This research discusses the business model challenges faced by cag aggregator platform models in developing countries. Technology-based platforms have been disrupting traditional businesses and rewriting the rules of the game. Ola cabs has been instrumental in shaping the Indian platform business landscape in a big way. Using case methodology the author analyses the situation and business model to present the salient features of Ola’s model. However, this paper also puts the spotlight on the inherent challenges in this model and warns the need for continuous business model innovation and service quality.

The article addresses the issue of consumer preferences for types of coffee in Poland (ground coffee, instant coffee, coffee beans, instant coffee mixes and instant cappuccino). The main source of the study is the results of primary research conducted using a structured interview (CAPI—Computer Assisted Personal Interview) on a nationwide sample of 800 coffee consumers. The research was conducted by Grupa IQS Sp. z o.o. from Warsaw in January 2016 for the MOKATE Group based on the assumptions and guidelines developed by the authors of the article. The main purpose of the article is to present the identified coffee consumer preferences in Poland with regard to various kinds of coffee. The results of the research which have been included in the article indicate, among others, ongoing changes in the preferences of Polish consumers regarding their coffee choices. They prove that Polish consumers are drinking ground coffee more and more often. The consumption of instant coffee is decreasing.

The financial inclusion, including all the people with the finance, is very concerned issue all over the world where Bangladesh is also trying to include all the people with the finance. Bangladesh lies in such a group of countries where only 17.6% - 38.6% adults are presently under the reach of the formal financial services. This is because the present banks and other formal financial modes consider the outcome and profitability in a way that, the rural and non-developed areas are always out of the consideration. But these areas consist of the most population of Bangladesh. And only then financial inclusiveness will be successful in Bangladesh when people from these regions will be under formal financial consideration. The paper seeks for a solution to the issue and presents the Unit Banking System as a probable way towards financial inclusion. For implementing the system in Bangladesh, the system needs a slight modification to cope in Bangladeshi economic condition and address the specific needs without hampering the surroundings. Considering all these, the paper shows the status, problems and key points of financial scenario of inclusion in Bangladesh and shows policy for a Modified Unit banking System.

Agricultural extension and advisory services in Africa have significant impact on food security as well as economic and social development. Recent moves towards a pluralistic delivery system, including the emergence of private-sector led initiatives in many countries are subject of policy and academic discourse. Our study used an adapted, fit-for-purpose market systems development framework to review available research in extension and advisory services in selected sub-Sahara Africa countries. Using a literature survey methodology, we report evidence of multiple actors in extension delivery, findings that point towards evolution towards mixed delivery as well as objectives. While there are significant uptake of cost-recovery approaches among commercially-oriented farmers, many smallholder farmers still depended on donor-funded services. Our review adds to existing knowledge through incorporating a market systems development framework, which extends the often-used willingness to pay approach, and highlights the need for merger of the public and private-sector objectives to achieve developmental outcomes.

Accurate electricity price forecasting has become a substantial requirement since the liberalization of the electricity markets. Due to the challenging nature of the electricity prices, which includes high volatility, sharp price spikes and seasonality, various types of electricity price forecasting models still compete and can not outperform each other consistently. Neural Networks have been successfully used in machine learning problems and Recurrent Neural Networks (RNNs) have been proposed to address time-dependent learning problems. In particular, Long Short Term Memory and Gated Recurrent Units (GRU) are tailor-made for time series price estimation. In this paper, we propose to use Gated Recurrent Units as a new technique for electricity price forecasting. We have trained a variety of algorithms with rolling 3-year window and compared the results with the RNNs. In our experiments, 3-layered GRUs outperformed all other neural network structures and state of the art statistical techniques in a statistically significant manner in the Turkish day-ahead market.

With the increased liberation of trade and fierce competition in the automotive industry, Proton needs to embark on a strategic reform to survive and remain relevant in the challenging market. This case study aims to explain the effectiveness of the Post Geely acquisition's ten years master plan to enhance Proton's self-reliance and global competitiveness. This case suggests that while the company's ten-year Master Plan is holistic and shows positive results in the early years, there is a need for a new business strategy, given the challenges imposed by climate change's impact on the automotive industry moving forward. The potentials of the Electric Vehicles (EVs) market and the Internet of Things (IoT) to develop the necessary long-term competitive advantage. A market strategy integrating the 4Ps and 4Cs framework suggests a two-dimensional convergence of the market mix, incorporating the organization's market strategy with a more consumer expectations-centric and user experience. Strategic integration of Geely's technological assets in developing Proton's technical know-how can address Proton's challenges and opportunities ahead.

