Abstract
Increasing attention has been devoted in recent years to the firm’s ability to adapt its marketing strategies to a rapidly changing environment. Given that the abundance of news, reports, and announcements found in new electronic environments such as the WWW hampers an extensive manual search, computer-based systems have become important supportive tools for business planning purposes. Several studies investigate the impact of managerial traits on this question, however the potential influence of an inadequate information structure in automatic information-seeking tools is rarely addressed.
In this paper, we examine the effect of the quality of the information structure in automated information-seeking tasks. We use a prototypic system that aims to detect and to evaluate relevant information about financial markets, and systematically contaminate the information structure by index terms referring to an adjacent but different task. Empirical evidence from an experimental evaluation of documents from the Reuters text collection substantiates the relevance of the prior information structure to the automated information search.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Baeza-Yates, R., Ribeiro-Neto B. (1999) Modern Information Retrieval. Addison Wesley, Boston
ClO-Insight (2003) Research: Business Intelligence 2003-Are Your BI Systems Making You Smarter. URL=http://www.cioinsight.com/article2/0,3959,1098923,00.asp
Decker R., Wagner R., Scholz, S. (2004) Environmental Scanning in Marketing Planning-An Internet-Based Approach. Discussion Paper No. 516, University of Bielefeld, March 2004
Large A., Tedd L.A., Hartley R.J. (2001) Information Seeking in the Online Age: Principles and Practice. Saur, München
Lewis D.D. (1997) The Reuters-21578 Text Categorization Test Collection. URL=https://www.research.att.com/lewis/reuters21578.html
Nitze P.S., Parker K.R., Dishman P.L. (2003) Multi-class Interest Profiles: Applications in the Intelligence Process. Marketing Intelligence & Planning, 21, 263–271
Pirolli P., Card S. (1999) Information Foraging. Psychological Review, 106, 643–675
Reger R., Palmer T.B. (1996) Managerial Categorization of Competitors: Using Old Maps to Navigate New Environments. Organizational Science, 7, 22–39
Rouse, W.B. (2002) Need to Know-Information, Knowledge, and Decision Making. IEEE Transactions on Systems, Man, and Cybernetics, 32, 282–292
Stephens D.W., Krebs J.R. (1986) Foraging Theory. Princeton University Press, Princeton
Walters B.A., Jiang J.J., Klein G. (2003) Strategic Information and Strategic Decision Making: the EIS/CEO Interface in Smaller Manufacturing Companies. Information & Management, 40, 487–495
Xu X.M., Kaye G.R., Duan Y. (2003) UK Executives’ Vision on Business Environment for Information Scanning — a Cross Industry Study. Information & Management, 40, 381–389
Yang Y., Liu X. (1999) A Re-examination of Text Categorization Methods. Proceedings of 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM Press, Berkley, 42–49
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Scholz, S.W., Wagner, R. (2005). The Quality of Prior Information Structure in Business Planning - An Experiment in Environmental Scanning. In: Fleuren, H., den Hertog, D., Kort, P. (eds) Operations Research Proceedings 2004. Operations Research Proceedings, vol 2004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27679-3_30
Download citation
DOI: https://doi.org/10.1007/3-540-27679-3_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24274-1
Online ISBN: 978-3-540-27679-1
eBook Packages: Business and EconomicsBusiness and Management (R0)