The emergent role of digital technologies in the context of humanitarian supply chains: a systematic literature review
Tóm tắt
The role of digital technologies (DTs) in humanitarian supply chains (HSC) has become an increasingly researched topic in the operations literature. While numerous publications have dealt with this convergence, most studies have focused on examining the implementation of individual DTs within the HSC context, leaving relevant literature, to date, dispersed and fragmented. This study, through a systematic literature review of 110 articles on HSC published between 2015 and 2020, provides a unified overview of the current state-of-the-art DTs adopted in HSC operations. The literature review findings substantiate the growing significance of DTs within HSC, identifying their main objectives and application domains, as well as their deployment with respect to the different HSC phases (i.e., Mitigation, Preparedness, Response, and Recovery). Furthermore, the findings also offer insight into how participant organizations might configure a technological portfolio aimed at overcoming operational difficulties in HSC endeavours. This work is novel as it differs from the existing traditional perspective on the role of individual technologies on HSC research by reviewing multiple DTs within the HSC domain.
Tài liệu tham khảo
Abidi, H., De Leeuw, S., & Klumpp, M. (2014). Humanitarian supply chain performance management: A systematic literature review. Supply Chain Management: An International Journal, 19(5/6), 592–608
Akter, S., & Fosso Wamba, S. (2019). Big data and disaster management: A systematic review and agenda for future research. Annals of Operations Research, 283, 939–959. https://doi.org/10.1007/s10479-017-2584-2
Altay, N., & Green, W. G., III. (2006). OR/MS research in disaster operations management. European Journal of Operational Research, 175(1), 475–493
Altay, N., Gunasekaran, A., Dubey, R., & Childe, S. J. (2018). Agility and resilience as antecedents of supply chain performance under moderating effects of organizational culture within the humanitarian setting: A dynamic capability view. Production Planning and Control, 29(14), 1158–1174
Annamalai, V., Gupta, S. K., & Schwiebert, L. (2003). On tree-based convergecasting in wireless sensor networks. In 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003. (Vol. 3, pp. 1942–1947). IEEE.
Banomyong, R., Varadejsatitwong, P., & Oloruntoba, R. (2019). A systematic review of humanitarian operations, humanitarian logistics and humanitarian supply chain performance literature 2005 to 2016. Annals of Operations Research, 283(1–2), 71–86
Behl, A., & Dutta, P. (2019). Humanitarian supply chain management: A thematic literature review and future directions of research. Annals of Operations Research, 283(1), 1001–1044. https://doi.org/10.1007/s10479-018-2806-2
Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: A literature review. International Journal of Production Research, 57(15–16), 4719–4742. https://doi.org/10.1080/00207543.2017.1402140
Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 37(2), 471–482
Beynon-Davis, P. (2009). Business Information Systems. Palgrave Macmillan.
Carter, W. N. (2008). Disaster management: A disaster manager’s handbook. Philippines: ADB.
Cegiela, R. (2006). Selecting technology for disaster recovery. In 2006 International Conference on Dependability of Computer Systems, 160–167, IEEE Computer Society
Charles, A. (2010). Improving the design and management of agile supply chains: feedback and application in the context of humanitarian aid (Doctoral dissertation).
Chute, C., & French, T. (2019). Introducing care 4.0: An integrated care paradigm built on industry 4.0 capabilities. International Journal of Environmental Research and Public Health, 16(12), 2247
Dash, R., McMurtrey, M., Rebman, C., & Kar, U. K. (2019). Application of artificial intelligence in automation of supply chain management. Journal of Strategic Innovation and Sustainability, 14(3), 1–13
Day, J. M., Junglas, I., & Silva, L. (2009). Information flow impediments in disaster relief supply chains. Journal of the Association for Information Systems, 10(8), 1
Day, J. M. , Melnyk, S. A., Larson, P. D. , Davis, E. W., & Whybark, D. C. (2012). Humanitarian and disaster relief supply chains: a matter of life and death. Journal of Supply Chain Management, 48(2), 21–36
de Camargo Fiorini, P., Jabbour, C. J. C., de Sousa Jabbour, A. B. L., & Ramsden, G. (2021). The human side of humanitarian supply chains: A research agenda and systematization framework. Annals of Operations Research,. https://doi.org/10.1007/s10479-021-03970-z
de Campos, E. A. R., Resende, L. M., & Pontes, J. B. (2019). External aspects and trust factors in horizontal networks of companies: A theoretical proposal for the construction of a model for evaluation of trust. Journal of Intelligent Manufacturing, 30, 1547–1562. https://doi.org/10.1007/s10845-017-1339-x
Delmonteil, F. X., & Rancourt, M. È. (2017). The role of satellite technologies in relief logistics. Journal of Humanitarian Logistics and Supply Chain Management, 7(1), 57–78
Denyer, D., & Tranfield, D. (2009). Producing a systematic review. In D. A. Buchanan & A. Bryman (Eds.), The Sage handbook of organizational research methods. (pp. 671–689). London: Sage Publications.
Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., & Fosso Wamba, S. (2017). World class sustainable supply chain management: Critical review and further research direction. International Journal of Logistics Management, 28(2), 332–362
Dubey, R., Altay, N., Gunasekaran, A., Blome, C., Papadopoulos, T., & Childe, S. J. (2018). Supply chain agility, adaptability and alignment: Empirical evidence from the Indian auto components industry. International Journal of Operations & Production Management, 38(1), 129–148. https://doi.org/10.1108/IJOPM-04-2016-0173
Dubey, R. (2019). Developing an integration framework for crowdsourcing and internet of things with applications for disaster response. In Social entrepreneurship: Concepts, methodologies, tools, and applications (pp. 274–283). IGI Global.
