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Information intermediaries for emergency preparedness and response: A case study from public health

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Abstract

Information intermediaries play a critical role in information supply chains for emergency preparedness. Yet, their responsibilities have not been adequately examined in the literature. Using a state public health department as an exemplar, we explore the roles and challenges experienced by one intermediary organization as it faced the unique challenges of deploying a public health emergency preparedness system. We further discuss the influence of stakeholder participation and commitment, inter-organizational collaboration, issues related to organizational structure and resources, and the challenges specific to developing and institutionalizing an IT system for emergency preparedness. Based on the public health case, a set of propositions focused on trust, coordination, information sharing and incentive alignment are developed to illustrate the role of information intermediaries.

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Notes

  1. The SEIR model is a classic epidemiological model that captures the spread of an epidemic in a homogeneous population (Anderson and May 1982). This model describes four discrete states of an epidemic: Susceptible, Exposed, Infectious and Recovered. Infectious individuals spread the disease to the (non-immune) susceptible population. Those in the susceptible population to which the disease is transmitted become exposed and after a period of time, the incubation (or latent) period, they become infectious. Individuals remain infectious for a period of time, the infectious period, and then recover (with immunity).

  2. Maricopa county represents 3.8 million of the 6.1 million population in the State of Arizona (2006 Census).

References

  • Anderson, R. M., & May, R. M. (1982). Directly transmitted infectious diseases: control by vaccination. Science, 215(4536), 1053–1060. doi:10.1126/science.7063839.

    Article  Google Scholar 

  • Bailey, J. P., & Bakos, Y. (1997). An exploratory study of the emerging role of information intermediaries. International Journal of Electronic Commerce, 1(3), 7–20.

    Google Scholar 

  • Burton, O., & Ipe, M. (2007). Organizational adaptations in national security: the impact of bioterrorism on surveillance processes and resources. In H. Chen, T. S. Raghu, R. Ramesh, A. Vinze, & D. Zeng (Eds.), Handbooks in information systems: national security(2nd ed.). Boston, MA: Elsevier.

    Google Scholar 

  • Chen, R., Sharman, R., Rao, R., & Upadhyaya, S. (2008). Coordination in emergency response management. Communications of the ACM, 51(5), 66–73. doi:10.1145/1342327.1342340.

    Article  Google Scholar 

  • Choudhury, V. (1997). Strategic choices in the development of interorganizational information systems. Information Systems Research, 8(1), 1–24. doi:10.1287/isre.8.1.1.

    Article  Google Scholar 

  • Choudhury, V., & Sampler, J. L. (1997). Information specificity and environmental scanning: an economic perspective. MIS Quarterly, 21(1), 25–53. doi:10.2307/249741.

    Article  Google Scholar 

  • Christiaanse, E., & Venkatraman, N. (2002). Beyond saber: an empirical test of expertise exploitation in electronic channels. MIS Quarterly, 26(1), 15–38. doi:10.2307/4132339.

    Article  Google Scholar 

  • Ewusi-Mensah, K., & Przasnyski, Z. H. (1991). On information systems project abandonment: an exploratory study of organizational practices. MIS Quarterly, 15(1), 67–88. doi:10.2307/249437.

    Article  Google Scholar 

  • General Accounting Office (2004). Bioterrorism: information technology strategy could strengthen federal agencies’ ability to respond to public health emergencies. Washington, DC: United States Government Printing Office.

    Google Scholar 

  • Grossman, S. J. (1981). An introduction to the theory of rational expectations under asymmetric information. Strategic Management Journal, 25, 1155–1178.

    Google Scholar 

  • Grover, V. (1993). An empirically derived model for the adoption of customer-based interorganizational information systems. Decision Sciences, 24(3), 603–640. doi:10.1111/j.1540-5915.1993.tb01295.x.

    Article  Google Scholar 

  • Grover, V., Lederer, A. L., & Sabherwal, R. (1988). Recognizing the politics of MIS. Information & Management, 14(3), 145–156. doi:10.1016/0378-7206(88)90005-5.

    Article  Google Scholar 

  • Kambil, A., & van Heck, E. (1998). Reengineering the Dutch flower auctions: a framework for analyzing exchange organizations. Information Systems Research, 9(1), 1–19. doi:10.1287/isre.9.1.1.

    Article  Google Scholar 

  • Kanter, R. M. (1994). Collaborative advantage: successful partnerships manage the relationships, not just the deal. Harvard Business Review, 72, 98–108.

    Google Scholar 

  • Janssen, M., & Sol, H. G. (2000). Evaluating the role of intermediaries in the electronic value chain. Internet Research, 10(5), 406. doi:10.1108/10662240010349417.

    Article  Google Scholar 

  • Janssen, M., & Verbraeck, A. (2005). Evaluating the information architecture of an electronic intermediary. Journal of Organizational Computing and Electronic Commerce, 15(1), 35–60. doi:10.1207/s15327744joce1501_3.

    Article  Google Scholar 

  • Lichtenstein, S. P., Slovic, B., & Fischhoff, B. (1978). Judged frequency of lethal events. Journal of Experimental Psychology. Human Learning and Memory, 4(6), 551–578. doi:10.1037/0278-7393.4.6.551.

    Article  Google Scholar 

  • Lyytinen, K., & Hirschheim, R. (1987). Information system failures. Oxford Surveys in Information Technology, 4, 257–309.

    Google Scholar 

  • Malone, T. W., Yates, J., & Benjamin, R. I. (1987). Electronic market and electronic hierarchies. Communications of the ACM, 30(6), 484–497. doi:10.1145/214762.214766.

    Article  Google Scholar 

  • March, J. G., & Simon, H. A. (1958). Organizations. New York, NY: Wiley.

    Google Scholar 

  • Nelson, K. E., Williams, C. M., & Graham, N. M. H. (2005). Infectious disease epidemiology: theory and practice. Boston, MA: Jones and Bartlett.

    Google Scholar 

  • Ramnath, A. M., Paul, R. J., & Macredie, R. (1998). Understanding IOS development. European Conference on IS’98, 4, 179–194.

    Google Scholar 

  • Rasmusen, E. (2001). Games and information: an introduction to game theory. Malden, MA: Blackwell.

    Google Scholar 

  • Resnick, P., Zeckhauser, R., & Avery, C. (1995). Roles for electronic brokers. In G. W. Brock (Ed.), Toward a competitive telecommunications industry: selected papers from the 1994 telecommunications policy research conference (pp. 289–306). Mahwah, NJ: Earlbaum.

    Google Scholar 

  • Smith, K. G., Grimm, C. M., & Gannon, M. J. (1992). Dynamics of competitive strategy. Newbury Park, CA: Sage.

    Google Scholar 

  • Weber, M. (1987). Decision making with incomplete information. European Journal of Operational Research, 28, 44–57. doi:10.1016/0377-2217(87)90168-8.

    Article  Google Scholar 

  • Weill, P., & Olson, M. H. (1989). Managing investments in IT: mini case studies and examples. MIS Quarterly, 13(1), 3–17. doi:10.2307/248694.

    Article  Google Scholar 

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Correspondence to Minu Ipe.

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Ipe, M., Raghu, T.S. & Vinze, A. Information intermediaries for emergency preparedness and response: A case study from public health. Inf Syst Front 12, 67–79 (2010). https://doi.org/10.1007/s10796-009-9162-3

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