Denmark. Country report Annual RepTrak Report

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1 Annual RepTrak Report Country report 2013 Denmark RepTrak is a registered trademark of Reputation Institute 2013 Reputation Institute, all rights reserved

2 About Reputation Institute Reputation Institute is the world's leading reputation management consultancy, enabling leaders to make more confident business decisions that build and protect reputational capital and drive competitive advantage. We enable leaders to make business decisions that build and protect reputation capital and drive competitive advantage Independently owned and founded in 1997, we operate in 30 countries. Our Global RepTrak Pulse is the world's largest reputation study. Measuring more than 2000 companies from 25 industries across 40 countries, the study provides key insights into what drives perceptions and how they influence marketplace behaviour. RepTrak Pulse provides powerful global benchmarking for tracking corporate reputations in industries and countries around the world, and serves as the basis for continued thought leadership in the field of reputation management. Knowledge Publication Conferences Training Research Information Analysis Presentation Advice Insight Strategy Activation 2

3 Table of contents Section 1 Introduction 4 Section 2 Country results 11 Appendix 1 Demographics 26 Appendix 2 Methodology 28 Appendix 3 Terminology 33 3

4 Section 1 Introduction About the study. The RepTrak model. Executive summary.

5 About this study What follows are the results of the RepTrak Pulse 2013 reputation study conducted in Denmark by the Reputation Institute. The reputations of the biggest and most visible companies in Denmark were measured via an online survey among a representative sample of the general public in Denmark. Data collection took place in January and February Contact information For more information about the study please contact: Charlotte Bang-Møller: 5

6 The RepTrak model explains Reputation For Deep Dive studies The RepTrak Model Reputation Institute s generic model for reputation is structured around four core themes, seven reputation dimensions and 23 reputation attributes. Together, these elements explain a company s reputation. 1 - Reputation RepTrak Pulse is the core of a company s reputation and shows how strong the emotional bond is between the company and the public. 2 - Dimensions The RepTrak model consists of seven operational dimensions and 23 attributes that explain the reputation profile. 3 - Attributes The individual attributes mean different things to people and are perceived differently in terms of weighted importance. Analyses identify areas that are most important for strengthening a company s reputation. Drivers can be at dimension and attribute level and show how the company gains value for money in its communication

7 RepTrak - Rational vs. Emotional For Deep Dive studies What is the relationship between RepTrakTM Pulse and the 7 reputation dimensions? RepTrak Pulse measures the overall reputation based on people's immediate emotional perception of the company. In contrast, the 7 reputation dimensions examine people s rational perception of corporate reputation based on specific and detailed statements. RepTrak Pulse score is not necessarily always equal to the average of the 7 reputation dimensions. People s emotional perception may be influenced by an overall positive attitude to the company, which is not necessarily rewarded by a proper evaluation of the respective company's products, innovation, workplace, governance, citizenship, leadership or performance. Emotional Rational explanation of the emotional 7

8 Why should we care about reputation? Getting to bottom-line results Touch Points Reputation Behavior Business Results Direct experience What a company communicates What others say 8

9 About this study Significant differences and normative scale Significant differences In any study based on a sample of the population there is a statistical error in all measurements. The table below shows the difference needed between two scores before they can be said to be significantly different. Statistic Significance RepTrak Pulse and Multistatement dimensions Single-statement dimensions and Attributes > 1,0 > 1,5 Only score differences that are statistically significant will be shown in this report. Normative scale Using an extensive database containing results from thousands of studies throughout the world since 1998, Reputation Institute has developed a Normative Scale (in everyday language The Traffic Light ) that indicates whenever a particular score is high or low when benchmarked against previous studies of a similar character. Excellent/Top tier 80+ Strong/Robust Average/Moderate Weak/Vulnerable Poor/Low est tier <40 9

