Business Models - Science topic

Publisher:

Emerald Publishing

Book Title:

Data Science for Decision Makers: Leveraging Business Analytics, Intelligence, and AI for Organizational Success

Editors:

· Dr. Miltiadis D. Lytras, The American College of Greece, Greece

· Dr. Lily Popova Zhuhadar, Western Kentucky University, USA

Book Description

As the digital landscape evolves, the integration of Business Analytics (BA), Business Intelligence (BI), and Artificial Intelligence (AI) is revolutionizing Decision-Making processes across industries. Data Science for Decision Makers serves as a comprehensive resource, exploring these fields' convergence to optimize organizational success. With the continuous advancements in AI and data science, this book is both timely and essential for business leaders, managers, and academics looking to harness these technologies for enhanced Decision-Making and strategic growth. This book combines theoretical insights with practical applications, addressing current and future challenges and providing actionable guidance. It aims to bridge the gap between advanced analytical theories and their applications in real-world business scenarios, featuring contributions from global experts and detailed case studies from various industries.

Book Sections and Chapter Topics

Section 1: Foundations of Business Analytics and Intelligence

· The evolution of business analytics and intelligence

· Key concepts and definitions in BA and BI

· Data management and governance

· Analytical methods and tools

· The role of descriptive, predictive, and prescriptive analytics

Section 2: Artificial Intelligence in Business

· Overview of AI technologies in business

· AI for data mining and pattern recognition

· Machine learning algorithms for predictive analytics

· Natural language processing for business intelligence

· AI-driven decision support systems

Section 3: Integrating AI with Business Analytics and Intelligence

· Strategic integration of AI in business systems

· Case studies on AI and BI synergies

· Overcoming challenges in AI adoption

· The impact of AI on business reporting and visualization

· Best practices for AI and BI integration

Section 4: Advanced Analytics Techniques

· Advanced statistical models for business analytics

· Deep learning applications in BI

· Sentiment analysis and consumer behavior

· Realtime analytics and streaming data

· Predictive and prescriptive analytics case studies

Section 5: Ethical, Legal, and Social Implications

· Data privacy and security in AI and BI

· Ethical considerations in data use

· Regulatory compliance and standards

· Social implications of AI in business

· Building trust and transparency in analytics

Section 6: Future Trends and Directions

· The future of AI in business analytics

· Emerging technologies and their potential impact

· Evolving business models driven by AI and analytics

· The role of AI in sustainable business practices

· Preparing for the next wave of digital transformation

Objectives of the Book

· Provide a deep understanding of AI’s role in transforming business analytics and intelligence.

· Present strategies for integrating AI to enhance Decision-Making and operational efficiency.

· Address ethical and regulatory considerations in data analytics.

· Serve as a practical guide for executives, data scientists, and academics in a data-driven economy.

Important Dates

· Chapter Proposal Submission Deadline: 25 November 2024

· Full Chapter Submission Deadline: 31 January 2025

· Revisions Due: 4 April 2025

· Submission to Publisher: 1 May 2025

· Anticipated Publication: Winter 2025

Target Audience

· Business Professionals and Executives: Seeking insights to improve Decision-Making.

· Data Scientists and Business Analysts: Expanding their toolkit with AI and analytics techniques.

· Academic Researchers and Educators: Using it as a resource for teaching and research.

· IT and MIS Professionals: Enhancing their understanding of BI systems and data management.

· Policy Makers and Regulatory Bodies: Understanding the social and regulatory impacts of AI and analytics.

Keywords

· Artificial Intelligence

· Business Analytics

· Business Intelligence

· Data Science

· Decision-Making

Submission Guidelines

We invite chapter proposals that align with the outlined sections and objectives. Proposals should include:

· Title

· Authors and affiliations

· Abstract (200-250 words)

· Keywords

Contact Information

Dr. Miltiadis D. Lytras: miltiadis.lytras@gmail.com

Dr. Lily Popova Zhuhadar: lily.popova.zhuhadar@wku.edu

I'd love to hear from you all, when you see a topic like this what comes to mind?

What are the possible ways of going about the research?

I have decided to carry out this research based on the assumption that the gaming industry tends to be an early(earlier if correct) adopter of innovative technological advancements, in this case, AI tools and processes for either their businesses or their game developments, and even by gamers for marketing of their gameplay(examples such as ideation processes for content creation) and I am interested in how SMEs can learn from these practices to improve their business Processes.

