رفع بحران نقدینگی در زنجیره تأمین دارویی ایران با اعتبار فروش به‌عنوان ابزار هماهنگی بهینه در شرایط قیمت ثابت

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، دپارتمان مهندسی صنایع، دانشگاه یزد، یزد، ایران

2 استاد، دپارتمان مهندسی صنایع، دانشگاه یزد، یزد، ایران

چکیده
در صنعت داروسازی ایران، توزیع‌کنندگان از اعتبار فروش به‌عنوان اصلی‌ترین ابزار مدیریت تقاضا و حفظ سهم بازار استفاده می‌کنند. با این حال، استفاده بی‌برنامه و بیش از حد اعتبار تجاری (فروش)، عامل عمده بحران نقدینگی داروخانه‌ها، کاهش شدید حجم سفارش، گاهی ورشکستگی‌های کامل و در نتیجه کاهش دسترسی بیماران به داروهای ضروری شده است. این پژوهش یک مدل هماهنگی بهینه مبتنی بر اعتبار فروش ارائه می‌دهد و نشان می‌دهد که همین ابزار رایج صنعت، در صورت تنظیم علمی دوره اعتبار، قادر است بحران مالی را به‌طور قابل توجهی کاهش دهد. مدل پیشنهادی در چارچوب بازی استکلبرگ پیشرو-پیرو فرموله شده و زوال وابسته به دما (توزیع وایبول) را برای رعایت محدودیت‌های زنجیره سرد دارویی در نظر می‌گیرد. با به‌کارگیری برنامه‌ریزی کسری مقعر، شبه‌مقعر بودن تابع سود سالانه اثبات شده و وجود جواب بهینه یکتا و سراسری برای هر ترکیب پارامترهای قراردادی تضمین می‌گردد. روش حل ترکیبی از الگوریتم جستجوی تکراری کارآمد با اعتبارسنجی جامع بروت‌فورس در پایتون است. رویکرد پیشنهادی بدون نیاز به منابع مالی اضافی یا تغییر مقرراتی، بلافاصله قابل اجراست و از رویه‌های موجود صنعت استفاده می‌کند. نتایج عددی نشان‌دهنده بهبود تا ۱۹.۷٪ سود و افزایش بیش از سه برابری حجم سفارش نسبت به حالت نامتمرکز است. این پژوهش چارچوبی عملی و کم‌هزینه در اختیار توزیع‌کنندگان و داروخانه‌ها (خرده‌فروشان) قرار می‌دهد تا رایج‌ترین ابزار مدیریت تقاضای خود را به مکانیزمی مؤثر برای هماهنگی تبدیل کنند و به‌طور همزمان سودآوری، پایداری جریان نقدی و دسترسی بیماران به داروها را بهبود بخشند.

کلیدواژه‌ها


عنوان مقاله English

Alleviating Cash-Flow Crises in the Iranian Pharmaceutical Supply Chain through Optimal Trade-Credit Coordination under Fixed Pricing

نویسندگان English

Farnoush Otrodi 1
Hasan Khademi Zare 2
Yahya Zare Mehrjardi 2
Mohammad Bagher Fakhrzad 2
1 PhD Student, Department of Industrial Engineering, Yazd University, Yazd, Iran.
2 Professor, Department of Industrial Engineering, Yazd University, Yazd, Iran.
چکیده English

In the Iranian pharmaceutical industry, distributors widely rely on trade credit as the primary demand-management instrument to preserve market share. However, unplanned and excessive extensions of credit periods have become a major source of pharmacy liquidity crises, sharp reductions in order volumes, occasional bankruptcies, and, ultimately, diminished patient access to essential medicines. This study develops an optimal trade-credit coordination model and demonstrates that scientifically calibrating the credit duration, using this prevalent industry practice, can substantially alleviate financial distress. The model is formulated within a Stackelberg leader–follower framework and incorporates temperature-dependent Weibull deterioration to capture the cold-chain constraints of pharmaceutical products. Concave fractional programming is employed to establish that the annual total profit function is strictly pseudo-concave, thereby guaranteeing the existence and uniqueness of a global optimal solution for feasible contract parameters. The solution methodology combines an efficient iterative search algorithm with exhaustive brute-force validation implemented in Python. The proposed approach requires no additional financial resources or regulatory changes and can be readily implemented using existing industry practices. Numerical results indicate profit improvements of up to 19.7% and more than a threefold increase in order quantity relative to the decentralized baseline. Overall, the framework provides distributors and pharmacies (retailers) with a practical, cost-free means of transforming a common demand-management instrument into an effective coordination mechanism that enhances profitability, cash-flow stability, and patient access to medicines.

