and thereby create a connection Jon Bosak The founders of Tradeshift already knew Jon Bosak from previous work, and therefore already had established the connection. That is argued to show a strong use of means as an origin for this partnership as it was preexisting relations which turned into a partnership of value-adding character. Moreover, as also taking the role as a technology relation, the strong engagement which is entailed in that type of relationship signifies a strong degree of strategic alliance in the relation Media Detailed Information about the engagement with journalists representing different media was not obtained in the case of Tradeshift. However, it can be applied that the engagement with the Media have to some degree been supported through a causal reasoning. This was evident in the way that Tradeshift pursued the strategy to chose sides distancing themselves from the established market and thereby making themselves interesting for the media. It was found that this resembles a causal approach as Tradeshift actively pursued media with their provocative external communication. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Tradeshift 90

92 Tradeshift Main Findings The figure below sums up which principles were found present for the relationships, and the strength of these, as outlined above. Table 11. Network relations of Tradeshift, according to reasoning for engaging Relation Means Leverage contingencies Affordable loss Strategic alliances Causation PayPal TDC IT/Design Morten Lund Jon Bosak Media External developers Source: Own development The principles undergirding the network relation engagements of Tradeshift show reveals a rather confusing picture where it seems all approach are evident without supporting any of the effectual principles particularly. The most evident is means, implying that several of the partners were engaged on behalf of a pre-established ties Echo.it Sortedam Ventures Echo.it gave up equity when they engaged with Sortedam Ventures. The terms allowed for the technology company to provide their services for a much reduced rate: We got a sellable product very fast and also cheaper than otherwise (Int. 2, Echo.it). For Echo.it, this partnership had the clear advantage of limiting the direct loss on invested technology if the company was to fail. It engaged with Sortedam Venture because they had a stronger interest in Echo.it s success if there was equity at stake. This provides strong support for the affordable loss principle. The technology company was, especially in the very early phase, a central strategic partner in the efforts to build a sellable product. The CEO of Echo.it explains that the people at Sortedam ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Echo.it 91

93 Ventures has been crucial in how the development of the platform was formed, and it was for example clearly Simon [Sortedam Ventures] who brought the whole gamefication angle to the platform. This is found to be a strong presence of the strategic alliance principle. The partnership came into being by close network relations of the CEO, which support a strong means approach to the partnership DSB At Echo.it they had the intention of starting with the most difficult client in the most difficult market (Int. 2, Echo.it). According to the CEO, this approach did not entail that they were focused on landing a specific company, but rather they tried to approach several larger companies which they thought could see the value of using the Echo.it platform. One lead was a reference from a board member, from which Echo.it was given a reference to a vice president at DSB. With no exisiting relation between Echo.it and the vice president, it was a cold call to start with. After initial meetings, the parties agreed on a setup where the S-Tog division of DSB would become the first customer of Echo.it. We find that there is a weak relation to means, as the relation has been initiated by networking, but it was not a critical element in reaching engagement. The agreement of the partnership entailed a dialogue, where it was agreed that as a first customer would pilot test the platform. DSB would be provided with an initial period where the platform would be made available for free. The upside for Echo.it was the possibility of testing the platform on a large scale within a working business environment, and the reputational effect it could have. Such a resource is highly valuable for a startup. With a lack of economic resources, the approach of exchanging resources other than economic ones is a prime example of affordable loss, which is why we find this principle to be a significant factor. As an early customer of Echo.it, DSB was prepared that the platform was not a finalized product, and smaller errors and the like could be expected. On the other hand, as the parties would collaborate closely on the integration of the platform, DSB had an opportunity of shaping the direction of the platform in terms of their needs. As such, this early partnership can be defined as a weak form of strategic alliance, as it was an important early partner for Echo.it, and they provided much valuable feedback for the development of the platform. The partnership did not, however, entail a further integration and co-development, so the strength of the strategic alliance partnership is not seen as significant. Setting up the partnership with DSB entailed much detailed planning. In the initial stages, detailed planning was laid out for how they could reach a planned launch date. As the platform was launched, goals for specific goals ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Echo.it 92

94 were set, like the number of Echos in that period of time. For these goals, Echo.it argued for a three month time-frame, and not six months which S-Tog proposed. We find that these long term elements constitute a weak form of causation, with the argument that most of these elements were suggestions or requirements of DSB, and not Echo.it. As DSB is a large company, the causational reasoning has to some extent been a product of partnering with a large company, where bureaucracy and certain procedures are to be followed. Being a small player, Echo.it was required to comply with the lines set out by S-Tog (Int. 2, Echo.it) Rasmus Aaen Through Echo.it s business network they made contact with Rasmus Aaen. This is why means is a strong principle explaining the origins of the relationship. As Rasmus Aaen had undergone many of the developmental processes which Echo.it faced, there was clear value in engaging him from Echo.it s perspective. Fortunately, he was interested in sharing his knowledge. Because of legal clauses, this relationship has been limited to an informal approach Consultancies For the consultancies, the first partnership with Bro Kommunikation has to a large extent constituted a precedent for the following consultancy partnerships. The partnership with Bro Kommunikation will therefore be examined thoroughly, as it represents the reasoning which led to the remaining consultancy partnerships. If relevant, other consultancy partnerships will be mentioned, to highlight relevant differences. The partnership with Bro Kommunikation was initiated by Echo.it s social network contact, who knew the founder of Bro Kommunikation. That person set up an initial meeting between the two companies. This approach has similarities with how the relationship with DSB originated, why we find that means is present in a weak form. Initially, Echo.it had strategic intentions of engaging with human resource consultancies, as the platform is mainly seen as a human resource management tool, but initial attempts to engage with such HR consultancies showed no results. To approach Bro Kommunikation was therefore not an indented strategic goal, but Bro Kommunikation showed great interest in their service and the partnership was set up. The consultancy partnerships are all based on a licensing model, where the consultancy partner takes a share of the revenue generated from customers they sign on to the Echo.it platform. Furthermore, they most often sell consultancy services as a part of the platform integration on top of this, which can be a significant revenue for the partner. This arrangement differs slightly among the partners, but for Echo.it, it has been important ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Echo.it 93