All views will be welcomed and taken into consideration

Dr. Miltiadis D. Lytras, Effat University, Saudi Arabia

Dr. Andreea Claudia Șerban, Bucharest University of Economic Studies, Romania

Dr. Patricia Ordóñez de Pablos, Universidad de Oviedo, Spain

Dr. Afnan Alkhaldi, Arab Open University, Kuwait

Dr. Sawsan Malik, Arab Open University, Kuwait

In an era defined by rapid technological advances and shifting market dynamics, the need for digital transformation is essential for business sustainability. Future-Proof: Innovative Approaches to Management and Digital Transformation in Modern Business offers a comprehensive exploration of contemporary management theories and practices, emphasizing their alignment with digital innovation. This book equips business leaders, managers, and academics with actionable insights to embrace emerging technologies, enhance operational performance, and gain a sustainable competitive edge. It bridges theoretical foundations with practical applications, addressing crucial topics such as operational efficiency, digital engagement strategies, and anticipating future trends.

With case studies and best practices, the book offers readers a deep understanding of how digital transformation can become a cornerstone for resilience and growth.

Foundations of Modern Management

• Overview of Modern Management Theories

• Principles of Effective Leadership in a Digital Era

• Cultural Change and Digital Transformation

• Strategic Planning and Execution in the Digital Age

Enhancing Business Performance with Technology

• Leveraging Big Data and Analytics

• Innovations in Customer Relationship Management

• Digital Marketing and Social Media Integration

• Operational Efficiency Through Automation

Digital Transformation Strategies

• Blueprint for Digital Transformation

• Technology Adoption and Integration Challenges

• Case Studies: Successful Digital Transformations

• Measuring the Impact of Digital Initiatives

Future Trends and Sustainability

• Emerging Technologies and Their Business Implications

• Sustainability and Ethics in Digital Business

• Building Resilient Business Models

• Leadership in a Future Shaped by AI

• Provide a holistic view of digital transformation’s role in enhancing business performance.

• Offer a practical framework combining traditional management with digital innovation.

• Highlight the critical importance of ethics and sustainability in digital transformation.

• Serve as a guide for business leaders and managers to effectively navigate digital transformation.

• Chapter Proposal Submission Deadline: 25 November 2024

• Notification of Proposal Acceptance: 5 December 2024

• Full Chapter Submission Deadline: 31 January 2025

• Revisions Due: 4 April 2025

• Submission to Publisher: 1 May 2025

• Anticipated Publication: Winter 2025

• Business Executives and Managers: Insights on strategic integration of digital technologies.

• Digital Transformation Consultants: Advanced strategies and best practices.

• IT Professionals and Technology Managers: Aligning technology solutions with business goals.

• Academics and Students in Business and Technology: Supporting education on digital transformation.

• Digital Transformation

• Strategic Management

• Business Innovation

• Operational Efficiency

• Change Management

• Agile Management

• Internet of Things (IoT)

• Cybersecurity

• Sustainability

• Artificial Intelligence (AI)

We invite chapter proposals aligned with the sections and objectives outlined in this CFC. Proposals should include:

• Title • Authors and Affiliations • Abstract: 200-250 words • Keywords

Dr. Afnan Alkhaldi: aalkhaldi@aou.edu.kw

Dr. Sawsan Malik: smalik@aou.edu.kw

AI-Driven Knowledge Management: Strategies for the Modern Business Landscape

Important Dates:

Submission of Chapter Proposals: Ocotber 30, 2025 Full Chapter Submission Due: December, 10, 2025 Revisions Due: February 15, 2025 Publication: Q4 2025

Editors:

Professor Meir Russ Professor Emeritus, Cofrin School of Business, University of Wisconsin - Green Bay, USA Research Fellow, Dept. of Information Science, Stellenbosch University, South Africa Email: meir.russ@gmail.com

Professor Miltiadis D. Lytras Visiting Researcher, Effat University, Kingdom of Saudi Arabia Deree College- The American College of Greece, Greece Email: miltiadis.lytras@gmail.com

Scopus: https://www.scopus.com/authid/detail.uri?authorId=55830169000

Google Scholar: https://scholar.google.com/citations?user=oA2FOOAAAAAJ&hl=el

Introduction to the Theme:

The rapid integration of AI into business processes has revolutionized the way organizations manage, process, and leverage knowledge. This book aims to explore the intersection of AI and Knowledge Management (KM), offering insights into how AI-driven solutions can enhance organizational learning, decision-making, and competitive advantage for sustainable business success. The book, “AI-Driven Knowledge Management: Strategies for the Modern Business Landscape,” aims to serve as a comprehensive guide, providing both theoretical and practical insights on how AI technologies are transforming KM practices across industries in a continuously changing market landscape and commercial contexts.

Objectives of the Book:

1. Understanding AI in Knowledge Management: Analyze how AI technologies such as machine learning, natural language processing, and intelligent data analytics can enhance KM processes.

2. Exploring AI-Driven Business Strategies: Examine how AI-driven KM strategies can impact organizational decision-making, innovation, and business performance.

