Annual RepTrak™ Reportimg.borsen.dk/img/cms/tuksi4/uploads/img_server... · Dansk Supermarked 3% n = 2.464 Matas 2% n = 689 Arla Foods 1% n = 1.088 The Coca-Cola Company 3% n =

RepTrak™ is a registered trademark of Reputation Institute

© 2013 Reputation Institute, all rights reserved

Annual

RepTrak™

Report

DenmarkCountry report 2013

2

About Reputation Institute

We enable leaders to make business

decisions that build and protect reputation

capital and drive competitive advantage

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.

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 AdviceResearch

Insight

Strategy

Activation

Publication

Conferences

Training

Information

Analysis

Presentation

3

Table of contents

Introduction Section 1 4

Country resultsSection 2 11

DemographicsAppendix 1 26

MethodologyAppendix 2 28

TerminologyAppendix 3 33

IntroductionSection 1

About the study. The RepTrak™ model. Executive

summary.

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 2013.

Contact information

For more information about the study please

contact:

[CONTACT] [[email protected]]

5

About this study

6

The RepTrak™ model explains Reputation For Deep Dive studies

1

2

3

The RepTrak™ ModelReputation 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 - ReputationRepTrak™ Pulse is the core of a company’s

reputation and shows how strong the emotional

bond is between the company and the public.

2 - DimensionsThe RepTrak™ model consists of seven

operational dimensions and 23 attributes that

explain the reputation profile.

3 - AttributesThe 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

8

Why should we care about reputation? Getting to bottom-line results

Direct experience

What a company

communicates

What others say

Touch Points Reputation Behavior Business Results

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.

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.

RepTrak™ Pulse and Multi-

statement dimensions> 1,0

Single-statement dimensions

and Attributes> 1,5

Statistic Signif icance

9

About this study Significant differences and normative scale

Excellent/Top tier 80+

Strong/Robust 70-79

Average/Moderate 60-69

Weak/Vulnerable 40-59

Poor/Low est tier <40

Country InsightsSection 2

Commentary by Henrik Strøier

11

Executive summary I

På 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 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 flere gode eksempler på virksomheder der evner at leve op de forventninger og der desværre også flere eksempler på virksomheder der dumper i Danmarks øjne.

se udvikling i dimension vægt

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 netop arketypen på en virksomheder hvor høj forretningsmoral, samfundssind, klasseprodukter 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; blandet med at udvise høj tillid og 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

Country resultsSection 3

List of nominated companies. Familiarity. Pulse

rankings. Pulse development. Country drivers.

Dimension rankings. Products vs. Enterprise

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 Microsoft

BP Nordea

Carlsberg Group (Carlsberg) Novo Nordisk

Coloplast Group Novozymes Denmark n=

Coop PANDORA Group 10.747

Danfoss 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

14

Most visible companies

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)

The published companies in Denmark 2013

15

Familiarity distribution Denmark (1/2)

Coop 3% n = 2.225

Google 2% n = 689

Dansk Supermarked 3% n = 2.464

Matas 2% n = 689

Arla Foods 1% n = 1.088

The Coca-Cola Company 3% n = 689

McDonald's 2% n = 689

Microsoft 2% n = 689

Hennes & Mauritz 3% n = 689

JYSK 2% n = 689

Aldi 2% n = 689

TDC 2% n = 2.551

Falck 2% n = 689

IKEA koncernen (IKEA) 2% n = 2.872

Danske Bank-koncernen 3% n = 3.094

LEGO Group (LEGO) 2% n = 4.331

SuperBest 2% n = 2.851

Apple Inc. (Apple) 2% n = 689

A.P. Møller - Mærsk 1% n = 1.910

Bang & Olufsen 3% n = 689

Novo Nordisk 1% n = 1.910

Nordea 2% n = 3.215

Vestas 1% n = 1.910

Danish Crow n 2% n = 689

Carlsberg Group (Carlsberg) 2% n = 4.031

Familiarity distribution (%)

[Denmark]

[sorted by very familiar]

58%

55%

53%

51%

49%

48%

48%

45%

45%

44%

43%

43%

42%

41%

40%

40%

39%

38%

37%

36%

35%

35%

33%

33%32%

32%

34%

35%

38%

41%

36%

40%

41%

39%

42%

40%

42%

43%

41%

37%

44%

42%

38%

52%

42%

53%

36%

52%

44%42%

6%

9%

7%

8%

7%

11%

9%

12%

12%

10%

13%

11%

11%

14%

19%

13%

15%

19%

10%

18%

9%

24%

12%

19%

21%

2%

1%

1%

1%

1%

2%

1%

1%

2%

1%

1%

2%

2%

2%

2%

2%

2%

3%

1%

2%

1%

2%

1%

2%

3%

Very familiar Somewhat familiar Have only heard the name Not at all familiar Not sure

