The future of the world is a topic that continues to generate debate and intrigue across generations, due to uncertainties and evolving concerns. As the industrial revolution, technological advancements, and urbanization have progressed, numerous challenges have arisen. Environmental pollution, income inequality at national and international levels, wars, and social conflicts all serve to underscore the significance of addressing future expectations. As a result, environmental, social, and economic sustainability has emerged as a pressing issue. In response, various economic and political calls have stressed the importance of sustainability. This study examines the relationship between sustainability and quality costs using a case example and explores a long-term benefit-cost analysis. It is suggested that, although quality costs may be higher in the short term, they yield greater benefits in the long run, thereby contributing to sustainable development.

This paper is the third part of our attempt to examine the governance, efficiency, and development of the Agricultural Knowledge and Innovation System (AKIS) in Bulgaria based on a project related to mechanisms and the modes of agrarian governance in Bulgaria. The research continues with the expert assessment on governance of AKIS in Bulgaria and the SWOT analysis regarding development strategy and intervention needs providing recommendations and actionable steps to address the identified weaknesses and enhance the effectiveness, efficiency, and inclusiveness of the AKIS governance. It is emphasizing the approaches of comparative data and institutional analysis, gap analysis, SWOT, strategic orientation, experts’ assessments to identify actors and relations, state and trends in development, assess strengths, weaknesses, opportunities, and threats, formulate adequate strategy, and specify overall and public intervention needs of AKIS in the country.

The prevalent economic principle of weak disposability has been the foundation for studies in environmental assessment using Data Envelopment Analysis (DEA). Recently, a shift from classical free disposability to weak disposability has been observed as an emerging trend for treating undesirable factors in research. Weak disposability is perceived to have significant analytical power in measuring the efficiency of Decision-Making Units (DMUs). Addressing the increment of undesirable inputs, a non-radial model grounded on a non-uniform augment factor is presented. The application of this proposed model anticipates a suitable quantity for the increment of undesirable inputs. Concurrently, the model ensures a corresponding reduction in desirable inputs. Numerical instances illuminate the practicality and robustness of the proposed model and demonstrate its superior performance over its original counterpart.

Developments in Blockchain technology and their increasing adoption have prompted examination of intersections with organizational internal control systems. Technological solutions leveraging blockchain reportedly enhance operational effectiveness and efficiency, core internal control objectives. Such improvements could increase financial and non-financial reporting reliability and facilitate regulatory compliance. The Committee of Sponsoring Organizations' (COSO) internal control framework provides a systematic methodology for designing and implementing effective controls utilizing blockchain technologies. Within the COSO 2013 framework's context, this study aims to identify risks that may arise from blockchain technology integration into financial reporting processes and outline corresponding control formulations. Specific focal points involve risk evaluation associated with blockchain technology adoption and control implementation proposals addressing identified issues. If properly designed, controls may optimize blockchain technology capabilities for transparent, accountable, and sustainable value generation. This initial examination offers strategic guidance on evidence-based advancement of business-community symbiosis locally and globally through continuous policy evolution. Regional contextualization and adaptability to emerging complexities will determine durability of theoretical edifices established.

A comparative investigation is conducted, employing Computational Fluid Dynamics (CFD) simulations to study two distinct room space configurations: one featuring a solar chimney and another integrating both a solar chimney and a geothermal system. The primary objective of this investigation is to scrutinize the thermal behavior, energy efficiency, and mass flow rates of these systems. Results underscore the considerable positive implications of the geothermal system integration. This amalgamation precipitates diminished average room temperatures and elevated mass flow rates, signifying superior thermal comfort and energy performance. The room implementing the geothermal system exhibited an average temperature of 302.2 Kelvin and a mass flow rate of 4.134 × 10⁻⁶ kg/s, in contrast to the room without the geothermal system, which demonstrated an average temperature of 309.6 Kelvin and a mass flow rate of 1.878 × 10⁻⁶ kg/s. These findings have practical repercussions for architects, engineers, and policymakers, facilitating well-grounded decisions in the domain of sustainable building design. The observed enhancement in thermal performance and mass flow rates underscore the potential merits of integrating geothermal systems, thereby promoting wider acceptance. Further research is recommended to investigate the influence of varied climatic conditions, building orientations, and room layouts on the efficiency of integrated solar chimney and geothermal designs. Examination of alternative renewable energy sources (RES), innovative building materials, and technologies is also suggested to elevate energy efficiency and sustainability in room space designs. This study contributes substantially to the expanding realm of sustainable building design, providing valuable insights for refining room space performance, curbing energy consumption, and heightening thermal comfort. By highlighting the advantages of renewable energy integration, particularly geothermal systems, the study stimulates the development of more energy-efficient and environmentally friendly building spaces.

