A systematic study of meetings in AEC/FM from the language/action perspective

Observing conversations during meetings held as part of a year-long pilot program on Building Information Modeling and Facility Management revealed the presence of communication inefficiencies among meeting participants. Although meeting participants voiced their unmet needs and misunderstandings during meetings, these breakdowns often went unnoticed and unresolved for months, slowing the progress of the pilot program. This showed that meeting participants cannot systematically understand what breakdowns were voiced and whether and how they were handled during meeting conversations. This thesis contributes a formalized method for systematically analyzing conversations in meetings from the Language Action Perspective (LAP) so that breakdown handling can be observed and analyzed. This method is composed of three elements: 1) A method to convert meeting conversations into structured data, 2) A method that uses structured meeting conversation data to identify breakdowns and their details, and 3) A method for using structured meeting conversation data to study how meeting participants handle breakdowns using the four conversation types from the LAP. The first contribution is a method that converts a meeting transcript into structured meeting conversation data that captures 1) how individual meeting participants use language 2) what meeting activities take place, and 3) what types of content are discussed during a meeting. It was formalized by following a deductive qualitative coding methodology and by taking the LAP. The second contribution is a method that finds and details breakdowns using structured meeting conversation data. It was formalized by creating an operational definition for the LAP's conceptualization of a breakdown. The third contribution is a method that provides a data-based and visual way to represent breakdown handling using structured meeting conversation data. This method was developed by operationalizing the four LAP conversation types and qualitative data analysis. Application of the first contribution to 13 meetings held by three different teams shows that the method to convert meetings into structured data is applicable to multiple meetings: the method converts over 90% of the utterances made into structured data. Validation of this method using four meetings demonstrates that the method is reliable. Two researchers could independently and consistently convert meeting conversations into structured data. Application of the second contribution to nine meetings resulted in finding 18 to 42 breakdowns per meeting. This shows that breakdowns can be found from structured meeting conversation data. Similar to the first contribution, two researchers could independently apply the method to the same meeting data and agree on whether part of a conversation voiced a breakdown in 85% of the cases. Application of the third contribution shows that structured meeting conversation data can be used to identify whether and how a breakdown is handled during a meeting conversation and across multiple meeting conversations. These contributions create the foundation for future research that automates the creation of structured meeting conversation data to analyze conversation patterns so that, e.g., the patterns of teams with incentivized versus disincentivized actors can be understood, and that develops metrics for meeting success related to specific conversation patterns

Keywords: Engineering.
Advisor: Fischer Martin
Eriksson Kent
Jain Rishee