10 Section 2 Country Insights Commentary by Henrik Strøier

11 Executive summary I På et overordnet plan afslører dette års analyse et interessant klima skifte ; den finansielle krise fik Danmark til at sætte fokus på value for money, produktkvalitet og god service og på bagkant af recessionen har forbrugere i Danmark efterspurgt klar, tydelig og ansvarlig ledelse men siden krisestemningen toppede i 09 & 10 ser vi et tydeligt forventnings skrifte; nu efterspørges forretningsmoral, gennemsigtighed og samfundssind i en kombination med evnen til at tjene penge. Der synes at være en tydelig rækkefølge; 1) Forbrugerfesten er slut vi er i krise > jeg skal sørge for at passe på egne penge og optimere min egen købekraft. 2) Krise er lig kaos > jeg støtter de virksomheder der trods krise og nedskæringer stadig holder fast i god kvalitet, et højt service niveau og som på samme tid har en langsigtet plan; hvad skal der ske? 3) Krisen bider sig fast > virksomheder kæmper for overlevelse og indtjening via fyringsrunder virksomhedslukninger, prisstigninger, gebyrer og samtidig afsløres det at en række virksomheder benytter sig af kritisable og i visse tilfælde ulovlige overlevelsesstrategier; priskarteller, svindel med råvarer, kollektiv lønnedgang for alle undtagen direktørgangen. listen er lang. 4) Moral og Profit > de virksomheder der vinder Danmarks hjerte og støtte er de virksomheder evner at tjene penge på en redelig facon danske forbrugere lægger i stigende grad vægt på virksomhedens opførsel, det betyder naturligvis ikke at kvalitet og service betyder mindre, det betyder derimod at Danmark forventer at høj moral og profit går hånd i hånd. og der er flere gode eksempler på virksomheder der evner at leve op de forventninger, men desværre også flere eksempler på virksomheder der dumper i Danmarks øjne. se udvikling i dimension vægt 11

12 Executive summary II Dette års måling af de 40 mest synlige virksomheder afslører også at: LEGO GROUP har placeret sig i en klasse for sig selv virksomheden der for ganske få år siden blev betragtet som altmodisch og ude af trit med markedet har genopfundet sig selv og er netop arketypen på en virksomhed hvor høj forretningsmoral, samfundssind, klasse produkter og profit går hånd i hånd. At Danmark elsker sine industri ikoner; Novo Nordisk, APMM, Danfoss og Grundfos trods års snak om ny versus gammel økonomi, trods års snak om innovations- og effektivitetskrise i industrien så viser feltet af gamle kendinge sig som endog meget krise resistente og danskerne belønner dem; med at udvise høj tillid og tildele dem forsat beundring. At Nordea forsat trodser tillidskrisen som bankerne generelt lider af Nordea nedskrev, tog tabene og rebede sejlene som den første i sektoren og har med sikker hånd undgået at tabe på goodwill kontoen - med tydelig sammenhæng mellem det sagte og det gjorte har Nordea cementeret sin lederrolle i en industri der mange ses som hovedårsagen til den finansielle krise. At Danske Bank har sat alle sejl til en ny CEO, en ny struktur og en ny strategi tiltag der begejstrer aktiemarkedet og investorer men som i den grad dumper i Danskernes øjne. Den ensidige fokus på bedre nøgletal har kostet banken sin goodwill egenkapital og man kan hævde at banken er gået emotionelt konkurs i Danmarks øjne. At televirksomheder som TDC, Telenor og Telia der bryster sig af tilgængelighed, ease of use og højt kundefokus stadig hører til blandt de virksomheder danske forbrugere elsker at hade - Telenors kundeservice blevt hængt til tørre på Facebook og har over fire år sat hele ti omdømme point til. At Arla Foods langsomt har arbejdet sig ud af skammekrogen som en virksomhed der fik skyld for at have taget livet af de lokale mejerier til i dag at være en global spiller med en ambition om at blive verdens største sustainable dairy company - virksomhedens fokus på miljø, dyrevelfærd og madspil synes at vinde gehør blandt moderne danske forbrugere. se udvikling i dimension vægt 12

13 Section 3 Country results List of nominated companies. Familiarity. Pulse rankings. Pulse development. Country drivers. Dimension rankings. Products vs. Enterprise