3. Case Studies and Practical Applications: Highlight successful implementations of AI in KM, drawing lessons from real-world examples.

4. Ethical and Managerial Implications: Discuss the ethical, managerial, and societal considerations of integrating AI into KM systems.

Indicative Topics:

We welcome chapters that address, but are not limited to, the following topics:

Section 1: Foundations of Knowledge Management Theory

This section lays the theoretical groundwork for understanding knowledge management, covering the evolution, key theories, and foundational concepts that underpin KM practices in modern enterprises. - Evolution of KM theories - Key concepts in KM - Models of KM - KM life cycles - Theoretical frameworks for KM analysis - The role of organizational culture in KM success - Psychological foundations of knowledge sharing - Ethical considerations in KM

Section 2: Knowledge Management Strategies: Integrating KM into Business Strategy

This section focuses on the strategic integration of KM into business practices, discussing how KM aligns with overall business objectives to enhance organizational effectiveness and decision-making. - Strategic alignment of KM - KM and corporate governance - Role of KM in competitive advantage - Integrating KM into business models - KM for innovation and creativity - KM in change management - KM in crisis management - Measuring the impact of KM on business performance

Section 3: Best Practices and Case Studies: KM at Team, Organizational, and Inter-organizational Levels

Presents practical applications and real-world case studies of KM across different levels of organizations. This section showcases successful implementations and lessons learned from diverse industries. - KM in small teams - Organizational knowledge networks - Cross-organizational KM projects - Sector-specific KM case studies (e.g., healthcare, finance, manufacturing) - Challenges in implementing KM - KM in non-profit organizations - Cross-border KM strategies and challenges

Section 4: Tacit Knowledge Management

Explores the complexities of managing tacit knowledge—knowledge that is unspoken and unwritten, residing in the minds of employees and in the culture of the organization. - Identification of tacit knowledge - Techniques for capturing tacit knowledge - Tools to disseminate tacit knowledge - Tacit knowledge and organizational culture - Case studies on tacit knowledge conversion - Storytelling as a tool for tacit knowledge transfer - Mentorship programs as a means of managing tacit knowledge

Section 5: Foundations of AI in Business

Introduces AI fundamentals relevant to business contexts, explaining how AI technologies are developed and applied to support business functions and enhance operational efficiencies. - AI technologies in business - Developing AI solutions for KM - AI in decision support systems - Machine learning models for KM - Ethical considerations in AI applications - AI and Big Data: Opportunities for KM - Implementing AI projects: From planning to execution

Section 6: AI as a Catalyst for KM Business Performance

Discusses how AI acts as a catalyst for enhancing KM processes, focusing on AI-driven innovations that transform how organizations capture, process, and utilize knowledge for business performance. - AI-driven KM tools - Impact of AI on KM efficiency - AI in knowledge discovery and generation - Integrating AI with existing KM systems - Future trends in AI for KM - AI in knowledge dissemination and collaboration - AI-powered decision-making and analytics for KM

Submission Guidelines:

Interested authors are invited to submit a two-page chapter proposal outlining the chapter's goals, methodology, and expected outcomes. Proposals should be submitted via email to both editors by October 30, 2024. Upon acceptance, full chapters will be due by December 10, 2024. All submissions will undergo a double-blind peer-review process.

Contact Information:

Professor Meir Russ: meir.russ@gmail.com

Professor Miltiadis Lytras: miltiadis.lytras@gmail.com

I've recently seen here high numbers of similar bots (one impersonating scholar with different name, sex and affiliation or in most cases pretending to be some female Asian post-grads and having some weird questions)

Did anyone has figured out what's the rationale? I have seen bots, I have not seen so far any clear scam, so wonder what's the motivation behind.

Keeping up with scientific papers on almost any subject is now a daunting task since the number of papers published is increasing exponentially. For example, within 12 months of Covid-19 being named in February 2020, there were over 300,000 citations in Google Scholar and about 50 of those papers had already been retracted. Today there are over a million citations on the topic. It is just not possible to read them all and Covid is not an isolated example.

In part, the problem stems from a change in publication practice from long established subscription journals run by societies for their members to the professional long-established publishers selling bundled journal titles to libraries - in which publication is slow but free to the author, to a new business model where authors pay thousands of dollars to publish quickly on-line and where peer review is basic or non-existent. Alongside that has been the rise of media managers promoting papers from their institute as novel and important together with a pressure to “publish or perish” to justify grant applications and tenure.

Academic publishing is now a US$12 billion industry with a return on capital of about 40%. This has led to the selling of fake papers, selling co-authorships, manipulation of h-scores, and the rise of the so-called “paper mills” that sell complete papers and authorships online and probably are involved in money laundering. Scientists too are cheating with plagiarism, AI graphics and text.

