| 研究生: |
許心玫 Hsu, Hsin-Mei |
|---|---|
| 論文名稱: |
Application of the TAM in the Channel of Online Shopping, TV Shopping, and Physical Store in Taiwan Application of the TAM in the Channel of Online Shopping, TV Shopping, and Physical Store in Taiwan |
| 指導教授: |
蔡明田
Tsai, Ming-Tien |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 企業管理學系 Department of Business Administration |
| 論文出版年: | 2005 |
| 畢業學年度: | 93 |
| 語文別: | 英文 |
| 論文頁數: | 114 |
| 中文關鍵詞: | -- |
| 外文關鍵詞: | Perceived Ease of Use, TAM, Perceived Risk, Perceived Usefulness |
| 相關次數: | 點閱:76 下載:1 |
| 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 |
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As the step of the advancement of technology, more and more convenience and fast shopping channels are developed. Especially, online shopping and TV shopping are developed vigorously in Taiwan. This study aims to investigate the behavior intention to use the channel of the online shopping, TV shopping, and physical store.
This study offers the model to predict and explain the behavior intention to use the channel of Internet, TV, or physical store for shopping. The perceived ease of use, perceived usefulness, perceived risk, and behavior intention to use are the key constructs that would like to discuss in this study. A comprehensive framework was developed based on previous researches.
Data was collected from an online survey website. The respondents all have the shopping experience of online shopping, TV shopping, or physical store. In order to test the validity of items, the Confirmatory Factor Analysis in this study. Structural Equation Modeling (SEM) and regression analysis were undertaken to test the goodness of fit (of the model with the data) and the hypotheses.
The research results show that the groups of consumers of online shop, TV shopping, and physical store have the differential characteristics. The relationship among perceived ease of use, perceived usefulness, and behavior intention are positive. And perceived risk would negatively affect the behavior intention in all of three kinds of shopping channel. The research conceptual model is a good model for test in three kinds of shopping channel.
1.Adams, D. A., Nelson, R. R., & Todd, P. A. (1992), “Perceived Usefulness,
Ease of Use, and Usage of Information Technology: A Replication”, MIS
Quarterly, 16 (2) :227-241
2.Adams, M. M., Mulinare, J., & Dooley, K. (1989), “Risk factors for
conotruncal cardiac defects in Atlanta”, J Am Coll Cardiol, 14: 432-442.
3.Agarwal, R. (1999), “The swaraj dream”, Down to Earth, 4 (15): 24-26.
4.Agarwal, R., & Prasad, J. (1999), “Are Individual Differences Germane to
the Acceptance of New Information Technologies”, Decision Science, 30 (2):
361-391
5.Arbuckle, J. L., & Wothke, W. (1999), Amos 4.0 user’s guide, IL:
SmallWaters Corporation.
6.Ajzen, I., & Fishbein, M. (1980), “Understanding attitudes and predicting
social behavior”, New Jersey, Prentice - Hall
7.Al-gahtani, S., & King, M. (1998), “Attitude, Satisfaction, and Usage:
Factors Contributing to Each in the Acceptance of Information Technology”,
Behavior and Information Technology (forthcoming), 18 (4): 277-297
8.Applegate, L. M., McFarlan, F. W., & McKenny, J. L. (1996), Corporate
Information Systems Management: Text and Case, Irwin, Chicago
9.Atkinson, J. W. (1964), An Introduction to motivation, New York: D.Van
Nostrand Company.
10.Bagozzi, R. P., & Yi, Y., (1988), “On the Evaluation of Structural
Equation Models”, Journal of the Academy of Marketing Science, 16 (1): 77-
94.
