INTERORGANIZATIONAL & INTERDISCIPLINARY PROJECT TEAMS A SCOPING REVIEW AND FUTURE RESEARCH DIRECTIONS FOR AEC INDUSTRY By Arnav Jain A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Construction Management – Master of Science 2023 ABSTRACT The Architecture, Engineering and Construction (AEC) industry demands collaboration between multiple high specialization organizations. These complex interorganizational and interdiscipli- nary project teams are a unique set of project teams that are mostly contracted for a temporary time where collaborators in most cases have no prior or future work relations with one another. While the teams research is at the heart of this and is well established in organizational project teams domain, there exists an established need to study teams in the context of interorganizational and interdisciplinary project teams. In the past two decades, scoping review as a research methodology has proved effective in determining future research directions for advancement of various aspects of research on project teams. However, scoping review of project teams literature utilizing a cita- tion network analysis (CNA) approach has not been used to find research directions specific to complex AEC interorganizational project teams while also evaluating their place in the larger spec- trum of project teams research. In response to this need, this study carried out a scoping review on a sample of publications studying project team settings across multiple domains. The publications were analyzed through citation network analysis tools which included several types of networks where nodes in the network represented journals, publications, countries, and keywords while the links between them highlighted the collaboration relations. Deliverables included current state of research on project teams connected across multiple domains within the project teams literature and directions for future research specific to AEC inter-organizational project teams. Keywords: Project Teams, Interorganizational Project Teams, AEC Project Teams, Scoping Re- view, Citation Network Analysis, Science of science Copyright by ARNAV JAIN 2023 ACKNOWLEDGEMENTS I would like to express my heartfelt gratitude and appreciation to my thesis committee chair and members who have contributed to the successful completion of my thesis. Their guidance, support, and encouragement have been instrumental in shaping my academic journey and research work. First and foremost, I am grateful to my thesis chair, Dr. Sinem, for her exceptional mentorship and unwavering dedication. She has not only been a professor and advisor but also a source of inspi- ration throughout the entire process. Without her expertise, guidance, and invaluable feedback, this thesis would not have been possible. I would also like to extend my sincere thanks to the other committee members, Dr. Kenneth Frank, Dr. Dong Zhao, and Dr. Hanzhe Zhang, for their valuable insights at the inception point of this research. Additionally, I am indebted to the members of the IOPT-4 research team, Meltem Duva, Hasan Bayhan, and Dong Xu. Working and learning from them has played a significant role in improving the quality and rigor of my research. Lastly, I would like to express my gratitude to the SPDC staff, Jill Selke, and Bill Balluff, for their contin- uous support and assistance throughout my time at the school. Their efficiency and professionalism have ensured that everything ran smoothly and allowed me to focus on my research. iv TABLE OF CONTENTS Chapter 1 1.1 1.2 1.3 1.4 1.5 INTRODUCTION ................................................................................................. 1 Problem Statement and the Need .................................................................................... 1 Goals and Objectives ....................................................................................................... 2 Overview of Methods ...................................................................................................... 2 Expected Results and Deliverables ................................................................................. 4 Reader’s Guide ................................................................................................................ 4 Chapter 2 2.1 2.2 2.3 2.4 2.5 2.6 LITERATURE REVIEW ..................................................................................... 5 Introduction ..................................................................................................................... 5 Teams .............................................................................................................................. 5 Project Teams .................................................................................................................. 7 Interorganizational Project Teams in the AEC Industry ............................................... 10 Literature Review Methodologies ................................................................................. 14 Summary ........................................................................................................................ 17 Chapter 3 METHODOLOGY .............................................................................................. 18 Introduction ................................................................................................................... 18 3.1 Data Collection .............................................................................................................. 19 3.2 Sample ........................................................................................................................... 24 3.3 3.4 Data Analysis ................................................................................................................. 24 3.5 Methodology Process Map ............................................................................................ 28 Data Quality Measures .................................................................................................. 29 3.6 Chapter 4 4.1 4.2 4.3 RESULTS ............................................................................................................. 30 Introduction ................................................................................................................... 30 State-of-Practice: Project Teams ................................................................................... 30 State-of-Practice and Future Research Areas: AEC Project Teams .............................. 54 Chapter 5 5.1 5.2 5.3 5.4 5.5 DISCUSSION AND CONCLUSION ................................................................. 71 Introduction ................................................................................................................... 71 Summary of Findings .................................................................................................... 71 Discussions .................................................................................................................... 73 Conclusions ................................................................................................................... 76 Limitations/ Gaps for Future Research .......................................................................... 77 REFERENCES ............................................................................................................................ 79 APPENDIX A: LIST OF PUBLICATIONS (SAMPLE FOR STUDY) ................................. 87 APPENDIX B: CO-OCCURRENCE TIMELINE NETWORK ........................................... 117 APPENDIX C: LIST OF PUBLICATIONS IN KEYWORD CLUSTERS ......................... 118 APPENDIX D: CITATIONS CLUSTER IDENTIFICATION ............................................. 120 v Chapter 1 INTRODUCTION 1.1 Problem Statement and the Need The Architecture, Engineering and Construction (AEC) industry consists of complex interor- ganizational and interdisciplinary project teams (Garcia et al., 2021; Korkmaz & Singh, 2012). These teams are formed amongst owners, designers, contractors, and various stakeholders to de- liver projects (Solis et al., 2013). They are a unique set of project teams that are contracted for a temporary time where collaborators represent multiple organizations, disciplines, and backgrounds and in most cases, have no prior or future work relations with one another (Schexnayder & Fiori, 2021). In addition to this temporary nature of the inter-organizational and interdisciplinary AEC teams, with the constant increase in scale and complexity of AEC projects, these project teams struggle to achieve efficient and effective communication to drive project success (Cheung et al., 2013; Oliver et al., 2018; Senescu et al., 2013; Solis et al., 2013). With multiple factors affect- ing an AEC project team, trust and motivation play a crucial role in ensuring smooth working relationships, both at an organizational and individual level (Cheung et al., 2013; Rotimi et al., 2016). To increase productivity in such interorganizational collaborations, the AEC industry has investigated high performance teams that are driven to establish trust within team members, shared values and goals and open communication lines (Jørgensen, 2018). Teams research is at the heart of this and is well established in organizational projects domain with a focus on how project teams are related to individual or project performance (Caniëls et al., 2019; Jørgensen, 2018). Considering the existing team literature’s focus on organizational teams and/or disciplinary teams, there exists an established need to study teams in the context of interorganizational and interdisciplinary project teams. Teams research has also found its place in the context of student project teams with a focus on skills for future of work related to leadership, team culture, task planning, communication, and time management (Galbraith & Webb, 2013; Presler-Marshall et al., 2022; Weeks & Kelsey, 2007). Further exploration of teams literature indicates that scoping review as a research methodology has proved effective in the past two decades in determining future research directions for advance- ment of various aspects of project teams (Kereri & Harper, 2019; Mathieu et al., 2019; Park et al., 2020). Mathieu et al. (2019) conducted a scoping review with a focus on team effectiveness in complex work teams, while Kereri & Harper (2019) used Social Network Analysis to identify the collaboration levels in construction project teams using social factors based on real-time data. The 1 valuable recommendations of the many existing scoping reviews out there have been embraced by many scholars in assessing the dynamic nature of project teams and its effect on project team performance. However, scoping review of project teams literature utilizing a citation network analysis (CNA) approach has not been used to find research directions specific to complex AEC interorganizational project teams while also evaluating their place in the larger spec- trum of project teams research. (Leppink & Pérez-Fuster, 2019; Mathieu et al., 2019; Park et al., 2020). In response to the above-mentioned gap, this study conducted a systematic scoping review of pro- ject teams literature to investigate and advance inter-organizational collaborations within project teams. Such a review can reveal the relations and evolution of research on project teams consider- ing key differentiating concepts such as type of industry, student versus authentic project teams, virtual versus co-located team settings etc. (Carter et al., 2015; Kereri & Harper, 2019). 1.2 Goals and Objectives The goal of this study was to carry out a scoping review of existing research on project teams and conduct a citation network analysis using SNA to explore and advance inter-organizational and interdisciplinary collaborations within AEC project teams. The specific study objectives are as follows: 1. Objective 1: Explore the trends and evolution of project teams literature differentiated by characteristics such as type of industry, authentic versus student teams, virtual vs co-lo- cated teams and organizational vs interorganizational teams. 2. Objective 2: Explore the evolution of prior works within project teams research with a focus to study: a. State-of-research of AEC interorganizational project teams; and b. Future research directions for interorganizational collaborations within the AEC industry. The main research question that will direct this research study is as follows: What is the state of practice for AEC project teams based on the literature and how has project teams research evolved and is connected across domains? 1.3 Overview of Methods This study utilizes a scoping review methodology combined with citation network analysis using SNA of prior research on project teams (Leppink & Pérez-Fuster, 2019; McLaren & Bruner, 2 2022). The scoping review methodology was conducted using an online citation database called “SCOPUS” (Carter et al., 2015; Mathieu et al., 2019; Park et al., 2020). To ensure construct va- lidity, a preliminary literature search was carried out to identify all the existing scoping review articles related to project teams to identify the relevant search strategy and methods of analysis for this study (Carter et al., 2015; Mathieu et al., 2019; Park et al., 2020). The citations covered in the study were reached upon through multiple independent systematic search paths (Mathieu et al., 2019). To ensure reliability, one of the starting points for the search was through an expert team working on project teams that helped this study identify key researchers who have made contribu- tions to teams and project teams literature. Independent keyword searches with filters on source and type of articles led to multiple publications lists. For internal validity, the lists through different search paths were combined to finalize a comprehensive publications list which serves as the sample for this study. The final list of publications focuses on research on project team settings done within multiple industries (for e.g., AEC, manufacturing, healthcare, information technology etc.). A citation network analysis using multiple node characteristics of these publications was con- ducted as it serves as an effective method to examine the overall state of a focus within a research field (McLaren & Bruner, 2022). The node in the network analysis varies from being a journal of the publications, country based on co-authorships, author keywords and the publications itself. Each network analysis was layered/explored through categorization into multiple categories: Authentic versus student project teams, Type of Industry, Virtual versus co-located teams and Organizational versus Interorganizational (Carter et al., 2015; Kereri & Harper, 2019). The publi- cations within the sample focusing on AEC interorganizational teams were further categorized based on single versus multiteam systems (Shuffler et al., 2015) and level of analysis (Chan et al., 2021; Luciano, Bartels, et al., 2018). The categorization of publications was also used to create visualizations of combination of multiple categories on a timeline on the same graph to capture the evolution and distribution of literature on project team settings. The various methods of citation network analysis and evolution over timeline graphs helped this study derive useful insights into the state-of-practice of project teams connected across multiple domains. It also gave results related to evolution and potential future research areas specific to AEC interorganizational project teams. 3 1.4 Expected Results and Deliverables The expected results and deliverables of the study are: a) Current state of research on project teams connected across multiple domains within the project teams literature; and b) Directions for future research specific to AEC inter-organizational project teams and future of workforce development. 1.5 Reader’s Guide In the following sections, Chapter-2 presents the literature review on various established aspects and evolution of teams literature and scoping review methods for defining the key methods used to carry out this study. Methodology for performing the scoping review on the sample of publica- tions is discussed in Chapter-3. Chapter-4 highlights the various results, visualizations, and key findings from the analysis. Chapter-5 talks about the results and their respective theoretical appli- cations on project teams research with recommendations for future research areas. 4 Chapter 2 LITERATURE REVIEW 2.1 Introduction Through this chapter, the researcher conducts a literature review of established aspects and evolu- tion of teams literature. From teams literature, the literature review transitions to project teams as a subset of the larger teams literature. The literature review then explores the current state of re- search of project teams with a focus on AEC industry and provides evidence on an established need to study teams literature in the context of interorganizational and interdisciplinary project teams. The chapter then covers scoping review and various methods of citation network analysis as an effective tool to study the current state of research to derive future research directions for both AEC project teams and future of workforce development. Hence, this chapter is organized in the following subsections: teams, project teams, interorganizational project teams in the AEC in- dustry and literature review methodologies. 2.2 Teams What is a Team? A team composition consists of members representing the company or different organizations (Schexnayder & Fiori, 2021). From the perspective of a system, teams are defined as “complex dynamic systems that exist in a context, develop as members interact over time, and evolve and adapt as situational demands unfold” (Kozlowski & Ilgen, 2006, p. 78). Keeping team member roles and responsibilities in mind, Kozlowski & Ilgen (2006, p. 79) define teams as “are two or more individuals who socially interact (face-to-face or virtually); possess one or more com- mon goals; are brought together to perform organizationally relevant tasks; exhibit interdependen- cies with respect to workflow, goals, and outcomes; have different roles and responsibilities; and are embedded together in an encompassing organizational system, with boundaries and linkages to the broader system context and task environment.” (Katzenbach & Smith, 2005) state that shared commitment is the most crucial aspect of a team. Majority of the work done in any organization is successfully completed via teamwork and is driven by shared commitment (Katzenbach & Smith, 2005; Kozlowski, 2018; Marks et al., 2001). Marks et al. (2001, p. 236) define teamwork as “peo- ple working together to achieve something beyond the capabilities of individuals working alone.” Kozlowski (2018) elaborates that over the past two decades, as the organizations all over the world realigned work around teams, the character of teamwork and the various factors which influence has been the focus of teams and organizational literature. 5 The organizational structure of an effective team varies from team to team and typically has designated roles and responsibilities for each person on the team (Porter et al., 2003; Schexnayder & Fiori, 2021). Within the spectrum of hierarchal teams, teams have been looked at through mul- tiple models over the years which are: (a) Individual decision-making model, (b) team lens model, and (c) multilevel theory (MLT) of team decision making” (Humphrey et al., 2002, p. 175). Humphrey et al. (2002, p. 184) elaborate that MLT of team decision making identifies four levels of analysis: (1) Decision Level, (2) Individual Level, (3) Dyadic Level and (4) Team Level. The various characteristics of successful teams have been researched by numerous researchers to develop theoretical models focusing on team effectiveness (Kozlowski & Bell, 2008; Marks et al., 2001). Kozlowski & Bell (2008) state that teams are often restricted in being viewed as means to cater to organizational demands and adaptability. Hence, clusters of individuals within teams play an important role in building effective and adaptable work teams (Dasí et al., 2021; Kozlowski, 2018). On the other hand, with the evolution in research in related to team structure and team & individual characteristics, Marks et al. (2001) focus on the importance of team processes that the team members adopt to collaborate within teams that will help the management align training and development of future teams. Additionally, research has also focused on errors in teams (Bell & Kozlowski, 2011; Maltarich et al., 2018). Bell & Kozlowski (2011) discuss the importance of identifying the origin and emergence of errors in teams. They further identified the factors that influence management of errors in teams but found a lack of representation of product & service and project teams to clearly define how workflow interdependence and boundary permeability affect error management. Teams research is well established in organizational projects domain with a focus on how teams are related to individual or project performance (Caniëls et al., 2019; Jørgensen, 2018; Zhou et al., 2017). Cohen & Bailey (1997) defined four broad categories of teams: (a) Work teams: Work teams are the most generic teams that come up when discussing teams as they are ongoing units of work for producing goods and/or services. (b) Parallel Teams: Parallel teams are the teams that exist parallelly in cohesion with an existing formal organizational structure to perform functions that the organization itself cannot perform that well. 6 (c) Management Teams: These teams provide directions to sub-units within an organization and ensure their integration with other interdependent sub-units across key processes of the busi- ness. (d) Project Teams: Project teams refer to a time-limited group of individuals working collabora- tively on the development of a new product or service. The tasks undertaken by these teams are intricate and diverse, requiring a substantial application of knowledge, expertise and judge- ment. The activities performed by project teams tend to be simultaneous rather than sequential. Moreover, these teams often comprise individuals from various disciplines and functional units. Hence, project teams represent a unique type of team which will be discussed in detail in the fol- lowing section. 2.3 Project Teams What is a Project Team? What are the unique features that make project teams different from other teams? “A project team is a team whose members and participants usually belong to different departments and institutes and are assigned to join the same project” (Jafari Navimipour & Charband, 2016, p. 731). Over the span of a project, participants come with different knowledge base, experience, and expertise to achieve a common overall goal (Dasí et al., 2021; Jafari Navimipour & Charband, 2016). Project teams have also been defined as groups with high specialization and low external integration (Sundstrom et al., 1990). On the other hand, Cohen & Bailey (1997) argued that external communication was a differentiating factor for project teams when compared with other work teams. They further elaborated on functional diversity and shared team understanding directly affect the performance of a project team. With the ever increasing and continuously changing 21st century, project teams play a crucial role in contemporary organizations as they are flexible in nature that promote expertise sharing and knowledge building (Zhou et al., 2017). Jafari Navimipour & Charband (2016) studies knowledge sharing within project teams based on the following parameters: Culture, learning, creativity, knowledge management, organizational climate, knowledge exchange, the development of close relationships, performance, trust, communication quality, job satisfaction, attitude toward knowledge sharing, tacit knowledge sharing, and rewards. 7 Within the literature focusing on project teams, several variables have been explored which in- clude: 1. Team Composition: The composition of project teams, including the diversity of skills, knowledge, and expertise among team members, are related to team performance and success (Belout & Gauvreau, 2004). Multiple studies have examined key factors such as team size, team member roles, and the balance between specialists and generalists within the team. 2. Communication and collaboration: Effective communication and collaboration are critical factors for successful project teams. Some important variables studied related to communica- tion and collaborations are communication patterns, information sharing, coordination mech- anisms, and the use of collaborative technologies and innovation within project teams (Caniëls et al., 2019; Kleinsmann & Valkenburg, 2005). 3. Leadership: Leadership plays a vital role in driving guidance and motivation within project teams. Studies have examined the impact of factors like leadership styles, leadership behaviors, and the role of project managers on team success. (Aryee et al., 2012; Shenhar & Dvir, 2007). 4. Team Dynamics: Team dynamics includes factors such as team cohesion, trust, conflict man- agement, and decision-making processes, which have been explored as influential variables affecting project team success (Belout & Gauvreau, 2004; Buvik & Rolfsen, 2015). 5. Organizational Support: The support provided by an organization to its project teams can have an impact on project team success. Prior studies have explored factors such as resource availability, organizational culture, project management practices, and multi levels of hierar- chy that exist within an organization (Aryee et al., 2012). 6. Project Planning and Execution: Variables related to project planning and execution include scope, of the project, goal clarity, task scheduling and risk management which have been found to be related to project team success (Pinto & Slevin, 1988; Svejvig & Andersen, 2014). 7. Learning and Knowledge Management: The ability of project teams to learn from experi- ences, share knowledge, and apply lessons learned are key variables related to project team success. This includes variables such as knowledge transfer, learning processes, and knowledge retention within the team (Ahlfänger et al., 2022; Kozlowski & Bell, 2008). It is important to note that the various variables mentioned above vary across different industries based on the nature of the project or research focus of different studies. Project teams exist within 8 different industries such as healthcare, information technology, AEC, human resource develop- ment etc. (Carlson et al., 2018; Greetham & Ippolito, 2018; Hansen, 2006; Iorio & Taylor, 2014). Student vs Authentic Teams: Project teams research has also found its place in the context of student project teams with a focus on skills for future of work related to leadership, team culture, task planning, communication, and time management (Galbraith & Webb, 2013; Presler-Marshall et al., 2022; Weeks & Kelsey, 2007). In response to the industry’s requirement for teamwork skills in the graduates they hire, schools from various disciplines have responded to this need by increas- ing the use of team projects in their curriculum (Druskat & Kayes, 2000). Druskat & Kayes (2000) describe these teams as short-term project teams which comprise of students from diverse back- grounds and skill sets. These short-term project team settings are instrumental in preparing indi- viduals for the workforce. Virtual vs Co-located Teams: The research on co-located versus virtual project teams has been a topic of interest in recent years (Zhang et al., 2018). While co-located teams traditionally refer to teams working in common physical environments/location, virtual teams contain project mem- bers that work remotely and rely on communication technologies to collaborate and deliver pro- jects. Ongoing research on virtual project teams has revealed multiple factors being under explo- ration. Some advantages of virtual teams are that organizations can hire project team members from a diverse pool of talent not limited by geographical constraints (Bell & Kozlowski, 2002). Research on virtual project teams has also led to advancements in collaboration technology. On the other hand, Garro-Abarca et al. (2021) have given useful insights on the ongoing challenges in virtual project teams related to communication, coordination and trust development primarily af- fected by the absence of face-to-face interactions. In addition to virtual and traditional co-located teams, hybrid communication project networks combining elements of both co-located and virtual teams has been explored by project teams seek- ing to make the most of the benefits of both the approaches (Neumayr et al., 2022; Sithambaram et al., 2021). With the post pandemic world switching to hybrid and/or virtual teams (Kinnula et al., 2018; Willermark & Pareto, 2020), the field of scientific research on project teams is going to see an upward trend in more studies on virtual collaboration networks. With the existing project teams literature’s focus on organizational and/or disciplinary project teams within multiple sub-domains or variable related to project team success (Drouin & Sankaran, 9 2017), the literature review explores interorganizational and inter-disciplinary project teams in the AEC industry in the following section. 