I want to know the business model of this website named "ResearchGate" and how they make money to run their website business.

As part of a capstone project, we are a group of graduate students researching innovations (technological or otherwise) that have the potential to transform the business model in American journalism. Our challenge is to propose ideas that make it more financially sustainable without sacrificing public trust. Much of our focus has been on advertising as the adjacent business and we also have been exploring different applications of AI, blockchain, etc., but are hoping to gain more insights generated by "out-of-the-box" thinking.

What innovations have you encountered that you think could help support a unique business like news? We will credit you for any new paths you might set us on!

Thank you.

What are the key aspects, benefits, and downsides of System Dynamics if applied to business model innovation for digital transformation?

This inquiry seeks to explore the transformative effects of the Direct-to-Consumer (D2C) business model on the e-commerce industry. It aims to understand how D2C strategies have altered consumer behavior, distribution channels, and performance indicators such as sales growth, customer acquisition costs, and retention rates. The focus is on identifying shifts in market trends, operational challenges, and the overall impact on the competitive landscape of e-commerce.

Hi,

I want to study sustainability in firms, particularly at MESO level. I want to explain these levels from a social science perspective. Which one do you propose?

Micro is within the firm and their direct consumers.

Meso is when firms apply business models and collaborate and value co-created.

Macro is a collection of Meso's at a larger scale region, national etc.

What social science theory I can use to explain these levels and the interaction between them?

Thank you.

I'm currently researching about the possible outcomes of implementing AI in the business model canvas framework. Considering it being such an amazing & simple tool to view & understand the state-of-the-art of a project, I'm worried it might become too complex or lose some of its characteristics/qualities. What do you think?

Which center do you recommend for postdoctoral or PhD research in the field of business sustainability? (Sustainable business model innovation, sustainable human resource management, sustainable leadership, sustainable corporate governance) I am looking for interested professors who have enough time and want to cooperate with them in this field? (with an emphasis on the approach of digital dynamic capabilities)

Thank you

Dr.Mohammad Kargar Shouraki

In the context of the integration of business entities into the currently developing processes of green transformation of the economy, adding the issue of achieving sustainable development goals to the company's mission, implementing green technologies and eco-innovations that contribute to a decrease in the level of emissions in terms of greenhouse gas emissions, exhaust emissions and other pollutants negatively affecting the state of the environment, implementing green investments that reduce the level of energy intensity of buildings and economic processes, etc., the scale of opportunities for improving sustainable business models is also growing. The aforementioned sustainable business models are an important part of green business transformation, conducted in a company or enterprise. On the other hand, the scale of opportunities for improving sustainable business models applied to business entities can be significantly increased by implementing new ICT and Industry 4.0/5.0 information technologies into business, including but not limited to generative artificial intelligence technologies. Recently, the level and generic number of applications of generative artificial intelligence in various business fields of companies and enterprises has been growing rapidly. On the Internet, intelligent applications equipped with generative artificial intelligence technology are appearing in the open, which can be applied to the execution of complex and resource-intensive data and information processing, i.e. such activities that until recently were performed only by humans. In addition, intelligent chatbots and other intelligent applications that enable automation of the execution of complex, multi-faceted, multi-criteria tasks perform the aforementioned tasks in many times less time and with much higher efficiency compared to if the same tasks were to be performed by a human. The ability of tools equipped with generative artificial intelligence to intelligently execute the ordered command is generated by teaching it in the process of deep learning and applying advanced information systems based on artificial neural networks.

In view of the above, I address the following question to the esteemed community of scientists and researchers:

And what is your opinion on this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

Dariusz Prokopowicz

Hello everyone,

I'm conducting research on the influence of business model disclosure on external financing status and earnings persistence among companies listed on the New York Stock Exchange (NYSE). My approach involves agent-based modeling. I'm encountering challenges in defining the game rules governing this simulation and would greatly appreciate guidance or references that could aid in establishing robust and valid game rules specific to this context.

Specifically, I aim to understand how the level or nature of business model disclosure might impact the financing behavior and earnings continuity of companies within the NYSE environment. Could anyone suggest academic papers, methodologies, or frameworks that might assist in formulating appropriate game rules and relevant agents for this agent-based model?

Thank you in advance for any insights or guidance you can provide!

Best regards,

Shahryar Tavangarzadeh

Every single industrial enterprise has its own business model. They are the specific way an enterprise functions. In engineering we have 3d and 2d models which we design and develop and put into manufacturing. What is the knowledge that helps us along the way of first designing a business model of a new enterprise and then guides us into realizing this same business model by establishing a real enterprise with numerous of employees, buildings, machines, know-how to use it all and to realize the product we create according to our idea for a business model?

