ASSESSMENT OF THE RELATIVE VALUE OF KNOWLEDGE TRANSFER PROCESSES TO THE SUCCESS OF

INTERNATIONAL PROJECTS

by

Arthur Simon Pantelides

B.S. in Aerospace Engineering, May 1989, Boston University

M.S. in Mechanical Engineering, May 1991, Boston University

M.E.M. Engineering Management, August 2002, The George Washington University

A Dissertation submitted to

the Faculty of The School of Engineering and Applied Science

of The George Washington University in partial satisfaction of the requirements

for the degree of Doctor of Philosophy

May 17, 2009

Dissertation directed by

Shahram Sarkani Professor of Engineering Management and Systems Engineering

Thomas Andrew Mazzuchi

Professor of Operations Research and Engineering Management

The School of Engineering and Applied Science of the George Washington University

certifies that Arthur Simon Pantelides has passed the Final Examination for the degree

of Doctor of Science as of March 6th 2009. This is the final approved form of the

dissertation.

ASSESSMENT OF THE RELATIVE VALUE OF KNOWLEDGE TRANSFER PROCESSES TO THE SUCCESS OF INTERNATIONAL PROJECTS

Arthur Simon Pantelides

Dissertation Research Committee :

Shahram Sarkani, Professor of Engineering Management and Systems Engineering, Dissertation Co-Director Thomas Andrew Mazzuchi, Professor of Operations Research and Engineering Management, Dissertation Co-Director E. Lile Murphree, Professor of Engineering Management and Systems Engineering, Committee Chair Frank Allario, Professor of Engineering Management and Systems Engineering, Committee Member Gerhard Antony, President, Neugart USA LP, Committee Member

ii

© Copyright by Arthur Simon Pantelides, 2009 All Rights Reserved

iii

Dedicated to My Parents

Thank You for Everything That You Have Done for Me.

And

Dedicated to the Next Generation : Max, Alex, and Mila

May You Do Great Things !

iv

Acknowledgements

Above all, I would like to thank my family who always encouraged me to pursue my

studies to completion.

I would especially like to thank Miss Effi Vakalou who helped me significantly with this

final report, with her diligent reading, re-reading, and great editing skills, as well as for

her translations with German text; and her overall support.

Thank you to my colleagues at Sumitomo Drive Technologies and Sumitomo Heavy

Industries who provided much feedback, suggestions, reviews, and clarifications.

With a special thanks to Mr. and Mrs. Jun Asai for assisting with the Japanese language

and translations.

I am grateful to Dr. Shahram Sarkani, Dr. Thomas Mazzuchi, and Dr. Frank Allario for

their continued support and guidance; and for maintaining a top-notch academic

program which I am proud to have completed.

Finally, I would like to thank my mentor Dr. Gerhard Antony, a great engineer,

businessman, and wonderful person, who has provided hours and hours of great

conversation not only on the subject matter but in life in general for close to 15 years

I have had the privilege to know him.

v

Abstract

ASSESSMENT OF THE RELATIVE VALUE OF KNOWLEDGE TRANSFER

PROCESSES TO THE SUCCESS OF INTERNATIONAL PROJECTS

As the activities of companies become global in nature there is an emerging need to

understand the processes that lead to the success of large projects in which the core

competency is centered in a parent company, an engineering development center that is

located in a subsidiary company in another country, and special application customers

that are distributed across the globe. This situation requires an ever-increasing role for

professional project managers in subsidiary companies to cross international boundaries

in order to connect the parent company with the ultimate user who has a specific

application.

The modern Project Manager must consider many facets of their responsibilities

including : (1) managing corporate knowledge as a strategic asset; (2) transferring

corporate knowledge to the project team and transferring engineering capabilities back

to corporate; and, (3) developing customer requirements that ensure project success. In

order to meet these responsibilities, the project manager needs to understand the

diversity of technical communication from parent to subsidiary, the cultural vagaries of

these communications, in addition to maintaining an eye on the knowledge transfer

process. The challenges for an organization is to manage its knowledge assets and

handle knowledge transfer between headquarters and its subsidiaries in an optimum

manner so that international projects succeed in meeting their objectives.

vi

The project manager is a key player in the process. Statistics show however that most

international projects either fail or do not achieve their ultimate business goals and it’s

not clear at this point what are the primary causes.

This study will investigate, identify, and analyze the factors and attributes associated

with successes of international projects examining cultural and knowledge transfer

processes of foreign-owned heavy machinery companies with U.S. subsidiaries.

The study will consider a very important tool in managing such projects – technical

communications. It plans to improve understanding of how communication structures

and mechanisms of companies are integrating factors between culture and the

knowledge transfer chain, and how, in turn, they impact project success. Based on the

findings, the study will propose a conceptual framework from which key cultural

attributes and knowledge transfer processes within certain communication mechanisms,

can be modeled for potentially identifying project success.

vii

Table of Contents

DEDICATION…………………………………………………………………………….. iv

ACKNOWLEDGEMENTS………………………………………………………………. v

ABSTRACT………………………………………………………………………………. vi

TABLE OF CONTENTS………………………………………………………………… viii

LIST OF FIGURES……………………………………………………………………… xi

LIST OF TABLES………………………………………………………………………. xiii

CHAPTER 1 : INTRODUCTION……………………………………………………….. 1

1.1 Problem Statement…………………………………………………………. 4

1.2 Research Background……………………………………………………… 5

1.3 Research Objectives and Value to the Discipline………………………. 6

1.4 Thesis Organization………………………………………………………… 12

CHAPTER 2 : LITERATURE REVIEW……………………………………………….. 14

2.1 Knowledge Management and Transfer…………………………………… 14

2.2 Culture……………………………………………………………………….. 28

2.2.1 National Culture…………………………………………………. 29

2.2.2 Corporate / Organizational Culture……………………………. 39

2.3 Communication : Methodologies, Mechanisms, and Tools……………. 46

2.3.1 Theoretical Basis………………………………………………… 47

2.3.2 Groups and Teams……………………………………………… 58

2.3.3 International / Intercultural Communications…………………. 64

2.3.4 Communications by Engineers………………………………… 66

2.4 Project Management……………………………………………………….. 69

2.4.1 Communicating Effective Project Management……………… 70

viii

2.4.2 The Successful Project………………………………………… 72

2.5 Literature Review Summary & Research Potential……………………… 76

CHAPTER 3 : RESEARCH DESIGN and METHODOLOGY………………………. 82

3.1 Research Objectives - Hypotheses Mapping……………………………. 82

3.2 Method……………………………………………………………………….. 92

3.3 Population…………………………………………………………………… 93

3.4 Instrument / Cross-Cultural Survey Research Design………………….. 98

3.4.1 Basic Principles and Best Practices…………………………… 99

3.4.2 Pilot Study Program…………………………………………….. 102

3.4.3 Cross-Cultural Survey Limitations & Difficulties……………… 105

3.4.4 Final Question Development and Mapping……………………110

3.5 Validation & Reliability……………………………………………………… 117

3.6 Analysis Approach………………………………………………………….. 119

CHAPTER 4 : RESULTS and DATA ANALYSIS…………………………………… 121

4.1 Survey Results……………………………………………………………… 121

4.1.1 Basic Information / Demographics……………………………. 124

4.1.2 Headquarters & Subsidiary Communication…………………. 127

4.1.3 Headquarters & Subsidiary KT and Corporate Culture…….. 132

4.1.4 What is Project Success……………………………………….. 138

4.1.5 Project Success at Your Company…………………………… 142

4.2 Data Analysis / Hypotheses Testing …………………………………….. 145

4.2.1 Targeted Correlational Analysis………………………………. 148

4.2.2 Statistical Significance & Measures of Association…………. 169

4.2.2.1 Chi-square test (χ2) and Cramer’s V…………….. 169

ix

4.2.2.2 ANOVA Confirmation by Survey Question……… 182

4.2.3 Analysis Summary……………………………………………. 182

CHAPTER 5 : CONCLUSION…………………………………………………. ……… 186

5.1 Discussion and Implications………………………………………. ……… 186

5.2 Theoretical Construct and Future Research……………………………. 198

REFERENCES…………………………………………………………………………… 201

APPENDICES……………………………………………………………………………. 209

APPENDIX A : Hofstede Summary & Relational Mapping……………………. 210

APPENDIX B : Survey Instrument………………………………………………. 212

APPENDIX C : Survey Raw & Supplemental Data……………………………. 229

APPENDIX D : Illustrative Example Case……………………………………… 250

APPENDIX E : Sample Multilingual Documentation from the Industry……… 251

APPENDIX F : Photographs from the Industry………..............……………… 252

APPENDIX G : Comprehensive List of Gross Population…………………… 253

x

List of Figures

Figure 1-1 – Basic Concept of Research…………………………………………….. 3

Figure 1-2 – Conceptual Framework…………………………………………………. 9

Figure 2-1 – Three Models of Communication………………………………………. 50

Figure 2-2 – Integrating Research Components…………………………………….. 77

Figure 2-3 – Identifying the Research Focus Within the Framework……………… 79

Figure 2-4 – Higher-Tier Knowledge Transfer Models for Parent-Subsidiary…….. 80

Figure 3-1 – Higher-Level Research Objective………………………………………. 84

Figure 3-2 – Sub-Hypotheses Cluster-Mapping and Inter-Relationship…………… 90

Figure 3-3 – Hypotheses Development and Mapping to Objectives……………….. 91

Figure 3-4 – AGMA Website ScreenPrint…………………………………………….. 96

Figure 3-5 – Likert Scale Used in Survey Instrument…………………………………100

Figure 3-6 – Pilot Program Protocol Considerations…………………………………. 104

Figure 3-7 – Survey Instrument Front-Cover Instructions Page……………………. 109

Figure 3-8 – Overall Survey Question Mapping……………………………………… 116

Figure 4-1 – Surveys Return Results…………………………………………………. 121

Figure 4-2 – Survey Language Results………………………………………………. 122

Figure 4-3 – Geographic Location of Respondent Company Results…………….. 122

Figure 4-4 – Response Rates by Region……………………………………………… 123

Figure 4-5 – Number of Returned Surveys by Week………………………………… 123

Figure 4-6 – Job Classification by Target Country…………………………………… 124

Figure 4-7 – Company Size, Age, Expat Situation Profile Results…………………. 126

Figure 4-8a,b – Survey Question 45 : Project Results Charts………………………. 143

xi

Figure 4-9a,b – Survey Question 46 : Project Results Charts……………………… 143

Figure 4-10a,b – Survey Question 47 : Project Results Charts……………………. 143

Figure 4-11a,b – Survey Question 48 : Project Results Charts…………………….. 143

Figure 4-12a,b – Survey Question 49 : Project Results Charts…………………….. 144

Figure 4-13a,b – Survey Question 50 : Project Results Charts…………………….. 144

xii

List of Tables

Table 2-1 – Four Modes of Knowledge Conversion…………………………………. 17

Table 2-2 – Comparison of Management Models Regarding Knowledge Creation……………………………………………………… 19 Table 2-3 – Frictions and Potential Solutions to Knowledge Transfer…………….. 24

Table 2-4a – Mapping Communication Traditions and Theories…………………… 54

Table 2-4b – Mapping Communication Traditions and Theories : Ref. 1…………. 55 Table 2-4c – Mapping Communication Traditions and Theories : Ref. 2………… 56 Table 2-4d – Mapping Communication Traditions and Theories : Final Refinement………………………………………………………… 57 Table 2-5a – Mapping of Positive and Negative Group Role Behavior Characteristics of Teams……………………………………………….. 61

Table 2-5b – Mapping of Positive and Negative Group Role Behavior Characteristics of Teams : Relationship to 3 Constructs……………. 62

Table 2-5c – Mapping of Positive and Negative Group Role Behavior Characteristics of Teams : Characteristic Grouping…………………. 63

Table 3-1 – Overall Population Potential Target Pool……………………………….. 95

Table 3-2 – Final Distribution Population Companies / Organizations…………….. 97

Table 3-3 – Questionnaire Rationalization Summary………………………………… 113

Table 3-4 – Data Collection Timeline………………………………………………….. 118

Table 4-1 – One-on-One Communication Structure Survey Data…………………. 127

Table 4-2 – One-to-Many Communication Structure Survey Data…………………. 128

Table 4-3 – Man-to-One Communication Structure Survey Data………………….. 129

Table 4-4 – Many-to-Many Communication Structure Survey Data……………….. 130

Table 4-5 – Written / Documented Communications Survey Data………………… 130

Table 4-6 – Verbal, Face-to-Face Communications Survey Data…………………. 131

xiii

Table 4-7 – Trust Survey Data…………………………………………………………. 132

Table 4-8 – Hold-Back of Information Either by Headquarters or Subsidiary Data 1…………………………………………………………. 133 Table 4-9 – Hold-Back of Information Either by Headquarters or Subsidiary Data 2………………………………………………………… 134 Table 4-10 – Technical Project Specs & Customer Knowledge Survey Data……. 135

Table 4-11 – Technology Tools Survey Data………………………………………… 135

Table 4-12 – Cooperation & Collaboration / Culture Survey Data…………………. 136

Table 4-13 – Structure of Decision-Making and Processes Survey Data…………. 136

Table 4-14 – Employee Input Into Decision-Making Survey Data…………………. 137

Table 4-15 – Shared-Meaning Between Headquarters and Subsidiary Survey Data……………………………………………………………… 138 Table 4-16 – Project Success : Time, Budget, Performance Survey Data……….. 138

Table 4-17 – Post-Project Reviews Survey Data……………………………………. 139

Table 4-18 – Employee Morale, Satisfaction, and Project Success Survey Data… 139

Table 4-19 – Customer Satisfaction and Repeat Business, and Project Success.. 140

Table 4-20 – Financial, Commercial Gains, Market Share, and Project Success… 140

Table 4-21 – Risk Management and Project Success Survey Data………………. 141

Table 4-22 – Projects and Opportunity for Knowledge Creation…………………… 141

Table 4-23 – Project Success and Successful Knowledge Transfer………………. 142

Table 4-24 – Descriptive Statistics Analysis Summary of Survey Questions……… 147

Table 4-25 – Chi-square and Cramer’s V Significance and Association Values….. 181 and Interpretations

Table 4-26 – Analysis Results Summary and Hypotheses Disposition…………… 183

Table 5-1 – Variable Utilization Matrix…………………………………………………. 187

xiv

CHAPTER 1 – INTRODUCTION

One can argue that there is no such thing as a true “local” project anymore. This is

especially true with larger-scale power-transmission machinery projects for a growing list

of industrial applications.

A waste-water treatment facility in Argentina for example, may utilize three-dozen

thousand- horsepower machines purchased from a Japanese heavy industry

conglomerate. The project is managed by the company’s overseas technical center in

the United States. This operation may include engineers from Asia, Europe, as well as

the United States. Machinery parts are sourced from Japan, China, Brazil, and Italy; with

engineering expertise from these same countries as well as Germany and Sweden. In

this example, it is critical to manage clear specifications and technical knowledge

transfer between the Argentinean customer, the global parts suppliers, and the

Japanese original equipment manufacturer of the main units. Clearly the managing

project team at the subsidiary operation in the U.S. of the Japanese company has its

work cut out for it. Unfortunately the project failed. In this case a key technical

specification was not communicated and all the units had to be retrofitted after

installation resulting in a 40% cost overrun.

A German company is building the new international airport in Athens, Greece. The

Project Manager is from England with most of his experience actually in the Netherlands.

His core team is made up of local Greek engineers. The miles of conveyor systems for

the airport’s baggage handling system require over a thousand power transmission units

sourced from Italy. The team manages to successfully complete the design and

implementation of the system early, under budget, and with improved performance of the

1

system. On the other hand, the sky-ramps which lead from the terminal to the planes,

are powered by German units, with Japanese variable frequency controller drives. The

project is marginally successful according to the Czech company who managed it since

no one foresaw a key factor in the local operating conditions due to the areas very hot

weather in the summer months.

These three different but similar examples demonstrate that projects are increasingly

becoming more international in nature; thus more complex from a management

perspective. One can argue that globalization and industry began with Columbus in 1492

eventually evolving from Europe to the Americas, then continuing its evolution across the

Pacific into Asia, from Japan and Korea, to Taiwan, into China and SouthEast Asia and

into India. Who knows what will be the next evolutionary jump in this global circum-

transformation, Russia, the Middle East, Africa ? What we know, as Thomas Friedman

writes, “…the world is flat” [42] and its created opportunities for international project

management that did not previously exist. But along with these opportunities there are

also challenges.

This research study proposes to investigate and assess the value of knowledge transfer

processes to the success of international projects. It will seek out and identify key

attributes linking knowledge transfer with project success once “success” is defined

within the current research context. The research will utilize power-transmission

industrial machinery manufacturers within its case study and scope due to 3 key

reasons :

1. Internationally there are only 4 or 5 truly global manufacturers of this type of

large-scale industrial equipment with subsidiaries in the United States;

enabling us to obtain representative data that is strongly representative of the

industry

2

2. These manufacturers have a fairly diverse cultural base; essentially these

companies are either Japanese, Italian, German, or Swiss. This provides for

a good cultural sampling for our research; meaning that the cultural aspects

of communication, technology transfer and project management can be fairly

well-represented.

3. This type of machinery is fundamental in virtually all industries utilizing power

and motion transmission thus it can be considered an important core

technology.

Figure 1-1 : Basic Concept of the Research ( Photos used with permission from Sumitomo Drive Technologies; the authors place of business )

Overseas Parent’s

Headquarters

U.S. Subsidiary Gearbox & Motor

Manufacturer

U.S. or Foreign Customer and

System Integrator

Final Job Sitein U.S. or

other Country

Technical Knowledge Transfer & Mana

Project S

Final Site Performance Regement pecifications quirements

Impact on Cust. Job Site Project Startup Success

Managing U.S. Operation- Customer R l ti hi

Managing the Parent-Subsidiary R l ti hi

3

1.1 Problem Statement

The majority of foreign (and in most cases American) heavy machinery companies

manufacturing in the United States are not optimizing their knowledge transfer functions

and it is hypothesized that this directly effects the success of their large industrial

projects.

To improve probability of project success in large projects requiring technical information

flow between a company’s foreign headquarters outside the U.S. and its local U.S.-

based operations, the company’s knowledge transfer processes need to be optimized

within a set of attributes. Suboptimal processes result in :

poor delivery performance – resulting in late project startup by the customer;

thus schedule / time - a typical metric of project success, is not being met

project cost overruns – resulting in decreased margins for the manufacturer;

another project success metric (cost) not being met

suboptimum performance requirement fulfillment resulting in increased after-

market involvement by both sides (manufacturer and customer, and in some

cases the customers’ customer or end-user); another project success metric

widely used (performance), not being met

customer dissatisfaction resulting in non-recurring business for the machinery

manufacturer

poor morale in the non-technical employees of the gear manufacturer ( in

departments and areas such as : purchasing, production control, logistics,

customer service, management / executive)

4

high turnover in technical employees of the gear manufacturer ( in departments

and areas such as : engineering, design, production ); including Project Managers

dissatisfaction of the gear manufacturers’ headquarters personnel outside the U.S.

resulting in further technical decisions that may not be the right ones; a sort of

spiral effect

It is hypothesized that for foreign industrial machinery manufacturers producing in the

U.S. a key factor influencing this overall suboptimum performance is how technical

knowledge transfer is structured (channels and attributes) and subsequently managed

between U.S. operations and their overseas foreign-based headquarters; and how this

affects project team success. Thus the problem is a structural management problem with

influences and variables of knowledge management, culture, (both corporate and

national), communication, and other factors to be identified, quantified, evaluated,

reported, and a theory introduced for remedying the situation so that large international

project and teams can have a better probability of success.

The concept of KTS, or Knowledge Transfer Supply-Chain between a U.S. subsidiary

and its overseas headquarters and its impact on project performance will be used as a

key measure. The study seeks out to identify specific attributes within this KTS structure

of these multinational companies that define successful projects. We propose that KTS

is of significant value to international project / team success.

1.2 Research Background

According to Joshi, Sarker, and Sarker, “research in the area of knowledge transfer has

been conducted from three different epistemological stances : cognitivistic,

5

connectionistic, and autopoietic”[66]. The cognitivistic approach views knowledge as

data. According to Joshi et al. the connectionistic approach views knowledge as

contextual in which local differences exist and impact the knowledge entity [66]. Those

that follow this theory contend that knowledge transfer within this context is difficult due

to the “…contextualized nature of the knowledge” [66] and factors of shared

understanding. The autopoietic perspective is rooted in the notion that knowledge and

thus knowledge transfer is based on an autonomous and evolutionary foundation which

develops on its own and with knowledge not really being shared but more being created

[87]. We believe that within the context and scope of our research pertaining to

international companies, the connectionistic perspective will be most suitable.

1.3 Research Objectives and Value to the Discipline

The primary assumption going forward is that there is in fact a correlation among the

way foreign company expats and local representatives working in a subsidiary in the U.S.

and within an engineering and manufacturing function in our study population are

managed and the way communication flows between them and headquarters

(knowledge transfer). There does exist a relationship that can be identified and used to

model and describe a knowledge transfer function or process; and this can be related to

project success.

Essentially the study will be initiated with the assumption that these knowledge transfer

processes can be identified, quantified, modeled, and utilized to improve chance of

success of projects. There will be certain assumptions that will have to be made as to

what constitutes “success.” These will be identified and addressed.; one possibility is

the speed at which technical information flows and eventually results in on-time project

6

completion or on-time delivery of product. This can be a good approach because it does

not take into account the product itself but an auxiliary operational metric instead. Thus,

certain assumptions regarding the operation and the metrics to be used will have to be

made.

Research Objectives

1. Establish what is the most meaningful concept of project success to the target

study companies. How do they measure success and what are the similarities in

measuring project success among them. Establish these common factors for

success that can then be used to further the investigation.

2. Identify specific knowledge transfer attributes and descriptive variables of

multinational industrial manufacturing companies with foreign headquarters and U.S.

subsidiaries involved in international projects (our target companies). Make a

preliminary judgment on how these attributes and descriptive variables are related,

if at all, to the company’s project management successes; what is important, what is

not important, etc.

3. Identify key correlations in knowledge transfer processes between the 3 culturally

diverse groups of companies that make up the majority of our target industrial

manufacturers (German, Italian, Japanese); identify communication attributes that

related to the companies’ corporate and national culture and how these establish a

tool link with the knowledge transfer function.

4. Establish a final correlated relationship between knowledge transfer factors and

project success; conclude a final relationship among the attributes and variables of

knowledge transfer and project success, and establish a conceptual model for this.

7

5. Increase the knowledge and understanding in the fields of International Project

Management, Intra-Corporate Technical Communication Management, Knowledge

Management / Transfer Methodology. These are areas which would be a great

interest to students of engineering management, international business, operations

management even sociology and organizational behavior.

The innovation that will result from this study will be a conceptual model utilizing a

defined set of attributes and relationships for setting up optimized knowledge transfer

channels between a technical / manufacturing company’s foreign headquarters and its

subsidiary operations within the United States. These channels will enable the operation

to be better equipped in managing larger scale international projects which require

information flow (marketing requirements) upstream to the manufacturers’ headquarters

and downstream (final technical specifications and product) to the final customer which

may be located in the U.S. or in another country. The research will identify key attributes

integral to knowledge transfer for successful international projects.

Thru a literature review we will identify past research which has addressed various

aspects of the discipline of Project Management including substantial work done on

project management’s relationship to project team culture, and project management

communication aspects. However, we will show and seek to address a fundamental

lack of research in the area of integrating knowledge transfer and its utilization of

various communication methodologies as it relates to various aspects and levels

of culture (national, team, corporate) leading to success in international projects.

Specific attributes will be identified within this overall integration concept which when

properly considered and balanced by future project managers, will enable an improved

8

probability of success. This integrative theoretical concept model of knowledge transfer,

communication processes, culture, within international projects leading to a success

probability will be finally derived. This integration or relation hypothesis and its

resulting, and supporting success attributes is the innovation of the research.

A conceptual framework established by the author is shown in Figure 1-2.

Figure 1-2 : Conceptual Framework

There has been extensive research into project management, to a lesser extent but still

noteworthy research has been done on the cultural aspects of project teams and their

dynamics. However, based on Shenhar and Dvir’s Project paper Management Research

9

- The Challenge and Opportunity, [107] a paper appearing in the June 2007 Project

Management Journal, there are several areas that require considerable research

opportunities. In this recent journal article, they contend that statistics of project success

suggest that most projects fall short of meeting their goals. The authors offer areas of

potential future research in regards to three aspects of project management and

success : from a strategic business aspect, from a operations process aspect, and from

a team leadership aspect. Our study will focus on 2 of these areas : operational /

process and team leadership. Knowledge transfer as it relates to project success is

integral to the process of project management; while the cultural side which in turn also

relates how processes are accomplished within multinational companies is related more

towards the team and leadership dynamics aspect.

Our study is unique in that it will attempt to integrate and present factors which in

themselves are the binding variables for the various past aspects of project management.

What is meant is that there has been significant past research in the field, however there

has been little research in the area and affect of combining knowledge transfer

with communication mechanisms as tools for the transfer, and cultural aspects

and relating these to project success. It is this combination which our study seeks to

research and contribute to the body of knowledge.

Our research can be available to be used by international industrial companies who are

considering to establishing operations in the U.S. The research can present the factors

which would lead to a higher probability of project success once those companies are in

the U.S. These factors relating to knowledge transfer and the mechanisms for it

(communication channels, etc.) can be combined with a company’s cultural makeup

(both corporate culture and national culture) to provide an optimum scenario for that

10

company to set up its project management processes. Thus, the stakeholders and

interested parties could possibly be :

The heavy industrial machinery industry, and companies especially from, but

not limited to, Japan, Italy, and Germany who have a stake in overseas

operations and project management while the core of their knowledge resides

at their headquarters back home. Other countries which are gaining ground

here are : Korea, Finland, and Sweden.

Chinese companies who are considering structuring potentially new operations

in the U.S. and getting into the industry in the next 5 to 10 years that will be

involved in project management and knowledge transfer with their headquarters.

It is felt that the research that will result from the study of Japanese companies

will be of great interest to the Chinese.

Academics and students of Engineering and Project Management; Social

Scientists in team communication and culture disciplines and studies ;

knowledge management students and professionals, especially those in the

area of studying knowledge transfer; and business management students and

researchers, especially those interested in structuring operations and business

processes within a multinational setting.

This study will add to the body of knowledge in managing engineers and technical

personnel and contribute further to the overall understanding and discipline of

Engineering and Project Management from an international point of view. We feel that

this is becoming more and more important since companies are operating from an

increasingly more global perspective. For example, family-owned manufacturers in

11

Northern Italy, a region well-known for its entrepreneurial manufacturing character, are

now expanding into the U.S. and even China. Whereas before these companies and

region of Italy was thought of as the “China of Europe” now they are operating

internationally. Without a doubt the culture and processes that are set-up contribute to

such a company’s project management success.

There are many such national examples from Italy, to Japan, to Germany and others. In

some cases choices are made to have local headquarters personnel relocate to the USA,

subsequent knowledge transfer is handled a certain way under certain conditions in

regards to projects. In some cases these companies are too small and no personnel is

interested to relocate, so local personnel must be found; knowledge transfer under this

condition is handled differently. The study will provide insight to the discipline in

identifying optimum processes.

1.4 Thesis Organization

This dissertation consists of five chapters : Introduction, Literature Review, Research

Design and Methodology, Results and Data Analysis, and Conclusions.

Chapter 1 – Introduction provides a general introduction and outlines the problem and

background related to the study. This chapter also outlines the research objectives and

key questions which the investigation is structured around.

Chapter 2 – Literature Review provides a comprehensive literature review of the

major areas addressed in the investigation : Knowledge Management and Transfer,

12

Culture, Communication Methodologies Mechanisms and Tools, and Project

Management. Because the scope of research includes areas that are fairly extensive in

themselves, such as the topic of Culture, or Communication, this Chapter is focused on

those specific areas of the literature in each segment which relate to our particular

investigation. The chapter is completed with a visual literature map demonstrating the

particular area in which our research will be focusing.

Chapter 3 – Research Design and Methodology outlines the research methodology

utilized in our research. It begins with our Research-Objectives-Hypotheses mapping

and process which outlines and demonstrates the full integration across the research.

We also outline the methodology for our cross-cultural research and provide a detailed

description of the survey tool used to gather our data.

Chapter 4 – Results and Data Analysis presents the overall survey results and the

data analysis these results were subjected to in the investigation. This is outlined in four

main areas : Headquarters and Subsidiary Communications, Knowledge Transfer,

Corporate Culture, and Project Success. Results are initially presented utilizing cross-

tabulated contingency tables which is a very common and accepted method for

representing survey data. Additionally, this data is analyzed using targeted correlational

analysis based on our hypotheses and utilizing chi-square (χ2) and Cramer’s V

methodologies for statistical significance and measures of association.

Chapter 5 – Conclusions provides a discussion of our findings and implications for the

industry. It provides for final conclusions and recommendations for continued process

improvements within the particular industry and finally presents the limitations of the

study while proposing recommendations for future research.

13

CHAPTER 2 – LITERATURE REVIEW

2.1 Knowledge Management and Transfer

Widely recognized by scholars as the foundation reference in the area knowledge

management, Ikujiro Nonaka’s and Hirotaka Takeuchi’s “The Knowledge-Creating

Company” [87] was first published in 1995, in English interestingly enough, before

being translated to Japanese the following year. In the text Nonaka and Takeuchi

provide a strong foundation for the discipline of knowledge management. It is here that

the concept of tacit vs. explicit knowledge is outlined in great detail and in fact linked to

the cultural delineation of East vs. West conceptual approaches to business and social

interaction in general. Nonaka and Takeuchi describe explicit knowledge as “…that

which can be articulated in formal language including grammatical statements,

mathematical expressions, specifications, manuals, and so forth” [87]. Tacit knowledge

is “…hard to articulate with formal language” [87]. The authors define it as “…personal

knowledge embedded in individual experience,” [87], and that which “…involves

intangible factors such as personal belief, perspective, and the value system” [87]. This

is important because it provides a link to one of our sub-hypotheses relating knowledge

transfer and cultural aspects of a company. Nonaka and Takeuchi discuss the cognitive

dimension of tacit knowledge and how this reflects our image of reality (now) and one’s

vision of the future [87]. This further integrates the concept of culture and in fact some of

the basic research done by Geert Hofstede in his work Culture and Organizations :

Software of the Mind [58].

14

In “The Knowledge-Creating Company” Takeuchi and Nonaka contend that this tacit

knowledge has become “…an important source of Japanese companies’

competitiveness” [87]. We intend to investigate this within the particular scope of our

research and in particular within the framework of project success. What is not covered

in the text is any kind of research that extends the hypotheses to Japanese company

subsidiaries. This will also be part of our focus.

An interesting aspect of Nonaka’s and Takeuchi’s work is their assessment of what in

fact actually is knowledge and the relationship between Eastern and Western thought.

They argue that the Western tradition of “…epistemology, rationalism, and empiricism

differs sharply with regard to what constitutes the actual source of knowledge” [87].

Within the West this further evolves into pragmatism which can be seen as somewhat of

a uniquely American philosophical tradition. While in the East, Japan (one of our focus

countries in our study) has a different evolution of its intellectual tradition in regards to

knowledge, namely : “… (1) oneness of humanity and nature; (2) oneness of body and

mind; and (3) oneness of self and other” [87]. According to Nonaka and Takeuchi,

“…these traits have formed the foundation of the Japanese view towards knowledge as

well as the Japanese approach towards management…” [87]. Once again our

approach will be to consider these also within the context of the subsidiary relationship

(Japanese Parent Company, U.S. Subsidiary Operation) where there is a duality and in

fact a dynamic at work. Do these still hold true ?

A central focus in Nonaka’s and Takeuchi’s text are the processes which collectively

make up knowledge conversion and subsequent transfer, these are : tacit to explicit

(externalization); explicit to explicit (combination); explicit to tacit (internalization);

15

and tacit to tacit (socialization) [87]. These processes are outlined in some detail

below.

Socialization : Tacit Tacit

“Socializing is the process of sharing experiences thus creating tacit

knowledge…” [87]. Also Tacit knowledge can be acquired without using

language such as when an apprentice observing and imitating a master

craftsman. A specific Japanese example are Honda Motors and the

“brainstorming camps” it has developed enabling its employees to meet in an

informal setting in order to solve difficult problems [87]. It is interesting to note

that although not directly stated by the authors, based on our research into the

communications aspect of knowledge transfer, we found that what Nonaka and

Takeuchi present here is essentially a concept of Conversation Analytics

communication theory.

Externalization : Tacit Explicit

“Externalization is a process of articulating tacit knowledge into explicit concepts”

[87]. This is “…typically seen in the process of concept creation…”[87], and very

much integrated into product innovation. Ideas, concepts, images, hypotheses

are “hammered-out” into articulated knowledge in various forms such as writing,

instructions, diagrams, etc. According to the authors, when this is too difficult to

do directly thru analytical methods, externalization can take place thru metaphor

and / or analogy [87]. Canon copiers is a good example of this. It analogized a

disposable copier cartridge with a beer can thus creating the first disposable

aluminum copier cartridge.

Combination : Explicit Explicit

“Combination is a process of systemizing concepts into a knowledge system” [87].

Various forms of training, instruction and formal education fall under this type of

knowledge conversion.

Internalization : Explicit Tacit

According to Nonaka and Takeuchi, “Internalization is a process of incorporating

explicit knowledge into tacit knowledge. It is closely related to learning by doing”

[87]. For explicit knowledge to become tacit there are 2 steps involved. The

16

knowledge should first be verbalized or recorded into documents, manuals, etc.

(Externalization). We can say that this “standardizes” the knowledge. The next

step is for this material to be used by individuals in order to create and expand

their personal tacit knowledge (Internalization). If this is done on a wide-basis

within an organization, and from the same “standardized” foundation of explicit

knowledge, the individual tacit knowledge that is created by the employees

becomes part of the organizational culture. Honda and Sony are prime examples.

According to Nonaka and Takeuchi’s research, “…among the 4 modes of knowledge

conversion, externalization holds the key to knowledge creation, because it creates

new explicit concepts from tacit knowledge” [87]. This allows for these to be shared

more easily. And, it is this type of process which a significant number of Japanese

companies utilize based on the socio-cultural origins of their views on knowledge and

learning. One of the areas our research will focus on is the tacit to explicit

( Externalization ) creation and transfer which we contend is central to successful

knowledge transfer between parent and subsidiary and in fact one of the central

hypotheses for the Nonaka and Takeuchi text in the way how Japanese companies

create knowledge. Our research will extend Nonaka’s and Takeuchi’s in the sense that it

will focus on the relationship between parent and subsidiary something that was not

directly addressed in prior research.

Table 2-1 : Four Modes of Knowledge Conversion ( This table is a variation of Figure 3-2 in Nonaka and Takeuchi [87] )

TO : Tacit Knowledge Explicit Knowledge

Tacit Knowledge Socialization Externalization FROM :

Explicit Knowledge Internalization Combination

17

Nonaka and Takeuchi’s research outlined 5 conditions required in an organization in

order to promote the knowledge transfer process : intention, autonomy, fluctuation (or

creative chaos), redundancy, and requisite variety. We will show how these relate

within the scope of our investigation specifically for the parent-subsidiary operational set-

up and relationship. Further, one of the first requisite steps that the authors identify in

creating and sharing knowledge is sharing tacit knowledge. They also admit that this is

probably the most difficult step as well since tacit knowledge can not be communicated

of transferred easily and depends on individual background, personal perspective, inner-

motivation and emotions, feelings, etc. [87]. Our research and investigative approach

will extend this concept by considering and integrating facets of communication theory.

Once again, extending the potential established by Nonaka and Takeuchi.

A further interesting point by the authors is the concept of middle-up-down

management which, they contend, Japanese companies follow and is responsible for

an improved knowledge creation and transfer [87]. Essentially this is an iterative process

where it’s the middle-management organizational structure that drives the critical

knowledge process both downward to the rank and file, and upward to top level

management. According to Nonaka and Takeuchi, this factor emphasizing the

importance of middle-management is the distinguishing factor between Japanese and

Western management. [87] The authors propose the following Table 2-2 as a

comparison of 3 management models regarding knowledge creation and transfer. This is

relevant for our research in the sense that it relates management structure and

organizational culture with knowledge transfer which we believe is integral to

establishing and maintaining success not only with projects and project teams but for

subsidiary performance overall.

18

Table 2-2 : Comparison of 3 Management Models Regarding Knowledge Creation ( This table is a variation of Figure 5-1 in Nonaka and Takeuchi [87] )

Top-Down Bottom-Up Middle-Up-Down

Agent of Knowledge Creation

Top Management Entrepreneurial Individual

Team

Top Management Role

Commander Sponsor / Mentor Catalyst

Who

Middle Management Role

Information Processor

Autonomous Entrepreneur

Team Leader

Accumulated Knowledge

Explicit Tacit Explicit and Tacit What

Knowledge Conversion

Partial Partial Full

Where Knowledge Storage Computerized, Database, Manuals

Individuals Organizational

Organization Hierarchical Project Hierarchical Task Force

Communication Orders / Instructions

Self-Organizing Dialogue

Tolerance for Ambiguity

Low Some High

How

Weakness Strong dependence on Top Management

Time-consuming and cost of coordinating individuals

Human Exhaustion and Redundancies

Finally the authors provide a set of guidelines for enabling organizations to create a

knowledge “spiral” of knowledge creation and transfer : “…create a knowledge vision;

develop a knowledge crew; build a high-density field of interaction at the front line;

piggyback on the new-product development process; adopt middle-up-down

management; switch to a hypertext organization; construct a knowledge network with

the outside world…” [87].

19

Beyond Nonaka’s and Takeuchi’s work, we have seen a significant amount of research

the past 15 to 20 years in knowledge management and a subset of that discipline –

knowledge transfer.

According to Joshi et al. “…Initial work on knowledge transfer has focused on

international technology…”[66]. Additionally, research into knowledge transfer has

focused on corporate governance in relation to such areas as strategic alliances,

mergers, and corporate acquisitions. However according to Joshiet al. [66] very little

research has been pursued in the understanding of the factors affecting knowledge

transfer within teams. The researchers have focused on knowledge transfer and a

communication-based approach in their paper : “Knowledge Transfer within Information

Systems Development Teams : Examining the Role of Knowledge Source Attributes"

[66], however the research is based on Information Systems development with a primary

focus on the source’s mechanisms in transferring knowledge.

In 1998 Thomas H. Davenport’s and Laurence Prusak’s, published Working

Knowledge : How Organizations Manage What they Know [31]. Their work provides a

more “hands-on” practical approach on how Knowledge Management and Knowledge

Transfer have been successfully integrated into core business processes, has become

part of the business strategy, culture and behavior of successful organizations. This is

interesting for us because of our discovery that in the industry within the scope of our

research there is virtually no such initiative to really integrate these into the core

business. Many of the companies we surveyed seemed to be struggling to understand :

(1) what they know now; (2) what they need to know to survive; and (3) what they

need to do about it. The research we conducted is in an industry in which tacit

20

knowledge is slowly disappearing instead of being captured; this is primarily due to the

overall graying of the workforce in this industry.

According to Davenport and Prusak the primary aim of their research is to provide an

“…understanding of what knowledge is within organizations…how is it different from

data and information… who has it… where is it… who uses it…” [31]. They argue that it

is important to build a link between knowledge management and transfer with the actual

knowledge work process this knowledge is designed to support. They go on to outline

these linkages as taking the form of people whose job is to-and-from front line processes

to the core of the organization; and project management approaches where proactive

reviews take place of what has actually been learned at each phase [31]. The authors

also outline the importance of creating a corporate culture that values the creation,

sharing, and use of knowledge. We will demonstrated that in the scope of our research

we have found that our survey companies do in fact profess such leanings but

unfortunately very few actually take any active measures to put these into place.

Furthermore based on our investigation we will demonstrate that very few companies

within the industry demonstrate a such a conducive corporate culture for this to take

place.

Davenport and Prusak provide some good definitions that remain useful for our research

and should be noted throughout. These definitions below are taken from Working

Knowledge: How Organizations Manage What they Know [31]. We have paraphrased

the definitions for Information and Knowledge.

Data – “…a set of discrete, objective facts about events… structured

records of transactions... there is no inherent meaning in data” [31].

21

Information – data with meaning and some form of added value thru

contextualization, categorization, calculation, correction, and perhaps

summarization to a communicated message [31].

Knowledge – information that is put to work, utilized; it develops over time

from experience and contains judgment [31].

It is interesting to further consider the authors’ definition of knowledge in the sense that

“…knowledge contains judgment” [31]. Based on our research, the question that can be

asked and should be considered is who’s judgment needs to be considered – that of

the parent company, or that o the subsidiary, or both ? Judgment also is based on

values and beliefs which, once again, we must consider exactly who’s values and beliefs

within the parent-subsidiary relationship may take precedent. Beyond making the

argument that companies in the future must differentiate themselves within the global

economy based on what they know, the authors, clearly state that “…in a global

economy knowledge may be a company’s greatest competitive advantage” [31]. In a

sense this is a reiteration of what Nonaka and Takeuchi [87] presented as their central

theme and its what we are proposing for the more complex model of the parent-

subsidiary relationship and function of success.

An interesting model created by the authors and one which relates to our notion of

communication being a key factor in our research, is that of the “Knowledge Market”

complete with its buyers, sellers, brokers, political influences and dynamics, and its price

system. This price system is interesting because its based on 3 significant factors of

“…reciprocity, repute, and altruism…” [31]. Essentially, the authors contend that

knowledge transfer takes place based on a perceived self-interest, based on the

reputation of the source, and / or based on the “…natural impulse to help others…and

22

for the “good of the firm” [31]. This is interesting because, although not acknowledge by

Davenport and Prusak, it relates directly to our research into Social Exchange

Communication Theory.

The authors also go on to outline 3 key factors for “Knowledge Market” inefficiency :

(1) incompleteness of information; (2) asymmetry of knowledge; and (3) localness of

knowledge. All of these were further investigated within the scope of our research; for

example, the incompleteness of information is directly related to language limitations

between parent-subsidiary communications; the asymmetry of knowledge and its

localness also play a huge role in how international parent-subsidiaries handle

knowledge transfer depending on parent subsidiary age, country of origin, and

organizational culture. However, Davenport and Prusak do ultimately conclude that

trust is the key for their “Knowledge Market” model to operate efficiently. In fact the level

of trust within the parent subsidiary relationship is a key factor which we surveyed in our

own research and will present here.

According to Davenport and Prusak, “…spontaneous, unstructured knowledge transfer is

vital to a firm’s success” [31]. And this transfer usually takes the form of both structured

as well as unstructured communication. The authors maintain that having personal

interaction is a key factor, but one which must be considered within the culture of the

organization. The authors contend that in recent years and with the evolution of

corporations to a more isolationist operational model where talk is not considered real

work, there is a danger that knowledge transfer will be threatened [31]. Language is

another major variable for knowledge transfer success. According to Davenport and

Prusak “…a shared language is essential to productive knowledge transfer. Without it,

individuals will neither understand nor trust one another” [31]. This is a key factor for

23

our research which we will explore. Davenport and Prusak propose the following transfer

equation : Transfer = Transmission + Absorption

This is similar to several communication models which will be discussed. The authors go

on to describe some methods used to maintain a high-level of transfer by Japanese

companies; these include “talk rooms” that encourage exchange, as well as the familiar

after-work social gathering that has become famous in Japan for fostering relationships

and communication.

Davenport and Prusak’s research identified several key “frictions” that inhibit knowledge

transfer. The authors also provide potential solutions. These are reference in Table 2-3.

Table 2-3 : Frictions and Potential Solutions to Knowledge Transfer ( This table is a variation of the table on page 97 of Davenport and Prusak [31] )

Friction Possible Solution

Lack of Trust Build relationships and trust thru face-to-face meetings

Different Cultures, Vocabularies, Frames of Reference

Create common ground through education, discussion, publications, teaming, job rotation

Lack of time and meeting places; narrow idea of productive work

Establish times and places for knowledge transfers : talk-rooms, conferences, reports

Status and rewards go to knowledge owners

Evaluate performance and provide incentives based on sharing

Lack of absorptive capacity in recipients

Educate employees for flexibility; provide time for learning; hire for openness to ideas

Belief that knowledge is prerogative of particular groups, not-in-vented-here syndrome

Encourage nonhierarchical approach to knowledge; quality of ideas more important than status of source

Intolerance for mistakes or need for help

Accept and reward creative errors and collaboration; no loss of status from not knowing everything

24

Beyond the basic Knowledge Management foundation material mentioned, there has

been additional research in associating knowledge transfer and culture by : Karlsen and

Gottschalk’s "An Empirical Evaluation of Knowledge Transfer Mechanisms for It

Projects” [67], and "Factors Affecting Knowledge Transfer in It Projects" [68]. Karlsen

and Gottschalk discuss five types of knowledge transfer : Serial, Near, Far, Strategic,

Expert. Their research methodology was similar to what we utilized, namely a Likert

scale type survey of 51 questions conducted in Norway in 2002. They had a fairly low

response rate of 6.5% but concluded that there was no significant non-response bias

[67]. But their focus was on Information (IT) Systems and the development of IT projects.

They do focus on project success and make the connection of knowledge transfer to

success but under a different set of circumstances within the IT industry and not within

multinational teams. They focus on culture more from the corporate point of view rather

than the national or multinational company within an industrial manufacturing setting.

We will indirectly extend the notion of Serial, Near, Far, Strategic, and Expert

Knowledge Transfer and how these relate within the scope of our research.

Additionally, Lin, Geng, and Whinston’s "A Sender-Receiver Framework for Knowledge

Transfer" [74] presents a sender-receiver approach to compensating an incomplete

knowledge transfer scenario under four different type of information structures :

Symmetric Complete, Sender-Advantage Asymmetric, Symmetric Incomplete,

Receiver-Advantage Asymmetric. This has direct similarities to a communication

theoretical framework which is important in knowledge transfer. Again the research is

focused on IT within inter-organizational communication but not within international or

multinational companies. Also the communication aspect is not widely mentioned and

fully integrated in the Lin, Geng, and Whinston research.

25

There have been numerous studies done on knowledge transfer and organizational

learning, among them Elias G. Carayannis’ “Knowledge Transfer Through

Technological Hyperlearning in Five Industries” [17] which proposes a four-level and

four-mode structured approach of a system which could serve as “…a major source of

sustainable competitive advantage for an organization” [17]. This particular study is

mentioned because of the direct implication of company success based on successful

organizational learning by way of a certain knowledge transfer structure.

Soderquist’s "Organizing Knowledge Management and Dissemination in New Product

Development." [111] does in fact consider tacit knowledge and cross-functional team

collaboration in 12 global manufacturing companies and identifies 3 organizational

structures for knowledge management. His research is based on American, German,

French, and Japanese companies. But the research is lacking in identifying specific

factors in project success. So, whereas it is significant in the discipline of knowledge

transfer and culture and does demonstrate a positive correlation; there is little if any

tying-in of this result into specific project management success factors identification in

this research.

Another researcher has done work in the area of KM and more specific knowledge flow

is Juan Roman-Velázquez. In his dissertation "An Empirical Study of Knowledge

Management in the Government and Nonprofit Sectors: Organizational Culture

Composition and Its Relationship with Knowledge Management Success and the

Approach for Knowledge Flow [99] at The George Washington University in 2004, he

presented a detailed statistical analysis of knowledge flow based on 4 cultural types :

Clan, Adhocracy, Market, Hierarchy. His approach shows close parallel to what we

are proposing in our research based on survey and the gathering of data. The difference

26

here is that Roman-Velázquez focuses on the government and non-profit sectors and he

is another researcher which does not directly link the study to project success.

MIT’s Paul Carlile in his 2 papers "Transferring, Translating, and Transforming : An

Integrative Relational Approach to Sharing and Assessing Knowledge across

Boundaries" [19] and

"A Pragmatic View of Knowledge and Boundaries: Boundary Objectives in New Product

Development" [18] focuses on the transfer of knowledge by international companies

and teams but looks at this from a generalized strategic level as opposed to an

operational project-oriented approach, again tied into project success. In the later work

he outlines several approaches at this strategic level such as Syntactic (language),

Semantic (interpretation), and Pragmatic (consequences) [18].

Past research has also focused on knowledge transfer from customer to supplier [93]

and has considered further cultural ties to knowledge transfer such as Aleksandra

Hauke’s “Impact of Cultural Differences on Knowledge Transfer in British, Hungarian,

and Polish Enterprises” [55] published in 2006 which focuses on a study done among

British, Hungarian, and Polish companies. Hauke’s investigation integrated Geert

Hofstede’s [58] landmark research on culture and organizations originally done in the

1960s and which has been refined by the author ever since. It is interesting to note

Hauke’s main argument is that of the need for trust and the fact that managers play a

very important role in developing and nurturing this trust. This concept will be a central

theme in our research as well. The central concept of trust in knowledge management

has been researched and discussed extensively by Davenport and Prusak [31], Goh and

Swee [47], and others.

