Journals / Ulisa: Uluslararası Çalışmalar Dergisi / 2024 / Cilt: 8 Sayı: 2

Analysis of Economic Determinants of the Effectiveness of Humanitarian Logistics

İnsani Yardım Lojistiğinde Ekonomik Belirleyiciler ve Etkinlik Analizi

Hikmet Akyol(Gümüşhane Üniversitesi)0000-0001-9119-7416
Melahat Batu Ağırkaya(IĞDIR ÜNİVERSİTESİ, IĞDIR MESLEK YÜKSEKOKULU)0000-0002-8703-5622
Pages
70–80
Publication Date
2024-12-31
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Inferences were made for policymakers, practitioners, and researchers through the results of the study.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Natural disasters, wars, economic bottlenecks, and other humanitarian crises in underdeveloped countries can cause widespread destruction and loss of life.
📊
Key Findings & Data:For this purpose, the period of 2014-2019 for 20 less-developed countries was estimated using data envelopment and panel data analysis methods.
💡
Conclusion & Impact:Inferences were made for policymakers, practitioners, and researchers through the results of the study.
🔬Design:Araştırma Makalesi
📍Scope:2014-2019 Verileri
⚙️Variables:İnsani Yardım Lojistiği · Ekonomik Kalkınma · Az Gelişmiş Ülkeler

Abstract

Natural disasters, wars, economic bottlenecks, and other humanitarian crises in underdeveloped countries can cause widespread destruction and loss of life. The main purpose of humanitarian aid operations is to provide emergency aid, comprising food, water, shelter, and basic health supplies, to crises in underdeveloped countries. In this respect, efficiency analysis is one of the focal points of humanitarian aid logistics research. This research examined the economic determinants of the effectiveness of humanitarian logistics in underdeveloped countries. For this purpose, the period of 2014-2019 for 20 less-developed countries was estimated using data envelopment and panel data analysis methods. Within the research framework, the effectiveness of humanitarian aid logistics was first determined using the data envelopment technique and the Malmquist total factor productivity index. The data envelopment method is a linear programming method that reveals the effectiveness of decision units because of analyzing too many input and output factors. The Malmquist index is used to determine the periodic change in productivity. In the study, the input parameters were adults and children living with HIV, population ratio, and per capita health expenditures. The output units comprised people with HIV treated with antiretroviral therapy, life expectancy at birth, and the total population enjoying at least basic drinking water and sanitation services. In the next research stage, the effects of selected economic indicators on the effectiveness of humanitarian aid logistics were analyzed using panel regression estimators. Inferences were made for policymakers, practitioners, and researchers through the results of the study.

Özet

Az gelişmiş ülkelerde yaşanan doğal afetler, savaşlar, ekonomik darboğazlar ve diğer insani krizler geniş çaplı yıkıma ve can kayıplarına neden olabilmektedir. İnsani yardım operasyonlarının ana amacı az gelişmiş ülkelerde yaşanan krizlere gıda, su, barınma ve temel sağlık malzemelerinden oluşan acil yardımların temin edilmesidir. Bu bakımdan insani yardım lojistiği araştırmalarının odak noktalarından birisini etkinlik analizleri oluşturmaktadır. Bu araştırma az gelişmiş ülkelerde insani yardım lojistiğinin etkinliğinin ekonomik belirleyicilerini incelemiştir. Bu amaçla 20 az gelişmiş ülke için 2014-2019 dönemi veri zarflama ve panel veri analizi yöntemleri kullanılarak tahmin edilmiştir. Araştırma çerçevesinde ilk olarak insani yardım lojistiğinin etkinliği veri zarflama tekniği ve Malmquist toplam faktör verimliliği endeksi kullanılarak belirlenmiştir. Veri zarflama yöntemi, çok fazla girdi ve çıktı faktörünün analiz edilmesi sonucu karar birimlerinin etkinliğini ortaya koyan doğrusal bir programlama yöntemidir. Malmquist endeksi ise verimliliğin dönemsel değişimini tespit etmek amacıyla kullanılmaktadır. Araştırmada girdi parametrelerini HIV ile yaşayan yetişkinler ve çocuklar, nüfus oranı ve kişi başına düşen sağlık harcamaları oluşturmuştur. Çıktı birimlerini Antiretroviral tedavi ile tedavi edilen HIV'li kişiler, doğumda beklenen yaşam süresi, en azından temel içme suyu ve sanitasyon hizmetlerinden yararlanan toplam nüfus oluşturmuştur. Araştırmanın sonraki aşamasında ise seçilmiş ekonomik göstergelerin insani yardım lojistiğinin etkinliği üzerindeki etkileri panel regresyon tahmincileri kullanılarak analiz edilmiştir. Çalışma sonuçları üzerinden politika yapıcıları, pratisyenler ve araştırmacılar için çıkarımlarda bulunulmuştur.

