‘The moderating effect of the International Risk Management

(1)

APPENDIX

Source picture: www.milbank.com via Google pictures

‘The moderating effect of the International Risk Management

factor on the legitimacy of Top Management Team diversity in achieving positive company performances’

By

Leonora Lummina Kuipers S1508245

Supervisor: Dr. Marjolein Offenbeek Co-referent: Dr. Bart Jan Pennink

Institution: University of Groningen

Faculty of Management and Organization

Msc. International Business and Management

(2)

Table of content

Appendix I

Conceptual model 2

Appendix II

Value labels Nationality 3

Appendix III

Diversity score per TMT all of the scores per

Demographic 4

Appendix IV

Correlations 7

Appendix V

Tables 14-29 11

Appendix VI

Original SPSS OUTPUT 19

(3)

APPENDIX I

CONCEPTUAL MODEL

Overall TMT diversity heterogeneity score

=======================

 TMT Age

 TMT Functional background

 TMT Educational field

 TMT Team tenure

 TMT nationality

 TMT Gender

(Demographic characteristics of TMT members)

Firm

Performance/Return on sales

TNC environment on MICRO level:

Moderating Factor: International Risk Management

 Country risk

 Revenue risk

 Fixed asset risk

 Foreign employee risk

(4)

APPENDIX II Value labels Nationality

UK 1

The Netherlands 2

Germany 3

Belgium 4

France 5

Italy 6

Luxembourg 7

Denmark 8

Ireland 9

Greece 10

Portugal 11

Spain 12

Austria 13

Finland 14

Sweden 15

Cyprus 16

Czech Republic 17

Estonia 18

Hungary 19

Latvia 20

Lithuania 21

Malta 22

Poland 23

Slovakia 24

Slovenia 25

Norway 26

Switzerland 27

Turkey 28

US 29

China 30

Brazil 31

South-Africa 32

Antigua and Barbuda 33

Australia 34

Uganda 35

India 36

Singapore 37

Canada 38

Tunis 39

Colombia 40

Israel 41

New Zealand 42

Argentina 43

Egypt 44

Malaysia 45

Namibia 46

Mozambique 47

Lebanon 48

Bosnia-Herzegovina 49

Zimbabwe 50

Scotland 51

AfricanAmerican 52

Marrocco 53

LatinAmerican 54

Japan 55

(5)

APPENDIX III diversity score per TMT all of the scores per category / per demographic

characteristic

9,00 are missing values

Functional Educational National Tenure Age Gender

1 General

electrics

,93 ,90 ,41 ,77 ,00 ,56

2 Vodafone

Group PLC

9,00 9,00 ,72 ,76 ,75 ,00

3 Ford Motor 9,00 9,00 9,00 9,00 9,00 9,00

4 General

Motors

,89 ,75 ,59 ,75 ,83 ,27

5 British

Petroleum Company

,73 ,76 ,00 ,67 ,80 ,00

6 Exxon Mobil ,64 ,36 ,70 ,00 9,00 ,00

7 Shell ,82 ,64 ,90 ,64 ,58 ,64

8 Toyota Motor

corporation

9,00 9,00 9,00 9,00 9,00 9,00

9 Total 9,00 9,00 9,00 9,00 9,00 9,00

10 France

Telecom

,93 ,70 ,25 ,00 ,71 ,40

11 Volkswagen

Ag

,91 ,64 ,70 ,43 ,58 ,00

12 Sanofi Aventis 9,00 9,00 9,00 9,00 9,00 9,00

13 Deutsche

telecom

,82 ,43 ,00 ,43 ,67 ,00

14 RWE group ,85 ,91 ,40 ,59 ,58 ,00

15 Suez ,00 ,71 ,56 ,64 ,67 ,00

16 Eon ,95 ,69 ,00 ,59 ,94 ,00

17 Hutchison

Whampoa

,00 ,70 ,52 ,93 ,60 ,49

18 Siemens AG ,86 ,79 ,35 ,68 ,90 ,00

19 Nestle SA ,87 ,85 ,91 ,66 ,80 ,00

20 Electricite de France

,73 ,65 ,40 ,18 ,84 ,27

21 Honda motor

Co LTD

9,00 9,00 9,00 9,00 9,00 9,00

22 Vivendi

Universal

9,00 9,00 ,71 ,33 ,93 ,00

23 Chevron

Texaco

,93 ,65 ,71 ,54 ,54 ,00

24 BMW AG ,57 9,00 ,00 ,67 ,60 ,00

25 Daimler

Chrysler

,51 ,73 ,69 ,66 ,80 ,00

26 Pfizer Inc 9,00 9,00 9,00 9,00 9,00 9,00

27 ENI 9,00 9,00 ,00 ,50 ,00 ,00

28 Nissan Motor

LTD

9,00 9,00 9,00 9,00 9,00 9,00

29 IBM ,90 ,77 ,37 ,62 9,00 ,46

30 Conoco Philips ,93 ,75 ,00 ,76 ,75 ,28

31 Hewlett-

Packard

,88 ,79 ,35 ,43 9,00 ,79

32 Mitsubishi

Corporation

9,00 9,00 9,00 9,00 9,00 9,00

33 Telefonica SA ,82 ,73 ,67 ,00 ,00 ,00

34 Roche Group ,93 ,88 ,82 ,83 9,00 ,00

35 Telecom Italia ,85 ,57 ,00 ,59 ,54 ,00

(6)

