Fix It or Leave It? Customer Recovery from Self-service Technology Failures
Zhen Zhu,
Cheryl Nakata,
K. Sivakumar and
Dhruv Grewal
Journal of Retailing, 2013, vol. 89, issue 1, 15-29
Abstract:
Self-service technologies (SSTs), such as airport check-in kiosks, can provide customers faster, better, and less expensive services. Yet sometimes customers experience service failures with these technologies. This study investigates the process by which customers recover from SST failures using their own effort (i.e., customer recovery) and explores their decisions to stay with or switch from the SST. Drawing from expectancy and attribution theories, we develop a process model centered on customer-recovery expectancy and test the model by tracking actual failure responses. The results show that internal attribution, perceived control over the SST, and SST interactivity all positively influence customer-recovery expectancy. In turn, expectancy affects customers’ recovery effort and recovery strategies, depending on the availability of competitive information. Furthermore, greater recovery effort increases the likelihood of staying with an SST, whereas more recovery strategies increase the likelihood of switching. The theoretical and managerial implications of these findings include ways to design SSTs to enhance recovery expectancy, a key mechanism of the recovery process, and thus to encourage customers to persist with the technologies.
Keywords: Customer recovery; Expectancy theory; Attribution theory; Self-service technology; Service failure; Service recovery; Cross-channel switching (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (42)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0022435912000759
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jouret:v:89:y:2013:i:1:p:15-29
DOI: 10.1016/j.jretai.2012.10.004
Access Statistics for this article
Journal of Retailing is currently edited by A. Roggeveen
More articles in Journal of Retailing from Elsevier
Bibliographic data for series maintained by Catherine Liu ().