Dubey, R., Altay, N., & Blome, C. (2019a). Swift trust and commitment: The missing links for humanitarian supply chain coordination? Annals of Operations Research, 283(1), 159–177
Dubey, R., Gunasekaran, A., & Papadopoulos, T. (2019b). Disaster relief operations: Past, present and future. Annals of Operations Research, 283(1), 1–8
Dubey, R., Gunasekaran, A., Childe, S. J., Roubaud, D., Wamba, S. F., Giannakis, M., & Foropon, C. (2019c). Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain. International Journal of Production Economics, 210, 120–136
Dubey, R., Bryde, D. J., Foropon, C., Graham, G., Giannakis, M., & Mishra, D. B. (2020a). Agility in humanitarian supply chain: An organizational information processing perspective and relational view. Annals of Operations Research,. https://doi.org/10.1007/s10479-020-03824-0
Dubey, R., Gunasekaran, A., Bryde, D. J., Dwivedi, Y. K., & Papadopoulos, T. (2020b). Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting. International Journal of Production Research, 58(11), 3381–3398
Durach, C. F., Kembro, J., & Wieland, A. (2017). A new paradigm for systematic literature reviews in supply chain management. Journal of Supply Chain Management, 53(4), 67–85
Estellés-Arolas, E., Navarro-Giner, R., & González-Ladrón-de-Guevara, F. (2015). Crowdsourcing fundamentals: definition and typology. In Advances in crowdsourcing (pp. 33–48). Springer.
Fosso Wamba, S. F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234–246
Galindo, G., & Batta, R. (2013). Review of recent developments in OR/MS research in disaster operations management. European Journal of Operational Research, 230(2), 201–211
Garay-Rondero, C., Martinez-Flores, J., Smith, N., Caballero Morales, S., & Aldrette-Malacara, A. (2019). Digital supply chain model in Industry 4.0. Journal of Manufacturing Technology Management (in press). https://doi.org/10.1108/JMTM-08-2018-0280
Gavidia, J. V. (2017). A model for enterprise resource planning in emergency humanitarian logistics. Journal of Humanitarian Logistics and Supply Chain Management, 7(3), 246–265
Ghobakhloo, M. (2018). The future of manufacturing industry: A strategic roadmap toward Industry 4.0. Journal of Manufacturing Technology Management, 29(6), 910–936
Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869. https://doi.org/10.1016/j.jclepro.2019.119869
Glock, C. H., Grosse, E. H., & Ries, J. M. (2017). Decision support models for supplier development: Systematic literature review and research agenda. International Journal of Production Economics, 193, 798–812
Govindan, K., & Soleimani, H. (2017). A review of reverse logistics and closed-loop supply chains: A journal of cleaner production focus. Journal of Cleaner Production, 142, 371–384
Govindan, K., Soleimani, H., & Kannan, D. (2015). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future. European Journal of Operations Research, 240(3), 603–626
Green III, W. G., & McGinnis, S. R. (2002). Thoughts on the higher order taxonomy of disasters. Notes on the Science of Extreme Situations, Paper No 7.
Gunasekaran, A., Dubey, R., Wamba, S. F., Papadopoulos, T., Hazen, B. T., & Ngai, E. W. T. (2018). Bridging humanitarian operations management and organisational theory. International Journal of Production Research, 56(21), 6735–6740
Gupta, S., Altay, N., & Luo, Z. (2019). Big data in humanitarian supply chain management: A review and further research directions. Annals of Operations Research, 283(1), 1153–1173
Günther, W. A., Mehrizi, M. H. R., Huysman, M., & Feldberg, F. (2017). Debating big data: A literature review on realizing value from big data. The Journal of Strategic Information Systems, 26(3), 191–209
Haworth, B. (2016). Emergency management perspectives on volunteered geographic information: Opportunities, challenges and change. Computers, Environment and Urban Systems, 57, 189–198
Heaslip, G., Kovács, G., & Haavisto, I. (2018). Innovations in humanitarian supply chains: The case of cash transfer programmes. Production Planning & Control, 29(14), 1175–1190
Holguín-Veras, J., Jaller, M., Van Wassenhove, L. N., Pérez, N., & Wachtendorf, T. (2012). On the unique features of post-disaster humanitarian logistics. Journal of Operations Management, 30(7–8), 494–506
Ivanov, D., Dolgui, A., & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829–846
Jeble, S., Kumari, S., Venkatesh, V. G., & Singh, M. (2019). Influence of big data and predictive analytics and social capital on performance of humanitarian supply chain. Benchmarking: An International Journal, 27(2), 606–633
Jefferson, T. L. (2006). Evaluating the role of information technology in crisis and emergency management. VINE: The journal of information and knowledge management systems, 36(3), 261–264
Kabra, G., & Ramesh, A. (2015). Analyzing drivers and barriers of coordination in humanitarian supply chain management under fuzzy environment. Benchmarking: An International Journal, 22(4), 559–587
Kabra, G., & Ramesh, A. (2016). Information technology, mutual trust, flexibility, agility, adaptability: Understanding their linkages and impact on humanitarian supply chain management performance. Risk, Hazards & Crisis in Public Policy, 7(2), 79–103
Kabra, G., & Ramesh, A. (2017). An analysis of the interactions among the enablers of information communication technology in humanitarian supply chain management: A fuzzy-based relationship modelling approach. In Handbook of research on intelligent techniques and modeling applications in marketing analytics (pp. 62–73). IGI Global.
