Multichannel retailer’s channel choice and product pricing: Influence of investment in fit-disclosing technology by competing retailers

Joshi, Raunak; Basu, Sumanta; Jonnalagedda, Sreelata; Avittathur, Balram

doi:10.1016/j.ijpe.2023.108895

Cited by 5 publications

(1 citation statement)

References 37 publications

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“…Provides a holistic and multi-dimensional view of clothing [33,34] Enables quick and wide-ranging selection of clothing from various brands and styles [35] Eliminates the need to visit physical stores for trying on [36] Offers a basic understanding of clothing [35] Can be used at any time and location [33] Brings novelty and excitement to the try-on process [33,37] The try-on process is enjoyable [33,35,36,38] Allows users to see other users' try-on results on social media [33,38] Table 1. Cont.…”

Section: Positive Descriptionmentioning

confidence: 99%

A Study on the Willingness of “Generation Z” Consumers to Use Online Virtual Try-On Shopping Services Based on the S-O-R Framework

Wang,

Jiang

2024

Systems

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Virtual try-on services, which significantly reduce return rates and enhance user shopping experiences, pose a crucial question: how can user willingness to use these services be increased? Additionally, “Generation Z” consumers, known for their unique traits and significant consumption potential, have been relatively understudied in this context. To address this theoretical gap, this study employs the Stimulus–Organism–Response (S-O-R) theory as its research framework, using online virtual shoe try-on services as a case study. Focusing on “Generation Z” consumers, this study utilizes literature review, user research, factor analysis, and linear regression to establish a user experience evaluation scale and behavior model. The user experience evaluation scale identifies positive elements such as convenience, price value, visual information acquisition, emotional value, and social interaction. The negative elements include technical limitations, personalized service deficiencies, and uncertainty. In the behavior model, all elements influence user attitudes. Notably, only the negative elements directly affect users’ willingness to use the service, except social interaction among the positive elements, which positively impacts usage intention. This study also reveals that “Generation Z” consumers have novel requirements for social interaction. This research effectively addresses existing theoretical gaps and provides a foundational theory for the development of related services and technologies.

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