Objective: This study aims to investigate the significance of health insurance in the context of India's growing population, with a particular focus on Uttar Pradesh, the country's most populous state. By examining various factors, such as the cost of health insurance in relation to its perceived benefits, the study seeks to understand the drivers behind health insurance uptake in the state. The importance of health insurance is underscored by the high cost of quality healthcare and the prevalent lack of awareness regarding its benefits. This paper emphasizes the need for health insurance and explores the reasons behind individuals' reluctance to prioritize its benefits over short-term gains.

Methods: A mixed-methods approach was employed in this study. Quantitative data was collected to gauge the impact of cost on health insurance adoption and to assess how an individual's income influences their perception of health insurance. Surveys using Google Forms were administered in urban areas to obtain numerical data reflecting the general population's views on the current situation and their willingness to purchase health insurance. The sample comprised 402 respondents from Uttar Pradesh, representing diverse age groups, social backgrounds, and income levels. Data from the National Family Health Survey and the National Sample Survey Office were used as reference points to determine the prevalence of insurance uptake and to evaluate the representativeness of the sample.

Results: The findings suggest that the cost factor, specifically the cost of health insurance premiums and the long-term returns they offer, remains the primary determinant of health insurance adoption.

Practical Implications: This research underscores the importance of health insurance in the Indian society and identifies the factors influencing individuals' decisions to purchase a policy. Furthermore, the study proposes that making health insurance more affordable and raising awareness among the population could address the issue of low uptake. Consequently, this work aims to heighten awareness of health insurance's importance among Uttar Pradesh residents and recommend that policy makers implement strategies to make it more accessible, thereby influencing public behavior.

Gender can determine mobility habits and patterns in everyday life. Yet, different mobility needs of men and women are often ignored in the urban transport systems analysis and planning. Different attitudes and perceptions can determine the transport mode choice as well as the basic characteristics of a person’s trip. Integrated transport and urban planning require taking into account these differences for reasons of inclusivity. This paper identifies gender differences in travel perceptions, attitudes and behaviours using inferential statistical analysis of questionnaire surveys contacted in the city of Thessaloniki, Greece, and discusses the policy directions to enhance gender mobility equity. The results are cross-checked with international literature to explore the role of local culture in explaining gender gaps in urban mobility.

This study aimed to evaluate citizen satisfaction with e-Government (eGov) services in Turkey amid the COVID-19 pandemic and identify the key factors influencing satisfaction levels. Data were collected from a random sample of 396 citizens residing in Usak, Turkey, who utilized eGov services throughout the crisis. Factor analysis and multiple linear regression methods were employed to examine the gathered data. The results revealed that the performance of eGov services and citizens' trust in the government were significant predictors of satisfaction with eGov services in the context of a pandemic. These findings offer valuable insights into enhancing eGov implementation in Turkey and suggest potentially beneficial strategies for nations with similar eGov infrastructures and socio-economic development. The broader implications of these findings for both practical applications and future research are subsequently explored in this study.

This study focuses on formulating an integration algorithm for manufacturing firms aiming to infuse the immense potential of Industry 4.0 technologies into lean manufacturing systems. The goal is to unlock and harness the advantages offered by these advanced technologies in an economically efficient manner. An analytic approach has been implemented in this investigation, examining a broad array of relevant empirical research. This comprehensive analysis serves to derive a universal algorithm predicated on the principles of both lean methodology and Industry 4.0. The complexities and challenges of amalgamating lean methodology and Industry 4.0 have been scrutinized meticulously in this study. The study elaborates on the extent to which Industry 4.0 technologies can augment lean production practices, delves into the difficulties encountered by corporations during the integration process, and suggests measures to surmount these obstacles. Moreover, potential benefits realized through this integration are explored. The algorithm proffered in this study permits a phased integration approach. Firms have the flexibility to adopt the integration in specific production segments or processes initially and progressively expand, aligning with their capabilities, resources, and the level of process maturity. Such an integration strategy allows companies to leverage Industry 4.0 in overcoming restrictions traditionally associated with the lean approach.

This investigation elucidates the correlation between membership in a Free Trade Agreement (FTA) and the degree of financial integration among Central European Free Trade Agreement (CEFTA) countries. A particular emphasis is placed on discerning whether CEFTA affiliation enhances financial integration. A comprehensive panel data analysis spanning two decades (2000-2020) is implemented, incorporating cross-sectional and time-series data. The influence of various determinants on financial integration is quantified through an Estimated Generalized Least Squares (EGLS) panel regression model, integrating panel-corrected standard errors. The findings consistently reveal that CEFTA membership bolsters financial integration. Moreover, the study substantiates that control variables such as inflation rate, market size, and corporate tax rate, incorporated in the regression model, significantly contribute to the variance of financial integration at a minimum 5% significance level. Conversely, trade openness demonstrated a positive, albeit statistically insignificant, effect. Empirical evidence suggests that CEFTA affiliation positively impacts financial integration, underscoring the necessity for more profound regional economic amalgamation. The significance of these findings can be observed in two dimensions: the contribution to existing literature on CEFTA region trade integration, and the broader discourse on financial integration. Insight gleaned from these findings recommends that CEFTA members should intensify mutual trade integration and diminish trade barriers to foster comparative advantages.

