| 研究生: |
謝銘仁 Hsieh, Ming-Zen |
|---|---|
| 論文名稱: |
智慧型手機在物流業營業司機之接受度研究-以新竹貨運為例 An Investigation on Smartphone Acceptance among Sales Drivers in Logistics Industry-The Case of Hsin Chu Trans |
| 指導教授: |
陳正忠
Chen, Cheng-Chung |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 交通管理科學系 Department of Transportation and Communication Management Science |
| 論文出版年: | 2005 |
| 畢業學年度: | 93 |
| 語文別: | 中文 |
| 論文頁數: | 99 |
| 中文關鍵詞: | 智慧型手機 、物流 、科技接受模式 、自我效能 、創新擴散理論 |
| 外文關鍵詞: | Smartphone, IDT, Self-Efficacy, TAM, Logistics |
| 相關次數: | 點閱:80 下載:5 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
本研究旨在探討物流業中營業司機對於智慧型手機應用在其工作的接受度,透過問卷調查以及實驗兩種研究方法蒐集研究所需之相關資料,整合科技接受模式(TAM)、自我效能(Self-Efficacy)、創新擴散理論(IDT)三項理論發展本研究模式,瞭解影響台灣地區之物流業營業司機接受智慧型手機的因素;至於採用實驗的主要用意在於瞭解智慧型手機的何項功能對於物流業的營運較為有助益。
本研究是蒐集新竹貨運在台北、新竹、台中、台南和高雄的營業司機做為問卷調查的樣本,調查的實證結果發現影響物流業營業司機的因素有認知易用、自我效能、相容性、個人、環境以及態度這六項;自我效能會顯著正向影響認知易用,認知易用會顯著正向影響行為意願,相容性、個人、環境皆會顯著正向影響到態度,而環境除了直接影響態度外亦會顯著正向影響行為意願,態度會顯著正向影響行為意願。
而實驗的對象本研究則是分為已e化業者、未e化業者和就讀交通管理科系瞭解物流業的在校學生這三個族群,從實驗的結果本研究有幾點發現:物流業界認為智慧型手機網路電話的功能會比行事曆還要有用,智慧型手機的簡報功能會比掃瞄條碼還要有用,GPS 的功能又會比簡報的功能來的有用,網路電話的功能會比收發簡訊還要有用,GPS 的功能會比掃瞄條碼還要有用。
The purpose of this research is to find out the acceptance of sales drivers in logistic industry to use the smartphone in their work. This research uses two methods to collect data: survey and experiment. This research integrates Technology Acceptance Model (TAM), Self-Efficacy, and Innovation Diffusion Theory (IDT) into the research model to find out the factors of sales drivers in logistic industry accepting the smartphone. The reason of experiment is to understand what kinds of functions of the smartphone are useful to logistic industry.
This research collects data from sales drivers work in Hsin Chu Trans in Taipei, Hsinchu, Taichung, Tainan, and Kaohsiung as the subject of survey. The empirical results show that perceived ease of use (PEOU), self-efficacy, compatibility, individual, environment, and attitude are the factors of affecting sales drivers to accept the smartphone. Self-efficacy has significant effect on PEOU. PEOU has significant effect on behavior intention. Compatibility, individual, and environment have significant effect on attitude. Environment also has significant effect on behavior intention. Attitude has significant effect on behavior intention.
The subject of experiment is classified three groups: the employees of electronic enterprise, the employees of non-electronic enterprise, and the students are studying in the department of transportation and communication management science. The findings of experiment are as follow. First, logistic industry consider that the web phone is perceived useful than the calendar. Second, PowerPoint is perceived useful than scanning bar code. Third, GPS is perceived useful than PowerPoint. Fourth, the web phone is perceived useful than sending and receiving message. Fifth, GPS is perceived useful than bar code scanning.
1. Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and
perceived voluntariness in the acceptance of information technologies.
Decision Science, 28(3), 557-582.
2. Aitchison, J., & Silvey, D. C. (1958). Maximum likelihood estimation of
parameters subject to restraints. Annals of Mathematical Statistics, 29,
813-828.
