Charting the evolutionary conceptual pathway of analytic network process research: A main path analysis

This study delves into the flow and structure of knowledge prevalent in Analytic Network Process (ANP) literature. It traces the evolutionary pathway of ANP research, spotlighting seminal works and unfolding the development of topics over time. Analysing 4583 ANP literature records from 1986 to 2022, this research utilizes two pivotal data sources: Web of Science (WoS) and Dimensions. This main path analysis (MPA) approach is coupled with techniques such as citation analysis, social network analysis, and centrality measures to identify most influential papers, as well as using a search path algorithm (SPC) to provide higher weights to papers that serve as bridges connecting different research paths rather than simply counting all citations equally. Key works emerged as focal points in both datasets, including notable contributions from Lee, Kheybari and Büyüközkan, with the Dimensions dataset uniquely highlighting Saaty as the initial conceptual knowledge source of the ANP. The centrality measures unearthed persistent bridge roles undertaken by key contributors such as Saaty and Sarkis over different time periods. Furthermore, a detailed topic analysis discerned eight distinctive thematic clusters among the two data sources: analytical network process, network process, fuzzy analytic, evaluation laboratory, supply chain, quality function, hierarchy process, and information systems. These clusters emerged, providing a comprehensive map of ANP topics and their evolution. The study offers a comprehensive framework for scholars to navigate the expansive domain of ANP research. Identifying pivotal works and emergent themes provides direction for future research endeavours. It allows practitioners to gain invaluable insights into the foundational and transformative works in the ANP realm, enhancing their understanding and application of the methodology. This paper proposes of a dual methodological strategy: First, by using traditional academic data sources (WoS) along with a more encompassing Dimensions database; and second, by using a SPC algorithm to weight MPA papers based on their connecting role among different research paths. At the discipline level, this study carves out a novel vantage point in understanding the ANP research landscape. It offers an integrated portrayal of the field's conceptual evolution, identifying specific cluster topics as an indispensable resource for scholars, practitioners, and students.