🔖

Cite This Article

Akyol, H., Ağırkaya, M. B. (2024). Analysis of Economic Determinants of the Effectiveness of Humanitarian Logistics. Ulisa: Uluslararası Çalışmalar Dergisi, Cilt: 8 Sayı: 2, 70–80. https://ajindex.com/articles/1563246

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (34)

  1. Argollo da Costa, S., Campos, V., & Bandeira, R. (2012). 5th meeting of the EURO Working Group on Transportation Supply Chains in Humanitarian Operations: Cases and Analysis. Procedia - Social and Behavioral Sciences, 54, 598-607. DOI: 10.1016/j.sbspro.2012.09.777
  2. Akan, E., Baştuğ, S., Kiraci, K., & Lai, K. (2024). The humanitarian logistics performance measurement model: A case study of COVID-19. Scientific Journals of the Maritime University of Szczecin. Scientific Journals of the Maritime University of Szczecin, 78(150), 56-78. DOI: 10.17402/607
  3. Akben, İ., & Taşdoğan, O. (2021). İnsanı Yardım Kuruluşlarının, Verimlilik, Etkinlik ve Lojistik Performans Değerlendirmesi. Journal of Transportation and Logistics, 61(1), 2-16. DOI: https://doi.org/ 10.26650/JTL.2021.910435
  4. Alda, E., & Cuesta, J. (2019). Measuring the efficiency of humanitarian aid. Economics Letters, 183(108618), 2-4. DOI: https://doi.org/10.1016/j.econlet.2019.108618
  5. ALNAP (2015). The state of the humanitarian system. ALNAP Study. London: ALNAP/ODI.
  6. Arellano, M. (1987). Computing robust standard errors for within-group estimators. Oxford Bulletin of Economics and Statistics, 49, 431-434. DOI: https://doi.org/10.1111/j.1468-0084.1987.mp49004006.x
  7. Baki, B., & Abuasad, N. (2020). The evaluation of humanitarian supply chain performance based on Balanced Scorecard-DEMATEL approach. The Journal of Operations Research, Statistics, Econometrics and Management Information Systems, 8(2), 163-180. DOI: 10.17093/alphanumeric.736730
  8. Baki, B. (2020). The Evaluation of Humanitarian Supply Chain Performance Based On Balanced Scorecard-DEMATEL Approach. alphanumeric journal., 8(2), 164-180. DOI: 10.17093/alphanumeric.736730
  9. Beamon, B., & Balcik, B. (2008). Performance measurement in humanitarian relief chains. International Journal of Public Sector Management, 21(1), 4-25. DOI 10.1108/09513550810846087
  10. Corbett, C., Pedraza-Martinez, A., & Wassenhove, L. (2022). Sustainable humanitarian operations: An integrated perspective. Prod Oper Manag, 31, 4393–4406. DOI: 10.1111/poms.13848
  11. Da Costa, S., Campos, V., & Bandeira, R. (2012). Supply Chains in Humanitarian Operations: Cases and Analysis. Procedia - Social and Behavioral Sciences, 54, 598-607. DOI: https://doi.org/10.1016/j.sbspro.2012.09.777
  12. Froot, K. (1989). (). Consistent covariance matrix estimation with cross-sectional dependence and heteroskedasticity in financial data. The Journal of Financial and Quantitative Analysis, 24(3), 333-355. DOI: https://doi.org/10.2307/2330815
  13. Hausman, J. (1978). Specification tests in econometrics. Econometrica, 46, Econometrica. DOI: https://doi.org/10.2307/1913827
  14. IMF (2023). Fiscal monitor: on the path to policy normalization. Washington, DC: IMF, April.
  15. Jusoh, M., Hassan, N., Hassan, M., & Hashim, H. (2022). Human resource management and humanitarian operations performance: A case study of humanitarian organizations in Malaysia. Interdisciplinary. Journal of Information, Knowledge, and Management, 17, 235-258. DOI: https://doi.org/10.28945/49
  16. Johnson, B., Keskinocak, P., Lorca, A., Pekgun, P., & Swann, J. (2012). M. Celik, O. Ergun, Humanitarian Logistics. In INFORMS TutORials in Operations Research, 3(5), 18-49. DOI: https://doi.org/10.1287/educ.1120.0100.
  17. Kembro, J., Kunz, N., Frennesson, L., & Vega, D. (2023). Revisiting the definition of humanitarian logistics. J Bus Logist., 45:e12376. DOI: https://doi.org/10.1111/jbl.12376