Let's discuss with more detail what is covered by a business model in an industrial enterprise. Starting by the purpose of us knowing it and diving down into what a TRUE business model should explain about a given enterprise.

Dear colleagues

I am desperately looking for free tools available for creating research business models. I have explored a few options, but most of them come with a hefty price tag. If anyone has any recommendations or suggestions for free tools that can assist in creating research business models, I would greatly appreciate it. Thank you in advance for your assistance!

Some days ago I received a review proposal from PLOS ONE...comments required within 10 days. Is this the standard time they expect for a proper review?

I've a lot of doubts...anyway..here below what I wrote when I decided to decline:

'Well, the paper totally fits in my research field but a review expected within 10 days is not affordable at all, included the fact that I would do it for free while you get money from authors. Your open access business model relies on free work of reviewers. I think it is not fair.'

What is your opinion?

????

Please help me with this

Among the various factors of technological and developmental advantage of individual countries in terms of international comparisons, the possession of advanced technologies, including biotechnology, green energy technologies but also new ICT information technologies and technologies typical of the current fourth technological revolution, Industry 4.0 technologies, stands out. The possession of these technologies determines the possibilities for the development of many industries, including the manufacture of products that are increasingly produced as highly technological products equipped with, for example, microchips.

Microchips are no longer used only in computers, laptops, PDAs, tablets, smartphones, supercomputers built in research centres and further types of highly technological products, but also in white goods, consumer electronics, TV, motor vehicles, including cars, aircraft, military equipment, etc. and, more recently, in systems based on artificial intelligence being built and developed. Microchip production is associated with certain determinants for the development of other economic sectors as well. The production of microchips is a highly energy-intensive process. Therefore, it is also necessary to develop new, renewable and emission-free energy sources to supply electricity to, among other things, microchip production processes.

Currently, there are aspirations and research in many countries to identify opportunities for the development of advanced ICT and/or to create the conditions for the creation of a kind of next "Silicon Valley", including microchip manufacturing companies. As in the case of other industries, so in the case of new ICT information technologies and Industry 4.0, the key factors determining the possibility of building new companies producing advanced microchips include such basic categories of capital as financial capital, possession of research and development centres, science centres generating also the intellectual capital of the staff of employees, possession of modern lines and machine parks produced mainly by domestic industries, generating technological and production capital, with which industrial plants and companies included in technological sectors are equipped. However, this is not all that is required to build a thriving sort of new, next "Silicon Valley" and to be able to be at the forefront of the new ICT information technologies, Prezmysł 4.0, including the production of highly technological microchips. Perhaps among the mentioned key determinants of the development of technology companies are new specific business models, new styles of management, personnel management and motivation to create technological innovations. In addition, perhaps the key factors determining the development of technology companies should also include a highly economically efficient mix of flexible pro-development economic policies, including policies to support the development of science, scientific research, the development of research and development centres, policies to develop innovation; systemically developed highly efficient corruption-free financial support programmes from the state's public finance system; a friendly economic policy for the development of innovative startups; modern ownership models and shareholding structures of technology companies, research institutes and research and development centres, etc.

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this subject?

Please respond,

I invite you all to discuss,

Thank you very much,

The above text is entirely my own work written by me on the basis of my research.

I have not used other sources or automatic text generation systems such as ChatGPT in writing this text.

Copyright by Dariusz Prokopowicz

Best regards,

Dariusz Prokopowicz

Hello!

Following the completion of the national research on sports club business models, I am looking for collaboration opportunities to conduct research on sports club business models in other countries. I have conducted my research on volleyball clubs however I am not limited to this sport only.

If anyone has the possibility of access to conduct surveys - I am very open to future cooperation. I would also be happy to join an erasmus+ exchange cooperation (e.g. STA).

Best wishes!

Adam

I am searching for theoretical support to explain the relationship between digital entrepreneurship and business model innovation of small and medium-sized enterprises.

What are the most promising new business models and financing mechanisms for sustainable agriculture, and how can we scale up successful models to support more farmers and communities?

The OI process revolves around new form of knowledge inflows and outflows that accelerate interior innovation and expand the markets for the external use of innovation. OI within the public sector is an umbrella term that describes processes, outcomes, and business models of a new form of innovation creation.

In a systemic crisis like today, why pay to publish?

Nowadays, knowledge transfer must be a source of survival, not a business model.

How to transfer knowledge with digital tools and media?

What is the relationship between digital entrepreneurship and business model innovation?

SMEs can be research samples?

Today every one talking of Innovation and startups. Every country, via institutional mechanism  have more focused plan for Innovation and startup. I feel it impact the Scientific Research ecosystem. Once the stage off, it will hard to reverse. Please share your suggestion on how innovation impact the pace of scientific research.

