پیش‌بینی راهکارهای مناسب جهت پیاده‌سازی مدیریت زنجیره تأمین تجهیزات در سالن‌های ورزشی
محورهای موضوعی :
مدیریت دانش
فاطمه بیابانی
1
(کارشناسی ارشد، گروه مدیریت ورزشی، دانشگاه آزاد اسلامی، قروه، ایران.)
نوید مهتاب
2
(استادیار گروه مدیریت ورزشی، دانشگاه آزاد اسلامی، قروه، ایران)
فاطمه معتقدی
3
(کارشناسی ارشد، گروه مدیریت ورزشی، دانشگاه آزاد اسلامی، همدان، ایران.)
تاریخ دریافت : 1400/06/18
تاریخ پذیرش : 1400/08/05
تاریخ انتشار : 1400/11/01
کلید واژه:
باشگاه‌های ورزشی,
مدیریت,
زنجیره تأمین,
چکیده مقاله :
هدف این پژوهش شناسایی راهکارهای مناسب جهت پیاده‌سازی مدیریت زنجیره تأمین تجهیزات در سالن‌های ورزشی بود. جهت دستیابی به این هدف از روش تحقیق اکتشافی نوع تحقیقات ترکیبی استفاده گردید. جامعه آماری در بخش کیفی تحقیق متخصصان مدیریت ورزشی که نمونه به حجم 15 نفر انتخاب گردید که حجم نمونه تا رسیدن به اشباع نظری بوده است و در بخش کمی تحقیق از روش نمونه‌گیری در دسترس نمونه‌ای به حجم 245 نفر از مشتریان سالن‌های ورزشی به‌صورت تصادفی انتخاب شدند. برای جمع‌آوری اطلاعات در بخش کیفی پژوهش از روش مصاحبه استفاده گردید و در بخش کمی پژوهش نیز از پرسشنامه تدوین‌شده در بخش کیفی تحقیق استفاده شد که بر اساس نتایج آلفای کرونباخ میزان پایایی پرسشنامه برابر با 87/0 بود و روایی محتوایی پرسشنامه نیز توسط متخصصین مورد تائید قرار گرفت. برای تحلیل اطلاعات در بخش کیفی از تحلیل محتوا استفاده گردید و در بخش کمی از روش تحلیل عاملی تأییدی و آزمون فریدمن استفاده گردید. یافته‌ها در بخش کیفی پژوهش نشان داد که مدیریت زنجیره تأمین خدمات از مؤلفه‌های مدیریت منابع، هزینه مداری، ارزیابی عملکرد، نیازسنجی، تأمین خدمات، تعاملات، مدیریت تقاضا، ظرفیت انگاری، مدیریت اطلاعات تشکیل‌شده است. نتایج تحلیل عاملی تأییدی با مقدار RMSEA05/0 مورد تائید قرار گرفت. نتایج آزمون فریدمن نیز نشان داد که طبق نتایج مدیریت تقاضا، نیازسنجی و مدیریت منابع به ترتیب با میانگین رتبه 75/6 و 06/6 و 01/6 بیشترین تأثیر را به‌عنوان راهکار مناسب دارند.
چکیده انگلیسی:
The purpose of this study was to identify appropriate solutions to implement the supply chain management in sports halls. in order to achieve this purpose, exploratory research method was used. statistical population in the qualitative part of research management experts, which was selected as sample to 15 people, sample size to theoretical saturation and in the quantitative part of the research method of sampling method, sample size of 245 people were selected randomly. in order to collect information in the qualitative part of the research, the interview method was used and in the quantitative part of the research, the questionnaire was used in the qualitative part of the research, which was based on cronbach's alpha, which was equal to 87 / 0 and content validity of the questionnaire was also approved by experts. to analyze the data in the qualitative section, content analysis was used and a quantitative part of confirmatory factor analysis and friedman test was used. findings in the qualitative part of research show that supply chain management is composed of components of resource management, orbital cost, performance evaluation, service supply, demand management, constructivism, information management. the results of the confirmatory factor analysis were confirmed by RMSEA05. the results of friedman test showed that according to the results of demand management,and resource management respectively had the highest impact as a suitable solution, respectively.
منابع و مأخذ:
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Asamoah, D., Agyei-Owusu, B., Andoh-Baidoo, F. K., & Ayaburi, E. (2021). Inter-organizational systems use and supply chain performance: Mediating role of supply chain management capabilities. International Journal of Information Management, 58, 102195.
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Büyüközkan, G., & Göçer, F. (2018). Digital Supply Chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157-177.
Casado-Vara, R., Prieto, J., De la Prieta, F., & Corchado, J. M. (2018). How blockchain improves the supply chain: Case study alimentary supply chain. Procedia computer science, 134, 393-398.
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Dong, C., Boute, R., McKinnon, A., & Verelst, M. (2018). Investigating synchromodality from a supply chain perspective. Transportation Research Part D: Transport and Environment, 61, 42-57.