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

JP/Politikens hus 3% n = 4.105

Shell (Dansk Shell) 4% n = 4.057

Telenor 3% n = 3.935

Telia 3% n = 3.877

Berlingske media 4% n = 4.046

Danfoss 3% n = 5.412

Grundfos 3% n = 5.458

3 6% n = 4.588

Siemens Wind Pow er 3% n = 689

ISS 5% n = 4.846

BP 4% n = 689

PANDORA Group 5% n = 5.030

Novozymes 5% n = 4.626

Coloplast Group 5% n = 5.020

Saxo Bank 5% n = 5.015

Familiarity distribution (%)

[Denmark]

[sorted by very familiar]

29%

26%

26%

25%

23%

21%

18%

18%

14%

14%

13%

13%

12%

9%9%

41%

43%

35%

40%

42%

44%

40%

28%

29%

32%

30%

29%

26%

22%22%

22%

24%

33%

30%

27%

29%

33%

33%

35%

36%

36%

39%

37%

43%

55%

4%

3%

3%

3%

5%

3%

5%

15%

18%

14%

17%

14%

20%

20%

9%

Very familiar Somewhat familiar Have only heard the name Not at all familiar Not sure

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

16

Familiarity distribution Denmark (2/2)

RepTrak™ Pulse

Denmark 2013

n = 10.747

87,1

82,2

79,5

79,1

79,0

78,9

76,6

75,7

74,9

73,9

73,9

73,5

72,9

72,6

72,2

70,4

68,3

66,1

65,9

65,6

65,0

61,9

61,6

60,2

58,3

57,9

56,6

56,2

54,3

52,9

51,6

51,2

50,6

49,7

48,5

47,9

46,9

46,0

42,3

35,8

0

10

20

30

40

50

60

70

80

90

100

LE

GO

Gro

up

(LE

GO

)

Novo N

ord

isk

Danfo

ss

A.P

. M

ølle

r -

Mæ

rsk

Go

og

le

Gru

ndfo

s

Fa

lck

Carlsb

erg

Gro

up

(C

arlsbe

rg)

Ma

tas

Novozym

es

App

le I

nc. (A

pple

)

Ban

g &

Olu

fsen

Sie

me

ns W

ind P

ow

er

Colo

pla

st G

roup

IKE

A k

on

cern

en (

IKE

A)

Coop

Mic

roso

ft

Dansk S

upe

rma

rked

Arla

Food

s

JY

SK

Vesta

s

Henn

es &

Ma

uri

tz

Nord

ea

Th

e C

oca

-Cola

Com

pan

y

JP

/Po

litik

en

s hu

s

Danis

h C

row

n

She

ll (D

ansk S

hell)

PA

ND

OR

A G

roup

Berl

ingske m

ed

ia

ISS

Te

leno

r

Sup

erB

est

TD

C 3

Ald

i

Saxo B

an

k

Te

lia

McD

ona

ld's

BP

Danske B

an

k-ko

ncern

en

17

RepTrak™ Pulse Denmark 2013

Excellent/Top tier 80+

Strong/Robust 70-79

Average/Moderate 60-69

Weak/Vulnerable 40-59

Poor/Low est tier <40

18

RepTrak™ Pulse development Pulse ranking 2013 vs. 2012 (1/2)

Denmark

[sorted by 2013] 2012 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 Danfoss 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 climb 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 2013 -17,6

# 17 Microsoft 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 = 6.159 7.006

RepTrak™ Pulse development

87,1

35,8

4,1

2012-

2013

Denmark

[sorted by 2013] 2012 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

# 34 3 46,1 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 = 3.097 3.741


2012-

2013

19

RepTrak™ Pulse development Pulse ranking 2013 vs. 2012 (2/2)

20

RepTrak™ Pulse development 2010 – 2013

Denmark

[sorted by 2013] 2009 2010 2011 2012 2013 2009 2010 2011 2012 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 - - - - 61,9