95 that all parties see the partnership as a significant upside for their consultancy. This setup allows for a resource exchange between the parties, where the downside for Echo.it is at a minimum, thus emphasizing how the setup is strongly based on the affordable loss principle IBM The partnership with IBM came into being when IBM read about Echo.its partnership with DSB. Based on that background, they contacted Echo.it to further discuss the possibility of Echo.it joining the IBM Partner Programme. As the CEO of Echo.it had just been encouraged to seek out more partnerships by a venture capitalist, with the argument that per cent of exits are with partners, IBM seemed like a prospective partner for Echo.it. The partnership was initiated, and there have been talks about Echo.it becoming a part of the portfolio in the consultancy department of IBM. However, this has not materialized yet, and the CEO of Echo.it highlighted a central aspect: You have to recognize, that it takes a lot of resources, but I think that in the long run, it can be really good (Int. 2, Echo.it). Thus, the background for the partnership was based on the principle of leveraging contingencies, which was exploited by Echo.it. The scope of the partnership was at the time of engagement unknown, and has to date not shown significant impact for Echo.it. Though, to date IBM has been a strategic partner for Echo.it as a reputational network, but the motivation of engaging was to a certain degree influenced by the possibility that IBM can be a possible purchaser of Echo.it in a longer time perspective. Such a long term goal-oriented perspective of Echo.it is interpreted as a weak degree of causation Other stakeholders For the semi-structured relationships with Ph.Ds, bloggers and others, the CEO explains: We have many... I m not sure how to categorize them... people who want to talk to us, and some of them we keep in close contact with (Int. 1, Echo.it). This interest from external parties contacting Echo.it mainly according to the CEO - stems from the hot-topic nature of gamefication. Echo.it is, according to the CEO, one of the only companies applying it as the central idea of a commercial company. These relationships almost solely stem from the external parties contacting Echo.it, and they most often engage in these meetings. This can be related to a strong element of leveraging contingencies, as possibilities, where the possible scope is unknown, are sought Echo.it Main Findings The figure below sums up which principles were found present for the relationships, and the strength of these, as outlined above. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Echo.it Main Findings 94

96 Table 12. Network relations of Echo.it, according to reasoning for engaging Relations of Echo.it Means Leverage contingencies Affordable loss Strategic alliances Causation Sortedam Ventures DSB Rasmus Aaen Bro Kommunikation Klaus Lund Sarah Gregersen Ph.Ds, bloggers Quadric IBM Hill & Knowlton Source: Own development Overall, the principle of affordable loss is the main identified principle, which highlights that Echo.it paid much attention to minimizing the downside of the engagements. More specifically, the venture has to date solely invested resources in terms of time and effort, but avoided the use of economic resources by finding other ways to engage. Apart from the affordable loss principle, the remaining principles are only present to a smaller degree Billy s Billing Danløn and Webshop Platforms As described in analysis part one, Billy s Billing found it valuable to engage in network relations with Danløn and the webshop platform company due to the size of their customer base. As covering these in individual subsections would lead to excessive repetition it is deemed sensible to explain both here. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Billy s Billing 95

97 The CEO of Billy s Billing had identified a range of companies which was assessed beneficial to partner up with. Moreover, there was an agreement about terms and goals of what this partnership between the two parties which was very detailed, as asked for by the external company (Int. 2, Billy s Billing). For these reasons we find strong evidence of a causal approach. What Billy s Billing pursued in their network ties was to acquire customers through getting access to the customers of these companies, as also seen in most of the other case companies. We perceive such an approach to be a clear indication of a strong presence of the affordable loss principle Media An important unexpected reputational network, which became evident in our interviews, was the media. In general Billy s Billing has been relatively causal in his approach to these partnerships due to the fact that the CEO had in collaboration with a PR partner decided on a strategy to approach media signifying a rather strong causal approach: It was just a standard approach media gives credibility if we can get a partnership and a relation to the media, then we can tap into what they have built over several centuries but it s an ordinary PR strategy They don t write about anything which they think wouldn t interest their readers so if you can understand the form for what readers want to have, then you can also easier get into a partnership with media (Int. 2, Billy s Billing) Berlingske In regards of the approach of Berlingske, Billy s Billing simply approached the journalists which they had built relations with in order to tell them about a story which they thought might be interesting to them. Thus, as a pre-existing relationship was utilized we find that there is no doubt about the presence of the means principle why it is found to be strong. Also we argue to have a strong degree of causation as the approach was explained as a traditional media strategy where the PR partner was envolved signifying a strong emphasis on a strategic assesment Børsen In the case of Børsen, the CEO of Billy s Billing embraced the possibility which arose from a focus on cloud computing they had at the time. He contacted Børsen to tell them that they are on their way with an auditing program based in the cloud, which Børsen could see the benefit of. Hence, this network tie seems to be ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Billy s Billing 96