Gibson, H., McIntyre, S., MacKay, S., & Riddington, G. (2005). The economic impact of sports, sporting events, and sports tourism in the UK The DREAM™ Model. European Sport Management Quarterly, 5(3), 321-332.
Isik, F. (2011). Complexity in supply chains: a new approach to quantitative measurement of the supply-chain-complexity. Supply chain management, 21(4), 417-432.
Ivanov, D., Dolgui, A., & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829-846.
Jadhav, A., Orr, S., & Malik, M. (2019). The role of supply chain orientation in achieving supply chain sustainability. International journal of production economics, 217, 112-125.
Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2020). Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications. International journal of production economics, 219, 179-194.
KAREGAR GH., GOUDARZI M., ASSADI H., HONARI H. (2006). ANALYZING THE CONDITIONS OF IRAN SPORTS COMPLEXES DETERMINING EFFECTIVE FACTORS ON PRODUCTIVITY FROM EXPERTS' POINT OF VIEW AND PROVIDING PRODUCTIVITY MODEL , Volume - , Number 28; Page(s) 127 To 149.
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Li, S. (2020). Supply Chain Financing Strategy in Sports Industry Based on Game Theory. International Conference on Application of Intelligent Systems in Multi-modal Information Analytics,
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Nunes, L., Causer, T., & Ciolkosz, D. (2020). Biomass for energy: A review on supply chain management models. Renewable and Sustainable Energy Reviews, 120, 109658.
Patterson, K. A., Grimm, C. M., & Corsi, T. M. (2003). Adopting new technologies for supply chain management. Transportation Research Part E: Logistics and Transportation Review, 39(2), 95-121.
Pope, D. (2020). Assessing Cause and Effect in Supply Chain Problems Using Sports Ranking Models. Operations and Supply Chain Management: An International Journal, 13(1), 23-30.
Roy, M. D., & Sana, S. S. (2021). Inter-dependent lead-time and ordering cost reduction strategy: a supply chain model with quality control, lead-time dependent backorder and price-sensitive stochastic demand. Opsearch, 1-21.
Sodhi, M. S., & Tang, C. S. (2021). Supply chain management for extreme conditions: Research opportunities. Journal of Supply Chain Management, 57(1), 7-16.
Somjai, S., Rattamanee, K., Thongdonpum, K., & Jermsittiparsert, K. (2019). The stakeholder’s pressure and environmental supply chain: Does the environmental training matter in Thai sports manufacturing firms?
Tarighi, R., Sajjadi, S. N., Hamidi, M., & Khabiri, M. (2017). Factors affecting the development of the electronic marketing capacity of professional sports federations. Annals of Applied Sport Science, 5(2), 87-96.
Thomas, D. J., & Griffin, P. M. (1996). Coordinated supply chain management. European journal of operational research, 94(1), 1-15.
Tiwari, S., Wee, H.-M., & Daryanto, Y. (2018). Big data analytics in supply chain management between 2010 and 2016: Insights to industries. Computers & industrial engineering, 115, 319-330.
Wiedmer, R., & Griffis, S. E. (2021). Structural characteristics of complex supply chain networks. Journal of Business Logistics, 42(2), 264-290.
Wieland, A. (2021). Dancing the supply chain: Toward transformative supply chain management. Journal of Supply Chain Management, 57(1), 58-73. (Persian).
Yektayar, M. (2019). Prioritizing Supply Chain Management Indicators in Sport. Sport Management Studies, 11(54), 71-92 (Persian). https://doi.org/10.22089/smrj.2018.4898.1946
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Al-Qaysi, B. J., & Hussein, H. A. (2019). Technology Management for Supply Chain in Sports Clubs Iraqi and Its Reflection on the Excellence Performance. Int. J Sup. Chain. Mgt Vol, 8(1), 804.
Asamoah, D., Agyei-Owusu, B., Andoh-Baidoo, F. K., & Ayaburi, E. (2021). Inter-organizational systems use and supply chain performance: Mediating role of supply chain management capabilities. International Journal of Information Management, 58, 102195.
Ayyildiz, E., & Gumus, A. T. (2021). Interval-valued Pythagorean fuzzy AHP method-based supply chain performance evaluation by a new extension of SCOR model: SCOR 4.0. Complex & Intelligent Systems, 7(1), 559-576.
Barman, A., Das, R., & De, P. K. (2021). An analysis of optimal pricing strategy and inventory scheduling policy for a non-instantaneous deteriorating item in a two-layer supply chain. Applied Intelligence, 1-25.
Beamon, B. M. (1998). Supply chain design and analysis:: Models and methods. International journal of production economics, 55(3), 281-294.
Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: a literature review. International Journal of Production Research, 57(15-16), 4719-4742.
Butt, A. S. (2021). Strategies to mitigate the impact of COVID-19 on supply chain disruptions: a multiple case analysis of buyers and distributors. The International Journal of Logistics Management.