11.Bauer, R. A. (1960), Consumer Behaviour as Risk Taking in Dynamic Marketing
for a Changing World, ed. Robert S. Hancock, Chicago: American Marketing
Association
12.Bauer, R. A. (1967),Consumer Behavior as Risk Taking, In Donald F. Cox
(eds), Risk Taking and Information Handling in Consumer Behavior, Boston,
MA; Harvard University Press
13.Bentler, P. M. (1982), “Confirmatory factor analysis via noniterative
estimation: A fast, inexpensive method”, Journal of Marketing Research,
19, 417-424
14.Browne, M. W., & Cudeck, R. (1993), Alternative ways of assessing model
fit, In K.A. Bollen & J.S. Long (Eds), Testing structural equation models.
Newbury Park, CA: Sage. 136-162
15.Bhatnagar, S. (2000), Getting Value from IT Investments: Experiences from
Two Organizations, Information Technology in Context: Studies from the P
Perspective of Developing Countries. C. W. Avgerou, Geoff. Aldershot,
Ashgate Publishing Ltd.: 83-95.
16.Bhatnagar, A., Misra, S. L., & Rao, H.R. (2000), ”On Risk, Convenience,
and Internet Shopping Behavior- Why some Consumers are Online Shoppers
while others are not”, Communications of the ACM, Association for
Computing Machinery, 43 (11): 98-105
17.Bhimani, A. (1996),”Securing the commercial Internet”, Communications of
the ACM, Association for Computing Machinery, 39 (6):29-35
18.Burke, R. R. (2002),”Technology and the Customer Interface: What Consumers
Want in the Physical and Virtual Store”, Journal of the Academy of
Marketing Science, 30 (4):411-432
19.Chan, S. c., & Lu, M. t. (2004),”Understanding Internet Banking Adoption
and Use Behavior: A Hong Kong Perspective”, Journal of Global Information
Information Management, 12 (3):21-43
20.Chau, P. Y. K. (1996), ”An Empirical Assement of a Modified Technology
Acceptance Model”, Journal of Management Information Systems,13 (2): 185-
204
21.Chiravuri, A., & Nazareth, D. (2001), Consumer Trust in Electronic
Commerce: An Alternative Framework Using Technology Acceptance, Seventh
Americas Conference on Information Systems
22.Cox , D. F. (1967), Risk Taking and Information Handling in Consumer
Behavior, Graduate School of Business Administration, Boston, 34-81
23.Cox, D. F., & Rich, S. U. (1964),”Perceived Risk and Consumer Decision-
Making- The Case of Telephone Shopping”, JMR, Journal of Marketing
Research (pre-1986), 1(000004): 32-39
24.Cunningham, S. M. (1967), “The major dimensions of perceived risk”, In
Cox, D. F. (Eds.) Risk taking and information handling in consumer
behavior, Boston: Harvard University Press, 82- 108
25.Dahlberg, T., Mallat, N., & Oorni, A. (2003), Trust enhanced technology
acceptance model-consumer acceptance of mobile payment solution: tentative
evidence
26.Davis, F. D. (1986), A Technology Acceptance Model for Empirically Testing
New-User Information system: Theory and Results, Unpublished Doctoral
dissertation, Sloan School of Management, Massachusetts Institute of
Technology.
