Research Notes on Digital Business Transformation and Artificial Intelligence
Borut Werber (Volume editor)
Summary
Excerpt
Table Of Contents
- Cover
- Title Page
- Copyright Page
- Table of Contents
- Preface to »Research Notes on Digital Business Transformation and Artificial Intelligence«
- The quest for cellular automata: a case of strategic business IT alignment (Robert Leskovar and Blaž Kavčič)
- 1. Introduction
- 2. Overview of cellular automata development
- 3. Methodology
- 4. Experiments
- 5. Discussion and conclusions
- Acknowledgement
- Bibliography
- Database normalization – can ChatGPT manage it? (Borut Werber and Uroš Rajkovič)
- 1. Introduction
- 2. Introduction to data normalization
- 3. Conclusion
- Acknowledgement
- Bibliography
- What about microchip implants? Digital transformation of the human body (Alenka Baggia, Borut Werber and Anja Žnidaršič)
- 1. Introduction
- 2. Microchip implants
- 3. Research methodology
- 4. Results
- 5. Discussion and conclusions
- Acknowledgement
- Bibliography
- Data maturity assessment of SMEs and definition of measurement scales (Blaž Gašperlin, Andreja Pucihar and Mirjana Kljajić Borštnar)
- 1. Introduction
- 2. Background and theoretical findings
- 3. Methodology
- 4. Data maturity criteria and measurement scales for assessing data maturity of small and medium-sized enterprises
- 5. Discussion
- 6. Conclusion
- Acknowledgments
- Bibliography
- E-invoicing as a driver for digital transformation of Slovene economy (Rok Bojanc, Andreja Pucihar and Gregor Lenart)
- 1. Introduction
- 2. Literature review
- 3. Research method
- 4. Survey results
- 5. Discussion
- 6. Conclusions
- Acknowledgements
- Bibliography
- Exploring consumer online purchase behaviour (Marjeta Marolt)
- 1. Introduction
- 2. Digital consumer
- 3. Methodology
- 4. Findings
- 5. Discussion and conclusion
- Acknowledgments
- Bibliography
- Recent changes in the ISO 27000 series of information security standards (Alenka Brezavšček and Doroteja Vidmar)
- 1. Introduction
- 2. Preliminaries
- 3. Novelties in the latest editions of ISO/IEC 27001 and 27002
- 4. Discussion
- 5. Conclusion
- Bibliography
- Parametrization of the SI Epidemic Model for COVID-19: A Comparative Analysis Across Six Countries (Andrej Škraba and Črtomir Rozman)
- 1. Introduction
- 2. Methodology and data
- 3. Results
- 4. Discussion
- Acknowledgement
- Bibliography
- Facial Recognition System Development (Nejc Čelik and Mirjana Kljajić Borštnar)
- 1. Introduction
- 2. Methodology
- 3. Results
- 4. Discussion
- 5. Conclusion
- Acknowledgement
- Bibliography
Research Notes on Digital Business
Transformation and Artificial Intelligence
Berlin · Bruxelles · Chennai · Lausanne · New York · Oxford
Library of Congress Cataloging-in-Publication Data
A CIP catalog record for this book has been applied for at the Library of Congress.
Library of Congress Control Number: 2025000546
Bibliographic Information published by the Deutsche Nationalbibliothek
The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data is available in the internet at http://dnb.d-nb.de.
Cover Image: © Shutter_M/Shutterstock.com
Cover design by Peter Lang Group AG
Open Access: This work is licensed under a Creative Commons Attribution CC-BY 4.0 license. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
ISBN 978-3-631-92432-7 (Print)
E-ISBN 978-3-631-92491-4 (E-PDF)
E-ISBN 978-3-631-92492-1 (E-PUB)
DOI 10.3726/b22722
© 2025 Peter Lang Group AG, Lausanne (Switzerland)
Published by Peter Lang GmbH, Berlin (Germany)
All rights reserved.
All parts of this publication are protected by copyright.
Any utilization outside the strict limits of the copyright law, without the permission of the publisher, is forbidden and liable to prosecution.
This applies in particular to reproductions, translations, microfilming, and storage and processing in electronic retrieval systems.
This publication has been peer reviewed.
Table of Contents
Preface to »Research Notes on Digital Business Transformation and Artificial Intelligence
The quest for cellular automata: a case of strategic business IT alignment
Database normalization – can ChatGPT manage it?
