الگوی مدیریت عملکرد در زنجیره تامین خدمات بانک های خصوصی کشور با رويكرد پويايي شناسي سيستم ها

محورهای موضوعی : مدیریت منابع انسانی

فرشید بیگدلی ¹ , محمدرضا دلوی ² , سعید آقاسی ³

1 -
2 - محمدرضا دلوی دانشیار، گروه مدیریت، واحد دهاقان، دانشگاه آزاد اسلامی، دهاقان، ایران.
3 - استادیار دانشکده مدیریت دانشگاه آزاد اسلامی واحد دهاقان

تاریخ دریافت : 1403/03/02 تاریخ پذیرش : 1403/04/28 تاریخ انتشار : 1403/05/15

کلید واژه: مدیریت عملکرد, زنجیره تامین خدمات, بانک های خصوصی, پويايي شناسي سیستم,

چکیده مقاله :

زمینه و هدف: بانک ها بر این امر واقف هستند که برای موفقیت در زنجیره تامین خدمات، نقش مدیریت عملکرد بسیار حائز اهمیت می باشد. از این رو، هدف این پژوهش طراحی مدل مدیریت عملکرد در زنجیره تامین خدمات بانک های خصوصی کشور با رویکرد پویا شناسی سیستم ها می¬باشد. روش بررسی: در این پژوهش، ابتدا در بخش کیفی برای طراحی مدل از روش داده بنیاد استفاده شد و مصاحبه ای از 12 نفر از خبرگان مرتبط با موضوع تا اشباع نظری انجام شد. سپس برای طراحی الگوی پویایی سیستم از نرم‌افزارVensim استفاده گردید. یافته‎ ها: یافته های حاصل از پویاشناسی سیستم ها نشان داد چهار سناریو در حوزه عوامل علی، مداخله گر، بسترها و راهبردها برای تحلیل مدیریت عملکرد در زنجیره تامین خدمات در بانک های خصوصی کشور وجود دارد. نتیجه گیری: استفاده از مدل‌های پویایی‌شناسی سیستم‌ها می‌تواند به تحلیل بهتر و شفاف‌تر تعامل بین اجزای زنجیره تأمین خدمات کمک کند. در صورت بررسی و تقویت هر کدام از سناریوها، در مدیریت عملکرد در زنجیره تأمین خدمات بهبود حاصل می شود.

چکیده انگلیسی:

Background and purpose: Banks are aware that the role of performance management is very important for success in the service supply chain. Therefore, the purpose of this research is to design a performance management model in the service supply chain of private banks in the country with a systems dynamics approach. Research method: In this research, firstly, in the qualitative part, the foundation data method was used to design the model, and an interview was conducted with 12 experts related to the subject until theoretical saturation. Then Vensim software was used to design the dynamic model of the system. Findings: The findings of systems dynamics showed that there are four scenarios in the field of causal factors, intervenors, platforms and strategies for performance management analysis in service supply chain in private banks of the country. Conclusion: The use of systems dynamics models can help to better and more transparently analyze the interaction between the components of the service supply chain. If each of the scenarios is examined and strengthened, performance management in the service supply chain will be improved.

منابع و مأخذ:

References
Ahyani, E., Rifky, S., Muharam, S., Murnaka, N. P., Kadiyo, K., & Dhuhani, E. M. (2024). Implementation of Teacher Performance Management to Improve Education Quality. Cendikia: Media Jurnal Ilmiah Pendidikan, 14(4), 391-398. https://doi.org/10.35335/cendikia.v14i4.4855
Ali, A., Haq, F., Marwat, A., Khan, S., & Adnan, A. (2024). Empirical Research on the Mediating Impact of Integration between Supply Chain Management Practices and Supply Chain Management Performance. Qlantic Journal of Social Sciences. 5(1), 363-373. https://doi.org/10,55737/qjss.799071365
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. https://doi.org/10.1016/j.ijinfomgt.2020.102195
Bakhtiari, H. (2023). The effect of organizational culture on supply chain performance; The mediating role of supply chain resilience and agility (case study: steel industry of Qom province). 13th International Conference on Management and Humanities Research, Tehran. [In Persian]. https://www.noormags.ir/view/fa/articlepage/2138203
Bogdan, M., & Adriana, S. A. V. A. (2018). Supply chain finance, a solution to improve business efficiency. Acta Technica Napocensis-Series: Applied Mathematics, Mechanics, and Engineering, 61(4), 1-6. https://atna-mam.utcluj.ro/index.php/Acta/article/view/1110
Esmaeilikia, M., Fahimnia, B., Sarkis, J., Govindan, K., Kumar, A., & Mo, J. (2016). Tactical supply chain planning models with inherent flexibility: definition and review. Annals of Operations Research, 224(2), 407-427. DOI:10.1007/s10479-014-1544-3
Fakhrzad, M. B., Khayat Sarkar, H., & Johari Naimi, F. (2019). Investigating the relationship between supply chain management strategy and sustainable supply chain performance with a structural equation modeling approach. Journal of industrial engineering research in production systems, 8(17), 215-255 [In Persian]. https://doi.org/10.22084/ier.2021.21288.1954
Farsi, M., Bailly, A., Bodin, D., Penella, V., Pinault, P. L., Nghia, E. T. T., & Erkoyuncu, J. A. (2020). An optimisation framework for improving supply chain performance: case study of a bespoke service provider. Procedia Manufacturing, 49, 185-192.‏ DOI:10.1016/j.promfg.2020.07.017
Frederico, G. F., Garza-Reyes, J. A., Anosike, A., & Kumar, V. (2019). Supply Chain 4.0: concepts, maturity and research agenda. Supply Chain Management: An International Journal, 25(2), 262-282‏ https://doi.org/10.1108/SCM-09-2018-0339
Garai, A., & Roy, T. K. (2020). Multi-objective optimization of cost-effective and customer-centric closed-loop supply chain management model in T-environment. Soft Computing, 24(1), 155-178. DOI:10.1007/s00500-019-04289-5
Gopal, P. R. C., Rana, N. P., Krishna, T. V., & Ramkumar, M. (2024). Impact of big data analytics on supply chain performance: an analysis of influencing factors. Annals of Operations Research, 333(2), 769-797.‏ DOI:10.1007/s10479-022-04749-6
Gupta, P., & Sethi, M. (2024). Transforming the Performance Management System at Sapient. Asian Journal of Management Cases.‏ DOI:10.1177/09728201241231652
Hung, J. L., He, W., & Shen, J. (2020). Big data analytics for supply chain relationship in banking. Industrial Marketing Management, 86, 144-153.‏ https://doi.org/10.1016/j.indmarman.2019.11.001
Ivanov, D., & Dolgui, A. (2020). A digital supply chain twin for managing supply chain risk. International Journal of Production Research, 58(10), 3023-3036. DOI:10.1080/09537287.2020.1768450
Jones, O. W., Devins, D., & Barnes, G. (2024). Developing SME performance management practices: Interventions for improving productivity. International Journal of Productivity and Performance Management, 73(1), 327-360. DOI: https://doi.org/10.1108/ijppm-03-2022-0157
Kazmi, S. H. A., Ahmed, R. R., Soomro, K. A., Hashem, E. A. R., Akhtar, H., & Parmar, V. (2021). Role of augmented reality in changing consumer behavior and decision making: Case of Pakistan. Sustainability, 13(24), 14064.‏ https://doi.org/10.3390/su132414064
Lee, S., Oh, H. Y., & Choi, J. (2020). Service design management and organizational innovation performance. Sustainability, 13(1), 4.‏ https://doi.org/10.3390/su13010004
Lima-Junior, F. R., & Carpinetti, L. C. R. (2020). An adaptive network-based fuzzy inference system to supply chain performance evaluation based on SCOR metrics. Computers & Industrial Engineering, 139, c. https://doi.org/10.1016/j.cie.2019.106191