98 realized through an external event which Billy s Billing had success in complementing with their story and it can therefore be proclaimed that a strong origin of Leverage Contingencies was evident Tv2 In the establishment of the network relation with Tv2, an externality was also exploited in two different settings. One of the employees at Billy s Billing participated in a dinner where he met an employee from Tv2. The Tv2 employee happened to work in the department which writes about entrepreneurs and finance. At the same time the PR person who is associated with Billy s Billing wrote Tv2 to tell them that Billy s Billing has a story which they might find interesting: Then there was suddenly two approaches to the same department which made them see that it would make sense [to bring a story about Billy s Billing] (Int. 2, Billy s Billing). Thus, it can be implied that leverage contingencies was a strong parameter defining the approach to this partnership SEO Company After having a rather disappointing experience with a SEO company located abroad, the CEO of Billy s Billing was looking for a new supplier. At a conference he randomly met another CEO from a smaller company offering this service. The CEO of Billy s Billing could see how they also had a lot of smaller companies as customers. This engagement led into a strong partnership beyond the supplier-customer relationship where the SEO company stretched its boundaries to deliver services which they have not offered to other customers before. Besides offering regular SEO services they also educate employees of Billy s Billing in the skill. It is a fact that Billy s Billing is a big customers for the SEO company which might be the direct reason for the supernormal efforts they may put into this relationships. Others might point at the fact that modern suppliers are obligated to deliver more-than-expected services to keep and win customers. However, as the following quote signifies it is tight, it is almost as if they were working internally here (Int. 2, Billy s Billing). We argue that the network relation is more than just modern supplier and thus proclaim that there are elements of co-creation in the sense of the strategic alliance. The CEO of Billy s Billing could have chosen not to talk to this person, or simply just not succeed in creating the relation and thereby not succeeding in seizing this opportunity. Due to the coincidence laying behind this engagement it can be implied that the origin lays in the leverage contingencies principle. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Billy s Billing 97

99 Billy s Billing - Summing up The figure below sums up which principles were found present for the relationships, and the strength of these, as outlined above. Table 13. Network relations of Billy's Billing, according to reasoning for engaging Relations of Billy s Billing Means Leverage contingencies Affordable loss Strategic alliances Causation Børsen Tv2 Danløn Webshop service Berlinske SEO Source: Own development Leverage contingencies and Causation are the two strongest principles which explanatory to the approach of engaging in the dyadic ties. In general it can be said that the approach towards engaging with the partnerships was often based on cold calls without any leads into the company. Also, the CEO of Billy s BIlling seemed to have a surprisingly strategic approach to partnerships. Causation often seemed to explain the motivations for the partnerships. While there are strategic elements to assessing partnerships, contracts are in general loose and seem to be a last resort primarily when dealing with other small companies. Conversely when affiliating with larger companies, contracts are often sought for from their side Opeepl Metroxpres Building on a strategic approach of aiming at partnering up with a major Danish newspaper, there was a clear goal for Opeepl in contacting Metroexpress, as other newspapers were approached simultaneously, which entails a strong degree of causal reasoning. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Opeepl 98

100 In line with other partnerships of Opeepl, the partnership with MetroXpress was build on the exchange of noneconomic resources until Opeepl would be able to generate revenue, which MetroXpress would gain a share of. Therefore, the affordable loss principle is strongly present. There was a very close collaboration among the partners, and they had intentions of building a large panel in collaboration. Such collaborative behavior within the core of the Opeepl product is seen as evidence of a weak presence of the strategic alliance principle Yougov In 2010, Opeepl entered an agreement with Yougov, which entailed a mutual exchange of resources as the CEO of Opeepl explains: They have the sales force, they also have the panel we sort of lacked both (Int. 2, Opeepl). With the agreement, Opeepl is not imposed any expenses from Yougov, unless a sale has proceeded. Furthermore, Opeepl gains revenue from the sales which Yougov generates with the Opeepl software as a white label solution. For both scenarios, there is no economic risk for Opeepl involved, as there are no upfront payments. The principle of affordable loss is therefore highly evident in the partnership. The CEO of Opeepl explains that there is more to the partnership: From Yougovs perspective, it was also because they want to be innovative, and do new things, why new technology is interesting [for them]... And for us, we wanted a partner who was well known in the market and a representative panel (Int. 2, Opeepl). After the engagement, the partnership has changed its course over time: And then you have to cope with that things do not develop as you expect that is what we have done to a very high degree with Yougov. Okay, this did not work out, let us then try this approach instead (Int. 2, Opeepl). The partnership can therefore be said to entail a weak degree of the strategic alliance principle. This is underlined by how the CEO stresses that it is definitely the most important partnership we have entered (Int. 2, Opeepl). Prior to the partnership with Yougov, Opeepl had certain objectives in their pursuit of a central strategic partner. As such, Opeepl intended to partner up with a research company, whom had a reliable panel, and would be able to sell the Opeepl services. The startup approached several potential research companies, while Yougov was the company which the partnership was initiated with: Yougov was an obvious opportunity there were different obvious opportunities as partners, but Yougov found it interesting, and then they become the ones you continue to work on (Int. 2, Opeepl). With this strategic goal in mind, it can be derived that Opeepl was basing their partner approach on a strategic partner analysis, implying a highly causal approach. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Opeepl 99

101 Coolsms As Opeepl needed an external supplier of an SMS-gateway, they explored the opportunities for such suppliers, which implies market analysis, and hence a strong causal approach. After engaging with Coolsms, it has developed into more than a mere supplier relationship, as Coolsms gives interesting inputs on how to use tele and sms and provides interesting customer ideas (Int. 2, Opeepl) Major Customers It was not by chance that the first customers of the Opeepl service were major corporations. Opeepl deliberately chose to go for these larger companies, based on a strategic analysis of the market, implying a highly causal approach. The major companies, which are all customers at Opeepl, have played a role going beyond that of a customer. These companies have extensive experience and knowledge of performing the analysis types which Opeepl offers the data background for executing. This gives them a basis for providing highly valuable inputs, which are important for Opeepl, which have no previous experience from the sector. According to the CEO of Opeepl, the companies engage with Opeepl in part because they find it interesting to work with a small startup (Int. 2, Opeepl). The reasoning for Opeepl to engage in these relationships, going beyond that of a customer, is based on two motivations. First, in some instances, it was the deliberate goal of Opeepl to engage the customer further in the platform, in order to gain their insights on the further development. Second, in other instances, it was sudden opportunities (leverage contingencies), which Opeepl saw and exploited, which led to feedback on the platform. Exemplifying the approach, the CEO highlights the customer, Cloetta: For example Cloetta, they have used it a lot, and therefore they are also more engaged with the system, and this had led to me having a meeting this week with Cloetta, where they will provide feedback. Our investor is also coming The guy at Cloetta used to work at GFK [analysis company, red.], so he has a lot of experience and good input to comment on what he thinks the system should be like (Int. 2, Opeepl). Interestingly, the upside for these major customers in their further engagement can seem rather low, as they receive no discount or extra benefits from Opeepl. The CEO of Opeepl points out that most are genuinely interested in the startup: People like to work with entrepreneurs people find it fun that you have made something different, and this is something we often hear and they want to hear the story behind the startup ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Opeepl 100

