Social enterprises are very common in Birmingham having the largest concentrations of social enterprises in the United Kingdom. With the emergence of the Covid-19 pandemic, the operations and management of social enterprises in Birmingham has been greatly affected. This study seeks to analyse the impact of the Covid-19 pandemic on the operations and funding of social enterprises in Birmingham UK. In order to achieve this, the study is going to carry out a qualitative methodology in order to analyse the impact Covid-19 has had on social enterprises. The research is going to select relevant stakeholders through a non-purposive sampling criteria identifying individuals who have direct interest in the functioning of social enterprises. The relevant stakeholders will be expected to respond to semi structured interviews that are structured to evoke responses relevant to this area of research. The research realized that Social enterprises in Birmingham are a critical player in the economy of UK with many individuals depending on the social enterprise industry. In addition to that, the study realised that the Covid-19 pandemic exposed social enterprises to various financial and market risks. Moreover, social enterprises were forced to make a change in their organizational structure through cost management changes and offering alternative services. However, the government came in support through provision of grants and funding to boost the social enterprise economy.

Understanding and evaluating urban investment environment is essential for effectively improving the efficiency of resource allocation between cities and promoting overall development of the regional economy. This paper takes 15 node cities on maritime Silk Road covered by the “Belt and Road” as the research object, establishes a dynamic evaluation index system for investment environment, and uses projection pursuit cluster to analyze and evaluate the investment environment of the cities. It is found that the investment environment potential of a city is directly related to the level of social development, economic development, and the degree of opening to the outside world. It is recommended that node cities should seize the important opportunity of the construction of the Maritime Silk Road, introduce world-wide human, financial and material resources to promote regional resources allocation and flow, and continuously improve and upgrade the investment environment quality.

This study measures the technical and scale efficiency of Micro and Small Enterprises (MSEs) and input slacks using Data Envelop Analysis (DEA) model and identifies the determinants of efficiencies of MSEs by employing ordinary least square (OLS) econometrics model. A sample of 375 randomly selected MESs are included in the study. The study found that the average technical and scale efficiency of MSEs are relatively low; technical efficiency averaged at 30 percent and 38.4 percent under constant returns to scale (CRS) and variable returns to scale (VRS) assumptions, respectively. Besides, the overall average scale efficiency score of MSEs was estimated at 77.8 percent. The highest mean technical and scale efficiencies were registered in the construction (71.8 percent) and manufacturing (85.7 percent) sectors, respectively. Whereas, the lowest technical and scale efficiency goes to urban agriculture sector and service sector, with 38.9 percent and 67.2 percent, respectively. The level of inputs, enterprise age and sector, human capital, labor productivity variables significantly affect relative technical efficiency level of MSEs with different directions while variables such as start-up capital, gender of the enterprise manager and availability of support from the government identified statistically not significant in determining the MSEs’ technical efficiency.

This study empirically investigates the effect of productive safety net programme (PSNP) on household food consumption and dietary diversity in Ethiopia. The study applied random effects with instrumental variable to estimate the effect of PSNP membership. The result of the study indicates that though PSNP membership improves household food consumption, it reduces household dietary diversity score. Household food consumption and dietary diversity are also significantly influenced by sex, age, education status of household head, household size, livestock ownership, distance to the nearest market and participation in non-farm activities. The findings of this study suggest that PSNP membership should be reinforced by building household awareness of the benefits of consuming a variety of foods. In addition, PSNP membership should be designed to endow the households to accumulate essential assets, especially livestock.

Understanding and evaluating urban investment environment is essential for effectively improving the efficiency of resource allocation between cities and promoting overall development of the regional economy. This paper takes 15 node cities on maritime Silk Road covered by the “Belt and Road” as the research object, establishes a dynamic evaluation index system for investment environment, and uses projection pursuit cluster to analyze and evaluate the investment environment of the cities. It is found that the investment environment potential of a city is directly related to the level of social development, economic development, and the degree of opening to the outside world. It is recommended that node cities should seize the important opportunity of the construction of the Maritime Silk Road, introduce world-wide human, financial and material resources to promote regional resources allocation and flow, and continuously improve and upgrade the investment environment quality.

This study aimed to examine trust in information provided by public authorities and financial measures put in place to address the impact of COVID-19. Using a cross-national approach among four Western countries; the United States of America, Norway, Australia, and the United Kingdom provides an analysis of responses related to trust and how they were associated with age group, gender, education level, employment status, size of place of residence, infection sta-tus, and social media use. When controlling for all included variables in logistic regression analyses, the likelihood of having trust in the public authorities’ information was higher for women, those with higher levels of education, and those living in urban areas. Being infected with the coronavirus, and spending more time daily on social media was associated with lower likelihood reporting trust in information. Although policies implemented to respond to eco-nomic concerns varied cross-nationally, higher age, identifying as female, being employed, liv-ing in a city, and lower levels of social media usage were associated with higher likelihood of trusting in the financial measures put in place to counteract the economic effects of COVID-19.

We investigate the effect of geopolitical risk on the returns of the Information Technology, Communication Services, and Consumer Staples sector firms within the S&P 500 index. We use the event study methodology and perform more than 17,000 regressions to provide empirical evidence at the sector level that geopolitical risk leads to different responses across these 3 sectors. The response of the Information Technology sector is negative for all event windows under study, except the one spanning 10 days prior to the geopolitical event and 10 days after. The Communication Services sector has positive returns as a result of geopolitical events for all event windows, except the one from the geopolitical event date and 5 days after. The Consumer Staples sector shows a negative impact on geopolitical risk for all event windows except the one from the geopolitical event date and 5 days after, demonstrating a negative correlation to the Communication Services sector.

The stress testing methodology should be implemented and applied to the entity's overall financial system at least annually, and if the organization operates in a volatile economy, it should be performed at least twice a year. Finally, managers should include regular training and development sessions for relevant employees of their organization to be fully informed and more informed and informed, considering the evolving science, theory and practicality of a discrete range of stress testing mechanisms that can be appropriately applied to overall financial framework and system of multiple financial institutions and banks. In addition, stress testing is essentially a methodology that collects and analyzes certain future macro-prudential and micro-prudential economic drivers and indicators, the primary purpose of which is to assess the future financial and economic well-being, level of growth and status quo of a financial institution, bank, organization, credit institution or economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. with the primary intention of assessing the future financial and economic well-being, level of growth and status quo of a group of financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically targeted and incorporated into a paper that substantially and broadly discussed and summarized the importance of the feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. with the primary intention of assessing the future financial and economic well-being, level of growth and status quo of a group of financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. the level of growth and status quo of the financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries. region. the level of growth and status quo of the financial institutions, banks, organizations, credit institutions or the economy or the nation as a whole. In addition, several of these reviews were specifically focused and incorporated into the paper, which substantially and broadly discussed and summarized the importance, feasibility and implementation and conclusions of different stress testing approaches for financial institutions and banks, especially in European and Chinese countries.

This study aims to determine the Implication of innovation, proactivity, risk-taking, artistic orientation, and financial literacy on creative economy businesses during the COVID-19 pandemic. This was conducted on 120 creative economy businessmen in Bandar Lampung City, which is a miniature of Indonesia with multiethnic cultures. The results showed innovation is not significant, but proactive attitude, artistic orientation, and financial literacy have a significant implication on the performance of creative economic businesses during the Covid-19 pandemic.

With the recent coronavirus pandemic (Covid-19) online sales of clothing retail have become a necessity to survive in the market. It is for this reason that the objective of the research was to know the purchase intention of clothing by young consumers through the online channel of small and micro companies (MiPyMe) located in the countries of Mexico, Colombia and Peru. To do this, using a structural equations model, it was intended to analyze the relationships between the variables trust, satisfaction, perceived value, quality of interaction and image in the electronic context as antecedent variables of online purchase intention, in accordance with the theoretical framework. 638 surveys were applied to young consumers in Mexico, Colombia and Peru. Sociodemographic characteristics included gender, age, country, and knowledge of a MiPyMe online clothing store. The results reveal that, of the total of young people surveyed, 62.7% stated that they did not know of any online clothing store of a MiPyMe. The contrasting of the hypotheses indicates that the quality of interaction directly and positively influences perceived value, that the image directly and positively influences the satisfaction and purchase intention of the consumer of the MiPyMe of Colombia, Mexico and Peru. These results may be useful for entrepreneurs in this business sector to rethink their online business strategies, as well as for the governments of these nations to promote this sector with training and specialized technical assistance.

For better export performance in cross border e-commerce, a contingency model integrates e-commerce into traditional export marketing strategy (EMS) with internal and external determinants of EMS. However, EMS of Micro, small, and medium-sized enterprises (MSMEs) is understudied. This study validates and modifies existing model for MSMEs. As a qualitative study, multiple sources of data including interviews, internal documents, and group discussions were used regarding business cases of entrepreneurs and supporting organizations in Mongolia and Korea. This research suggets contingency model for MSMEs with modified factors and different strategies in each factor. Specifically, intermal determinants are managerial capability, product competitiveness, and strategic marketing orientation. External determinants are export market competitivceness, export market infrastructure and entry barriers. EMS for MSMEs consists of the same factors with the original model but come up with different strategies. Theoretical and managerial implications were discussed.

This article explores the question of the rate of digital progress in the context of the labor market. Specific features of the current situation are indicated: temporality of socio-technological transformations, which is becoming less and less compatible with the harmonious development of man and society; the pace at which machines acquire intelligence; total devaluation of mental labor; unresolved issue of the role of man in the world of intelligent machines; the criticality of the problem of the labor market, due to its global nature, social significance and the rate of socio-technological changes. It is emphasized that these circumstances in the short term threaten the sustainable development of the global society, whose reactions to the transformation of technological and socio-economic infrastructure are significantly lagging behind. It is concluded that there is an urgent need to strengthen social responsibility, determined by the new ethics of relations between humans and machines with AI, supplemented by the primacy of the dignity of the social role of humans. The authors point out the urgent need to revise ideas about work as the main purpose of a person and about realization in the profession as the main factor that determines the self-esteem of an individual and his social status.

The human capital index is a multivariate variable used to measure the assessment of human resource productivity in the future. Human capital has a connection with economic development. Moreover, the study looks to analyses the relationship between Human Capital and Economic Growth indicators such as HCI and GDP. Human Capital relates to the development of individual skills to make them function more profitable for the national economy. The study was aimed at investigating the effect of population, the number of people engaged and the average annual hours worked by engaged persons on the human capital index. The analysis was in SPSS for the findings. Correlation tests were used for analysis. The study revealed that population, the number of people engaged and the average annual hours worked by engaged persons had a significant positive effect on the human capital index.

We follow the PRISMA extension for scoping reviews to review the emerging international body of empirical evidence on consumers’ attitudes and willingness to pay (WTP) for novel foods produced with New Plant Engineering Techniques (NPETs). NPETs include genome/gene editing, cisgenesis, intragenesis, RNA interference and others. These novel foods are often beneficial for the environment and human health and more sustainable under increasingly prevalent climate extremes. These techniques can also improve animal welfare and disease resistance when applied to animals. Despite these promising attributes, evidence suggests that many, but not all, consumers discount these novel foods relative to conventional ones. Our review sorts out findings to identify conditioning factors that can increase the acceptance of and WTP for these novel foods in a significant segment of consumers. International patterns of acceptance are identified. We also analyze how information and knowledge interact with consumer acceptance of these novel foods and technologies. Heterogeneity of consumers—across cultures and borders and in attitudes towards science and innovation—emerges as a key determinant of acceptance and WTP. Acceptance and WTP tend to increase when socially beneficial attributes—as opposed to producer-oriented cost-saving attributes—are generated by NPETs. NPET-improved foods are systematically less discounted than transgenic foods. Most of the valuation estimates are based on hypothetical experiments and surveys and await validation through revealed preferences in actual purchases in food retailing environments.