27

One interesting study has been conducted and presented by Michael D. Santoro and

Shanthi Gopalakrishnan’s "The Institutionalization of Knowledge Transfer Activities

within Industry-University Collaborative Ventures” [104]. It focuses on the relationship

and knowledge transfer activities and processes between industry and academia. The

study was based on 189 companies and 21 US universities and established that culture

plays a key-role and directly impacts the success of the transfer when there is a stable

direction-oriented approach and firms are more trusting. There study focused on

industrial companies in the US.

2.2 Culture

According to Grisham [50] it is usually sociologists, anthropologists, and psychologists

that normally research and investigate culture. Engineers and Engineering-related

managers have paid little attention to the topic in the past twenty years. Although

culture plays a very important role in all these fields; a role which continues to grow as

borders essentially dissolve.

The quintessential research conducted on national culture remains that done by Dr.

Geert Hofstede, professor of Organizational Anthropology and International

Management at Maastricht University in the Netherlands. Hofstede conducted his

original study in 1968 and a follow-up study in 1972. His research was published in

1980 as “Culture’s Consequences : International Differences in Work-Related Values”

[58] Hofstede defines culture as “the collective programming of the mind; which

manifests itself not only in values, but in more superficial ways : in symbols (metaphors),

heroes, and rituals” [58]. Hofstede contends that a person’s behavioral patterns of

thinking, feeling, and acting are based partially on mental programs, the source of which

28

lie within the social environments in which one grew up and collected their life

experiences. According to Hofstede “…programming starts within the family; it

continues within the neighborhood, at school, in youth groups, at the workplace, and in

both the local and extended living community” [58]. Hofstede contends that this

programming extends thru several “layers” of culture at various levels : national, regional,

ethnic, gender, generational, social class, and for those employed – organizational,

corporate, and departmental. We will investigate this aspect further in subsequent

sections in the dissertation regarding Engineering and Corporate culture.

According to Hofstede, culture is a collective phenomenon; a “…collective programming

of the mind that distinguishes the members of one group or category of people from

others” [58]. As such, it is important to realize that applying the norms of one

person, group, or society to another is not a good approach. This of course is important

for our research because of the fact that the national cultures we are interested in seem

to be very far from each other in terms of the definitions outlined above although the

basic scope of work or field we are studying is the same (large industrial gear production

and Project Management). This is a unique opportunity in which extensive research has

not been conducted; therefore it is interesting to consider Hofstede research and

theories within the context of our own dissertation scope.

2.2.1 National Culture

Nations have essentially evolved and developed fairly recently. They are political

constructs which we all belong to and associate with in some form or another as

Americans, Japanese, Greeks, Italians, and so forth. Distinguishing culture among

nations is in fact not strictly correct but for the sake of this research and others that

29

have been done, we will continue to use the term “National Culture.” We are

justified to a point in that within nations there always seems to be a strong force to

integrate societies – the classic example being the United States. However we do

remain cognizant of the fact that terms such as “typically American,” “typically

Japanese,” rightly or wrongly are used but need to be taken with a deeper

understanding according to Hofstede [58].

Hofstede’s extensively-validated research and conclusions are summarized below.

Appendix A provides a summary of Hofstede’s research for further reference.

1. Power Distance – “…the extent to which the less powerful members of

institutions and organizations within a country expect and accept that power is

distributed unequally” [58]. A Low Power Distance Index (PDI) signifies

decentralization of authority such as a flat organization where individuals essentially

consider themselves equal; while a high PDI indicates a more rigid hierarchical

working environment.

2. Individualism vs. Collectivism – the degree to which individuals are supposed

to look after themselves or remain integrated into groups (as in family), institutions,

organizations. In individualistic societies the ties between individuals are loose. In

collectivistic societies people are “…integrated into strong, cohesive in-groups…

protect their members…in exchange for unquestioning loyalty” [58]. A low

Individualism Index (IDV) indicates collectivism and confrontation avoidance; while

a high IDV indicates individualism and a tendency not to back away from

confrontation. Low IDV / collectivistic cultures usually utilize high-context (implied)

communication; whereas high IDV / individualistic cultures rely on low-context

(explicit) communication.

3. Masculinity / Femininity – the distribution of emotional roles between genders -

from tough, assertive, and materially-focused masculine to modest, tender and

quality-of-life-oriented feminine [58]. The measure for this dimension is Hofstede’s

masculinity index (MAS).

30

4. Uncertainty Avoidance – “…the extent to which the members of a culture feel

threatened by ambiguous or unknown situations” [58]. “The degree to which people

try to control the uncontrollable, and their resistance to change” [50]. Hofstede

uses the Uncertainty Avoidance Index (UAI) to measure this dimension. A low UAI

indicates trust, less resistance to change and low stress / anxiety. A high UAI

indicates distrust of others, high anxiety, higher uncontrolled emotions and

resistance to change. It should be noted that Uncertainty Avoidance is not the

same as Risk Avoidance; there is a subtle difference. The former deals with a

situation in which anything (unknown) can happen; while the latter by associating

risk, it is not an unknown any further. [58]

5. Long / Short Term Orientation – “…extent to which a culture programs its

members to accept delayed gratification of their material, social, and emotional

needs” [50]. Hofstede established the Long-Term Orientation Index (LTO) to

measure this dimension a low LTO (short-term-oriented) indicates the “right-here-

right-now” leanings of Western cultures and business where performance is

measured quarterly; while data clearly shows that a high LTO is associated with

East Asian cultures / countries such as China, Taiwan, Japan, Korea, Vietnam and

others; where time is provided for someone to make their contribution.

Hofstede’s research has been replicated and thus validated several times. C.L.

Scott’s research, summarized in the 1980 article : “Interpersonal Trust : A

Comparison of Attitudinal and Situational Factors” showed a very interesting result

for us in that “… trust varied more on the basis of the trustee’s attributes rather

than the trustor’s propensity to trust” [50]. This will be discussed within our

research because it has wide implications in regards to establishing effective

knowledge transfer structures between parent and subsidiary. Interestingly enough

Scott further “…hypothesized that integrity and ability (technical, interpersonal,

etc.) predicted trust better than simple benevolence…” [50].

31

In 1990 Edward Twitchell Hall described an interesting way to understand cultures

thru effective communication [50]. One particularly interesting concept he proposed

is that of high and low context cultures. “High context cultures like the Japanese,

rely heavily on relationships while low context cultures like Americans rely more on

contracts” [50]. Hall discussed space which is the subset theory of Proxemics, as

well as time which various cultures have a monochronic (linear) approach while

others have a polychronic (multi-parallel) disposition.

In relating culture to international projects, one interesting research conducted in

2005 and published in the International Journal of Project Management was that of

Shore and Cross. They indicate that the relationship between project management

and national culture has generally not received the emphasis it deserves in the

literature. The authors pose a number of questions which specifically address

Project Management and which were paraphrased by Grisham. These are noted

here because they relate directly to our scope : “Is the study of national culture

relevant to Project Management ?”…”Which cultural dimensions are likely to affect

the management process ?”... “Which management issues are linked to the

influence of culture ?”... “Does culture affect project outcomes ?” [50].

An interesting factor to consider is the concept of cultural distance discussed in

Trenholm [118]. Trenholm defines cultural distance as “…the extent two cultures

differ” [118]. It will be important for our dissertation because we are considering

the relationship between cultural pairs of foreign parent company overseas with

local subsidiary in the United States. Recent work on this topic was conducted by

Antia, Lin, and Pantzalis in their 2005 paper : “Cultural Distance and Valuation of

Multinational Corporations” [5]. Their findings indicated that cultural distance

32

factors do in fact have a negative effect on firm valuation [5]. This is interesting

because it could potentially indicate a less than optimum operations strategy being

affected by the cultural distance factors and in turn affecting the overall company

valuation, profit, performance, etc. Antia, Lin, and Pantzalis go on to point out in

their conclusions that “…the notion of cultural distance does in fact seem to impede

the transfer of intangibles…” [5], such as knowledge thus leading to the negative

effect on valuation. The Antia, Lin, Pantzalis paper essentially expanded the

previous (1997) work of Gomez-Mejia and Palich : “Cultural Diversity and the

Performance of Multinational Firms” [49].

It is interesting to note that according to some researchers, among them Larry

Samovar and Richard Porter, based on their published material in “Intercultural

Communications” 8th edition (1997), Japan and the United States stand at the very

maximum in terms of cultural distance. We content that on the surface Japanese

culture seems to be very Western-oriented especially with the younger generation,

however there are deep-rooted differences which in fact do make this pairing one of

the most culturally distant. We shall now examine this further from a knowledge

management perspective.

According to Nonaka and Takeuchi [87], the Western tradition on knowledge,

learning, and reasoning has a long history going back to classical Greece and even

further, while there is almost none to speak of in Japan. In Western tradition the 2

dominant approaches are rationalism (mathematics is a good example) and

empiricism (experimental data-based science) [87]. Paraphrasing Nonaka and

Takeuchi - the “Japanese” approach to knowledge, corporate management practice,

as well as everyday life in general, integrates : Shinto, Confucianism, Buddhism,

33

Taoism, and Western Scientific Materialism [87]. The Japanese value system itself

stems from these 5 areas, greatly influencing corporate culture and thought.

According to Nonaka and Takeuchi, these make up the so-called “Japanese ethic”

which is a very important aspect to consider in terms of culture [87].

Shinto emphasizes harmony of elements and holds that Japanese race is

descended from gods. Thus the overwhelming concept of harmony in all

surroundings and situations and the traditional belief of superiority of the Japanese

race is a long-standing tradition.

Confucianism was brought to Japan from China approximately 2,500 years ago and

is more of a social code of rules of behavior rather than a religion. Confucianism

identifies types of relationships with distinctly clear patterns of behavior that govern

each. We contend that this distinct social code is easily transferable to Japanese

corporations (especially the very conservative companies) in relation to their

seniority system.

Like Confucianism, Buddhism and Taoism also originated in China and were

originally brought to Japan approximately 1,000 years ago. Japanese society

developed its own mixture of these two concepts calling the result Zen Buddhism.

Zen stresses meditation and concentration and actually reinforces Shinto [87]. In

modern Japan, traditionalists still practice these concepts.

According to the well-known author on Japan Boye Lafayette De Mente, an

additional and interesting basis for modern day Japanese values and behavior is

the notion of wet-rice farming. De Mente supports the claim of several historians

34

that the introduction of fairly complicated wet-rice farming to Japan from China

created a lifestyle that instilled the people of Japanese with qualities of patience,

perseverance, diligence, cooperation, and group dependence. Maintaining wet-rice

farming systems is virtually impossible for one individual or even one family, and

requires those qualities mentioned above. The fact that Japan is an isolated country

of which the majority of the terrain is very rugged and natural resources are

relatively scares, only adds to the difficulty. In Japan the saying goes “eating rice

from the same pot” meaning : we, the Japanese, are all in it together. This “group

think” plays an important role in knowledge creation and use. It is the idea that the

group is more important than the individual which enables many Japanese

companies to create and disseminate much information to all in the company

instead of keeping information compartmentalized.

From the above descriptions we can say that for the Japanese, knowledge means

wisdom that is acquired from the perspective of the whole personality; knowledge

that develops from relationships; and knowledge through flexibility. This is one of

the central themes of Nonaka and Takeuchi [87]. According to Nonaka and

Takeuchi, “In Zen Buddhist training students are required to devote themselves to

the world of ‘non-logic’ throughout their learning process” [87]. This is virtually

opposite of rationalism in the West. This emphasizes direct personal and physical

experience over intellectualism and logic of the West. Furthermore and according

to Nonaka and Takeuchi, “…while most Western views of human relationships are

atomistic and mechanistic, the Japanese view is collective and organic…” [87].

Thus the main distinction between Western and Japanese thought on knowledge is

one of the scientific vs. the humanistic approach.

35

In the early part of the 19th Century the well-known sociologist Frederick W. Taylor

attempted to “manage by science.” He prescribed certain scientific methods to

organize and operate work. Scientific Management was “…an attempt to formalize

workers’ experiences and tacit skills into objective and scientific knowledge...” [87],

according to Nonaka and Takeuchi. This approach did not lend itself to

personalization whatsoever.

In the 1920s and 1930s a group of management academics at Harvard headed by

the well-known George Mayo conducted experiments that established relationships

between employee morale, employee sense of belonging, and constructs based on

high levels of personalization (in effect the opposite of Taylor). Mayo went on to

develop a new management theory of “human relations” which presented

individuals as social creatures inherently linked to their social structure both in and

out of the workplace. Mayo’s theory touches upon the Japanese way of

management and group culture.

On the surface one may consider that the value system in Germany is similar to

Japan’s. German’s have an innate desire to seek consensus and a strong respect

for maintaining order. This is reflected in the German phrase : “Ordnung muss sein”

(there must be order !) [85]. One expects the same sense of group identity as

found in Japan, to also exist in Germany. Decisions are made based on one’s ties

to society, company, and family, though not necessarily in that order; and any

actions or decisions that disrupt the social order are seen as inherently wrong.

Furthermore, according to Morrison and Conaway [85], Germans do demonstrate

substantial individual freedom which is based on their ability to compartmentalize

36

and distinctly separate norms of behavior accordingly. Therefore as long as one

satisfies the requirements to their group, personal behavior may have some latitude.

The author of this dissertation personally witnessed a relatively minor act while on a

German train which somewhat supports this concept.

“While traveling on a train outside Berlin in 1999, we saw 4 German youths

around the ages of 15 to 20 years old sitting on the train seat with their feet,

punk-type leather boots and all, on the seats opposite. The interesting point was

that all of them had placed newspaper on the seats so that they would not dirty

these seats having their feet up.” ( Author’s personal observation )

Of course this is of minor consequence and one small observation, but it somewhat

crystallizes the idea noted above, namely that Germans value their individuality and

personal freedom as long as social obligations and requirements are satisfied.

Along with order, punctuality is key in Germany. According to Morrison and

Conaway, Germans can be “…very risk-averse and cautious about making

decisions… and they are more oriented toward near-term issues…” [85] (as has

also been substantiated by Hofstede’s LTO or Long-Term Orientation Index).

Germany has historically been closed to outside information and overall variation.

According to Hofstede, in German schools, the curriculum favored is a highly-

structured approach with distinct objectives to be met . Hofstede goes on to say that

“German students are brought up in the belief that anything which is easy enough

for them to understand is dubious and probably unscientific” [58]. Teachers and

knowledgeable elders are shown respect and this sense of mentorship and

development can also be seen in the country’s apprentice program which, although

37

becoming less and less popular in Germany, still remains a major structured

conduit to the country’s skilled workforce.

The concept of knowledge and knowledge transfer is treated differently in Germany

than Japan. While Japan may focus on the human side of this transfer; Germans

tend to focus on the technological side or information-management “tools.”

Interestingly-enough Germany ranks very high in the development of such tools,

especially for business. While the United States and to a lesser extent, the United

Kingdom, have focused research in these primarily revolving around security, it is

Germany who in effect has been gaining ground in such tools as ERP and CRM

systems (arguably a kind of knowledge management systems). One of the most

popular system currently is SAP.

One can make the case that in Japan the sense of obligation to the group is the

central focus. In German culture a sense of structured-order is the key. In Italian

culture its relationships. The sense of relationship to family as well as regional

culture is very important. Establishing strong, trusting human relationships is key

and there is a strong sense of loyalty to one’s family, and close regional and

professional associates.

According to Morrison and Conaway [85], the cognitive style of Italian culture is

based on readily accepting information that may be provided by a relatively

knowledgeable source. However, the processing of this information is very

subjective and associative according to Morrison and Conway. “Subjective feelings

are more important than faith in an ideology or objective facts in deciding what s

true” [85].

38

This is different than the Germans who are analytic and objective; but it’s somewhat

similar to the Japanese who are themselves subjective in their thinking but who do

in fact put much more emphasis on traditional values than either the Italians or

Germans. Furthermore, according to Morrison and Conaway, Italian culture is very

diverse but at the same time there is a sense of “…cultural resilience and

continuity” [85]. This is something similar to the Japanese.

2.2.2 Corporate / Organizational Culture

According to Eisenberg, Goodall, and Trethewey, there are 3 broad perspectives

that categorize recent organizational culture research : practical, interpretive, and

critical-postmodern. The practical approach views an organization’s culture as

another “feature” of that organization that can be created by management and

utilized in order to improve the effectiveness of the organization. According to the

authors, this approach was hypothesized and described by Terrence Deal and Allan

Kennedy in their 1982 text : “Corporate Cultures : The Rites and Rituals of

Corporate Life.” [as referenced in 37] Furthermore, the popular text “In Search of

Excellence : Lessons from America’s Best-Run Corporations” by Peters and

Waterman [as referenced in 37] also subscribe to this view.

The interpretive view essentially contends that culture is too complex to be

managed by one or several individuals of a company. According to Eisenberg,

Goodall, and Trethewey, the interpretive view treats culture as a socially-

constructed entity, one which is always in flux and based on the everyday

communicative behaviors among the members of an organization [37]. This

39

approach to understanding culture, according to Eisenberg, Goodall and Trethewey,

has shifted our focus in recent times towards understanding how people

communicate and create meaning within their communication. This is important in

knowledge management and transfer, specifically in tacit knowledge transfer.

Finally the critical-postmodern view of organizational culture supported by the

researchers Stanley Deetz and Joanne Martin, considers degrees of integration,

differentiation, and fragmentation in describing organizational culture.

Although recent work in organizational culture has experienced a revival primarily

due to globalization and the need for multicultural management, organizational

culture research is actually not a new discipline. Research in organizational culture

has been conducted since Max Weber’s Theory of Bureaucracy. A comprehensive

review of Weber’s original theories can be found in The Theory of Social and

Economic Organizations. In the early 1930s the well-known Hawthorne studies at

Western Electric Company in Chicago provided additional insight the field of

organizational culture [96]. For our research our focus will be on organizational

culture and how it relates to communication and knowledge transfer.

Although there have been numerous definitions of organizational culture in the

literature, we focus on theories of organizational culture which emphasize the ways

“…people construct (a shared) organizational reality…” [75], essentially identifying

what its members consider meaningful and valuable. John Van Maanen and

Stephen Barley’s 1985 work entitled “Cultural Organization: Fragments of a

Theory,” outline four domains of organizational culture which are relevant to our

research in considering culture in relation to communication; these are

paraphrased here : the Ecological Context – deals with the surroundings or

40

physical world within which the organization operates; Differential Interaction –

establishes and describes the networks of the organization; Collective

Understanding – identifies the content of the culture of the organization such as

values, ideals, ideas, beliefs, practices; Individual Domain – the practices and

actions of the individuals within the organization [75].

As one can easily interpret based on these domains, organizational cultures are

always in a state of flux based on a continuously-changing environment.

Furthermore Van Maanen and Barley identify the fact that a single culture within an

organization is almost impossible; with the exception perhaps of IBM in the 1960

and 1970s (author’s personal note). They contend that often subcultures identified

with particular groups, departments, sections, functions, processes, systems will

emerge. This will be a key point in the research of this dissertation and one which

has not been investigated to a great extent. Another key area which has only

recently been considered for in-depth research is the fact that there is a

fundamental shift in the overall research in organizational culture with a greater

emphasis of this idea of flux tied into communication and the notion of shared

meaning and understanding emerging from communication theory – a central

aspect of the research in this dissertation also directly related to the concept of

shared meaning within the context of tacit knowledge. According to Littlejohn and

Foss :

“…recent work on organizational culture has marked an

important shift from functionalism to interpretation – from the

assumption that an organization has pre-existing elements that

act together in a predictable manner, to the assumption that

there is a constantly-changing set of meanings constructed

through communication” [75].

41

According to Michael Pacanowsky’s and Nick O’Donnell-Trujillo’s 1983 work

“Organizational Communication as Cultural Performance,” [as referenced in 75],

organizational culture is something which is “…created, maintained, and

consistently modified thru daily interaction within the organization” [75]. Their work

extended that of Victor Turner’s 1974 “Dramas, Fields, and Metaphors.”

There is a tremendous amount of research on organizational culture but the focus

of this dissertation must evolve around previous and specific research in

conjunction with communication. The basic concept that we would like to identify is

that organizational culture, and in fact, organizations themselves are created thru

communication which is a core tool in the transfer of knowledge, specifically tacit

knowledge. Since our research is international in nature which involves certain

aspects of Japanese organizations some review and discussion can be made on

certain aspects of Japanese corporate culture as it relates to knowledge

management and transfer.

According to Chen [21] as with Japanese society in general, Japanese companies

are fairly rigidly organized and very hierarchical. He contends that, “although

companies promote a sense of equality through equal compensation and wage

parity this is true only within each specific level of the organization, that is, these

concepts are valid horizontally not vertically” [21]. At the top of the organizational

structure is the kaicho (chairman), who is followed by the shacho (president). In

most companies however the vast majority of the actual work is accomplished by

the kacho (department manager). This is important as we will see later.

42

Leaders in Japan tend to be generalists and not so much specialists in something.

Their main responsibility is to maintain the morale of their workers, who do the

actual work and keep the company functioning. Furthermore there is a strong

tendency for Japanese people to choose their leaders with personal qualities rather

than particular set of skills, experience or some specific knowledge. Younger new

employees are observed in a very systematic manner usually by their direct

supervisors and the very strong HR department which many bigger Japanese

corporations maintain. As these younger employees are developed and come up

the ranks their futures within the company are being planned. These employees are

likely to be good listeners and good harmonizers working towards group cohesion.

Above all wa or harmony is of prime importance to both Japanese society as well

as to the Japanese organization, especially the more traditional companies. The

Japanese try to promote wa in all social situations of their daily lives. Harmony is

the single key for maintaining face for Japanese and many Asian cultures. The goal

for Japanese managers is to maintain group togetherness.

According to Nonaka and Takeuchi [87] Japanese managers see themselves as

humanists with a primary focus on their group. However, Japanese humanism is

not the same as Western humanism. IN the West the focus is on the individual, in

Japan its on relationships between an individual and a group [87]. Japanese strive

to develop a self that is in harmony with the surroundings while in the West the

exact opposite occurs. Westerners strive to express a unique personal character

that sets them apart individually.

We have seen that harmony and relationships are very important. One method

promoting these is Ringi seido a commonly-used formal procedure of

43

management by group consensus. A ringisho is a proposal that originates in one

section, and is forwarded to all relevant sections on the same level, the section

heads, the managers, the directors and the president of the company [21]. The

ultimate purpose of this system is to eliminate dissension and get general

agreement on a proposal. This system provides for greater participation in the

decision-making process within the Japanese company. Essentially any decision

adopted through this method has already been agreed upon. An added benefit of

this system is the fact that many individuals throughout the company gain a wide-

range of information and valuable knowledge on certain particular important

aspects and decisions of the corporation; thus better, more informed decisions can

be made leading to greater innovation; and, according to Nonaka and Takeuchi, a

spreading of knowledge within the company takes place.

According to Nonaka and Takeuchi, in Japanese corporations, middle managers

are at the very center of knowledge management. Although Japanese companies

are very structured and hierarchical, much weight and decision-making takes place

at the mid-management level. This is unlike the West which has adopted primarily a

Top-Down approach or more recently a Bottom-Up approach with empowerment

and other similar programs.

As described by Nonaka and Takeuchi, the Top-Down approach is the

quintessential hierarchical model. In terms of knowledge creation, this occurs within

an information-processing approach. Basic information is filtered upward to the top

management who then use this to create plans and orders which are then passed

down the pyramid to those assigned to carry them out. Top management concepts

become the operational conditions for middle managers who must decide how to

44

make them happen. The middle managers then make the operational plans for the

“front-line” employees who must implement them. The Top-Down approach is well-

suited for dealing with explicit knowledge. But, essentially in controlling knowledge

creation from the top, it tends to neglect the development of tacit knowledge that

occurs on the “front-lines” [87].

In the Western Top-Down model, middle managers process much information but,

they tend not to have a major role in creating information. As stated above this

approach can be said to be more information processing (flow) instead of

knowledge creation and management.

The Bottom-Up approach is centered on autonomy which, according to Nonaka and

Takeuchi, is something that enhances tacit knowledge. Top management serves as

sponsor of entrepreneurially minded front-line employees. But, a negative aspect of

this model is that more autonomy and less interaction takes place within the

organization; a kind of “every-man for himself” mentality. Thus knowledge is created

individually and not necessarily optimized by interaction (culture and

communication), and in many cases not shared or disseminated within the

company as it should be.

According to Nonaka and Takeuchi [87], in both Top-Down and Bottom-Up,

knowledge conversion is not optimized but limited. suggests a third approach

focused at the middle. It is the middle managers which create knowledge and

generate what they refer to a “double knowledge spiral,” involving both top

management and front-line employees. These middle managers are usually the

leaders of development teams, self-organized task forces, and other such intra-

45

departmental groups. Thus, according to the authors, they are at the “…very center

of knowledge management, positioned at the intersection of both vertical and

horizontal flows of information within the company” [87]. As paraphrased from

Nonaka and Takeuchi - these managers are the so called “knot” that binds top

management with the front-line or the “bridge” between visionary ideals formed at

the top and the often chaotic reality which exists at the bottom front-lines. These

middle managers are the so called true “knowledge engineers” in Japanese

corporations [87].

Finally in considering the question : “Why is culture so important for a

organization ?” We can consider the following by William Schneider as outlined in

the 2001 Doctoral dissertation of Vincent Michel Ribiere [96] but slightly modified by

the author. Culture is important because :

“…it provides consistency for the organization and its people; it provides

order and structure for activity within the organization; it establishes and

internal way of life for members; it determines conditions for effectiveness; it

strongly influences how an organization is structured; it sets the patterns for

internal relationships among members; it defines effective and ineffective

performance; it anchors an organization’s approach to management; it

provides the boundaries for strategy and strategic planning” [96].

2.3 Communication : Methodologies, Mechanisms, and Tools

“Communication is at the heart of all organizational operations and international

relations. It is the most important tool we have for getting things done. It is the

basis for understanding, cooperation, and action. Yet communication is both

hero and villain – it transfers information, meets people’s needs, and gets

things done, but far too often it also distorts messages, causes frustration, and

renders people and organizations ineffective ” [53].

46

Excerpted is the transcript of Avianca Flight 52 from Bogotá Columbia to JFK

New York. The flight ran out of fuel, crashing in Long Island in Jan. 1990; killing

73 passengers. ________________________________________________________________________________________

Captain to Copilot : “tell them we are in emergency”

Copilot to Air-Traffic Controller : “we are running out of fuel…l”

Air-Traffic Controller : “climb and maintain 3,000”

Copilot to Air-Traffic Controller : “uh…we’re running out of fuel”

Air-Traffic Controller : “I’m going to bring you about 15 miles northeast and then turn you back……is that fine with you and your fuel ?”

Copilot : “I guess so…..” ________________________________________________________________________________________

Taken from Exhibit 2-1 in Harris and Moran’s Managing Cultural Differences [53].

2.3.1 Theoretical Basis

We contend that one cannot maintain nor even initiate any form of meaningful

knowledge transfer without utilizing various forms of communication. As with

considering the cultural aspect of knowledge and knowledge transfer,

communication also is fundamental. How does one define “communication” ?

Certainly it is not an easy task since “communication” and the verb “communicate”

are two of the most overworked terms in the English language according to

Theodore Clevenger in his 1991 work “Can One Not Communicate?: A Conflict of

Models.” Frank Dance’s paper “The Concept of Communication” published in

1970 in the Journal of Communication, provided a major step forward in defining

communication within 3 basic dimensions : level of observation, intentionality,

and judgment. Furthermore scholars have also begun to distinguish between

Eastern and Western traditions in defining communication. While “…Eastern

theories focus on wholeness and unity…” Western norm is to focus on the parts,

packets, essentially the fragmented portions of communication… “without

47

necessarily being overly concerned with the integration or unification of those parts”

[75]. Sarah Trenholm in her text “Thinking Through Communication: An

Introduction to the Study of Human Communication” proposes several practical

definitions. It is noteworthy to paraphrase these here : “a process of acting on

information”; “…a process through which we make sense out of the world and

share this sense with others…” ; “ a process in which a source transmits a

message to a receiver with conscious intent to affect the receivers behavior…” ;

“the transmission of information, ideas, emotions, skills, etc., by use of words,

symbols, pictures, figures, graphs, etc.” [118].

All of the above definitions play some role within the context of knowledge transfer,

for example it is critical when transferring tacit knowledge to be able to define the

background meaning of that knowledge. It is certainly not simple data and

information which one can argue is not even considered explicit, let alone tacit

knowledge. In order for us to make the connection between communication and

knowledge transfer we can consider three different models of understanding

regarding communication : Communication as action, interaction, and transaction.

In 1949 Charles Shannon from MIT and Bell Labs described communication as a

linear process comprised of several key elements : source, message, receiver,

channel and noise [118]. This linear action model takes a fairly narrow and

simplistic view in that it suggests that a person is only a sender or a receiver. It

does not fit our concept within the scope of knowledge transfer. In 1954 Wilbur

Schramm proposed that the relationship between sender and receiver be

considered. Certainly this is a step in the right direction regarding our concept with

knowledge transfer simply due to the fact that within a company one must take into

48

account the relationship between the parties involved in the transfer, along with the

protocols, processes, procedures, and norms depending on how the company is

structured, whether rigid or loose hierarchical, flat or cross-functional. This concept

of relationship was utilized in establishing portions of our survey. Schramm

proposed a circular interactional model of communication which emphasized

two-way interaction not seen in Shannon’s earlier linear model. An additional

important feature of this model that we are interested in is that it takes into account

a person’s field of experience or how a person’s culture, experiences, and heredity

influence that person’s ability to communicate [124]. This of course now ties in the

very important culture variable.

A similar concept is presented in Littlejohn and Foss’ text “Theories of Human

Communication” [75] which propose an interesting basic three-stage model of

inquiry as a starting point for understanding communication. According to the

authors “…the first stage is asking questions, …the second stage is observation,

…and the third stage is constructing answers” [75]. This parallels to some degree

Dance’s three basic dimensions of observation, intentionality, and judgment

mentioned earlier. Even though this may seem fairly straight-forward, the important

point that the researchers make is that inquiry is not linear but a circular,

interactional model similar to Schramm’s.

It is these ideas from basic communication theory that take us one step closer to

applying the concept to knowledge transfer, however, we are not there yet and

need to go even beyond both the linear and the circular models and consider a third

transactional communication model initially proposed by D.C. Barnlund in his

1970 paper : “A Transactional Model of Communication.” This model emphasizes

49

the simultaneous and continuous sending and receiving of messages in a

cooperative manner in which the sender and receiver are mutually responsible for

the effect and effectiveness of the communication. In the linear model meaning is

sent from one person to the other; in the circular model meaning is achieved thru

feedback; but in the transactional model the participants “build shared meaning”

[124]. This is directly related to our concept of successfully managing knowledge

transfer especially with tacit knowledge. The three basic models discussed here

are shown in Figure 2-1 below.

Figure 2-1 : Three Basic Models of Communication. ( These are variations by the author of Fig. 1.3, 1.4, and 1.5 in West and Turner [124] )

50

An additional factor to consider is the context or environment in which

communication takes place. This is situational and essentially has 6 levels :

Interpersonal, Small Group, Organizational, Intercultural, Public or Rhetorical,

and Mass. There is a wide range of research that has gone into each context

including relationship maintenance strategies, group decision-making,

organizational hierarchy and power, employee morale, culture and rule-setting,

ethnocentrism, to name just a few. Based on our dissertation’s scope we will

consider Interpersonal, Small Groups, Organizational, and Intercultural

communications.

Table 2-4a summarizes the mapping of the various communication theories

researched based on the holistic approach of Robert Craig’s work “Communication

Theory as a Field.” Craig divides the world of communication theory into the

following six traditions.

Semiotic – “…based on signs which can be considered stimuli designating some

other condition(s)… and symbols which usually designate complex signs and

where meaning arises from the relationship among an object, a person, and a

sign...” [75].

Phenomenological – “this tradition concentrates on the conscious experience of

the person ….and how individuals actively interpret their experiences and

come to understand their surroundings…” [75]. Stanley Deetz summarizes

the three basic principles of this tradition : “…knowledge is found directly in

conscious experience; meaning is based on potential, basically how we relate

to something or someone determines meaning for us; language is the vehicle

of meaning” [75]. It is worthy to note the indirect ties with the field of tacit

51

knowledge and its transfer, especially within the context of mutual language –

something that will be explored within our research.

Cybernetic – based on “…complex systems in which many interacting elements

influence one another” [75]; the idea of “system” and “networks” are central

themes to this particular tradition.

Sociopsychological – based on Western thought of the individual being the

central focus, including “social behavior, psychological variables, individual

effects, personality traits, and perceptions and cognition” [75]. Key questions

that can be established based on some of the key themes of the

Sociopsychological tradition are : (1) How can individual knowledge transfer

behavior be predicted ? (2) How does an individual take into account and

accommodate different knowledge transfer situations ? (3) How do

communicators adapt their behaviors to one another regarding the sharing of

knowledge ? (4) How is information assimilated, organized, and used in

ultimately deriving knowledge and leading to successful project strategies

and plans ? (5) How is information integrated to form beliefs and attitudes

affecting project success ? (6) How are expectations formed in interactions

with others primarily within international project teams ? These are

paraphrased based on the original text in Littlejohn and Foss’ “Theories of

Human Communication” [75].

Sociocultural – this tradition is culturally-centric and based on Eastern thought of

the Group being the central focus and “…how people together create the

realities of their social groups, organizations, and cultures” [75]. Research

here focuses on how identities are established thru the social group.

Needless to say this is a central theme of the Japanese culture.

52

Critical – based on the themes of privilege and power which are central to

hierarchical organizations. Concerned with the understanding of power

structures, beliefs, and ideologies, and how interests are served within these

structures. [75]

Table 2-4a below is originally constructed based on the general content structure

found in Littlejohn and Foss’ “Theories of Human Communication” [75]. It serves as

the starting point for our identification of potential gaps in past literature which we

need to address in our research.

53

54

We would like to better-define and refine our communication theory mapping and

identify which theories relate to our dissertation scope in the closest manner. The

first step in doing this is to eliminate the Semiotic, Phenomenological, and Critical

traditions since, based on our detailed review, they do not relate very directly to the

three areas of our theoretical construct, namely : (1) Knowledge Management /

Knowledge Transfer, (2) Project Management, and (3) Culture. Once this is done,

we also code the remaining theories based on their relationship to our three

construct areas and we obtain Table 2-4b shown below. This is an originally-

constructed table from 2-4a.

55

We next eliminate those remaining theories within the 3 remaining traditions that we

the

wn

could not directly associate with any of the three areas of our construct and maintain

those in which we could directly associate with KM / KT, Project Management, and

Culture. We also identify the major gaps in the remaining map, noting that these

seem to exist primarily in the Message and Communicator topic areas as well as

Culture section. All of which offer opportunities for research segments within our

framework from the communication topic point of view. The remaining map is sho

in Table 2-4c below. This is an originally-constructed table from 2-4b.

56

As a final refinement in our mapping, we replace the 3 tradition-identifying columns

(Cybernetic, Sociopsychological, Sociocultural) with the three constructs associated

to our framework / dissertation (KM / KT, PM, Culture) and align the theories we

associated closely with each construct (per the color coding) in rows across the 6

communication topic areas. By doing this we can identify more specifically which

relationships between our construct areas and the general areas of communication

theory still maintain a deficiency in terms of theoretical background. We therefore

can identify more specific focus areas of our research and further justify the overall

theoretical framework we created. This is an originally-constructed table from 2-4c.

57

This final Table 2-4d now exposes some key points. KM / KT can be related to

almost all of the 6 topic areas of communication. The only one in which we found

specific and direct communication theory relating to KM / KT was in the area of

Culture which we note with the Gap notation. In effect we have mapped nine

established communication theories linking the main communication topic are

Knowledge Transfer. We have also identified seven communication theories closely

linked to Project Management which address four out of six communication topic

areas. It is logical to see that the majority of these theories, four out of seven relat

closely to Group communications. It is interesting once again to see that there is

some deficiency in the area of Culture, but also in the area of Organizational

Communication. What this indicates, surprisingly, is that there is little direct

theoretical basis and research done on how Project Management fits betwee

Organization and also the culture of that organization – therefore PM, Organization

Culture, and National Culture is a logical research linkage we can pursue. This is

very interesting because it does present a focus on a key area of our research and

further justifies our theoretical construct which overall seeks to link Knowledge

Transfer with Project Success (PM) / International Engineering Team success

(Culture).

no

as with

e

n the

al

.3.2 Groups and Teams

ased on our dissertation focus on knowledge transfer and international

reas of

can

2

B

engineering team and project success we must consider research in the a

team and group communications since it has been stated that “…the key to

successful… groups is effective communication” [54]. Team communication

58

be defined for our purposes as “…..the transactional process of using symbolic

behavior to achieve shared meaning among members over a period of time…” [54].

In 2001 S.L. Tubbs published “A Systems Approach to Small Group Interaction” in

which certain characteristics of complex systems were applied to group interaction

and dynamics. The reason for his approach was the fact that communication within

groups is often disorderly, chaotic, discontinuous, and constantly evolving. Although

the research encompassed a general holistic view of group communications, it was

not focused on aspects of international engineering teams. The concepts developed

can be applied to our research as well but we feel that our work will go beyond and

focus on specific conditional interaction of specialized teams with subtle

communication patterns and characteristics.

One researcher which has considered group functioning within a multicultural

scope is John Oetzel and the development of his Effective Intercultural Work

Group Theory [as referenced in 75] He proposed 3 important cultural differences

Clusters : (1) individualism vs. collectivism – similar to the work of Hofstede in that

it considers and gages a culture’s tendency towards individualism vs. the group;

(2) self-construal - demonstrating “…how members think about themselves…”[75];

and (3) face concerns – “…how group members manage personal image…in terms

of self-face, other-face, and mutual-face…” [75] Oetzel realized that “…cultural

differences necessitate effective communication but also make it difficult” [75].

Unfortunately this dilemma is very much still evident today.

In relating a team’s or group’s role normative role within an overall organization, the

1969 work of E.H. Schein, “Process Consultation: Its Role in Organizational

Development” stands out. Schein researched the collective values of groups, how

59

these are formed, and how they relate and are prescribed by an organizational

culture or an underlying understanding of how groups are expected to operate. This

is interesting because it serves as a linking components of our research which does

consider the role of the organization and its overall structure.

Additional research on roles and there function in teams has been done by A.P

Hare, Griffin, Bales, Bochner, and others as referenced in Harris and Sherblom [54].

Overall the research in this area has been undertaken from a higher-level

perspective and what we propose in our dissertation is to apply some of the

concepts within a detailed extension of our framework of international engineering

project teams which seems to not have been researched to a great extent.

Table 2-5a below summarizes the overall mapping of group role behavior that has

been researched. This table is a modified version found in Harris and Sherblom [54].

This is presented here for 2 reasons : (1) so that we can present a more visual

approach in identifying key areas related to our research as done similarly with the

communication theory mapping above and furthermore integrating and

complimenting the mapping above in coming to a final “gap analysis” conclusion

that will be addressed by our research; and (2) presenting one possible ideal role

structure for teams which can be referenced by what we conclude within our

research in terms of what companies within our scope are doing and what they are

not doing in support of our conclusions.

Table 2-5a below is a modified version of Table 3.1 found in Harris and Sherblom’s Small Group and Team Communications [54]

60

As done previously with communication theory mapping we identify and code those

roles in Table 2-5a which directly contribute and relate to Knowledge Management

/ Knowledge Transfer, Project Management, and Culture. The same color coding

scheme is used. The resulting Table 2-5b highlights the relationship between our

three constructs and Group Task vs. Group Maintenance Roles. Table 2-5b is an

originally-constructed table from 2-5a.

61

Considering our refinement one step further, we can eliminate the Negative Roles /

Self-Oriented Behaviors column, focusing only on those characteristics we would

like to enforce and group these roles together while still maintaining them under

their respective column labeling. This is shown in Table 2-5c. What is made

immediately clear is the fact that the majority of Group Task Roles fall under a

Project Management and KM / KT orientation while the Group Maintenance Roles

are more oriented towards culture and maintaining a positive and efficient group

relationship. The benefit we can obtain from performing such visual mapping

62

manipulation is that the process can indicate some strong (and not so strong)

relationships based on previous research. It can also indicate a direction in which

current and / or future research can focus in order to optimize and establish some

reasonable and expected results. With the particular method of organization of

Table 2-5c, we can focus on particular roles within the Project Management portion

of the construct and its impact on the overall Group Tasking process, the Cultural

portion of the construct and its impact on the Group Maintenance portion while

noting and taking into account some dual characteristic of the KM / KT related roles

which fall under both, although primarily under Tasking. The key is that we establish

a relationship with key areas of our proposed theoretical construct and tied them

into previous research, specifically in areas where there either is a lack of a

complete theoretical basis or there are some “gaps.”

63

An additional area to note is the research done on group cohesiveness by Griffin

in 2005 and also noted in Harris and Sherblom [54]. It is worthy to note this

particular characteristic because it relates directly to one of research focal points,

namely the importance within the Japanese natural schema of behavior based both

on culture as well as the particular organization one belongs to. Cohesiveness is

essentially “…the extent to which members are loyal and committed to the

group…”[54], they identify with in various situations. One area that will be studied

within the researched proposed in this dissertation and which has not seen recent

research is that of groupthink as it manifests itself from excessive cohesiveness.

We will argue and propose a direct case study to demonstrate the real pitfalls

associated with this within the scope of our research.

2.3.3 International / Intercultural Communications

“The roots of the study of intercultural communication can be traced to the post -

World War II era when the United States came to dominate the world stage” [77].

In 1946 the Foreign Service Act was passed which established the Foreign Service

Institute (FSI). It was at the FSI that Edward Twitchell Hall initially pioneered his

systematic study of culture and communications [77].

According to Martin and Nakayama [77], there are three contemporary approaches

to studying intercultural communications : (1) the Social Science or Functionalist

approach, (2) the Interpretive approach, and (3) the Critical approach. Interestingly-

enough each approach differs in its theory integrating culture and communication.

The Social Science / Functionalist approach maintains that communication is

influenced by culture. The Interpretive approach theorizes that culture is created

64

and maintained by communication. The Critical approach states that culture is a site

of power struggles and communication is a medium for this.

William Gudykunst, a leading communications researcher added to the research

done by Hofstede regarding individualistic vs. collectivistic cultures. In his paper :

“A Model of Uncertainty Reduction in Intergroup Encounters” published in the

Journal of Language and Social Psychology in 1985, Gudykunst found that different

culture, depending on their orientation, will approach a communication encounter

either directly or indirectly with the desire to either “get-the-job-done” or establish an

initial relationship beforehand. Gudykunst later extended his theory to include the

element of anxiety by introducing his Anxiety Uncertainty Management Theory

which explains the role of anxiety and uncertainty in individuals’ communicating

across cultural lines [77].

Additional work in the culture / communication arena has been conducted by Stella

Ting-Toomey in 1985 and in 2005 with Gao, Trubisky, Yang, Kim, et al. in the

development of Face Negotiation Theory [77]. We content that this is an important

aspect we have seen within the scope of our research as well.

In the area of conversational strategies and cultural differences, Min-Sun Kim in her

work : “Cross-Cultural Comparisons of the Perceived Importance of Conversational

Constraints” published in 1994, and again in 2005 with “Culture-Based

Conversational Constraints Theory,” attempts to explain how and why people make

particular conversational choices. Similar studies have been conducted by Gallois,

Giles, Jones, et al., as referenced in Martin and Nakayama [77].

65

This is by no means an exhaustive listing on theories and research within this

particular area of communication. The key concept is the understanding that there

is no single theory which can be considered without limitation. All these works have

been useful in identifying variations in cultural patterns which manifest themselves

with communication but all are limited in some form or another. The reason for this

is the simple fact that the research lies across two very complex and huge areas of

study : Culture and Communication. There are many variables that simply cannot

be identified and many scholars increasingly believe that “…communication is

often more creative than predictable” [77]. Our research will focus on a particular

aspect of various theories as they apply to Knowledge transfer for which

communication is a tool, with the goal of establishing a relationship with project

management. Thus we limit our scope to these particular areas in which

interestingly-enough not much research has taken place. The key for us to utilize

those specific areas and concepts within the overall bodies of knowledge in Culture,

Communication, etc. and fit them into our construct to develop an innovative idea

within our scope.

2.3.4 Communications by Engineers

Elizabeth Varnes’ 1993 dissertation, “A Sociotechnical Approach to the Study of

Semiautonomous Work Group Communication in Technical Organizations” [121]

presented research done to understand how team members define effective group

communications. The research was undertaken using a socio-technical approach

examining the adequacy of the social system encompassing the teams, in relation

to the actual tasks that have to be performed and the technologies used to carry

66

out these tasks [121]. Varnes’ research is an extension of W.A. Pasmore’s 1988

work “Designing Effective Organizations: The Sociotechnical Systems Perspective”

Within this Sociotechnical approach Varnes’ found a need and desire of team

members to utilize more effective communication tools in order to improve their

technical work. This may not seem like such a profound finding however it directly

relates to our research within our particular scope. We will demonstrate that this

same desire is expressed by technical teams within our research scope and within

the industry under investigation in general, however few companies have taken up

the call to improve their communication tools and we will show that this does impact

overall performance. We content that this is extremely important in the area of

technical communications and specification management because of the

complicated nature of the project work under investigation.

In 2000 Myra Lynette Corrello published her dissertation “Communication and the

Engineering Profession : Perspectives from the Field” [24] in which she discusses

how “…engineers perceive the role of communication in their profession and how

the phenomenon of Communication Apprehension affects their perception” [24].

She contends that “…Engineers are increasingly expected to be both effective

engineers but also marketers and that communication is becoming increasingly

important in their daily work especially when technology tools are alleviating some

of the workload pressures on the technical side of their work…” [24]. Corrello

references eight formal studies conducted from 1974 thru 1996 investigating

communication within the engineering profession.

67

In 2005 Colleen Garside’s dissertation “A Qualitative Analysis of Verbal Interaction

in Mechanical Engineering Design Teams : Genres of Practice” [43] researched the

concept that “each community has its own cultural values… and these are linked to

judgments of situational appropriateness…and so does mechanical engineering as

a discipline, processes a cultural outlook on communication…” [43].

Garside’s research did take into account the specific discipline in which we are

interested in, however she approached her research from a daily work perspective

specific to Design Engineering Teams rather than large Industrial Project Teams

managed by a group / team of international engineers.

In reviewing the literature overall regarding Engineering communication we have

discovered several areas where we see some deficiencies and where we hope to

address these within the scope of our research. There has been very little research

done focusing on Project Engineering / Management and small technical /

engineering group communication. There are limitations in the research in the

areas of communication and engineering team-leadership and motivation; and in

the area of multinational engineering teams. We contend that these are

increasingly important areas especially as business is becoming global in nature

and, as Corrello correctly stated in her research, Engineers are being asked to

handle more and more non-engineering tasks. It is also important within our

context within the scope of project success and international team effectiveness.

68

2.4 Project Management

Along with Dr. John Saee, as outlined in his paper : “Best Practices in Project

Management in Contemporary Global Economy,” [102] we contend that there are

essentially three interacting forces involved when we discuss Project Management.

These are paraphrased here as : (1) the overwhelming global expansion and ever-

increasing flux of knowledge; (2) the growing demand for complex, sophisticated,

customized goods and services; and (3) the continued expansion of intense global

competition. [102]

According to Vladimir Mikheev and David Pells’ “The 3rd Wave – A New Management

Paradigm for Project and Program Management,” basic Project Management “…is

maturing in most industries including energy, oil & gas, petrochemicals, pharmaceuticals,

automotive, and certain heavy industries…” [81]. Unfortunately it’s not the case in the

machinery industry which relates to our research. Mikheev and Pells describe their

concept of the maturation of project management and related research. What they call

the 1st Wave occurred from the 1950s thru about 1980 and was based on much

development that was done for World War II and the computer age. This period was

strongly focused on process development and improvement.

The 2nd Wave took place in the 1980s thru the turn of the century, 2000 and focused on

people and the criticality of leadership to project success. A defining moment in this

development was PMI’s Project Management Body of Knowledge publication in 1987

and the initiation of the Project Management Professional Certification program. The 3rd

Wave according to Mikheev and Pells [81] began in 2000 and focuses on a strategic

69

global perspective, where organizations come to understand the value of Project

Management as a competitive resource that is closely tied to knowledge management.

2.4.1 Communicating Effective Project Management

The importance of communication in projects, in particular its influence on the

acceptance of change and something new is well-documented as outlined in Saee’s

paper “Best Practice in Project Management in Contemporary Global Economy” [102].

“Lack of communication has been cited as the biggest reason for project failures...” [102]

One of the key points in relating communication with project management and eventual

project success is what we refer to as “communication logistics” - quantity, quality, and

timing.

Diallo and Thuillier’s work published in 2004 – “The Success of International

Development Projects, Trust and Communication : An African Perspective” [33] as well

as Loosemore and Muslmani’s “Construction Project Management in the Persian Gulf :

Inter-Cultural Communications” [76] focus on the need to establish and maintain trust in

order to have effective communications and thus create a higher probability that a

project (in these case in Sub-Saharan Africa and the Middle East) will be successful.

