Enhancing User Acceptance of Sustainability-Oriented Modularity in Industrial Design: Key Drivers and Insights
DOI:
https://doi.org/10.5281/zenodo.13692491Keywords:
Modularity, Industrial Design, User Acceptance, Sustainability, Structural Equation Modeling (SEM)Abstract
The focus on environmental sustainability is transforming industrial design, shifting from linear models to sustainable approaches. This study examines modularity—a design strategy using interchangeable components for assembly, replacement, or upgrades—to enhance sustainability in industrial design. Despite its potential, modularity's adoption is limited by user acceptance. The research develops a user acceptance model for sustainability-oriented modularity, including factors like Perceived Sustainability Benefits, Usability, Customization Potential, and Cost Efficiency. Using qualitative interviews and surveys, the study identifies key acceptance drivers. Findings highlight the influence of sustainability, usability, and environmental awareness, offering insights for enhancing modularity adoption in sustainable design.
References
Baldwin, C. Y., & Clark, K. B. (2000). Design rules: The power of modularity. MIT Press. https://doi.org/10.7551/mitpress/2366.001.0001
Bocken, N. M., de Pauw, I., Bakker, C., & van der Grinten, B. (2016). Product design and business model strategies for a circular economy. Journal of Industrial and Production Engineering, 33(5), 308-320. https://doi.org/10.1080/21681015.2016.1172124
Creswell, J. W., & Clark, V. L. P. (2017). Designing and conducting mixed methods research. Sage Publications. https://doi.org/10.1111/j.1753-6405.2007.00096.x
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning. https://doi.org/10.1007/978-3-642-04898-2_395
Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Press. https://www.guilford.com/books/Principles-and-Practice-of-Structural-Equation-Modeling/Rex-Kline/9781462551910
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill. https://doi.org/10.1007/978-3-030-39903-0_301545
Roy, R., & Cheruvu, K. (2009). A competitive framework for industrial product-service systems. International Journal of Internet Manufacturing and Services, 2(1), 4-29. https://doi.org/10.1504/IJIMS.2009.031337
Schmidt, W. P., & Butt, F. (2006). Life cycle tools within Ford of Europe’s product sustainability index: Case study Ford S-MAX & Ford Galaxy. The International Journal of Life Cycle Assessment, 11(5), 315-322. https://doi.org/10.1065/lca2006.08.267
Sonego, M., Echeveste, M. E. S., & Debarba, H. G. (2018). The role of modularity in sustainable design: A systematic review. Journal of Cleaner Production, 176, 196-209. https://doi.org/10.1016/j.jclepro.2017.12.106
Tamilmani, K., Rana, N. P., Prakasam, N., & Dwivedi, Y. K. (2019). The battle of brain vs. heart: A literature review and meta-analysis of “hedonic motivation” use in UTAUT2. International Journal of Information Management, 46, 222-235. https://doi.org/10.1016/j.ijinfomgt.2019.01.008
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
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