American

37 Fiat Spa 9,00 9,00 9,00 9,00 9,00 9,00

38 Unilever ,51 ,71 ,83 ,00 ,45 ,00

39 Carrefour ,00 ,73 ,63 ,43 ,67 ,00

40 Proctor and

Gamble

,98 ,77 ,29 9,00 ,60 ,52

41 Sony

Corporation

9,00 9,00 9,00 9,00 9,00 9,00

42 Mitsui & co Ltd

9,00 9,00 9,00 9,00 9,00 9,00

43 Wal-Mart

Stores

,97 ,82 ,08 ,81 9,00 ,54

44 Deutsche Post

AG

,73 ,67 ,43 ,83 9,00 ,00

45 Compagnie de

Saint Gobain SA

9,00 9,00 9,00 9,00 9,00 9,00

46 Veoila

Environment SA

9,00 9,00 9,00 9,00 9,00 9,00

47 Philips

electronics

,88 ,82 ,93 ,43 ,79 ,00

48 Lafarge SA ,51 ,89 ,46 ,50 ,87 ,00

49 Repsol YPF

SA

9,00 9,00 9,00 9,00 9,00 9,00

50 Novartis ,86 ,68 ,71 ,59 9,00 ,00

51 Glaxo Smith &

Kline

,90 ,87 ,54 ,54 9,00 ,00

52 Endesa 9,00 9,00 9,00 9,00 9,00 9,00

53 Bayer AG ,51 ,51 ,00 ,50 ,60 ,00

54 Altria group

inc

,71 ,79 ,20 ,81 9,00 ,31

55 BASF AG 9,00 9,00 ,00 ,66 ,86 ,00

56 Alcan inc 9,00 9,00 9,00 9,00 9,00 9,00

57 Koninklijke

Ahold

,57 9,00 1,00 ,00 ,54 ,00

58 Renault SA ,76 ,88 ,32 ,54 ,69 ,00

59 Petronas 9,00 9,00 9,00 9,00 9,00 9,00

60 Dow Chemical

COmpany

,76 ,71 ,83 ,00 9,00 ,00

61 Volvo ,00 ,81 9,00 ,67 ,83 ,22

62 AES

corporation

,73 ,88 ,20 9,00 9,00 ,33

63 British

American Tobacco

,51 ,00 ,55 ,67 9,00 ,00

64 Mc Donald

Corp

,95 ,82 ,53 ,67 ,00 ,75

65 Pinault

Printemps redoute SA

,82 ,25 ,20 ,75 ,88 ,00

66 National Grid

Transco

,85 ,82 ,33 ,81 ,60 ,00

67 Matsushita

Electric Industrial LTD

9,00 9,00 9,00 9,00 9,00 9,00

68 United

technologies corporation

9,00 9,00 9,00 9,00 9,00 9,00

(7)

69 Metro AG ,00 ,71 ,50 ,83 ,75 ,00

70 Thomson

Corporation

,76 ,73 ,40 ,50 9,00 ,00

71 Coca Cola

Company

9,00 9,00 9,00 9,00 9,00 9,00

72 NOKIA ,91 ,93 ,56 ,54 ,85 ,31

73 Singtel ltd ,43 ,86 ,18 ,22 ,68 ,79

74 Johnson &

Johnson

9,00 9,00 9,00 9,00 9,00 9,00

75 Diageo PLC ,83 ,76 ,58 ,66 ,59 ,00

76 Mittal Steel

Company NV

9,00 9,00 9,00 9,00 9,00 9,00

77 Inbev 9,00 9,00 ,79 ,00 ,77 ,28

78 Astrazeneca 9,00 9,00 ,50 ,33 ,75 ,00

79 L'air Liquide

Groupe

9,00 9,00 9,00 9,00 9,00 9,00

80 Abbott

Laboratories

,91 ,76 ,33 ,31 ,00 ,22

81 Hitachi Ltd 9,00 9,00 9,00 9,00 9,00 9,00

82 Thyssen Group 9,00 9,00 ,25 ,83 ,87 ,00

(8)

APPENDIX IV

Correlation

Correlations: original SPSS output

Correlations

1 ,053

. ,364

45 45

,053 1

,364 .

45 46

Pearson Correlation

Sig. (1-tailed )

N Pearson Correlation

Sig. (1-tailed )

N LogNormalFunctional

LogFucntieAuden

LogNormal Functional

LogFucntie Auden

Correlations

Correlations

1 ,027

. ,431

45 45

,027 1

,431 .

45 46

Pearson Correlation

Sig. (1-tailed )

N LogNormalFunctional

LogFunctieAdjusted

LogNormal Functional

LogFunctie Adjusted

Correlations

Correlations

1 -,387 **

. ,007

39 39

-,387 ** 1

,007 .

39 39

Pearson Correlation

Sig. (1-tailed )

N LogNormalAge

LogAudenAge

LogNormal

Age LogAudenAge

Correlation is significant at the 0.01 level (1-tailed

). **.

Correlations

Correlations

1 -,323 *

. ,022

39 39

-,323 * 1

,022 .

39 39

Pearson Correlation

Sig. (1-tailed )

N LogNormalAge

LogAdjustedAge

LogNormal

Age LogAdjusted

Age

). *.

(9)

Correlations

Correlations

1 -,039

. ,396

47 47

-,039 1

,396 .