Scientific and technological advances in telecommunications and onboard electronics, and advances in sustainability standards, dictated major changes to various industrial sectors, including the automotive industry, where hard and soft approaches to manufacturing are vying for market dominance. This work presents a prospective analysis of the autonomous vehicle (AV) market, analyzing three of the main US AV technology firms, Tesla, Waymo and Apple. Their designs and solutions are compared, and prospective scenarios were constructed based on an analysis of their strengths, weaknesses, opportunities and threats (SWOT). The results suggest that Tesla currently exhibits the greatest market leadership in the group studied. However, it was concluded that in the medium term, Waymo would surpass Tesla and assume market leadership. In the long run, it was concluded that Apple will overcome its rivals and dominate this market.

The objective of this study is to determine the impact of COVID-19 on the performance of Pakistani Stock Market. This study uses the data of COVID-19 related positive cases, fatalities, recovers and the closing prices of PSX 100 index of the first half of 2020. The findings of the study suggest that only COVID-19 recoveries are influencing the performance of the index and the daily positive cases and fatalities are insignificantly related to the performance. Further studies can be performed by incorporating other variables such as economic growth, interest rate and inflation rate along with the COVID-19 related variables at a cross-country level.

Increasing market participation among smallholder farmers have a big potential to uplift living standards of poor through increasing production and consumption pattern. Although, smallholder farming made 95% of total crop production in Ethiopia, they are exposed to a marketing bottleneck that hinders benefits from their produce. The objective of this study was analyzing factors determining smallholder Teff farmer decision to participate in output market and level of marketed output.The study used data from 190 respondents from four selected Teff dominant kebeles of Gena-Bossa districts in Dawro Zone, through structured questioner. This investigation was imperative because no adequate research has been done in study area in examining the hindering factors of farmers’ market participation. Moreover, in the prior study, different authors come up with varied outcomes in diverse country and geographic location concerning poor farmers’ market participation decision. The descriptive statistics and Heckman two stage econometric methods were employed to analyze data collected from sampled household. The significance of coefficient of inverse Mill’s ratio ( ) indicates the presence of self-selection bias and the effectiveness of applying Heckman two stage model. The results of study show that the smallholder decision to participate in output market were positively influenced by size of land holding, availability of family labor force, education status of household head, accessibility of credit service and access to market price information. On the other hand, size of family member, sex of house hold head being female and distance to market place discourage probability of Teff farmer market participation decision. Moreover, the second stage estimation reveals that, the education status of house hold head, size of farm land, amount of Teff crop produced, accessibility of market information, the size of family labor force and being member to farm cooperative increase the quantity of marketable output, whereas, large number of family size decline the level of Teff crops marketed. The policy that assist poor farmers in obtaining market skills; create affordable credit service; strengthen community based producer groups and capacitating the females socially and economically in the community believed to minimize the problems encountering small farmers in a way to market their crop

The purpose of this paper is to identify factors that influenced customer satisfaction in the Moscow taxi market. The previous researches in customer satisfaction of transportation services laid the foundation of factor model. The resulting list of factors was revised by taxi market experts. The augmented model provided the basis for quantitative survey. The research sample included 310 respondents who have been using taxi services in Moscow during past 2 years. Survey data was analyzed using multiple choice regression method. Analysis results show significant differences between frequent and casual taxi users and a certain number of passenger experience factors that have no influence on customer satisfaction:for frequent users it is discount, for regular users - trip environment, and for rare clients - technical support&security and trip comfort.

The aim of this cross-country research is to examine how the profit and loss sharing mudarabah investment deposits are classified and disclosed in the financial statement of Islamic banks. The cross-country study examined the financial statements of fifty-one fully-fledged Islamic banks. The results of the data analysis show that Islamic banks disclose the mudarabah investment account in different ways. The absence of standardized disclosure for mudarabah investment deposit confuses the stakeholders. This research suggests to the regulators to fully or partially adopt the AAOIFI standards specifically for Islamic financial institutions.

