An empirical study of real-time information-receiving using industry 4.0 technologies in downstream operations

Arsalan Mujahid Ghouri, Venkatesh Mani, Zhilun Jiao, V.G. Venkatesh, Yangyan Shi and Sachin Kamble
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Arsalan Mujahid Ghouri: UPSI - Universiti Pendidikan Sultan Idris
Venkatesh Mani: Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School
Zhilun Jiao: NKU - Nankai University
V.G. Venkatesh: Métis Lab EM Normandie - EM Normandie - École de Management de Normandie = EM Normandie Business School
Yangyan Shi: Macquarie University [Sydney], BIT - Beijing Institute of Technology
Sachin Kamble: EDHEC - EDHEC Business School - UCL - Université catholique de Lille

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Abstract: Industry 4.0 requires firms to adopt the latest technology to be more effective. However, previous studies have not addressed customer engagement (CE) and its direct benefit (buying) and indirect benefits (referring, influencing, and feedback) using modern technologies such as industry 4.0. The present study analyses customer engagement in regard to real-time information receiving (RTIR) in the downstream operations implemented through software-as-a-service technology. The data is collected from 533 customers of small businesses in retail, food & beverages, and accommodation sectors. The study's empirical model is validated using the theory of information sharing (ToIS). The outcomes specify that RTIR is the antecedent of CE. The results show the mediation effect of customer orientation on RTIR and CE relationship. The study also confirms that gender moderates three out of the four examined relationships between RTIR and CE. Subsequently, our outcomes offer a deeper understanding of RTIR and CE, imbedded in ToIS. This article exposes industry practitioners to RTIR and CE in terms of direct benefit and indirect benefits with modern technologies in downstream operations. This study provides a new theoretical framework using ToIS to advance RTIR in downstream operations through SaaS and CE.

Date: 2021-01-04
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Published in Technological Forecasting and Social Change, 2021, 165, pp.120551. ⟨10.1016/j.techfore.2020.120551⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05013833

DOI: 10.1016/j.techfore.2020.120551

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