Framing and Tracing Human-Centered Design Teams’ Method Selection: An Examination of Decision-Making Strategies

Author:

Rao Vivek1,Kim Euiyoung2,Kwon Jieun3,Agogino Alice M.4,Goucher-Lambert Kosa5

Affiliation:

1. Department of Mechanical Engineering, University of California, Berkeley, 420 Sutardja Dai Hall, Berkeley, CA 94720

2. Department of Design, Organization, and Strategy (DOS), Delft University of Technology, Room B-4-040, Landbergstraat 15, Delft 2628 CE, The Netherlands

3. College of Design, University of Minnesota, The Sharp Forest Apartment 207-103, Suseodong, Gangnamgu, Seoul 06203, South Korea

4. Department of Mechanical Engineering, University of California, Berkeley, Blum Hall 200E, Berkeley, CA 94704

5. Department of Mechanical Engineering, University of California, Berkeley, 6179 Etcheverry Hall, Berkeley, CA 94720

Abstract

Abstract Designers’ choices of methods are well known to shape project outcomes. However, questions remain about why design teams select particular methods and how teams’ decision-making strategies are influenced by project- and process-based factors. In this mixed-methods study, we analyze novice design teams’ decision-making strategies underlying 297 selections of human-centered design methods over the course of three semester-long project-based engineering design courses. We propose a framework grounded in 100+ factors sourced from new product development literature that classifies design teams’ method selection strategy as either Agent- (A), Outcome- (O), or Process- (P) driven, with eight further subclassifications. Coding method selections with this framework, we uncover three insights about design team method selection. First, we identify fewer outcomes-based selection strategies across all phases and innovation types. Second, we observe a shift in decision-making strategy from user-focused outcomes in earlier phases to product-based outcomes in later phases. Third, we observe that decision-making strategy produces a greater heterogeneity of method selections as compared to the class average as a whole or project type alone. These findings provide a deeper understanding of designers’ method selection behavior and have implications for effective management of design teams, development of automated design support tools to aid design teams, and curation of design method repositories.

Funder

Center for Long-Term Cybersecurity, University of California Berkeley

Publisher

ASME International

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Mechanical Engineering,Mechanics of Materials

Reference97 articles.

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