This paper investigates the effect of economic policy uncertainty (EPU) on the systemic risk of the fintech industry. To achieve this goal, we first estimate the evolution of system-wide systemic risk using the CatFin method. We further examine whether EPU significantly affects systemic risk. Our findings demonstrate that the systemic risk of the fintech industry is time-variant and sensitive to major crisis events. Systemic risk tends to increase after major crises, especially the outbreak of the COVID-19 pandemic. EPU has a considerable impact on systemic risk, notably during periods of turmoil.

The precise prediction of carbon emissions trading prices is the foundation for the stable and sustainable development of the carbon financial market. In recent years, influenced by a combination of factors such as the pandemic, trading regulations, and policies, carbon prices have exhibited strong random volatility and clear non-stationary characteristics. Traditional single-perspective prediction methods based on conventional statistical models are increasingly inadequate due to the homogenization of features and are struggling to adapt to China's regional carbon emissions trading market. Therefore, this paper proposes a multi-perspective fusion-based prediction method tailored to the Chinese market. It leverages carbon emissions trading information from key cities as relevant features to predict the price changes in individual cities. Inspired by the development of artificial intelligence, this paper implements various time series models based on deep neural networks. The effectiveness of the multi-perspective approach is validated through multiple metrics. It provides scientific decision-making tools for domestic carbon emissions trading investors, making a significant contribution to strengthening carbon market risk management and promoting the establishment and rational development of a unified carbon market in China.

Based on fully considering the actual differences in statistical indicators between Hong Kong, Macao, and the nine cities in the Pearl River Delta, this paper constructs a high-quality urban development evaluation system that is suitable for the actual development of the Guangdong-Hong Kong-Macao Greater Bay Area. The Entropy Weighted TOPSIS two-step method is used to process data and systematically investigate the changes in the high-quality development index of 11 cities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2013 to 2020. The study found that the Guangdong-Hong Kong-Macao Greater Bay Area has thoroughly implemented the new development concept, and the level of high-quality development has continued to improve. The profound integration effect of the Guangdong-Hong Kong-Macao Greater Bay Area has appeared, and it has promoted the high-quality development of the region in coordination. The construction of the Guangdong-Hong Kong-Macao Greater Bay Area has strongly promoted the great practice of "one country, two systems" to achieve stability and prosperity.

The workforce participation rate, and hence the level of employment, for women in Pakistan is among the lowest in South Asia – standing at 25 percent in 2023. Conventional explanations attribute this to poor skills and cultural norms of families and society at large. Empirical work has established that low levels of education, and community attitudes regarding gender roles, hinder women's labor force participation. Ethnographic work suggests that household rules – family culture – on who makes decisions about opportunities for married women to work outside of the home for pay – profoundly impact female employment. This is due to the limited availability of data pertaining to explicit assessments of familial traditions that are pertinent to women's participation in the workforce beyond their domestic sphere. Drawing on data from the Pakistan Social and Living Standards Measurement Survey (PSLM): 2005-2006 – which provides information, from married women, on who in the family decides if they can work – we address this shortcoming in the literature. We find that in families where the decision lies clearly, and exclusively, in the hands of males, married women are 18-19 percent less likely to be employed than if the family culture is for married women – alone – to make this decision. Moreover, this is a much larger deterrent to work than poor education and residential location.

The Weibull distribution is extensively useful in the field of finance, insurance and natural disasters. Recently, It has been considered as one of the most frequently used statistical distributions in modelling and analyzing stock pricing movement and uncertain prediction in financial and investment data sets, such as insurance claims distribution. It is well known that the Bayes estimators of the two-parameter Weibull distribution do not have a compact form and the closed-form expression of the Bayes estimators cannot be obtained. In this paper and the Bayesian setting, it is assumed that the scale parameter of the Weibull model has a gamma prior under the assumption that its shape parameter is known. A simulation study is performed using random claims amount to compare the performance of the Bayesian approach with traditional maximum likelihood estimators in terms of Root Mean Square Errors (RMSE) and Mean Absolute Error (MAE) for different sample sizes, with specific values of the scale parameter and shape parameters. The results have been compared with the estimated result via the maximum likelihood method. The result revealed that the Bayesian approach behaves similarly to the maximum likelihood method when the sample size is small. Nevertheless, in all cases for both methods, the RMSE and MAE decrease as the sample size increases. Finally, applications of the proposed model to the insurance claim data set have been presented.

