67
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Discovering Latent Topics and Trends in Digital Technologies and Disaster Management Research: A Structural Topic Modeling Approach

, PhD, , PhD & , PhD

References

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
  • Aldrich, D. P., & Meyer, M. A. (2015). Social capital and community resilience. The American Behavioral Scientist, 59(2), 254–269. https://doi.org/10.1177/0002764214550299
  • AlHinai, Y. S. (2020). Disaster management digitally transformed: Exploring the impact and key determinants from the UK national disaster management experience. International Journal of Disaster Risk Reduction, 51, 101851. https://doi.org/10.1016/j.ijdrr.2020.101851
  • Bai, X., Zhang, X., Li, K. X., Zhou, Y., & Fai Yuen, K. (2021). Research topics and trends in the maritime transport: A structural topic model. Transport Policy, 102, 11–24. https://doi.org/10.1016/j.tranpol.2020.12.013
  • Baudoin, M.-A., Henly-Shepard, S., Fernando, N., Sitati, A., & Zommers, Z. (2014). Early warning systems and livelihood resilience: Exploring opportunities for community participation.
  • Bers, J. A., Lynn, G. S., & Spurling, C. L. (1997). A venerable tool for a new application: Using scenario analysis for formulating strategies for emerging technologies in emerging markets. Engineering Management Journal, 9(2), 33–40. https://doi.org/10.1080/10429247.1997.11414938
  • Bhushan, S. (2019). Design thinking in hospitality education and research. Worldwide Hospitality & Tourism Themes, 11(4), 449–457. https://doi.org/10.1108/WHATT-04-2019-0022
  • Blei, D. M. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022. https://doi.org/10.1214/07-AOAS114
  • Blei, D. M., & Lafferty, J. D. (2007). A correlated topic model of science. The Annals of Applied Statistics, 1(1), 17–35. https://doi.org/10.1214/07-AOAS114
  • Blum, J. R., Eichhorn, A., Smith, S., Sterle-Contala, M., & Cooperstock, J. R. (2014). Real-time emergency response: Improved management of real-time information during crisis situations. Journal on Multimodal User Interfaces, 8(2), 161–173. https://doi.org/10.1007/s12193-013-0139-7
  • Bouchet-Valat, M. (2020). SnowballC: Snowball stemmers based on the C libstemmer UTF-8 library. R package version 0.5 1.
  • Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. INFORMATION COMMUNICATION & SOCIETY, 15(5), 662–679. https://doi.org/10.1080/1369118X.2012.678878
  • Bruns, A., & Eugene Liang, Y. (2012). Tools and methods for capturing twitter data during natural disasters. First Monday. https://doi.org/10.5210/fm.v17i4.3937
  • Bui, D., Ho, T.-C. H., Pradhan, B., Pham, B.-T., Nhu, V.-H., & Revhaug, I. (2016). GIS-Based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, bagging, and MultiBoost ensemble frameworks. Environmental Earth Sciences, 75(14), 1101. https://doi.org/10.1007/s12665-016-5919-4
  • Burkov, I., Gorgadze, A., & Trabskaia, I. (2023). Satisfaction dimensions influencing consumers’ behavioral intentions through structural topic modeling analysis of restaurant reviews. Consumer Behavior in Tourism and Hospitality, 18(2), 200–214. https://doi.org/10.1108/CBTH-06-2022-0126
  • Chen, X., Zou, D., Cheng, G., & Xie, H. (2020). Detecting latent topics and trends in educational technologies over four decades using structural topic modeling: A retrospective of all volumes of Computers & Education. Computers & Education, 151, 103855. https://doi.org/10.1016/j.compedu.2020.103855