I'm currently working in germany for a medium-sized mechanical engineering company on business process modeling with BMPN 2.0 end-to-end. That was a very laborious process. Now there are decisions to be made. How to proceed with a digital transformation. Not only the paperwork is considered here, but also the integration of machines. Sales are still struggling. What experiences have you had with such projects? What suggestions can you give me?

I am searching for theoretical background and variables related to "Digital entrepreneurship: innovative business models for small and medium enterprises (SMEs)". I am looking for support.

I am a student and currently searching for a research topic in the area of Online Platforms, it can be from a marketing perspective, how to market a platform, can from a management perspective, also can from a startup perspective, and the initial approaches on solving chicken and eggs problems.

What are the limitations of the Resource Based View (RBV) Theory of the firm?

Hello,

I have a background in sustainable business model innovation / circular economy but have spent the last 5 years or so working on a project focused on airport noise management. I am looking to get up to speed on what I might have missed and I'm wondering what people think is the essential academic literature on these themes in the past 5 years or so.

Any advice much appreciated!

Thanks,

Graeme

Blockchain is one of the most influential technologies of the last century, a century that has the potential to disrupt business models in a wide range of industries such as finance, supply chain management, logistics, business, value creation and basic tasks such as marketing, accounting. has it

- Digital transformation

- E-government

- New business model

What are the main papers related to the freemium business model (in the perspective of gaming industry, especially MMORPG)?

Hi there, I am submitting my topic for my masters thesis next week and after lots of research I am interested in doing de-internationalization. I feel this is a relevant topic due to COVID-19 and Brexit. I am interested in doing qualitative research with a case study approach (either single/multiple).

The following are my potential research questions.

Benefits/downsides of de-internationalization?

What are the implications of de-internationalization on the firm’s business model?

Which parts of the firm’s business model are affected most, how and why by de-internationalization?

I am however struggling on what industry to investigate and I feel I need to find a scope on how to make it more concise as since it is only a masters thesis. Any suggestions/feedback would be great appreciated. Thanks!

Sustainability transitions and business models for sustainability to offer new insights into how business model innovation may act as a catalyst for system-wide sustainability transitions.

Hello,

i don't quite understand what difference there is between the term business logic and business model. Are they used synonymously? I know of only one source that says a business model is a business logic when the supply, value creation, marketing and revenue are aligned from a theoretical perspective. Accordingly, one speaks of supply logic, value creation logic, marketing logic and revenue logic.

Is this correct?

How does business model of a firm influence its organizational structure? Any pointers are highly appreciated. Thanks a lot.

Does the business model get defined based on the structure? I doubt it, but just checking for any exceptions.

What kind of scientific research dominate in the field of Business Intelligence?

What are the important topics in the field: Business Intelligence?

Business entity management processes are more and more often supported by computerized Business Intelligence platforms that facilitate multi-criteria analysis and reporting.

Probably in the future, the business analyst will be supported by artificial intelligence.

It would be a great advance in the field of automation and objectification of multi-criteria economic analyzes of business entities.

Complex, multi-criteria analyzes regarding the verification of large companies' operations require aggregation and analytical processing of large data sets in Big Data database systems.

However, in what direction will technological progress be realized in this field?

In the future, as part of the progressing computerization of analytical processes, it will be possible to implement artificial intelligence to the processes of analyzing large collections of information collected in Big Data database systems.

Apparently, we are now living in the era of the fourth technological revolution, known as Industry 4.0.

The previous three technological revolutions:

1. The industrial revolution of the eighteenth and nineteenth centuries, determined mainly by the industrial application of the invention of a steam engine.

2. Electricity era of the late nineteenth century and early twentieth century.

3. The IT revolution of the second half of the twentieth century determined by computerization, the widespread use of the Internet and the beginning of the development of robotization.

The current fourth technological revelation, known as Industry 4.0, is motivated by the development of the following factors:

- artificial intelligence,

- cloud computing,

- machine learning,

- Big Data database technologies,

- Internet of Things.

On the basis of the development of these IT instruments and technologies, business analytics of companies such as Business Intelligence and the above-mentioned areas have been dynamically developing in recent years.

In view of the above, I turn to you with the following question: In what direction will the current technological revolution, known as Industry 4.0, develop?

Please, answer, comments. I invite you to the discussion.

Dear Colleagues and Friends from RG

Some of the currently developing aspects and determinants of the applications of data processing technologies in Big Data database systems are described in the following publications:

I invite you to discussion and cooperation.

Best wishes

What kind of scientific research dominate in the field of Ethics and good practices in business?

Please, provide your suggestions for a question, problem or research thesis in the issues: Ethics and good practices in business.

Please reply.

