Configurational analysis of conditions influencing customers’ channel switching intention in omnichannel retailing: a fuzzy-set analysis

Anh Thi Nguyen (), Alrence S. Halibas (), Robert McClelland () and Nguyen Hoang Thuan ()
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Anh Thi Nguyen: RMIT Vietnam
Alrence S. Halibas: RMIT Vietnam
Robert McClelland: RMIT Vietnam
Nguyen Hoang Thuan: RMIT Vietnam

Quality & Quantity: International Journal of Methodology, 2024, vol. 58, issue 1, No 8, 178 pages

Abstract: Abstract This research examined the interplay among personal factors, namely channel lock-in, cross-channel synergy, attribute-based decision making (ADM); environmental factors, namely others’ past switching behaviour (OPB), pressure to switch from others (PSO); and behavioural factors, namely perceived self-efficacy and perception on facilitating conditions as antecedents to customers’ channel switching intention in an omnichannel context. Drawing on the complexity theory and set theory, we applied configurational analysis using the fuzzy-set Qualitative Comparative Analysis. The result of the analysis indicated two (2) sufficient configurations that led to an intention to switch channels. Both configurations contained ADM, OPB, and PSO conditions that highlight the importance of personal factors and environmental factors needed for the presence of an intention to switch channels. However, no sufficient configurations were obtained that indicate an absence of intention to switch channels. This study challenges theoretical underpinnings by demonstrating that omnichannel channel-switching behaviours can be explained from a configurational perspective. The configurations produced by this study can serve as a basis for researchers who plan to conduct asymmetric modelling of customers' channel-switching behaviour in an omnichannel context. Finally, this paper suggests omnichannel retail strategies and management as informed by these configurations.

Keywords: Channel switching behaviour; Customer experience; Configurational analysis; fsQCA; Omnichannel; Qualitative comparative analysis (QCA) (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11135-023-01633-8

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