Büyüközkan, G., & Göçer, F. (2018). Digital Supply Chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157-177.
Casado-Vara, R., Prieto, J., De la Prieta, F., & Corchado, J. M. (2018). How blockchain improves the supply chain: Case study alimentary supply chain. Procedia computer science, 134, 393-398.
Cox, A. (1999). Power, value and supply chain management. Supply chain management: An international journal.
De Giovanni, P. (2020). Blockchain and smart contracts in supply chain management: A game theoretic model. International journal of production economics, 228, 107855.
Dolgui, A., Ivanov, D., & Sokolov, B. (2020). Reconfigurable supply chain: The X-network. International Journal of Production Research, 58(13), 4138-4163.
Dong, C., Boute, R., McKinnon, A., & Verelst, M. (2018). Investigating synchromodality from a supply chain perspective. Transportation Research Part D: Transport and Environment, 61, 42-57.
Gibson, H., McIntyre, S., MacKay, S., & Riddington, G. (2005). The economic impact of sports, sporting events, and sports tourism in the UK The DREAM™ Model. European Sport Management Quarterly, 5(3), 321-332.
Isik, F. (2011). Complexity in supply chains: a new approach to quantitative measurement of the supply-chain-complexity. Supply chain management, 21(4), 417-432.
Ivanov, D., Dolgui, A., & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829-846.
Jadhav, A., Orr, S., & Malik, M. (2019). The role of supply chain orientation in achieving supply chain sustainability. International journal of production economics, 217, 112-125.
Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2020). Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications. International journal of production economics, 219, 179-194.
KAREGAR GH., GOUDARZI M., ASSADI H., HONARI H. (2006). ANALYZING THE CONDITIONS OF IRAN SPORTS COMPLEXES DETERMINING EFFECTIVE FACTORS ON PRODUCTIVITY FROM EXPERTS' POINT OF VIEW AND PROVIDING PRODUCTIVITY MODEL , Volume - , Number 28; Page(s) 127 To 149.
Kshetri, N. (2018). 1 Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80-89.
Lambert, D. M., & Cooper, M. C. (2000). Issues in supply chain management. Industrial marketing management, 29(1), 65-83.
Li, S. (2020). Supply Chain Financing Strategy in Sports Industry Based on Game Theory. International Conference on Application of Intelligent Systems in Multi-modal Information Analytics,
Min, H., & Zhou, G. (2002). Supply chain modeling: past, present and future. Computers & industrial engineering, 43(1-2), 231-249.
Mubarik, M. S., Bontis, N., Mubarik, M., & Mahmood, T. (2021). Intellectual capital and supply chain resilience. Journal of Intellectual Capital.
Nunes, L., Causer, T., & Ciolkosz, D. (2020). Biomass for energy: A review on supply chain management models. Renewable and Sustainable Energy Reviews, 120, 109658.
Patterson, K. A., Grimm, C. M., & Corsi, T. M. (2003). Adopting new technologies for supply chain management. Transportation Research Part E: Logistics and Transportation Review, 39(2), 95-121.
Pope, D. (2020). Assessing Cause and Effect in Supply Chain Problems Using Sports Ranking Models. Operations and Supply Chain Management: An International Journal, 13(1), 23-30.
Roy, M. D., & Sana, S. S. (2021). Inter-dependent lead-time and ordering cost reduction strategy: a supply chain model with quality control, lead-time dependent backorder and price-sensitive stochastic demand. Opsearch, 1-21.
Sodhi, M. S., & Tang, C. S. (2021). Supply chain management for extreme conditions: Research opportunities. Journal of Supply Chain Management, 57(1), 7-16.
Somjai, S., Rattamanee, K., Thongdonpum, K., & Jermsittiparsert, K. (2019). The stakeholder’s pressure and environmental supply chain: Does the environmental training matter in Thai sports manufacturing firms?
Tarighi, R., Sajjadi, S. N., Hamidi, M., & Khabiri, M. (2017). Factors affecting the development of the electronic marketing capacity of professional sports federations. Annals of Applied Sport Science, 5(2), 87-96.
Thomas, D. J., & Griffin, P. M. (1996). Coordinated supply chain management. European journal of operational research, 94(1), 1-15.
Tiwari, S., Wee, H.-M., & Daryanto, Y. (2018). Big data analytics in supply chain management between 2010 and 2016: Insights to industries. Computers & industrial engineering, 115, 319-330.
Wiedmer, R., & Griffis, S. E. (2021). Structural characteristics of complex supply chain networks. Journal of Business Logistics, 42(2), 264-290.
Wieland, A. (2021). Dancing the supply chain: Toward transformative supply chain management. Journal of Supply Chain Management, 57(1), 58-73. (Persian).
Yektayar, M. (2019). Prioritizing Supply Chain Management Indicators in Sport. Sport Management Studies, 11(54), 71-92 (Persian). https://doi.org/10.22089/smrj.2018.4898.1946
