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«Group Information Behavioural Norms and the Effective Use of a Collaborative Information System: A Case Study by Colin David Furness A thesis ...»

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Group Information Behavioural Norms and the

Effective Use of a Collaborative Information System:

A Case Study

by

Colin David Furness

A thesis submitted in conformity with the requirements

for the degree of Doctor of Philosophy

Faculty of Information

University of Toronto

© Copyright by Colin David Furness 2010

ii

Group Information Behavioural Norms and the

Effective Use of a Collaborative Information System:

A Case Study Colin David Furness Doctor of Philosophy Faculty of Information University of Toronto Abstract This research investigated whether Group Information Behavioural Norms (GIBNs) are correlated with the effective use of a collaborative information system. Previous research seeking to conceptualize ‘social influence’ in technology adoption has not attempted to include GIBNs. The dependent variable, ‘Effective Use’, comprised two subjective Effectiveness Judgments and three objective Actual Use measures. A mediating variable, ‘Group Adoption’ (GA) of the information system, was conceived as a behavioural expression of group norms and hypothesized to correlate with both GIBNs and Effective Use. It was also hypothesized that GIBNs would have a stronger relationship with Effective Use than the widely used Technology Acceptance Model (TAM) dimensions of Perceived Usefulness and Perceived Ease of Use.

iii A mixed-methods case study approach was used because measurement of stable norms in workplace groups was required. A medium-sized engineering firm was chosen, and the collaborative information system studied was Knowledge Forum (KF), an educational research tool that was implemented to promote the exchange of information.

There were both expected and unexpected results. GIBNs outperformed the TAM in explaining all three Actual Use variables, although the TAM was the sole significant correlate for one Effectiveness Judgment variable. Information Sharing and Proactive Information Use had opposite correlations with Effective Use, suggesting the existence of distinct information ‘sharing’ and ‘proactive use’ group norms. In addition, the TAM and GIBNs seem to have complementary influences on Effective Use. GA was unexpectedly observed to have the strongest relationship with Effective Use, having a significant relationship with four of five Effective Use measures. GA was also observed to mediate the TAM but not GIBNs.

The results of a case study cannot be extensively generalized. However, the findings are important in three ways. First, this research provides evidence that GIBNs and the TAM exert complementary influences on Effective Use, and that Effective Use is best explained by also including GA. Second, GA may represent a valuable ‘social influence’ extension to the TAM, as a behavioural expression of group norms for collaborative information systems. Finally, this study illustrates the importance of a multi-dimensional

–  –  –

Acknowledgements The full story of how this dissertation came to completion would be a good deal longer than this volume itself. It was, of course, the product of many hands, with significant guidance from many minds. I would first like to acknowledge those good teachers who collectively ignited my passion for this research, starting more than two decades ago when Professor Jonathan Freedman taught me psychology research methodology. Two years later, my first job would be working for Chris Handley, a true visionary in the workplace use of information systems, just when PCs began appearing on office desks.

That is where I became interested in the dynamics of employees and information technology, and I then took pivotal human-computer interaction courses from Professor Ron Baecker. Soon after, Professor Andrew Clement instructed me in the social impacts of information technology, and Joan Cherry later guided my master’s thesis, helping me hone the needed research skills that underpin this work. These five people shaped my thinking in important ways, and their influences are concretely reflected here.

Once my PhD research began in earnest, I received considerable accommodation from the firm that I studied. I met many fine employees during the course of designing and executing my data collection procedures, and interviews which followed. In particular, Allen Atamer and Victor Alksnis went above and beyond in their insight, advice and explanation of the organization and its information systems. They contributed substantial

–  –  –

Significant assistance was also provided by my two statistics tutors, to whom I owe great thanks. Donna Chan helped me structure my results chapter and helped me navigate multiple regression analysis. Douglas Garrett has an enviable depth of statistical expertise, and he deftly showed me how to solve more than one problem that had brought me to a standstill. In addition, my two editors were immensely helpful. Veronica Tunzi ensured that my writing mechanics were consistent and clear, and Tanya Andrusieczko contributed her extensive APA style expertise.

Long before data collection even began, however, I was very fortunate indeed to have Professors Lynne Howarth and Mark Chignell join my supervisory committee.

Supervising a doctoral student is a selfless undertaking; they were generous with their time, expertise, and attention for a period of over five years. Lynne helped me a great deal in clarifying my research questions and methodological choices, and was artful in identifying weak areas in my writing, wherever they lurked. Mark contributed invaluable expertise in quantitative data analysis, and it was his feedback and guidance that has given me confidence in my choices of statistical techniques, and interpretation of results.





