IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v38y2022i3p1234-1244.html
   My bibliography  Save this article

Forecasting in humanitarian operations: Literature review and research needs

Author

Listed:
  • Altay, Nezih
  • Narayanan, Arunachalam

Abstract

Forecasting research in the humanitarian context is scarce. In this literature review, our goal is not only to show why forecasting research is important for the humanitarian sector, but also to identify what has been done so far, and where are the needs for further research. We conducted a structured literature search in Scopus, Web of Science, ABI Inform, and Google Scholar resulted in only 38 papers published between 1990 and 2018. Based on our findings we highlight three case studies as exemplary research in forecasting within the humanitarian context and list seven future research streams with specific research needs identified in each stream.

Suggested Citation

  • Altay, Nezih & Narayanan, Arunachalam, 2022. "Forecasting in humanitarian operations: Literature review and research needs," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1234-1244.
    • Handle: RePEc:eee:intfor:v:38:y:2022:i:3:p:1234-1244
    DOI: 10.1016/j.ijforecast.2020.08.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207020301151
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijforecast.2020.08.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. A. Chevuturi & A. P. Dimri, 2016. "Investigation of Uttarakhand (India) disaster-2013 using weather research and forecasting model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(3), pages 1703-1726, July.
    2. Gemma Berenguer & Pinar Keskinocak & J. George Shanthikumar & Jayashankar M. Swaminathan & Luk Van Wassenhove & Álvaro Lorca & Melih Çelik & Özlem Ergun & Pınar Keskinocak, 2017. "An Optimization-Based Decision-Support Tool for Post-Disaster Debris Operations," Production and Operations Management, Production and Operations Management Society, vol. 26(6), pages 1076-1091, June.
    3. Sanjay L. Ahire & Pelin Pekgün, 2018. "Harvest Hope Food Bank Optimizes Its Promotional Strategy to Raise Donations Using Integer Programming," Interfaces, INFORMS, vol. 48(4), pages 291-306, August.
    4. Taleb, Nassim Nicholas, 2009. "Errors, robustness, and the fourth quadrant," International Journal of Forecasting, Elsevier, vol. 25(4), pages 744-759, October.
    5. Clay Whybark, D., 2007. "Issues in managing disaster relief inventories," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 228-235, July.
    6. Mohammed Dore, 2003. "Forecasting the Conditional Probabilities of Natural Disasters in Canada as a Guide for Disaster Preparedness," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 28(2), pages 249-269, March.
    7. L N Van Wassenhove, 2006. "Humanitarian aid logistics: supply chain management in high gear," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 475-489, May.
    8. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    9. Vere-Jones, David, 1995. "Forecasting earthquakes and earthquake risk," International Journal of Forecasting, Elsevier, vol. 11(4), pages 503-538, December.
    10. Davis, Lauren B. & Samanlioglu, Funda & Qu, Xiuli & Root, Sarah, 2013. "Inventory planning and coordination in disaster relief efforts," International Journal of Production Economics, Elsevier, vol. 141(2), pages 561-573.
    11. Sheu, Jiuh-Biing, 2010. "Dynamic relief-demand management for emergency logistics operations under large-scale disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 1-17, January.
    12. S Taskin & E J Lodree,, 2011. "A Bayesian decision model with hurricane forecast updates for emergency supplies inventory management," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1098-1108, June.
    13. Xuejun Shen & Limin Ou & Xiaojun Chen & Xin Zhang & Xuerui Tan, 2013. "The Application of the Grey Disaster Model to Forecast Epidemic Peaks of Typhoid and Paratyphoid Fever in China," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-6, April.
    14. Cheng Miao & Mingtao Ding, 2017. "Analysis of influence of natural disaster on the economy and prediction of recovery time based on grey forecasting–difference comparison model: a case study in the upper Min River," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(2), pages 1135-1150, January.
    15. Davis, Lauren B. & Jiang, Steven X. & Morgan, Shona D. & Nuamah, Isaac A. & Terry, Jessica R., 2016. "Analysis and prediction of food donation behavior for a domestic hunger relief organization," International Journal of Production Economics, Elsevier, vol. 182(C), pages 26-37.
    16. Mude, Andrew G. & Barrett, Christopher B. & McPeak, John G. & Kaitho, Robert & Kristjanson, Patti, 2009. "Empirical forecasting of slow-onset disasters for improved emergency response: An application to Kenya's arid north," Food Policy, Elsevier, vol. 34(4), pages 329-339, August.