Diallo and Thuillier specifically identified a strong correlation between the quality of

communication among members of the project team and success of a project within

their research scope. Muslmani and Loosemore integrated Hofstede’s dimensions and

analyzed actual communication patterns in the Arabic language; patterns which

demonstrate similarities to our research in the Japanese culture.

70

Further cultural and communication research related to Project Management and Project

Success has been published by Henrie [57]; Zwikael, Shimizu, and Globerson [129];

Jansen [63]; and Riemer and Jansen [97]. Riemer and Jansen incorporate so called

emotional intelligence (EQ) factors which are directly associated with cultural differences

which is part of our research focus. The key point to be made and expanded upon from

this research is that empathy, self-awareness, and intercultural awareness, unfortunately

are qualities which are lacking in many “global engineers” and something which must be

investigated within our particular research framework and scope. The 2007 text :

“Emotional Intelligence for Project Managers” by Anthony Mersino [80] , provides a

comprehensive overview of this particular topic. The only slight drawback with this

reference however is that it does not provide a rigorous quantitative approach to

establish any relationship with EQ and project success.

Moenaert, Caeldries, Lievens, and Wauters of the University of Ghent, Belgium

published a paper in 2000 titled “Communication Flows in International Product

Innovation Teams” [83] in which they identified 5 requirements that determine the

effectiveness and efficiency of communication in international product development

teams : transparency, knowledge codification, knowledge credibility, communication cost,

and secrecy [83]. This particular research does provides some good insight into the

relationship between knowledge, specifically the codification of knowledge, that is, the

process of structuring tacit into explicit, and success of international teams. It also

touches on the effects of organizational and national culture and the socio-cultural

qualities that every organization develops. The limitation of the research however is that

it focuses on European R&D-based companies and functions; whereas our research is

based on daily operational projects which are not considered R&D initiatives

71

2.4.2 The Successful Project

According to Dr. Lynn Crawford a long-time researcher in Project Management, the 1974

work of Murphy, Baker, and Fischer remains “…one of the most extensive and

authoritative research on the factors contributing to project success” [26]. They used

data from 650 aerospace and construction projects to identify 10 factors that strongly

related to perceived project success. They also identified 23 project manager

characteristics that were necessary for perceived success [86]. These are fairly heavily

focused on people and having the right team which can affect and ensure the right

processes and systems are integrated to the extent that a project will (most likely) be

successful. Furthermore, Crawford’s 2004 paper : “Senior Management Perceptions of

Project Management Competence” [27] in the International Journal of Project

Management focuses on the skills and competencies required of project management

leadership. Crawford lists 13 variables analyzed thru logistic regression analysis which

are associated with project success and project management top performers. Out of

these 13 variables, 4 relate either directly or indirectly to communication, and 5 relate to

organizational structure including impact by a parent organization [27]. This lends

support to our particular research framework.

In the 1980s several studies drew on and extended the work of Murphy, Baker and

Fischer, specifically those of Pinto and Slevin which used a sample of 418 PMI members

responding to questions asking them to rate the relevance to project implementation

success of ten critical success factors as previously identified by Murphy, Baker, and

Fischer. [26] , [91] The following factors where identified as critical by Pinto and Slevin

to the success of projects : Project Mission, Top Management Support, Project Plan,

Customer Consultation of Project Requirements, Recruitment, Selection, Training of

72

Project Personnel, Technical Tasks, Customer Agreement / Acceptance, Project

Monitoring / Feedback, Communication, Trouble-Shooter. They are documented based

on Crawford’s research papers [25], [26], [27], and Pinto et al [91].

Further significant research done with project management and project success in the

1990s include that of Ashley [6], Geddes [45], Jiang [65], Zimmerer [128], Whittaker

[125], and Clark [23] . However one of the key difficulties in this area of research

remains - how to reasonably quantify the concept of project success with a formalized

universal set of criteria that can be agreed upon by general group of practitioners. In

effect, project success however has maintained a definition based on a case-by-case

situational basis. It remains subjective. This particular issue has been addressed

recently by various researchers such as Rad, Koelmans, Altman, Dvir, and others. The

most recent study has been by Lee-Kelley and Sankey. "Global Virtual Teams for Value

Creation and Project Success : A Case Study" [72] They identify key factors affecting

success; they include “…time zone and cultural differences in particular, affect

communication and team relations…” [72]. The researchers also describe effects from

diverging management agendas, leadership styles (again related to culture), and role

uncertainty, something we feel also relates to culture as per the research conducted by

Hofstede. Although they touch upon communication, the research does not delve into

actual knowledge transfer and the communications structure as tool for this transfer.

Yu, Flett, and Bowers’ “Developing a Value-Centered Proposal for Assessing Project

Success” [127] propose a value-centered approach to measuring project success. They

develop and define two key concepts in their study : Net Project Execution Cost

(NPEC) and Net Product Operation Value (NPOV). Along with these they conclude 12

possible project outcomes based on the values of NPEC and NPOV and compare final

73

outcome to initial estimates. In their studies they do not directly take into account

knowledge transfer in any of their variables.

Other researchers including Dr. David Bryde’s work “Methods for Managing Different

Perspectives of Project Success” [16] have developed Key Performance Indicators

(KPI) to measure project success in this area, once again knowledge transfer is hardly

mentioned. A significant paper in the area of project functions and their impact to project

success has been written by Jha and Iyer "Critical Determinants of Project Coordination"

[64] for the International Journal of Project Management in 2005. They have outlined 20

important coordination activities that relate to project coordination and overall success.

They subsequently found that only 6 of these 20 factors were “statistically significant”

and of these only 2 were “very significant” [64]. A key area to focus on would be on how

knowledge transfer relates to these two activities that the researchers identified as

important : (1) estimation of optimum resources required; (2) agreement on detailed

methods of construction [64]. We feel (2) is of primary interest because it relates more

directly to the overall knowledge transfer function in terms of the industry we are

considering (complex machinery, assembly, setup, and start-up.

Dov Dvir and Aaron Shenhar, two key researchers in project management, have

collaborated on several occasions with Asher Tishler, Stanislav Lipovetsky, and others

to publish various works on quantifying project success. In 1998 they presented their

work - “In Search of Project Classification: A Non-Universal Approach to Project

Success Factors” [35] which concluded that the shortcomings of past research prior to

that time has been the tendency to try to provide a universal approach to quantifying

project success. They argue that project success determination is not universalistic and

74

there should not be such an all-encompassing approach. They employ a linear

discriminant analysis methodology in order to first classify projects and then determine

factors for success. In their study, they identify several managerial and organizational

variables, some of which relate directly to communication style, project control, and

reporting; in additional to technical requirements definition, technical and operational

specs and capacity to meet specs. These are the areas which knowledge transfer as a

whole is important although they do not take the actual knowledge transfer into account,

rather they focus on a multitude of factors. One very surprising aspects of their 1998

research is the conclusion that “learning capability” is only a weak predictor of success.

This would be contrary to what would be expected and it is mentioned as such in their

conclusion. They propose future research into this area. We feel that our research will

relate to this more directly.

A 2002 work from virtually the same research team of Shenhar, Tishler, Dvir, Lipovetsky

and Lechler, attempts to refine the previous research into project management success

by using a multivariate, typological approach with a strict statistical methodology in

identifying the key variables. "Refining the Search for Project Success Factors : A

Multivariate, Typological Approach." [108] They concede that still no conclusive

evidence or common agreement on project success / failure measurements exists and

they attempt to further refine their previous research with additional data and variable

identification. Unfortunately (or fortunately for our research) again there is no direct

investigation of the knowledge transfer and project success relationship. This is the crux

of our research.

75

2.5 Literature Review Summary & Research Potential

The research team of Dvir and Shenhar recently published their latest paper "Project

Management Research: The Challenge and Opportunity" [107] in the June 2007 edition

of the Project Management Journal, in which they identify key areas of future research

potential. This paper directs future studies of project management in several key areas

which we feel we are addressing with our research. One of these areas is the need to

provide integrative research into project management; that is, the challenge to combine

research from other disciplines. This is exactly what we are aiming to do, provide a

holistic approach utilizing research from Knowledge Management, knowledge

transfer utilizing communication methods and processes and combining these

with a cultural aspect of companies (both corporate and national) in order to

identify key success factors in project management. According to Dvir and Shenhar,

“…..this multidisciplinary approach represents a unique challenge to researchers….”

[107]. Essentially the “hole we are trying to fill” with our proposed research is that of

past research not integrating knowledge transfer processes and relating these to project

management success. In certain isolated cases, it has been attempted for IT projects

and but nothing further. In other cases, industrial projects have been considered but not

from a multinational company perspective. We focus on integrating these into a single

research target of multinational industrial companies, structuring their knowledge

transfer processes to provide the optimum probability of project success, once we

identify what constitutes project success within our scope.

As is readily apparent past research associated with the components of our current

research has been quit extensive, the problem is however this holistic approach (of

these components) that Dvir and Shenhar mention has not taken place within the

76

important areas we are considering. Based on our extensive literature review, we did not

find any specific research that integrated the components we require for our research

and within the scope study we are considering. This concept can be shown in Figure 2-2

which can be considered an interim precursor to our overall research framework.

Our research is based overall on a management problem; more specifically a technical

and engineering management problem since we focus on knowledge transfer of

engineering and industrial manufacturing projects. From a higher level point of view this

is an issue of how international companies with subsidiaries in the United States

manage their operations. This will involve research in international business which as a

discipline began to develop in the 1970s in conjunction with the expansion of

international business itself. Cross-culture management research, however, was very

limited throughout the 1970s and 1980s [15]. Only in the 1990s with continued

internationalization did interest and deeper research began to emerge and take shape.

Furthermore, according to Briscoe and Schuler [15] “…much of the published research

77

is based on an American perspective done by American or America-trained

researchers…research published by non-western scholars or in non-English sources

has gone virtually unnoticed…” [15], by both the academic and business world in the

United States.

As outlined in this chapter there has been significant research in project management

and what constitutes project success under various conditions. However there is no

agreement on a universal set of criteria for success. It remains subjective even after the

fundamental work of Murphy, Baker, and Fischer. Furthermore there seems to be no

significant and recent research of knowledge transfer associated with project

management success except some research in IT and civil projects. There seems to be

nothing on industrial machinery projects managed by multinational manufacturing

companies. Once again our focus is in this area because this industry is critical and

involved in practically every other type of heavy industrial, infrastructure, even

commercial segment. Also according to Henrie, “while project management literature

discusses and proposes that culture is an influence on projects, a clear theory of what

this influence is, is lacking” [57]. The area where there is a clear lack of research seems

to be in the communication structure between headquarters and subsidiary and how this

is utilized as a tool within the knowledge transfer function and how culture plays a role.

Our research will seek to realize these areas within a common framework of industrial

manufacturers and how they operate their business units / subsidiaries in the United

States and the effect this has on project success. Identifying the attributes of these

relationship for this success. Figure 2-3 provides a more refined graphical interpretation

of our research focus as developed over this chapter. This was established as an

original model for our research.

78

The significance of having the right people in Project Management roles is emphasized

by several researchers including Bresnen et al. [14] Their conclusion was to create a

key role, namely that of REM Regional Engineering Manager that would coordinate and

facilitate communication and knowledge transfer. In effect these “knowledge brokers”

would be the nodes in the communication structure of international project teams

hopefully improving the probability of project success. This is an interesting concept

because it identifies with one of our own models, namely the so-called one-to-one or

point-to-point structure (See Figure 2-4 below). Unfortunately the scope of Bresnen’s

79

research does not cover the particular parent subsidiary relationship which for us is a

central theme for which we have devised several higher tier communication structures

(in addition to Bresnen’s REM concept). Bresnen’s research most closely identifies with

our “point-to-point” model. Based on our research, we content that there are situations

where the other models must be considered as better optimized under certain conditions.

Figure 2-4 : Higher-Tier Knowledge Transfer Models for Parent-Subsidiary

Finally a core reference that was discovered within our research is Stock, Greis, and

Dibner’s 1996 research publication appearing in the IEEE Transactions of Engineering

Management, and titled “Parent-Subsidiary Communication in International

Biotechnology R&D” [114] This research has some close parallels to what we are

proposing, namely in the areas of parent-subsidiary communications between European

and Japanese multinational companies and their subsidiaries in the United States.

Stock, Greis, and Dibner’s research examines the flow of technical communication and

80

how this is transmitted to and from parent firms. The paper presents a close parallel also

to our own methodology and this is why it is mentioned here prior to the next chapter.

However, once again this previous research does not consider the important aspect of

knowledge transfer and more importantly the transfer of tacit knowledge into something

that can be usable at either location (parent or subsidiary) in improving the chances of

project success of international teams.

Based on our extensive literature review, we can confirm that the particular research

framework, under our defined scope, we have undertaken is in fact something which has

not been researched previously and can provide both scholarly and business benefits as

outlined in Chapter 1.

81

CHAPTER 3 – RESEARCH DESIGN and METHODOLOGY

The research was conducted with a survey instrument used to gather data on which a

correlational analytical methodology was utilized. “The correlational approach is effective

in determining whether, and to what extent, a relationship exists between 2 or more

quantifiable variables” [44]. The overall methodology was modeled after Dr. Vincent

Michel Ribiere’s research approach in a similar investigation conducted in 2000-2001. In

addition to this particular approach we researched and analyzed an actual detailed case

which is used as a specific illustrative example of the principles developed. The case

example content is located in Appendix D. Although our case example is used to

confirm some of our findings we realize that it does not, by any means, incorporate a full

confirmation of the theoretical construct established. This approach however is typically

considered as “…an appropriate methodology in an initial research effort that is intended

to develop some theoretical understanding…” [57]. This multi-method, or what is

referred to as triangulation has also been successfully utilized in research conducted

by Stock [114] and Jansen [63]. For our research this methodology was appropriate

and applicable since the intent was to establish an understanding of the relationship

between knowledge transfer attributes and international team project success.

3.1 Research Objectives – Hypotheses Mapping

The primary assumption going forward is that there is in fact a correlation among the

way foreign company expats and local representatives working in a subsidiary in the U.S.

and within an engineering and manufacturing function in our study population are

managed and the way communication flows between them and headquarters

(knowledge transfer). There does exist a relationship that can be identified and used to

82

model and describe a knowledge transfer function or process; and this can be related to

project success.

The research objectives as initially outlined in Chapter 1 are :

Establish what is the most meaningful concept of project success to the target

study companies. How do they measure success and what are the similarities in

measuring project success among them. Establish these common factors for

success that can then be used to further the investigation.

Identify specific knowledge transfer attributes and descriptive variables of

multinational industrial manufacturing companies with foreign headquarters and U.S.

subsidiaries involved in international projects (our target companies). Make a

preliminary judgment on how these attributes and descriptive variables are

related, if at all, to the company’s project management successes; what is important,

what is not important, etc.

Identify key correlations in knowledge transfer processes between the 3 culturally

diverse groups of companies that make up the majority of our target industrial

manufacturers (German, Italian, Japanese); identify communication attributes that

related to the companies’ corporate and national culture and how these establish a

tool link with the knowledge transfer function.

Establish a final correlated relationship between knowledge transfer factors and

project success; conclude a final relationship among the attributes and variables of

knowledge transfer and project success, and establish a conceptual model for this.

Our underlying hypothesis is that there exists a correlation between how knowledge

transfer takes place within our population and the success of the population companies’

international projects. Identifying the attributes of successful knowledge transfer,

identifying the attributes of project success and establishing a correlation or relationship

between the two is essentially the higher-level goal.

This is illustrated simply in Figure 3-1.

83

Figure 3-1 : Higher Level Research Objective

Knowledge Transfer

Attributes International Team / Project

Success Attributes

What is the Relationship ?

Based on this overall objective, the formal directional hypothesis is defined as :

H1 : There is a relationship between successful knowledge transfer between parent – subsidiary and organizational project success.

The overall null hypothesis of course is the logical opposite and defined as :

H0 : There is no a relationship between successful knowledge transfer between parent – subsidiary and organizational project success.

From this we begin the process of establishing the important sub hypotheses which

frame the research hypothesis. These sub hypotheses are integral to our overall

directional hypothesis above because of the various research - associated factors and

variables as demonstrated in the extensive Literature Review Section (Chapter 2). Here

we will establish a map between the objectives of the research and the established sub

hypotheses thus creating the foundation for our formal directional hypothesis defined

above. It should be noted that these relate to our target research population.

Sub hypotheses are broken down into three main groups (in addition to the

demographics portion) : (1) Headquarters and Subsidiary Communications; (2)

Headquarters and Subsidiary Knowledge Transfer and Corporate Culture; and (3)

Project Success Characteristics and Interpretation. This is the general structure of our

survey tool as well. This will be discussed further below.

84

Based on our Literature Review and the different attributes under consideration, we

anticipate that trust plays a crucial role in how communication channels within the

organization are structured. It is anticipated that these semi-formal channels in fact arise

and take shape from the daily communication “work” and interaction that takes place

both within the subsidiary and between subsidiary and parent headquarters. A key point

is that this communication, whether the daily interaction at the subsidiary or the more

formal communication structure between subsidiary and parent, in which we contend

that knowledge transfer takes place, is established with little to no consideration of the

communication concepts outlined in Chapter 2. However since these concepts create

the building blocks of this communication; and in turn the communication establishes the

conduits of knowledge transfer of which trust is of the utmost importance, and

furthermore, trust is in our opinion a key factor in morale; we hypothesize the following

sub hypotheses Cluster B :

HB1 : There is a positive relationship between the way technical communications are handled on a daily basis and trust

HB2 : There is a positive relationship between how technical communication channels are modeled between subsidiary and headquarters and trust

HB3 : There is a positive relationship between how technical communication channels are modeled between subsidiary and headquarters and establishing a truly shared meaning in succesful knowledge transfer .

Furthermore, we hypothesize that based on various demographic factors of the

organization, in fact the “best” model for knowledge transfer is the many-to-many

concept at the higher tier. This leads to :

HB4 : Organizations that implement a many -to-many technical communication channel model are more likely to establish and maintain a truly learning and trusting relationship

85

Utilizing the link to employee morale but within an operational framework in which

organizational structure and the relationship between subsidiary and parent

headquarters is considered, we anticipate a link between morale (at the subsidiary) with

the level of perceived satisfaction at headquarters. Here we must be careful to

emphasize that this is in fact a perception of satisfaction at headquarters. By

constructing the research from survey question to sub hypotheses in such a way we

focus on the attitudes and dispositions of the personnel at the subsidiary operation

something which we are emphasizing with this research. We are now in the position to

consider how this relates to project success. We contend two points : (1) that there

exists a relationship between the perception of headquarters satisfaction with its

subsidiary and project success, (i.e., if there is a multitude of successful projects that the

subsidiary has accomplished, then it would seem almost a given that perception would

be that headquarters has a high satisfaction rating of its subsidiary); (2) that there is a

strong positive relationship between subsidiary employee morale and project success;

once again this would seem intuitive. This rationale is outlined in sub hypothesis

Cluster E :

HE1 : There is a positive relationship between subsidiary employee morale and project success.

HE2 : There is a positive relationship between parent headquarters satisfaction and project success

HE3 : There is a positive relationship between parent headquarters satisfaction and subsidiary employee morale

If we consider once again our Literature Review in Chapter 2, we saw from a

communications point of view and from the discussion regarding Hofstede’s research

[58] that certain circumstances, scenarios, and situations, give rise to an internal /

86

innate need to understand personal position within an organization. We have seen this in

several references and past research. There is a propensity for individuals (some

cultures more than others in fact) for face to be maintained during interaction,

uncertainty to be avoided to some practical degree; we anticipate that these cultural

considerations in fact relate to the degree in which an employee has direct input into

decisions that affect him or her. Furthermore, from groups, teams, and technical

communication, as well as thru our project success literature review, we hypothesize

that there is a positive relationship between certain fairly structured operational

standards in handling projects, but within the appropriate level of communication

pertinent to each situation (basically understanding and allowing for the various

communication factors), and project success. This rationale outlined above regarding

employees’ abilities to have direct input to decisions, and the need for a structure

environment which would allow for a greater probability of project success, form 2

additional sub hypotheses shown here :

HD1 : There is a positive relationship between proactively conducting and managing a system for post-project reviews and lessons -learned meetings and project success.

HD2 : There is a positive relationship between employees having a direct input into decisions that affect them and project success.

It should be noted that HD2 stems directly from both E and B Clusters previously

mentioned, namely the discussion on personnel morale (directly from HE1) and our

contention that the many-to-many knowledge transfer model (HB3) is the optimum

structure for establishing true knowledge transfer and learning. This should be fairly

intuitive when we consider that HD2 deals with employees making their own decisions –

the morale issue; and employees establishing direct links to headquarters as opposed to

having single individual acting as “gate-keepers” in communication and knowledge

87

transfer between subsidiary and parent headquarters. We further contend that HD1 and

HD2 affect directly project success factors and measures as outlined in our subsequent

sub hypothesis shown here.

HD3 : Organizations focus on delivery and performance , more so than cost , recurring business, and knowledge -gain, as the key measures for project success.

The progression of the sub hypotheses development above thru Clusters B, D, and E

has enabled us to address our first research objective, namely to identify the most

meaningful concept of project success for our target population. In effect we contend

that delivery and performance is of the utmost importance, outweighing price and other

factors such as corporate learning.

As outlined previously, the key to knowledge transfer is establishing a shared meaning

primarily with trying to convey and transfer tacit knowledge. This was discussed in detail

by Nonaka and Takeuchi [87], as well as Davenport’s and Prusak [31]. Extending the

framework from our sub hypotheses Cluster B (HB3 and HB4) which hypothesizes the

relationship among communication channels, shared meaning , and our many-to-many

concept, we can derive a conceptual relationship and formulate a 4th Cluster C which

relates shared meaning and employees’ direct decision-making abilities, which relate to

an organization’s structure HC1 ; technology tools as a means of easing cooperation and

collaboration HC2, ; leading to the formulation of sub- hypothesis HC3 which we stipulate

a relationship between trust and successful knowledge transfer. This Cluster is mapped

to our second research objective discussing knowledge transfer attributes for which we

contend that trust is a primary attribute that unfortunately may be lacking as researched

in previous studies. We need to identify the relationship for our target population.

88

HC1 : There is a positive relationship between employees having a direct input into decisions that affect them and establishing a truly shared meaning in succesful knowledge transfer.

HC2 : There is a positive relationship between the availability of technology tools and a true spirit of cooperation / collaboration between subsidiary and headquarters .

HC3 : There is a positive relationship between trust and knowledge transfer that occurs in both directions between headquarters and subsidiary .

Finally, we must consider the demographic data which we obtained and outline how

specific characteristics of an organization, its structure, that is, how rigidly hierarchical it

is, or not, its size, maturity (age), as well as how many expats are working in the

organization and what is their level of project management experience; all these factors

should be taken into account and related to our third research objective which considers

attributes and variables regarding corporate culture and structure. It should be noted

also that from a national culture point of view we will be considering these sub

hypotheses individually as well; that is individually within the framework of America,

German, Italian, and Japanese companies. Any similarities will be noted and any

differences will be examined in detail. This, along with our entire data set will be

presented and analyzed in the next chapter. Below is Cluster A relating to demographics.

The input into Cluster A is a logical extension of Cluster B primarily dealing with

communications. Figure 3-2 shows the Cluster Inter-Relationships leading to the

research objectives and Figure 3-3 shows the actual sub hypotheses.

HA1 : There is a positive relationship between the size of the subsidiary and headquarters and how technical communication channels are modeled

HA2 : There is a positive relationship between the age of the subsidiary and headquarters and how technical communication channels are modeled

89

HA3 : There is a positive relationship between organizational culture and structure and establishing a truly shared meaning in succesful knowledge transfer

HA4 : There is a positive relationship between the number of expats in the subsidiary and establishing a truly shared meaning in succesful knowledge transfer

90

91

3.2 Method

In following a correlational approach, we model our analysis in a similar way as Vincent

Michel Ribiere’s 2000-2001 research [96]. This methodology, as previously utilized by

Gay, “attempts to determine whether, and to what degree, a relationship exists between

two or more quantifiable variables…prediction of some outcome or hypothesis

confirmation is based on a strong relationship between the variables…” [44]. Based on

our conceptual framework shown in Chapter 1 Figure 1-2, we establish the following

relationships :

Per our Literature Review and our Research Structure we define the following moving

forward :

Corporate Culture Independent Variables / Attributes. Parent – Dependent vs. Independent, Parent – Integrated vs. Non-Integrated, Hierarchically Rigid vs. Loose, Democratic vs. Autocratic, Trusting vs. Holdback, Degree of Social and Cultural Empathy to Parent

National Culture Independent Variables / Attributes.

Hofstede [58] Set : Power Distance, Individualism vs. Collectivism, Masculinity / Femininity, Uncertainty Avoidance, Long / Short-Term Orientation, Trust, Degree of Ethnocentrism

92

Basic Communication Theory Independent Variables / Attributes. Modified Hall [51] Set : Transmission = f (Speed, Context, Space, Time, Flow, Sequence) ; Absorption, Trust

International Communication Independent Variables / Attributes.

Language, Degree of Technology Usage, Time Lag & Time Difference, Degree of Feedback, Degree of Integration into both Parent and Subsidiary Strategic Initiative

Groups & Teams Communication Independent Variables / Attributes.

Individualism vs. Collectivism, Degree of Self-Construal & Face-Concern (in relation to Role Behavior Characteristics of Teams, See Table 2-5c), Trust

Project Success Dependent Variables / Attributes.

Delivery, Budget, Technical Performance, Market-Share Expansion / Growth, Employee Morale, Knowledge-Gained / Lessons-Learned.

3.3 Population

The survey instrument distribution population will be world-wide gear and machinery

manufacturers, consultants, and academic personnel associated with our target industry,

including those international manufacturers having operations in the United States.

Table 3-1 provides a summary of the target population overall available pool / potential.

The target population was identified thru several means including personal experience

and associations in the industry for 15 years as well as the well-documented AGMA

(American Gear Manufacturers Association) 2007 Members Directory utilizing the proper

industrial and geographical categories and filtering . It should be noted that this directory

is international and not limited to specifically - American gear manufacturers. A

comprehensive list of the entire detailed potential survey distribution population pool is

located in Appendix G for reference. This pool contains approximately 870 specifically-

identified individuals which make up the greater available potential population.

93

The survey will be addressed to specific individuals; it will not be distributed “blindly.”

We refined this overall list of 870 or so and targeted a specific population of 168

individuals which fit our particular job classification criteria and fit the scope of the

research in terms of specific function within the overall industrial gear industry. This was

verified to a great extent by initial contact via telephone. We avoided a “shotgun”

approach to the survey and focused on a tightly targeted group of Project Managers /

Engineers, Application Managers / Engineers, Product Managers / Engineers, Sales

Managers or Engineer, Purchasing Managers / Engineer, Design Managers / Engineers,

R&D Managers or Engineers.

These specific job classifications were established based on our experience in the

industry of corporate structure in terms of what personnel is involved in large scale

projects such as those within our scope. It is these individuals holding these positions

that also maintain communications channels to and from parent and subsidiary. In the

possible case that the company is fairly small and such communications are handled at

a higher executive level, as is the case sometimes, we left an open-ended question in

terms of job-title position. We did not restrict our study to any particular organizational

size, history, or whether public or private. We did focus on those particular companies

dealing with large-scale projects within our scope and with national orientations we are

researching, in particular : American / Canadian, German, Swiss, Italian, Japanese; and

secondary : Other European and Other Asian.

94

Table 3-1 : Overall Population Potential Target Pool Job Function / Position of Potential Respondents

Sector

Location Potential

DestinationsPotential

Respondents

1

2

3

4

5

6

7

8

USA and Canada

110 ~ 400

Europe, East & West

36 ~ 160

Asia Including Australia & India

43 ~ 170

Industry

and Corporate

Other 14 ~ 20 203 750

USA and Canada

29 ~ 70

Europe, East & West

2 ~ 5

Asia Including Australia & India

3 ~ 5

Consulting

Other 2 ~ 2

36 82

USA and Canada

10 ~ 12

Europe, East & West

6 ~ 19

Asia Including Australia & India

6 ~ 8

Academic

Other 2 ~ 2

24 41

Job Function Codes 1 = Project Manager or Engineer 2 = Application Manger or Engineer 3 = Product Manager or Engineer 4 = Sales Manager or Engineer 5 = Purchasing Manager or Engineer 6 = Design Manager or Designer 7 = R&D Manager or Engineer 8 = Other (to be specified in the survey)

95

As mentioned previously we refined our target population to 168 individuals from the

870+ available pool / potential. This refinement was based on a 2nd phase confirmation

of updated information from the AGMA web site (see figure 3-4) and a more in-depth

investigation of specific target companies dealing directly and primarily within our scope

as one of their core businesses and /or job functions. We feel that by doing this we have

significantly improved both survey response levels and data quality. The specific target

population is shown in abbreviated format in Table 3-2 and listed by ID#, company and

operations locations only. Names of individuals which the survey was sent to, are

omitted in order to maintain anonymity. This final list makes up our single-stage

sampling population.

Figure 3-4 American Gear Manufacturers Association Web Site www.agma.org ( used with permission from AGMA )

96

97 97

3.4 Instrument / Cross-Cultural Survey Research Design

The research instrument utilized consists of a self-administered questionnaire designed

and optimized to collect our required data. The questionnaire or survey is the preferred

type of data collection instrument for our particular research because it provided for an

economical and fast way for obtaining our data. This is true especially since data was

required from international sources outside the United States.

Our survey was cross-sectional and based on the well-known Tailored Design Method

a four-phase administration process outlined in Dr. Don Dillman’s text : Mail and Internet

Surveys: The Tailored Design Method [34]. Essentially the methodology focuses on

carefully constructed and repetitive communications emphasizing a survey’s usefulness

and the importance of a response from each person in the sample. This is done thru a

structured procedure of continued communication with the target group and as much on

an individual basis as possible emphasizing “…survey response as a sort of social

intellectual exchange…” [34]. And according to Dillman this approach has the goal of

“…minimizing survey error which typically takes the form of sampling, coverage,

measurement, and nonresponsive errors respectively” [34].

Of particular importance in this survey is the fact that the research will be focusing on

manufacturers in various countries but primarily from Japan, Italy, Germany and to some

extent Switzerland. We realize that conducting surveys is a rather difficult endeavor and

conducting international surveys makes things even more complicated, however, based

on the Tailored Design Method discussed above as well as guidelines and procedures

presented in the foremost text on international surveys : Cross-Cultural Survey Methods,

98

by Dr. Janet Harkness, Dr. Fons Van de Vijver, and Dr. Peter Mohler [52] , we were

able to obtain an excellent return rate of 41%.

It should also be noted that the survey was designed in such as way as to obtain

additional data for future expanded research. The questionnaire, as will be discussed

below, was designed solely for this research but also provides data for further research

namely in analyzing in greater detail attitudes of respondents vs. actual organization

processes and systems. It collects data of what is actually being done in organizations

but it also collects data on what personnel feel is important on how things should be

done. Some of this data will be analyzed and used in support of our specific hypotheses

but it will also be available for future research. The questionnaire was purposely and

specifically designed in such a manner.

In addition to utilizing the Tailored Design Methodology, two additional key actions

were taken to further confirm an optimum understanding and response to the

questionnaire : (1) establish one “universal” survey in which all necessary translations

are immediately available on the instrument itself; and (2) conduct a preliminary pilot

survey so that questions can be better- finalized and clarified. These key points along

with all additional guidelines related to the survey are discussed in further detail below.

3.4.1 Basic Principles and Best Practices

There are 3 basic techniques for collecting primary data : survey research, direct

measurement, and observation [95]. “Survey research provides a proven

methodology for determining information with a known accuracy-level about a larger

99

population” [95]. Furthermore, there are essentially 5 general methods in collecting

survey data : mailings, web-based, telephone, in-person interviews, and intercept.

Our primary and initial distribution method was a mass-mailing of a printed survey

questionnaire followed by several timed email follow-up contacts. The advantages

of this methodology are numerous, including cost savings, convenience, timing,

anonymity, reduced interviewer-induced bias, and the opportunity for visual

enhancement to clarify any complexities. In developing the questionnaire, we

maintained a focus on objectivity, avoiding leading and loaded questions and kept

an eye on potential built-in assumptions. We tried to keep questions and

expressions simple, direct, and as familiar as possible and practical and

maintaining a specificity in the nature of the questions, that’s is asking precise

questions.

“One of the most popular ways of asking a subjective question is to use ratings

scales, that is a single, well-defined continuum in which the answer is expected to

be placed” [62]. For our survey we utilized a 9-position or category Likert Scale

shown in Figure 3-5 below. “Although…scales can include 12 categories or more, it

is preferable to use between 5 and 9 categories” [62]. Furthermore, various

research shows that “…scales intended to measure bipolar concepts should use

negative - to - positive values…” [62], preferably labeling only the extreme values

and the mid-point. This is what we used as a governing guideline in our scaling.

100

Three key areas need to be considered in survey design : question wording,

question coding, and survey appearance including flow. During the overall

development of the survey, from textural, structural, and visual points of view the

following guidelines below were applied. These are found in various forms in

several references [95], [62], [28], [34], [99] but we primarily utilized Harkness,

Van de Vijver, Mohler [52] with some slight modifications. These are considered

survey / questionnaire best practices and good design principles to be used to

minimize bias. The list below is primarily from Harkness, Van de Vijver, and

Mohler’s “Cross Cultural Survey Methods” [52] with some modifications by the

author.

Introduce the study in a cover page with a simple and clear explanation of purpose

Provide simple and complete instructions located where they are needed and visually distinguish them as instructions

Utilize appropriate spacing, alignment, color coding, fonts, emphasis, and visual queues

Utilize sequential and consistent numbering throughout

Group questions into fairly logical sections with similar qualities and relevance

Make choices that are mutually exclusive to maximize accuracy

Short, simple sentences with 25 or less words each

Use active rather than passive voice

Repeat nouns instead of using pronouns

Avoid metaphors and colloquialisms

Avoid the subjective which may introduce bias

Avoid negative or double negative expressions

Provide context where required for key items

Provide redundancy for key items

Avoid possessive forms

Use specific rather than general terms

Avoid terms leading to vagueness (such as probably, maybe, perhaps)

101

3.4.2 Pilot Study Program

In order for us to confirm that we did in fact have an optimized survey tool for our

research, we conducted a two-phased pilot study which culminated into the final

questionnaire that was actually used in the data gathering and which is also

documented in Appendix B. The pre-testing of the questionnaire was conducted

using the conventional method approach in which respondents are given the

opportunity to complete the survey followed by a structured interview session.

Phase 1 of the pilot study / survey was conducted on Monday and Tuesday, Nov.

5th and 6th 2007 with various respondents from Sumitomo Drive Technologies; a

Japanese heavy machinery manufacturer located in Virginia, United States. In

addition, the preliminary survey was also provided to mG miniGears Inc., an Italian

precision gear component manufacturer in Virginia, USA, and Stihl Inc. a German

company who is not directly involved in the gear industry, but does utilize geared

parts and machinery. It was hypothesized that the technical nature of this German

manufacturer (Stihl Inc.) and the fact that we discussed our questionnaire with

German Engineers working at its plant in Virginia, will nevertheless assist us in our

survey finalization. The pilot survey was given to 10 individuals (between the 3

companies) with the following job titles : Project Manager, Senior Project Manager,

Application Engineer, Product Engineer, Sales Engineer, VP of Sales, After-Market

Coordinator. In this round, we tested our survey questions primarily in English as

well as the initial translations into Italian, German, and Japanese languages. The

thought was that the respective non-American technical personnel would provide

input into our translations.

102

From Phase 1 we identified some poorly-phrased questions – some that where

unclear and somewhat difficult to understand exactly what was being asked. We

focused on improving both questionnaire quality and comprehensiveness since in

fact we did miss a very important question in the initial pre-test, namely asking the

respondent to identify their company’s overall successful project percentage. This

fundamental question was in fact inadvertently omitted initially but was identified by

the Phase 1 pre-test process. Phase 1 also tested questionnaire acceptability in

terms of length of the survey, privacy, ethical, and moral issues and standards.

There were no findings or concerns in these areas.

Phase 2 of the pilot study program was initiated after the basic Phase 1

modifications were completed. The basic concept of Phase 2 was to utilize

respondents outside of the United States who would bear a reasonable

resemblance to our population for the purpose of identifying any unique reading,

translation, question clarity, and assumption issues. Phase 2 involved actual on-

site visits to 6 target machinery companies in Switzerland and Germany between

Nov. 14 ~ 22, 2007. Manufacturers and project Managers in Oerlikon, Wil, Uzwil,

and Winterthur, Switzerland (near Zurich), as well as in Friedrichshafen (Germany)

were given our refined survey and interviewed. In this final Phase 2 of the pilot

study the final translations were confirmed and we were provided with some useful

information for improving our questions – hypotheses links.

Between Phase 1 and Phase 2 of the pilot study, we confirmed our research

instrument using 9 companies (3 in the U.S., 6 abroad) and 24 individuals (10 in the

U.S., 12 abroad) who we feel closely represented our target population. These

individuals were not utilized again for the actual survey but others in their

103

organizations were, with the exception of Stihl Inc. which we determined to omit out

completely due to its non-exact organizational match to our scope. The overall pilot

study program / protocol is outlined in Figure 3-6. A modified version of Iarossi’s

[62] methodology was used.

Figure 3-6 : Pilot Program / Protocol Considerations ( Modified version of Box 3.1 in Giuseppe Iarossi’s “The Power of Survey Design” [62] )

104

3.4.3 Cross-Cultural Survey Limitations & Difficulties

In addition to what has been mentioned previously regarding survey research, best-

practices, guidelines and structure required in order to obtain usable data; there is

another aspect to our research that makes the survey process somewhat more

difficult specifically in this case. The fact that the survey will be sent internationally

to recipients in Japan, Germany, Italy, Switzerland, and other European and Asian

countries establishes this as a cross-cultural type survey inherent with its own

difficulties revolving around language, translation, and actual meaning.

Cross-national or cross-cultural type research comes at somewhat of a price. It can

be expensive and time-consuming if not managed correctly. It can be difficult to

carry-out and may raise more questions than answers [52]. However there is a real

and increasing need to expand cross-national or cross-cultural research simply due

to the fact that the world is getting smaller. Globalization, internationalization, global

trade, global practices, standards, and procedures are increasingly becoming the

norm. All these are impacting different countries and cultures throughout the world

and the fact is that we must consider expanding our horizons in terms of

understanding and empathy to other cultures. The need for more cross-cultural

research can be found throughout the research literature. It is no loner feasible to

considering everything from a Western frame of reference.

According to Harkness, Van de Vijner, and Mohler “…the most commonly adopted

approach in conducting culturally-comparative research is to decide on a survey

design and to replicate / implement this as best as possible in each of the

populations involved in the project” [52]. And, this is in fact what we did within our

105

research methodology. The key objective in doing this however is to ensure that we

maintain a “ask-the-same question” (ASQ) approach when replication does take

place. What this means is to make sure that our translation is not so much a literal

translation or transliteration of the words as opposed to conveying actual meaning

and being able to effectively maintain equivalence across the different cultural

groups in terms of concept (conceptual equivalence) as well as measurement and

scalar equivalence during analysis. “What this scalar equivalence means is

essentially that a well-translated indicator (question) can still generate certain non-

equivalent response patterns from different cultures” [52].

According to Harkness, Van de Vijner, and Mohler [52], when developing new

material in cross-cultural surveys there are 3 structural approaches in questionnaire

design : sequential, parallel, and simultaneous. As one can infer the most common

approach is sequential, that is, the source questionnaire is developed and then

“adapted to another culture” by translation. This is the approach we took. The

difficulty once again is to make sure that there is equivalence and the ASQ

approach is maintained most importantly from a meaning point of view. How we

overcame this difficulty is to implement an iterative translation process utilizing

professional translators in tune and knowledgeable with the technical jargon used.

This was done with all 3 of our languages – Japanese, Italian, and German (other

than English). The advantage of this approach is the potential to develop high

cultural context suitability within the survey thus leading to a decrease in potential

concept inadequacy or bias and in effect creating a “good” tool for the research.

The disadvantages to this methodology however, according to Harkness, Van de

Vijner, and Mohler are high development costs and potential for cross-cultural

suitability not being optimized if the survey tool is not pre-tested. [52] As a matter

106

of fact however, our survey development process took these potential pitfalls into

account.

A translated question must ask the same question as the original source question

(English) both linguistically and pragmatically; essentially we must consider….is the

concept we are trying to convey thru our question the same for the different cultures

we are interested in ?

Several strategies were utilized in order for us to assure that our translations were

adequate :

Professional translators were utilized whose native language

was the language we were seeking.

Independent translation reviewers were utilized to check the initial

translation and for the most part these reviewers were engineers and

deeply knowledge about the concepts we were trying to convey.

In addition to the initial professional translators, the reviewers

themselves maintained the target language as their native language.

Translators had direct contact with the researcher so that an iterative

process of shared meaning could be established during the translation

process. Thus translations were fully integral to the development

process and never an afterthought.

Finally, a rigorous Two-Phased Pilot Study and pre-test were utilized

with independent target language speakers most of which were also

engineers and familiar with our concepts and which enabled a “3rd filter

pass” in terms of language translation and fine-tuning.

Based on the above points, we feel confident that our translated cross-cultural

survey is in fact more than adequate and suitable for our research.

107

From a structural layout point of view we originally considered having all 3

translations for each question in the immediate vicinity of that question, this is

what is sometimes referred to as the EU Metrics model. However we soon

discovered that this would not be very practical and became increasingly

unwieldy and cluttered our overall format.

In keeping with our objective of maintaining only one survey instead of multiple

translated versions being sent-out independently, we decide to construct a

single questionnaire with 4 main sections identifying the 4 languages : English,

German, Japanese, and Italian. The recipient can receive the survey and

quickly go to the section they feel most comfortable in to proceed with the

questions. If for some reason there may be an issue in interpretation due to

translation, the recipient can always refer to another section to read the same

question in another language and perhaps obtain a better understanding of

what is being asked, if needed. Finally Likert Scales and other non-verbal

visual guides were consistently used in an effort to provide an optimum

instrument across all language sections. The final survey instrument is fully

documented in its entirety in Appendix B. Figure 3-7 demonstrates some of

the concepts described. It shows the first, introductory / instruction page of the

survey.

108

Figure 3-7 : Survey Instrument Front Cover / Instructions Page

109

3.4.4 Final Question Development and Mapping

“Two basic rules make good questions : Relevance and Accuracy. Relevance is

achieved when the questionnaire designer is familiar with the questions, knows

exactly each question’s objective(s), and the type of information needed” [62].

While accuracy relates to “…the collection of the information in a reliable and valid

manner” [62]. Furthermore, and based on Dr. Don Dillman’s [34] approach some

general criteria should considered in assessing survey questions, such as : Does

the question require an answer ? To what extent do survey recipients already have

an accurate, and ready answer for the question being asked ? Is the respondent

willing to reveal the requested information ? Will the respondent feel motivated to

answer each question ?

In addition to the front multi-translated cover page providing the introduction and

instructions, and shown in previous Figure 3-7, the research questionnaire consists

of 5 main sections :

A. Basic Information – incorporating the survey respondents job position,

experience, the company situation, ownership, structure, size, and other

various demographics

B. Headquarters and Subsidiary Communication – this portion surveys the basic

communication situation at the subsidiary.

C. Headquarters and Subsidiary Knowledge Transfer and Corporate Culture –

this portion surveys the situation, attitudes, trust issues, relating to knowledge

transfer between the subsidiary and the headquarters parent company.

D. What is Project Success ? – this portion of the survey solicits the respondents

input on project success as they may define it as well as how their company

usually defines it.

110

E. Project Success at Your Company – this portion of the questionnaire solicits a

value percentage of some key project characteristics and employee morale

levels both at the subsidiary and headquarters.

Dr. Linda Henderson’s paper : “Encoding and Decoding Communication

Competencies in Project Management – an Exploratory Study,” [56] served as a

central reference in establishing the survey questions primarily in Section B :

Headquarters and Subsidiary Communications; and Section D : What is Project

Success ? of our survey instrument. A good number of our questions are

modified constructs based on Dr. Henderson’s questions on communicator

competence, team satisfaction, team effectiveness and productivity. Questionnaire

Section B also utilized modified versions of questions developed by Gregory N.

Stock, Noel Greis, and Mark Dibner’s : “Parent-Subsidiary Communication in

International Biotechnology R&D.” [114] In addition some question development

utilized Manuel Sosa, Steven Eppinger, Michael Pich, et.al : “Factors That

Influence Technical Communication in Distributed Product Development: An

Empirical Study in the Telecommunications Industry.” [112] For the most part

questions in Sections C : Headquarters and Subsidiary Knowledge Transfer and

Corporate Culture and to a lesser extent, Section D : What is Project Success ?

were developed from Dr. Jan Terje Karlsen’s and Petter Gottschalk’s 2003

research : “An Empirical Evaluation of Knowledge Transfer Mechanisms for IT

Projects.” [67] Further references to our questions can be found also in Karlsen’s

and Gottschalk’s 2004 paper : “Factors Affecting Knowledge Transfer in IT

Projects.” [68]

111

Table 3-3 below summarizes each of the major questions in the survey noting

factors such as relevance, accuracy, related variables, question objective(s), link to

hypotheses, and references.

112

113

114

115 115

Figure 3-8 shows the overall mapping from past research referenced in basic question

development, to actual questionnaire questions (shown numerically), to our research

objectives and hypotheses, and finally linked to our original conceptual model framework.

116

3.5 Validation & Reliability

Within our research context and specifically with our survey instrument, validation refers

to the steps required to ensure that we measure what we need to measure; that our

methodology meets the requirements and objectives of the research. Validation is

evolutionary and iterative to a point where final verification can occur. For our research

as a whole a portion of the validation process occurs thru the in-depth literature review

process. This is due to the fact that the first step in the validation process is to determine

actual requirements of the research. This occurs in part based on what has been

researched prior and where the research gaps exist. Following this thorough Literature

Review as outlined in Chapter 2, part of our validation process throughout this evolution,

occurred in monthly follow-up meetings with our local GWU advisor, Dr. Frank Allario.

Additionally there were several meetings with the entire group of advisors and

dissertation directors : Dr. Thomas Mazzuchi, and Dr. Shahram Sarkani, in addition to Dr.

Allario.

A fairly general definition of reliability is - the probability that something such as a system,

product, process, etc., will accomplish its designated purpose satisfactorily. In relation to

our research and in the survey instrument in particular, reliability can refer to “…the

accuracy and precision of a data collection procedure” [96].

In addition to the comments made in the immediate previous sections regarding the

survey instrument, questions were validated based on their use in part or in whole in

previous research. This is outlined in Section 3.4.4. where question mapping is shown.

Questions were finalized for our particular population in a Two-Phase Pilot Study : (1)

an initial pre-test was conducted utilizing 3 local international manufacturers : Sumitomo

117

Drive Technologies (Japanese), Stihl Inc. (German), and mG miniGears (Italian); this

was done on from November 5th and 6th 2007; (2) to obtain a more refined instrument

and process, from November 14th – 22nd 2007, the survey was provided to several

manufacturers in Switzerland and Germany, along with conducting follow-up interviews.

Thru this refinement process of taking questions which had previously been utilized and

validated, and refining them to specific target population; we feel that validation was

assured. Table 3-4 shows the overall timeline for data collection.

Table 3-4 : Data Collection Timeline

1. Potential Gross Population Pool Identified : August 2007

2. Refinement to Actual Target Survey Population : September 2007

3. Pre-Test Pilot Study Phase 1 : ( 3 Local Companies : German, Italian, Japanese )

November 5th – 6th 2007

4. Pretest Pilot Study Phase 2 : ( 6 Companies in Switzerland )

November 14th – 22nd 2007

Tailored Design Method A ~ D Our Research Timeline Misc Notes

A 1st Contact Prenotice Letter

January 30th – 31st 2008 Utilized email only, not hardcopy letter.

B 2nd Contact Cover Letter & Survey

February 5th 2008

February 8th 2008

February 15th 2008

February 19th 2008 February 22nd 2008

Hardcopies via post :

133 surveys sent out

16 additional surveys sent out

2 additional contacts identified, surveys sent out (internationally)

17 final surveys distributed (locally)

C 3rd Contact Thank You & Reminder

February 17th – 22nd 2008 Utilized email only; attached replacement survey

D 4th Contact Letter & Replacement Survey

February 27th – 29th 2008 Utilized email only; attached replacement survey

5. Last survey ( #69 ) received from Japan March 30th 2008 ( approx. 1 month after deadline)

118

3.6 Analysis Approach

The general approach for this research will be that of a correlation analytical

methodology applied to data obtained from a survey instrument. This approach is

effective “…in determining whether, and to what extent, a relationship exists between 2

or more quantifiable variables” [44]. Prediction of outcome or hypothesis confirmation

will be based on a strong relationship between the variables and will utilize ANOVA.