  • Chengalur-Smith, I., Belardo, S., & Pazer, H. (1999). Adopting a disaster-management-based contingency model to the problem of ad hoc forecasting: Toward information technology-based strategies. IEEE Transactions on Engineering Management, 46(2), 210–220. https://doi.org/10.1109/17.759151
  • Cohen, S. E. (2013). Sandy marked a shift for social media use in disasters. Emergency Management. http://www.emergencymgmt.com/disaster/Sandy-Social-Media-Use-in-Disasters.html
  • Comfort, L. K. (2007). Crisis management in hindsight: Cognition, communication, coordination, and control. Public Administration Review, 67(s1), 189–197. https://doi.org/10.1111/j.1540-6210.2007.00827.x
  • Coombs, W. T., & Sherry, J. H. (2002). Helping crisis managers protect reputational assets: Initial tests of the situational crisis communication theory. Management Communication Quarterly, 16(2), 165–186. https://doi.org/10.1177/089331802237233
  • Corsini, L., Dammicco, V., & Moultrie, J. (2021). Frugal innovation in a crisis: The digital fabrication maker response to COVID-19. R&D Management, 51(2), 195–210. https://doi.org/10.1111/radm.12446
  • Crawford, K., & Finn, M. (2015). The limits of crisis data: Analytical and ethical challenges of using social and mobile data to understand disasters. Geo Journal, 80(4), 491–502. https://doi.org/10.1007/s10708-014-9597-z
  • 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
  • Dyer, J. H., & Singh, H. (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23(4), 660–679. https://doi.org/10.2307/259056
  • 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. https://doi.org/10.1109/MPRV.2017.11
  • Fajardo, J. T. B., & Oppus, C. M. (2010). A mobile disaster management system using the android technology. WSEAS Transactions on Communications, 9(6), 343–353.
  • Galbraith, J. R. (1974). Organization design: An information processing view. Interfaces, 4(3), 28–36. https://doi.org/10.1287/inte.4.3.28
  • Gao, H., Barbier, G., & Goolsby, R. (2011). Harnessing the crowdsourcing power of social media for disaster relief. IEEE intelligent systems, 26(3), 10–14. https://doi.org/10.1109/MIS.2011.52
  • Gaur, L., Singh, G., & Agarwal, V. (2021). Leveraging artificial intelligence tools to combat the COVID-19 crisis. In Communications in computer and Information Science, communications in computer and information science (pp. 321–328). Springer Singapore.
  • Geng, S., Hou, H., & Yang, J. (2022). A hybrid decision support model for deploying humanitarian operations to respond to earthquakes. Engineering Management Journal, 34(4), 705–717. https://doi.org/10.1080/10429247.2022.2027206
  • Hall, P. (2007). Early warning systems: Reframing the discussion. The Australian Journal of Emergency Management, 22(2), 32–36.
  • Hillmann, J. (2021). Disciplines of organizational resilience: Contributions, critiques, and future research avenues. Review of Managerial Science, 15(4), 879–936. https://doi.org/10.1007/s11846-020-00384-2
  • Hu, N., Zhang, T., Gao, B., & Bose, I. (2019). What do hotel customers complain about? Text analysis using structural topic model. Tourism Management, 72, 417–426. https://doi.org/10.1016/j.tourman.2019.01.002
  • Imran, M., Castillo, C., Diaz, F., & Vieweg, S. (2015). Processing social media messages in mass emergency: A survey. ACM Computing Surveys, 47(4), 67:1–:67:38. https://doi.org/10.1145/2771588
  • Jaeger, P. T., Shneiderman, B., Fleischmann, K. R., Preece, J., Qu, Y., & Wu, P. F. (2007). Community response grids: E-government, social networks, and effective emergency management. Telecommunications Policy, 31(10–11), 592–604.
