Development of a Collaboration Recommendation Model between Global Consulting Firms using Link Prediction

Global construction and engineering consulting (E&C) firms are actively seeking entry into overseas markets based on loan projects from multilateral development banks to provide a basis for entry into overseas markets and sustainable growth. Bids on these projects are competitive between global top firms in terms of the technical level and price due to the limited number of projects; thus, developing a successful partnership to complement competence has become an essential element to win bids. In this regard, many studies have analyzed enterprises through characteristic analyses or the derivation of influential factors from the past social networks based on social network analysis (SNA). However, few studies have been conducted to reflect the process of changes to analyze collaborative relationships. Thus, this study aims to identify dynamic changes in past social networks and develop a model that can predict changes in the relationships between E&C firms based on similarities or differences between firms, presenting a methodology to target firms for appropriate collaboration. The analysis results demonstrate that the sensitivity of the developed prediction model was 70.26%, which could accurately predict 163 out of 232 actual cooperative cases.