3. Ajzen, I. (1985). From intentions to actions: a theory of planned behavior.
Action-Control: From Cognition to Behavior, Heidelberg: Springer-Verlag.
4. Asia Market Research Dot Com (2003). What is back translation? Retrieved
October 7, 2004, from http://www.asiamarketresearch.com/glossary/
back-translation.htm
5. Bandura, A. (1982). Self-efficacy mechanism in human agency. American
Psychologist, 37, 122-147.
6. Bandura, A. (1986). Social foundations of thought and action. Prentice Hall,
Englewood Cliffs, NJ.
7. Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1, 185-216.
8. Brislin, R. W. (1976). Translation: applications and research. New York:
Gardner Press, Inc.
9. Brislin, R. W. (1980). Translation and content analysis of oral and written
materials. In H. C. Triandis & J. W. Berry (Eds.), Handbook of
cross-cultural psychology: Methodology (Vol. 2, pp. 389-444). Boston, MA:
Allyn & Bacon.
10. Chau, P. Y. K. (1996). An empirical assessment of a modified technology
acceptance model. Journal of Management Information Systems, 13(2),
185-204.
11. Chau, P. Y. K., & Hu, P. J. H. (2002). Investigating healthcare professionals’decisions to accept telemedicine technology: an empirical test of competing theories. Information & Management, 39(4), 294-311.
12. Chen, L. D., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online
consumers: an extended technology acceptance perspective. Information &
Management, 39(8), 705-719.
13. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development
of a measure and initial test. MIS Quarterly, 19(2), 189-211.
14. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user
acceptance of information technology. MIS Quarterly, 13(3), 319-340.
15. Davis, F. D., Bagozzi, R.P., & Warshaw, P. R. (1989). User acceptance of two
theoretical models. Management Science, 35(8), 982-1003.
16. Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance
model with task-technology fit constructs. Information & Management,
36(1), 9-21.
17. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
18. Flett, R., Alpass, F., Humphries, S., Massey, C., Morriss, S., & Long, N. (2004). The technology acceptance model and use of technology in New Zealand
dairy farming. Agricultural Systems, 80(2), 199-211.
19. Gefen, D. (2000). E-commerce: the role of familiarity and trust. Omega: The
International Journal of Management Science, 28(6), 725-737.
20. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online
shopping: an integrated model. MIS Quarterly, 27(1), 51-90.
21. Gefen, D., & Keil M. (1998). The impact of developer responsiveness on
perceptions of usefulness and ease of use: an extension of the technology
acceptance model. ACM SIGMIS Database, 29(2), 35-49.
22. Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of e-mail: an extension to the technology acceptance model. MIS Quarterly,
21(4), 389-400.
23. Grover, V. & Gosla, M. (1993). The initiation, adoption, and implementation of telecommunications technologies in U.S. organizations. Journal of
Management Information Systems, 10(1), 141-164.
24. Harrison, G. G., Stormer, A., Herman, D. R., & Winham, D. M. (2003).
Development of a Spanish-language version of the U.S. household food
security survey module. The Journal of Nutrition, 133(4), 1192-1197.
25. Hartwick, J., & Barki, H. (1994). Explaining the role of user participation in information system use. Management Science, 40(4), 440-465.
26. Heijden, H. V. D. (2003). Factors influencing the usage of websites: the case of a generic portal in the Netherlands. Information & Management, 40(6),
541–549.
27. Henry, J. W., & Stone, R. W. (1994). A structural equation model ofend-user
satisfaction with a computer-based medical information system. Information
Resources Management Journal, 7(3), 21-33.
28. Hill, T., Smith, N. D., and Mann, M. F. (1987). Role of efficacy expectations in predicting the decision to use advanced technologies: The case of computers.
Journal of Applied Psychology, 72(2), 307-313.
29. Hong, W., Thong, J. Y. L., Wong, W. M., & Tam K. Y. (2001). Determinants of
user acceptance of digital libraries: an empirical examination of individual
differences and systems characteristics. Journal of Management Information Systems, 18(3), 97-124.
30. Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended
TAM with social influences and flow experience. Information & Management, 41(7), 853-868.