I invite you to the discussion

Best wishes

Edupreneurship is the connection between digital education, teacher training and entrepreneurship. When teachers begin to develop their own educational practice with the mindset and methods of an entrepreneur, new forms of teaching will emerge. These teaching innovations will leave the classroom and lead to new educational products or business models, because entrepreneurs want to sell and disseminate their ideas. The education system is being renewed from within. Unfortunately, there are hardly any studies or concepts on edupreneurship. Can you help? I am looking for suggestions, projects or literature on this topic.

There is little doubt that blockchain technologies will have a great impact on business processes and business models. In the sense of brainstorming and collecting ideas: What are the links between sustainability management and blockchain technologies?

In which areas of economic activity, in which branches of the economy, what offer of products or services is currently offered in your country the most startups or other small companies, enterprises from the SME sector?

Please reply

Best wishes

In my opinion, the scope and possibilities of business cooperation with the world of science are constantly growing, especially in the areas of technical sciences, biotechnology, energy, materials science, information technology, ecology, etc. and in the development of innovations, patents and inventions created in various fields of technology, technology, etc.

Do you agree with me on the above matter?

In the context of the above issues, the following question is valid:

Please reply

I invite you to the discussion

Thank you very much

Best wishes

I am currently investigating the topic of internet business models , in particular internet intermediaries. The details that i cam across so far are a bit outdated and i appreciate any direction to modern literature and also framework and models to shape outcomes in this area.

Regards

Dear Network, I am currently writing my master thesis on the impact of COVID-19 pandemic on business model innovation. Watch the video for a brief summary of what to expect: http://tiny.cc/6zy9uz.

I am reaching out to you as I need your support! I am conducting a survey (language: English, German) for which I need participants. I am looking for people from top management, innovation and R&D managers or people who otherwise have an influence on their company's innovation activities.  The survey will take max 10 min and I am eternally grateful, plus I will send you the results if you like. I hope you will help me to complete my thesis successfully.

Start SURVEY: http://tiny.cc/5zy9uz Thanks a million and best regards, Teresa Reidt

What research data is available/known (e.g. papers, surveys, simulations, data sets, etc.) on modelling a Business Enterprise finances (Microeconomics) based on mapping its Financial Elements (like Asset, Debt, Equity, Income, Expenses, etc.) to the concepts of natural laws of Physics (like Mass, Energy, Force, Momentum etc.)?

From the realm of strategic management - is it still the golden standard to analyze the indust using Porter’s 5 Forces, then using this to select a “generic strategy” I.e: cost-leadership strategy, differentiation strategy, or focus strategy? Or within today’s world of digital business models and blended markets, are there different ways of analyzing and then electing a corporate strategy?

Dear Colleagues,

Which biases / measuring errors do I have to address when doing a survey, where the independent & dependent variable is collected via the same questionnaire from one person?

I already addressed common method bias by integrating a marker variable.

In particular any other biases / measuring errors I can address when setting up the questionnaire (like the remedy for common method bias with the marker variable)

Many thanks in advance!!

What are your thoughts about the CE model and how has the adoption of this business model contributed positively or negatively to homes, firms or countries most especially during the pandemic.

Does the development of data processing technology in Big Data database systems and other technologies developed in the field of technological revolution Industry 4.0 generate new business management concepts?

At present, in the age of the technological revolution known as the 4.0 industry, new technology management or Internet-based companies are emerging.

The technological revolution in recent years, known as Industry 4.0, is motivated by the development of the following factors:

Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence.

Added to this is the development of data processing analytics in Business Intelligence enterprises, the development of life science technologies, biotechnology, eco-innovation, energy, medical intelligence, etc.

On the basis of the development of the new technological solutions mentioned in recent years, the processes of innovatively organized analyzes of large information collections gathered in Big Data database systems dynamically develop.

In the context of this problem, many questions arise:

What other technological improvements, innovative organizational, technical and IT solutions will be developed in the future based on the development of the above-mentioned factors?

What kinds of innovations will be able to be created in the coming years, in the future based on the integration of the above-mentioned main determinants of the development of the current technological revolution known as Industry 4.0?

What kind of new categories of added value may be created in the future if the above-mentioned technological solutions are more involved in the creation of biotechnological, ecological, product and other innovations.

Will new technologies be created in this way, with the help of which it will be possible to generate solutions to the problems of excessive exploitation of Earth resources in the process of civilization development?

Do business management processes play a particularly important role in the context of the effective functioning of business entities in currently developing economies based on knowledge, information and technology?

Is e-management a new concept of managing virtual enterprises or rather managing online technology companies?

Are new management concepts of innovative enterprises and start-ups based mainly on knowledge, information, entrepreneurship and creation of innovations?

Does the development of data processing technology in Big Data database systems and other technologies developed in the field of technological revolution Industry 4.0 generates the emergence of new business management concepts?

