A conceptual framework of supply chain volatility (SCV) is developed to help researchers and practitioners converge their discussions and understandings on this vital phenomenon. Sources, dimensions and moderators of SCV are investigated and a conceptual framework is proposed. The paper aims to discuss these issues.
Data triangulation was performed through reviewing 2,789 peer-reviewed articles and conducting a group exercise with 23 practitioners. Consequently, 364 sources were identified. Through a structured synthesis process that built on the Q-methodology with multiple academics, a framework of meta-level sources, dimensions and moderators of SCV was developed. An additional on-site meeting with 17 practitioners was conducted aiming at delineating the dimensions by their effect on SCV.
The authors propose 20 meta-level sources that contribute to five distinct dimensions of SCV, proposing behavior of customers and decision makers as contextual moderating variables. A classification scheme consisting of three descriptive SCV-affecting characteristics is proposed to delineate the dimension’s effect on SCV: relative deviating impact, repetitiveness and influenceability. Results are summarized in 15 propositions.
The paper extends knowledge on SCV and provides a coherent conceptualization of the phenomenon for future research. The proposed framework demands quantitative testing to derive more reliable conclusions.
The framework aims at reducing the gap between research and practice. It helps managers to understand researchers’ discussions and how to derive expedient implications from them.
It is the first study that systematically synthesizes widely spread literature in this field to derive a conceptual framework that seeks to explain SCV in a holistic way.
The authors would like to thank the Kuehne Foundation for the financial support of this research project.
Nitsche, B. and Durach, C.F. (2018), "Much discussed, little conceptualized: supply chain volatility", International Journal of Physical Distribution & Logistics Management, Vol. 48 No. 8, pp. 866-886. https://doi.org/10.1108/IJPDLM-02-2017-0078Download as .RIS
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