Achieving supply chain resilience: the role of supply chain ambidexterity and supply chain agility

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Abstract

Purpose

This study analyzes the role of supply chain ambidexterity (SC-Ambidexterity) in developing supply chain resilience (SC-Resilience). We describe SC-Ambidexterity as a simultaneous application of supply chain adaptability (SC-Adaptability) and supply chain alignment (SC-Alignment) capabilities. We also consider the role of supply chain agility (SC-Agility) in the relationship between SC-Ambidexterity and SC-Resilience. We further suggest that the relationship between SC-Ambidexterity and SC-Resilience may be stronger in case of higher market uncertainty.

Design/methodology/approach

Based on the dynamic capabilities view (DCV) of the firm, we develop a set of hypotheses that are tested through a survey of manufacturing firms in Pakistan. The hypothesized model is tested through structural equation modeling (SEM).

Findings

The results of this study show a positive effect of SC-Ambidexterity on SC-Resilience. SC-Agility positively mediates the relationship between SC-Ambidexterity and SC-Resilience. However, our results show that this relationship does not vary at different levels of environmental uncertainty.

Originality/value

This study provides the seminal operationalization of SC-Ambidexterity in the supply chain context. It further shows the importance of SC-Ambidexterity and SC-Agility in contributing toward SC-Resilience.

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Most cited references 120

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Common method biases in behavioral research: A critical review of the literature and recommended remedies.

Philip M Podsakoff, Scott MacKenzie, Jeong-Yeon Lee … (2003)

Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.