# 3 Danfoss 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 - - 62,8 60,9 60,2

# 5 Google - - 81,6 83,2 79,0 # 25 JP/Politikens hus - - - - 58,3

# 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 79,1 - - 76,6 # 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 - - - 53,5 56,2

# 9 Matas - - - - 74,9 # 29 Berlingske media - - - - 54,3

# 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 # 34 3 - - 48,8 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 Microsoft 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 - - - 44,1 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 = 6.349 6.121 4.443 5.328 6.111 3.250 3.910 5.051 3.928 4.635


n = 10.410

Adj. R2 = 0,675

Dimension drivers

Denmark 2013

12,2% 19,5%

15,2% 11,5%

12,9% 11,5%

17,2%

2009 2010 2011 2012 2013

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

Performance 8,4 9,0 10,1 12,3 12,2

n = 17.832 14.700 13.200 6.512 10.410

Adj. R2 = 0,669 0,638 0,688 0,681 0,675

Denmark

Dimension drivers

Products & Services

InnovationWorkplace

Governance

Citizenship

LeadershipPerformance

5

10

15

20

25

30

21

Denmark drivers 2013 and development

22

Dimension distribution Denmark

Dimension distribution Q1 2013

Score

Products & Services 11% 12% 66,2

Innovation 11% 20% 62,7

Workplace 9% 45% 61,1

Governance 14% 32% 57,8

Citizenship 12% 39% 58,8

Leadership 10% 38% 62,8

Performance 7% 31% 68,1

n = 10.747

Denmark

[by dimension order]

46%

43%

28%

36%

32%

32%

34%

31%

26%

18%

17%

17%

20%

28%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Negative (1-2) Neutral (3-5) Positive (6-7) "Not sure %"

23

Denmark dimension ranking

** indicates single statement dimension

Products/Services, Innovation, Workplace

n = 3.276 n = 3.272 n = 2.858

Danfoss

Siemens Wind Pow er**

Bang & Olufsen**

IKEA koncernen (IKEA)

Google**

Novo Nordisk

LEGO Group (LEGO)

Grundfos

Danfoss

Falck**

Matas**

Microsoft**


Bang & Olufsen**

Products & Services

Bang & Olufsen**

Google**

LEGO Group (LEGO)

Novo Nordisk

Grundfos

Denmark dimension top 10

Google**

Apple Inc. (Apple)**

Novo Nordisk

LEGO Group (LEGO)

Grundfos

Danfoss

Matas**

A.P. Møller - Mærsk


Coloplast Group

WorkplaceInnovation

Novozymes

87,3

83,8

83,3

83,1

82,9

81,0

78,8

78,2

77,8

77,3

85,4

85,0

84,3

82,8

78,0

76,5

76,3

75,3

71,5

71,3

81,1

80,1

78,6

77,1

73,7

72,2

72,2

71,5

71,1

70,7

24



Governance, Citizenship

n = 3.768 n = 3.773

Grundfos

Danfoss

Novo Nordisk

Google**

LEGO Group (LEGO)

Governance

Coloplast Group

Novozymes

Carlsberg Group (Carlsberg)

Matas**



Carlsberg Group (Carlsberg)

Vestas**

Novozymes

LEGO Group (LEGO)

Grundfos

Novo Nordisk

Danfoss

A.P. Møller - Mærsk

Citizenship


Google**

79,6

77,1

75,1

74,5

71,0

69,1

69,0

68,8

68,3

68,0

81,8

79,9

79,3

78,6

74,6

72,9

72,2

71,7

71,6

70,9

25



Leadership, Performance

n = 3.788 n = 3.277


Microsoft** Microsoft**

IKEA koncernen (IKEA)

LEGO Group (LEGO) Novo Nordisk

Novo Nordisk Google**

A.P. Møller - Mærsk LEGO Group (LEGO)