2.4 Interorganizational Project Teams in the AEC Industry The Architectural, Engineering and Construction (AEC) industry represents a special case of pro- ject teams which are interorganizational and interdisciplinary in nature (Garcia et al., 2021; Korkmaz & Singh, 2012). Garcia et al. (2021) further elaborates that these project teams are formed amongst owner, designer, contractor, and various stakeholders that collaborate to deliver projects related to the built environment. What makes these project teams unique is their tempo- rary nature where collaborators represent multiple organizations, disciplines, and backgrounds and in most cases, have no prior or future work relations with one another (Schexnayder & Fiori, 2021; Solis et al., 2013). In addition to this temporary nature of the inter-organizational and inter- disciplinary AEC teams, with the constant increase in scale and complexity of AEC projects, these project teams struggle to achieve efficient and effective communication to drive project success (Cheung et al., 2013; Senescu et al., 2013; Solis et al., 2013). With multiple factors affecting an AEC project team, trust and motivation play a crucial role in ensuring smooth working relationships, both at an organizational and individual level (Cheung et al., 2013; Rotimi et al., 2016). Marlow et al.(2018) argue that quality triumphs frequency when it comes to communication for project performance. Timely communication has a positive impact on project performance as numerous construction activities are inter-connected and overlap with each other. (Safapour et al., 2019). With several types of communication (e-mail exchange, in- person meetings, project management information systems, phone calls etc.) exhibiting a variety of challenges in the AEC industry, a key research area related to construction productivity has been found to be “improving communication and collaboration between stakeholders” (Q. Chen et al., 2018; Marlow et al., 2018, p. 27). What quality means here is beyond the content of the information or its method of exchange, but it is also about who it is with and how frequent that exchange is at the ongoing stage of a project in the AEC industry. Zhou et al. (2017) identified project team types used in research related to construction, education and information technology industry based on a seven-dimensional scaling model which are as follows: construction project team, CM/GC project team, DB project team, Build Operate Transfer project team, infrastructure project team, megaproject team, construction management team, en- gineering project design team, on-site vs virtual design team, ancient construction project team, 10 multicultural construction project team, geographically dispersed construction project team, BIM- enabled construction team, BIM-enabled construction team, green project team, academic research project team, agile project team and virtual project team. To increase productivity in such interorganizational collaborations, the AEC industry has investi- gated high performance teams that are driven on establishing trust within team members, shared values and goals and open communication lines (Jørgensen, 2018). Communication networks within an AEC project team dynamically evolve during the project with multiple short-term net- works being formed for collaboration depending on the scale and the timeline of task at hand (Garcia et al., 2021). Zhao et al. (2021) further argue that there is an inconsistency between the organization framework and collaboration behavior that exists within AEC project team networks. Chinowsky et al. (2010) states that a team can deliver high performance by focusing on team suc- cess instead of individual goals. He further elaborates on the crucial and innovative role of social network analysis (SNA) model for construction in his research that links to enhancement of project team performance. Social network model has equipped project team research to dig deeper into interdependencies and the various team components (Carter et al., 2015; Kereri & Harper, 2019; Park et al., 2020). Multiple reviews in the past 5 years have had gaps/potential for future research on project teams that involve studying the missing levels of analysis to test out the various mediating variables across project team constructs (Chan et al., 2021; Leiringer & Zhang, 2021). Chan et al. (2021) describes these levels of analysis as the following: individual, sub-team, project team and at the organization level. While these levels exist within a project team, multiple studies have looked at another crucial type that exists with project teams i.e., single team versus multiteam systems (MTSs) (Luciano, DeChurch, et al., 2018). Single vs Multiteam Systems: Within an interorganizational setup, two types of teams can exist, single teams and multiteam systems (MTS) (Shuffler et al., 2015). Shuffler et al. (2015) points out that while both exist within interorganizational setups, the major difference between the two types of team systems is that single teams bring together individuals from different organizations to work on a specific project and multiteam systems involve multiple teams working together in coordina- tion and collaboration with each other. In a multiteam system, there are multiple teams within a project team, each working on their own goals and responsibilities that have certain connections 11 and interdependencies (Asencio & DeChurch, 2017). These teams work together in order to achieve an overarching goal/objective. The key differences between single versus multiteam systems within an interorganizational setup are as follows: 1. Structure: Single teams typically have a single team leader or project manager responsible for overseeing the team’s activities. In contrast, multiteam systems often have more com- plex structures with multiple leaders or managers who coordinate and facilitate effective collaborations across teams (Asencio & DeChurch, 2017; Garcia et al., 2021). 2. Interdependence and complexity: Single teams might collaborate with other teams within a project team, but their primary focus is on their project or goal and is not dependent on the success of other teams. On the other hand, teams within multiteam systems are highly interdependent and depend on each other for project team success. Multiteam systems are more complex than single teams as managing and coordinating multiple teams with differ- ent goals, dynamics, and organizational cultures requires additional attention to communi- cation, collaboration, and team alignment (Garcia et al., 2021). 3. Duration: Single teams within interorganizational setups are often formed for a specific project or a period of time. Once the project is completed, the team may dissolve or recon- figure for new projects. Multiteam systems, on the other hand, can be more long-term and persistent, as they involve ongoing collaboration and coordination between multiple teams (Shuffler et al., 2015). Diving deep into the existence of the above-mentioned types of teams in the AEC industry, these types of teams are prevalent on different project depending on the stage of the project lifecycle, type of project delivery and scale and complexity of the construction project (Campbell et al., 2022). Single teams are often observed in Design-Bid-Build (DBB) and Design-Build (DB) pro- jects in the AEC industry. Within DBB, single teams are more prevalent during the building phase when the construction firm typically assembles a project team composed of employees, subcon- tractors and potentially representatives from the owner or design firm. Within DB firms, the single team system is prevalent throughout the project lifecycle. The design-build firm forms a cohesive team comprising architects, engineers, construction professionals, and other necessary experts who collaborate throughout the course of the project to ensure construction process alignment with the design intent (Baiden et al., 2006). 12 Multiteam systems (MTS) are often observed in large and complex AEC projects that demand multiple teams to collaborate and coordinate in order to achieve the project’s objectives. A few examples of such projects are: (a) Mega construction projects; (b) Public-private-partnerships; (c) complex renovation or retrofit project and (d) large-scale infrastructure project. Level of Analysis: In the context of interorganizational AEC project teams, multiple studies have examined different levels of analysis to understand the dynamics and functioning of interorgani- zational setups (Ahola, 2018; Manata et al., 2018). Chan et al. (2021) describes these levels of analysis as the following: individual, sub-team, project team and at the organization level. 1. Individual Level: This level of analysis focuses on understanding the characteristics, be- haviors, and attributes of individual team members within a project team. The individual level factors that have been explored in past research are individual skills, attitudes, moti- vation, and personality traits that have been found to have a direct impact on team perfor- mance and collaboration (Ahearne et al., 2015; Garcia & Mollaoglu, 2020). 2. Sub-Team Level: This level of analysis focuses on studying the dynamics and communi- cation networks within smaller units or sub-teams that exist within the larger interorgani- zational project team. In AEC project, an example of a sub-team would be defined based on function or disciplines like architectural design, structural engineering, MEP etc., (Baiden et al., 2006). 3. Project Team Level: This level involves the overall functioning, performance, and project outcomes of the project teams. Past studies have studied multiple variables related to pro- ject team constructs that include team coordination, team decision making, conflict man- agement, team communication, team effectiveness etc., (Buvik & Rolfsen, 2015; Jafari Navimipour & Charband, 2016). While multiple researchers have looked at AEC interorganizational project teams, their place within the existing literature on project team settings is still limited and project teams literature focus has largely been on organizational teams and/or disciplinary teams. Hence, there exists an established need to study the state of research of interorganizational and interdisciplinary project teams within the AEC industry and find a methodology to derive future research di- rections/propositions in this area. 13 2.5 Literature Review Methodologies Bibliometric Analysis and Scoping Review Multiple methodologies exist out there that aim to study existing research in order to derive future research areas within a field of research (C. Chen & Song, 2019). A quantitative method used to examine patterns of publications and citations within a specific field or research area is called bibliometric analysis. Multiple review articles of the past have adopted this method of analysis (Cancino et al., 2017; Nobanee et al., 2021). It involves the collection and analysis of bibliographic data, such as the number of publications, authors, journals, and citations. Bibliometric analysis helps identify influential authors, journals, and research trends within a particular discipline. It often involves analyzing citation patterns, co-authorship networks, and keyword analysis to assess the visibility, influence, and collaboration within a specific field of research (Cancino et al., 2017; Nobanee et al., 2021). Further exploration of teams and project teams literature indicates that scoping review as a research methodology has proved effective in the past two decades in determining future research directions for advancement of various aspects of research on project teams (Kereri & Harper, 2019; Mathieu et al., 2019; Park et al., 2020). A scoping review is a systematic and comprehensive method used to map and summarize research findings on a specific topic Pham et al. (2014). It involves identi- fying and screening a large number of studies to provide an overview of existing literature. C. Chen & Song (2019) mention that scoping reviews can be helpful in identifying gaps in knowledge, defining research questions, and informing the design of future studies. 2 types of literature re- views exist: traditional (non-systematic) and systematic (Ahola, 2018). Ahola (2018) elaborates that the scoping review process in systematic literature review is transparent by each step of the search process in detail which include the journal database, keywords searched for, reasoning for including or excluding publications and the methods used to analysis the final sample. Scoping review as a research methodology in combination with bibliometrics analysis has become a noted approach for analyzing research areas and provides research evidence (C. Chen & Song, 2019; Engebø et al., 2020; Pham et al., 2014). These methodologies are broadly connected through citation network analysis driven by social network analysis (SNA) theory (Carter et al., 2015). Citation network analysis using SNA helps uncover connections, influences, and collaborations within the scientific community by analyzing citation or co-citation patterns and relationships be- tween researchers and publications. 14 Analysis Methods used in Scoping Reviews and Bibliometric Analysis The various methods of analysis identified in prior scoping reviews involving network analysis are as follows: Evolution of publications over time; Co-citation Analysis of Journals; Cluster Analysis; Co-occurrence network of Author Keywords; Country Co-Authorship Network Anal- ysis and Document Citation Network Analysis using SNA. A co-citation analysis of journals maps two documents from different journals that are cited from the same document in a third journal (Cancino et al., 2017). Major research interests in a scientific field can be found in keywords as they capture an incisive description of a research paper (Xu et al., 2022). Xu et al. (2022) mentions that visualizing the keywords in a keyword co-occurrence network (KCN) can offer a good picture of any research domain and helps in understanding the organization and connections between specific research interests over an identified timespan. Radhakrishnan et al. (2017) elaborate that in a KCN, each node represents a keyword, and the links represents the co-occurrence of a pair of keywords. A citation network analysis identifies groups of documents that are connected based on their citation relationships. Using SNA, they analyze the structure of the co-citation relationships to determine clusters of documents that tend to cite each other or are frequently cited together by other documents Past Scoping Reviews within the Project Teams Literature Many scoping reviews of teams literature have been carried out in the past two decades (Kereri & Harper, 2019; Mathieu et al., 2019; Park et al., 2020). Mathieu et al. (2019) in their review of team effectiveness in complex work teams concluded with the following: “Team interventions have matured and demonstrated their efficacy when targeted at different leverage points in team lifecycles and episodic processing and proven valuable for enhancing team effectiveness and human welfare in many industries…Teams are increasingly being conceptualized as dynamic networks of activities that reside in a multilevel context and coevolving with environmental variables. Dynamic theories are being advanced, digital trace measurement protocols are being developed, and innovative research designs and analytic techniques are being implemented.” Kereri & Harper (2019) in their literature review on social networks and construction teams em- phasize on using SNA to identify the collaboration levels in construction project teams using social 15 factors based on real-time data. The social factors include shared goals, independence, open com- munication, trust, shared commitment to working together, shared ac-countability, shared values, and experience (Kereri & Harper, 2019). Zerjav et al. (2023) in their review of project management review articles encourage authors to take up literature review methodology with a focus on micro- level practices within projects, and their teams and leadership. A review of existing project man- agement review articles based on their focus and contributions produced the hierarchy starting from perspectives on project management to project networks to organizations lastly ending at individuals and teams (Zerjav et al., 2023). Scoping/literature reviews have also been performed within the teams' research from a network perspective. Park et al. (2020) in their review on work teams from a network perspective concluded with the following: “…Overall, our review suggests that social networks have a significant impact on teams. We suggested that future scholars should better represent the coevo- lution of network relationships within and between teams, consider the fuzzy boundaries of teams, and model team phenomena in terms of multiplex or mul- tidimensional networks... We believe that continued application of network thinking and methodology to the study teams holds great promise for advancing our understanding of organizational work team functioning and effectiveness.” Limited scoping reviews exist with a focus on interorganizational project teams in the AEC indus- try. Ahola (2018) in their review describe three ideal network types in interorganizational projects: market-based network, dyad-driven network, and integrated core network. They propose a future research area towards exploring different approaches on how the organizational composition is linked to project goal based on both forecasts and actual results. The valuable recommendations of the existing scoping reviews have been embraced by many scholars in assessing the dynamic nature of project teams and its effect on project team perfor- mance. However, scoping review of project teams literature utilizing a citation network anal- ysis (CNA) approach has not been used to find research directions specific to complex AEC interorganizational project teams while also evaluating their place in the larger spectrum of project teams research. (Leppink & Pérez-Fuster, 2019; Mathieu et al., 2019; Park et al., 2020). 16 2.6 Summary In response to the above-mentioned gap, this study aims to conduct a systematic scoping review combined with bibliometric analysis of project teams literature to investigate and advance inter- organizational collaborations within project teams. Such a review can reveal the relations and evo- lution of research on project teams considering key differentiating concepts such as type of indus- try, student versus authentic project teams, virtual versus co-located team settings etc. (Carter et al., 2015; Kereri & Harper, 2019). 17 Chapter 3 METHODOLOGY 3.1 Introduction The main research question directing this study is as follows: What is the state of practice for AEC project teams based on the literature and how has project teams research evolved and is connected across domains? To achieve this goal, the study adopts a scoping review methodology combined with a citation network analysis using SNA of prior research on project team settings across multiple domains (McLaren & Bruner, 2022; Wen et al., 2021). The first step of the systematic literature search was to conduct a preliminary literature search of the existing scoping review articles related to project teams to identify the relevant search strategy. The articles in the list below constitute the result of this search that guided this work’s systematic literature review methodology process: • Carter, Dorothy & Dechurch, Leslie & Braun, Michael & Contractor, Noshir. (2015). Social Network Approaches to Leadership: An Integrative Conceptual Review. The Journal of ap- plied psychology. 100. 10.1037/a0038922. • Jafari Navimipour, N., & Charband, Y. (2016). Knowledge sharing mechanisms and tech- niques in project teams: Literature review, classification, and current trends. Computers in Hu- man Behavior, 62, 730–742. • Leppink, J., & Pérez-Fuster, P. (2019). Social Networks as an Approach to Systematic review. Health Professions Education, 5(3), 218–224 • Mathieu, J. E., Gallagher, P. T., Domingo, M. A., & Klock, E. A. (2019). Embracing Com- plexity: Reviewing the Past Decade of Team Effectiveness Research. Annual Review of Or- ganizational Psychology and Organizational Behavior, 6, 17–46. • Park, S., Grosser, T. J., Roebuck, A. A., & Mathieu, J. E. (2020). Understanding Work Teams from a Network Perspective: A Review and Future Research Directions. Journal of Manage- ment, 46(6), 1002–1028. • Pham MT, Rajić A, Greig JD, Sargeant JM, Papadopoulos A, McEwen SA. A scoping review of scoping reviews: advancing the approach and enhancing the consistency. Res Synth Methods. 2014 Dec;5(4):371-85 18 • Wen, Q.-J., Ren, Z.-J., Lu, H., & Wu, J.-F. (2021). The progress and trend of BIM research: A bibliometrics-based visualization analysis. Automation in Construction, 124, 103558. https://doi.org/10.1016/j.autcon.2021.103558 Following the lessons learned, this chapter is organized in the following subsections: Data Collec- tion, Sample, Data Analysis, Methodology Process Map and Data Quality Measures. The current study’s methods for data collection and analysis are discussed in the subsections hereafter. 3.2 Data Collection The scoping review methodology was conducted using an online citation database called “SCO- PUS” (Carter et al., 2015; Mathieu et al., 2019; Park et al., 2020). The list of references for this study were finalized by combining citation lists through multiple independent systematic search paths (Carter et al., 2015; Mathieu et al., 2019) which are captured in as follows: Search Path 1: Author Search (Pham et al., 2014) One of the starting points for the literature search was through an author search in SCOPUS. With the help of an expert team, the researcher identified key authors who have made contributions to teams and project teams literature. The list of key researchers along with their domain/most con- tributed topics is listed in Table 3.2-1. Table 3.2-1 List of Key Researchers for Author Search Author Domain/Most Contributed Topics Carter D.R. Bibliometric Analysis, Communication Chinowsky P. Construction Industry, Project-based Organizations Contractor N. Communication, Crews, Space Flight Franz T.M. Clinical Teams, Communication Hollenbeck J.R. Leader-Member Exchange, Transformational Leadership Kozlowski S.W.J. Organizational Behavior, Scientific Societies Leicht R.M. Construction Industry, Project-based Organizations Luciano M.M. Delivery of Healthcare, Hospital Organization Mathieu J.E. High Performance Work Systems, Communication Taylor J.E. Zerjav V. Construction Industry, Project Delivery Construction Industry, Project Delivery 19 1. The researcher set the following filters in the SCOPUS database before exporting the citations list: a. Document Type: Article, Review b. Publication Stage: Final (i.e., in process publications were eliminated at this stage) 2. This step filtered the references down to 755 and the citations were exported in a CSV format. 3. The researcher, then, went through the title, keywords, abstracts, and discussions of each pub- lication to filter the publications to those focusing on ‘project team settings.’ The final count after this step was 206. A few examples of publication titles that did not meet the criteria men- tioned in this step are as follows: • “A call for technology developers to apply life cycle and market perspectives when assessing the potential environmental impacts of chemical technology projects.” • “A project sponsor's impact on practice-based learning within projects.” Search Path 2: Article Title, Abstract, Keywords Search (Mathieu et al., 2019) The second starting point for literature search was through “title, keyword, abstract” search in SCOPUS. 1. The researcher input “Project Teams” as the search word. Through this step, the count of ref- erences obtained was 87,603. 2. The researcher then limited the document type to either an article or a review which filtered the references down to 47,551. 3. The next step was to set the publication stage as final (i.e., in process publications were elimi- nated at this stage) which filtered the references to 46,965. 4. In the next step, the researcher did a keyword search of ‘project teams’ or ‘project team’ within the 46,965 references which brought down the references to 656 documents and the citations were exported in a CSV format. 5. The publications which have not been cited at all (i.e., Count under ‘Cited by’ = 0) were re- moved from the list and filtered the references down to 554. Search Path 3: Article Title, Abstract, Keywords Search (Carter et al., 2015): The third starting point for literature search was through “title, keyword, abstract” search in SCO- PUS. 1. The researcher input “Teamwork” as the search word. Through this step, the count of refer- ences obtained was 46,273. 20 2. The researcher then limited the document type to either an article or a review which filtered the references down to 31,966. 3. The next step was to set the publication stage as final (i.e., in process publications were elimi- nated at this stage) which filtered the references to 31,531. 4. The researcher then did a ‘search within documents’ (i.e., searching for project teams within the references found in step 3 of Search Path 3. This step filtered the references to 6,064. 5. In the next step, the researcher did a keyword search of ‘project teams’ or ‘project team’ within the 6,064 references which brought down the references to 107 and the citations were exported in a CSV format. 6. The publications which have not been cited at all (i.e., Count under ‘Cited by’ = 0) were re- moved from the list and filtered the references down to 102. Search Path 4: Article Title, Abstract, Keywords Search within the AEC Literature (Kereri & Harper, 2019) The fourth starting point for literature search was through “title, keyword, abstract” search in SCO- PUS. 1. The researcher input “Project Networks” as the search word. Through this step, the count of references obtained was 1,027. 2. The researcher then put the following filters in order to capture the references from AEC liter- ature as a source: a. Source Title Filter: i. Journal of Construction Engineering and Management ii. Automation in Construction iii. International Journal of Project Management iv. Construction Management and Economics v. Journal of Management in Engineering vi. Engineering Construction and Architectural Management vii. Journal of Computing in Civil Engineering viii. Social Science and Medicine ix. Journal of Environmental Management x. Journal of Civil Engineering and Management xi. IEEE Transactions on Engineering Management 21 xii. International Journal of Managing Projects in Business xiii. Engineering Project Organizations Journal/Conference b. Document Type: Article, Review c. Publication Stage: Final 3. Step 2 of Search Path 4 filtered the references to 154 and the citations were exported in a CSV format. 4. The publications which have not been cited at all (i.e., Count under ‘Cited by’ = 0) were re- moved from the list and filtered the references down to 114. Combining Search Path 2, Search Path 3, and Search Path 4: 1. The list of publications from search path 2, search path 3 and search path 4 were then combined to get a total of 770 publications. 2. The researcher found multiple duplicates (i.e., publications that were found in multiple search paths), kept one of each and removed the duplicate publications. This step filtered the publica- tions to 702. 3. The researcher, then, went through the abstracts and discussions of each publication to limit the search to those focusing on ‘project teams.’ The final count after this step was 586 publi- cations. Combining Search Path 1 (Author Search) with combination of Search Path 3 and Search Path 4: 1. The researcher then combined the final list of publications from Search Path 1 (206 publica- tions) and the final list after combining search paths 2, 3 and 4 (586 publications) to get a total of 718 publications. 