This study is the first to examine whether the performance of credit rating, one of the most important data-based decision-making of banks, can be improved by using banking system log data that is extensively accumulated inside the bank for system operation. This study uses the log data recorded for the mobile app system of Kakaobank, a leading internet bank used by more than 14 million people in Korea. After generating candidate variables from Kakaobank's vast log data, we develop a credit scoring model by utilizing variables with high information values. Consequently, the discrimination power of the new model compared to the credit bureau grades was significantly improved by 1.84% points based on the Kolmogorov–Smirnov statistics. Therefore, the results of this study imply that if a bank utilizes its log data that have already been extensively accumulated inside the bank, decision-making systems, including credit scoring, can be efficiently improved at a low cost.

The deep neural network - BERT model (Bidirectional Encoder Representations from Transformers) and the stocks cumulative abnormal return is used in this article to analyze the sentiment of financial texts. The proposed approach, unlike those used so far, does not require the creation of dictionaries, takes into account the broad context of words and their meaning in financial texts, eliminates the problem of ambiguity of words in various contexts, does not require manual labelling of data and is free from the subjective assessment of the researcher. The sentiment of financial texts in the meaning presented in this paper is directly related to the market reaction to the information contained in these texts. For texts belonging to one of the two classes (positive or negative) with the highest probability the BERT model gives the results of predictions with a precision level of 62.38% for the positive class and 55% for the negative class. The results at this level can be used in event study, market efficiency research, investment strategy development or support of investment analysts using fundamental analysis.

Background-The outbreak of COVID-19 pandemic has affected the global economy from its starting. Indian economy is also affected by the pandemic and experienced a lot of economic damages. India has become the global hotspot of COVID-19 during the second wave of the pandemic and recorded the second-highest position in terms of positivity rate after China. The present study attempts to analyze the economic issues that emerged in the first and second waves of the pandemic in India. Method/Approach-There is no econometric tools or analytical models used in the present study. This study attempts to evaluate the two research questions which are formed on the basis of some previous studies by various organizations and researchers. The research questions are as follow, First, what are the sectors those are primarily affected at the time of the first COVID-19 outbreak? Second, which economic issues and impacts emerged in the second wave of the pandemic? Results/ Findings-From the study, it is found that the second wave of COVID-19 is not much affected by the Indian economy. At this time, no nationwide lockdown was announced by the Government. But so, it was much severe in the time of the first wave of COVID-19. Many sectors were affected by the pandemic like agriculture, MSMEs, Tourism, etc., and these resulted in substantial unemployment problems in the economy. The study is trying to analyze these problems and concluding it with a few policy recommendations for the economy of India.

The aim of the paper is to identify the most likely factors that determine the demand for Renewa-ble Energy Consumption (R.E.C.) in European countries. Although in Europe a high environmen-tal awareness is omnipresent, countries differ in scope and share of R.E.C. due to historical ener-getic policies and dependencies, investments into renewable and traditional energetic sectors, R&D development, structural changes required by energetic policy change, and many other fac-tors. The study refers to a set of macroeconomic, institutional, and social factors affecting energetic renewable policy and R.E.C. in selected European countries in two points of time: i.e., before and after the Paris Agreement. The Bayesian Average Classical Estimates (BACE) is applied to indicate the most likely factors affecting R.E.C. in 2015 and 2018. The comparison of the results reveals that the G.D.P. level, nuclear and hydro energy consumption were the determinants significant in both analyzed years. Furthermore, it became clear that in 2015 the R.E.C. depended strongly on the energy consumption structure, while in 2018, the foreign direct investment and trade openness played their role in increasing renewable energy consumption. The direction of changes is positive and complies with sustainable development goals (S.D.G.s).

Financial Payment has evolved into mobile payment for easy access and convenience. Despite the benefits of mobile payment, the adoption rate is unsatisfactory worldwide. Therefore, understanding the customer's adoption intention factors is essential for both researchers and practitioners. This study examines mobile payment intention and actual use by adapting the integrated framework, which combines the Mobile Technology Acceptance Model and the Theory of Planned Behaviour with additional new constructs found to be related. The new model consists of 12 variables moderated by the individual's experience and is examined via a structured PLS equation mixed-mode methodology. Knowing mobile payment influence will shape the industry strategic decision and socially contribute to transforming society into a cashless society. This paper provides an opportunity to prove the relationship between technology variables and human behaviour concerning mobile payment adoption. In contrast, this study novelty adopted an integrated model that combines MTAM with the TPB.

The paper explains the dynamics of monetary aggregates in Russia with the help of country's trade balance, the creation of deposits by commercial banks and cross-border flows of rubles and (foreign) currency. The volumes of deposits and flows, in turn, depend on changes in the currency/ruble exchange rate and favorable external economic conditions. The model was estimated by the Kalman filter, the adequacy was confirmed by stimulation. Monthly money supply forecasts have an accuracy of ~ 1%. It was found that the volume of additional deposits created per month is ~ 300 billion RUB (this leads to real inflation of 9.5% per annum), money flows that are not related to payments for goods: rubles inflow from abroad ~ 100 billion RUB, currency goes abroad ~ 15 billion USD. With the growth / fall of the dollar exchange rate by 1 RUB per month, during the same month, the creation of additional ruble deposits and the arrival of rubles from outside decreases / increases by 0.114 billion USD. The increase of the Currency Reserve Assets of Russia is accompanied by going abroad ~ 5% of the increase.

This article has been developed to assess the economic feasibility of a roof-top photovoltaic installation of industrial self-consumption. Numerical models that enable an interested person to obtain the main expected parameters will be generated. To do this, a calculation methodology will be generated through which the reader, knowing the location of the facility and dimensions of the roof, will be able to calculate the maximum installable power, the main parameters related to production, the cost of the installation, and the LCOE of the plant. The use of actual costs will be facilitated in case they are known, but it will remain possible to apply the costs of the major equipment (modules, inverter, and structure) considered throughout the article. This developed calculation methodology will also allow a quick comparison of the forecasts of production, CAPEX, and LCOE of plants designed with different inclinations and different types of modules. Consequently, it will be especially useful for decision-making before developing the plant's basic engineering. Moreover, the calculations used for modeling the LCOE will be analyzed in depth. This analysis will allow evaluating how the different technical variables affect the profitability of a photovoltaic installation, such as the selected tilt, the location, the module's technology, or the available area.

A method for calibrating models of agricultural production and resource use presented by Howitt [1] for policy analysis is proposed to leverage multidisciplinary agricultural research at the National Center for Alluvial Aquifer Research (NCAAR). An illustrative example for Sunflower County, MS is presented to show how plot-level research can be extended to draw systemic region or basin wide implications. A hypothetical improvement in yields for dryland soybean varieties is incorporated to the model and shown to have a positive impact on aquifer outcomes and producer profits. The example illustrates that a change in one practice-crop combination can have system-wide impacts as evidenced by the change in acreages for all crops and practices.

This study focuses on a sample of Chinese listed companies from 2019 to 2020 to explore the relationships among corporate social responsibility, financial constraints, and financial performance. In addition, we discuss five factors affecting financial constraints. We also analyze the types of enterprises that can improve their financial performance by implementing corporate social responsibility keeping in mind the factors that lead to a high degree of financial constraint. The results indicate that: 1. The degree of financial constraints has a negative and significant impact on financial performance; 2. There is a reverse relationship between the degree of financial constraints and the effectiveness of corporate social responsibility measures; 3. Enterprises with high financial constraints (due to lower financial slack and revenue growth rates) can significantly improve their financial performance through the implementation of effective corporate social responsibility programs. 4. Enterprises with high financial constraints, caused by financial slack and revenue growth rate, can significantly improve their financial performance by implementing corporate social responsibility programs.

Distortion of financial statements is recognized as one of the most important issues in the field of accounting and auditing, which is also one of the most common issues today. In this regard, the present research was conducted, in which stock exchange information was used to investigate, predict, and model accounting distortions. For this purpose, financial performance, non-financial metrics, market-based metrics and commitment, or selection items were reviewed over a 6-year period. For collecting data of distorting companies, database of the Society of Certified Public Accountants in Iran was used and the information was analyzed using data mining methods (decision tree, neural networks, and Bayesian method). The results showed that analysis of financial statements҆ information has a high accuracy in determining and identifying the distorted financial statements. Using this information, it is possible to get better acquainted with the methods of document distortion and to take necessary measures in order to control and prevent administrative violations at national and international levels. Given frequent occurrence of these violations, artificial intelligence models can be used to identify these papers.

sustainability reporting, critical paradigm, upstream oil, and gasThe operating activities of the upstream oil and gas industry directly impact the environment. This industry faces significant social challenges and directly impacts the environment. Many Reputable international sustainability institutions organize sustainability awards. However, community conditions do not have a positive impact on sustainability practices. There are vari-ous serious violations related to sustainability, environmental pollution, multiple cases of cor-ruption, human rights, and other violations. In contrast, the companies receiving this award also received inspection findings of violations committed by The Audit Board of the Republic of In-donesia. This study uses critical discourse analysis that begins with phenomena related to viola-tions of sustainability reporting from scientific journals and other references using a systematic literature review approach over the last ten years. It produces a critical paradigm that is not val-ue-free, which is the basis for framing thought utilizing the theory of hegemony. The results of this study indicate that the upstream oil and gas industries are obliged to implement Corporate Social Responsibility (CSR) practices and Sustainability Reports (SR), has biased factors that are contrary to the sustainability concept and are not under the sustainability award based on evi-dence obtained from the stages of manuscript analysis with systematic literature review

Methods to handle uncertainty in economic evaluation have gained much attention in the literature and the cost-effectiveness acceptability curve (CEAC) is the most widely used method to summarize and present uncertainty associated with program costs and effects in cost-effectiveness analysis. Some researchers have emphasized the limitations of the CEAC for informing decision and policy makers as the CEAC is insensitive to radial shifts of the joint distribution of incremental costs and effects in the North-East and South-West quadrants of the cost-effective plane (CEP). Furthermore, it has been pointed out that the CEAC does not incorporate risk-aversion in valuing uncertain costs and effects. In the present article we show that the cost-effectiveness affordability curve (CEAFC) captures both dimensions of the joint distribution of incremental costs and effects on the CEP and is therefore sensitive to radial shifts of the joint distribution on the CEP. Furthermore, the CEAFC also informs about the budget impact of a new intervention as it estimates the joint probability an intervention is both affordable and cost-effective. Moreover, we show that the cost-effectiveness risk-aversion curve (CERAC) allows to incorporate risk-aversion into the analysis and can therefore be used to inform decision-makers who are risk-averse. We use data from a published cost-effectiveness model of palbociclib in addition to letrozole versus letrozole alone for the treatment of oestrogen-receptor positive, HER-2 negative, advanced breast cancer to demonstrate the differences between CEAC, CEAFC and CERAC and show how these can jointly be used to inform decision and policy makers.

We review the emerging international body of evidence on attitudes and willingness to pay (WTP) for novel foods produced with New Plant Engineering Techniques (NPETs). NPETs include genome/gene editing, cisgenesis, intragenesis, RNA interference and others. These novel foods are often beneficial for the environment and human health and more sustainable under increasingly prevalent climate extremes. These techniques can also improve animal welfare and disease resistance when applied to animals. Despite these promising attributes, evidence suggests that many, but not all consumers, discount these novel foods relative to conventional ones. Our systematic review sorts out findings to identify conditioning factors which can increase the acceptance of and WTP for these novel foods in a significant segment of consumers. International patterns of acceptance are identified. We also analyze how information and knowledge interact with consumer acceptance of these novel foods and technologies. Heterogeneity of consumers across cultures and borders, and in attitudes towards science and innovation emerges as key determinants of acceptance and WTP. Acceptance and WTP tend to increase when beneficial attributes—as opposed to producer-oriented cost-saving attributes—are generated by NPETs. NPETs improved foods are systematically less discounted than transgenic foods. Most of the valuation elicitations are based on hypothetical experiments and surveys and await validation through revealed preferences in actual purchases in food retailing environments.

