Loading...

Data driven decisions in enterprises – implications for business education and cases

by Riza Öztürk (Volume editor) Haldun AKPINAR (Volume editor)
Edited Collection 230 Pages

Summary

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.

Table Of Contents

  • Cover
  • Title
  • Copyright
  • About the editors
  • About the book
  • This eBook can be cited
  • Contents
  • List of Contributors
  • Foreword
  • Part I Data-Driven Decisions in Enterprises: Implications for Business Cases
  • Data-Driven Business at Miele: An Implementation Case in the Manufacturing Industry (Stefan Breit and Yuan Liu)
  • Process Mining as a Tool for Corporate Value Production (Alessandro Spano, Serena Racis and Sonia Cocco)
  • A Cross-Sector Comparative Analysis of a Multidimensional Framework of Value Creation through Big Data (Margareta Teodorescu and Ela Sibel Bayrak Meydanoğlu)
  • Data-Driven Security (Achim Schmidtmann)
  • AI Enabled “Just Walkout Technology” in Shopping Malls: Empirical Evidence to Predict Consumer Purchase Intention with Moderating Role of Shopping Convenience (Suraj Shah, Maurvi Vasavada, Sameer Rohadia and Mahendra Sharma)
  • Business Valuation Methods in Europe: Similarities and Differences (Thomas Walther)
  • Applying Situated Visualization for Supporting Consumer Decision-Making (Ela Sibel Bayrak Meydanoğlu)
  • Resource-Based Theory: Insights in a Managerial Point of View (Olta Nexhipi, Mario Gjoni and Erisa Musabelliu)
  • Data Reports with Dynamic Documents: Using R, Markdown, RStudio, Shiny (Wolfgang Kohn)
  • Analysis of an SME Company Using the Altman Z-Score Model (Arjeta Hallunovi)
  • Part II Data-Driven Decisions in Enterprises: Implications for Business Education
  • A Constructive Learning Model for Digital Skills in Treasury (Andreas Uphaus)
  • Using Research-Based Learning on Barriers to Digital Transformation to Impact Student Engagement during a Pandemic (Sven Packmohr and Henning Brink)
  • Teaching Business Students to Code: Thoughts on Why and How (Felix Zeidler)

←6 | 7→

List of Contributors

Ela Sibel Bayrak Meydanoğlu

Department of Business Administration/Faculty of Economics and Administrative Sciences

Turkish-German University, Istanbul, Turkey

E-Mail: meydanoglu@tau.edu.tr

Stefan Breit

Miele & Cie. KG, Carl-Miele-Straße 29, 33332 Gütersloh, Germany

Henning Brink

Department of Organization and Information Systems

Osnabrück University, Osnabrück, Germany

E-Mail: henning.brink@uni-osnabrueck.de

Sonia Cocco

University of Cagliari, Italy

Mario Gjoni

Aleksander Moisiu Durrës University

mariogjoni@uamd.edu.al

Arjeta Hallunovi

Department of Finance-Accounting

University Aleksander Moisiu Durrës, Durrës, Albania

E-Mail: arjetahallunovi@yahoo.com

Wolfgang Kohn

Fachbereich Wirtschaft

Fachhochschule Bielefeld, Bielefeld, Germany

E-Mail: wolfgang.kohn@fh-bielefeld.de

Yuan Liu

Miele & Cie. KG, Carl-Miele-Straße 29, 33332 Gütersloh, Germany

yuan.liu@miele.com

←7 | 8→

Erisa Musabelliu

Aleksander Moisiu Durrës University, Durrës, Albania

erisamusabelliu@hotmail.it

Olta Nexhipi

Aleksander Moisiu Durrës University, Durrës, Albania

oltanexhipi@uamd.edu.al

Sven Packmohr

DVMT / TS

Malmö University, Malmö, Sweden

E-Mail: sven.packmohr@mau.se

Serena Racis

University of Cagliari, Italy

Sameer Rohadia

Ganpat University, Gujarat, India

sameer.rohadia@ganpatuniversity.ac.in

Achim Schmidtmann

Department of Economics

University of Applied Science, Bielefeld, Germany

E-Mail: achim.schmidtmann@fh-bielefeld.de

Suraj Shah

Ganpat University, Gujarat, India

sms01@ganpatuniversity.ac.in

Mahendra Sharma

Ganpat University, Gujarat, India

prochancellor@ganpatuniversity.ac.in

Alessandro Spano

University of Cagliari, Italy

E-Mail: spano@unica.it

Margareta Teodorescu

Faculty of Business and Management

Koblenz University of Applied Sciences, Koblenz, Germany

E-Mail: teodorescu@hs-koblenz.de

←8 | 9→

Andreas Uphaus

Faculty of Business

University of Applied Sciences, Bielefeld, Germany

E-Mail: andreas.uphaus@fh-bielefeld.de

Maurvi Vasavada

Ganpat University, Gujarat, India

chairperson.cms@ganpatuniversity.ac.in

Thomas Walther

WP Walther

Minden, Germany

E-Mail: walther@wp-walther.de

Felix Zeidler

Department of Business Administration

Bielefeld University of Applied Sciences, Bielefeld, Germany

E-Mail: felix.zeidler@fh-bielefeld.de

←10 | 11→

Foreword

It is a fact that it has been a long time since information and communication technologies crossed the Rubicon River. But an unending effort is still being made to make improvements. There are aphorisms about dice such as Einstein’s famous God does not play dice. The aim is to remove randomness, albeit partially, to try to see the future in the twilight instead of trying to see in the dark. Since Alan Turing’s concept of thinking machines, new research and new concepts have constantly been on the agenda for decades to achieve this goal.