This study examines the effect of market risk on the financial performance of 31 non-financial companies listed on the Casablanca Stock Exchange (CSE) over the period 2000-2016. We utilize three alternative variables to assess financial performance, namely return on assets, return on equity and profit margin. Next, we use the degree of financial leverage, the book-to-market ratio, and the gearing ratio as market risk variables. Besides, we employ the pooled OLS model, the fixed effects model, the random-effects model, the difference GMM and the system GMM models. The results show that market risk indicators have a negative and significant influence on the companies' financial performance. The elasticities are greater following the book-to-market ratio compared to the degree of financial leverage and the gearing ratio, respectively. In most cases, the firm size, the tangibility ratio, and the cash holdings ratio have a positive effect on financial performance, whereas the firms' age, the debt-to-income ratio, stock turnover, and leverage hurt the performance of these non-financial companies. Therefore, decision-makers and managers should mitigate market risk through appropriate strategies of risk management, such as derivatives and insurance techniques.

The Italian herbal products market is the most prosperous in Europe. The proof is represented by the use of these products in several marketing categories, ranging from medicine to nutrition and cosmetics. Market and legislation in Italy are at the same time cause and consequence of this peculiar situation. In fact, the legislation on botanical food supplements in Italy is very permissive and at the same time the market shows an overall satisfaction of users and strong feedback in terms of consumption, which brings a widening use of medicinal plants, formerly the prerogative of pharmaceuticals, to other fields such as nutrition. This review summarizes the market and normative panorama of herbal products in Italy, highlighting the blurred boundaries of health indications, marketing authorizations and quality controls between herbal medicines and non pharmaceutical products, such as food supplements, cosmetics and other herbal-based “parapharmaceuticals”.

The COVID-19 crisis has emphasized the importance of digital transformation of SMEs and has served as an accelerator. Digital transformation empowers SMEs to rethink the way they make decisions and apply technology in meaningful and sustainable ways. The purpose of this study is to explore the role of digital transformation, fostered by COVID-19, and its potential contribution to the sustainability of SMEs. This paper examines a new conceptual framework designed on resource-based theory perspectives by using a survey data of 246 SMEs in Latvia and employing mediation analysis. The main findings of the study are that digital orientation and digital capability have direct positive effects on digital transformation; higher levels of digital orientation and capability, mediated by digital transformation, lead to higher revenue; as well as a more sophisticated business model in the case of digital orientation. Even if we cannot confirm that higher digital capability, mediated by digital transformation, leads to a more sophisticated business model, we found statistically significant direct effects from digital capability to digital transformation and from digital transformation to business model. These findings can be useful for policymakers, managers and practitioners to clarify how digital orientation, digital capability intermediated through digital transformation affect sustainability of SMEs.

There is an increasing concern on the quality of jobs and productivity witnessed in the flexible employment arrangements. The aim of this study is to examine the relationship between various employment arrangements and the workplace performance. Home-based working-teleworking, flexible timing and compressed hours are the main employment types examined using the Workplace Employee Relations Survey (WERS) in years 2004 and 2011. The workplace performance is measured by two outcomes- the financial performance and labour productivity. First, the determinants of those flexible employment types are explored. Second, the ordinary least squares (OLS) method is followed. Third, an instrumental variable (IV) approach is applied to account for plausible endogeneity and to estimate the causal effects. The findings reveal a significant and positive relationship between these types of flexible employment arrangements and the workplace performance. Education, age, wage, quality of relations between managers-employees, years of experience, the area of the market the workplace is operated and the competition are significant factors and are positively associated with the propensity of the flexible employment arrangements implementation. This can have various profound policy implications for employees, employers and the society overall, including family-work balance, coping with family demands, improving the firm performance, reducing traffic congestion and stress among others. It is the first study that explores the relationship between flexible employment types and workplace performance using an IV approach. This allows us to estimate the causal effects of flexible employment types and the possible associated social implications.

