Business & Management Studies

The adoption of artificial intelligence powered workforce management for effective revenue growth of micro, small, and medium scale enterprises (MSMEs)

The adoption of artificial intelligence powered workforce management for effective revenue growth of micro, small, and medium scale enterprises (MSMEs)

The findings suggest to MSME decision-makers that AI-powered workforce management may help revenue growth, workforce risk reduction, intelligent business and marketing, and thoughtful, innovative, and safe information exchange.

Authors

Sachin Kumar Mangla, Full Professor and Director, Research Center for Digital Circular Economy for Sustainable Development Goals (DCE-SDG), Jindal Global Business School, O.P. Jindal Global University, Haryana, India.

Mukesh Kumar, Department of Mechanical Engineering, National Institute of Technology Patna, Patna, India.

Rakesh D. Raut, Department of Operations and Supply Chain Management, National Institute of Industrial Engineering (NITIE), Mumbai, India.

Alberto Ferraris, Department of Management, University of Torino, Turin, Italy; Laboratory for International and Regional Economics, Graduate School of Economics and Management, Ural Federal University, Yekaterinburg, Russia; Faculty of Economics and Business, University of Rijeka, Rijeka, Croatia.

Vikas Kumar Choubey, Department of Mechanical Engineering, National Institute of Technology Patna, Patna, India.

Summary

Artificial intelligence (AI) has been used in various industries to provide innovative and intelligent features in micro, small and medium enterprises (MSMEs). Big industries started adopting AI for their HR and workforce management (WFM) activities, however, past literature suggests a lack of AI adoption in MSMEs. In the ongoing pandemic, a large number of job loss is reported in the literature.

Thus, artificial intelligence-powered intelligent workforce management (WFM) may be critical during or post-pandemic to manage the huge employment in MSMEs. In this study, we develop and test a conceptual framework based on three areas where AI-powered WFM adoption for MSMEs revenue development has been highlighted.

These are (a) risk management (workforce), (b) business and marketing, and (c) information exchange. Six hypotheses have been proposed and tested using structural equation modelling (SEM) with responses from 307 employees. According to the research findings, all of the offered hypotheses are significant.

The findings suggest to MSME decision-makers that AI-powered WFM may help revenue growth, workforce risk reduction, intelligent business and marketing, and thoughtful, innovative, and safe information exchange.

MSMEs are required to use AI in the information sharing that help in workforce risk management, business and marketing, and intelligent workforce management that scale-up the economic growth.

Published in: Production Planning & Control

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