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شناسایی و اولویت‌بندی چالش‌های پیاده‌سازی سیستم‌های خدمات محصول هوشمند به‌روش بهترین بدترین راف ـ فازی | ||
| مدیریت صنعتی | ||
| دوره 14، شماره 4، 1401، صفحه 539-564 اصل مقاله (639.33 K) | ||
| نوع مقاله: مقاله علمی پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/imj.2022.336855.1007910 | ||
| نویسندگان | ||
| مریم اسماعیل زاده1؛ عالیه کاظمی* 2؛ حسین صفری3 | ||
| 1کارشناسی ارشد، گروه مدیریت صنعتی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران. | ||
| 2استاد گروه مدیریت عملیات و علوم تصمیم، دانشکده مدیریت، دانشگاه تهران، تهران، ایران. | ||
| 3استاد گروه مدیریت تکنولوژی و نوآوری، دانشکده مدیریت، دانشگاه تهران، تهران، ایران. | ||
| چکیده | ||
| هدف: هدف از این پژوهش، بررسی و شناسایی چالش‌های پیاده‌سازی سیستم‌های خدمات محصول هوشمند و ارزیابی و اولویت‌بندی این چالش‌ها، به‌عنوان یکی از اقدام‌های اساسی اولیه برای اجرای این سیستم است. روش: در این مقاله ابتدا چالش‌های پیاده‌سازی سیستم‌های خدمات محصول هوشمند، از طریق مرور ادبیات، بررسی اسناد، مصاحبه با صاحب‌نظران و روش دلفی فازی شناسایی شد. در ادامه با استفاده از روش بهترین بدترین راف ـ فازی، چالش‌های شناسایی‌شده اولویت‌بندی شدند. یافته‌ها: بیست چالش پیاده‌سازی سیستم‌های خدمات ـ محصول هوشمند، در هفت گروه اصلی طبقه‌بندی و به‌روش بهترین بدترین راف ـ فازی ارزیابی شدند. بر اساس نتایج، چالش‌های مالی و فرایندی، مهم‌ترین گروه شناخته شد. روش بهترین بدترین راف ـ فازی با بررسی هم‌زمان عدم قطعیت درون‌فردی و بین‌فردی باعث می‌شود که ارزیابی به‌دست‌آمده، دقت و عینیت بیشتری را در مقایسه با روش بهترین بدترین مبتنی بر منطق فازی یا مبتنی بر تئوری راف ارائه دهد. نتیجه‌گیری: با استفاده از نتایج این پژوهش شرکت‌های تولیدی و خدماتی، می‌توانند چالش‌های پیش‌ِرو در مسیر پیاده‌سازی سیستم‌های خدمات محصول هوشمند را دقیق‌تر ارزیابی کنند و به‌نحوی مناسب، منابع محدود سازمانی را برای رفع چالش‌های شناسایی‌شده اختصاص دهند. | ||
| کلیدواژه‌ها | ||
| سیستم خدمات ـ محصول؛ سیستم هوشمند؛ چالش‌های پیاده‌سازی سیستم؛ روش بهترین بدترین راف ـ فازی | ||
| عنوان مقاله [English] | ||
| Identifying and Prioritizing Challenges of Implementing Smart Product-service Systems Using the Best-worst Rough-fuzzy Method | ||
| نویسندگان [English] | ||
| Maryam Esmeilzadeh1؛ Aliyeh Kazemi2؛ Hossein Safari3 | ||
| 1MSc., Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran. | ||
| 2Prof., Department of Operations Management and Decision Sciences, Faculty of Management, University of Tehran, Tehran, Iran. | ||
| 3Prof., Department of Innovation and Technology Management, Faculty of Management, University of Tehran, Tehran, Iran. | ||
| چکیده [English] | ||
| Objective: Smart product-service systems (SPSS) as a new paradigm was presented recently, which created considerable changes in the industry and production, especially in the production of smart home appliances. Despite many achievements in implementing SPSS, this system faces many challenges in the development and implementation processes. This study aims to identify and analyze the challenges of implementing an SPSS and evaluate and prioritize them as one of the most basic initial steps in implementing the system. Methods: In this paper, first, the challenges of implementing SPSS are identified through literature review, document review, interviews with experts, and the fuzzy Delphi method. Then the best-worst rough-fuzzy method is used to prioritize the identified challenges. Results: Twenty challenges of implementing SPSS were classified into seven main groups consisting of staff, information security, technology, finance and process, design, infrastructure, and government/market, and evaluated by the best-worst rough-fuzzy method. The main challenges are financial and process, technology, employees, design, market and government, infrastructure and information security, respectively. In the same way, the weight and rank of all twenty challenges classified in these groups were determined. Since evaluating and prioritizing the challenges of implementing the SPSS is a multi-criteria decision-making process and includes uncertainties that may lead to incorrect evaluation results, in this research, the concepts of rough set theory and fuzzy logic, which are efficient in such conditions, are used as the prioritization method. Since the best-worst rough-fuzzy method simultaneously integrates both intra-individual and interpersonal uncertainty and takes advantage of the features of the fuzzy set in managing individual verbal ambiguities and the benefits of the rough set theory in examining the diversity of group preferences, the model has a good performance for finding optimal and fuzzy rough weights of challenges and makes the obtained evaluation more accurate and objective than the best-worst method based on fuzzy logic or rough theory. Conclusion: Since SPSS is rapidly expanding as a new field in manufacturing and industry, and the development of smart home appliances is one of the waves of technology in the future and will provide new and exciting opportunities for businesses, home appliance manufacturing companies are bound to compete to get their share of these opportunities. Industrial enterprises, especially in the home appliance industry, can be more profitable, and improve their market share in this industry by turning to the integration of products and smart services based on information and communication technology and joining the production companies that use SPSS. Using the results of this study, manufacturing and service companies can more accurately assess the challenges ahead in implementing SPSS and appropriately allocate organizational resources to manage the challenges. | ||