The driving force behind adopting the idea of ​​sustainable development are producers and retailers. Unfortunately, when preparing their product range for consumers, many of them still only pay attention to the size of the customers’ earnings, how often they shop and how much they buy when shopping. In consumer segmentation, sustainable values ​​that consumers apply when making their purchasing decisions are rarely taken into account. The aim of this article is to show that values ​​such as environmental protection, the ethical behaviour of producers, fair trade or maximising the utility function of consumption are so important in the purchasing process in the coffee market that they can be used as segmentation variables. The Polish coffee market was selected to carry out segmentation taking into account the consumers' sustainable values. The main source of the article is the results of a standardized online survey conducted on a nationwide sample of 800 coffee consumers in July 2018. Multi-dimensional analyses such as extrapolative factor analysis (EFA) and cluster analysis (CA) were used to describe the obtained results. As a result, six segments of coffee consumers were identified and described: “responsible, aspiring to be connoisseurs”, “loyal coffee enthusiasts”, “pragmatic users”, “coffee laypersons”, “sophisticated connoisseurs”, “consumerists, connoisseurs, but not at any price”. Among the identified segments, the sustainable consumption values ​​most often mentioned refer to "responsible, aspiring to be connoisseurs", and the least often - ”consumerists, connoisseurs, but not at any price”. The conclusions presented in the last part of the article may be used by manufacturing and trade enterprises, operating on the coffee market, in order to respond to the identified needs and expectations of consumers and by governmental and social organisations so as to determine the directions of pro-ecological education of consumers.

Prediction of stock groups values has always been attractive and challenging for shareholders. This paper concentrates on the future prediction of stock market groups. Four groups named diversified financials, petroleum, non-metallic minerals and basic metals from Tehran stock exchange are chosen for experimental evaluations. Data are collected for the groups based on ten years of historical records. The values predictions are created for 1, 2, 5, 10, 15, 20 and 30 days in advance. The machine learning algorithms utilized for prediction of future values of stock market groups. We employed Decision Tree, Bagging, Random Forest, Adaptive Boosting (Adaboost), Gradient Boosting and eXtreme Gradient Boosting (XGBoost), and Artificial neural network (ANN), Recurrent Neural Network (RNN) and Long short-term memory (LSTM). Ten technical indicators are selected as the inputs into each of the prediction models. Finally, the result of predictions is presented for each technique based on three metrics. Among all algorithms used in this paper, LSTM shows more accurate results with the highest model fitting ability. Also, for tree_based models, there is often an intense competition between Adaboost, Gradient Boosting and XGBoost.

This paper highlights the impact of financial inclusion on individuals’ borrowing and saving decisions in the United States and the United Arab Emirates. It does so, using data from the 2014 Global Financial Inclusion database, and an empirical strategy consisting of first testing the significance of the joint bivariate model over its binary conterparts using the Lagrange multiplier test, followed by a contrast between the fully-parametric and semi-parametric specifications of the saving and borrowing equations. Based on model performance measures, the semi-parametric bivariate probit specification is identified as a better framework for describing the two processes of saving and borrowing, with a correlation coefficient of 12.3%. Although no significant difference exists between UAE and US residents in borrowing behavior, we find that US residents are 31.4% more likely to save than their UAE counterparts. In addition, and in line with the Permanent Income Hypothesis, the results reveal the absence of an income based saving or borrowing gradient in the two countries. Conversely, we found the prevalence of a gender based saving (12.4%) and borrowing (13.8%) inequality in favor of the male gender. Furthermore, access to a bank account and a debit card, companies policy of direct wage and salary transfer, and government transfer programs with direct deposit options are all financial inclusion strategies that are found to significantly raise the likelihood of saving and borrowing. As such, companies with payroll practices based on cash or physical paycheck issuing, especially in the US, should revise such policy to create more financial inclusion, and thereby more saving potential which in turn would contribute to further borrowing, investment and growth of the national economy.

This research aims to determine the influence of the independent commissioners, audit committee, institutional ownership, firm size and leverage against the integrity of the financial reporting information. This research is quantitative research with the causal approach. This study uses secondary data and panel data regression analysis method. The research results prove that audit committee, institutional ownership and leverage effect on the integrity of the financial reporting information. But it does not prove that the independent commissioner and firm size effect on the integrity of the financial reporting information.

An optimal withdrawal strategy beginning at age 65 provides a lifetime income from a portfolio, adjusted annually for inflation, while reducing the probability of living in financial ruin to an ac-ceptable level. This paper analyzes the probability of living in financial ruin, potentially for multiple years, rather than just the event of ruin. A stochastic Excel model was developed to simulate the effect of varying investment returns on a portfolio with two asset classes; large company stocks and long-term government bonds. A stochastic model is also applied to retiree mortality. The following variables were analyzed to determine their relative impact on withdrawal strategies: • Withdrawing a constant percentage of the portfolio, • Gender, • Initial asset allocation, • Asset allocation rebalancing methods, and • Low investment return environments. For both genders and most withdrawal rates, an approximately equal initial asset allocation of stocks and bonds, combined with a level rebalancing function, provided the lowest probability of living in financial ruin. Because each investment return followed its own probability distribution function, some retirees experienced financial ruin even in the most conservative simulations.