102 when you have something which is different, which they find useful, they will also use some time for feedback (Int. 2, Opeepl) Go Aften Danmark In the relationship with Go Aften Danmark, the TV program is provided a discounted price for the services they bring. They are the only customer of Opeepl who gets a discount. For the reduced payment, We gain something we need and they gain something they need (Int. 1, Opeepl). By avoiding marketing costs by providing their product for free instead, is seen as a weak form of the affordable loss principle. There is no economic risk, as Opeepl with the reduced price, still covers their costs. Also, the relationship, to some degree, entails clear strategic goals of the relationship (Int. 2, Opeepl), and hence a weak causal element is found present Per Møller Opeepl came into contact with Per Møller through common network relations, which entails a weak degree of the means principle. Per Møller engaged with the venture, and provided valuable insights into management and market information, and have been able to leverage his own network for the benefit of Opeepl Opeepl Main Findings The figure below sums up which principles were found present for the relationships, and the strength of these, as outlined above. Table 14. Network relations of Opeepl, according to reasoning for engaging Relations of Opeepl Means Leverage contingencies Affordable loss Strategic alliances Causation MetroXpress Yougov Coolsms Major customers Go Aften Danmark Per Møller Source: Own development ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Opeepl Main Findings 101

103 The partnerships of Opeepl are to a high degree based on strategic analysis by Opeepl, demonstrated by the causal approach to many of the relationships. Opeepl have been able to point out the resources which they were lacking internally, and then assess possible partners which could provide such resources for the company. By a simple market analysis, Opeepl then contacted possible partners, taking meetings with the interested parties and further engaged with the partners who suited the needs of Opeepl. As such, Opeepl does most often not choose a specific company as the best partner option, but rather approach a range of companies which possess the resources needed. Evident for the central partnership of Opeepl with Yougov, and earlier with MetroXpress, is the startup s focus and ability to enter the partnerships with no economic risks associated, demonstrating a focus on affordable loss Cross Case Analysis This chapter analyses the findings from the second part of the analysis relating to the propositions which are explained in section 4.3. The figure below summarizes the findings from each case, in relation to the principles. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Cross Case Analysis 102

104 BILLY S BILLING OPEEPL ECHO.IT TRADESHIFT April 2013 Table 15. Reasoning for engaging in network relations, across cases Start up Relation Means Leverage contingenci es Morten Lund External developers Affordable loss Strategic alliances Jon Bosak Causation IT/Design PayPal Media TDC Sortedam Ventures DSB Rasmus Aaen Bro Kommunikation Klaus Lund Sarah Gregersen Ph.Ds, bloggers Quadric IBM Hill & Knowlton MetroXpress Yougov Coolsms Major customers Go Aften Danmark Per Møller Børsen Tv2 Danløn Webshop service SEO Source: Own development The following will examine the findings across cases, in relation to each principle investigated Means Interestingly, means did not materialize as a highly explanatory principle of the origins of external relations. This despite our expectations which were based on earlier research, which argued that social and personal relations of entrepreneurs are a main source of network relations for startups (Hite and Hesterly, 2001; Uzzi, 1997). ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Cross Case Analysis 103

105 For both Tradeshift and Echo.it, there were instances where means led to important relationships, but as such, existing relations only led to a limited number of relations. For Opeepl and Billy s Billing, we found that existing relations had only been leveraged to a very limited extent. A possible explanation for these two latter case companies could be their limited existing network within the industry, as they had no prior industry experience prior to their respective startup. This is a factor backed up by the Opeepl CEO: We didn t have a network within this industry, so quite quickly, we went for professional partnerships (Int. 1, Opeepl). Hence, means was not as significant a factor for explaining how network commitments were engaged, as expected Leverage Contingencies To leverage contingencies, implies taking advantage of sudden occurrences in ones environment (Sarasvathy, 2008). As such, this principle is difficult to predict, but was expected to be present as a factor of how relationships could have originated. Within three of the case companies, Tradeshift, Echo.it and Opeepl, there were cases where this principle was strong, implying that the relationship had originated from a sudden occurrence in the environment of the startup. The exception was Opeepl, where this principle was barely present. Overall, the principle of leveraging contingencies is by definition random, which is why it is difficult to derive how important the principle has been. The findings suggest that it has not been a significant factor for how relationships were engaged Affordable Loss Basing decisions on entering into a relation on the affordable loss principle was often seen in partnerships which held a central position for the startups. This entails that the startups managed to enter relationships, with a minimum of risk, risking only what they could afford to lose to engage in the relationship (Dew et al, 2009). Rather than giving up resources upfront, which could entail economical resources, the case companies in more instances offered the partners equity, or the sharing of economic profits gained from the relationship over time. Basing these relations, which often brings critical resources to the startups, on affordable loss, entails that the startups have avoided upfront economic expenses and enables the startups to fail cheap by exploiting available resources (Sarasvathy, 2001, 2008). With the high emphasis on the affordable loss principle across the case companies, it confirms the expectation of the startups engaging in relations on this background. This was to such a degree and for such central relationships, that it can be said to be very highly present in the decision making process of the startups. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Cross Case Analysis 104