Since ancient times, every organization has had to collect and process information. Sun Tzu, one of the famous generals of China and the author of The Art of War, which is considered the oldest military treatise in the world written on strategy, emphasized the importance of knowing yourself and your opponent about 2,500 years ago:

If you know the enemy and know yourself, you need not fear the result of a hundred battles. If you know yourself but not the enemy, for every victory gained you will also suffer a defeat. If you know neither the enemy nor yourself, you will succumb in every battle.

In his Il Principe (The Prince), Machiavelli drew attention to the need for large-scale intelligence activities for the establishment and maintenance of power in similar ways in army and state administration.

The foundations of competitive intelligence in the territory of today’s Germany are based on the acquisition of intelligence for its own sales force by the Fürst Fugger Bank in the 15th century. In these reports, called Fugger News, intelligence obtained about the known world through agents was sent to those who did business with the bank and to some princes in the region. Another example of intelligence in these lands is the request to regularly report political, economic, and commercial information to central units in the orders sent to top-level officers on foreign duty in the 15th century. More modern German intelligence activities can be seen in the 18th century. In Europe, the Germans managed to seize the international patents and production rights to most formulas and processes, especially with their intelligence activities in the chemical sector, competing against French and British companies.

With a few exceptions, this approach still holds today. In our age, we have more data and more processing power. In our world, where information and communication technologies are reshaping and continuing to shape in every field, it is clear that enterprises that can follow the flow of information, grind the ←11 | 12→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. Every living organism, whether human, animal or plant, or enterprise, has the chance to survive if it has information about its internal and external environment and can use this information correctly to adapt in the best possible way. The only way to realize all this is to gain internal and external intelligence in the most superior way, convert the obtained data into knowledge in the most effective way, and use them in the decision-making process. As Internet access and capacity increase, a business’s environment has become the whole world today. 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 we have seen 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.

These developments in Information and Communication Technologies affect the structure of educational institutions and require the curricula to be constantly rearranged and reorganized in parallel with the developments. Naturally, the same situation applies to faculty members. Faculty members should be aware that every day, some of the knowledge they have gets outdated and needs to be renewed. Educational institutions that cannot keep up with this change will inevitably lose their reputation within a short time. Business informatics and business administration education will inevitably merge, and every business administration education should renew itself completely according to technological developments.

From this point of view, under the title of “Data-Driven Decisions in Enterprises: Implications for Business Education” and “Data-Driven Decisions in Enterprises: Implications for Business Cases,” papers collected from various universities worldwide, especially from Germany, are included in this conference proceeding. I hope that the articles on big data, data analytics, decision-making, and education in the conference proceeding will give the reader a new perspective.

Do not forget! Alea Iacta Est! On this road of no return, both human capabilities and businesses have to change every day.

Haldun Akpinar

April 2022

←14 | 15→
Stefan Breit and Yuan Liu

Data-Driven Business at Miele: An Implementation Case in the Manufacturing Industry

Abstract: Digitalization in an industrial company can only be fruitful if embedded into the overall corporate strategy and organization. At Miele, the overarching strategy is called “Pioneering 4/8” and describes the company’s ambitions toward the year 2030, with digitalization being an integral part. Thus, today at Miele, approximately 1,000 employees are engaged in different areas of strategy execution. “Miele X” in Amsterdam serves as a global digitalization hub and community focused on creating delightful end-to-end customer experience; the “Smart Home” unit is an industrial bridge from product-related digital innovations to digital business models, and the Miele Global IT department provides the necessary process and system backbones. Together they develop strategies to generate and benefit from defined data streams to induce deep business insides and customer-oriented product innovations. For example, several camera-based visual controls jointly determine the baking progress in Miele’s GEN 7000 ovens and thus enable customer assistance for cooking processes. With the customers’ consent, the recorded images from Miele appliances from all over the world are analyzed with Artificial Intelligence (AI) to improve the automated cooking algorithms. Nonetheless, the benefit of using AI exceeds the pure operation of the appliances. Further values can be generated for the consumers with a variety of smart functions around the appliances, especially when these are interconnected. This potential can be tapped by embedding the appliances into an ecosystem which is entered via the Miele App. Apart from product development, AI also bears huge potential in the manufacturing processes of an industrial company. Some of the most promising practices include predictive maintenance, predictive quality, and the optimization of production parameters. However, the yield of using AI is only as good as the people who create, apply, and interpret it. The future of the manufacturing industry depends on a modern academic curriculum to shape future talents with the required capabilities and mindset.

Details

Pages
230
ISBN (PDF)
9783631892923
ISBN (ePUB)
9783631892930
ISBN (Softcover)
9783631878712
DOI
10.3726/b20350
Language
English
Publication date
2023 (January)
Keywords
Augmented Reality Business Transformation Controlling Corporate Reputation Digital Marketing Digital Marurity Models Digital Transformation Finance Human Resource Management Social Sustainability
Published
Berlin, Bern, Bruxelles, New York, Oxford, Warszawa, Wien, 2023. 230 pp., 33 fig. b/w, 22 tables.

Biographical notes

Riza Öztürk (Volume editor) Haldun AKPINAR (Volume editor)

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.

Previous

Title: Data driven decisions in enterprises – implications for business education and cases