تحلیل دینامیکی سیستم سفارش‌گذاری در زنجیرة تأمین با رویکرد پویایی شناسی سیستم‌ها
محورهای موضوعی : مدیریت صنعتی
sayyed mohammad reza davoodi
1
(Assistant Professor. Department of Management, Dehaghan Branch, Islamic Azad University, Dehaghan, Iran)
Shahab forutan chehr
2
(Phd student of industrial management Dehaghan Branch, Islamic Azad University, Dehaghan, Iran)
کلید واژه: پویایی شناسی سیستم‌ها, زنجیرة تأمین, شبیه سازی, سیستم سفارش‌گذاری,
چکیده مقاله :
چکیده: زنجیره تأمین سیستم پویایی است که در برگیرنده کلیه فعالیت‌های مربوط به ایجاد و تحویل یک محصول، از مرحله مواد خام تا رسیدن به مشتری نهایی می‌باشد. مدیریت زنجیره تامین ساپکو نیازمند تصمیمات آینده نگر و طراحی ظرفیت‌های جدید با رویکردی جامع و به هم پیوسته است. یکی از ابزارهای مدیریتی براساس این نگرش، علم پویایی سیستم می‌باشد. این علم توانایی شبیه سازی زنجیره تأمین‌های مختلف را دارد، به کمک این شبیه سازی پیامدهای نامشخص تصمیم-گیری ها آشکار می‌شود. تحلیل نوسانات رفتار سفارشات مشتریان می‌تواند نقش کلیدی در پیش بینی میزان تأمین تقاضای مورد نیاز مشتریان، فروش، تحویل به موقع، تعدیل پرسنل فروش و سایر عوامل فراهم سازد. در این مقاله تحلیل دینامیکی سیستم سفارش گذاری در زنجیره تامین با رویکرد پویایی شناسی سیستم مورد بررسی قرار گرفته است. در این مقاله بر پایة اصول روش پویایی‌های سیستم، پس از بیان مسئلة سیستم سفارش‌گذاری در زنجیرة تأمین، فرضیه‌های پویای به وجود آورندة مسئلة مد نظر تبیین شده؛ سپس مدل دینامیکی مربوط به مسئلة نوسان‌ها در سیستم سفارش گذاری ارائه می‌شود. در این راستا ابتدا متغیرهای اصلی شناسایی و روابط آن‌ها در قالب حلقه-های علّی تدوین گردیده، سپس با طراحی مدل اصلی و در قالب نمودار انباشت جریان تکمیل و در نرم-افزار شبیه‌سازی شده است. بعد از طراحی و شبیه‌سازی مدل نهایی آزمون‌های اعتبارسنجی و تحلیل حساسیت بر روی مدل صورت گرفت که نشان از معتبر بودن مدل داشت.
The supply chain is a dynamic system that includes all activities related to the creation and delivery of a product, from the raw material stage to the final customer. Sapco's supply chain management needs future decisions and the design of new capacities with a comprehensive and interconnected approach. One of the management tools based on this approach is the system's dynamic knowledge. This science has the ability to simulate the supply chain, with the help of this simulation, the uncertain outcomes of decisions are revealed. An analysis of the fluctuations in the behavior of customer orders can provide a key role in predicting customer demand, sales, timely delivery, sales staff adjustments, and other factors. In this paper, the dynamic analysis of the order system in the supply chain with the dynamics of the system is examined. In this paper, based on the principles of the dynamics of the system, following the statement of the ordering system problem in the supply chain, the hypotheses that give rise to the problem are explained; then the dynamic model related to the problem of fluctuations in the ordering system of presentation It will be. first, the main variables were identified and their relationships were formulated in the form of Ali rings, then, by designing the main model, in the form of flow accumulation chart, was simulated in the software. After designing and simulating the final model, validation tests and sensitivity analysis were performed on the model that showed the validity of the model.
1. Aghaei, M., Vahedi, E., Safari Kahreh, M. & Pirooz, M. (2014). An examination of the relationship between Services Marketing Mix and Brand Equity Dimensions. Procedia - Social and Behavioral Sciences, 109, 865 – 869.
