Title: Expertise Flows in AEC Projects: an Analysis of Multi-Level Teams for Sustainability
Architectural, Engineering, and Construction (AEC) project teams adopt different methods to facilitate collaboration to achieve sustainability goals, which requires a high level of expertise integration. Tracking expertise flows in interdisciplinary and inter-organizational project networks is challenging because of the unique project nature, fluid expertise boundaries, and varying project requirements. It can be even more difficult considering sustainability outcomes, due to the need for high-level expertise integration. Social network approach addresses the integration and information flow dynamics. However, there is a knowledge gap regarding what network characteristics are favorable for improved sustainability outcomes in AEC projects, how they evolve during delivery, and how relevant expertise flows through project networks. To respond to the need in the literature, this study aims to develop a holistic understanding of AEC project team networks and associated characteristics that allow experts to exchange knowledge to optimize sustainability outcomes for built environment projects. We longitudinally collected e-mail exchange, observational, and archival data during the design phase of an AEC case study project and performed Social Network Analysis (SNA) bolstered by mixed methods. Results suggest that network topology matters for AEC project teams. In other words, understanding the interactions between components of a network (e.g., expertise areas represented and distributed in the network and the number of boundary spanners) is as important as the network parameters for better sustainability outcomes. more »« less
Garcia, Angelo Joseph; Duva, Meltem; Mollaoglu, Sinem; Zhao, Dong; Frank, Kenneth A.; Benitez, Jackeline
(, Proceedings of Construction Research Congress 2020)
null
(Ed.)
Architectural, Engineering, and Construction (AEC) project team networks frequently increase the density of information sharing ties to improve team performance. However, increased density might not result in team members receiving adequate in-formation to collaborate towards common goals. There is a need to examine how net-work ties should be set up to manage information flows. Thus, the research goal is to explore the features of information sharing networks and their relationship with team performance in AEC projects. To achieve this goal, we collected communication data from an AEC project team with 179 members involved in total during the schematic design phase. Then, we performed social network analysis using Gephi and UCINET software. Results suggest that AEC project team networks are dynamic and adopt a core-periphery structure to share information early in project delivery. Including civil and mechanical subcontractors into the core subnetwork to collaborate with owners, designers, and general contractors can improve team performance. The study’s contribution to the body of knowledge is expanding our understanding of the characteristics and evolution of information sharing networks in AEC projects for optimized team performance.
Ability to effectively work in teams is one of the desired outcomes of engineering and engineering technology programs. Unfortunately, working in teams is still challenging for many students. Rather than contributing to team projects, some students resort to social loafing. Social loafing tends to destroy both teamwork performance and individual learning, especially in solving ill-structured problems, such as design. Furthermore, a bad experience on a past team is a significant concern as it could generate negative feelings toward future team projects. Formation of collaborative teams is a critical first step in team-project-based design courses as team composition directly affects not only teamwork processes and outcomes, but also teamwork skills and experience. This NSF-IUSE sponsored project aims to enhance students’ teamwork experiences and teamwork learning through 1) understanding how to form better student design teams and 2) identifying exercises that will effectively improve team member collaboration. We do this by comparing student characteristics and design task characteristics with the quality of the design team outcome, and examining the resulting correlations. Student characteristics cover six categories: 1) background information, 2) work structure preferences, 3) personality, 4) ability, 5) motivation, and 6) attitude. Task characteristics and design team outcomes are characterized using the Creative Product Semantic Scale. In this article, we present correlations between student/team characteristics and design project outcome, and correlations between task characteristics and design project outcome for 2020-2021 senior design teams at two institutions. For both institutions, we will present correlations between individual student characteristics and team outcome. For one institution, we will also present correlation between team-level characteristics and team outcomes.
