The aim of this article is to compare two artificial intelligence-based tools developed within the two most prominent scientific databases: Scopus AI and Web of Science Research Assistant. This comparison provides valuable feedback for researchers and authors seeking support in their academic work involving the exploration of extensive bibliographic databases. The growing popularity of AI tools supporting scholarly research offers significant facilitation for researchers, yet it simultaneously raises ethical questions and prompts discussions about the autonomy and integrity of academic work. The method applied in this study is a comparative analysis of the Scopus AI and Web of Science Research Assistant tools. The research is conducted in successive stages. The first stage involves a comparison of the results generated by both tools in response to the same research query: " Sustainable Strategic Management in Enterprises ". The second stage entails an examination of the technical capabilities and limitations of each tool, identifying the methodological steps and components where they complement or contradict each other. The insights derived from the observed differences and similarities serve as the basis for recommendations concerning the use and further improvement of these tools from a researcher’s perspective. The use of such AI-based support tools necessitates greater attentiveness on the part of authors, along with careful validation of the results. These tools should remain auxiliary aids in the process of academic publishing.

This article explores the opportunities and challenges associated with the creation of green jobs in the Information and Communication Technologies (ICT) sector. Drawing upon a targeted literature review of publications indexed in the Scopus and Web of Science databases, the study identifies key directions for green job creation, including roles in the design and development, implementation, and monitoring of green ICT technologies. It also maps out systemic barriers such as definitional ambiguity, insufficient integration of sustainability into education and training, skills gaps, and high technological costs. A novel contribution of the study lies in emphasizing the benefits of green jobs in the ICT sector not only for the economy, environment, and society, but also for employees themselves -highlighting aspects such as future-proof skills, career satisfaction, and opportunities for green self-employment. The article introduces a functional categorization of green roles and discusses the practical implications for policymakers, educators, and companies. The results point to the urgent need for interdisciplinary educational pathways, standardized certification frameworks, and inclusive labour market policies. The research reveals that green jobs in ICT may emerge through both cost-effective and innovation-driven mechanisms and concludes that the sustainable transformation of the digital sector depends on the engagement of a new generation of ICT professionals equipped with green competences.

The aim of this article is to explore the interdependencies between cybersecurity and sustainable development, to map the scientific landscape at their intersection using bibliometric techniques, and to identify emerging key research gaps. To investigate how this relationship has been addressed in the scholarly literature, a bibliometric review was conducted on selected 425 publications that include the terms ‘cybersecurity’ and ‘sustainable development’. The article presents a broad comparison of the Scopus and Web of Science databases, with a justification for choosing the Scopus database. Co-citation, keyword-co-occurrence and thematic-evolution analyses carried out with VOSviewer and Bibliometrix, respectively, allowed to identify four principal research themes: (1) smart-energy infrastructure and technical security, (2) cyber-resilient critical systems, (3) ESG-oriented digital management and (4) sustainable industrial transformation. The primary novelty of this study lies in its contributions aligned with the research questions: (RQ1) the exploration of the connections between the terms ‘cybersecurity’ and ‘sustainable development’; and (RQ2) the widening and presentation of the concept of green cybersecurity, defined as the deliberate design, deployment, and security solutions management that uphold environmental protection without compromising system resilience. The future research can focus on the multidisciplinary research agenda and strategy recommendations are then articulated to align ICT management and green jobs creation with circular-economy principles. Therefore, this study identified two relatively unexplored domains: (I) life-cycle-aware security design and (II) ultra-low-carbon cybersecurity.

This study aims to identify, classify, and critically evaluate key research trends in forecasting models related to sustainable development within the energy sector. A structured query was applied to the OpenAlex bibliometric database, focusing on titles, abstracts, and keywords containing the terms forecasting, sustainability, and energy. This targeted approach ensured thematic relevance and minimised the inclusion of unrelated publications. The retrieved dataset underwent a multi-stage analysis using the Bibliometrix package in the R programming environment. Three forms of thematic clustering were applied: (1) based on thematic orientation, (2) according to the temporal evolution of research topics, and (3) reflecting emerging or declining development trends. To enhance methodological robustness, a triangulated approach was adopted, combining quantitative bibliometric mapping with qualitative sentiment evaluation. In the subsequent stage, negative sentiment analysis was conducted using a custom-developed tool. This alternative approach, focused on negative sentiment, enabled the identification of critical themes, including systemic barriers, technological limitations, and strategy inconsistencies that impede the advancement of forecasting models for sustainability in the energy domain. The proposed integration of sentiment analysis intensity into bibliometric review represents a methodological contribution to the field. The findings highlight structural and conceptual challenges while offering insight into future research trajectories. Addressing these barriers is essential for enhancing the practical relevance and strategic impact of forecasting models and is a managerial contribution particularly in the context of green jobs and sustainable strategic management.