In this paper, we focus on the impact of financial liberalization on stability of emerging stock market. We identify crises in a group of Latin American (Argentina, Brazil and Chile) and Asian countries (Philippines, Korea, Taiwan and Thailand) during 1975–2005. This paper aims to apply the methodology of CMAX method. Our results indicate that liberalization triggers more unstable stock market in the short run and generate several crises. Still, liberalization seems to generate more stable financial markets in the long run. Financial liberalization does not increase the frequency of crises in emerging countries and at long-term, crises are less several.

Many countries have been facing the problem of bank insolvency across the globe. Asset deterioration is one of the main reasons for insolvency of banks. The objective of the paper is to ascertain the determinants of nonperforming loans (NPLs) in the banking sector of Pakistan for the period 2006-16. Other than the bank specific and macro variables proposed by the literature, the roles of weighted maturity and output gap are for the first time examined. We find significant impact of output gap on NPLs however weighted maturity has insignificant role in shaping the future NPLs. Bank specific drivers of NPLs include bank size and capital adequacy ratio.

The utility of ICTs for providing market information to rural smallholder farmers is growing rapidly, and access to reliable information and sources is considered crucial for beneficial market interaction. This study explored critical factors contributing to usage of electronic sources for market information search among rural smallholder livestock farmers. Using data collected from 129 respondents through a non-random sampling technique; descriptive and regression analysis was applied to identify key factors responsible for their awareness and use of ICT-based market information sources. Level of education was found to be a driver of awareness of ICT-based sources, and use of these sources was influenced by farmer-specific characteristics such as household size, education, income, membership of cooperatives and herd-size. The key ICT tools used was radio and mobile phones, widely available in the study area. Identified constraints to use of these ICTs include cost and patchy network signals in some areas. Policy interventions to reduce cost of mobile phone services and expansion of base stations; including practical recommendations for improved programming in radio and television offerings, are considered indispensable for greater uptake of e-information sources among smallholder livestock farmers.

This study examines whether information about the winners of the Sustainability Reporting Award (SRA) contributes to the usefulness of the information in the financial statements. This study used a sample consisting of 110 winners of SRA (SRA firms) and 110 companies that did not receive SRA (non-SRA firms) from 2008 to 2016. The study found that earnings per share (EPS), book value per share (BVPS), and earnings per share change (EPSC) are value relevant information. Results of comparison between SRA firms and non-SRA fimrs, this study found that EPS positive association with stock price and with returns for SRA firms is higher than that for non-SRA firms. Findings of this study also show that, value relevance of BVPS for non-SRA firms is higher than that for SRA firms. When mesures of Price and BVPS are transformed into natural logarithm, the value relevance of BVPS for SRA firms is higher than that for non-SRA firms. Thus, the results are sensitive to measures of the variables. The findings of this study indicate that information about the winners of SRA contributes to the usefulness of financial statements.

An application of deep convolutional neural network and recurrence plot for financial market movement prediction is presented. Though it is challenging and subjective to interpret its information, the pattern formed by a recurrence plot provide a useful insight into the dy- namical system. We used a recurrence plot of seven financial time series to train a deep neural network for financial market movement predic- tion. Our approach is tested on our dataset and achieved an average of 53.25% classification accuracy. The result suggests that a well trained deep convolutional neural network can learn a recurrence plot and pre- dict a financial market direction.

The Directive 2014/95, in force in 2017, is the first European step that requires mandatory non-financial information to undertakings (all “public interest entities” with more than 500 employees). The regulation is concerning sustainability information as environmental, social and employee, human rights and anti-corruption and bribery matters and disclosure of diversity policy for board members. The study, in the strand of the regulation of accounting, part of the broader field of research into accounting regulation, contributes to the debate on the quality of regulation, in this specific case referred to sustainability disclosure. The regulation of sustainability matters is studied in literature broadly in a post-implementation phase and at national level. This research, instead, aims to analyse, through the causal chain of regulatory policy, in the ex-ante stage, the quality of the regulation and, at least, the usefulness of the normative pressure. The Oil & Gas sector is chosen as sample of the study, because it is one of the most advanced sectors in sustainability disclosure. The examination of the law, in terms of content requirements (what) and location of information (where), is the basis to apply the disclosure-scoring system, a partial form of content analysis, to the reports of the sample. The findings reveal a good level of completeness of non-financial information, however, there are some areas that have to be improved to reach the requests of the Directive. Results show also the presence of overlap between financial reports and sustainability ones. In conclusion, the regulation is useful to prompt undertakings to reflect on their reporting and so doing improve their sustainability approach.

