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AI-Driven Quality Function Deployment for Product Service Systems: A Comparative Study in the Photovoltaic systems’ Sector

Mario Fargnoli et al.

Engineering Management Journal2026https://doi.org/10.1080/10429247.2026.2621689article
ABDC B
Weight
0.50

Abstract

Nowadays, the adoption of integrated product-service solutions has become imperative for companies dealing with ever-increasing, sophisticated customer requests. Advanced informatics tools can support companies in collecting and interpreting a large amount of information to provide more customer-tailored solutions. However, few studies have investigated the use of Artificial Intelligence (AI) tools in multiple criteria decision-making (MCDM) for the development of integrated product-service offerings. Using a case study from the green energy sector, this study explores the integration of AI tools with Quality Function Deployment for Product-Service Systems (QFDforPSS) to refine customer-centric PSS development by leveraging data from customer care services and customer relationship management systems. Results obtained by AI tools were compared with those of experts. Research findings underscore AI’s capability to extract detailed insights from customer data, enabling a more holistic and concurrent development of PSS characteristics. This research introduces a novel data-driven framework for PSS design, demonstrating AI’s potential to transform customer service data into actionable specifications and providing a more thorough analysis of PSS features. The study not only suggests several implications that can assist management in improving business offerings in the photovoltaic industry but also augments knowledge on the capabilities of QFD powered by AI tools.

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https://doi.org/https://doi.org/10.1080/10429247.2026.2621689

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@article{mario2026,
  title        = {{AI-Driven Quality Function Deployment for Product Service Systems: A Comparative Study in the Photovoltaic systems’ Sector}},
  author       = {Mario Fargnoli et al.},
  journal      = {Engineering Management Journal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/10429247.2026.2621689},
}

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AI-Driven Quality Function Deployment for Product Service Systems: A Comparative Study in the Photovoltaic systems’ Sector

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.