Methods Dealing with Complexity in Selecting Joint Venture Contractors for Large‐Scale Infrastructure Projects

Abstract

The magnitude of business dynamics has increased rapidly due to increased complexity, uncertainty, and risk of large-scale infrastructure projects. This fact made it increasingly tough to "go alone" into a contractor. As a consequence, joint venture contractors with diverse strengths and weaknesses cooperatively bid for bidding. Understanding project complexity and making decision on the optimal joint venture contractor is challenging. This paper is to study how to select joint venture contractors for undertaking large-scale infrastructure projects based on a multiattribute mathematical model. Two different methods are developed to solve the problem. One is based on ideal points and the other one is based on balanced ideal advantages. Both of the two methods consider individual difference in expert judgment and contractor attributes. A case study of Hong Kong-Zhuhai-Macao-Bridge (HZMB) project in China is used to demonstrate how to apply these two methods and their advantages.

Tackling Complexity in Green Contractor Selection for Mega Infrastructure Projects: A Hesitant Fuzzy Linguistic MADM Approach with considering Group Attitudinal Character and Attributes’ Interdependency

“…Therefore, different sets of evaluative attributes for contractor selection with different scenarios are needed. During last two decades, many efforts have been paid to identify selection attributes and construct comprehensive contractor selection methods with different applications [8,10,18,19,23,24,26,28,67,68].…”

“…One basic observation from existing literature for considering evaluative attributes is that, being analogous to selecting suppliers in supply chain management [69], decision-makers are supposed to not only consider competitive capability that distinguishes contractors from each other by business operations, but also examine contractor's cooperation capacity with other partner contractors that indeed influences the project success [8,70]. More importantly, since the construction industry has great impact on environment and the governments worldwide have introduced various policies and regulations for controlling them [6], green practices thus has become a crucial facet for evaluating green contractors [68,71].…”

“…Recently, increasing attentions have been paid to investigate appropriate evaluative cooperation attributes for contractor selection. Representatively, based on the conceptual model of partnering and alliancing in construction project management, Liang et al [8] elaborated a set of cooperation attributes for selecting joint venture contractors in largescale infrastructure projects, including compatible culture, contract, communication, collaboration, cooperation ability and cooperation satisfaction. To provide a deeper insights 4 Complexity on factors that affect contractors' cooperation under international construction joint ventures in construction projects, Hwang et al [27] conducted a survey and reported 'sharing of project risks' as the top attractive factor and 'differences in culture and working style' as the top negative factor among others.…”

“…Obviously, Hwang, et al [27] and Hwang and Han [29] contributed a feasible way to deduce more reasonable evaluative attributes on contractor's cooperation capability; however, to our best knowledge, there is still a lack of thorough investigation on a consensus set of evaluative attributes on contractor's cooperation capability for referencing. Therefore, in the light of Liang et al [8], Hwang, et al [27], and Hwang and Han [29], we here take 'Cooperation management capability' as one of the main evaluative attributes to assess contractors.…”

“…Due to self-evident complexity in large-scale projects like mega infrastructure, understanding scenarios of work packages and selecting appropriate contractors are intrinsically complicate [7,8]. To confront the complexity in contractor selection, Safa et al [5] suggested utilizing results of competitive intelligence (CI) systems as favorable inputs 2 Complexity to multiple attributes decision-making (MADM) methodologies.…”