Behavior Intention and its Influential Factors for Motorcycle Express Service

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姓名

洪聖筑(Sheng-Chu Hung) 查詢紙本館藏

畢業系所

土木工程學系

論文名稱

(Behavior Intention and its Influential Factors for Motorcycle Express Service)

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摘要(中)

由於共享經濟越來越受歡迎，新穎的快遞方式-「機車快遞」正在起步，GoGoVan打破地方性與時間的限制，解決閒置的人力，整合運輸物流，打造了創新的物流媒合平台。本研究調查了影響使用機車快遞之因素及其相互關係，以計畫行為理論(theory of planned behavior, TPB)與科技接受模式(technology acceptance model, TAM)以及額外的感知風險作為研究的基礎架構，利用 (1) 偏最小平方結構方程模式(PLS-SEM)探究因素間之路徑關係； (2) 偏最小平方多群組分析(PLS-MGA)闡述可觀測的異質性，如：性別與使用者類型，以及 (3) 預測導向偏最小平方法(PLS-POS)探索不可觀測的異質性。為了進行實證分析，本研究在蒐集了314個有效樣本，結果顯示：(1) 在計畫行為理論與科技接受模式中，除了主觀規範外，其餘的因子均會直接或間接影響行為意向； (2) 其他納入的影響因素，如：知覺風險對行為意向有負向影響； (3) 異質性分析的結果，調查樣本中辨別出兩潛在類別，其中使用者類型對模型中部分路徑存有調節效果。最後，提出研究結論、意涵與未來研究方向。

摘要(英)

This research investigates interrelationships of factors influencing the use of motorcycle express service which is essentially a type of the sharing economy for fully utilization of surplus motorcycle capability for cargo transportation without having additional investment. The research framework is constructed mainly based on theory of planned behavior (TPB), technology acceptance model (TAM), and additional factor called perceived risk. The research framework is then analyzed with (1) partial least squares structural equation modeling (PLS-SEM) for exploring path relationships of influential factors of motorcycle express, (2) partial least squares multi-group analysis (PLS-MGA) for elaborating observed heterogeneity, like gender and user types, (3) partial least squares prediction-oriented segmentation (PLS-POS) for unobserved heterogeneity. To conduct the empirical study, we collected a sample of 287 respondents from both users and nonusers for GoGoVan motorcycle express service. The result shows: (1) except for subjective norm, all factors drawn from TPB and TAM can exert influence and explain, either directly or indirectly, the effect on the behavior intention of using motorcycle express. Other influencing factor, i.e., perceived risk, has negative effect on behavioral intention, (2) perceived usefulness mediates the impact of perceived ease to use on behavior intention, (3) heterogeneous analysis was performed by PLS-MGA for genders and user types and by PLS-POS which reveals that two latent classes can be identified among respondents, and segment 2 (i.e., experienced group) exert partial moderation effect. In the end, discussion and implications for future research are given.

關鍵字(中)

★ 共享經濟
★ 機車快遞
★ 計畫行為理論
★ 偏最小平方法
★ 異質性分析

關鍵字(英)

★ The sharing economy
★ motorcycle express
★ theory of planned behavior
★ partial least squares structural equation modeling
★ heterogeneity analysis

論文目次

Abstract i
中文摘要 ii
誌謝 iii
Table of contents iv
Table of figures vii
Table of tables viii
1. Introduction 1
2. Problem scenario and statement 2
3. Theoretical background and hypotheses 5
3.1 Theory of planned behavior 5
3.2 Technology acceptance model 6
3.3 Role of Perceived risk 8
3.4 Heterogeneous 8
3.4.1 Observed heterogeneity (due to gender or user types) 8
3.4.2 Unobserved heterogeneity (due to latent variable) 9
3.5 Framework of research model 10
4. Research methods 14
4.1 Partial least squares structural equation modeling (PLS-SEM) 14
4.2 Partial least squares -Prediction-Oriented Segmentation (PLS-POS) with considerations on heterogeneity 15
5. Measures 17
6. Empirical results 19
6.1 Data collection 19
6.2 Descriptive statistics 19
6.3 Common method variance 21
6.4 Measurement model 22
6.4.1 Reliability 22
6.4.2 Validity 24
6.5 Test of hypotheses 25
6.6 Heterogeneous analysis 27
6.6.1 Analysis on observed heterogeneity 28
6.6.2 Analysis on unobserved heterogeneity 30
6.7 Summary 36
7. Discussion and practical implications 37
8. Contribution and limitation 39
8.1 Contribution 39
8.2 Research limitations and future research 40
References 41
Appendix A: Negative Listing of Goods 44
Appendix B: MICOM 45
Appendix C: Partial least squares multi-group analysis (PLS-MGA) 50
Appendix D: Measurement items 51
Appendix E: Descriptive statistics for measurement items 54
Appendix F: Sobel Test 56

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指導教授

陳惠國(Huey-Kuo Chen)

審核日期

2017-7-31

推文