This paper explores the integral connections between Information Technology (IT), Information and Communication Technologies (ICT), and self-employment, with a specific focus on fostering sustainable development. Through a comprehensive literature review and bibliometric analysis using VOSviewer software, this research identifies the current discourse and maps out future research directions that combine IT, ICT, and self-employment with sustainability objectives. Despite the increasing integration of IT and ICT in various sectors, there remains a significant gap in research that links these technologies directly with green practices and sustainable development goals. This study contributes to closing this gap by highlighting how digital tools and technologies can promote environmental sustainability, economic resilience, and social well-being. Particular attention in the undertaken deliberations was focused on demonstrating the role of IT and ICT in promoting the greening of self-employment. Furthermore, within the context of future research, the necessity of addressing a broader research context concerning the role of IT and ICT in creating a green labor market was recognized. In this area, issues related to the flow between green self-employed individuals and green jobs were observed, including a specific focus on the concept of golden-green jobs.

Contemporary generative AI tools are becoming integral to business development strategies. Organizations are seeking applications for innovative technologies in science and various areas of operations. Intelligent systems bridge the gap between the scientific world and business practice. This is significant in using generative artificial intelligence in Sustainable Strategic Management (SSM) to create Green Jobs (GJs). Despite the popularity of topics like sustainable strategic management and creating GJs, science rarely combines these into interdisciplinary research. This article stands out from other review articles by using the innovative Scopus AI tool to explore a significant construct from theoretical and practical perspectives. The aim of this article is to highlight the potential for collaboration between science and business in creating GJs using Business Intelligent Systems (BIS) in SSM. The methodology of exploratory scientific inquiry supports this goal. This article employs a new research method, the Scopus AI tool. The results undergo critical analysis and interpretation, presenting conclusions and recommendations for using intelligent systems to create GJs in sustainable strategic management.

In this article, the Scopus scientific database was searched, focusing on journals categorized under the scientific subject area of "computer science". Using a bibliometric query, scientific articles in the Scopus database were examined. The article discusses the research problem of identifying green jobs in the field of computer science, aiming to identify current and future key research areas. Unfortunately, only a portion of the results directly relate to the field of computer science, despite the articles being indexed under computer science journals. The articles analyzed were assigned to computer science, but it is not the article itself that is assigned to the discipline of "computer science", but rather the journals and the articles contained within them. The article highlights the potential for interpretative errors in the bibliometric analysis of publications assigned to the "computer science" area, especially when authors solely seek feedback relevant to this field. The article also discusses the limitations of the research and future promising research directions, such as not only "green jobs" but also "golden-green jobs". These two types of jobs are elements of the green labor market and are part of the green economy sector while simultaneously belonging to the field of computer science.

Sustainable Strategic Management (SSM) involves identifying and refining the most crucial strategic directions for a company in the areas of economics, society, and the environment. Efforts in these areas also contribute to achieving sustainable development goals in business management. The application of Business Intelligent Systems (BIS) to achieve strategic goals and implement strategies enhances business outcomes, agility, scalability, and flexibility of enterprises. This article aims to identify key research areas concerning SSM and BIS in the context of sustainable development. The research methodology employed is a literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) schema in the Scopus database. Bibliometric mapping was conducted using VOSviewer software, with results presented in the form of diagrams, tables, and accompanying descriptions. The article explores both previously researched areas and fills a research gap by presenting a new theoretical perspective on SSM supported by BIS. The scientific and methodological implications summarize the current state of knowledge in the studied areas and result from the conducted research procedures, which can be replicated in other academic databases. Therefore, practical implications include identifying areas of SSM suitable for implementing BIS in companies committed to achieving sustainable development goals.

