An integrated supply chain – human resource management approach for improved supply chain performance

Abstract

Purpose

Human resource management (HRM) is struggling to cope with the increasingly volatile demand for skilled resources in the logistics and supply chain sector. Thus, this study discovers the possible integration of HRM and supply chain management (SCM) practices for improved supply chain performance. The purpose of this study is to explore the effect of intra HRM–SCM and joint HRM–SCM decisions on the performance of the supply chain.

Design/methodology/approach

An intra HRM–SCM and joint HRM–SCM model is developed following an empirical study. Survey data collected from 109 supply chain managers from Indian logistics firms are used to test the developed hypotheses. Structural equation modeling is used to analyze and validate the model.

Findings

The results suggest that supply chain performance is significantly influenced by joint HRM–SCM, compared to intra HRM–SCM practices, especially under volatile demand environments. Training and development, recruitment and selection, and performance management affect joint HRM–SCM significantly compared to the other three factors identified. Moreover, HRM and SCM show strong correlation and mutual support in identifying and fulfilling the demand of the logistics and supply chain sector.

Practical implications

With a growing trend toward globalization and digitalization, a joint HRM–SCM model will help businesses make robust and informed decisions for improved supply chain performance.

Originality/value

An empirical relationship between joint HRM–SCM, intra HRM–SCM, supply chain inhibitors and supply chain performance is established in this study. Although some part of this relationship may already exist, the study provides robust evidence to support this complex, collaborative relationship.

Citation

Jena, S.K. and Ghadge, A. (2021), "An integrated supply chain – human resource management approach for improved supply chain performance", The International Journal of Logistics Management, Vol. 32 No. 3, pp. 918-941. https://doi.org/10.1108/IJLM-03-2020-0151