Forest enterprise has been identified as a means of generating income among people; plays a vital role in enhancing the quality of life of forest-dependent people. Despite the opportunities timber marketing offers the people, the disparities in the income generation of the marketers in the Bodija sawn wood Market and the effect of socio-economic factors on income generation of the marketers is not well understood. This study was conducted to assess the socio-economic determinants of contributions of timber marketing to the income of timber merchants in Bodija sawn-wood Market. One hundred structured questionnaires were administered randomly in five zones of the sawn wood Market to obtain information on the socio-economic background of the sawn wood marketers and the contribution of timber trade to their incomes. The result indicated that 99.0% of the respondents were male while females constituted 1.00%. Seventy-five percent of the marketers had post-primary education and 25% had primary education. Two percent of the marketers had below 10 years of marketing experience, twenty-six percent had between 11 and 20 years, 57.00% had between 21 and 30 years, and 15.00% had more than 30years experience. Fifty-eight percent of the respondents earned between ₦10000-₦60000 (1US$ = 360.00) from timber marketing, thirty-one percent earned between ₦60001 and ₦110000, 7% earned between ₦110001 and ₦160000, while 4% earned above ₦160000 per month. Chi-square analysis of the socio-economic characteristics of the respondents and income generation at α level of 0.05 indicated that ethnicity (0.001) and years of experience (0.009) significantly influenced income while the level of education (0.101), age (0.122), and religion (0.745) had no significant influence on the incomes of marketers. Experience is an important factor in sawn wood marketing and a major determinant of the contribution of timber marketing to the income of timber marketers in Bodija sawn wood Market.

Blockchain is a path-breaking paradigm, and cryptocurrencies are one of the main application areas of Blockchain technology. Bitcoin leads the cryptocurrency markets, both in terms of market capitalization and in scientific interest. In this paper, we performed a comprehensive bibliometric study of the Bitcoin-related literature. Using the Scopus database, we created a sample that comprises 4495 documents written in the 2011–2020 period. Furthermore, we provided insights about dimensions such as the change in the number of publications over the course of years, the main research areas, types of published documents, most important platforms and sources of Bitcoin publications, highly cited studies, productive authors, author’s countries, and finally main funders of Bitcoin-related research. Lastly, our bibliometric study manifests the current state and future path of Bitcoin literature from distinct perspectives.

The purpose of this study is to examine the relationship between the institutional investors which can affect financial performance for corporate sustainability on the income smoothing. Therefore, this study focus on the connection between the nature of stock rights and income smoothing in China. For this study, hypotheses were established on the relationship each state-controlled companies, income smoothing, and information equilibrium of individual investors, and empirical analysis was conducted through related variables. The analysis results are summarized in three categories as follows. First, this research finds that state-controlled firms (CONTs) prefer income smoothing activities compared to non-state-controlled firms for the long-term sustainable development of firms using data from 2011 to 2019. Second, this study found out that Institutional investors support the behavior of CONTs to smooth their earnings because this behavior is seen as an attempt by CONTs to convey valuable private information to other investors. Third, we was able to discover that institutional investors' monitoring effect is predominantly driven by pressure-resistant institutional investors. This research complements the lack of empirical research on income smoothing and enable to give a guideline that the type of stock rights is a critical key determinant of participation in income smoothing activities for stable growth and sustainability in the future.

Semantic rules link purely theoretical terms like “price” and “electron” to things we can measure. Without them, theories cannot be tested empirically. When inappropriate, they produce false rejections. Economists routinely ignore semantic rules. Empirical journal articles essentially never mention them. More to the point, the conventional tests that reject the Law of One Price and Purchasing Power Parity never consider them. As a result, those rejections are unwarranted because such tests use inappropriate semantic rules. Both theories should be restored to not rejected and then retested using the more appropriate semantic rules described here. By using appropriate semantic rules, this paper is able to combine Covered Interest Parity and Purchasing Power Parity into a single theory that links auction markets for financial assets and commodities to auction markets for exchange rates. Using appropriate semantic rules for both theories also explains several puzzles in open economy macroeconomics and opens up broad new vistas for research.

We review the emerging international body of evidence on attitudes and willingness to pay (WTP) for novel foods produced with New Plant Engineering Techniques (NPETs). NPETs include genome/gene editing, cisgenesis, intragenesis, RNA interference and others. These novel foods are often beneficial for the environment and human health and more sustainable under increasingly prevalent climate extremes. These techniques can also improve animal welfare and disease resistance when applied to animals. Despite these promising attributes, evidence suggests that many, but not all consumers, discount these novel foods relative to conventional ones. Our systematic review sorts out findings to identify conditioning factors which can increase the acceptance of and WTP for these novel foods in a significant segment of consumers. International patterns of acceptance are identified. We also analyze how information and knowledge interact with consumer acceptance of these novel foods and technologies. Heterogeneity of consumers across cultures and borders, and in attitudes towards science and innovation emerges as key determinants of acceptance and WTP. Acceptance and WTP tend to increase when beneficial attributes—as opposed to producer-oriented cost-saving attributes—are generated by NPETs. NPETs improved foods are systematically less discounted than transgenic foods. Most of the valuation elicitations are based on hypothetical experiments and surveys and await validation through revealed preferences in actual purchases in food retailing environments.

The business practices and the vast academic research on the field have shown that even in the years of the great economic recession, there CSR and Ethics in business environment are still on the spotlight. The current study is conducted in Greece and is a cross-sector analysis. The study aims to evaluate if the concept of Carroll’s pyramid (1991) is still applied nowadays. This model expresses the business priorities, admitting that the rational business prioritizes profit as the base of the pyramid, followed by a legal way of operating, followed by ethical and philanthropic responsibilities. However, the growing interest on CSR and ethical issues may set this model on question. Baden (2016) has developed a critical evaluation that showing that the priorities have been changed. We employ a similar methodology to evaluate these priorities within the Greek business environment. A sample of 950 participants has been employed. The sample is consisted of various business hierarchy employees, from various Greek cities. The results show that despite the bad economic situation of the country, the economic responsibilities are not ranked on highest position: legal and ethical responsibilities are prioritized against economic responsibilities. These results confirm the findings of Baden (2016) and contribute on the relevant literature considering the necessity of CSR and Ethical issues in business environment nowadays.

The analysis and measurement of poverty is a crucial issue in the field of social science. Poverty is a multidimensional notion that can be measured using composite indicators relevant to synthesizing statistical indicators. Subjective choices could, however, affect these indicators. We propose interval-based composite indicators to avoid the problem, enabling us in this context to obtain robust and reliable measures. Based on a relevant conceptual model of poverty we have identified, we will consider all the various factors identified. Then, considering a different random configuration of the various factors, we will compute a different composite indicator. We can obtain a different interval for each region based on the distinct factor choices on the different assumptions for constructing the composite indicator. So we will create an interval-based composite indicator based on the results obtained by the Monte-Carlo simulation of all the different assumptions. The different intervals can be compared, and various rankings for poverty can be obtained. For their parameters, such as center, minimum, maximum, and range, the poverty interval composite indicator can be considered and compared. The results demonstrate a relevant and consistent measurement of the indicator and the shadow sector's relevant impact on the final measures.

The pharmaceutical industry is facing the pressure of a global economy, loss of value in local markets and the highly intense innovation that characterizes this sector. This has a heavy impact, particularly in smaller economies. With this investigation, we intend to identify the determinants of internationalization as levers for sustainability in the pharmaceutical export sector of a small economy. Data was collected from a sample representing 63% of the total universe, Portuguese pharmaceutical organizations with exporting activity. Contextualization of the sector and a bibliographic review were previously carried out, which laid the groundwork for the empirical framework. This study revealed a deeply internationalized sector conditioned by a few shortcomings, namely a certain lack of sustainable competitive advantages, relatively low investment in research and development (R&D), insufficient innovation in internationalization strategies as well as scarce institutional support. Our findings may help pave the way for a more complete understanding of the dynamics of internationalization in highly competitive sectors.

This study examined the relationship between financial sector liberalization and agricultural sector output in Nigeria using annual data spanning the period 1986-2020. Specifically, the objectives of the study are to examine the relationship between lending rate, exchange rate, commercial bank credit to agriculture, inflation rate and agricultural sector output in Nigeria. Ex-post facto research design was employed and the annual time series data were collated from Central Bank of Nigeria (CBN) Statistical Bulletin. The econometrics methods of unit root, co-integration and error correction mechanism were used for the analyses. The outcome of the ADF unit root test show that the variables were stationary. Also the co-integration result showed that there exist co-integration amongst the variables in the model. The results from Error Correction Model indicates that lending rate and inflation rate have a negative relationship on agricultural sector output while exchange rate and commercial bank credit to agriculture have positive relationship on agricultural sector output. Based on these results, this study recommends that government and policy makers in Nigerian should initial policies that will boost investments in the agricultural sector through direct provision of credits to agriculturist and banks should also lend at a very low and subsidized interest rate to enable farmers’ access agricultural loans that will boost agricultural productivity in the economy.

The Capital Asset Pricing Model is a widely applied model to describe risky markets and to deduce their systematic risk. Its estimation, therefore, remains an important task in Econo-financial studies. Empirically, it focuses on the impact of return interval on the betas. Existing studies somehow turn around the same idea of measuring the value of the beta according to the uniform intervals of time during a fixed period. However, it is noticed easily, and especially in the last decade that many factors such as socio-political, and Econo-environmental ones have led to a perturbation in the timeline of the worldwide development, and especially in countries and regions having political changes. This led us to introduce a new idea of risk estimation taking into account the non-uniform changes in markets by introducing a non-uniform wavelet analysis. We aim to explain the Econo-political situation of Arab spring countries and the effect of the revolutions on the market beta. The main novelty is firstly the construction of a dynamic backward-forward model for missing data, and next the application of random non-uniform wavelets. The proposed procedure will be acted empirically on a sample corresponding to TUNINDEX stock as a representative index of the Tunisian market actively traded over the period January 14, 2016, to January 13, 2021. The chosen 5-years period is important as it constitutes the first 5-years-after the revolution and depends strongly on the Socio-Econo-political stability in the revolutionary countries.

During the last two decades, energy poverty has captured a growing attention of researchers and policymakers due to its strong association with economic poverty and poor economic performance. This study uses a broad set of macro level indicators and makes the first attempt to measure energy poverty and its impact on economic growth of Pakistan over the period 1990 to 2017. In particular, our energy poverty indicator considers four main dimensions of energy poverty, namely, energy services, clean energy, energy governance and energy affordability. Our main results show that though the overall energy poverty has reduced in Pakistan during the selected sample period, the country shows an increasing dependence on polluted energy supply in order to meet its growing demand of energy. In second stage of the investigation, we test the neoclassical growth theory where we incorporate energy poverty along with human capital as source of economic growth. Our cointegration results reveal a strong relationship between energy poverty and economic growth that is also dynamically stable in short run. These strong negative linkages between energy poverty with economic growth for the sample economy complement the previous literature on the subject.

