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An improved QFD model with the integration of BCM and CoCoSo method under the trust network

Yifan Wu et al.

International Journal of Information Technology and Decision Making2026https://doi.org/10.1142/s0219622026500458article
ABDC C
Weight
0.50

What the paper says

Quality function deployment (QFD) is a widely recognized tool for enhancing the quality of products and services. By the translation from customer requirements (CRs) to technical characteristics (TCs), customers’ requirements for products or services can be better satisfied. However, the traditional QFD reveals some inherent shortcomings, thereby making it difficult to adapt to complex decision-making environments and limiting practical applicability. The trust relationship between experts enhances the reliability of decision-making. Building on this idea, this paper proposes a trust relationship-based improved QFD model, aiming to address the shortcomings and enhance its decision-making reliability. In this paper, three major aspects are tackled: (1) the relative importance of CRs is determined using the base criterion method; (2) the priority of TCs is generated with the combined compromise solution method; and (3) the expert clustering process is conducted using an improved K-means algorithm. To validate the proposed model, a case study about the production of a CNC (Computer numerical control) machine is presented. Furthermore, the sensitivity analysis and discussions are performed to demonstrate the stability and superiority.

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https://doi.org/https://doi.org/10.1142/s0219622026500458

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@article{yifan2026,
  title        = {{An improved QFD model with the integration of BCM and CoCoSo method under the trust network}},
  author       = {Yifan Wu et al.},
  journal      = {International Journal of Information Technology and Decision Making},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1142/s0219622026500458},
}

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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.