31. Hu, P. J., Chau, P. Y. K., Liu Sheng, O. R., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine
technology. Journal of Management Information Systems, 16(2), 91-112.
32. Hu, P. J. H., Clark, T. H. K., & Ma, W. W. (2003). Examining technology
acceptance by school teachers: a longitudinal study. Information & Management, 41(2), 227-241.
33. Hu, Q., Saunders, C., & Gebelt, M. (1997). Research report: diffusion of
information systems “outsourcing”: a reevaluation of influence sources.
Information System Research, 8(3), 288-301.
34. Hwang, J. L., Nochajski, S. M., Linn, R. T., & Wu, Y-W. B. (2004). The
development of the school function assessment–Chinese version for cross-cultural use in Taiwan. Occupational Therapy International, 11(1), 26-39.
35. Igbaria, M. (1993). User acceptance of microcomputer technology: an empirical
test. OMEGA International Journal of Management Science, 21, 73-90.
36. Karsten, K., & Roth, R. M. (1998). T he relationship of computer experience and computer self-efficacy to performance in 88 introductory computer literacy
courses. Journal of Research on Computing in Education, 31(1), 14-24.
37. Keat, T. K., & Mohan, A. (2004). Integration of TAM based electronic commerce
models for trust. Journal of American Academy of Business, Cambridge, 5(1/2), 404-410.
38. Keil, M. (1991). Managing MIS implementation: identifying and removing
barriers to use. Unpublished Doctoral Thesis, Harvard University.
39. Koufaris, M. (2002). Applying the technology acceptance model and flow theory
to online consumer behavior. Information Systems Research, 13(2), 205-224.
40. Koufaris, M., & Sosa, W. H. (2004). The development of initial trust in an online company by new customers. Information & Management, 41(3), 377–397.
41. Kwasi, A. G., & Salam, A. F. (2004). An extension of the technology acceptance model in an ERP implementation environment. Information & Management,
41(6), 731-745.
42. Kwon, T. H. & Zmud, R. W. (1987). Unifying the fragmented models of
information systems implementation. In R. J. Boland & R. A. Hirschheim
(Eds.), Critical Issues in information Systems Research (pp. 227-251). New
York: John Wiley & Sons.
43. Lee, K. H. (2001). A cross-cultural study of the career maturity of Korean and United States high school students. Journal of Development, 28(1), 43-57.
44. Lee, K. C., & Lee, S. (2003). A cognitive map simulation approach to adjusting the design factors of the electronic commerce web sites. Expert Systems
with Applications, 24(1), 1-11.
45. Lee, S. Y., & Bentler, P. M. (1980). Some asymptotic properties of constrained generalized least squares estimation in covariance structure models. South African Statistical Journal, 14, 121-136.
46. Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model.
Information & Management, 40(3), 191-204.
47. Levine, T. (1997). Commitment to learning: effects of computer experience,
confidence and attitudes. Journal of Research on Computing in Education, 16(1), 83-105.
48. Liao, S., Shao, Y. P., Wang, H., & Chen, A. (1999). The adoption of virtual
banking: an empirical study. Internation of Journal of Information Management, 19, 63-74.
49. Liaw, S. S., & Huang, H. M. (2003). An investigation of user attitudes toward
search engines as an information retrieval tool. Computers in Human Behavior, 19(6), 751–765.
50. Lou, H., Luo, W., & Strong, D. (2000). Perceived critical mass effect on
groupware acceptance. European Journal of Information System, 9, 91-103.
51. Maneesriwongul, W., & Dixon, J. K. (2004). Instrument translation process: a
methods review. Journal of Advanced Nursing, 48(2), 175–186.
52. Martocchio, J. J., & Dulebohn, J. (1994). Performance feedback effects in
training: the role of perceived controllability. Personnel Psychology, 47(2),
357-373.
53. Mathieson, K., Peacock, E., & Chin, W. W. (2001). Extending the technology
acceptance model: the influence of perceived user resources. ACM SIGMIS Database, 32(3), 86-112.
54. Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a world-wide-web
context. Information & Management, 38(4), 217–230.
55. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure
the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
56. Neuman, A., Greenberg, D. F., Labovitz, D. R., & Suzuki, L. A. (2004).
Cross-cultural adaptation of the sensory profile: establishing linguistic equivalency of the Hebrew version. Occupational Therapy International, 11(2), 112-130.
57. Nunnally, J. C. (1978). Psychometric theory. NY: McGraw-Hill.
58. Ong, C. S., Lai, J. Y., & Wang, Y. S. (2004). Factors affecting engineers’
acceptance of asynchronous e-learning systems in high-tech companies.
Information & Management, 41(6), 795–804.
59. Plouffe, C. R., Hulland, J. S., & Vandenbosch, M. (2001). Research report:
richness versus parsimony in modeling technology adoption decisions -
understanding merchant adoption of a smart card-based payment system.
Information Systems Research, 12(2), 208-222.
60. Porter, L. W., and Lawler, E. E. (1986). Managerial attitudes and performance. Richard D. Irwin, Homewood, IL.
61. Rao, C. R. (1948). Large sample tests of statistical hypotheses concerning several parameters with application to problems of estimation. Proceeding s of the Cambridge Philosophical Society, 44, 50-57.
62. Rawstorne, P., Jayasuriya, R., & Caputi, P. (2000). Issues in predicting and
explaining usage behaviors with the technology acceptance model and the
theory of planned behavior when usage is mandatory. Proceedings of the
twenty first international conference on Information systems, 35-44.
63. Rogers, E. M. (1962). Diffusion of innovations. NY: Free Press.
64. Rogers, E. M. (1983). Diffusion of innovations. (3rd ed.). NY: Free Press.
65. Rogers, E. M. (1995). Diffusion of innovations. (4th ed.). NY: Free Press.
66. Selim, H. M. (2003). An empirical investigation of student acceptance of course websites. Computers & Education, 40(4), 343–360.
67. Shih, H. P. (2004a). An empirical study on predicting user acceptance of
e-shopping on the Web. Information & Management, 41(3), 351-368.
68. Shih, H. P. (2004b). Extended technology acceptance model of Internet
utilization behavior. Information & Management, 41(6), 719-729.
69. Simon, A., Sohal A., & Brown, A. (1996). Generative and case study research
in quality management— Part I: theoretical considerations. International
Journal of Quality & Reliability Management, 13(1), 32-42.
70. Small, R., Yelland, J., Lumley, J., Rice, P. L., Cotronei, V., & Warren, R. (1999). Cross-cultural research: trying to do it better 2. Enhancing data quality. Australian and New Zealand Journal of Public Health, 23(4), 390-395.
71. Sörbom, D. (1989). Model modification. Psychometrika, 54, 371-384.
72. Straub, D. W. (1994). The effect of culture on IT diffusion: e-mail and fax in Japan and the U.S. Information Systems Research, 5(1), 23-47.
73. Taylor, S., & Todd, P. (1995a). Assessing IT usage the role of prior experience. MIS Quarterly, 19(4), 561-570.
74. Taylor, S., & Todd, P. (1995b). Understanding information technology usage: a
test of competing models. Information Systems Research, 6(2), 144-176.
75. Teo, H. H., Chan, H. C., Wei, K. K., & Zhang, Z. (2003). Evaluating information accessibility and community adaptivity features for sustaining virtual learning communities. International Journal of Human-Computer Studies,
59(5), 671–697.
76. Thong, J. Y. L., Hong, W., & Tam, K. Y. (2002). Understanding user acceptance
of digital libraries: what are the roles of interface characteristics,
organizational context, and individual differences? International Journal of
Human-Computer Studies, 57(3), 215-242.
77. Torkzadeh, G., & Koufteros, X. (1994). Factorial validity of a computer
self-efficacy scale and the impact of computer training. Educational and
Psychological Measurement, 54(3), 813-821.
78. Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived
ease of use: development and test. Decision Science, 27(3), 451-481.
79. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science,
46(2), 186-204.
80. Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for
directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.
81. Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line
shopping: the case for an augmented technology acceptance model. Information & Management, 41(6), 747–762.
