Current literature on relationship management has focused on formal mechanisms such as contracts but has neglected the inter-organizational behavior that determines the effective adoption of relational mechanisms in the context of megaprojects. This study examines the antecedents and consequences of relational behavior of participating organizations in megaprojects based on the theory of planned behavior (TPB). A sample of 285 senior managers working on China’s megaprojects was surveyed, and the results were analyzed using partial least square structural equation modeling (PLS-SEM), revealing that: (1) the adoption of relational behavior is equally motivated by an organization’s behavioral intention and perceived behavioral control (PBC), and (2) relational behavior, especially information exchange, contributes the most toward achieving a high project relationship quality. A closer examination of the data found that two moderating effects, namely project culture and prior experience with other participating organizations, were particularly important. These findings contributed to four implications for project participating organizations to cultivate relational behavior and improve relationship quality in megaprojects, including identifying potential behavioral benefits, enhancing relational competence, establishing collaborative culture, and reinforcing information sharing.

As the scale and complexity of capital projects continue to increase, so do collaboration requirements among owners, engineers, architects, contractors, and other stakeholders in the project lifecycle. These organizational network challenges can impede successful project delivery. Innovation is a key factor in executing complex projects that require expertise from each party in a collaboration network. Unlike in many other industries, collaborations in architecture, engineering, and construction (AEC) project networks are typically temporary and require periods of intense collaboration. In an effort to understand the characteristics and evolutionary paths of innovative collaboration networks in the AEC industry, the authors collected data on more than 200 projects over a 15-year period (2000–2014) that were awarded the State Science and Technology Advancement Prize (SSTAP) of China and examine each of these as innovation collaboration cases. Social network analysis (SNA) techniques are used to understand the network characteristics and to examine the evolutionary patterns over time. The results find the studied innovative collaboration networks to be large and interwoven. Universities, with significantly greater betweenness centralities, serve as key network nodes in spreading creativity and promoting practical–theoretical integrations. This study also reveals that fewer repeated collaborations lead to more innovativeness. In other words, repeated collaborations may have a negative impact on novel and challenging AEC projects. Understanding such characteristics could promote innovations in the AEC industry and aid in the selection of strategic partners to participate in the execution of large and complex AEC projects more efficiently and effectively.

Collaboration networks are a compilation of dynamic relationships among multiple stakeholders within and across organizations. A megaproject may involve hundreds of organizations that may be competing for a new subproject while collaborating on other subprojects. However, some organizations have competitive advantages to win more tenders than others, and the reasons for such emergence are not thoroughly investigated yet. This study analyzed the network-based bidding competitiveness and the evolution of collaboration networks by social network analysis (SNA) through a 6-year (2008–2013) case study of a zone development project in Wuxi, China, a total number of 1,897 construction projects. The constructed megaproject collaboration network consists of four key project stakeholders: owners, contractors, designers, and quality supervisors. The analytical results show that during the evolution of the collaboration network in China, contractors and designers who exhibit higher normalized degree centralities and larger $K$ -core values are more likely to win a new project tendering competitively. At the same time, owners are primarily inclined to choose the “return” partners, especially designers, as collaborators for future projects. This study enriches the existing literature on the bidding competitiveness in megaprojects and helps us better understand the mechanism of collaboration and competition in megaprojects and provides effective and dynamic strategies to establish relational contracts in megaprojects.

Based on the Foucauldian concept of governmentality, this paper overcomes the atomistic view of external stakeholder engagement research to examine the specific conditions under which community engagement in urban infrastructure public-private partnerships (PPPs) can be transformational and create social value with and for communities. In particular, it shows that a transformational approach to community engagement is, in practice, closer to a form of governance that emphasizes involved stakeholders’ responsibility. It traces this line of argument through the literature and practice of social enterprises and other hybrid collaborations in the private sector. Conceptually, it contributes to a political and transformational understanding of community engagement within the context of public-private partnerships. First, by proposing a “governmentality analytical framework” for understanding and uncovering the often purposefully concealed dynamic power relations in the engagement process between the state, communities, and private investors. Second, by proposing a set of guiding principles on how to: empower communities to be organized; reconfigure the institutional environment to offer incentives and reliability; and design public-private partnerships as hybrid organizations capable of including other actors, such as non-governmental organizations.

An accurate schedule estimation is critical for megaprojects such as skyscrapers, which have features such as high economic values and wide societal awareness. An inaccurate schedule may have serious consequences such as going seriously overbudget or developing a poor public image. However, the accuracy of using traditional methods to predict a skyscraper’s schedule is low because of the limitation of available information at the early stage, large uncertainties, complex influencing factors, and their coupling effects on the project schedule. To improve the accuracy of schedule estimation, this paper establishes a revised case-based reasoning (CBR) model to estimate the schedule for skyscrapers. The CBR model comprises three steps, including (1) identify seven key influencing factors, (2) retrieve and rank candidate cases according to their similarity to the target case, and (3) revise selected cases based on multiple regression analysis (MRA). The model was then tested by using 33 skyscrapers in ...