Microsoft Excel® and MiniTab® will be software that will be utilized.

Furthermore we researched and analyzed an actual detailed case which is used as a

specific illustrative example of the principles developed. The case example content is

located in Appendix D. Although our case example is used to confirm some of our

findings we realize that it does not incorporate a full confirmation of the theoretical

construct established. This approach however is typically considered as “…an

appropriate methodology in an initial research effort that is intended to develop some

theoretical understanding” [57]. This multi-method, or what is referred to as

triangulation has also been successfully utilized in research conducted by Stock [14]

and Jansen [63]. For our research this methodology was appropriate and applicable

since the intent was to establish an understanding of the relationship between

knowledge transfer attributes and international team project success. The case evolved

around an organization faced with an actual problem related directly to the scope and

concepts addressed in our research. Since the case is currently still in progress and

involves some legal issues we would like to note that the information in Appendix D has

been edited to some extent.

The purpose of sampling thru our survey instrument is to be able to correctly make

certain generalizations about our population. We will estimate a true mean and standard

119

deviation of our overall population by analyzing the probability of our sample’s likelihood

of approximating the true sample mean. Sampling and survey response qualifications

will be conducted thru response bias and basic wave analysis. Actual sample size will be

determined and confirmed using internal scale variable analysis. Sampling frames will

be evaluated for appropriateness but, we are considering a simple random sampling

approach which we feel will give us adequate representation within the entire population.

Descriptive statistics will be utilized on dependent and independent variables quantified

thru the survey instrument, where appropriate. This analysis will include quantifying and

selecting the most appropriate measure of central tendency such as mode, median, and

arithmetic mean; and the relationship to skewness. This appropriate selection is required

when these measures are relatively close to each other which we suspect. Due to the

utilization of our Likert Scale, scaled frequency distributions and factor analysis will be

considered and analyzed under appropriate situations. Additionally, measures of

dispersion such as range and standard deviation will be commonly applied techniques

to the data.

Going beyond the fundamental descriptive statistics which can be limiting when

multivariate relationships are present, we will be utilizing cross-tabulated contingency

tables that will depict the relationship between two or more of our variables and provide

the foundation for further analysis. This analysis will take the form of multiple regression

and correlation, tests for statistical significance such as chi-square ( χ2 ) and ANOVA, as

previously mentioned. Hypothesis testing based on our samples will be utilized; while a

number of output representations is considered. Relationships among the data will be

concluded, thus leading to attribute determination and final research conclusions and

thus satisfying our objectives, will be established.

120

CHAPTER 4 – RESULTS & DATA ANALYSIS

4.1 Survey Results

As mentioned in the previous chapter, surveys were sent to 168 specifically targeted

individuals from a greater potential pool of 870+. Based on this highly-selective and

targeted population, a 95% confidence level, and a selected margin of error of +/- 10%,

a minimum sample size return rate of 62 was calculated to be appropriate. We received

69 returned surveys giving us a return rate of approximately 41% thus falling within the

minimum required sample size for this study. This was a good sampling representative

of the overall population. Return rates were fairly comparable across the three areas :

USA, Europe (Mainly Germany and Italy), and Asia (mainly Japan). Figure 4-1

graphically represents returned surveys vs. not-returned.

Figure 4-1 : Surveys Returned

99

69

Surveys Not ReturnedSurveys Returned

Out of the 69 returned surveys, 45 were returned in English even though some of these

were returned from abroad. 10 surveys were returned in German and an almost equal

number (9) were returned in the Japanese language. Approximately half of this number

(5) came back in Italian. The majority of the surveys that were returned in a language

other than English came from abroad. Response rates were captured by week and in

121

order to measure bias, we performed a simple wave analysis based on the change of

the mean on randomly selected questions in the survey. We did not distinguish any

variations based on return timing nor on return survey language or even based on

geographic area. We concluded that our survey response characteristics were sound.

Some of this information is shown in the figures below.

Figure 4-2 : Survey Language

4510

95

Returned English Language SurveyReturned German Language SurveyReturned Japanese Language SurveyReturned Italian Language Suvey

Figure 4-3 : Geographic Location of Respondent Company

29

11

9

9

9 2JapanItalyUSAGermanyOther EuropeanOther Asia

It is noteworthy to mention that the response rate from Asia, specifically from Japan (at

65%) was more than twice as great as that of either the United States ( at 31%) or

Europe (at 29%). This is shown in Figure 4-4. It is hypothesized that the name-

recognition of the researcher’s place of employment which was mentioned in the survey

(Sumitomo) may have played a role in this particular instance, perhaps motivating Asian

122

and specifically Japanese respondents a greater deal than their counterparts from the

United States and Europe. Any bias based on this will be analyzed and reported. As

mentioned, there was no bias based on response rates from a time point of view – when

surveys were returned / received. Number of returns per week are shown in Figure 4-5.

Simple wave analysis confirmed no adverse affect. Note surveys were sent out the first

week of February 2008.

0%

10%

20%

30%

40%

50%

60%

70%

Asia USA Europe

Figure 4-4 : Response Rates by Region

0

10

20

30

40

week o

f 2/11

week o

f 2/18

week o

f 2/25

week o

f 3/3

week o

f 3/10

week o

f 3/17

week o

f 3/24

week o

f 3/31

Figure 4-5 : Number of Returned Surveys by Week

123

4.1.1 Basic Information / Demographics

Approximately 59% of the respondents classified themselves as either Project,

Application, Product, and/or Sales Engineers or Managers directly handling major

project business, which is the focus of this research. 22% listed themselves as

Design and/or R&D Engineers and Managers indirectly associated with project

business providing technical support. The remaining 19% were usually at a higher

executive level in the company structure and provided multi-project strategic

management. 59% of the respondents indicate they had more than 20 years

experience in their industry and about half of those respondents indicated more

than 20 years of specific project management experience. 23% indicated between

11 and 20 years industry experience. Figure 4-6 provides some additional detail on

job classifications by country of respondent. Figure 4-6 : Job Classification by Target Country

TOTAL

5

14

1210

05

10

13

Project ManagementApplication Eng.Product Eng.SalesPurchasingDesignR&DOther

Japan3

6

17

03

3

5

Germany

05

4100

2

2

Italy

0 2

300

1

1

1

USA1

1

31000

3

124

Approximately 62% worked at their company’s subsidiary in the United States,

while the remaining 38% worked either at a U.S. headquarters of the American

company or abroad at the foreign company’s overseas headquarters usually

located in Germany, Japan, or Italy. 86% of the respondents indicated that their

company had one or more corporate expats working on major project business at

the subsidiary while 40% of the respondents indicated there were subsidiary

personnel working as expats at the foreign headquarters. 62% of the responses

indicated they worked at a publicly-traded company while 29% indicated a private

company, while 8% were not sure. 58% of the companies had more than 1000

employees; of these particularly large companies more than 70% had significantly

large subsidiaries of 100+ employees.

Figure 4-7 is a representation of 3 variables that will be useful for us. It is

informationally interesting because it compares company size (personnel), age, and

expat situation both at the subsidiary level as well as at the parent headquarters

level. This represents the typical profile of our target companies both here and in

their home countries.

We can see that the “oldest” companies in our research are in fact Japanese and

German with an average age of about 65 years. American companies come in 2nd

at an average age of about 55 to 60 years old (headquarters). Italian companies are

younger at an average age of about 45 years old. Furthermore we can easily see

that the Japanese companies seem to be the largest. This is confirmed when we

consider such large heavy industrial companies such as Sumitomo, Mitsubishi,

Kawasaki, and others. When we consider these companies’ subsidiaries in the USA,

we see that overall subsidiary size is comparable – typically it ranges at somewhere

of about 100 to 300 employees. Once again, mirroring the trend of their

125

headquarters, the subsidiaries also vary in age, with the Japanese subsidiaries

having been in the U.S. the longest (oldest) at about 30 to 35 years; the Germans

are a close 2nd with an average age of their presence in the U.S. of about 25 years,

and again the Italian companies seem to be the relative newcomers with their

presence in the U.S. at less than 10 years on average. However, interesting as

these figures may be the additional 3rd variable represented by this “bubble” graph

is the expat situation both at headquarters and at the subsidiary; specifically, how

many cross-over expats are at each others location, Americans at abroad and

foreign expats here.

We can clearly see that American companies have the most expats on average

(14) than the others. The Japanese have the lowest number averaging only one

U.S. expat at their headquarters in Japan. This is interesting and will be discussed

later. The German and Italian company headquarters in their respective countries

do not do much better and on average maintain two U.S. expat employees at their

European headquarters. All 3 however – Japanese, German, and Italian companies

do maintain on average three employees from headquarters in their U.S.

subsidiaries. This is also interesting and will be discussed later.

Figure 4-7 : Company Size / Age / Expat Situation Profile

142

2

1

14

3

33

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

0 10 20 30 40 50 60 70 8Company Age

Com

pany

Siz

e (P

erso

nnel

)

0

ITALIANSubsidiary

GERMANSubsidiary

AMERICANSubsidiary

ITALIANPARENT

JAPANESESubsidiary

JAPANESEPARENTAMERICAN

PARENT

GERMANPARENT

126

The remainder of the data results is presented here utilizing cross-tabulated

contingency tables. This is done because this methodology is powerful in

presenting and establishing a starting point for simultaneous analysis of more than

one variable which we will consider in the following section : 4.2 Data Analysis /

Hypotheses Testing. Furthermore, since we are “…interested in the relationship

and influence of one variable over another, the use of contingency tables is

appropriate” [95]. According to Rea and Parker these tables add an explanatory

dimension to simple frequency distributions. Finally, all survey basic raw data is

readily available in Appendix C.

4.1.2 Headquarters & Subsidiary Communication

f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 0 0.0% 0 0.0% 1 8.3% 1 11.1% 0 0.0% 2 2.9% 0 0.0% 0 0.0% 0 0.0% 2 22.2% 0 0.0% 2 3.0%

+3 2 6.9% 2 25.0% 5 41.7% 0 0.0% 2 20.0% 11 16.2% 0 0.0% 3 37.5% 3 27.3% 0 0.0% 2 20.0% 8 11.9%+2 7 24.1% 1 12.5% 0 0.0% 0 0.0% 0 0.0% 8 11.8% 0 0.0% 0 0.0% 4 36.4% 0 0.0% 2 20.0% 6 9.0%+1 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9% 2 6.9% 1 12.5% 0 0.0% 0 0.0% 0 0.0% 3 4.5%

Neutral 0 0 0.0% 0 0.0% 0 0.0% 2 22.2% 3 30.0% 5 7.4% 4 13.8% 0 0.0% 1 9.1% 1 11.1% 1 10.0% 7 10.4%-1 3 10.3% 0 0.0% 2 16.7% 0 0.0% 0 0.0% 5 7.4% 4 13.8% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 6 9.0%-2 6 20.7% 4 50.0% 2 16.7% 2 22.2% 1 10.0% 15 22.1% 7 24.1% 1 12.5% 1 9.1% 5 55.6% 2 20.0% 16 23.9%-3 3 10.3% 0 0.0% 1 8.3% 1 11.1% 3 30.0% 8 11.8% 5 17.2% 3 37.5% 0 0.0% 0 0.0% 2 20.0% 10 14.9%

Completely Disagree -4 7 24.1% 1 12.5% 1 8.3% 2 22.2% 1 10.0% 12 17.6% 7 24.1% 0 0.0% 0 0.0% 1 11.1% 1 10.0% 9 13.4%

TOTALS : 29 100.0% 8 100.0% 12 100.0% 9 100.0% 10 100.0% 68 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0%

Table 4-1 : One-on-One Communication Structure

Survey Question 12 13Survey Question Japan Germany Italy USA Other Total Japan Germany Italy USA Other Total

Question 12 : At my company the technical communication channel between our subsidiary and our headquarters is one-to-one. This means there is a single person at the subsidiary talking with a single person at headquarters. They both then distribute the information to others at their respective locations. Question 13 : A one-to-one communication channel set-up is optimum for coordinating tech info and knowledge transfer.

More than 65% of Japanese companies do not agree with a 1-to-1 communication

structure at their operation and almost 90% personally feel that it is not the best

approach in setting communications and a knowledge transfer structure. This is an

interesting result because there have been cases where this is exactly how such

structures are in fact constructed in many Japanese companies. German and Italian

127

respondents seem split on both questions if this is in fact the structure at their

organizations and if this is the optimum set-up.

f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 3.0% 0 0.0% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 1 1.5%

+3 2 6.9% 0 0.0% 6 54.5% 0 0.0% 0 0.0% 8 11.9% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%+2 7 24.1% 1 12.5% 2 18.2% 2 22.2% 0 0.0% 12 17.9% 1 3.4% 0 0.0% 1 9.1% 2 22.2% 0 0.0% 4 6.0%+1 4 13.8% 3 37.5% 2 18.2% 1 11.1% 1 10.0% 11 16.4% 2 6.9% 1 12.5% 2 18.2% 1 11.1% 0 0.0% 6 9.0%

Neutral 0 1 3.4% 0 0.0% 1 9.1% 1 11.1% 4 40.0% 7 10.4% 6 20.7% 0 0.0% 1 9.1% 1 11.1% 2 20.0% 10 14.9%-1 0 0.0% 0 0.0% 0 0.0% 0 0.0% 2 20.0% 2 3.0% 4 13.8% 0 0.0% 3 27.3% 0 0.0% 2 20.0% 9 13.4%-2 4 13.8% 3 37.5% 0 0.0% 0 0.0% 1 10.0% 8 11.9% 5 17.2% 5 62.5% 3 27.3% 1 11.1% 5 50.0% 19 28.4%-3 3 10.3% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 4 6.0% 5 17.2% 2 25.0% 1 9.1% 0 0.0% 1 10.0% 9 13.4%

Completely Disagree -4 7 24.1% 1 12.5% 0 0.0% 3 33.3% 2 20.0% 13 19.4% 5 17.2% 0 0.0% 0 0.0% 3 33.3% 0 0.0% 8 11.9%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0%

Table 4-2 : One-to-Many Communication Structure

Survey Question 14 15Survey Question Other TotalJapan GermanyItaly USA Italy USAOther TotalJapan Germany

Question 14 : At my company the technical communication channel between our subsidiary and our headquarters is one-to-many. This means there is a single person at the subsidiary talking with multiple / many people at headquarters. That single person then distributes the information at the subsidiary accordingly to who needs it. Question 15 : A one-to-many communication channel set-up is optimum for coordinating tech. info and knowledge transfer.

Results indicate essentially a split in Japanese company response on this particular

communication structure and its usage within their organizations. German

companies also are somewhat split on this structure as well, while interestingly

results indicate that Italian companies, by a majority 90%, do in fact practice this

type of structure. It is hypothesized that perhaps this is the case for Italian

manufacturers due to the relative younger age of their subsidiaries in the USA as

well as the fact that these companies also tend to be smaller in size tan their

German and Japanese counterparts. Results on question 15 indicate that a majority

of Japanese respondents (more than 85%) indicate that a 1-to-many scenario is not

considered optimum, even though its actual utilization is confirmed by Question 14.

128

f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 0 0.0% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 2 3.0% 0 0.0% 1 12.5% 0 0.0% 0 0.0% 0 0.0% 1 1.5%

+3 3 10.3% 2 25.0% 3 27.3% 0 0.0% 0 0.0% 8 11.9% 1 3.4% 1 12.5% 4 40.0% 0 0.0% 0 0.0% 6 9.1%+2 4 13.8% 1 12.5% 0 0.0% 1 11.1% 0 0.0% 6 9.0% 3 10.3% 1 12.5% 0 0.0% 1 11.1% 0 0.0% 5 7.6%+1 5 17.2% 0 0.0% 0 0.0% 0 0.0% 2 20.0% 7 10.4% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 1 10.0% 2 3.0%

Neutral 0 1 3.4% 1 12.5% 0 0.0% 1 11.1% 3 30.0% 6 9.0% 6 20.7% 1 12.5% 0 0.0% 1 11.1% 4 40.0% 12 18.2%-1 1 3.4% 1 12.5% 0 0.0% 1 11.1% 1 10.0% 4 6.0% 3 10.3% 0 0.0% 0 0.0% 0 0.0% 1 10.0% 4 6.1%-2 1 3.4% 2 25.0% 1 9.1% 0 0.0% 2 20.0% 6 9.0% 2 6.9% 1 12.5% 1 10.0% 2 22.2% 1 10.0% 7 10.6%-3 6 20.7% 0 0.0% 3 27.3% 2 22.2% 0 0.0% 11 16.4% 5 17.2% 3 37.5% 2 20.0% 1 11.1% 2 20.0% 13 19.7%

Completely Disagree -4 8 27.6% 1 12.5% 2 18.2% 4 44.4% 2 20.0% 17 25.4% 8 27.6% 0 0.0% 3 30.0% 4 44.4% 1 10.0% 16 24.2%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0% 29 100.0% 8 100.0% 10 100.0% 9 100.0% 10 100.0% 66 100.0%

Table 4-3 : Many-to-One Communication Structure

Italy USASurvey Question 16 17Survey Question

Japan GermanyJapan Germany Italy USA Other Total Other Total

Question 16 : At my company the technical communication channel between our subsidiary and our headquarters is many-to-one. This means there many at the subsidiary talking with a single person at headquarters. The single person coordinates information with others at headquarters as needed. Question 17 : A many-to-one communication channel set-up is optimum for coordinating tech info and knowledge transfer.

Results indicate that Japanese, German, and Italian companies are basically split

almost evenly on this question regarding agreement or disagreement. This would

indicate that this type of structure does indeed exist in their corporations. Most likely

this would involve some kind of international planning department with a specified

manager handling inquiries from the subsidiaries. This is in fact practiced but tends

to slow down communications and affects the transmission factors of speed,

context (depending on language capabilities of this Department), and it could also

affect trust in such a way as to have headquarters dependent on their International

Planning or Support Department to deal with the subsidiaries instead of cross-

communication across all departments. Also, once again whereas German and

Italian respondents were split on how favorable they saw this structure personally;

Japanese respondents overwhelmingly felt that this was not optimum.

129

f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 3 10.3% 1 12.5% 0 0.0% 1 11.1% 2 20.0% 7 10.4% 7 24.1% 1 12.5% 3 27.3% 1 11.1% 1 10.0% 13 19.4%

+3 8 27.6% 0 0.0% 2 18.2% 1 11.1% 1 10.0% 12 17.9% 8 27.6% 0 0.0% 2 18.2% 3 33.3% 2 20.0% 15 22.4%+2 0 0.0% 3 37.5% 2 18.2% 0 0.0% 2 20.0% 7 10.4% 3 10.3% 0 0.0% 0 0.0% 0 0.0% 2 20.0% 5 7.5%+1 1 3.4% 0 0.0% 2 18.2% 0 0.0% 1 10.0% 4 6.0% 2 6.9% 3 37.5% 0 0.0% 0 0.0% 0 0.0% 5 7.5%

Neutral 0 1 3.4% 0 0.0% 0 0.0% 2 22.2% 2 20.0% 5 7.5% 2 6.9% 0 0.0% 0 0.0% 2 22.2% 1 10.0% 5 7.5%-1 2 6.9% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 3 4.5% 0 0.0% 0 0.0% 1 9.1% 1 11.1% 3 30.0% 5 7.5%-2 5 17.2% 0 0.0% 0 0.0% 1 11.1% 1 10.0% 7 10.4% 2 6.9% 1 12.5% 2 18.2% 0 0.0% 0 0.0% 5 7.5%-3 8 27.6% 4 50.0% 5 45.5% 1 11.1% 0 0.0% 18 26.9% 3 10.3% 1 12.5% 3 27.3% 0 0.0% 0 0.0% 7 10.4%

Completely Disagree -4 1 3.4% 0 0.0% 0 0.0% 2 22.2% 1 10.0% 4 6.0% 2 6.9% 2 25.0% 0 0.0% 2 22.2% 1 10.0% 7 10.4%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0%

Table 4-4 : Many-to-Many Communication Structure

Survey Question 18 19Survey Question Italy USA Other TotalJapan Germany Italy USA Other Total Japan Germany

Question 18 : At my company the technical communication channel between our subsidiary and our headquarters is many-to-many. This means that multiple / many people at our subsidiary talk with multiple / many people at headquarters as required. There is no real formal channels of communication. Question 19 : A many-to-many communication channel set-up is optimum for coordinating tech info and knowledge transfer.

Almost 70% of Japanese respondents indicated that they consider the many-to-

many model the optimum structure for communications and knowledge transfer

even though there is disagreement on this structure as the actual mechanism in

their corporations. This agreement that this many-to-many structure, by far,

surpassed both German and Italian responses that ranged only between 37~40%

agreement.

f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 5 17.2% 0 0.0% 0 0.0% 3 33.3% 0 0.0% 8 11.8% 9 31.0% 0 0.0% 0 0.0% 5 55.6% 1 9.1% 15 22.1%

+3 9 31.0% 2 25.0% 0 0.0% 1 11.1% 6 54.5% 18 26.5% 5 17.2% 1 12.5% 10 90.9% 2 22.2% 6 54.5% 24 35.3%+2 9 31.0% 5 62.5% 3 27.3% 2 22.2% 3 27.3% 22 32.4% 11 37.9% 3 37.5% 0 0.0% 0 0.0% 2 18.2% 16 23.5%+1 5 17.2% 1 12.5% 1 9.1% 2 22.2% 0 0.0% 9 13.2% 3 10.3% 4 50.0% 0 0.0% 1 11.1% 0 0.0% 8 11.8%

Neutral 0 1 3.4% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 3 4.4% 0 0.0% 0 0.0% 1 9.1% 1 11.1% 2 18.2% 4 5.9%-1 0 0.0% 0 0.0% 1 9.1% 0 0.0% 0 0.0% 1 1.5% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%-2 0 0.0% 0 0.0% 6 54.5% 0 0.0% 1 9.1% 7 10.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-5 : Written / Documented Communications

Survey Question 20 21Survey Question Japan Germany Italy USA Other Total Japan Germany Italy USA Other Total

Question 20 : At my company we handle technical communications between subsidiary and headquarters in a formal documented way using e-mail, fax, or other structured means. We do things in writing. Question 21 : The best way for handling technical communication between subsidiary and headquarters is in writing, by e-mail, fax, and / or other structured documented means.

130

Virtually all (at 96%) Japanese respondents indicate that handling communications

in writing is the best way and this is how it’s done at their companies. This is

interesting in 2 ways, first it indicates that written communication is preferred

because it may be easier for headquarters personnel to review and respond. It is

fairly well-known that many individuals prefer written communication as opposed to

on-the-spot verbal communication because of fear and other factors associated

with their level of knowledge of that foreign language, and for the Japanese its no

different; in fact it is even more desired due to the emphasis on written over verbal

foreign language instruction within the Japanese education system.

Secondly, we must also consider the time-difference and the difficulty in

coordinating verbal communications whether by phone or video conference when

the time difference between subsidiary and headquarters is 12 to 13 hours.

Germans as well prefer written communications and it’s hypothesized that this may

be due to the precise and low context nature of the culture. Perhaps not surprisingly,

more than half of the respondents from Italian manufacturers indicate that this is not

the way it’s done at their company. Once again it is felt that the relatively young age

of subsidiaries within the U.S. may play a role in the fact that such formalized

systems perhaps have not been fully implemented.

f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 0 0.0% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 2 2.9% 4 13.8% 2 25.0% 2 18.2% 1 11.1% 0 0.0% 9 13.2%

+3 1 3.4% 0 0.0% 2 18.2% 1 11.1% 1 9.1% 5 7.4% 10 34.5% 2 25.0% 4 36.4% 1 11.1% 0 0.0% 17 25.0%+2 4 13.8% 3 37.5% 2 18.2% 0 0.0% 4 36.4% 13 19.1% 4 13.8% 2 25.0% 0 0.0% 0 0.0% 4 36.4% 10 14.7%+1 3 10.3% 4 50.0% 1 9.1% 0 0.0% 1 9.1% 9 13.2% 5 17.2% 2 25.0% 0 0.0% 1 11.1% 4 36.4% 12 17.6%

Neutral 0 1 3.4% 0 0.0% 1 9.1% 3 33.3% 0 0.0% 5 7.4% 1 3.4% 0 0.0% 1 9.1% 3 33.3% 0 0.0% 5 7.4%-1 6 20.7% 1 12.5% 1 9.1% 2 22.2% 2 18.2% 12 17.6% 0 0.0% 0 0.0% 4 36.4% 1 11.1% 1 9.1% 6 8.8%-2 7 24.1% 0 0.0% 2 18.2% 2 22.2% 1 9.1% 12 17.6% 3 10.3% 0 0.0% 0 0.0% 2 22.2% 1 9.1% 6 8.8%-3 5 17.2% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 7 10.3% 2 6.9% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 2 2.9%

Completely Disagree -4 2 6.9% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 3 4.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 1 1.5%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-6 : Verbal, Face-to-Face Communications

Survey Question 22 23Survey Question Other TotalJapan GermanyItaly USA Italy USAOther TotalJapan Germany

131

Question 22 : At my company we handle technical communications between subsidiary and headquarters, by phone, video conference, or face-to-face meetings whenever possible. We try to speak to each other instead of writing. Question 23 : The best way for handling technical communication between subsidiary and headquarters is by phone or video conference. It is preferable to look and directly speak to and hear the other person while discussing technical issues.

Not surprisingly and in conjunction with the results from Questions 20 and 21,

Japanese respondents do not agree with face-to-face and/or verbal

communications. They indicate by a majority of about 68% that this is normally not

how it’s done at their corporations. German respondents however indicate that in

fact this does take place in German parent-subsidiary communications, this is

indicated by a majority 87% of respondents. Italian respondents are essentially split

almost evenly. Interestingly enough however both German and Japanese

respondents indicated that they would prefer to communicate (more) in a verbal,

face-to-face manner, by video conference, and the like. 100% of German

respondents either Agree or Completely Agree with this idea, while about 75% of

Japanese also fall in this category.

4.1.3 Headquarters & Subsidiary KT and Corporate Culture

f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 0 0.0% 1 11.1% 0 0.0% 2 22.2% 0 0.0% 3 4.3% 8 27.6% 1 12.5% 1 9.1% 3 33.3% 0 0.0% 13 19.1%

+3 2 6.9% 2 22.2% 0 0.0% 4 44.4% 2 18.2% 10 14.5% 7 24.1% 2 25.0% 8 72.7% 4 44.4% 5 45.5% 26 38.2%+2 1 3.4% 2 22.2% 0 0.0% 1 11.1% 1 9.1% 5 7.2% 5 17.2% 5 62.5% 2 18.2% 0 0.0% 3 27.3% 15 22.1%+1 2 6.9% 1 11.1% 0 0.0% 0 0.0% 3 27.3% 6 8.7% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 2 18.2% 2 2.9%

Neutral 0 1 3.4% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 2 2.9% 2 6.9% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 2 2.9%-1 0 0.0% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 2 2.9% 5 17.2% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 5 7.4%-2 13 44.8% 1 11.1% 5 45.5% 0 0.0% 1 9.1% 20 29.0% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 2 2.9%-3 8 27.6% 2 22.2% 6 54.5% 1 11.1% 1 9.1% 18 26.1% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%

Completely Disagree -4 2 6.9% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 3 4.3% 0 0.0% 0 0.0% 0 0.0% 2 22.2% 0 0.0% 2 2.9%

TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-7 : Trust

Italy USASurvey Question 24 25Survey Question

Japan GermanyJapan Germany Italy USA Other Total Other Total

Question 24 : At my company there is an open and sharing of technical information and knowledge. Nothing is held back from each other by either subsidiaries nor headquarters. There is trust. We are a learning organization, an environment of continuous improvement. This is encouraged by management.

132

Question 25 : The best approach in terms of knowledge sharing between headquarters and subsidiary is openness, full-sharing, and trust. You should not keep information from others as an advantage for yourself.

Almost 80% of Japanese respondents indicate disagreement with the statement

that there is open, sharing of information and trust. This is a significant result

because it indicates a presence of distrust within their organizations. Italian

companies also overwhelmingly at 99% seem to share the same kind of sense of

mistrust, no sharing, no openness. In contrast, both German and U.S. companies

indicate agreement that this sense of trust and openness and sharing does in fact

exist. However we need to consider this information with some care. Across the

board all respondents agreed that this however is required and the best approach.

f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 3 10.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 3 4.4% 3 10.3% 0 0.0% 1 9.1% 3 33.3% 1 9.1% 8 11.6%

+3 0 0.0% 2 25.0% 2 18.2% 0 0.0% 1 9.1% 5 7.4% 11 37.9% 2 22.2% 9 81.8% 0 0.0% 1 9.1% 23 33.3%+2 1 3.4% 1 12.5% 3 27.3% 0 0.0% 1 9.1% 6 8.8% 9 31.0% 0 0.0% 1 9.1% 1 11.1% 2 18.2% 13 18.8%+1 0 0.0% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 2 2.9% 0 0.0% 2 22.2% 0 0.0% 0 0.0% 1 9.1% 3 4.3%

Neutral 0 2 6.9% 0 0.0% 2 18.2% 1 11.1% 2 18.2% 7 10.3% 1 3.4% 0 0.0% 0 0.0% 1 11.1% 4 36.4% 6 8.7%-1 4 13.8% 0 0.0% 1 9.1% 0 0.0% 3 27.3% 8 11.8% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.4%-2 12 41.4% 2 25.0% 2 18.2% 1 11.1% 1 9.1% 18 26.5% 2 6.9% 3 33.3% 0 0.0% 0 0.0% 0 0.0% 5 7.2%-3 6 20.7% 2 25.0% 1 9.1% 3 33.3% 2 18.2% 14 20.6% 2 6.9% 1 11.1% 0 0.0% 1 11.1% 2 18.2% 6 8.7%

Completely Disagree -4 1 3.4% 1 12.5% 0 0.0% 3 33.3% 0 0.0% 5 7.4% 0 0.0% 1 11.1% 0 0.0% 3 33.3% 0 0.0% 4 5.8%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0% 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%

Table 4-8 : Hold-Back of Information Either by Headquarters or Subsidiary - 1

Survey Question 26 27Survey QuestionUSA Other TotalGermany Italy USA ItalyOther TotalJapan Japan Germany

Question 26 : At my company for whatever reason the subsidiary does hold back from headquarters some technical information, knowledge and know-how acquired from local market experience and customers. Question 27 : At my company for whatever reason headquarters does hold back from the subsidiary some centrally-based core technical information, knowledge and know-how.

Results indicate that the majority of Japanese, German, and American respondents

feel that at their company there is no holding back of information by the subsidiary

for any reason. Italian respondents are split. Surprisingly enough, however, almost

80% of Japanese respondents indicate that headquarters in fact does hold back

133

information from the subsidiary. More surprisingly even though there was a split in

responses from Italian companies on whether the subsidiary holds back, the

majority (more than 90%) indicate that their headquarters does in fact hold back

information. This is an interesting result in that it relates to trust issues between

headquarters and the subsidiaries. There seems to be an aspect of “us vs. them”

which can lead to morale issues and be unproductive in the operation of the

subsidiary. Furthermore this can then it can spiral back to headquarters and create

a negative situation there as well eventually leading to a self-fulfilling prophecy of

inefficiency and poor morale which can impact project success.

f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%

+3 1 3.4% 1 12.5% 1 9.1% 0 0.0% 1 9.1% 4 5.9%+2 8 27.6% 0 0.0% 1 9.1% 1 11.1% 0 0.0% 10 14.7%+1 2 6.9% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 3 4.4%

Neutral 0 2 6.9% 0 0.0% 0 0.0% 2 22.2% 4 36.4% 8 11.8%-1 0 0.0% 0 0.0% 1 9.1% 0 0.0% 1 9.1% 2 2.9%-2 1 3.4% 1 12.5% 1 9.1% 1 11.1% 0 0.0% 4 5.9%-3 6 20.7% 5 62.5% 7 63.6% 1 11.1% 3 27.3% 22 32.4%

Completely Disagree -4 8 27.6% 1 12.5% 0 0.0% 4 44.4% 1 9.1% 14 20.6%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-9 : Hold-Back of Information Either by Headquarters or Subsidiary - 2

Survey Question 28Japan Germany Italy USA Other Total

Question 28 : It is acceptable for either headquarters or the subsidiary to hold back information from time to time in order to gain some real or perceived advantage. Critical information is a source of power that can be used.

Results indicate a split between agreement and disagreement within Japanese

companies on whether its OK to hold back. The rest of the respondents disagree

with holding back information. Again, the results are interesting from a trust point of

view. We will see later in the report that these attitudes of withholding information

whether by subsidiary or parent company and whether true or simply perceived do

reflect an aspect of culture whether Indo-European, Asian, and the like.

134

f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9%

+3 6 20.7% 4 44.4% 6 54.5% 1 11.1% 2 18.2% 19 27.5%+2 4 13.8% 3 33.3% 3 27.3% 3 33.3% 2 18.2% 15 21.7%+1 1 3.4% 1 11.1% 1 9.1% 0 0.0% 0 0.0% 3 4.3%

Neutral 0 3 10.3% 0 0.0% 0 0.0% 0 0.0% 2 18.2% 5 7.2%-1 2 6.9% 0 0.0% 0 0.0% 1 11.1% 4 36.4% 7 10.1%-2 7 24.1% 1 11.1% 1 9.1% 3 33.3% 1 9.1% 13 18.8%-3 5 17.2% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 5 7.2%

Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%

Table 4-10 : Technical Project Specs. & Customer Knowledge

Survey Question 29Other TotalJapan Germany Italy USA

Question 29 : At my company we usually do not have any problems with customers transferring their Technical Project Specifications to us. Our customers are knowledgeable, they know what they want, and what is available in the market.

Japanese respondents to this Question 29 are split almost evenly in indicating

problems with customer transfer of technical project specifications. Since the

majority of German, Italian and most U.S. companies seem to feel that this is not a

problem for them; we think that perhaps this relates to language issues with

Japanese companies.

f % f % f % f % f % f %Completely Agree +4 0 0.0% 1 12.5% 0 0.0% 2 22.2% 0 0.0% 3 4.4%

+3 4 13.8% 2 25.0% 5 45.5% 2 22.2% 2 18.2% 15 22.1%+2 4 13.8% 4 50.0% 0 0.0% 1 11.1% 4 36.4% 13 19.1%+1 1 3.4% 1 12.5% 0 0.0% 1 11.1% 3 27.3% 6 8.8%

Neutral 0 3 10.3% 0 0.0% 0 0.0% 2 22.2% 0 0.0% 5 7.4%-1 4 13.8% 0 0.0% 3 27.3% 0 0.0% 1 9.1% 8 11.8%-2 6 20.7% 0 0.0% 2 18.2% 1 11.1% 1 9.1% 10 14.7%-3 6 20.7% 0 0.0% 1 9.1% 0 0.0% 0 0.0% 7 10.3%

Completely Disagree -4 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Survey Question 30Japan Germany Italy USA Other Total

Table 4-11 : Technology Tools

Question 30 : At my company we use fairly new technology tools to facilitate knowledge transfer and sharing between headquarters and the subsidiaries. We keep up with technology.

German respondents indicate significant usage of technology tools. 100% response

from German companies indicates agreement with the survey Question / Statement

30; whereas a strong portion of Japanese respondents (about 59%) indicate no

135

such usage or minimal usage of technology regarding knowledge transfer

facilitation.

f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9% 8 27.6% 4 50.0% 1 9.1% 4 44.4% 2 18.2% 19 27.9%

+3 1 3.4% 5 55.6% 2 18.2% 1 11.1% 6 54.5% 15 21.7% 18 62.1% 4 50.0% 7 63.6% 2 22.2% 6 54.5% 37 54.4%+2 7 24.1% 0 0.0% 2 18.2% 3 33.3% 3 27.3% 15 21.7% 1 3.4% 0 0.0% 3 27.3% 2 22.2% 2 18.2% 8 11.8%+1 2 6.9% 1 11.1% 1 9.1% 0 0.0% 0 0.0% 4 5.8% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%

Neutral 0 3 10.3% 0 0.0% 0 0.0% 3 33.3% 1 9.1% 7 10.1% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 2 2.9%-1 6 20.7% 3 33.3% 0 0.0% 0 0.0% 0 0.0% 9 13.0% 0 0.0% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 1 1.5%-2 8 27.6% 0 0.0% 4 36.4% 1 11.1% 1 9.1% 14 20.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-3 1 3.4% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 3 4.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-12 : Cooperation & Collaboration / Culture

Survey Question 31 32Survey Question Japan Germany Italy USA Other Total Japan Germany Italy USA Other Total

Question 31 : At my company cooperation and collaboration is critical to our success and strong within our culture; everyone understands and practices this for mutual benefit both within the subsidiary and between headquarters and subsidiary. Question 32 : A spirit of true cooperation and collaboration is the most important aspect of knowledge transfer.

Japanese respondents seem to disagree with this particular statement on

cooperation and collaboration existing between parent and subsidiary entities at

their corporations. About 60% indicate that there may be problems with true

cooperation and collaboration. German and Italian responses indicate a split.

However all respondents across the board overwhelmingly indicate that a spirit of

cooperation and collaboration is in fact critical and the most important aspect of

knowledge transfer. It just seems from the responses that even though individual

may feel this way, it is lacking in practice.

f % f % f % f % f % f %Completely Agree +4 0 0.0% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 1 1.4%

+3 2 6.9% 1 11.1% 0 0.0% 0 0.0% 2 18.2% 5 7.2%+2 11 37.9% 2 22.2% 1 9.1% 4 44.4% 1 9.1% 19 27.5%+1 1 3.4% 1 11.1% 0 0.0% 2 22.2% 4 36.4% 8 11.6%

Neutral 0 1 3.4% 2 22.2% 0 0.0% 2 22.2% 3 27.3% 8 11.6%-1 4 13.8% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 6 8.7%-2 6 20.7% 3 33.3% 8 72.7% 0 0.0% 0 0.0% 17 24.6%-3 3 10.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 3 4.3%

Completely Disagree -4 1 3.4% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 2 2.9%

TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%

Table 4-13 : Structure of Decision-Making and Processes

Survey Question 33Japan Germany Italy USA Other Total

136

Question 33 : At my company there is a high level of agreement about how things are done; we have a fairly strong structure where each and every one follows strict guidelines on doing things.

Japanese and German responses indicate a split between agreement and

disagreement with this Question / Statement; Italian respondents however indicate

that such structure really does not exists; thus they overwhelmingly disagree at

about 90% rate. This could once again indicate the relatively young age of Italian

subsidiaries compared to both German and Japanese companies. The fact could

be that Italian subsidiaries in the U.S. could still be maturing and creating these

needed structures within their operations while both Japanese and German

companies have evolved these systems already.

f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9%

+3 1 3.4% 2 22.2% 0 0.0% 1 11.1% 2 18.2% 6 8.7%+2 2 6.9% 6 66.7% 0 0.0% 2 22.2% 1 9.1% 11 15.9%+1 3 10.3% 0 0.0% 0 0.0% 0 0.0% 2 18.2% 5 7.2%

Neutral 0 1 3.4% 1 11.1% 0 0.0% 3 33.3% 2 18.2% 7 10.1%-1 11 37.9% 0 0.0% 0 0.0% 0 0.0% 2 18.2% 13 18.8%-2 8 27.6% 0 0.0% 3 27.3% 2 22.2% 2 18.2% 15 21.7%-3 0 0.0% 0 0.0% 7 63.6% 0 0.0% 0 0.0% 7 10.1%

Completely Disagree -4 2 6.9% 0 0.0% 1 9.1% 0 0.0% 0 0.0% 3 4.3%

TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%

Table 4-14 : Employee Input Into Decision-Making

Survey Question 34Japan Germany Italy USA Other Total

Question 34 : At my company most employees have direct input into decisions that affect them.

Most Japanese companies (about 70%) disagree and indicate that employees do

not have a strong sense of direct input into decisions that may affect them. The

same holds true and to a greater extent at about 90% for Italian companies. It

would seem that employees in both Japanese and Italian manufacturers at least in

this industry) are not directly influential in decision-making. On the other hand

German companies seem to provide more leeway and opportunity in their

137

employees having more direct input. They overwhelmingly answered in the positive

at about 88% in agreement with survey Question 34.

f % f % f % f % f % f %Completely Agree +4 0 0.0% 1 12.5% 0 0.0% 1 11.1% 0 0.0% 2 2.9%

+3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 1 1.5%+2 0 0.0% 0 0.0% 0 0.0% 3 33.3% 2 18.2% 5 7.4%+1 3 10.3% 4 50.0% 0 0.0% 2 22.2% 2 18.2% 11 16.2%

Neutral 0 1 3.4% 0 0.0% 0 0.0% 2 22.2% 3 27.3% 6 8.8%-1 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-2 11 37.9% 1 12.5% 3 27.3% 0 0.0% 2 18.2% 17 25.0%-3 10 34.5% 2 25.0% 6 54.5% 1 11.1% 1 9.1% 20 29.4%

Completely Disagree -4 4 13.8% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 6 8.8%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-15 : Shared-Meaning Between Headquarters and Subsidiary

Survey Question 35Japan Germany Italy USA Other Total

Question 35 : There is true shared-meaning between our company’s headquarters and subsidiaries. We really do understand each other.

Corresponding to previous results, once again Japanese and Italian company

respondents seem to feel that there is no shared-meaning between headquarters

and subsidiary; that there is no true understanding.

4.1.4 What is Project Success

f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 7 24.1% 1 11.1% 4 28.6% 4 44.4% 1 9.1% 17 23.6% 8 27.6% 1 12.5% 1 9.1% 3 33.3% 3 27.3% 16 23.5%

+3 10 34.5% 5 55.6% 3 21.4% 2 22.2% 6 54.5% 26 36.1% 12 41.4% 7 87.5% 8 72.7% 3 33.3% 6 54.5% 36 52.9%+2 3 10.3% 3 33.3% 2 14.3% 0 0.0% 2 18.2% 10 13.9% 6 20.7% 0 0.0% 2 18.2% 2 22.2% 2 18.2% 12 17.6%+1 2 6.9% 0 0.0% 0 0.0% 2 22.2% 0 0.0% 4 5.6% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

Neutral 0 3 10.3% 0 0.0% 0 0.0% 1 11.1% 2 18.2% 6 8.3% 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9%-1 3 10.3% 0 0.0% 4 28.6% 0 0.0% 0 0.0% 7 9.7% 2 6.9% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 2 2.9%-2 1 3.4% 0 0.0% 1 7.1% 0 0.0% 0 0.0% 2 2.8% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

TOTALS : 29 100.0% 9 100.0% 14 100.0% 9 100.0% 11 100.0% 72 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-16 : Project Success : Time, Budget, Performance

Survey Question 36 37Survey QuestionJapan Germany Italy USA Other Total Japan Germany Italy USA Other Total

Question 36 : At my company we measure Project Success as completing a project on-time, on-budget, and meeting all technical performance specifications in terms of function and quality. Question 37 : The best measure of project success is by means of delivery, budget, and performance.

Essentially the majority of respondents regardless of company nationality indicated

that delivery, price, and technical performance are in fact key measures of project

138

success. Across the board Japanese ( 75% ), German ( 100% ), Italian ( 64% ), and

American ( 66% ) companies in this industry still measure project success based on

these original factors.

f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 3 4.3%

+3 2 6.9% 1 11.1% 0 0.0% 1 11.1% 0 0.0% 4 5.8%+2 1 3.4% 0 0.0% 0 0.0% 1 11.1% 2 18.2% 4 5.8%+1 1 3.4% 1 11.1% 0 0.0% 1 11.1% 3 27.3% 6 8.7%

Neutral 0 1 3.4% 0 0.0% 0 0.0% 1 11.1% 3 27.3% 5 7.2%-1 4 13.8% 3 33.3% 0 0.0% 1 11.1% 0 0.0% 8 11.6%-2 10 34.5% 0 0.0% 2 18.2% 2 22.2% 1 9.1% 15 21.7%-3 7 24.1% 3 33.3% 7 63.6% 1 11.1% 1 9.1% 19 27.5%

Completely Disagree -4 2 6.9% 1 11.1% 2 18.2% 0 0.0% 0 0.0% 5 7.2%

TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%

Table 4-17 : Post-Project Reviews

Survey Question 38Japan Germany Italy USA Other Total

Question 38 : At my company we conduct fairly structured post-project reviews and lessons-learned sessions. These are important to identify and understand ways to improve our project capabilities. Virtually no majority, whether Japanese, German, Italian, nor American, conducts

structured post-project reviews and lessons-learned sessions.

f % f % f % f % f % f %Completely Agree +4 3 10.3% 1 12.5% 5 45.5% 1 11.1% 1 9.1% 11 16.2%

+3 11 37.9% 1 12.5% 0 0.0% 1 11.1% 5 45.5% 18 26.5%+2 2 6.9% 6 75.0% 3 27.3% 2 22.2% 4 36.4% 17 25.0%+1 5 17.2% 0 0.0% 1 9.1% 3 33.3% 0 0.0% 9 13.2%

Neutral 0 5 17.2% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 6 8.8%-1 0 0.0% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 1 1.5%-2 3 10.3% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 4 5.9%-3 0 0.0% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 2 2.9%

Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-18 : Employee Morale, Satisfaction, and Project Success

Survey Question 39Japan Germany Italy USA Other Total

Question 39 : Employee morale and satisfaction at the subsidiary is an important measure of project success even though there may be no direct impact at all on cost, delivery and performance.

Results indicate consistently that almost all respondents regardless of company

nationality feel that employee morale, satisfaction is an important measure of

project success. How important compared to price, delivery and performance,

unfortunately was not indicated in any particular individual survey question but will

be analyzed within this research. It is interesting that respondents overwhelmingly

139

consider the typical project success factors but also consider employee morale and

satisfaction. This was a result that was not really expected within this fairly mature

and some would consider “old-fashioned” industry.

f % f % f % f % f % f %Completely Agree +4 9 31.0% 1 12.5% 3 27.3% 1 11.1% 3 27.3% 17 25.0%

+3 10 34.5% 4 50.0% 7 63.6% 4 44.4% 3 27.3% 28 41.2%+2 8 27.6% 3 37.5% 1 9.1% 2 22.2% 3 27.3% 17 25.0%+1 1 3.4% 0 0.0% 0 0.0% 2 22.2% 2 18.2% 5 7.4%

Neutral 0 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-1 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-2 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-3 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%

Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-19 : Customer Satisfaction and Repeat Business, and Project Success

Survey Question 40Japan Germany Italy USA Other Total

Question 40 : Fully satisfied customers leading to repeat business is the most important measure of project success. This means also eliminating after-market repairs and problems. Results indicate a strong agreement to the statement on satisfied customers and

repeat business being an indicator of project success. Virtually all responses

indicated a 90%n or greater agreement rate.

f % f % f % f % f % f %Completely Agree +4 3 10.3% 0 0.0% 1 9.1% 2 22.2% 1 9.1% 7 10.1%

+3 9 31.0% 3 33.3% 9 81.8% 3 33.3% 5 45.5% 29 42.0%+2 7 24.1% 3 33.3% 1 9.1% 2 22.2% 3 27.3% 16 23.2%+1 3 10.3% 2 22.2% 0 0.0% 1 11.1% 2 18.2% 8 11.6%

Neutral 0 3 10.3% 1 11.1% 0 0.0% 1 11.1% 0 0.0% 5 7.2%-1 3 10.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 3 4.3%-2 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.4%-3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%

Table 4-20 : Financial and Commercial Gains, Increase Market Share, and Project Success

Survey Question 41Japan Germany Italy USA Other Total

Question 41 : My company measures project success based on what was achieved commercially, financially, increase market share.

As with Question / Comment 40, again there was strong agreement with

commercial and financial indicators of project success. American and Italian

responses indicated a stronger more complete agreement as opposed to Japanese

and German whose responses are more spread. We hypothesize that this relates to

the desire to increase market share by relatively newer Italian manufacturers both

140

in the United States and globally. Along those lines this would also indicate the

desire for American manufacturers in this industry to perhaps regain some market

share lost to foreign competitors. Japanese respondents were more spread which

would indicate perhaps some stability in their situation in the industry.

f % f % f % f % f % f %Completely Agree +4 3 10.3% 0 0.0% 1 9.1% 1 11.1% 3 27.3% 8 11.8%

+3 6 20.7% 4 50.0% 5 45.5% 1 11.1% 3 27.3% 19 27.9%+2 8 27.6% 4 50.0% 4 36.4% 3 33.3% 3 27.3% 22 32.4%+1 4 13.8% 0 0.0% 1 9.1% 1 11.1% 2 18.2% 8 11.8%

Neutral 0 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9%-1 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%-2 3 10.3% 0 0.0% 0 0.0% 2 22.2% 0 0.0% 5 7.4%-3 3 10.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 3 4.4%

Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-21 : Risk Management and Project Success

Survey Question 42Japan Germany Italy USA Other Total

Question 42 : A very important aspect of project success is how effectively you deal with the inevitable problems that arise during the project; in other words, Risk Management.