47 47

Pearson Correlation

Sig. (1-tailed )

N LogNormalEducation

LogAudeneduback

LogNormal Education

Log Audened

uback

Correlations

Correlations

1 -,044

. ,385

47 47

-,044 1

,385 .

47 47

Pearson Correlation

Sig. (1-tailed )

N LogNormalEducation

LogAdjustededuback

LogNormal Education

Log Adjustede

duback

Correlations

Correlations

1 -,094

. ,265

47 47

-,094 1

,265 .

47 47

Pearson Correlation

Sig. (1-tailed )

N LogNormalNational

LogAudennational

LogNormal National

Log Audennati

onal

Correlations

Correlations

1 -,095

. ,262

47 47

-,095 1

,262 .

47 47

Pearson Correlation

Sig. (1-tailed )

N LogNormalNational

LogAdjustednational

LogNormal National

Log Adjustedn

ational

(10)

Correlations

1 -,032

. ,415

48 48

-,032 1

,415 .

48 48

Pearson Correlation

Sig. (1-tailed )

N LogNormalTeamTenure

LogAudenTenure

LogNormal TeamTenure

LogAuden Tenure

Correlations

Correlations

1 -,049

. ,369

48 48

-,049 1

,369 .

48 48

Pearson Correlation

Sig. (1-tailed )

N LogNormalTeamTenure

LogAdjustedTenure

LogNormal TeamTenure

LogAdjusted Tenure

Correlations

Correlations

1 ,151

. ,263

20 20

,151 1

,263 .

20 20

Pearson Correlation

Sig. (1-tailed )

N LogNormalGender

LogAudengender

LogNormal Gender

Log Audengender

Correlations

Correlations

1 ,430 *

. ,029

20 20

,430 * 1

,029 .

20 20

Pearson Correlation

Sig. (1-tailed )

N LogNormalGender

LogAdjustedgender

LogNormal Gender

Log Adjustedg

ender

). *.

Correlations

(11)

Correlations

1 ,021

. ,442

49 49

,021 1

,442 .

49 50

Pearson Correlation

Sig. (1-tailed )

N LogNormalEduLevel

LogAudenEdulevel

LogNormal EduLevel

LogAuden Edulevel

Correlations

Correlations

1 ,000

. ,499

49 49

,000 1

,499 .

49 50

Pearson Correlation

Sig. (1-tailed )

N LogNormalEduLevel

LogAdjustedEdulevel

LogNormal EduLevel

LogAdjusted Edulevel

(12)

APPENDIX V: Tables

Table 14:

Regression – Moderator analysis functional background diversity

Hypothesis 1 :

Y(LN)=β**

0

+ β

1

X + β

2

Z +(β

3

X*Z)

Return on Sales

Constant and R² β0=11,056 and ,040

Functional Background diversity (Log) β1= ,200

P value ,187/2 ,0935* (single)

IRM factor Auden β2= -,022

P value ,892 /2 ,446 (multiple)

Functional Background diversity moderated by IRM Auden (log Z.value)

β3= -,001 P value ,996 /2 ,498 (multiple)

IRM Factor Adjusted β2= -,068

P value ,659 /2 ,329 (multiple) Functional Background diversity moderated by IRM Adjusted (log Z.value) β3= 0,055

P value ,725/2 ,363 (multiple)

(N) observations 45

Notes: * significant at 10%¹ ** significant at 5%

Table 15:Mann Whitney/Wilcoxon: Functional diversity high versus medium/low Functional diversity High

versus medium/low N Mean Rank Sum of Ranks

1,00 36 26,36 949,00

2,00 14 23,29 326,00

Company Performance

Total 50

1In my research I chose a probability of α 0,10 and α 0,05.

Test Statistics(a)

Company Performance

Mann-Whitney U 221,000

Wilcoxon W 326,000

Z -0,670

Asymp. Sig. (2-tailed) 0,503

a. Grouping Variable: Functional diversity high versus medium/low

(13)

Table 16:Regression – Moderator analysis educational background diversity

Hypothesis 2: Y(LN)=β**

₀+ β₁X + β₂Z +(β₃

X*Z)

Return on Sales

Constant and R2 β0= 10,612 and ,031

Educational Background diversity (Log) β1= -,176

P value ,237/2 ,1185 (single)

IRM factor Auden β2= -,175

Educational Background diversity moderated by IRM Auden (log Z.value)

IRM factor Adjusted β2= ,001

P value ,994 /2 ,497 (multiple) Educational Background diversity moderated by IRM Adjusted (log Z.value) β3= -,100

(N) observations 47

Notes: * significant at 10% ** significant at 5%

Table 17:Mann Whitney/Wilcoxon: Educational background diversity high versus medium/low Educational diversity High

versus medium/low N Mean Rank Sum of Ranks

1,00 38 23,29 885,00

2,00 10 29,10 291,00

Company Performance

Total 48

Company Performance

Wilcoxon W 885,000

Z -1,168

Exact Sig. [2*(1-tailed Sig.)] 0,252

Asymp. Sig. (1 tailed) 0,126 a. Not corrected for ties.

b. Grouping Variable: Educational diversity high versus medium/low

(14)

Table 18:Regression – Moderator analysis educational level diversity

Hypothesis 2sub: Y(LN)=β**

0+ β1X + β2Z + (β3

X*Z)

Return on Sales

Educational Level diversity (Log) β1= -,019

P value ,898/2 ,449 (single)