106 Strategic Alliances Entering relations as strategic alliances that entailed a close collaboration partnership were the case for very few relations across the case companies. As the principle implies pre-commitment and co-creation (Dew et al, 2009), we expected close collaboration with external relations, to see a strong presence of this element. This was not found to be the case for most of the relationships of the case companies, and the strategic alliance principle was thus present in few cases, but not as significantly as expected Causation To apply a causal approach to the network relations was mainly the case in two different approaches. For both instances, these approaches were widely present for the case companies. First, related to the reasoning of the companies, it was found that the companies in several instances approached external relations with a clear strategic goal for what resources they intended to obtain by engaging. It can be argued that these considerations, often based on simple market analysis where different options were laid out, to some degree implies causal reasoning. For example, both Tradeshift and Echo.it set out to partner up with major Danish corporations as a first real major pilot tester of their service, entailing that the companies had a goal for what they wanted to achieve. It should be noted that the origins of the actual relationships that came into being for Tradeshift and Echo.it (TDC and DSB), were more effectual in the way they were approached, as it often entailed a great deal of networking. Second, more related to the strategic conditions of the startup, when the case companies engaged with larger companies, it was seen how the case companies were obligated to conform to the bureaucracy and terms of the large companies. This entails that they had determined to set longer term goals, make contracts etc., which entails a causal approach Summing up The analysis has showed how the principle of means was not as commonly applied, as was expected. Also, taking advantage of sudden occurrences (leveraging contingencies) was not a significant explanatory factor for why network relations had been engaged. But for affordable loss, it was found that the case companies to a large extent emphasized this principle, as they focused on the downside of engaging with a relation, and minimizing their own resource use. Engaging in a close collaboration (strategic alliances) with a network relationship was found in some cases. Finally, it was found that a causal logic approach was significantly applied. ANALYSIS PART 2 PRINCIPLES FOR ENGAGING Cross Case Analysis 105

107 7. ANALYSIS PART 3 NETWORK RELATIONS AND PRINCIPLES FOR ENGAGING Introduction Reputational Network Relations Marketing Network Relations Co-opetition Network Relations Technology Network Relations In the third and last analysis part, we utilize findings from analysis parts one and two, to empirically explain how network types are linked to certain effectual principles. In this section, a link is created between two different lines of study, fulfilling one of the main objectives of the thesis. 106

108 7.1. Introduction The analysis below is aimed to empirically test the expectations proposed in the conceptual framework, section 4.4. The theoretically based propositions were constructed to attempt to link how the reasoning elements (Sarasvathy, 2001) can be linked to the types of network relations (Lechner and Dowling, 2003). In the following, it will be assessed whether we find support for our propositions.findings beyond the scope of the propositions, will be further investigated in the subsequent section, the discussion (section 8.0) Reputational Network Relations We now assess the proposition related to reputational relations. Appendix 1 depicts all the reputational relations across the case companies Proposition: Means We suggested that there was reason to believe that startups would engage in reputational networks, based on mainly the existing professional networks of the entrepreneurs in the startups. The table above illustrates how the networks which serve as a reputational resource for the startups, are only to a very little extent based on existing relationships. Tradeshift is an exception, as two important relationships - namely that of Jon Bosak and that of TDC - originated from existing relations. As already discussed in the findings of the second part of the analysis, means was generally not a principle widely acknowledged as the motivation for engaging in relations, and this also holds true when specifically looking at the reputational relations. However, this finding is related with the way the conceptual framework is composed, as it impedes us in directly isolating network types. The reputational relations of the case companies, which have mainly been engaged as another network type, are therefore not seen as an exploitation of the startups existing relations. This is related to limitations of the current framework, which will be further discussed in the discussion section (8.0) Marketing Network Relations We here assess the proposition related to marketing relations. Appendix 2 depicts all the marketing relations across the case companies. ANALYSIS PART 3 NETWORK RELATIONS AND PRINCIPLES FOR ENGAGING Introduction 107

109 Proposition: Affordable Loss Across the case companies, we find a relatively high degree of marketing relationships, where the affordable loss principle is present. In Tradeshift, a significant partnership with PayPal was engaged, where the startup limited its economic resource expenses by exchanging equity in the company. The partnership provided market information and had intentions of a closer integration of the Tradeshift services into the Paypal platform. In Echo.it, marketing partnerships with both individual consultants and larger consultancy companies had developed into both a primary sales channel resource, but also highly regarded as a feedback channel for market information. All these relations are based on a model where the revenue of sales by the partner is shared. The downside, in terms of resources needed by Echo.it, is therefore limited. In Opeepl, the relationship with Yougov implied a highly central partnership, which both provided market information and sales resources. Rather than merely paying for the services of Yougov up front, Opeepl engaged in a partnership which entailed that Opeepl avoided upfront costs, but rather provided an upside for both partners. In Billy s Billing, similar arrangements had been engaged with webshops and the company Danløn, where their integration of the product of Billy s Billing was based on a minimal economic resource expense for Billy s Billing, exploiting external partners as a marketing resource. On this basis, we found significant support for affordable loss, as a principle for explaining how the startups have engaged in external marketing relationships. Underpinning this, none of the startups have engaged in marketing relations, which have required upfront payment for the startup, signifying a focus on the downside, and a focus on limiting the allocated resources. Also, it was found that marketing relationships are mainly approached on an agreement where the relation is provided with an upside, by entering into a partnership with the venture Co-opetition Network Relations As our empirical findings did not reveal any co-opetition networks, we have not been able to obtain information indicating any proof our expectation regarding co-opetition relations. ANALYSIS PART 3 NETWORK RELATIONS AND PRINCIPLES FOR ENGAGING Co-opetition Network Relations 108

