Acceptance of recommendations to buy in online retailing

Journal of Retailing and Consumer Services

Volumn 17, Issue 3, 2010, Pages 173-180

  Baier, Daniel ^a   Stüber, Eva ^a  

^a BRANDENBURG UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

Online retailing; Recommendations to buy; Technology Acceptance Model

Indexed keywords

COMMUNICATION; DESIGN; ELECTRONIC COMMERCE; INFORMATION SYSTEM; INTERNET; MODEL; RETAILING; SERVICE PROVISION; SHOPPING ACTIVITY; TECHNOLOGY ADOPTION;

EID: 77952550958     PISSN: 09696989     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jretconser.2010.03.005     Document Type: Article

References (68)

1. Ahn H.J. Utilizing popularity characteristics for product recommendation. International Journal of Electronic Commerce 2006-2007, 11(2):59-80.
2. Aksoy L., Bloom P.N., Lurie N.H., Cooil B. Should recommendation agents think like people?. Journal of Service Research 2006, 8(4):297-315.
3. Alba J., Lynch J., Weitz B., Janiszewski C., Lutz R., Sawyer A., Wood S. Interactive home shopping: consumer, retailer, and manufacturer incentives to participate in electronic marketplaces. Journal of Marketing 1997, 63(3):38-53.
4. Ansari A., Essegaier S., Kohli R. Internet recommendation systems. Journal of Marketing Research 2000, 37(3):363-375.
5. Ansari A., Mela C.F. E-Customization. Journal of Marketing Research 2003, 40(2):131-145.
6. Ariely D., Lynch J.G., Aparicio M. Learning by collaborative and individual-based recommendation agents. Journal of Consumer Psychology 2004, 14(1/2):81-95.
7. Bagozzi R.P. The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems 2007, 8(4):244-254.
8. Barlow A.K.J., Siddiqui N.Q., Mannion M. Development in information and communication technologies for retail marketing channels. International Journal of Retail and Distribution Management 2004, 32(3):157-163.
9. Bodapati A.V. Recommendation systems with purchase data. Journal of Marketing Research 2008, 45(1):77-93.
10. Burke R. Hybrid recommender systems: survey and experiments. User Modeling and User-Adapted Interaction 2002, 12(4):331-370.
11. BVH, 2008. Entwicklung des E-Commerce in Deutschland (BtC), Düsseldorf.
12. Castaneda J.A., Munoz-Leiva F., Luque T. Web acceptance model: moderating effects of user experience. Information & Management 2007, 44(4):384-396.
13. Chau P.Y.K., Au G., Tam K.Y. Impact of information presentation modes on online shopping: an empirical evaluation of a broadband interactive shopping service. Journal of Organizational Computing and Electronic Commerce 2000, 10(1):1-22.
14. Chuttur, M.Y., 2009. Overview of the technology acceptance model: origins, developments and future directions, Indiana University, USA. Sprouts: Working Papers on Information Systems, 9(37).
15. Comegys C., Hannula M., Väisänen J. Longitudinal comparison of Finnish and US online shopping behaviour among university students: the five-stage buying decision process. Journal of Targeting, Measurement and Analysis for Marketing 2006, 14(4):336-356.
16. Davis F.D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 1989, 13(3):319-340.
17. Davis F.D., Bagozzi R.P., Warshaw P.R. User acceptance of computer technology: a comparison of two theoretical models. Management Science 1989, 35(8):982-1003.
18. Dishaw M.T., Strong D.M. Extending the technology acceptance model with task-technology fit constructs. Information & Management 1999, 36(1):9-21.
19. Ebster C., Wagner U., Valis S. The effectiveness of verbal prompts on sales. Journal of Retailing and Consumer Services 2006, 13(3):169-176.
20. Fishbein M., Ajzen I. Belief, Attitude, Intention, and Behavior: an Introduction to Theory and Research 1975, Addison-Wesley, Reading, MA.
