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Risk-agility interactive model: a new look at agility drivers

Seyed Mahmoud Zanjirchi (Yazd University, Yazd, Iran)
Negar Jalilian (Yazd University, Yazd, Iran)
Ali Mirhoseini (Yazd University, Yazd, Iran)

Journal of Modelling in Management

ISSN: 1746-5664

Article publication date: 6 November 2017

671

Abstract

Purpose

According to the definitions presented for agility drivers, it can be mentioned that supply chain risk factors in terms of feature have very close roles to agility drivers and both of these factors impact the uncertainty in the environment. However, the risk factors with a wider domain are more comprehensive. This study aims to examine the effectiveness of risk as a driver on the organizational agility.

Design/methodology/approach

To conduct the research, after identification of influential risk factors of supply chain and indicators of organizational agility, questionnaires needed for the research were designed and after confirming their validity and reliability were distributed among the member of the sample. To assess the relationship between supply chain risk and the amount of organizational agility, data obtained from the questionnaires were analyzed using structural equation modeling technique.

Findings

The results of data analysis showed that supply chain risk factors could be considered as a driver affecting the organizational agility. In addition, in this study, supply chain risk factors were ranked using interpretive structural modeling. The presented comprehensive model indicated that based on causal relationships between risk factors, sovereign risk as the basis for model (three levels) and product and customer satisfaction risks as the output of the model (Level 1) were considered.

Originality/value

This paper fulfills an identified need to study how the risk factors as drivers of supply chain agility can have effect on agility.

Keywords

Citation

Zanjirchi, S.M., Jalilian, N. and Mirhoseini, A. (2017), "Risk-agility interactive model: a new look at agility drivers", Journal of Modelling in Management, Vol. 12 No. 4, pp. 690-711. https://doi.org/10.1108/JM2-01-2016-0007

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

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