Kata Kunci
disaster management
Twitter platform
Cara Mengutip
Abstrak
The rapid progress of information technology systems influences disaster management, for example Twitter is used in Indonesia for disaster management. The purpose of this research is to determine the influence of technology with the variables subjective norm, image, output quality, result demostrability, perceived usefulness, perceived ease of use, use of Twitter, information accessibility, adaptability, resilience, and proactiveness to provide an overview of the disaster management situation. The research was conducted using a questionnaire method and convenience sampling technique on Twitter social media users, obtaining 150 respondents. The research applies the PLS-SEM version 4.0.9.9 SmartPLS method. The research results show that all research variables have a positive effect on disaster management. The research carried out can provide an overview of the disaster management situation by utilizing technological information.
Referensi
Ajzen, I. (1991) “The Theory of Planend Behavior,” Organizational Behaviour and Human Decision Processes. 50(2), pp. 179–211. Available at: https://doi.org/10.1016/0749-5978(91)90020-T.
Akbari, M. et al. (2020) “Acceptance of 5 G technology: Mediation role of Trust and Concentration,” Journal of Engineering and Technology Management, 57, p. 101585.
Al-Jabri et al. (2012) "MOBILE BANKING ADOPTION: APPLICATION OF DIFFUSION OF INNOVATION THEORY," Journal of Electronic Commerce Research; Long Beach, 13(4), pp. 379-391.
Alavi, S. et al. (2014) “Organic Structure and Organisational Learning as The Main Antecedents of Workforce Agility,” International Journal of Production Research, 52(21), pp. 6273–6295.
Cai, Z. et al. (2018) “Improving the Agility of Employees through Enterprise Social Media: The Mediating Role of Psychological Conditions,” International Journal of Information Management, 38(1), pp. 52–63.
Chen, Y., Fay, S. and Wang, Q. (2011) “The Role of Marketing in Social Media: How Online Consumer Reviews Evolve,” Journal of Interactive Marketing, 25(2), pp. 85–94.
Damayanti, V. (2019) “The Effect of Perceived Usefulness and Perceived Ease of Use on Purchase Intention Through Brand Image As an Intervening Variable in Yogyakarta Ust Shopee Users,” Jurnal Ilmiah Ekonomi Dan Bisnis, 16(2), pp. 99–109.
Davenport, T.H. (1993) Process innovation : Reengineering Work through Information Technology, Technology & Engineering. Harvard Business School Press: Boston.
Davis, F.D. (1989) “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” Management Information System Quartely, 13(3), pp. 319–340.
Dönmez-Turan, A. and Kir, M. (2019) “User Anxiety as an External Variable of Technology Acceptance Model: A Meta-Analytic Study,” Procedia Computer Science, 158, pp. 715–724.
Dorasamy, M., Raman, M. and Kaliannan, M. (2013) “Knowledge management systems in support of disasters management: A two decade review,” Technological Forecasting and Social Change, 80(9), pp. 1834–1853.
Gefen, D. and Straub, D. (2000) “The Relative Importance of Perceived Ease of Use in IS Adoption: A Study of E-Commerce Adoption,” Journal of the Association for Information Systems, 1(1), pp. 1–30.
Geldenhuys, M., Łaba, K. and Venter, C.M. (2014) “Meaningful Work, Work Engagement and Organisational Commitment,” SA Journal of Industrial Psychology, 40(1), pp. 1–10.
Goodhue, D.L. and Thompson, R.L. (1995) “Task-Technology Fit and Individual Performance,” Management Information System, 19(2), pp. 213–236. Available at: https://www.jstor.org/stable/249689.
Gurtner, S., Reinhardt, R. and Soyez, K. (2014) “Designing Mobile Business Applications for Different Age Groups,” Technological Forecasting and Social Change, 88, pp. 177–188.
Holden, R.J. and Karsh, B.T. (2010) “The Technology Acceptance Model: Its Past and Its Future in Health Care,” Journal of Biomedical Informatics, 43(1), pp. 159–172.
Huang, Z.J. and Cai, L.A. (2015) “Modeling Consumer-Based Brand Equity for Multinational Hotel Brands - When Hosts Become Guests,” Tourism Management, 46, pp. 431–443.
Irawan, R.L. and Hurriyati, R. (2021) “The Effects of Subjective Norm on The Intention to Use of The Online Shopping Customers in Bandung,” Proceedings of the 5th Global Conference on Business, Management and Entrepreneurship (GCBME 2020), 187, pp. 367–370.
Kamal, S.A., Shafiq, M. and Kakria, P. (2020) “Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM),” Technology in Society, 60.
Kavota, J.K., Kamdjoug, J.R.K. and Wamba, S.F. (2020) “Social media and disaster management: Case of the north and south Kivu regions in the Democratic Republic of the Congo,” International Journal of Information Management, 52, p. 102068.
Kim, J. and Hastak, M. (2018) “Social Network Analysis: Characteristics of Online Social Networks After a Disaster,” International Journal of Information Management, 38(1), pp. 86–96.
