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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">PBES</journal-id><journal-title-group><journal-title>Proceedings of Business and Economic Studies</journal-title></journal-title-group><issn>2209-2641</issn><eissn>2209-265X</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/pbes.v7i5.8607</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Dynamic Analysis of Customer Demand Based on Intuitionistic Fuzzy Number in Product Planning</title><url>https://artdesignp.com/journal/PBES/7/5/10.26689/pbes.v7i5.8607</url><author>YiYongguang,WangZengqiang</author><pub-date pub-type="publication-year"><year>2024</year></pub-date><volume>7</volume><issue>5</issue><history><date date-type="pub"><published-time>2024-10-22</published-time></date></history><abstract>To address the fuzziness and variability in determining customer demand importance, a dynamic analysis method based on intuitionistic fuzzy numbers is proposed. First, selected customers use intuitionistic fuzzy numbers to represent the importance of each demand. Then, the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator, yielding a dynamic vector of the subjective importance of the demand index. Finally, the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Wang ZQ, Chen ZS, Garg H, et al., 2022, An Integrated Quality-Function-Deployment and Stochastic-Dominance-Based Decision-Making Approach for Prioritizing Product Concept Alternatives. Complex Intell Syst, 8(3): 2541–2556. https://doi.org/10.1007/s40747-022-00681-1</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B2" content-type="article"><label>2</label><element-citation publication-type="journal"><p>Wang H, Xin YJ, Deveci M, et al., 2024, Leveraging Online Reviews and Expert Opinions for Electric Vehicle Type Prioritization. Computers &amp; Industrial Engineering, 197(11): 110579. https://doi.org/10.1016/j.cie.2024.110579</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B3" content-type="article"><label>3</label><element-citation publication-type="journal"><p>Chen ZS, Zhu Z, Wang XJ, et al., 2023, Multiobjective Optimization-Based Collective Opinion Generation with Fairness Concern. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 53(9): 5729–5741. https://doi.org/10.1109/TSMC.2023.3273715</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B4" content-type="article"><label>4</label><element-citation publication-type="journal"><p>Houede DA, Ibrango I, Ouedraogo A, 2024, Entropy Solutions for Some Elliptic Anisotropic Problems Involving Variable Exponent with Fourier Boundary Conditions and Measure Data. Journal of Elliptic and Parabolic Equations, 10(1): 237–277. https://doi.org/10.1007/s41808-023-00259-z</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B5" content-type="article"><label>5</label><element-citation publication-type="journal"><p>Wang Z, Fung RYK, Li YL, et al., 2018, An Integrated Decision-Making Approach for Designing and Selecting Product Concepts Based on QFD and Cumulative Prospect Theory. International Journal of Production Research, 56(5): 2003–2018. https://doi.org/10.1080/00207543.2017.1351632</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