2. The researcher found multiple duplicates (i.e., publications that were found in multiple search paths), kept one of each and removed the duplicate publications. This step filtered the publica- tions to 518. To ensure internal validity, the final list of publications was validated by one additional researcher with experience in project teams research by going through all the articles (Kereri & Harper, 2019). At the end of this step, 512 articles remained which became the final sample of this study. The above-mentioned systematic literature search process is depicted in Figure 3.2-1. 22 Figure 3.2-1 Scoping Review Literature Search Process Map 23 3.3 Sample The unit of analysis driving this study are articles and reviews obtained via an open citation data- base called SCOPUS (Leppink & Pérez-Fuster, 2019) with the publications in their final stage. As discussed in the previous sub-section, 512 publications were finalized as the sample for this study which are provided in detail in Appendix A. Appendix A covers the publication title, author, year of publication and cite score. The final list of publications covers all the articles and reviews stud- ying project team settings across different domains. While exporting the citations lists from SCO- PUS, the following information was exported for each publication: Author(s), Author(s) ID, Doc- ument Title, Year, Source Title, Volume, Citation Count, Source & Document Type, Publication Stage, Abstract & Keywords (Author Keywords, Index Keywords) and References. 3.4 Data Analysis This study adopted mixed methods to analyze the sample of 512 publications. In order to explore the trends and evolution of research on project team settings across multiple domains and catego- ries, additional information was extracted from the final list of 512 publications. The author went through the abstract, methods and results section of each of these publications to code for the following 4 categories: • C1: Type of Industry • C2: Virtual vs Co-located Teams • C3: Authentic vs Student Teams • C4: Organizational vs Interorganizational Teams After coding for the above-mentioned categories, the sample was filtered to extract publications specific to the AEC industry and focusing on interorganizational project team setups. This set of publications was further coded by the author based on the following 2 categories: • C5: Single vs Multiteam Systems • C6: Level of Analysis (Individual, Sub-Team, or Project Team) The above-mentioned categories were methodologically identified and refined while performing the literature review in this study. After the initial coding of the sample for all the categories (C1 to C6), data analysis was carried out at 2 levels, L1 and L2. L1: The overall sample of 512 publications based on project team settings across multiple domains was analyzed. It aimed to provide insights into the state-of-practice of project teams connected 24 across multiple domains. It also aimed to derive useful results on the position of research specific to AEC project teams within the broader landscape of project teams. The mixed methods used for this level of analysis are as follows: 1. Evolution over Time Analysis: This analysis involved mapping timeline visualizations of multiple categories on the same graph (for e.g., Type of industry plotted against authentic vs student teams). The timeline visualizations mapped each publication as a node along the timeline, where a second category was assigned as a color to the node and the node size was based on the number of cites received by the publication. 2. Journal Co-citation Analysis: A co-citation analysis of journals covering all the publica- tions was performed. A co-citation analysis of journals maps two documents from different journals that are cited from the same document in a third journal. 3. Country Co-authorship Network Analysis: A co-authorship network of countries de- picts collaborations between various researchers affiliated with institutions in different countries. The network represents collaborations between authors based on their joint pub- lications. 4. Keyword Co-occurrence Network (KCN) Analysis: Major research interests in a scien- tific field can be found in keywords as they capture an incisive description of a research paper (Xu et al., 2022). To dive deeper into the study of project teams, a keyword co- occurrence network (KCN) was constructed using VOSviewer. Subsequently, the network underwent cluster analysis utilizing Citespace, allowing for the identification of research areas associated with the keyword clusters. The KCN gave insights on potential keyword hotspots for future research on project team settings. L2: The sample specific to AEC project teams was analyzed which aimed to gather insights on the evolution and potential future research areas for AEC interorganizational project teams. The mixed methods used for this level of analysis are as follows: 1. Evolution over Time: This analysis involved mapping timeline visualizations of catego- ries C5 and C6 to study the evolution of AEC interorganizational project teams related to single versus multiteam systems and at what level of analysis have the project team settings been analyzed. 2. Citation Network Analysis using SNA: A citation network analysis using SNA (adja- cency matrix) was performed to capture the connected papers within the sample of AEC 25 project teams. Subsequently, the network underwent cluster analysis utilizing Citespace, allowing for the identification of research areas associated with the publication clusters. The clusters were further analyzed in combination with keyword hotspots identified through KCN (in L1 analysis) by analyzing a comprehensive set of connected publications related to the identified research hotspots (Discussed in detail in Section 4.3.2). Data Analysis Tools All analyses was be done using Excel, VOSviewer (Wen et al., 2021) and Citespace (C. Chen & Song, 2019) which are free downloadable open-source software. • VOSviewer is a software to extract bibliometric maps from a database like Web of Science or SCOPUS. The graphical network visualizations created in VOSviewer are based on web links to scientific publications, journals, authors, countries, keywords, or terms based on co-author- ship, co-occurrence, citation, bibliographic coupling, or co-citation (van Eck & Waltman, 2010). VOSviewer was used to perform journal co-citation analysis, country co-authorship analysis, KCN and citation network analysis. • Citespace bases its results primarily on co-citation analysis theory and pathfinder algorithm. It is designed to identify the key intellectual and pivotal points in the research development of a domain (C. Chen & Song, 2019). Citespace was used in this study to conduct co-citation analysis of literature and perform cluster analysis within co-occurrence analysis of keywords and documents citation network analysis. VOSviewer uses the smart local moving algorithm introduced by Waltman and Van Eck in their paper titled "A smart local moving algorithm for large-scale modularity-based community detec- tion" published in 2013. The primary purpose of this algorithm is to detect communities or clusters in networks based on modularity optimization. Modularity is a measure that quantifies the strength of the division of a network into communities. Here's a brief overview of how the smart local moving algorithm works: • Modularity: Modularity (Q) is a key concept in community detection algorithms. It measures the difference between the fraction of edges within communities and the expected fraction of edges that would exist in a random network with the same node degrees. Higher modularity value indicates better-defined communities. • Initialization: The algorithm starts by assigning each node in the network to its own com- munity, creating as many communities as there are nodes. 26 • Local Moving: The algorithm then proceeds through iterations of local moving steps. In each step, it considers moving a node from its current community to one of its neighboring communities. The algorithm evaluates the change in modularity that would result from such a move. If the move would increase modularity, the node is moved to the new com- munity; otherwise, it remains in its current community. • Iterative Improvement: The local moving steps are iterated multiple times, with nodes being considered for moving in a random order during each iteration. This randomness helps to avoid getting stuck in local optima and allows for the exploration of different so- lutions. • Termination: The algorithm continues to perform local moving steps until no further im- provement in modularity can be achieved, or until a predefined number of iterations is reached. • Community Detection: After the algorithm has terminated, the final communities that have been identified are considered as the clusters or communities in the network. The smart local moving algorithm is computationally efficient, making it suitable for large-scale networks that contain a large number of nodes and edges. It often produces meaningful community structures that can be effectively visualized using tools like VOSviewer. Figure 3.5-1 depicts the process map of the research methodology adopted in this study. 27 3.5 Methodology Process Map Figure 3.5-1 Methodology Process Map 28 *C1, C2, C3… represent the labels for multiple categorizations that were done for the publications in the sample *L1 and L2 represent the labels for the two levels at which the analysis was performed Detailed methodology maps for 2 levels of data analysis discussed above i.e., L1 (Figure 4.2-1) and L2 (Figure 4.3-1) are given in Chapter 4. 3.6 Data Quality Measures In order to maintain research quality, several validity and reliability measures were adopted during the study which are as follows: • An open-source database (SCOPUS) was used for the systematic search of references and the final list of publications (Carter et al., 2015; Mathieu et al., 2019); • Thorough documentation of steps for every systematic literature search path to reach the final list of publications (Pham et al., 2014); • Multiple search paths were adopted as a data quality measure to get a comprehensive and reli- able list of final publications as the sample for this study (Mathieu et al., 2019); • A specific search path with a focus on AEC journals (source of reference) was used in order validate the higher-level keyword search paths using “project teams” as the keyword which did not have any filter on the source of reference; • An Author Search was conducted as a search path using identified key authors who have made contributions to teams and project teams' literature to ensure reliability (Pham et al., 2014); • To ensure internal validity, the final list of publications was validated by an additional re- searcher with experience in project teams research (Kereri & Harper, 2019). 29 Chapter 4 RESULTS 4.1 Introduction The main research question directing this research study is as follows: What is the state of practice for AEC project teams based on the literature and how has project teams research evolved and is connected across domains? This chapter covers results from the two levels of analysis performed on the sample. First, the overall sample of 512 publications based on project team settings across multiple domains was studied. It provided insights into the state-of-practice of project teams connected across multiple domains. It also focused on the position of research specific to AEC project teams within the broader landscape of project teams. Second, the sample specific to AEC project teams was studied which gave results related to evolution and potential future research areas for AEC interorganiza- tional project teams. 4.2 State-of-Practice: Project Teams Section 4.2 focuses on the state-of-research on project teams across multiple industries. Figure 4.2-1 describes the methodology followed in this section: 30 Figure 4.2-1 Methods to Results Process Map for Section 4.2 4.2.1 Evolution over Time The unit of analysis driving this study are journal articles and reviews obtained via an open citation database called SCOPUS with the publications in their final stage. As discussed in the previous chapter, 512 publications were finalized as the sample for this study. APPENDIX lists those pub- lications in detail including title and year of publication. The sample of 512 publications was coded based on the following categories: type of industry, virtual vs co-located teams, authentic vs stu- dent teams and organizational vs interorganizational. 31 Organizational versus Interorganizational Project Teams Out of the 512 publications that serve as the sample for this study, 408 publications (79.6%) study organizational project teams, while 104 cover inter-organizational (20.4%) project teams. In Fig- ure 4.2-2, the timeline distribution of publications is depicted with a separation between organiza- tional and interorganizational categorization. Figure 4.2-2 Evolution of Publications relating to Project Teams (Organizational vs Interorgani- zational) Figure 4.2-2 above shows that the study on organizational project teams: • dates back to the year 1974 (Dressler & Nash, 1974) performed for the first time in the healthcare industry; and • has witnessed a steady upward trend since 1994, reaching its peak in 2016. Figure 4.2-2 above also shows that the study on interorganizational project teams: • surfaced for the first time in 1990 (Regensburg & Van Der Veen, 1990) which studied a project team working on a multidisciplinary design project; and • has been relatively limited, yet they have exhibited a notable upward trend from 2009 to 2021. 32 Figure 4.2-3 captures the evolution of publications spread across several types of industries plotted on the y-axis. Each node in the graph represents a publication which is further layered by color (depicting whether the publication studied organizational or interorganizational teams). The node size is dependent on the number of cites received by the publication. Figure 4.2-3 Evolution of Publications 1 (differentiated by multiple categories) The majority of research on interorganizational project teams can be seen with the AEC teams and some in R&D and science and Engineering teams. The blue nodes in Figure 4.2-3 provide evi- dence that reinforces the underlying motivation driving this study. It becomes increasingly appar- ent that there is limited research focused on interorganizational project teams. 33 Authentic versus Student Project Teams Figure 4.2-4 captures the evolution of publications spread across several types of industries plotted on the y-axis. Each node in the graph represents a publication which is further layered by color (depicting whether the publication was studied in authentic or student teams or both). The node size is dependent on the number of cites received by the publication. Figure 4.2-4 Evolution of Publications 2 (differentiated by multiple categories) Figure 4.2-4 above shows that the study on project teams: • were initiated in the healthcare industry and in R&D and science teams; • has been the most consistent in authentic R&D and science teams; 34 • has the most cited articles between the years, 2000 to 2007, most picked up by authentic teams in R&D and science, psychology, information technology and healthcare; • have limited studied involving both authentic and student teams in aerospace engineering, biotechnology, digital marketing, food & beverages, media, online gaming, and transporta- tion; • have only been studied in both authentic and student teams in the same studies in psychology; • have limited studies studying project teams from multiple industries; • have limited studies involving student teams; • related to student teams date back to 1996 (T. W. Porter & Lilly, 1996) where data was col- lected from 80 student teams working on a new product introduction project; and • related to student teams have been mostly covered in courses related to education sciences, engineering, business management and AEC with the greatest number of citations in business management. Virtual vs Co-located Project Teams Figure 4.2-5 captures the evolution of publications spread across several types of industries plotted on the y-axis. Each node in the graph represents a publication which is further layered by color (depicting whether the studied project team was virtual, co-located or both). The node size is de- pendent on the number of cites received by the publication. 35 Figure 4.2-5 Evolution of Publications 3 (differentiated by multiple categories) Figure 4.2-5 above shows that the study on project teams: • related to a hybrid project team was studied for the first time in an AEC project team in 1996 (P. Chinowsky & Goodman, 1996); • related to virtual project teams surfaced for the first time in an AEC project team (Anumba & Duke, 1997) which explores the effective utilization of Internet and intranet technologies within a collaborative communications infrastructure designed for construction project teams; and 36 • have no studies related to virtual project teams in the following industries: Aerospace engi- neering, automotive engineering, environmental engineering, food and beverages, healthcare, manufacturing, non-profit, retail, supply chain management and transportation. Figure 4.2-7 and Figure 4.2-6 capture the trends in the evolution of study of co-located or virtual project teams. Figure 4.2-7 further distributes the sample based on authentic and student teams marked on the y-axis while Figure 4.2-6 does a similar distribution based on organizational and interorganizational teams. The node size is dependent on the number of cites received by the pub- lication. Figure 4.2-6 Evolution over Time (Co-located vs Virtual) based on Interorganizational versus Organizational Figure 4.2-6 shows that research on project teams: • under traditional co-located organizational project teams started back in the day in 1976 and the research peaked between 2008 to 2012; • related to virtual project teams has been explored much more in organizational project teams as compared to interorganizational project teams; and 37 • related to virtual project teams surfaced for the first time in an interorganizational project team (Anumba & Duke, 1997) which explores the effective utilization of Internet and intranet tech- nologies within a collaborative communications infrastructure designed for construction pro- ject teams. Figure 4.2-7 Evolution over Time (Co-located vs Virtual) based on Student versus Authentic Teams Figure 4.2-7 shows that the study on project teams: • • related to co-located teams has existed both in authentic and student teams; and related to virtual project teams has existed mostly for authentic teams but has not been explored much in student project teams. With the post pandemic world switching to hybrid and/or virtual teams (Kinnula et al., 2018; Willermark & Pareto, 2020), we are going to see that changing a lot and hence, there is a need for research of project team settings for virtual student project teams. 4.2.2 Publication Trends in Prominent Journals Using VOSviewer (Cancino et al., 2017), a co-citation analysis of journals covering all the publi- cations in the study sample (n = 512) was performed. A co-citation analysis of journals maps two documents from different journals that are cited from the same document in a third journal 38 (Cancino et al., 2017). The result is shown in Figure 4.2-8. In Figure 4.2-8, node size indicates the importance/relevance of that journal within project teams’ research, using number of citations; while the node color indicates connected clusters of authors in cited work (Van Eck & Waltman, 2010). The co-citation relationships are shown with the lines between the nodes and their thickness shows the total link strength. As seen in Figure 4.2-8, two clusters were found in our study sample. The most significant journals in terms of total link strength and citation frequency in cluster 1, pink color, are International Journal of Project Management, Academy of Management Review and Administrative Science Quarterly. On the other hand, the significant journals from cluster 2, yellow color, are Journal of Applied Psychology and Academy of Management Journal. Figure 4.2-8 Mapping of Journals covering publications on Project Teams (journal co-citation analysis) Table 4.2-1 Top 10 Highly cited journals in Project Teams Research Journal Host Country Citations Journal of Applied Psychology USA 845 Total Link Strength 21588 39 Table 4.2-1 (cont’d) Academy of Management Journal Journal of Management Organizational Science Journal of Organizational Behavior Small Group Research USA USA USA United King- dom USA Academy of Management Review Administrative Science Quarterly International Journal of Project Management United King- USA USA Strategic Management Journal dom United King- dom 689 348 381 232 209 443 395 648 175 18515 10224 9592 7207 5657 12066 10225 10048 5012 Table 4.2-1 shows that among the top ten cited journals seven are published in the USA and the remaining three are in the United Kingdom. This observation highlights the predominant develop- ment of project team research within these journal outlets. The data presented in Table 4.2-1 and Figure 4.2-8 reveals that no single journal emerges as the central journal indicating that multiple journals have had an impact with their contributions to research on project team settings. AEC Project Teams Research A secondary journal co-citation network was extracted from the study sample by filtering for pub- lications related to the AEC Industry which is shown in Figure 4.2-9. 40 Figure 4.2-9 Mapping of Journals covering publications on AEC Project Teams (journal co-cita- tion analysis) Figure 4.2-9 shows that the co-citation analysis identified multiple overlapping clusters that exist within journals related to AEC project teams research. The most significant journals in terms of total link strength and citation frequency in each cluster are: • Red Cluster (Academy of Management Review; Journal of Management; Journal of Applied Psychology): They all belong to the field of organizational behavior, management, and psychology. These journals primarily focus on research related to business and man- agement, organizational theory and behavior, human resource management, project man- agement, social and personality psychology, and related topics. • Blue Cluster (International Journal of Project Management; Journal of Construction Engineering and Management): These journals primarily focus on research related to var- ious aspects of management, organizational behavior, and project management. • Green Cluster (International Journal of Project Management; Automation in Con- struction, Engineering; Construction and Architectural Management): These journals 41 primarily focus on research related to various aspects of construction and project manage- ment, as well as the use of information systems and technology in these domains. • Purple Cluster (Organizational Science; Strategic Management Journal): These jour- nals primarily focus on research related to various aspects of management, strategy, organ- ization, and business policy. • Yellow Cluster (Journal of Construction, Engineering and Management): They all be- long to the field of management, with a specific focus on construction management and project management. The data presented reveals that multiple journals have had an impact with their contributions to research on project team settings in the AEC industry. 4.2.3 Author-based Corporations across Countries Xu et al. (2022) assert that network analysis is a useful tool to identify the countries at the forefront of any scientific research. Furthermore, they suggest that this approach can facilitate the identifi- cation of countries or regions that are likely to be strong partners for research collaborations (Xu et al., 2022). This sub-section looks at author-based country affiliations within research on project team settings based on the study sample of 512 publications. A co-authorship network of countries depicts collaborations between various researchers affiliated with institutions in different countries. The network represents collaborations between authors based on their joint publications (Zyoud & Zyoud, 2021). After constructing the co-authorship network, VOSviewer aggregates the author nodes based on their country affiliations. This step involves grouping authors from the same country into single nodes representing their respective countries. VOSviewer calculates the similarity between each pair of nodes (authors or countries) in the network (Romero & Portillo-Salido, 2019). VOSviewer applies a clustering algorithm to group similar nodes together. Figure 4.2-10 displays a co-authorship network of citing countries where thickness of the link between two countries represents the collaboration strength between them. The node size corre- sponds to the contribution of each node (i.e., bigger the node, bigger the country’s contribution based on co-authorship) (Zyoud & Zyoud, 2021). The node color indicates that the nodes are re- lated to each other within the same cluster (van Eck & Waltman, 2010; Zyoud & Zyoud, 2021). 42 Figure 4.2-10 Collaboration Networks of Countries in Project Teams Research (Based on co-authorship network of countries) Figure 4.2-10 shows that research on project teams: • has the most significant contribution from United States with strong collaboration strengths with People’s Republic of China, Australia, England, and Taiwan; • has People’s Republic of China and Australia in the next top ranks with noteworthy contribu- tions to the field of project teams research; • based on co-authorship network of countries has frequent author-based cooperation seen in the following country pairs: USA & People’s Republic of China, USA & Australia, USA & Neth- erlands, USA & Taiwan, People’s Republic of China & Australia, and People’s Republic of China & England; and • has academic exchanges and collaborations from a wide spectrum of countries. AEC Project Teams Research A secondary co-authorship network was extracted from the study sample by filtering for publica- tions related to the AEC Industry which is shown in Figure 4.2-11. 43 Figure 4.2-11 Collaboration Networks of Countries in Project Teams Research within the AEC Industry (Based on Co-authorship network of Countries) As depicted in Figure 4.2-11, the United States, People's Republic of China, England, and Aus- tralia occupy the top ranks, indicating a considerable number of co-cited research articles in the AEC industry from these collaborations. However, compared to Figure 4.2-10, the visualization network shows limited involvement of other countries. This suggests that there is a need to focus more on expanding author collaborations within current research on project team settings in the AEC industry. 