This paper studies the duration patterns of unemployment spells for immigrants and the determinants of unemployment’s completion into one of a number of studied labour market states in Finland. We estimate a duration model for unemployment with competing risks of its terminating into employment, labour market training or economic inactivity. Taking into account the wide period of observation and opportunities to analyse processes of labour market integration during various periods of economic development in Finland, in combination with the individualistic character of the labour careers of immigrants, this research is beneficial owing to the many various findings concerning labour market integration of immigrants. The approach undertaken in this research has a dualistic “descriptive-dynamic” character under which integration is understood as a never-ending process, which is conditioned by a time period of long-term existence and a context of solitary action. We find that transitions out of unemployment spells have a cyclical character; after every new “cycle” in unemployment, the probability of terminating unemployment decreases further. We also find that ascriptive factors make sense in the process of job-placement of immigrants from unemployment. Therefore, the gender, education and age of immigrants, as well as the effect of the period in which first unemployment occurred, potentially predict transitions out of unemployment and further labour market integration of immigrants.

This study explores the impact of financial inclusions on financial resilience. In doing so, we utilize the World Bank’s data on global financial inclusions. Our study confirms that the respondents with financial accounts are more resilient than those without accounts. The chances of being financially resilient are around 1.4 times higher for the account holders than their counterparts. We find a significant relationship between gender and financial resilience; males are 1.4 times more resilient than females when other covariates are considered in the regression model.

Market channel choice makes important contributions to the incomes and other livelihood attributes among smallholder farmers in developing countries. Often considered from a number of perspectives, the dominant view articulated suggests an advantageous integration into formal market channels. This position is questioned as it has implications for smallholder farmers’ food security and rural incomes. Using a mixed methods approach, the study collected primary data from 174 smallholder farmers and applied both a descriptive and multinomial logit regression model to analyze factors contributing to cocoyam production and market channel choices among respondents in the study area. Findings indicate that financial returns and available markets were key factors in cocoyam production, while amount received was a driver of market channel choice among 89% of respondents who sold directly at farm-gate. Farmers’ age (p=0.044), household size (p=0.043), distance to market (p=0.021), additional income (p=0.017) and amount received (p=0.014) were significant variables (p<.05) in the determinants of market channel choice. The study recommended improving market information provision and strengthening farmer associations which will enable smallholder farmers in rural communities to make informed choices with respect to produce price, access other markets and consolidate their collective market bargaining position.

Buyer practices have changed as individuals are figuring out how to live with the new truth of COVID-19. Take-out and conveyance orders have expanded, and our customer has added new items to their menu because of new client inclinations. With every one of the continuous changes, the customer had numerous unanswered inquiries, for example, Smartbridge has broad involvement with café innovation development Café TECHNOLOGY CAPABILITIES :Are the most famous items as yet unchanged after COVID? :Which are the most sold item blends now? :What is the acknowledgment of new things? :What are clients purchasing alongside new things? :How have liquor deals changed? The customer previously had reports that followed item deals and operational measurements, notwithstanding, there was a need to get a more profound knowledge into item examination. The customer expected to recognize what items and introductions were being sold all the more frequently, measure the acknowledgment of new items, and figure out what items clients buy together to improve advertising efforts, advancements, and deals. he E-business industry is filling immensely in the Indian market. The modest 4G web bundles in India clearly gives a push to these ventures. Thus, as Covid19 first hit in Quite a while, individuals got terrified to go out from their homes in light of the fact that, in their mind, it's a dread of Covid. They even wonder whether or not to go out to purchase fundamental (FMCG) products. Frenzy purchasing additionally has seen and to stay away from this dread of COVID-19, individuals are offering inclinations to the E-Commerce destinations to purchase fundamental products and a few clients are new which joined to purchase fundamental merchandise during this Pandemic Lockdown period. Numerous clients are moving their purchasing conduct from disconnected retail locations to online stores. This paper examines the customer buying pattern during lockdown.