The answer to how to stop economic growth must be political rather than economic. Economic growth made by men has an impetus which can only be stopped by a deliberate choice. It takes national and international decisions to stop it. In order to organize a moratorium on economic growth (which eventually must lead to a stop on growth) I suggest to create blocks of nations in the world. The European Union can function as a model for such a block. The E.U. is on its way of becoming a supra-national government which was created to ensure a level playing field for its members. Now it is meant to create economic growth for its members, in the future its administration should be used to stop it. Blocks should agree on the targets to reach a durable economy. Globally or between certain more advanced blocks a date should be set to stop economic growth after that date. Each block should implement the goals to reach a durable economy and prevent products reaching its market that violate the goals of durability. Blocks in developing countries cannot be expected to stop economic growth. They need that growth for two reasons. Eventually they must reach the level of existence in the more advanced block and secondly they must have the time to improve the standard for durability of their products. They need the aid of the developed countries to reach a higher but also more durable level of production, but this aid comes with a quid pro quo, In the meantime they must do their utmost to stop wars in their regions and conduct a responsible population-policy to reduce the growth of their population and let it reduce on the long term.

The global agricultural supply chain grapples with inherent challenges, including opacity, inefficiency, and ethical concerns, necessitating innovative solutions, particularly within Indian Agriculture Supply Chain Management. Despite these challenges, a notable research gap emerges due to the limited exploration of adoption factors specific to the Indian agricultural context. To bridge this gap, a comprehensive investigation is initiated to delve into the nuanced dynamics of blockchain technology adoption in the Indian agricultural supply chain. The primary aim of this study is to provide insights into these adoption dynamics, employing a three-stage methodology. Starting with an extensive literature review to identify key adoption factors, the study then distributed a well-crafted questionnaire to 200 respondents, yielding 150 complete and analyzable responses. The chosen methodologies, including a one-sample t-test and exploratory factor analysis, allow for a quantitative assessment of the significance of various factors. The study's findings reveal crucial dimensions influencing blockchain adoption, such as perceived benefits, ease of use, trust, efficiency, ethical considerations, data security, integrity, regulatory compliance, and collaboration and stakeholder engagement, providing a comprehensive understanding of the adoption landscape. In conclusion, this research significantly contributes to comprehending the nuanced adoption dynamics of blockchain technology in the Indian agricultural supply chain, supported by a substantial sample size and robust methodological choices. The implications extend to stakeholders navigating the evolving agricultural supply chain, offering valuable insights for future research, policy considerations, and practical strategies, with a central focus on fostering transparency, efficiency, and ethical standards to address global agricultural supply chain challenges.

The diplomatic relations between Azerbaijan and Pakistan have undergone significant development since the late 1990s. Despite some studies focusing on diplomatic and political relations, the economic dimension of this partnership has not been systematically covered. In this paper, a robust least squares (RLS) approach is used to model bilateral trade between the two countries and identify statistically significant determinants, including economic, institutional, and cultural factors, after analyzing the main economic and subsectoral trade dynamics of both countries. The results reveal that Azerbaijan's imports from Pakistan are significantly associated with the country's higher income and market size, while Pakistan's elevated exchange rate and trade costs hinder bilateral trade. In addition, Pakistan's rising manufacturing output increases exports to Azerbaijan but decreases imports from Azerbaijan. Among institutional determinants, government effectiveness, the trade freedom index (TFI), and political stability play significant roles in bilateral trade. Lastly, it was found that cultural proximity increases Pakistani exports to Azerbaijan but not imports from Azerbaijan. The analysis also indicates that domestic savings stimulate Pakistani exports. These findings underscore the complex nature of bilateral trade between Azerbaijan and Pakistan and highlight the need for institutional arrangements to harmonize trade flows and boost welfare gains from trade. The results may be of great importance to intergovernmental working groups, domestic policymakers, and businesses.