The bivalve mollusk, Anadara tuberculosa (Black Shell, in Spanish Concha prieta, "CP"), is found on America's Pacific coast, where it is harvested for subsistence and commercial markets. This paper aims to diagnose the performance of the black shell's value chain. We also identify several challenges that must be addressed to improve the sustainability of the black shell fishery in Ecuador. The descriptive methodology was quantitative, with a non-experimental, field, cross-sectional, and ex post facto design. Similar questionnaires were designed, validated, and applied to each link in the production chain to collect information. The performance of the value chain was diagnosed in the dimensions of productivity, competitiveness, and quality of life, reaching a 75.1% index, a result that indicates that the value chain has a moderate to good performance level. However, the value chain can be improved if the following challenges are met: 1) Restoration of the mangrove ecosystem, 2) Promotion of low-intensity shellfish aquaculture, 3) Good sanitary management and purification, 4) Promotion of value-focused ventures, 5) Strengthening of organizations and agreements for the use and custody of mangroves, and 6) Strengthening of institutions that contribute to the advancement of these challenges.

This document evaluates the impact of computer use on wages in Colombia in 2018. For this analysis, a Propensity Score Matching model is used to evaluate the impact of the use of learning technologies on the wages and years of education of Colombians, based on the 2018 quality of life survey. The results show that the use of the computer, laptop, tablet, internet, transferred files, Excel and radio for learning have a positive impact on the wages of Colombians. This research allows a better understanding of the technological effects on wages and provides information for the design of public policies in the development of technological skills.

FinTech has been in the focus of the discussion for quite some time. However, the market share of FinTech companies is still relatively small in compared to more traditional financial services. The purpose of this paper is to analyse the status quo, current developments and challenges ahead for the Latvian FinTech sector. We combine three analyses: the political and legal, the economic, the social and the technological environment (PEST) analysis, an analysis of the size and performance of FinTech companies during the last 10 years, and a survey among FinTech companies. We find that the current status of regulation is one of the main obstacles to FinTech development, because it does not sufficiently consider FinTech-specific aspects. Problems in attracting skilled workforce, and an environment that is not very supportive of new developments in finance are further challenges and might explain at least part of the growth and performance difficulties. A revision, modernization and harmonization of regulation is essential to create a level playing field for all market participants: FinTech companies, traditional financial service providers and those originally traditional players that are integrating FinTech solutions in their business model. Further efforts are also required to foster the Latvia’s attractiveness for skilled workforce. We hope that this study helps increase the visibility of Latvian FinTech and contributes to the development of the new Latvian FinTech strategy.

Any effort to combat corruption can benefit from an examination of past and projected worldwide trends. In this paper, we forecast the level of corruption in countries by integrating an artificial neural network modeling and time series analysis. The data were obtained from 113 countries from 2007 to 2017. The study is carried out at two levels: (a) global level where all countries are considered as a monolithic group; and (b) cluster level, where countries are placed into groups based on their development-related attributes. For each cluster, we use the findings from our previous study on the cluster analysis of global corruption using machine learning methods that identified the four most influential corruption factors, and we use those as independent variables. Then, using the identified influential factors, we forecast the level of corruption in each cluster using a nonlinear autoregressive recurrent neural network with exogenous inputs (NARX), an artificial neural network technique. The NARX models were developed for each cluster, with the objective function in terms of the Corruption Perceptions Index (CPI). For each model, the optimal neural network is determined by finetuning the hyperparameters. The analysis was repeated for all countries as a single group. The accuracy of the models is assessed by comparing the mean square errors (MSE) of the time series models. The results suggest that the NARX artificial neural network technique yields reliable future values of CPI globally or for each cluster of countries. This can assist policymakers and organizations in assessing the expected efficacies of their current or future corruption control policies from a global perspective as well as for groups of countries.

Since its adoption in September 2015, the 2030 Agenda has laid the foundations for a model of shared prosperity for a sustainable world. We are going through a complicated pandemic that shows profound inequalities affecting our economies, health, and quality of life. For this reason, our aim in this work is to make known the state of the art of scientific research related to inequality, poverty, and climate change and to propose lines of improvement that can contribute to achieving 3 of the 17 SDGs (End poverty-SDG 1-, Reduce inequality-SDG 10-, and Climate action -SDG 13-), proposed in the 2030 Agenda. To do so, we have used a systematic literature review methodology. The results show that poverty, inequality and climate change is a subject that has been little studied and articulated by researchers, with significant differences between the different areas studied. Topics related to sustainability and economics are those with the highest number of publications (51.7%). The rest are distributed among the 12 existing departments. Another relevant finding is that the effects of climate change are more pressing for more vulnerable populations, including impoverished women from rural areas and children from underdeveloped countries. This is a gender and social inequality that has been little addressed in climate change studies. Food security and energy poverty is another under-exploited aspect in this area. According to the results obtained in this work, we consider that the circular economy could improve these indicators, constituting a line of future research. Thus, one of its main objectives is to eliminate negative externalities, specifically existing social inequalities within the current linear economy model.

Historical legacy of Eastern European and Balkans’ health systems was mutually interdependent and shaped by local socioeconomic circumstances. Three distinctive systems of risk sharing and health financing to develop since the late XIX century were the Bismarck, Beveridge, and Semashko systems. Modern day healthcare systems in these countries are challenged by population ageing, accelerated innovation in medical technology, growing purchasing power and rising demand for healthcare services. Supply side changes contribute to demand side efficiency bottlenecks in financing, driving the costs of the already expensive medical care up. All of the nations have a large share of citizens experiencing difficulty with affordability and access to medical care, particularly in rural and remote areas. Network of Health technology assessment agencies have mushroomed over the past three decades. Principles of health economics theory and cost-effective resource allocation are slowly gaining ground in governing authorities’ mindset and decision-making process. For many years to come, pharmaceuticals and medical services will remain dependent on out-of-pocket spending. Currently accelerating and spreading 4.0 Industrial Revolution, together with the Belt and Road Initiative, are likely to substantially impact the further economic development of this vast region. Post-Pandemic ‘Green’ Recovery strategies adopted by many of the Eastern European governments shall also make this transition towards sustainable development more difficult and challenging given the large dependency of all these economies upon traditional carbon fuels.

This study aims to identify the COVID-19 impact on the green banking activities including green financing of banks and non-bank financial institutions (NBFIs) during the pandemic. Besides, this study also reveals the in-house environmental management of banks and NBFIs during the COVID-19 outbreak. To analyze the impact of the pandemic on green banking activities, secondary data were obtained from the quarterly and annual reports of Bangladesh Bank (BB) on green banking activities, annual reports and websites of the sample banks and NBFIs in Bangladesh for the period 2020–2019. The study utilized descriptive statistics, relative percentage changes, and varying tables and graphs to analyze the obtained secondary data. Consequently, the empirical findings revealed that, compared to the pre-pandemic period, banks’ total green financing rose by 7.26% during the pandemic, while total green financing of NBFIs plummeted by 18.53% during the same period. In addition, the category-wise results indicate that green financing of the private commercial banks (PCBs) decreased by 11% during the COVID-19 pandemic, contrasting the 56.54% increase witnessed by the state-owned commercial banks (SOCBs) during the same period. Interestingly, our findings showed that green financing of foreign-owned commercial banks (FCBs) during the pandemic increased by 78.69% in 2020 compared to 2019. During the same period, BB refinancing scheme for green products/initiatives of banks and NBFIs grew by 76.97%. The results further showed that the PCBs and FCBs’ in-house environmental management expanded during the outbreak except for the number of solar-powered ATM booths, which dropped by 68.25% for PCBs and 9.09% for FCBs. On the other hand, SOCBs’ in-house environmental management grew during the pandemic. Furthermore, the results indicate that the Bangladeshi banks’ automation towards green banking were satisfactory during the pandemic. Therefore, major policy implications for the green economic recovery of the government, BB, and mangers of the banks and financial institutions in emerging economies like Bangladesh were discussed.

This study aims to summarize the literature on sustainable global supply chain management so that researchers and practitioners can see the trends in the area in a single place. Systematic literature review (SLR) or Content analysis is used as a methodology of this literature review, studies that are published within the time frame of 2010 to 2020 are included in this literature. Dimensions to analyze each article includes; year of publications, methodology of research, data collection type, unit of analysis, industry, a country in which data is being collected, respondents’ types, the theory that is used in the study, dimensions of the sustainability and finally the purpose of study either it is to test the already existing theory or building up a new theory. I found that sustainable global supply chain management is an emerging field and there is potential in the area for researchers to explore the area.

Green credit policy as an important tool to guide China's sustainable economic development, how to effectively play the function of capital deployment and improve the efficiency of industrial green innovation is an important issue facing the construction of ecological civilization. This paper uses China's Green Credit Guideline introduced in 2012 as a quasi-natural experiment , based on relevant panel data of industries from 2007 to 2018, uses the Super-SBM model including non-expected output to measure the green innovation efficiency of 35 industries in China, and constructs the PSM-DID model to explore how green credit policy impact on the green innovation efficiency of heavily polluted industries, the results show that : green credit policy significantly contributes to green innovation efficiency of heavily polluted industries with a lag. Further study finds that green credit policy pushes heavily polluted industries to improve green innovation efficiency by increasing financing cost and R&D investment; meanwhile, the heterogeneity test shows that the higher the state-owned share of industry, the greater the promoted effect of green credit policy on green innovation efficiency of heavily polluted industries. Finally, in order to accelerate the implementation of green credit policy and promote the green innovation efficiency of heavily polluted industries, relevant countermeasures are proposed from three aspects: banks, enterprises and government.

The main obstacle affecting the natural and herbal products industry is the infringement of trade patents. This resulted in losing the opportunity to compete with others in this business. Creating additional value to this business is, therefore, a way of leading to patenting for trade protection for entrepreneurs. This study was conducted to develop the structural equation modeling of guidelines for creating additional value for Thai herbs to support trade patent. The study comprises a mixed method with three parts. In the first part, data comes from interviews with selected 9 specialists. The second part was supported by interviews to create the questionnaire and distributed it to 500 entrepreneurs, the next step was the data analysis using structural equation modeling (SEM). The third part used data from the SEM model to discussion focused on developing the conceptual model by 7 experts. The analysis of the developed model passed the criteria for evaluating consistency and empirical data. All hypotheses proposed in this study were supported, the findings revealed that all factors had a direct effect at a statistically significant level of 0.001. Furthermore, this investigation allows knowing the Brand Identity factor were practically important for creating value of Thai herbs leading to patent protection.

The main aim of sustainable development is to ensure an intelligible and long-lasting balance between the economy, society, and the environment. Sustainable tourism could only be successful if the inter-relationships between all three dimensions are accepted. In the limited number of research analyses, the focus of the research is on competition between tourist countries and destinations. This study has used Game theory to analyze the competition applies time-series data in selected neighboring countries measure of a VAR-based spillover index, developed by [1] to investigate the time-varying relationship between tourism and Gross Domestic Product. Each country analyzed Vector Error Correction (VEC) and Granger analysis to explore the causal short and long-term tourism and use a sample that spans from 1997 to 2019. From the main results of Cholesky, the total spillover index is 59.0% between Russia and Mongolia which suggests a moderate interdependence among the four variables. Findings indicate that neither China nor Mongolia have a short-run influence on tourism development. China's inbound tourism is affected in the long run by Mongolia's inbound tourism but not vice versa can be explained by the fact that the number of tourists visiting Mongolia would include China in their travels.

Tree resin, which in addition to its widespread use in industry is also a macroergic component which has not yet been used for energy purposes. The main goal of this work is to determine the energy content of the resin of spruce, pine and larch and wood components – pulp and turpentine. The combustion heats of resin (MJ/kg) from each timber was determined calorimetrically. The energy values of tree resin (>38.0 MJ.kg-1) were 2.2 and 2.4 times higher than that of bleached and unbleached cellulose, the highest value was recorded for the turpentine (>39.0 MJ.kg-1). The best way of resin tapping is the America method, providing 5 kg resin ha-1 yr-1. The resin quantity tapped was raised at least 3 times applying stimulant, its production cost compared to other feedstocks was the cheapest. The tree resin can be applied as a good means to mitigate global warming and consequently dampen climate change. One tonne of tree resin burned instead of coal spares the atmosphere by 5.0 Mt CO2 since it is environmentally neutral. As resin heating values approach to the lower end of ones of liquid hydrocarbon fuels, greater efforts are needed to examine the most efficient energy use of resin.