Kabra, G., Ramesh, A., Akhtar, P., & Dash, M. K. (2017). Understanding behavioural intention to use information technology: Insights from humanitarian practitioners. Telematics and Informatics, 34(7), 1250–1261
Kane, G. C., Alavi, M., Labianca, G., & Borgatti, S. P. (2014). What’s different about social media networks? A framework and research agenda. MIS Quarterly, 38(1), 275–304
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25
Kovács, G., & Spens, K. (2007). Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution and Logistics Management, 37(2), 99–114
Kovács, G., & Spens, K. M. (2011). Trends and developments in humanitarian logistics-a gap analysis. International Journal of Physical Distribution & Logistics Management, 41(1), 32–45
Kovács, G., & Falagara Sigala, I. (2021). Lessons learned from humanitarian logistics to manage supply chain disruptions. Journal of Supply Chain Management, 57(1), 41–49
Lasi, H., Fettke, P., Kemper, Feld, H., & Hoffmann, M. (2014). Industry 4.0. Business and Information System Engineering, 6, 239–242
Lee, C. S., & Ma, L. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in human behavior, 28(2), 331–339
Lefebvre, C. (2009). Integrating cell phones and mobile technologies into public health practice: A social marketing perspective. Health Promotion Practice, 10(4), 490–494
Liao, Y., Deschamps, F., Roch, E., & Pierin, L. F. (2017). Past, Present and future of industry 4.0—A systematic literature review and research agenda proposal. International Journal of Production Research, 55(12), 3609–3629
Lu, Q., Goh, M., & De Souza, R. (2018). An empirical investigation of swift trust in humanitarian logistics operations. Journal of Humanitarian Logistics and Supply Chain Management, 8(1), 70–86
Machado, C. G., Winroth, M. P., & Ribeiro da Silva, E. H. D. (2019). Sustainable manufacturing in industry 4.0: An emerging research agenda. International Journal of Production Research, 58(5), 1462–1484. https://doi.org/10.1080/00207543.2019.1652777
Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., & Ghalsasi, A. (2011). Cloud computing—The business perspective. Decision support systems, 51(1), 176–189
Mesmar, S., Talhouk, R., Akik, C., Olivier, P., Elhajj, I. H., Elbassuoni, S., … & Ghattas, H. (2016). The impact of digital technology on health of populations affected by humanitarian crises: Recent innovations and current gaps. Journal of public health policy, 37(2), 167–200
Modgil, S., Singh, R. K., & Foropon, C. (2020). Quality management in humanitarian operations and disaster relief management: A review and future research directions. Annals of Operations Research,. https://doi.org/10.1007/s10479-020-03695-5
Novais, L., Maqueira, J. M., & Ortiz-Bas, Á. (2019). A systematic literature review of cloud computing use in supply chain integration. Computers & Industrial Engineering, 129, 296–314
Novaro Mascarello, L., & Quagliotti, F. (2018). Design of inoffensive sUAS for humanitarian missions. Aircraft Engineering and Aerospace Technology, 90(3), 524–531
Núñez-Merino, M., Maqueira-Marín, J. M., Moyano-Fuentes, J., & Martínez-Jurado, P. J. (2020). Information and digital technologies of Industry 4.0 and Lean supply chain management: a systematic literature review. International Journal of Production Research, 58(16), 5034–5061. https://doi.org/10.1080/00207543.2020.1743896
Nyce, C., & Cpcu, A. (2007). Predictive analytics white paper. American Institute for CPCU. Insurance Institute of America.
Ozguven, E. E., & Ozbay, K. (2013). A secure and efficient inventory management system for disasters. Transportation Research Part C: Emerging Technologies, 29, 171–196
Oztemel, E., & Gursev, S. (2020). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31, 127–182. https://doi.org/10.1007/s10845-018-1433-8
Pagliosa, M., Tortorella, G., & Espindola-Ferreira, J.C. (2019). Industry 4.0 and lean manufacturing a systematic literature review and future research directions. Journal of Manufacturing Technology Management (in press). https://doi.org/10.1108/JMTM-12-2018-0446
Papadopoulos, T., Gunasekaran, A., Dubey, R., Altay, N., Childe, S. J., & Fosso Wamba, S. (2017). The role of Big Data in explaining disaster resilience in supply chains for sustainability. Journal of Cleaner Production, 142, 1108–1118
Paré, G., Trudel, M. C., Jaana, M., & Kitsiou, S. (2015). Synthesizing information systems knowledge: A typology of literature reviews. Information & Management, 52, 183–199
Pedraza-Martinez, A. J., & Van Wassenhove, L. N. (2016). Empirically grounded research in humanitarian operations management: The way forward. Journal of Operations Management, 45(1), 1–10
Prasanna, S. R., & Haavisto, I. (2018). Collaboration in humanitarian supply chains: An organisational culture framework. International Journal of Production Research, 56(17), 5611–5625
Privett, N. (2016). Information visibility in humanitarian operations: Current state-of-the-art. In Advances in managing humanitarian operations. Springer, Cham. https://doi.org/10.1007/978-3-319-24418-1_8
Pyakurel, U., & Dhamala, T. (2017). Continuous dynamic contraflow approach for evacuation planning. Annals of Operations Research, 253, 573–598
Queiroz, M. M., Ivanov, D., Dolgui, A., & Wamba, S. F. (2020). Impacts of epidemic outbreaks on supply chains: Mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Annals of Operations Research, 1–38.
