The stage-driven information seeking process to reduce uncertainty and increase value is systematically validated with real users (n=60) with real work tasks from social sciences and applied sciences domains in a UK and Danish university. A broad set of information sources are applied and core relevance criteria are measured. The research seeks to test the hypothesis that the information seeking process is seen as a dynamic and iterative development to reduce uncertainty through four stages until the problem is solved: (1) problem recognition: kind of problem, (2) problem definition: nature of the problem, (3) problem resolution: finding an answer to the problem, (4) solution statement: answer to the problem or how to deal with it. The hypothesis can be rejected in this case since there is no significant decrease in uncertainty level from stage 1 to 4.
C.C. Kuhlthau , A principle of uncertainty for information seeking , Journal of Documentation, 49(4) (1993) 339-355.
2.
C.C. Kuhlthau , Seeking Meaning: A Process Approach to Library and Information Services, 2nd edition (Libraries Unlimited, Westport, CT, 2003).
3.
T.D. Wilson , Models in information behaviour research, Journal of Documentation, 55(3) (1999) 249-270.
4.
T.D. Wilson , N. Ford, D. Ellis, A. Foster and A. Spink, Information seeking and mediated searching. Part 2: uncertainty and its correlates, Journal of the American Society for Information Science and Technology, 53(9) (2002) 704-715.
5.
P. Borlund, Experimental components for the evaluation of interactive information retrieval systems, Journal of Documentation, 56(1) (2000) 71-90.
6.
P. Ingwersen and K. Järvelin, The Turn: Integration of Information Seeking and Retrieval in Context ( Springer, Berlin, 2005).
7.
A. Spink, Multiple search sessions model of end-user behaviour: an exploratory study , Journal of the American Society for Information Science , 47(8) ( 1996) 603-609.
8.
A. Spink and C. Cole (eds), New Directions in Cognitive Information Retrieval (Springer, Berlin, 2005).
9.
P. Vakkari, Task complexity, problem structure and information actions: integrating studies on information seeking and retrieval, Information Processing & Management, 35 (1999) 819-837.
10.
M.D. White and P. Wang, A qualitative study of citing behavior: contributions, criteria and metalevel documentation concerns, Library Quarterly, 67(2) (1997) 122-154.
11.
E. Zerubavel , Social Mindscapes: an Invitation to Cognitive Sociology (Harvard University Press, Cambridge, MA, 1997).
12.
R. Cummins and D.D. Cummins (eds), Minds, Brains, and Computers: the Foundations of Cognitive Science: an Anthology (Blackwell, Malden, MA, 2000).
13.
S.T. Fiske and S.E. Taylor, Social Cognition: From Brains to Culture (McGraw-Hill, New York, NY, 2008).
14.
J. Bruner, Acts of Meaning (Harvard University Press, Cambridge, MA, 1990).
15.
B. Hjørland , Domain analysis in information science: eleven approaches, Journal of Documentation, 58(4) (2002) 422-462.
16.
A. Foster , A nonlinear model of information-seeking behavior , Journal of the American Society for Information Science and Technology, 55(3) (2004) 228-237.
17.
S. Procter, Organizations and organized systems: from direct control to flexibility. In: S. Ackroyd, R. Batt, P. Thompson and P.S. Tolbert (eds), The Oxford Handbook of Work and Organization (Oxford Handbooks Online, Oxford, 2009) 462-484.
18.
D. Gallie, M. White, Y. Cheng and M. Tomlinson, Restructuring the Employment Relationship (Clarendon Press , Oxford, 1998).
19.
A. Lindbeck and D.J. Snower, Multitask learning and the reorganization of work: from Tayloristic to holistic organization, Journal of Labor Economics, 18(3) (2000) 353-376.
20.
Association of Operations Management, APICS Illustrated Dictionary, 12th edition (Association of Operations ManagementAlexandria, VA, 2008). Available at: www.apics.org
21.
F.W. Taylor, The Principles of Scientific Management (Harper & Brothers , New York, NY, 1911).
22.
N. Slack, S. Chambers, R. Johnston and A. Betts, Operations and Process Management: Principles and Practice for Strategic Impact , 2nd edition (Pearson Education , Harlow, 2009).
23.
B. Crandall, G. Klein and R.R. Hoffman, Working Minds: a Practitioners Guide to Cognitive Task Analysis ( MIT Press, Cambridge, MA, 2006).
24.
K. Byström and P. Hansen, Conceptual framework for tasks in information studies, Journal of the American Society for Information Science and Technology, 56(10) (2005) 1050-1061.
25.
R.S. Taylor , Question-negotiation and information seeking in libraries, College and Research Libraries, 29(3) (1968) 178-194.
26.
N.J. Belkin , R.N. Oddy and H.M. Brooks, ASK for information retrieval: part i: background and theory, Journal of Documentation, 38(2) (1982) 61-71.
27.
N.J. Belkin , R.N. Oddy and H.M. Brooks, ASK for information retrieval: part ii: results of a design study, Journal of Documentation, 38(2) (1982) 145-164.
28.
C.A. Hert, Understanding Information RetrievalInteraction: Theoretical and Practical Implications (Ablex, Greenwich, CT, 1997).
29.
B.J. Jansen, Understanding User-Web Interactions via Web Analytics, Synthesis Lectures on Information Concepts, Retrieval, and Services, 1:1, 1-102 ( Morgan & Claypool Publishers, San Rafael, CA, 2009).
30.
M.H. Bazerman and D.A. Moore, Judgment in Managerial Decision Making, 7th edition (Wiley, Chichester, 2009).
31.
P. Hedström , Dissecting the Social: on the Principles of Analytical Sociology (Cambridge University Press, Cambridge, 2005).
32.
S. Fuchs, The Professional Quest for Truth: a Social Theory of Science and Knowledge (State University of New York Press, Albany, NY, 1992).
33.
J. Kallehauge , Value and Uncertainty in Information Seeking (University of Sheffield, Sheffield , 2008), PhD thesis. Available at: www.jesperkallehauge.eu/phdthesis.pdf (accessed 18 January 2010 ).
C.L. Barry, User-defined relevance criteria: an exploratory study, Journal of the American Society for Information Science, 45(3) (1994) 149-159.
36.
T.K. Park, The nature of relevance in information retrieval: an empirical study, Library Quarterly, 63(3) (1993) 318-351.
37.
L. Schamber, User’s Criteria for Evaluation in Multimedia Information Seeking and Use Situations (Syracuse University, Syracuse, 1991).
38.
P.L. Berger and T. Luckmann, The Social Construction of Reality: a Treatise in the Sociology of Knowledge (Penguin Books, Harmondsworth, 1966).
39.
C.J.W. Choo, The Knowing Organization: How Organizations Use Information to Construct Meaning, Create Knowledge, and Make Decisions, 2nd edition (Oxford University Press, Oxford, 2007).
40.
N. Brunsson, The Consequences of Decision-making (Oxford University Press, Oxford, 2007).
41.
P.J. Carrington, J. Scott and S. Wasserman (eds), Models and Methods in Social Network Analysis (Cambridge University Press, Cambridge, 2005 ).
42.
G. Caldarelli and A. Vespignani (eds), Large Scale Structure and Dynamics of Complex Networks: from Information Technology to Finance and Natural Science (World Scientific, Singapore, 2007).
43.
M. Thelwall , L. Vaughan and L. Björneborn, Webometrics, Annual Review of Information Science and Technology, 39 (2005) 81-135.
44.
R. Diestel, Graph Theory, 3rd edition (Springer, Berlin, 2006).