IRM Factor Auden β2= ,010

Educational Level diversity moderated by IRM Auden (log Z.value)

β3= ,051 P value ,747/2 ,373 (multiple)

P value ,870 /2 ,435 (multiple) Educational Level diversity moderated by IRM Adjusted (log Z.value) β3= -,047

(N) observations 49

Table 19:Mann Whitney/Wilcoxon: Educational level diversity high versus medium/low Educational Level diversity

High versus low N Mean Rank Sum of Ranks

1,00 30 27,93 838,00

2,00 26 29,15 758,00

Company Performance

Total 56

Company Performance

Wilcoxon W 838,000

Z -0,279

a. Grouping Variable: Educational Level diversity high versus medium low

(15)

Table 20:Regression – Moderator analysis educational level diversity

Hypothesis 3: Y(LN)=β**

0+ β1X + β2Z + (β3

X*Z)

Return on Sales

Team Tenure diversity (Log) β1= ,283

P value ,051/2 ,0255** (single)

P value ,379 /2 ,189 (multiple) Team tenure diversity moderated by IRM

Auden (log Z.value)

β3= -,169 P value ,292/2 ,146 (multiple)

IRM Factor Adjusted β2= ,063

P value ,676 /2 ,338 (multiple) Team Tenure diversity moderated by IRM Adjusted (log Z.value) β3= -,164

(N) observations 48

Table 21:Mann Whitney/Wilcoxon: Team tenure diversity high versus medium/low Tenure diversity High versus

medium/low N Mean Rank Sum of Ranks

1,00 20 28,65 573,00

2,00 32 25,16 805,00

Company Performance

Total 52

Company Performance

Wilcoxon W 805,000

Z -0,809

a. Grouping Variable: Tenure diversity high versus medium/low

(16)

Table 22:Regression – Moderator analysis age diversity

Hypothesis 4:

Y(LN)=β**

0

+ β

1

X + β

2

Z+ (β

3

X*Z)

Return on Sales

Age diversity (Log) β1= -,025

P value ,878/2 ,439 (single)

Age diversity moderated by IRM Auden (log Z.value)

P value ,953 /2 ,329 (multiple) Age diversity moderated by IRM Adjusted (log Z.value) β3= -,295

(N) observations 39

Notes: * significant at 10% ** significant at 5%

Table 23:Mann Whitney/Wilcoxon: Age diversity high versus medium/low Age diversity High versus

1,00 26 22,69 590,00

2,00 18 22,22 400,00

Company Performance

Total 44

Company Performance

Wilcoxon W 400,000

Z -0,119

a. Grouping Variable: Age diversity high versus medium/low

(17)

Table 24:Regression – Moderator analysis nationality diversity

Hypothesis 5: Y(LN)=β**

0+ β1X + β2Z + (β3

X*Z)

Return on Sales

Nationality diversity (Log) β1= -,083

P value ,579/2 ,2895 (single)

Nationality diversity moderated by IRM Auden (log Z.value)

β3= -,181 P value ,264/2 ,132 (multiple)

IRM Factor Adjusted β2= ,042

P value ,792 /2 ,396 (multiple) Nationality diversity moderated by IRM Adjusted (log Z.value) β3= -,139

(N) observations 47

Table 25:Mann Whitney/Wilcoxon: Nationality diversity high versus medium/low National diversity High versus

1,00 15 31,13 467,00

2,00 40 26,83 1.073,00

Company Performance

Total 55

Company Performance

Wilcoxon W 1.073,000

Z -0,888

a. Grouping Variable: National diversity high versus medium/low

(18)

Table 26:Regression – Moderator analysis gender diversity

Hypothesis 6:

Y(LN)=β**

0

+ β

1

X + β

2

Z +(β

3

X*Z)

Return on Sales

Gender diversity (Log) β1= -,009

P value ,971/2 ,4855 (single)

IRM Factor Auden β2= -,104

Gender diversity moderated by IRM Auden (log Z.value)

β3= ,077 P value ,783 /2 ,391(multiple)

Gender diversity moderated by IRM Adjusted (log Z.value) β3= 0,032 P value ,898/2 ,449 (multiple)

(N) observations 20

Notes: * significant at 10% ** significant at 5%

Table 27:Mann Whitney/Wilcoxon: Gender diversity high versus medium/low Gender diversity High versus

1,00 4 16,50 66,00

2,00 54 30,46 1.645,00

Company Performance

Total 58

Company Performance

Wilcoxon W 66,000

Z -1,596

Exact Sig. [2*(1-tailed Sig.)] 0,117

a. Not corrected for ties.

b. Grouping Variable: Gender diversity high versus medium/low

(19)

Table 29:Regression – Moderator analysis overall diversity

Overall Diversity: Y(LN**)=β0

+ β

1

X + β

2

Z +(β

3

X*Z)

Return on Sales

Overall diversity (Log) β1= ,256

P value ,150/2 ,075** (single)

IRM Factor Auden β2= -,006

Overall diversity in TMT moderated by IRM Auden (log Z.value)

β3= ,008 P value ,970/2 ,485(multiple)

P value ,904/2 ,452 (multiple) Overall diversity in TMT moderated by IRM

Adjusted (log Z.value)

β3= - ,008 P value ,972/2 ,486 (multiple)

(N) observations 33

(20)

APPENDIX: Original SPSS OUTPUT Hypotheses Testing

Hypothesis 1 Functional background

Variables Entered/Removed(b)

Model

Variables Entered

Variables

Removed Method

1 LogNormalF

unctional(a) . Enter

a All requested variables entered.

b Dependent Variable: LogFunctieROS

Model Summary(b)

Model R R Square

Adjusted R Square

Std. Error of the Estimate

1 ,200(a) ,040 ,018 ,90001

a Predictors: (Constant), LogNormalFunctional b Dependent Variable: LogFunctieROS

ANOVA(b)

Model

Sum of

Squares df Mean Square F Sig.