21. Fittkau, Maaß, 2009. 27. WWW-Benutzer-Analyse W3B, Fittkau and Maaß.
22. Fitzsimons G.J., Lehmann D.R. Reactance to recommendations: when unsolicited advice yields contrary responses. Marketing Science 2004, 23(1):82-94.
23. Gaul W., Geyer-Schulz A., Hahsler M., Schmidt-Thieme L. eMarketing mittels recommendersystemen. Marketing ZFP 2002, 24(Spezialausgabe):47-55.
24. Garbarino E., Strahilevitz M. Gender difference in the perceived risk of buying online and the effects of receiving a site recommendation. Journal of Business Research 2004, 57(7):768-775.
25. Gefen D., Straub D.W. Gender differences in the perception and use of e-mail: An extension to the technology acceptance model. MIS Quarterly 1997, 21(4):389-400.
26. Gefen D., Karahanna E., Straub D.W. Trust and TAM in online shopping: an integrated model. MIS Quarterly 2003, 27(1):51-90.
27. Gentry L., Calantone R. A comparison of three models to explain shop-bot use on the web. Psychology & Marketing 2002, 19(11):945-956.
28. Ha S., Stoel L. Consumer e-shopping acceptance: antecendents in a technology acceptance model. Journal of Business Research 2009, 62(5):565-571.
29. Hansen H.R., Knotzer N., Madlberger M. Empfehlungssysteme zur Verkaufsberatung im Internet. State-of-the-art und Konsumentenakzeptanz. Wirtschaftsinformatik 2007, 49(Sonderheft):50-61.
30. Häubl G., Trifts V. Consumer decision making in online shopping environments, the effects of interactive decision aids. Marketing Science 2000, 19(1):4-21.
31. van der Heijden H., Verhagen T., Creemers M. Understanding online purchase intentions: contributions from technology and trust perspectives. European Journal of Information Systems 2003, 12(1):41-48.
32. Henseler J., Ringle C.M., Sinkovics R.R. The use of partial least squares path modeling in international marketing. Advances in International Marketing 2009, 20:277-319.
33. Herlocker J.L., Konstan J.A., Riedl J.T. An empirical analysis of design choices in neighborhood-based collaborative filtering algorithms. Information Retrieval 2002, 5(4):287-310.
34. Holzwarth M., Janiszewski C., Neumann M.M. The influence of avatars on consumer shopping behavior. Journal of Marketing 2006, 70(4):19-36.
35. Iacobucci D., Arabie P., Bodapati A. Recommendation agents on the internet. Journal of Interactive Marketing 2000, 14(3):2-11.
36. Igbaria M., Guimaraes T., Davis G.B. Testing the determinants of microcomputer usage via a structural equation model. Journal of Management Information Systems 1995, 11(4):87-115.
37. Jarvenpaa S.L., Tractinsky N., Vitale M. Consumer trust in an internet store. Information Technology and Management 2000, 1(1-2):45-71.
38. Kamaruizaman Y. Adoption of travel e-shopping in the UK. International Journal of Retail and Distribution Management 2007, 35(9):703-719.
39. Keil M., Tan B.C., Wei K.-K., Saarinen T., Tuunainen V., Wassenaar A. A cross-cultural study on escalation of commitment behaviour in software projects. Management Information Systems Quarterly 2000, 24(2):299-325.
40. Kim B.-D., Kim S.-O. A new recommender system to combine content-based and collaborative filtering systems. Journal of Database Marketing 2001, 8(3):244-252.
41. Königstorfer J., Gröppel-Klein A. Experiences of failure and anger when using the mobile and wired internet: the interference of acceptance-and resistance-driving factors. Marketing JRM 2007, 29(1e):34-47.
42. Kramer T. The effect of measurement task transparency on preference construction and evaluations of personalized recommendations. Journal of Marketing Research 2007, 44(2):224-233.
43. Lee H.-H., Fiore A.M., Kim J. The role of the technology acceptance model in explaining effects of image interactivity technology on consumer responses. International Journal of Retail and Distribution Management 2006, 34(8):621-644.
