The effect of motivators, supply, and lean management on sustainable supply chain management practices and performance: Systematic literature review and modeling

Abstract

Purpose

The purpose of this paper is to conceptualize a model for sustainable supply chain management (SSCM) that integrates the antecedents, practices and performance measures of sustainability. It also examines if lean management (LM) and supply management (SM) are antecedents of SSCM.

Design/methodology/approach

A systematic review of literature was undertaken across multiple streams, including operations management, SCM, sustainability, business ethics and performance management. Articles relevant to SSCM published over a span of 31 years (1988–2018) were searched using keywords and specific selection criteria.

Findings

From the literature, three dependent constructs – motivators of sustainability, LM and SM – and three independent constructs – environmental practices in SCM, social practices in SCM and SSCM performance – are identified and defined. Linkages between these constructs are hypothesized to develop a theoretical framework called the “integrated lean/supply management with sustainability motivators, practices and performance model.”

Research limitations/implications

Built on the principles-practices-outcomes framework proposed earlier, this model is comprehensive in its coverage of sustainability antecedents, practices and performance. Further, it covers the SCM triad – the supplier, the focal firm and the customers – as well as the roles they play in sustainability performance.

Originality/value

By identifying LM and SM as additional antecedents of SSCM, this study suggests that sustainability may be realized through LM and SM principles. Further, the proposed model presents a novel integration of literature from diverse domains.

Citation

Baliga, R., Raut, R. and Kamble, S. (2020), "The effect of motivators, supply, and lean management on sustainable supply chain management practices and performance: Systematic literature review and modeling", Benchmarking: An International Journal, Vol. 27 No. 1, pp. 347-381. https://doi.org/10.1108/BIJ-01-2019-0004