Examining the critical success factors of productive entrepreneurship: an ISM-MICMAC approach

Abstract

Purpose

The concept of productive entrepreneurship has been recognised as a strategic approach to address the various challenges economies face, such as high unemployment, low economic growth and limited diversification. However, studies on the productive entrepreneurship’s critical success factors (CSFs) are rare and fragmented. Hence, this paper aims to identify the CSFs of productive entrepreneurship and determine their relationship among to offer a meaningful framework for enhancing the result of entrepreneurial activities in the emerging economy.

Design/methodology/approach

The authors conducted an extensive literature review and consulted experts to identify 14 CSFs for productive entrepreneurship. The technique of interpretive structural modelling (ISM) was used to determine the relationships and interconnectedness between these factors. In addition, this study used matrix of cross-impacts applied to a classification (MICMAC) analysis to determine the significance of CSFs in relation to the productive entrepreneurship.

Findings

The results indicate that the regulatory environment, incubators and accelerators and mentorship were the most influential factors for productive entrepreneurship in the Indian context. In contrast, social mobility and resilience were found to be the least influential factor.

Research limitations/implications

The study's findings can enable researchers, policymakers and entrepreneurs to make informed decisions and develop effective strategies to enhance the productive entrepreneurship.

Originality/value

The unique approach of research (ISM and MICMAC analysis) expands the frameworks of the entrepreneurship ecosystem with a comprehensive and dynamic emergent investigation into the foundation of productive entrepreneurship.

Citation

Sahu, C.K. and Panda, R.K. (2024), "Examining the critical success factors of productive entrepreneurship: an ISM-MICMAC approach", Journal of Modelling in Management, Vol. 19 No. 6, pp. 2248-2276. https://doi.org/10.1108/JM2-05-2023-0109