    17. Wright, George & Goodwin, Paul, 2009. "Decision making and planning under low levels of predictability: Enhancing the scenario method," International Journal of Forecasting, Elsevier, vol. 25(4), pages 813-825, October.
    18. Shin-Liang Chan & Wann-Ming Wey & Pin-Huai Chang, 2014. "Establishing Disaster Resilience Indicators for Tan-sui River Basin in Taiwan," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 115(1), pages 387-418, January.
    19. John Boylan & Aris Syntetos, 2006. "Accuracy and Accuracy Implication Metrics for Intermittent Demand," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 4, pages 39-42, June.
    20. Yagci Sokat, Kezban & Zhou, Rui & Dolinskaya, Irina S. & Smilowitz, Karen & Chan, Jennifer, 2016. "Capturing Real-Time Data in Disaster Response Logistics," Journal of Operations and Supply Chain Management (JOSCM), Fundação Getulio Vargas, Escola de Administração de Empresas de São Paulo (FGV EAESP), vol. 9(1), July.
    21. Zheng-Xin Wang, 2013. "A genetic algorithm-based grey method for forecasting food demand after snow disasters: an empirical study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 68(2), pages 675-686, September.
    22. Ju-Liang Jin & Jian Cheng & Yi-Ming Wei, 2008. "Forecasting flood disasters using an accelerated genetic algorithm: Examples of two case studies for China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 44(1), pages 85-92, January.
    23. Taskin, Selda & Lodree Jr., Emmett J., 2010. "Inventory decisions for emergency supplies based on hurricane count predictions," International Journal of Production Economics, Elsevier, vol. 126(1), pages 66-75, July.
    24. Mohan, S. & Gopalakrishnan, M. & Mizzi, P.J., 2013. "Improving the efficiency of a non-profit supply chain for the food insecure," International Journal of Production Economics, Elsevier, vol. 143(2), pages 248-255.
    25. Ju Myung Song & Weiwei Chen & Lei Lei, 2018. "Supply chain flexibility and operations optimisation under demand uncertainty: a case in disaster relief," International Journal of Production Research, Taylor & Francis Journals, vol. 56(10), pages 3699-3713, May.
    26. Altay, Nezih & Litteral, Lewis A. & Rudisill, Frank, 2012. "Effects of correlation on intermittent demand forecasting and stock control," International Journal of Production Economics, Elsevier, vol. 135(1), pages 275-283.
    27. Sha-lei Zhan & Nan Liu, 2016. "Determining the optimal decision time of relief allocation in response to disaster via relief demand updates," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(3), pages 509-520, February.
    28. James Done & Greg Holland & Cindy Bruyère & L. Leung & Asuka Suzuki-Parker, 2015. "Modeling high-impact weather and climate: lessons from a tropical cyclone perspective," Climatic Change, Springer, vol. 129(3), pages 381-395, April.
    29. Li, Bin & Hernandez, Ivan & Milburn, Ashlea Bennett & Ramirez-Marquez, Jose Emmanuel, 2018. "Integrating uncertain user-generated demand data when locating facilities for disaster response commodity distribution," Socio-Economic Planning Sciences, Elsevier, vol. 62(C), pages 84-103.
    30. Boone, Tonya & Ganeshan, Ram & Jain, Aditya & Sanders, Nada R., 2019. "Forecasting sales in the supply chain: Consumer analytics in the big data era," International Journal of Forecasting, Elsevier, vol. 35(1), pages 170-180.
    31. Gina Galindo Pacheco & Rajan Batta, 2016. "Forecast-driven model for prepositioning supplies in preparation for a foreseen hurricane," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(1), pages 98-113, January.
    32. Rob J. Hyndman, 2006. "Another Look at Forecast Accuracy Metrics for Intermittent Demand," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 4, pages 43-46, June.
    33. John H. Park & Burak Kazaz & Scott Webster, 2018. "Surface vs. Air Shipment of Humanitarian Goods under Demand Uncertainty," Production and Operations Management, Production and Operations Management Society, vol. 27(5), pages 928-948, May.
    34. Ping‐Hung Hsieh, 2004. "A Data‐Analytic Method for Forecasting Next Record Catastrophe Loss," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 71(2), pages 309-322, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alekh Gour & Shikha Aggarwal & Subodha Kumar, 2022. "Lending ears to unheard voices: An empirical analysis of user‐generated content on social media," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2457-2476, June.
    2. Dubey, Rameshwar & Bryde, David J. & Dwivedi, Yogesh K. & Graham, Gary & Foropon, Cyril, 2022. "Impact of artificial intelligence-driven big data analytics culture on agility and resilience in humanitarian supply chain: A practice-based view," International Journal of Production Economics, Elsevier, vol. 250(C).