Please reply. I invite you to the discussion

Much has been said and written about microgrid, but there is still no clarity on what the business model and the legal framework that make them viable should be. Within this new scenario, what will be the role of distribution companies ?.

Certainly, we are in a technological, political and economic environment that demands innovative solutions. I would like to start a collaborative discussion on this subject, with the aim of sharing the views of researchers from different places in the world.

we are all aware of inefficiencies and waste (time, material, talent) in the Architecture, Engineering and Construction (AEC) sector. We also do know that we need to increase overall productivity and quality while reducing costs. But is it possible in the "status quo", using existing processes, materials and tools?

New technologies have demonstrated technical feasibility in R&D (both in Academia and Industry). Yet, there seems little demand from the market itself. How is that - are we lacking appropriate business model design, technology transfer capabilities or modes of open innovation?

Do we need entrepreneurship for these new technologies in construction?

Unethical practices in business constitute a negative aspect of business processes and often generate additional costs for contractors and consumers. On the other hand, the scale of the gray market in the national economy is often correlated with the level of fiscal burdens and the quality of legal regulations regarding the commencement of business activities.

The high share of shadow economy in various branches of the national economy is also lower income from taxes and fees to the central state budget and to local budgets of local government units.

High fiscal burdens and imprecisely formulated legal regulations regarding running a business activity apart from generating a high level of gray economy in the economy may also be a source of unethical practices used in business between contractors or between producers and suppliers of products and services and consumers.

The large scale of the shadow economy in the national economy and the applied unethical practices in business is one of the key factors in the imperfections of the country's economic system.

According to the above, the current question is: Does the scale of occurrence of unethical practices in business correlate with the size of the shadow economy in national economies?

Please, answer, comments. I invite you to the discussion.

Business model development, government regulations, purchase based incentive policies are motivators of e-buses adoption.

However, the reality of implementation in Europe is different from that of South America. What would be the main influential variables?

What is a business model? What comes to your mind when you come across the word business model. Managers must have a clear understanding of the business model to formulate a strategy. That's why we need to develop a simple explanation of the business model.

I am researching about Product-as-a-service (PaaS) circular business models in the B2B as well as B2C context. Currently, I am still looking for companies that have successfully established the PaaS model in their business. So far, I only came across the well-known industry examples (e.g. Rolls-Royce, Philips, Michelin, Xerox, Ricoh, etc.) which are all from the B2B sector.

Do you know any companies in the B2C sector that have transformed from a linear product-selling business model to a PaaS model or companies (e.g. Start-Ups) that started their business based on the PaaS model? So far I only know some companies in the fashion industry (e.g. MUD Jeans or luxury renting services). In case you know more examples from other industries, please let me know.

In case you have other examples from the B2B sector in mind not mentioned above and which are interesting to investigate, please also reply to this post.

Thank you for your support!

Does technological innovation bring about the improvement of social productivity, and then there is corresponding business model innovation and management practice innovation? For example: due to the emergence of Internet technology, there are Internet enterprises with business models like Amazon and Alibaba. In other words, is technological innovation the key to solving problems and social development ？

By the mid-1990s, in consequence of the Information Revolution (ca. 1980–2000), the role of information and communication technology in organizations had grown to such an extent that one could already discern first-level impacts on organizational configuration, organizational culture, business strategy, management processes, work, and workplace. What might be second-level impacts on organizations (e.g., business models, creativity and innovation, psychological contracts) from the ongoing Digital Revolution (ca. 2000s–)? What implications might there be for the nature of organizing, the quest for the agile organization, leveraging information and communication technology for agility, and agility and leadership?

Multinational organizations as well as SME or any type of business organization for that matter share the same principle which is succeed. However success is not usually the end result due to XXX factors either internal or external or else, they all have left the business opportunity to other competitors or any other reason of such.

Below is a small list i picked from the net about these companies that really got my attention because they all shared greatness in their days and completely got cast away afterwards:

1- Kodak

2- Nokia

3- Xerox

Therefore, i would kindly solicit the help of anyone who thinks he has a close as possible answer (CFI's) that he/she could foresee before the their business ends up in a failure, what could be the possible way, approach or strategy that might help, and how to separate the right CFI from the wrong one.

Thank you in advance for your answers.

Currently, I'm trying to analyze one Chinese firm. For that my need to identify that company business model. This firm is not so much popular. so, right now the problem is my need to identify that company's business model but I don't know how to do it. My problem is:

Please share your idea and recommendations with me.

SaaS product is an end to end marketing analytic system (web-application), providing B2B services. Company I’m working with uses a default monetisation model, which is subscription. In addition, this model is divided into different tariffs depending on the delivered number of features.

The question is:

How to calculate price for different tariffs? What can it depend on?

And how to calculate the value of each feature?