The burgeoning Metaverse represents an unprecedented technology frontier that is poised to redefine our financial, societal, and cultural paradigms. This research introduces a new economic term, Metanomics, to the academic discourse by conceptualizing an economic structure in which the virtual needs of humans and virtual entities are met in virtual universes, production, distribution and finance processes are designed for this purpose and interact with the real universe. A profound examination of the potential sectoral, macroeconomic, and financial repercussions of Metanomics has been carried out. Expected improvements in sectors like education, healthcare, and tourism include increased productivity, emergence of new job roles, cost efficiencies, and heightened profitability. On the macroeconomic front, an escalation in total factor productivity, employment opportunities, and growth rates is anticipated. The unique aspect of this system pertains to its potential influence on the financial landscape. Novel financial institutions wielding innovative financial instruments are forecasted to emerge in the Metaverse. Consequently, a new arena of financial transactions linking the virtual and real-world economies is predicted to emerge, causing an expansion of the financial transaction volume in the real world. These transactions, primarily facilitated by cryptocurrencies, will contribute to an accelerated globalization process. Therefore, this research endeavours to forecast the ways the Metaverse might reshape future financial systems, predict the repercussions of these interplays on the global economy, delineate potential risks and opportunities, and propose relevant policy recommendations.

Between 2018 and 2020, in the approximately 2,600 km of Italian road tunnels, 2,899 people were injured and 60 died in 1,885 road accidents. The accident frequency was lower than on open roads, while the injury/fatality rate was higher. Using the recursive partitioning and regression trees method (rpart), we developed two accident models useful for predicting the probability of involvement of "vehicle type" in short and long tunnels. Variables such as the type of accident, the circumstances, the type of road, the carriageway, the time of the accident, the journey purpose (whether work-related or not), and the length of the tunnel defined the nodes and paths of the regression tree associated with a vehicle type involved. The “road type” was the best predictors for short tunnels while the “journey purpose” was the best predictor for long tunnels. The most important result of the study refers to the similarity between the probability of an accident in short and long tunnels for a specific segment of road users: commuting and non-commuting car drivers and drivers of heavy goods vehicles on-duty. The study showed that this road user segment in short tunnels has an accident probability half that observed in long tunnels.

Neutrosophic sets, expanded from the constructs of fuzzy and intuitionistic fuzzy sets, can accommodate degrees of truth, indeterminacy, and falsity for each element. This attribute equips them with an aptitude for a more refined interpretation of ambiguous or uncertain data. This study presents an innovative application of Neutrosophic Data Envelopment Analysis (Neu-DEA), incorporating pentagonal neutrosophic numbers in both input and output data. This novel methodology involves the transformation of traditional DEA models into a Pentagonal neutrosophic DEA model, subsequently converting it into a Crisp Linear Programming (CrLP) model. A unique ranking function is integral to this process. Performance evaluation of decision-making units (DMUs) is accomplished through the resolution of the CrLP model, with subsequent ranking of the DMUs based on their relative efficiency scores. The utility and effectiveness of this novel technique is validated through a numerical example.

Driven by the swift progression of next-generation information technologies, a notable escalation in the synergistic aggregation of productive services and manufacturing industries is recorded. Prior research has primarily concentrated on the implications of standalone industry aggregation. In the current study, the theoretical ramifications of industry synergy aggregation on green total factor productivity have been delineated, with the foundation laid upon Marshall's conceptualization of agglomeration externalities. To empirically validate these theoretical underpinnings, a panel threshold model has been utilized. The data set comprises 92 cities of prefecture-level and above from five significant urban agglomerations: Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, Chengdu-Chongqing, and the Middle Yangtze River area, spanning a period of 2010 to 2019. Results unveil a $\backsim$-shaped association between industry synergy aggregation and green total factor productivity. The existence of both agglomeration economies and diseconomies is substantiated in the current phase of industry synergy aggregation. Employing labor force pools and shared intermediate inputs as threshold variables, the initial impact of industry synergy aggregation on green total factor productivity appears to be negative, but after crossing the first threshold, the impact becomes positive, only to revert to negative post traversing the second threshold. Alternatively, when knowledge spillover is taken as the threshold variable, the influence begins as negative, turns positive post the first threshold, and retains the positive influence beyond the second threshold, exhibiting a stronger promoting effect. The findings highlight the recommendation that industry development strategies ought not to be solely centered on the geographical congregation of productive services and manufacturing industries. Instead, a significant emphasis on exploiting the benefits of agglomeration externalities is advised. Specifically, for cities grappling with excessive industry synergy aggregation, strategies should prioritize facilitating industrial relocation as a means to temper the inhibitory effects of agglomeration diseconomies on green total factor productivity.