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Charting the Path of Technology-Integrated Competence in Industrial Design during the Era of Industry 4.0

Author

Listed:
  • Meng Zhang

    (Department of Industrial Design, ERICA Campus, Hanyang University, Ansan 15588, Republic of Korea)

  • Xi Zhang

    (Department of Industrial Design, ERICA Campus, Hanyang University, Ansan 15588, Republic of Korea)

  • Zibin Chen

    (Department of Industrial Design, ERICA Campus, Hanyang University, Ansan 15588, Republic of Korea)

  • Zhi Wang

    (Department of Industrial Design, Hubei University of Technology, Wuhan 430068, China)

  • Chenyang Liu

    (Academy of Arts & Design, Tsinghua University, Beijing 100084, China)

  • Kyungjin Park

    (Department of Industrial Design, ERICA Campus, Hanyang University, Ansan 15588, Republic of Korea)

Abstract

The fusion of emerging technologies with industrial design has catalyzed a fundamental shift in the aesthetics, user experiences, and service frameworks of products in the Industry 4.0 era. Simultaneously, this convergence has heightened the demands placed on the technological integration competencies of designers. Consequently, there exists a necessity to articulate a precise developmental trajectory for proficiency in industrial design that incorporates these novel technologies. This study initiates with a bibliometric analysis to quantify the scholarly literature relevant to this research domain. Subsequently, leveraging the insights from this analysis, semi-structured interviews were conducted with 15 experts spanning the United States, Europe, South Korea, and China. Our conclusions show the following: (1) Co-word analysis and cluster analysis techniques are applied to identify 80 technologies and four technological clusters that demonstrate strong associations with industrial design in the Industry 4.0 era. (2) Employing coding techniques and thematic analysis, four distinct skill domains emerge for technology-integrated industrial design: Industrial Design Skills, Industrial Design Knowledge, Ethical Considerations in Industrial Design, and Industrial Design Industry Insight. Furthermore, a limitation that affects these competencies is identified. (3) A recommended methodology for assessing these competencies is proposed. This study represented an expansion upon existing industrial design competencies. The empirical data generated herein serves as a valuable resource for practitioners and educators within the field of industrial design. Furthermore, it provides a theoretical groundwork for future models addressing technology-infused industrial design capabilities.

Suggested Citation

  • Meng Zhang & Xi Zhang & Zibin Chen & Zhi Wang & Chenyang Liu & Kyungjin Park, 2024. "Charting the Path of Technology-Integrated Competence in Industrial Design during the Era of Industry 4.0," Sustainability, MDPI, vol. 16(2), pages 1-23, January.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:751-:d:1319663
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    References listed on IDEAS

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    1. Kipper, Liane Mahlmann & Iepsen, Sandra & Dal Forno, Ana Julia & Frozza, Rejane & Furstenau, Leonardo & Agnes, Jéssica & Cossul, Danielli, 2021. "Scientific mapping to identify competencies required by industry 4.0," Technology in Society, Elsevier, vol. 64(C).
    2. Lorna Wildgaard, 2015. "A comparison of 17 author-level bibliometric indicators for researchers in Astronomy, Environmental Science, Philosophy and Public Health in Web of Science and Google Scholar," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 873-906, September.
    3. Su, Hsin-Ning & Moaniba, Igam M., 2017. "Investigating the dynamics of interdisciplinary evolution in technology developments," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 12-23.
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    Cited by:

    1. Jiaqi Li & Qinchuan Liu, 2025. "RETRACTED ARTICLE: Application of Generative Artificial Intelligence AIGC Technology Under Neural Network Algorithm in Game Character Art Design," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(1), pages 4652-4683, March.
    2. Yu Yao & Xiang Wang & Kaiqiang Sun, 2025. "Research on key factors influencing Chinese designers’ use of AIGC: An extension based on TAM and TRI," PLOS ONE, Public Library of Science, vol. 20(2), pages 1-29, February.

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