The School of Economics, Management and Political Science of the University of Minho (EEG) is proud to announce that Hesham Mohamed has presented his doctoral thesis entitled "Structural Characteristics and Interfirm Relationship of Tourism Supply Chain".
In the author's words: "A supply chain can be viewed as a complex network of relationships and processes that links several organizations involved in the flow of materials, services, finances, and information. Social Network Analysis (SNA) is a modelling technique and analytical approach well-suited for identifying and examining the structural features of supply networks and the patterns of connections between members within the network. This thesis consists of three interrelated studies within the domain of SNA and SCM.
The first study presents a systematic review and bibliometric analysis of 113 articles published in 62 journals between 2008 and 2023.
The analysis shows how SCM researchers have used SNA techniques to analyse node- and network-level metrics. The study identifies future research directions and points out gaps in the literature. The findings advance our knowledge of the relational structure and configuration ofthe supply network, a timely insight given the current global disruptions.
The second study investigates the relationship between network embeddedness and the operational performance of tourism firms, with environmental uncertainty as a moderating variable. Survey data collected from 311 tourism firms in Egypt is analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings demonstrate that relational and structural embeddedness both have a positive impact on operational performance. The beneficial effect of structural embeddedness isIncreased under high levels of environmental uncertainty, indicating that network positioning may serve as a buffer against uncertainty in turbulent business environments.
The third study combines network analysis metrics and machine learning to examine how structural equivalence and tie heterogeneity predict the operational performance of tourism firms. The operational performance is modeled using Random Forest classifiers. Structural equivalence and tie heterogeneity are analyzed across business and institutional relationships. The results show how different structural attributes can predict performance outcomes and offer a useful framework for aligning network design strategies to operational performance goals."
The doctoral thesis was supervised by Professor Nazaré Rego, Lecturer in the Department of Management at the School of Economics, Management and Political Science of the University of Minho.
EEG congratulates Hesham Mohamed on his defence and wishes him every success in his professional and personal life!