110 7.5. Technology Network Relations As proposed in the section of the conceptual framework, it was expected that strategic alliance and affordable loss could be part of an explanation of why startups would engage in technology networks. Across the case companies examined in this study, only few technology network relations were identified. Relatively, the number of observations is substantially smaller than what was found in regards of reputational and marketing network ties. Only three of the case companies engaging in technology networks while Tradeshift was found to be most active in this category. We now assess the proposition related to technology relations. Appendix 3 depicts all the reputational relations across the case companies Proposition: Affordable Loss As Tradeshift did pursue the best IT developers and designers to work together with their own internal team on making heavy technological solutions and professional design, they might not have been able to afford it had they not offered equity as compensation. Thus, it is found how, in order to minimize the risk of losing substantial amounts of cash instead pay the IT and design development partners in equity. A similar agreement was seen in the case of Echo.it, which at an early stage engaged in a technology partnership with Sortedam Ventures, providing significant external resources for developing their platform. Echo.it limited the economic downside by offering Sortedam Ventures equity, which entailed that Echo.it got markedly reduced prizes for the further development of the core product from the technology partner. Therefore, we find that in the cases where technology relations were engaged, the affordable loss principle was an important strategic condition for engaging in these partnerships. As it was only present for two cases, we do however not find significant support for this finding Proposition: Strategic Alliances The partnership of Echo.it with Sortedam Ventures featured a high degree of collaboration, which is why we observed a strong degree of the strategic alliance principle. In regards of Jon Bosak, a relation of Tradeshift, it is seen how this important partnership showed rather strong signs of the strategic alliance principle, as the cocreation of the international trading language required a close partnership. The SEO company, a relationship of Billy s Billing, was also engaged with a close partnership, where both parties were highly engaged in the technical development of SEO competencies, as the interviews revealed ANALYSIS PART 3 NETWORK RELATIONS AND PRINCIPLES FOR ENGAGING Technology Network Relations 109

111 that both parties did more than they normally would do. However, we do not find support of a strong relationship as it was unclear in our empirical data how high a level of engagement the partnerships had required. As a strong degree of strategic alliances was found in more than haft of the cases we argue to have observed a significant link between strategic alliances and technology networks Summing up In the quest of linking technology network ties to the effectual principles of affordable loss and strategic alliance, we did find some support for these propositions. Regarding strategic alliances, it was observed how it was highly present in the observed technology ties, which we interpret as a clear support of our expectations. This signifies that when technology network ties are engaged in, they are often so in the setting of a strong cooperation where the level of engagement is high from both sides. We also found support in regards of affordable loss, as where it was found, it was found to be strong. However, affordable loss was not present in as many cases as strategic alliances. ANALYSIS PART 3 NETWORK RELATIONS AND PRINCIPLES FOR ENGAGING Technology Network Relations 110

112 8. DISCUSSION Introduction Types of Networks Principles of Effectuation Limitations of the Study In this chapter, the applicability of the framework is critically assessed on the basis of the empirical investigation. We discuss the integration of the two different lines of studies to point out how it was suitable and where we experienced challenges. This also entails a discussion of selected empirical findings that were not covered by the analytical framework. DISCUSSION Technology Network Relations 111

113 8.1. Introduction In this paper, we attempted to empirically test the principles of effectuation theory, as to provide explanatory factors for how startups engage in specific types of external relationships. We must emphasize that few researchers have attempted to empirically model and test effectuation" (Perry et al, 2012), which is why it has only been possible to draw on earlier research to a limited extent. The novelty of this approach calls for a discussion of the chosen theoretical concepts suitability, and their explanatory ability for this study. The following discussion will therefore reflect on the conceptual framework, in relation to the interaction with the empirical findings. This section will first briefly assess the chosen network types (Lechner and Dowling, 2003; Lechner et al, 2006). Next, the section will assess the principles applied as explanatory factors (Sarasvathy, 2001, 2008). For both sections, we will further explore empirical findings for specific elements not explained by the conceptual framework. Furthermore, this section provides insights to suggestions for further research, based on the current study Types of Networks Prior to operationalizing the effectuation principles as explanatory factors, it was relevant to relate these factors to a more nuanced view of the type of relationships engaged by entrepreneurs. We argued that this was more valuable than merely approaching relations as contributing equally comparable resources. By adopting the framework laid out by Lechner and Dowling (2003) and Lechner et al. (2006), this provided a focus on the resources obtained through the relations (Slotte-Kock and Coviello, 2010). As there was a good fit amongst the conceptual framing of the network types and the empirically-noted relations, we assess that the typology overall was useful. We highlight the important contribution of such a framework, in its ability to focus on the exploitation of external resources. Our empirical investigations also gave rise to two main considerations regarding the applied typology. First, in some cases, important empirical findings could not be fitted to the typology. For example, two case companies had utilized online open-source forums to further develop their technology. Thus the forums had an instrumental role in these companies development. While the closest fit would be a technology network tie, an online forum is difficult to categorize as an external relationship. Hence, fitting network ties into categories can be a limiting factor in a qualitative study of entrepreneurship. DISCUSSION Introduction 112

114 Second, another challenge of applying the framework was network relations that fell into more than one of the four categories. Empirically, this was mainly the case for reputational relations, which were often mainly engaged as either marketing or technology relations, and then became a reputational relation as a secondary benefit. As relationship classification can alter over time, it was emphasized that this study provided a snapshot of the network types at the time of the interviews. With these considerations in mind, we find that future studies could adopt this typology, as it provides insights into resources, which relationships bring to a startup. To further qualify this, future research should investigate how the resources from these network relations influence the performance of the startup Principles of Effectuation Empirically, it was interesting to see whether a set of principles, entailing means, affordable loss, strategic alliances and leverage contingencies, which have not been specifically developed to explain how relationship engagement, could provide such an explanation. Overall, the principles provided an interesting perspective, and we find them a decent point for departure for further research into this topic. We found two important elements worth adhering to when applying the principles. First, the principles are found to be rather broad in their scope. This has implications when applied empirically. The broad scope meant that one relationship could often be explained by more than one principle. As such, a relationship could, for example, be engaged by the exploitation of a social relation (means), and simultaneously it could be observed how the startup could have displayed a focus on the downside of engaging (affordable loss). We suggest that further research limits the scope of each principle, to provide more well-defined explanatory factors. Second, relating to the above, we found that the distinction between origins and strategic conditions was relevant in the empirical setting. As proclaimed in the literature review section (3.0) we found that there is a difference between which level the effectual principles are explanatory for in an empirical setting. Therefore, it can be implied that a distinction between the effectual principles might be relevant when attempting to operationalize their functionality in empirical studies. Aside from these considerations, the empirical findings also gave rise to interesting findings, which could not be explained by the framework, despite the relevance for our research question. We therefore discuss these findings here. DISCUSSION Principles of Effectuation 113

