Exploring the acceptance of technology for mobile shopping: an empirical investigation among Smartphone users
Abstract
Although mobile shopping (m-shopping) has become a popular alternative approach for purchasing goods around the world, research on m-shopping acceptance is still in its early stages and is restricted to specific countries. Moreover, this research is primarily based on data from samples that were collected by persons without m-shopping experience, in general, and, in particular, it has even missed the opportunity offered by Smartphones for this research. Considering that consumer's m-shopping behaviour is more and more stimulated by the use of Smartphones, this study contributes to the literature on that topic by exploring acceptance factors of consumers in Germany who have already experienced shopping using Smartphones. Using a modified technology acceptance model (TAM), the results show that, in addition to the traditional TAM factors, perceived enjoyment and trust in the m-vendor affect the consumer's intention to engage in m-shopping, which, in turn, determines m-shopping behaviour in general. Managerial and theoretical implications are discussed.
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Consumers' m-shopping behavior is significantly determined by their behavioral intention to use m-shopping.
“Gro ß (2015) in an empirical study, suggested that consumers' m-shopping behavior is significantly determined by their behavioral intention to use m-shopping also confirming previous empirical findings (AldasManzano et al., 2009; Yu, 2012).”
From Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology (2018) · cites this paper as Groß, 2015
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · see citing works
Trust and TAM in Online Shopping: An Integrated Model1
Gefen, D., Karahanna, E., & Straub, D. W. (2003) · MIS Quarterly · doi:10.2307/30036519 · Cited by 8,635 · see citing works
Technology Acceptance Model 3 and a Research Agenda on Interventions
Venkatesh, V., & Bala, H. (2008) · Decision Sciences · doi:10.1111/j.1540-5915.2008.00192.x · Cited by 8,159 · see citing works
Venkatesh, V. (2000) · Information Systems Research · doi:10.1287/isre.11.4.342.11872 · Cited by 6,664 · see citing works
Extrinsic and Intrinsic Motivation to Use Computers in the Workplace <sup>1</sup>
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.1992.tb00945.x · Cited by 6,231 · see citing works
Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008) · Decision Support Systems · doi:10.1016/j.dss.2007.07.001 · Cited by 3,613 · see citing works
Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012) · MIS Quarterly · doi:10.2307/41410402 · Cited by 2,184 · see citing works
On-line trust: concepts, evolving themes, a model
Corritore, C. L., Kracher, B., & Wiedenbeck, S. (2003) · International Journal of Human-Computer Studies · doi:10.1016/s1071-5819(03)00041-7 · Cited by 1,200 · see citing works
Porter, C. E., & Donthu, N. (2006) · Journal of Business Research · doi:10.1016/j.jbusres.2006.06.003 · Cited by 1,066 · see citing works
Beldad, A., de Jong, M., & Steehouder, M. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.03.013 · Cited by 754 · see citing works
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Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., & Lytras, M. D. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.04.017 · Cited by 468 · see citing works
A meta-analysis of antecedents and consequences of trust in mobile commerce
Sarkar, S., Chauhan, S., & Khare, A. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.008 · Cited by 375 · see citing works
Marriott, H. R., & Williams, M. D. (2018) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2018.01.017 · Cited by 270 · see citing works
Mobile payment adoption in Latin America
Bailey, A. A., Bonifield, C. M., Arias, A., & Villegas, J. (2022) · Journal of Services Marketing · doi:10.1108/jsm-04-2021-0130 · Cited by 78 · see citing works
The influence of perceived risk on mobile shopping cart abandonment
Rodrigues, M. A., Proença, J., & Soares, I. (2024) · Journal of Strategic Marketing · doi:10.1080/0965254x.2022.2160480 · Cited by 22 · see citing works
- Authors
- Groß, M.
- Affiliations
- Brandenburg University of Technology Cottbus-Senftenberg (DE)
- Corresponding author
- Groß, Michael
- Venue
- The International Review of Retail, Distribution and Consumer Research
- Publisher
- Informa UK Limited
- Published
- 2014-12-11
- Volume
- 25
- Issue
- 3
- Pages
- 215-235
- ISSN
- 0959-3969 (ISSN-L)
- 1466-4402
- OpenAlex
- W2047449978
- Cited by
- 124
- References
- 10
- Citations by year
- 2025: 6 · 2024: 8 · 2023: 9 · 2022: 10 · 2021: 23 · 2020: 19 · 2019: 16 · 2018: 12 · 2017: 15 · 2016: 3 · 2015: 3
- FWCI
- 13.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The International Review of Retail Distribution and Consumer Research (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Keywords
- mobile shopping, technology acceptance, smartphone users, technology acceptance model, perceived enjoyment, purchase intention, consumer behavior, e-commerce
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