Reddick, C. (2011). Information technology and emergency management: Preparedness and planning in US states. Disasters, 35(1), 45–61
Richards, N. M., & Smart, W. D. (2016). How should the law think about robots? In Robot law. Edward Elgar Publishing.
Risius, M., & Spohrer, K. (2017). A blockchain research framework. Business & Information Systems Engineering, 59(6), 385–409
Rodríguez-Espíndola, O., Chowdhury, S., Beltagui, A., & Albores, P. (2020). The potential of emergent disruptive technologies for humanitarian supply chains: The integration of blockchain, Artificial Intelligence and 3D printing. International Journal of Production Research, 58(15), 4610–4630
Rowe, F. (2014). What literature review is not: Diversity, boundaries and recommendations. European Journal of Information Systems, 23(3), 241–255
Sandvik, K. B., Jumbert, M. G., Karlsrud, J., & Kaufmann, M. (2014). Humanitarian technology: A critical research agenda. International Review of the Red Cross, 96(893), 219–242
Schiffling, S., Hannibal, C., Tickle, M., & Fan, Y. (2020). The implications of complexity for humanitarian logistics: A complex adaptive systems perspective. Annals of Operations Research,. https://doi.org/10.1007/s10479-020-03658-w
Schniederjans, D. G., & Hales, D. N. (2016). Cloud computing and its impact on economic and environmental performance: A transaction cost economics perspective. Decision Support Systems, 86, 73–82
Sebastian, I., Ross, J., Beath, C., Mocker, M., Moloney, K., & Fonstad, N. (2017). How big old companies navigate digital transformation. MIS Quarterly Executive, 16(3), 197–213
Seifert, L., Kunz, N., & Gold, S. (2018). Humanitarian supply chain management responding to refugees: A literature review. Journal of Humanitarian Logistics and Supply Chain Management, 8(3), 398–426. https://doi.org/10.1108/JHLSCM-07-2017-0029
Shklovski, I., Palen, L., & Sutton, J. (2008). Finding community through information and communication technology in disaster response. In Proceedings of the 2008 ACM conference on Computer supported cooperative work (pp. 127–136).
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339
Tatham, P., & Kovács, G. (2010). The application of ‘swift trust’ to humanitarian logistics. International Journal of Production Economics, 126(1), 35–45. https://doi.org/10.1016/j.ijpe.2009.10.006
Tortorella, G. L., & Fettermann, D. (2018). Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies. International Journal of Production Research, 56(8), 2975–2987
Tufekci, S., & Wallace, W. A. (1998). The emerging area of emergency management and engineering. IEEE Transactions on Engineering Management, 45(2), 103–105
Thomé, A. M. T., Scavarda, L. F., & Scavarda, A. J. (2016). Conducting systematic literature review in operations management. Production Planning & Control, 27(5), 408–420
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222
Ülkü, M. A., Bell, K. M., & Wilson, S. G. (2015). Modeling the impact of donor behavior on humanitarian aid operations. Annals of Operations Research, 230(1), 153–168
UNDRR. United Nations Office for Disaster Reduction. (2020). UNDRR Annual Report. 2019. Retrieved December 19, 2020 from https://www.undrr.org/publication/undrr-annual-report-2019
UNISDR. United Nations International Strategy for Disaster Reduction. (2009). UNISDIR terminology in disaster risk reduction. Retrieved July 12, 2020 from https://www.preventionweb.net/files/7817_UNISDRTerminologyEnglish.pdf
Van Blyenburgh, P. (1999). UAVs: an overview. Air & Space Europe, 1(5–6), 43–47
Van der Laan, E. A., De Brito, M. P., Van Fenema, P. C., & Vermaesen, S. C. (2009a). Managing information cycles for intra-organisational coordination of humanitarian logistics. International Journal of Services, Technology and Management, 12(4), 362–390
Van der Laan, E. A., De Brito, M. P., & Vergunst, D. A. (2009b). Performance measurement in humanitarian supply chains. International Journal of Risk Assessment and Management, 13(1), 22–45
Van Wassenhove, L. N. (2006). Humanitarian aid logistics: supply chain management in high gear. Journal of the Operational research Society, 57(5), 475–489
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J., Fabian, N., & Haenlein, M. (2019). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Vermesan, O., Friess, P., Guillemin, P., Gusmeroli, S., Sundmaeker, H., Bassi, A., … & Doody, P. (2011). Internet of things strategic research roadmap. Internet of things-global technological and societal trends, 1, 9–52
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144
Vinck, P. (2013). World disasters report 2013: Focus on technology and the future of humanitarian intervention. International Federation of Red Cross and Red Crescent Societies.
Walter, L. S. (1990). The uses of satellite technology in disaster management. Disasters, 14(1), 20–35
Waugh, W. L. (2015). Living with hazards, dealing with disasters: An introduction to emergency management: An introduction to emergency management. London: Routledge.
Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS Quarterly, 26(2), 13–23
Wolfswinkel, J. F., Furtmueller, E., & Wilderom, C. P. (2013). Using grounded theory as a method for rigorously reviewing literature. European journal of information systems, 22(1), 45–55
Xu, L. D., Xu, E. L., & Li, L. (2018). Industry 4.0: state of the art and future trends. International Journal of Production Research, 56(8), 2941–2962
Yadav, D. K., & Barve, A. (2015). Analysis of critical success factors of humanitarian supply chain: An application of Interpretive Structural Modeling. International journal of disaster risk reduction, 12, 213–225
Yang, Q., Barria, J. A., & Green, T. C. (2011a). Communication infrastructures for distributed control of power distribution networks. IEEE Transactions on Industrial Informatics, 7(2), 316–327
Yang, H., Yang, L., & Yang, S. H. (2011b). Hybrid Zigbee RFID sensor network for humanitarian logistics centre management. Journal of Network and Computer Applications, 34(3), 938–948
Abedin, B., & Babar, A. (2018). Institutional vs. non-institutional use of social media during emergency response: A case of Twitter in 2014 Australian Bush Fire. Information Systems Frontiers, 20, 729–740. https://doi.org/10.1007/s10796-017-9789-4
Ahmed, A. (2015). Role of GIS, RFID and handheld computers in emergency management: An exploratory case study analysis. Journal of Information Systems and Technology Management, 12(1), 3–27
Ahn, T., Seok, J., Lee, I., & Han, J. (2018). Reliable flying IoT networks for UAV disaster rescue operations. Mobile Information Systems, 2018, 2572460
Alamdar, F., Kalantari, M., & Rajabifard, A. (2017). Understanding the provision of multi-agency sensor information in disaster management: A case study on the Australian state of Victoria. International journal of disaster risk reduction, 22, 475–493
Angeles, R. (2018). Blockchain-based healthcare: Three successful proof-of-concept pilots worth considering. Journal of International Technology and Information Management, 27(3), 47–83
Angraal, S., Krumholz, H. M., & Schulz, W. L. (2017). Blockchain technology—Applications in health care. Circulation Cardiovascular Quality and Outcomes. https://doi.org/10.1161/CIRCOUTCOMES.117.003800
Behl, A., & Dutta, P. (2018). Humanitarian supply chain management: A thematic literature review and future directions of research. Annals of Operations Research, 283(1), 1001–1044. https://doi.org/10.1007/s10479-018-2806-2
Bellomo, N., Clarke, D., Gibelli, L., Townsend, P., & Vreugdenhil, B. J. (2016). Human behaviours in evacuation crowd dynamics: From modelling to “big data” toward crisis management. Physics of life reviews, 18, 1–21
Bhuvana, N., & Arul Aram, I. (2019). Facebook and Whatsapp as disaster management tools during the Chennai (India) floods of 2015. International Journal of Disaster Risk Reduction, 39, 101–135
Bidgoli, H. (2018). Successful integration of information technology in healthcare: Guides for managers. Journal of Strategic Innovation & Sustainability, 13(3), 22–37
Bjerge, B., Clark, N., Fisker, P., & Raju, E. (2016). Technology and information sharing in disaster relief. PLoS ONE, 11(9), e0161783
Bogue, R. (2016). Search and rescue and disaster relief robots: Has their time finally come? Industrial Robot: An International Journal, 43(2), 138–143
Bravo, R. Z. B., Leiras, A., & Cyrino Oliveira, F. L. (2019). The use of UAV s in humanitarian relief: An application of POMDP-based methodology for finding victims. Production and Operations Management, 28(2), 421–440
Brinch, M. (2018). Understanding the value of big data in supply chain management and its business processes: Towards a conceptual framework. International Journal of Operations and Production Management, 38(7), 1589–1614
Burns, R. (2018). Datafying disaster: Institutional framings of data production following superstorm sandy. Annals of the American Association of Geographers, 108(2), 569–578. https://doi.org/10.1080/24694452.2017.1402673
Chowdhury, S., Emelogu, A., Marufuzzaman, M., Nurre, S. G., & Bian, L. (2017). Drones for disaster response and relief operations: A continuous approximation model. International Journal of Production Economics, 188, 167–184
Chung, K., & Park, R. C. (2016). P2P cloud network services for IoT based disaster situations information. Peer-to-Peer Networking and Applications, 9(3), 566–577
Cinnamon, J., Jones, S. K., & Adger, W. N. (2016). Evidence and future potential of mobile phone data for disease disaster management. Geoforum, 75, 253–264
Clark, N. E. (2017). Towards a standard licensing scheme for the access and use of satellite earth observation data for disaster management. Acta Astronautica, 139, 325–331
Collins, M., Neville, K., Hynes, W., & Madden, M. (2016). Communication in a disaster—The development of a crisis communication tool within the S-HELP project. Journal of Decision Systems, 25(1), 160–170. https://doi.org/10.1080/12460125.2016.1187392
Croatti, A., Ricci, A., & Viroli, M. (2017). Towards a mobile augmented reality system for emergency management: The case of SAFE. International Journal of Distributed Systems and Technologies. https://doi.org/10.4018/IJDST.2017010104
Demir, F., Ahmad, S., Calyam, P., Jiang, D., Huang, R., & Jahnke, I. (2017). A next-generation augmented reality platform for mass casualty incidents (MCI). Journal of Usability Studies, 12(4), 193–214