The dynamic patterns of technology adoption among firms clustered by size are investigated to assess the implications arising from the digital divide. Using data from the “Survey on the Use of Information and Communication Technologies in Enterprises (IUTICE)" dataset for 2003-2022, provided by the Portuguese Institute of Statistics, the research centers on three key variables – internet connectivity, website presence, and computer usage – which are examined across a spectrum of firms’ scales, shedding light on the evolving trends in technology adoption. Employing a combination of descriptive statistical analysis, trend assessment, and cross-sectional comparisons, this research shows noteworthy insights. Interestingly, the adoption rates for all three technology variables exhibit a consistent upward trajectory, indicative of a movement towards digitalization within the business landscape. Smaller firms have demonstrated notable strides, manifesting a reduction in the technology adoption disparity relative to their larger counterparts. The findings underscore the influential roles played by resource constraints and digital competencies in shaping technology adoption trajectories, and their correspondence with the Resource-Based View (RBV) framework underscores the role of organizational resources and capabilities on the digital divide. The ramifications extend beyond individual firms, resonating with the global scholarly discourse and advocating for equitable integration of technology. As firms, irrespective of size, grapple with the challenges posed by the digital era, this study provides deep insights that can guide the formulation of strategies aimed at cultivating an inclusive and technologically empowered business environment.

This paper provides a thorough review of the shifting landscape of economic analysis, spotlighting recent trends and predicting future paths. While traditional economic models remain key for interpreting economic activity, they are being supplemented by fresh methods and cross-disciplinary viewpoints. The increased attention to inequality studies, using advanced statistical techniques and unique data sources, underscores the growing emphasis on fairness and distribution within economic analysis. The incorporation of behavioral elements into economic models also expands our comprehension of economic decision-making and market results. Notably, the emergence of computational economics-integrating artificial intelligence (AI), big data, and machine learning into economic scrutiny-represents a major development. Often referred to as ’smart economics,’ this field employs technology to formulate, address complex economic dilemmas, and perceive economic activity in unconventional ways. Yet, the application of AI and machine learning in economics introduces new hurdles around data privacy, algorithmic bias, and the transparency of model outcomes. The impact of the digital revolution on economic analysis is significant, as the advent of computational economics and the surge of big data are transforming research techniques and policy implications. Concurrently, the advent of the circular economy indicates a radical shift in our perspective on economic sustainability, carrying considerable implications for environmental policy and business tactics.  In the future, it’s anticipated that these trends will further modify the realm of economic analysis, with AI and machine learning integration, emphasis on sustainability and fairness, and the influence of big data becoming more pronounced. As these changes take place, it’s imperative for researchers, policymakers, and practitioners to remain adaptable and flexible, prepared to capitalize on the opportunities and tackle the challenges these trends present.

Purpose: To realize the benefits a Quality Management System (QMS), an organization needs to effectively implement its principles. This includes embracing these principles within an enabling environment. Hence, organizational structure is a critical success factor for adopting quality management systems. This paper aims at understanding how the organizational structure impacts ISO 9001 QMS implementation and vise versa, besides exploring how quality management initiatives affect organizational resilience through parts. Design/methodology/approach: The research deploys a qualitative methodology, with an outsider-insider approach. 32 semi-structured interviews were conducted, plus one final reflective interview. Interview questions dealt with structural constructs: communication, employee engagement, employee empowerment, process/routine-orientation, multidisciplinarity, cross-functionality, expertise-utilization and change-readiness. The questions also dealt with how the organizational structure impacted ISO 9001 implementation and vice versa. Findings: The results show that ISO 9001 implementation was more successful and fruitful under process-orientation and to some degree under semi-process orientation, while it looked inconsistent under routine-orientation. This indicates a significant role played by the organizational structure when it comes to ISO 9001 implementation. More importantly, the results also demonstrate that ISO 9001 implementation managed to improve organizational resilience by consistently driving the organizational structure toward higher levels of process-orientation for process-oriented units, whereas it failed to realize such impact for routine-oriented units. Originality/value: This study is unique as it is the first - within the reviewed literature - to examine the moderating role of the organizational structure between the ISO 9001 standard and organizational resilience. It draws a roadmap for the successful realization of organizational resilience through quality management systems, considering organizational structure constructs.