Abstract: As global concerns about climate change and air quality intensify, nations are increasingly adopting sustainable transportation solutions, with electromobility emerging as a key alternative. This article examines the adoption of electric vehicles (EV) in Poland, a member state of the European Union (EU) historically reliant on fossil fuels, where the former government aimed to achieve one million electric vehicles by 2025, but is now seeing that it is failing to reach a number even close to this one. Using a mixed methods approach through a survey of academic representatives, the study investigates public perceptions, motivations, and challenges associated with the adoption of EVs in Central Europe. Key factors influencing consumer behaviour, such as government policies, infrastructure development, and societal readiness, are analysed to understand this transition's complexities. The findings reveal significant barriers, including range anxiety, inadequate charging infrastructure, and cost concerns, consistent with global research. However, the study also highlights that a lack of environmental consideration in car purchase decisions further impedes the transition to more sustainable powertrain options. By identifying the dynamics shaping the adoption of electric vehicles in Poland, this research aims to inform policymakers and stakeholders, highlighting tailored approaches to promote electromobility as a cornerstone of the country's environmental strategy and economic future. The findings contribute to the broader discourse on sustainable transportation in the EU, underscoring the potential of electromobility to enhance the environmental sustainability of Poland while navigating the challenges of transitioning from fossil fuel dependency.

Abstract: Service quality research has traditionally focused either on identifying Kano two-dimensional quality categories or detecting service quality deficiencies. However, integrating these perspectives remains a challenge due to the Kano model's nonlinear characteristics and the Importance-Performance and Gap Analysis (IPGA) model's linear approach. This study proposes the Kano-IPGA (KIPGA) model, incorporating Mutual Information (MI) to bridge the gap between these two models. The KIPGA model first employs moderated regression analysis to classify service attributes into Kano’s quality categories. MI is then used to calculate relative importance (RI), while relative performance (RP) is determined using the original IPGA approach. The results are mapped into the KIPGA strategic matrix, categorizing service attributes into eight management strategies. An empirical analysis of Taiwan’s online insurance systems demonstrates the model’s effectiveness in simultaneously identifying Kano categories and prioritizing service quality improvements. The findings reveal that Critical Improvement and Enhanced Improvement regions require immediate attention. The proposed KIPGA model offers a systematic approach for service quality management, providing decision-makers with a structured framework to allocate resources effectively and enhance customer satisfaction. This study contributes to service quality research by offering an integrated model that accounts for both linear and nonlinear quality assessment perspectives.

Abstract:

Large language models (LLMs) are reshaping information consumption and influencing public discourse, raising concerns over their role in narrative control and polarization. This study applies Wittgenstein’s theory of language games to analyze worldviews embedded in responses from four LLMs. Surface analysis revealed minimal variability in semantic similarity, thematic focus, and sentiment patterns. However, the deep analysis, using zero-shot classification across geopolitical, ideological, and philosophical dimensions, uncovered key divergences: liberalism (H = 12.51, p = 0.006), conservatism (H = 8.76, p = 0.033), and utilitarianism (H = 8.56, p = 0.036). One LLM demonstrated strong pro-globalization and liberal tendencies, while another leaned toward pro-sovereignty and national security frames. Diverging philosophical perspectives, including preferences for utilitarian versus deontological reasoning, further amplified these contrasts. The findings highlight that LLMs, when scaled globally, could serve as covert instruments in narrative warfare, necessitating deeper scrutiny of their societal impact.

Abstract:

The Information Technology (IT) industry is not only an emerging global sector but also has the potential to support various business verticals. The rapid pace at which we demand and process information, and the significant convenience it brings to our lives, is remarkable. However, it is important to recognize that the IT industry, particularly the general computing sector, significantly contributes to energy consumption and carbon emissions. This systematic review aims to identify the key requirements for greening emerging technologies. The main objective of this study includes examining sources of energy consumption and greenhouse gas emissions within the IT sector and exploring the potential of various IT technologies to improve energy efficiency. This review study adopted systematic review processes that involved filtering 1988 academic articles down to 374 relevant studies, focusing on seven technologies: cloud computing, mobile computing, Internet of Things, big data analytics, networking, blockchain technology, and AI. Findings of this review study reveal a classification framework for these technologies, highlighting their unique contributions and potential for energy savings. The study emphasizes the importance of adopting cross-technology techniques to enhance sustainability. This review study demonstrateds by developing a comprehensive understanding of each technology's role in energy conservation and proposing integrative approaches to greening IT. This work provides a valuable reference for organizations aiming to implement green practices and supports future research in sustainable IT solutions.

