Adaptive information systems and modelling in economics and management science


Type Research Project

Funding Bodies
  • Austrian Science Fund

Duration April 1, 1997 - March 31, 2002

http://www.wu-wien.ac.at/am/
  • Computer Integrated Manufacturing (CIM) AE (Details)
  • Mathematical Methods in Statistics AE (Former organization)
  • Tourism and Leisure Studies AE (Former organization)
  • Produktionsmanagement (Taudes) AE (Details)

Tags

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  • Buchta, Christian (Details)
  • Dolnicar, Sara (Former researcher)
  • Feurstein, Markus (Former researcher)
  • Frühwirth-Schnatter, Sylvia (Details)
  • Hornik, Kurt (Details)
  • Lukanowicz, Martin (Former researcher)
  • Mazanec, Josef (Details)
  • Mild, Andreas (Details)
  • Mitsche, Nicole (Former researcher)
  • Natter, Martin (Former researcher)
  • Pötzelberger, Klaus (Details)
  • Prato, Doris (Former researcher)
  • Strasser, Helmut (Details)
  • Taudes, Alfred (Details) Project Head
  • Zeller, Ralph (Former researcher)
 

Abstract (German)

Der SFB besteht aus 4 Bereichen mit 6 Initiativen, in denen 'Adaptive Methoden' Anwendung finden. Ein erfolgskritisches Erfordernis für die Arbeitsweise ist hier die interdisziplinäre Ausrichtung, insbesondere bei der Zusammenarbeit von Formal- und Substanzwissenschaftern.<P>Die Bereiche 'Computational Intelligence' und 'Statistical Modelling' bringen das methodische Know-how seitens der Mathematik und Statistik ein, stellen theoretische Vergleiche zwischen neuen und konventionellen Verfahren an und fungieren als kalkülsprachliche Grundlage aller wirtschaftlichen Anwendungsbereiche.<P>Die Initiativen 'Market Segmentation and Product Positioning', 'Artificial Factory' und 'Artificial Financial Markets' hingegen stellen die wirtschaftswissenschaftliche Seite und die Anwendungsaspekte dar. Sie prüfen die Nützlichkeit der von den Grundlageninitiativen empfohlenen oder eigens konstruierten Methoden und Modelle anhand realer wirtschaftlicher Probleme aus den Bereichen Marketing, Produktion und Finanzmärkte und stellen empirische Leistungsvergleiche mit klassischen Datenanalyseverfahren an.<P>Biocomputing, Neuronale Netzwerke, Genetische Algorithmen, Fuzzy Systems - alle diese Schlagworte bezeichnen rasant wachsende Forschungsgebiete, die in erster Linie technischen Disziplinen zugeordnet werden. Eine stärkere Anbindung an Management-Aufgaben ist jedoch gefragt. Einen neuen Weg gehen daher die derzeit 50 Wissenschafter der WU Wien, der TU Wien und der Universität Wien. Gemeinsames Nahziel ist die Untersuchung effizienter Einsatzmöglichkeiten von adaptiven Verfahren im Bereich der Datenanalyse bei wirtschaftlichen Anwendungen. Die Arbeiten aller beteiligten Forschungsinstitutionen verfolgen als Fernziel die Simulation betrieblicher und marktwirtschaftlicher Ursachen-Wirkungszusammenhänge, um die Theoriebildung voranzutreiben.


Abstract (English)

An important task of Economics and Management Science is the development of models for explaining economic phenomena, for prediction and for decision support. In the last decade a new paradigm of adaptive models and information systems has emerged. It includes neural networks, learning automata, genetic algorithms, simulated annealing, artificial life, rule learning, fuzzy systems, and adaptive methods of data exploration like projection pursuit and adaptive partitioning algorithms. These approaches have learning capabilities during operation and do not impose rigorous assumptions. Thus they show the potential to complement and improve the existing tool-box for economic modelling and managerial decision support. In view of this potential the Vienna University of Economics and Business Administration has established an integrated research program for adaptive models and information systems in economics and management science. It is expected that research activities will lead to improve<UL>
<LI>the quality of forecasting of economic time series</LI>
<LI>explanation of financial markets and investment decision</LI>
<LI>processes efficiency of organisational structures and planned organisational
change theory of neural pattern recognition and</LI>
<LI>the pattern recognition methodology for large scale applications.</LI></UL>
The primary goals of the SFB are<UL>
<LI>to contribute significantly to Adaptive Modelling research in economics and business administration</LI>
<LI>to channel and to concentrate individual research efforts</LI>
<LI>to ensure dissemination of results</LI>
<LI>to intensify international cooperation</LI>
<LI>to set up an educational program to train a significant share of the personnel required, and finally,</LI>
<LI>to establish a self-sustained organisation within 10 years.</LI></UL>

Partners

  • Humboldt University - Germany
  • Technical University Vienna, Department of Statistics - Austria
  • Technical University Vienna, Department of Econometrics, Operations Research and Systems Theory - Austria
  • University of Vienna, Department of Business Administration - Austria
  • Austrian Research Institute for Artificial Intelligence - Austria

Publications

Forthcoming

2002 Mild, A., Natter, M.. 2002. Collaborative Filtering or Regression Models for Internet Recommendation Systems?. Journal of Targeting, Measurement and Analysis for Marketing (Details)

Book (monograph)

