Assessing the alignment between supply chain performance management and organizational culture: a fuzzy rule-based classification approach

Abstract

To understand the relationship between supply chain performance and organizational culture can help predict scenarios and improve decision-making. However, their interface remains unexplored due to the complexity of quantitatively address the interference of subjectivity. Soft computing techniques associated with computational processing of human language have the potential to overcome this difficulty and are rarely applied to this context. Therefore, after concluding the association between grey clustering (GC) and fuzzy grey cognitive maps (FGCM) to analyze and quantify the causal relationship between culture and performance, this research project aims to assess their alignment through a fuzzy rule-based classification approach. Similar studies were not found in the literature and, therefore, new perspectives can be provided. The development of this research, based on the SCOR (Supply Chain Operations Reference) model indicators (SCC, 2017) and Hofstede's (2001) cultural dimensions, consists in four stages: literature review, computational implementation of the fuzzy rule-based classifier (FRBC), conduction of an illustrative application and result analysis. The main contribution is the integration of the FRBC to a tool that sets guidelines for action plans to promote the alignment between organizational culture and supply chain performance management, which is combined to the GC-FGCM based decision-making model. It is expected to provide reliable and practical results that foster the search for the congruence between organizational culture and performance management in supply chains adherent to different competitive strategies. (AU)