  • Jiang, Y., & Stylos, N. (2021). Triggers of consumers’ enhanced digital engagement and the role of digital technologies in transforming the retail ecosystem during COVID-19 pandemic. Technological Forecasting & Social Change, 172, 121029. https://doi.org/10.1016/j.techfore.2021.121029
  • Juvet, T. M., Corbaz-Kurth, S., Roos, P., Benzakour, L., Cereghetti, S., Moullec, G., Suard, J.-C., Vieux, L., Wozniak, H., Pralong, J. A., & Weissbrodt, R. (2021). Adapting to the unexpected: Problematic work situations and resilience strategies in healthcare institutions during the COVID-19 pandemic’s first wave. Safety Science, 139, 105277. https://doi.org/10.1016/j.ssci.2021.105277
  • Kabra, G. (2017). Understanding barriers and enablers to training in humanitarian organizations: A SAP-LAP framework. Development & Learning in Organizations: An International Journal, 31(6), 10–13. https://doi.org/10.1108/DLO-05-2017-0047
  • Kabra, G., Ramesh, A., Akhtar, P., & Kumar Dash, M. (2017). Understanding behavioural intention to use information technology: Insights from humanitarian practitioners. Telematics and Informatics, 34(7), 1250–1261. https://doi.org/10.1016/j.tele.2017.05.010
  • Kabra, G., Ramesh, A., Jain, V., & Akhtar, P. (2023). Barriers to information and digital technology adoption in humanitarian supply chain management: A fuzzy AHP approach. Journal of Enterprise Information Management, 36(2), 505–527. https://doi.org/10.1108/JEIM-10-2021-0456
  • Kabra, G., Srivastava, S. K., & Ghosh, V. (2023). Mapping the field of sustainable procurement: A bibliometric analysis. Benchmarking: An International Journal, 30(10), 4370–4396. https://doi.org/10.1108/BIJ-06-2022-0418
  • Karimiziarani, M., Jafarzadegan, K., Abbaszadeh, P., Shao, W., & Moradkhani, H. (2022). Hazard risk awareness and disaster management: Extracting the information content of Twitter data. Sustainable Cities and Society, 77, 103577. https://doi.org/10.1016/j.scs.2021.103577
  • Karimiziarani, M., & Moradkhani, H. (2023). Social response and disaster management: Insights from Twitter data assimilation on hurricane ian. International Journal of Disaster Risk Reduction, 95, 103865. https://doi.org/10.1016/j.ijdrr.2023.103865
  • Kelman, I., & Michael, H. G. (2014). Early warning systems defined. In A. Singh & Z. Zommers (Eds.), Reducing disaster: Early warning systems for climate change (pp. 89–108). Springer Netherlands.
  • Khan, A., Gupta, S., & Kumar Gupta, S. (2020). Multi-hazard disaster studies: Monitoring, detection, recovery, and management, based on emerging technologies and optimal techniques. International Journal of Disaster Risk Reduction, 47, 101642. https://doi.org/10.1016/j.ijdrr.2020.101642
  • Khan, S., Mishra, J., Ahmed, N., Daisy Onyige, C., Elaine Lin, K., Siew, R., & Han Lim, B. (2022). Risk communication and community engagement during COVID-19. International Journal of Disaster Risk Reduction, 74(102903), 102903. https://doi.org/10.1016/j.ijdrr.2022.102903
  • Kuhn, K. D. (2018). Using structural topic modeling to identify latent topics and trends in aviation incident reports. Transportation Research Part C: Emerging Technologies, 87, 105–122. https://doi.org/10.1016/j.trc.2017.12.018
  • Kumar, V., & Srivastava, A. (2022). Trends in the thematic landscape of corporate social responsibility research: A structural topic modeling approach. Journal of Business Research, 150, 26–37. https://doi.org/10.1016/j.jbusres.2022.05.075
  • Linardos, V., Drakaki, M., Tzionas, P., & Karnavas, Y. (2022). Machine learning in disaster management: Recent developments in methods and applications. Machine Learning and Knowledge Extraction, 4(2), 446–473. https://doi.org/10.3390/make4020020
  • Lindstedt, N. C. (2019). Structural topic modeling for social scientists: A brief case study with social movement studies literature, 2005–2017. Social Currents, 6(4), 307–318. https://doi.org/10.1177/2329496519846505
  • Linnenluecke, M. K., Marrone, M., & Singh, A. K. (2019). Conducting systematic literature reviews and bibliometric analyses. Australian Journal of Management, 45(2), 175–194.
  • Lyu, J., Zhou, S., Liu, J., & Jiang, B. (2023). Intelligent-technology-empowered active emergency command strategy for urban hazardous chemical disaster management. Sustainability, 15(19), 14369. https://doi.org/10.3390/su151914369
  • McCarthy, I. P., Collard, M., & Johnson, M. (2017). Adaptive organizational resilience: An evolutionary perspective. Current Opinion in Environmental Sustainability, 28, 33–40. https://doi.org/10.1016/j.cosust.2017.07.005
  • Mckinsey. (2021). China consumer report 2021 understanding Chinese consumers: Growth engine of the world.
  • Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group*, T. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of internal medicine, 151(4), 264-269.
  • Neelam, S., & Kumar Sood, S. (2021). A scientometric review of global research on smart disaster management. IEEE Transactions on Engineering Management, 68(1), 317–329. https://doi.org/10.1109/TEM.2020.2972288
  • Oktari, R. S., Munadi, K., Idroes, R., & Sofyan, H. (2020). Knowledge management practices in disaster management: Systematic review. International Journal of Disaster Risk Reduction, 51, 101881. https://doi.org/10.1016/j.ijdrr.2020.101881
  • Park, E. O., Chae, B. K., & Kwon, J. (2018). The structural topic model for online review analysis: Comparison between green and non-green restaurants. Journal of Hospitality & Tourism Technology, 11(1), 1–17. https://doi.org/10.1108/JHTT-08-2017-0075
  • Pierri, N., & Timmer, Y. (2022). The importance of technology in banking during a crisis. Finance and Economics Discussion Series 2022-02, 2022(20), 1–47. https://doi.org/10.17016/feds.2022.020
  • Poussin, J. K., Wouter Botzen, W. J., & Aerts, J. C. J. H. (2014). Factors of influence on flood damage mitigation behaviour by households. Environmental Science & Policy, 40, 69–77. https://doi.org/10.1016/j.envsci.2014.01.013
  • Pribadi, K. S., Abduh, M., Wirahadikusumah, R. D., Hanifa, N. R., Irsyam, M., Kusumaningrum, P., & Puri, E. (2021). Learning from past earthquake disasters: The need for knowledge management system to enhance infrastructure resilience in Indonesia. International Journal of Disaster Risk Reduction, 64, 102424. https://doi.org/10.1016/j.ijdrr.2021.102424
  • Ravenda, D., Valencia-Silva, M. M., Argiles-Bosch, J. M., & García-Blandón, J. (2022). The strategic usage of Facebook by local governments: A structural topic modelling analysis. Information & Management, 59(8), 103704. https://doi.org/10.1016/j.im.2022.103704
  • Rebeeh, Y., Pokharel, S., Abdella, G. M., & Hammuda, A. (2019). A framework based on location hazard index for optimizing operational performance of emergency response strategies: The case of petrochemical industrial cities. Safety Science, 117, 33–42. https://doi.org/10.1016/j.ssci.2019.03.020
  • Reddy, M. C., Paul, S. A., Abraham, J., McNeese, M., DeFlitch, C., & Yen, J. (2009). Challenges to effective crisis management: Using information and communication technologies to coordinate emergency medical services and emergency department teams. International Journal of Medical Informatics, 78(4), 259–269. https://doi.org/10.1016/j.ijmedinf.2008.08.003
  • Roberts, M. E., Stewart, B. M., & Airoldi, E. M. (2016). A model of text for experimentation in the social sciences. Journal of the American Statistical Association, 111(515), 988–1003. https://doi.org/10.1080/01621459.2016.1141684
  • Roberts, M. E., Stewart, B. M., Tingley, D., Lucas, C., Leder‐Luis, J., Kushner Gadarian, S., Albertson, B., & Rand, D. G. (2014). Structural topic models for open‐ended survey responses. American Journal of Political Science, 58(4), 1064–1082. https://doi.org/10.1111/ajps.12103
  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
  • Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude Change1. The Journal of Psychology, 91(1), 93–114. https://doi.org/10.1080/00223980.1975.9915803
  • Rogers, R. W. (1983). Cognitive and physiological processes in fear appeals and attitude change: A revised theory of protection motivation. In J. T. Cacioppo & R. E. Petty (Eds.), Social Psychology: A Source Book (pp. 153–176). Guilford Press.