Regressio

n 1,455 1 1,455 1,797 ,187(a)

Residual 34,831 43 ,810

1

Total 36,286 44

a Predictors: (Constant), LogNormalFunctional b Dependent Variable: LogFunctieROS

Coefficients(a) Unstandardized

Coefficients

Standardized Coefficients

Model B Std. Error Beta t Sig.

(Constant) 11,056 ,208 53,162 ,000

1

LogNormalFun

ctional ,827 ,617 ,200 1,340 ,187

a Dependent Variable: LogFunctieROS

Residuals Statistics(a)

Minimum Maximum Mean Std. Deviation N

Predicted Value 10,3509 11,0366 10,8431 ,18187 45

Residual -1,82345 1,80186 ,00000 ,88972 45

(21)

Std. Predicted Value -2,707 1,064 ,000 1,000 45

Std. Residual -2,026 2,002 ,000 ,989 45

a Dependent Variable: LogFunctieROS

Regression

Variables Entered/Removed ^b

Mod Auden Funct, Zscore(Lo gFucntie Auden), Zscore(Lo gNormal

Functional) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

All requested variables entered.

a.

Dependent Variable: LogFunctieROS

b.

Model Summary

,201 ^a ,041 -,030 ,92147

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAudenFunct,

Zscore(LogFucntieAuden ),

Zscore(LogNormalFunctional )

a.

ANOVA ^b

1,473 3 ,491 ,578 ,633 ^a

34,814 41 ,849

36,286 44

Regression Residual Total Model

1

Sum of

Predictors: (Constant ), ModAudenFunct, Zscore

(LogFucntieAuden ),

a.

b.

Coefficients ^a

10,843 ,138 78,766 ,000

,183 ,144 ,201 1,269 ,212

-,019 ,142 -,022 -,137 ,892

-,001 ,174 -,001 -,005 ,996

(Constant )

Zscore(LogNormal Functional) Zscore(LogFucntieAuden )

ModAudenFunct Model 1

B Std. Error

Unstandardized Coefficients

Beta Standardized

Coefficients

t Sig.

(22)

Regression

Mod Adjusted Funct, Zscore(Lo gFunctie Adjusted), Zscore(Lo gNormal

Functional) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

b.

Model Summary

,219 ^a ,048 -,022 ,91801

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAdjustedFunct,

Zscore(LogFunctieAdjusted ),

a.

ANOVA ^b

1,734 3 ,578 ,686 ,566 ^a

34,553 41 ,843

36,286 44

1

Sum of

Predictors: (Constant ), ModAdjustedFunct, Zscore

(LogFunctieAdjusted ),

a.

b.

Coefficients ^a

10,842 ,137 79,196 ,000

,187 ,139 ,206 1,346 ,186

-,061 ,137 -,068 -,445 ,659

,050 ,141 ,054 ,354 ,725

(Constant )

Zscore(LogNormal Functional) Zscore(LogFunctie Adjusted) ModAdjustedFunct

Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

(23)

Hypothesis 2 Educational background

Model

Variables Entered

Variables

Removed Method

1 LogNormal

Education(a )

. Enter

b Dependent Variable: LogROSeduback

Model R R Square

Adjusted R Square

1 ,176(a) ,031 ,009 ,90002

a Predictors: (Constant), LogNormalEducation b Dependent Variable: LogROSeduback

ANOVA(b)

Model

Sum of

Regressio

n 1,163 1 1,163 1,435 ,237(a)

Residual 36,451 45 ,810

1

Total 37,614 46

a Predictors: (Constant), LogNormalEducation b Dependent Variable: LogROSeduback

Coefficients

(Constant) 10,612 ,225 47,142 ,000

1

LogNormalEdu

cation -,659 ,550 -,176 -1,198 ,237

a Dependent Variable: LogROSeduback

Predicted Value 10,6585 11,5285 10,8306 ,15899 47

Residual -1,82955 1,76531 ,00000 ,89018 47

Std. Residual -2,033 1,961 ,000 ,989 47

a Dependent Variable: LogROSeduback

(24)

Regression

Mod Auden EduBack, Zscore(Lo gNormal Educatio n), Zscore(Lo g Audenedu

back) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

Dependent Variable: LogROSeduback

b.

Model Summary

,192 ^a ,037 -,030 ,91783

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAudenEduBack,

Zscore(LogNormalEducation ),

Zscore(LogAudeneduback )

a.

ANOVA ^b

1,390 3 ,463 ,550 ,651 ^a

36,224 43 ,842

37,614 46

1

Sum of

Predictors: (Constant ), ModAudenEduBack, Zscore

(LogNormalEducation ),

Zscore(LogAudeneduback )

a.

b.