Denis, G., de Boissezon, H., Hosford, S., Pasco, X., Montfort, B., & Ranera, F. (2016). The evolution of Earth Observation satellites in Europe and its impact on the performance of emergency response services. Acta Astronautica, 127, 619–633
D’Haene, C., Verlinde, S., & Macharis, C. (2015). Measuring while moving (humanitarian supply chain performance measurement–status of research and current practice). Journal of Humanitarian Logistics and Supply Chain Management, 5(2), 146–161
Drosio, S., & Stanek, S. (2016). The Big Data concept as a contributor of added value to crisis decision support systems. Journal of Decision systems, 25(1), 228–239
Dubey, R., Luo, Z., Gunasekaran, A., Akter, S., Hazen, B. T., & Douglas, M. A. (2018). Big data and predictive analytics in humanitarian supply chains. The International Journal of Logistics Management, 29(2), 485–512
Dubey, R., Gunasekaran, A., Childe, S. J., Roubaud, D., Fosso Wamba, S., Giannakis, M., & Foropon, C. (2019). Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain. International Journal of Production Economics, 210, 120–136
Dubey, R., Gunasekaran, A., Bryde, D. J., Dwivedi, Y. K., & Papadopoulos, T. (2020). Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting. International Journal of Production Research, 58(11), 3381–3398. https://doi.org/10.1080/00207543.2020.1722860
Dwiputranti, I., Oktora, A., Okdinawati, L., & Fauzan, M. (2019). Acceptance and use of information technology: Understanding information systems for Indonesia’s humanitarian relief operations. Gadjah Mada International Journal of Business, 21(3), 242–262
Elbanna, A., Bunker, D., Levine, L., & Sleigh, A. (2019). Emergency management in the changing world of social media: Framing the research agenda with the stakeholders through engaged scholarship. International Journal of Information Management, 47, 112–120
Ejaz, W., Azam, M. A., Saadat, S., Iqbal, F., & Hanan, A. (2019). Unmanned aerial vehicles enabled IoT platform for disaster management. Energies, 12(14), 2706
Erdelj, M., Natalizio, E., Chowdhury, K. R., & Akyildiz, I. F. (2017). Help from the sky: Leveraging UAVs for disaster management. IEEE Pervasive Computing, 16(1), 24–32
Erdelj, M., Król, M., & Natalizio, E. (2017). Wireless sensor networks and multi-UAV systems for natural disaster management. Computer Networks, 124, 72–86
Ghapar, A. A., Yussof, S., & Bakar, A. A. (2018). Internet of Things (IoT) architecture for flood data management. International Journal of Future Generation Communication and Networking, 11(1), 55–62
Giordan, D., Hayakawa, Y., Nex, F., Remondino, F., & Tarolli, P. (2018). The use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management. Natural Hazards & Earth System Sciences, 18(4), 1079–1096
Golabi, M., Shavarani, S. M., & Izbirak, G. (2017). An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case study of Tehran earthquake. Natural Hazards, 87(3), 1545–1565
Goswami, A., & Kumar, A. (2016). A survey of event detection techniques in online social networks. Social Network Analysis and Mining, 6(1), 107. https://doi.org/10.1007/s13278-016-0414-1
Grabowski, M., Rizzo, C., & Graig, T. (2016). Data challenges in dynamic, large-scale resource allocation in remote regions. Safety Science, 87, 76–86
Granell, C., & Ostermann, F. O. (2016). Beyond data collection: Objectives and methods of research using VGI and geo-social media for disaster management. Computers, Environment and Urban Systems, 59, 231–243
Griffith, D. A., Boehmke, B., Bradley, R. V., Hazen, B. T., & Johnson, A. W. (2019). Embedded analytics: Improving decision support for humanitarian logistics operations. Annals of Operations Research, 283(1–2), 247–265
Ha, Q. P., Yen, L., & Balaguer, C. (2019). Robotic autonomous systems for earthmoving in military applications. Automation in Construction, 107, 102934
Haddud, A., DeSouza, A., Khare, A., & Lee, H. (2017). Examining potential benefits and challenges associated with the Internet of Things integration in supply chains. Journal of Manufacturing Technology Management, 28(8), 1055–1085
Horita, F. E., de Albuquerque, J. P., Marchezini, V., & Mendiondo, E. M. (2017). Bridging the gap between decision-making and emerging big data sources: An application of a model-based framework to disaster management in Brazil. Decision Support Systems, 97, 12–22
Hu, L., Ong, D. M., Zhu, X., Liu, Q., & Song, E. (2015). Enabling RFID technology for healthcare: Application, architecture, and challenges. Telecommunication Systems, 58(3), 259–271
Hu, Q., & Kapucu, N. (2016). Information communication technology utilization for effective emergency management networks. Public Management Review, 18(3), 323–348
Hu, Y., Zhu, J., Li, W., Zhang, Y., Zhu, Q., Qi, H., Zhang, H., Cao, Z., Yang, W., & Zhang, P. (2018). Construction and optimization of three-dimensional disaster scenes within mobile virtual reality. International Journal of Geo-Information, 7(6), 215. https://doi.org/10.3390/ijgi7060215
Ittmann, H. W. (2015). The impact of big data and business analytics on supply chain management. Journal of Transport and Supply Chain Management, 9(1), 1–9
Jang, K. B., & Woo, T. H. (2019). Analysis of humanoid robotics for nuclear disaster management incorporated with biomechanics. Nuclear Technology & Radiation Protection, 34(3), 291–298