14 Most visible companies The published companies in Denmark 2013 List of companies Denmark [Sorted alphabetically] 3 ISS A.P. Møller - Mærsk JP/Politikens hus RepTrak Pulse average Aldi JYSK 63,6 Apple Inc. (Apple) LEGO Group (LEGO) Arla Foods Matas Bang & Olufsen McDonald's Berlingske media Microsof t BP Nordea Carlsberg Group (Carlsberg) Novo Nordisk Coloplast Group Novozymes Denmark n= Coop PANDORA Group Danf oss Saxo Bank Danish Crow n Shell (Dansk Shell) Dansk Supermarked Siemens Wind Pow er Danske Bank-koncernen SuperBest Falck TDC Google Telenor Grundfos Telia Hennes & Mauritz The Coca-Cola Company IKEA koncernen (IKEA) Vestas Berlingske media was fielded as Berlingske media (Berlingske, BT); Coop was fielded as Coop (Kvickly, SuperBrugsen, Dagli'Brugsen, Fakta og Irma); Dansk Supermarked was fielded as Dansk Supermarked (Bilka, Føtex og Netto); ISS was fielded as ISS (ISS Facility Services); JP/Politikens hus was fielded as JP/Politikens hus (JP, Politiken, Ekstrabladet; Vestas was fielded as Vestas (Vestas Wind Systems) 14

15 Familiarity distribution Denmark (1/2) Familiarity distribution (%) [Denmark] [sorted by very familiar] Very familiar Somewhat familiar Have only heard the name Not at all familiar Not sure Coop 58% 32% 6% 2% 3% n = Google 55% 34% 9% 1% 2% n = 689 Dansk Supermarked 53% 35% 7% 1% 3% n = Matas 51% 38% 8% 1% 2% n = 689 Arla Foods 49% 41% 7% 1% 1% n = The Coca-Cola Company 48% 36% 11% 2% 3% n = 689 McDonald's 48% 40% 9% 1% 2% n = 689 Microsof t 45% 41% 12% 1% 2% n = 689 Hennes & Mauritz 45% 39% 12% 2% 3% n = 689 JYSK 44% 42% 10% 1% 2% n = 689 Aldi 43% 40% 13% 1% 2% n = 689 TDC 43% 42% 11% 2% 2% n = Falck 42% 43% 11% 2% 2% n = 689 IKEA koncernen (IKEA) 41% 41% 14% 2% 2% n = Danske Bank-koncernen 40% 37% 19% 2% 3% n = LEGO Group (LEGO) 40% 44% 13% 2% 2% n = SuperBest 39% 42% 15% 2% 2% n = Apple Inc. (Apple) 38% 38% 19% 3% 2% n = 689 A.P. Møller - Mærsk 37% 52% 10% 1% 1% n = Bang & Olufsen 36% 42% 18% 2% 3% n = 689 Novo Nordisk 35% 53% 9% 1% 1% n = Nordea 35% 36% 24% 2% 2% n = Vestas 33% 52% 12% 1% 1% n = Danish Crow n 33% 44% 19% 2% 2% n = 689 Carlsberg Group (Carlsberg) 32% 42% 21% 3% 2% n = % 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 15

16 Familiarity distribution Denmark (2/2) Familiarity distribution (%) [Denmark] [sorted by very familiar] Very familiar Somewhat familiar Have only heard the name Not at all familiar Not sure JP/Politikens hus 29% 41% 22% 4% 3% n = Shell (Dansk Shell) 26% 43% 24% 3% 4% n = Telenor 26% 35% 33% 3% 3% n = Telia 25% 40% 30% 3% 3% n = Berlingske media 23% 42% 27% 5% 4% n = Danf oss 21% 44% 29% 3% 3% n = Grundfos 18% 40% 33% 5% 3% n = % 28% 33% 15% 6% n = Siemens Wind Pow er 14% 29% 35% 18% 3% n = 689 ISS 14% 32% 36% 14% 5% n = BP 13% 30% 36% 17% 4% n = 689 PANDORA Group 13% 29% 39% 14% 5% n = Novozymes 12% 26% 37% 20% 5% n = Coloplast Group 9% 22% 43% 20% 5% n = Saxo Bank 9% 22% 55% 9% 5% n = % 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 16