The 2019 Social Science Extreme Events Research (SSEER) Census summarizes the results of responses gathered from 949 social scientists who filled out the SSEER survey between its release date on July 8, 2018 and December 31, 2019. This report characterizes the diversity and wide range of disciplinary skills and expertise among the research community. It is organized into the following categories: (1) researcher geographic location; (2) disciplinary background and expertise; (3) educational and professional background; (4) level of involvement in hazards and disaster research (core, periodic, situational, emerging); (5) research methods and approaches; (6) disaster types, phases, and specific extreme events studied; and (7) researcher demographic characteristics. The document concludes with further readings, data citations, and a brief description of the SSEER network. This annual report responds to longstanding calls to better characterize the composition of the hazards and disaster workforce. The 2018 and 2019 SSEER Census reports are available for download via PDF and also online at: https://converge.colorado.edu/research-networks/sseer/sseer-census/. Social scientists who study hazards and disasters can become a part of this network and annual count by joining SSEER at: https://converge.colorado.edu/research-networks/sseer/. More information on SSEER and the other National Science Foundation-funded reconnaissance and research networks is available on the CONVERGE website at: https://converge.colorado.edu/research-networks/.This project includes a survey instrument, data, and annual census reports from the National Science Foundation (NSF)-funded Social Science Extreme Events Research (SSEER) network, which is headquartered at the Natural Hazards Engineering Research Infrastructure (NHERI) CONVERGE facility at the Natural Hazards Center at the University of Colorado Boulder. The SSEER network, which was launched in 2018, was formed, in part, to respond to the need for more specific information about the status and expertise of the social science hazards and disaster research workforce. The mission of SSEER is to identify and map social scientists involved in hazards and disaster research in order to highlight their expertise and connect social science researchers to one another, to interdisciplinary teams, and to communities at risk to hazards and affected by disasters. Ultimately, the goals of SSEER are to amplify the contributions of social scientists and to advance the field through expanding the available social science evidence base. To see the SSEER map and to learn more about the SSEER initiative, please visit: https://converge.colorado.edu/research-networks/sseer. All social and behavioral scientists and those in allied disciplines who study the human, economic, policy, and health dimensions of disasters are invited to join this network via a short online survey. This DesignSafe project includes: (1) the SSEER survey instrument; (2) de-identified data, which is updated annually as new researchers join the SSEER network and returning members update their information; and (3) SSEER annual census reports. These resources are available to all who are interested in learning more about the composition of the social science hazards and disaster workforce. SSEER is part of a larger ecosystem of NSF-funded extreme events research and reconnaissance networks designed to help coordinate disciplinary communities in engineering and the sciences, while also encouraging cross-disciplinary information sharing and interdisciplinary integration. To learn more about the networks and research ecosystem, please visit: https://converge.colorado.edu/research-networks/.
The 2018 Social Science Extreme Events Research (SSEER) Census summarizes the results of responses gathered from 648 social scientists who filled out the SSEER survey between its release date on July 8, 2018 and December 31, 2018. This report characterizes the diversity and wide range of disciplinary skills and expertise among the research community. It is organized into the following categories: (1) researcher geographic location; (2) disciplinary background and expertise; (3) educational and professional background; (4) level of involvement in hazards and disaster research (core, periodic, situational, emerging); (5) research methods and approaches; (6) disaster types, phases, and specific extreme events studied; and (7) researcher demographic characteristics. The document concludes with further readings, a data citation, and a brief description of the SSEER network. This report—which is the first census of social scientists who study hazards and disasters—responds to longstanding calls to better characterize the composition of the hazards and disaster workforce. The 2018 SSEER Census is available for download via PDF and also online at: https://converge.colorado.edu/research-networks/sseer/sseer-census/. Social scientists who study hazards and disasters can become a part of this network and annual count by joining SSEER at: https://converge.colorado.edu/research-networks/sseer/. More information on SSEER and the other National Science Foundation-funded reconnaissance and research networks is available on the CONVERGE website at: https://converge.colorado.edu/research-networks/.This project includes a survey instrument, data, and annual census reports from the National Science Foundation (NSF)-funded Social Science Extreme Events Research (SSEER) network, which is headquartered at the Natural Hazards Engineering Research Infrastructure (NHERI) CONVERGE facility at the Natural Hazards Center at the University of Colorado Boulder. The SSEER network, which was launched in 2018, was formed, in part, to respond to the need for more specific information about the status and expertise of the social science hazards and disaster research workforce. The mission of SSEER is to identify and map social scientists involved in hazards and disaster research in order to highlight their expertise and connect social science researchers to one another, to interdisciplinary teams, and to communities at risk to hazards and affected by disasters. Ultimately, the goals of SSEER are to amplify the contributions of social scientists and to advance the field through expanding the available social science evidence base. To see the SSEER map and to learn more about the SSEER initiative, please visit: https://converge.colorado.edu/research-networks/sseer. All social and behavioral scientists and those in allied disciplines who study the human, economic, policy, and health dimensions of disasters are invited to join this network via a short online survey. This DesignSafe project includes: (1) the SSEER survey instrument; (2) de-identified data, which is updated annually as new researchers join the SSEER network and returning members update their information; and (3) SSEER annual census reports. These resources are available to all who are interested in learning more about the composition of the social science hazards and disaster workforce. SSEER is part of a larger ecosystem of NSF-funded extreme events research and reconnaissance networks designed to help coordinate disciplinary communities in engineering and the sciences, while also encouraging cross-disciplinary information sharing and interdisciplinary integration. To learn more about the networks and research ecosystem, please visit: https://converge.colorado.edu/research-networks/.