  • Roshan, M., Warren, M., & Carr, R. (2016). Understanding the use of social media by organisations for crisis communication. Computers in Human Behavior, 63, 350–361. https://doi.org/10.1016/j.chb.2016.05.016
  • Saroj, A., & Pal, S. (2020). Use of social media in crisis management: A survey. International Journal of Disaster Risk Reduction, 48, 101584. https://doi.org/10.1016/j.ijdrr.2020.101584
  • Sawalha, I. H. (2015). Managing adversity: Understanding some dimensions of organizational resilience”. Management Research Review, 38(4), 346–366. https://doi.org/10.1108/MRR-01-2014-0010
  • Sawalha, I. H. (2023). Evolution of Modern Disaster Management. Foresight, 25(6), 808–820. https://doi.org/10.1108/FS-08-2022-0093
  • Shi, L., Fu, S., Han, J., Liu, T., Zhan, S., & Wang, C. (2023). The mine emergency management capability based on EWM-CNN comprehensive evaluation. Engineering Management Journal, 1–11. https://doi.org/10.1080/10429247.2023.2264162
  • Somers, S. (2009). Measuring resilience potential: An adaptive strategy for organizational crisis planning. Journal of Contingencies and Crisis Management, 17(1), 12–23. https://doi.org/10.1111/j.1468-5973.2009.00558.x
  • Subba, R., & Bui, T. (2017). Online convergence behavior, social media communications and crisis response: An empirical study of the 2015 nepal earthquake police twitter project.
  • Sun, W., Bocchini, P., & Davison, B. D. (2020a). Applications of artificial intelligence for disaster management. Natural Hazards, 103(3), 2631–2689. https://doi.org/10.1007/s11069-020-04124-3
  • Sun, W., Bocchini, P., & Davison, B. D. (2020b). Model for estimating the impact of interdependencies on system recovery. Journal of Infrastructure Systems, 26(3), 04020031. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000569
  • Sutton, J. N. (2010). Twittering tennessee: Distributed networks and collaboration following a technological disaster. ISCRAM.
  • Syed, S., & Spruit, M. (2017). Full-text or abstract? Examining topic coherence scores using latent Dirichlet Allocation. In 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA) (pp. 165–174). Laguna Hills, CA.
  • Tamakloe, R., & Park, D. (2023). Discovering latent topics and trends in autonomous vehicle-related research: A structural topic modelling approach. Transport Policy, 139, 1–20. https://doi.org/10.1016/j.tranpol.2023.06.001
  • Thakral, P., Ranjan Srivastava, P., Sunand Dash, S., Jasimuddin, S. M., & Zhang, Z. (. (2023). Trends in the thematic landscape of HR analytics research: A structural topic modeling approach. Management Decision, 61(12), 3665–3690. https://doi.org/10.1108/MD-01-2023-0080
  • Tonidandel, S., Summerville, K. M., Gentry, W. A., & Young, S. F. (2022). Using structural topic modeling to gain insight into challenges faced by leaders. The Leadership Quarterly, 33(5), 101576. https://doi.org/10.1016/j.leaqua.2021.101576
  • Tornatzky, L. G., Fleischer, M., & Chakrabarti, A. K. (1990). Processes of technological innovation. Lexington books.
  • Vahid, B., Piadeh, F., Chen, A. S., & Behzadian, K. (2024). Stakeholder analysis in the application of cutting-edge digital visualisation technologies for urban flood risk management: A critical review. Expert Systems with Applications, 236, 121426. https://doi.org/10.1016/j.eswa.2023.121426
  • Vermiglio, C., Noto, G., Pedro Rodríguez Bolívar, M., & Zarone, V. (2022). Disaster management and emerging technologies: A performance-based perspective. Meditari Accountancy Research, 30(4), 1093–1117. https://doi.org/10.1108/MEDAR-02-2021-1206
  • Wang, Q., Li, W., Yu, Z., Abbasi, Q., Imran, M., Ansari, S., Sambo, Y., Wu, L., Li, Q., & Zhu, T. (2023). An overview of emergency communication networks. Remote Sensing, 15(6), 1595. https://doi.org/10.3390/rs15061595
  • Weichselgartner, J., & Pigeon, P. (2015). The role of knowledge in disaster risk reduction. International Journal of Disaster Risk Science, 6, 107–116.
  • Wut, T. M., Xu, J. B., & Wong, S.-M. (2021). Crisis management research (1985–2020) in the hospitality and tourism industry: A review and research agenda. Tourism Management, 85, 104307. https://doi.org/10.1016/j.tourman.2021.104307

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.