17 RepTrak Pulse Denmark ,1 LEGO Group (LEGO) 82,2 Novo Nordisk 79,5 Danfoss 79,1 A.P. Møller - Mærsk 79,0 Google 78,9 Grundfos 76,6 Falck 75,7 Carlsberg Group (Carlsberg) 74,9 Matas 73,9 Novozymes 73,9 Apple Inc. (Apple) 73,5 Bang & Olufsen 72,9 Siemens Wind Power 72,6 Coloplast Group 72,2 IKEA koncernen (IKEA) 70,4 Coop 68,3 Microsoft RepTrak Pulse Denmark ,1 Dansk Supermarked 65,9 Arla Foods 65,6 JYSK 65,0 Vestas 61,9 Hennes & Mauritz 61,6 Nordea 60,2 The Coca-Cola Company 58,3 JP/Politikens hus 57,9 Danish Crown 56,6 Shell (Dansk Shell) 56,2 PANDORA Group 54,3 Berlingske media 52,9 ISS 51,6 Telenor Excellent/Top tier 80+ Strong/Robust Average/Moderate Weak/Vulnerable Poor/Low est tier <40 51,2 SuperBest 50,6 TDC 49,7 3 48,5 Aldi 47,9 Saxo Bank 46,9 Telia 46,0 McDonald's 42,3 BP 35,8 Danske Bank-koncernen n =

18 RepTrak Pulse development Pulse ranking 2013 vs (1/2) RepTrak Pulse development Denmark [sorted by 2013] # 1 LEGO Group (LEGO) 89,6 87,1-2,4 Highest score 2013 # 2 Novo Nordisk 80,0 82,2 2,2 LEGO Group (LEGO) # 3 Danf oss 80,8 79,5-1,3 # 4 A.P. Møller - Mærsk 77,8 79,1 1,3 # 5 Google 83,2 79,0-4,2 # 6 Grundfos 80,4 78,9-1,5 Lowest score 2013 # 7 Falck - 76,6 Danske Bank-koncernen # 8 Carlsberg Group (Carlsberg) 76,4 75,7 # 9 Matas - 74,9 # 10 Novozymes - 73,9 # 11 Apple Inc. (Apple) 77,9 73,9-4,0 Biggest clim b 2013 # 12 Bang & Olufsen 81,0 73,5-7,5 McDonald's # 13 Siemens Wind Pow er 76,7 72,9-3,8 # 14 Coloplast Group - 72,6 # 15 IKEA koncernen (IKEA) 72,2 72,2 # 16 Coop 71,2 70,4 Biggest fall ,6 # 17 Microsof t 73,0 68,3-4,7 Danske Bank-koncernen # 18 Dansk Supermarked 68,3 66,1-2,2 # 19 Arla Foods 62,4 65,9 3,5 # 20 JYSK 71,7 65,6-6,0 # 21 Vestas 68,6 65,0-3,6 # 22 Hennes & Mauritz - 61,9 # 23 Nordea 64,7 61,6-3,1 # 24 The Coca-Cola Company 60,9 60,2 # 25 JP/Politikens hus - 58,3 n = ,1 35,8 4,1 18

19 RepTrak Pulse development Pulse ranking 2013 vs (2/2) RepTrak Pulse development Denmark [sorted by 2013] # 26 Danish Crow n - 57,9 # 27 Shell (Dansk Shell) - 56,6 # 28 PANDORA Group 53,5 56,2 2,8 # 29 Berlingske media - 54,3 # 30 ISS 55,0 52,9-2,1 # 31 Telenor 56,3 51,6-4,7 # 32 SuperBest 54,0 51,2-2,8 # 33 TDC 48,1 50,6 2,5 # ,1 49,7 3,6 # 35 Aldi 50,1 48,5-1,6 # 36 Saxo Bank - 47,9 # 37 Telia 47,8 46,9 # 38 McDonald's 41,8 46,0 4,1 # 39 BP 44,1 42,3-1,8 # 40 Danske Bank-koncernen 53,4 35,8-17,6 n =