4.2.4 Research Trends based on Author Keywords Major research interests in a scientific field can be found in keywords as they capture an incisive description of a research paper (Xu et al., 2022). Using VOSviewer, a keyword co-occurrence network (KCN) based on the publications studying project teams was constructed as shown in Figure 4.2-12 and Figure 4.2-13 (Radhakrishnan et al., 2017). Radhakrishnan et al. (2017) elaborate that in a KCN, each node represents a keyword, and the links represents the co-occurrence of a pair of keywords. The weight of the link is determined by the 44 frequency of a pair of words co-occurring in multiple articles. Xu et al. (2022) mentions that vis- ualizing the keywords in a network can offer a good picture of any research domain and helps in understanding the connections between specific research interests over an identified timespan. Hence, a KCN gives insights into the cumulative knowledge of a domain of research and can be used to explore existing and upcoming knowledge hotspots based on clustering patterns, link strengths and the spread of the keywords across a given timeline. Figure 4.2-12 Initial Co-occurrence Network of Keywords (Before removing generic keywords such as management, project, project teams) Before the initial KCN was created, identical terms (e.g., project team, project teams, virtual teams, virtual team) were merged (as project teams, virtual teams respectively). The initial co-occurrence network analysis (Figure 4.2-12) of all the author keywords captures generic central keywords like project teams, project management, teams, management, and teamwork validating the primary sample targeting all the publications related to the study of various aspects of project teams. For more accurate clustering of analysis results, the generic keywords were omitted as they do not link to any research trends this study aims to explore (Pham et al., 2014). Figure 4.2-13 demonstrates the updated co-occurrence network of keywords after removing the generic keywords. To ensure a comprehensive coverage of both low and high frequency keywords, a minimum occurrence 45 threshold of 2 was established (Pham et al., 2014). Applying this filter identified a total of 228 keywords, out of which 221 were found to be connected. Project Team Performance Team-Based Approaches in Construction Education and Industry Knowledge Sharing and its impact on Team Performance Factors Affecting Organizational Performance Team Effectiveness Project Team Conflict Management Agile Project Management and Team Development Collaborative Project Management Team Resilience Knowledge Management Figure 4.2-13 Keyword Hotspots in Project Teams Research (co-occurrence network of Author Keywords) 46 Based on the data from the KCN in Figure 4.2-13, the top five author keywords explored the most within research on project teams in the order of their total link strength are knowledge sharing, trust, knowledge management, innovation, and communication. All the five keywords have their average publication years between 2012 and 2015 (Refer to the layered average publication year KCN in APPENDIX B. Using Cite space (C. Chen & Song, 2019), the connected co-occurring keywords depicted in Figure 4.2-13 can be organized into the following 10 clusters: Table 4.2-2 Identified Keyword Cluster based on Keyword Co-occurrence Network Keyword Clus- ter Project Team Performance Focus Area Keywords The cluster captures the factors that contribute to the success of project teams and the chal- lenges that they face in achieving their goals. creative problem solving, project performance, work engagement, creativity, construction project team, transformational leadership, project deliv- ery, structural equation modeling, case study, pro- ject manager, hybrid teams, exploration, exploita- tion, construction projects, engineering, interac- tion, team effectiveness, virtuality, virtual teams, task interdependence, design, organization, con- flict, trust, construction, knowledge, ambidexter- ity, skills, internet, project leadership, uncertainty, staffing, it, action research, information manage- ment, communications Team-Based Approaches in Construction Education and Industry The keywords linked in this cluster are related to various team-based ap- proaches that are used in the construction in- dustry and education, as well as the challenges and outcomes associ- these ap- ated with proaches. systematic literature review, team-based learning, project-based learning, shared leadership, inter- professional, self-efficacy, assessment, civil engi- neering, consultants, project teams, software engi- neering, quality, challenges, industrialized build- ing system (ibs), social networks, multidiscipli- nary, knowledge management, capstone design, team development, project outcomes, relational contracting, social exchange theory, team work- ing, construction teams, virtual work, integration, team, building, construction industry, procure- ment, education, empowerment, supply chain management 47 Table 4.2-2 (cont’d) Knowledge Sharing and its Impact on Team Perfor- mance The cluster captures the factors that contribute to or hinder the effec- of tive sharing knowledge within teams and the impact of knowledge sharing on team performance. Factors Affect- ing Organiza- tional Perfor- mance Team Effec- tiveness Some of the keywords in this group are related to the structural and cul- tural characteristics of organizations and the processes and practices that facilitate or hinder organizational perfor- mance in project-based contexts. The cluster captures the factors that contribute to or hinder the effec- of functioning tive teams. Project Team Conflict Man- agement The cluster captures the factors related to con- flict management Agile Project Management and Team De- velopment This group encom- passes keywords related to project management methodologies as well as team-related con- cepts knowledge hiding, qualitative research, social net- work, team stability, professional development, team performance, cross-functional teams, deci- sion-making, team learning, team learning behav- iors, multiple team membership, individual perfor- mance, project team performance, human factors, knowledge-based systems, learning processes, team processes, team communication, social fac- tors, knowledge acquisition, information systems, developing countries, cohesion, is project teams, user involvement organizational structure, complexity, diversity, contractors, integrated project team, longitudinal case study, culture, networks, productivity, social network analysis, innovation, boundary spanning, interdependence, tacit knowledge, data mining, or- ganizational issues, project networks, agile meth- odology, planning, simulation, globalization, vir- tual organization, steamwork team cohesion, psychological safety, turnover in- tention, team coordination, knowledge leadership, organizational culture, team creativity, ocb, organ- izational citizenship behavior, transactive memory system, virtual team, coaching, learning barriers, emotional intelligence, knowledge diversity, so- cial capital, knowledge creation, learning, multi- disciplinary project teams process conflict, task conflict, conflict manage- ment, cross-functional project teams, decision sup- port systems, project success, structure, relation- ship conflict, teamwork effectiveness, knowledge integration, organizational control, information technology, optimization, multicultural manage- ment, decision making, team building, implemen- tation, systems development development, multi-objective optimization, scrum, team creation, competency, fuzzy sets, ag- ile, team leadership, virtual enterprise, agile pro- ject management, cooperation, team formation, leadership, management, fuzzy log, ict, technol- ogy, motivation, human resource management, virtual reality 48 Table 4.2-2 (cont’d) Collaborative Project Man- agement Team Resili- ence This cluster captures the process of teams work- ing together towards a common goal and the process of information and expertise exchange within a team. This group encom- passes keywords related to team-related con- cepts which are essen- tial for building effec- tive and resilient teams. articulating capacity, common knowledge, virtual project teams, absorptive capacity, integrated pro- ject delivery, integrated project delivery (ipd), co- ordination, knowledge transfer, multiteam sys- tems, communication, virtual projects, collabora- tion, new product development, risk management, team size, virtual project team, team management, resource sharing team resilience, communication norms, global project teams, interpersonal trust, role clarity, group potency, efficiency, effectiveness, perfor- mance, group performance, satisfaction feedback Knowledge Management The cluster captures factors that lead to cre- ating an environment that encourages creat- ing. Sharing and appli- cations of knowledge within an organization. communication performances, project team cul- ture, building information modelling, knowledge sharing, project-based organization, organiza- tional culture, project organization, corporate cul- ture, organizational learning After identifying the clusters formed by the 221 connected keywords, the differentiated keywords were plotted on a timeline as shown in Figure 4.2-14 (based on the data from the layered average publication year KCN in APPENDIX B. The x-axis represents the average publication year of each keyword. Each node represents a key- word, and the color of the node is the keyword cluster (from Figure 4.2-13) it belongs to. The size of each node represents the number of occurrences of each keyword within the sample of 512 publications. 49 Figure 4.2-14 Evolution of Keywords (co-occurrence network of Author Keywords) *Each row depicts the first keyword, the keyword with most occurrences and all the keywords occurring after 2019 in their respective keyword cluster *The dotted line marks the year 2019 highlighting the keywords occurring in the past 4 years Figure 4.2-14 provides insight into the temporal relevance of the identified keywords in the past 25 years of scientific research of project team settings. Within each cluster row in Figure 4.2-14, the first keyword, their last keyword and/or the keywords with their average publication year after 2019 have been labelled next to the node. The keywords with their average publication year after 2019 (as shown in Figure 4.2-14) are low frequency connected keywords that are presently under exploration in the context of project team settings (C. Chen & Song, 2019; Pham et al., 2014). 50 Figure 4.2-15 lists the low frequency keywords, the clusters they belong to and determines the nature of these keyword occurrences based on the following categories: Organizational vs Interor- ganizational Teams, Authentic vs Student Teams, Co-located vs Virtual Teams, AEC vs Non-AEC and Type of Industry. Figure 4.2-15 Keyword Hotspots in Project Team Settings (2019 to 2022 Sample n = 34) The categorization of the keyword hotspots in Figure 4.2-15 highlights several important concepts related to the recent research trends in the studies on project teams. It shows that base on the keyword co-occurrence network, the study on project teams related to: • Virtual authentic teams have a scope to explore keyword hotspots like work engagement, knowledge hiding, psychological safety, task performance, knowledge leadership, articulat- ing capacity, common knowledge, and team resilience which are currently otherwise under exploration in co-located project team settings; 51 • Authentic interorganizational project teams can explore keyword hotspots like creative prob- lem solving, work engagement, psychological safety, turnover intention, team cohesion, or- ganizational structure, articulating capacity, common knowledge, and team resilience; • Student teams has their research hotspots based on the keywords work engagement, turnover intention, task performance, team cohesion and team creativity. These keywords come under two clusters: Project Team Performance and Team Effectiveness; • Student teams have surfaced mostly in courses related to business management and engineer- ing in the last 4 years; and • Virtual student teams have an emerging need for research exploring work engagement and task performance. AEC Interorganizational Project Teams Within the spread of these keywords across multiple industries, keyword hotspots and their re- search clusters can be identified specific to AEC interorganizational project teams. Based on the keyword co-occurrence network in Figure 4.2-15, study on AEC interorganizational project teams can potentially have their research focus around following keyword hotspots: Table 4.2-3 Keyword Hotpot Areas for AEC Interorg. Project Teams (based on KCN) Research Cluster Project Team Performance Project Team Effectiveness Collaborative Project Management Articulating Capacity, Common Knowledge Team Resilience Keyword Hotspots Creative Problem Solving, Work Engagement Psychological Safety, Turnover Intention Team Resilience Section 4.3.2 further explores these keyword hotspots for AEC interorganizational project teams by studying them in relation to identified clusters within the connected publications on AEC pro- ject teams through a citation network analysis. 4.2.5 Summary To capture the evolution of research on project teams and how it is connected across domains, this section covered multiple types of analysis done on the sample. The main findings and research trends/propositions can be summarized as follows: 1. The most cited publications doing research on project team settings lie between the years, 2000 and 2007, and are primarily studying authentic project teams in the fields of R&D 52 and science, psychology, information technology, business management and the AEC in- dustry. 2. Top five author keywords explored the most within project teams research are knowledge sharing, trust, knowledge management, innovation, and communication with all of them having their average publication year between 2012 and 2015. 3. Research on interorganizational project team settings has received limited attention but show an upward trend in the past decade. It has been explored the most in the AEC industry followed by its limited presence in R&D and Science and Engineering teams. 4. Research on student teams has been limited with notable exceptions in courses related to business management and engineering. Therefore, future research should aim to broaden their scope to academic fields related to other industries. 5. Research on virtual project teams has limited studies within interorganizational setups and within the spectrum of student teams. Future research should prioritize exploring these settings further. 6. The research gap regarding virtual project teams is particularly evident in industries like automotive engineering, non-profits, and environmental engineering. 7. Future investigations on virtual project teams can focus on variables related to work en- gagement, knowledge hiding, psychological safety, task performance, knowledge leader- ship and team resilience. 8. Analysis of author-based country co-authorship networks highlights the need to enhance global collaborations among researchers studying project team settings in the AEC indus- try. 9. Recent research trends, based on keyword analysis over the past four years, have primarily focused on AEC industry, Business Management, and Information Technology. 10. There is potential for investigating specific research keyword hotspots related to AEC in- terorganizational project teams. Research areas such as collaborative project manage- ment and team resilience offer avenues for exploration. Relevant keywords include Team Resilience, Articulating Capacity, Common Knowledge, Psychological Safety, Turnover Intention, Creative Problem Solving, and Work Engagement. The key findings and their applications are further discussed in Chapter 5. 53 4.3 State-of-Practice and Future Research Areas: AEC Project Teams Section 4.2 focused on the state-of-research on project teams across multiple industries and also looked at the position of research specific to the AEC industry within the broader landscape of project teams. This section looks at the sample specific to AEC project teams. Figure 4.3-1 de- scribes the methodology followed in this section: Figure 4.3-1 Methods to Results Process Map for Section 4.3 54 4.3.1 Evolution over Time Single vs Multiteam Systems and Level of Analysis Multiple reviews in the past 5 years have had gaps/potential for future research on project teams that involve studying the missing levels of analysis to test out the various mediating variables across project team constructs (Chan et al., 2021; Leiringer & Zhang, 2021). Chan et al. (2021) describes these levels of analysis as the following: individual, sub-team, project team and at the organization level. While these levels exist within a project team, multiple studies have looked at another crucial type that exists with project teams i.e., single team versus multiteam systems (MTSs) (Luciano, DeChurch, et al., 2018). Hence, 85 publications on interorganizational project teams in the AEC industry were coded based on the categorization of single versus multiteam systems and further coded based on the level of analysis conducted in each study. Within the publications studying AEC project teams, 85 publications look at interorganizational project team settings. Figure 4.3-2 captures the evolution of the 85 publications spread across the publications years plotted on the x-axis. Each node in the graph represents a publication which is further layered by color depicting whether the publication studied the project team settings at an individual level, sub-team level, project team level or a combination of the three. The node size is dependent on the number of cites received by the publication. 55 Figure 4.3-2 Evolution of Publications related to AEC Interorganizational Project Teams (categorized by Single vs Multiteam Systems and Level of Analysis) Figure 4.3-2 depicts the study on AEC interorganizational project teams, highlighting noteworthy observations: • The majority of research on interorganizational AEC project teams has been explored in single team systems at the project team level; • The exploration on multiteam systems within AEC interorganizational project team settings emerged in the last fifteen years; • Within the study on multiteam systems, significant emphasis has been given to project team constructs at the project team level, as well as a combination of individual and project team levels; • The exploration of studies in interorganizational setups analyzing project teams at all the three level of analysis i.e., individual, sub-team and project team level is limited; and 56 • Limited attention has been given to studying interrelated project networks at the sub-team level. Hence, future research holds immense potential in focusing on sub-teams as a valuable level of analysis. 4.3.2 Future Research Areas based on Citation Network Analysis Using VOSviewer, a citation network analysis was performed on the publications related to the AEC industry (n=117) as shown in Figure 4.3-3. A citation network analysis in VOSviewer iden- tifies groups of documents that are connected based on their citation relationships. The algorithms in VOSviewer analyze the structure of the co-citation network to determine clusters of documents that tend to cite each other or are frequently cited together by other documents (Radhakrishnan et al., 2017). The node color indicates connected clusters of publications in cited work (Van Eck & Waltman, 2010) and the thickness of the links shows the total link strength. 68 connected publica- tions were found, and 10 clusters were identified. 57 Cluster Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Color N Cluster Color N 5 4 3 3 2 12 Cluster 6 12 Cluster 7 11 Cluster 8 9 Cluster 9 7 Cluster 10 Figure 4.3-3 Citation Network Analysis of Publications on AEC Project Teams Table 4.3-1 covers the various clusters identified in the citation network (Figure 4.3-3) of con- nected publications (n = 68) and identifies the common research focus for each cluster. It can be noted that due to the interconnectedness of the clusters, there are certain overlaps in the research focus. 58 Table 4.3-1 Clusters of publications on AEC Project Teams (based on CNA) Research Focus Cluster Cluster 1 The common theme of the publications is project management and collaboration networks within project teams. These publications explore various aspects of pro- ject networks, interdependencies, effectiveness, organizational structures, knowledge transfer, collaboration, and project team dynamics. Cluster 2 The common theme of the publications is trust development and group resilience within project team settings. The publications explore topics such as team perfor- mance, trust development, knowledge sharing, team member selection, innovation, group resilience, leadership, team learning, coordination, and knowledge sharing within project-based organizations. Cluster 3 The common theme of the cluster is the study of communication and conflict man- agement within AEC project teams. These publications mostly adopt case studies as their research method particularly in the context Sri Lanka, Australia, and China. The various research focus includes the role of communication in hybrid arrange- ments, emotional intelligence and performance, intragroup conflicts, support and commitment factors and communication management. The publications aim to pro- vide insights and strategies for improving communication effectiveness, teamwork, conflict resolution, and overall project success within the construction industry. Cluster 4 The common theme of the publications is knowledge sharing within AEC project teams. These publications focus on understanding and exploring various aspects of knowledge sharing, including the modes of interaction (technology-based vs. face- to-face), knowledge-sharing strategies, and behavior related to knowledge sharing within project teams. The publications aim to shed light on the dynamics, chal- lenges, and factors influencing knowledge sharing among team members in project- based settings, with a focus on improving knowledge management and collabora- tion for better project outcomes. Cluster 5 The common theme of the publications is how project teams can effectively collab- orate, communicate, and implement innovation in complex engineering projects, with a particular emphasis on virtual teams, geographically dispersed teams, and IPD projects in the AEC industry. Cluster 6 The common theme of the publications is the impact of organizational perfor- mance on the success of AEC project teams. These publications explore various aspects of project team management, including organizational groupings, horizontal leader identification, project member assignment strategies, and the influence of project managers. The focus is on understanding the relationship between project team dynamics, perceived justice, turnover intentions, goal feedback, recognition, and performance success within project-based organizations. 59 Table 4.3-1 (cont’d) Cluster 7 The common theme of the publications is learning and knowledge management within AEC project teams. These publications focus on various aspects of fostering learning, improving relationships, assembling integrated project teams, and linking individual, team, and organizational learning. The publications aim to provide in- sights and strategies for improving learning processes, collaboration, and overall project performance within AEC project team settings. Cluster 8 The common theme of the publications is the performance of integrated project teams in the AEC industry. These publications explore various aspects related to the effectiveness and performance of integrated project teams in various stages of the project lifecycle. The focus is on understanding the factors that influence the performance of integrated project teams, including the early design stages, collabo- rative procurement approaches, and the management of unexpected change events. Cluster 9 The common theme of the publications is trust measurement and perceived level of virtuality in hybrid construction project teams. The common theme explored is the analysis and investigation of factors, dynamics, and challenges that impact communication and virtuality in diverse settings. The common theme of the publications is the examination of the relationship be- tween psychological factors related to team dynamics within project teams. The publications explore the influence of individual-level psychological factors, such as stress and anxiety, on team processes and outcomes within AEC project teams. Cluster 10 The clusters identified in Table 4.3-1 were further plotted on a graph to see the distribution of the connected publications within each cluster based on the following categories: • Single vs Multiteam Systems; • Level of Analysis (Individual, Sub-Team, or Project Level); and • Virtual vs Co-located Teams. 60 Figure 4.3-4 Categorization of clusters identified within connected publications on AEC project teams based on citation network analysis) *The empty boxes indicate that these publications are limited to organizational aspects within AEC project teams The categorization of the clusters identified within connected publications on AEC project teams in Figure 4.3-4 highlights several important trends related to interorganizational project team set- tings in the AEC industry. It shows that the study on AEC interorganizational project teams: • has potential for future research to focus on learning and knowledge management, perfor- mance of integrated project teams, trust measurement and perceived level of virtuality and psychological factors related to team dynamics; 61 • related to multiteam systems has been explored the most in research areas like IPD Projects and Project Management and Collaboration Networks; • related to sub-team level of analysis has been explored the most in research related to the per- formance of integrated project teams and project management collaboration networks; and • related to virtual project networks has potential in the research areas: knowledge sharing within project teams and trust development and group resilience. Within the clusters of connected publications studying AEC project team settings, it is evident that multiple publications within each cluster primarily focus on team dynamics within organizational boundaries. Hence, there rises a clear need for future expansion of research related to interorgani- zational setups and multiteam systems in the AEC industry. Potential Research Hotspots Each identified cluster specified crucial connected papers in related literature (Nobanee et al., 2021). Utilizing these clusters, the study examined the intersection of research areas alongside our findings in keyword research hotspots, primarily focusing on two key areas: Team Resilience & Stability and Collaborative Project Management Networks. Next 2 sub-sections look at the rele- vant publications related to each of the above-mentioned research hotspots. The list of the relevant samples was collected through a combination of publications list obtained from Keyword Co-oc- currence Network in Section 4.2.4 and the clusters identified in Figure 4.3-3 which are closely related to the research hotspot. For each research hotspot, the relevant publications were explored in detail based on the following: Author, Publication Title, Research Focus, Level of Analysis, Project Type, Methods, Key Find- ings and Gap/Potential for Future Research (Chan et al., 2021; Leiringer & Zhang, 2021). The gaps/potential for future research identified for each research hotspots were then combined and converted into agendas for future research recommendations/propositions. Team Resilience and Stability A comprehensive list of publications centered around keyword hotspots related to team resilience was created (Table 4.3-2) using a combination of two primary clusters identified through citation network analysis: cluster 2 and cluster 10 from Table 4.3-1. Cluster 2 focuses on trust development and group resilience, examining the dynamics and factors that contribute to the resilience of teams. Cluster 10 studies the relationship between psychological factors and team dynamics, giving in- sights on how various psychological elements influence the overall performance and resilience of 62 teams. Hence, this sub-section aims to offer agendas for future research related to team resilience and its implications in AEC interorganizational project teams. Table 4.3-2 Sample Publications - Team Resilience and Stability Author Publication (cite score) Focus Level of Analy- sis; Project Type; Methods Key Find- ings Gap/Potential for Future Research Wei M., Hao S., Ren X. (2022) Non-spatial proximity and project team resili- ence: the role of knowledge sharing and team cohe- sion (3) Influence of team compo- sition on pro- ject team re- silience based on proximity and explores the role of knowledge sharing and team cohe- sion in their relationship. Project Team; Construction Projects in China; Cross- sectional Survey Value prox- imity, social proximity, knowledge sharing, and team cohe- sion have a positive in- fluence on project team resilience. Carry out a longitudinal survey to measure pro- ject team resil- ience; explore more mediat- ing variables like collective potency and team psycho- logical safety. Individual; Con- struction Pro- jects in Chile; Cross-sectional Survey Pavez I., Gómez H., Laulié L., González V.A. (2021) Project team resilience: The effect of group po- tency and interper- sonal trust (10) Testing a model in which inter- personal trust group po- tency drive the percep- tion of team resilience in project team members. Carry out a longitudinal survey to measure pro- ject team resil- ience; test pro- ject team resil- ience for team- level out- comes. Affect- based trust and group potency me- diate the re- lationship between cognition- based trust and project team resili- ence. 63 Table 4.3-2 (cont’d) Building high-per- forming and integrated project teams (9) Ahiaga- Dagbui D.D., Tokede O., Morrison J., Chirn- side A. (2020) Buvik M.P., Tvedt S.D. (2017) Savels- bergh C.M.J.H., Poell R.F., van der Heijden B.I.J.M. (2015) The influ- ence of pro- ject com- mitment and team com- mitment on the relation- ship be- tween trust and knowledge sharing in project teams (43) Does team stability me- diate the re- lationship between leadership and team learning? an empirical study among dutch pro- ject teams (36) Individual and Project Team; Water Supply Upgrade Project in Australia; Case study (tri- angulated data sources) Studies the