SWOT analysis of Industry 4.0 variables using AHP methodology and structural equation modelling

Abstract

Purpose

Advanced digitalization techniques combined with artificial intelligence and automated robotic systems have created “Smart” organizations resulting in a new revolution in the industrial production systems as Industry 4.0 (I4.0). The research is aimed to do a meticulous scanning of internal and external environment pertaining to I4.0 implementation in the manufacturing industry in India.

Design/methodology/approach

A survey was conducted among the manufacturing managers and information technology professionals about the factors affecting I4.0 application, and 20 such internal and external factors were identified. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were executed for factor analysis, and four dimensions in terms of strengths, weaknesses, opportunities and threats (SWOT) factors were determined from the variables. The analytical hierarchy process (AHP) methodology was then applied.

Findings

Results show that increased productivity and efficiency appeared to be the biggest strength of I4.0 while the biggest weakness is the need for specialized training and skills. The biggest opportunity is found to be increasing trust of customers in Internet transactions and employee resistance to adopting new technologies turned out to be the biggest threat.

Practical implications

Organizations will be able to evaluate the strengths, work upon weakness, exploit the opportunities and protect against external challenges and threats beforehand while implementing I4.0 technologies.

Originality/value

The four dimensions in terms of SWOT pertaining to manufacturing industry have been identified by collecting original data from the manufacturing industry, and AHP and CFA were then carried out to prioritize and verify them.

Citation

Jain, V., Ajmera, P. and Davim, J.P. (2022), "SWOT analysis of Industry 4.0 variables using AHP methodology and structural equation modelling", Benchmarking: An International Journal, Vol. 29 No. 7, pp. 2147-2176. https://doi.org/10.1108/BIJ-10-2020-0546