تعهد نامه
مجله پژوهش در بهداشت محیط

مجله پژوهش در بهداشت محیط

تحلیل عوامل موثر بر مدیریت پسماند در زنجیره تأمین سرد دارو (مورد مطالعه: زنجیره تأمین انسولین در ایران)

نوع مقاله : Research Paper

نویسندگان
1 دانشجوی کارشناسی ارشد مدیریت صنعتی، گروه مدیریت صنعتی، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران.
2 دانشجوی دکتری مدیریت صنعتی، دانشکده مدیریت صنعتی و فناوری، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران.
3 دانشیار گروه مدیریت صنعتی، دانشکده علوم اداری و اقتصاد، دانشگاه اراک، اراک، ایران.
چکیده
زمینه و هدف: زنجیره تأمین سرد دارو به شدت به نوسانات دمایی و نقص‌های فنی حساس است و هرگونه اختلال در آن باعث فساد دارو و تولید پسماند دارویی خطرناک می‌شود. این پژوهش با هدف شناسایی و اولویت‌بندی عوامل مؤثر بر مدیریت پسماند در زنجیره تأمین سرد انسولین در ایران انجام شده است.

مواد و روش‌ها: پژوهش حاضر از نوع تحلیلی-کاربردی و پیمایشی است. ابتدا عوامل اولیه از مرور نظام‌مند ادبیات استخراج شد. سپس با روش دلفی فازی و نظر ۱۶ خبره پالایش شدند و ۱۲ عامل نهایی تأیید شد. در نهایت وزن‌دهی و رتبه‌بندی با روش بهترین-بدترین فازی نوع دوم و مشارکت ۳ خبره متخصص انجام گرفت.

یافته‌ها: مهم‌ترین عوامل به ترتیب پایش و کنترل محیطی، مسائل فنی و شکست تجهیزات، زیرساخت‌های حمل‌ونقل سرد، مدیریت انبارداری، فناوری‌های ردیابی و بلاکچین شناخته شدند. بعد فنی-فناورانه بیشترین وزن، بعد لجستیکی دوم و بعد مدیریتی کمترین وزن را داشت. فساد انسولین در ایران عمدتاً ناشی از ضعف کنترل دمایی و تجهیزات است.

نتیجه‌گیری: اولویت اصلی برای کاهش پسماند انسولین باید تقویت پایش بلادرنگ دما، نگهداری پیشگیرانه تجهیزات و ناوگان حمل‌ونقل سرد باشد. عوامل مدیریتی و آموزشی نقش مکمل دارند و بدون اصلاح زیرساخت‌های فنی و لجستیکی تأثیر کمی خواهند داشت.
کلیدواژه‌ها

عنوان مقاله English

Analyzing the Factors Affecting Waste Management in Pharmaceutical Cold Supply Chain (Case of Study: Insulin Supply Chain in Iran)

نویسندگان English

Matin Heydari Rostami 1
Shahab Bayatzadeh 2
HamidReza Talaie 3
1 MSc Student of Industrial Management, Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’I University, Tehran, Iran.
2 PhD Student of Industrial Management, Faculty of Industrial Management & Technology, College of Management, University of Tehran, Tehran, Iran.
3 Associate Professor, Department of Industrial Management, Faculty of Administrative Sciences and Economics, Arak University, Arak, Iran.
چکیده English

Background and Objective: The pharmaceutical cold supply chain is susceptible to temperature fluctuations and technical failures, and disruptions can lead to drug spoilage and hazardous pharmaceutical waste. This study aimed to identify and prioritize the factors influencing waste management in the cold supply chain of insulin in Iran.

Materials and Methods: This analytical-applied, survey-based research first identified initial factors through a systematic literature review. These factors were then refined using the Fuzzy Delphi method with input from 16 experts, resulting in the confirmation of 12 final factors. Finally, weighting and ranking were performed using the Interval Type-2 Fuzzy Best-Worst Method with the participation of 3 highly experienced experts.

Results: The most important factors, in order of priority, were environmental monitoring and control; technical issues and equipment failure; cold transportation infrastructure; warehousing and storage management; and tracking technologies and blockchain. The technical-technological dimension received the highest weight, followed by the logistical dimension, while the managerial dimension had the lowest weight. Weaknesses in temperature control and equipment performance are mainly responsible for insulin spoilage in Iran.

Conclusion: The primary focus for reducing insulin waste should be on strengthening real-time temperature monitoring, preventive maintenance of cold equipment, and upgrading refrigerated transportation fleets. Managerial and educational factors play a supporting role and will have a limited impact without first addressing technical and logistical infrastructure deficiencies.