effectiveness and limita- tions of a project facili- tation model as a tool for developing successful in- ter-organiza- tional rela- tionships Individual and Project Team; Construction Projects in Nor- way; Medication Analysis To test how trust directly and indirectly affects knowledge sharing in AEC project teams Influence of leadership on team learning behaviors with team stability as a potential me- diator Project Team; Building and utilities, Infra- structure, Area Decontamina- tion, and devel- opment; Cross- sectional Survey Further studies need to explore characteristics, experience, and profile for project facilita- tor to ensure maximum suc- cess; empirical studies need to be done to de- fine the types of projects that would benefit from a facilita- tion model Consider mul- tilevel nature of project teams for fu- ture analysis; Carry out a longitudinal survey to cap- ture the dy- namic nature of trust, com- mitment, and knowledge sharing Examine whether the leadership be- haviors that promote team learning vary over time de- pending on the project phase Results in- dicate that facilitated workshops positively affect team perfor- mance by sustaining best for practice principles and psycho- logical safety In the con- text of pro- ject teams, project commit- ment is more im- portant for knowledge sharing than team com- mitment. Both per- son-oriented and task- oriented leadership were found to be posi- tively re- lated to team learn- ing behav- iors in pro- ject teams 64 Table 4.3-2 (cont’d) Buvik M.P., Rolfsen M. (2015) Individual and Project Team; School Con- struction Project in Norway; Sin- gle case study Influence of prior ties be- tween team members in- fluence trust development with a project team Prior ties and trust de- velopment in project teams - a case study from the construction industry (111) Positive prior ties enhance a higher level of trust and create good conditions for the ini- tial phase of a construc- tion project Future research should explore negative prior experiences’ effect on the project; Also include expec- tations of team members re- lated to future interactions when studying trust develop- ment The analysis done in Table 4.3-2 allows for a number of observations: • The majority of the research on aspects of team resilience and stability is based on cross-sec- tional surveys or qualitative case studies conducted on single projects; • There are relatively limited studies that measure team resilience through a facilitation model for building psychological safety in inter-organizational setups; • Recognizing the multilevel nature of project teams, future research can investigate the dynam- ics of trust, commitment, and team stability across different level within the project team struc- ture and capture this analysis over a longitudinal study which can provide insights on how these factors evolver over time; • Multiple publications suggest conducting further studies through longitudinal studies to cap- ture factors like future team member expectations (Buvik & Rolfsen, 2015), the dynamic na- ture of trust and commitment (Buvik & Tvedt, 2017) and effect of variables like psychological safety on team resilience (Wei et al., 2022); and • While recommendations to conduct further studies through longitudinal studies are common, such recommendations are still majorly unaddressed. Project Management Collaboration Networks A comprehensive list of publications centered around keyword hotspots related to collaborative project management networks was created (Table 4.3-2) using a combination of three primary clusters identified through citation network analysis: cluster 1 (Project Management Collaboration Networks), cluster 4 (Knowledge Sharing within AEC project teams) and cluster 8 (Performance 65 of Integrated Project Teams) given in Table 4.3-1. Cluster 1 focuses on project management and collaboration networks within project teams. These publications explore different aspects of pro- ject networks, interdependencies, knowledge transfer, collaboration, and project team dynamics. The publications in cluster 4 explore various aspects of knowledge sharing, including the modes of interaction (technology-based vs. face-to-face), knowledge-sharing strategies, and behavior re- lated to knowledge sharing within project teams. Cluster 8 covers publications related to the effec- tiveness and performance of integrated project teams in various stages of the project lifecycle. Table 4.3-3 Sample Publications - Project Management Collaboration Networks Level of Analysis, Project Type, Meth- ods Individual, Project Team; Multi- ple construc- tion and in- frastructure projects; Cross-sec- tional Survey Individual, Sub-Team, Project Team; An AEC project team work- ing on an in- stitutional project; Mixed meth- ods Key Find- ings Individual learning has a positive impact on both internal and external team learn- ing. Project managers can promote core-periph- ery struc- tures to help in project team coordi- nation at the earliest stages of de- sign Gap/Poten- tial for Fu- ture Re- search Future studies can look at the missing variables like leadership and task/project complexity linked to mul- tiple project team member- ship Explore the network dy- namics in complex in- terorganiza- tional AEC teams consid- ering different modalities, in- teraction qual- ity, project delivery method and phases of con- struction Author Publication Focus Chan, Kai-Ying & Oer- lemans, Leon & Meslec, Nicoleta. (2021) The impact of multiple project team member- ship on individ- ual and team learning: A mi- cro-meso multi- level empirical study Research aims to study the ef- fect of multiple project team membership on individual and team learning. Garcia A.J., Mollaoglu S., Frank K.A., Duva M., Zhao D. (2021) Emergence and evolution of net- work structures in complex in- terorganiza- tional project teams To study how temporary knowledge transfer net- works within AEC project teams evolve during the pro- ject delivery stage and adopt structure dif- ferent and in- dependent from each other 66 Table 4.3-3 (cont’d) Joseph Garcia A., Mollaoglu S. (2020) Individuals' Ca- pacities to Ap- ply Transferred Knowledge in AEC Project Teams Garcia A.J., Mollaoglu S. (2020) Measuring Key Knowledge-Re- lated Factors for Individuals in AEC Project Teams This study fo- cuses on the key knowledge-re- lated factors that affect the individuals to apply that knowledge transferred to them in project teams in the AEC industry. Individual level; An IPD large scale con- struction project; Multiple re- gression model on a longitudinal project This study aims to identify essential indi- vidual-level knowledge-re- lated factors and develop in- dicators to measure them. Individual level; An IPD con- struction project; Sur- vey collec- tion The way in- dividuals in a project team absorb the knowledge transferred to them is directly re- lated to the articulating capacity of the knowledge sender The study confirmed the validity and reliabil- ity of the in- dicators to measure in- dividual- level knowledge- related fac- tors which are knowledge application, absorptive capacity, common knowledge, and articu- lating ca- pacity Explore where to put individuals with high ab- sorptive and articulating capacity a project team structure; Uti- lize the find- ings in inter- organizational project teams in other indus- tries Future re- search to per- form struc- tural equation modeling or multilinear re- gression with the measure- ment model and use knowledge application as a dependent variable; the measurement model to be tested in pro- jects of differ- ent sizes and other delivery methods 67 Table 4.3-3 (cont’d) Ni Guodong, Cui Qing- bin, Sang Linhua, Wang Wenshun, Xia Dongchun (2017) Knowledge- sharing, cul- ture, project- team interac- tion, and knowledge- sharing perfor- mance among project members Zelkowicz A., Iorio J., Taylor J.E., Via C.E. (2015) Exploring the role of cultural boundary span- ners at complex boundaries in global virtual AEC networks Solis F., Sinfield J.V., Abraham D.M. (2013) Hybrid ap- proach to the study of inter- organization high perfor- mance teams To explore a mechanism to improve knowledge- sharing perfor- mance with a focus on knowledge sharing culture (KSCu) and project-team interaction (PTI) Project Team Level; 78 Chinese AEC Engi- neering Management organiza- tions; Cross- sectional sur- vey and structural equation modelling To test the effi- cacy of cultural boundary span- ners placed at a knowledge and technical boundary do- main for im- proving net- work perfor- mance Study of hybrid methodology using network theory and jobs-to-be- done frame- work for high performance teams. Individual and Project Team level; Global Vir- tual Project Networks among grad- uate across the globe; longitudinal study using SNA and Team Re- cordings Individual and Project Team level; healthcare construction project; Sin- gle case study (SNA Metrics) Future re- search needs to focus on in- dividual be- havioural fac- tors such as knowledge- sharing atti- tude, willing- ness, and mo- tivation The model of testing cul- tural bound- ary spanners needs to be tested on au- thentic project teams on complex vir- tual interor- ganizational projects Lack of appli- cation of structured in- terviews, sur- veys, and lon- gitudinal sur- veys to judge the effective- ness of the SNA metrics There exists a positive relationship between KSCu and knowledge- sharing per- formance; PTI plays a factor in the effect of KSCu on knowledge- sharing per- formance Interactions in a network based on cultural spanners have a nega- tive impact the effi- ciency of knowledge transfer in virtual pro- ject net- works SNA met- rics with problem solving frameworks can generate comprehen- sive insights for compo- sition and team perfor- mance of HPTs The analysis done in Table 4.3-3 allows for a number of observations: 68 • Additional studies need to be conducted in multicultural contexts to better understand the im- pact of cultural diversity within interorganizational collaboration networks; • Further exploration is needed to study collaboration networks in the context of multiple project team memberships and consider variables like project/task complexity along with possible as- sociations with knowledge-related factors; • Studies on integrated project teams and multiteam systems can be seen in the context of IPD (Integrated Project Delivery). Multiple studies (Engebø et al., 2020; Garcia & Mollaoglu, 2020) suggest testing the various models related to knowledge sharing and collaboration net- works within different project delivery methods (for e.g., Design-Bid-Build, Design-Build); • Emphasis needs to be placed on investigating collaboration networks through longitudinal case studies of inter-organizational project teams on complex projects; • Future research can consider exploring project team network dynamics considering factors like communication modalities, interaction quality, and phase of the project; and • In order to ensure generalizability of the ever-evolving findings on collaborations networks in AEC project teams, it is essential to test the various project team network models on interor- ganizational teams in industries beyond the AEC industry. 4.3.3 Summary To capture the evolution of research and future research areas for AEC interorganizational project teams, this section covered multiple types of analysis done on the sample of 117 publications based on AEC project teams. The main findings and research trends/propositions can be summarized as follows: 1. The majority of research on AEC interorganizational project teams focuses on single team systems with findings at the project team level. 2. Research on AEC interorganizational project team setups has been limited in examining all three levels of analysis: individual, sub-team and project team levels. 3. Future research should address the exploration of interrelated project networks within AEC interorganizational project teams, particularly at the sub-team level. 4. The majority of the research focused on multiteam systems within AEC interorganizational teams are found in the research domains of IPD Projects and integrated project team col- laboration networks. 69 5. Through citation network analysis of interconnected papers, several potential research ar- eas for AEC interorganizational project teams have emerged. These include learning and knowledge management, integrated project team performance, measurement of trust, per- ception of virtuality, and psychological factors influencing team dynamics. 6. Within AEC interorganizational project teams, research on virtual project collaboration networks presents future research opportunities for investigating knowledge sharing among project teams, as well as the development of trust and group resilience. 7. Limited studies have examined the measure of team resilience through a facilitation model for building psychological safety in interorganizational setups. 8. Acknowledging the multilevel nature of project teams, future research should explore the dynamics of trust, commitment, and team stability across different levels within the project team structure. Longitudinal studies can provide valuable insights into how these factors evolve over time. 9. To gain a better understanding of the impact of cultural diversity within interorganizational collaboration networks, additional studies need to be conducted in multicultural contexts. 10. Additional research is needed to examine collaboration networks within the context of mul- tiple project team memberships. This investigation should consider variables like pro- ject/task complexity and explore potential associations with knowledge-related factors. 11. In order to ensure the generalizability of findings on collaboration networks in AEC project teams, which are continually evolving, it is crucial to test the various project team network models on interorganizational teams in industries beyond the AEC industry. The key findings and their applications are further discussed in Chapter 5. 70 Chapter 5 DISCUSSION AND CONCLUSION 5.1 Introduction In this chapter, the author presents the summary of findings and then discusses their implications and applications in the domain of research on project teams. The author also highlights the research deliverables accomplished in this study. The chapter is concluded by presenting limitations to this study and a recommendation for future studies of a similar nature. 5.2 Summary of Findings This section talks about the key findings found at two levels of results in the study: (a) state-of- practice for project teams and (b) state-of-practice and future research areas for AEC interorgani- zational project teams. State-of-Practice: Project Teams The main findings and research trends/propositions can be summarized as follows: 1. The most cited publications doing research on project team settings lie between the years, 2000 and 2007, and are primarily studying authentic project teams in the fields of R&D and science, psychology, information technology, business management and the AEC in- dustry. 2. Top five author keywords explored the most within project teams research are knowledge sharing, trust, knowledge management, innovation, and communication with all of them having their average publication year between 2012 and 2015. 3. Research on interorganizational project team settings has received limited attention but show an upward trend in the past decade. It has been explored the most in the AEC industry followed by its limited presence in R&D and Science and Engineering teams. 4. Research on student teams has been limited with notable exceptions in courses related to business management and engineering. Therefore, future research should aim to broaden their scope to academic fields related to other industries. 5. Research on virtual project teams has limited studies within interorganizational setups and within the spectrum of student teams. Future research should prioritize exploring these settings further. 6. The research gap regarding virtual project teams is particularly evident in industries like automotive engineering, non-profits, and environmental engineering. 71 7. Future investigations on virtual project teams can focus on variables related to work en- gagement, knowledge hiding, psychological safety, task performance, knowledge leader- ship and team resilience. 8. Analysis of author-based country co-authorship networks highlights the need to enhance global collaborations among researchers studying project team settings in the AEC indus- try. 9. Recent research trends, based on keyword analysis over the past four years, have primarily focused on AEC industry, Business Management, and Information Technology. 10. There is potential for investigating specific research keyword hotspots related to AEC in- terorganizational project teams. Research areas such as collaborative project manage- ment and team resilience offer avenues for exploration. Relevant keywords include Team Resilience, Articulating Capacity, Common Knowledge, Psychological Safety, Turnover Intention, Creative Problem Solving, and Work Engagement. State-of-Practice and Future Research Areas: AEC Interorganizational Project Teams The main findings and research trends/propositions can be summarized as follows: 1. The majority of research on AEC interorganizational project teams focuses on single team systems with findings at the project team level. 2. Research on AEC interorganizational project team setups has been limited in examining all three levels of analysis: individual, sub-team and project team levels. 3. Future research should address the exploration of interrelated project networks within AEC interorganizational project teams, particularly at the sub-team level. 4. Majority of the research focused on multiteam systems within AEC interorganizational teams are found in the research domains of IPD Projects and integrated project team col- laboration networks. 5. Through citation network analysis of interconnected papers, several potential research ar- eas for AEC interorganizational project teams have emerged. These include learning and knowledge management, integrated project team performance, measurement of trust, per- ception of virtuality, and psychological factors influencing team dynamics. 6. Within AEC interorganizational project teams, research on virtual project collaboration networks presents future research opportunities for investigating knowledge sharing among project teams, as well as the development of trust and group resilience. 72 7. Limited studies have examined the measure of team resilience through a facilitation model for building psychological safety in interorganizational setups. 8. Acknowledging the multilevel nature of project teams, future research should explore the dynamics of trust, commitment, and team stability across different levels within the project team structure. Longitudinal studies can provide valuable insights into how these factors evolve over time. 9. To gain a better understanding of the impact of cultural diversity within interorganizational collaboration networks, additional studies need to be conducted in multicultural contexts. 10. Additional research is needed to examine collaboration networks within the context of mul- tiple project team memberships. This investigation should consider variables like pro- ject/task complexity and explore potential associations with knowledge-related factors. 11. In order to ensure the generalizability of findings on collaboration networks in AEC project teams, which are continually evolving, it is crucial to test the various project team network models on interorganizational teams in industries beyond the AEC industry. 5.3 Discussions Based on the various findings on research trends and future research areas that emerge through a scoping review performed in this study, this section provides the implications and applications of those findings in the domain of project teams research. Research on project teams across multiple industries: The literature on project teams has ex- tensively discussed different factors and variables (Caniëls et al., 2019; Kleinsmann & Valken- burg, 2005) that influence project team functioning and success. However, it is important to rec- ognize that these variables can differ across industries due to the unique characteristics of project teams, scale of the project and research focus specific to each industry (Zhou et al., 2017). This study examined a diverse range of industries, including healthcare, information technology, AEC, human resource development etc. as identified in the literature (Carlson et al., 2018; Greetham & Ippolito, 2018; Hansen, 2006; Iorio & Taylor, 2014). The findings emphasize the significant con- tributions of fields such as R&D and Science, Psychology, Information Technology, Business Management, and AEC to the understanding of project team settings. However, it is worth noting that multiple industries are underrepresented in the study such as aerospace engineering, biotech- nology, digital marketing, food & beverages, media, online gaming, and transportation, highlight- ing the need for future research expansion in these areas. 73 Authentic versus Student Project Teams (Future of Workforce Development): Publications studying project teams exhibit a significant variation when considering the nature of the teams involved: authentic teams in the real world or student teams that is the future of workforce (Presler- Marshall et al., 2022; Weeks & Kelsey, 2007). Project team settings in student teams are designed to develop the necessary skills for future professionals and eventually transition into authentic teams. In response to the industry's demand for graduates with strong teamwork skills, educational institutions across disciplines have increasingly incorporated team projects into their curricula (Druskat & Kayes, 2000). The results indicate that the research on these student teams has primar- ily been explored in courses related to business management and engineering with limited explo- ration in other areas. Therefore, future research should aim to broaden their scope to academic fields related to other industries. This study also highlights the potential future research areas which can be explored within student team settings which are: work engagement, turnover inten- tion, task performance, team cohesion and team creativity. The study also found a lack of research in student teams related to virtual team collaborations. Virtual vs Co-located Project Teams (Advancing virtual collaboration networks): The post- pandemic era has emphasized the importance and continued necessity of virtual team collabora- tions (Kinnula et al., 2018; Willermark & Pareto, 2020). This study indicates that majority of re- search on virtual team networks has been prevalent in industries such as AEC, R&D and Science, and Information Technology. This study identified several potential future research areas for vir- tual team collaborations, which include work engagement, knowledge hiding, psychological safety, task performance, knowledge leadership, and team resilience. These keywords primarily emerged from research conducted during and after the pandemic, demonstrating the growing chal- lenges faced by virtual teams. The cut-off date for data collection in this study dates to end of November 2022. The study reveals several noteworthy trends and identifies potential areas for future research. Utilizing evolution of time graphs, the evolution in various categorizations is evident but not all categories exhibit sig- nificant trends. However, one category stands out as promising, particularly in light of the growing interest in hybrid project setups: co-located (in person) versus virtual/hybrid project teams. However, the study points towards a lack of a lot of publications in the final stages related to virtual teams in the dataset from the past year, suggesting that similar studies in the future could shed light on more significant changes in research trends concerning virtual teams in the post-pandemic 74 world (Willermark & Pareto, 2020). Additionally, the study revealed a lack of research on virtual or hybrid team networks in industries such as automotive engineering, non-profits, and environ- mental engineering. This insight highlights the reliance of certain industries on face-to-face inter- actions for project success and could be considered as a key category in similar scoping reviews in the future. To gain deeper insights into this category, future studies can further explore this aspect by incorporating studies published up to 2023. By doing so, researchers can better address the dynamics of in person vs hybrid project teams and add more valuable findings for the evolving field of project teams research. Future of research on Interorganizational Collaborations and the AEC Industry: As backed by the literature (Caniëls et al., 2019; Jørgensen, 2018), the studies on interorganizational project teams have received limited attention but show an upward trend in the past decade. While several studies have examined interorganizational collaboration networks in the AEC industry, this study indicates that they still remain limited in the broader context of project teams. The AEC industry comprises intricate interorganizational and interdisciplinary project teams ( Korkmaz & Singh, 2012) involving numerous dynamic factors related to project team success. As collaboration networks within these teams exist at different levels within the composition of a single or a multiteam system (Shuffler et al., 2015), this study investigated the levels of analysis covered in research on AEC interorganizational project team settings. The existing research on AEC interorganizational project teams primarily focuses on single team systems at the project team level, indicating a scarcity of studies on large-scale and complex pro- jects which mostly have multiteam systems in place. Hence, selecting appropriate projects (scale, complexity, and project delivery method) for study on interorganizational project teams becomes crucial to advancing the understanding of project team performance in more complex settings (Campbell et al., 2022). The study notes that while multiteam systems are prevalent in integrated project delivery (IPD) cases, the number of IPD case studies remains limited. This prompts the exploration of whether constructs tested in IPD projects can be applied to design-build (DB) or design-bid-build (DBB) firms handling large-scale projects. The study also reveals that the stage of the construction project can play a crucial factor in determining the research outcomes and hence, stage of project needs to be explored in similar scoping reviews in the future. As research on interorganizational project teams has revealed the complex nature of the dynamic project networks involved (Engebø et al., 2020; Garcia & Mollaoglu, 2020), this study identified 75 two potential future research hotspots for AEC interorganizational project teams: team resilience and stability, and project management collaboration networks. Moreover, with a focus on virtual collaborations within these teams, the study suggests investigating knowledge sharing among vir- tual project teams and studying the development of trust and group resilience within virtual col- laboration networks. The study also highlights that in order to ensure the generalizability of find- ings on collaboration networks in AEC project teams, it is crucial to test the various project team network models longitudinally on interorganizational teams in industries beyond the AEC indus- try. By addressing these research gaps, a deeper understanding of collaboration dynamics in the AEC industry can be achieved, contributing to improved project outcomes and overall success. 5.4 Conclusions Working towards the main goal of this research, “What is the state of practice for AEC project teams based on the literature and how has project teams research evolved and is connected across domains?” the study achieved its deliverables through a scoping review and multiple citation net- work analysis methods: The study established and accomplished the following objectives: 1. Explore the trends and evolution of project teams literature differentiated by characteristics such as type of industry, authentic versus student teams, virtual vs co-located teams and or- ganizational vs interorganizational teams. 