What about microchip implants? Digital transformation of the human body
Data maturity assessment of SMEs and definition of measurement scales
E-invoicing as a driver for digital transformation of Slovene economy
Exploring consumer online purchase behaviour
Recent changes in the ISO 27000 series of information security standards
Parametrization of the SI Epidemic Model for COVID-19: A Comparative Analysis Across Six Countries
Preface to »Research Notes on Digital Business Transformation and Artificial Intelligence«
The inception of the Research Notes on Digital Business Transformation and Artificial Intelligence began in 2023 with the simple idea of sharing our research findings with the academic community. Most of the authors were members of or close to the Department of Informatics, Faculty of Organisational Sciences at the University of Maribor. The game plan for the research was determined by global trends in the industry and scientific advances and breakthroughs in numerous fields. Digital business transformation and artificial intelligence were the magic words that aroused great interest in the scientific community. For the authors, these buzzwords were the natural extension of their research endeavours. Many of us began in the era of system dynamics, modelling and simulation, decision support systems, expert systems, reliability, security, e-business and e-commerce. Now it seems that they have merged into a complex with many interrelated components, where each one and the whole being important to the industry and the academic community.
This book is dedicated to all those, past and present, who have contributed to the above areas as researchers and mentors. Special recognition is due to our emeritus professors: the late Miroljub Kljajić for his pioneering research in the field of modelling, simulation and system dynamics, Vladislav Rajkovič for his fundamental research in the field of expert systems and decision support systems, and Jože Gričar, the founder of the Bled Conference on Electronic Data Interchange and Electronic Commerce.
We would also like to express our heartfelt thanks to our families and loved ones, whose support has been indispensable throughout this journey.
The authors gratefully acknowledge the financial support of the following institutions:
- Slovenian Research and Innovation Agency ( research core funding no. P5-0018),
- the Ministry of Higher Education, Science and Innovation of the Republic of Slovenia as part of the Next Generation EU National Recovery and Resilience Plan (grant no. 3330-22-3515; NOO no.: C3330-22-953012), and
- the Erasmus+ programme of the European Union (grant no. 2021-1-MK01-KA220-HED-000027646).
Specific acnowledgements are included in related chapters. Furthermore, this book would not have been possible without the kind and active support of Professor Iztok Podbregar, Dean of the Faculty of Organizational Sciences at the University of Maribor, and the reviewers Professor Michal Kvet (University of Žilina) and Professor Olga Cherednichenko (University of Lyon)
In preparing this book, we have tried to strike a balance between technological and organisational aspects and between depth and accessibility. Each chapter offers detailed insights while remaining comprehensible, self-contained and open to further quests. The contributions are the result of the collaboration of many experts, each bringing their unique perspective and expertise. We can only hope that the content will be providing teasers for both experienced researchers and newcomers to the field.
The journey begins with a deep dive into cellular automata and its role in enhancement of strategic allignment of business and IT. Chapter 2 offers practical insights for database designers and developers looking to utilise AI in their workflows. In the next chapter, research provides valuable insights into the societal dynamics shaping the adoption of microchip implants and their impact on digital transformation. The model for assessing data maturity among SMEs, empowering them to leverage data effectively in their operations is presented in Chapter 4. Chapter 5 discusses the legal framework and empirical findings on the opportunities and challenges of e-invoicing adoption. In Chapter 6, surveys and data analyses reveal the most important trends and preferences in online shopping. Chapter 7 provides a comprehensive overview of the revision of selected information security standards and their role in facilitating digital transformation through improved cybersecurity. Chapter 8 brings insight into the role of AI in predictive analytics and in preparing for future epidemic modelling and public health interventions. The final chapter presents new approaches and methods related to the functionality and security of facial recognition systems.
We hope that this book will serve as a valuable resource for many researchers and generate even more rigorous and high-profile ideas.
With sincere appreciation,
Robert Leskovar and Borut Werber
May, 2024
The quest for cellular automata: a case of strategic business IT alignment
Abstract: This research is a follow-up of the survey on the strategic alignment between business and IT (information technology) in Slovenia in 2021. Cellular automata are defined by a 4-tuple: the finite or infinite lattice, the finite set of cell states or values, the finite neighbourhood and the local transition function defined by the transition table/rule. A brief overview of the development in the field of cellular automata is presented. Some notable examples of significant contributions to various aspects of cellular automata are: rule 110, Wolfram’s classification, synchronisation and pattern formation. In recent years, cellular automata have continued to evolve with the advances in technology and computing power. In period 2019–2022, more than 11 thousand scientific articles contributed to several disciplines, mainly in the fields of computer science, engineering, mathematics, physics, environmental science and science technology.The main part of this research presents experiments aimed at: a) developing CA based on the idea of partial differential equations (the focus is on experimenting with different values of gains, internal and external factors) and b) developing CA based on a finite set of rules and an offset caused by random noise (the focus is on experimenting with different rules). The research has shown that experiments with PDE-based CAs strongly depend on the determination of the gain and the function of the internal and external components. The experiment was conducted with five different values of gain, three functions of internal components and three functions of external components. The experiments with rule- based CAs involve the random generation of rules. In a time-limited experiment (60 seconds), 12 to 14 thousand random rules were generated. A subset of these rules had the property of leading the evolution of alignments from arbitrary initial states to arbitrary final states. The implications of the last finding are significant. The inclusion of machine learning algorithms would help to shorten the search time and narrow down the set of likely valid rules that determine the evolution of strategic business IT alignment in company.