The paper is a follow-up of a previous investigation and effort to develop the ontology of the smart city (Komninos, N., Bratsas, C., Kakderi, C., and Tsarchopoulos, P. "Smart city ontologies: Improving the effectiveness of smart city applications". Journal of Smart Cities, vol. 1(1), 1-17. https://www.komninos.eu/wp-content/uploads/2015/07/2015-Smart-City-Ontologies-Published.pdf). Since the publication of this article in 2015, research and literature on smart cities have evolved significantly, as have the technologies for digital spaces and applications that support city functions. These developments are reflected in the present form of the smart city ontology 2.0 we propose. It depicts the building blocks of the smart city ontology (technologies, structure, function, planning), and the object properties and data properties that connect structural blocks and classes. The aim of the SCO 2.0 is to provide a better understanding and description of the smart/intelligent city landscape; identify the main components and processes, the terms used to describe them, their definition and meaning; clarify key processes related to the integration of the different dimensions of the smart city, mainly the physical, social, and digital dimensions. The paper is accompanied by an owl file, developing the ontology through the editor Protégé.

The authors developed a wealth curve (bell curve) that can predict a group of individual’s wealth based on the crossover interaction effect of the average intelligence quotient (one's ability to perform, comprehend and learn) and emotional awareness (emotional ability to recognize and make sense of emotions). To move towards the right on the X-axis of the Kabir wealth curve (e.g. accumulate more wealth), individuals have to improve emotional awareness and choose a professional career path that lands higher income. Similarly, those facing social injustice can accumulate more wealth by improving emotional awareness, which will help them navigate challenging environments.

As one of the unique destinations in Iran, Abdanan Black Twin Lake attracts many tourists yearly. Among striking features is the presence of minerals, boiling springs, and its beautiful landscape. Human beings are willing to spend money on such natural resources. An economic valuation can be interfered constructively and positively in improving environmental policies. So, quantifying these benefits is of the utmost importance. The paper mainly estimated the tourists' willingness to pay and their recreational value using the contingent valuation method. Random sampling was conducted on 384 people using the two-dimensional double-choice questionnaire in spring 2019. In the Twin Lake Recreational Value Questionnaire, the main questions were devoted to the visitors' willingness to pay, with three bids of 0.07 $, 0.14 $, and 0.22$. Among 384 respondents, 304 (79%) were willing to pay for recreational use of the lake, and 80 respondents (21%) were not. The likelihood, the model's parameters were estimated. The findings indicated the average tourists' willingness to pay for recreational value was estimated at 0.09$ per visit and the recreational value of this lake for each household was estimated at 0.40$. The findings revealed the effect of education, household income, household size and tourists' willingness to pay was significant.

Growth benefits of high speed rail (HSR) for enterprises are not automatic, but require a buoyant local economy and a robust strategy. Against above background, main objectives of ex-ante case study have been to investigate local socio-economic and spatial impacts of proposed HSR project around Ahmedabad station area on Mumbai-Ahmedabad HSR corridor, analyze the opportunities and challenges of HSR development and draw policy implications. Qualitative research methodology has been used to elicit the perceptions and perspectives of randomly selected 43 small, medium and large enterprises. Data has been analyzed using descriptive statistics. The study reveals that HSR induced greater human interaction will activate local economy, improve business efficiency and generate employment. Frequent travels on business trips can influence enterprises decision to settle near HSR station for easy access and likely to promote realty development. The proposed HSR project should be developed in synergy with urban dynamics of cities in transition and metropolitan service cities. Poor public transport connectivity is likely to be a major challenge in improving HSR accessibility and enhancing overall impacts of HSR, which can be improved by developing an integrated urban transport system, for which cooperation of all stakeholders and coherence with firms’ strategies is essential.

Teacher burnout has been revealed to be one of the most common negative consequence of the COVID-19 pandemic The purpose of this study was to identify distinct psychological resources and burnout risk profiles of teachers and to examine their association with Kolb’s Educator Roles and the professional experience. Methods: The survey data were collected from 330 preschool and primary school (84 males, Mage = 38.3, SD = 9.14) teachers using a convenience sampling method. Results: The two-step cluster analysis revealed two distinct profiles. The first profile, ‘High psychological resources, no burnout risk’, was characterised by absent symptoms of burnout and increased levels of well-being, self-control, and positive emotionality. The second profile, ‘Moderate psychological resources, mild burnout’, was associated with medium levels of well-being, self-control and positive emotionality accompanied by mild burnout. Our findings highlighted that cluster 1 had a significantly higher score for the Facilitator role and cluster 2 for the Expert and Coach roles. In addition, teachers with less professional experience were more likely to belong to cluster 1, taking into account their good skills on digital literacy. Conclusions: These findings help to provide new insights into the explanation of teacher burnout and the design of intervention programmes.

Increasing the metacognitive abilities of chemistry students is an indisputable output of the teaching and learning process today. Collaborative problem based learning is a learning method that has been tested and proven to be applied, especially in Western countries in increasing the metacognitive abilities of students, but it is still very minimal applied in Asian countries, including Indonesia. Thus, this study was conducted to explore previous studies that examined collaborative problem-based learning in improving students' metacognitive abilities. The research design used in this study is a Systematic Literature Review with the requirements of the inclusion of articles on collaborative problem-based learning in improving the metacognitive abilities of chemistry students, accredited national and international publications between 2010 and 2020, full text, journal articles, and open access. The results of the exploration that were carried out found 102 articles, then the title and abstract were read into 20 articles, and 4 articles were read in full, which fulfilled all the stipulated inclusion requirements. The results of the systematic literature review conducted in this study provide empirical evidence of literacy that problem based learning improves the metacognitive abilities of chemistry students. However, most of research conducted still uses various instruments, which are not standardized and validated.

Diverse forms of artificial intelligence (AI in further text) are at the forefront of triggering digital security innovations, based on the threats that are arising in this post COVID world. On the one hand, companies are experiencing difficulty in dealing with security challenges with regard to a variety of issues ranging from system openness, decision making, quality control and web domain, just to mention a few. On the other hand, in the last decade, research has focused on security capabilities based on tools such as platform complacency, intelligent trees, modeling methods and outage management systems, in an effort to understanding the interplay between AI and those issues. The dependence on the emergence of AI in running industries and shaping the education, transports and health sectors is now well known in literature. AI is increasingly employed in managing data security across economic sectors. Thus, a literature review of AI and system secu-rity within the current digital society is opportune. This paper aims at identifying research trends in the field through a Systematic Bibliometric Literature Review (LRSB) of research on AI and system security. The review entails 77 articles published in Scopus® database, presenting up-to-date knowledge on the topic. The LRSB results were synthesized across current research subthemes. Findings are presented. The originality of the paper relies on its LRSB method, together with extant review of articles that have not been categorized so far. Implications for future re-search are suggested.

The growth of regularly generated data from many financial activities has significant implications for every corner of financial modeling. This study has investigated the utilization of these continuous growing data by a means of an automated process. The automated process can be developed by using Machine learning based techniques that analyze the data and gain experience from the underlying data. Different important domains of financial fields such as Credit card fraud detection, bankruptcy detection, loan default prediction, investment prediction, marketing and many other financial models can be modeled by implementing machine learning models. Among several machine learning based techniques, the use of parametric and non-parametric based methods are approached by this research. Two parametric models namely Logistic Regression, Gaussian Naive Bayes models and two non-parametric methods such as Random Forest, Decision Tree are implemented in this paper. All the mentioned models are developed and implemented in the field of Credit card fraud detection, bankruptcy detection, loan default prediction. In each of the aforementioned cases, the comparative study among the classification techniques is drawn and the best model is identified. The performance of each classifier on each considered domain is evaluated by various performance metrics such as accuracy, recall, precision, F1-score and mean squared error. In the credit card fraud detection model the decision tree classifier performs the best with an accuracy of 99.1% and, in the loan default prediction and bankruptcy detection model, the random forest classifier gives the best accuracy of 97% and 96.84% respectively.

Cross-border e-commerce is an opportunity for micro, small and medium sized enterprise (MSMEs) in developing countries. Based on a resource-based approach, this research studied how to support resource lacking enterprises with export marketing strategy. It dealt with actual business cases of Mongolian entrepreneurs trying to export Mongolian products to Korean market. Multiple source data including interviews, internal documents, and group discussions, were matched with theories to come up with strategies and validated by supporting organizations in Mongolia and Korea. The research suggests that MSMEs should rely on third party digital platforms rather than setting up their own. For product strtategy of the marketing mix, sellecting competitive product categories and supporting them adjusting to foreign markets and quality assurance is needed. For price strategy, loccally high priced products should use a price penetration strategy with a lower price compared to competing foreign products. For place strategy, supporting organizations should partner with exporters for collective delivery. For promotion strategy, they need to support the capacity of MSMEs enabling them to use digital marketing tools effectivly. These strategies were validated and adopted by supporting organizations in Monglia and Korea.

Supplier selection (SC) continues to be a crucial component in manufacturing procurement. Using the PLCC advantages generates revenue and lowers costs more than might be anticipated. Supplier selection (SC) product life cycle cost (SCPLCC) is an important consideration among corporations, SCPLCC problem has become associated with deciding how one supplier should be selected from possible alternatives. Past literature on this topic is limited. We try to close this gap in knowledge. In this study, we attempt to apply two types of goal programming, multiobjective linear programming and revised multichoice goal programming to develop a PLCC-based concept to solve the SCPLCC problem and construct a decision-making tool for application to a case of supply chain management in a Taiwanese light-emitting diode company in the high-tech industry. Our study main contribution Company managers can easily use the two approaches of the SCPLCC model with different parameters to solve SCPLCC model problems. Finally, we are comparing five models found RMCGP with weighted linear goal programming had an adequate effect for application to the PLCC concept for high-technology Company; this cloud makes company decision–makers focus on low PLCC and select a better supplier in sustainable supply chains development.

With increased participation in telework expected to continue, to support emerging hybrid work models in the aftermath of the Covid-19, it is important to consider the long-term impact this practice could have on sustainability outcomes. This paper describes a systematic review of 113 academic journal articles and identifies associations between telework and sustainability, explored by previous researchers. Those associations were categorized and discussed, based on their contributions to different United Nations Social Development Goals. Most of research was found to focus on countries classified as having a very high human development index status, and regions with a low, medium or high human development index, largely ignored. The SWOT matrix technique was used to illustrate the strengths and weaknesses identified in the current literature as well as threats and opportunities for future work. This can help to ensure policy coherence and that strategies to promote one outcome, such as economic productivity improvements, does not undermine another, such as improved health. Practical implications and potential research opportunities were identified across a range of SDG impact areas, including good health and well-being, gender equality, reduced inequality, climate mitigation, sustainable cities and resilient communities. On the whole, our impression is that increased rates of telework present an important opportunity to improve sustainability outcomes, however, it will be important that integrated and holistic policy is developed that mitigates key risks.

The Anthropocene has created a new cartography where various discursive levels are intertwined. It unites two fields of knowledge: geology and anthropology. In the 19th century, Romanticism challenged the separation between natural sciences and spirit sciences. With the Anthropocene a geological era is established, but with an epistemological dimension: environmental catastrophes are not a passive "object", they become an agent of social and political change. Images of the world (Weltbild) turn nature into an animated whole that challenges the dual vision: observer and observed. There is no nature without "observer", nor geology without anthropology. The Anthropocene modifies the foundations of our view of the world where we had excluded life. This is how concepts such as symbiogenesis, homeostasis, etc., which make visible and try to explain phenomena that are otherwise inexplicable. The Naturwissenschaft by J.W. Goethe is a point of support, with all these ideas that develop in the 20th century and anticipate the Anthropocene term of the 21th century. While the concepts of "belief" and "science" continue to be sharpened, rehabilitating "old quarrels" around anthropology, cosmology, theology, etc. The dignity of man is at stake.