Jorge, V. A., Granada, R., Maidana, R. G., Jurak, D. A., Heck, G., Negreiros, A. P., … & Amory, A. M. (2019). A survey on unmanned surface vehicles for disaster robotics: Main challenges and directions. Sensors, 19(3), 702
Jumbert, M. G. (2018). Control or rescue at sea? Aims and limits of border surveillance technologies in the Mediterranean Sea. Disasters, 42(4), 674–696
Kamel Boulos, M. N., Wilson, J. T., & Clauson, K. A. (2018). Geospatial blockchain: Promises, challenges, and scenarios in health and healthcare. International Journal of Health Geographics, 17(25), 1–10. https://doi.org/10.1186/s12942-018-0144-x
Khan, M., Yong, L. H., & Han, B. J. (2019). Emerging techniques for enhancing the performance of humanitarian logistics. International Journal of Supply Chain Management, 8(2), 450–459
Kim, I. S., Choi, Y., & Jeong, K. M. (2017). A new approach to quantify safety benefits of disaster robots. Nuclear Engineering and Technology, 49(7), 1414–1422
Kiss Leizer, G. K., & Tokody, D. (2017). Radiofrequency identification by using drones in railway accidents and disaster situations. Interdisciplinary Description of Complex Systems, 15(2), 114–132
Kiss Leizer, G. K., & Károly, G. (2018). Possible areas of application of drones in waste management during rail accidents and disasters. Interdisciplinary Description of Complex Systems, 16(3), 360–368
Kumagai, H., Sakurauchi, H., Koitabashi, S., Uchiyama, T., Sasaki, S., Noda, K., … & Suzuki, Y. (2019). Development of resilient information and communications technology for relief against natural disasters. Journal of Disaster Research, 14(2), 348–362
Kwok, P. K., Yana, M., Chanb, B. K. P., & Laub, H. Y. K. (2019). Crisis management training using discrete-event simulation and virtual reality techniques. Computers & Industrial Engineering, 135, 711–722
Lai, C. H. (2017). A study of emergent organizing and technological affordances after a natural disaster. Online Information Review, 41(4), 507–523
Landwehr, P. M., Wei, W., Kowalchuck, M., & Carley, K. M. (2016). Using tweets to support disaster planning, warning and response. Safety Science, 90, 33–47
Li, L., Ota, K., Dong, M., & Borjigin, W. (2017). Eyes in the dark: Distributed scene understanding for disaster management. IEEE Transactions on Parallel and Distributed Systems, 28(12), 3458–3471
Li, J., Lu, D., Zhang, G., Tian, J., & Pang, Y. (2019). Post-disaster unmanned aerial vehicle base station deployment method based on artificial bee colony algorithm. IEEE Access, 7, 168327–168336
Latif, S., Qadir, J., Farooq, S., & Imran, M. A. (2017). How 5g wireless (and concomitant technologies) will revolutionize healthcare? Future Internet, 9(4), 93
Li, B., & Li, Y. (2017). Internet of things drives supply chain innovation: A research framework. International Journal of Organizational Innovation, 9(3), 71–92
Li, F., Zheng, Z., & Jin, C. (2016). Secure and efficient data transmission in the Internet of Things. Telecommunication Systems, 62(1), 111–122
Liu, Z., & Wang, C. (2019). Design of traffic emergency response system based on Internet of Things and data mining in emergencies. IEEE Access, 7, 113950–113962
Madhavaram, S., Matos, V., Blake, B. A., & Appan, R. (2017). ICTs in the context of disaster management, stakeholders, and implications. Journal of Information, Communication and Ethics in Society, 15(1), 32–52
Mascarello, L. N., & Quagliotti, F. (2017). The civil use of small unmanned aerial systems (sUASs): Operational and safety challenges. Aircraft Engineering and Aerospace Technology: An International Journal, 89(5), 703–708
Merwaday, A., Tuncer, A., Kumbhar, A., & Guvenc, I. (2016). Improved throughput coverage in natural disasters: Unmanned aerial base stations for public-safety communications. IEEE Vehicular Technology Magazine, 11(4), 53–60
Mishra, D., Luo, Z., Jiang, S., Papadopoulos, T., & Dubey, R. (2017). A bibliographic study on big data: Concepts, trends and challenges. Business Process Management Journal, 23(3), 555–573
Mishra, D., Gunasekaran, A., Papadopoulos, T., & Childe, S. J. (2018). Big Data and supply chain management: A review and bibliometric analysis. Annals of Operations Research, 270(1–2), 313–336
Mulder, F., Ferguson, J., Groenewegen, P., Boersma, K., & Wolbers, J. (2016). Questioning Big Data: Crowdsourcing crisis data towards an inclusive humanitarian response. Big Data & Society, 3(2), 1–13
Nawari, O., & Ravindran, S. (2019). Blockchain and building information modeling (BIM): Review and applications in post-disaster recovery. Buildings, 9(149), 1–32. https://doi.org/10.3390/buildings9060149
Nedjati, A., Vizvari, B., & Izbirak, G. (2016). Post-earthquake response by small UAV helicopters. Natural Hazards, 80(3), 1669–1688
Ofli, F., Meier, P., Imran, M., Castillo, C., Tuia, D., Rey, N., … & Joost, S. (2016). Combining human computing and machine learning to make sense of big (aerial) data for disaster response. Big data, 4(1), 47–59
Otto, A., Agatz, N., Campbell, J., Golden, B., & Pesch, E. (2018). Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey. Networks, 72(4), 411–458
Poblet, M., García-Cuesta, E., & Casanovas, P. (2018). Crowdsourcing roles, methods and tools for data-intensive disaster management. Information Systems Frontiers, 20, 1363–1379. https://doi.org/10.1007/s10796-017-9734-6