27.Davis, F. D. (1989), “Perceived Usefulness, Perceived Ease of Use, and Use
Acceptance of Information Technology”, MIS Quarterly, 13:319-340
28.Davis, F. D. (1993),”User Acceptance of Information technology: System
characteristics, user perceptions and behavioral impacts”, Int. Journal of
Man-Machine studies, 38:475-485
29.Davis, F.D., Bagozzi, R. P., & Warshaw, P. R. (1989), “User Acceptance of
Computer Technology: A comparison of Two theoretical model”, Management
Science, 5(8):982-1003
30.Fishbein, M. & Ajzen, I. (1975), Belief, Attitude, Intention and Behavior:
An Intention to Theory and Research, Reading, MA: Addision-Wesley
31.Featherman, M. S. (2001), ”Extending the Technology Acceptance Model by
Inclusion of Technology Acceptance Model by Inclusion of Perceived Risk”,
Proceedings of the Americas conference of Information Systems,Boston MA,
758-760
32.Featherman, M. S., & Pavlou, P. A. (2002), “Prediction E-Services
Adoption: A Perceived Risk Facets Perspective”, 2002-Eighth Americas
Conference on Information Systems, 1034-1046
33.Fenech, T. (1998),”Using perceived ease of use and perceived usefulness to
predict acceptance of the World Wide Web”, Computer Networks, 30 (1):629-
630
34.Gefen, D. (2003), “TAM or Just plain Habit: A Look at Experienced Online
Shoppers", Journal of End User Computing, 15 (3):-13
35.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
36.Gefen, D., & Straub, D.W. (2000),”The Relative Importance of Perceived
Ease of Use in IS Adoption: A Study of E-Commerce Adoption”, Journal of
the Association for Information Systems, 1 (8):1-28
37.Gefen, D., Karahanna, E., & Straub, D.W. (2003),”Trust and TAM in Online
Shopping: An Integrated Model”, MIS Quarterly, 27 (1):51-90
38.Ghorab, K. E. (1997),”The Impact of Technology Acceptance Considerations
on System Usage, and Adopted Level of Technological Sophistication: An
Empirical Investigation”, International Journal of Information Management,
17 (4):249-259
39.Goldmedia GmbH (2004), TV shopping and T-commerce in Europe, Screen Digest
Limited, Lymehouse Studios
40.Grewal D., Gotleib, J., & Marmorstein, H. (1994),”The moderating affects
of message framing and source credibility on the price-perceived risk
relationship”, Journal of consumer Research, 21:145-153
41.Hauser, J. R., & Shugan, S. M. (2000),”Intensity measures of consumer
preference”, Operations Research, 28: 278-320
42.Heijden, H. v. d., Verhagen, T., & Creemers, M. (2000),”Predicting online
purchase behavior: replications and tests of competing models”, Serie
research memoranda, 2000-16
43.Hendrickson, A.R., Massey, P.D.M., & Cronan, T.P. (1993),”On the Test-
Retest Reliability of Perceived Usefulness and Perceived Ease of Use
Scales”, MIS Quarterly, 17 (2):227-230
44.Hill, R.E.T., Gole, M.J., & Barnes, S.J. (1989), Olivine adcumulates in the
Norseman- Wilum greenstone belt, Weston Australia: Implications for the
volcanology of Komatiites, In: Prendergast, M.D. & Jones, M.J. (editors),
Magmatic sulphides- the Zimbabwe Volume. Institute of Mining & Metallurgy,
London, 189-206.
45.Hof, R. D. (2001), “Don't Cut Back Now”, Business Week, Issue 3751
46.Hu, L., & Bentler, P. M. (1999), Cutoff criteria for fit indexes in
covariance structural Equation Modeling, 6(1):1-55
47.Radner, R. & Rothschild, M. (1975),”On the allocation of effort”, Journal
of Economic Theory, 10:358-376
48.Igbaria, M. (1993),”User acceptance of Microcomputer Technology: An E
Empirical Test”, OMEGA Int. Journal of Management Science, 21 (1):73-90
49.Igbaria, M., & Iivari, J. (1995), “The Effects of Self-efficacy on
Computer Usage”, Omega, Int. Journal of Management Science, 23 (6): 587-605
50.Igbaria, M., Iivari, J., & Maragahh, H. (1995),”Why Individuals Use
Computer Technology? A Finnish Case Study”, Information and Management,
29:227-238
51.Igbaria, M., Zinatelli, P., & Cragg, N.; Cavaye, A. (1997), “Personal
Computing Acceptance Factors in Small Firms: A Structural Equation Model”,
MIS Quarterly, 21(3):279-306
52.IT Databank Annual Report- Market Intelligence Center 2004
53.Jackson, C. M., Chow, S., & Leith, R. A. (1997),”Toward an Understanding
of the Behavioral Intention to Use an Information System”, Decision
Sciences, 28(2):357-389
54.Jacoby, J., & Kaplan, L. B. (1972), The Components of Perceived Risk, in
Advance in Consumer Research, M. Venkatesan, ed. Chicago: Association for
Consumer Research:383-393.
