臺灣博碩士論文加值系統

印尼是一個人口眾多的國家，其網購率居世界前列，這一激增主要是由新冠疫情帶來的挑戰所驅動的。隨著在線交易的增加，印尼的就業市場也出現了社交商務的顯著增長，特別是在Instagram上。購物代理的崛起，也稱為受託服務代理或“預訂”，突顯了該平台如何轉變社交商務。本研究旨在分析多個因素之間的關係——信任作為感知服務質量的調節變量、個性化、客戶滿意度、產品多樣性、價格、電子口碑（e-WOM）、享樂價值和購買意圖。為探討這些關係，共制定了七個假設。調查通過Google Forms進行，目標是203名在Instagram上通過購物代理進行購買的有效印尼用戶。收集的數據使用SmartPLS 4的偏最小二乘-結構方程模型（PLS-SEM）進行分析。結果顯示，七個假設中有六個是顯著的，表明大多數研究變量之間存在強烈的關係。然而，有一個假設不顯著，突顯了需要進一步研究的領域。該研究還指出了若干需要在未來研究中解決的局限性，包括樣本量、考慮的社交媒體平台範圍和變量範圍。通過解決這些局限性，未來的研究可以提供更全面的見解，幫助購物代理更好地理解和滿足客戶的需求，從而促進消費者滿意度和購買意圖的提升，適應印尼不斷發展的數字市場。

關鍵詞：代購、認知服務品質、產品多樣性、電子口碑、購買意圖

Indonesia, a high-population country, has one of the highest rates of online shopping in the world, a surge driven significantly by the challenges posed by the COVID-19 pandemic. Alongside this increase in online transactions, Indonesia's job market has seen a significant rise in social commerce, particularly on Instagram. The rise of purchasing agents, also known as entrusted service agents or “pre-orders,” on Instagram underscores how the platform is transforming social commerce. This study aimed to analyze the relationships between several factors—trust as a moderator of perceived service quality, personalization, customer satisfaction, product diversity, price, electronic word of mouth (e-WOM), hedonic value, and purchase intention. Seven hypotheses were formulated to explore these relationships. A survey was conducted using Google Forms, targeting 203 valid Indonesian users who had made purchases through a purchasing agent on Instagram. The collected data was analyzed using Partial Least Square – Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The results revealed that six out of the seven hypotheses were significant, indicating strong relationships among most of the variables studied. However, one hypothesis was not significant, highlighting an area that requires further investigation. The study also identified several limitations that should be addressed in future research, including the sample size, the range of social media platforms considered, and the scope of variables included.

Keywords: purchasing agent, perceived service quality, product diversity, electronic word of mouth, purchase intention

TABLE OF CONTENTS

摘要 I
ABSTRACT II
ACKNOWLEDGMENT III
TABLE OF CONTENTS IV
LIST OF FIGURES VII
LIST OF TABLES VIII
CHAPTER I INTRODUCTION 1
1.1 Research Background 1
1.2 Research Motivation 4
1.3 Research Purpose 6
1.4 Research Process 6
CHAPTER II LITERATURE REVIEW 9
2.1 Purchase Agent 9
2.2 Purchase Intention 10
2.3 Trust 11
2.4 Perceived Service Quality (PSQ) 12
2.5 Personalization 12
2.6 Customer Satisfaction 13
2.7 Product Diversity 13
2.8 Price 14
2.9 Electronic Word of Mouth (eWOM) 14
2.10 Hedonic Value 15
2.11 Relationship Between Hypotheses 15
2.11.1 Perceived Service Quality and Customer Satisfaction 15
2.11.2 Personalization and Customer Satisfaction 16
2.11.3 Customer Satisfaction and Purchase Intention 16
2.11.4 Product Diversity and Purchase Intention 17
2.11.5 Price and Purchase Intention 17
2.11.6 eWOM and Purchase Intention 18
2.11.7 Hedonic Value and Purchase Intention 18
CHAPTER III METHODOLOGY 20
3.1 Research Design 20
3.1.1 Subject and Object of Research 20
3.1.2 Quantitative Research 22
3.1.3 Questionnaire Design 22
3.1.4 Data Gathering 23
3.1.5 Unit Analysis 23
3.1.6 Sampling Design 23
3.1.7 Conceptual and Operational Definition 24
3.2 Data Analysis Method 26
3.2.1 Structural Equation Model (SEM) 27
3.2.1.1 Partial Least Squares - Structural Equation Modeling (PLS-SEM) 28
3.3 Measurement Model 29
3.3.1 Validity Test 29
3.3.1.1 Discriminant Validity 29
3.3.1.2 Cross Loading Values 29
3.3.1.3 Fornell-Larcker Criterion 30
3.3.1.4 Heterotrait-Monotrait (HTMT) Criterion 30
3.3.2 Reliability Test 31
3.4 Structural Model 33
3.4.1 Significance and Relevance of Formative Items 33
3.4.2 Variance Inflation Factor (VIF) 33
3.4.3 Model’s Explanatory Power 34
3.5 Predictive Model 34
3.6 Model Fit 35
CHAPTER IV RESEARCH FINDINGS AND DISCUSSION 38
4.1 Respondent Profile 38
4.2 Actual Study Result 40
4.2.1 Descriptive Statistics 40
4.2.2 Hypotheses Testing 42
4.2.2.1 Validity Testing 42
4.2.2.1.1 Average Variance Extracted (AVE) 43
4.2.2.1.2 Cross-Loading 43
4.2.2.1.3 Fornell-Larcker Criterion 45
4.2.2.1.4 Heterotrait-Monotrait (HTMT) 45
4.2.2.2 Reliability Testing 46
4.3 Structural Model 47
4.3.1 Significance and Relevance of Formative Items 47
4.3.2 Variance Inflation Factor (VIF) 49
4.3.3 Model Explanatory Power 49
4.4 Predictive Model 51
4.5 Model Fit 51
4.6 Discussion 52
CHAPTER V CONCLUSION AND RECOMMENDATIONS 59
5.1 Conclusion 59
5.2 Implications 60
5.3 Limitation 62
5.4 Further Research 62
REFERENCES 64
INTERNET REFERENCES 81
APPENDIX 82

 
LIST OF FIGURES

Figure 1. The Internet Users over Time in The World based on Kepios Research 1
Figure 2. Research Flow Chart 8
Figure 3. The Buying Decision Process 10
Figure 4. Research Framework 20
Figure 5. Structural Model Testing 48

 
LIST OF TABLES

Table 1.1. The Countries with The Most Active Instagram Users 3
Table 3.1. Variables Definition 20
Table 3.2. Questionnaire’s Conceptual and Operationalization 24
Table 3.3. The Summarized Criteria Values of Validity 31
Table 3.4. The Summarized Criteria Values of Reliability 32
Table 3.5. The Summary of The Structural and Model Fit Criteria 36
Table 4.1. Respondent Profile 38
Table 4.2. Descriptive Statistics 40
Table 4.3. The Average Variance Extracted (AVE) Test Result 43
Table 4.4. The Cross-Loading Test Result 44
Table 4.5. The Fornell-Larcker Criterion Test Result 45
Table 4.6. The Heterotrait-Monotrait (HTMT) Test Result 45
Table 4.7. The Outer Loading and Reliability Test Result 46
Table 4.8. Hypotheses Testing Result 49
Table 4.9. Inner Model VIF Result 49
Table 4.10. R-square (R2) Result 50
Table 4.11. f-square (f2) Result 50
Table 4.12. Predictive Model Test Result 51
Table 4.13. Model Fit Test Result 52
Table 4.14. Summary of the Hypotheses Result 52

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