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Lookup NU author(s): Ruifeng Zhou
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© 2023 Informa UK Limited, trading as Taylor & Francis Group. Many theoretical methods have been applied to research user behaviour and requirements. However, the uncertainty associated with customer characteristics often biases the conclusions drawn from customer research and affects the effectiveness of product design. In this paper, Bayesian networks (BN) are introduced into the research on customer behaviour analysis based upon theory of planned behaviour (TPB), and an analysis model driven by customer research data is established from the perspective of user behaviour intention to guide design optimisation. Combining the User background Factor with the TPB Factor, the model analyses the uncertainty of the association between the two, and corrects the errors in the designer's prior knowledge through structural learning. By a case study the paper finds that the evaluations that enhance customers’ subjective norms and perceived behavioural control lead to a greater probability of purchase or use. In addition, customers with specific characteristics are more inclined to generate behaviour intention. The paper finally provides a design optimisation plan based upon the result of the research and discusses about the advantages of the research approaches and the directions of future researches.
Author(s): Liu Y, Hu K, Zhou R, Ai X, Chen Y
Publication type: Article
Publication status: Published
Journal: International Journal of Production Research
Year: 2024
Volume: 62
Issue: 13
Pages: 4696-4716
Online publication date: 26/10/2023
Acceptance date: 05/10/2023
ISSN (print): 0020-7543
ISSN (electronic): 1366-588X
Publisher: Taylor and Francis Ltd
URL: https://doi.org/10.1080/00207543.2023.2271093
DOI: 10.1080/00207543.2023.2271093
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