A good majority, as indicated by the results, feels that risk management is also a

measure of project success although Japanese respondents do not have a very

strong preference for this particular measure.

f % f % f % f % f % f %Completely Agree +4 5 17.2% 0 0.0% 1 9.1% 3 33.3% 2 18.2% 11 16.2%

+3 14 48.3% 3 37.5% 7 63.6% 0 0.0% 3 27.3% 27 39.7%+2 6 20.7% 4 50.0% 2 18.2% 4 44.4% 1 9.1% 17 25.0%+1 2 6.9% 0 0.0% 0 0.0% 2 22.2% 2 18.2% 6 8.8%

Neutral 0 0 0.0% 1 12.5% 1 9.1% 0 0.0% 3 27.3% 5 7.4%-1 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%-2 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%-3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-22 : Projects and Opportunity for Knowledge Creation

Survey Question 43Japan Germany Italy USA Other Total

Question 43 : The unique nature of projects means that there are many opportunities for knowledge creation both at the subsidiary and at headquarters.

Results show that Japanese respondents tend to value to a somewhat greater

extent than their counterparts the opportunity for knowledge creation within the

141

context of new projects. Although both German and Italian respondents agree that

this is an important factor and measure, Japanese response indicates a complete

agreement at more than 17%. However interestingly enough American respondents

also strongly agree at more than 33% that there is opportunity for knowledge

creation within projects. It would seem that Japanese companies, in addition to their

American counterparts, understand a little bit better the relationship in knowledge

creation with new experiences such as projects. This goes back Nonaka and

Takeuchi’s [87] concepts in creating knowledge.

f % f % f % f % f % f %Completely Agree +4 5 17.2% 0 0.0% 3 27.3% 2 22.2% 3 27.3% 13 19.1%

+3 8 27.6% 3 37.5% 5 45.5% 0 0.0% 5 45.5% 21 30.9%+2 9 31.0% 5 62.5% 3 27.3% 4 44.4% 1 9.1% 22 32.4%+1 4 13.8% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 6 8.8%

Neutral 0 0 0.0% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 2 2.9%-1 2 6.9% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 3 4.4%-2 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%-3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%

TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%

Table 4-23 : Project Success and Successful Knowledge Transfer

Survey Question 44Japan Germany Italy USA Other Total

Question 44 : Successful Knowledge transfer among all parties involved in a project : headquarters, subsidiary, customer, final end-user, is an important measure of project success even though there may be no direct impact at all on cost, delivery, and performance.

Results indicate that Japanese, German, and Italian respondents agree that

knowledge transfer is in fact an important measure of project success. American

response indicates a wider spread and not such a strong agreement as the others.

4.1.5 Project Success at Your Company

The results specific to project success evaluation at the respondents’ companies

are shown in Figures 4-8 thru 4-13 in frequency distribution graphs in order to

better-distinguish some differences between company nationalities.

142

02468

10

121416

f

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

4-8a : Question 45 Percentage of projects delayed due to poor delivery performance. All

0123456789

f

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

4-8b : Question 45 Percentage of projects delayed due to poor

delivery performance.

USA

EuropeAsia

0

2

4

6

8

10

12

f

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

4-9a : Question 46 Percentage of projects experiencing cost overruns leading to decreased margins. All

0

1

2

3

4

5

6

7

f

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

4-9b : Question 46 Percentage of projects experiencing cost

overruns leading to decreased margins.

USAEurope

Asia

0

5

10

15

20

f

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

4-10a : Question 47 Percentage of recurring project business due to good customer satisfaction. All

0123456789

10

f

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

4-10b : Question 47 Percentage of recurring project business

due to good customer satisfaction.USAEurope

Asia

0246

1012141618

8f

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

4-11a : Question 48 Percentage of overall successful projects is…..

All

0

2

4

6

8

10

12

f

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

4-11b : Qestion 48 Percentage of overall successful projects

is…..USA

Europe

Asia

143

0

5

Overall, frequency distribution tabulation and subsequent statistical analyses

indicate that in terms of structuring communication channels, smaller companies

and subsidiaries tend to prefer one-to-one relationships and communication

channels between subsidiary and parent. This typically results in a 56% success

rate on major projects for all companies surveyed. When companies start evolving

into bigger entities, there is increasing disagreement with this one-to-one

relationship and the tendency is for the parent to encourage multilateral

communication channels which tend to slightly increase the success rate of projects

to approximately 68% for all companies surveyed. The potential for increased

resources as the entity grew bigger was considered only in terms of communication

and personnel instead of other material resources, with the exception of

technological communication tools such as video conferencing.

10

15

20

f

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

4-12a : Question 49 Percentage of subsidiary employees with a generally positive outlook and work morale. All

012345678

f

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

4-12b : Question 49 Percentage of subsidiary employees with a

generally positive outlook and work morale.

USA

Europe

Asia

0

5

10

15

20

f

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

4-13a : Question 50 Percentage of dissatisfaction from our parent headquarters is about….. All

012345678

f

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

4-13b : Question 50 Percentage of dissatisfaction from our

parent headquarters is about…..

USA

Europe

Asia

144

The vast majority of companies in this industry maintain the classical definition of

project success of : on-time delivery, on-budget, and meeting all performance

specifications but a significant proportion, over 67% indicated that delivery from

their parent company was the key success factor for these major projects.

4.2 Data Analysis / Hypotheses Testing

Measures of central tendency and dispersion, which we initially consider in our analysis,

“…constitute the fundamental elements of descriptive statistics” [95]. They describe and

summarize a large amount of data typically obtained thru survey methodologies such as

with our own specific research. These analyses are fairly simple and elegant because

they provide description thru single statistical values.

Initial analysis was conducted on all fundamental survey questions in order to obtain a

baseline of our data. This is important because the next step is establishing an analysis

on the relationship among the data, specifically the relationship between variable

established from the various questions. Therefore an understanding of the initial data

disposition prior to initiating such a relational analysis is important. If there already exists

some initial relationship prior to our correlational methodology, it needs to be identified

and accounted for within the subsequent analysis we are most interested in below.

The simple arithmetic mean was calculated to identify data located above and below the

central point in addition to providing a relative distance of the data to that point. This is

important in order to establish the baseline for each survey question from which

145

subsequent analyses such as ANOVA will be handled. The median also was calculated

to provide an additional measure comparable to the arithmetic mean. According to Rea

and Parker [95] when working with cross-tabulated contingency tables, “…it is normal

not to expect the median and the mean to coincide or even be close in magnitude to

each other based on a scaled frequency distribution used such as a Likert Scale…” [95].

Based on Rea and Parker’s “Designing and Conducting Survey Research” [95] the

arithmetic mean seems to be the most appropriate measure to consider. We calculated

and documented both this and the median.

The additional measure of central tendency is the mode which is useful in identifying the

particular category (in ordinal scaled surveys) which is “most popular” with respondents,

or most “typical” of the population surveyed. This calculation will help identify some

beliefs and trends and add to our discussion and conclusions from an overall

perspective.

The well-known standard deviation measure was individually calculated in order to

provide a good measure of dispersion that does not eliminate any outliers or extreme

values yet is not overly influenced by them. Finally we included a simple chi-square

calculation (χ2 ) for all the distribution function data obtained for each survey question

so that we could confirm that no initial relationship exists prior to initiating our

correlational analysis relating to our hypotheses.

Our initial analysis is summarized in tabular form in Table 4-23.

146

mean median mode std.dev chi-sqr. mean median mode std.dev chi-sqr. mean median mode std.dev chi-sqr. mean median mode std.dev chi-sqr. mean median mode std.dev chi-sqr. mean median mode std.dev chi-sqr.

x m M s χ2 x m M s χ2 x m M s χ2 x m M s χ2 x m M s χ2 x m M s χ2

1. Question 12 -1.07 15.00 0.00 2.49 0.30 -0.50 4.50 0.00 2.55 0.65 0.50 6.50 1.00 2.78 0.20 -1.11 5.00 1.00 2.47 0.26 -0.90 5.50 0.00 2.39 0.09 -0.71 34.50 2.00 2.60 -2. Question 13 -2.03 15.00 0.00 1.56 0.20 -0.13 4.50 0.00 2.71 0.14 1.18 6.00 0.00 1.75 0.03 -0.67 5.00 0.00 2.67 0.01 -0.40 5.50 2.00 2.58 0.87 -0.85 34.00 6.00 2.40 -3. Question 14 -0.59 15.00 1.00 2.70 0.76 -0.63 4.50 0.00 2.00 0.29 2.18 6.00 0.00 1.03 0.00 -0.67 5.00 1.00 2.94 0.65 -1.10 5.50 0.00 1.64 0.00 -0.22 34.00 2.00 2.56 -4. Question 15 -1.45 15.00 5.00 1.89 0.80 -1.88 4.50 0.00 1.17 0.42 -0.73 6.00 0.00 1.48 0.77 -0.56 5.00 1.00 2.87 0.03 -1.50 5.50 0.00 0.92 0.73 -1.27 34.00 1.00 1.87 -5. Question 16 -1.07 15.00 1.00 2.64 0.69 -0.13 4.50 1.00 2.42 0.52 -0.18 6.00 0.00 3.33 0.05 -2.33 5.00 0.00 2.05 0.75 -1.10 5.50 0.00 1.76 0.17 -0.99 34.00 6.00 2.65 -6. Question 17 -1.52 15.00 1.00 2.19 0.91 -0.25 4.50 1.00 2.73 0.21 -0.80 5.50 0.00 3.16 0.07 -2.33 5.00 0.00 2.00 0.74 -1.20 5.50 1.00 1.60 0.52 -1.32 33.50 - 2.41 -7. Question 18 -0.10 15.00 1.00 2.82 0.48 -0.25 4.50 0.00 2.82 0.18 -0.27 6.00 0.00 2.56 0.33 -0.78 5.00 1.00 2.70 0.26 1.00 5.50 1.00 2.45 0.45 -0.07 34.00 7.00 2.76 -8. Question 19 1.34 15.00 2.00 2.71 0.89 -0.75 4.50 0.00 2.73 0.05 0.36 6.00 0.00 3.02 0.36 0.44 5.00 0.00 2.87 0.46 0.70 5.50 1.00 2.37 0.15 0.72 34.00 5.00 2.82 -9. Question 20 2.41 15.00 0.00 1.07 0.57 2.13 4.50 0.00 0.60 0.61 -0.55 6.00 0.00 1.78 0.00 2.33 5.00 0.00 1.41 0.30 2.00 6.00 0.00 1.54 0.33 1.82 34.50 0.00 1.67 -

10. Question 21 2.59 15.00 0.00 1.22 0.11 1.63 4.50 0.00 0.70 0.01 2.73 6.00 0.00 0.86 0.01 3.00 5.00 0.00 1.41 0.17 2.36 6.00 0.00 1.23 0.27 2.51 34.50 0.00 1.21 -11. Question 22 -1.00 15.00 1.00 1.95 0.72 1.13 4.50 0.00 0.93 0.09 0.00 6.00 2.00 2.22 0.87 0.11 5.00 0.00 1.97 0.06 0.73 6.00 1.00 2.30 0.62 -0.16 34.50 5.00 2.13 -12. Question 23 1.62 15.00 4.00 2.11 0.61 2.50 4.50 0.00 1.12 0.86 1.45 6.00 0.00 2.10 0.05 0.33 5.00 1.00 1.94 0.12 0.45 6.00 0.00 1.88 0.05 1.34 34.50 6.00 2.07 -13. Question 24 -1.66 15.00 2.00 1.86 0.54 0.78 5.00 1.00 2.57 0.63 -2.55 6.00 0.00 0.50 0.31 2.00 5.00 0.00 2.26 0.01 0.09 6.00 1.00 2.23 0.19 -0.72 35.00 3.00 2.47 -14. Question 25 1.83 15.00 5.00 2.13 0.21 2.50 4.50 0.00 0.71 0.42 2.91 6.00 0.00 0.51 0.61 1.78 5.00 0.00 3.12 0.04 1.91 6.00 0.00 1.44 0.08 2.09 34.50 2.00 1.96 -15. Question 26 -1.24 15.00 0.00 2.11 0.28 -0.75 4.50 0.00 1.41 0.62 0.36 6.00 0.00 2.06 0.31 -2.44 5.00 0.00 1.71 0.06 -0.45 6.00 1.00 1.83 0.54 -0.96 34.50 5.00 2.25 -16. Question 27 1.79 15.00 0.00 2.01 0.50 -0.56 5.00 0.00 2.45 0.01 3.00 6.00 0.00 0.43 0.13 -0.11 5.00 0.00 3.48 0.01 0.55 6.00 1.00 2.10 0.06 1.23 35.00 6.00 2.48 -17. Question 28 -0.93 15.00 1.00 2.75 0.39 -2.25 4.50 0.00 2.05 0.59 -1.73 6.00 0.00 2.09 0.30 -2.11 5.00 0.00 2.13 0.60 -0.91 6.00 1.00 2.02 0.20 -1.37 34.50 4.00 2.45 -18. Question 29 0.00 15.00 1.00 2.36 0.47 1.89 5.00 0.00 1.52 0.63 2.09 6.00 0.00 1.44 0.40 0.67 5.00 0.00 2.26 0.51 0.36 6.00 0.00 1.72 0.11 0.72 35.00 5.00 2.20 -19. Question 30 -0.59 15.00 4.00 2.21 0.38 2.38 4.50 0.00 0.86 0.34 0.45 6.00 0.00 2.39 0.29 1.67 5.00 2.00 1.94 0.16 1.27 6.00 0.00 1.48 0.35 0.53 34.50 - 2.27 -20. Question 31 -0.07 15.00 1.00 1.87 0.46 1.44 5.00 0.00 1.83 0.06 -0.27 6.00 0.00 2.34 0.22 1.22 5.00 0.00 1.75 0.17 2.00 6.00 0.00 1.54 0.24 0.59 35.00 15.00 2.08 -21. Question 32 3.07 15.00 0.00 0.87 - 3.50 4.50 0.00 0.50 - 2.82 6.00 0.00 0.57 - 2.78 5.00 0.00 1.55 - 2.73 6.00 0.00 1.05 - 2.99 34.50 0.00 0.98 -22. Question 33 0.00 15.00 1.00 2.15 0.40 0.22 5.00 0.00 1.81 0.93 -1.45 6.00 0.00 1.16 0.03 1.56 5.00 0.00 1.17 0.12 0.73 6.00 0.00 1.81 0.03 0.12 35.00 8.00 2.00 -23. Question 34 -0.72 15.00 1.00 1.82 0.09 2.00 5.00 0.00 0.82 0.00 -2.82 6.00 0.00 0.57 0.00 0.78 5.00 0.00 1.99 0.21 0.36 6.00 2.00 1.72 0.65 -0.33 35.00 7.00 2.12 -24. Question 35 -2.24 15.00 0.00 1.38 - 0.00 4.50 0.00 2.29 - -2.91 6.00 0.00 0.67 - 1.00 5.00 0.00 1.83 - 0.18 6.00 0.00 1.80 - -1.26 34.50 6.00 2.13 -25. Question 36 2.10 15.00 3.00 1.81 0.99 2.78 5.00 0.00 0.63 0.38 1.64 7.50 0.00 2.22 0.17 2.67 5.00 0.00 1.49 0.17 2.36 6.00 0.00 1.23 0.49 2.21 36.50 0.00 1.72 -26. Question 37 2.69 15.00 0.00 1.34 - 3.13 4.50 0.00 0.33 - 2.91 6.00 0.00 0.51 - 2.78 5.00 0.00 1.23 - 3.09 6.00 0.00 0.67 - 2.85 34.50 0.00 1.06 -27. Question 38 -1.38 15.00 1.00 2.06 0.83 -1.33 5.00 0.00 2.11 0.43 -3.00 6.00 0.00 0.60 0.16 0.22 5.00 1.00 2.30 0.89 0.55 6.00 1.00 1.83 0.02 -1.12 35.00 4.00 2.22 -28. Question 39 1.66 15.00 0.00 1.79 0.15 2.38 4.50 0.00 0.70 0.13 1.91 6.00 0.00 2.54 0.00 1.44 5.00 1.00 1.42 0.17 2.27 6.00 0.00 1.48 0.60 1.85 34.50 - 1.78 -29. Question 40 2.76 15.00 0.00 1.38 0.70 2.75 4.50 0.00 0.66 0.63 3.18 6.00 0.00 0.57 0.35 2.44 5.00 0.00 0.96 0.33 2.64 6.00 0.00 1.07 0.51 2.76 34.50 0.00 1.13 -30. Question 41 1.76 15.00 3.00 1.63 0.61 1.89 5.00 0.00 0.99 0.80 3.00 6.00 0.00 0.43 0.25 2.44 5.00 0.00 1.26 0.90 2.45 6.00 0.00 0.89 0.92 2.17 35.00 0.00 1.35 -31. Question 42 1.17 15.00 3.00 2.18 0.74 2.50 4.50 0.00 0.50 0.62 2.55 6.00 0.00 0.78 0.87 1.11 5.00 1.00 1.97 0.52 2.64 6.00 0.00 1.07 0.72 1.78 34.50 8.00 1.83 -32. Question 43 2.52 15.00 0.00 1.35 0.60 2.13 4.50 0.00 0.93 0.60 2.64 6.00 0.00 0.98 0.75 0.00 5.00 0.00 2.71 0.16 1.91 6.00 0.00 1.50 0.18 2.38 34.50 1.00 1.28 -33. Question 44 2.14 15.00 0.00 1.50 0.81 2.38 4.50 0.00 0.48 0.51 3.00 6.00 0.00 0.74 0.79 1.78 5.00 0.00 1.55 0.38 2.73 6.00 0.00 1.21 0.54 2.35 34.50 0.00 1.34 -

OTHER

Table 4-23 : Descriptive Statistics Analysis Summary for Survey Questions - Sections B, C, D, E

TOTALJAPAN GERMANY ITALY USA

147

4.2.1 Targeted Correlational Analysis

The analysis presented in this and the following section was done utilizing the

software MiniTab® (ver.14). Additionally, Microsoft’s Visio® was used to graphically

consolidate and represent the material in a consistent manner within this report.

24-US

20-U

S

43210

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 1.15617R-Sq 6.4%R-Sq(adj) 0.0%

Fitted Line Plot20-US = 0.7857 + 0.2143 24-US

24-IT

20-I

T

6543210

6

5

4

3

2

1

0

S 1.99256R-Sq 17.2%R-Sq(adj) 5.3%

Fitted Line Plot20-IT = 0.7967 + 0.3481 24-IT

24-GR

20-G

R

2.01.51.00.50.0

5

4

3

2

1

0

S 1.45023R-Sq 35.7%R-Sq(adj) 26.5%

Fitted Line Plot20-GR = - 0.2778 + 1.167 24-GR

24-JP

20-J

P

14121086420

9

8

7

6

5

4

3

2

1

0

S 3.77087R-Sq 16.7%R-Sq(adj) 4.9%

Fitted Line Plot20-JP = 4.386 - 0.3611 24-JP

20, 22, 24

HB1 Daily communication method and trust.Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

As. Primary Attrib. Set(s) :

Basic and International Communication, Corporate and National Culture

Correlations: 20-JP, 24-JP Pearson correlation of 20-JP and 24-JP = -0.409P-Value = 0.274

Correlations: 20-GR, 24-GR Pearson correlation of 20-GR and 24-GR = 0.597P-Value = 0.089

Regression Analysis: 20-JP versus 24-JP The regression equation is20-JP = 4.39 - 0.361 24-JPPredictor Coef SE Coef T PConstant 4.386 1.594 2.75 0.02824-JP -0.3611 0.3043 -1.19 0.274S = 3.77087 R-Sq = 16.7% R-Sq(adj) = 4.9%Analysis of VarianceSource DF SS MS F PRegression 1 20.02 20.02 1.41 0.274Residual Error 7 99.54 14.22Total 8 119.56

Regression Analysis: 20-GR versus 24-GR The regression equation is20-GR = - 0.278 + 1.17 24-GRPredictor Coef SE Coef T PConstant -0.2778 0.7643 -0.36 0.72724-GR 1.1667 0.5921 1.97 0.089S = 1.45023 R-Sq = 35.7% R-Sq(adj) = 26.5%Analysis of VarianceSource DF SS MS F PRegression 1 8.167 8.167 3.88 0.089Residual Error 7 14.722 2.103Total 8 22.889

Correlations: 20-IT, 24-IT Pearson correlation of 20-IT and 24-IT = 0.414P-Value = 0.267

Correlations: 20-US, 24-US Pearson correlation of 20-US and 24-US = 0.254P-Value = 0.510

Regression Analysis: 20-IT versus 24-IT The regression equation is20-IT = 0.797 + 0.348 24-ITPredictor Coef SE Coef T PConstant 0.7967 0.7522 1.06 0.32524-IT 0.3481 0.2889 1.20 0.267S = 1.99256 R-Sq = 17.2% R-Sq(adj) = 5.3%Analysis of VarianceSource DF SS MS F PRegression 1 5.763 5.763 1.45 0.267Residual Error 7 27.792 3.970Total 8 33.556

Regression Analysis: 20-US versus 24-US The regression equation is20-US = 0.786 + 0.214 24-USPredictor Coef SE Coef T PConstant 0.7857 0.4940 1.59 0.15624-US 0.2143 0.3090 0.69 0.510S = 1.15617 R-Sq = 6.4% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.643 0.643 0.48 0.510Residual Error 7 9.357 1.337Total 8 10.000

148

24-US

22-U

S

43210

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 1.19095R-Sq 0.7%R-Sq(adj) 0.0%

Fitted Line Plot22-US = 1.071 - 0.0714 24-US

24-IT

22-I

T

6543210

2.0

1.5

1.0

0.5

0.0

S 0.757473R-Sq 27.7%R-Sq(adj) 17.4%

Fitted Line Plot22-IT = 1.002 + 0.1799 24-IT

24-GR

22-G

R

2.01.51.00.50.0

4

3

2

1

0

S 1.61344R-Sq 3.5%R-Sq(adj) 0.0%

Fitted Line Plot22-GR = 0.5556 + 0.3333 24-GR

24-JP

22-J

P

14121086420

7

6

5

4

3

2

1

0

S 2.00617R-Sq 40.8%R-Sq(adj) 32.3%

Fitted Line Plot22-JP = 2.077 + 0.3553 24-JP

20, 22, 24

HB1 Daily communication method and trust.Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

As. Primary Attrib. Set(s) :

Basic and International Communication, Corporate and National Culture

Correlations: 22-US, 24-US Pearson correlation of 22-US and 24-US = -0.085P-Value = 0.829

Correlations: 22-IT, 24-IT Pearson correlation of 22-IT and 24-IT = 0.526P-Value = 0.145

Correlations: 22-GR, 24-GR Pearson correlation of 22-GR and 24-GR = 0.188P-Value = 0.628

Correlations: 22-JP, 24-JP Pearson correlation of 22-JP and 24-JP = 0.638P-Value = 0.064

Regression Analysis: 22-IT versus 24-IT The regression equation is22-IT = 1.00 + 0.180 24-ITPredictor Coef SE Coef T PConstant 1.0023 0.2860 3.51 0.01024-IT 0.1799 0.1098 1.64 0.145S = 0.757473 R-Sq = 27.7% R-Sq(adj) = 17.4%Analysis of VarianceSource DF SS MS F PRegression 1 1.5392 1.5392 2.68 0.145Residual Error 7 4.0164 0.5738

Regression Analysis: 22-US versus 24-US The regression equation is22-US = 1.07 - 0.071 24-USPredictor Coef SE Coef T PConstant 1.0714 0.5088 2.11 0.07324-US -0.0714 0.3183 -0.22 0.829S = 1.19095 R-Sq = 0.7% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.071 0.071 0.05 0.829Residual Error 7 9.929 1.418Total 8 10.000

Regression Analysis: 22-GR versus 24-GR The regression equation is22-GR = 0.556 + 0.333 24-GRPredictor Coef SE Coef T PConstant 0.5556 0.8504 0.65 0.53424-GR 0.3333 0.6587 0.51 0.628S = 1.61344 R-Sq = 3.5% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.667 0.667 0.26 0.628Residual Error 7 18.222 2.603Total 8 18.889

Regression Analysis: 22-JP versus 24-JP The regression equation is22-JP = 2.08 + 0.355 24-JPPredictor Coef SE Coef T PConstant 2.0774 0.8481 2.45 0.04424-JP 0.3553 0.1619 2.19 0.064S = 2.00617 R-Sq = 40.8% R-Sq(adj) = 32.3%Analysis of VarianceSource DF SS MS F PRegression 1 19.383 19.383 4.82 0.064Residual Error 7 28.173 4.025Total 8 47.556

149

24-US

12-U

S

43210

2.0

1.5

1.0

0.5

0.0

S 0.699854R-Sq 42.9%R-Sq(adj) 34.7%

Fitted Line Plot12-US = 1.429 - 0.4286 24-US

24-IT

12-I

T

6543210

5

4

3

2

1

0

S 1.68873R-Sq 0.2%R-Sq(adj) 0.0%

Fitted Line Plot12-IT = 1.299 + 0.0280 24-IT

24-GR

12-G

R

2.01.51.00.50.0

4

3

2

1

0

S 1.42539R-Sq 4.5%R-Sq(adj) 0.0%

Fitted Line Plot12-GR = 0.5556 + 0.3333 24-GR

24-JP

12-J

P

14121086420

7

6

5

4

3

2

1

0

S 2.81127R-Sq 13.0%R-Sq(adj) 0.5%

Fitted Line Plot12-JP = 2.476 + 0.2315 24-JP

12, 14, 16, 18, 24

HB2 Communication channel between subsidiary and parent company; and trust

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

International Communication and Corp. CultureAs. Primary

Attrib. Set(s) :

Correlations: 12-JP, 24-JP Pearson correlation of 12-JP and 24-JP = 0.360P-Value = 0.341

Correlations: 12-GR, 24-GR Pearson correlation of 12-GR and 24-GR = 0.212P-Value = 0.585

Correlations: 12-IT, 24-IT Pearson correlation of 12-IT and 24-IT = 0.043P-Value = 0.912

Correlations: 12-US, 24-US Pearson correlation of 12-US and 24-US = -0.655P-Value = 0.056

Regression Analysis: 12-US versus 24-US The regression equation is12-US = 1.43 - 0.429 24-USPredictor Coef SE Coef T PConstant 1.4286 0.2990 4.78 0.00224-US -0.4286 0.1870 -2.29 0.056S = 0.699854 R-Sq = 42.9% R-Sq(adj) = 34.7%Analysis of VarianceSource DF SS MS F PRegression 1 2.5714 2.5714 5.25 0.056Residual Error 7 3.4286 0.4898Total 8 6.0000

Regression Analysis: 12-IT versus 24-IT The regression equation is12-IT = 1.30 + 0.028 24-ITPredictor Coef SE Coef T PConstant 1.2991 0.6375 2.04 0.08124-IT 0.0280 0.2449 0.11 0.912S = 1.68873 R-Sq = 0.2% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.037 0.037 0.01 0.912Residual Error 7 19.963 2.852Total 8 20.000

Regression Analysis: 12-GR versus 24-GR The regression equation is12-GR = 0.556 + 0.333 24-GRPredictor Coef SE Coef T PConstant 0.5556 0.7512 0.74 0.48424-GR 0.3333 0.5819 0.57 0.585S = 1.42539 R-Sq = 4.5% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.667 0.667 0.33 0.585Residual Error 7 14.222 2.032Total 8 14.889

Regression Analysis: 12-JP versus 24-JP The regression equation is12-JP = 2.48 + 0.232 24-JPPredictor Coef SE Coef T PConstant 2.476 1.188 2.08 0.07624-JP 0.2315 0.2269 1.02 0.341S = 2.81127 R-Sq = 13.0% R-Sq(adj) = 0.5%Analysis of VarianceSource DF SS MS F PRegression 1 8.233 8.233 1.04 0.341Residual Error 7 55.323 7.903Total 8 63.556

150

24-IT

14-I

T

6543210

6

5

4

3

2

1

0

S 1.99122R-Sq 12.0%R-Sq(adj) 0.0%

Fitted Line Plot14-IT = 1.568 - 0.2827 24-IT

24-US

14-U

S

43210

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 0.989743R-Sq 14.3%R-Sq(adj) 2.0%

Fitted Line Plot14-US = 1.286 - 0.2857 24-US

24-GR

14-G

R

2.01.51.00.50.0

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 1.35693R-Sq 0.0%R-Sq(adj) 0.0%

Fitted Line Plot14-GR = 0.8889 + 0.0000 24-GR

24-JP

14-J

P

14121086420

7

6

5

4

3

2

1

0

S 2.66647R-Sq 3.5%R-Sq(adj) 0.0%

Fitted Line Plot14-JP = 2.875 + 0.1078 24-JP

12, 14, 16, 18, 24

HB2 Communication channel between subsidiary and parent company; and trust

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

International Communication and Corp. CultureAs. Primary

Attrib. Set(s) :

Correlations: 14-US, 24-US Pearson correlation of 14-US and 24-US = -0.378P-Value = 0.316

Correlations: 14-IT, 24-IT Pearson correlation of 14-IT and 24-IT = -0.347P-Value = 0.360

Correlations: 14-GR, 24-GR Pearson correlation of 14-GR and 24-GR = 0.000P-Value = 1.000

Correlations: 14-JP, 24-JP Pearson correlation of 14-JP and 24-JP = 0.186P-Value = 0.632

Regression Analysis: 14-JP versus 24-JP The regression equation is14-JP = 2.87 + 0.108 24-JPPredictor Coef SE Coef T PConstant 2.875 1.127 2.55 0.03824-JP 0.1078 0.2152 0.50 0.632S = 2.66647 R-Sq = 3.5% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 1.785 1.785 0.25 0.632Residual Error 7 49.771 7.110Total 8 51.556

Regression Analysis: 14-GR versus 24-GR The regression equation is14-GR = 0.889 + 0.000 24-GRPredictor Coef SE Coef T PConstant 0.8889 0.7152 1.24 0.25424-GR 0.0000 0.5540 0.00 1.000S = 1.35693 R-Sq = 0.0% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.000 0.000 0.00 1.000Residual Error 7 12.889 1.841Total 8 12.889

Regression Analysis: 14-IT versus 24-IT The regression equation is14-IT = 1.57 - 0.283 24-ITPredictor Coef SE Coef T PConstant 1.5678 0.7517 2.09 0.07524-IT -0.2827 0.2887 -0.98 0.360S = 1.99122 R-Sq = 12.0% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 3.801 3.801 0.96 0.360Residual Error 7 27.755 3.965Total 8 31.556

Regression Analysis: 14-US versus 24-US The regression equation is14-US = 1.29 - 0.286 24-USPredictor Coef SE Coef T PConstant 1.2857 0.4229 3.04 0.01924-US -0.2857 0.2645 -1.08 0.316S = 0.989743 R-Sq = 14.3% R-Sq(adj) = 2.0%Analysis of VarianceSource DF SS MS F PRegression 1 1.1429 1.1429 1.17 0.316Residual Error 7 6.8571 0.9796Total 8 8.0000

151

24-IT

16-I

T

6543210

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 1.28927R-Sq 14.2%R-Sq(adj) 1.9%

Fitted Line Plot16-IT = 0.9766 + 0.2009 24-IT

24-US

16-U

S

43210

4

3

2

1

0

S 1.32095R-Sq 12.8%R-Sq(adj) 0.3%

Fitted Line Plot16-US = 1.357 - 0.3571 24-US

24-GR

16-G

R

2.01.51.00.50.0

2.0

1.5

1.0

0.5

0.0

S 0.835711R-Sq 0.0%R-Sq(adj) 0.0%

Fitted Line Plot16-GR = 0.8889 - 0.0000 24-GR

24-JP

16-J

P

14121086420

9

8

7

6

5

4

3

2

1

0

S 2.91353R-Sq 0.2%R-Sq(adj) 0.0%

Fitted Line Plot16-JP = 3.127 + 0.0297 24-JP

12, 14, 16, 18, 24

HB2 Communication channel between subsidiary and parent company; and trust

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

International Communication and Corp. CultureAs. Primary

Attrib. Set(s) :

Correlations: 16-JP, 24-JP Pearson correlation of 16-JP and 24-JP = 0.048P-Value = 0.903

Correlations: 16-GR, 24-GR Pearson correlation of 16-GR and 24-GR = 0.000P-Value = 1.000

Correlations: 16-IT, 24-IT Pearson correlation of 16-IT and 24-IT = 0.376P-Value = 0.318

Correlations: 16-US, 24-US Pearson correlation of 16-US and 24-US = -0.357P-Value = 0.345

Regression Analysis: 16-US versus 24-US The regression equation is16-US = 1.36 - 0.357 24-USPredictor Coef SE Coef T PConstant 1.3571 0.5644 2.40 0.04724-US -0.3571 0.3530 -1.01 0.345S = 1.32095 R-Sq = 12.8% R-Sq(adj) = 0.3%Analysis of VarianceSource DF SS MS F PRegression 1 1.786 1.786 1.02 0.345Residual Error 7 12.214 1.745Total 8 14.000

Regression Analysis: 16-IT versus 24-IT The regression equation is16-IT = 0.977 + 0.201 24-ITPredictor Coef SE Coef T PConstant 0.9766 0.4867 2.01 0.08524-IT 0.2009 0.1870 1.07 0.318S = 1.28927 R-Sq = 14.2% R-Sq(adj) = 1.9%Analysis of VarianceSource DF SS MS F PRegression 1 1.920 1.920 1.16 0.318Residual Error 7 11.636 1.662Total 8 13.556

Regression Analysis: 16-GR versus 24-GR The regression equation is16-GR = 0.889 - 0.000 24-GRPredictor Coef SE Coef T PConstant 0.8889 0.4405 2.02 0.08324-GR -0.0000 0.3412 -0.00 1.000S = 0.835711 R-Sq = 0.0% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.0000 0.0000 0.00 1.000Residual Error 7 4.8889 0.6984Total 8 4.8889

Regression Analysis: 16-JP versus 24-JP The regression equation is16-JP = 3.13 + 0.030 24-JPPredictor Coef SE Coef T PConstant 3.127 1.232 2.54 0.03924-JP 0.0297 0.2351 0.13 0.903S = 2.91353 R-Sq = 0.2% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.135 0.135 0.02 0.903Residual Error 7 59.420 8.489Total 8 59.556

152

24-IT

18-I

T

6543210

5

4

3

2

1

0

S 1.59428R-Sq 24.5%R-Sq(adj) 13.7%

Fitted Line Plot18-IT = 0.7967 + 0.3481 24-IT

24-US

18-U

S

43210

2.0

1.5

1.0

0.5

0.0

S 0.749149R-Sq 1.8%R-Sq(adj) 0.0%

Fitted Line Plot18-US = 1.071 - 0.0714 24-US

24-GR

18-G

R

2.01.51.00.50.0

4

3

2

1

0

S 1.23764R-Sq 43.2%R-Sq(adj) 35.1%

Fitted Line Plot18-GR = - 0.2778 + 1.167 24-GR

24-JP

18-J

P

14121086420

9

8

7

6

5

4

3

2

1

0

S 2.79606R-Sq 27.6%R-Sq(adj) 17.2%

Fitted Line Plot18-JP = 2.035 + 0.3683 24-JP

12, 14, 16, 18, 24

HB2 Communication channel between subsidiary and parent company; and trust

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

International Communication and Corp. CultureAs. Primary

Attrib. Set(s) :

Correlations: 18-US, 24-US Pearson correlation of 18-US and 24-US = -0.134P-Value = 0.732

Correlations: 18-IT, 24-IT Pearson correlation of 18-IT and 24-IT = 0.495P-Value = 0.176

Correlations: 18-GR, 24-GR Pearson correlation of 18-GR and 24-GR = 0.658P-Value = 0.054

Correlations: 18-JP, 24-JP Pearson correlation of 18-JP and 24-JP = 0.525P-Value = 0.147

Regression Analysis: 18-JP versus 24-JP The regression equation is18-JP = 2.04 + 0.368 24-JPPredictor Coef SE Coef T PConstant 2.035 1.182 1.72 0.12924-JP 0.3683 0.2256 1.63 0.147S = 2.79606 R-Sq = 27.6% R-Sq(adj) = 17.2%Analysis of VarianceSource DF SS MS F PRegression 1 20.830 20.830 2.66 0.147Residual Error 7 54.726 7.818Total 8 75.556

Regression Analysis: 18-GR versus 24-GR The regression equation is18-GR = - 0.278 + 1.17 24-GRPredictor Coef SE Coef T PConstant -0.2778 0.6523 -0.43 0.68324-GR 1.1667 0.5053 2.31 0.054S = 1.23764 R-Sq = 43.2% R-Sq(adj) = 35.1%Analysis of VarianceSource DF SS MS F PRegression 1 8.167 8.167 5.33 0.054Residual Error 7 10.722 1.532Total 8 18.889

Regression Analysis: 18-IT versus 24-IT The regression equation is18-IT = 0.797 + 0.348 24-ITPredictor Coef SE Coef T PConstant 0.7967 0.6019 1.32 0.22724-IT 0.3481 0.2312 1.51 0.176S = 1.59428 R-Sq = 24.5% R-Sq(adj) = 13.7%Analysis of VarianceSource DF SS MS F PRegression 1 5.763 5.763 2.27 0.176Residual Error 7 17.792 2.542Total 8 23.556

Regression Analysis: 18-US versus 24-US The regression equation is18-US = 1.07 - 0.071 24-USPredictor Coef SE Coef T PConstant 1.0714 0.3201 3.35 0.01224-US -0.0714 0.2002 -0.36 0.732S = 0.749149 R-Sq = 1.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.0714 0.0714 0.13 0.732Residual Error 7 3.9286 0.5612Total 8 4.0000

153

35-US

12-U

S

3.02.52.01.51.00.50.0

2.0

1.5

1.0

0.5

0.0

S 0.918073R-Sq 1.7%R-Sq(adj) 0.0%

Fitted Line Plot12-US = 1.100 - 0.1000 35-US

35-IT

12-I

T

6543210

5

4

3

2

1

0

S 1.68978R-Sq 0.1%R-Sq(adj) 0.0%

Fitted Line Plot12-IT = 1.356 - 0.0188 35-IT

35-GR

12-G

R

43210

4

3

2

1

0

S 1.42622R-Sq 4.4%R-Sq(adj) 0.0%

Fitted Line Plot12-GR = 1.075 - 0.2090 35-GR

35-JP

12-J

P

121086420

7

6

5

4

3

2

1

0

S 2.83405R-Sq 11.5%R-Sq(adj) 0.0%

Fitted Line Plot12-JP = 2.518 + 0.2185 35-JP

12, 14, 16, 18, 35

HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

As. Primary Attrib. Set(s) :

International Communication; Corp. and National Culture

Correlations: 12-JP, 35-JP Pearson correlation of 12-JP and 35-JP = 0.340P-Value = 0.371

Correlations: 12-GR, 35-GR Pearson correlation of 12-GR and 35-GR = -0.209P-Value = 0.590

Correlations: 12-IT, 35-IT Pearson correlation of 12-IT and 35-IT = -0.025P-Value = 0.949

Correlations: 12-US, 35-US Pearson correlation of 12-US and 35-US = -0.129P-Value = 0.741

Regression Analysis: 12-US versus 35-US The regression equation is12-US = 1.10 - 0.100 35-USPredictor Coef SE Coef T PConstant 1.1000 0.4218 2.61 0.03535-US -0.1000 0.2903 -0.34 0.741S = 0.918073 R-Sq = 1.7% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.1000 0.1000 0.12 0.741Residual Error 7 5.9000 0.8429Total 8 6.0000

Regression Analysis: 12-IT versus 35-IT The regression equation is12-IT = 1.36 - 0.019 35-ITPredictor Coef SE Coef T PConstant 1.3563 0.6612 2.05 0.07935-IT -0.0188 0.2834 -0.07 0.949S = 1.68978 R-Sq = 0.1% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.013 0.013 0.00 0.949Residual Error 7 19.988 2.855Total 8 20.000

Regression Analysis: 12-GR versus 35-GR The regression equation is12-GR = 1.07 - 0.209 35-GRPredictor Coef SE Coef T PConstant 1.0746 0.5779 1.86 0.10535-GR -0.2090 0.3696 -0.57 0.590S = 1.42622 R-Sq = 4.4% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.650 0.650 0.32 0.590Residual Error 7 14.239 2.034Total 8 14.889

Regression Analysis: 12-JP versus 35-JP The regression equation is12-JP = 2.52 + 0.219 35-JPPredictor Coef SE Coef T PConstant 2.518 1.198 2.10 0.07435-JP 0.2185 0.2287 0.96 0.371S = 2.83405 R-Sq = 11.5% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 7.333 7.333 0.91 0.371Residual Error 7 56.223 8.032Total 8 63.556

154

35-IT

14-I

T

6543210

6

5

4

3

2

1

0

S 1.94466R-Sq 16.1%R-Sq(adj) 4.1%

Fitted Line Plot14-IT = 1.684 - 0.3781 35-IT

35-US

14-U

S

3.02.52.01.51.00.50.0

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 1.00712R-Sq 11.3%R-Sq(adj) 0.0%

Fitted Line Plot14-US = 0.7000 + 0.3000 35-US

35-GR

14-G

R

43210

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 1.11541R-Sq 32.4%R-Sq(adj) 22.8%

Fitted Line Plot14-GR = 0.4179 + 0.5299 35-GR

35-JP

14-J

P

121086420

7

6

5

4

3

2

1

0

S 2.63302R-Sq 5.9%R-Sq(adj) 0.0%

Fitted Line Plot14-JP = 2.770 + 0.1404 35-JP

12, 14, 16, 18, 35

HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

As. Primary Attrib. Set(s) :

International Communication; Corp. and National Culture

Correlations: 14-JP, 35-JP Pearson correlation of 14-JP and 35-JP = 0.242P-Value = 0.530

Correlations: 14-GR, 35-GR Pearson correlation of 14-GR and 35-GR = 0.569P-Value = 0.109

Correlations: 14-IT, 35-IT Pearson correlation of 14-IT and 35-IT = -0.401P-Value = 0.284

Correlations: 14-US, 35-US Pearson correlation of 14-US and 35-US = 0.335P-Value = 0.378

Regression Analysis: 14-US versus 35-US The regression equation is14-US = 0.700 + 0.300 35-USPredictor Coef SE Coef T PConstant 0.7000 0.4627 1.51 0.17435-US 0.3000 0.3185 0.94 0.378S = 1.00712 R-Sq = 11.3% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.900 0.900 0.89 0.378Residual Error 7 7.100 1.014Total 8 8.00

Regression Analysis: 14-IT versus 35-IT The regression equation is14-IT = 1.68 - 0.378 35-ITPredictor Coef SE Coef T PConstant 1.6844 0.7610 2.21 0.06235-IT -0.3781 0.3261 -1.16 0.284S = 1.94466 R-Sq = 16.1% R-Sq(adj) = 4.1%Analysis of VarianceSource DF SS MS F PRegression 1 5.084 5.084 1.34 0.284Residual Error 7 26.472 3.782Total 8 31.556

Regression Analysis: 14-GR versus 35-GR The regression equation is14-GR = 0.418 + 0.530 35-GRPredictor Coef SE Coef T PConstant 0.4179 0.4520 0.92 0.38635-GR 0.5299 0.2891 1.83 0.109S = 1.11541 R-Sq = 32.4% R-Sq(adj) = 22.8%Analysis of VarianceSource DF SS MS F PRegression 1 4.180 4.180 3.36 0.109Residual Error 7 8.709 1.244Total 8 12.889

Regression Analysis: 14-JP versus 35-JP The regression equation is14-JP = 2.77 + 0.140 35-JPPredictor Coef SE Coef T PConstant 2.770 1.113 2.49 0.04235-JP 0.1404 0.2125 0.66 0.530S = 2.63302 R-Sq = 5.9% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 3.026 3.026 0.44 0.530Residual Error 7 48.530 6.933Total 8 51.556

155

35-US

16-U

S

3.02.52.01.51.00.50.0

4

3

2

1

0

S 1.39386R-Sq 2.9%R-Sq(adj) 0.0%

Fitted Line Plot16-US = 1.200 - 0.2000 35-US

35-IT

16-I

T

6543210

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 1.18322R-Sq 27.7%R-Sq(adj) 17.4%

Fitted Line Plot16-IT = 0.8250 + 0.3250 35-IT

35-GR

16-G

R

43210

2.0

1.5

1.0

0.5

0.0

S 0.669150R-Sq 35.9%R-Sq(adj) 26.7%

Fitted Line Plot16-GR = 1.194 - 0.3433 35-GR

35-JP

16-J

P

121086420

9

8

7

6

5

4

3

2

1

0

S 2.81076R-Sq 7.1%R-Sq(adj) 0.0%

Fitted Line Plot16-JP = 2.686 + 0.1664 35-JP

12, 14, 16, 18, 35

HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

As. Primary Attrib. Set(s) :

International Communication; Corp. and National Culture

Correlations: 16-JP, 35-JP Pearson correlation of 16-JP and 35-JP = 0.267P-Value = 0.487

Correlations: 16-GR, 35-GR Pearson correlation of 16-GR and 35-GR = -0.599P-Value = 0.088

Correlations: 16-IT, 35-IT Pearson correlation of 16-IT and 35-IT = 0.526P-Value = 0.145

Regression Analysis: 16-JP versus 35-JP The regression equation is16-JP = 2.69 + 0.166 35-JPPredictor Coef SE Coef T PConstant 2.686 1.188 2.26 0.05835-JP 0.1664 0.2268 0.73 0.487S = 2.81076 R-Sq = 7.1% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 4.253 4.253 0.54 0.487Residual Error 7 55.302 7.900Total 8 59.556

Regression Analysis: 16-GR versus 35-GR The regression equation is16-GR = 1.19 - 0.343 35-GRPredictor Coef SE Coef T PConstant 1.1940 0.2711 4.40 0.00335-GR -0.3433 0.1734 -1.98 0.088S = 0.669150 R-Sq = 35.9% R-Sq(adj) = 26.7%Analysis of VarianceSource DF SS MS F PRegression 1 1.7546 1.7546 3.92 0.088Residual Error 7 3.1343 0.4478Total 8 4.8889

Regression Analysis: 16-IT versus 35-IT The regression equation is16-IT = 0.825 + 0.325 35-ITPredictor Coef SE Coef T PConstant 0.8250 0.4630 1.78 0.11835-IT 0.3250 0.1984 1.64 0.145S = 1.18322 R-Sq = 27.7% R-Sq(adj) = 17.4%Analysis of VarianceSource DF SS MS F PRegression 1 3.756 3.756 2.68 0.145Residual Error 7 9.800 1.400Total 8 13.556

Regression Analysis: 16-US versus 35-US The regression equation is16-US = 1.20 - 0.200 35-USPredictor Coef SE Coef T PConstant 1.2000 0.6404 1.87 0.10335-US -0.2000 0.4408 -0.45 0.664S = 1.39386 R-Sq = 2.9% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.400 0.400 0.21 0.664Residual Error 7 13.600 1.943Total 8 14.000

156

35-US

18-U

S

3.02.52.01.51.00.50.0

2.0

1.5

1.0

0.5

0.0

S 0.665475R-Sq 22.5%R-Sq(adj) 11.4%

Fitted Line Plot18-US = 1.300 - 0.3000 35-US

35-IT

18-I

T

6543210

5

4

3

2

1

0

S 1.50461R-Sq 32.7%R-Sq(adj) 23.1%

Fitted Line Plot18-IT = 0.6531 + 0.4656 35-IT

35-GR

18-G

R

43210

4

3

2

1

0

S 1.63223R-Sq 1.3%R-Sq(adj) 0.0%

Fitted Line Plot18-GR = 0.7761 + 0.1269 35-GR

35-JP

18-J

P

121086420

9

8

7

6

5

4

3

2

1

0

S 2.91702R-Sq 21.2%R-Sq(adj) 9.9%

Fitted Line Plot18-JP = 2.182 + 0.3227 35-JP

12, 14, 16, 18, 35

HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

As. Primary Attrib. Set(s) :

International Communication; Corp. and National Culture

Correlations: 18-JP, 35-JP Pearson correlation of 18-JP and 35-JP = 0.460P-Value = 0.213

Correlations: 18-GR, 35-GR Pearson correlation of 18-GR and 35-GR = 0.113P-Value = 0.773

Correlations: 18-IT, 35-IT Pearson correlation of 18-IT and 35-IT = 0.572P-Value = 0.108

Regression Analysis: 18-JP versus 35-JP The regression equation is18-JP = 2.18 + 0.323 35-JPPredictor Coef SE Coef T PConstant 2.182 1.233 1.77 0.12035-JP 0.3227 0.2354 1.37 0.213S = 2.91702 R-Sq = 21.2% R-Sq(adj) = 9.9%Analysis of VarianceSource DF SS MS F PRegression 1 15.993 15.993 1.88 0.213Residual Error 7 59.563 8.509Total 8 75.556

Regression Analysis: 18-GR versus 35-GR The regression equation is18-GR = 0.776 + 0.127 35-GRPredictor Coef SE Coef T PConstant 0.7761 0.6614 1.17 0.27935-GR 0.1269 0.4230 0.30 0.773S = 1.63223 R-Sq = 1.3% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.240 0.240 0.09 0.773Residual Error 7 18.649 2.664Total 8 18.889