Coefficients ^a

10,834 ,134 80,803 ,000

-,166 ,136 -,184 -1,221 ,229

-,025 ,141 -,027 -,175 ,862

,100 ,192 ,081 ,519 ,606

(Constant )

Zscore(LogNormal Education) Zscore(Log Audeneduback) ModAudenEduBack Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

Regression

(25)

Mod Adjusted EduBack, Zscore(Lo gNormal Educatio n), Zscore(Lo g Adjustede

duback) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

b.

Model Summary

,202 ^a ,041 -,026 ,91606

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAdjustedEduBack,

Zscore(LogNormalEducation ),

Zscore(LogAdjustededuback )

a.

ANOVA ^b

1,530 3 ,510 ,608 ,614 ^a

36,084 43 ,839

37,614 46

1

Sum of

Predictors: (Constant ), ModAdjustedEduBack, Zscore

(LogNormalEducation ),

Zscore(LogAdjustededuback )

a.

b.

Coefficients ^a

10,824 ,134 80,760 ,000

-,145 ,138 -,160 -1,053 ,298

,001 ,145 ,001 ,007 ,994

-,151 ,244 -,100 -,618 ,540

(Constant )

Zscore(LogNormal Education) Zscore(Log Adjustededuback)

ModAdjustedEduBack Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

(26)

Educational level

Model

Variables Entered

Variables

Removed Method

1 LogNormal

EduLevel(a) . Enter

b Dependent Variable: LogROSEdulevel

Model R R Square

Adjusted R Square

1 ,019(a) ,000 -,021 ,89928

a Predictors: (Constant), LogNormalEduLevel b Dependent Variable: LogROSEdulevel

ANOVA(b)

Model

Sum of

Regressio

n ,014 1 ,014 ,017 ,898(a)

Residual 38,009 47 ,809

1

Total 38,023 48

a Predictors: (Constant), LogNormalEduLevel b Dependent Variable: LogROSEdulevel

Coefficients

(Constant) 10,780 ,274 39,326 ,000

1

LogNormalEdu

Level -,082 ,630 -,019 -,130 ,898

a Dependent Variable: LogROSEdulevel

Predicted Value 10,7836 10,8572 10,8115 ,01681 49

Residual -1,93291 1,70992 ,00000 ,88986 49

Std. Residual -2,149 1,901 ,000 ,990 49

a Dependent Variable: LogROSEdulevel

(27)

ModEdu Level Auden, Zscore(Lo gAuden Edulevel), Zscore(Lo gNormal

EduLevel) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

Dependent Variable: LogROSEdulevel

b.

Model Summary

,053 ^a ,003 -,064 ,91792

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModEduLevelAuden,

Zscore(LogAudenEdulevel ),

Zscore(LogNormalEduLevel )

a.

ANOVA ^b

,107 3 ,036 ,042 ,988 ^a

37,916 45 ,843

38,023 48

1

Sum of

Predictors: (Constant ), ModEduLevelAuden, Zscore

(LogAudenEdulevel ),

a.

b.

Coefficients ^a

10,810 ,131 82,403 ,000

-,033 ,141 -,037 -,232 ,818

,009 ,131 ,010 ,066 ,948

,057 ,175 ,051 ,325 ,747

(Constant )

Zscore(LogNormalEdu Level) Zscore(LogAuden Edulevel) ModEduLevelAuden

Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

Regression

(28)

Mod Adjusted Edulevel, Zscore(Lo g Adjusted Edulevel), Zscore(Lo gNormal

EduLevel) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

b.

Model Summary

,058 ^a ,003 -,063 ,91768

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAdjustedEdulevel,

Zscore(LogAdjustedEdulevel ),

a.

ANOVA ^b

,127 3 ,042 ,050 ,985 ^a

37,896 45 ,842

38,023 48

1

Sum of

Predictors: (Constant ), ModAdjustedEdulevel, Zscore

(LogAdjustedEdulevel ),

a.

b.

Coefficients ^a

10,811 ,131 82,466 ,000

-,008 ,136 -,009 -,058 ,954

-,022 ,132 -,025 -,165 ,870

-,051 ,164 -,047 -,308 ,759

(Constant )

Zscore(LogNormalEdu Level) Zscore(LogAdjusted Edulevel) ModAdjustedEdulevel

Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

(29)

Hypothesis 3 Team Tenure

Model

Variables Entered

Variables

Removed Method 1

LogNormalT eamTenure(

a)

. Enter

b Dependent Variable: LogROSTenure

Model R R Square

Adjusted R Square

1 ,283(a) ,080 ,060 ,81465

a Predictors: (Constant), LogNormalTeamTenure b Dependent Variable: LogROSTenure

ANOVA(b)

Model

Sum of

Regressio

n 2,666 1 2,666 4,017 ,051(a)

Residual 30,528 46 ,664

1

Total 33,194 47

a Predictors: (Constant), LogNormalTeamTenure b Dependent Variable: LogROSTenure

Coefficients

(Constant) 11,179 ,223 50,097 ,000

1

LogNormalTeam

Tenure ,688 ,343 ,283 2,004 ,051

a Dependent Variable: LogROSTenure

Predicted Value 9,9874 11,1259 10,7993 ,23815 48

Residual -1,69935 1,56342 ,00000 ,80594 48

Std. Residual -2,086 1,919 ,000 ,989 48

a Dependent Variable: LogROSTenure

Regression

(30)

Mod Auden Tenure, Zscore(Lo gNormal Team Tenure), Zscore(Lo gAuden

Tenure) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

Dependent Variable: LogROSTenure

b.