Lin, J.S.C. and Chang, H.C. (2011) “The Role of Technology Readiness in Self-Service Technology Acceptance,” Managing Service Quality, 21(4), pp. 424–444.
Martínez-Rojas, M., Pardo-Ferreira, M. del C. and Rubio-Romero, J.C. (2018) “Twitter as a tool for the management and analysis of emergency situations: A systematic literature review,” International Journal of Information Management, 43, pp. 196–208.
Moore, G.C. and Benbasat, I. (1991) “Development of an instrument to measure the perceptions of adopting an information technology innovation,” Information Systems Research, 2(3), pp. 192–222.
Mukkamala, A. and Beck, R. (2018) “The Role of Social Media for Collective Behavior Development in response to Natural Disasters,” in European Conference on Information Systems.
Ngangi, S.C.W. and Santoso, A.J. (2019) “Customer Acceptance Analysis of Customer Relationship Management (CRM) Systems in Automotive Company using Technology Acceptance Model (TAM) 2,” Indonesian Journal of Information Systems, 1(2), pp. 133–146.
Rogers, E.M. (1983) Diffusion of Innovations. third, Achieving Cultural Change in Networked Libraries. third. Edited by N.Y. 10022 The Free Press A Division of Macmillan Publishing Co., Inc. 866 Third Avenue, New York.
Rogers, E.M. (2003) Diffusion of Innovations. The Free Press: New York.
Rogers, E.M. (2010) Diffusion of Innovations. 4th Edition, The Free Press: New York.
Roy, K.C. et al. (2020) “Understanding the efficiency of social media based crisis communication during hurricane Sandy,” International Journal of Information Management, 52, p. 102060.
Ruz, G.A., Henríquez, P.A. and Mascareño, A. (2020) “Sentiment analysis of Twitter data during critical events through Bayesian networks classifiers,” Future Generation Computer Systems, 106, pp. 92–104.
Sarstedt, M., Ringle C.M., and Hair, J.F. (2017) Partial Least Squares Structural Equation Modeling with R, Practical Assessment, Research and Evaluation.
Scherer, R., Siddiq, F. and Tondeur, J. (2019) “The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education,” Computers and Education, 128, pp. 13–35.
Shan, S. et al. (2019) “Disaster management 2.0: A real-time disaster damage assessment model based on mobile social media data—A case study of Weibo (Chinese Twitter),” Safety Science, 115, pp. 393–413.
Simon, T., Goldberg, A. and Adini, B. (2015) “Socializing in Emergencies - A Review of the Use of Social Media in Emergency Situations,” International Journal of Information Management, 35(5), pp. 609–619.
Spence, P.R., Lachlan, K.A. and Rainear, A.M. (2016) “Social Media and Crisis Research: Data Collection and Directions,” Computers in Human Behavior, 54, pp. 667–672.
Strong, D.M., Lee, Y.W. and Wang, R.Y. (1997) “Data quality in context DQ problems,” Communications of the ACM, 40(5), pp. 103–110.
Tajudeen, F.P., Jaafar, N.I. and Ainin, S. (2018) “Understanding the Impact of Social Media Usage among Organizations,” Information and Management, 55(3), pp. 308–321.
Vallacher, R.R., Wegner, D.M. and Somoza, M.P. (1989) “That’s Easy For You to Say: Action Identification and Speech Fluency,” Journal of Personality and Social Psychology, 56(2), pp. 199–208.
Venkatesh, V. and Bala, H. (2008) “Technology Acceptance Model 3 and a Research Agenda on Interventions,” Decision Sciences, 39(2), pp. 273–315.
Wamba, S.F. et al. (2017) “Role of Intrinsic and Extrinsic Factors in User Social Media Acceptance within Workspace: Assessing Unobserved Heterogeneity,” International Journal of Information Management, 37(2), pp. 1–13. Available at: https://doi.org/10.1016/j.ijinfomgt.2016.11.004.
Wang, R.Y. (1996) “Beyond accuracy: What data quality means to data consumers,” Journal of Management Information Systems, 12(4), pp. 5–34.
Wardiono, K., Dimyati, K. and Absori, A. (2021) “Law, Philosophy and Disasters: Earthquake-Handling Case in Yogyakarta, Indonesia,” International Journal of Law and Management, 63(5), pp. 479–497.
Webber, M., Sarris, A. and Bessell, M. (2010) “Organisational Culture and the Use of Work–Life Balance Initiatives: Influence on Work Attitudes and Work–Life Conflict,” The Australian and New Zealand Journal of Organisational Psychology, 3, pp. 54–65.
Wu, M.Y. et al. (2011) “TAM2-Based Study of Website User Behavior-Using Web 2.0 Websites as an Example,” WSEAS Transactions on Business and Economics, 8(4), pp. 133–151.
Zolkepli, I.A. and Kamarulzaman, Y. (2015) “Social Media Adoption: The Role of Media Needs and Innovation Characteristics,” Computers in Human Behavior, 43, pp. 189–209.
Artikel ini berlisensiCreative Commons Attribution-ShareAlike 4.0 International License.
Hak Cipta (c) 2024 Ahmad Bastomi, Anjar Priyono