Keywords: cellular automata, machine learning, artificial intelligence, strategic business alignment, digital business transformation
1. Introduction
An earlier study by Leskovar and Kavčič (2022) addressed the state of strategic alignment between business and IT (information technology) in Slovenia in 2021. It was inspired by the emerging interest in strategic alignment between business and IT and digital transformation (e.g. Gerow et al., 2014, Global institute for IT Management, 2019, Njanka et al., 2020, Verhoef et al., 2021, Erl and Stoffers, 2022). The translated Luftman questionnaire (2017) covers six areas: Communication, Measurement, IT Management, Partnership, IT Architecture and Skills. The authors received 68 surveys from Slovenian companies (the response rate was 4%). The statistical analysis of the survey includes frequencies, descriptive statistics, correlations and clustering. The calculation of the Cronbach’s α coefficient using SPSS and R tools showed extremely high consistency. The classification of company orientations showed that the optimal number of clusters is two. These two clusters can be briefly described as “mature” and “less mature.” Based on the survey, the authors constructed an algorithm that calculated the scores - the current states of the alignment areas. In addition, the authors proposed three scales to categorise the scores into 5 levels of compliance maturity. These levels were named similarly to the capability maturity levels of the CMMI model used in the software industry. Three modes of the discrete criterion conversion function were defined: a) strict, called KMax (logistic function), b) mild, called KMid (linear function), and c) minimalist, called KMin (shifted linear function). The idea of this article is that the alignment maturity levels could represent the states of a cellular automaton (CA) that can be used to search and predict the evolution of alignment domains for certain entities engaged in basic research (Leskovar and Kavčič, 2022). As a reminder, CA is defined as a 4-tuple:
where:
- Z is the finite or infinite lattice
- S is a finite set of cell states or values
- N is the finite neighbourhood and
- f is the local transition function, defined by the transition table/rule.
For the observed topic, namely the strategic business IT alignment, it would be possible to define a two-dimensional grid with real geographic locations. Unfortunately, the small number of responses returned would make the grid too sparse. Therefore, we decided to construct a one-dimensional CA where the current cell has two neighbouring cells (alignments). The initial finite set of cell states had five named and defined intervals. For this investigation, we have added another one that is close to “zero”. So we have six states. We have also limited the number of neighbours to two - left and right of the current neighbour. Since there are six alignment areas, we can define 120 possible pairs of neighbours of the current cell. Local transition functions usually depend on the previous state and are based on the perspective of partial differential equations. The new state also depends on the change caused by the difference between the abstract left and right neighbours. More often, however, the transition from the current state to the new state is defined as a simple rule in the form:
Details
- Pages
- VI, 308
- Publication Year
- 2025
- ISBN (PDF)
- 9783631924914
- ISBN (ePUB)
- 9783631924921
- ISBN (Softcover)
- 9783631924327
- DOI
- 10.3726/b22722
- Open Access
- CC-BY
- Language
- English
- Publication date
- 2025 (June)
- Keywords
- Digital Buisness Transformation Artificial Intelligence Cellular Automata Database Modelling Microchip Implant Data Maturity Model Online Customer Behaviour Cyber Security Epidemic Modelling Facial Recognition
- Published
- Berlin, Bruxelles, Chennai, Lausanne, New York, Oxford, 2025. vi, 308 pp., 50 fig. col., 28 fig. b/w, 68 tables
- Product Safety
- Peter Lang Group AG
Biographical notes
Robert Leskovar (Volume editor)
Borut Werber (Volume editor)
Prof. Robert Leskovar received his PhD from University of Maribor. His research interest includes simulation and modelling, multiple criteria decision making, digital marketing and artificial intelligence. He published over forty original scientific papers and is author or coauthor of more than twenty chapters in scientific monographs. Borut Werber is Assoc. Prof. PhD of Information Systems at the Faculty of Organizational Sciences, University of Maribor. His research interest includes micro-businesses computer use, RFID microchip implants and deep learning models - DLM. Participated in several research such as MASTIS, IDADOSH and Use of AI for skin cancer recognition – EU founded student work.