  18. Kim, H., & Lee, C. (2018). Efficiency analysis for nonprofit organizations using DEA- focused on humanitarian assistance organizations in South Korea. Asia Pacific Journal of Innovation and Entrepreneurship, 12(2), 165-180. DOI: 10.1108/APJIE-04-2018-0018
  19. Klumpp, M., & Loske, D. (2021). Long-term economic sustainability of humanitarian logistics-a multi-level and time-series data envelopment analysis. International Journal of Environmental Research and Public Health, 18(2219), 2-19. DOI: https://doi.org/10.3390/ijerp
  20. Kovacs, G., & Spens, K. (2007). Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution & Logistics Management, 37(2), 99-114. DOI: 10.1108/09600030710734820
  21. Malmquist, S. (1953). Index Numbers and Indifference Curves. Trabajos de Estatistica, 4, 209-242. DOI: https://doi.org/10.1007/BF03006863
  22. Negi, S. (2022). Humanitarian logistics challenges in disaster relief operations: A humanitarian organisations’ perspective. Journal of Transport and Supply Chain Management, 16(0), a691. DOI: https://doi.org/10.4102/jtscm.v16i0.691
  23. Nikbakhsh, E., & Farahani, R. Z. (2011). 15 - Humanitarian Logistics Planning in Disaster Relief Operations, Editor(s): Reza Zanjirani Farahani, Shabnam Rezapour, Laleh Kardar, Logistics Operations and Management, 291-332. DOI: https://doi.org/10.1016/B978-0-12-385202-1.00015-3.
  24. Nunes, R., & Pereira, S. (2022). Intellectual structure and trends in the humanitarian operations field. Annals of Operations Research, 319, 1099-1157. DOI: https://doi.org/10.1007/s10479-021-04022-2
  25. Starr, M., & Wassenhove, L. (2014). Introduction to the Special Issue on Humanitarian Operations and Crisis Management. Production and Operations Management., 232(6), 925–937. DOI: 10.1111/poms.12227
  26. Stoddard, A., Poole, L., Taylor, G., King, B., Jillani, S., & Potter, A. (2017). Efficiency and Inefficiency in Humanitarian Financing. United States Agency for International Development (USAID).
  27. Pesaran, M. (2004). General diagnostic tests for cross section dependence in panels. Cambridge: Working Papers.
  28. Rodríguez-Espíndola, O., Ahmadi, H., Gastélum-Chavira, D., Ahumada-Valenzuela, O., Chowdhury, S., Dey, P., & Albores, P. (2023). Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation. Socio-Economic Planning Sciences, 89 (101669), 2-26. DOI: https://doi.org/10.1016/j.seps.2023.101669
  29. Rogers, W. (1993). Regression standard errors in clustered samples. Stata Technical Bulletin, 3, 19-23. The UN Refugee Agency. (2024). Syria emergency. https://www.unhcr.org/uk/emergencies/syria-emergency adresinden alındı
  30. Tone, K. (2004). Malmquist productivity index. In: Cooper, W.W., Seiford, L.M., Zhu, J. (eds) Handbook on Data Envelopment Analysis. International Series in Operations Research & Management Science, 71. Springer, Boston, MA. DOI: https://doi.org/10.1007/1-4020-7798-X_8
  31. Vhikai, R., Mugoni, E., Mataka, A., & Saruchera, F. (23024). Digitalisation and efficient humanitarian logistical operations in Zimbabwe. Cogent Social Sciences, 10 (1), 2321725. DOI: https://doi.org/10.1080/23311886.2024.2321725
  32. World Bank. (2024). How four logistics companies stepped up relief efforts in humanitarian crises. https://www.weforum.org/impact/how-humanitarian-logistics-partners-have-stepped-up-delivery-amid-multiple-crises/ adresinden alındı
  33. World Economic Forum. (2024). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators adresinden alındı.
  34. Rodríguez-Espíndola, O., Ahmadi, H., Gastélum-Chavira, D., Ahumada-Valenzuela, O., Chowdhury, S., Dey, P., & Albores, P. (2023). Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation. Socio-Economic Planning Sciences, 89 (101669), 2-26. DOI: https://doi.org/10.1016/j.seps.2023.101669