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Proposal for modeling social robot acceptance by retail customers: CAN model + technophobia

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  • Subero-Navarro, Ã urea
  • Pelegrín-Borondo, Jorge
  • Reinares-Lara, Eva
  • Olarte-Pascual, Cristina

Abstract

Acceptance of social robots (SRs) in retail is a new field of research in marketing arising from the dilemma between the potential benefits of SRs and the possibility that shoppers will reject them. The main aim of this paper is to advance in the modeling of new technology (NT) acceptance by proposing an extension of the integrative Cognitive-Affective-Normative (CAN) model that improves its explanatory and predictive power by including technophobia (TE) with a view to understanding SR acceptance in retail. The CAN + TE model is tested with a sample of 1069 individuals, resulting in an R2 of 0.73, surpassing the explanatory power of classical models. Emotions – specifically, pleasure – and TE are found to be the biggest drivers of SR acceptance for retail customers, followed by performance expectancy and social influence. Arousal and effort expectancy have no significant effect. These findings have theoretical implications for NT modeling and practical implications for reviving retail – which has been hit hard by the pandemic – opening research lines in both contexts related to the future of SRs.

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  • Subero-Navarro, à urea & Pelegrín-Borondo, Jorge & Reinares-Lara, Eva & Olarte-Pascual, Cristina, 2022. "Proposal for modeling social robot acceptance by retail customers: CAN model + technophobia," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:joreco:v:64:y:2022:i:c:s0969698921003799
    DOI: 10.1016/j.jretconser.2021.102813
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    Cited by:

    1. Wang, Yawei & Kang, Qi & Zhou, Shoujiang & Dong, Yuanyuan & Liu, Junqi, 2022. "The impact of service robots in retail: Exploring the effect of novelty priming on consumer behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    2. Alesanco-Llorente, María & Reinares-Lara, Eva & Pelegrín-Borondo, Jorge & Olarte-Pascual, Cristina, 2023. "Mobile-assisted showrooming behavior and the (r)evolution of retail: The moderating effect of gender on the adoption of mobile augmented reality," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    3. Swaraj S. Bharti & Kanika Prasad & Shwati Sudha & Vineeta Kumari, 2023. "Customer acceptability towards AI-enabled digital banking: a PLS-SEM approach," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(4), pages 779-793, December.
    4. Dhiman, Neeraj & Jamwal, Mohit & Kumar, Ajay, 2023. "Enhancing value in customer journey by considering the (ad)option of artificial intelligence tools," Journal of Business Research, Elsevier, vol. 167(C).
    5. Aric Rindfleisch & Nobuyuki Fukawa & Naoto Onzo, 2022. "Robots in retail: Rolling out the Whiz," AMS Review, Springer;Academy of Marketing Science, vol. 12(3), pages 238-244, December.

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