44. Lee Y., Kozar K.A., Larsen K.R. The technology acceptance model: past, present, and future. Communications of AIS 2003, (12):752-780.
45. Li Y., Lu L., Li X. A hybrid collaborative filtering method for multiple-interests and multiple-content recommendation in e-commerce. Expert Systems with Applications 2005, 28(1):67-77.
46. Mathieson K. Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information Systems Research 1991, 2(3):173-191.
47. McKechnie S., Winkihofer H., Ennew C. Applying the technology acceptance model to the online retailing of financial services. International Journal of Retail and Distribution Management 2006, 34(4/5):388-410.
48. Mild A., Reutterer T. An improved collaborative filtering approach for predicting cross-category purchases based on binary market basket data. Journal of Retailing and Consumer Services 2003, 10(3):123-133.
49. Moon J., Kim Y. Extending the TAM for a world-wide-web context. Information & Management 2001, 38(4):217-230.
50. Mulpuru, S., 2007. Which personalization tools work for eCommerce-and why. Forrester Research.
51. O'Cass A., Fenech T. Web retailing adoption: exploring the nature of internet users web retailing behaviour. Journal of Retailing and Consumer Services 2003, 10(2):81-94.
52. Pavlou P.A. Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce 2003, 7(3):101-134.
53. Pavlou P.A., Gefen D. Building effective online marketplaces with institution-based trust. Information Systems Research 2004, 51(1):37-59.
54. Pavlou P.A., Fygension M. Understanding and predicting electronic commerce adoption: an extension of the theory of planned behavior. MIS Quarterly 2006, 30(1):115-143.
55. Porter C.E., Donthu N. Using the technology acceptance model to explain how attitudes determine internet usage: the role of perceived access barriers and demographics. Journal of Business Research 2006, 59(9):999-1007.
56. Ringle, C.M.,Wende, S., Will, A., 2005. SmartPLS2.0 M3. Available at http://www.smartpls.de.
57. Segars A.H., Grover V. Re-examining perceived ease of use and usefulness: a confirmatory factor analysis. MIS Quarterly 1993, 17(4):517-525.
58. Senecal S., Nantel J. The influence of online product recommendations on consumers' online choices. Journal of Retailing 2004, 80(2):159-169.
59. Stern B.B., Royne M.B., Stafford T.F., Bienstock C.C. Consumer acceptance of online auctions: an extension and revision of the TAM. Psychology & Marketing 2008, 25(7):619-636.
60. Taylor S., Todd P. Assessing IT usage: the role of prior experience. MIS Quarterly 1995, 19(4):561-571.
61. Tenenhaus M., Esposito Vinzi V., Chatelin Y.-M., Lauro C. PLS path modeling. Computational Statistics & Data Analysis 2005, 48(1):159-205.
62. Venkatesh V. Creation of favorable user perceptions: exploring the role of intrinsic motivation. MIS Quarterly 1999, 23(2):239-260.
63. Venkatesh V., Davis F.D. A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science 2000, 46(2):186-204.
64. Wang W., Benbasat I. Recommendation agents for electronic commerce: effects of explanation facilities on trusting beliefs. Journal of Management Information Systems 2007, 23(4):217-246.
65. Wold H.O. Causal flows with latent variables: partings of the ways in the light of NIPALS modeling. European Economic Review 1974, 5(1):67-86.
66. Wold H.O. Soft modeling: the basic design and some extensions. Systems under Indirect Observations, Part II 1982, 1-54. K.G. Jö reskog, H.O. Wold (Eds.).
67. Venkatesh, V., 1999. Creation of Favorable User Perceptions: Exploring the Role of Intrinsic Motivation, MIS Quarterly, 23 (2), 239-260.
68. Zellweger P. Web-based sales: defining the cognitive buyer. Electronic Markets 1997, 7(3):10-16.