TY - JOUR
T1 - Information Sharing in and Across Government Agencies
T2 - The Role and Influence of Scientist, Politician, and Bureaucrat Subcultures
AU - Drake, David B.
AU - Steckler, Nicole A.
AU - Koch, Marianne J.
N1 - Funding Information:
Drake David B. Catalyst Communications ddrake@catalst.com Steckler Nicole A. Oregon Health & Science University steckler@ohsu.edu Koch Marianne J. Oregon Health & Science University kochm@ohsu.edu 02 2004 22 1 67 84 2004 This article is based on an exploratory, interdisciplinary study of issues related to information sharing within and across three public agencies. Based on Schein’s work, three subcultures within the public sector (scientist, politician, and bureaucrat) were identified as a framework to examine these issues. Dawes’s three categories of benefits and barriers, associated with interagency information sharing (technical, organizational, and political), were also used in developing the framework. Their work has been extended by identifying three types of differences (view, use, and purpose) among these subcultural relationships to data and information. Four types of systems (social, constituency, technical, and organizational) that influence information-sharing processes within and across agencies also were identified. Two cases are offered to illustrate key points about information sharing across subcultures and some implications for research and practice to enhance abilities within the public sector to appropriately and effectively share information. culture data information sharing digital government collaboration knowledge management hwp-legacy-fpage 67 hwp-legacy-dochead Journal Article Brown, R. W. ( 1986 ). Social psychology(2nd ed.). New York: Free Press. Dawes, S. S. ( 1996 ). Interagency information sharing: Expected benefits, manageable risks. Journal of Policy Analysis and Management , 15 (3), 377 -394. Dawes, S. S. ( 2001 ). Knowledge networking in the public sector(NSF Grant Summary # SES-9979639). Retrieved from www.ctg.albany.edu/projects/kn/knmenu.html De Long, D. W.,& Fahey, L. ( 2000 ). Diagnosing cultural barriers to knowledge management. Academy of Management Executive , 14 (4), 113 -127. Delcambre, L. ( 2000 ). Harvesting information to sustain our forests: Creating an adaptive management portal(NSF Grant Proposal # EIA 9983518). Retrieved from www.cse.ogi.edu/forest/index.php Drake, D. B. ( 2002 ). Knowledge management and communities of practice. A presentation to the Learning Stakeholders Group of Multnomah County, Portland, OR. Fountain, J. E. ( 2001 ). Building the virtual state: Information technology and institutional change. Washington, DC: Brookings Institution Press. Gergen, K. J. ( 1985 ). The social constructionist movement in modern psychology. American Psychologist , 40 , 266 -275. Hansen, M. T.,& von Oetinger, B. ( 2001 ). IntroducingT-shaped managers: Knowledge management’s next generation. Harvard Business Review , 79 (3), 107 -116. Jung, C. G. ( 1970 ). Psychological reflections. Princeton, NJ: Princeton University Press. Landsbergen, D.,& Wolken, G. ( 2001 ). Realizing the promise: Government information systems and the fourth generation of information technology. Public Administration Review , 61 (2), 206 -220. McDermott, R., & O’Dell, C. ( 2001 ). Overcoming cultural barriers to sharing knowledge. Journal of Knowledge Management , 5 (1), 76 -85. Nissen, M. E. ( 2002 ). An extended model of knowledge flow dynamics. Communications of the Association for Information Systems , 8 , 251 -266. Nonaka, I., & Takeuchi, H. ( 1995 ). The knowledge-creating company. New York: Oxford University Press. Schein, E. H. ( 1996, Fall ). Three cultures of management: The key to organizational learning. Sloan Management Review , 38 (1), 9 -21. Shenk, D. ( 1997 ). Data smog: Surviving the information glut.New York: HarperSanFrancisco. Shotter, J. ( 2002 ). Conversational realities: Constructing life through language. London: Sage. Stewart, T. A. ( 1997 ). Intellectual capital: The new wealth of organizations.New York: Doubleday. Teepen, T. ( 2003, August 17 ). Shades ofLysenko: Bush administration distorts science for policy. Oregonian, p. F3 -F3. Tuomi, I. ( 1999 ). Data is more than knowledge: Implications of the reversed hierarchy of knowledge management and organizational memory. Journal of Knowledge Management Systems , 16 (3), 103 -117. Wenger, E. ( 2000 ). Communities of practice: The key to knowledge strategy. In E. L. Lesser, M. A. Fontaine,& J. A. Slusher (Eds.), Knowledge and communities(pp. 3 -20). Boston: Butterworth-Heinemann. Wenger, E., McDermott, R., & Snyder, W. M. ( 2002 ). Cultivating communities of practice: A guide to managing knowledge. Boston: Harvard Business School Press. Williams, H. S. ( 1996 ). Paradigms: Data use vs. data base. Innovating , 16 (2), 9 -24. Zuboff, S. ( 1988 ). In the age of the smart machine. New York: Basic Books.
PY - 2004/3
Y1 - 2004/3
N2 - This article is based on an exploratory, interdisciplinary study of issues related to information sharing within and across three public agencies. Based on Schein's work, three subcultures within the public sector (scientist, politician, and bureaucrat) were identified as a framework to examine these issues. Dawes's three categories of benefits and barriers, associated with interagency information sharing (technical, organizational, and political), were also used in developing the framework. Their work has been extended by identifying three types of differences (view, use, and purpose) among these subcultural relationships to data and information. Four types of systems (social, constituency, technical, and organizational) that influence information-sharing processes within and across agencies also were identified. Two cases are offered to illustrate key points about information sharing across subcultures and some implications for research and practice to enhance abilities within the public sector to appropriately and effectively share information.
AB - This article is based on an exploratory, interdisciplinary study of issues related to information sharing within and across three public agencies. Based on Schein's work, three subcultures within the public sector (scientist, politician, and bureaucrat) were identified as a framework to examine these issues. Dawes's three categories of benefits and barriers, associated with interagency information sharing (technical, organizational, and political), were also used in developing the framework. Their work has been extended by identifying three types of differences (view, use, and purpose) among these subcultural relationships to data and information. Four types of systems (social, constituency, technical, and organizational) that influence information-sharing processes within and across agencies also were identified. Two cases are offered to illustrate key points about information sharing across subcultures and some implications for research and practice to enhance abilities within the public sector to appropriately and effectively share information.
KW - Collaboration
KW - Culture
KW - Data
KW - Digital government
KW - Information sharing
KW - Knowledge management
UR - http://www.scopus.com/inward/record.url?scp=0442322891&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0442322891&partnerID=8YFLogxK
U2 - 10.1177/0894439303259889
DO - 10.1177/0894439303259889
M3 - Article
AN - SCOPUS:0442322891
SN - 0894-4393
VL - 22
SP - 67
EP - 84
JO - Social Science Computer Review
JF - Social Science Computer Review
IS - 1
ER -