A socio-cognitive theorisation of how data-driven digital transformation affects operational productivity?

Mohsin Malik, Amir Andargoli, Imran Ali and Roberto Chavez

International Journal of Production Economics, 2024, vol. 277, issue C

Abstract: The literature on the antecedents of successful data-driven digital transformations needs clarity on if and how employees' cognitions and behaviours have any bearing on data-driven digital transformations with implications for operational productivity. This paper addresses this gap by drawing on socio-cognitive theory to examine how employees' cognitions (psychological safety) shape individual behaviours (employee-led process improvement) to affect organisational attainments such as data-driven digital transformations and operational productivity. A theoretical framework linking psychological safety to operational productivity through individual and serial mediations of ‘employee-led process improvement' and ‘data-driven digital transformation’ is statistically tested by collecting survey data from 183 healthcare providers in Australia. The results indicate that when employees' perceptions of interpersonal risks are allayed (psychological safety), it has a significant positive effect on operational productivity directly and indirectly through the individual and serial mediations of employee-led process improvement and data-driven digital transformations. The socio-cognitive theorisation of psychological safety as the driving mechanism that facilitates employee-led process improvement, data-driven digital transformation and operational productivity is a first in the academic literature with implications for both theory and practice.

Keywords: Socio-cognitive theory; Cognitions; Psychological safety; Employee involvement; Process improvement; Data-driven digital transformation; Operational productivity (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:277:y:2024:i:c:s0925527324002603

DOI: 10.1016/j.ijpe.2024.109403

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