博碩士論文 104322081 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:19 、訪客IP:3.12.164.139
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)
相關論文
★ 圖書館系統通閱移送書籍之車輛途程問題★ 起迄對旅行時間目標下高速公路匝道儀控之研究
★ 結合限制規劃法與螞蟻演算法求解運動排程問題★ 共同邊界資料包絡分析法在運輸業之應用-以國內航線之經營效率為例
★ 雙北市公車乘客知覺服務品質、知覺價值、滿意度、行為意向路線與乘客之跨層次中介效果與調節式中介效果★ Investigating the influential factors of public bicycle system and cyclist heterogeneity
★ A Mixed Integer Programming Formulation for the Three-Dimensional Unit Load Device Packing Problem★ 高速公路旅行時間預測之研究--函數資料分析之應用
★ Inferring transportation modes (bus or vehicle) from mobile phone data using support vector machine and deep neural network.★ 混合羅吉特模型於運具選擇之應用-以中央大學到桃園高鐵站為例
★ Preprocessing of mobile phone signal data for vehicle mode identification using map-matching technique★ 含額外限制式動態用路人均衡模型之研究
★ 動態起迄旅次矩陣推估模型之研究★ 動態號誌時制控制模型求解演算法之研究
★ 不同決策變數下動態用路人均衡路徑選擇模型之研究★ 動態人口分布最佳化控制之研究-雙層規劃模型之應用
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 ( 永不開放)
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
參考文獻



物流技術與戰略雜誌 ,https://www.logisticnet.com.tw/publication.asp?id=29,民國105年2月。
GOGOVAN官方網站,https://www.gogovan.tw/service.,民國106年7月29日。
Uber官方網站,https://www.uber.com/zh-TW/,民國106年7月29日。
Lyft官方網站,https://www.lyft.com/,民國106年7月29日。
Car2go官方網站,https://www.car2go.com/US/en/,民國106年7月29日。
Zipcar官方網站,http://www.zipcar.com.tw/,民國106年7月29日。
Airbnb官方網站,https://www.airbnb.com.tw/,民國106年7月29日。
黑貓宅急便官方網站,http://www.t-cat.com.tw/send/index.aspx. ,民國106年7月29日。
Ajzen, I., Fishbein M., 1980. Book title: Understanding Attitudes and Predicting Social Behavior, Englewood Cliffs, NJ: Prentice-Hall.
Ajzen, I., 1985. Book title: From intentions to actions: A Theory of Planned Behavior. Heidelberg, Springer, Germany.
Ajzen, I., 1991. “The theory of planned behavior.” Organizational Behavior and Human Decision Processes, 50 (2): 179-211. doi:10.1016/0749-5978(91)90020-T.
Bauer, R. A., 1960. “Consumer behavior as risk taking.” In: Dynamic marketing for a Changing World, Hancock, R.S. (Ed.), American Marketing Association, Chicago: 389-398. doi: 10.4018/978-1-4666-7357-1.ch101.
Becker, J. M., Rai, A., Ringle, C. M., Völckner, F., 2013. “Discovering unobserved heterogeneity in structural equation models to avert validity threats.” MIS Quarterly, 37 (3): 665-694. doi: 10.2307/248719.
Chen, C.T., 2016. Investigating the Influential Factors of Public Bicycle System and Cyclist Heterogeneity. Master Thesis, National Central University, Taoyuan, Taiwan.
Cheng, Y.-H., Huang, T.-Y., 2013. “High speed rail passengers’ mobile ticketing adoption.” Transportation Research Part C: Emerging Technologies, 30 (10): 143- 160. doi: 10.1016/j.trc.2013.02.001.
Chin, W. W., 1998. “The partial least squares approach for structural equation modeling.” In Modern Methods for Business Research, Marcoulides, G. A. (Ed.): 295–236. London: Lawrence Erlbaum Associates. doi: 10.1108/S1745-3542(2012)0000008007.
Davis, F. D., 1989. “Perceived usefulness, perceived ease of use, and user acceptance of information technology.” MIS Quarterly, 13 (3): 319-340. doi: 10.2307/249008.
Dowling, G. R., Staelin, R., 1994. “A model of perceived risk and intended risk-handling activity.” Journal of Consumer Research, 21 (1): 119-134. doi: 10.1086/209386.
Garson, G. D. 2016. Book title: Partial least squares: Regression and structural equation models. Asheboro, NC: Statistical Associates Publishers.