This article analyzes the subject of wearables and Sustainable Development (SD) in the scientific literature and is an attempt to present possible implications for Green Jobs (GJs) and the green labor market. There is a growing trend toward purchasing new wearable devices among consumers, which are more and more interested in the SD. These devices combine the functions of many other devices using smart technology and connectivity. They can communicate with other wearables or equipment, such as vehicles, machines, and buildings. Wearables have a wide range of applications. They allow monitoring of vital functions, and behavior, display information, improve communication, help to plan daily activities, and aid decision-making. Therefore, these devices are becoming increasingly important in daily life and business. Wearable technology uses the Internet of Things (IoT) and connectivity to synchronize data between devices. From a scientific perspective, it is interesting to explore how wearables are related to the SD in transitioning the economy toward green economy areas. The main goal of this article is to demonstrate the relevance of wearables to SD in scientific literature. Additionally, this paper aims to outline future implications for GJs, green self-employment, green competencies, and the green labor market. The method adopted in this study was a bibliometric review conducted in the Scopus database with the VOSviewer software support. The results are presented in the form of bibliometric maps and keyword tables. The study's results suggest that wearables have been rarely addressed in the context of managing employees in the workplace from the SD perspective.

Artificial Intelligence (AI) has emerged as an innovative technology with significant potential to transform industries and societies worldwide. In the context of Sustainable Development (SD), AI presents a unique opportunity to address the managerial challenges related to sustainability. This study explores the relationship between AI and SD in the management context, highlighting the potential of AI to contribute to SD through various applications. The research presents a bibliometric literature review of scientific publications on AI and SD, identifying key areas where AI can make a significant contribution to achieving sustainability in business management. These areas include sustainable agriculture, computer sciences, economy and business management, and decision-making processes. The challenges and ethical considerations associated with the use of AI in business management literature in the context of SD were also discussed. In addition, the paper presents the implications of AI for decision-making and management practices, particularly in terms of the development of AI strategies and the adoption of AI-based solutions in environmental performance. The integration of AI into management practices can facilitate SD and help organizations achieve their strategic goals, which has been proposed and discussed in this article. Moreover, the research contributes to the ongoing discourse on the role of AI and SD in management. The study concludes by calling for further research and collaboration among various stakeholders to maximize the potential of AI in SD.

This article analyzes the intersection between Sustainable Development (SD) and cybersecurity, identifying interdependencies crucial for economic growth and societal well-being. Using bibliometric analysis and a thematic map, the study identifies key trends and emerging topics. The research adopts a Structured Literature Review (SLR) variation with queries and explores the Scopus database to present bibliometric and scientometric information. The article emphasizes the need for integrated frameworks that consider both concepts to ensure sustainable, equitable, and secure economic growth. The article emphasizes the importance of understanding the social and environmental implications of cybersecurity practices within SD initiatives while highlighting the focus on developing technology-driven solutions for cybersecurity challenges. The proposed research agenda for the intersection of SD and cybersecurity offers insights and information for researchers, industry professionals, and marketing professionals. The study's methodology has implications for practice in multiple areas, including marketing, where the analysis of trends can inform marketing strategies and practices. Overall, this article contributes to the existing literature by identifying research gaps and future research areas emerging from the integration of SD and cybersecurity. The article's findings and insights provide a valuable resource for researchers, industry professionals, and marketing professionals interested in the intersection of these two concepts.

The growing game's popularity is caused by their possibilities in decision-making training. Management games allow avoiding potential mistakes related to the business choices, but they require several updates and improvements in terms of context and new trends. The business environment is constantly changing and requires new creative approaches to be trained. One of them is the business greening and realizing the idea of sustainable behavior and engagement in managerial games. This paper aims to propose managerial game improvements to achieve better game engagement and become more interesting for students because of its real business world connection. The object of the research and analysis is the Marketplace®, which is the educational managerial game. In this paper, the game analysis three levels were presented to propose the recommendations for the Marketplace game development. The main finding is that an assessment survey should occur in the game climax, to engage and immerse students in the game. The survey questions should also be reexamined to develop a more dynamic game analysis. Then the game itself has to consist of sustainable development of practical solutions and enable students’ creativity to raise their engagement.