Drawing on contextualization literature, this paper seeks to evaluate the impact of contextual theology from a Latin American perspective. Bevans' (2002) Praxis Model of contextual theology sets the conceptual framework used to evaluate the evangelical response to the sociopolitical crisis in Nicaragua. The case study provides an example of how Bevans’ Praxis Model can be applied by looking at the manner with which the evangelical and the catholic church have responded to the sociopolitical upheaval in Nicaragua. The literature on contextualization highlights how theologizing is inextricably tied to culture, that contextual theology is necessary to effectively communicate the truth of the Gospel in varying cultural contexts, and that the issues of syncretism and the plurality of theologies can be effectively addressed.

One of the key challenges of stock trading is the stock prices follow a random walk process, which is a special case of a stochastic process, and are highly sensitive to new information. A random walk process is difficult to predict in the short-term. Many linear process models that are being used to predict financial time series are structural models that provide an important decision boundary, albeit not adequately considering the correlation or causal effect of market sentiment on stock prices. This research seeks to increase the predictive capability of linear process models using the SPDR S\&P 500 ETF (SPY) and the CBOE Volatility (VIX) Index as a proxy for market sentiment. Three econometric models are considered to forecast SPY prices: (i) Auto-Regressive Integrated Moving Average (ARIMA), (ii) Generalized Auto Regressive Conditional Heteroskedasticity (GARCH), and (iii) Vector Autoregression (VAR). These models are integrated into two technical indicators, Bollinger Bands and Moving Average Convergence Divergence (MACD), focusing on forecast performance. The profitability of various algorithmic trading strategies is compared based on a combination of these two indicators. This research finds that linear process models that incorporate the VIX Index do not improve the performance of algorithmic trading strategies.

This paper empirically analyzes the relationship between digital inclusive finance and rural income, and demonstrates that digital inclusive finance plays a significant role in promoting rural income, based on the 2012-2018 panel data of 17 cities in Henan Province of China. Further dimensional research unveils that all of its breadth of coverage, depth of use and degree of digitization present significant positive correlation with rural income, and a robustness test was conducted through the sub-sample method. In addition, according to regression analysis on the influencing factors of digital inclusive finance through the Tobit model, the level of economic development, the Internet popularity rate and the urbanization rate have a positive effect on the development of digital inclusive finance in Henan, while the income gap between urban and rural areas and the degree of opening up have a negative effect. Finally, predicated on the analysis of the restrictive factors of Henan’s digital inclusive finance in increasing rural income, the paper puts forward specific policy proposals based on the native state quo.

The authors developed a wealth curve that can predict a group of individual’s wealth based on the crossover interaction effect of the average intelligence quotient (one's ability to perform, comprehend and learn) and emotional intelligence (emotional awareness and emotional ability to express and handle interpersonal relationships judiciously and empathically).

MIGAL – Galilee Research Institute is a regional R&D center in the northeast peripheral region of Israel. An internationally recognized applied research institute, MIGAL specializes in biotechnology and computational sciences, plant sciences, precision agriculture and environmental sciences, as well as food, nutrition and health. Most of MIGAL’s researchers serve as the core faculty at Tel Hai Academic College (TH). Despite the country’s small surface area, socioeconomic inequality in Israel is high by OECD standards, with wage differences between rich and poor regions reaching up to 400%. The aims of this study are to identify possible socioeconomic impacts of MIGAL–TH on the peripheral northeast’s development. We discuss the effects of academic research and institutions of higher education on mitigating differences between the center and periphery of the country. Data for MIGAL, TH and the northeastern peripheral region were collected from the yearly reports of the two institutions and the Israel Central Bureau of Statistics. MIGAL was found to serve as a link between research, academic teaching and socioeconomic development in the northeast periphery. Several variables related to this link and describing MIGAL–TH and northeastern periphery development were analyzed over time: MIGAL’s budget, total number of employees and number of employees with PhDs; number of TH graduate students; socioeconomic index (SEI) of the northeastern periphery and its position on the Israeli list of regional SEIs. The signs and significance levels of their trends indicate a potential socioeconomic impact of academic research and higher education on peripheral development in the northeast of the country. Research budgets and the creation of jobs for academics living in the region are just a few examples of this impact.

This study aimed to evaluate whether primary school classroom teachers reported changes in physical education teaching self-efficacy (SE-PE) and work engagement (WE) during the first COVID-19 wave. Six-hundred-twenty-two classroom teachers filled in an online questionnaire on SE-PE and WE, referring to before and during the lockdown, and on perceived digital competence. While controlling for perceived digital competence, a mixed between-within Repeated Measures Multivariate Analysis of Covariance (RM-MANCOVA) was performed, with a two-time (before vs. during the lockdown) and three age-categories (≤40 vs. 41-50 vs. ≥51 years) factorial design. The RM-MANCOVA revealed that perceived digital competence significantly adjusted teachers’ SE-PE and WE values (p<0.001). The analysis yielded a significant multivariate main effect by time (p< 0.001) and by time × age-categories (p=0.001). Follow-up univariate ANCOVA showed significant differences by time in teachers’ SE-PE (p<0.001) and WE (p < 0.001), with a reduction of both values from before to during the lockdown. A Bonferroni post hoc pairwise comparisons showed teachers’ SE-PE significantly decreased in all age categories (p<0.001). The present findings confirm the importance of promoting SE-PE among primary school teachers, regardless of the crisis due to the COVID-19 pandemic. Teachers’ self-efficacy and WE are essential to master the challenges of PE teaching.

As sustainability gains significance within Higher Education Institutions (HEIs) worldwide, the University of British Columbia (UBC) stands as one of the global champions of sustainability. In 2019, Times Higher Education ranked UBC as number one in the world for taking urgent action to combat climate change and its impacts and ranked one in Canada for making cities inclusive, safe, resilient, and sustainable. Over the years, UBC students have been instrumental to sustainability on the UBC campus by advocating for divestment, climate justice, and other sustainability commitments and projects in the university. Hence, this qualitative study examines students’ engagement with or their perception of the university’s sustainability programs and image. The study found that students acknowledged and commended the university’s sustainability efforts in teaching, research, providing sustainability-related opportunities for students, and in sustainability operations. However, students also addressed hesitation on the part of university administration in championing climate justice and bolder climate action. The conclusion is that continued support and engagement with students are critical for UBC to achieve its climate action plans and sustainability goals in general. The study contributes to the ongoing discourse on the influential role of young people and the youth climate movement in catalyzing ambitious global climate action at all levels.

The paper aims to illustrate the different roles that social sciences can play in the study of the energy transition. To this end, a scheme is developed that frames the relative position of the social sciences with respect to other disciplines (metaframe). Secondly, socialization is identified as a charismatic category capable of providing an original, typically sociological contribution to the complex and hesitant energy transition (masterframe)

People living in slums and other deprived areas in low- and middle-income country (LMIC) cities are under-represented in censuses, and subsequently in "top-down" gridded population estimates. Modelled gridded population data are a unique source of disaggregated population information to calculate local development indicators such as the Sustainable Development Goals (SDGs). This study evaluates if, and how, WorldPop-Global (WPG) -Unconstrained and -Constrained “top-down” datasets might be improved in a simulated realistic LMIC urban population by incorporating slum profile population counts into model training. We found that the WPG-Unconstrained model with or without slum training data grossly underestimated population in urban deprived areas while grossly overestimating population in rural areas. SDG 11.1.1, the percent of population living in slums, for example, was estimated to be 20% or less compared to a "true" value of 29.5%. The WPG-Constrained model, which included building auxiliary datasets, far more accurately estimated the population in all grid cells (including rural areas), and the inclusion of slum training data further improved estimates such that SDG 11.1.1 was estimated at 27.1% and 27.0%, respectively. Inclusion of building metrics and slum training data in “top-down” gridded population models can substantially improve grid cell-level accuracy in both urban and rural areas.

In this article we propose an application of humanitarian logistics theory to build a supportive framework for economic reactivation and pandemic management based on province vulnerability against COVID-19. The main research question is: which factors are related to COVID-19 mortality between Peruvian provinces? We conduct a spatial regression analysis to explore which factors determines the differences in COVID-19 cumulative mortality rates for 189 Peruvian provinces up to December 2020. The most vulnerable provinces are characterized by having low outcomes of long-run poverty and high population density. Low poverty means a high economic activity that leads to more deaths of COVID-19. There is a lack of supply of a set of relief goods defined as Pandemic Response and Recovery Supportive Goods and Services (PRRSGS). These goods must be delivered in order to mitigate the risk associated to COVID-19. A supportive framework for economic reactivation can be built based on regression results and a delivery strategy can be discussed according to the spatial patterns that we found for mortality rates.

This paper provides attempts to formalize Hayek’s theory of knowledge. It has been theoretically shown that exponential income distribution is a spontaneous order of the well-functioning market economy. We show that this theoretical result is supported by the empirical evidence from the United Kingdom and China. In particular, we empirically show how the income structure of China evolved towards an exponential distribution after the market-oriented economic reformation. Furthermore, we strictly prove that, if the income structure of an economy obeys an exponential distribution, the income summation over all households leads to an aggregate production function with Hicks-neutral-like technical progress, in which the technology factor is exactly equal to society’s information stock that is a result of combining all of decentralized decisions.

This paper summarizes the estimates of the total changes in sales, expenses, and income of participants of the horticulture research and extension programs at the Mississippi State University - Coastal Research and Extension Center for the past five years. Major items outline the estimation procedures for the past five years. The average annual values were used in estimating the total economic impacts of added gross sales, expenses, and incomes of participants in horticulture events. The cumulative total impacts reach $8.7 million in sales, 76 jobs, $1.4 million in labor income, $2.4 million in value-added, and $0.4 million in local, state, and federal taxes. In addition, the total willingness to pay for the horticulture program by the adult participants reached $1.8 million. In comparison, the annual public spending on the horticulture program averaged $1.4 million, creating additional substantial economic impacts to the region.

The rapid spread of COVID-19 worldwide was accompanied by intense fears, confusion, worries, anger and stress threatening people’s mental health. Unprecedented measures to slow down and prevent the transmission of COVID-19 have had various impacts on the population’s health behaviour and mental health. The main purpose of the present study is to investigate the lockdown’s effects on university students’ mental health in Romania. Based on a cross-sectional design, the survey data were collected from a sample of 722 participants (247 males; M = 21.1 years; SD ± 1.73). A path analysis was performed to verify the hypothesised direct and indirect effects included in the multiple mediation model. The findings showed a positive association between stress and boredom proneness, missing daily social interactions, spending more time on phone conversations and the increasing interest in following news about the pandemic. The path analysis revealed an excellent fit between the proposed multiple mediation model and the sample data. Boredom proneness and missing daily social interactions both affected stress, directly and indirectly, through more time spent on phone conversations. In addition, it was found that the increased interest in following news about the pan-demic mediated the relationship between boredom proneness and perceived stress. In terms of gender differences, our findings revealed that female students experienced significantly higher stress levels than male students, perceived to a greater extent the lack of daily social interactions and spent more time on phone conversations. Overall, the findings further extend the empirical evidence on university students’ mental health in the context of the COVID-19 pandemic. Therefore, universities need to organise support programmes focused on developing university students’ coping strategies to maintain their mental health even in adverse contexts.

