Modelling and analysis of key enablers of digital transformation in food SMEs using ISM and MICMAC approach

Bhavesh Chandrayan, Sumit Gupta, Ravinder Kumar, Govind Sharan Dangayach and Sandeep Jagtap

International Journal of Intelligent Enterprise, 2023, vol. 10, issue 4, 419-444

Abstract: The food business in India is the backbone of the country, meeting the fundamental human need of food for a large portion of the country's population while also exporting it to other countries. Small and medium-sized enterprises (SMEs) account for the major share of total food production, even though they lack the necessary technological infrastructure and operating standards. Due to COVID-19 crisis, the food sector has been obliged to resolve and upgrade to the new laws tralatitious by the government, which has significantly stimulated the long-awaited digital transformation of food SMEs in India. The purpose of this study is to identify and analyse the major enablers of digital transformation in food SMEs. The interpretive structural modelling (ISM) methodology has been used to categorise the identified enablers of digital transformation, which further helps in identifying the most proactive enabler and assess the integration of other enablers in the technological paradigm.

Keywords: digital transformation; enablers; Industry 4.0; interpretive structural modelling; ISM; food SMEs; MICMAC. (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=133826 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijient:v:10:y:2023:i:4:p:419-444

Access Statistics for this article

More articles in International Journal of Intelligent Enterprise from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().