Regression Analysis: 18-IT versus 35-IT The regression equation is18-IT = 0.653 + 0.466 35-ITPredictor Coef SE Coef T PConstant 0.6531 0.5888 1.11 0.30435-IT 0.4656 0.2523 1.85 0.108S = 1.50461 R-Sq = 32.7% R-Sq(adj) = 23.1%Analysis of VarianceSource DF SS MS F PRegression 1 7.709 7.709 3.41 0.108Residual Error 7 15.847 2.264Total 8 23.556

Regression Analysis: 18-US versus 35-US The regression equation is18-US = 1.30 - 0.300 35-USPredictor Coef SE Coef T PConstant 1.3000 0.3058 4.25 0.00435-US -0.3000 0.2104 -1.43 0.197S = 0.665475 R-Sq = 22.5% R-Sq(adj) = 11.4%Analysis of VarianceSource DF SS MS F PRegression 1 0.9000 0.9000 2.03 0.197Residual Error 7 3.1000 0.4429Total 8 4.0000

157

24-US

18-U

S

43210

2.0

1.5

1.0

0.5

0.0

S 0.749149R-Sq 1.8%R-Sq(adj) 0.0%

Fitted Line Plot18-US = 1.071 - 0.0714 24-US

24-IT

18-I

T

6543210

5

4

3

2

1

0

S 1.59428R-Sq 24.5%R-Sq(adj) 13.7%

Fitted Line Plot18-IT = 0.7967 + 0.3481 24-IT

24-GR

18-G

R

2.01.51.00.50.0

4

3

2

1

0

S 1.23764R-Sq 43.2%R-Sq(adj) 35.1%

Fitted Line Plot18-GR = - 0.2778 + 1.167 24-GR

24-JP

18-J

P

14121086420

9

8

7

6

5

4

3

2

1

0

S 2.79606R-Sq 27.6%R-Sq(adj) 17.2%

Fitted Line Plot18-JP = 2.035 + 0.3683 24-JP

18, 24

HB4 Many-to-many subsidiary communication channel and learning / trusting relationship

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

As. Primary Attrib. Set(s) :

International Communication; Corp. and National Culture; trust (as a major subset attribute)

Correlations: 18-JP, 24-JP Pearson correlation of 18-JP and 24-JP = 0.525P-Value = 0.147

Correlations: 18-GR, 24-GR Pearson correlation of 18-GR and 24-GR = 0.658P-Value = 0.054

Regression Analysis: 18-JP versus 24-JP The regression equation is18-JP = 2.04 + 0.368 24-JPPredictor Coef SE Coef T PConstant 2.035 1.182 1.72 0.12924-JP 0.3683 0.2256 1.63 0.147S = 2.79606 R-Sq = 27.6% R-Sq(adj) = 17.2%Analysis of VarianceSource DF SS MS F PRegression 1 20.830 20.830 2.66 0.147Residual Error 7 54.726 7.818Total 8 75.556

Regression Analysis: 18-GR versus 24-GR The regression equation is18-GR = - 0.278 + 1.17 24-GRPredictor Coef SE Coef T PConstant -0.2778 0.6523 -0.43 0.68324-GR 1.1667 0.5053 2.31 0.054S = 1.23764 R-Sq = 43.2% R-Sq(adj) = 35.1%Analysis of VarianceSource DF SS MS F PRegression 1 8.167 8.167 5.33 0.054Residual Error 7 10.722 1.532Total 8 18.889

Correlations: 18-IT, 24-IT Pearson correlation of 18-IT and 24-IT = 0.495P-Value = 0.176

Regression Analysis: 18-IT versus 24-IT The regression equation is18-IT = 0.797 + 0.348 24-ITPredictor Coef SE Coef T PConstant 0.7967 0.6019 1.32 0.22724-IT 0.3481 0.2312 1.51 0.176S = 1.59428 R-Sq = 24.5% R-Sq(adj) = 13.7%Analysis of VarianceSource DF SS MS F PRegression 1 5.763 5.763 2.27 0.176Residual Error 7 17.792 2.542Total 8 23.556

Correlations: 18-US, 24-US Pearson correlation of 18-US and 24-US = -0.134P-Value = 0.732Regression Analysis: 18-US versus 24-US The regression equation is18-US = 1.07 - 0.071 24-USPredictor Coef SE Coef T PConstant 1.0714 0.3201 3.35 0.01224-US -0.0714 0.2002 -0.36 0.732S = 0.749149 R-Sq = 1.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.0714 0.0714 0.13 0.732Residual Error 7 3.9286 0.5612Total 8 4.0000

158

35-US

34-U

S

3.02.52.01.51.00.50.0

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 1.09545R-Sq 16.0%R-Sq(adj) 4.0%

Fitted Line Plot34-US = 0.6000 + 0.4000 35-US

35-IT

34-I

T

6543210

7

6

5

4

3

2

1

0

S 0.470562R-Sq 96.6%R-Sq(adj) 96.1%

Fitted Line Plot34-IT = - 0.1375 + 1.112 35-IT

35-GR

34-G

R

43210

6

5

4

3

2

1

0

-1

S 1.98931R-Sq 13.4%R-Sq(adj) 1.1%

Fitted Line Plot34-GR = 1.478 - 0.5373 35-GR

35-JP

34-J

P

121086420

12

10

8

6

4

2

0

S 3.97364R-Sq 0.9%R-Sq(adj) 0.0%

Fitted Line Plot34-JP = 2.959 + 0.0818 35-JP

34, 35

HC1Employees having direct input to decisions affecting them and shared meaning in succesful KTHypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

Corporate culture, Groups and Teams Communication, trust as a major attribute subset

As. Primary Attrib. Set(s) :

Correlations: 34-JP, 35-JP Pearson correlation of 34-JP and 35-JP = 0.096P-Value = 0.806

Correlations: 34-GR, 35-GR Pearson correlation of 34-GR and 35-GR = -0.367P-Value = 0.332

Correlations: 34-IT, 35-IT Pearson correlation of 34-IT and 35-IT = 0.983P-Value = 0.000

Correlations: 34-US, 35-US Pearson correlation of 34-US and 35-US = 0.400P-Value = 0.286

Regression Analysis: 34-US versus 35-US The regression equation is34-US = 0.600 + 0.400 35-USPredictor Coef SE Coef T PConstant 0.6000 0.5033 1.19 0.27235-US 0.4000 0.3464 1.15 0.286S = 1.09545 R-Sq = 16.0% R-Sq(adj) = 4.0%Analysis of VarianceSource DF SS MS F PRegression 1 1.600 1.600 1.33 0.286Residual Error 7 8.400 1.200Total 8 10.00

Regression Analysis: 34-IT versus 35-IT The regression equation is34-IT = - 0.137 + 1.11 35-ITPredictor Coef SE Coef T PConstant -0.1375 0.1841 -0.75 0.48035-IT 1.11250 0.07892 14.10 0.000S = 0.470562 R-Sq = 96.6% R-Sq(adj) = 96.1%Analysis of VarianceSource DF SS MS F PRegression 1 44.006 44.006 198.73 0.000Residual Error 7 1.550 0.221Total 8 45.556

Regression Analysis: 34-GR versus 35-GR The regression equation is34-GR = 1.48 - 0.537 35-GRPredictor Coef SE Coef T PConstant 1.4776 0.8060 1.83 0.10935-GR -0.5373 0.5156 -1.04 0.332S = 1.98931 R-Sq = 13.4% R-Sq(adj) = 1.1%Analysis of VarianceSource DF SS MS F PRegression 1 4.299 4.299 1.09 0.332Residual Error 7 27.701 3.957Total 8 32.000

Regression Analysis: 34-JP versus 35-JP The regression equation is34-JP = 2.96 + 0.082 35-JPPredictor Coef SE Coef T PConstant 2.959 1.680 1.76 0.12235-JP 0.0818 0.3207 0.25 0.806S = 3.97364 R-Sq = 0.9% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 1.03 1.03 0.07 0.806Residual Error 7 110.53 15.79Total 8 111.56

159

31-US

30-U

S

3.02.52.01.51.00.50.0

2.0

1.5

1.0

0.5

0.0

S 0.748013R-Sq 34.7%R-Sq(adj) 25.4%

Fitted Line Plot30-US = 0.5833 + 0.4167 31-US

31-IT

30-I

T

43210

5

4

3

2

1

0

S 1.80447R-Sq 10.8%R-Sq(adj) 0.0%

Fitted Line Plot30-IT = 0.7071 + 0.4214 31-IT

31-GR

30-G

R

543210

4

3

2

1

0

S 1.44137R-Sq 2.3%R-Sq(adj) 0.0%

Fitted Line Plot30-GR = 0.7735 + 0.1154 31-GR

31-JP

30-J

P

9876543210

6

5

4

3

2

1

0

S 1.96193R-Sq 28.3%R-Sq(adj) 18.0%

Fitted Line Plot30-JP = 1.981 + 0.3851 31-JP

30, 31

HC2Technology tools , and true spirit of cooperation and collaboration between subsidiary , parent headquartersHypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

International Communication, National Culture, Trust

As. Primary Attrib. Set(s) :

Correlations: 30-JP, 31-JP Pearson correlation of 30-JP and 31-JP = 0.532P-Value = 0.141

Correlations: 30-GR, 31-GR Pearson correlation of 30-GR and 31-GR = 0.152P-Value = 0.695

Correlations: 30-IT, 31-IT Pearson correlation of 30-IT and 31-IT = 0.329P-Value = 0.388

Correlations: 30-US, 31-US Pearson correlation of 30-US and 31-US = 0.589P-Value = 0.095

Regression Analysis: 30-JP versus 31-JP The regression equation is30-JP = 1.98 + 0.385 31-JPPredictor Coef SE Coef T PConstant 1.9814 0.9931 2.00 0.08631-JP 0.3851 0.2319 1.66 0.141S = 1.96193 R-Sq = 28.3% R-Sq(adj) = 18.0%Analysis of VarianceSource DF SS MS F PRegression 1 10.611 10.611 2.76 0.141Residual Error 7 26.944 3.849Total 8 37.556

Regression Analysis: 30-GR versus 31-GR The regression equation is30-GR = 0.774 + 0.115 31-GRPredictor Coef SE Coef T PConstant 0.7735 0.5574 1.39 0.20831-GR 0.1154 0.2827 0.41 0.695S = 1.44137 R-Sq = 2.3% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.346 0.346 0.17 0.695Residual Error 7 14.543 2.078Total 8 14.889

Regression Analysis: 30-IT versus 31-IT The regression equation is30-IT = 0.707 + 0.421 31-ITPredictor Coef SE Coef T PConstant 0.7071 0.8213 0.86 0.41831-IT 0.4214 0.4575 0.92 0.388S = 1.80447 R-Sq = 10.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 2.763 2.763 0.85 0.388Residual Error 7 22.793 3.256Total 8 25.556

Regression Analysis: 30-US versus 31-US The regression equation is30-US = 0.583 + 0.417 31-USPredictor Coef SE Coef T PConstant 0.5833 0.3298 1.77 0.12031-US 0.4167 0.2159 1.93 0.095S = 0.748013 R-Sq = 34.7% R-Sq(adj) = 25.4%Analysis of VarianceSource DF SS MS F PRegression 1 2.0833 2.0833 3.72 0.095Residual Error 7 3.9167 0.5595Total 8 6.0000

160

26-US

24-U

S

3.02.52.01.51.00.50.0

4

3

2

1

0

S 1.25357R-Sq 21.4%R-Sq(adj) 10.2%

Fitted Line Plot24-US = 1.500 - 0.5000 26-US

26-IT

24-I

T

3.02.52.01.51.00.50.0

6

5

4

3

2

1

0

S 2.58767R-Sq 1.4%R-Sq(adj) 0.0%

Fitted Line Plot24-IT = 0.895 + 0.2674 26-IT

26-GR

24-G

R

2.01.51.00.50.0

2.0

1.5

1.0

0.5

0.0

S 0.724807R-Sq 38.7%R-Sq(adj) 30.0%

Fitted Line Plot24-GR = 0.4839 + 0.5806 26-GR

26-JP

24-J

P

121086420

14

12

10

8

6

4

2

0

S 2.38944R-Sq 74.0%R-Sq(adj) 70.3%

Fitted Line Plot24-JP = 0.055 + 0.9830 26-JP

24, 26, 27

HC3 Trust and knowledge holdback by either subsidiary and / or parent headquarters

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

International Communication, Trust (as a major attribute subset)

As. Primary Attrib. Set(s) :

Correlations: 24-JP, 26-JP Pearson correlation of 24-JP and 26-JP = 0.860P-Value = 0.003

Correlations: 24-GR, 26-GR Pearson correlation of 24-GR and 26-GR = 0.622P-Value = 0.074

Correlations: 24-IT, 26-IT Pearson correlation of 24-IT and 26-IT = 0.120P-Value = 0.759

Correlations: 24-US, 26-US Pearson correlation of 24-US and 26-US = -0.463P-Value = 0.210

Regression Analysis: 24-US versus 26-US The regression equation is24-US = 1.50 - 0.500 26-USPredictor Coef SE Coef T PConstant 1.5000 0.5528 2.71 0.03026-US -0.5000 0.3619 -1.38 0.210S = 1.25357 R-Sq = 21.4% R-Sq(adj) = 10.2%Analysis of VarianceSource DF SS MS F PRegression 1 3.000 3.000 1.91 0.210Residual Error 7 11.000 1.571Total 8 14.000

Regression Analysis: 24-IT versus 26-IT The regression equation is24-IT = 0.90 + 0.267 26-ITPredictor Coef SE Coef T PConstant 0.895 1.338 0.67 0.52526-IT 0.2674 0.8371 0.32 0.759S = 2.58767 R-Sq = 1.4% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.683 0.683 0.10 0.759Residual Error 7 46.872 6.696Total 8 47.556

Regression Analysis: 24-GR versus 26-GR The regression equation is24-GR = 0.484 + 0.581 26-GRPredictor Coef SE Coef T PConstant 0.4839 0.3444 1.40 0.20326-GR 0.5806 0.2762 2.10 0.074S = 0.724807 R-Sq = 38.7% R-Sq(adj) = 30.0%Analysis of VarianceSource DF SS MS F PRegression 1 2.3226 2.3226 4.42 0.074Residual Error 7 3.6774 0.5253Total 8 6.0000

Regression Analysis: 24-JP versus 26-JP The regression equation is24-JP = 0.05 + 0.983 26-JPPredictor Coef SE Coef T PConstant 0.055 1.067 0.05 0.96026-JP 0.9830 0.2204 4.46 0.003S = 2.38944 R-Sq = 74.0% R-Sq(adj) = 70.3%Analysis of VarianceSource DF SS MS F PRegression 1 113.59 113.59 19.90 0.003Residual Error 7 39.97 5.71Total 8 153.56

161

27-US

24-U

S

3.02.52.01.51.00.50.0

4

3

2

1

0

S 1.41000R-Sq 0.6%R-Sq(adj) 0.0%

Fitted Line Plot24-US = 1.083 - 0.0833 27-US

27-IT

24-I

T

9876543210

6

5

4

3

2

1

0

S 2.53425R-Sq 5.5%R-Sq(adj) 0.0%

Fitted Line Plot24-IT = 1.458 - 0.1933 27-IT

27-GR

24-G

R

3.02.52.01.51.00.50.0

2.0

1.5

1.0

0.5

0.0

S 0.894427R-Sq 6.7%R-Sq(adj) 0.0%

Fitted Line Plot24-GR = 0.8000 + 0.2000 27-GR

27-JP

24-J

P

121086420

14

12

10

8

6

4

2

0

S 4.63822R-Sq 1.9%R-Sq(adj) 0.0%

Fitted Line Plot24-JP = 3.713 - 0.1524 27-JP

24, 26, 27

HC3 Trust and knowledge holdback by either subsidiary and / or parent headquarters

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

International Communication, Trust (as a major attribute subset)

As. Primary Attrib. Set(s) :

Correlations: 24-JP, 27-JP Pearson correlation of 24-JP and 27-JP = -0.139P-Value = 0.721

Correlations: 24-GR, 27-GR Pearson correlation of 24-GR and 27-GR = 0.258P-Value = 0.502

Correlations: 24-IT, 27-IT Pearson correlation of 24-IT and 27-IT = -0.234P-Value = 0.545

Correlations: 24-US, 27-US Pearson correlation of 24-US and 27-US = -0.077P-Value = 0.844

Regression Analysis: 24-JP versus 27-JP The regression equation is24-JP = 3.71 - 0.152 27-JPPredictor Coef SE Coef T PConstant 3.713 2.035 1.82 0.11127-JP -0.1524 0.4107 -0.37 0.721S = 4.63822 R-Sq = 1.9% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 2.96 2.96 0.14 0.721Residual Error 7 150.59 21.51Total 8 153.56

Regression Analysis: 24-GR versus 27-GR The regression equation is24-GR = 0.800 + 0.200 27-GRPredictor Coef SE Coef T PConstant 0.8000 0.4110 1.95 0.09327-GR 0.2000 0.2828 0.71 0.502S = 0.894427 R-Sq = 6.7% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.4000 0.4000 0.50 0.502Residual Error 7 5.6000 0.8000Total 8 6.0000

Regression Analysis: 24-IT versus 27-IT The regression equation is24-IT = 1.46 - 0.193 27-ITPredictor Coef SE Coef T PConstant 1.4585 0.9228 1.58 0.15827-IT -0.1933 0.3039 -0.64 0.545S = 2.53425 R-Sq = 5.5% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 2.599 2.599 0.40 0.545Residual Error 7 44.957 6.422Total 8 47.556

Regression Analysis: 24-US versus 27-US The regression equation is24-US = 1.08 - 0.083 27-USPredictor Coef SE Coef T PConstant 1.0833 0.6218 1.74 0.12527-US -0.0833 0.4070 -0.20 0.844S = 1.41000 R-Sq = 0.6% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.083 0.083 0.04 0.844Residual Error 7 13.917 1.988Total 8 14.000

162

48-US

38-U

S

2.01.51.00.50.0

2.0

1.5

1.0

0.5

0.0

S 0.501876R-Sq 11.8%R-Sq(adj) 0.0%

Fitted Line Plot38-US = 1.132 - 0.2368 48-US

48-IT

38-I

T

76543210

7

6

5

4

3

2

1

0

-1

S 1.65149R-Sq 56.2%R-Sq(adj) 49.9%

Fitted Line Plot38-IT = - 0.6068 + 0.6859 48-IT

48-GR

38-G

R

76543210

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 0.959338R-Sq 46.3%R-Sq(adj) 38.6%

Fitted Line Plot38-GR = 0.1282 + 0.3269 48-GR

48-JP

38-J

P

121086420

10

8

6

4

2

0

S 3.12592R-Sq 18.1%R-Sq(adj) 6.4%

Fitted Line Plot38-JP = 2.165 + 0.3525 48-JP

38, 48

HD1 Post-project review and lessons-learned and project success

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

Project Success, Group / Team CommunicationAs. Primary

Attrib. Set(s) :

Correlations: 38-JP, 48-JP Pearson correlation of 38-JP and 48-JP = 0.426P-Value = 0.253

Correlations: 38-GR, 48-GR Pearson correlation of 38-GR and 48-GR = 0.681P-Value = 0.044

Correlations: 38-IT, 48-IT Pearson correlation of 38-IT and 48-IT = 0.749P-Value = 0.020

Correlations: 38-US, 48-US Pearson correlation of 38-US and 48-US = -0.344P-Value = 0.365

Regression Analysis: 38-JP versus 48-JP The regression equation is38-JP = 2.16 + 0.352 48-JPPredictor Coef SE Coef T PConstant 2.165 1.344 1.61 0.15148-JP 0.3525 0.2830 1.25 0.253S = 3.12592 R-Sq = 18.1% R-Sq(adj) = 6.4%Analysis of VarianceSource DF SS MS F PRegression 1 15.156 15.156 1.55 0.253Residual Error 7 68.400 9.771Total 8 83.556

Regression Analysis: 38-US versus 48-US The regression equation is38-US = 1.13 - 0.237 48-USPredictor Coef SE Coef T PConstant 1.1316 0.2154 5.25 0.00148-US -0.2368 0.2442 -0.97 0.365S = 0.501876 R-Sq = 11.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.2368 0.2368 0.94 0.365Residual Error 7 1.7632 0.2519Total 8 2.0000

Regression Analysis: 38-IT versus 48-IT The regression equation is38-IT = - 0.607 + 0.686 48-ITPredictor Coef SE Coef T PConstant -0.6068 0.8222 -0.74 0.48448-IT 0.6859 0.2290 2.99 0.020S = 1.65149 R-Sq = 56.2% R-Sq(adj) = 49.9%Analysis of VarianceSource DF SS MS F PRegression 1 24.464 24.464 8.97 0.020Residual Error 7 19.092 2.727Total 8 43.556

Regression Analysis: 38-GR versus 48-GR The regression equation is38-GR = 0.128 + 0.327 48-GRPredictor Coef SE Coef T PConstant 0.1282 0.4776 0.27 0.79648-GR 0.3269 0.1330 2.46 0.044S = 0.959338 R-Sq = 46.3% R-Sq(adj) = 38.6%Analysis of VarianceSource DF SS MS F PRegression 1 5.5577 5.5577 6.04 0.044Residual Error 7 6.4423 0.9203Total 8 12.0000

163

48-IT

34-I

T

76543210

8

7

6

5

4

3

2

1

0

-1

S 1.61561R-Sq 59.9%R-Sq(adj) 54.2%

Fitted Line Plot34-IT = - 0.7094 + 0.7244 48-IT

48-US

34-U

S

2.01.51.00.50.0

3.0

2.5

2.0

1.5

1.0

0.5

0.0

S 1.06022R-Sq 21.3%R-Sq(adj) 10.1%

Fitted Line Plot34-US = 1.395 - 0.7105 48-US

48-GR

34-G

R

76543210

6

5

4

3

2

1

0

S 1.91868R-Sq 19.5%R-Sq(adj) 8.0%

Fitted Line Plot34-GR = 1.923 - 0.3462 48-GR

48-JP

34-J

P

121086420

12

10

8

6

4

2

0

S 1.93748R-Sq 76.4%R-Sq(adj) 73.1%

Fitted Line Plot34-JP = 0.7140 + 0.8361 48-JP

34, 48

HD2 Employees having direct input into decisions and project success

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

Corporate Culture and Project Success, Teams.As. Primary

Attrib. Set(s) :

Correlations: 34-JP, 48-JP Pearson correlation of 34-JP and 48-JP = 0.874P-Value = 0.002

Correlations: 34-GR, 48-GR Pearson correlation of 34-GR and 48-GR = -0.441P-Value = 0.234

Correlations: 34-IT, 48-IT Pearson correlation of 34-IT and 48-IT = 0.774P-Value = 0.014

Regression Analysis: 34-US versus 48-US The regression equation is34-US = 1.39 - 0.711 48-USPredictor Coef SE Coef T PConstant 1.3947 0.4550 3.07 0.01848-US -0.7105 0.5160 -1.38 0.211S = 1.06022 R-Sq = 21.3% R-Sq(adj) = 10.1%Analysis of VarianceSource DF SS MS F PRegression 1 2.132 2.132 1.90 0.211Residual Error 7 7.868 1.124Total 8 10.000

Regression Analysis: 34-IT versus 48-IT The regression equation is34-IT = - 0.709 + 0.724 48-ITPredictor Coef SE Coef T PConstant -0.7094 0.8043 -0.88 0.40748-IT 0.7244 0.2240 3.23 0.014S = 1.61561 R-Sq = 59.9% R-Sq(adj) = 54.2%Analysis of VarianceSource DF SS MS F PRegression 1 27.284 27.284 10.45 0.014Residual Error 7 18.271 2.610Total 8 45.556

Regression Analysis: 34-GR versus 48-GR The regression equation is34-GR = 1.92 - 0.346 48-GRPredictor Coef SE Coef T PConstant 1.9231 0.9552 2.01 0.08448-GR -0.3462 0.2661 -1.30 0.234S = 1.91868 R-Sq = 19.5% R-Sq(adj) = 8.0%Analysis of VarianceSource DF SS MS F PRegression 1 6.231 6.231 1.69 0.234Residual Error 7 25.769 3.681Total 8 32.000

Regression Analysis: 34-JP versus 48-JP The regression equation is34-JP = 0.714 + 0.836 48-JPPredictor Coef SE Coef T PConstant 0.7140 0.8331 0.86 0.42048-JP 0.8361 0.1754 4.77 0.002S = 1.93748 R-Sq = 76.4% R-Sq(adj) = 73.1%Analysis of VarianceSource DF SS MS F PRegression 1 85.279 85.279 22.72 0.002Residual Error 7 26.277 3.754Total 8 111.556

Correlations: 34-US, 48-US Pearson correlation of 34-US and 48-US = -0.462P-Value = 0.211

164

44-US

36-U

S

43210

4

3

2

1

0

S 1.49830R-Sq 1.8%R-Sq(adj) 0.0%

Fitted Line Plot36-US = 0.8571 + 0.1429 44-US

44-IT

36-I

T

543210

4

3

2

1

0

S 1.49668R-Sq 35.3%R-Sq(adj) 26.0%

Fitted Line Plot36-IT = 0.8985 + 0.5376 44-IT

44-GR

36-G

R

543210

5

4

3

2

1

0

S 1.06904R-Sq 69.2%R-Sq(adj) 64.8%

Fitted Line Plot36-GR = 0.2727 + 0.8182 44-GR

44-JP

36-J

P

9876543210

10

8

6

4

2

0

S 2.56767R-Sq 47.3%R-Sq(adj) 39.8%

Fitted Line Plot36-JP = 1.123 + 0.6515 44-JP

36, 44

HD3 OTD, Cost, Performance as project success factors vs. recurring business, knowledge gained

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

Project Success, Basic Communication as it relates directly to KT

As. Primary Attrib. Set(s) :

Correlations: 36-US, 44-US Pearson correlation of 36-US and 44-US = 0.134P-Value = 0.732

Correlations: 36-IT, 44-IT Pearson correlation of 36-IT and 44-IT = 0.594P-Value = 0.092

Correlations: 36-GR, 44-GR Pearson correlation of 36-GR and 44-GR = 0.832P-Value = 0.005

Correlations: 36-JP, 44-JP Pearson correlation of 36-JP and 44-JP = 0.688P-Value = 0.041

Regression Analysis: 36-JP versus 44-JP The regression equation is36-JP = 1.12 + 0.651 44-JPPredictor Coef SE Coef T PConstant 1.123 1.198 0.94 0.38044-JP 0.6515 0.2600 2.51 0.041S = 2.56767 R-Sq = 47.3% R-Sq(adj) = 39.8%Analysis of VarianceSource DF SS MS F PRegression 1 41.405 41.405 6.28 0.041Residual Error 7 46.150 6.593Total 8 87.556

Regression Analysis: 36-GR versus 44-GR The regression equation is36-GR = 0.273 + 0.818 44-GRPredictor Coef SE Coef T PConstant 0.2727 0.4007 0.68 0.51844-GR 0.8182 0.2062 3.97 0.005S = 1.06904 R-Sq = 69.2% R-Sq(adj) = 64.8%Analysis of VarianceSource DF SS MS F PRegression 1 18.000 18.000 15.75 0.005Residual Error 7 8.000 1.143Total 8 26.000

Regression Analysis: 36-IT versus 44-IT The regression equation is36-IT = 0.898 + 0.538 44-ITPredictor Coef SE Coef T PConstant 0.8985 0.6018 1.49 0.17944-IT 0.5376 0.2753 1.95 0.092S = 1.49668 R-Sq = 35.3% R-Sq(adj) = 26.0%Analysis of VarianceSource DF SS MS F PRegression 1 8.542 8.542 3.81 0.092Residual Error 7 15.680 2.240Total 8 24.222

Regression Analysis: 36-US versus 44-US The regression equation is36-US = 0.857 + 0.143 44-USPredictor Coef SE Coef T PConstant 0.8571 0.6401 1.34 0.22244-US 0.1429 0.4004 0.36 0.732S = 1.49830 R-Sq = 1.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.286 0.286 0.13 0.732Residual Error 7 15.714 2.245Total 8 16.000

165

48-IT

49-I

T

76543210

7

6

5

4

3

2

1

0

S 2.10391R-Sq 42.0%R-Sq(adj) 35.6%

Fitted Line Plot49-IT = 0.7817 + 0.6690 48-IT

48-US

49-U

S

43210

2.0

1.5

1.0

0.5

0.0

S 0.779253R-Sq 3.0%R-Sq(adj) 0.0%

Fitted Line Plot49-US = 0.7326 + 0.1047 48-US

48-GR

49-G

R

76543210

7

6

5

4

3

2

1

0

S 2.10391R-Sq 42.0%R-Sq(adj) 35.6%

Fitted Line Plot49-GR = 0.7817 + 0.6690 48-GR

48-JP

49-J

P

121086420

9

8

7

6

5

4

3

2

1

0

S 2.28956R-Sq 35.0%R-Sq(adj) 27.7%

Fitted Line Plot49-JP = 1.474 + 0.4408 48-JP

48, 49

HE1 Subsidiary employee morale and project successHypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

Project Success, Corporate culture, trust as a subset

As. Primary Attrib. Set(s) :

Correlations: 49-JP, 48-JP Pearson correlation of 49-JP and 48-JP = 0.591P-Value = 0.055

Correlations: 49-GR, 48-GR Pearson correlation of 49-GR and 48-GR = 0.648P-Value = 0.031

Correlations: 49-IT, 48-IT Pearson correlation of 49-IT and 48-IT = 0.648P-Value = 0.031

Correlations: 49-US, 48-US Pearson correlation of 49-US and 48-US = 0.174P-Value = 0.608

Regression Analysis: 49-US versus 48-US The regression equation is49-US = 0.733 + 0.105 48-USPredictor Coef SE Coef T PConstant 0.7326 0.2850 2.57 0.03048-US 0.1047 0.1971 0.53 0.608S = 0.779253 R-Sq = 3.0% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.1712 0.1712 0.28 0.608Residual Error 9 5.4651 0.6072Total 10 5.6364

Regression Analysis: 49-IT versus 48-IT The regression equation is49-IT = 0.782 + 0.669 48-ITPredictor Coef SE Coef T PConstant 0.7817 0.9376 0.83 0.42648-IT 0.6690 0.2619 2.55 0.031S = 2.10391 R-Sq = 42.0% R-Sq(adj) = 35.6%Analysis of VarianceSource DF SS MS F PRegression 1 28.889 28.889 6.53 0.031Residual Error 9 39.838 4.426Total 10 68.727

Regression Analysis: 49-GR versus 48-GR The regression equation is49-GR = 0.782 + 0.669 48-GRPredictor Coef SE Coef T PConstant 0.7817 0.9376 0.83 0.42648-GR 0.6690 0.2619 2.55 0.031S = 2.10391 R-Sq = 42.0% R-Sq(adj) = 35.6%Analysis of VarianceSource DF SS MS F PRegression 1 28.889 28.889 6.53 0.031Residual Error 9 39.838 4.426Total 10 68.727

Regression Analysis: 49-JP versus 48-JP The regression equation is49-JP = 1.47 + 0.441 48-JPPredictor Coef SE Coef T PConstant 1.4742 0.8693 1.70 0.12448-JP 0.4408 0.2004 2.20 0.055S = 2.28956 R-Sq = 35.0% R-Sq(adj) = 27.7%Analysis of VarianceSource DF SS MS F PRegression 1 25.366 25.366 4.84 0.055Residual Error 9 47.179 5.242Total 10 72.545

166

48-US

50-U

S

43210

4

3

2

1

0

S 1.31307R-Sq 0.8%R-Sq(adj) 0.0%

Fitted Line Plot50-US = 0.8895 - 0.0872 48-US

48-IT

50-I

T

76543210

6

5

4

3

2

1

0

S 2.33705R-Sq 6.8%R-Sq(adj) 0.0%

Fitted Line Plot50-IT = 1.925 + 0.2352 48-IT

48-GR

50-G

R

76543210

6

5

4

3

2

1

0

S 2.33705R-Sq 6.8%R-Sq(adj) 0.0%

Fitted Line Plot50-GR = 1.925 + 0.2352 48-GR

48-JP

50-J

P

121086420

9

8

7

6

5

4

3

2

1

0

S 2.24327R-Sq 7.1%R-Sq(adj) 0.0%

Fitted Line Plot50-JP = 2.118 + 0.1623 48-JP

48, 50

HE2 Parent headquarters satisfaction and project success

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

Project Success and Corporate culture As. Primary

Attrib. Set(s) :

Correlations: 50-US, 48-US Pearson correlation of 50-US and 48-US = -0.087P-Value = 0.799

Correlations: 50-IT, 48-IT Pearson correlation of 50-IT and 48-IT = 0.260P-Value = 0.440

Correlations: 50-GR, 48-GR Pearson correlation of 50-GR and 48-GR = 0.260P-Value = 0.440

Correlations: 50-JP, 48-JP Pearson correlation of 50-JP and 48-JP = 0.266P-Value = 0.430

Regression Analysis: 50-US versus 48-US The regression equation is50-US = 0.890 - 0.087 48-USPredictor Coef SE Coef T PConstant 0.8895 0.4802 1.85 0.09748-US -0.0872 0.3321 -0.26 0.799S = 1.31307 R-Sq = 0.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.119 0.119 0.07 0.799Residual Error 9 15.517 1.724Total 10 15.636

Regression Analysis: 50-IT versus 48-IT The regression equation is50-IT = 1.93 + 0.235 48-ITPredictor Coef SE Coef T PConstant 1.925 1.041 1.85 0.09848-IT 0.2352 0.2909 0.81 0.440S = 2.33705 R-Sq = 6.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 3.571 3.571 0.65 0.440Residual Error 9 49.156 5.462Total 10 52.72

Regression Analysis: 50-GR versus 48-GR The regression equation is50-GR = 1.93 + 0.235 48-GRPredictor Coef SE Coef T PConstant 1.925 1.041 1.85 0.09848-GR 0.2352 0.2909 0.81 0.440S = 2.33705 R-Sq = 6.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 3.571 3.571 0.65 0.440Residual Error 9 49.156 5.462Total 10 52.727

Regression Analysis: 50-JP versus 48-JP The regression equation is50-JP = 2.12 + 0.162 48-JPPredictor Coef SE Coef T PConstant 2.1177 0.8517 2.49 0.03548-JP 0.1623 0.1963 0.83 0.430S = 2.24327 R-Sq = 7.1% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 3.437 3.437 0.68 0.430Residual Error 9 45.290 5.032Total 10 48.727

167

49-US

50-U

S

2.01.51.00.50.0

4

3

2

1

0

S 1.05409R-Sq 36.0%R-Sq(adj) 28.9%

Fitted Line Plot50-US = 0.0000 + 1.000 49-US

49-IT

50-I

T

76543210

6

5

4

3

2

1

0

S 2.27245R-Sq 11.9%R-Sq(adj) 2.1%

Fitted Line Plot50-IT = 1.778 + 0.3016 49-IT

49-GR

50-G

R

76543210

6

5

4

3

2

1

0

S 2.27245R-Sq 11.9%R-Sq(adj) 2.1%

Fitted Line Plot50-GR = 1.778 + 0.3016 49-GR

49-JP

50-J

P

9876543210

9

8

7

6

5

4

3

2

1

0

S 1.90384R-Sq 33.1%R-Sq(adj) 25.6%

Fitted Line Plot50-JP = 1.303 + 0.4712 49-JP

49, 50

HE3 Parent headquarters satisfaction and subsidiary employee morale

Hypotheses :

Questions :

Variables :

JAPAN GERMANY

ITALY USA

As. Primary Attrib. Set(s) :

Project Success, Corporate culture, trust as a subset.

Correlations: 50-JP, 49-JP Pearson correlation of 50-JP and 49-JP = 0.575P-Value = 0.064

Correlations: 50-GR, 49-GR Pearson correlation of 50-GR and 49-GR = 0.344P-Value = 0.300

Correlations: 50-IT, 49-IT Pearson correlation of 50-IT and 49-IT = 0.344P-Value = 0.300

Correlations: 50-US, 49-US Pearson correlation of 50-US and 49-US = 0.600P-Value = 0.051

Regression Analysis: 50-JP versus 49-JP The regression equation is50-JP = 1.30 + 0.471 49-JPPredictor Coef SE Coef T PConstant 1.3033 0.8227 1.58 0.14849-JP 0.4712 0.2235 2.11 0.064S = 1.90384 R-Sq = 33.1% R-Sq(adj) = 25.6%Analysis of VarianceSource DF SS MS F PRegression 1 16.106 16.106 4.44 0.064Residual Error 9 32.622 3.625Total 10 48.727

Regression Analysis: 50-US versus 49-US The regression equation is50-US = 0.000 + 1.00 49-USPredictor Coef SE Coef T PConstant 0.0000 0.4827 0.00 1.00049-US 1.0000 0.4440 2.25 0.051S = 1.05409 R-Sq = 36.0% R-Sq(adj) = 28.9%Analysis of VarianceSource DF SS MS F PRegression 1 5.636 5.636 5.07 0.051Residual Error 9 10.000 1.111Total 10 15.636

Regression Analysis: 50-IT versus 49-IT The regression equation is50-IT = 1.78 + 0.302 49-ITPredictor Coef SE Coef T PConstant 1.7778 0.9779 1.82 0.10249-IT 0.3016 0.2741 1.10 0.300S = 2.27245 R-Sq = 11.9% R-Sq(adj) = 2.1%Analysis of VarianceSource DF SS MS F PRegression 1 6.251 6.251 1.21 0.300Residual Error 9 46.476 5.164Total 10 52.727

Regression Analysis: 50-GR versus 49-GR The regression equation is50-GR = 1.78 + 0.302 49-GRPredictor Coef SE Coef T PConstant 1.7778 0.9779 1.82 0.10249-GR 0.3016 0.2741 1.10 0.300S = 2.27245 R-Sq = 11.9% R-Sq(adj) = 2.1%Analysis of VarianceSource DF SS MS F PRegression 1 6.251 6.251 1.21 0.300Residual Error 9 46.476 5.164Total 10 52.727

168

4.2.2 Statistical Significance and Measures of Association

As with the previous section, we utilized MiniTab® (version 14) for the analysis in

this section as well, and with the results formatted in a Microsoft’s Visio® template.

Final results and hypotheses discussion is located at the end of this section.

4.2.2.1 Chi-square test (χ2) and Cramer’s V

The tables below outline the results and analysis from MiniTab regarding Chi-

square. As is apparent , they are categorized by company nationality (per the

original returned surveys) and follow the same organization as the correlational

analysis.

20, 22, 24

HB1 Daily communication method and trust.

Basic and International Communication, Corporate and National Culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

20 -JP 24-JP Total 1 5 0 5 2 .50 2 .50 2 .500 2.500

2 9 2 11 5 .50 5 .50 2 .227 2.227

3 9 1 10 5 .00 5 .00 3 .200 3.200

4 5 2 7 3 .50 3 .50 0 .643 0.643

5 1 1 2 1 .00 1 .00 0 .000 0.000

7 0 13 13 6 .50 6 .50 6 .500 6.500

8 0 8 8 4 .00 4 .00 4 .000 4.000

9 0 2 2 1 .00 1 .00 1 .000 1.000

Total 29 29 58

Chi-Sq = 40.140, DF = 7

20 -GR 24-GR Total 1 0 1 1 0 .47 0 .53 0 .471 0.418

2 2 2 4 1 .88 2 .12 0 .007 0.007

3 5 2 7 3 .29 3 .71 0 .883 0.785

4 1 1 2 0 .94 1 .06 0 .004 0.003

7 0 1 1 0 .47 0 .53 0 .471 0.418

8 0 2 2 0 .94 1 .06 0 .941 0.837

Total 8 9 17

Chi-Sq = 5.245, DF = 5

20 -IT 24-IT Total 3 3 0 3 1 .50 1 .50 1 .500 1.500

4 1 0 1 0 .50 0 .50 0 .500 0.500

6 1 0 1 0 .50 0 .50 0 .500 0.500

7 6 5 11 5 .50 5 .50 0 .045 0.045

8 0 6 6 3 .00 3 .00 3 .000 3.000

Total 11 11 22

Chi-Sq = 11.091, DF = 4

20 -US 24-US Total 1 3 2 5 2 .50 2 .50 0 .100 0.100

2 1 4 5 2 .50 2 .50 0 .900 0.900

3 2 1 3 1 .50 1 .50 0 .167 0.167

4 2 0 2 1 .00 1 .00 1 .000 1.000

5 1 0 1 0 .50 0 .50 0 .500 0.500

6 0 1 1 0 .50 0 .50 0 .500 0.500

8 0 1 1 0 .50 0 .50 0 .500 0.500

Total 9 9 18

Chi-Sq = 7.333, DF = 6

169

20, 22, 24

HB1 Daily communication method and trust.

Basic and International Communication, Corporate and National Culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

22 -JP 24-JP Total 2 1 2 3 1 .50 1 .50 0 .167 0.167

3 4 1 5 2 .50 2 .50 0 .900 0.900

4 3 2 5 2 .50 2 .50 0 .100 0.100

5 1 1 2 1 .00 1 .00 0 .000 0.000

6 6 0 6 3 .00 3 .00 3 .000 3.000

7 7 13 20 10 .00 10 .00 0 .900 0.900

8 5 8 13 6 .50 6 .50 0 .346 0.346

9 2 2 4 2 .00 2 .00 0 .000 0.000

Total 29 29 58

Chi-Sq = 10.826, DF = 7

22 -GR 24-GR Total 1 0 1 1 0 .47 0 .53 0 .471 0.418

2 0 2 2 0 .94 1 .06 0 .941 0.837

3 3 2 5 2 .35 2 .65 0 .178 0.158

4 4 1 5 2 .35 2 .65 1 .153 1.025

6 1 0 1 0 .47 0 .53 0 .596 0.529

7 0 1 1 0 .47 0 .53 0 .471 0.418

8 0 2 2 0 .94 1 .06 0 .941 0.837

Total 8 9 17

Chi-Sq = 8.972, DF = 6

22 -IT 24-IT Total 2 2 0 2 1 .00 1 .00 1 .000 1.000

3 2 0 2 1 .00 1 .00 1 .000 1.000

4 1 0 1 0 .50 0 .50 0 .500 0.500

5 1 0 1 0 .50 0 .50 0 .500 0.500

6 1 0 1 0 .50 0 .50 0 .500 0.500

7 2 5 7 3 .50 3 .50 0 .643 0.643

8 2 6 8 4 .00 4 .00 1 .000 1.000

Total 11 11 22

Chi-Sq = 10.286, DF = 6

22 -US 24-US Total 1 1 2 3 1 .50 1 .50 0 .167 0.167

2 1 4 5 2 .50 2 .50 0 .900 0.900

3 0 1 1 0 .50 0 .50 0 .500 0.500

5 3 0 3 1 .50 1 .50 1 .500 1.500

6 2 1 3 1 .50 1 .50 0 .167 0.167

7 2 0 2 1 .00 1 .00 1 .000 1.000

8 0 1 1 0 .50 0 .50 0 .500 0.500

Total 9 9 18

Chi-Sq = 9.467, DF = 6

12, 14, 16, 18, 24

HB2 Communication channel between subsidiary and parent company; and trust

International Communication and Corp. Culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

12 -JP 24-JP Total 2 2 2 4 2 .00 2 .00 0 .000 0.000

3 7 1 8 4 .00 4 .00 2 .250 2.250

4 1 2 3 1 .50 1 .50 0 .167 0.167

5 0 1 1 0 .50 0 .50 0 .500 0.500

6 3 0 3 1 .50 1 .50 1 .500 1.500

7 6 13 19 9 .50 9 .50 1 .289 1.289

8 3 8 11 5 .50 5 .50 1 .136 1.136

9 7 2 9 4 .50 4 .50 1 .389 1.389

Total 29 29 58

Chi-Sq = 16.463, DF = 7

12 -GR 24-GR Total 1 0 1 1 0 .47 0 .53 0 .471 0.418

2 2 2 4 1 .88 2 .12 0 .007 0.007

3 1 2 3 1 .41 1 .59 0 .120 0.107

4 0 1 1 0 .47 0 .53 0 .471 0.418

7 4 1 5 2 .35 2 .65 1 .153 1.025

8 0 2 2 0 .94 1 .06 0 .941 0.837

9 1 0 1 0 .47 0 .53 0 .596 0.529

Total 8 9 17

Chi-Sq = 7.099, DF = 6

12 -IT 24-IT Total 1 1 0 1 0 .52 0 .48 0 .438 0.478

2 5 0 5 2 .61 2 .39 2 .192 2.391

6 2 0 2 1 .04 0 .96 0 .877 0.957

7 2 5 7 3 .65 3 .35 0 .747 0.815

8 1 6 7 3 .65 3 .35 1 .926 2.101

9 1 0 1 0 .52 0 .48 0 .438 0.478

Total 12 11 23

Chi-Sq = 13.840, DF = 5

12 -US 24-US Total 1 1 2 3 1 .50 1 .50 0 .167 0.167

2 0 4 4 2 .00 2 .00 2 .000 2.000

3 0 1 1 0 .50 0 .50 0 .500 0.500

4 1 0 1 0 .50 0 .50 0 .500 0.500

5 2 0 2 1 .00 1 .00 1 .000 1.000

6 0 1 1 0 .50 0 .50 0 .500 0.500

7 2 0 2 1 .00 1 .00 1 .000 1.000

8 1 1 2 1 .00 1 .00 0 .000 0.000

9 2 0 2 1 .00 1 .00 1 .000 1.000

Total 9 9 18

Chi-Sq = 13.333, DF = 8

170

12, 14, 16, 18, 24

HB2 Communication channel between subsidiary and parent company; and trust

International Communication and Corp. Culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

14 -JP 24-JP Total 1 1 0 1 0 .50 0 .50 0 .500 0.500

2 2 2 4 2 .00 2 .00 0 .000 0.000

3 7 1 8 4 .00 4 .00 2 .250 2.250

4 4 2 6 3 .00 3 .00 0 .333 0.333

5 1 1 2 1 .00 1 .00 0 .000 0.000

7 4 13 17 8 .50 8 .50 2 .382 2.382

8 3 8 11 5 .50 5 .50 1 .136 1.136

9 7 2 9 4 .50 4 .50 1 .389 1.389

Total 29 29 58

Chi-Sq = 15.982, DF = 7

14 -GR 24-GR Total 1 0 1 1 0 .47 0 .53 0 .471 0.418

2 0 2 2 0 .94 1 .06 0 .941 0.837

3 1 2 3 1 .41 1 .59 0 .120 0.107

4 3 1 4 1 .88 2 .12 0 .664 0.590

7 3 1 4 1 .88 2 .12 0 .664 0.590

8 0 2 2 0 .94 1 .06 0 .941 0.837

9 1 0 1 0 .47 0 .53 0 .596 0.529

Total 8 9 17

Chi-Sq = 8.303, DF = 6

14 -IT 24-IT Total 2 6 0 6 3 .00 3 .00 3 .000 3.000

3 2 0 2 1 .00 1 .00 1 .000 1.000

4 2 0 2 1 .00 1 .00 1 .000 1.000

5 1 0 1 0 .50 0 .50 0 .500 0.500

7 0 5 5 2 .50 2 .50 2 .500 2.500

8 0 6 6 3 .00 3 .00 3 .000 3.000

Total 11 11 22

Chi-Sq = 22.000, DF = 5

14 -US 24-US Total 1 1 2 3 1 .50 1 .50 0 .167 0.167

2 0 4 4 2 .00 2 .00 2 .000 2.000

3 2 1 3 1 .50 1 .50 0 .167 0.167

4 1 0 1 0 .50 0 .50 0 .500 0.500

5 1 0 1 0 .50 0 .50 0 .500 0.500

6 0 1 1 0 .50 0 .50 0 .500 0.500

8 1 1 2 1 .00 1 .00 0 .000 0.000

9 3 0 3 1 .50 1 .50 1 .500 1.500

Total 9 9 18

Chi-Sq = 10.667, DF = 7

12, 14, 16, 18, 24

HB2 Communication channel between subsidiary and parent company; and trust

International Communication and Corp. Culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