20 RepTrak Pulse development RepTrak Pulse development Denmark [sorted by 2013] # 1 LEGO Group (LEGO) 88,2 88,0 87,2 89,6 87,1 # 21 Vestas 82,7 80,9 73,8 68,6 65,0 # 2 Novo Nordisk 82,7 82,0 83,5 80,0 82,2 # 22 Hennes & Mauritz ,9 # 3 Danf oss 84,6 81,1 81,3 80,8 79,5 # 23 Nordea 59,8 60,0 61,4 64,7 61,6 # 4 A.P. Møller - Mærsk 77,6 76,1 76,4 77,8 79,1 # 24 The Coca-Cola Company ,8 60,9 60,2 # 5 Google ,6 83,2 79,0 # 25 JP/Politikens hus ,3 # 6 Grundfos 80,7 79,9 80,4 80,4 78,9 # 26 Danish Crow n 59,9 54,4 57,9-57,9 # 7 Falck 79,2 79, ,6 # 27 Shell (Dansk Shell) 59,8 56,7 57,7-56,6 # 8 Carlsberg Group (Carlsberg) 78,4 78,6 77,1 76,4 75,7 # 28 PANDORA Group ,5 56,2 # 9 Matas ,9 # 29 Berlingske media ,3 # 10 Novozymes 79,0 78,0 77,9-73,9 # 30 ISS 51,1 53,2 56,8 55,0 52,9 # 11 Apple Inc. (Apple) 78,5 78,6-77,9 73,9 # 31 Telenor - 61,4 55,9 56,3 51,6 # 12 Bang & Olufsen 80,6 78,3 81,0 81,0 73,5 # 32 SuperBest - 42,6 50,8 54,0 51,2 # 13 Siemens Wind Pow er - 72,8-76,7 72,9 # 33 TDC 52,0 56,3 48,6 48,1 50,6 # 14 Coloplast Group 77,4 76,9 74,4-72,6 # ,8 46,1 49,7 # 15 IKEA koncernen (IKEA) 75,7 76,8 77,0 72,2 72,2 # 35 Aldi 45,7 45,8 50,6 50,1 48,5 # 16 Coop 68,9 69,8-71,2 70,4 # 36 Saxo Bank - 54,1 49,3-47,9 # 17 Microsof t 68,5 69,0 70,4 73,0 68,3 # 37 Telia 46,7 45,2 46,8 47,8 46,9 # 18 Dansk Supermarked 67,6 65,1-68,3 66,1 # 38 McDonald's 43,7 44,4 49,9 41,8 46,0 # 19 Arla Foods 55,7 58,4 63,1 62,4 65,9 # 39 BP ,1 42,3 # 20 JYSK 70,3 67,5 68,8 71,7 65,6 # 40 Danske Bank-koncernen 59,8 49,5 58,8 53,4 35,8 n =

21 Denmark drivers 2013 and development Dimension drivers Denmark Dimension drivers Denmark 12,2% 19,5% 25 12,9% 11,5% 15,2% 11,5% 17,2% Products & Services Governance Citizenship Leadership Perf ormance Workplace Innovation n = Adj. R 2 = 0, Products & Services 27,2 25,7 23,3 21,2 19,5 Innovation 10,7 10,7 11,1 9,9 11,5 Workplace 9,9 9,8 11,0 11,9 11,5 Governance 14,8 15,6 14,7 17,3 17,2 Citizenship 13,3 13,7 13,9 14,9 15,2 Leadership 15,7 15,5 15,8 12,5 12,9 Perf ormance 8,4 9,0 10,1 12,3 12,2 n = Adj. R 2 = 0,669 0,638 0,688 0,681 0,675 21

