Artikel
Improving Environmental Scanning Systems Using Bayesian Networks
As companies environment is becoming increasingly volatile, scanning systems gain in importance. We propose a hybrid process model for such systems' information gathering and interpretation tasks that combines quantitative information derived from regression analyses and qualitative knowledge from expert interviews. For the latter, we apply Bayesian networks. We derive the need for such a hybrid process model from a literature review. We lay out our model to find a suitable set of business environment indicators to forecast a company's key financials. Deriving lessons learned from a prototype in the industrial sector, we evaluate the utility of our model following the design science research paradigm. We find our model to especially convince in completeness, transparency and transportability when compared with "pure" mathematical models.
- Language
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Englisch
- Bibliographic citation
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Journal: BuR - Business Research ; ISSN: 1866-8658 ; Volume: 6 ; Year: 2013 ; Issue: 2 ; Pages: 196-213 ; Göttingen: VHB - Verband der Hochschullehrer für Betriebswirtschaft, German Academic Association of Business Research
- Classification
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Management
- Subject
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Bayesian networks
balancing opportunities and threats
case study
corporate management
design science research in IS
information systems (IS) design
regression analyses
- Event
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Geistige Schöpfung
- (who)
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Welter, Simon
Mayer, Jörg H.
Quick, Reiner
- Event
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Veröffentlichung
- (who)
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VHB - Verband der Hochschullehrer für Betriebswirtschaft, German Academic Association of Business Research
- (where)
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Göttingen
- (when)
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2013
- DOI
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doi:10.1007/BF03342749
- Handle
- URN
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urn:nbn:de:0009-20-38103
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Welter, Simon
- Mayer, Jörg H.
- Quick, Reiner
- VHB - Verband der Hochschullehrer für Betriebswirtschaft, German Academic Association of Business Research
Time of origin
- 2013
Other Objects (12)
Improving Environmental Scanning Systems Using Bayesian Networks
Advances in Bayesian networks
Inversion of Bayesian networks
Hybrid semiparametric Bayesian networks
Improving adaptive seamless designs through Bayesian optimization
Improving adaptive seamless designs through Bayesian optimization
Improving randomness characterization through Bayesian model selection
Bayesian Networks and Decision Graphs
Bayesian nonparametric models for networks
Locally Bayesian learning in networks
Bayesian learning for neural networks
Bayesian networks and decision graphs
Improving Environmental Scanning Systems Using Bayesian Networks
Advances in Bayesian networks
Inversion of Bayesian networks
Hybrid semiparametric Bayesian networks
Improving adaptive seamless designs through Bayesian optimization
Improving adaptive seamless designs through Bayesian optimization
Improving randomness characterization through Bayesian model selection
Bayesian Networks and Decision Graphs
Bayesian nonparametric models for networks
Locally Bayesian learning in networks
Bayesian learning for neural networks
Bayesian networks and decision graphs
Improving Environmental Scanning Systems Using Bayesian Networks
Advances in Bayesian networks
Inversion of Bayesian networks
Hybrid semiparametric Bayesian networks
Improving adaptive seamless designs through Bayesian optimization
Improving adaptive seamless designs through Bayesian optimization
Improving randomness characterization through Bayesian model selection
Bayesian Networks and Decision Graphs
Bayesian nonparametric models for networks
Locally Bayesian learning in networks
Bayesian learning for neural networks