Data driven decisions in enterprises - implications for business education and cases
(Sprache: Englisch)
The topic "Big Data" represents a major challenge for companies and there is an enormous need for "data intelligence" in order to use this information specifically for the competitiveness. This volume contains contributions on challenges, hurdles and...
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The topic "Big Data" represents a major challenge for companies and there is an enormous need for "data intelligence" in order to use this information specifically for the competitiveness. This volume contains contributions on challenges, hurdles and examples in intelligent data structuring both in corporate practice and in teaching.
Klappentext zu „Data driven decisions in enterprises - implications for business education and cases “
In our world, where information and communication technologies are reshaping and continuing to shape every field, it is clear that enterprises that can follow the flow of information, grind the information they collect in information mills, and provide intelligence by using their internal and external information, can adapt to changing conditions in a timely and effective manner in proportion to its power. At this point, the aim is to automate the realization of this whole process to the greatest possible extent. In this context, the important developments in the last 20 years have been focusing on business intelligence, big data, deep learning, reinforcement learning, data intelligence, decision intelligence, automated decision-making, and other concepts and the development of application tools.From this point of view, under the title of "Data-driven decisions in enterprises - implications for business education and cases," papers collected from various universities worldwide are included in this conference proceedings.
Inhaltsverzeichnis zu „Data driven decisions in enterprises - implications for business education and cases “
Data driven decisions in enterprises - implications for business cases, Data Driven Business at Miele - An implementation case in the manufacturing industry, Process Mining as a tool for corporate value production, A cross-sector comparative analysis of a multidimensional framework of value creation through big data, Data-driven security, AI enabled "Just walkout technlology" in shopping malls: empirical evidence to predict consumer purchase intention with moderating role of shopping convenience, Business Valuation Methods in Europe - Similarities and Differences. Applying situated visualization for supporting consumer decision making, Resource based theory: insights in a managerial point of view, Data reports with dynamic documents: using R, Makdown, RStudio, Shiny, , Analysis of an SME company using the Altman Z-Score model, A constructive learning model for digital skills in treasury, Using researched-based learning on barriers to digital transformation to impact student engagement during a pandemic, Teaching Business students to code - thoughts on Why and How
Autoren-Porträt
Riza Öztürk is a Professor of Statistical and Mathematical Methods in Economics and Business Administration at Bielefeld University of Applied Sciences and since 2020 Dean of the Faculty of Business.Haldun Akpinar is a Professor of Business Informatics at Marmara University and has been Department Head of the German Department of Business Informatics since 2003. He also lectured on Quantitative Decision Making Systems, Data Mining & Knowledge Discovery and Artificial Intelligence.
Bibliographische Angaben
- 2023, Neuausgabe, 230 Seiten, 55 Abbildungen, Maße: 14,8 x 21 cm, Kartoniert (TB), Englisch
- Herausgegeben: Riza Öztürk, Haldun AKPINAR
- Verlag: Peter Lang Ltd. International Academic Publishers
- ISBN-10: 3631878710
- ISBN-13: 9783631878712
Sprache:
Englisch
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