16 -US 24-US Total 1 0 2 2 1 .00 1 .00 1 .000 1.000

2 0 4 4 2 .00 2 .00 2 .000 2.000

3 1 1 2 1 .00 1 .00 0 .000 0.000

5 1 0 1 0 .50 0 .50 0 .500 0.500

6 1 1 2 1 .00 1 .00 0 .000 0.000

8 2 1 3 1 .50 1 .50 0 .167 0.167

9 4 0 4 2 .00 2 .00 2 .000 2.000

Total 9 9 18

Chi-Sq = 11.333, DF = 6

16 -IT 24-IT Total 1 2 0 2 1 .00 1 .00 1 .000 1.000

2 3 0 3 1 .50 1 .50 1 .500 1.500

7 1 5 6 3 .00 3 .00 1 .333 1.333

8 3 6 9 4 .50 4 .50 0 .500 0.500

9 2 0 2 1 .00 1 .00 1 .000 1.000

Total 11 11 22

Chi-Sq = 10.667, DF = 4

16 -GR 24-GR Total 1 0 1 1 0 .47 0 .53 0 .471 0.418

2 2 2 4 1 .88 2 .12 0 .007 0.007

3 1 2 3 1 .41 1 .59 0 .120 0.107

4 0 1 1 0 .47 0 .53 0 .471 0.418

5 1 0 1 0 .47 0 .53 0 .596 0.529

6 1 0 1 0 .47 0 .53 0 .596 0.529

7 2 1 3 1 .41 1 .59 0 .245 0.218

8 0 2 2 0 .94 1 .06 0 .941 0.837

9 1 0 1 0 .47 0 .53 0 .596 0.529

Total 8 9 17

Chi-Sq = 7.634, DF = 8

16 -JP 24-JP Total 2 3 2 5 2 .50 2 .50 0 .100 0.100

3 4 1 5 2 .50 2 .50 0 .900 0.900

4 5 2 7 3 .50 3 .50 0 .643 0.643

5 1 1 2 1 .00 1 .00 0 .000 0.000

6 1 0 1 0 .50 0 .50 0 .500 0.500

7 1 13 14 7 .00 7 .00 5 .143 5.143

8 6 8 14 7 .00 7 .00 0 .143 0.143

9 8 2 10 5 .00 5 .00 1 .800 1.800

Total 29 29 58

Chi-Sq = 18.457, DF = 7

171

12, 14, 16, 18, 24

HB2 Communication channel between subsidiary and parent company; and trust

International Communication and Corp. Culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

18 -JP 24-JP Total 1 3 0 3 1 .50 1 .50 1 .500 1.500

2 8 2 10 5 .00 5 .00 1 .800 1.800

3 0 1 1 0 .50 0 .50 0 .500 0.500

4 1 2 3 1 .50 1 .50 0 .167 0.167

5 1 1 2 1 .00 1 .00 0 .000 0.000

6 2 0 2 1 .00 1 .00 1 .000 1.000

7 5 13 18 9 .00 9 .00 1 .778 1.778

8 8 8 16 8 .00 8 .00 0 .000 0.000

9 1 2 3 1 .50 1 .50 0 .167 0.167

Total 29 29 58

Chi-Sq = 13.822, DF = 8

18 -GR 24-GR Total 1 1 1 2 0 .94 1 .06 0 .004 0.003

2 0 2 2 0 .94 1 .06 0 .941 0.837

3 3 2 5 2 .35 2 .65 0 .178 0.158

4 0 1 1 0 .47 0 .53 0 .471 0.418

7 0 1 1 0 .47 0 .53 0 .471 0.418

8 4 2 6 2 .82 3 .18 0 .490 0.436

Total 8 9 17

Chi-Sq = 4.825, DF = 5

18 -IT 24-IT Total 2 2 0 2 1 .00 1 .00 1 .000 1.000

3 2 0 2 1 .00 1 .00 1 .000 1.000

4 2 0 2 1 .00 1 .00 1 .000 1.000

7 0 5 5 2 .50 2 .50 2 .500 2.500

8 5 6 11 5 .50 5 .50 0 .045 0.045

Total 11 11 22

Chi-Sq = 11.091, DF = 4

18 -US 24-US Total 1 1 2 3 1 .50 1 .50 0 .167 0.167

2 1 4 5 2 .50 2 .50 0 .900 0.900

3 0 1 1 0 .50 0 .50 0 .500 0.500

5 2 0 2 1 .00 1 .00 1 .000 1.000

6 1 1 2 1 .00 1 .00 0 .000 0.000

7 1 0 1 0 .50 0 .50 0 .500 0.500

8 1 1 2 1 .00 1 .00 0 .000 0.000

9 2 0 2 1 .00 1 .00 1 .000 1.000

Total 9 9 18

Chi-Sq = 8.133, DF = 7

12, 14, 16, 18, 35

HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT International Communication; Corp. and National Culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

12 -US 35-US Total 1 1 1 2 1 .00 1 .00 0 .000 0.000

3 0 3 3 1 .50 1 .50 1 .500 1.500

4 1 2 3 1 .50 1 .50 0 .167 0.167

5 2 2 4 2 .00 2 .00 0 .000 0.000

7 2 0 2 1 .00 1 .00 1 .000 1.000

8 1 1 2 1 .00 1 .00 0 .000 0.000

9 2 0 2 1 .00 1 .00 1 .000 1.000

Total 9 9 18

Chi-Sq = 7.333, DF = 6

12 -IT 35-IT Total 1 1 0 1 0 .52 0 .48 0 .438 0.478

2 5 0 5 2 .61 2 .39 2 .192 2.391

6 2 0 2 1 .04 0 .96 0 .877 0.957

7 2 3 5 2 .61 2 .39 0 .142 0.155

8 1 6 7 3 .65 3 .35 1 .926 2.101

9 1 2 3 1 .57 1 .43 0 .204 0.223

Total 12 11 23

Chi-Sq = 12.084, DF = 5

12 -GR 35-GR Total 1 0 1 1 0 .50 0 .50 0 .500 0.500

2 2 0 2 1 .00 1 .00 1 .000 1.000

3 1 0 1 0 .50 0 .50 0 .500 0.500

4 0 4 4 2 .00 2 .00 2 .000 2.000

7 4 1 5 2 .50 2 .50 0 .900 0.900

8 0 2 2 1 .00 1 .00 1 .000 1.000

9 1 0 1 0 .50 0 .50 0 .500 0.500

Total 8 8 16

Chi-Sq = 12.800, DF = 6

12 -JP 35-JP Total 2 2 0 2 1 .00 1.00 1 .000 1 .000

3 7 0 7 3 .50 3.50 3 .500 3 .500

4 1 3 4 2 .00 2.00 0 .500 0 .500

5 0 1 1 0 .50 0.50 0 .500 0 .500

6 3 0 3 1 .50 1.50 1 .500 1 .500

7 6 11 17 8 .50 8.50 0 .735 0 .735

8 3 10 13 6 .50 6.50 1 .885 1 .885

9 7 4 11 5 .50 5.50 0 .409 0 .409

Total 29 29 58

Chi-Sq = 20.058, DF = 7

172

12, 14, 16, 18, 35

HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT International Communication; Corp. and National Culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

14 -JP 35-JP Total 1 1 0 1 0 .50 0 .50 0 .500 0.500

2 2 0 2 1 .00 1 .00 1 .000 1.000

3 7 0 7 3 .50 3 .50 3 .500 3.500

4 4 3 7 3 .50 3 .50 0 .071 0.071

5 1 1 2 1 .00 1 .00 0 .000 0.000

7 4 11 15 7 .50 7 .50 1 .633 1.633

8 3 10 13 6 .50 6 .50 1 .885 1.885

9 7 4 11 5 .50 5 .50 0 .409 0.409

Total 29 29 58

Chi-Sq = 17.997, DF = 7

14 -GR 35-GR Total 1 0 1 1 0 .50 0 .50 0 .500 0.500

3 1 0 1 0 .50 0 .50 0 .500 0.500

4 3 4 7 3 .50 3 .50 0 .071 0.071

7 3 1 4 2 .00 2 .00 0 .500 0.500

8 0 2 2 1 .00 1 .00 1 .000 1.000

9 1 0 1 0 .50 0 .50 0 .500 0.500

Total 8 8 16

Chi-Sq = 6.143, DF = 5

14 -IT 35-IT Total 2 6 0 6 3 .00 3 .00 3 .000 3.000

3 2 0 2 1 .00 1 .00 1 .000 1.000

4 2 0 2 1 .00 1 .00 1 .000 1.000

5 1 0 1 0 .50 0 .50 0 .500 0.500

7 0 3 3 1 .50 1 .50 1 .500 1.500

8 0 6 6 3 .00 3 .00 3 .000 3.000

9 0 2 2 1 .00 1 .00 1 .000 1.000

Total 11 11 22

Chi-Sq = 22.000, DF = 6

14 -US 35-US Total 1 1 1 2 1 .00 1 .00 0 .000 0.000

3 2 3 5 2 .50 2 .50 0 .100 0.100

4 1 2 3 1 .50 1 .50 0 .167 0.167

5 1 2 3 1 .50 1 .50 0 .167 0.167

8 1 1 2 1 .00 1 .00 0 .000 0.000

9 3 0 3 1 .50 1 .50 1 .500 1.500

Total 9 9 18

Chi-Sq = 3.867, DF = 5

12, 14, 16, 18, 35

HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT International Communication; Corp. and National Culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

16 -US 35-US Total 1 0 1 1 0 .50 0 .50 0 .500 0.500

3 1 3 4 2 .00 2 .00 0 .500 0.500

4 0 2 2 1 .00 1 .00 1 .000 1.000

5 1 2 3 1 .50 1 .50 0 .167 0.167

6 1 0 1 0 .50 0 .50 0 .500 0.500

8 2 1 3 1 .50 1 .50 0 .167 0.167

9 4 0 4 2 .00 2 .00 2 .000 2.000

Total 9 9 18

Chi-Sq = 9.667, DF = 6

16 -IT 35-IT Total 1 2 0 2 1 .00 1 .00 1 .000 1.000

2 3 0 3 1 .50 1 .50 1 .500 1.500

7 1 3 4 2 .00 2 .00 0 .500 0.500

8 3 6 9 4 .50 4 .50 0 .500 0.500

9 2 2 4 2 .00 2 .00 0 .000 0.000

Total 11 11 22

Chi-Sq = 7.000, DF = 4

16 -GR 35-GR Total 1 0 1 1 0 .50 0 .50 0 .500 0.500

2 2 0 2 1 .00 1 .00 1 .000 1.000

3 1 0 1 0 .50 0 .50 0 .500 0.500

4 0 4 4 2 .00 2 .00 2 .000 2.000

5 1 0 1 0 .50 0 .50 0 .500 0.500

6 1 0 1 0 .50 0 .50 0 .500 0.500

7 2 1 3 1 .50 1 .50 0 .167 0.167

8 0 2 2 1 .00 1 .00 1 .000 1.000

9 1 0 1 0 .50 0 .50 0 .500 0.500

Total 8 8 16

Chi-Sq = 13.333, DF = 8

16 -JP 35-JP Total 2 3 0 3 1 .50 1 .50 1 .500 1.500

3 4 0 4 2 .00 2 .00 2 .000 2.000

4 5 3 8 4 .00 4 .00 0 .250 0.250

5 1 1 2 1 .00 1 .00 0 .000 0.000

6 1 0 1 0 .50 0 .50 0 .500 0.500

7 1 11 12 6 .00 6 .00 4 .167 4.167

8 6 10 16 8 .00 8 .00 0 .500 0.500

9 8 4 12 6 .00 6 .00 0 .667 0.667

Total 29 29 58

Chi-Sq = 19.167, DF = 7

173

12, 14, 16, 18, 35

HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT International Communication; Corp. and National Culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

18 -JP 35-JP Total 1 3 0 3 1 .50 1 .50 1 .500 1.500

2 8 0 8 4 .00 4 .00 4 .000 4.000

4 1 3 4 2 .00 2 .00 0 .500 0.500

5 1 1 2 1 .00 1 .00 0 .000 0.000

6 2 0 2 1 .00 1 .00 1 .000 1.000

7 5 11 16 8 .00 8 .00 1 .125 1.125

8 8 10 18 9 .00 9 .00 0 .111 0.111

9 1 4 5 2 .50 2 .50 0 .900 0.900

Total 29 29 58

Chi-Sq = 18.272, DF = 7

18 -GR 35-GR Total 1 1 1 2 1 .00 1 .00 0 .000 0.000

3 3 0 3 1 .50 1 .50 1 .500 1.500

4 0 4 4 2 .00 2 .00 2 .000 2.000

7 0 1 1 0 .50 0 .50 0 .500 0.500

8 4 2 6 3 .00 3 .00 0 .333 0.333

Total 8 8 16

Chi-Sq = 8.667, DF = 4

18 -IT 35-IT Total 2 2 0 2 1 .00 1 .00 1 .000 1.000

3 2 0 2 1 .00 1 .00 1 .000 1.000

4 2 0 2 1 .00 1 .00 1 .000 1.000

7 0 3 3 1 .50 1 .50 1 .500 1.500

8 5 6 11 5 .50 5 .50 0 .045 0.045

9 0 2 2 1 .00 1 .00 1 .000 1.000

Total 11 11 22

Chi-Sq = 11.091, DF = 5

18 -US 35-US Total 1 1 1 2 1 .00 1 .00 0 .000 0.000

2 1 0 1 0 .50 0 .50 0 .500 0.500

3 0 3 3 1 .50 1 .50 1 .500 1.500

4 0 2 2 1 .00 1 .00 1 .000 1.000

5 2 2 4 2 .00 2 .00 0 .000 0.000

6 1 0 1 0 .50 0 .50 0 .500 0.500

7 1 0 1 0 .50 0 .50 0 .500 0.500

8 1 1 2 1 .00 1 .00 0 .000 0.000

9 2 0 2 1 .00 1 .00 1 .000 1.000

Total 9 9 18

Chi-Sq = 10.000, DF = 8

18, 24

HB4 Many-to-many subsidiary communication channel and learning / trusting relationship International Communication; Corp. and National Culture; trust (as a major subset attribute)

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

18 -JP 24-JP Total 1 3 0 3 1 .50 1.50 1 .500 1 .500

2 8 2 10 5 .00 5.00 1 .800 1 .800

3 0 1 1 0 .50 0.50 0 .500 0 .500

4 1 2 3 1 .50 1.50 0 .167 0 .167

5 1 1 2 1 .00 1.00 0 .000 0 .000

6 2 0 2 1 .00 1.00 1 .000 1 .000

7 5 13 18 9 .00 9.00 1 .778 1 .778

8 8 8 16 8 .00 8.00 0 .000 0 .000

9 1 2 3 1 .50 1.50 0 .167 0 .167

Total 29 29 58

Chi-Sq = 13.822, DF = 8

18 -GR 24-GR Total 1 1 1 2 0 .94 1 .06 0 .004 0.003

2 0 2 2 0 .94 1 .06 0 .941 0.837

3 3 2 5 2 .35 2 .65 0 .178 0.158

4 0 1 1 0 .47 0 .53 0 .471 0.418

7 0 1 1 0 .47 0 .53 0 .471 0.418

8 4 2 6 2 .82 3 .18 0 .490 0.436

Total 8 9 17

Chi-Sq = 4.825, DF = 5

18 -IT 24-IT Total 2 2 0 2 1 .00 1 .00 1 .000 1.000

3 2 0 2 1 .00 1 .00 1 .000 1.000

4 2 0 2 1 .00 1 .00 1 .000 1.000

7 0 5 5 2 .50 2 .50 2 .500 2.500

8 5 6 11 5 .50 5 .50 0 .045 0.045

Total 11 11 22

Chi-Sq = 11.091, DF = 4

18 -US 24-US Total 1 1 2 3 1 .50 1 .50 0 .167 0.167

2 1 4 5 2 .50 2 .50 0 .900 0.900

3 0 1 1 0 .50 0 .50 0 .500 0.500

5 2 0 2 1 .00 1 .00 1 .000 1.000

6 1 1 2 1 .00 1 .00 0 .000 0.000

7 1 0 1 0 .50 0 .50 0 .500 0.500

8 1 1 2 1 .00 1 .00 0 .000 0.000

9 2 0 2 1 .00 1 .00 1 .000 1.000

Total 9 9 18

Chi-Sq = 8.133, DF = 7

174

34, 35

HC1Employees having direct input to decisions affecting them and shared meaning in succesful KT

Corporate culture, Groups and Teams Communication, trust as a major attribute subset

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

34 -JP 35-JP Total 1 1 0 1 0 .50 0 .50 0 .500 0.500

2 1 0 1 0 .50 0 .50 0 .500 0.500

3 2 0 2 1 .00 1 .00 1 .000 1.000

4 3 3 6 3 .00 3 .00 0 .000 0.000

5 1 1 2 1 .00 1 .00 0 .000 0.000

6 11 0 11 5 .50 5 .50 5 .500 5.500

7 8 11 19 9 .50 9 .50 0 .237 0.237

8 0 10 10 5 .00 5 .00 5 .000 5.000

9 2 4 6 3 .00 3 .00 0 .333 0.333

Total 29 29 58

Chi-Sq = 26.140, DF = 8

34 -GR 35-GR Total 1 0 1 1 0 .53 0 .47 0 .529 0.596

2 2 0 2 1 .06 0 .94 0 .837 0.941

3 6 0 6 3 .18 2 .82 2 .510 2.824

4 0 4 4 2 .12 1 .88 2 .118 2.382

5 1 0 1 0 .53 0 .47 0 .418 0.471

7 0 1 1 0 .53 0 .47 0 .529 0.596

8 0 2 2 1 .06 0 .94 1 .059 1.191

Total 9 8 17

Chi-Sq = 17.000, DF = 6

34 -IT 35-IT Total 7 3 3 6 3 .00 3 .00 0 .000 0.000

8 7 6 13 6 .50 6 .50 0 .038 0.038

9 1 2 3 1 .50 1 .50 0 .167 0.167

Total 11 11 22

Chi-Sq = 0.410, DF = 2

34 -US 35-US Total 1 1 1 2 1 .00 1 .00 0 .000 0.000

2 1 0 1 0 .50 0 .50 0 .500 0.500

3 2 3 5 2 .50 2 .50 0 .100 0.100

4 0 2 2 1 .00 1 .00 1 .000 1.000

5 3 2 5 2 .50 2 .50 0 .100 0.100

7 2 0 2 1 .00 1 .00 1 .000 1.000

8 0 1 1 0 .50 0 .50 0 .500 0.500

Total 9 9 18

Chi-Sq = 6.400, DF = 6

30, 31

HC2Technology tools , and true spirit of cooperation and collaboration between subsidiary , parent headquarters

International Communication, National Culture, Trust

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

30 -JP 31-JP Total 1 0 1 1 0 .50 0 .50 0 .500 0.500

2 4 1 5 2 .50 2 .50 0 .900 0.900

3 4 7 11 5 .50 5 .50 0 .409 0.409

4 1 2 3 1 .50 1 .50 0 .167 0.167

5 3 3 6 3 .00 3 .00 0 .000 0.000

6 4 6 10 5 .00 5 .00 0 .200 0.200

7 6 8 14 7 .00 7 .00 0 .143 0.143

8 6 1 7 3 .50 3 .50 1 .786 1.786

9 1 0 1 0 .50 0 .50 0 .500 0.500

Total 29 29 58

Chi-Sq = 9.209, DF = 8

30 -GR 31-GR Total 1 1 0 1 0 .47 0 .53 0 .596 0.529

2 2 5 7 3 .29 3 .71 0 .508 0.452

3 4 0 4 1 .88 2 .12 2 .382 2.118

4 1 1 2 0 .94 1 .06 0 .004 0.003

6 0 3 3 1 .41 1 .59 1 .412 1.255

Total 8 9 17

Chi-Sq = 9.259, DF = 4

30 -IT 31-IT Total 2 5 2 7 3 .50 3 .50 0 .643 0.643

3 0 2 2 1 .00 1 .00 1 .000 1.000

4 0 1 1 0 .50 0 .50 0 .500 0.500

6 3 0 3 1 .50 1 .50 1 .500 1.500

7 2 4 6 3 .00 3 .00 0 .333 0.333

8 1 2 3 1 .50 1 .50 0 .167 0.167

Total 11 11 22

Chi-Sq = 8.286, DF = 5

30 -US 31-US Total 1 2 1 3 1 .50 1 .50 0 .167 0.167

2 2 1 3 1 .50 1 .50 0 .167 0.167

3 1 3 4 2 .00 2 .00 0 .500 0.500

4 1 0 1 0 .50 0 .50 0 .500 0.500

5 2 3 5 2 .50 2 .50 0 .100 0.100

7 1 1 2 1 .00 1 .00 0 .000 0.000

Total 9 9 18

Chi-Sq = 2.867, DF = 5

175

24, 26, 27

HC3 Trust and knowledge holdback by either subsidiary and / or parent headquartersInternational Communication, Trust (as a major attribute subset)

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

24 -JP 26-JP Total 1 0 3 3 1 .50 1.50 1 .500 1 .500

2 2 0 2 1 .00 1.00 1 .000 1 .000

3 1 1 2 1 .00 1.00 0 .000 0 .000

4 2 0 2 1 .00 1.00 1 .000 1 .000

5 1 2 3 1 .50 1.50 0 .167 0 .167

6 0 4 4 2 .00 2.00 2 .000 2 .000

7 13 12 25 12 .50 12.50 0 .020 0 .020

8 8 6 14 7 .00 7.00 0 .143 0 .143

9 2 1 3 1 .50 1.50 0 .167 0 .167

Total 29 29 58

Chi-Sq = 11.992, DF = 8

24 -GR 26-GR Total 1 1 0 1 0 .53 0 .47 0 .418 0.471

2 2 2 4 2 .12 1 .88 0 .007 0.007

3 2 1 3 1 .59 1 .41 0 .107 0.120

4 1 0 1 0 .53 0 .47 0 .418 0.471

7 1 2 3 1 .59 1 .41 0 .218 0.245

8 2 2 4 2 .12 1 .88 0 .007 0.007

9 0 1 1 0 .53 0 .47 0 .529 0.596

Total 9 8 17

Chi-Sq = 3.620, DF = 6

24 -IT 26-IT Total 2 0 2 2 1 .00 1 .00 1 .000 1.000

3 0 3 3 1 .50 1 .50 1 .500 1.500

5 0 2 2 1 .00 1 .00 1 .000 1.000

6 0 1 1 0 .50 0 .50 0 .500 0.500

7 5 2 7 3 .50 3 .50 0 .643 0.643

8 6 1 7 3 .50 3 .50 1 .786 1.786

Total 11 11 22

Chi-Sq = 12.857, DF = 5

24 -US 26-US Total 1 2 0 2 1 .00 1 .00 1 .000 1.000

2 4 0 4 2 .00 2 .00 2 .000 2.000

3 1 0 1 0 .50 0 .50 0 .500 0.500

4 0 1 1 0 .50 0 .50 0 .500 0.500

5 0 1 1 0 .50 0 .50 0 .500 0.500

6 1 0 1 0 .50 0 .50 0 .500 0.500

7 0 1 1 0 .50 0 .50 0 .500 0.500

8 1 3 4 2 .00 2 .00 0 .500 0.500

9 0 3 3 1 .50 1 .50 1 .500 1.500

Total 9 9 18

Chi-Sq = 15.000, DF = 8

24, 26, 27

HC3 Trust and knowledge holdback by either subsidiary and / or parent headquartersInternational Communication, Trust (as a major attribute subset)

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

24 -US 27-US Total 1 2 3 5 2 .50 2 .50 0 .100 0.100

2 4 0 4 2 .00 2 .00 2 .000 2.000

3 1 1 2 1 .00 1 .00 0 .000 0.000

5 0 1 1 0 .50 0 .50 0 .500 0.500

6 1 0 1 0 .50 0 .50 0 .500 0.500

8 1 1 2 1 .00 1 .00 0 .000 0.000

9 0 3 3 1 .50 1 .50 1 .500 1.500

Total 9 9 18

Chi-Sq = 9.200, DF = 6

24 -IT 27-IT Total 1 0 1 1 0 .50 0 .50 0 .500 0.500

2 0 9 9 4 .50 4 .50 4 .500 4.500

3 0 1 1 0 .50 0 .50 0 .500 0.500

7 5 0 5 2 .50 2 .50 2 .500 2.500

8 6 0 6 3 .00 3 .00 3 .000 3.000

Total 11 11 22

Chi-Sq = 22.000, DF = 4

24 -GR 27-GR Total 1 1 0 1 0 .50 0 .50 0 .500 0.500

2 2 2 4 2 .00 2 .00 0 .000 0.000

3 2 0 2 1 .00 1 .00 1 .000 1.000

4 1 2 3 1 .50 1 .50 0 .167 0.167

7 1 3 4 2 .00 2 .00 0 .500 0.500

8 2 1 3 1 .50 1 .50 0 .167 0.167

9 0 1 1 0 .50 0 .50 0 .500 0.500

Total 9 9 18

Chi-Sq = 5.667, DF = 6

24 -JP 27-JP Total 1 0 3 3 1 .50 1 .50 1 .500 1.500

2 2 11 13 6 .50 6 .50 3 .115 3.115

3 1 9 10 5 .00 5 .00 3 .200 3.200

4 2 0 2 1 .00 1 .00 1 .000 1.000

5 1 1 2 1 .00 1 .00 0 .000 0.000

6 0 1 1 0 .50 0 .50 0 .500 0.500

7 13 2 15 7 .50 7 .50 4 .033 4.033

8 8 2 10 5 .00 5 .00 1 .800 1.800

9 2 0 2 1 .00 1 .00 1 .000 1.000

Total 29 29 58

Chi-Sq = 32.297, DF = 8

176

38, 48

HD1 Post-project review and lessons-learned and project success

Project Success, Group / Team Communication

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

38 -JP 48-JP Total 1 1 0 1 0 .52 0 .48 0 .449 0.482

2 2 0 2 1 .04 0 .96 0 .898 0.964

3 1 0 1 0 .52 0 .48 0 .449 0.482

4 1 3 4 2 .07 1 .93 0 .554 0.595

5 1 0 1 0 .52 0 .48 0 .449 0.482

6 4 12 16 8 .29 7 .71 2 .217 2.381

7 10 5 15 7 .77 7 .23 0 .641 0.689

8 7 3 10 5 .18 4 .82 0 .641 0.688

9 2 4 6 3 .11 2 .89 0 .394 0.424

Total 29 27 56

Chi-Sq = 13.880, DF = 8

38 -GR 48-GR Total 2 1 2 3 0 .82 2 .18 0 .040 0.015

4 1 0 1 0 .27 0 .73 1 .939 0.727

5 0 2 2 0 .55 1 .45 0 .545 0.205

6 3 5 8 2 .18 5 .82 0 .307 0.115

7 0 5 5 1 .36 3 .64 1 .364 0.511

8 3 7 10 2 .73 7 .27 0 .027 0.010

9 1 3 4 1 .09 2 .91 0 .008 0.003

Total 9 24 33

Chi-Sq = 5.817, DF = 6

38 -IT 48-IT Total 2 0 2 2 0 .63 1 .37 0 .629 0.288

5 0 2 2 0 .63 1 .37 0 .629 0.288

6 0 5 5 1 .57 3 .43 1 .571 0.720

7 2 5 7 2 .20 4 .80 0 .018 0.008

8 7 7 14 4 .40 9 .60 1 .536 0.704

9 2 3 5 1 .57 3 .43 0 .117 0.054

Total 11 24 35

Chi-Sq = 6.563, DF = 5

38 -US 48-US Total 1 1 0 1 0 .64 0 .36 0 .198 0.357

2 1 0 1 0 .64 0 .36 0 .198 0.357

3 1 0 1 0 .64 0 .36 0 .198 0.357

4 1 1 2 1 .29 0 .71 0 .063 0.114

5 1 0 1 0 .64 0 .36 0 .198 0.357

6 1 1 2 1 .29 0 .71 0 .063 0.114

7 2 1 3 1 .93 1 .07 0 .003 0.005

8 1 0 1 0 .64 0 .36 0 .198 0.357

9 0 2 2 1 .29 0 .71 1 .286 2.314

Total 9 5 14

Chi-Sq = 6.741, DF = 8

34, 48

HD2 Employees having direct input into decisions and project success

Corporate Culture and Project Success, Teams.

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

34 -US 48-US Total 1 1 0 1 0 .64 0 .36 0 .198 0.357

2 1 0 1 0 .64 0 .36 0 .198 0.357

3 2 0 2 1 .29 0 .71 0 .397 0.714

4 0 1 1 0 .64 0 .36 0 .643 1.157

5 3 0 3 1 .93 1 .07 0 .595 1.071

6 0 1 1 0 .64 0 .36 0 .643 1.157

7 2 1 3 1 .93 1 .07 0 .003 0.005

9 0 2 2 1 .29 0 .71 1 .286 2.314

Total 9 5 14

Chi-Sq = 11.096, DF = 7

34 -IT 48-IT Total 2 0 2 2 0 .63 1 .37 0 .629 0.288

5 0 2 2 0 .63 1 .37 0 .629 0.288

6 0 5 5 1 .57 3 .43 1 .571 0.720

7 3 5 8 2 .51 5 .49 0 .094 0.043

8 7 7 14 4 .40 9 .60 1 .536 0.704

9 1 3 4 1 .26 2 .74 0 .053 0.024

Total 11 24 35

Chi-Sq = 6.579, DF = 5

34 -GR 48-GR Total 2 2 2 4 1 .09 2.91 0 .758 0 .284

3 6 0 6 1 .64 4.36 11 .636 4 .364

5 1 2 3 0 .82 2.18 0 .040 0 .015

6 0 5 5 1 .36 3.64 1 .364 0 .511

7 0 5 5 1 .36 3.64 1 .364 0 .511

8 0 7 7 1 .91 5.09 1 .909 0 .716

9 0 3 3 0 .82 2.18 0 .818 0 .307

Total 9 24 33

Chi-Sq = 24.597, DF = 6

34 -JP 48-JP Total 1 1 0 1 0 .52 0 .48 0 .449 0.482

2 1 0 1 0 .52 0 .48 0 .449 0.482

3 2 0 2 1 .04 0 .96 0 .898 0.964

4 3 3 6 3 .11 2 .89 0 .004 0.004

5 1 0 1 0 .52 0 .48 0 .449 0.482

6 11 12 23 11 .91 11 .09 0 .070 0.075

7 8 5 13 6 .73 6 .27 0 .239 0.256

8 0 3 3 1 .55 1 .45 1 .554 1.669

9 2 4 6 3 .11 2 .89 0 .394 0.424

Total 29 27 56

Chi-Sq = 9.343, DF = 8

177

36, 44

HD3 OTD, Cost, Performance as project success factors vs. recurring business, knowledge gainedProject Success, Basic Communication as it relates directly to KT

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

36 -JP 44-JP Total 1 7 5 12 6 .00 6 .00 0 .167 0.167

2 10 8 18 9 .00 9 .00 0 .111 0.111

3 3 9 12 6 .00 6 .00 1 .500 1.500

4 2 4 6 3 .00 3 .00 0 .333 0.333

5 3 0 3 1 .50 1 .50 1 .500 1.500

6 3 2 5 2 .50 2 .50 0 .100 0.100

7 1 1 2 1 .00 1 .00 0 .000 0.000

Total 29 29 58

Chi-Sq = 7.422, DF = 6

36 -GR 44-GR Total 1 1 0 1 0 .53 0 .47 0 .418 0.471

2 5 3 8 4 .24 3 .76 0 .138 0.155

3 3 5 8 4 .24 3 .76 0 .360 0.405

Total 9 8 17

Chi-Sq = 1.948, DF = 2

36 -IT 44-IT Total 1 4 3 7 3 .92 3 .08 0 .002 0.002

2 3 5 8 4 .48 3 .52 0 .489 0.622

3 2 3 5 2 .80 2 .20 0 .229 0.291

6 4 0 4 2 .24 1 .76 1 .383 1.760

7 1 0 1 0 .56 0 .44 0 .346 0.440

Total 14 11 25

Chi-Sq = 5.563, DF = 4

36 -US 44-US Total 1 4 2 6 3 .00 3.00 0 .333 0 .333

2 2 0 2 1 .00 1.00 1 .000 1 .000

3 0 4 4 2 .00 2.00 2 .000 2 .000

4 2 1 3 1 .50 1.50 0 .167 0 .167

5 1 1 2 1 .00 1.00 0 .000 0 .000

6 0 1 1 0 .50 0.50 0 .500 0 .500

Total 9 9 18

Chi-Sq = 8.000, DF = 5

48, 49

HE1 Subsidiary employee morale and project success

Project Success, Corporate culture, trust as a subset

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

48 -JP 49-JP Total 3 0 1 1 0 .51 0 .49 0 .509 0.529

4 3 1 4 2 .04 1 .96 0 .454 0.472

5 0 1 1 0 .51 0 .49 0 .509 0.529

6 12 4 16 8 .15 7 .85 1 .818 1.888

7 5 8 13 6 .62 6 .38 0 .398 0.413

8 3 5 8 4 .08 3 .92 0 .284 0.295

9 4 6 10 5 .09 4 .91 0 .235 0.244

Total 27 26 53

Chi-Sq = 8.576, DF = 6

48 -GR 49-GR Total 2 2 0 2 0 .94 1 .06 1 .191 1.059

3 0 1 1 0 .47 0 .53 0 .471 0.418

4 0 2 2 0 .94 1 .06 0 .941 0.837

5 2 2 4 1 .88 2 .12 0 .007 0.007

6 5 3 8 3 .76 4 .24 0 .405 0.360

7 5 6 11 5 .18 5 .82 0 .006 0.005

8 7 6 13 6 .12 6 .88 0 .127 0.113

9 3 7 10 4 .71 5 .29 0 .618 0.550

Total 24 27 51

Chi-Sq = 7.116, DF = 7

48 -IT 49-IT Total 2 2 0 2 0 .94 1 .06 1 .191 1.059

3 0 1 1 0 .47 0 .53 0 .471 0.418

4 0 2 2 0 .94 1 .06 0 .941 0.837

5 2 2 4 1 .88 2 .12 0 .007 0.007

6 5 3 8 3 .76 4 .24 0 .405 0.360

7 5 6 11 5 .18 5 .82 0 .006 0.005

8 7 6 13 6 .12 6 .88 0 .127 0.113

9 3 7 10 4 .71 5 .29 0 .618 0.550

Total 24 27 51

Chi-Sq = 7.116, DF = 7

48 -US 49-US Total 3 0 1 1 0 .38 0 .62 0 .385 0.240

4 1 0 1 0 .38 0 .62 0 .985 0.615

5 0 1 1 0 .38 0 .62 0 .385 0.240

6 1 1 2 0 .77 1 .23 0 .069 0.043

7 1 2 3 1 .15 1 .85 0 .021 0.013

8 0 2 2 0 .77 1 .23 0 .769 0.481

9 2 1 3 1 .15 1 .85 0 .621 0.388

Total 5 8 13

Chi-Sq = 5.254, DF = 6

178

48, 50

HE2 Parent headquarters satisfaction and project success

Project Success and Corporate culture

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

48 -US 50-US Total 2 0 2 2 0 .71 1 .29 0 .714 0.397

3 0 4 4 1 .43 2 .57 1 .429 0.794

4 1 1 2 0 .71 1 .29 0 .114 0.063

6 1 1 2 0 .71 1 .29 0 .114 0.063

7 1 0 1 0 .36 0 .64 1 .157 0.643

9 2 1 3 1 .07 1 .93 0 .805 0.447

Total 5 9 14

Chi-Sq = 6.741, DF = 5

48 -IT 50-IT Total 2 2 6 8 3 .69 4 .31 0 .776 0.665

3 0 5 5 2 .31 2 .69 2 .308 1.978

4 0 2 2 0 .92 1 .08 0 .923 0.791

5 2 3 5 2 .31 2 .69 0 .041 0.035

6 5 6 11 5 .08 5 .92 0 .001 0.001

7 5 2 7 3 .23 3 .77 0 .969 0.830

8 7 3 10 4 .62 5 .38 1 .232 1.056

9 3 1 4 1 .85 2 .15 0 .721 0.618

Total 24 28 52

Chi-Sq = 12.946, DF = 7

48 -GR 50-GR Total 2 2 6 8 3 .69 4 .31 0 .776 0.665

3 0 5 5 2 .31 2 .69 2 .308 1.978

4 0 2 2 0 .92 1 .08 0 .923 0.791

5 2 3 5 2 .31 2 .69 0 .041 0.035

6 5 6 11 5 .08 5 .92 0 .001 0.001

7 5 2 7 3 .23 3 .77 0 .969 0.830

8 7 3 10 4 .62 5 .38 1 .232 1.056

9 3 1 4 1 .85 2 .15 0 .721 0.618

Total 24 28 52

Chi-Sq = 12.946, DF = 7

48 -JP 50-JP Total 1 0 3 3 1 .47 1 .53 1 .473 1.420

2 0 8 8 3 .93 4 .07 3 .927 3.787

3 0 4 4 1 .96 2 .04 1 .964 1.894

4 3 3 6 2 .95 3 .05 0 .001 0.001

5 0 3 3 1 .47 1 .53 1 .473 1.420

6 12 1 13 6 .38 6 .62 4 .946 4.769

7 5 2 7 3 .44 3 .56 0 .711 0.686

8 3 2 5 2 .45 2 .55 0 .121 0.117

9 4 2 6 2 .95 3 .05 0 .378 0.364

Total 27 28 55

Chi-Sq = 29.452, DF = 8

49, 50

HE3 Parent headquarters satisfaction and subsidiary employee morale Project Success, Corporate culture, trust as a subset.

Hypotheses :

Questions :

Variables :

JAPAN GERMANY ITALY USA

As. Primary Attrib. Set(s) :

49 -JP 50-JP Total 1 0 3 3 1 .44 1 .56 1 .444 1.341

2 0 8 8 3 .85 4 .15 3 .852 3.577

3 1 4 5 2 .41 2 .59 0 .823 0.764

4 1 3 4 1 .93 2 .07 0 .445 0.413

5 1 3 4 1 .93 2 .07 0 .445 0.413

6 4 1 5 2 .41 2 .59 1 .054 0.978

7 8 2 10 4 .81 5 .19 2 .107 1.957

8 5 2 7 3 .37 3 .63 0 .788 0.732

9 6 2 8 3 .85 4 .15 1 .198 1.112

Total 26 28 54

Chi-Sq = 23.444, DF = 8

49 -GR 50-GR Total 2 0 6 6 2 .95 3 .05 2 .945 2.840

3 1 5 6 2 .95 3 .05 1 .285 1.239

4 2 2 4 1 .96 2 .04 0 .001 0.001

5 2 3 5 2 .45 2 .55 0 .084 0.081

6 3 6 9 4 .42 4 .58 0 .455 0.439

7 6 2 8 3 .93 4 .07 1 .094 1.055

8 6 3 9 4 .42 4 .58 0 .566 0.546

9 7 1 8 3 .93 4 .07 2 .404 2.318

Total 27 28 55

Chi-Sq = 17.354, DF = 7

49 -IT 50-IT Total 2 0 6 6 2 .95 3 .05 2 .945 2.840

3 1 5 6 2 .95 3 .05 1 .285 1.239

4 2 2 4 1 .96 2 .04 0 .001 0.001

5 2 3 5 2 .45 2 .55 0 .084 0.081

6 3 6 9 4 .42 4 .58 0 .455 0.439

7 6 2 8 3 .93 4 .07 1 .094 1.055

8 6 3 9 4 .42 4 .58 0 .566 0.546

9 7 1 8 3 .93 4 .07 2 .404 2.318

Total 27 28 55

Chi-Sq = 17.354, DF = 7

49 -US 50-US Total 2 0 2 2 0 .94 1 .06 0 .941 0.837

3 1 4 5 2 .35 2 .65 0 .778 0.692

4 0 1 1 0 .47 0 .53 0 .471 0.418

5 1 0 1 0 .47 0 .53 0 .596 0.529

6 1 1 2 0 .94 1 .06 0 .004 0.003

7 2 0 2 0 .94 1 .06 1 .191 1.059

8 2 0 2 0 .94 1 .06 1 .191 1.059

9 1 1 2 0 .94 1 .06 0 .004 0.003

Total 8 9 17

Chi-Sq = 9.775, DF = 7

179

The chi-square test, such as the one conducted here using the MiniTab® software

and whose results are displayed in the previous pages, essentially seeks to identify

whether findings are appropriate and thus can be generalized to a full population, or

if the findings are simply due to sampling error [95]. However, such tests for

statistical significance determine whether a relationship exists between variables,

but they do not measure strength of such a potential relationship.

A fairly simple and versatile measure of association derived directly from the chi-

square values is Cramer’s V. This test is used extensively in survey research. The

relationship between Chi-Square and Cramer’s V is show below; where n denotes

the sample size and M the minimum number of either rows or columns (whichever

is the smaller value).

V = χ2

n ( M-1 )

We summarize our intermediate analysis results, including chi-square and Cramer’s

V below. At the end of this Chapter a comprehensive summary is also be presented.

180

Table 4-24 : Chi-Square ( χ2 ) and Cramer's V Significance and Association Summary Values and Interpretations

Hypotheses Question / Country χ2 dF χ2*.05 M n V Interpretation** of V

Japan 40.14 7 3 58 0.588 Relatively strong associationGermany 5.24 5 3 17 0.393Italy 11.09 4 3 22 0.502 Relatively strong associationUSA 7.33 6 3 18 0.451Japan 10.83 7 3 58 0.306Germany 8.97 6 3 17 0.514Italy 10.29 6 3 22 0.484USA 9.47 6 3 18 0.513Japan 16.46 7 3 58 0.377 Moderate AssociationGermany 7.10 6 3 17 0.457Italy 13.84 5 3 23 0.549 Relatively strong associationUSA 13.33 8 3 18 0.609Japan 15.98 7 3 58 0.371 Moderate AssociationGermany 8.30 6 3 17 0.494Italy 22.00 5 3 22 0.707 Strong AssociationUSA 10.67 7 3 18 0.544Japan 18.46 7 3 58 0.399 Moderate AssociationGermany 7.63 8 3 17 0.474Italy 10.67 4 3 22 0.492 Relatively strong associationUSA 11.33 6 3 18 0.561Japan 13.82 8 3 58 0.345Germany 4.82 5 3 17 0.377Italy 11.10 4 3 22 0.502 Relatively strong associationUSA 8.13 7 3 18 0.475Japan 20.06 7 3 58 0.416 Relatively strong associationGermany 12.80 6 3 16 0.632 Strong AssociationItaly 12.10 5 3 23 0.513 Relatively strong associationUSA 7.33 6 3 18 0.451Japan 17.99 7 3 58 0.394 Moderate AssociationGermany 6.14 5 3 16 0.438Italy 22.00 6 3 22 0.707 Strong AssociationUSA 3.87 5 3 18 0.328Japan 19.17 7 3 58 0.407 Relatively strong associationGermany 13.33 8 3 16 0.645Italy 7.00 4 3 22 0.399USA 9.67 6 3 18 0.518Japan 18.27 7 3 58 0.397 Moderate AssociationGermany 8.67 4 3 16 0.521Italy 11.10 5 3 22 0.502 Relatively strong associationUSA 10.00 8 3 18 0.527Japan 13.82 8 3 58 0.345Germany 4.82 5 3 17 0.377Italy 11.09 4 3 22 0.502 Relatively strong associationUSA 8.13 7 3 18 0.475Japan 26.14 8 3 58 0.475 Relatively strong associationGermany 17.00 6 3 17 0.707 Strong AssociationItaly 0.41 2 3 22 0.097USA 6.40 6 3 18 0.422Japan 9.21 8 3 58 0.282Germany 9.26 4 3 17 0.522 Relatively strong associationItaly 8.29 5 3 22 0.434USA 2.87 5 3 18 0.282Japan 11.99 8 3 58 0.321Germany 3.62 6 3 17 0.326Italy 12.86 5 3 22 0.541 Relatively strong associationUSA 15.00 8 3 18 0.645 Strong AssociationJapan 32.30 8 3 58 0.528 Relatively strong associationGermany 5.67 6 3 18 0.397Italy 22.00 4 3 22 0.707 Strong AssociationUSA 9.20 6 3 18 0.506Japan 13.88 8 3 56 0.352Germany 5.82 6 3 33 0.297Italy 6.56 5 3 35 0.306USA 6.74 8 3 14 0.491Japan 9.34 8 3 56 0.289Germany 24.60 6 3 33 0.611 Strong AssociationItaly 6.58 5 3 35 0.307USA 11.10 7 3 14 0.630Japan 7.42 6 3 58 0.253Germany 1.95 2 3 17 0.239Italy 5.56 4 3 25 0.333USA 8.00 5 3 18 0.471Japan 8.58 6 3 53 0.285Germany 7.12 7 3 51 0.264Italy 7.12 7 3 51 0.264USA 5.25 6 3 13 0.449Japan 29.45 8 3 55 0.517 Relatively strong associationGermany 12.95 7 3 52 0.353Italy 12.95 7 3 52 0.353USA 6.74 5 3 14 0.491Japan 23.44 8 3 54 0.466 Relatively strong associationGermany 17.35 7 3 55 0.397 Moderate AssociationItaly 17.35 7 3 55 0.397 Moderate AssociationUSA 9.77 7 3 17 0.536

* criteria based on Rea, Parker Reference [95], page 186 - Critical Values of the Chi-Square Distribution** criteria based on Rea, Parker Reference [95], page 189 - Interpretation of Calculated Cramer's V

12 / 35

18 / 24

16 / 24

14 / 24

18 / 24

18 / 35

16 / 35

14 / 35

24 / 27

24 / 26

30 / 31

34 / 35

48 / 49

36 / 44

34 / 38

38 / 48

HE2

HE3 49 / 50

48 / 50

HD1

HD2

HD3

HE1

HC1

HC2

HC3

HC3

HB3

HB3

HB3

HB4

HB2

HB2

HB2

HB3

HB1 20 / 24

HB1

HB2 12 / 24

22 / 24

x

xxxxx

x

x

x

x

x

xxx

x

x

x

x

xxx

x

xxx

x

xxx

xxxx

x

xxxxxx

xxxxxxxxxx

xxx

x

181

4.2.2.2 ANOVA Confirmation by Survey Question

Results obtained from our analysis using MiniTab® are documented in Appendix C

under the heading ANOVA Raw Data. Our final analysis results, as well as

Hypotheses disposition and discussion, are shown in the following section and in

tabulated form.

4.2.3 Analysis Summary

Based on our results and subsequent analysis including the Correlational, and

ANOVA analysis performed in MiniTab® we can establish a relational model once

we establish and conclude a final disposition on our Hypotheses; please refer to

summary Tables 4-24, 4-2, and 4-26, as well as Appendix C for ANOVA results.

We had previously established the following construct for which we now establish

the model based on our results.

Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +

…. …. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + e

where fcc is the function for the corporate culture set, fnc is the function for the

national culture set, and so on. Because not all models can be ideally perfect, we

also include an error term e.

182

Table 4-25 : Analysis Results Summary and Hypotheses Disposition

Null Hypotheses ( H0... )

Associated Primary Attribs.

Pearson Correl.

r

Based on r > +/- 0.5 χ2 χ2*

.05Interpretation** of Cramer's V

Conclusion by Country

Conclusion by Set

JP -0.409 40.14 Reject Null

Reject NullReject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject NullReject Null

Reject Null

Reject Null

Reject NullReject Null

Reject NullReject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject Null

Reject NullReject Null

Reject Null

Reject Null

Reject Null Hypothesis

Reject Null Hypothesis

Reject Null Hypothesis

Reject Null Hypothesis

Reject Null Hypothesis

Reject Null Hypothesis

Reject Null Hypothesis

Reject Null Hypothesis

Reject Null Hypothesis

Relatively strong associationGR 0.597 5.24

IT 0.414 11.09 Relatively strong associationUS 0.254 7.33

JP 0.638 10.83

GR 0.188 8.97

IT 0.526 10.29

US -0.085 9.47

JP 0.360 16.46 Moderate AssociationGR 0.212 7.10

IT 0.043 13.84 Relatively strong association InconclusiveUS -0.655 13.33

JP 0.186 15.98 Moderate Association InconclusiveGR 0.000 8.30

IT -0.347 22.00 Strong AssociationUS -0.378 10.67

JP 0.048 18.46 Moderate Association InconclusiveGR 0.000 7.63

IT 0.376 10.67 Relatively strong associationUS -0.357 11.33

JP 0.525 13.82

GR 0.658 4.82

IT 0.497 11.10 Relatively strong associationUS -0.134 8.13

JP 0.340 20.06 Relatively strong associationGR -0.209 12.80 Strong Association InconclusiveIT -0.025 12.10 Relatively strong association InconclusiveUS -0.129 7.33

JP 0.242 17.99 Moderate Association InconclusiveGR 0.569 6.14

IT -0.401 22.00 Strong AssociationUS 0.335 3.87

JP 0.267 19.17 Relatively strong associationGR -0.599 13.33

IT 0.526 7.00

US -0.169 9.67

JP 0.460 18.27 Moderate AssociationGR 0.113 8.67

IT 0.572 11.10 Relatively strong associationUS -0.474 10.00

JP 0.525 13.82

GR 0.658 4.82

IT 0.495 11.09 Relatively strong association

US -0.134 8.13

JP 0.096 26.14 Relatively strong association Inconclusive

GR -0.367 17.00 Strong Association

IT 0.983 0.41

US 0.400 6.40

JP 0.532 9.21

GR 0.152 9.26 Relatively strong association Inconclusive

IT 0.329 8.29

US 0.589 2.87

JP 0.860 11.99

GR 0.622 3.62

IT 0.120 12.86 Relatively strong association InconclusiveUS -0.463 15.00 Strong AssociationJP -0.139 32.30 Relatively strong association InconclusiveGR 0.258 5.67

IT -0.234 22.00 Strong AssociationUS -0.077 9.20

JP 0.426 13.88

GR 0.681 5.82

IT 0.749 6.56

US -0.344 6.74

JP 0.874 9.34

GR -0.441 24.60 Strong Association

IT 0.774 6.58

US -0.462 11.10

JP 0.688 7.42

GR 0.832 1.95

IT 0.594 5.56

US 0.134 8.00

JP 0.591 8.58

GR 0.648 7.12

IT 0.648 7.12

US 0.174 5.25

JP 0.266 29.45 Relatively strong association InconclusiveGR 0.260 12.95

IT 0.260 12.95

US -0.087 6.74

JP 0.575 23.44 Relatively strong associationGR 0.344 17.35 Moderate Association InconclusiveIT 0.344 17.35 Moderate Association InconclusiveUS 0.600 9.77

* criteria based on Rea, Parker Reference [95], page 186 - Critical Values of the Chi-Square Distribution** criteria based on Rea, Parker Reference [95], page 189 - Interpretation of Calculated Cramer's V

Organizations focus on delivery and performance, more so than cost, recurring business, and knowledge-gain, as the key measures for project success.