The pandemic caused by SARS-CoV-2 virus obstructed the Chinese economy and has expanded to the rest of the world at a rapid pace affecting at least 215 countries, areas and territories. The advancement of the disease and its economic repercussions is profoundly ambiguous, making it challenging for policymakers to formulate suitable microeconomic and macroeconomic policy responses. The scenarios in this paper illustrate how an outbreak could significantly affect the global economy in the short run. It has been estimated that each additional month of crisis would cost from about 2.5-3% of the global GDP and that the GDP growth would take a blow, reaching about 3-6%, depending on the country. Scenarios also suggest that GDP can drop by more than 10% and even exceed 15% in some countries. Via addressing the economic consequence of COVID-19 in different industries and countries, the paper presents assessments of the likely global economic costs of COVID-19 and the GDP growth of different countries. Economies will be negatively affected because of the high number of jobs at risk. Countries highly dependent on foreign trade are more negatively affected. Given that disease and its economic influence are highly unpredictable in numerous aspects, the global economy at the moment is the most critically threatened in history.

Pearl millet is an important food crop in the arid and semi-arid tropical regions of Africa and Asia. These regions are home to millions of poor smallholder’s households living in harsh agro ecology and reported higher prevalence of malnutrition. Such poor households have few options in terms of food crops, besides the limited markets. Indeed, pearl millet is one of the food crops they continue to grow for their food and nutritional security. Pearl millet is important sources of dietary carbohydrates, energy, protein, and important minerals such as calcium, iron and zinc. Considering inherent high nutritional values and climate resilient nature (drought and heat), demand for pearl millet as food, beside valued for its Stover as a source of livestock fodder, is projected to grow strongly in Asia (India) and Africa (West and Central Africa). Iron (cause anemia) and zinc (cause stunting) deficiencies are widespread and serious public health problems worldwide, including India and Africa. Biofortification is a cost-effective and sustainable agricultural strategy to address this problem. Research on pearl millet has shown that large genetic variability (30-140 mg/kg Fe and 20-90 mg/kg Zn) available in this crop can be effectively utilized to develop high-yielding cultivars with high iron and zinc densities. Both Open –pollinated varieties (Dhanshakti and Chakti) and hybrids (ICMH 1202, ICMH 1203 and ICMH 1301) of pearl millet with high grain yield (>3.5 tons/ha in hybrids) and high levels of iron (70-75 mg/kg) and zinc (35-40 mg/kg) densities have been developed and released. Currently, India growing >70,000 ha of biofortified pearl millet, besides more pipeline hybrids and varieties are under various stage of testing at the national (India) and international (west Africa) trials for possible release. Genomic tools will be an integral part of breeding program particularly for nutritional traits to use diagnostic markers and genomic selection. Clinical studies showed that 200g grains from biofortified cultivar would provide bioavailable Fe to meet full recommended daily allowance (RDA) in children, adult men and 80% of the RDA in women. Till today, no markets to promote biofortified cultivars/grains/products as no incentive price and such products aims to address food and nutritional security challenges simultaneously. The demand is likely to increase only after investment and integration into modern public distribution system, nutritional intervention schemes, private seed and food companies with strong mainstreaming nutritional policies. In the non-traditional regions, this will contribute to livestock and poultry feed industry as spill-over benefits to improve nutrition.

The study aims to examine the effects of artificial intelligence (AI) on the consistency and analysis of financial statements in hotels in ASEZA, Jordan. This research is an exploratory, empirical study, which uses the methodology of data collection and interpretation to draw conclusions. The researchers used the arithmetic mean, standard deviation, T-test and ANOVA test to calculate the degree of significance of the study questions. The findings of a basic linear regression study of the impact of AI implemented in Jordanian hotels on the integration of accounting information systems and the association between AI and the integration of accounting information systems (R = 59.6%) also indicate that the fixed limit value amounted to (2.060) and the value of (Beta) for T-test