کلیدواژه‌ها English

Supply chain coordination
Regulated pharmaceutical markets
Trade credit
Brute-force validation
Python
[1]    Ozawa, S., C. R. Higgins, T. T. Yemeke, J. I. Nwokike, L. Evans, M. Hajjou, &V. S. Pribluda, (2020), Importance of medicine quality in achieving universal health coverage. PLoS One. 15(7): p. e0232966. https://doi.org/10.1371/journal.pone.0232966
[2]    Manders, E. A., S. van den Berg, S. J. de Visser, &C. E. Hollak, (2025), Drug pricing models, no ‘one-size-fits-all’approach: a systematic review and critical evaluation of pricing models in an evolving pharmaceutical landscape. The European Journal of Health Economics. 26(4): p. 683-696, https://doi.org/10.1007/s10198-024-01731-w. 
[3]    Zhao, M., &J. Wu, (2017), Impacts of regulated competition on pricing in Chinese pharmaceutical market under urban employee basic medical insurance. Expert Review of Pharmacoeconomics & Outcomes Research. 17(3): p. 311-320. https://doi.org/10.1080/14737167.2017.1251318.
[4]    Chakraborty, S., How to do Dynamic Resource Allocation in the Generic Pharma Industry? 2021, Indian School of Business (India).
[5]    Aborode, A. T., O. Oginni, M. Abacheng, O. Edima, E. Lamunu, T. N. Folorunso, C. I. Oko, A. R. Iretiayo, L. Lawal, &R. Amarachi, (2025), Healthcare debts in the United States: a silent fight. Annals of Medicine and Surgery. 87(2): p. 663-672.
[6]    Eslamitabar, S., (2025), Pharmaceutical Pricing and Reimbursement in Iran: Providing a Solution to Improve Access and Production. Journal of Law and Health Studies. 1(2): p. 157-173.
[7]    Mosa, M., A. A. , &A. R. G. , (2021), A bi-objective MILP model for lot sizing and scheduling problem: Possibilistic fuzzy goal programming approach. Modern Research in Decision Making. 6(2): p. 181-212, [In Persian].
[8]    Dahooie, a. H., S. M. Sajadi, &F. Tavan, (2021), Business Processes Design of Small and Medium Enterprises of Perishable Items in order to Determination of Optimum Production Policy with Simulation Approach. Management Research in Iran. 19(3): p. 7-35, [In Persian].
[9]    Claassen, G., P. Kirst, A. T. T. Van, J. Snels, X. Guo, &P. van Beek, (2024), Integrating time-temperature dependent deterioration in the economic order quantity model for perishable products in multi-echelon supply chains. Omega-International Journal of Management Science. 125.
[10]    Dehghan Tooranposhti, A., S. Eslamitabar, &A. Sobhanian, (2025), Comparative study of pharmaceutical pricing systems in Iran and selected countries. Journal of Health Administration. 28(2): p. 82-89.
[11]    Bahrami, f., A. Zarei, M. S. Nikabadi, &f. farokhizadeh, (2024), Examining the performance of the drug supply and distribution chain using blockchain technology based on the dynamic system approach. Modern Research in Decision Making. 9(3): p. 34-70,  [In Persian]. 
[12]    Setak, M., M. Tavana, &H. Talafi Daryani, (2025), A two-level supply chain coordination model for perishable products under optimal markdown time and trade credit policies. Opsearch. 62(1): p. 268-306, https://doi.org/10.1007/s12597-024-00765-1. 
[13]    Kwon, Y. W., J.-B. Sheu, S. Talluri, J. Yoon, &S. H. Yoo, (2024), Performance of Quantity Discount Contract Under Supply and Demand Disruptions. IEEE Transactions on Engineering Management. 71: p. 5782-5797, https://doi.org/ 10.1109/TEM.2024.3366562.
[14]    Maleki, F., S. Yaghoubi, &A. Fander, (2023), Organic level vs. sales effort in coordination of green food supply chain for deteriorating items. Environment, Development and Sustainability. 25(11): p. 13065-13097, https://doi.org/10.1007/s10668-022-02603-0. 
[15]    Luo, M., G. Zhou, &H. Xu, (2023), A differential game model research on dynamic pricing and coordination of fresh agricultural products supply chain based on freshness. Economic research-Ekonomska istraživanja. 36(2): p. 2177696, https://doi.org/10.1080/1331677X.2023.2177696. 