Abstract:

In this paper, we analyze the multidimensional characteristics of climate change in a dynamic decision-making framework, considering the concepts of uncertainty and irreversibility. It provides a lens on the many aspects of climate change and ways that policy and other strategies can drive change. It examines where climate models came from and the controversies surrounding their accuracy. It also argues that some key lessons have emerged from international agreements around climate change. To this end, the objective is to provide actionable solutions for greenhouse gas emissions reduction, building climate resilience, and establishing sustainable futures for vulnerable communities. The paper highlights the importance of investments in renewable energy to mitigate climate risks and increase resiliency across the globe. The framework addresses cost variability, adoption probabilities, and discount rates to provide practical recommendations and policy frameworks for decision-makers and financiers to facilitate the transition to renewable energy strategies. Thereby contributing to sustainable development and enhanced climate resilience.

Abstract: The unprecedented challenges of the Anthropocene, such as climate change, social inequality, and rapid technological disruption, have shaped an era where traditional leadership models are increasingly inadequate for navigating complexity and driving systemic change. This paper talks about Regenerative Leadership, a model that changes things for the better using neuroplasticity intelligence, AI to help with decisions, and the AHA SHIFT framework. It gives leaders the flexibility, ethical leadership, cultural change, and systemic thinking they need for long-term success. By aligning organizational growth with societal well-being, this model provides a pathway for fostering innovation, collaboration, and human-centric development.   Central to this leadership paradigm is the Trinity Growth Model, which anchors the Awakening phase in the personal transformation of leaders through coaching, neuroplasticity-based practices, and cognitive rewiring. These practices cultivate cognitive flexibility and emotional resilience, enabling leaders to respond to uncertainty and vulnerability while driving systemic change. Leveraging AI as a decision-making tool further enhances leadership by mitigating cognitive biases and providing real-time, data-driven insights, ensuring that decisions align with ethical and sustainability goals.   The **5Ps framework—People, Planet, Prosperity, Partnership, and Purpose** serves as the foundation of regenerative leadership, redefining success by expanding its focus beyond profitability to encompass societal impact, ethical governance, and environmental stewardship. Drawing on empirical research and case studies from diverse pioneering organizations, this paper demonstrates how regenerative leadership can transform industries in depth by fostering purpose-driven innovation and cross-sector collaboration.   Finally, this research introduces a Regenerative Leadership Playbook, offering actionable strategies for cultivating integrative consciousness in leadership development. We propose future research directions to explore the wider effects of regenerative leadership on organizational performance, leadership adaptability, and societal outcomes. By providing a roadmap for scaling regenerative leadership across diverse industries, this paper envisions a future where leaders drive systemic change and long-term sustainability, ensuring resilience and prosperity for humanity in the Anthropocene.

Abstract: The combination of stochastic derivative pricing models and downside risk measures often leads to the paradox (risk,return)=(-infinity,+infinity) in a portfolio choice problem. The construction of a portfolio of derivatives with high expected return and very negative downside risk (henceforth "golden strategy") has been only studied if all the involved derivatives have the same underlying asset. This paper also considers multi-asset derivatives, gives practical methods to build multi-asset golden strategies for both the expected shortfall and the expectile risk measure, and shows that the use of multi-asset options makes it more efficient the performance of the obtained golden strategy. Practical rules are given under the Black-Scholes-Merton multi-dimensional pricing model.

Abstract: During foraging decisions, animals often perform irrational choices. The selective-value effect is the lack of preference for an option consisting of one high-preferred item plus one less-preferred item, compared to a single high-preferred item. A similar bias is the less-is-better effect, in which individuals prefer a single high-preferred item rather than an option including both a high-preferred item and a less-preferred one. Here, we investigated the occurrence of these decisional biases in twelve capuchins monkeys (Sapajus spp.) by exploring, for the first time in this species, both the role of the relative value of the high- vs. less-preferred food and the length of the intertrial interval. Overall, capuchins performed rational choices, as they preferred the mixed over the single option. However, at the individual level, some capuchins showed the selective-value effect. According with previous findings in apes, both the relative value of the high- vs. less-preferred food and the length of the intertrial interval modulated capuchins’ preference for the mixed option. This study sheds further light on the factors affecting violations of rationality in primate food choices, suggesting that these decisions might reflect cognitive adaptations for optimizing sensory feedback and/or nutrient intake rather than being just irrational.