Leadership

Carlsberg Group (Carlsberg) Grundfos

JYSK** Novozymes

Novozymes JYSK**

Grundfos Apple Inc. (Apple)**

Danfoss A.P. Møller - Mærsk


Performance

84,4

83,9

80,9

79,1

77,6

76,7

76,1

75,6

74,0

71,3

87,7

85,2

85,1

84,9

81,3

79,6

79,4

78,0

77,8

76,5

26

Support for the most and least reputable companies in Denmark

Supportive behavior distribution

Count

5 Most reputable companies 5% 14% n = 2.326

5 least reputable companies 43% 11% n = 1.127



















Hear positive things about

Benefit of the doubt

Work for

Most reputable companies vs. least reputable companies

Recommend as investment

Buy

Recommend products

Trust

Recommend company

Say something positive

Invest

36%

36%

35%

38%

39%

42%

34%

35%

39%

44%

35%

25%

33%

26%

31%

28%

35%

46%

41%

41%

45%

10%

49%

8%

48%

11%

51%

9%

51%

11%

37%

8%

35%

8%

41%

7%

57%

10%

41%

11%

0% 20% 40% 60% 80% 100%

Negative (1-2) Neutral (3-5) Positive (6-7) Not sure

27

Industry ranking Denmark

Pharmaceuticals (3) n = 1.960

Computer (3) n = 317

Consumer Products (3) n = 693

Retail - General (4) n = 610

Energy (7) n = 1.515

Information & Media (3) n = 891

Retail - Food (4) n = 961

Financial - Insurance (5) n = 1.309

Financial - Bank (6) n = 1.829

Telecommunications (4) n = 1.207

Total n= 11.292

Denmark

Industry rank

76,2

68,4

60,4

58,4

53,4

73,7

65,3

58,5

57,2

49,7

0 20 40 60 80 100

DemographicsAppendix 1

Respondent profile.

Respondent profile Denmark 2013

29

Denmark

7.420

Gender

Male 50%

Female 50%

18-24 14%

25-34 19%

35-44 24%

45-64 43%

Capital area 25%

Islands 33%

Jutland 42%

Low education 13%

Middle education 17%

Long education 71%

All respondents

Age

Region

Education

Demographic group: counts and %

MethodologyAppendix 2

Fielding methodology. Research design. Key

analyses and modelling techniques.

Fielding methodology & Research design

Qualified respondents are: Adults between 18-64 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 emailed 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 0-100 scale).

.

31

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 multi-

collinearity 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

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:

Confidence Interval = Average Score +/- 1.96 * Average Standard Deviation of Attributes / SQRT (Sample Size * # of Attributes)

Directional Scores

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

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

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.

.

Global distribution of attitudes

US & Canada, 4%

Europe, -3%

Asia, 12%

Australia &

New Zealand, -9%South Africa, 20%

Latin America, 14%

Very positive

Positive

Neutral

Negative

Very negative

34

TerminologyAppendix 3

List of abbreviations.

Abbreviations Supportive behaviours and dimensions

36

Question Short form Full form

Q515_1 Trust If [COMPANY] w as faced w ith a product or service problem, I w ould trust them to do the right thing

Q515_2 Say something positive I w ould say something positive about [COMPANY]

Q515_3 Buy If I had the opportunity, I w ould buy the products/services of [COMPANY]

Q515_4 Recommend products I w ould recommend the products/services of [COMPANY]

Q515_5 Invest If I had the opportunity, I w ould invest in [COMPANY]

Q515_6 Recommend as investment If I had the opportunity, I w ould recommend [COMPANY] as an investment

Q515_7 Work for I w ould w ork for [COPMANY1]

Q515_8 Hear positive things about [COMPANY] is a company that I generally hear people say positive things about

Q515_9 Benefit of the doubt I w ould give the benefit of the doubt to [COMPANY] if the company w as facing a crisis

Q515_10 Recommend company I w ould recommend [COMPANY] to others

Q515_11 Communicate something negative about I w ould go out of my w ay to communicate something negative about [Company1]

Abbreviations

Supportive behavior

Question Short form Full form

Q310_1 Products & Services [COMPANY] offers high quality products and services -- it offers excellent products and reliable services

Q310_2 Innovation [COMPANY] is an innovative company -- it makes or sells innovative products or innovates in the w ay it does business

Q310_3 Workplace [COMPANY] is an appealing place to w ork -- it treats its employees w ell

Q310_4 Citizenship [COMPANY] is a good corporate citizen -- it supports good causes and protects the environment

Q310_5 Governance [COMPANY] is a responsibly-run company -- it behaves ethically and is open and transparent in its business dealings

Q310_6 Leadership [COMPANY] is a company w ith strong leadership -- it has visible leaders and is managed effectively

Q310_7 Performance [COMPANY] is a high-performance company -- it delivers good financial results

Dimensions

Documents

Annual RepTrak™ Reportimg.borsen.dk/img/cms/tuksi4/uploads/img_server... · Dansk Supermarked 3% n = 2.464 Matas 2% n = 689 Arla Foods 1% n = 1.088 The Coca-Cola Company 3% n =