I am also grateful to Professor Kim Dalkir of McGill University, who kindly agreed to serve as external appraiser and examiner for my oral defence on July 30, 2010. She gave considerable time in a meticulous examination of my dissertation, she provided a very helpful evaluation, and she travelled a great deal on my behalf to do so – all before even having met me. That these faculty members volunteered their time so freely for my

–  –  –

During the final two years of this work, I was concurrently employed by Infonaut Inc., working part-time for Matthew McPherson and Niall Wallace. They were unfailing in their support for this work, and made continual accommodations for me. They are keen innovators who preach the value of connecting academia to industry – and they practice it well. I am grateful for their forbearance as well as for their thought leadership.

Of the many mentioned (and not mentioned) above, only one person has been directly involved with my doctoral studies from the first day, Professor Chun Wei Choo. Chun Wei has boundless patience and even more subject matter knowledge. He remained cheerfully committed to my work through my long, slow, and oft-delayed journey. He provided unending guidance and support, impeccable judgment and wisdom, countless hours of time, and numerous research assistantships. I believe that Chun Wei provided more to this project than everyone else above combined, and I am eternally in his debt.

Finally, my dear wife Amy has invested in this effort like nobody else could, far beyond enduring my rants and raves. For the past two years, every hour I spent on this work was time away from my family. This has meant many hundreds of extra hours of parenting displaced to her alone, and it has also slowed her own doctoral work. Amy is a truly remarkable spouse and mother; few could ever be as empathetic and supportive as she.