22 Dimension distribution Denmark Dimension distribution Q Denmark [by dimension order] Negative (1-2) Neutral (3-5) Positive (6-7) "Not sure %" Score Products & Services 11% 46% 31% 12% 66,2 Innovation 11% 43% 26% 20% 62,7 Workplace 9% 28% 18% 45% 61,1 Governance 14% 36% 17% 32% 57,8 Citizenship 12% 32% 17% 39% 58,8 Leadership 10% 32% 20% 38% 62,8 Perf ormance 7% 34% 28% 31% 68,1 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% n =

23 Denmark dimension ranking Products/Services, Innovation, Workplace Denmark dimension top 10 Products & Services LEGO Group (LEGO) Novo Nordisk Grundfos Bang & Olufsen** 87,3 83,8 83,3 83,1 Innovation Google** Apple Inc. (Apple)** Novo Nordisk LEGO Group (LEGO) 85,4 85,0 84,3 82,8 Workplace Google** Novo Nordisk LEGO Group (LEGO) Grundfos 81,1 80,1 78,6 77,1 Google** 82,9 Grundfos 78,0 Danf oss 73,7 Danf oss 81,0 Novozymes 76,5 Falck** 72,2 Matas** 78,8 Danf oss 76,3 Matas** 72,2 A.P. Møller - Mærsk 78,2 Siemens Wind Pow er** 75,3 Microsof t** 71,5 Apple Inc. (Apple)** 77,8 Bang & Olufsen** 71,5 Siemens Wind Pow er** 71,1 Coloplast Group 77,3 IKEA koncernen (IKEA) 71,3 Bang & Olufsen** 70,7 n = n = n = ** indicates single statement dimension 23

24 Denmark dimension ranking Governance, Citizenship Denmark dimension top 10 Governance LEGO Group (LEGO) Grundfos Danf oss Novo Nordisk 79,6 77,1 75,1 74,5 Citizenship LEGO Group (LEGO) Grundfos Novo Nordisk Danf oss 81,8 79,9 79,3 78,6 Google** 71,0 A.P. Møller - Mærsk 74,6 Coloplast Group 69,1 Siemens Wind Pow er** 72,9 Novozymes 69,0 Carlsberg Group (Carlsberg) 72,2 Carlsberg Group (Carlsberg) 68,8 Vestas** 71,7 Matas** 68,3 Novozymes 71,6 Siemens Wind Pow er** 68,0 Google** 70,9 n = n = ** indicates single statement dimension 24

25 Denmark dimension ranking Leadership, Performance Denmark dimension top 10 Leadership LEGO Group (LEGO) Novo Nordisk A.P. Møller - Mærsk Grundfos 84,4 83,9 80,9 79,1 Performance Novo Nordisk Google** LEGO Group (LEGO) Apple Inc. (Apple)** 87,7 85,2 85,1 84,9 Danf oss 77,6 A.P. Møller - Mærsk 81,3 Apple Inc. (Apple)** 76,7 IKEA koncernen (IKEA) 79,6 Carlsberg Group (Carlsberg) 76,1 Grundfos 79,4 JYSK** 75,6 Novozymes 78,0 Novozymes 74,0 JYSK** 77,8 Microsof t** 71,3 Microsof t** 76,5 n = n = ** indicates single statement dimension 25

26 Support for the most and least reputable companies in Denmark Most reputable companies vs. least reputable companies Supportive behavior distribution Negative (1-2) Neutral (3-5) Positive (6-7) Not sure Count 5 Most reputable companies 5% 36% 45% 14% n = Buy 5 least reputable companies 43% 36% 10% 11% n = Recommend products 5 Most reputable companies 4% 35% 49% 12% n = least reputable companies 40% 38% 8% 13% n = Trust 5 Most reputable companies 3% 39% 48% 10% n = least reputable companies 32% 42% 11% 14% n = Recommend company 5 Most reputable companies 4% 34% 51% 11% n = least reputable companies 43% 35% 9% 13% n = Say something positive 5 Most reputable companies 3% 39% 51% 7% n = least reputable companies 34% 44% 11% 12% n = Invest 5 Most reputable companies 11% 35% 37% 17% n = least reputable companies 51% 25% 8% 16% n = Recommend as investment 5 Most reputable companies 8% 33% 35% 25% n = least reputable companies 43% 26% 8% 23% n = Work for 5 Most reputable companies 14% 31% 41% 15% n = least reputable companies 52% 28% 7% 13% n = Hear positive things about 5 Most reputable companies 3% 35% 57% 5% n = least reputable companies 33% 46% 10% 11% n = Benefit of the doubt 5 Most reputable companies 4% 41% 41% 14% n = least reputable companies 33% 41% 11% 16% n = % 20% 40% 60% 80% 100% 26

