The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.
A customer value, satisfaction, and loyalty perspective of mobile application recommendations
Open accessAbstract
Although both anecdotal and academic sources have suggested that interpersonal recommendation is an important means to promote mobile applications (apps), little to no research has investigated this topic. To fill the void, we develop a research model based on the Customer Value, Satisfaction, and Loyalty Framework (VSL). While prior VSL studies treated customer value as a black box and examined its effects as a whole, this research breaks down customer value to utilitarian benefits (consisting of app utility and app quality), hedonic benefits (consisting of app aesthetics and enjoyment), monetary sacrifices and non-monetary sacrifices (consisting of technicality, knowledge of alternative quality and privacy risk). This research extends VSL to the mobile app context and discerns factors that influence app recommendation. Based on the data analysis of 347 app users, we found that intention to recommend is a strong predictor of app recommendation behavior. Satisfaction with apps, users' app continuance intention, and hedonic benefits obtained from using apps are the direct antecedents of intention to recommend. Moreover, non-monetary sacrifices and utilitarian benefits have indirect effects on intention to recommend through satisfaction and app continuance intention. Contrary to our hypotheses, we did not find the significant effects of monetary sacrifices in the refined VSL. We also provide a detailed discussion about these findings, and the theoretical and practical implications of the research.
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Tam, C., Santos, D., & Oliveira, T. (2020) · Information Systems Frontiers · doi:10.1007/s10796-018-9864-5 · Cited by 567
The influence of perceived value on purchase intention in social commerce context
Gan, C., & Wang, W. (2017) · Internet Research · doi:10.1108/intr-06-2016-0164 · Cited by 442
Why people participate in the sharing economy: an empirical investigation of Uber
Lee, Z. W. Y., Chan, T. K. H., Balaji, M. S., & Chong, A. Y.-L. (2018) · Internet Research · doi:10.1108/intr-01-2017-0037 · Cited by 305
Can AI chatbots help retain customers? Impact of AI service quality on customer loyalty
Chen, Q., Lu, Y., Gong, Y., & Xiong, J. (2023) · Internet Research · doi:10.1108/intr-09-2021-0686 · Cited by 260
Qin, H., Peak, D. A., & Prybutok, V. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102337 · Cited by 259
Self-citation
Metadata
- Authors
- Xu, C., Peak, D., & Prybutok, V.
- Venue
- Decision Support Systems
- Publisher
- Elsevier BV
- Published
- 2015-11
- Volume
- 79
- Pages
- 171-183
- ISSN
- 0167-9236 (ISSN-L)
- OpenAlex
- W1230363684
- Cited by
- 358
- References
- 90
- FWCI
- 36.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.