–  –  –

Chapter 1 - Introduction

1.1 PROBLEM STATEMENT

1.2 DEFINITIONS

1.2.1 Groups

1.2.2 Collaborative Information Systems

1.3 PURPOSE OF THE RESEARCH

1.4 FRAMING THE RESEARCH PROBLEM

1.5 FRAMING THE RESEARCH QUESTION

1.6 OBJECTIVES AND STRUCTURE OF THIS DISSERTATION

Chapter 2 - Literature Review

2.1 MEASURING INFORMATION SYSTEMS SUCCESS

2.1.1 Approaches to Information Systems Success Measurement

2.1.2 The Information Systems Success Model

2.1.3 Operationalizing ‘Effective Use’

2.2 INFORMATION SYSTEMS ADOPTION

2.2.1 Individual Differences

2.2.2 Diffusion of Innovations Theory

2.2.3 Task-Technology Fit

2.2.4 Technology Acceptance Model

2.2.5 The Unified Theory of Acceptance and Use of Technology (UTAUT).................. 34 2.2.6 Group Adoption

2.3 INFORMATION PROCESSING IN GROUPS

2.3.1 Face-to-Face Versus Electronically Mediated Groups

2.3.2 Task Characteristics and Collaborative Work

2.3.3 Groups and Information Sharing

2.3.4 Groups and Decision-Making.

2.4 INFORMATION BEHAVIOUR IN A GROUP SETTING

2.4.1 Conceptualizing Information Behaviour

2.4.2 Information Ecology

2.4.3 Information Use Environment

2.4.4 Information Orientation

2.4.5 Organizational Culture

2.5 SYNTHESIS

2.6 CONCEPTUAL MODEL AND RESEARCH QUESTIONS

ix Chapter 3 - Method

3.1 INTRODUCTION

3.2 CONCEPTUAL MODEL AND VARIABLES

3.3 INDEPENDENT VARIABLES

3.3.1 Technology Acceptance Model

3.3.2 Group Information Behavioural Norms

3.3.3 Group Adoption

3.4 DEPENDENT VARIABLE: EFFECTIVE USE

3.4.1 Actual Use

3.4.2 Use Experience (Subjective Satisfaction)

3.4.3 Perceived Performance Impact

3.5 EXTERNAL VARIABLES AS BARRIERS TO EFFECTIVE USE

3.6 OPERATIONAL RESEARCH QUESTIONS AND HYPOTHESES

3.6.1 Overview

3.6.2 Explanatory Ability of the TAM for Actual Use

3.6.3 Explanatory Ability of the TAM for Effectiveness Judgments

3.6.4 The Relationship between GIBNs and Effective Use

3.6.5 Explanatory Ability of GIBNs for Group Adoption

3.6.6 Explanatory Ability of Group Adoption for Effective Use

3.6.7 Relative Contributions of the TAM and GIBNs to Effective Use

3.7 THE CASE STUDY APPROACH

3.7.1 Rationale

3.7.2 Suitability

3.7.3 Case Studies and Generalization

3.8 SETTING

3.8.1 The Organization

3.8.2 Operationalization of ‘Groups’ at the Firm

3.8.3 Knowledge Forum

3.8.4 External Variables and Rationale for this Setting

3.9 QUANTITATIVE DATA COLLECTION

3.9.1 Participants

3.9.2 Confidentiality

3.9.3 Harvesting Server Logs

3.9.4 Questionnaire Booklet

3.9.5 Pilot Test of Questionnaire Booklet

3.9.6 Questionnaire Launch

3.10 QUALITATIVE DATA COLLECTION

3.10.1 Purpose for Qualitative Data

3.10.2 Participants

3.10.3 Interview Procedure

3.11 SUMMARY

x Chapter 4 - Results

4.1 INTRODUCTION

4.2 QUESTIONNAIRE RESPONSE CHARACTERISTICS

4.2.1 Overview

4.2.2 Response Rate

4.2.3 Missing Values Analysis

4.2.4 Power Analysis

4.3 RESPONDENT CHARACTERISTICS

4.3.1 Overview

4.3.2 General Demographics

4.3.3 Synthesis

4.4 GROUP MEMBERSHIP CHARACTERISTICS

4.4.1 Overview

4.4.2 Measurement and Transformation of Groups

4.4.3 Effects of Group Membership

4.4.4 Synthesis

4.5 KNOWLEDGE FORUM (KF) USE CHARACTERISTICS

4.5.1 Overview

4.5.2 Usage Measures

4.5.3 Correction of Data Anomalies

4.5.4 Transformation of Actual Use Statistics

4.5.5 External Variables: Barriers to Actual Use

4.5.6 Synthesis

4.6 GROUP INFORMATION BEHAVIOURAL NORMS RESULTS

4.6.1 Overview

4.6.2 Descriptive Statistics

4.6.3 Factor Analysis

4.6.4 Distribution and Transformation

4.6.5 Synthesis

4.7 GROUP ADOPTION INSTRUMENT RESULTS

4.7.1 Overview

4.7.2 Descriptive Statistics

4.7.3 Item Reliability Issues

4.7.4 Factor Analysis

4.7.5 Revised Descriptive and Distribution Statistics

4.7.6 Synthesis

4.8 TAM INSTRUMENT RESULTS

4.8.1 Overview

4.8.2 Descriptive Statistics

4.8.3 Factor Analysis

4.8.4 Distribution Statistics and Transformations

xi 4.8.5 Synthesis

4.9 EFFECTIVENESS JUDGMENTS RESULTS

4.9.1 Overview

4.9.2 Descriptive Statistics and Reliability

4.9.3 Factor Analysis

4.9.4 Distribution Statistics and Transformation

4.9.5 Synthesis

4.10 EVALUATION OF CONSTITUENT HYPOTHESES

4.10.1 Overview

4.10.2 H1: TAM Correlations with Actual Use

4.10.3 H2: TAM Correlations with Effectiveness Judgments

4.10.4 H3: Group Information Behavioural Norms Correlations with Effective Use...... 171 4.10.5 H4: Group Information Behavioural Norms Correlations with Group Adoption.. 174 4.10.6 H5: Group Adoption Correlations with Effective Use

4.10.7 Synthesis

4.11 OVERARCHING HYPOTHESES: RELATIVE CONTRIBUTION TO EFFECTIVE USE... 177 4.11.1 Multiple Regression Overview

4.11.2 External Variables: Ordinal and Categorical Considerations

4.11.3 Threat to Validity: Multicollinearity

4.11.4 Threat to Validity: Heteroscedasticity

4.11.5 Threat to Validity: Type I and Type II Errors

4.12 RELATIVE CONTRIBUTION TO EFFECTIVENESS JUDGMENTS

4.12.1 Overview

4.12.2 Hypothesis Evaluation: Predictors of Total Impact Judgments

4.12.3 Hypothesis Evaluation: Predictors of Use Experience Judgments

4.12.4 Synthesis

4.13 RELATIVE CONTRIBUTION TO ACTUAL USE

4.13.1 Overview

4.13.2 Additional Regression Techniques for Actual Use Models

4.13.3 Hypothesis Evaluation: Predictors of Actual Use – Percent Read

4.13.4 Hypothesis Evaluation: Predictors of Actual Use – Read+Write

4.13.5 Hypothesis Evaluation: Predictors of Actual Use – Grand Sum Use................. 200 4.13.6 Synthesis

4.14 SUMMARY OF HYPOTHESIS TESTING

4.15 PARTICIPANT INTERVIEWS

4.15.1 Overview

4.15.2 External Variables

4.15.3 KF Use Characteristics

4.15.4 Synthesis

xii Chapter 5 - Discussion

5.1 SUMMARY OF THE RESEARCH

5.1.1 Research Problem & Method

5.1.2 Hypotheses and Results

5.2 DISCUSSION OF RESULTS

5.2.1 R1 & R2: Does the TAM Predict Effective Use?

5.2.2 R3: What is the Relationship Between GIBNs and Effective Use?



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