2. Ahmadi, A., Fekri, R., Babayanpoor, M. & Fathian, M. (2016). Agility of supply chain after-sales service of heavy vehicles in Iran. Management Improvement Journal, 10, 01-122.
3. Aminbeidokhti, A., Mohammadi,A. & Hosseinpoor, O. (2016). The Relationship between Organizational Entrepreneurship and Organizational Agility: Testing the Mediator Role of Organizational Commitment. Higher Education Letter, 9, 135-155.
4. Ansari, M. & Nasabi, V. (2013). Creating a Brand-Specific Value Through Advertising Blend: Assessing the Mediator of Knowledge, Loyalty, and Brand Relationship. Journal of Business Management, 14, 37-51.
5. Azar, A. (2002). Path Analysis and Reasoning in Management Science. Journal of Qom Higher Education Complex, 15, 59-96.
6. Azizi, S. Darvishi, Z. & Nemayan, F. (2011). The Factors Determining the Brand Value by Financial Approach in Companies Acquired in Tehran Stock Exchange. Journal of Business Management, 6, 4-9.
7. Ben Saeed, N., Nematiyan, M. & Albonaiemi, E. (2015). Effective factors on the value of international brands in Iranian consumers (Case Study of Samsung brand in Khuzestan market). International Journal of Humanities and Cultural Studies (IJHCS), 2, 974-984. 8. Bravo Gil, R., Fraj Andrés, E., 8.Martínez Salinas, E. (2007). Family as a source of consumer-base brand equity. Journal of Product & Brand Management, 16, 188-199.
9. Christopher. M. (2000). The Agile supply chain competing in volatile Markets. Industrial Marketing Management, 29, 37-44.
10. Dashti, M.A., & Jalalian, N. (2016). The study of relationship between coach-oriented management style and organizational agility in Shahid Sadoughi University of Medical Sciences. TB, 15, 44-54.
11. Dehdashti, Z., Yarahmadi, A., Lorestani, H. & Kashipazan, A. (2015). An Investigation into the Effects of Self-Definition of Consumers on Their Attitudinal and Behavioral Loyalty with Regards
12. Khatami Firoozabadi, M,. Olfat, L., Amiri, M. & Sharifi, H. (2016). Prioritizing Supply Chain Complexity Drivers using Fuzzy Hierarchical Analytical Process. Journal of industrial management, 9(1), 79-102.
13. Li L., Zabinsky Z.B.; Incorporating uncertainty in to a supplier selection problem, I .J .of Production Economics Article in Press, 2010
14. Mingers, J. (2004). Real-izing information systems: critical realism as an underpinning philosophy for information systems. Information and Organization, 14(2), 87–103.
15. Modarres Yazdi, M., Safari, H. & Ajdari, B. (2014). A cognitive map of causal relationship between supply chain management practices, supply chain enablers and supply chain performance: a fuzzy approach. Journal of industrial management, 6(3), 615-634.
16. Ozbayrak, M., Papadopoulou, C. & Akgun, M. (2007). Systems dynamics modeling of a manufacturing supply chain system. Simulation Modeling Practice and Theory, 15(10), 1338–1355.
17. Poles, P. & Cheong, F. (2008). Inventory Control In Closed Loop Supply Chain Using System Dynamics. Pmit University, School Of Business Information Technology. Sterman, J. (2000). Business Dynamics: systems thinking and modeling for a complex world, McGraw-Hill, Boston.
18. Yang, F., Zhang, B. & Su, Z. (2013). Analysis and Verification of Bullwhip Effect based on System Dynamics. Applied Mechanics and Materials, 340 (7), 312-
319.
19. Yuan, X., Shen, L., & Ashayeri, J. (2010). Dynamic simulation assessment of collaboration strategies to manage demand in gap in high-tech product diffusion. Robotics and Computer Integrated Manufacturing, 26(6), 647-657.