2002 David, H., Doerner, K., Dorffner, G., Fent, T., Feurstein, M., Hartl, R., Mild, A., Natter, M., Reimann, M., Taudes, A.. 2002. Quantitative Models of Learning Organizations. Interdisciplinary Studies in Economics and Management, Springer (Details)

Journal article

2003 Mild, A., Reutterer, T.. 2003. An improved collaborative filtering approach for predicting cross-category purchases based on binary market basket data. Journal of Retailing and Consumer Services, 10, 3, 123-133 (Details)
  Natter, M., Mild, A.. 2003. DELI: An interactive new product development tool for the analysis and evaluation of market research data. Journal of Targeting, Measurement and Analysis for Marketing, 12, 1, 43-52 (10) (Details)
  Mild, A., Natter, M., Taudes, A.. 2003. Der Wiener Strommarkt nach der Liberalisierung: Eine Analyse mit Hilfe eines simultanen Segmentierungs- und Mapping Ansatzes. Transfer: Werbeforschung und Praxis, 3/2003 (Details)
  Buchta, C., Meyer, D., Mild, A., Pfister, A., Taudes, A.. 2003. Technological Efficiency and Organizational Inertia: A Model of the Emergence of Disruption. Computational and Mathematical Organization Theory, 9, 2, 127-146 (Details)
  Mild, A., Reutterer, T.. 2003. Une approche de filtrage collaboratig mise au point pour prédire des achats intercatégories basée sur des paniers de données binaires. Recherche et Applications en Marketing, 18, 4 (Details)
2001 Martin Natter, Markus Feurstein. 2001. Correcting for CBC Model Bias: A Hybrid Scanner Data - Conjoint Model. The International Review of Retail, Distribution and Consumer Research (IRRDCR), 11, 3, July 2001, 1-8 (Details)
  Natter, M., Mild, A., Feurstein, M., Dorffner, G., Taudes, A.. 2001. The Effect of Incentive Schemes and Organizational Arrangements on the New Product Development Process. Management Science, 47, 8, 1029-1045 (Details)

Chapter in edited volume

2005 Buchta, Christian, Meyer, David, Mild, Andreas, Pfister, Alexander, Taudes, Alfred. 2005. Disruptive technologies: the threat and its defense. In Adaptive Information Systems and Modelling in Economics and Management Science, Hrsg. Alfred Taudes, 127-143. Wien: Springer (Details)
2000 Strasser, Helmut. 2000. Reduction of complexity. In: A Nonparametric Approach to Perception-Based Market Segmentation: Foundations., Hrsg. J. Mazanec and H. Strasser, 99-140. Wien: Springer. (Details)
  Strasser, Helmut. 2000. Statistical Analysis of Consumer Perceptions. In A Nonparametric Approach to Perception-Based Market Segmentation: Foundations., Hrsg. J. Mazanec and H. Strasser, 141-186. Wien: Springer. (Details)

Contribution to conference proceedings

2003 Mild, Andreas, Reutterer, Thomas. 2003. Analysis of cross-category and inter-temporal purchase relationships in market basket data. Proceedings of the 32nd EMAC Conference, Glasgow (Details)

Paper presented at an academic conference or symposium

2005 Taudes A., Mild A.. 2005. Integrated Knowledge Creation and Search in New Product Development ¿ an Agent-Based Investigation. AESCS 2005 , The Fourth International Workshop on Agent-based Approaches in Economic and Social Complex Systems, Tokyo (Details)
2004 Buchta Ch., Meyer D., Mild A., Pfister A., Taudes A.. 2004. The Defense of Disruptive Technologies. AESCS 2004 , The Third International Workshop on Agent-based Approaches in Economic and Social Complex Systems, Kyoto (Details)
2003 Buchta Ch., Meyer D., Mild A., Pfister A., Taudes A.. 2003. An Agent-Based Simulation Model of Disruptive Technologies. ISAGA 2003 - 34th Annual Conference of the International Simulation and Gaming Association, 79-88, Kazusa Academic Park, Chiba, Japan (Details)
2000 Feurstein, M., Natter, M., Taudes, A., Mild, A.. 2000. Dynamic Bargaining in Product Development. INFORMS Section on Group Decision and Negotiation (GDN), Glasgow (Details)

Working/discussion paper, preprint

2002 Mild, Andreas, Reutterer, Thomas. 2002. An improved collaborative filtering approach for predicting cross-category purchases based on binary market basket data. Report Series No. 76, Special Research Programme on Adaptive Information Systems and Management in Economics and Management Science. Austrian Science Foundation (FWF) grant SFB#10. (Details)
2001 Mild, A., Natter, M.. 2001. A Critical View on Recommender Systems. Working Paper No. 82, July 2001, Working Paper Series: Adaptive Information Systems and Modelling in Economics and Management Science, Wirtschaftsuniv. Wien (Details)
2000 Buchta, C., Dolnicar, Sara, Köck, R., Skriner, E.. 2000. A Note on Typological Concepts for Complexity Reduction of Binary Survey Data. Working Paper No. 62, January 2000, SFB 'Adaptive Information Systems and Modeling in Economics and Management Science', Vienna (Details)

Classification

  • 5350 Innovation research (Details)
  • 5307 Business and management economics (Details)
  • 5333 Business management (Details)
  • 1122 Artificial intelligence (Details)
  • 1139 Neuronal (neural) networks (Details)

Expertise

  • organizational learning
  • artificial economy
  • financial market
  • market segmentation