2. Explore the evolution of prior works within project teams research with a focus to study the state-of-research and future research directions of AEC interorganizational project teams The sample of 512 publications included in this study covered various industries and a wide range of categories regarding the types of project teams studied in research. In Chapter 4, the study iden- tified several avenues for future research in the field of project teams. The findings were presented through tables and figures, which included figures related to evolution over timelines and citation network analysis. Each network consisted of nodes representing journals, publications, countries, and keywords while the links between them highlighted the collaboration relations. The proposed future research areas covered specific research propositions for virtual project teams, interorganizational collaborations within virtual project teams, student teams (the future of work- force development), interorganizational collaborations within AEC project teams, and recommen- dations for industries that promise exploration in future research but are currently underrepresented in the project team literature. Additionally, the study identified potential keywords and specific 76 research hotspots for future studies focusing on AEC interorganizational project teams. The in- sights from this study provide guidance for researchers interested in exploring key areas within the field of AEC project teams and offers opportunities to dive deeper into specific research directions. Ultimately, this study aims to serve as a foundation for future investigations into project teams. By summarizing the current state-of-practice of project teams research and providing insights for fur- ther development, it is hoped that this research will contribute to the advancement and growth of future studies on project team settings. 5.5 Limitations/ Gaps for Future Research Although the study has made some interesting inferences, some shortcomings still exist in this study. 1. Since the results and discussions are based on previous research studies, the conclusions should be tested for and validated through empirical studies in the future. 2. Although the comprehensiveness of the selected database has been ensured in this study, additional searches for other databases and additional keyword searches can be added in future studies. 3. While this study looked at multiple categories to explore the evolution of project teams across multiple industries, some categories the future reviews can explore are as follows: geographical location of the projects, project scale, stage of the project (specific to the AEC industry). 4. It should be noted that the analysis of the state of research in this study relied on available visualization tools. While these tools provided valuable insights, there may be other visu- alization techniques or approaches that could have provided additional perspectives. 5. Furthermore, a potential improvement for future studies would be to advocate for the in- clusion of coding for team-related categories as a requirement in major journal sources. This enhancement would facilitate a more comprehensive and standardized approach to conducting scoping reviews, enabling researchers to gain a more holistic understanding of the field. 6. Diving deeper into research related to bibliometric analysis for future areas of study, a meta-analysis can be conducted to gain valuable statistical insights into the impact of treat- ing multiple variables within a research field. While project team research has a long his- tory, it remains a complex and multifaceted subject. By delving deeper into relevant studies 77 and performing a meta-analysis, we can uncover essential statistical insights regarding the effects of treating multiple variables. Unfortunately, multi-level studies in interorganiza- tional setups are currently scarce. Consequently, the current lack of a specific sample size required for such meta-analysis indicates that the field is not yet fully matured. This, in turn, highlights the need for more comprehensive work in interorganizational studies across various domains, paving the way for metanalytic studies for future advancements. 78 REFERENCES Ahearne, M., Jelinek, R., Mathieu, J., Rapp, A., & Schillewaert, N. 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Coronavirus disease-19 in environmental fields: A bibliometric and visualization mapping analysis. Environment Development and Sustainability, 23. https://doi.org/10.1007/s10668-020-01004-5 86 APPENDIX A: LIST OF PUBLICATIONS (SAMPLE FOR STUDY) Table 5.5-1 List of Publications (Sample for Study) Authors Title Mathieu J.E., Hollenbeck J.R., Knippenberg D.V., Ilgen D.R. Edson M.C. Liu W.-H., Cross J.A. Badir Y.F., Büchel B., Tucci C.L. Kukenberger Mathieu J.E., Ruddy T. M.R., Zhou Y., Cheung C.M., Hsu S.-C. Lumseyfai J. Pirró G., Mastroianni C., Talia D. Hans R.T., Mnkandla E. Chang Y.F., Watada J., Ishii H. Strnad D., Guid N. Hosseini S.M., Akhavan P., Abbasi M. Haselberger D. Keller R.T. A century of work teams in the journal of applied psychology A Complex Adaptive Systems View of Resilience in a Project Team A comprehensive model of project team technical performance A conceptual framework of the impact of NPD pro- ject team and leader empowerment on communica- tion and performance: An alliance case context A Cross-Level Test of Empowerment and Process Influences on Members’ Informal Learning and Team Commitment A dimensional model for describing and differenti- ating project teams A Four-Pillared Holistic Model for Improving Per- formance in Engineering Virtual Project Teams A framework for distributed knowledge manage- ment: Design and implementation A framework for improving the recognition of pro- ject teams as key stakeholders in information and communication technology projects A fuzzy MCDM approach to building a model of high-performance project team - a case study A fuzzy-genetic decision support system for project team formation A knowledge sharing approach for R&D project team formation A literature-based framework of performance-re- lated leadership interactions in ICT project teams A longitudinal study of the individual characteris- tics of effective R&D project team leaders Hosseini S.M., Akhavan P. A model for project team formation in complex en- gineering projects under uncertainty: A knowledge- sharing approach A model for selecting project team members using multicriteria group decision making A multi-objective multi-stage stochastic model for project team formation under uncertainty in time re- quirements Alencar L.H., de Almeida A.T. Rahmanniyay F., Yu A.J., Seif J. Year Cited by 2017 243 2012 2016 2012 36 36 36 2015 57 2017 2020 6 2 2010 27 2019 2012 4 9 2010 59 2017 2016 2017 2017 3 4 11 12 2010 34 2019 6 87 Table 5.5-1 (cont’d) Rahmanniyay F., Yu A.J. A multi-objective stochastic programming model for project-oriented human-resource management optimization A Multilevel Examination of the Impact of Team Interpersonal Processes 2019 11 2015 8 2004 413 Killumets E., D’Innocenzo L., Maynard M.T., Mathieu J.E. DeShon R.P., Kozlowski S.W.J., Schmidt A.M., Milner K.R., Wiechmann D. Ding Z., Ng F., Li J. White M.J., Gutierrez A., C., McLaughlin Eziakonwa C., Newman L.S., White M., Thayer B., Davis K., Williams M., Asselin G. Coates G., Duffy A.H.B., Hills W., Whitfield R.I. Natvig D., Stark N.L. Hosseini M.R., Bosch- Sijtsema P., Arashpour M., Chileshe N., Merschbrock C. Mathieu J.E., Tannenbaum S.I., Donsbach J.S., Al- liger G.M. Aubry A.-F. Mueller J. Karlsen J.T., Berg M.E. Tai S., Wang Y., Anumba C.J. Ford C., Sullivan D.M. Cavdur F., Sebatli A., Kose-Kucuk M., Rodoplu C. Bell B.S., Kozlowski S.W.J. A multiple-goal, multilevel model of feedback ef- fects on the regulation of individual and team per- formance A parallel multiple mediator model of knowledge sharing in architectural design project teams A pilot for understanding interdisciplinary teams in rehabilitation practice 2014 2013 35 22 A preliminary approach for modelling and planning the composition of engineering project teams A project team analysis using Tuckman’s model of small-group development A qualitative investigation of perceived impacts of virtuality on effectiveness of hybrid construction project teams 2007 2016 2018 5 5 4 A Review and Integration of Team Composition Models: Moving Toward a Dynamic and Temporal Framework A seat at the table: The benefits of integrating bio- analytical sciences into development project teams A specific knowledge culture: Cultural antecedents for knowledge sharing between project teams A study of the influence of project managers’ sig- nature strengths on project team resilience A survey on communications in large-scale con- struction projects in China A time for everything: How the timing of novel contributions influences project team outcomes A two-phase binary-goal programming-based ap- proach for optimal project-team formation 2014 270 2014 1 2014 109 2020 2009 2004 2019 11 47 73 6 A typology of virtual teams: Implications for effec- tive leadership 2002 681 88 Table 5.5-1 (cont’d) Liu L., Wang X., Sheng Z. Achieving ambidexterity in large, complex engi- neering projects: A case study of the Sutong Bridge project Adaptive, generative, and transformative learning in project teams Sessa V.I., London M., Pingor C., Gullu B., Patel J. Chen T.-Y., Chen Y.-M. Wang L., Tian L. McHugh O., Conboy K., Lang M. Gren L., Goldman A., Ja- cobsson C. Yang S., Cui G., Lu S. Imangulova Z., Kolesnyk L. Puck J.F., Mohr A.T., Rygl D. Oh K., Kim Y., Lee J. Waters N.M., Beruvides M.G. Advanced multi-phase trust evaluation model for collaboration between coworkers in dynamic vir- tual project teams Affinity and tacit knowledge management in pro- ject team Agile practices: The impact on trust in software pro- ject teams Agile ways of working: A team maturity perspec- tive Ambidextrous learning of engineering project team: Relying on control or BIM AI VR AR MR? An algorithm for building a project team consider- ing interpersonal relations of employees An empirical analysis of managers' adjustment to working in multinational project teams in the pipe- line and plant construction sector An empirical study of communication patterns, leadership styles, and subordinate satisfaction in R&D project teams in Korea An empirical study of large-sized companies with knowledge work teams and their impacts on project team performance An Exploratory Configurational Analysis of Knowledge Hiding Antecedents in Project Teams Moh’d S.S., Černe M., Zhang P. Strubler D.C., York K.M. An exploratory study of the team characteristics 2021 2007 Frank A.G., Ribeiro J.L.D. An integrative model for knowledge transfer be- 2014 model using organizational teams Gregory P., Strode D.E., Sharp H., Barroca L. Meese N., McMahon C. Von Stetten A., Beimborn D., Weitzel T. tween new product development project teams An onboarding model for integrating newcomers into agile project teams Analysing sustainable development social struc- tures in an international civil engineering consul- tancy Analyzing and managing the impact of cultural be- havior patterns on social capital in multinational IT project teams: A case study approach 89 2012 14 2011 26 2009 20 2012 2012 2020 2020 2016 1 81 11 2 2 2008 31 1991 22 2012 12 9 11 29 2 2022 2012 10 2012 9 2001 72 2015 23 2011 2016 2008 2011 1996 2005 2003 2001 30 16 15 4 37 50 30 2 Table 5.5-1 (cont’d) Analyzing shared and team mental models Langan-Fox J., Wirth A., Code S., Langfield-Smith K., Wirth A. Akgün A.E., Keskin H., Cebecioglu A.Y., Dogan D. Akgün A.E., Keskin H., Byrne J.C., Gunsel A. Huo X., Zhang L., Guo H. Antecedents of Relationship Conflict in Cross- Antecedents and consequences of collective empa- thy in software development project teams Antecedents and results of emotional capability in software development project teams Elenurm T. Safakish G., Wood D.A. Moenaert R.K., Caeldries F. Rahman M.M., Kumaras- wamy M.M. Loo R. Del Cerro G., Le mée J., Mar E., Wei C.-S., Wei- man C., Wortzel A. Lewis Philip, Aldridge Dayne, Swamidass Paul M. Crutchfield T.N., Klamon K. Miranda C., Goñi J.I., Hil- liger I., Lugo J. Leicht R.M., Lewis A., Ri- ley D.R., Messner J.I., Darnell B. Sankaran S., Vaagaasar A.L., Bekker M.C. Moon H., Hollenbeck J.R., Humphrey S.E., Ilgen D.R., West B., Ellis A.P.J., Porter C.O.L.H. Zhang P., Ng F.F. Functional Project Teams Applying cross-cultural student teams for support- ing international networking of Estonian enterprises Approaches to communications and cultural issues to aid planning and execution of oil and gas sector mega projects Architectural redesign, interpersonal communica- tion, and learning in R&D Assembling integrated project teams for joint risk management Assessing "team climate" in project teams Assessing communication modes in design project teams Assessing teaming skills acquisition on undergrad- uate project teams 1998 69 Assessing the Dimensions and Outcomes of an Ef- fective Teammate Assessing the work of geographically distributed teams in engineering-design: Time allocation in the design process as a form of in-class analytics Assessing traits for success in individual and team performance in an engineering course 2014 2020 2009 3 2 6 Assignment of project team members to projects: Project managers’ influence strategies in practice Asymmetric adaptability: Dynamic team structures as one-way streets 2020 11 2004 104 Attitude toward knowledge sharing in construction teams 2012 68 90 Table 5.5-1 (cont’d) Yang S., Cui G., Abdal Noor B., Lu S. Brewer G., Gajendran T. Attitudes, behaviors and the transmission of cul- tural traits: Impacts on ICT/BIM use in a project team Balance between affect and outcome control or face and behavior control for better learning: evidence from Chinese engineering project team Becoming motivated to be a good actor in a student project team: A theoretical investigation of student citizenship behavior and the use of peer evaluations Benefits and Problems With Student Teams: Sug- gestions for Improving Team Projects Chou S.Y., Ramser C. Hansen R.S. Dunston P.S., Reed A.G. Benefits of small projects team initiative Oyedele A., Owolabi L.O., H.A., Oyedele Olawale O.A. Pemsel S., Widén K. Big data innovation and diffusion in projects teams: Towards a conflict prevention culture 2012 28 2022 2019 3 1 2006 205 2000 2020 14 5 2011 16 York A.S., McCarthy K.A., Darnold T.C. Cole M.L., Cox J.D., Stav- ros J.M. Stokes S.L., Jr. D.D., Ahiaga-Dagbui Tokede O., Morrison J., Chirnside A. Schentrup D., Whalen K., Black E., Blue A., Chacko L. Herbst A.S. Sagar S.K., Arif M., Oladinrin O.T., Rana M.Q. Scorer S., Cate T., Wil- kinson L., Pollock P., Har- gan J. Allen D., Lowe K., Jones E., James W., Doyle T., Andrew J., Davies D., Moore K., Brophy S. Han Y., Li Y., Taylor J.E., Zhong J. Bridging boundaries between organizations in con- struction Building biotechnology teams: Personality does matter Building collaboration in teams through emotional intelligence: Mediation by SOAR (strengths, op- portunities, aspirations, and results) Building effective project teams Building high-performing and integrated project teams 2009 2019 1990 2020 Building interprofessional team effectiveness in a nurse-led rural health center 2018 Capturing knowledge from lessons learned at the work package level in project engineering teams Challenges negating virtual construction project team performance in the Middle East Challenging Behavior Project Team: A Six Month Pilot Project Evaluation 2017 2022 1993 6 8 4 6 3 8 2 3 Changing the face of challenging behavior services: The Special Projects Team 2006 18 Characteristics and Evolution of Innovative Collab- oration Networks in Architecture, Engineering, and Construction: Study of National Prize-Winning Projects in China 2018 24 91 Charting a course for collaboration: A multiteam perspective 2012 29 Circular organizational structure for project teams Civil engineers' personal values/demographics link- age in project team building Client-facing Interprofessional Project Teams: The Role of Engineers’ ‘Situated Judgment’ Coaching IT project teams: a design toolkit Code-switching in newly formed multinational pro- ject teams: Challenges, strategies and effects Cognitive divergence and shared mental models in software development project teams Cognitive elaboration during wiki use in project teams: An empirical study Cohesion and performance: A meta-analytic review of disparities between project teams, production teams, and service teams Collaboration in project teams: The role of mastery and performance climates Communication behaviors to implement innova- tions: How do AEC teams communicate in IPD pro- jects? Communication in construction: a management perspective through case studies in Sri Lanka Communications in hybrid arrangements: Case of Australian construction project teams Senaratne S., Ruwanpura M. Reza Hosseini M., Zavadskas E.K., Xia B., Chileshe N., Mills A. Webster J., Wong W.K.P. Comparing traditional and virtual group forms: Identity, communication and trust in naturally oc- curring project teams Composing in Groups: The Concept of Authority in Cross Functional Project Team Work Conceptual framework of sustainable management of the process of forming a project team with func- tional redundancy Loehr L. Table 5.5-1 (cont’d) Asencio R., Carter D.R., DeChurch L.A., Zaccaro S.J., Fiore S.M. Dias W.P.S. Damci A., Arditi D., Polat G. Wilde R.J., Guile D. Rezania D., Lingham T. Vigier M., Spencer-Oatey H. Levesque L.L., Wilson J.M., Wholey D.R. Zhang Y., Fang Y., Wei K.-K., He W. Chiocchio F., Essiembre H. Caniëls M.C.J., Chiocchio F., van Loon N.P.A.A. Sun W., Mollaoglu S., Miller V., Manata B. Dotsenko N., Chu- Chu- machenko D., machenko I., Galkin A., Lis T., Lis M. Rola P., Kuchta D., Kopczyk D. Tey K.H., Chai C.S., Olanrewaju A.L., Aminah M.Y. Fiore S.M., Carter D.R., Asencio R. 1990 2017 2021 2009 2017 3 3 1 16 11 2001 245 2013 17 2009 170 2019 2015 2016 2017 32 27 41 11 2008 83 1995 11 2021 3 Conceptual model of working space for Agile (Scrum) project team Conceptualising 4CS in construction project team integration 2016 17 2018 3 Conflict, trust, and cohesion: Examining affective and attitudinal factors in science teams 2015 13 92 Table 5.5-1 (cont’d) Senaratne S., Hapuarach- chi A. Ahmad I.U., Sein M.K. Canonico P., de Nito E., Mangia G. Tuuli M.M., Rowlinson S., Koh Y.T. Davison R.B., Hollenbeck J.R., C.M., Barnes Sleesman D.J., Ilgen D.R. Wen Q., Qiang M. Steiner M., Kanai J. Peled A. Torres S., Piñero Y., Piñero P.Y., Capretz L.F. Rickards T., Moger S. Zhang L., He J. Anthony E.L., Green S.G., McComb S.A. Müller R., Spang K., Oz- can S. Böhm C. Jetu F.T., Riedl R., Roithmayr F. Jetu F.T., Riedl R. Raiden A.B., Dainty A.R.J., Neale R.H. Bole V., Fink L., Prašnikar J. Construction project teams and their development: Case studies in Sri Lanka Construction project teams for TQM: A factor-ele- ment impact model Control mechanisms and knowledge integration in exploitative project teams: A case study from the coal fired power plant industry Control modes and mechanisms in construction project teams: Drivers and consequences Coordinated Action in Multiteam Systems 2009 1997 2012 12 12 11 2010 11 2012 128 Coordination and Knowledge Sharing in Construc- tion Project-Based Organization: A Longitudinal Structural Equation Model Analysis Creating effective multidisciplinary capstone pro- ject teams Creating winning information technology project teams in the public sector Creation and evaluation of software teams - A so- cial approach Creative Leadership Processes in Project Team De- velopment: An Alternative to Tuckman's Stage Model Critical Factors Affecting Tacit-Knowledge Shar- ing within the Integrated Project Team Crossing functions above the cross-functional pro- ject team: The value of lateral coordination among functional department heads Cultural differences in decision making in project teams Cultural flexibility in ICT projects: A new perspec- tive on managing diversity in project teams Cultural patterns influencing project team behavior in Sub-Saharan Africa: A case study in Ethiopia Cultural values influencing project team success: An empirical investigation in Ethiopia Current barriers and possible solutions to effective project team formation and deployment within a large construction organisation Customer focus competencies and the dynamics of project teams 2016 36 2016 6 2000 12 2014 3 2000 97 2016 2014 46 20 2009 36 2013 2011 2013 2004 8 15 11 40 2016 3 93 Table 5.5-1 (cont’d) Tomek S. Chen T.-Y., Chen Y.-M., Chu H.-C. Goh J.C.-L., Pan S.L., Zuo M. Liang J., Shu R., Farh C.I.C. Han J., Hovav A. Varhelahti M., Turnquist T. Savelsbergh C.M.J.H., Poell R.F., van der Heijden B.I.J.M. del Carmen Triana M., Kirkman B.L., Wagstaff M.F. Harding J.A., Popplewell K. Comu S., Unsal H.I., Tay- lor J.E. J.S., Loignon Thomas A.C., Woehr D.J., Loughry M.L., Ohland M.W. Lin L., Wang H. Lee S.M., Farh C.I.C. Developing a multicultural, cross-generational, and multidisciplinary team: An introduction for civil engineers Developing a trust evaluation method between co- workers in virtual project team for enabling re- source sharing and collaboration Developing the agile is development practices in large-scale it projects: The trust-mediated organiza- tional controls and it project team capabilities per- spectives Differential implications of team member promo- tive and prohibitive voice on innovation perfor- mance in research and development project teams: A dialectic perspective Dimensionality of social capital and organizational citizenship behavior in information systems project teams Diversity and Communication in Virtual Project Teams Does team stability mediate the relationship be- tween leadership and team learning? An empirical study among Dutch project teams Does the Order of Face-to-Face and Computer-Me- diated Communication Matter in Diverse Project Teams? An Investigation of Communication Order Effects on Minority Inclusion and Participation Driving concurrency in a distributed concurrent en- gineering project team: A specification for an Engi- neering Moderator Dual impact of cultural and linguistic diversity on project network performance Dyadic Viability in Project Teams: the Impact of Liking, Competence, and Task Interdependence Dynamic incentive model of knowledge sharing in construction project team based on differential game Dynamic leadership emergence: Differential im- pact of members' and peers' contributions in the idea generation and idea enactment phases of inno- vation project teams 2011 12 2008 39 2013 34 2019 44 2016 2021 6 5 2015 36 2012 12 1996 31 2011 24 2020 4 2019 15 2019 12 94 Table 5.5-1 (cont’d) Srivastava A., Pinto J. Furukawa C. Lee M.R. Reed A.H., Knight L.V. Jünger H.C., Scharpf S. Lam P.T.I., Wong F.W.H., Tse K.T.C. Assaf S., Hassanain M.A., Mughal H. Van Der Vegt G., Emans B., Van De Vliert E. Wickramasinghe Widyaratne R. Garcia A.J., Mollaoglu S., Frank K.A., Duva M., Zhao D. Di Marco M.K., Taylor J.E., Alin P. Hahn J., Moon J.Y., Zhang C. Brewer G., Gajendran T. Dynamic linkages of empowering and transforma- tional leadership with knowledge sharing in project teams Dynamics of a critical problem-solving project team and creativity in a multiple-project environ- ment E-ethical leadership for virtual project teams Effect of a virtual project team environment on communication-related project risk Effectiveness in project teams of integrated project delivery models with multi-party contracts com- pared to conventional and partnering models [Effektivität in projektteams integrierter projekta- bwicklungsmodelle mit mehr-parteienverträgen gegenüber konventionel-len und partnerschaft- lichen modellen] Effectiveness of ICT for Construction information exchange among multidisciplinary project teams Effectiveness of project teams and their impact on the performance of Saudi construction projects Effects of interdependencies in project teams 2022 2016 2009 2010 2020 2 5 28 62 1 2010 26 2014 8 1999 45 2012 103 2010 19 2021 2016 2021 1 3 6 V., Effects of interpersonal trust, team leader support, rewards, and knowledge sharing mechanisms on knowledge sharing in project teams Effects of organizational support on components of Drouin N., Bourgault M., Gervais C. virtual project teams Wang L., Lin H., Jiang W. Effects of Project Leader Workplace Anxiety on Project Team Member Organizational Citizenship Behavior: A Moderated Mediation Model Eliciting and mapping tacit knowledge on team- work success of six sigma teams Emergence and Evolution of Network Structures in Complex Interorganizational Project Teams Zou T.X.P., Lee W.B. Emergence and role of cultural boundary spanners in global engineering Project networks Emergence of new project teams from open source software developer networks: Impact of prior col- laboration ties Emerging ICT trends in construction project teams: A Delphi survey 2010 108 2008 202 2009 7 95 Table 5.5-1 (cont’d) Azad S.A.K. Emotional intelligence (EI) and performance im- provement system (PIS) in construction industry using digital monitoring smart test: A key for effec- tive construction organization Emotional intelligence (EI) capabilities training: Turner R., Lloyd-Walker can it develop EI in project teams? B. Empowering the construction project team Newcombe R. Empowering the project team: Impact of leadership Tuuli M.M., Rowlinson S., Fellows R., Liu A.M.M. style and team context Tuuli M.M., Rowlinson S. Empowerment in project teams: A multilevel exam- Zhang L., Guo H. Hoegl M., Muethel M. Frow N., Marginson D., Ogden S. Sutharshan A. Bennett C.I. Paros A., Kelly P.S., Sprinkle T.A. Weimann P., Pollock M., Scott E., Brown I. Hirshfield L.J. Newell S., Huang J., Tans- ley C. Morey J.C., Simon R., Jay G.D., Wears R.L., Salis- bury M., Dukes K.A., Berns S.D. Wu S.J., Ragatz G.L. ination of the job performance implications Enabling knowledge diversity to benefit cross-func- tional project teams: Joint roles of knowledge lead- ership and transactive memory system Enabling Shared Leadership in Virtual Project Teams: A Practitioners' Guide Encouraging strategic behaviour while maintaining management control: Multi-functional project teams, budgets, and the negotiation of shared ac- countabilities in contemporary enterprises Enhancing Agile methods for multi-cultural soft- ware project teams Enhancing Ethnic Diversity at a Big Ten University Through Project TEAM: A Case Study in Teacher Education Enhancing project team outcomes despite provi- sional work: a discussion to leverage cross-genera- tional advantages Enhancing team performance through tool use: How critical technology-related issues influence the performance of virtual project teams Equal but not equitable: Self-reported data obscures gendered differences in project teams ERP implementation: A knowledge integration challenge for the project team Error reduction and performance improvement in the emergency department through formal team- work training: Evaluation results of the medteams project Evaluating the total effect of early supplier involve- ment on project team effectiveness: Collaboration and interaction 2011 1 2008 1996 2012 2009 2019 2016 2005 43 42 12 36 31 33 69 2011 4 2002 32 2022 1 2013 28 2018 2006 13 29 2002 720 2010 9 96 Table 5.5-1 (cont’d) Son J., Rojas E.M. Evolution of collaboration in temporary project teams: An agent-based modeling and simulation ap- proach Examination of communication processes in de- sign-build project delivery in building construction Examining a curvilinear relationship between com- munication frequency and team performance in cross-functional project teams Tran D.Q., Nguyen L.D., Faught A. Patrashkova-Volzdoska S.A., R.R., McComb Green S.G., Compton W.D. Cheng K.-T., Hung Y.-W. Examining the effect of absorptive capacity in in- formation system development project team in Tai- wan Experience-based learning about LMX leadership and fairness in project teams: A dyadic directional approach Experience-driven model of decision-making pro- cesses in project teams Exploitative learning in project teams: Do cognitive capability and strategic orientations act as modera- tor variables? Explore Knowledge-Sharing Strategy and Evolu- tionary Mechanism for Integrated Project Team Based on Evolutionary Game Model Orłowski C., Sarzyński A., Sitek T., Ziółkowski A. Huang Y.-C., Ma R., Lee K.