115 Multidimensional Relationships The interviews with the case companies highlighted how the framework of effectual principles have limitations when network relations have a multi-dimensional aspect (Larson and Starr, 1993). This theoretical issue, was especially significant for reputational relationships, why the following will use this as an example. The multidimensional aspect of the relationships is visible in the first part of the analysis, where it is indicated where more networks types are present for any single relation. The analysis highlighted that many reputational relations were also engaged as marketing or technology relations. This proved that reputational relations were often an extension of another relationship. But when these multidimensional network types were related to the principle of means, it impeded the analysis. Means provided a snapshot of the relationship as a whole, and not for each network type which a relation could represent. Thus, means provided a snapshot of a relationship at the time of engagement, relating to the main function of the relationship. Hence, this does not take into account if the relationship is also exploited as another network type. A representative example highlights this: As Opeepl engaged in a central partnership with Yougov, the main gained resources were of a marketing character. The relationship also provided reputational resources, as Yougov - a recognized analysis company - provided legitimacy for Opeepl s service. As the relationship was not initiated by social relations, the principle of means was not present in our findings. But if the reputational aspect of the relation was isolated, the argument would become that the reputational aspect had emerged from means. However, this was not the case with the applied framework, which can be argued to be misleading of the actual observation. Hence, the explanatory framework comes short of explaining this direct relation of reputational and marketing relations. Our empirical research highlighted that reputational relationships were often, across the case companies, engaged with as a marketing relations, but then later exploited as a reputational resource. We saw that very few of the relations of the case companies were engaged for the sole purpose of a reputational relation. We find this interesting as it highlights how the entrepreneurs are able to exploit the variety of resources of their external relationships The Proactive Entrepreneur Another finding from the empirical investigations relates to what we termed the origins of a relationship, implying how it emerged. Rather than exploiting direct social and personal network relations, we found that startups, to a significant extent, applied a different approach. Our findings suggest that a significant amount of the relationships are DISCUSSION Principles of Effectuation 114

116 based on the entrepreneurs getting linked with people they did not know beforehand. For example, it is observed for the central relationships of DSB and Bro Kommunikation with Echo.it, and for TDC with Tradeshift. This has been described as non-redundant ties (Granovetter, 1973), which implies ties between one network member and another which are not directly connected to each other 12. There is, so to speak, a missing link between the two members, and it is this link which was often provided by the network of the entrepreneurs. We find this interesting, and it can be discussed whether that this is already encompassed within the principle of means. We argue, however, that means mainly emphasizes the use of the direct ties of the entrepreneur, reflected in contacts and resources at hand (Dew et al, 2009: 576). For non-redundant ties, it can be argued that the entrepreneur is not knowledgeable of what resources these might bring. Another approach was also found across the case companies. Several relationships had originated from the entrepreneur s initial cold-calls. This was the case for central partnerships, where specific resources were sought externally, such as Opeepl s connection with MetroXpress and Yougov, Morten Lund for Tradeshift, and Quadric for Echo.it. This is explained by the CEO of Opeepl: It is all about just picking up the phone and say hey, we have a deal for you, do you want to play along? It has been a lot like that all the way through (Int. 2, Opeepl). We find this approach to represent the effectual logic, as it comes very close to trying to control the future (Sarasvathy and Dew, 2003: 12), by taking proactive steps to steer the company in a desired direction. However it can also be argued that it entails causal elements in terms of assessing required resources and laying out options for gaining such resources. Here, an important distinction is that the case companies were not adamant on a specific relation, but went after those who showed interest, and engaged with those. This is an effectual approach in essence. But to be able to include this behavior as an effectual approach to relations, we lack underlying principles supporting such proactive behavior. Such a principle of effectuation would be an extension of how relationships originate, together with means and leverage contingencies. Prior research strongly supports the importance of exploiting one s social network as an entrepreneur (Hite, 2005; Jack, 2010; Slotte-Kock and Coviello, 2010). As this supports the principle of means, it was interesting that our empirical findings are not in line with these expectations. These findings highlight how entrepreneurs in practice actively seek resources from external relations, while not necessarily utilizing existing ties to do so. 12 e.g. A has ties with B and C but B and C do not have contact with each other (Lechner and Dowling, 2003: 3). DISCUSSION Principles of Effectuation 115

117 8.4. Limitations of the Study There is a variety of uncertainty factors contained in a study of this kind, which is why we argue that our results can only be generalized to a limited extent. We have drawn on theoretical research with a limited number of case studies. This offers little statistical significance, to be generalizable for the whole industry. The limited number of cases (four) could also be subject to an idiosyncratic phenomenon (Eisenhardt, 1989). Nonetheless, we find it plausible to replicate our findings for similar cases, settings and timing. DISCUSSION Limitations of the Study 116

118 9. CONCLUSION Field of Study Types of Network Relations Principles for Engaging Linking Network Types and Principles for Engaging In this last chapter, we answer our research question. The section is structured according to the analysis parts, which emphasize how each of the analytical sections were instrumental to answering our research question. 117

