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dc.contributor.authorPotdar, Vidyasagar
dc.contributor.authorJoshi, S.
dc.contributor.authorHarish, R.
dc.contributor.authorBaskerville, Richard
dc.contributor.authorWongthongtham, Pornpit
dc.date.accessioned2018-06-29T12:27:59Z
dc.date.available2018-06-29T12:27:59Z
dc.date.created2018-06-29T12:08:36Z
dc.date.issued2018
dc.identifier.citationPotdar, V. and Joshi, S. and Harish, R. and Baskerville, R. and Wongthongtham, P. 2018. A process model for identifying online customer engagement patterns on Facebook brand pages. Information Technology & People. 31 (2): pp. 595-614.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/69009
dc.identifier.doi10.1108/ITP-02-2017-0035
dc.description.abstract

© 2018 Emerald Publishing Limited. Purpose: The purpose of this paper is to develop and empirically test a process model (comprising of seven dimensions), for identifying online customer engagement patterns leading to recommendation. These seven dimensions are communication, interaction, experience, satisfaction, continued involvement, bonding, and recommendation. Design/methodology/approach: The authors used a non-participant form of netnography for analyzing 849 comments from Australian banks Facebook pages. High levels of inter-coder reliability strengthen the study’s empirical validity and ensure minimum researcher bias and maximum reliability and replicability. Findings: The authors identified 22 unique pattern of customer engagement, out of which nine patterns resulted in recommendation/advocacy. Engagement pattern communication-interaction-recommendation was the fastest route to recommendation, observed in nine instances (or 2 percent). In comparison, C-I-E-S-CI-B-R was the longest route to recommendation observed in ninety-six instances (or 18 percent). Of the eight patterns that resulted in recommendation, five patterns (or 62.5 percent) showed bonding happening before recommendation. Research limitations/implications: The authors limited the data collection to Facebook pages of major banks in Australia. The authors did not assess customer demography and did not share the findings with the banks. Practical implications: The findings will guide e-marketers on how to best engage with customers to enhance brand loyalty and continuously be in touch with their clients. Originality/value: Most models are conceptual and assume that customers typically journey through all the stages in the model. The work is interesting because the empirical study found that customers travel in multiple different ways through this process. It is significant because it changes the way the authors understand patterns of online customer engagement.

dc.publisherEmerald Publishing Limited
dc.titleA process model for identifying online customer engagement patterns on Facebook brand pages
dc.typeJournal Article
dcterms.source.volume31
dcterms.source.number2
dcterms.source.startPage595
dcterms.source.endPage614
dcterms.source.issn0959-3845
dcterms.source.titleInformation Technology & People
curtin.departmentSchool of Management
curtin.accessStatusFulltext not available


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