Organizations DO NOT focus on delivery and performance, more so than cost, recurring business, and knowledge-gain, as the key measures for project success.

There is NO positive relationship between subsidiary employee morale and project success.

There is a positive relationship between subsidiary employee morale and project success.

There is a positive relationship between proactively conducting and managing a system for post-project reviews and lessons-learned meetings and project success.

There is NO positive relationship between proactively conducting and managing a system for post-project reviews and lessons-learned meetings and project success.

There is NO positive relationship between employees having a direct input into decisions that affect them and project success.

There is a positive relationship between employees having a direct input into decisions that affect them and project success.

There is a positive relationship between trust and knowledge transfer that occurs in both directions between headquarters and subsidiary.

There is NO positive relationship between the way technical communications are handled on a daily basis and trust.

There is NO positive relationship between how technical communication channels are modeled between subsidiary and headquarters and trust.

There is NO positive relationship between how technical communication channels are modeled between subsidiary and headquarters and establishing a truly shared meaning in succesful knowledge transfer.

There is NO positive relationship between trust and knowledge transfer that occurs in both directions between headquarters and subsidiary.

There is a positive relationship between employees having a direct input into decisions that affect them and establishing a truly shared meaning in succesful knowledge transfer.

There is NO positive relationship between employees having a direct input into decisions that affect them and establishing a truly shared meaning in succesful knowledge transfer.

There is a positive relationship between the availability of technology tools and a true spirit of cooperation / collaboration between subsidiary and headquarters.

There is NO positive relationship between the availability of technology tools and a true spirit of cooperation / collaboration between subsidiary and headquarters.

Organizations that implement a many-to-many technical communication channel model are more likely to establish and maintain a truly learning and trusting relationship.

Organizations that implement a many-to-many technical communication channel model are NOT more likely to establish and maintain a truly learning and trusting relationship.

There is a positive relationship between how technical communication channels are modeled between subsidiary and headquarters and establishing a truly shared meaning in succesful knowledge transfer.

Trust, Modified Hall Set, Language, Deg.of Feedback, Hofstede Set, Parent Dependency and Level of Integration.

Parent Dependency and Level of Integration; Degree of Hierarchical Organization; Trust; level of holdback; Degree of Social and Cultural Empathy to Parent

Parent Dependency and Level of Integration; Degree of Hierarchical Organization; Trust; level of holdback; Degree of Social and Cultural Empathy to Parent; Language; Degree of Strategic Integration

Trust; Degree of Feedback; Language; Hofstede Set;

Degree of Hierarchical Organization; Democratic vs. Autocratic

Degree of Technology Usage; Time Lag and Difference; Trust; Hofstede Set

Trust; Degree of Holdback by Subsidiary

Trust; Degree of Holdback by Parent

There is a positive relationship between how technical communication channels are modeled between subsidiary and headquarters and trust.

Delivery, Budget, Tech. Performance; Degree of Knowledge-gained & Lessons-LearnedDeg. of Hierarchical Organization; Democratic vs. Autocratic; Delivery, Budget, Tech. Perform Delivery, Budget, Tech. Performance; Deg. of Knowledge-gained & Lessons-Learned; Market Share expansion

Trust; Delivery, Budget, Tech. Performance

Degree of Social and Cultural Empathy to Parent; Delivery, Budget, Tech. Performance

Trust; Degree of Parent-Integration; Project Success Set (indirect)

Inconclusive

Associated Question

RelationshipHypotheses

There is a positive relationship between the way technical communications are handled on a daily basis and trust.

Inconclusive

Inconclusive

Inconclusive

Inconclusive

Inconclusive

Inconclusive

Inconclusive

Inconclusive

Inconclusive

Inconclusive

12 / 35

18 / 24

16 / 24

14 / 24

18 / 24

18 / 35

16 / 35

14 / 35

24 / 27

24 / 26

30 / 31

34 / 35

48 / 49

36 / 44

34 / 38

38 / 48

HE2

HE3 49 / 50

48 / 50There is a positive relationship between parent headquarters satisfaction and project success.

There is NO positive relationship between parent headquarters satisfaction and project success.

There is NO positive relationship between parent headquarters satisfaction and subsidiary employee morale.

There is a positive relationship between parent headquarters satisfaction and subsidiary employee morale.

HD1

HD2

HD3

HE1

HC1

HC2

HC3

HC3

HB3

HB3

HB3

HB4

HB2

HB2

HB2

HB3

HB1 20 / 24

HB1

HB2 12 / 24

22 / 24

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject Null

Fail to Reject NullFail to Reject Null

Fail to Reject Null Hypothesis

183

Once again, with the resulting analysis and results of our hypotheses testing, we

establish the appropriate influences to our model which is calculated thru

regression analysis within MiniTab®

Japan Model :

Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +

…. …. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + e

Project Success(JP) = 1.79 + 0.276(JP)cc - 0.224(JP)nc + 0.276(JP)bc + 0.625(JP)ic - 0.566(JP)gt + e

German Model :

Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +

…. …. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + e

Project Success(GR) = - 0.15 + 0.935(GR)cc + 1.87(GR)nc - 0.71 (GR)bc - 0.767(GR)ic - 0.116(GR)gt + e

Italy Model :

Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +

…. …. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + e

Project Success(IT) = 3.89 + 2.06(IT)cc - 1.37(IT)nc + 0.478(IT)bc - 1.01(IT)ic - 0.845(IT)gt + e

Unfortunately we could not conclude anything of significance for the United States.

This is based on the fact that we did not have enough data for this subset and as is

apparent in Table 4-26, for the most part we failed to reject the Null Hypotheses

184

in regards to USA responses. Additionally our model must be further verified thru

a validation program because of the fact that there were areas were no conclusion

could be made. We feel these areas which we could not definitively establish a

conclusion regarding our Hypotheses have the potential to “water-down” or diminish

the strength of this model. However we feel confident that this is an excellent initial

theoretical construct which we had initially set out to create within the objectives of

our research. Based on the sub hypotheses analysis we reject the Null Hypotheses

and confirm that there is in fact a relationship between successful knowledge

transfer between parent and subsidiary organizational project success.

Further, qualitative, discussion is presented in Chapter 5. This is where we will

discuss further the actual attributes and their importance per the individual sets in

the model(s).

COMPOSITE Model :

Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +

….…. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + e Project Success(All) = 12.8 + 0.004(All)cc + 0.291(All)nc

- 0.053(All)bc + 0.020(All)ic - 0.790(All)gt + e

185

CHAPTER 5 – CONCLUSION

5.1 Discussion and Implications

The goal of this research was to assess the relative value of knowledge transfer

processes and their relationship to the success of international project management

teams and projects and identify attributes for success. The mathematical / quantitative

relationship was established and documented in Chapter 4. This relationship is

composed of 5 terms or what we refer to as attribute “sets” : a corporate culture

attribute set (cc); a national culture attribute set (nc); a basic communication theory

attribute set (bc); an international communication attribute set (ic); and a group / team

communication attribute set (gt). The form of the equation is shown below.

Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +

….…. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + error term

Furthermore with the relationship construct of our research that culture overall is a

function of both corporate and national cultural attributes particular to say Japanese

companies, or German companies, or rigidly hierarchical companies vs. team-oriented

organization; that communications overall is a construct of basic communication theory,

as well as international, and group / team communications; and with the concept that

knowledge transfer is in effect a construct or function of communication and culture; we

feel we have provided a good integration within our theoretical framework for which our

subsequent analysis essentially provided the weighing factors of the variables. This can

be referenced in our Variable Utilization Matrix, Table 5-1 below.

186

we get away from the analytics and discuss some of the practical implications for the

If

industry we can begin to see some real value in day-to-day potential operational process

improvements. Going from the analytics to the “practical” or going from quantitative to

qualitative we basically start looking at the individual variables which make up the sets

we described above, and which are shown in Table 5-1, and see how these (based on

responses from our survey instrument) can provide some insight within our industry.

187

One of the key areas investigated was how communication between subsidiary and

zed

iary talks to one person at headquarters

arters

d subsequent analysis on which model is best for which type of company, let

lt since

apparent discrepancy between data and real-world practice we

also

It was concluded that the one-to-one model has been optimized for those small

ls

headquarters takes place at a higher-tier level. Four models were initially conceptuali

based on real-world practice. These are :

1. one-to-one : one person at subsid

2. one-to-many : one person at subsidiary talks to many at headquarters

3. many-to-one : many persons at subsidiary talk to one person at headqu

4. many-to-many : unilateral communication across all personnel as required

The data an

alone which model is best overall, was mixed. More than 65% of Japanese companies

did not agree with a one-to-one model and more than 90% of Japanese company

respondents personally felt that this was not the best approach for a higher-tier

knowledge transfer structure. As previously mentioned this is an interesting resu

this is in fact how a good deal of Japanese companies do in fact structure their

communications and knowledge transfer systems.

In trying to identify this

finally realized the relationship not only for Japanese companies but for both German

and Italian organizations as well. The key was in several related factors such as :

company size, age, and number of expats being stationed at the subsidiary. We

investigated whether the company’s foreign expats being stationed at headquarters and

whether the company being private vs. public had an influence; but there was no such

influence based on these factors.

subsidiaries which are essentially run by a transplant from headquarters who dea

188

directly with technical matters within the large projects in question. In such cases both

explicit and tacit knowledge transfer does in fact occur very efficiently and results in an

above-average project team success rate. But, in effect, in these situations the

individual handling the transfer is also more than likely the defacto project manager of a

relatively small project team made up primarily of headquarters personnel, so therefore

not international. It is extremely difficult for such a structure to be maintained as

projects become more complex and the natural tendency is of course for the company to

expand. Therefore this model is fairly limiting and correlates to smaller company size

and limited project scope.

Similarly, Model 2 (one-to-many) is limited to smaller subsidiaries in the United States

and primarily to those that have very limited production capabilities outside their home-

country headquarters. Additionally the technical transfer conduit in this case will not be a

technically-trained engineer but will most likely be an executive level individual that has

the authority to prioritize and make requests from several areas back at headquarters.

Unfortunately in this situation there is a real danger to sub-optimize the technical

specification transfer between customer and headquarters. It was concluded that for this

type of arrangement to succeed the technological side of communication such as direct

video conferencing or face-to-face meetings amongst all parties must occur on a fairly

frequent basis in order to minimize the danger of the company not meeting project

specifications and expectations.

Model 3, stipulating many subsidiary employees communicating directly with a single

headquarters “filter” individual, on the surface may seem to provide a streamlined

approach to coordinating communication with one or more subsidiaries of a large foreign

manufacturer, however the data and the comments made during the course of the

189

research indicate that logistically this is a difficult approach in terms of workload for a

single individual at headquarters. Once again as the company grows and knowledge

transfer demands increase, the effectiveness of this approach will decrease; it is

unsustainable. Furthermore, and even though we did not investigate this concept in

great detail, we feel that in this and similar situations where the headquarters has

competing priorities between say a U.S. subsidiary and another foreign subsidiary in

China or SouthEast Asia for example, there is tendency for the headquarters to focus

more in those fast-paced growing economies even though the headquarters may be

faced with legitimate alternate areas of growth such as Latin and South America. The

data indicated that priorities (at least up to mid-2008) were in fact focused in Asia and

not the United States. We make this claim based on review of specific on-time-delivery

data. This data can be for both actual product manufactured at parent headquarters and

destined for the Americas, but for our case here we focus on on-time-delivery of

technical information from parent headquarters to U.S. subsidiary. If this

information, such as a large project proposal / quotation is done by a single individual or

is filtered thru a single individual at headquarters, on-time-delivery suffers. Response

rates have grown to several weeks in these situations and the level of service does in

fact deteriorate and leads to a morale issue in the subsidiary personnel complaining that

they can not provide adequate service to their local customers. By no stretch of the

imagination, one would also think that this would both directly and indirectly impact

project business.

Model 4, a many-to-many type of communication structure for knowledge transfer seems

to be the ideal approach favored by the majority of larger companies. A positive

correlation was analyzed and determined between this model, the personal opinion and

perspective of individuals with over 20 years experience in Project Management and

190

with larger more established companies of 500 or more employees. Furthermore we

confirmed our hypotheses that organizations that implement the many-to-many technical

communications channel model are more likely to establish and maintain a truly learning

and trusting relationship between subsidiary and parent company. This we feel is an

important finding because : (1) it enables a subsidiary to develop and mature the “right

way” and (2) it helps the parent expand globally, the “right way.” There have been

situations were a one-to-one or one-to-many filter has remained in place and,

unfortunately, adversely impacted not only the subsidiary but also the parent

organization. One specific example which relates more towards Asian rather than

European companies is in the area of language and the threat of not developing

language resources and international cross-departmental relationship because a filtered

knowledge transfer model remained in place. Perhaps the key next step (future

research) is to identify at what point in a subsidiary’s growth stage does one switch from

a one-to-one or one-to-many model to that of many-to-many structure in order to

maintain optimal operational efficiency and knowledge flow across all departments

between subsidiary and parent company.

From a national culture point of view, the research data and analysis indicated a slightly

greater tendency for Japanese as well as European companies to measure project

success in both tangible and intangible constructs. For example, delivery, price, and

performance is central to all companies but the European and Asian companies also

rated employee morale and satisfaction as a part of project success. They also agreed

that knowledge transfer is an important measure of project success as well. U.S.

companies also felt this was a factor but not to the extent of the others. Furthermore

Japanese companies seem to lead the way in terms of thinking of projects as

opportunities for further knowledge creation. This seems to confirm Nonaka and

191

Takeuchi’s [87] central theme which they presented in their text “The Knowledge-

Creating Company: How Japanese Companies Create the Dynamics of Innovation” In

his reference the concept of Knowledge Creation leading to Continuous Innovation

leading to Competitive Advantage is the key hypothesis. Although in the past 15 years

the entire idea of a Japanese miracle management system has been questioned for

various reasons outside the scope of this research, this concept that Nonaka and

Takeuchi present is valid and in fact was confirmed by a portion of our data, as stated. A

greater portion of Japanese companies place greater value on the intangibles that can

be gained thru successful projects.

As outlined in Chapter 2 Western management traditions are rooted in explicit

knowledge, that is, something clear-cut, formal, systematic. Japanese companies

however have a different understanding of knowledge based on different values and

beliefs. They do recognize the importance of explicit knowledge but to these

organizations it seems, a far more important type of knowledge is tacit knowledge.

Tacit knowledge however is “…highly personal and difficult to formalize thus making it

difficult to communicate and share with others…”[87], and, according to Nonaka and

Takeuchi, “…it includes subjective insights, intuitions, hunches and is rooted in the

individual’s experience, ideals, and values” [87]. Throughout various portions of our

data we did see a sensitivity for Japanese companies towards this sort of abstract

concept beyond the traditional ideas of project management and success.

The difficulty for Japanese companies however, we came to realize in taking a closer

look a the data, is that of language. Language falls under our international

communications attribute set and unfortunately even though it seems from a cultural and

knowledge management point of view Japanese companies may seem to have an

192

advantage as Nonaka and Takeuchi contend, their disadvantage is that in this industry

(we must qualify the statement) Japanese companies do not communicate with their

subsidiaries in an optimal manner simply because back at the parent facility their is in

fact a shortage of English speaking personnel. This also goes back to our concept of

one-to-one filtering between parent and subsidiary and the two single-multipoint variant

models. The result of this fact is that knowledge conversion, to use Nonaka and

Takeuchi’s term, between explicit and tacit, between parent and subsidiary……is

hampered and a major portion of the idea of a learning organization, even though ideally

is desired on a personal level, as is apparent from our data, in reality it is hampered.

This also relates to our data gathered on day-to-day communication and knowledge

transfer. Even though we understand that tacit knowledge may be difficult to convey by

standard means such as documentation, based on our results and analysis, an

overwhelming majority of Japanese companies (96%) indicated that they prefer written

communication over other means. We feel that this also relates to language and the fact

that writing could potentially be easier than speaking, especially when you have a 12-

hour time window between transmission as is the case between a U.S. subsidiary and a

parent in Japan. Unfortunately because of this another set of attributes can be

negatively affected. So, whereas the international communication set which includes

language can influence our model in one direction, the basic communication set in turn

may have to be adjusted say for the fact that now transmission characteristics have

changed. This of course is seen in real life when company’s rely on email versus

telephone or video conferencing.

Recently however there are initiatives within Japanese companies to greatly improve

language capabilities. Appendix E provides a representation of a multilingual process

designed to systematically translate and provide dual language capabilities that can be

193

utilized and shared between parent and subsidiary. From a technological point of view

this may not seem new at all and in fact it is not, it existed years ago, however from a

conceptual knowledge sharing, learning, trust, and communications aspect this is new

territory where parent headquarters whether in Tokyo or Berlin is actually proactively

sharing core knowledge. Unfortunately what we discovered based on our data is that

only a few companies in the industry today practice this philosophy. Again, it’s the

mentality of the organization relating language and knowledge transfer. It is not the

technology and certainly it should not be …….“how many expats can I place at my

subsidiaries to establish a suboptimal knowledge transfer and communication structure.”

The reason we go to such a great detail in our comments regarding this aspect is

because our analysis did in fact reveal a relationship between both organizational and

national culture and knowledge transfer and to a certain extent we confirmed some of

the basic concepts established by Davenport and Prusak [31]. Additionally such

interaction also starts to involve trust which we will discuss below, but suffice it to say

that it is an important component of the overall system under consideration. In fact trust

was a significant factor involved with knowledge transfer and with us rejecting the

specific null sub hypotheses in both Japanese and German companies.

As for utilizing technology tools for optimal communication and as a conduit for

knowledge transfer, unfortunately the majority in the industry regardless of company size,

or any other significant variables, rated low in the use of such technology with the

exception of German companies who based on the data seem to have embraced

technology to a greater extent compared to their counterparts. Also, survey respondents

preferred these tools but the companies themselves, again with the exception of

Germany, utilized them in a very limited manner. Although we did not delve into the

194

details, a potential future research opportunity could be to what extent does this

technology contribute to knowledge transfer.

Regarding morale and project success our results were mixed and inconclusive.

Although we could reject the null hypotheses and establish a relationship between

morale and project success, we could not fulfill the overall construct and expand it to

parent headquarters satisfaction and project success (failed to reject the null

hypotheses) and closing the circle with the final portion of parent headquarters

satisfaction and subsidiary employee morale (inconclusive). This can also be considered

an interesting area for future research – namely the relationship between subsidiary

employee morale, parent headquarters level of satisfaction, and project success,

and the interaction among these variables.

Suggested Operational Process Improvements Based on our Research :

Project success for the target companies tends to focus on delivery, meeting

performance requirements, and cost; in that order. Because of the nature in this

industry for headquarters to supply critical engineering information as well as

core and auxiliary products, it seems on-time-delivery (schedule) is the major

factor. Although data was not specifically collected on the reasons for delivery

being the critical factor, it is inferred that competing priorities at headquarters is

the main reason. It is recommended that companies either address the

underlying issues involved or place resources and emphasis on meeting

on-time delivery.

Smaller companies favor single-points of contact but realize their limitations with

both company growth as well as optimal project success. Larger more

established companies have successfully developed unilateral many-to-many

model type communication and knowledge transfer channels. The key area

that a company needs to realize and come to understand is at what point

in its, and its subsidiary’s, maturity development do the knowledge

195

transfer channels change in order to maintain operational efficiency,

otherwise there will be a deterioration in operations.

European companies seem to be leading Asian companies in successfully

transferring their knowledge from headquarters to subsidiary. An important part

of this is language and the fact that over 85% of the European companies

studied conduct their international business in English thus complimenting the

many-to-many model (Model 4) of knowledge transfer by not requiring

headquarters expats at the subsidiary to act as filters; something that Asian

companies have done in the past but recently are starting to migrate away from

this practice in a similar approach to the Europeans. According to the August

2008 issue of Talent Management Journal 25% of the world’s population

speaks English, it’s the official language of 50+ countries, 1 billion people are

learning English today and according to the British Council this number will

double by 2015. Establish English as a common business language in

order to facilitate communications and knowledge transfer.

Although realizing the potential for technology tool such as video conferencing

and other collaboration software, there was no significant use of such

technology (with the exception of the Germans) to further alleviate and

expedite knowledge transfer between headquarters and subsidiary. This is

indicative of the industry overall. Companies in this industry need to embrace

knowledge transfer and communication tools in order to stay competitive in an

increasingly global economy. There is a tendency for these companies to focus

on core business of machining steel and making machinery and not be

concerned with technology such as internet, video, collaboration software, etc.

It is recommended to invest in technological infrastructure to facilitate

communications and thus knowledge transfer.

There is an indication that there is a hold-back of certain knowledge and

product technology that does in fact take place between headquarters and

subsidiary (both ways). Respondents indicated that this is undesirable but a

certain portion did concede thru their survey data that this does take place. In

some cases our data indicated more than 90% feel either the subsidiary or

196

headquarters is withholding information from the other ! Furthermore,

subsequent analysis did indicate that this may play a role in morale, and

certainly trust issues. Top Management in these companies need to

consider how the companies operate in relation to standing orders on

information sharing both at the subsidiary level and headquarters.

Companies also need to strengthen their unilateral communication structures

amongst all project teams and members. Having single points of contact to filter

information between subsidiary and headquarters will not suffice and is

unsustainable. The additional benefit of having Model 4 unilateral

communication and knowledge transfer lines is the continued development of

parent company headquarter employees in both language and international

business practices. An interesting idea that we would like to put forth is the

following – company executives should consider a reverse migration of

subsidiary expats TO headquarters for extensive stays. Up to now we have

been discussing Japanese nationals for example staying at the subsidiary in the

U.S. while the subsidiary is established. Perhaps we have reached a maturity

level in the industry where now American subsidiary personnel should be

systematically assigned stays in Japan to affect a change at Headquarters ?

This holds true also for European companies.

There needs to be continued development of well-structured and professional

project management education within the industry in order to develop the next

generation of project managers coordinating international teams. Very few if any

respondents indicated any sort of professional project management structure

including conducting any sort of post-project reviews or lessons learned. We

recommend to strengthen the professional project management

knowledge within these companies. More and more global competition

will require improved project management skills.

Thru this continued development of project management and international

project teams, it is hoped that some of the lingering attitudes of “us vs. them”

that still appear between a subsidiary and its headquarters in a majority of

international organizations in this industry and the manufacturing sector overall,

197

will slowly evaporate; to be replaced by improved morale and true team

cooperation. In the researchers opinion, this is inevitable, it is only a mater of

facilitating and accelerating its acceptance. This is critical because if it does not

occur it can create a sort of “death spiral” effect between headquarter levels of

satisfaction and levels of employee morale at the subsidiary. Although we could

not definitively make a conclusion on this because of its fairly complex nature,

we feel it is a major factor that affects various areas and attributes in our study.

5.2 Theoretical Construct and Future Research

Our model construct is shown below; and for our overall research we established the

composite equation shown in blue text below the model.

Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +

…. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + error term Project Success(All) = 12.8 + 0.004(All)cc + 0.291(All)nc

- 0.053(All)bc + 0.020(All)ic - 0.790(All)gt + e

Our model should be further verified thru a validation program because of the fact

that there were areas were no conclusion could be made thus leaving some

variable / attribute sets with not as much weight as others and therefore not as

much influence as they potentially could have exerted. We feel the areas which we

could not definitively establish a conclusion regarding our Hypotheses have the

slight potential to “water-down” or diminish the strength of this model to some

extent. We are confident that this effect however is minimal.

Another potential limitation is that the data collected to establish the model thru our

analysis represented the perception of various individuals, as opposed to an

198

objective measure. We compensated for this by constructing our survey in such a

way as to request : (1) information from the respondent’s company and how it

operates but also request (2) input from the respondent on how they feel

themselves regarding the same issue in most cases. Although we did not apply a

full analysis in the differences in responses, this could be a next area to investigate.

In fact the way we constructed our survey will enable us to continue to utilize the

data to further expand and conduct additional research and refinement of our

hypotheses without the need for further data collection (if conducted within a

reasonable period of time). We are planning to expand this initial research and

continue to publish refinements in the coming 8 to 12 months on a post-doctoral

level.

Overall we feel confident that this is an excellent initial theoretical construct which

we had initially set out to create within the objectives of our research. Based on the

sub hypotheses analysis we reject the Null Hypotheses and confirm that there is in

fact a relationship between successful knowledge transfer between parent

and subsidiary organizational project success.

The influence of the trust attribute does merit further research. Here it was treated

in an ancillary way and based on our results we feel that there could be more to

gain from additional investigation on how trust plays a role not only in Project

Management and Knowledge Transfer, but from an overall operational

management point of view.

We are also considering a tighter integration to the Hofstede analysis utilizing his

indices in a much more integrative way so as to be able to predict the cultural

199

component and be able to assist potential users of this work in aligning

international project teams. This can be done, we feel, fairly easily by : (1)

utilizing the eigenvalues and eigenvectors within our data analysis; and (2) either

graphically “vectorizing” the Hofstede data in an appropriate way and adding the

two, or using the indices as mentioned above and mathematically establishing an

improved project team model.

Ultimately we would like to code our research methodology into a program that

could provide a computer-based approach for predicting project success within

the industry; perhaps even commercializing this if practical.

200

References

[1] Ady, Jeffrey C. "Minimizing Threats to the Validity of Cross-Cultural Organizational Research." International and Intercultural Communications Annual 18 (1994).

[2] Albert, Rosita Daskal. "Cultural Diversity and Intercultural Training in Multinational

Organizations." International and Intercultural Communications Annual 18 (1994). [3] Altmann, Erika. Project Success: A Longitudinal View. Melbourne, Australia: Victoria

University School of Management, 2005. [4] Andrews, Deborah C. Technical Communication in the Global Community. Upper Saddle

River, NJ Prentice Hall, 1998. [5] Antia, Murad, J. Barry Lin, and Christos Pantzalis. Cultural Distance and Valuation of

Multinational Corporations. Tampa, Florida: University of South Florida, 2005. [6] Ashley, David, Clive Lurie, and Edward Jaselskis. "Determinants of Construction Project

Success." Project Management Journal XVIII.2 (1987): 69-79. [7] Ayas, Karen. "Professional Project Management : A Shift Towards Learning and a

Knowledge Creating Structure." International Journal of Project Management 14.3 (1996): 131-36.

[8] Baumgarte, Roger, and Phillippe Blanchard. "Cultural Issues in Corporate Hierarchies:

Keeping Your Distance Isn't That Simple." Global Contexts: Case Studies in International Technical Communication. Ed. Deborah S. Bosley. The Allyn & Bacon Series in Technical Communication. Boston: Allyn and Bacon, 2001.

[9] Beranek, Thomas. "Global Project Management : Graduate Course." Masters. University of

Maryland, 2006. [10] Bishop, K.A., and R.B. Gembey. "Managing Information Flow on a Megaproject."

International Journal of Project Management 3.1 (1985). [11] Black, J. Stewart, and Hal B. Gregersen. "The Right Way to Manage Expats." Harvard

Business Review 1999: 52-62. [12] Blankevoort, P.J. "Effects of Communication and Organization." International Journal of

Project Management. Jersey, UK: Butterworth & Co. Ltd., 1979. [13] Bosley, Deborah S. Global Contexts: Case Studies in International Technical

Communication. The Allyn & Bacon Series in Technical Communication. Needhan Heights, MA: Pearson Education, 2001.

[14] Bresnen, Mike, et al. "Social Practices and Management of Knowledge in Project

Environments." International Journal of Project Management 21 (2003): 157-66. [15] Briscoe, Dennis R., and Randall S. Schuler. International Human Resource Management.

2nd ed. New York: Routledge, 2004. [16] Bryde, David J. "Methods for Managing Different Perspectives of Project Success." British

Journal of Management 16 (2005): 119-31.

201

[17] Carayannis, Elias. "Knowledge Transfer through Technological Hyperlearning in 5

Industries." Technovation 19 (1999): 141-61. [18] Carlile, Paul R. "A Pragmatic View of Knowledge and Boundaries: Boundary Objectives in

New Product Development." Organization Science 13.4 (2002): 442-55. [19] ---. "Transferring, Translating, and Transforming : An Integrative Relational Approach to

Sharing and Assessing Knowledge across Boundaries." 3rd Annual MIT / UCI Knowledge and Organizations Conference. Laguna Beach, CA: Center for Research on Information Technology and Organizations, 2004.

[20] Carlile, Paul R., and Eric S. Rebentisch. "Into the Black Box: The Knowledge

Transformation Cycle." Management Science 49.9 (2003): 1180-95. [21] Chen, Min. Asian Management Systems: Chinese, Japanese and Korean Styles of

Business. London, UK: International Thompson Business Press, 1995. [22] Cieri, Helen de, Julie Wolfram Cox, and Merilyn Fenwick. "A Review of International Human

Resource Management: Integration, Interrogation, Imitation." International Journal of Management Reviews 9.3 (2007).

[23] Clark, Angela. "A Practical Use of Key Success Factors to Improve the Effectiveness of

Project Management." International Journal of Project Management 17.3 (1999): 139-45. [24] Corrello, Myra Lynette. "Communication and the Engineering Profession: Perspectives from

the Field." University of Kentucky, 2000. [25] Crawford, Lynn. "Global Body of Project Management Knowledge and Standards." The

Wiley Guide to Managing Projects (Draft). Ed. Morris. Hoboken, NJ: John Wiley & Sons, 2004. 1150-96.

[26] ---. "Profiling the Competent Project Manager." Trans. Project Management Institute. Project

Management Research at the Turn of the Millennium: Proceedings of PMI Research Conference. Paris, France, 2000. 3-15.

[27] ---. "Senior Management Perceptions of Project Management Competence." International

Journal of Project Management 23.2005 (2004): 7-16. [28] Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods

Approaches. 2nd ed. Thousand Oaks, CA: Sage Publications, 2003. [29] Cushman, Donald P., and Sarah Sanderson King. "Communication in Multinational

Organizations in the United States and Western Europe." International and Intercultural Communications Annual 18 (1994).

[30] Daoudi, Jaouad. Impact of Diversity on Teamwork Satisfaction in Distributed Teams:

Preliminary Results from an Online Survey. Montreal, Canada: Ecole Polytechnique de Montreal, 2007.

[31] Davenport, Thomas H., and Laurence Prusak. Working Knowledge : How Organizations

Manage What They Know. Boston: Harvard Business School Press, 20000.

202

[32] Davis, Boyd H., Jeutonne Brewer, and Ye-Ling Chang. "Usage as an Interactive Strategy for International Team-Building." Global Contexts: Case Studies in International Technical Communication. Ed. Deborah S. Bosley. The Allyn & Bacon Series in Technical Communication. Boston: Allyn and Bacon, 2001.

[33] Diallo, Amadou, and Denis Thuillier. "The Success of International Development Projects,

Trust and Communication : An African Perspective." International Journal of Project Management 23 (2004): 237-52.

[34] Dillman, Don A. Mail and Internet Surveys: The Tailored Design Method. 2nd ed. Hoboken,

NJ: John Wiley & Sons, 2007. [35] Dvir, D., et al. "In Search of Project Classification: A Non-Universal Approach to Project

Success Factors." Israel: Elsevier Science B.V., 1998. 915-35. [36] Earley, P. Christopher, and Soon Ang. Cultural Intelligence : Individual Interactions across

Cultures. Stanford, CA: Stanford University Press, 2003. [37] Eisenberg, Eric M., H.L. Goodall, and Angela Threthewey. Organizational Communication:

Balancing Creativity and Constraint. 5th ed. Boston: Bedford / St. Martin's, 2007. [38] Faems, Dries, Maddy Janssens, and Bart Van Looy. Transferring and Creating

Technological Knowledge in Interfirm R&D Relationships: The Initiation and Evolution of Interfirm Learning. Leuven, Netherlands: Katholieke Universiteit Leuven, 2007.

[39] Fish, Alan. "Selecting Managers for Cross-Border Assignments : Building Value into the

Process." International Journal of Management Reviews 1.4 (1999): 461-83. [40] Forsberg, Kevin, Hal Mooz, and Howard Cotterman. Visualizing Project Management :

Models and Frameworks for Mastering Complex Systems. Hoboken, NJ: John Wiley & Sons, Inc., 2005.

[41] Forssberg, Sanna, and Siiri Malm. "Internal Communication in an Mnc: An Underestimated

Key to Success." Masters. Goteborg University, 2001. [42] Friedman, Thomas L. The World Is Flat : A Brief History of the Twenty-First Century. 3 ed.

New York: Picador - Farrar, Strauss, Giroux, 2007. [43] Garside, Colleen. "A Qualitative Analysis of Verbal Interaction in Mechanical Engineering

Design Teams: Genres of Practice." The University of Utah, 2005. [44] Gay, Lorraine, and P.L. Diehl. Research Methods for Business and Management. New

York: MacMillan, 1992. [45] Geddes, M. "Project Leadership and the Involvement of Users in It Projects." International

Journal of Project Management 8.4 (1990): 214-16. [46] Geissler, Markus. "Aligning Technology with Culture: Connecting Information and

Communication Technology Adoption to Cultural Dimensions." Ph.D. Capella University, 2006.

[47] Goh, Swee C. "Managing Effective Knowledge Transfer : An Integrative Framework and

Some Practice Implications." Journal of Knowledge Management 6.1 (2002): 23-30. [48] Goldman, Alan. "Communication in Japanese Multinational Organizations." International

and Intercultural Communications Annual 18 (1994).

203

[49] Gomez-Mejia, Luis R., and Leslie E. Palich. "Cultural Diversity and the Performance of

Multinational Firms." Journal of International Business Studies 28.2 (1997): 309-35. [50] Grisham, Thomas. "Cross-Cultural Leadership." Royal Melbourne Institute Technology

University, 2006. [51] Hall, Edward T. The Dance of Life. New York, NY: Anchor Books, 1983. [52] Harkness, Janet A. Cross-Cultural Survey Methods. Wiley Series in Survey Methodology.

Ed. Walter A. Shewhart. Hoboken, NJ: Wiley Interscience, 2003. [53] Harris, Philip R., and Robert T. Moran. Managing Cultural Differences. Ed. Judith E.

Soccorsy. 5th ed. Houston: Butterworth-Heinemann / Gulf Publishing 1999. [54] Harris, Thomas E., and John C. Sherblom. Small Group and Team Communication. Ed.

Jeanne Zalesky. 4th ed. Boston: Pearson Education / Allyn and Bacon, 2008. [55] Hauke, Aleksandra. Impact of Cultural Differences on Knowledge Transfer in British,

Hungarian, and Polish Enterprises. Poznan, Poland: Fondazione Eni Enrico Mattei / University of Economics, Poznan, Poland, 2006.

[56] Henderson, Linda S. "Encoding and Decoding Communication Competencies in Project

Management - an Exploratory Study." International Journal of Project Management 22 (2004): 469-76.

[57] Henrie, Morgan E. "Multi-National Project Team Communications and Cultural Influences."

Old Dominion University, 2005. [58] Hofstede, Geert, and Gert Jan Hofstede. Cultures and Organizations: Software of the Mind.

New York: McGraw-Hill, 2005. [59] Hoft, Nancy L. International Technical Communication. New York: John Wiley & Sons, 1995. [60] Hope, C.A., and A.P. Muhlemann. "The Impact of Culture on Best-Practice Production /

Operations Management." International Journal of Management Reviews 3.3 (2001): 199-217.

[61] Hundal, Mahendra S. "Time-Driven Product Development." Integrated Product and Process

Development. Eds. John M. Usher, Utpal Roy and Hamid R. Parsaei. Wiley Series in Engineering Design and Automation. New York: Wiley Interscience, 1998.

[62] Iarossi, Giuseppe. The Power of Survey Design. Washington DC: The World Bank, 2006. [63] Jansen, Detlev E. "Intercultural Communication in Engineering: A Research Programme to

Investigate the Cultural Influences in the Negotiation of Engineering Projects." World Transactions on Engineering and Technology Education 1.1 (2002): 7-12.

[64] Jha, K. N., and K.C. Iyer. "Critical Determinants of Project Coordination." International

Journal of Project Management 24 (2005): 314-22. [65] Jiang, James, Gary Klein, and Joseph Balloun. "Ranking of System Implementation

Success Factors." Project Management Journal XXVII.4 (1996): 49-53.

204

[66] Joshi, K.D., Saonee Sarker, and Suprateek Sarker. "Knowledge Transfer within Information Systems Development Teams : Examining the Role of Knowledge Source Attributes." Decision Support Systems 43 (2007): 322-35.

[67] Karlsen, Jan Terje, and Petter Gottschalk. "An Empirical Evaluation of Knowledge Transfer

Mechanisms for It Projects." The Journal of Computer Information Systems 44.1 (2003): 112-19.

[68] ---. "Factors Affecting Knowledge Transfer in It Projects." Engineering Management Journal

16.1 (2004): 3-10. [69] Kim, Young Yun, and Sheryl Paulk. "Intercultural Challenges and Personal Adjustments: A

Qualitative Analysis of the Experiences of American and Japanese Co-Workers." International and Intercultural Communications Annual 18 (1994).

[70] Koelmans, R.G. "Project Success and Performance Evaluation." Trans. The South African

Institute of Mining and Metallurgy. International Platinum Conference 'Platinum Adding Value'. South Africa: The South African Institute of Mining and Metallurgy, 2004. 229-36.

[71] Lattin, James, J. Douglas Carroll, and Paul E. Green. Analyzing Multivariate Data. Pacific

Grove, CA: Brooks / Cole Division of Thomson Learning, 2003. [72] Lee-Kelley, Liz, and Tim Sankey. "Global Virtual Teams for Value Creation and Project

Success : A Case Study." International Journal of Project Management (2007). [73] Lieberman, Devorah A., and Ellene Gurtov. "Co-Cultural Communication within the

Organization." International and Intercultural Communications Annual 18 (1994). [74] Lin, Lihui, Xianjun Geng, and Andrew B. Whinston. "A Sender-Receiver Framework for

Knowledge Transfer." MIS Quarterly 29.2 (2005). [75] Littlejohn, Stephen W., and Karen A. Foss. Theories of Human Communication. 9th ed.

Belmont, CA: Thomson Wadsworth, 2008. [76] Loosemore, M., and H.S. Al Muslmani. "Construction Project Management in the Persian

Gulf : Inter-Cultural Communication." International Journal of Project Management 17.2 (1999): 95-100.

[77] Martin, Judith N., and Thomas K. Nakayama. Intercultural Communication in Contexts. 4th

ed. Boston: McGraw Hill, 2007. [78] McDevitt, Annette Sandlin. "Cultural Variations as Predictors of Negotiation Outcomes:

Implications for International Business Communication." The University of Memphis, 2006. [79] Mehri, Darius. Notes from Toyota-Land: An American Engineer in Japan. Ithaca, New York:

Cornell University Press, 2005. [80] Mersino, Anthony. Emotional Intelligence for Project Managers. New York: American

Management Association, 2007. [81] Mikheev, Vladimir, and David Pells. "The Third Wave - a New Management Paradigm for

Project and Program Management." PMForum.org, 2005. [82] Mitchell, Charles. International Business Culture. The Short Course in International Trade

Series. Novato, CA: World Trade Press, 2000.

205

[83] Moenaert, Rudy K., et al. "Communication Flows in International Product Innovation Teams." The Journal of Product Innovation Management 17 (2000): 360-77.

[84] Mooz, Hal, Kevin Forsberg, and Howard Cotterman. Communicating Project Management.

Hoboken, NJ: John Wiley & Sons, 2003. [85] Morrison, Terri, and Wayne A. Conaway. Kiss, Bow, or Shake Hands. 2 ed. Avon,

Massachusetts Adams Media, 2006. [86] Murphy, David, Bruce Baker, and Dalmar Fisher. "Determinants of Project Success."

Boston College, 1974. [87] Nonaka, Ikujiro, and Hirotaka Takeuchi. The Knowledge-Creating Company: How Japanese

Companies Create the Dynamics of Innovation. New York: Oxford University Press, 1995. [88] Nooteboom, Bart. Problems and Solutions in Knowledge Transfer. Rotterdam, Netherlands:

Erasmus Universiteit Rotterdam, 2001. [89] Osterloh, Margit, and Bruno S. Frey. Motivation, Knowledge Transfer, and Organizational

Forms. Zurich, Switzerland: University of Zurich, 1999. [90] Pantelides, Arthur. The Japanese Approach to Knowledge Creation, Transfer, and

Innovation: The George Washington University School of Engineering and Applied Science, 2001.

[91] Pinto, Jeffrey, and Denis Slevin. "Critical Factors in Successful Project Implementation."

IEEE Transactions of Engineering Management EM-34.1 (1987): 22-27. [92] ---. "Project Success: Definitions and Measurement Techniques." Project Management

Journal XIX.1 (1988): 67-72. [93] Prevot, Frederic. Interfirm Knowledge Transfer Methods. Marseille, France: Euromed

Marseille - Ecole de Management, 2007. [94] Rad, Parviz F. "Project Success Attributes." Cost Engineering 45.4 (2003): 23-29. [95] Rea, Louis M., and Richard A. Parker. Designing and Conducting Survey Research: A

Comprehensive Guide. 3rd ed. San Francisco: Jossey-Bass / Wiley, 2005. [96] Ribiere, Vincent Michel. "Assessing Knowledge Management Initiative Successes as a

Function of Organizational Culture." Doctoral. The George Washington University, 2001. [97] Riemer, Marc J., and Detlev E. Jansen. "Non-Verbal Intercultural Communication

Awareness for the Modern Engineer." World Transactions on Engineering and Technology Education 2.3 (2003): 373-78.

[98] Robbins, Stephen P. Organizational Behavior. 9th ed. Upper Saddle River, NJ: Prentice

Hall, 2001. [99] Roman-Valazquez, Juan A. "An Empirical Study of Knowledge Management in the

Government and Nonprofit Sectors: Organizational Culture Composition and Its Relationship with Knowledge Management Success and the Approach for Knowledge Flow." The George Washington University, 2004.

[100] Roy, Rajkumar. Industrial Knowledge Management: A Micro-Level Approach. London:

Springer-Verlag, 2001.

206

[101] Ruch, William V. Corporate Communications: A Comparison of Japanese and American

Practices. Westport, Connecticut: Grenwood Press, 1984. [102] Saee, John. "Best Practice in Project Management in Contemporary Global Economy."

Journal of Management Systems 13.4 (2001): 81-95. [103] Salas, Eduardo, C. Shawn Burke, and Janis A. Cannon-Bowers. "Teamwork : Emerging

Principles." International Journal of Management Reviews 2.4 (2000): 339-56. [104] Santoro, Michael D., and Shanthi Gopalakrishnan. "The Institutionalization of Knowledge

Transfer Activities within Industry-University Collaborative Ventures." Journal of Engineering and Technology Management 17 (2000): 299-319.

[105] Sapsed, Jonathan, et al. "Teamworking and Knowledge Management : A Review of

Converging Themes." International Journal of Management Reviews 4.1 (2002): 71-85. [106] Schuler, Randall S., Pawan S. Budwar, and Gary W. Florkowski. "International Human

Resource Management : Review and Critique." International Journal of Management Reviews 4.1 (2002): 41-70.

[107] Shenhar, Aaron J., and Dov Dvir. "Project Management Research: The Challenge and

Opportunity." Project Management Journal 38.2 (2007): 93-99. [108] Shenhar, Aaron J., et al. "Refining the Search for Project Success Factors : A Multivariate,

Typological Approach." R&D Management 32.2 (2002): 111-26. [109] Shuter, Robert, and Richard L. Wiseman. "Communication in Multinational Organizations:

Conceptual, Theoretical, and Practical Issues." International and Intercultural Communications Annual 18 (1994).

[110] Slack, Nigel, and Michael Lewis. Operations Strategy. Ed. Tom Tucker. Upper Saddle

River, NJ: Prentice Hall / Pearson education, 2003. [111] Soderquist, Klas Eric. "Organizing Knowledge Management and Dissemination in New

Product Development." Long Range Planning 39 (2006): 497-523. [112] Sosa, Manuel E., et al. "Factors That Influence Technical Communication in Distributed

Product Development: An Empirical Study in the Telecommunications Industry." IEEE Transactions of Engineering Management 49.1 (2002): 45-58.

[113] Staples, Katherin. "Technical Communication from 1950-998: Where Are We Now ?"

Technical Communication Quarterly 8.2 (1999): 153-64. [114] Stock, Gregory N., Noel P. Greis, and Mark D. Dibner. "Parent-Subsidiary Communication

in International Biotechnology R&D." IEEE Transactions of Engineering Management 43.1 (1996): 56-68.

[115] Teboul, JC. Bruno, Ling Chen, and Lynn M. Fritz. "Intercultural Organizational

Communication Research in Multinational Organizations." International and Intercultural Communications Annual 18 (1994).

[116] Thrush, Emily A. "High-Context and Low Context Cultures: How Much Communication Is

Too Much ?" Global Contexts: Case Studies in International Technical Communication. Ed. Deborah S. Bosley. The Allyn & Bacon Series in Technical Communication. Boston: Allyn and Bacon, 2001.

207

[117] Tolich, Martin, Martin Kenney, and Nicole Biggart. "Managing the Managers: Japanese

Management Strategies in the USA." Journal of Management Studies 36.5 (1999): 587-607.

[118] Trenholm, Sarah. Thinking through Communication: An Introduction to the Study of

Human Communication. 5th ed. Boston: Pearson Education / Allyn and Bacon, 2008. [119] Udo, Nathalie, and Sonja Koppensteiner. "What Are the Core Competencies of a

Successful Project Manager ?" PMI Global Congress. Prague, Czech Republic: Projectway LLC, 2004.

[120] Urick, Heath. "The ABC’s of International Expatriate Assignments." Wisconsin SHRM

State Conference 2006. Madison, Wisconsin: Aon Consulting, 2006. [121] Varnes, Elizabeth B. "A Sociotechnical Approach to the Study of Semiautonomous Work

Group Communication in Technical Organizations." old Dominion University, 1993. [122] Verganti, Roberto. "Anticipating Manufacturing Constraints and Opportunities in the

Concept Generation and Product Planning Phases." Integrated Product and Process Development. Eds. John M. Usher, Utpal Roy and Hamid R. Parsaei. Wiley Series in Engineering Design and Automation. New York: Wiley Interscience, 1998.

[123] Walter, John, and Abby Dress. "Determining the Knowledge Base Uncovers a Company's

Core Competencies." Gear Technology 2007: 11-15. [124] West, Richard, and Lynn H. Turner. Introducing Communication Theory Analysis and

Application. 3rd ed. Boston: McGraw Hill, 2007. [125] Whittaker, Brenda. "What Went Wrong ? Unsuccessful Information Technology Projects."

Information Management and Computer Security 7.1 (1999): 23-29. [126] Wiemann, John M., et al. "A Relational Model of Communication Competence." Theories

of Human Communication. Ed. Branislav Kovacic. Suny Series, Human Communication Processes. Albany, NY: State University of New York Press, 1997. 25-44.

[127] Yu, Angus G., Peter D. Flett, and John A. Bowers. "Developing a Value-Centered

Proposal for Assessing Project Success." International Journal of Project Management 23 (2005): 428-36.

[128] Zimmerer, Thomas, and Mahmoud Yasin. "A Leadership Profile of American Project

Managers." Project Management Journal 29.1 (1998): 31-38. [129] Zwikael, Ofer, Kazuo Shimizu, and Shlomo Globerson. "Cultural Differences in Project

Management Capabilities : A Field Study." International Journal of Project Management 23 (2005): 454-62.

208

Appendices

APPENDIX A : Hofstede Summary & Relational Mapping……………………. 210

APPENDIX B : Survey Instrument………………………………………………. 212

APPENDIX C : Survey Raw & Supplemental Data……………………………. 229

APPENDIX D : Illustrative Example Case……………………………………… 250

APPENDIX E : Sample Multilingual Documentation from the Industry……… 251

APPENDIX F : Photographs from the Industry………..............……………… 252

APPENDIX G : Comprehensive List of Gross Population…………………… 253

Appendices Have Been Omitted in this Version.

209