Abstract: A simple hypergraph H with vertex set X and edge set E is representable as a family of Von Neumann- Morgenstern stable sets -or VNM- if there exists an irreflexive simple digraph D with vertex set X such that each edge of H is a VNM--stable set of D. It is shown that a simple hypergraph H is VNM if and only if each edge of H is a maximal clique of the conjugation graph of H. A related algorithm that identifies finite VNM-hypergraphs is also provided.

Abstract: The endowment effect is a long-standing and powerful phenomenon in behavioral economics whereby people consistently overvalue objects they possess compared to the prices buyers will offer to acquire them. The endowment effect is usually considered irrational and causes disadvantageous choices in realms from online auctions to home sales to domestic clutter. Finding ways to reduce the impact of endowment processes could benefit people and society in myriad ways. Drawing from social psychology, we predicted that people would be more generous toward partners in a common experimental endowment mug task when their partner was portrayed as in pain or need. Combining existing study methods, two pilot studies successfully replicated the endowment effect in control conditions but eliminated or reversed it toward partners in physical (N = 156) or emotional (N = 278) pain (respectively). A pre-registered, in-person study (N = 106) directly contrasted physical pain, emotional pain, and control conditions. We again replicated the endowment effect toward control partners and eliminated it toward partners in physical or emotional pain (buyer prices increased and seller prices decreased; ηp2 = .13). People’s generosity toward those in need can be harnessed to release them from an often troubling and disadvantageous need to hold onto unneeded items that could benefit others.

Abstract: This study dives into the essential issue of sustainable water management techniques in East Af-rica. Recognizing water as a key component of sustainable agricultural development, the study highlights the importance of a complete approach that takes into account technological, socio-economic, and environmental issues. As East Africa faces rising problems from climatic variability and change, which have a direct impact on water availability and agricultural output, the need for comprehensive policies becomes clear. The review reveals significant gaps in previous research, including a lack of focus on the socioeconomic consequences of water management methods, gender dynamics, long-term assessments, indigenous knowledge integration, and climate change adaptation. By highlighting these areas, the study emphasizes the necessity of future research in addressing these gaps and developing more effective and sustainable water management solutions for East Africa.

Abstract: The ability to vote is one of the most valuable rights and privileges afforded by the Constitution of the United States to its citizens. For many, voting is not just a civic duty; it is also a choice, e.g., a way to have a voice regarding issues that affect them and that they care about. Even before the inception of restrictive voter identification laws, civil and voting rights groups have expressed concerns over the impact some laws may have on specific sections of the electorate and consequently, how they influence voter turnout. Indeed, the research on voter participation or suppression is very active. Voting is crucial to our democracy, and any changes to it may affect the efficiency of the democratic process. The bigger question is whether voters behave rationally by engaging in a cost-benefit calculus in deciding whether or not to vote. Using data science, this paper will examine the probability of voting and investigate its impact via cost and benefit among other variables using the 2020 American National Election Studies (ANES) dataset. In addition, the study will also assess the impact voter perceptions of “a sense of duty” on voter turnout. Empirical work provides additional evidence that feelings of civic duty truly do motivate voter turnout (Galais et al. 2016). Anthony Downs (1957), in his text “An Economic Theory of Democracy,” outlined a theoretical framework from an economic-based approach for voting behavior. Commonly known as the rational choice theory, he discussed similarities of the functions between consumers and voters and between business and political parties while maximizing a utility function. The goal of corporations is to improve their financial gain significantly. The utility for voting shows a lot more complexity and heterogeneity. One can posit that voters endeavor to increase the utility of their vote by maximizing electoral benefits acquired from political propositions (Antunes 2010, p. 157). Such actions have the potential to foster apathy toward political participation, including voting. Using the latest statistical analyses methods, we identify and understand the factors that benefited and hindered voting in the ANES 2020 data and the impact of voter benefits and costs on turnout.