Lin, J., Lin, S., Benitez, J., Luo, X., & Ajamieh, A. (2023). How to build supply chain resilience: The role of fit mechanisms between digitally-driven business capability and supply chain governance. Information & Management, 60(2), 103747. doi.org/10.1016/j.im.2022.103747
Liu, X., Zhang, K., Chen, B., Zhou, J., & Miao, L. (2018). Analysis of logistics service supply chain for the One Belt and One Road initiative of China. Transportation Research Part E: Logistics and Transportation Review, 117, 23-39. https://doi.org/10.1016/j.tre.2018.01.01
Mehri Babadi, E., Iranzadeh, S., & Fathi Hefeshjani, K. (2022). Presenting a model to evaluate the performance of large supply chain in oil and gas industries (case study: National Company of South Oil-rich Regions). Quarterly Journal of Iranian Management Sciences Association, 17(65), 83-121 [In Persian]. https://doi.Journal.iams.ir/article_369.html
Mondol, E. P. (2021). The impact of block chain and smart inventory system on supply chain performance at retail industry. International Journal of Computations, Information and Manufacturing (IJCIM), 1(1), 56-76.‏ https://doi.org/10.54489/ijcim.v1i1.30
Mukhsin, M., Taufik, H., Ridwan, A. & Suryanto, T. (2022). The mediation role of supply chain agility on supply chain orientation-supply chain performance link. Uncertain Supply Chain Management, 10(1), 197-204. DOI:10.1080/12460125.2017.1351862
Nagariya, R., Kumar, D., & Kumar, I. (2020). Service supply chain: from bibliometric analysis to content analysis, current research trends and future research directions. Benchmarking: An International Journal,‏ 28(1), 33-396. https://doi.org/10.1108/BIJ-04-2020-0137
Pakurár, M., Haddad, H., Nagy, J., Popp, J., & Oláh, J. (2019). The impact of supply chain integration and internal control on financial performance in the Jordanian banking sector. Sustainability, 11(5), 1248.‏ https://doi.org/10.3390/su11051248
Shahabi, V., Azar, A., Faizi Razi, F., & Fallah Shams, M. F. (2021). Analysis of factors affecting the development of the supply chain of banking services in the fourth industrial revolution. Management Researches in Iran, in print [In Persian]. https://ensani.ir/fa/article/511366
Sundar, D. K., Nichola, D. J., & Yadavalli, V. S. (2000). Social networks, the banking supply chain and financial inclusion in South Africa: A Framework. Proceedings of the 41st International Conference on Computers & Industrial Engineering.
https://repository.iimb.ac.in/handle/2074/11679
Tripathi, S., & Talukder, B. (2023). Supply chain performance and profitability in Indian automobile industry: Evidence of segmental difference. Global Business Review, 24(2), 371-392.‏ DOI:10.1177/0972150919898302
Vasconcelos, T. R. S. D., & Fontana, M. E. (2023). Logistics service provider performance evaluation based on different perceptions in the reverse supply chain. International Journal of Logistics Systems and Management, 45(1), 67-87.‏ http://www.inderscience.com/link.php?id=130968
Wieland, A. (2021). Dancing the supply chain: Toward transformative supply chain management. Journal of Supply Chain Management, 57(1), 58-73.‏ https://doi.org/10.1111/jscm.12248
Wu, Q., Zhu, J., & Cheng, Y. (2023). The effect of cross-organizational governance on supply chain resilience: A mediating and moderating model. Journal of Purchasing and Supply Management, 29(5), 100817. https://doi.org/10.1016/j.pursup.2023.100817
Yan, B., Chen, X., Cai, C., & Guan, S. (2020). Supply chain coordination of fresh agricultural products based on consumer behavior. Computers & Operations Research, 123, 105038.‏ https://doi.org/10.1016/j.cor.2020.105038
Zaman, S. I., Khan, S. A., Qabool, S., & Gupta, H. (2023). How digitalization in banking improve service supply chain resilience of e-commerce sector? A technological adoption model approach. Operations Management Research, 16(2), 904-930.‏ DOI:10.1007/s12063-022-00341-0
‏‏Zhang, H., Xiong, H., Wang, G., & Jiang, P. (2024). How institutional pressures improve environmental management performance in construction projects: an agent-based simulation approach. Environment Development and Sustainability, 26(1), 1281-1311. DOI:10.1007/s10668-022-02758-w
Zhao, N., Hong, J., & Lau, K. H. (2023). Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model. International Journal of Production Economics, 259(4), 108817. DOI:10.1016/j.ijpe.2023.108817