Structural supply chain complexity index and construct validity: a data-driven empirical approach

Abstract

Purpose

Given the lack of focus on a standardized measurement framework (e.g. benchmarking tool) to assess and quantify complexity within the supply chain, this study has developed a unified supply chain complexity (SCC) index and validated its utility by examining the relationship with firm performance. More importantly, it examines the role of firm owners' business knowledge, sales strategy and board management on the relationship between SCC and firm performance.

Design/methodology/approach

In this study, the unit of analysis is Indian manufacturing companies listed on the Bombay Stock Exchange (BSE). This research has merged panel data from two secondary data sources: Bloomberg and Prowess and empirically operationalized five key SCC drivers, namely, number of suppliers, the number of supplier countries, the number of products, the number of plants and the number of customers. The study employs panel data regression analyses to examine the proposed conceptual model and associated hypotheses. Moreover, the present study employs models that incorporate robust standard errors to account for heteroscedasticity.

Findings

The results show that complexity has a negative and significant effect on firm performance. Further, the study reveals that an owner's business knowledge and the firm's effective sales strategy and board management can significantly lessen the negative effect of SCC.

Originality/value

This study develops an SCC index and validates its utility. Also, it presents a novel idea to operationalize the measure for SCC characteristics using secondary databases like Prowess and Bloomberg.

Citation

Pant, P., Dutta, S. and Sarmah, S.P. (2023), "Structural supply chain complexity index and construct validity: a data-driven empirical approach", International Journal of Emerging Markets, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJOEM-01-2023-0086