Haenlein, M., Kaplan, A. M., 2004. “A beginner′s guide to partial least squares analysis.” Understanding Statistics, 3 (4): 283-297. doi: 10.1207/s15328031us0304_4.
Hair, J. F., Ringle, C. M., Sarstedt, M., 2011. “PLS-SEM: Indeed a silver bullet.” Journal of Marketing Theory and Practice, 19 (2): 139-152. doi: 10.2753/MTP1069-6679190202.
Hair, J. F., Sarstedt, M., Ringle, C. M., Mena, J. A., 2012. “An assessment of the use of partial least squares structural equation modeling in marketing research.” Journal of the Academy of Marketing Science, 40 (3): 414-433. doi: 10.1007/s11747-011-0261-6.
Hair, J. F., Hult, G. T. M., Ringle, C., Sarstedt, M., 2014. Book title: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), Sage, Thousand Oaks, CA.
Henseler, J., Ringle, C. M., and Sarstedt, M. 2016. “Testing Measurement Invariance of Composites Using Partial Least Squares.” International Marketing Review, 33 (3): 405-431. doi: 10.1108/IMR-09-2014-0304.
Jaffe, S., 2015. Uber isn’t driving gender equality: Why its new hiring scheme is a road to nowhere. ” March 28. http://www.salon.com/2015/03/28/.
Kim, D.J., Ferrin, D.L., Rao, H.R., 2008. “A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents.” Decision Support Systems, 44 (2): 544-564. doi: 10.1016/j.dss.2007.07.001.
Kim, H.C., Nicholson, A., Kusumastuti, D., “2017. Analysing freight shippers′ mode choice preference heterogeneity using latent class modelling.” Transportation Research Procedia, 25: 1109-1125. doi: 10.1016/j.trpro.2017.05.123.
Lohmöller, J.-B., 1989. Book title: Latent Variables Path Modeling with Partial Least Squares. Physica-Verlag, Heidelberg.
Miyazaki, A.D., Fernandez, A., 2001. “Consumer perceptions of privacy and security risks for online shopping.” The Journal of Consumer Affairs, 35 (1): 27- 44. doi: 10.1111/j.1745-6606.2001.tb00101.x.
Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., 2004. “Consumer acceptance of online banking: An extension of the technology acceptance model.” Internet Research-Electronic Networking Applications and Policy, 14 (3): 224-235, doi:10.1108/10662240410542652.
Rhodes, N., Pivik, K., 2011. “Age and gender differences in risky driving: The roles of positive affect and risk perception.” Accident analysis and prevention, 43 (3): 923-931. doi: 10.1016/j.aap.2010.11.015.
Rigdon, E. E., Ringle, C. M., Sarstedt, M., 2010. “Structural modeling of heterogeneous data with partial least squares.” Review of Marketing Research, Naresh, K. Malhotra (ed.), 7 (7): 255-296. doi: 10.1108/S1548-6435(2010)0000007011.
Rigdon, E. E., Ringle, C. M., Sarstedt, M., Gudergan, S. P., 2011. “Assessing heterogeneity in customer satisfaction studies: across industry similarities and within industry differences.” Advances in International Marketing, 22: 169-194. doi: 10.1108/S1474-7979(2011)0000022011.
Sánchez-Prieto, J.C., Olmos-Migueláñez, S., García- Peñalvo, F. J., 2016. “MLearning and pre-service teachers: An assessment of the behavioral intention using an expanded TAM model.” Computers in Human Behavior, 72: 644–654. doi: 10.1016/j.chb.2016.09.061.
Sandip, R., 2016. Book title: The Impacts of Gender, Personality, and Previous Use on Attitude Towards the Sharing Economy and Future Use of the Services, California State University, Fresno.
Westerlund, J., Papageorgiou, L. G., and Westerlund, T., 2005. “A problem formulation for optimal mixed-sized box packing.” Computer Aided Chemical Engineering, 20: 913–918. doi: 10.1016/S1570-7946(05)80274-3.
Yumeng, M., Rong, D., 2016. “Knowledge sharing-based value co-creation between e-commerce enterprises and logistics service providers.” HCI in Business, Government, and Organizations: eCommerce and Innovation, : 248-257. doi: 10.1007/978-3-319-39396-4_23.
指導教授 陳惠國(Huey-Kuo Chen) 審核日期 2017-7-31
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明