臺灣博碩士論文加值系統

Social networking sites have created incredible opportunities for marketing and advertising in nearly every part of the world. The biggest social networking site (Facebook) as of December, 2012 claims to have over 1 billion monthly active users. One of the biggest problems for marketers is how to effectively advertise their products and who to effectively target. This study is based on integrating social network theory and an extension of social identity theory in an attempt to predict social networking site users intentions for e-commerce. Respondents from Mainly Taiwan and the Unites States of America were chosen as the sample for this survey.

Findings indicated the network characteristics; tie strength and network centrality; were effective in predicting a users’ social identity with the social networking site. In addition, social identity with the social networking site was a successful predictor of social commerce intentions. However, network density was the one social networking characteristic found to not have an effect on social identity with the social networking site. This study fills research gaps in using social networking characteristics in the e-commerce and social networking site context. From these findings, strategies can be formed to target socially advantageous individuals outlined from literature review to more effectively gain market share.

TABLE OF CONTENTS
ABSTRACT I
ACKNOWLEDGEMENTS II
TABLE OF CONTENTS III
LIST OF TABLES VI
LIST OF FIGURES VII
CHAPTER ONE INTRODUCTION 1
1.1 Research Background and Motivation. 1
1.2. Research Purpose and Objective. 3
1.2.1 Research Purpose. 3
1.2.2 Research Objectives. 4
1.3 Study Structure. 5
CHAPTER TWO LITERATURE REVIEW 6
2.1 Theoretical Framework. 6
2.1.1 Social Network Theory. 6
2.1.2 Social Identity Theory. 7
2.1.3 Influence of Strong and Weak Ties. 10
2.1.4 Network Centrality. 12
2.1.5 Network Density. 15
2.1.6 Social Commerce Intention. 16
2.2 Relationships Among Research Constructs. 17
2.2.1 Relationship Between Tie Strength and Perceived Network Density. 17
2.2.2 Relationship Between the Tie Strength and Social Identity with the SNS. 18
2.2.3 Relationship Between Perceived Network Density and Social Identity with the Social Networking Site. 20
2.2.4 Relationship Between Perceived Network Centrality and Social Identity with the SNS. 22
2.2.5 Relationship Between Social Identity with the Social Networking Site and Social Commerce Intention. 24
CHAPTER THREE RESEARCH DESIGN AND METHODOLOGY 26
3.1 Research Design. 26
3.2 Data Collection. 27
3.3 Hypotheses to be Tested. 28
3.4 Construct Measurement. 28
3.4.1 Pilot Study. 28
3.4.2 Main Study. 29
3.5 Description of Sample. 31
3.6 Data Analysis. 33
3.6.1 Descriptive Statistics. 33
3.6.2 Confirmatory Factor Analysis. 33
3.6.3 Pearson Correlation Analysis. 34
3.7.4 Validity and Reliability Tests. 34
3.7.5 Partial Least Squares Regression (PLS). 34
CHAPTER FOUR RESEARCH RESULTS 36
4.1 Descriptive Analysis. 36
4.2 Confirmatory Factor Analysis. 38
4.3 Pearson Correlation. 39
4.4 Validity and Reliability Test. 42
4.5 Cross-Factor Loading Matrix. 42
4.6 Partial Least Square Regression Analysis. 43
CHAPTER FIVE CONCLUSION AND SUGGESTIONS 45
5.1 Research Conclusion and Discussions. 45
5.2 Implications and Contributions. 48
5.3 Managerial Implications. 49
5.4 Research Limitations and Future Research. 50
REFERENCES 52
APPENDICES 57

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