This paper delivers up-to-date bibliometric research dealing with deep learning used in forecasting alternative costs in leasing. The study presents a theoretical approach that is developed by the bibliometric maps. The aim of this paper is the identification and exploration of the research gap. The study illustrates the relationships between different science areas, such as applied economics and finances, computer science, deep learning, and machine learning. The alternative costs in the literature are related to non-financial areas and the other Artificial Intelligence (AI) methods to calculate them. There is a scarcity of alternative costs calculation with deep learning procedures or their theoretical analysis. To fill this gap, this study uses VOSviewer software to explore queries’ results in the Scopus database and to illustrate the knowledge about alternative costs in deep or machine learning. The results show that: (I) the number of publications tends to increase gradually; (II) prediction or forecasting of the alternative costs is connected directly neither to the lost benefits, nor costs and risk assessment; (III) most studies concern the use of statistical methods in forecasting, but only a few use machine learning algorithms or decision trees. This scientific paper serves as a starting point for future studies dedicated to the deep learning procedures to forecast alternative costs in leasing or other financial processes.

The usage of machine learning methods in the financial sector, regarding repayment prediction or forecasting, is quite a new topic, constantly gaining in importance. The concept of the alternative costs in the literature covering machine learning and deep learning occurs most often in connection with the non-financial areas as costs of lost benefits. This empirical paper presents research dedicated to deep learning used in forecasting the alternative costs of leasing represented by the variable KUK_PRC. The study is based on the experimental approach and uses real organization data to solve the forecasting problems in the financial area with AI solutions. This research contributes to the science by identifying and exploration of the research gap in the field of applied economics and finances. The main finding of this paper is the proposed forecasting ACSeq-DNN model that forecasts opportunity costs with smaller deviations from actual values than the forecasting achieved by state-of-the-art models.

Growing interdependencies between organizations lead them towards the creation of inter-organizational networks where cybersecurity and sustainable development have become one of the most important issues. The Environmental Goods and Services Sector (EGSS) is one of the fastest developing sectors of economy fueled by the growing relationships between network entities based on the ICT usage. In this sector the Green Cybersecurity is an emerging issue because it secures processes related directly and indirectly to the environmental management and protection. In the future the multidimensional development of the EGSS can help European Union to overcome the upcoming crises. At the same time computer technologies and cybersecurity can contribute to the implementation of the concept of sustainable development. The development of environmental technologies along with their cybersecurity is one of the aims of the realization of sustainable production and domestic security concepts among the EU countries. Hence, the aim of this article is a theoretical discussion and research on the relationships between cybersecurity and sustainable development in the inter-organizational networks. Therefore, the article is an attempt to give an answer to the question about the current state of the implementation of cybersecurity in relation to the EGSS part of the economy in different EU countries.

The graduates’ careers are the most spectacular and visible outcome of excellent university education. This is also important for the university performance assessment, when its graduates can easily find job on the labour market. The information about graduates’ matching their qualifications and fields of studies versus undertaken employment, create an important set of data for future students and employers to be analysed. Additionally, there is business environment pressure to transform work places and whole organizations towards more green and sustainable form. Green Jobs (GJ) are the element of the whole economy transformation. This change is based on the green qualifications and green careers which translate theoretical assumptions into business language. Therefore, the choice of future career path is based specified criteria, which were examined by surveys performed among graduates by the career office at Wroclaw University of Technology (WUT) in Poland. The aim of this article was to address the question about most significant criteria of green career paths among graduates of WUT in 2019. The special attention was paid for the GJ understood as green careers. In this article the multi-criteria Bellinger’s method was explained, presented and then used to analyse chosen factors of choice graduates’ career paths and then compared with Gale-Shapley algorithm results in a comparative analysis. The future research can develop a graduate profile willing to be employed in GJ.

Green jobs, although defined differently, are created in various sectors of the economy. This is because many organizations strive to implement the idea of ​​a green economy. Some sectors of the economy are conducive to the direct creation of green jobs, others distinguish skills and actions that can indirectly contribute to the creation of green employment. The purpose of this study is to analyze green jobs compared to Industry 4.0. Changes towards a green economy coincide with the fourth Industrial Revolution (Industry 4.0), which supports green governance. The style of common fields set by green jobs and Industry 4.0 comes to the synergy effect, which is manifested in the practical actions presented in the chapter. Smart cities are a special case, where green infrastructure is developing to support electromobility and reduce the effects of anthropopressure.