近年來，在人工智慧（Artificial Intelligence, A.I.）與巨量資料（Big Data）技術的蓬勃發展下，零售業的服務模式已逐漸由傳統的與服務人員互動轉變為自助式科技服務，不僅帶動了智慧零售的發展，也促成了智慧商店的興起。過去探討智慧商店的研究多止於商店本身服務品質的探討，鮮少關注其服務對於企業本身之影響，然而企業提供智慧商店服務除了創新之外，應有其他用意存在，例如建立更為正面的品牌形象，並加強消費者對於使用其企業所提供之服務的意願。本研究以訊號理論為基礎，由文獻中整理並探討哪些因素可做為消費者評估智慧商店服務品質的內外部線索，並進一步探討其對企業品牌形象與消費者行為之影響。本研究使用線上問卷，以統一企業旗下7-ELEVEN之X-STORE為例進行設計，共回收262份有效樣本，並透過統計分析確保本研究量表具有足夠之信效度。研究結果顯示，智慧商店的科技特性、服務特性與商店知名度皆對於智慧商店服務品質的評估有正向影響，但消費者對於服務人員的互動需求則非影響服務品質的主要因素。此外，智慧商店的服務品質也會正向影響企業的品牌形象，進而影響消費者未來對於企業所提供之其他服務的使用意圖。最後，本研究亦根據研究結果提出理論與實務上的建議，期望對未來相關領域的研究有所助益。

Recently, with the rapid development of artificial intelligence（A.I.）and big data technologies, the service model of retailing industry has gradually changed from the traditional way interacting with service personnel to self-service technology services, which has not only led the development of smart retailing but also contributed to the rise of smart stores. In the past, the research on smart stores mostly focused on the service quality of the store itself and paid little attention to what impacts smart store services would bring for the company. However, there should be other intentions in addition to innovation for the company on providing smart store services, such as establishing a more positive brand image and enhancing the consumer’s willingness to use services provided by the company. Using the signaling theory as the foundation, this study sorts out and explores what factors can be used as intrinsic and extrinsic cues for consumers to evaluate the quality of smart store services, and further examining its impact on the brand image and consumer behaviors. This study used the X-STORE of 7-ELEVEN which is established by the Uni-President Enterprises Corporation as the research target to design the questionnaire. Data collected from 262 valid samples on the internet performs enough reliability and validity for the research model. The research results show that the technology characteristics, service features and store popularity of the smart store all have positive impacts on the evaluation of the smart store service quality, but the consumer’s need for interaction with service personnel is not the main factors for assessing the service quality. In addition, the quality of the smart store services will also positively affect the brand image of the company, which in turn influences the consumer’s intention to use other services provided by the company in the future. Finally, based on the research results, this study proposed some theoretical and practical implications. Suggestions for future research are also discussed.

Table of Contents
論文審定書 i
論文公開授權書 ii
誌謝 iii
摘要 iv
Abstract v
Table of Contents vii
List of Figures ix
List of Tables x
Chapter 1 Introduction 1
1.1 Research Background 1
1.2 Research Motivation 4
1.3 Research Question and Purpose 7
1.4 Research Process 9
Chapter 2 Literature Review 11
2.1 Smart Store 11
2.2 Signaling Theory 15
2.2.1 Asymmetry of Information 16
2.2.2 Signals 18
2.2.3 Signal Outcome 20
2.2.4 Signaling Theory in E-commerce 21
Chapter 3 Research Method 23
3.1 Research Model 23
3.1.1 Intrinsic Cues of Smart Store Service Quality 24
3.1.1.1 Technology Characteristics 24
3.1.1.2 Service Features 24
3.1.2 Extrinsic Cues of Smart Store Service Quality 25
3.1.2.1 Store Popularity 25
3.1.3 Smart Store Service Quality 26
3.2 Research Hypothesis 27
3.2.1 Intrinsic Cues of Smart Store Service Quality 27
3.2.1.1 Technology Characteristics 27
3.2.1.2 Service Features 28
3.2.2 Extrinsic Cues of Smart Store Service Quality 29
3.2.2.1 Store Popularity 29
3.2.3 Need for Interaction 30
3.2.4 Smart Store Service Quality 30
3.2.5 Brand Image and Service Usage Intention 31
3.3 Operational Definition 32
3.4 Research Design 34
3.4.1 Subjects 34
3.4.2 Questionnaire Design 35
3.4.3 Pilot Test and Data Collection 45
Chapter 4 Data Analysis 46
4.1 Demographic Information 46
4.2 Measurement Model 48
4.2.1 Reliability 49
4.2.2 Convergent Validity 52
4.2.3 Discriminant Validity 54
4.2.4 Multicollinearity Check 56
4.2.5 Common Method Bias 57
4.3 Structural Model 62
Chapter 5 Conclusion and Suggestion 67
5.1 Results and Discussion 67
5.1.1 Comparison of Intrinsic and Extrinsic Cues 68
5.1.2 The Role of Service Interaction 69
5.1.3 The Impacts of Smart Stores on Consumer Decisions 70
5.2 Theoretical and Practical Implications 71
5.2.1 Implications for Theory 71
5.2.2 Implications for Practice 72
5.3 Limitations 73
5.4 Future Study 73
References 75
Appendix 88
 
List of Figures
Figure 1 1 Research Process 10
Figure 3 1 Research Model 23
Figure 4 1 PLS analysis of the proposed model 65
 
List of Tables
Table 2 1 Review of empirical self-service technology research 13
Table 3 1 The operational definition of each construct 33
Table 3 2 Measurement items of perceived enjoyment 36
Table 3 3 Measurement items of perceived ease of use 37
Table 3 4 Measurement items of perceived usefulness 37
Table 3 5 Measurement items of speed of service 38
Table 3 6 Measurement items of store atmosphere 39
Table 3 7 Measurement items of self-control 39
Table 3 8 Measurement items of public familiarity 40
Table 3 9 Measurement items of media report 41
Table 3 10 Measurement items of need for interaction 42
Table 3 11 Measurement items of self-service technology quality 43
Table 3 12 Measurement items of service innovation 43
Table 3 13 Measurement items of brand image 44
Table 3 14 Measurement items of service usage intention 45
Table 4 1 Demographic information 47
Table 4 2 Reliability test for the scales 50
Table 4 3 Descriptive statistics for the constructs 52
Table 4 4 PLS confirmatory factor analysis and cross-loadings 53
Table 4 5 Correlation among constructs and the square root of the AVE 55
Table 4 6 Heterotrait-Monotrait ratio (HTMT) 56
Table 4 7 Multicollinearity check 57
Table 4 8 Harman’s single factor test 58
Table 4 9 Latent method factor test 60
Table 4 10 The results of hypothesis validation 66

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