Abstract: The theoretical and conceptual frameworks commonly used to study university-to-industry technology transfer (i.e., university technology transfer) are potentially distorting our understanding of the phenomenon and impeding knowledge creation about it. Reification is a particularly chronic pathology in university technology transfer research. Additionally, studies are predominantly from the perspective of universities. Examination of university technology transfer from the perspective of private sector firms (i.e., the demand side perspective), particularly small and medium-sized enterprises, seems to be lacking. Moreover, the quantitative correlational methodologies which are predominantly used to research university technology transfer cannot adequately capture the casual complexity to which the phenomenon is likely subject. This myopia in university technology transfer research is likely driven in part by the theories and conceptual frameworks that scholars have chosen to apply in their studies. This paper presents a human-centered framework for examining macro level organization phenomena that mitigates the problem of reification in technology transfer studies and enables better examinations of the phenomena from the perspective of demand side actors and well as supply side participants. Its usefulness is demonstrated using a mini case study that applies the framework to critique a previously published paper.

Abstract: The pandemic crisis of Covid-19 disturbed the social and the economic systems in which some changes happened during the pandemic and other changes extended subsequently. This paper is reflecting on the Sudan case, a country of a moderate population and large area with poor socioeconomic standard and infrastructure. The paper is based on the analysis of primary data and policy recommendations of an original research undertaken in five States in Sudan during the period Sept.2021-Sept.2022. The sample of the study selected from most five States that were affected by the Corona pandemic, namely: Khartoum State, Gezira State in the Central Region, Kassala State and Gadarif State from the Eastern Region, and Nyala State in the South Darfur Region in the west of the country. The research built on a quantitative research method, used the questionnaire as a tool for data collection from a sample size of 723 family head-households. The study is gaining a better understanding of the social, economic and health challenges that faced Sudanese households during the COVID-19 lock down and within the pandemic period. The study showed crucial results that the education of children was disturbed due to unavailability of the distance education in schools. In contrast some families maintained the education of the children as enrolled in private schools. In addition, the paper shows how the families used different approaches to educate their children and involve them into traditional informal and formal education ways. Additionally, the results explained the coping strategies with available resources that families used to manage economic crises and how this interferes with children education. Furthermore, the study proposing appropriate social policies and interventions that address the needs of the family in the current and future pandemic crisis.

Abstract: Decision sciences (DSC) involve studying complex dynamic systems and processes to aid informed choices subject to constraints in uncertain conditions. It integrates multidisciplinary methods, techniques, and strategies to evaluate decision engineering processes, identifying alternatives and providing insights towards enhancing prudent decision-making. This study analyzes the evolutionary trends and innovation in DSC education and research to uncover the transformations over the years. We employ the science mapping method, text analytics, and metadata from bibliographic databases to evaluate thematic and social structures. The results highlight data science methods, including data mining and business/learning analytics as essential components. The evolutionary trends in DSC education and research mirror the development in practice, including technological transformation, computer science advances, and engineering processes. Sustainable education through virtual/online learning also constitutes a significant component of scientific production. The evolutionary trends in DSC education and research highlight innovative pedagogical approaches and strategies, including computer simulation and games ('play and learn'). The current era witnessed generative artificial intelligence (GenAI) adoption (e.g., ChatGPT) in teaching, learning, and scholarly activities amidst challenges (academic integrity, plagiarism, intellectual property violations, and other ethical and legal issues). Future research will implement and integrate AI automatic detection systems to address some GenAI adoption challenges.

Abstract: Abstract:The ecological protection of cultivated land is crucial for advancing high-quality agricultural development. This study analyzes the impact of agricultural socialization services on the ecological conservation of farmland, focusing on the reduction of chemical fertilizers and pesticides among rice farmers in the Jianghan Plain area. Utilizing data from 743 farmer household surveys conducted in 2023, the findings reveal that agricultural socialization services significantly encourage farmers to reduce chemical input usage. Specifically, a 1% increase in the level of agricultural socialization services correlates with a 14% decrease in chemical fertilizers and a 16.4% decrease in pesticides per mu. The study identifies scale operation, factor substitution, and alleviation of capital constraints as mediating factors enhancing the efficacy of these services. Furthermore, heterogeneity analysis indicates that these services are more effective in reducing chemical inputs among large-scale and newer-generation farmers compared to their small-scale and older counterparts. Additionally, technology-intensive socialized services exhibit a stronger impact on reducing chemical inputs than labor-intensive services.