Open Access Policy: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/

کلیدواژه‌ها English

Cold Supply Chain
Fuzzy Delphi
Interval Type-2 Fuzzy Best-Worst Method
Insulin
Pharmaceutical Waste Management
1.    Aditjandra P, Hussain I, Utomo D, Gripton A, Greening P. Cold chain for sustainable infrastructure planning. Transportation Research Procedia. 2025; 82:481–94. 
2.    Iyer P, Robb D. Cold chain optimisation models: A systematic literature review. Comput Ind Eng. 2025;110972. 
3.    Asim Z, Sorooshian S, Al Shamsi IR, Muniyanayaka D, Al Azzani A. Supply chain 4.0 a source of sustainable initiative across food supply chain: trends and barriers. In: Human perspectives of industry 40 organizations. CRC Press; 2025. p. 17–37. 
4.    Bouazzi IR, Zaidi MM, Shati R, Bedywi L, Alahmari S, Al Qahtani R, et al. Medication cold chain improvement by using IoT-based smart tracking: a case study in KSA. Engineering Research Express. 2025;7(1):015266. 
5.    Heinemann L, Braune K, Carter A, Zayani A, Krämer LA. Insulin storage: a critical reappraisal. J Diabetes Sci Technol. 2021;15(1):147–59. 
6.    Maikawa CL, Mann JL, Kannan A, Meis CM, Grosskopf AK, Ou BS, et al. Engineering insulin cold chain resilience to improve global access. Biomacromolecules. 2021;22(8):3386–95. 
7.    Naderi A, Benis KZ, Dowlati M, Seyedin H, Behnami A, Farzadkia M. Identifying methods and challenges of waste management in natural disasters. J Environ Manage. 2025; 373:123514. 
8.    Hosseini-Motlagh SM, Jazinaninejad M, Nami N. Coordinating a socially concerned reverse supply chain for pharmaceutical waste management considering government role. Environ Dev Sustain. 2022;1–26. 
9.    Mostafanejad R, Ghassab-Abdollahi N, Derakhshani N, Rezapour R. Medication waste and disposal behaviors among Iranian households: A Cross-sectional study. Sci Rep. 2025;15(1):15714. 
10.    Heinemann L, Klonoff DC. Diabetes technology and waste: a complex story. J Diabetes Sci Technol. 2022;16(6):1381–4. 
11.    Haji M, Kerbache L, Sheriff KMM, Al-Ansari T. Critical success factors and traceability technologies for establishing a safe pharmaceutical supply chain. Methods Protoc. 2021;4(4):85. 
12.    Zeng W, Wang Y, Liang K, Li J, Niu X. Advancing Emergency Supplies Management: A Blockchain‐Based Traceability System for Cold‐Chain Medicine Logistics. Adv Theory Simul. 2024;7(4):2300704. 
13.    Khan AU, Ali Y. Sustainable supplier selection for the cold supply chain (CSC) in the context of a developing country. Environ Dev Sustain. 2021;1–30. 
14.    Arowosegbe OB, Ballali C, Kofi KR, Adeshina MK, Agbelusi J, Adeshina MA. Combating food waste in the agricultural supply chain: A systematic review of supply chain optimization strategies and their sustainability benefits. World Journal of Advanced Research and Reviews. 2024;24(01):122–40. 
15.    Alshdadi A, Kamel S, Alsolami E, Lytras MD, Boubaker S. An Iot smart system for cold supply chain storage and transportation μanagement. Engineering, Technology & Applied Science Research. 2024;14(2):13167–72. 
16.    Nha Trang NT, Nguyen TT, Pham H V, Anh Cao TT, Trinh Thi TH, Shahreki J. Impacts of collaborative partnership on the performance of cold supply chains of agriculture and foods: literature review. Sustainability. 2022;14(11):6462. 
17.    Bamakan SMH, Moghaddam SG, Manshadi SD. Blockchain-enabled pharmaceutical cold chain: Applications, key challenges, and future trends. J Clean Prod. 2021; 302:127021. 
18.    Fahrni ML, Ismail IAN, Refi DM, Almeman A, Yaakob NC, Saman KM, et al. Management of COVID-19 vaccines cold chain logistics: a scoping review. J Pharm Policy Pract. 2022;15(1):16. 
19.    Costa F, Lago A, Rocha V, Barros O, Costa L, Vipotnik Z, et al. A review on biological processes for pharmaceuticals wastes abatement—a growing threat to modern society. Environ Sci Technol. 2019;53(13):7185–202. 
20.    Dar MA, Maqbool M, Rasool S. Pharmaceutical wastes and their disposal practice in routine. Int J Inf Comput Sci. 2019; 6:76–92. 
21.    Rogowska J, Zimmermann A, Muszyńska A, Ratajczyk W, Wolska L. Pharmaceutical household waste practices: preliminary findings from a case study in Poland. Environ Manage. 2019; 64:97–106. 
22.    Hui TKL, Mohammed B, Donyai P, McCrindle R, Sherratt RS. Enhancing pharmaceutical packaging through a technology ecosystem to facilitate the reuse of medicines and reduce medicinal waste. Pharmacy. 2020;8(2):58. 