Model Summary

,331 ^a ,110 ,049 ,81962

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAudenTenure,

Zscore(LogNormalTeamTenure ),

Zscore(LogAudenTenure )

a.

ANOVA ^b

3,636 3 1,212 1,804 ,160 ^a

29,558 44 ,672

33,194 47

1

Sum of

Predictors: (Constant ), ModAudenTenure, Zscore

(LogNormalTeamTenure ),

Zscore(LogAudenTenure )

a.

b.

Coefficients ^a

10,794 ,118 91,152 ,000

,283 ,126 ,336 2,242 ,030

,113 ,127 ,135 ,888 ,379

-,177 ,166 -,169 -1,066 ,292

(Constant )

Zscore(LogNormalTeam Tenure) Zscore(LogAudenTenure )

ModAudenTenure Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

Regression

(31)

Mod Adjusted Tenure, Zscore(Lo g Adjusted Tenure), Zscore(Lo gNormal Team

Tenure) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

b.

Model Summary

,319 ^a ,102 ,041 ,82314

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAdjustedTenure,

Zscore(LogAdjustedTenure ),

Zscore(LogNormalTeamTenure )

a.

ANOVA ^b

3,382 3 1,127 1,664 ,189 ^a

29,812 44 ,678

33,194 47

1

Sum of

Predictors: (Constant ), ModAdjustedTenure, Zscore

(LogAdjustedTenure ),

Zscore(LogNormalTeamTenure )

a.

b.

Coefficients ^a

10,791 ,119 90,587 ,000

,295 ,132 ,351 2,231 ,031

,053 ,125 ,063 ,421 ,676

-,181 ,177 -,164 -1,018 ,314

(Constant )

Zscore(LogNormalTeam Tenure) Zscore(LogAdjusted Tenure) ModAdjustedTenure

Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

(32)

Hypothesis 4 AGE

Model

Variables Entered

Variables

Removed Method

1 LogNormal

Age(a) . Enter

b Dependent Variable: LogROSAge

Model R R Square

Adjusted R Square

1 ,025(a) ,001 -,026 ,81169

a Predictors: (Constant), LogNormalAge b Dependent Variable: LogROSAge

ANOVA(b)

Model

Sum of

Regressio

n ,016 1 ,016 ,024 ,878(a)

Residual 24,377 37 ,659

1

Total 24,393 38

a Predictors: (Constant), LogNormalAge b Dependent Variable: LogROSAge

Coefficients

(Constant) 10,761 ,278 38,660 ,000

1

LogNormal

Age -,111 ,713 -,025 -,155 ,878

a Dependent Variable: LogROSAge

Predicted Value 10,7682 10,8488 10,7992 ,02040 39

Residual -1,92583 1,67863 ,00000 ,80094 39

Std. Residual -2,373 2,068 ,000 ,987 39

a Dependent Variable: LogROSAge

(33)

Mod AudenAge, Zscore(Lo gNormal Age), Zscore(Lo gAuden

Age) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

Dependent Variable: LogROSAge

b.

Model Summary

,266 ^a ,071 -,009 ,80481

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAudenAge,

Zscore(LogNormalAge ), Zscore

(LogAudenAge )

a.

ANOVA ^b

1,723 3 ,574 ,886 ,458 ^a

22,670 35 ,648

24,393 38

1

Sum of

Predictors: (Constant ), ModAudenAge, Zscore

(LogNormalAge ),

Zscore(LogAudenAge )

a.

b.

Coefficients ^a

10,704 ,142 75,259 ,000

,012 ,145 ,016 ,085 ,932

,041 ,153 ,052 ,271 ,788

-,253 ,159 -,280 -1,585 ,122

(Constant )

Zscore(LogNormalAge )

Zscore(LogAudenAge )

ModAudenAge Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

Regression

(34)

Mod Adjusted Age, Zscore(Lo gNormal Age), Zscore(Lo g Adjusted

Age) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

b.

Model Summary

,298 ^a ,089 ,011 ,79694

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAdjustedAge,

Zscore(LogNormalAge ), Zscore

(LogAdjustedAge )

a.

ANOVA ^b

2,164 3 ,721 1,136 ,348 ^a

22,229 35 ,635

24,393 38

1

Sum of

Predictors: (Constant ), ModAdjustedAge, Zscore

(LogNormalAge ),

Zscore(LogAdjustedAge )

a.

b.

Coefficients ^a

10,709 ,138 77,776 ,000

,001 ,139 ,001 ,006 ,995

-,008 ,142 -,011 -,059 ,953

-,287 ,164 -,295 -1,746 ,090

(Constant )

Zscore(LogNormalAge )

Zscore(LogAdjustedAge )

ModAdjustedAge Model 1

B Std. Error Unstandardized

Coefficients

Beta Standardized

Coefficients

t Sig.

a.

