Discover the world's scientific knowledge

"The Huns(maybe white people) attack on China may represent historical white supremacy." https://www.researchgate.net/publication/372371182_How_White_Supremacy_Affects_East_Asians

Please apply as Research Associate (Doctorate or PostDoc) in Circular Economy and Sustainability Innovation at Institute for Integrated Quality Design (IQD) of Johannes Kepler Universität Linz, Austria. You need to have (or be close to) a Master's degree to apply for the entry level and a Doctorate degree for the PostDoc-level. Contribute to our pioneering research and teaching on collaboration, product/business model innovation, design strategies, and digitalization in the context of circularity and sustainability.

☑ Full or part time with high flexibility

☑ Low teaching load (2 hours/semester)

☑ Dynamic team of senior and junior scholars

☑ Unique scientific and industry networks

☑ High performance publication culture

☑ German language skills of advantage

Details on our website: https://www.jku.at/en/institute-for-integrated-quality-design/news/detail/news/vacancy-at-the-iqd-3/

Feel free to contact me for details. Looking forward to getting in touch.

Julia Schmitt (julia.schmitt@jku.at)

Nowadays there are plenty of core technologies for TC (Text Classification). Among all the ML learning approaches, which one would you suggest for training models for a new language and a vertical domain (alike Sports, Politics or Economy)?

What are some obvious examples of greenwashing in advertising campaigns of companies that present themselves as green companies pursuing sustainable development goals, developing green, pro-environmental, pro-climate projects, making green investments, e.g. in renewable and emission-free energy sources, which is not true?

In recent years, there have been more and more examples of the use of greenwashing in advertising campaigns, which consists in misleading the public, potential customers, who are presented with certain offers of companies as green, although they are not. More and more advertising campaigns, public relations activities, etc. carried out by more and more advertising companies and business entities presenting their product offers, services, company brands, use greenwashing. Greenwashing is also referred to in everyday language as "eco-costume", "green untruth" or "green lie", a phenomenon consisting in creating the impression among customers looking for goods produced in accordance with the principles of ecology and environmental protection that the product or the company producing it is in harmony with nature and ecology. For example, recently, in the country in which I operate, a number of advertising spots have appeared in various media, which portray certain large energy sector companies that are state-owned companies as green companies acting in accordance with the principles of sustainable development and developing green investments in the development of renewable and emission-free energy sources, but unfortunately not in accordance with the facts, and are an example of greenwashing. The largest state-owned companies in the energy and petrochemical sector engage in greenwashing because they are portrayed in advertising campaigns as developing renewable energy sources, including the construction of onshore and offshore wind farms, while the development of onshore wind energy has been blocked by the Polish government for the last seven years, the construction of wind farms in the Baltic Sea by Polish companies is only just being planned, and the structure of energy sources in the energy sector is still such that three quarters of Poland's energy is generated by burning coal and lignite.

In view of the above, I would like to address the following questions 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,

Best wishes,

Dariusz Prokopowicz

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

This article offers an approach to the general structure of the rhetoric in economy. In our case we adopted a perspective to study a particular aspect of the rhetoric that comes from the context of a particular controversy: the controversy on the advantages of the free commerce between Daly and Bhagwati. It is sustained that the positions in economy present with relative frequency interest conflicts that are revealed in the dialectic one of the arguments. A proponent in open defense of the free commerce is not released of presumptions reflected in the field of the rhetoric. Reason why to include the language dimensions of the argumentation in economy has advantages for the field of the explanation and the epistemology in the social sciences.

For example, "Appraise the impacts of different businesses on different levels (international, national, regional, local) of the economy using appropriate data and statistics" and "Evaluate the use of intrapreneurship and the benefits it can bring to organisations".

What are steps I have to do?

Does "evaluate" more details than "appraise"?. And what if I change these questions to "Evaluate the impacts of different businesses on different levels (international, national, regional, local) of the economy using appropriate data and statistics" and "Appraise the use of intrapreneurship and the benefits it can bring to organisations".

I just want to make sure which step I should do so that I won't get them wrong. These words really confused me as English is not my first language and I also search for the definition in ResearchGate but I still couldn't get it.

Thank you so much for your explanation.

The transdisciplinary nature of visual communication design makes it challenging to depict the complete process. There are a lot of factors involve that shapes the final design output. During my research, I went through figures, charts, flow sheets and diagrams that encompass a complete design process from ideation to final production. Not only that what impact does a design creates on society and vice versa? There are people who play major roles in design generation; client, consumer, designer and producer. Then there are factors like language, culture, economy, society, etc. I wish to have a more comprehensive visualization of the VCD process if you as a reader know such resources I would love to see.

Best Day!

If Aliens do exist : Collaborative Research With Alien Intelligence

Human entity

Alien entity

Machine entity

Human life (Natural life)

Alien life (Natural life)

Machine life (Artificial life)

Human language

Alien language

Machine language

Human Intelligence

Alien Intelligence

Machine Intelligence

Human Intelligence versus Alien Intelligence versus Machine Intelligence

Human-Alien Interaction

Machine-Alien Interaction

Human-Machine Interaction

Coordination and collaboration of Humans, Aliens and Machines,

Huaman Factors,

Alien Factors,

Emotional Intelligence for Humans, Aliens and Machines,

Alien Art, Philosophy, Culture, Science, Engineering, Technology,Industry, Economy and Civilization,

Alien Mathematics

Alien Computer and Software Industry

Alien Military Industry

Human Cognitive Phsycology

Alien Cognitive Phsycology

Machine Cognitive Phsycology

Human Social Phsycology

Alien Social Phsycology

Machine Social Phsycology

Human Social Intelligence

Alien Social Intelligence

Machine Social Intelligence

Peace and war between Humans, Aliens and Machines

Hybrids of Humans, Aliens and Machines

God for Humans, Aliens and Machines

Ethical issues

What else?Beyond Aliens . . .