27 Industry ranking Denmark Industry rank Denmark Pharmaceuticals (3) 76,2 n = Computer (3) 73,7 n = 317 Consumer Products (3) 68,4 n = 693 Retail - General (4) 65,3 n = 610 Energy (7) 60,4 n = Information & Media (3) 58,5 n = 891 Retail - Food (4) 58,4 n = 961 Financial - Insurance (5) 57,2 n = Financial - Bank (6) 53,4 n = Telecommunications (4) 49,7 n = Total n=

28 Appendix 1 Demographics Respondent profile.

29 Respondent profile Denmark 2013 Demographic group: counts and % Denmark All respondents Gender Male 50% Female 50% Age % % % % Region Capital area 25% Islands 33% Jutland 42% Education Low education 13% Middle education 17% Long education 71% 29

30 Appendix 2 Methodology Fielding methodology. Research design. Key analyses and modelling techniques.

31 Fielding methodology & Research design Qualified respondents are: Adults between who reported that they were either Somewhat Familiar or Very Familiar with one of the companies in the study. Furthermore, respondents who are not able to give valid responses to 3 of the 4 Pulse questions are screened out. Data collection method: Respondents filled out a 15 minute online RepTrak questionnaire designed to measure overall corporate reputation and related questions. The questionnaire used for this research is based on the proprietary RepTrak model developed by Reputation Institute for analysis of corporate reputations. Respondents were invited to participate in this project through ed invitations sent to a carefully screened online panel managed by an established commercial market research firm, member of ESOMAR. Respondents were randomly assigned to rate up to 5 companies in a Pulse study and 2 companies in a Deep Dive study with which they were familiar. Fielding period: January February, 2013 Number of respondents: A minimum of 300 respondents provided ratings for each Deep Dive and a minimum of 100 for each Pulse company in the study. Sample representation: Responses were weighted to represent the national profile on demographics, including age and gender. Note on Gaps: All Gaps are calculated using exact scores. Occasionally reported gaps appear to differ by 0.1 from gaps calculated between scores with one decimal. This is due to rounding error. Note on Sample Sizes: All sample sizes reported are based on weighted data. Occasionally the weighting procedure produces a slightly smaller or larger sample size than the unweighted raw data otherwise would. The example to the right shows n = 298 where the raw unweighted count is actually 300. Note on RepTrak Pulse Scores: The RepTrak Pulse is calculated on the basis of the answers from the four variables that measure the respondent s esteem, feeling, admiration and trust (captured in the Pulse score on a scale).. 31

32 Key Analysis & Modeling Techniques RepTrak Pulse Score All RepTrak analyses begin with a single reputation score (the RepTrak Pulse) that is decomposed into a set of underlying dimensions and attributes. The process of decomposition involves application of various forms of multivariate analyses designed to address interdependence and multicollinearity in data obtained from cognitive research. At the core, the RepTrak Pulse measures reputation consisting of three questions about the emotional appeal of the company and a rating of the Overall Reputation of the company. Structural Equation Modelling indicates that these four variables are a reliable indicator of the reputation construct. [Company] is a company I have a good feeling about [Company] is a company that I trust [Company] is a company that I admire and respect [Company] has a good overall reputation Attributes were measured on 7-point scales, where 1 = Strongly Disagree and 7 = Strongly Agree. Results are re-scaled to 100-point scale for easier interpretation. Driver Analysis The relative contribution of individual attributes/single-statement dimensions to the RepTrak Pulse is calculated from a factor adjusted regression modeling procedure. Individual attribute/single-statement dimension weights range from 0-1, and total to 100%. Dimension weights are calculated from the attribute weights. To determine drivers of reputation, the weights are developed with a Factor Adjusted Linear Regression: Factor analysis is used to determine the unique contribution of each attribute to the variance of the RepTrak Pulse. Equamax rotation is used to assign the factors to the attributes/single-statement dimensions. It creates an orthogonal structure of uncorrelated variables that allows the regression to be performed without interference from multicollinearity. It is used to maximize interpretation of the final set of regression coefficients. Linear Regression is run using the Raw Pulse Construct as the dependent variable and the factor scores as the independent variables. Only attributes that were found to be significantly correlated with the reputation (p<0.05) have driver weights assigned. 32

