The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Determinants of satisfaction and continuance intention towards self‐service technologies
Abstract
Purpose: Self‐service technologies (SSTs) allow customers to offer their own service encounters via the interaction of electronic service interfaces or machines rather than by interacting with a firm's service personnel. This paper aims to develop an integrated model designed to predict and explain an individual's continuous use of SSTs based on the concepts of technology readiness (TR), technology acceptance model (TAM), and theory of planned behavior (TPB). Design/methodology/approach: The participants are from 481 SST users as the sample finally. Structural equation modeling is applied to demonstrate the stability of the proposed model and the results of hypotheses testing. Findings: This paper finds that consumers' satisfaction significantly influences continuance intention, while the perceived usefulness, perceived ease of use, subjective norm (SN), and perceived behavioral control (PBC) simultaneously influence satisfaction. Optimism and innovativeness are also the significant motivators of satisfaction. However, TR's inhibitors (discomfort and insecurity) have no significantly negative influence on continuance intention towards adopting SST services. Research limitations/implications: Different from previous SSTs studies, this paper suggests that SN and PBC play critical factors in users' adoption at SSTs encounters. However, additionally empirical evidences should be discussed why the inhibitors (discomfort and insecurity) of TR have no effect. Originality/value: This paper proposes a comprehensive model to synthesize the essence of TR, TAM, and TPB for explaining customers' continuous intention of SSTs.
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Marketing AI recruitment: The next phase in job application and selection
van Esch, P., Black, J. S., & Ferolie, J. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.09.009 · Cited by 391
Aboelmaged, M. G. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2014.05.002 · Cited by 355
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Pantano, E., & Viassone, M. (2015) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2015.04.003 · Cited by 279
Recent related research in technology acceptance model: A literature review
Chen, S.-C., Li, S.-H., & Li, C.-Y. (2012) · Australian Journal of Business and Management Research · doi:10.52283/nswrca.ajbmr.20110109a14 · Cited by 226
Self-citation
Metadata
- Authors
- Chen, S., Chen, H., & Chen, M.
- Venue
- Industrial Management & Data Systems
- Publisher
- Emerald
- Published
- 2009-10-30
- Volume
- 109
- Issue
- 9
- Pages
- 1248-1263
- ISSN
- 0263-5577 (ISSN-L)
- OpenAlex
- W2054920172
- Cited by
- 288
- References
- 61
- FWCI
- 22.37
- Type
- journal article
- Language
- en
- Open access
- closed
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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.