Pransky, J. (2018). The Pransky interview: Professor Robin R. Murphy, co-founder of the field of disaster robotics and founder of roboticists without borders. Industrial Robot: An International Journal, 45(5), 591–596
Prasad, S., Zakaria, R., & Altay, N. (2018). Big data in humanitarian supply chain networks: a resource dependence perspective. Annals of Operations Research, 270(1–2), 383–413
Rabta, B., Wankmüller, C., & Reiner, G. (2018). A drone fleet model for last-mile distribution in disaster relief operations. International Journal of Disaster Risk Reduction, 28, 107–112
Ragini, J. R., Anand, P. R., & Bhaskar, V. (2018). Big data analytics for disaster response and recovery through sentiment analysis. International Journal of Information Management, 42, 13–24
Ray, P. P., Mukherjee, M., & Shu, L. (2017). Internet of things for disaster management: State-of-the-art and prospects. IEEE Access, 5, 18818–21883
Rego, A., Garcia, L., Sendra, S., & Lloret, J. (2018). Software Defined Network-based control system for an efficient traffic management for emergency situations in smart cities. Future Generation Computer Systems, 88, 243–253
Sakurai, M., & Murayama, Y. (2019). Information technologies and disaster management–Benefits and issues. Progress in Disaster Science, 2, 100012
Sánchez-García, J., García-Campos, J. M., Toral, S. L., Reina, D. G., & Barrero, F. (2016). An intelligent strategy for tactical movements of UAVs in disaster scenarios. International Journal of Distributed Sensor Networks, 12(3), 8132812
Savonen, B. L., Mahan, T. J., Curtis, M. W., Schreier, J. W., Gershenson, J. K., & Pearce, J. M. (2018). Development of a resilient 3-D printer for humanitarian crisis response. Technologies, 6(1), 30. https://doi.org/10.3390/technologies6010030
Schniederjans, D. G., Ozpolat, K., & Chen, Y. (2016). Humanitarian supply chain use of cloud computing. Supply Chain Management: An International Journal, 21(5), 569–588
Sebillo, M., Vitiello, G., Paolino, L., & Ginige, A. (2016). Training emergency responders through augmented reality mobile interfaces. Multimedia Tools and Applications, 75(16), 9609–9622
Shakhatreh, H., Sawalmeh, A. H., Al-Fuqaha, A., Dou, Z., Almaita, E., Khalil, I., … & Guizani, M. (2019). Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges. IEEE Access, 7, 48572–48634
Shavarani, S. M. (2019). Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution. Journal of Humanitarian Logistics and Supply Chain Management, 9(1), 70–81
Sinha, A., Kumar, P., Rana, N. P., Islam, R., & Dwivedi, Y. K. (2019). Impact of internet of things (IoT) in disaster management: A task-technology fit perspective. Annals of Operations Research, 283(1–2), 759–794
Stickley, A., Christensen, S., Duncan, W. D., & Buchbach, J. (2016). Predictive technology and natural hazards: Risk for Australian planning authorities? International Journal of Law in the Built Environment, 8(1), 42–55
Swaminathan, J. M. (2018). Big data analytics for rapid, impactful, sustained, and efficient (RISE) humanitarian operations. Production and Operations Management, 27(9), 1696–1700
Tadokoro, S., Kimura, T., Okugawa, M., Oogane, K., Igarashi, H., Ohtsubo, Y., … & Nakaoka, S. I. (2019). The World robot summit disaster robotics category–achievements of the 2018 preliminary competition. Advanced Robotics, 33(17), 854–875
Tanzi, T. J., & Isnard, J. (2019). Autonomous system for data collection: Location and mapping issues in post-disaster environment. Comptes Rendus Physique, 20(3), 204–217
Tatham, P., Loy, J., & Peretti, U. (2015). Three dimensional printing—A key tool for the humanitarian logistician? Journal of Humanitarian Logistics and Supply Chain Management, 5(2), 188–208. https://doi.org/10.1108/JHLSCM-01-2014-0006
Tatham, P., Ball, C., Wu, Y., & Diplas, P. (2017). Long-endurance remotely piloted aircraft systems (LE-RPAS) support for humanitarian logistic operations. Journal of Humanitarian Logistics and Supply Chain Management, 7(1), 2–25
Usuda, Y., Matsui, T., Deguchi, H., Hori, T., & Suzuki, S. (2019). The shared information platform for disaster management—The research and development regarding technologies for utilization of disaster information. Journal of Disaster Research, 14(2), 279–291
Wang, Y., Wu, Y., Sankar, C. S., & Lu, L. (2015). Leveraging information technology for disaster recovery: A case study of radio frequency identification (RFID) implementation for facility retrieval. Journal of Information Technology Case and Application Research, 17(1), 41–55
Xu, X., Zhang, L., Sotiriadis, S., Asimakopoulou, E., Li, M., & Bessis, N. (2018). CLOTHO: A large-scale Internet of Things-based crowd evacuation planning system for disaster management. IEEE Internet of Things Journal, 5(5), 3559–3568
Yu, M., Yang, C., & Li, Y. (2018). Big data in natural disaster management: A review. Geosciences, 8(5), 165
Zhao, N., Lu, W., Sheng, M., Chen, Y., Tang, J., Yu, F. R., & Wong, K. K. (2019). UAV-assisted emergency networks in disasters. IEEE Wireless Communications, 26(1), 45–51
Zheng, F., Tao, R., Maier, H. R., See, L., Savic, D., Zhang, T., Chen, Q., Assumpção, T. H., Yang, P., Heidari, B., Rieckermann, J., Minsker, B., Bi, W., Cai, X., Solomatine, D., & Popescu, I. (2018). Crowdsourcing methods for data collection in geophysics: State of the art, issues, and future directions. Reviews of Geophysics, 56(4), 698–740