The 2022 Social Science Extreme Events Research (SSEER) Census summarizes the results of responses gathered from 1,521 social scientists who responded to the SSEER survey between its release date on July 8, 2018 and December 31, 2022. This report characterizes the diversity, disciplinary skills, and expertise within the research community. It is organized into the following categories: (1) number of researchers; (2) researcher geographic location; (3) disciplinary background and expertise; (4) educational and professional background; (5) level of involvement in hazards and disaster research (core, periodic, situational, emerging); (6) research methods and approaches; (7) disaster types, phases, number of extreme events studied, and names of specific extreme events studied; and (8) researcher demographic characteristics. The document concludes with references for further review and a brief description of the SSEER network. This annual report responds to longstanding calls to better characterize the skills and demographic composition of the hazards and disaster workforce. The 2018-2022 SSEER Census reports are available for download as color and black & white PDF files at: https://converge.colorado.edu/research-networks/sseer/sseer-census/. Social scientists who study hazards and disasters can become part of this network and annual count by joining SSEER at: https://converge.colorado.edu/research-networks/sseer/. More information on SSEER and the other National Science Foundation-funded reconnaissance and research networks is available on the CONVERGE website at: https://converge.colorado.edu/research-networks/.This project includes a survey instrument, data, and annual census reports from the National Science Foundation (NSF)-funded Social Science Extreme Events Research (SSEER) network, which is headquartered at the Natural Hazards Engineering Research Infrastructure (NHERI) CONVERGE facility at the Natural Hazards Center at the University of Colorado Boulder. The SSEER network, which was launched in 2018, was formed, in part, to respond to the need for more specific information about the status and expertise of the social science hazards and disaster research workforce. The mission of SSEER is to identify and map social scientists involved in hazards and disaster research in order to highlight their expertise and connect social science researchers to one another, to interdisciplinary teams, and to communities at risk to hazards and affected by disasters. Ultimately, the goals of SSEER are to amplify the contributions of social scientists and to advance the field through expanding the available social science evidence base. To see the SSEER map and to learn more about the SSEER initiative, please visit: https://converge.colorado.edu/research-networks/sseer. All social and behavioral scientists and those in allied disciplines who study the human, economic, policy, and health dimensions of disasters are invited to join this network via a short online survey. This DesignSafe project includes: (1) the SSEER survey instrument; (2) de-identified data, which is updated annually as new researchers join the SSEER network and returning members update their information; and (3) SSEER annual census reports. These resources are available to all who are interested in learning more about the composition of the social science hazards and disaster workforce. SSEER is part of a larger ecosystem of NSF-funded extreme events research and reconnaissance networks designed to help coordinate disciplinary communities in engineering and the sciences, while also encouraging cross-disciplinary information sharing and interdisciplinary integration. To learn more about the networks and research ecosystem, please visit: https://converge.colorado.edu/research-networks/.
Duva, Meltem, Mollaoglu, Sinem, Zhao, Dong, and Frank, Kenneth A. Expertise Flows in AEC Projects: an Analysis of Multi-Level Teams for Sustainability. Retrieved from https://par.nsf.gov/biblio/10292337. Proceedings of EPOC 2020 .
Duva, Meltem, Mollaoglu, Sinem, Zhao, Dong, & Frank, Kenneth A. Expertise Flows in AEC Projects: an Analysis of Multi-Level Teams for Sustainability. Proceedings of EPOC 2020, (). Retrieved from https://par.nsf.gov/biblio/10292337.
Duva, Meltem, Mollaoglu, Sinem, Zhao, Dong, and Frank, Kenneth A.
"Expertise Flows in AEC Projects: an Analysis of Multi-Level Teams for Sustainability". Proceedings of EPOC 2020 (). Country unknown/Code not available. https://par.nsf.gov/biblio/10292337.
@article{osti_10292337,
place = {Country unknown/Code not available},
title = {Expertise Flows in AEC Projects: an Analysis of Multi-Level Teams for Sustainability},
url = {https://par.nsf.gov/biblio/10292337},
abstractNote = {Architectural, Engineering, and Construction (AEC) project teams adopt different methods to facilitate collaboration to achieve sustainability goals, which requires a high level of expertise integration. Tracking expertise flows in interdisciplinary and inter-organizational project networks is challenging because of the unique project nature, fluid expertise boundaries, and varying project requirements. It can be even more difficult considering sustainability outcomes, due to the need for high-level expertise integration. Social network approach addresses the integration and information flow dynamics. However, there is a knowledge gap regarding what network characteristics are favorable for improved sustainability outcomes in AEC projects, how they evolve during delivery, and how relevant expertise flows through project networks. To respond to the need in the literature, this study aims to develop a holistic understanding of AEC project team networks and associated characteristics that allow experts to exchange knowledge to optimize sustainability outcomes for built environment projects. We longitudinally collected e-mail exchange, observational, and archival data during the design phase of an AEC case study project and performed Social Network Analysis (SNA) bolstered by mixed methods. Results suggest that network topology matters for AEC project teams. In other words, understanding the interactions between components of a network (e.g., expertise areas represented and distributed in the network and the number of boundary spanners) is as important as the network parameters for better sustainability outcomes.},
journal = {Proceedings of EPOC 2020},
author = {Duva, Meltem and Mollaoglu, Sinem and Zhao, Dong and Frank, Kenneth A.},
editor = {Faust, Kasey and Kanjanabootra, Sittimont}
}
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