沈阳工业大学学报（社会科学版）2025，Vol.18Issue(2)：166-174,9.DOI:10.7688/j.issn.1674-0823.2025.02.04
基于粗糙数BWM-TOPSIS的智能产品服务系统评估研究
Research on smart product-service systems evaluation based on rough number BWM-TOPSIS and its application
摘要
Abstract
With the deep integration of digital technology and products,enterprises are facing problems such as diversified market demands and high demands from consumers for personalized service experiences.Many enterprises pay more attention to the close integration of products and services,hoping to meet the diversified needs of consumer groups and enhance their market competitiveness by improving the level of smart product-service systems.Currently,there is a relative lack of evaluation research on smart product-service systems,making it difficult for enterprises to accurately understand the advantages and disadvantages of their own solutions,thereby limiting their optimization and development.Based on existing literature and theory,this paper clarifies the core characteristics of smart product-service systems,considers factors related to the design of smart product-service systems,and constructs an evaluation index system for smart product-service systems,which includes 10 secondary indicators under four aspects:user experience,economy,environmental impact,and service.It uses the rough number improved best-worst method(BWM)to calculate indicator weights and accurately describes the distribution of fuzzy evaluation information to ensure the quality of decision information.At the same time,it uses the rough number improved TOPSIS method to rank the alternative solutions.By introducing Euclidean Distance and combining the concept of distance in rough set theory for calculation,the uncertain characteristics of the data are reflected.Four new energy intelligent vehicles,namely Tesla Model 3,NIO L7,Xiaopeng P7i,and NIO ET5,which are suitable for the research scenario,are selected as alternative solutions for example calculations.It is found that the smart product-service systems of NIO ET5 perform outstandingly under the evaluation criteria in this article.The evaluation method combining BWM and TOPSIS based on rough number improvement can effectively avoid uncertain factors in the evaluation of smart product-service systems.Rough numbers objectively integrate group opinions,and the combination of BWM and TOPSIS methods effectively simplifies the calculation process,improves the accuracy of judgments,and increases the reliability of weight results.This paper selects new energy vehicles that meet the application scenarios as research examples,fully demonstrating the feasibility and effectiveness of the constructed evaluation model.It provides an effective scientific basis and references for the development of smart product-service systems,promotes the development of smart product-service systems evaluation,and provides theoretical support and practical guidance for enterprises to achieve business model innovation and improve user satisfaction and competitiveness.关键词
智能产品服务系统/新能源汽车/粗糙数/最优最劣方法/TOPSIS算法Key words
smart product-service systems/new energy vehicles/rough number/best-worst method/TOPSIS method引用本文复制引用
温馨,翟淑媛..基于粗糙数BWM-TOPSIS的智能产品服务系统评估研究[J].沈阳工业大学学报（社会科学版）,2025,18(2):166-174,9.基金项目
教育部人文社会科学研究基金规划基金项目(22YJA630095). （22YJA630095）
