Critical operations capabilities for competitive manufacturing: a systematic review

Abstract

Purpose

The purpose of this paper is to investigate systematically the topic of operations capabilities within the operations strategy area. The output is a framework that will benefit researchers and firms to gain a more complete understanding of critical operations capabilities.

Design/methodology/approach

The research methodology is a systematic literature review. The aim of this study is to provide a snapshot of the diversity of studies being conducted in the field of operations capabilities, within the operations strategy area. In total, 157 papers were taken into consideration. Various operations capabilities were identified and synthesized in a conceptual framework.

Findings

The output of this paper is a conceptual framework of critical operations capabilities. Different operations capabilities and dimensions were identified in the literature. In total, seven dimensions were identified and included in the framework: cost, quality, delivery, flexibility, service, innovation, and environment.

Research limitations/implications

This research was conducted through a systematic literature review. The framework presented in this paper provides a summary of critical operations capabilities, and in addition theoretical support for managers and firms wishing to formulate an operations strategy.

Practical implications

In general, this research sets the basis for managers and practitioners concerning the formulation of successful operations strategies. In the long term, a deeper understanding and shared knowledge about competitive priorities and operations capabilities can positively influence the success of firms.

Originality/value

This paper extends the theory by providing researchers and managers with updated knowledge on operations capabilities.

Citation

Sansone, C., Hilletofth, P. and Eriksson, D. (2017), "Critical operations capabilities for competitive manufacturing: a systematic review", Industrial Management & Data Systems, Vol. 117 No. 5, pp. 801-837. https://doi.org/10.1108/IMDS-02-2016-0066