55.Jarvenpaa, S. L., & Tractinsky, N. (1999), “Consumer Trust in an Internet
Store: A Cross-Cultural Validation”, Journal of Computer-mediated
Communication, 5(2)
56.Japan External Trade Organization (2004), Telemarketing Expanding Fast in
Japan, JEIRO, March 18, 2004
57.Joreskog, K.G. (1969), “A general approach to confirmatory maximum
likelihood factor analysis”, Psychometrika, 32:443-482
58.Joreskog, K. G., & D. Sorbom (1989), LISREL 7 User’s Reference Guide,
Scientific Software
59.Joreskog, K.G., & Sorbom, D. (2002), LISREL8: Structural Equation Modeling
with the SIMPLIS Command Language, Fifth Printing. Lincolnwood. IL:
Scientific Software International
60.Kaufman-Scarborough, C., & Lindquist, J. D. (2002), “E-shopping in a
multiple channel environment”, Journal of Consumer Marketing, 19 (4):333-
350
61.Knight, F. H. (1921), Risk, Uncertainty and Profit, Houghton Mifflin:
Boston.
62.Kogan, N., & Wallach, M. A. (1964), Risk taking: A study in cognition and
personality, New York: Holt, Rinehart, & Winston
63.Koufaris, M. (2002), “Applying the Technology Acceptance Model and Flow
Theory to Online Consumer Behavior”, Information Systems Research. 13
(2):205-223
64.Larcker, D. F., & Lessig, V. P. (1980),”Perceived Usefulness of
Information: A Psychometric Examination”, Decision Sciences, 11 (1):121-134
65.Liebermann, Y., & Stashevsky, S. (2002),”Perceived risks as barriers to
Internet and e-commerce usage”, Qalitative Market Research, 5 (4):291-300
66.Malhotra, Y., & Galletta, D. F. (1999), Extending the Technology Acceptance
Model to Account for Social Influence: Theoretical Bases and Empirical
Validation, Proceedings of the 32nd Hawaii International Conference on
System Sciences-1999:1-14
67.Mitchell, V. W. (1998), “A role for consumer risk perceptions in grocery
retailing”, British Food Journal. Bradford, 100 (4):171
68.Monsuwe, T. P. y., Dellaert, B. G. C., & Ruyter, K. d. (2004),”What drives
consumers to shop online? A literature review”, International Journal of
Service Industry Management, 15 (1):102-121
69.Moon, J. W., & Kim, Y. G. (2001),”Extending the TAM for a World-Wide-Web
context”, Information & Management, 38 (2001):217-230
70.Morris, M., & Dillon, A. (1997),”How User Perceptions Influence Software
Use”, IEEE Software, 14 (4):58-65
71.Ostlund, H. G. (1974), Expedition "Odysseus 65" Radiocarbon age of Black
Sea Water”, In: the Black Sea-geology, chemistry and biology, E.T. Degens
and D.A. Ross, editors, AAPG Memoir 20:127-132.
72.Park, J., Lee, D., & Ahn, J. (2001), “Risk-Focused e-Commerce Adoption
Model-A Cross-Country Study”, working paper
73.Pavlou, P. A. (2001),”Consumer Intentions to adopt Electronic Commerce-
Incorporating trust and Risk in the Technology Acceptance Model”, DIGIT
workshop, New Orleans, Louisiana, 1-28
74.Peter, J. P., & Ryan, M. J. (1976),”An investigation of perceived risk at
the brand level”, JMR, Journal of Marketing Research (pre-1986), 13
(000002):184-188
75.Peterson, M. E., Pelroy, G. A., Poysky, F. T., Paranjpye, R. N., Dong, F.
M., Pigott, G. M., & Eklund, M. W. (1997), ”Heat - pasteurization process
for inactivation of nonproteolytic types of Clostridium botulinum in picked
Dungeness crabmeat”, Journal of Food Protect. 60 (8):928-934.