| کلیدواژه‌ها [English] | ||
| Service-product System, Smart system, System implementation challenges, Best-Worst rough-fuzzy method | ||
| مراجع | ||
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References Chang, B., Chang, C. W., & Wu, C. H. (2011). Fuzzy DEMATEL method for developing supplier selection criteria. Expert systems with Applications, 38(3), 1850-1858. Chen, S., Xiao, Y., Ren, T., Chen, J., & Huang, C. (2020, August). The Design Research of Smart Product-Service System Oriented to User Experience. In 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) (pp. 300-304). IEEE. Chen, Z., Lu, M., Ming, X., Zhang, X., & Zhou, T. (2020). Explore and evaluate innovative value propositions for smart product service system: A novel graphics-based rough-fuzzy DEMATEL method. Journal of Cleaner Production, 243, 118672. Chen, Z., Ming, X., Zhang, X., Yin, D., & Sun, Z. (2019). A rough-fuzzy DEMATEL-ANP method for evaluating sustainable value requirement of product service system. Journal of Cleaner Production, 228, 485-508. Chen, Z., Ming, X., Zhou, T., Chang, Y., & Sun, Z. (2020). A hybrid framework integrating rough-fuzzy best-worst method to identify and evaluate user activity-oriented service requirement for smart product service system. Journal of cleaner production, 253, 119954. Chowdhury, S., Haftor, D., & Pashkevich, N. (2018). Smart product-service systems (Smart PSS) in industrial firms: a literature review. Procedia Cirp, 73, 26-31. Guo, S., & Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems, 121, 23-31. Liang, F., Brunelli, M., & Rezaei, J. (2020). Consistency issues in the best worst method: Measurements and thresholds. Omega, 96, 102175. Mont, O. K. (2002). Clarifying the concept of product–service system. Journal of cleaner production, 10(3), 237-245. Phuyal, S., Bista, D., & Bista, R. (2020). Challenges, opportunities and future directions of smart manufacturing: a state of art review. Sustainable Futures, 2, 100023. Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57. Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126-130. Sjödin, D. R., Parida, V., Leksell, M., & Petrovic, A. (2018). Smart Factory Implementation and Process Innovation: A Preliminary Maturity Model for Leveraging Digitalization in Manufacturing Moving to smart factories presents specific challenges that can be addressed through a structured approach focused on people, processes, and technologies. Research-Technology Management, 61(5), 22-31. Song, W., & Cao, J. (2017). A rough DEMATEL-based approach for evaluating interaction between requirements of product-service system. Computers & Industrial Engineering, 110, 353-363. Stević, Ž., Pamučar, D., Kazimieras Zavadskas, E., Ćirović, G., & Prentkovskis, O. (2017). The selection of wagons for the internal transport of a logistics company: A novel approach based on rough BWM and rough SAW methods. Symmetry, 9(11), 264. Valencia Cardona, A. M., Mugge, R., Schoormans, J. P., & Schifferstein, H. N. (2014). Challenges in the design of smart product-service systems (PSSs): Experiences from practitioners. In Proceedings of the 19th DMI: Academic Design Management Conference. Design Management in an Era of Disruption, London, UK, September 2-4, 2014. Design Management Institute. Valencia, A., Mugge, R., Schoormans, J., Schifferstein, H. (2015). The design of smart product-service systems (PSSs): An exploration of design characteristics. International Journal of Design, 9(1). Vazquez-Martinez, G. A., Gonzalez-Compean, J. L., Sosa-Sosa, V. J., Morales-Sandoval, M., & Perez, J. C. (2018). CloudChain: A novel distribution model for digital products based on supply chain principles. International Journal of Information Management, 39, 90-103. Zhai, L. Y., Khoo, L. P., & Zhong, Z. W. (2008). A rough set enhanced fuzzy approach to quality function deployment. The International Journal of Advanced Manufacturing Technology, 37(5-6), 613-624. Zhang, F., Jiang, P., Zhu, Q., & Cao, W. (2012). Modeling and analyzing of an enterprise collaboration network supported by service-oriented manufacturing. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 226(9), 1579-1593. Zhang, J. (2017). Evaluating regional low-carbon tourism strategies using the fuzzy Delphi-analytic network process approach. Journal of Cleaner Production, 141, 409-419. Zheng, P., Wang, Z., Chen, C. H., & Khoo, L. P. (2019). A survey of smart product-service systems: Key aspects, challenges and future perspectives. Advanced engineering informatics, 42, 100973. | ||
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