(35)

Hypothesis 5 Nationality

Model

Variables Entered

Variables

Removed Method

1 LogNormal

National(a) . Enter

b Dependent Variable: LogROSnational

Model R R Square

Adjusted R Square

1 ,083(a) ,007 -,015 ,90176

a Predictors: (Constant), LogNormalNational b Dependent Variable: LogROSnational

ANOVA(b)

Model

Sum of

Regressio

n ,255 1 ,255 ,313 ,579(a)

Residual 36,593 45 ,813

1

Total 36,847 46

a Predictors: (Constant), LogNormalNational b Dependent Variable: LogROSnational

Coefficients

(Constant) 10,838 ,230 47,025 ,000

1

LogNormalNat

ional ,141 ,252 ,083 ,560 ,579

a Dependent Variable: LogROSnational

Predicted Value 10,4817 10,8379 10,7320 ,07440 47

Residual -1,71921 2,02734 ,00000 ,89190 47

Std. Residual -1,907 2,248 ,000 ,989 47

a Dependent Variable: LogROSnational

(36)

Mod Auden National, Zscore(Lo g Audennati

onal), Zscore(Lo gNormal

National) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

Dependent Variable: LogROSnational

b.

Model Summary

,192 ^a ,037 -,031 ,90856

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAudenNational,

Zscore(LogAudennational ),

Zscore(LogNormalNational )

a.

ANOVA ^b

1,351 3 ,450 ,546 ,654 ^a

35,496 43 ,825

36,847 46

1

Sum of

Predictors: (Constant ), ModAudenNational, Zscore

(LogAudennational ),

a.

b.

Coefficients ^a

10,718 ,133 80,512 ,000

,129 ,142 ,144 ,909 ,368

,058 ,137 ,064 ,421 ,676

-,155 ,137 -,181 -1,131 ,264

(Constant )

Zscore(LogNormal National) Zscore(Log Audennational) ModAudenNational Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

Regression

(37)

Mod Adjusted National, Zscore(Lo g Adjustedn

ational), Zscore(Lo gNormal

National) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

b.

Model Summary

,148 ^a ,022 -,046 ,91557

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAdjustedNational,

Zscore(LogAdjustednational ),

a.

ANOVA ^b

,802 3 ,267 ,319 ,812 ^a

36,046 43 ,838

36,847 46

1

Sum of

Predictors: (Constant ), ModAdjustedNational, Zscore

(LogAdjustednational ),

a.

b.

Coefficients ^a

10,720 ,134 79,740 ,000

,127 ,150 ,142 ,845 ,403

,038 ,143 ,042 ,266 ,792

-,133 ,165 -,139 -,808 ,424

(Constant )

Zscore(LogNormal National) Zscore(Log Adjustednational)

ModAdjustedNational Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

(38)

Hypothesis Gender

Model

Variables Entered

Variables

Removed Method 1

LogNormal

Gender(a) . Enter

b Dependent Variable: LogROSgender

Model R R Square

Adjusted R Square

1 ,009(a) ,000 -,055 1,11528

a Predictors: (Constant), LogNormalGender b Dependent Variable: LogROSgender

ANOVA(b)

Model

Sum of

Regressio

n ,002 1 ,002 ,001 ,971(a)

Residual 22,389 18 1,244

1

Total 22,391 19

a Predictors: (Constant), LogNormalGender b Dependent Variable: LogROSgender

Coefficients

(Constant) 10,756 ,534 20,155 ,000

1

LogNormalGe

nder ,020 ,551 ,009 ,037 ,971

a Dependent Variable: LogROSgender

Predicted Value 10,7253 10,7561 10,7386 ,00950 20

Residual -1,87312 1,76560 ,00000 1,08554 20

Std. Residual -1,679 1,583 ,000 ,973 20

a Dependent Variable: LogROSgender

(39)

Mod Auden Gender, Zscore(Lo gNormal Gender), Zscore(Lo g Audengen

der) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

Dependent Variable: LogROSgender

b.

Model Summary

,100 ^a ,010 -,176 1,17710

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAudenGender,

Zscore(LogNormalGender ), Zscore

(LogAudengender )

a.

ANOVA ^b

,222 3 ,074 ,053 ,983 ^a

22,169 16 1,386

22,391 19

1

Sum of

Predictors: (Constant ), ModAudenGender, Zscore

(LogNormalGender ),

Zscore(LogAudengender )

a.

b.

Coefficients ^a

10,728 ,266 40,354 ,000

,030 ,275 ,028 ,110 ,914

-,113 ,300 -,104 -,375 ,713

,073 ,261 ,077 ,281 ,783

(Constant )

Zscore(LogNormal Gender) Zscore(LogAudengender )

ModAudenGender Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

Regression

(40)

Mod Adjusted Gender, Zscore(Lo gNormal Gender), Zscore(Lo g Adjustedg

ender) ^a

. Enter Model

1 Variables

Entered

Variables

Removed Method

a.

b.

Model Summary

,188 ^a ,035 -,145 1,16182

Model 1

R R Square

Adjusted R Square

Predictors: (Constant ), ModAdjustedGender,

Zscore(LogNormalGender ),

Zscore(LogAdjustedgender )

a.

ANOVA ^b

,794 3 ,265 ,196 ,898 ^a

21,597 16 1,350

22,391 19

1

Sum of

Predictors: (Constant ), ModAdjustedGender, Zscore

(LogNormalGender ),

Zscore(LogAdjustedgender )

a.

b.

Coefficients ^a

10,753 ,282 38,172 ,000

,107 ,295 ,098 ,361 ,723

-,219 ,297 -,202 -,739 ,471

-,035 ,267 -,032 -,130 ,898

(Constant )

Zscore(LogNormal Gender) Zscore(Log Adjustedgender)

ModAdjustedGender Model 1

B Std. Error

Beta Standardized

Coefficients

t Sig.

a.

‘The moderating effect of the International Risk Management

APPENDIX