[16]    Chen, T., C. Liu, &X. Xu, (2022), Coordination of Perishable Product Supply Chains with a Joint Contract under Yield and Demand Uncertainty. Sustainability. 14(19): p. 12658, https://doi.org/10.3390/su141912658.
[17]    Wu, C., &Q. Zhao, (2014), Supplier–buyer deterministic inventory coordination with trade credit and shelf-life constraint. International Journal of Systems Science: Operations & Logistics. 1(1): p. 36-46, https://doi.org/10.1080/00207721.2014.886747.
[18]    Wang, Y., X. Deng, Q. Lu, M. Guan, F. Lu, &X. Wu, (2023), Developing platform supply chain contract coordination and a numerical analysis considering fresh-keeping services. Sustainability. 15(18): p. 13586, https://doi.org/10.3390/su151813586. 
[19]    Mahata, P., A. Gupta, &G. C. Mahata, (2014), Optimal pricing and ordering policy for an EPQ inventory system with perishable items under partial trade credit financing. International Journal of Operational Research. 21(2): p. 221-251, https://doi.org/10.1504/IJOR.2014.064607. 
[20]    Wu, Y., A. Zhu, L. Yu, &W. Wang, (2025), A study on fresh product supply chain management decisions considering subsidies and different transaction contracts. PLoS One. 20(5): p. e0322800, https://doi.org/10.1371/journal.pone.0322800
 [21]    Ran, W., &Y. Chen, (2023), Fresh produce supply chain coordination based on freshness preservation strategy. Sustainability. 15(10): p. 8184, 
https://doi.org/10.3390/su15108184
[22]    Zhang, Y., C. Zhou, T. Zhu, W. Chen, &C. Ni, (2024), Freshness-keeping Coordination in a Two-echelon Dynamic Supply Chain with Uncertainty: A Stackelberg Game Approach. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3406379
[23]    Yan, B., Y. Liu, &J. Fan, (2025), Two-echelon fresh product supply chain with different transportation modes. Annals of Operations Research. 349(2): p. 1379-1402, https://doi.org/10.1007/s10479-022-05092-6. 
[24]    Li, R., J.-T. Teng, &C.-T. Chang, (2021), Lot-sizing and pricing decisions for perishable products under three-echelon supply chains when demand depends on price and stock-age. Annals of Operations Research. 307(1): p. 303-328, https://doi.org/10.1007/s10479-021-04272-0. 
[25]    Qin, Y., J. Wang, &C. Wei, (2014), Joint pricing and inventory control for fresh produce and foods with quality and physical quantity deteriorating simultaneously. International Journal of Production Economics. 152: p. 42-48, https://doi.org/10.1016/j.ijpe.2014.01.005.
[26]    Giri, B., A. Chakraborty, &T. Maiti, (2016), Trade credit competition between two manufacturers in a two-echelon supply chain under credit-linked retail price and market demand. International Journal of Systems Science: Operations & Logistics. 3(2): p. 102-113, https://doi.org/10.1080/23302674.2015.1056271. 
[27]    Shavandi, H., H. Mahlooji, &N. E. Nosratian, (2012), A constrained multi-product pricing and inventory control problem. Applied Soft Computing. 12(8): p. 2454-2461, https://doi.org/10.1016/j.asoc.2012.03.036.  
[28]    Cambini, A., &L. Martein, Generalized convexity and optimization: Theory and applications. Vol. 616. 2008: Springer, https://doi.org/10.1016/j.asoc.2012.03.036.
[29]    Stoean, C., &R. Stoean, (2014), Support vector machines and evolutionary algorithms for classification. Single or Together, https://doi.org/10.1007/978-3-319-06941-8.
[30]    A,oozad, M. H., A. Jafarnejad, Y. M. Modares, &A. Mohaghar, (2014), Cooperation modeling for unlimited three echelon supply chain: Game theory approach. Management Research in Iran, [In Persian].
[31]    Administration, I. F. a. D. Public dashboards of the Iran Food and Drug Administration (IFDA). 2025.
[32]    Administration, F. a. D.; Available from: fda.gov.ir.
[33]    Resaneh, S.; Available from: https://salamatresaneh.ir/.
[34]    Organization, P. a. B.; Available from: https://www.mporg.ir/home.
[35]    THE, C. B. O., &I. R. O. IRAN. Statistics and data of CBI.