-W. Du Y., Zhou H., Yuan Y., Liu X. Graen G.B., Hui C., Taylor E.A. Yazid Z. Zaman U., Florez-Perez L., Khwaja M.G., Abbasi S., Qureshi M.G. Sackmann S.A., Martin F. Exploring cultural impacts on knowledge sharing behavior in project teams - Results from a simula- tion study Exploring leadership in self-managed project teams in malaysia Exploring the critical nexus between authoritarian leadership, project team member's silence and multi-dimensional success in a state-owned mega construction project Exploring the Dynamic Team Cohesion–Perfor- mance and Coordination–Performance Relation- ships of Newly Formed Teams Exploring the dynamics of knowledge integration: Acting and interacting in project teams Exploring the moral hazard evolutionary mecha- nism for BIM implementation in an integrated pro- ject team Exploring the occurrence of team learning behav- iours in project teams over time Exploring the role of cultural boundary spanners at complex boundaries in global virtual aec networks Braun M.T., Kozlowski S.W.J., Brown T.A., DeShon R.P. Enberg C., Lindkvist L., Tell F. Du Y., Zhou H., Yuan Y., Xue H. Raes E., Boon A., Kyndt E., Dochy F. Zelkowicz A., Iorio J., Taylor J.E., Via C.E. 97 2011 81 2017 14 2003 122 2022 2 2006 58 2015 1 2015 13 2019 11 2007 54 2015 3 2021 12 2020 18 2006 2019 2017 2015 89 14 9 7 Table 5.5-1 (cont’d) Reiter-Palmon R., Leone S. Huber G. Reza Hosseini M., Chileshe N., Baroudi B., Zuo J., Mills A. Kwofie T.E., Alhassan A., Botchway E., Afranie I. To M.L., Fisher C.D., Ash- kanasy N.M., Zhou J. Aubé C., Rousseau V., Brunelle E. Liston K., Fischer M., Winograd T. Mueller J. Facilitating creativity in interdisciplinary design teams using cognitive processes: A review Facilitating project team learning and contributions to organizational knowledge Factors affecting perceived level of virtuality in hy- brid construction project teams (HCPTs) A qualita- tive study Factors contributing towards the effectiveness of construction project teams Feeling differently, creating together: Affect heter- ogeneity and creativity in project teams Flow experience in teams: The role of shared lead- ership Focused sharing of information for multi-discipli- nary decision making by project teams Formal and informal practices of knowledge shar- ing between project teams and enacted cultural characteristics Shen W., Wang Y., Lee S. Formation of inter-project ties from the sender–re- cipient perspective: Roles of task interdependence and functional interdependence Formative evaluation of project TEAM (teens mak- ing environment and activity modifications) Kramer J.M., Roemer K., Liljenquist K., Shin J., Hart S. Rusman E., Van Bruggen J., Sloep P., Koper R. Godfrey Ochieng E., Price A.D. Barker M., Neailey K. A.L., Leal-Rodríguez Roldán J.L., Ariza-Montes J.A., Leal-Millán A. Stålsett K., Sjøvold E., Ol- sen T.R. Johnson M.D., Hollenbeck J.R., Scott DeRue D., Barnes C.M., Jundt D. Elbarkouky Fayek A.R. M.M.G., Fostering trust in virtual project teams: Towards a design framework grounded in a Trustworthiness ANtecedents (TWAN) schema Framework for managing multicultural project teams From individual learning to project team learning and innovation: A structured approach From potential absorptive capacity to innovation outcomes in project teams: The conditional mediat- ing role of the realized absorptive capacity in a re- lational learning context From routine to uncertainty: Leading adaptable teams within integrated operations Functional versus dysfunctional team change: Prob- lem diagnosis and structural feedback for self-man- aged teams Fuzzy similarity consensus model for early align- ment of construction project teams on the extent of their roles and responsibilities 98 2019 1999 2016 11 38 7 2015 24 2021 2018 2001 2015 5 23 70 73 2022 2 2014 20 2010 59 2009 1999 57 43 2014 150 2016 2 2013 25 2011 23 Hartmann T. Kristof-Brown A.L., Ste- vens C.K. J.D., DeRue J.R., Jundt Nahrgang D.S., Hollenbeck Spitzmuller M., D.K., Ilgen D.R. Paulsen H.F.K., Klonek F.E., Schneider K., Kauf- feld S. Guttenberg J.L. Chen M.-H. Li L., Müller R., Liu B., Wang Q., Wu G., Zhou S. Table 5.5-1 (cont’d) Pinto M.B. Gaining cooperation among members of hospital project teams 1990 4 Prasad K., Akhilesh K.B. Global virtual teams: What impacts their design and 2002 performance? Goal and process alignment during the implemen- tation of decision support systems by project teams Goal congruence in project teams: Does the fit be- tween members' personal mastery and performance goals matter? Goal setting in teams: The impact of learning and performance goals on process and performance 72 18 2011 2001 187 2013 22 Group Affective Tone and Team Performance: A Week-Level Study in Project Teams 2016 Group development model and Lean Six Sigma project team outcomes Guanxi networks and creativity in taiwanese project teams Horizontal-Leader Identification in Construction Project Teams in China: How Guanxi Impacts Coworkers’ Perceived Justice and Turnover Inten- tions How Different Forms of Social Capital Created Through Project Team Assignments Influence Em- ployee Adoption of Sustainability Practices 2020 2009 2021 9 2 9 1 How different team downsizing approaches influ- ence team-level adaptation and performance Reddy S.M.W., Torphy K., Liu Y., Chen T., Ma- suda Y.J., Fisher J.R.B., Galey S., Burford K., Frank K.A., Montambault J.R. DeRue D.S., Hollenbeck J.R., Johnson M.D., Ilgen D.R., Jundt D.K. Shepherd D.A., Patzelt H., Williams T.A., Warnecke D. Drouin N., Bourgault M. How organizations support distributed project teams: Key dimensions and their impact on decision making and teamwork effectiveness How project managers can encourage and develop positive emotions in project teams HOW PROJECT TEAMS ACHIEVE COORDI- NATED ACTION: A MODEL OF SHARED COGNITIONS ON TIME How Does Project Termination Impact Project Team Members? Rapid Termination, 'Creeping Death', and Learning from Failure Emil Berg M., Terje Karlsen J. Gevers J.M.P., Rutte C.G., van Eerde W. 2021 5 2008 63 2014 68 2013 20 2014 2003 17 14 99 Table 5.5-1 (cont’d) Liu Y., Keller R.T. Nauman S., Bhatti S.H., Imam H., Khan M.S. Krancher O., Dibbern J., Meyer P. Maurer I. Galli B.J. Han S.J., Chae C., Macko P., Park W., Beyerlein M. Solis F., Sinfield J.V., Abraham D.M. Tansley C., Huang J., Fos- ter C. Carter D.R., Dechurch L.A., Zaccaro S.J. Hahn J., Moon J.Y., Zhang C. Franz B., Leicht R., Mo- lenaar K., Messner J. Hartmann T., Fischer M., Haymaker J. Forester G.L., Thoms P., Pinto J.K. Bochenek G.M., Ragusa J.M. Ling F.Y.Y., Khoo W.W. Han J., Rapoport A., Fong P.S.W. Ojo A.O., Raman M., Chong S.C., Chong C.W. 2021 5 2022 3 2018 14 2010 193 2020 2017 2013 2013 2014 1 19 31 9 6 2006 11 2017 105 2009 2007 2004 98 14 8 2016 15 2020 6 2014 22 How Psychological Safety Impacts R&D Project Teams’ Performance: In a psychologically safe workplace, R&D project teams perform better, more readily share knowledge and engage in organ- izational citizenship behavior, and are less likely to leave. How Servant Leadership Drives Project Team Per- formance Through Collaborative Culture and Knowledge Sharing How social media-enabled communication aware- ness enhances project team performance How to build trust in inter-organizational projects: The impact of project staffing and project rewards on the formation of trust, knowledge acquisition and product innovation How to Effectively Manage Communication on Project Teams How virtual team leaders cope with creativity chal- lenges Hybrid approach to the study of inter-organization high performance teams Identity ambiguity and the promises and practices of hybrid e-HRM project teams Impact of leadership network structure on the crea- tive output of cross-functional multiteam systems Impact of social ties on open source project team formation Impact of Team Integration and Group Cohesion on Project Delivery Performance Implementing information systems with project teams using ethnographic-action research Importance of goal setting in virtual project teams team integrated project Improving through virtual (3d) collaboration Improving relationships in project teams in Malay- sia Incentive structures in multi-partner project teams interaction Individual antecedents of ACAP and implications of social context in joint engineering project teams: A conceptual model 100 Table 5.5-1 (cont’d) Ojo A.O., Raman M., Chong C.W. Garcia Joseph Mollaoglu S. Roman H.T. A., Individual differences and potential absorptive ca- pacity in joint project teams in the Nigerian up- stream oil industry Individuals' Capacities Knowledge in AEC Project Teams Industry-Academia Interactions and the PSE&G Student Project Team Concept to Apply Transferred Frank A.G., Ribeiro J.L.D. Influence factors and process stages of knowledge transfer between NPD teams: A model for guiding practical improvements Zhang C., Xu Y., Zhang C. Information seeking in an information systems pro- Gonzalez R.V.D. White K.B., Leifer R. Ling F.Y.Y., Tran H.B.T. Liu Y., Keller R.T., Bart- lett K.R. Moura I., Dominguez C., Varajão J. Chiocchio F., Lebel P., Dubé J.-N. ject team Information systems development success: Per- spectives from project team participants Information systems project team members: factors for high performance Informational role self-efficacy: A validation in in- terprofessional collaboration contexts involving healthcare service and project teams Ingredients to engender trust in construction project teams in Vietnam Initiative climate, psychological safety and knowledge sharing as predictors of team creativity: A multilevel study of research and development project teams Innovative performance of project teams: the role of organizational structure and knowledge-based dynamic capability Instilling collaborative and reflective practice in en- gineers: Using a team-based learning strategy to prepare students for working in project teams Integrated business model for improving integra- tion IBS project team in Malaysian construction in- dustry Integrated project development teams: Another fad . . . or a permanent change Integrated project team performance in early design stages–performance indicators influencing effec- tiveness in bridge design Integrated Project Teams: The way forward for UK defence procurement Moore D.R., Dainty A.R.J. Integrated project teams’ performance in managing Fleming Q.W., Koppel- man J.M. Ekström D., Rempling R., Plos M. Nawi M.N.M., Bahaudin A.Y., Azman M.N.A. Greetham M., Ippolito K. Moore D.M., Antill P.D. 2016 7 2020 15 1986 2014 2010 1986 2021 1 7 13 99 2 2016 24 2012 14 2021 7 2022 10 2018 10 2014 3 1996 40 2019 7 2001 1999 10 39 unexpected change events 101 Table 5.5-1 (cont’d) Baede E.J., Den Bekker E., Boiten J.-W., Cronin D., Van Gammeren R., De Vlieg J. Ratcheva V. Powers L.M., Summers J.D. Lin F.-r., Huang K.-j., Chen N.-s. Han J., Rapoport A. Taylor J.E., Levitt R.E. Skilton P.F., Forsyth D., White O.J. Anumba Ch.J., Duke A. Esther Paik J., Miller V., Mollaoglu S., Aaron Sun W. Chang T.-J., Yeh S.-P. Suprapto Y.L., Wibowo A., Harsono H. Zhang Z., Zhang L., Li A. Wu G., Liu C., Zhao X., Zuo J. Jones M.C., Harrison A.W. Bakker R.M., Boroş S., Kenis P., Oerlemans L.A.G. Rezvani A., Ashkanasy N., Khosravi P. Integrated project views: Decision support platform for drug discovery project teams 2012 5 Integrating diverse knowledge through boundary spanning processes - The case of multidisciplinary project teams Integrating graduate design coaches in undergradu- ate design project teams Integrating information retrieval and data mining to discover project team coordination patterns Intention-based fairness preferences in multi-part- ner project teams Inter-organizational knowledge flow and innova- tion diffusion in project-based industries Interdependence and integration learning in student project teams: Do team project assignments achieve what we want them to? Internet and intranet usage in a communications in- frastructure for virtual construction project teams Interorganizational Projects: Reexamining Innova- tion Implementation via IPD Cases Intra project team disagreement, conflict communi- cations, and team performance in cross-functional new product project teams: A decision-making quality perspective Intra-firm causal ambiguity on cross-functional project team’s performance: Does openness and an integrative capability matter? Investigating the Effects of Reward Interdepend- ence and Nonfinancial Incentives on NPD Collabo- ration in Diverse Project Teams Investigating the relationship between communica- tion-conflict interaction and project success among construction project teams IS project team performance: An empirical assess- ment It's Only Temporary: Time Frame and the Dynam- ics of Creative Project Teams Key Attitudes: Unlocking the Relationships be- tween Emotional Intelligence and Performance in Construction Projects 2009 97 2009 15 2006 2019 2005 2008 1997 2017 7 3 33 12 11 18 2014 2 2018 2019 4 8 2017 138 1996 2013 89 78 2020 11 102 Table 5.5-1 (cont’d) Nawi M.N.M., Osman W.N., Che-Ani A.I. Tian S., Zhao H., Xu X., Mu R., Ma Q. Fong P.S.W. Yoo D.K., Vonderembse M.A., Ragu-Nathan T.S. Zhikun D., Fungfai N. Mueller J. d'Armagnac S., Geraudel M., Salvetat D. Ma Z., Qi L., Wang K. Chen X., Li X., Clark J.G., Dietrich G.B. Jafari Navimipour N., Charband Y. Wang W.-T., Ko N.-Y. Frank A., Echeveste M. Ni G., Cui Q., Sang L., Wang W., Xia D. Jones M.C. Mathieu J.E., Rapp T.L. de Poel F.M., Stoker J.I., Van der Zee K.I. Miller D.M., Fields R., Kumar A., Ortiz R. Asgary N., Thamhain H. Key factors for integrated project team delivery: A proposed study in IBS Malaysian Construction Pro- jects Knowledge chain integration of design structure matrix-based project team: An integration model Knowledge creation in multidisciplinary project teams: An empirical study of the processes and their dynamic interrelationships Knowledge quality: Antecedents and consequence in project teams Knowledge sharing among architects in a project design team: An empirical test of theory of reasoned action in China Knowledge sharing between project teams and its cultural antecedents Knowledge sharing in a coopetition project team: An institutional logics perspective Knowledge sharing in Chinese construction project teams and its affecting factors: An empirical study Knowledge sharing in open source software project teams: A transactive memory system perspective Knowledge sharing mechanisms and techniques in project teams: Literature review, classification, and current trends Knowledge sharing practices of project teams when encountering changes in project scope: A contin- gency approach Knowledge transfer between NPD project teams: A method for the identification of improvement op- portunities Knowledge-Sharing Culture, Project-Team Interac- tion, and Knowledge-Sharing Performance among Project Members Large scale project team building: Beyond the ba- sics Laying the Foundation for Successful Team Perfor- mance Trajectories: The Roles of Team Charters and Performance Strategies Leadership and Organizational Tenure Diversity as Determinants of Project Team Effectiveness Leadership and organizational vision in managing a multiethnic and multicultural project team Leadership Lessons from Managing Multinational Project Teams 2014 18 2022 1 2003 160 2011 2009 79 35 2012 74 2019 2008 2013 4 78 57 2016 142 2012 21 2012 17 2018 50 2008 11 2009 176 2014 2000 2016 34 21 1 103 Table 5.5-1 (cont’d) Lai C.-Y., Hsu J.S.-C., Li Y. Ammeter A.P., Dukerich J.M. Gundersen G., Hellesøy B.T., Raeder S. Thamhain H.J. Couture M., Harvey J.-F. Bartsch V., Ebers M., Maurer I. Leadership, regulatory focus and information sys- tems development project team performance Leadership, team building, and team member char- acteristics in high performance project teams Leading International Project Teams: The Effec- tiveness of Transformational Leadership in Dy- namic Work Environments Leading technology-based project teams Leading temporary project teams: An analysis of task- and person-focused leadership over time Learning in project-based organizations: The role of project teams' social capital for overcoming bar- riers to learning 2018 2002 2012 2004 2021 33 81 46 30 1 2013 127 Druskat V.U., Kayes D.C. Learning versus performance in short-term project 2000 151 Senaratne S., Malewana C. Linking individual, team and organizational learn- 2011 teams Robertson R.L., Tippett D.D. Bond-Barnard Fletcher L., Steyn H. Cervone H.F. T.J., Roehrich J.K., Davies A., Frederiksen L., Sergeeeva N. Yazid Z., Osman L.H., Ha- mid R.A. Le Roy F., Fernandez A.- S. De Vries T.A., Hollenbeck J.R., Davison R.B., Walter F., Van Der Vegt G.S. Ochieng A.D.F. E.G., Price Iles P., Kaur Hayers P. Kettunen P. Chinowsky P.S., Good- man R.E. ing in construction project team settings Linking project team performance with team health 2002 Linking trust and collaboration in project teams to project management success Making decisions: Methods for digital library pro- ject teams Management innovation in complex products and systems: The case of integrated project teams 2018 2005 2019 5 6 68 10 25 Managing conflict in the self-managed project team 2018 3 Managing Coopetitive Tensions at the Working- group Level: The Rise of the Coopetitive Project Team Managing coordination in multiteam systems: Inte- grating micro and macro perspectives Managing cross-cultural communication in multi- cultural construction project teams: The case of Kenya and UK Managing diversity teams:A tentative model and case study Managing embedded knowledge Managing interdisciplinary project teams through the Web transnational project software project team in 2015 89 2016 31 2010 128 1997 2003 1996 94 14 8 104 Table 5.5-1 (cont’d) Senaratne S., Udawatta N. Managing intragroup conflicts in construction pro- 2013 Jiang J.J., Klein G., Tsai J.C.-A., Li Y. Harding J.A., Popplewell K., Cook D. Lin H.-K., Harding J.A., Shahbaz M. ject teams: Case studies in Sri Lanka Managing multiple-supplier project teams in new software development Manufacturing system engineering moderator: An aid for multidiscipline project teams Manufacturing system engineering ontology for se- mantic interoperability across extended project teams 2018 2003 2004 Behrend F.D., Erwee R. Mapping knowledge flows in virtual teams with 2009 Schröpfer V.L.M., Tah J., Kurul E. SNA Mapping the knowledge flow in sustainable con- struction project teams using social network analy- sis Marketing ergonomics within multi-disciplinary project teams Regensburg R.E., Van Der Veen F. Kononenko I., Sushko H. Mathematical model of software development pro- ject team composition optimization with fuzzy ini- tial data Maximizing workforce diversity in project teams: A network flow approach Measuring Key Communication Behaviors in Inte- grated Project Delivery Teams Bhadury J., Joy Mighty E., Damar H. Manata B., Miller V., Mollaoglu S., Garcia A.J. Garcia A.J., Mollaoglu S. Measuring Key Knowledge-Related Factors for In- Latorre R., Suárez J. Bstieler L., Gross C.W. Yang Y., Kuria G.N., Gu D.-X. Dossick C.S., Anderson A., Azari R., Iorio J., Neff G., Taylor J.E. W. Shelley A., Maqsood T. Wang J., Wei W., Ding L., Li J. dividuals in AEC Project Teams Measuring social networks when forming infor- mation system project teams Measuring the effect of environmental uncertainty on process activities, project team characteristics, and new product success Mediating Role of Trust Between Leader Commu- nication Style and Subordinate’s Work Outcomes in Project Teams Messy talk in virtual teams: Achieving knowledge synthesis through shared visualizations Metaphor as a means to constructively influence be- havioural interactions in project teams Method for analyzing the knowledge collaboration effect of R&D project teams based on Bloom's tax- onomy 105 20 11 26 84 25 56 2 4 57 24 8 13 34 2017 1990 2021 2000 2018 2020 2017 2003 2020 9 2014 34 2014 2 2017 10 Table 5.5-1 (cont’d) Rach V., Osakwe I., Medvedieva O., Ros- soshanskaya O., Borulko N. Oeij P.R.A., Van Vuuren T., Dhondt S., Gaspersz J., De Vroome E.M.M. White K.B. Wi H., Mun J., Oh S., Jung M. Ghaffari M., Sheikhah- madi F., Safakish G. Unsal H.I., Taylor J.E. Kwofie T.E., Adinyira E., Fugar F. Zhu M., Huang Y., Con- tractor N.S. Reyes A.M. Chiocchio F., Rabbat F., Lebel P. Chen Y.M., Wei C.-W. Rahman M.M., Kumaras- wamy M.M. Chan K.-Y. Kwofie T.E., Aigbavboa C.O., Molobela E.D. Wei M., Hao S., Ren X. Tseng T.-L.B., Huang C.- C., Chu H.-W., Gung R.R. Method for configuring the composition of a project team based on the criteria of subjective well-being 2019 3 1984 2018 Mindful infrastructure as antecedent of innovation resilience behaviour of project teams: Learning from HROs MIS project teams: An investigation of cognitive style implications Modeling and analysis of project team formation factors in a project-oriented virtual organization (ProVO) Modeling and risk analysis of virtual project team through project life cycle with fuzzy approach Modeling interfirm dependency: Game theoretic simulation to examine the holdup problem in pro- ject networks Modelling the effect of housing design unit contract packaging on mass housing project team communi- cation performance Motivations for self-assembling into project teams 2013 2016 2014 2011 2009 11 63 22 14 38 8 46 2 Multi-ethnic project team relationships in a high- tech organizational culture Multi-Level Efficacy Evidence of a Combined In- terprofessional Collaboration and Project Manage- ment Training Program for Healthcare Project Teams Multiagent approach to solve project team work al- location problems Multicountry perspectives of relational contracting and integrated project teams Multiple project team membership and perfor- mance: Empirical evidence from engineering pro- ject teams Nature of effects of dynamics of team control on project team effectiveness in construction project delivery Nonspatial Proximity and Project Team Resilience: The Role of Knowledge Sharing and Team Cohe- sion Novel approach to multi-functional project team formation 106 1998 2015 20 2009 2012 2014 2020 2022 11 33 14 1 1 2004 57 Table 5.5-1 (cont’d) Herbsleb J.D., Klein H., Olson G.M., Brunner H., Olson J.S., Harding J. Kwofie T.E., Aigbavboa C., Baiden-Amissah A. Miranda C., Goñi J., Hil- liger I. Bourouni A., Noori S., Jafari M. Mbengue A., Sané S. Rauniar R., Rawski G. Nordqvist S., Hovmark S., Zika-Viktorsson A. Zhikun D., Fungfai N.G., Jiayuan W. Kaiser K.M., Bostrom R.P. Paulus T.M., Bichelmeyer B., Malopinsky L., Pereira M., Rastogi P. Girard N.J., Watson D.S. Jiang J.J., Klein G., Dis- cenza R. Iorio J., Taylor J.E. Bennett C., Cole D., Thompson J.-N. Buvik M.P., Rolfsen M. Marks A., Lockyer C. Bąk-Grabowska Piwowar-Sulej K. D., Object-Oriented Analysis and Design in Software Project Teams 1995 54 Ontology of the communication performance pro- spects of building information modelling adoption among project teams in construction project deliv- ery Orchestrating conflict in teams with the use of boundary objects and trading zones in innovation- driven engineering design projects Organizational groupings and performance in pro- ject-based organizations: An empirical investiga- tion Organizational Learning Capability: Theoretical analysis and empirical study in the context of Offi- cial Development Aid project teams Organizational structuring and project team struc- turing in integrated product development project Perceived time pressure and social processes in pro- ject teams Personal construct based factors affecting willing- ness to share knowledge between architects in a project design team Personality characteristics of MIS project teams: An empirical study and action-research design Power distance and group dynamics of an interna- tional project team: A case study Practice models for perioperative nursing, effec- tiveness initiative being explored by Project Teams Pre-project partnering impact on an information system project, project team and project manager Precursors to engaged leaders in virtual project teams Preparing teachers of color at a predominantly white university: A case study of project TEAM Prior ties and trust development in project teams - A case study from the construction industry Producing Knowledge: The Use of the Project Team as a Vehicle for Knowledge and Skill Acqui- sition for Software Employees Professional training in the context of the diversity of workplaces: Project teams and non-standard forms of employment 2020 4 2021 2014 2 9 2013 11 2012 2004 2010 30 60 5 1982 112 2005 26 1992 2002 2015 2000 1 38 27 26 2015 111 2004 17 2021 1 107 Table 5.5-1 (cont’d) Weiser M., Morrison J. Chinowsky P., Taylor J.E., Di Marco M. Chinowsky P.S., Diek- mann J., O'Brien J. Scott-Young C., Samson D. Allen T., Katz R., Grady J.J., Slavin N. Pinto M.B., Pinto J.K. Project memory: Information management for pro- ject teams Project network interdependency alignment: New approach to assessing project effectiveness Project organizations as social networks Project success and project team management: Ev- idence from capital projects in the process indus- tries Project team aging and performance: The roles of project and functional managers Project team communication and cross-functional cooperation in new program development 1997 2011 64 80 2010 135 2008 158 1988 27 1990 359 Lievens A., Moenaert R.K. Project team communication in financial service in- 2000 Buffinton K.W., Martin K.A., Jablokow K.W. McComb S.A., Kennedy D.M., Green S.G., Comp- ton W.D. Gharaibeh H.M. novation Project team dynamics and cognitive style Project team effectiveness: The case for sufficient setup and top management involvement Project team learning in mega projects: Are we truly learning the lessons? Dressler D.M., Nash K.B. Project team organization and its application to cri- Pavez I., Gómez H., Laulié L., González V.A. Chi Y.-L., Chen C.-Y. Lloyd-Walker B., Ping Cheung Y. Zeller C. Fleming Quentin W., Kop- pelman Joel M. Dong G.-Q., Zhang W.-F., Wang X.-M. Rattan I. Allen R.K., Becerik B., Pollalis S.N., Schwegler B.R. Carlson E.A., Staffileno B.A., Murphy M.P. Lee C., Farh J.-L., Chen Z.-J. sis intervention Project team resilience: The effect of group potency and interpersonal trust Project teaming: Knowledge-intensive design for composing team members Project teams and change in the Australian banking industry Project teams as means of restructuring research and development in the pharmaceutical industry Project teams: The role of the project office Project-team and task-role based dynamic access control model for virtual enterprises Project-team effectiveness - Don't let It fade away Promise and barriers to technology enabled and open project team collaboration Promoting DNP-PhD collaboration in doctoral ed- ucation: Forming a DNP project team Promoting group potency in project teams: The im- portance of group identification 108 74 53 29 2 7 10 12 1 2002 2008 2016 1974 2021 2009 1999 2002 54 1998 2014 2005 2005 2018 2011 3 1 1 22 10 27 Table 5.5-1 (cont’d) Kim Y., Lee B. Case Randolph H., Singer Jean Shi J., Lin L., Tang D. Kneedler J.A., Murphy E.K., Wells M., Hercules P., Shoup A., Brazen L. Konradt U., Otte K.-P., Schippers M.C., Steenfatt C. Wu G., Zhao X., Zuo J. Rice-Bailey T. Dumitraşcu-Băldău I., Du- mitraşcu O. Novikov S., Komarova N., Dadyan K. Carmeli A., Levi A., Pec- cei R. Unger-Aviram E., Zwikael O., Restubog S.L.D. Ericksen J., Dyer L. Maruping L.M., Zhang X., Venkatesh V. Aram John D., Morgan Cyril P. Hopkins David S. Miller J.S., Cardy R.L. Müller M., Jedličková L. McCarthy S., O'Raghal- laigh P., Fitzgerald C., Adam F. R&D project team climate and team performance in Korea: A multidimensional approach Re: Project team empowerment aboard the starship Enterprise Reciprocal preference-based knowledge sharing in- centive of project team Reconceptualizing, Redefining Perioperative Nurs- ing. Project Team Report: Aorn Project Team to Reconceptualize/Redefine Perioperative Nursing Reflexivity in teams: A review and new perspec- tives Relationship between Project's Added Value and the Trust-Conflict Interaction among Project Teams Remote technical communicators: Accessing audi- ences and working on project teams Research on the behavior of factors that influence the international virtual project team performance, using data modeling techniques Research opportunities to improve the competitive- ness by using network project teams Resilience and creative problem-solving capacities in project teams: A relational view Revisiting Goals, Feedback, Recognition, and Per- formance Success: The Case of Project Teams Right from the start: Exploring the effects of early team events on subsequent project team develop- ment and performance Role of collective ownership and coding standards in coordinating expertise in software project teams ROLE OF PROJECT TEAM COLLABORATION IN R&D PERFORMANCE. ROLES OF PROJECT TEAMS AND VENTURE GROUPS IN NEW PRODUCT DEVELOPMENT. Self-monitoring and performance appraisal: Rating outcomes in project teams Several Notes on the Existential Hermeneutic Phe- nomenology for Project Management and Possibil- ities of Its Extension by Other Existential Concepts: Case Study From the Research Project Team Shared and fragmented understandings in interor- ganizational IT project teams: An interpretive case study 1995 45 1997 2014 1992 1 2 1 2016 73 2017 59 2014 2019 2020 2021 2013 8 4 1 11 17 2004 100 2009 1976 1975 79 40 7 2000 37 2020 6 2021 3 109 Table 5.5-1 (cont’d) Muethel M., Hoegl M. C.M., Scott-Young Georgy M., Grisinger A. Han S.J., Beyerlein M., Kolb J. Lee Y., Shafique F., Mollaoglu- Scott S. Zhang L., He J., Zhou S. Quintane E., Pattison P.E., Robins G.L., Mol J.M. Taylor J.E., Levitt R., Vil- larroel J.A. Liu L., Leitner D. Lee-Kelley L. Klein G., Jiang J.J., Shelor R., Balloun J.L. Hoegl M. Chen M.