In the paper, based on the 2012-2018 panel data of 17 cities in Henan Province of China, a panel regression model was constructed to empirically analyze the relationship between digital inclusive finance and rural income, and the empirical results demonstrate that digital inclusive finance plays a significant role in promoting rural income. Further dimensional research unveils that all of its breadth of coverage, depth of use and degree of digitization present significant positive correlation with rural income, and a robustness test was conducted through the sub-sample method. In addition, according to regression analysis on the influencing factors of digital inclusive finance through the Tobit model, the level of economic development, the Internet popularity rate and the urbanization rate have a positive effect on the development of digital inclusive finance in Henan, while the income gap between urban and rural areas and the degree of opening up have a negative effect. Finally, predicated on the analysis of the restrictive factors of Henan’s digital inclusive finance in increasing rural income, the paper puts forward specific policy proposals based on the native state quo.

Additive manufacturing (AM) has been the core area of sustainable manufacturing commonly recognized for its high efficiency in enabling cost-effective production towards sustainability. There are three models this research constituted: In Collection-Recycling-Manufacturing (CRM) model, technologies and processes are benchmarked followed by Business model that evaluates industrial key criteria. However, these are insufficient for AM to effectively play dominant role as the realization requires human factors such as multi-entities authorities, policy making and AM society to initiate and execute the plan. Strategy control model focuses on human-centric approaches such as demography, population control, policy, regulations, and management. It investigates each nation’s demography, and enables strategy, plan and control to relocate overcrowding population to rural areas. It also produces robust workforce to support AM and materials recycling through the appropriate applications. Through the construction of AM and materials recycling, strategy control model creates job opportunities for those unemployed people. It further builds infrastructure for the livelihood of new residents and supports AM home-based business (HBB).

Supplier selection (SC) product life cycle cost (SCPLCC) is an important consideration among corporations, SCPLCC problem has become associated with deciding how one supplier should be selected from possible alternatives. In this study, we applied two types of goal programming, multiobjective linear programming and revised multichoice goal programming to develop a PLCC-based concept to solve the SCPLCC problem and construct a decision-making tool for application to a case of supply chain management in a Taiwanese light-emitting diode company in the high-tech industry. Our study main contribution Company managers can easily use the two approaches of the SCPLCC model with different parameters to solve SCPLCC model problems. Finally, we comparing five models found RMCGP with weighted linear goal programming had an adequate effect for application to the PLCC concept for high-technology company; this cloud makes company decision–makers focus on low PLCC and select a better supplier in sustainable supply chains goal.

We show that an exponential income distribution will emerge spontaneously in a peer-to-peer economic network that shares the publicly available technology. Based on this finding, we identify the exponential income distribution as the benchmark structure of the well-functioning market economy. However, a real market economy may deviate from the well-functioning market economy. We show that the deviation is partly reflected as the invalidity of exponential distribution in describing the super-low income class that involves unemployment. In this regard, we find, theoretically, that the lower-bound u of exponential income distribution has a linear relationship with (per capita) unemployment compensation. In this paper, we test this relationship for the United Kingdom from 2001 to 2015. Our empirical investigation confirms that the income structure of low and middle classes (about 90% of populations) in the United Kingdom exactly obeys exponential distribution, in which the lower-bound u is exactly in line with the evolution of unemployment compensation.

Reporting on CSR activities has become the essence of reporting for modern business entities. In this regard, particular attention is paid to public interest companies. Therefore, the following paper aims to answer the question of whether there are differences in the linguistic structure of the studied CSR reports in three selected industry indices on the Warsaw Stock Exchange (WSE) in Poland, i.e. WIG-energy index, WIG-fuel index, WIG-mining index and their relationship with the performance of selected companies. The study was conducted on a purposely selected sample of companies between 2013 and 2018. A total of 138 CSR reports and 138 annual separate financial statements prepared in accordance with international balance sheet law were collected. The study was carried out based on a panel regression model. It was found that CSR reports contained similar average percentages of parts of speech such as nouns and adjectives. When linking the economic performance of companies, expressed with selected indices, to the information on the implementation of CSR concepts, it was revealed that the results are more likely to describe business performance when it is satisfactory.

This study investigates optimal decisions in a green supply chain consisting of a manufacturer and a leading retailer considering the green marketing and fairness preferences of member firms. Four Stackelberg game decision models are constructed in which the manufacturer and the re-tailer engage in green marketing separately when the manufacturer has no and has fairness preferences. The impacts of fairness preferences and green marketing on the optimal decision in the green supply chain are comparatively analyzed. The study finds that member firms perform green marketing regardless of the presence or absence of fairness preferences and that such be-havior increases the wholesale price, retail price, and market demand of low-carbon products as well as the profits of member firms and the supply chain. A more interesting finding is that the profit growth of member firms and the supply chain due to the manufacturer’s green marketing is more pronounced than that due to the retailer’s green marketing. When the retailer and the manufacturer engage in conduct green marketing, the manufacturer's fairness preferences have different effects on the wholesale price, retail price, market demand, level of green marketing efforts, member enterprises and profits of supply chain. Therefore, firms should consider the impact of green marketing and fairness preferences to make pricing and performance decisions, so as to achieve efficient operation of the whole supply chain and avoid double marginal effects. Finally, the above conclusions are verified through numerical simulation, providing a reference for the decision-making of member firms in the green supply chain.

The rural population percentage decreased from 82.7% to 68.9% in 2011, even though there is an increase in the total rural population, which stands at 833.7 million, and the rural population were now more than three times compared to the population seven decades ago. Another observation is the decrease in cultivators percentage from 71.9% to 45.1 %, while agriculture labour increase from 28.1% to 54.9% during the same period. Despite the increase in irrigated land and net area sown, the average holdings' size under the farmers is continuously decreasing, and it requires a study to look into the reasons. The research probes the role of Minimum Support Price (MSP) in supporting farmers and measuring market price above MSP needed to help marginal and small farmers remain above the poverty level. It explains how different market rates above MSP have a different impact on different categories of agriculture landholding. The study works on developing a common model that relates the impact of MSP on different farmers categories. The model can be generalized to all crops and regions and useful in designing policies that focus on uplifting the income of agricultural farmers.

Background: The study assessed men’s role in the preparedness against emerging pandemic of Ebola Virus Disease in Ogun State, Nigeria. It examined the changes in men’s hygiene practices as response to the news of the outbreak of Ebola Virus Disease. Methods: The data were extracted from a 2015 Cross-Sectional Survey on wellness, knowledge, attitude and practices towards the control and prevention of Ebola Virus Disease. The respondents (466 male) in the main survey were selected using simple random sampling technique within two enumeration areas (EAs). Results: The results revealed high level of knowledge of EVD but over 70% were not aware of centre for EVD treatment, 60.2% believed they are not susceptible to EVD. The practice of handshaking reduced, eating of hunted animals decreased only marginally by 6.9% and washing with soap increased by 4%. Conclusion: The study provides helpful information for public health policy especially in terms of behavioral risk factors that are prone to Ebola virus infections or other communicable diseases. It emphasises regular hand washing with soap and sanitizing agents and recommended that availability of treatment centres and vaccines that can enhance effective response in curtailing further health emergencies.

Our study provides guidelines on how to build long-term customer relationship in the non-contract mechanism context. More specifically, the findings show that special, social, and core benefits influence calculative commitment, and operational and special benefits influence affective commitment. This study also supports that calculative and affective commitment play a crucial role in understanding multi-channel agencies’ loyalty. In sum, this study revealed that calculative and affective commitment can be considered as partial or full mediators in the relationship between RBs (relational benefits) and loyalty. This study not only contributed to the existing SET (social exchange theory) and RBs paradigm but also provided practical implications for food distribution management.

During the COVID-19 outbreak, most university courses have been offered on online platforms. A sudden shift from face-to-face classroom learning to online formats could influence the learning effectiveness of classes. This study aims to investigate differences in the learning effectiveness of online and face-to-face lecture courses. It also explores factors that impact the effectiveness of online instruction. These factors include interactions among learners, interactions between learners and the instructor, the quality of online platforms, learners’ ability to use devices and follow instructions, and learners’ situational challenges. The study participants were 261 university students at King Mongkut’s University of Technology Thonburi in Bangkok, Thailand. All participants were enrolled in at least one lecture course, such as history, humans and the environment, the environment and development, or general philosophy, during the 2019 academic year. A questionnaire was distributed to participants after they completed these courses in May 2020. Paired simple t-test analyses were used to compare the effectiveness of online and face-to-face classes, and a multiple regression analysis was used to identify factors that impact the learning effectiveness of online classes. The results show that online classes are less effective than face-to-face courses. The multiple regression analysis also revealed that the effectiveness of online learning was significantly impacted by learners’ ability to interact with classmates during class, their ability to interact with instructors after the class, the quality of online platforms, and disturbances or distractions in learners’ environments.

An economic and business history approach is used to show the rise and relative failure of the Spanish wind industry during the period between 2004-2015, when Spain became the fourth country after China, the US and Germany in installed capacity of renewable energies and, in relative terms, the second country after Denmark. This study is unique in that it provides an integrated vision of the reasons for the relative fall of Spain in the world ranking of wind energy producers. The methodology of the economic analysis of industrial policies makes it possible to explain the fall in the relative importance of Spain in the international panorama of wind farms. There were no reasons related to technological obsolescence or inability of the CECRE managing renewable energies to explain the fall.

In recent years, land supply in Hong Kong has fallen sharply and fails to keep pace with the growth of population and number of households. Land shortage becomes urgent and dire. With the inadequate provision of residential land, housing supply is also adversely affected.Insufficient housing supply leads to surging property and rental price in the private market. According to the Rating and Valuation Department (RVD), the overall private domestic price index peaked in June 2017 at 336.1. Keen housing demand is also observed in the private rental market. RVD statistics showed that the domestic rental index also reached the peak at 183.6 in June 2017 and the vacancy rate of about 3.8% as at the end-2016, which is much lower than the average vacancy rate of 5% from 1996 to 2015 (Development Bureau, 2017).In addition, there is soaring housing demand in public housing. As at the end-December 2021, the average waiting time for general applicants was 5.7 years, which is nearly double of the Housing Authority’s target for providing the first flat offer to general applicants at around three years on average (Housing Authority, 2021). Identifying and securing sufficient land to meet both current and anticipated pressing housing demand becomes a key challenge of the government. In the light of this, the government has established a dedicated task force (Task Force on Land Supply) in September 2017 and appointed 30 professionals from different disciplines, such as planning, engineering, academia and think tank, to take a Marco-review on the land supply sources, look for feasible options as well as consider the pros and cons of various options. 18 land supply options were worked out for the public to make choices in the public engagement exercise. Among the 18 choices, the development area on the Periphery of Country Parks was regarded as one of the land supplies sources. This option does not only include the Hong Kong Housing Society’s studies on developing Two Pilot Areas on the Periphery of Tai Lam and Man On Shan Country Parks, but also include developing more areas on the periphery of Country Parks. The proposed option received overwhelming attention from the public and aroused debates in various perspectives. Its ecological value, recreational value, financial viability and even legitimacy were discussed. However, spatial analysis on the suitability of having residential development in Country Parks has not been conducted. Therefore, in this study, multi criteria GIS analysis is conducted to evaluate the geographic suitability of Hong Kong Country Parks for residential purpose with the consideration of various criteria.