    3. Pérez, Eduardo & Marthak, Yash V. & Méndez Mediavilla, Francis A., 2023. "Analysis and forecast of donations at domestic hunger relief organizations impacted by natural disasters," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    2. Rodríguez-Espíndola, Oscar & Ahmadi, Hossein & Gastélum-Chavira, Diego & Ahumada-Valenzuela, Omar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel, 2023. "Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    3. Kunz, Nathan & Reiner, Gerald & Gold, Stefan, 2014. "Investing in disaster management capabilities versus pre-positioning inventory: A new approach to disaster preparedness," International Journal of Production Economics, Elsevier, vol. 157(C), pages 261-272.
    4. Yusen Ye & Wen Jiao & Hong Yan, 2020. "Managing Relief Inventories Responding to Natural Disasters: Gaps Between Practice and Literature," Production and Operations Management, Production and Operations Management Society, vol. 29(4), pages 807-832, April.
    5. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    6. Rafiei, Rezvan & Huang, Kai & Verma, Manish, 2022. "Cash versus in-kind transfer programs in humanitarian operations: An optimization program and a case study," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    7. Prima Denny Sentia & Syaimak Abdul Shukor & Amelia Natasya Abdul Wahab & Muriati Mukhtar, 2023. "Logistic distribution in humanitarian supply chain management: a thematic literature review and future research," Annals of Operations Research, Springer, vol. 323(1), pages 175-201, April.
    8. Abhishek Behl & Pankaj Dutta, 2019. "Humanitarian supply chain management: a thematic literature review and future directions of research," Annals of Operations Research, Springer, vol. 283(1), pages 1001-1044, December.
    9. Li, Xiaoping & Batta, Rajan & Kwon, Changhyun, 2017. "Effective and equitable supply of gasoline to impacted areas in the aftermath of a natural disaster," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 25-34.
    10. Fianu, Sefakor & Davis, Lauren B., 2018. "A Markov decision process model for equitable distribution of supplies under uncertainty," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1101-1115.
    11. Consuelos Salas, Laura & Robles Cárdenas, Manuel & Zhang, Muhong, 2012. "Inventory policies for humanitarian aid during hurricanes," Socio-Economic Planning Sciences, Elsevier, vol. 46(4), pages 272-280.
    12. Rezapour, Shabnam & Farahani, Reza Zanjirani & Morshedlou, Nazanin, 2021. "Impact of timing in post-warning prepositioning decisions on performance measures of disaster management: A real-life application," European Journal of Operational Research, Elsevier, vol. 293(1), pages 312-335.
    13. Wang, Jing & Cai, Jianping & Yue, Xiaohang & Suresh, Nallan C., 2021. "Pre-positioning and real-time disaster response operations: Optimization with mobile phone location data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    14. Diehlmann, Florian & Klein, Miriam & Wiens, Marcus & Lüttenberg, Markus & Schultmann, Frank, 2020. "On the value of accurate demand information in public-private emergency collaborations," Working Paper Series in Production and Energy 51, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    15. Davis, Lauren B. & Samanlioglu, Funda & Qu, Xiuli & Root, Sarah, 2013. "Inventory planning and coordination in disaster relief efforts," International Journal of Production Economics, Elsevier, vol. 141(2), pages 561-573.
    16. Jónas Oddur Jónasson & Kamalini Ramdas & Alp Sungu, 2022. "Social impact operations at the global base of the pyramid," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4364-4378, December.
    17. Battarra, Maria & Balcik, Burcu & Xu, Huifu, 2018. "Disaster preparedness using risk-assessment methods from earthquake engineering," European Journal of Operational Research, Elsevier, vol. 269(2), pages 423-435.
    18. Xiaodan Pan & Martin Dresner & Benny Mantin & Jun A. Zhang, 2020. "Pre‐Hurricane Consumer Stockpiling and Post‐Hurricane Product Availability: Empirical Evidence from Natural Experiments," Production and Operations Management, Production and Operations Management Society, vol. 29(10), pages 2350-2380, October.
    19. Shubhra Paul & Lauren B. Davis, 2022. "An ensemble forecasting model for predicting contribution of food donors based on supply behavior," Annals of Operations Research, Springer, vol. 319(1), pages 1-29, December.
    20. TURKEŠ, Renata & PALHAZI CUERVO, Daniel & SÖRENSEN, Kenneth, 2016. "Pre-positioning of emergency supplies: Does putting a price on human life help to save lives?," Working Papers 2016012, University of Antwerp, Faculty of Business and Economics.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:intfor:v:38:y:2022:i:3:p:1234-1244. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.