-H., Chang Y.-C., Hung S.-C. Newell S., Tansley C., Huang J. Ogilvie K., Assimakopou- los D. Leonard A., van Zyl D. J., Lehtinen Vanhanen T.O.A. Aladwani A.M. Shared leadership functions in geographically dis- persed project teams Shared leadership in project teams: An integrative multi-level conceptual model and research agenda Shared leadership in teams: The role of coordina- tion, goal commitment, and knowledge sharing on perceived team performance Shared mental models and inter-organizational aec project teams Sharing tacit knowledge for integrated project team flexibility: Case study of integrated project delivery Short- and long-term stability in organizational net- works: Temporal structures of project teams Simulating learning dynamics in project networks Simultaneous pursuit of innovation and efficiency in complex engineering projects-a study of the an- tecedents and impacts of ambidexterity in project teams Situational leadership:Managing the virtual project team Skill coverage in project teams Smaller teams-better teamwork: How to keep pro- ject teams small Social capital and creativity in R&D project teams 2008 2005 Social Capital and Knowledge Integration in an ERP Project Team: The Importance of Bridging AND Bonding Social network analysis of team dynamics and in- tra-organizational development in an aerospace firm Social relationships in IT project teams: Its role, complexity and the management thereof Software engineering problems encountered by capstone project teams Some correlates of is project teams’ internal inter- action and outcome in a developing country Something(s) old and something(s) new: Modeling drivers of global virtual team effectiveness 2011 2019 2018 2020 2013 2013 2009 2012 7 40 34 1 75 51 38 54 2002 26 1999 6 75 181 2004 250 2007 3 2014 13 2014 1999 8 1 2012 137 2015 71 Maynard M.T., Mathieu J.E., Rapp T.L., Gilson L.L. Khedhaouria A., Jamal A. Sourcing knowledge for innovation: knowledge re- use and creation in project teams 110 Table 5.5-1 (cont’d) Bourgeon L. Balwant P. LUCIANO M.M., NAHR- GANG J.D., SHROP- SHIRE C. Donnelly H., Alemayehu D., Botgros R., Comic- Savic S., Eisenstein B., Lorenz B., Merchant K., Pelfrene E., Reith C., San- tiago J., Tiernan R., Wunderink R., Tenaerts P., Knirsch C. Colazo J. Pöysä-Tarhonen J., Elen J., Tarhonen P. Ainsworth J. Ford Robert C., McLaugh- lin Frank S. Sweeney P.J., Lee D.R. Lines B.C., Sullivan K.T., Wiezel A. Hamburg I. Baird A. Frank Cervone H. Kopczak L.R., Fransoo J.C. Rapp T.L., Mathieu J.E. Staffing approach and conditions for collective learning in project teams: The case of new product development projects Stay close! The role of leader distance in the rela- tionship between transformational leadership, work engagement, and performance in undergraduate project teams Strategic leadership systems: Viewing top manage- ment teams and boards of directors from a mul- titeam systems perspective Streamlining Safety Data Collection in Hospital- Acquired Bacterial Pneumonia and Ventilator-As- sociated Bacterial Pneumonia Trials: Recommen- dations of the Clinical Trials Transformation Initia- tive Antibacterial Drug Development Project Team 2007 30 2019 7 2020 25 2016 5 2014 Structural changes associated with temporal disper- sion in software development teams: Evidence from open source software project teams Student teams’ development over time: tracing the relationship between the quality of communication and teams’ performance Student-Led Project Teams: Significance of Regu- lation Strategies in High- and Low-Performing Teams Successful project teams: A study of MIS managers 1992 2016 2016 Support and commitment factors of project teams Support for organizational change: Change-readi- ness outcomes among AEC project teams Supporting Cross-Border knowledge transfer through Virtual Teams, communities and ICT Tools System orientation for the project team - the key to greater customer satisfaction Systematic vs intuitive decision making and the Pa- reto principle: Effective decision-making for pro- ject teams Teaching supply chain management through global projects with global project teams Team and individual influences on members' iden- tification and performance per membership in mul- tiple team membership arrangements 1999 2016 2011 1991 2015 2000 2019 111 1 10 7 19 18 18 9 3 3 28 34 Table 5.5-1 (cont’d) He J., Butler B.S., King W.R. Lisbona A., Las-Hayas A., Palací F.J., Bernabé M., Morales F.J., Haslam A. Pearlstein J. Goh K.T., Goodman P.S., Weingart L.R. Ortega A., Sánchez-Man- zanares M., Gil F., Rico R. Bell B.S., Kozlowski S.W.J., Blawath S. Mach M., Baruch Y. Savelsbergh C., Gevers J.M.P., van der Heijden B.I.J.M., Poell R.F. Gevers J.M.P., van Eerde W., Rutte C.G. Team cognition: Development and evolution in software project teams Team efficiency in organizations: A group perspec- tive on initiative Team formation that models real life: Teaching stu- dents to form better teams in the capstone and be- yond Team Innovation Processes: An Examination of Activity Cycles in Creative Project Teams Team learning and effectiveness in virtual project teams: The role of beliefs about interpersonal con- text Team Learning: A Theoretical Integration and Re- view Team performance in cross cultural project teams: The moderated mediation role of consensus, heter- ogeneity, faultlines and trust Team role stress: Relationships with team learning and performance in project teams Team self-regulation and meeting deadlines in pro- ject teams: Antecedents and effects of temporal consensus 2007 171 2020 2020 2013 2010 2012 2015 2 6 32 33 44 32 2012 59 2009 33 Shuffler M.L., Carter D.R. Teamwork situated in multiteam systems: Key les- 2018 46 Aljuwaiber A. Fruchter Bosch- R., Sijtsema P., Ruohomäki V. Pollack J., Matous P. Ding Z., Ng F., Wang J. sons learned and future opportunities Technology-based vs. face-to-face interaction for knowledge sharing in the project teams Tension between perceived collocation and actual geographic distribution in project teams 2019 5 2010 18 Testing the impact of targeted team building on pro- ject team communication using social network analysis Testing trust scale measurement invariance in pro- ject teams 2019 28 2014 1 Dennis A.R., Garfield M.J. The adoption and use of GSS in project teams: To- 2003 156 Phua F.T.T. Henderson L.S., Stackman R.W., Lindekilde R. ward more participative processes and outcomes The antecedents of co-operative behaviour among project team members: An alternative perspective on an old issue The centrality of communication norm alignment, role clarity, and trust in global project teams 2004 36 2016 47 112 Table 5.5-1 (cont’d) Oertig M., Buergi T. Mendez A. Auch F., Smyth H. Marnewick C., Marnewick A.L. Olaisen J., Revang O. Hewitt B., Walz D.B., McLeod A. May G.L., Gueldenzoph L.E. J.P., Román-Calderón Aguilar-Barrientos S., Es- calante J.E., Barbosa J., Arias Salazar A. Chiocchio F., Grenier S., O’Neill T.A., Savaria K., Willms J.D. Porter T.W., Lilly B.S. Contractor N. Gent L., Parry A.E., Parry M.E. Collier D. Jiang J.J., Klein G., Pick R.A. Radhakrishnan A., Zaveri J., David D., Davis J.S. Tsai W.-L. Hacker M. Forgues D., Koskela L. The challenges of managing cross-cultural virtual project teams The coordination of globalized R&D activities through project teams organization: An exploratory empirical study The cultural heterogeny of project firms and project teams The Demands of Industry 4.0 on Project Teams The dynamics of intellectual property rights for trust, knowledge sharing and innovation in project teams The effect of conflict and knowledge sharing on the information technology project team performance The effect of social style on peer evaluation ratings in project teams The Effect of Student Work Group Emotional Intel- ligence on Individual Task Performance in Teams 2006 2003 2010 2020 2017 65 31 6 20 42 2020 5 2006 33 2021 3 The effects of collaboration on performance: a mul- tilevel validation in project teams 2012 47 The effects of conflict, trust, and task commitment on project team performance The emergence of multidimensional networks The high-cooperation hospital project team The human factors of project team decision-making for radioactive waste management The impact of IS department organizational envi- ronments upon project team performances The impact of project team characteristics and cli- ent collaboration on project agility and project suc- cess: An empirical study The Impact of Project Teams on CMMI Implemen- tations: a Case Study from an Organizational Cul- ture Perspective The impact of top performers on project teams The influence of a collaborative procurement ap- proach using integrated design in construction on project team performance 1996 136 2009 1998 2013 29 7 2 2003 29 2022 2021 1 2 2000 2009 17 58 113 Table 5.5-1 (cont’d) Zhang L., Cheng J., Wang D. Buvik M.P., Tvedt S.D. Mathieu J.E., Goodwin G.F., Heffner T.S., Salas E., Cannon-Bowers J.A. Wu Z., Yin B., Ning P. Rico R., Alcover C.-M., Sánchez-Manzanares M., Gil F. Rusman E., Van Bruggen J., Sloep P., Valcke M., Koper R. Zhang Z., Min M. The influence of informal governance mechanisms on knowledge integration within cross-functional project teams: A social capital perspective The Influence of Project Commitment and Team Commitment on the Relationship between Trust and Knowledge Sharing in Project Teams The influence of shared mental models on team pro- cess and performance The Influence of Team Human Capital on Safety Performance of Engineering Project Team: The Mediating Role of Safety Citizenship Behavior The joint relationships of communication behaviors and task interdependence on trust building and change in virtual project teams The mind's eye on personal profiles: A cognitive perspective on profile elements that inform initial trustworthiness assessments and social awareness in virtual project teams The negative consequences of knowledge hiding in NPD project teams: The roles of project work at- tributes Wu G.-D. Chen J.V., Widjaja A.E., Chen B. Stephens J.P., Carmeli A. The positive effect of expressing negative emotions on knowledge creation capability and performance of project teams The relationship between project team dynamic fea- ture, conflict dimension and project success - An empirical research from Shanghai, China The relationships among environmental turbulence and socio-technical risk factors affecting project risks and performance in NPD project teams The research on role differentiation as a method of forming the project team Sherstyuk O., Olekh T., Kolesnikova K. Schofield J., Wilson D.C. The role of capital investment project teams in or- ganisational learning The Role of Feeling Known for Team Member Out- comes in Project Teams Theoretical and practical implications for engender- ing project team communication effectiveness in mass housing project delivery in Ghana Toward a group facilitation technique for project teams Toward a model of socializing project team mem- bers: An integrative approach Kwofie T.E., Adinyira E., Fugar F. Batistič S., Kenda R. Purvanova R.K. Witte E.H. 2015 17 2017 43 2000 1636 2021 1 2009 32 2013 5 2019 49 2016 56 2013 11 2017 3 2016 16 1995 7 2013 10 2017 9 2007 2018 20 16 114 Table 5.5-1 (cont’d) Shokory S.M., Suradi N.R.M. Zhu F., Wang L., Yu M., Müller R., Sun X. Kabore S.E., Sane S., Abo P. Keller R.T. Schweiger D.M., Atamer T., Calori R. Hankel A. Olomolaiye A., Egbu C. Shazi R., Gillespie N., Steen J. Raes E., Kyndt E., Dochy F. Stork D., Sapienza A.M. Herrera R.F., Mourgues C., Alarcón L.F., Pellicer E. Korzaan M., Harris A. Culp G., Smith A. Lungeanu A., Huang Y., Contractor N.S. Briner W., Geddes M. Hsu S.-C., Weng K.-W., Cui Q., Rand W. Weaver S.J., Che X.X., Pe- tersen L.A., Hysong S.J. Lee S., Sawang S. McHugh O., Conboy K., Lang M. Transformational leadership and its impact on ex- tra-role performance of project team members: The mediating role of work engagement Transformational leadership and project team mem- bers’ silence: the mediating role of feeling trusted Transformational leadership and success of interna- tional development projects (ID projects): moderat- ing role of the project team size Transformational leadership, initiating structure, and substitutes for leadership: A longitudinal study of research and development project team perfor- mance Transnational project teams and networks: Making the multinational organization more effective Transport optimization project team uses DMAIC to improve efficiency, customer satisfaction Trust and Knowledge Management in the Construc- tion Industry Trust as a predictor of innovation network ties in project teams Turning points during the life of student project teams: A qualitative study Uncertainty and equivocality in projects: Managing their implications for the project team Understanding Interactions between Design Team Members of Construction Projects Using Social Network Analysis Understanding Predictors of Over-Optimism in IS Project Teams Understanding psychological type to improve pro- ject team performance Understanding the assembly of interdisciplinary teams and its impact on performance Understanding the big picture: Positioning the pro- ject team Understanding the complexity of project team member selection through agent-based modeling Unpacking Care Coordination Through a Mul- titeam System Lens Unpacking the impact of attachment to project teams on boundary-spanning behaviors Using agile practices to influence motivation within IT project teams 2018 5 2019 12 2021 2 2006 325 2003 55 2012 2005 2 1 2015 68 2015 1995 2020 2020 2001 2014 1989 2016 2018 2016 2011 2 10 23 2 39 46 2 42 27 14 30 115 Table 5.5-1 (cont’d) El-Tayeh A., Gil N. Petkovic D. Kögl S., Silvius G. Stouffs R. Tuuli M., Morgan Rowlinson S. Adikaram A.S., Wijaya- wardena K. Kamareiy M., Hassanza- deh A., Elahi S. Guo H., Zhang L., Huo X., Xi G. Gorla N., Lam Y.W. tacit transfer Using digital socialization to support geograph- ically dispersed AEC project teams Using Learning Analytics to Assess Capstone Pro- ject Teams Using patterns to capture and knowledge in virtual project teams Visualizing information structures and its impact on project teams: An information architecture for the virtual AEC company What empowers individuals and teams in project settings? A critical incident analysis What happens to female employees in skewed IT project teams in Sri Lanka? Revisiting kanter What Kind of knowledge is concealed by project team members? (case study: Oil industries' com- missioning and operation company (OICO)) When and how cognitive conflict benefits cross- functional project team innovation: The importance of knowledge leadership Who should work with whom? Building effective software project teams Why cultural intelligence matters on global project teams Lin T.-C., Huang C.-C. Henderson L.S., Stackman R.W., Lindekilde R. Cummings J., Pletcher C. Why project networks beat project teams Holmer L.L. Haffer R., Haffer J., Mor- row D.L. Gällstedt M. Will we teach leadership or skilled incompetence? The challenge of student project teams Withholding effort in knowledge contribution: The role of social exchange and social cognitive on pro- ject teams Work Outcomes of Job Crafting Among the Differ- ent Ranks of Project Teams Working conditions in projects: Perceptions of stress and motivation among project team members and project managers Zuofa T., Ochieng E.G. Working separately but together: appraising virtual project team challenges Working smarter and greener: Collaborative knowledge sharing in virtual global project teams Writing the Project Team: Authority and Intertex- tuality in a Corporate Setting Olaisen J., Revang O. Hansen C.J. 2007 17 2016 2019 2001 9 3 7 2010 21 2015 2018 2019 4 3 8 2004 185 2018 2011 2001 32 17 29 2010 144 2021 3 2003 82 2017 2017 1995 17 61 16 116 APPENDIX B: CO-OCCURRENCE TIMELINE NETWORK Figure 5.5-1 Co-occurrence Timeline Network 117 APPENDIX C: LIST OF PUBLICATIONS IN KEYWORD CLUSTERS Table 5.5-2 List of Publications in Keyword Clusters Research Cluster Project Team Performance Knowledge Sharing and its impact on Team Perfor- mance Team Effec- tiveness Author Title Facilitating creativity in interdisciplinary design teams using cognitive processes: A review Resilience and creative problem-solving capaci- ties in project teams: A relational view What Kind of knowledge is concealed by project team members? (case study: Oil industries' com- missioning and operation company (OICO)) Reiter-Palmon R., Leone S. Carmeli A., Levi A., Peccei R. Kamareiy M., Has- sanzadeh A., Elahi S. Zhang Z., Min M. The negative consequences of knowledge hiding in NPD project teams: The roles of project work attributes An Exploratory Configurational Analysis of Knowledge Hiding Antecedents in Project Teams Enabling knowledge diversity to benefit cross- functional project roles of knowledge leadership and transactive memory system When and how cognitive conflict benefits cross- functional project team innovation: The im- portance of knowledge leadership Building high-performing and integrated project teams Moh’d S.S., Černe M., Zhang P. Guo H., Zhang L., Huo X., Xi G. Zhang L., Guo H. teams: Joint Year 2019 2021 2018 2019 2021 2019 2019 2020 Ahiaga-Dagbui D.D., Tokede O., Morrison J., Chirn- side A. Braun M.T., Ko- S.W.J., zlowski Brown T.A., DeShon R.P. Yang Y., Kuria G.N., Gu D.-X. Exploring the Dynamic Team Cohesion–Perfor- mance and Coordination–Performance Relation- ships of Newly Formed Teams 2020 Mediating Role of Trust Between Leader Com- munication Style and Subordinate’s Work Out- comes in Project Teams 2020 118 Liu Y., Keller R.T., Bartlett K.R. Liu Y., Keller R.T. How Psychological Safety Impacts R&D Project Teams’ Performance: In a psychologically safe workplace, R&D project teams perform better, more readily share knowledge and engage in or- ganizational citizenship behavior, and are less likely to leave. Initiative climate, psychological safety and knowledge sharing as predictors of team creativ- ity: A multilevel study of research and develop- ment project teams Horizontal-Leader Identification in Construction Project Teams in China: How Guanxi Impacts Coworkers’ Perceived Justice and Turnover In- tentions The Effect of Student Work Group Emotional Intelligence on Individual Task Performance in Teams Li L., Müller R., Liu B., Wang Q., Wu G., Zhou S. 2021 2021 2021 2021 Table 5.5-2 (cont’d) Team Effec- tiveness Collaborative Project Man- agement Team Resili- ence Román-Calderón J.P., Aguilar-Bar- rientos S., Es- calante J.E., Bar- bosa J., Arias Sala- zar A. Sagar S.K., Arif M., Oladinrin O.T., Rana M.Q. Joseph Garcia A., Mollaoglu S. Joseph Garcia A., Mollaoglu S. Karlsen J.T., Berg M.E. Pavez I., Gómez H., Laulié L., Gon- zález V.A. Challenges negating virtual construction project team performance in the Middle East 2022 Individuals' Capacities to Apply Transferred Knowledge in AEC Project Teams Measuring Key Knowledge-Related Factors for Individuals in AEC Project Teams A study of the influence of project managers’ signature strengths on project team resilience Project team resilience: The effect of group po- tency and interpersonal trust 2020 2020 2020 2021 119 APPENDIX D: CITATIONS CLUSTER IDENTIFICATION Table 5.5-3 List of Publications in Keyword Clusters Authors Title Clus- ter 1 1 1 Di Marco M.K.; Taylor J.E.; Alin P Chinowsky P.S.; Diek- mann J.; O'brien J. Son J.; Rojas E.M. 1 Unsal H.I.; Taylor J.E. Chinowsky P.; Taylor J.E.; Di Marco M. Solis F.; Sinfield J.V.; Abraham D.M. Zhang L.; He J.; Zhou S. Zelkowicz A.; Iorio J.; Taylor J.E.; Via C.E. Han Y.; Li Y.; Taylor J.E.; Zhong J. Garcia A.J.; Mollaoglu S.; Frank K.A.; Duva M.; Zhao D. Nordqvist S.; Hovmark S.; Zika-Viktorsson A. Maurer I. 2 Ding Z.; Ng F.; Li J. 1 1 1 1 1 1 1 1 2 2 Year 2010 2010 2011 2011 2011 2013 2013 2015 2018 2020 2020 2021 2004 2010 2014 Emergence and role of cultural boundary span- ners in global engineering project networks Project organizations as social networks Evolution of collaboration in temporary project teams: an agent-based modeling and simulation approach Modeling interfirm dependency: game theoretic simulation to examine the holdup problem in pro- ject networks Project network interdependency alignment: new approach to assessing project effectiveness Hybrid approach to the study of inter-organiza- tion high performance teams Sharing tacit knowledge for integrated project team flexibility: case study of integrated project delivery Exploring the role of cultural boundary spanners at complex boundaries in global virtual aec net- works Characteristics and evolution of innovative col- laboration networks in architecture engineering and construction: study of national prize-winning projects in china Individuals' capacities knowledge in aec project teams transferred dividuals in aec project teams Emergence and evolution of network structures in complex interorganizational project teams Perceived time pressure and social processes in project teams How to build trust in inter-organizational pro- jects: the impact of project staffing and project re- wards on the formation of trust knowledge acqui- sition and product innovation A parallel multiple mediator model of knowledge sharing in architectural design project teams 120 Garcia Joseph Mollaoglu S. Garcia A.J.; Mollaoglu S. Measuring key knowledge-related factors for in- to apply A.; Table 5.5-3 (cont’d) 2 2 Savelsbergh C.M.J.H.; Poell R.F.; Van Der Heijden B.I.J.M. Buvik M.P.; Rolfsen M. 2 Wen Q.; Qiang M. 2 2 2 2 2 Hsu S.-C.; Weng K.-W.; Cui Q.; Rand W. Buvik M.P.; Tvedt S.D. Oyedele A.; Owolabi H.A.; Oyedele L.O.; Olawale O.A. D.D.; Ahiaga-Dagbui Tokede O.; Morrison J.; Chirnside A. Pavez I.; G(cid:0)Mez H.; Lauli(cid:0) L.; Gonz(cid:0)Lez V.A. 2 Wei M.; Hao S.; Ren X. Does team stability mediate the relationship be- tween leadership and team learning? An empiri- cal study among dutch project teams Prior ties and trust development in project teams - a case study from the construction industry Coordination and knowledge sharing in construc- tion project-based organization: a longitudinal structural equation model analysis Understanding the complexity of project team member selection through agent-based modeling The influence of project commitment and team commitment on the relationship between trust and knowledge sharing in project teams Big data innovation and diffusion in projects teams: towards a conflict prevention culture 2015 2015 2016 2016 2017 2020 Building high-performing and integrated project teams 2020 Project team resilience: the effect of group po- tency and interpersonal trust 2021 Sweeney P.J.; Lee D.R. Tai S.; Wang Y.; Anumba C.J. Senaratne S.; Hapuarach- chi A. Senaratne S.; Udawatta N. Managing intragroup conflicts in construction Nonspatial proximity and project team resilience: the role of knowledge sharing and team cohesion Support and commitment factors of project teams 1999 2009 A survey on communications in large-scale con- struction projects in china Construction project teams and their develop- ment: case studies in sri lanka 2022 2009 3 3 3 3 3 Wu G.-D. 3 3 Senaratne S.; Ruwanpura M. Reza Hosseini M.; Zavadskas E.K.; Xia B.; Chileshe N.; Mills A. 3 Wu G.; Liu C.; Zhao X.; Zuo J. 3 Wu G.; Zhao X.; Zuo J. project teams: case studies in sri lanka The relationship between project team dynamic feature conflict dimension and project success - an empirical research from shanghai china Communication in construction: a management perspective through case studies in sri lanka Communications in hybrid arrangements: case of australian construction project teams Investigating the relationship between communi- cation-conflict interaction and project success among construction project teams Relationship between project's added value and the trust-conflict interaction among project teams 121 2013 2013 2016 2017 2017 2017 Table 5.5-3 (cont’d) 3 3 Rezvani A.; Ashkanasy N.; Khosravi P. Zaman U.; Florez-Perez L.; Khwaja M.G.; Abbasi S.; Qureshi M.G. 4 Ma Z.; Qi L.; Wang K. 4 Zhikun D.; Fungfai N. 4 4 4 4 Zhang P.; Ng F.F. Shi J.; Lin L.; Tang D. Mueller J. Ni G.; Cui Q.; Sang L.; Wang W.; Xia D. 4 Lin L.; Wang H. 4 4 5 5 5 5 5 Du Y.; Zhou H.; Yuan Y.; Liu X. Aljuwaiber A. Bell B.S.; Kozlowski S.W.J. El-Tayeh A.; Gil N. Liu L.; Leitner D. Sun W.; Mollaoglu S.; Miller V.; Manata B. Zhou Y.; Cheung C.M.; Hsu S.-C. Key attitudes: unlocking the relationships be- tween emotional intelligence and performance in construction projects Exploring the critical nexus between authoritarian leadership project team member's silence and multi-dimensional success in a state-owned mega construction project Knowledge sharing in chinese construction pro- ject teams and its affecting factors: an empirical study Knowledge sharing among architects in a project design team: an empirical test of theory of rea- soned action in china Attitude toward knowledge sharing in construc- tion teams Reciprocal preference-based knowledge sharing incentive of project team Formal and informal practices of knowledge shar- ing between project teams and enacted cultural characteristics Knowledge-sharing culture project-team interac- tion and knowledge-sharing performance among project members Dynamic incentive model of knowledge sharing in construction project team based on differential game Explore knowledge-sharing strategy and evolu- tionary mechanism for integrated project team based on evolutionary game model Technology-based vs. Face-to-face interaction for knowledge sharing in the project teams A typology of virtual teams: implications for ef- fective leadership Using digital socialization to support geograph- ically dispersed aec project teams Simultaneous pursuit of innovation and efficiency in complex engineering projects-a study of the an- tecedents and impacts of ambidexterity in project teams Communication behaviors to implement innova- tions: how do aec teams communicate in ipd pro- jects? A dimensional model for describing and differen- tiating project teams 2020 2021 2008 2009 2012 2014 2015 2018 2019 2019 2019 2002 2007 2012 2015 2017 122 Table 5.5-3 (cont’d) Interorganizational projects: reexamining innova- tion implementation via ipd cases 2017 5 5 6 6 6 6 6 7 7 7 7 8 8 8 9 9 9 Esther Paik J.; Miller V.; Mollaoglu S.; Aaron Sun W. Manata B.; Miller V.; Mollaoglu S.; Garcia A.J. Scott-Young C.; Samson D. Unger-Aviram E.; Zwikael O.; Restubog S.L.D. Bourouni A.; Noori S.; Jafari M. Sankaran S.; Vaagaasar A.L.; Bekker M.C. Li L.; M(cid:0)Ller R.; Liu B.; Wang Q.; Wu G.; Zhou S. Huber G. Measuring key communication behaviors in inte- grated project delivery teams Project success and project team management: evidence from capital projects in the process in- dustries Revisiting goals feedback recognition and per- formance success: the case of project teams Organizational groupings and performance in project-based organizations: an empirical investi- gation Assignment of project team members to projects: project managers(cid:0) influence strategies in prac- tice Horizontal-leader identification in construction project teams in china: how guanxi impacts coworkers(cid:0) perceived justice and turnover inten- tions Facilitating project team learning and contribu- tions to organizational knowledge Assembling integrated project teams for joint risk management Rahman M.M.; Kumaras- wamy M.M. Senaratne S.; Malewana C. Linking individual team and organizational learn- Ling F.Y.Y.; Khoo W.W. moore d.r.; dainty a.r.j. forgues d.; koskela l. ekstr(cid:0)m d.; rempling r.; plos m. ing in construction project team settings Improving relationships in project teams in ma- laysia Integrated project teams(cid:0) performance in manag- ing unexpected change events The influence of a collaborative procurement ap- proach using integrated design in construction on project team performance Integrated project team performance in early de- sign stages(cid:0)performance indicators influencing effectiveness in bridge design ding z.; ng f.; wang j. ochieng e.g.; price a.d.f. Managing cross-cultural communication in mul- ticultural construction project teams: the case of kenya and uk Testing trust scale measurement invariance in project teams Factors affecting perceived level of virtuality in hybrid construction project teams (hcpts) a quali- tative study reza hosseini m.; chileshe n.; baroudi b.; zuo j.; mills a. 123 2018 2008 2013 2014 2020 2021 1999 2005 2011 2016 1999 2009 2019 2010 2014 2016 Table 5.5-3 (cont’d) 10 10 savelsbergh c.; gevers j.m.p.; van der heijden b.i.j.m.; poell r.f. wang l.; lin h.; jiang w. Team role stress: relationships with team learning and performance in project teams 2012 Effects of project leader workplace anxiety on project team member organizational citizenship behavior: a moderated mediation model 2021 124