User-generated content (UGC) provides significant advantages for new product development (NPD) by providing a continuous, unsolicited stream of real-time consumer feedback. emerging organically across digital platforms, UGC offers a broader and more inclusive pool of insights compared to traditional methods that require active solicitation. By mining UGC, firms can efticiently capture need- and solution-related insights, identify innovative product ideas, extract valuable features, and better understand evolving customer requirements. This approach enhances product design efficiency, reduces market rejection rates, and accelerate time-to-market.
Building on these advantages, this thesis comprehensively examines the role of UGC in NPD process through a data-driven approach. The research pursues three main objectives. First, a systematic literature review (SLR) synthesizes existing research on UGC in NPD, identifying key themes, contexts, and methodologies through multifaceted techniques. This review highlights research gaps and proposes future directions. Second, the thesis also develops a framework for assessing consumer acceptance of a new product by analyzing UGC, employing topic modeling, sentiment analysis, and statistical modeling, demonstrated through a study on ChatGPT. Third, it introduces a framework for identifying product obsolescence factors and construeting time-series obsolescence indexes (OT) using UGC. This framework leverages large language models (LLMs) such as ChatGP I-40, along with multientena decision-making and sentiment analysis, to provide insights into produet longevity.
Overall, this thesis advances the understanding of how UGC can be systematically leveraged to support diverse purposes within the NPD process. By capturing real-time consumer insights, UGC facilitates market acceptance evaluation, and product lifecycle management. The proposed frameworks not only make theoretical contributions to the intersection of UGC and innovation management but also deliver practieal tools for fins seeking to enhance the efficiency, responsiveness, and sustainability of their product development efforts.
| Date | 27 Sept 2025 |
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| Original language | American English |
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| Awarding Institution | - École de technologie supérieure
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| Supervisor | Yvan Beauregard (Supervisor) |
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Azar Nasrabadi, M. (Author),
Beauregard (Supervisor),
27 Sept 2025Student thesis: Doctoral thesis › Doctorate in Engineering: Engineering