Organizational culture’s influence on supply chain performance analysis with fuzzy grey cognitive maps

Abstract

Purpose

This paper applies fuzzy grey cognitive maps (FGCM) to support multicriteria group decision making (GDM) on supply chain performance (SCP) considering the role of organizational culture as a moderating factor.

Design/methodology/approach

This paper follows the quantitative axiomatic prescriptive model-based research. It introduces a MGDM model that relies on the SCOR® model performance attributes and Hofstede’s cultural dimensions. The proposal is underpinned by the soft computing technique of FGCM, aimed at addressing the inherent subjectivity associated with evaluating the culture-performance relationship within supply chains.

Findings

The FGCM-based model proposes a management matrix tool for supporting SPC management. It results in a graphical representation that deconstructs SCP and organizational culture into key elements and provides directives for action plans that align improvement efforts. An illustrative application is presented to guide and promote the model’s application in different configurations of supply chains.

Practical implications

This model offers valuable insights into addressing the impact of organizational culture on decision-making related to SCP. Additionally, it facilitates scenario simulation. The management matrix visually illustrates how each performance attribute is influenced by each cultural dimension on a quantitative scale. It also ranks these attributes based on the overall level of influence they receive from culture.

Originality/value

The study provides a unique outlook on the use of FGCMs to support the SCP decisional process by detailing and accounting for the influence of organizational culture. This is done through the development of a novel matrix that allows for visual management and benchmarking.

Citation

Zanon, L.G., Sigahi, T.F.A.C., Anholon, R. and Carpinetti, L.C.R. (2024), "Organizational culture’s influence on supply chain performance analysis with fuzzy grey cognitive maps", Grey Systems: Theory and Application, Vol. 14 No. 4, pp. 733-753. https://doi.org/10.1108/GS-10-2023-0099