Modelling Virtual Enterprises Using a Multi-Agent Systems Approach: Case of Contruction Industry in Nairobi County Kenya

Abstract

Disparate enterprises can pool together their core competencies to form a temporary Organization to exploit a market opportunity. This inter-organizational collaboration of enterprises is referred to as a virtual enterprises(VE). The success of any VE is dependent on the members’ performance and influence of the partner attributes on its performance. These members and their attributes need to be carefully evaluated. The competitive advantage of any VE is jeopardized by the time it takes to set it up when information available about the partners is insufficient. Extensive research on the evaluation and selection of partners has been done, but only a few studies have been done in the construction industry. The research evaluates and selects partners to carry out project tasks for large buildings in Nairobi County.

Qualitative and quantitative research methods were used. The qualitative method comprised interviews (with the stakeholders). Purposive sampling technique was used. Themes and categorization was based on deductive approach. Subsequently, quantitative methods, namely, Fuzzy Analytical Hierarchy Process (FAHP) and Reduced Group Fuzzy Analytical Hierarchy Process (RGFAHP), Multi-Criteria Decision Making (MCDM) algorithms, were applied. A technique called Partners Selection and Performance Evaluation Technique (PaSPET) is proposed. The technique combines fuzzy approximate reasoning with conventional Analytical Hierarchy Process algorithm, designed to deal with imprecise evaluators’ judgment.

A Multi-Agent Systems (MAS) approach was chosen to simulate VEs. A MAS is a computerized system composed of multiple interacting intelligent agents within an environment. Partners can be represented as multiple agents. Prior evidence of MAS to facilitate formation of VEs is lacking. Results, however, show that RGFAHP is both efficient and effective. Its time complexity is n (n-1) compared to n (n+6) for FAHP. It uses all evaluation criteria unlike FAHP which excludes some criteria when they are assigned zero weights. RGFAHP reduces the number of pair wise comparisons required when a large number of attributes are to be compared. Validation of the system, carried out by stakeholders, show that FAHP and RGFAHP are approximately 99.7% AND 98.6% accurate respectively in the evaluation and selection of partners and partners’ performance evaluation.

Keywords: Multi Criteria Decision Making Model (MCDMM), Analytical Hierarchy Process (AHP), Fuzzy AHP (FAHP), Reduced Group FAHP (RGFAHP), Partners Evaluation and Selection Problem (PESP), Multi-Agent System (MAS).