119 9.1. Field of Study This paper acknowledged that the environment which early-stage ventures act in is characterised by Knightian Uncertainty (Knight, 1921), and that the startups are characterized by both a lack of resources (Stinchcombe, 1965), and a lack of reputation in the market (Baum, 1996). Through qualitative research methods, this study focused on how early-stage startups engage in external network relationships, and what resources these relationships bring to the startups. Where prior research demonstrated the importance of external relations as valuable providers of resources, limited focus has been given to further qualify which external resources startups prioritize. Furthermore, little attention has been given to how startups engage in external relationships. This led to the following research question: How do early-stage Danish SaaS startups engage in the network types they do? To answer this research question, we developed the analysis into three parts: 1) Further understanding the network relations; 2) The effectuation principles as explanatory factors; and 3) The link between these two. The following analysis is structured accordingly Types of Network Relations To further qualify network types and the resources they provide for a startup, we adopted a typology distinguishing four network types (Lechner and Dowling, 2003). The four network types, entailing reputational, marketing, co-opetition and technology relations, each provided insights for the resources provided by the external relation. This typology was found useful during the empirical studies. The empirical findings revealed that mainly reputational and marketing networks were present in the four case companies, which was also expected. There were also cases of technology relations, while no co-opetition relations were found. The reputational ties were found to bring valuable resources for the ventures legitimacy, by referring to the relations on the startups website and when other stakeholders were contacted. The marketing relationships brought valuable market information for the startup, and sales resources had been obtained through close sales partnerships. The few technology relations found all brought important external development capabilities for the core product of the ventures. CONCLUSION Field of Study 118

120 Hence, it was found that the early-stage SaaS startups engaged with network relations to mainly gain marketing and reputational resources for the venture, whereas technology resources were only prioritized in few cases Principles for Engaging The typology furthered our understanding of which types of external relations were engaged, and the resources they provided. Next, we set out to better understand the reasoning of the entrepreneurs for engaging in these relations. For this purpose, we then applied the explanatory principles of effectuation theory to the network relations. We divided the principles into origins and strategic conditions, and they, in short, entail: Origins of the relations o Means. Focusing on and exploiting one s existing social and professional external relations. o Leverage contingencies. Taking advantage of sudden occurrences in the environment. Strategic conditions of the relations o Affordable loss. Focusing on the downside to minimize risk and resources needed. o Strategic alliances. Close co-creation with a partner. o Causation. Clear strategic plan for the assessment and conditions of the relationship. These principles are not developed specifically for understanding network relationships. Despite this, we found them useful for gaining a better understanding of how startups engage in network relations. Our findings suggested that means was not as explanatory as expected, for how the relations emerged. The startups had applied leveraging contingencies in some cases, which had led to relationships for the startups. The principle of affordable loss was widely seen, and implied that the ventures engaged with relations where their own resource investment was minimal. Very close partnerships, entailing strategic alliances, were only seen in very few instances. Causation is argued to be the inverse of the effectual principles, which was important to include as a reasoning for engaging. The causal approach was widely observed, mainly in regards of engagements with larger partners. The empirical findings gave rise to considerations, as the cases highlighted how the entrepreneurs were very proactive in their approach to network relations, which was not captured by the framework. CONCLUSION Principles for Engaging 119

121 9.4. Linking Network Types and Principles for Engaging To answer our research question, we sought to prove links between the discovered network relationships and the principles adopted as explanatory factors. With this approach, there were both anticipated and unexpected findings. First, we found that the principle of affordable loss, entailing that the startup tends to focus on the downside of engaging in the relation, and hence limit committed resources, was highly present in marketing relations. Hence, obtaining marketing resources externally was related to the startup s ability to approach such resources with a limited investment of internal resources. Second, the few technology relationships observed were strongly based on the principle of strategic alliances. Hence, co-operating with external relations on technological resources for the core product entailed a close partnership. Third, we found that reputational relations, and thus legitimacy resources, were often approached as a new dimension of marketing relationships. This finding was unable to be explained within the framework, which gave rise to reflections on the framework. Fourth, the empirical findings gave rise to a discussion, as the framework was unable to explain a highly proactive approach to external relationships seen across the case companies. We suggested that this approach was effectual by essence, and should be considered for future research. These findings should be seen as a first attempt to better understand what resources arise from early-stage startups external network engagement, and how they relate to explanatory mechanisms for relationship engagement practices. CONCLUSION Linking Network Types and Principles for Engaging 120

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132 11. APPENDIX Appendix Overview Appendix 1: Conceptual Framework 3 Findings, Reputational Appendix 2: Conceptual Framework 3 Findings, Marketing Appendix 3: Conceptual Framework 3 Findings, Technology Appendix 4: Company products Appendix 5: Interview guide Appendix 6: Letter to companies Appendix 7: Opeepl - Interview 1 Appendix 8: Opeepl Interview 2 Appendix 9: Billy s Billing Interview 1 Appendix 10: Billy s Billing Interview 2 Appendix 11: Tradeshift Interview 1 Appendix 12: Tradeshift Interview 2 Appendix 13: Echo.IT - Interview 1 Appendix 14: Echo.IT Interview 2 APPENDIX 131

133 OPEEPL BILLY S BILLING ECHO.IT TRADESHIFT Appendix 1 Conceptual framework 3 findings, Reputational Start up Relations Means Leverage contingencies Affordable loss Strategic alliances Causation Morten Lund Jon Bosak PayPal TDC Media DSB IBM Bro Komm. Hill & Knowlton Quadric Ph.d s Børsen Tv2 Yougov MetroXpress Major Customers Go Aften DK APPENDIX 132

134 Opeepl BILLY S BILLING ECHO.IT TRADES HIFT Appendix 2 Conceptual framework 3 findings, Marketing Start up Relations Means Leverage contingencies Affordable loss Strategic alliances Causation TDC PayPal Bro Komm. Hill & Knowlton Quatri Klaus Lund Sarah Gregersen Rasmus Aaen Danløn Webshop services Yougov MetroXpress Coolsms Major customers Per Møller APPENDIX 133

135 Opeepl BILLY S BILLING ECHO.IT TRADESH IFT Appendix 3 Conceptual framework 3 findings, Technology Start up Relations Means Leverage contingencies Affordable loss Strategic alliances Causation TDC PayPal Bro Komm. Hill & Knowlton Quatri Klaus Lund Sarah Gregersen Rasmus Aaen Danløn Webshop services Yougov MetroXpress Coolsms Major customers Per Møller APPENDIX 134

136 Appendix 4- Company Products APPENDIX 135