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Data in design: How big data and thick data inform design thinking projects

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  • Mortati, Marzia
  • Magistretti, Stefano
  • Cautela, Cabirio
  • Dell’Era, Claudio

Abstract

Scholars and practitioners have recognized that making innovation happen today requires renewed approaches focused on agility, dynamicity, and other organizational capabilities that enable firms to cope with uncertainty and complexity. In turn, the literature has shown that design thinking is a useful methodology to cope with ill-defined and wicked problems. In this study, we address the question of the little-known role of different types of data in innovation projects characterized by ill-defined problems requiring creativity to be solved. Rooted in qualitative observation (thick data) and quantitative analyses (big data), we investigate the role of data in eight design thinking projects dealing with ill-defined and wicked problems. Our findings highlight the practical and theoretical implications of eight practices that differently make use of big and thick data, informing academics and practitioners on how different types of data are utilized in design thinking projects and the related principles and practices.

Suggested Citation

  • Mortati, Marzia & Magistretti, Stefano & Cautela, Cabirio & Dell’Era, Claudio, 2023. "Data in design: How big data and thick data inform design thinking projects," Technovation, Elsevier, vol. 122(C).
    • Handle: RePEc:eee:techno:v:122:y:2023:i:c:s0166497222002395
    DOI: 10.1016/j.technovation.2022.102688
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    Cited by:

    1. Cai, Ying & Lin, Jun & Zhang, Ruxin, 2023. "When and how to implement design thinking in the innovation process: A longitudinal case study," Technovation, Elsevier, vol. 126(C).
    2. Ilaria Mariani & Irene Bianchi, 2023. "Conceptualising Digital Transformation in Cities: A Multi-Dimensional Framework for the Analysis of Public Sector Innovation," Sustainability, MDPI, vol. 15(11), pages 1-22, May.

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