_||_1. Aghaei, M., Vahedi, E., Safari Kahreh, M. & Pirooz, M. (2014). An examination of the relationship between Services Marketing Mix and Brand Equity Dimensions. Procedia - Social and Behavioral Sciences, 109, 865 – 869.
2. Ahmadi, A., Fekri, R., Babayanpoor, M. & Fathian, M. (2016). Agility of supply chain after-sales service of heavy vehicles in Iran. Management Improvement Journal, 10, 01-122.
3. Aminbeidokhti, A., Mohammadi,A. & Hosseinpoor, O. (2016). The Relationship between Organizational Entrepreneurship and Organizational Agility: Testing the Mediator Role of Organizational Commitment. Higher Education Letter, 9, 135-155.
4. Ansari, M. & Nasabi, V. (2013). Creating a Brand-Specific Value Through Advertising Blend: Assessing the Mediator of Knowledge, Loyalty, and Brand Relationship. Journal of Business Management, 14, 37-51.
5. Azar, A. (2002). Path Analysis and Reasoning in Management Science. Journal of Qom Higher Education Complex, 15, 59-96.
6. Azizi, S. Darvishi, Z. & Nemayan, F. (2011). The Factors Determining the Brand Value by Financial Approach in Companies Acquired in Tehran Stock Exchange. Journal of Business Management, 6, 4-9.
7. Ben Saeed, N., Nematiyan, M. & Albonaiemi, E. (2015). Effective factors on the value of international brands in Iranian consumers (Case Study of Samsung brand in Khuzestan market). International Journal of Humanities and Cultural Studies (IJHCS), 2, 974-984. 8. Bravo Gil, R., Fraj Andrés, E., 8.Martínez Salinas, E. (2007). Family as a source of consumer-base brand equity. Journal of Product & Brand Management, 16, 188-199.
9. Christopher. M. (2000). The Agile supply chain competing in volatile Markets. Industrial Marketing Management, 29, 37-44.
10. Dashti, M.A., & Jalalian, N. (2016). The study of relationship between coach-oriented management style and organizational agility in Shahid Sadoughi University of Medical Sciences. TB, 15, 44-54.
11. Dehdashti, Z., Yarahmadi, A., Lorestani, H. & Kashipazan, A. (2015). An Investigation into the Effects of Self-Definition of Consumers on Their Attitudinal and Behavioral Loyalty with Regards
12. Khatami Firoozabadi, M,. Olfat, L., Amiri, M. & Sharifi, H. (2016). Prioritizing Supply Chain Complexity Drivers using Fuzzy Hierarchical Analytical Process. Journal of industrial management, 9(1), 79-102.
13. Li L., Zabinsky Z.B.; Incorporating uncertainty in to a supplier selection problem, I .J .of Production Economics Article in Press, 2010
14. Mingers, J. (2004). Real-izing information systems: critical realism as an underpinning philosophy for information systems. Information and Organization, 14(2), 87–103.
15. Modarres Yazdi, M., Safari, H. & Ajdari, B. (2014). A cognitive map of causal relationship between supply chain management practices, supply chain enablers and supply chain performance: a fuzzy approach. Journal of industrial management, 6(3), 615-634.
16. Ozbayrak, M., Papadopoulou, C. & Akgun, M. (2007). Systems dynamics modeling of a manufacturing supply chain system. Simulation Modeling Practice and Theory, 15(10), 1338–1355.
17. Poles, P. & Cheong, F. (2008). Inventory Control In Closed Loop Supply Chain Using System Dynamics. Pmit University, School Of Business Information Technology. Sterman, J. (2000). Business Dynamics: systems thinking and modeling for a complex world, McGraw-Hill, Boston.
18. Yang, F., Zhang, B. & Su, Z. (2013). Analysis and Verification of Bullwhip Effect based on System Dynamics. Applied Mechanics and Materials, 340 (7), 312-
319.
19. Yuan, X., Shen, L., & Ashayeri, J. (2010). Dynamic simulation assessment of collaboration strategies to manage demand in gap in high-tech product diffusion. Robotics and Computer Integrated Manufacturing, 26(6), 647-657.