76.Radner, R., & Rothschild, M. (1975), “On the allocation of effort”,
Journal of Economic Theory, 10:358-376
77.Robinson, J. P., & Shaver, P. R. (1973), Measures of psychological
attitudes, Ann Arbor, MI: Survey Research Center Institute for Social
Research, University of Michigan
78.Roselius, E. (1971), “Consumer rankings of risk reduction methods”,
Journal of Marketing, 35 (1):56-61
79.Salisbury, W.D., Pearson, R. A., Pearson, A. W. & Miller, D. W. (2001),”
Perceived security and World Wide Web purchasing intention”, Industrial
Management and Data Systems, 101 (3), 165-176
80.Segars, A. H., & Grover, V. (1993),”Re-Examining Perceived Ease of Use and
Usefulness: A Confirmatory Factor Analysis”, MIS Quarterly, 17 (4):517-527
81.Shimp, T. A., & Bearden, W. (1982),”Warranty and Other Extrinsic Cue
Effects on Consumer Risk Perceptions”, Journal of Consumer Research, 9
(June):38-46
82.Straub, D., Limayem, M., & Karahanne - Evaristo, E. (1995),”Measuring
System Usage: Implications for IS Theory Testing”, Management Science, 41
(8):1328-1342
83.Swanson, L. W. (1982), The projections of the ventral segmental area and
adjacent regions: a combined fluorescent retrograde tracer and
immunofluorescence study in the rat, Brain Res Bull “, 9 (1-6):321-353
84.Swinyard, W. R., & Smith, S. M. (2003),”Why People (Don't) Shop Online: A
Lifestyle Study of the Internet Consumer”, Psychology & Marketing, 20
(7):567-593
85.Szajna, B. (1996),”Empirical Evaluation of the Revised Technology
Acceptance Model”, Management Science, 42 (1):85-92
86.Taiwan Network Information Center, 2005/5/6
87.Tan, M., & Teo, T. S. H. (2000),”Factors influencing the adoption of
Internet banking”, Journal of the Association for Information Systems, 1
(5):1-42.
88.Tan, S. J. (1999),”Strategies for reducing consumers? Risk aversion in
Internet shopping”, Journal of Consumer Marketing, 16 (2), 163-180
89.Taylor, S., & Todd, P. (1995), ”Understanding information technology
usage: A test of competing models”, Information Systems Research, 6:144-
176.
90.Taylor, J. W. (1974),”The Role of Risk in Consume Behavior”, Journal of
Marketing, 38 (000002):54-60
91.Teo, C., Dornhoffer, J., Hanna, E., & Bower, C. (1999),”Application of
skill base techniques to pediatric neurosurgery”, Child Nervous System,
15: 103-109
92.Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991),”Personal
Computing: Toward a conceptual Model of Utilization”, MIS Quarterly, 15
(1):125-143
93.Venkatesh, V. (1999), ”Creation of favorable user perceptions: Exploring
the role of intrinsic motivation”, MIS Quarterly, 23:239-260
94.Venkatesh, V., & Davis, F. D. (1996),”A Model of the Antecedents of
Perceived Ease of Use: Development and Trust”, Decision Sciences, 27
(3):451-482
95.Venkatesh, V., & Davis, F. D. (2000),”A Theoretical Extension of the
Technology Acceptance Model: Four Longitudinal Field Studies”, Management
Science, 46 (2):186-204
96.Venkatesh, V., Morris, M., Davis, G. B., & Davis, F. D. (2003),”User
Acceptance of Information Technology: Toward a Unified View”, MIS
Quarterly, 27 (3):425- 475
97.War, M. R., & Lee, M. J. (2000), “Internet shopping, consumer search and
product branding”, The Journal of Product and Brand Management, Santa
Barbara, 9 (1):6
98.Ward, M. R. (2001),”Will Online Shopping Compete More with Traditional
Retailing or Catalog Shopping?” Economic Research and Electronic
Networking, 3 (2)103