23.    Arden NS, Fisher AC, Tyner K, Lawrence XY, Lee SL, Kopcha M. Industry 4.0 for pharmaceutical manufacturing: Preparing for the smart factories of the future. Int J Pharm. 2021; 602:120554. 
24.    Shahrabadi F, Kia H, Heidari A, Khalilzadeh M. A Fuzzy Bi-objective Mathematical Model for Perishable Medical Goods Supply Chain Network Considering Crisis Situations: An Empirical Study. Health Serv Insights. 2024; 17:11786329241288772. 
25.    Kochakkashani F, Kayvanfar V, Haji A. Supply chain planning of vaccine and pharmaceutical clusters under uncertainty: The case of COVID-19. Socioecon Plann Sci. 2023; 87:101602. 
26.    Goodarzian F, Navaei A, Ehsani B, Ghasemi P, Muñuzuri J. Designing an integrated responsive-green-cold vaccine supply chain network using Internet-of-Things: artificial intelligence-based solutions. Ann Oper Res. 2023;328(1):531–75. 
27.    Babagolzadeh M, Shrestha A, Abbasi B, Zhang Y, Woodhead A, Zhang A. Sustainable cold supply chain management under demand uncertainty and carbon tax regulation. Transp Res D Transp Environ. 2020; 80:102245. 
28.    Sazvar Z, Zokaee M, Tavakkoli-Moghaddam R, Salari SA sadat, Nayeri S. Designing a sustainable closed-loop pharmaceutical supply chain in a competitive market considering demand uncertainty, manufacturer’s brand and waste management. Ann Oper Res. 2022;1–32. 
29.    Ahmad RW, Salah K, Jayaraman R, Yaqoob I, Omar M, Ellahham S. Blockchain-based forward supply chain and waste management for COVID-19 medical equipment and supplies. Ieee Access. 2021; 9:44905–27. 
30.    Chisholm JM, Zamani R, Negm AM, Said N, Abdel daiem MM, Dibaj M, et al. Sustainable waste management of medical waste in African developing countries: A narrative review. Waste Management & Research. 2021;39(9):1149–63. 
31.    Debrah JK, Vidal DG, Dinis MAP. Raising awareness on solid waste management through formal education for sustainability: A developing countries evidence review. Recycling. 2021;6(1):6. 
32.    Chauhan A, Jakhar SK, Chauhan C. The interplay of circular economy with industry 4.0 enabled smart city drivers of healthcare waste disposal. J Clean Prod. 2021; 279:123854. 
33.    Udir KM, Golob U, Podnar K. Exploring public relations’ social impact: Insights from a Delphi study. Public Relat Rev. 2025;51(5):102637. 
34.    Saiyed S, Kumar V, Islam MS, Tedjakusuma AP, Verma P. Advancing sustainability in academic institutions: A GHRM Framework using fuzzy Delphi and DEMATEL method. Green Technologies and Sustainability. 2025;100294. 
35.    Rejeb A, Rejeb K, Keogh JG, Zailani S. Barriers to blockchain adoption in the circular economy: a fuzzy Delphi and best-worst approach. Sustainability. 2022;14(6):3611. 
36.    Liang Q, Mendel JM. Interval type-2 fuzzy logic systems: theory and design. IEEE Transactions on Fuzzy systems. 2000;8(5):535–50. 
37.    Du Z, Xie X, Qu Z, Hu Y, Stojanovic V. Dynamic event-triggered consensus control for interval type-2 fuzzy multi-agent systems. IEEE Transactions on Circuits and Systems I: Regular Papers. 2024;71(8):3857–66. 
38.    Mutlu M, Cetin NC, Onder S. A novel risk assessment approach for open-cast coal mines using hybrid MCDM models with interval type-2 fuzzy sets: a case study in Türkiye. Systems. 2024;12(8):267. 
39.    Alimohammadlou M, Sharifian S. Industry 4.0 implementation challenges in small-and medium-sized enterprises: an approach integrating interval type-2 fuzzy BWM and DEMATEL. Soft comput. 2023;27(1):169–86. 
40.    Wu Q, Zhou L, Chen Y, Chen H. An integrated approach to green supplier selection based on the interval type-2 fuzzy best-worst and extended VIKOR methods. Inf Sci (N Y). 2019; 502:394–417. 
41.    Danacı M, Yıldırım U. Comprehensive analysis of lifeboat accidents using the Fuzzy Delphi method. Ocean Engineering. 2023; 278:114371. 
42.    Naghipour MS, Rahim ZA, Iqbal MS. A 5G competency model based on the fuzzy Delphi method. Journal of Infrastructure, Policy and Development. 2024;8(10):6788.
43.         Bayatzadeh S, Talaie H, Sorourkhah A. Analyzing the quality of digitalization in supply chain collaboration models using an integrated fuzzy BWM-TOPSIS approach. Journal of quality engineering and management. 2024;14(3):224-43. (persian)
44.       Talaie H, Ziaeian M, Malekinejad P. Designing the establishment and implementation model of quality 4.0 with the integrated approach of interpretive structural modeling and structural equation modeling. Journal of quality engineering and management. 2022; 12(1):51-68. (persian)