Abstract: Nowadays, considering the growing tendency of companies towards e-commerce as well as green production, and dual-channel green supply chain management has become particularly important. This paper investigates pricing decisions within a dual-channel green supply chain framework while considering the capital constraints faced by risk-averse manufacturer. Simultaneously, the impact of the degree of risk aversion, consumer green preferences, and channel preferences on the optimal decision-making process of green supply chain members is analyzed. We address the issue of financial constraints faced by manufacturer through bank loans and trade credit financing and compare the two cases. Our findings illustrate that trade credit financing outperforms bank loan financing in the dual-channel green supply chain. Moreover, pricing decisions under different models are influenced by consumer preferences and risk aversion. Specifically, the greenness of the product, wholesale price, and sale price exhibit negative correlations with manufacturers' risk aversion but positive correlations with consumer preferences.

Abstract: The innovativeness of nongovernmental organisations, the basic institutions of civil society, is conditioned, among other things, by the endogenous potential of agency of the entities operating within them. The article attempts to answer two research questions regarding the above-mentioned issues: (1) how individual components of binding and bridging social capital (in the area of trust, norms and connections) determine innovative activity in a state of morphostasis, i.e. structural and cultural continuity, selected Silesian NGOs. (2) What type of reflexivity and the related nature of agency of the members of the NGOs surveyed dominates when undertaking innovative activities? At the theoretical level, the study was based on the concept of three components of social capital by James S. Coleman and the assumptions of Margaret Archer's morphogenetic theory of structure and agency, in particular, the types of reflexivity as a factor conditioning social agency. Based on them and using qualitative analysis of data obtained during focus group interviews (FGI) and SWOT questionnaires of surveyed organisations, a diagnosis of intraorganisational barriers to innovation was made. The Atlas.ti computer programme was used. This method allows for the examination of structural elements, cultural features of a given organisation, and the capabilities of individual entities. The dominance of bonding social capital components over bridging social capital components was noted (mainly in the dimension of trust), as the basic bond connecting members of the NGOs studied. It was accompanied by a communicative type of reflexivity of the respondents, with the aim of maintaining the existing organisational and social status quo. These key socio-cultural factors determine the morphostatic nature of the organisations studied, i.e., their focus on maintaining the organisational status quo. Such contexts petrify the existing power structure, but also the level of social tensions and distances, and limit the innovation potential.

Abstract: The field of financial literacy is intricate and developing. This systematic review of the literature provides a thorough overview of financial literacy. It examines the sample of 3182 papers of the period 1990 to 2023 from different databases such as Scopus, Web of Science, IEEE, Science Direct, and JSTOR and identifies important publications, knowledge gaps, and rising themes. The four major topics that emerged are the degree of financial literacy among various groups of people, gender disparity in financial literacy, the influence of financial literacy on financial behavior and planning, and the impact of financial education on day-to-day decisions. Groups with lower levels of financial literacy include adults, women, people in the lower-income band, rural people, etc. Financial planning and financial behavior are positively associated with financial literacy. Financial literacy could be enhanced with financial education; however, output depends upon program design and experimental group. The review also discusses financial literacy in the context of gender disparity, including its definition, difficulties encountered, and possible solutions. This systematic study will help researchers, practitioners, and policymakers by providing insightful information on financial literacy and its ramifications.

Abstract: The article presents a methodology for modeling the impact of factors of both on-farm activity and environmental factors on the resulting indicators of an international company. The dataset includes the company's profit, revenue, valuation, share price, and market share from 2012 through 2022. This empirical period is optimal for such a type of modeling. Modeling the impact of carbon emissions factors on the resulting indicators is considered based on complex systems theory. Endogenous model variables include indicators of the development of the international company. Predefined model variables reflect the influence of both the external environment and internal factors on the development indicators of an international company. An approach of picture fuzzy rough sets based on time series of endogenous and exogenous variables can provide an opportunity to analyze and consider the consequences of feedback changes in the systems of which they are a part. Based on the results of the analysis of the model construction, it is concluded that picture fuzzy rough sets can be an excellent way to model interdependent social processes.