33 Reporting Results Statistical Significance of Results Reported in RepTrak Projects Individual responses to questions asked in a survey enable the calculation of various statistical measures, including averages (means) and standard deviations. The greater the number of responses used in calculating an average, the more confident we are about the accuracy of the score. Similarly, the smaller the range of responses made to a specific question, the more confident we are about the score. Reputation Institute reports scores with a 95% confidence interval in the surveys that we conduct. The interval describes our confidence that, if we conducted the same study repeatedly, 95 times out of 100 the obtained score would lie within the confidence interval. It therefore describes how statistically different a score is likely to be from another score. If a measure is created from multiple questions, the variation in responses is reduced, and our confidence in the average obtained from the combined questions is higher, thereby shrinking the confidence interval. The specific formula Reputation Institute therefore uses to calculate a 95% confidence interval around the mean is therefore: Directional Scores Confidence Interval = Average Score +/ * Average Standard Deviation of Attributes / SQRT (Sample Size * # of Attributes) When analyzing subgroups and/or specific and hard-to-reach stakeholders, sample sizes will often have limited power and reliability. As the sample size shrinks, results become directional in nature. At extremely low counts, results become unreliable and are not shown. In this report low and insufficient counts are denoted as per below: *Low counts (<50) scores are directional (refer to appendix for details on directional scores) **Insufficient counts (<30) 33

34 Standardizing all Reputation Scores RepTrak Scores - Standardized and Comparable Market research shows that people are inclined to rate companies more or less favorably in different countries, or when they are asked questions directly or online. When asked in a personal interview, for example, it s known that people tend to give a company higher ratings than when they are asked by phone, or when they are asked to answer questions about the company online. This is a well-established source of systematic bias. Another source of systematic bias comes from national culture - in some countries, people are universally more positive in their responses than in other countries. In statistical terms, it means that the entire distribution of scores in a positive country is artificially shifted in a positive direction for all companies, good or bad. The distribution of scores in that country may also be more spread out than in another because people have more information and are able to make more subtle differences between companies. To overcome this systematic bias, Reputation Institute s policy is to adjust all RepTrak scores by standardizing them against the aggregate distribution of all scores obtained from the Reputation Institute s Annual Global RepTrak Pulse. Standardization has the effect of lowering scores in countries that tend to over-rate companies, and has the effect of raising scores for companies in countries that tend to rate companies more negatively.. Two adjustments are made for every RepTrak Score US & Canada, 4% Latin America, 14% Global distribution of attitudes Very positive Positive Neutral Negative Very negative Europe, -3% Asia, 12% Australia & New Zealand, -9% South Africa, 20% Reputation Institute uses its cumulative database of RepTrak Pulse scores about reputation scores internationally to carry out two adjustments: Country Adjustment: All scores derived from surveys are standardized by subtracting the country mean and dividing by the standard deviation of all known scores previously obtained in that country. In statistical terms, this adjustment normalizes the distribution of scores in the country to a mean of 0 and a standard deviation of 1, producing a z-score for the observation. Global Adjustment: The z-score obtained on the country level is then used to determine the globally adjusted score. In order to do this, the results are scaled back by multiplying each company s score by the global standard deviation and adding back the global mean. The resulting number is the globally adjusted score. As additional global research comes in, Reputation Institute regularly updates the country and global distributions that are used to create our standardized RepTrak scores. All RepTrak results are therefore comparable across industries, countries, and over time.. 34

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