82. Voss, K. E., Jr. Stem, D. E., Johnson, L. W., & Arce, C. (1996). An exploration of the comparability of semantic adjectives in three languages-a magnitude estimation approach. International Marketing Review, 13(5), 44-59.
83. Wang, Y. S. (2002). The adoption of electronic tax filing systems: an empirical study. Government Information Quarterly, 20(4), 333–352.
84. Wang, A. Y., & Newlin, M. H. (2002). Predictors of web-student performance:
The role of self-efficacy and reasons for taking an on-line class. Computers
in Human Behaviors, 18, 151-163.
85. Wolfe, R. A. (1994). Organizational innovation: review, critique and suggested research directions. Journal of Management Studies, 1994(May), 405-430.
86. Wu, I. L., & Wu, K. W. (in press). A hybrid technology acceptance approach for exploring e-CRM adoption in organizations. Behaviour & Information Technology.
87. Yang, H. D., & Yoo, Y. (2004). It’s all about attitude: revisiting the technology acceptance model. Decision Support Systems, 38(1), 19– 31.
88. Yi, M. Y., & Hwang, Y. (2003). Predicting the use of web-based information
systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal of Human-Computer Studies, 59(4), 431–449.
89. 什么是現代物流(小資料)(民90年12月5日)。人民日報.華南新聞。民94年6月4日,取自http://www.people.com.cn/BIG5/paper49/4878/527171.html
90. 中田信哉(2002)。物流入門。(陳玲玲譯)。台北市:大地。(原著出版年:1997年)
91. 中華民國物流協會(無日期)。由物流及運籌意義的解析與概念演變看物流
的行業定位。民94年6月15日,取自:http://www.talm.org.tw/package/..%5Cproduct%5C..
/uploadfile/TALM_%E7%94%B1%E7%89%A9%E6%B5%81%E5%8F%8A%E9%81%8B.HTM
92. 主要電信服務用戶數趨勢分析(民94)【資料檔】。台北市:交通部電信總局。
93. 交通部(民93)。國家貨運發展政策白皮書。台北市。
94. 何伯陽(民94年1月13日)。IDC:今年十大電信趨勢 整合功能勝出。Yahoo!奇摩新聞。民94年1月13日,取自:http://tw.news.yahoo.com/technology/
95. 吳萬益、林清河(民90)。企業研究方法(初版)。台北市:華泰。
96. 物流的定義(無日期)。新竹縣:現代化商業流通物流。民94年6月4日,
取自:http://www.materialflow.org.tw/ts1a.html
97. 姜鐵虎(民91)。構建供應鍊分析的戰略框架。上海:AMT 企業資源管理研究中心。
98. 陳孟功(民92)。校園無線區域網路(WLAN)-科技接受模式(TAM)之研究,
國立高雄師範大學工業科技教育研究所碩士論文。未出版,高雄市。
99. 陳焜元(民85)。行政管理資訊系統使用者參與效果之研究-技術接受性模
式檢証,國立政治大學公共行政學系碩士論文。未出版,台北市。
100. 陳順宇(民93)。多變量分析(3 版)。台北市:華泰。
101. 張意珮(民92)。真的很smart 的smartphone--談智慧型手機定義及未來趨
勢。拓墣產業研究所焦點報告,手機與行動通訊No.16,1-6。
102. 黃芳銘(民92)。結構方程模式理論與應用。台北市:五南。
103. 蒲文清(民93)。智慧型手機硬體平台及作業系統技術現況透視。民94年3月1日,取自:http://www.eettaiwan.com/ART_8800339462_617717%2C676964.HTM.c086e78a
104. 劉力新(民92)。光寶展出智慧型手機-S818。光寶科技。民93年10月8日,取自:http://www.liteon.com/magazine/getMagazineItem.do?pe_id=25&ca_id=5&co_id=203
105. 劉建宏(民93)。網際虛擬學習環境中學習效果之研究,國立高雄第一科技
大學資訊管理系碩士論文。未出版,高雄市。
106. 謝政益(民92)。網路電話接受度之研究,國立台灣科技大學資訊管理系所
碩士論文。未出版,台北市。