Emergency Management has not developed in a cohesive or comprehensive manner. Differing terms are used to name identical concepts. A standard comprehensive doctrine for the important development of emergency management is needed. In this paper I explain a doctrinal framework for emergency management. The paper states a clear identification of the five dimensions, and each of their components, necessary to the informed practice of Emergency Management. Although emergencies vary in cause and severity, the process of Emergency Management necessary for optimal handling of these emergencies varies little. The “All Hazards Approach” to emergency management establishes and reinforces commonality in processes, procedures, planning templates and organizational structure. The three types of agencies associated with emergency management activities are discussed, including the subject matter agency, coordinating agency, and supporting agency. The four critical functions of emergency management are detailed, and include mitigation, preparedness, response, and recovery, often all carried out concurrently. The ten activities, and seven resources of emergency management are highlighted. There are many ways to represent the integration of these five dimensions, to ensure completeness, while ensuring clarity; the two most common are described. When experts in Emergency Management follow the doctrine, they can coordinate all those involved to be sure that all aspects of any hazard are considered, and that all organizations/agencies, functions, activities, and resources of Emergency Management are coordinated and optimally active. Following this process is the only way to ensure the best outcomes from any emergency.

Intellectual quotient (IQ) is a measure of intellectual “ability” of performing, comprehension, and learning. Previous study reported that intelligence measures predict various measures of job performance and income. Emotional intelligence (EI) is the capacity of awareness, controlling and expression of one's emotions, seeking more feedback, and managing one's emotion to handle interpersonal relationships judiciously and empathically. These characteristics are also important for personal and professional success. Objective: This study tests a hypothesis whether the average national income rank is best predicted by the combined effect of the population's average intelligence quotient (one's ability to perform and learn) and emotional intelligence (emotional ability to express and handle interpersonal relationships). Method: The population average intelligence quotient, emotional intelligence, and indices of good governance, which include corruption perception index and educational expenses for each country were obtained from public data sources. The outcome variable for this study was the average national income rank. All the variables that are significant in univariate analysis were included in the multivariate regression analyses but excluded from the final model if not significant. Result: The total number of countries included in the final analysis was 81 because of missing values in different variables. The product of intelligent quotient (IQ) scores and emotional intelligence (EI) were found highly correlated at -0.75 ( p <0.05) with the national average income rank. The independent effect of intelligence quotient (IQ) and emotional intelligence (EI) was found not significant when their interaction effect (the product of IQ and EI) was introduced in the model. The R square value for the multivariate model with the interaction effect of intelligence quotient (IQ) and emotional intelligence (EI) was the highest at 0.73. The final model also included measures of good governance such as educational expense and corruption perception index (CPI). The corruption perception index (CPI) and educational expense were strongly correlated with measurements of good governance such as democracy index, functioning of government, electoral process and pluralism, political participation, and civil liberty, but these variables were found not significant in the multivariable model. Conclusion: The study concludes the effect of emotional intelligence and intelligence quotient are complementary to each other and holds the key to predicting average national income or wealth rank. This study also implies a nation may build more wealth if educational institutes focus on developing emotional intelligence (EI) and intelligence quotient (IQ).

This paper uses the spatial analysis software GeoDa as a tool, takes GRP (Gross regional product) of Sichuan Province in 2012 and 2018 as the dependent variable, and takes the city (autonomous prefecture) factor-driven, investment-driven and innovation-driven indicators as the dependent variable to explore the impact of innovation activities on regional economic development and the spatial distribution characteristics of regional economy. Through the comparison of the global correlation and local correlation, this paper explores the crux of the regional economic polarization and unbalanced development, and puts forward some measures to solve the existing economic development problems, such as cultivating and improving the regional industrial dependence, accelerating the regional transportation accessibility and convenience, and constructing the regional collaborative innovation system, So as to achieve the strategic goal of the construction of innovative Province in Sichuan Province.

In this study, I extend the Fama and French five-factor asset pricing model with a sixth factor, namely, carbon risk, to investigate its impact on equity returns. To measure carbon risk, a new factor ‘pollutant minus green,’ is developed using the difference between the weighted average returns of pollutant and green firms across 51 developed and emerging countries across four categories—North America, Europe, Emerging Markets, and the Asia Pacific. The results reveal that North America, Europe, and Asia Pacific markets have a carbon risk premium that gets eliminated in small-cap firms. The carbon risk factor is further tested in left-hand side (LHS) test asset portfolios and found to be more pronounced with size-effect anomaly; specifically, small stock firms report greater declining average returns because of more exposure than the mega-cap stocks to carbon dioxide emissions. Furthermore, size-effect anomaly prevails with profitability and investment factors across firms. Therefore, high profitability, as well as high investment small firms, show a greater decline than the big stock firms in average returns when their carbon dioxide emissions increase. The asset pricing model evaluation is carried out through the Gibbons, Ross, and Shanken test. The six-factor model directed at capturing carbon risk patterns in average equity returns performs better than the three-factor and five-factor models of Fama and French (1993 and 2015) in the majority of categories under 3x3 sorting and compete with both Fama and French model under 2x4x4 sorted LHS portfolios. The finding of this study offers various useful applications for investors, policymakers, brokers, corporations, governmental pollution abatement institutions, and other stakeholders who wish to obtain carbon risk premium.

This is a paper on Political Economic and Economic Policies into the European Green Deal framework and the Spanish recovery plan, with special attention to the tourism sector. First, there is a literature review, combining the scientific production with professional and institutional literature, to understand the topic development, from the former restrictive point to the current view at large. Second, it is offered a case study about the green jobs opportunity, according to wellbeing economics, for the Spanish tourism sector renewal. The paper provides valuable information to improve sectorial recovery plan, to coordinate the policymakers and the business managers and entrepreneurs.

The circular economy is an alternative paradigm whose purpose is the protection of the environment, the prevention of pollution and the growth of economic prosperity. This paper covers research which is qualitative in nature but has an exploratory scope through a documentary review, and includes proposals to promote sustainability. A more responsible consumption or use can be achieved by educating the user or consumer to return the product to production or repair through a collection service by way of reverse logistics (recovery of materials), followed by recycling or reuse of the product or its components to then offer these as recovered or recycled products on the market.

Over the past decade, China has witnessed fast-paced technological advancements in the media industry, as well as major shifts in the health agenda portrayed in the media. Therefore, a key starting point when discussing health communication lies in whether media attention and public attention towards health issues are structurally aligned, and to what extent the news media guide public attention. Based on data mined from 73,060 sets of the Baidu Search Index and Media Index on 20 terms covering different types of cancer from 2011 to 2020, the Granger test demonstrates that, in the last decade, public attention and media attention towards cancer in China has gone through two distinct phases. During the first phase, 2011-2015, Chinese news media still held the key in transferring the salience of issues on most cancer types to the public. In the second phase, from 2016-2020, public attention towards cancer has gradually diverged from media coverage, mirroring the imbalance and mismatch between the demand of active public and the supply of cancer information from news media. This study provides an overview of the dynamic transition on cancer issues in China over a ten-year span, along with descriptive results on public and media attention towards specific cancer types.

Based on 2010, 2013 and 2015 CGSS data, the impact of Internet use and social capital on the income gap among farmers in the past five years is assessed at three time points using the OLS method and a quantile regression method. The study finds that (1) the income gap among farmers increases continuously in the five-year period, while Internet use plays a positive impact on farmers’ income growth in all five quartiles; the coefficient differences are all significantly negative, indicating that Internet use plays a positive role in alleviating the income gap between high-income and low-income farmer subgroups, and (2) social capital plays a positive role in moderating the income gap among farmers and that Internet use by farmers expands the boundary of social capital, which in turn increases the income level of and alleviates the income gap among farmers.

Using the PLCC advantages generates revenue and lowers costs more than might be anticipated. It ensures better decisions by using a more perfect and practical assessment of revenues and costs. Although the supplier selection (SC) product life cycle cost (SCPLCC) is an important consideration among corporations, SCPLCC problem has become associated with deciding how one supplier should be selected from possible alternatives. In this study, we applied two types of goal programming, multiobjective linear programming and revised multichoice goal programming to develop a PLCC-based concept to solve the SCPLCC problem and construct a decision-making tool for application to a case of supply chain management in a Taiwanese light-emitting diode company in the high-tech industry. Our study main contribution Company managers can easily use the two approaches of the SCPLCC model with different parameters to solve SCPLCC model problems. Finally, we comparing five models found RMCGP with weighted linear goal programming had an adequate effect for application to the PLCC concept for high-technology company; this cloud make company decision–makers focus on low PLCC and select better supplier.

A more sustainable society and economy also implies a more sustainable behavior in the consumption of financial products. A possible change in focus can come from the demand side, so that more sustainable consumption of financial products have to go hand to hand with financial literacy. However, financial literacy, potential favoring of this sustainable behavior, is far from reaching an international consensus about its definition, object and scope. Two objectives are analyzed; the different interpretations of financial literacy in the academic literature, as well as its evolution and how, in what context and with what other concepts the term is used in social networks. Scientometric techniques and content analysis have been used to carry out a systematic review of literature and also NLP to analyze the comments on Social Networks. Critical moments are identified in the definition of financial literacy. Also ten sentiments are analyzed in social networks in wich positivity, trust, and anticipation predominate. Greater attention to this issue is necessary both from the private initiative and from public policies, so that financial literacy is an effective tool for a more sustainable behavior by consumers. Finally, a new definition is proposed based on our findings.

In this paper, the authors identified key elements important for circularity: (1) Background: The primary goal of circularity is to eliminate waste and to prove the constant use of resources. In the paper, we classify studies according to circular approaches. The authors identified main elements and classified them into categories important for circularity, starting with the managing and reducing waste and the recovery of resources; and ending with the circularity of material, and general circularity-related topics and presented scientific works dedicated to each of the above-mentioned categories. The authors analyzed several core elements from the first category aiming to investigate and connect different waste streams and provided a regression model; (2) Methods: The authors used a dynamic regression model to identify relationships among variables and selected the ones, which has an impact on the increase of biowaste. The research was delivered for the 27 European Union countries during the period between 2020 and 2019; (3) Conclusions: The authors indicated that the recycling rate of wasted electrical equipment in the previous year has an impact on the increase of recycling biowaste next year. This is explained as non-metallic spare parts of electronic equipment are used as biowaste for fuel production. And the separation process of the composites of electric equipment takes some time, on average the effect is evident in one year period.

The Nordic countries are practically always well positioned in the main international economic, social and sustainability indices and recommending the scientific literature that the variables that these indices intend to measure translate into sustainable economic growth, with this unprecedented empirical study we intend to verify through the ARDL methodology for space temporal 2004 -2018 if the maintenance of high scores in these indexes translates into effective economic growth. The ARDL methodology has the advantage of giving us short- and long-term coefficients. Using four of the main international indices, we conclude that for Nordic countries for economic growth, economic freedom is of no significance and business-friendly regulation is the most important variable. A fundamental discovery in our study (in which Granger's Causality complements the ARDL methodology) is that these countries have been able to adapt perfectly to the globalization process and that entrepreneurship has worked as an important contribution to the continued economic and social success of these countries, allowing them to continue to enjoy their “Nordic Welfare States” in these uncertain and troubled times. These variables have contributed to its economic and social sustainability.

Pharmaceutical industry faces the pressure of a global economy, the loss of value in local markets and the highly innovative intensity that characterizes the sector. With this investigation, we intend to carry out the first characterization of the Portuguese pharmaceutical industry. This study aims to identify the determinants of internationalization as levers of sustainability and to establish a pattern that corresponds to better outcomes in pharmaceutical companies’ internationalization ventures. All companies from the Portuguese pharmaceutical export sector, a total of 16 companies, were contacted. Data was collected from a highly representative sample corresponding to 63% of the total. A previous contextualization of the pharmaceutical sector and a bibliographic review were carried out, creating the basics of the empirical framework, a quantitative research. This study revealed a deeply internationalized sector, but the overall results are conditioned by some weaknesses, namely the lack of sustainable competitive advantages, a limitation in companies’ resources to compete in a global environment and the reduced innovation in the object of internationalization. It was also observed the reduced institutional support to export ventures. This sector is considered strategic given the high contribution to country's exports. The conclusions of this study may have important implications for Portuguese pharmaceutical industry, to institutional organizations supporting the sector and to the academic environment.