The purpose of this paper is to apply China’s economy growth prospects and its potential drivers of future. China's fast rise and its growth model have accelerated important existing structural trends in the global economy and made them decisive characteristics of the world economy. China's role in the world economy over the coming decades, an exercise which would not be possible without an investigation of the prospects for China's continued economic rise. On the one hand, China is a large export market for the United States. A lot of U.S. firms use China as the final destination of assembly in their global supply chain networks. China’s huge holdings of U.S. Treasury securities support the federal government finance its budget failures. However, some analysts contend that China consolidates a number of distortive economic policies such as protectionist industrial policies and an undervalued currency that undermine U.S. economic interests. They warn that efforts by the Chinese government to promote indigenous innovation, often through the use of subsidies and other distortive measures, could negatively affect many leading U.S. industries

2017 was an excellent year in terms of new drugs (chemical entities and biologics) approved by the FDA, with a total of forty-six. In turn, one of the highlights was the number of peptides (six) included in this list. Here, the six peptides are analysed in terms of chemical structure, synthetic strategy used for their production, source, biological target, and mode of action.

The emergence of the COVID-19 pandemic has propelled the use of alcohol-based hand sanitizers to the fore as a SARS-CoV-2 control measure. To be effective these products must comply with relevant quality parameters such as alcohol concentration, methanol limits and purity. The current study was designed to determine the quality of alcohol-based hand sanitizer products in the Nairobi metropolitan area. For this purpose, 74 commercially marketed samples were collected and subjected to analysis by gas chromatography. Only three samples (4.1%) complied with the regulatory specifications for alcohol content, methanol limits and pH. Five samples (6.8%) complied with the specification for alcohol content but did not meet methanol or pH limits. A total of 44 (59.5%) samples had methanol levels that exceeded threshold limits. Eleven samples (14.9%) were found with methanol substitution (i.e., methanol, instead of ethanol or isopropanol, was the main alcohol component). The results show that users of alcohol-based hand sanitizers are being exposed to substandard and falsified products which in addition to being non-efficacious pose harm due to unacceptable levels of toxic impurities. Regular, routine post-market surveillance is needed to prevent such products from reaching the market.

The aim of this research work was to provide model for predicting stock volatility in Nigeria Stock market. To achieve this, monthly data for Nigerian stock exchange, Exchange rate, Share index and inflation rate was collected for a period of January 1990 to December 2016.The descriptive statistics revealed these variables to exhibit volatility as a characteristics of financial time –varying series. DCC Model was fitted, were the coefficients for all the parameters and that of the correlation-Targeting (rho_21) are both negative and positive and tend very close to 1 and -1, indicating that high persistence in the conditional variances. The Model DCC, satisfied the properties of a good model of conditional mean and variance of the confidential Interval (C.I) of 1 and -1, that is, the conditional variances are finites and their series are strictly stationary. This therefore implies that the Nigerian Stock Exchange, Exchange rate, share index and Inflation rate will experience a non-steady shock in the Stock market. However Each of these variables have different length of recovery (volatility half- life) ranging from 1.5month, 6.5months, 6months to 2,4months for stock exchange, exchange rate, share index and inflation rate respectively. By implication, the volatility of these variables had a long memory, persistence and mean-reverting.

We examine the use of deep learning (neural networks) to predict the movement of the S&P 500 Index using past returns of all the stocks in the index. Our analysis finds that the future direction of the S&P 500 index can be weakly predicted by the prior movements of the underlying stocks in the index. Decomposition of the prediction error indicates that most of the lack of predictability comes from randomness and only a little from nonstationarity. We believe this is the first test of S&P500 market efficiency that uses a very large information set, and it extends the domain of weak-form market efficiency tests.

It has been observed that most adult citizens, globally, are not enjoying financial services. They are financially excluded, especially rural dwellers. Monetary authorities initiated financial inclusion, with the aim of including all adult population who are excluded from financial services into the financial system at an affordable cost to meet their basic needs. Studies have shown that it encourages household savings and affects growth positively. Central Bank of Nigeria initiated financial inclusion in 2012 and commenced implementation in 2014. Given the short period of its implementation, this study ascertained the effect on economic growth in Nigeria. The study used time series data ranging from 2004 to 2021. The study covered the pre-inclusion period, through its implementation period. Ordinary Least Square technique was adopted for data estimation. Preliminary and post-estimation tests were also conducted. Despite the short period of the implementation of financial inclusion strategy, the OLS result affirmed that it positively affects economic growth. It was concluded that financial inclusion is a growth driver. It was recommended that Central Bank of Nigeria, in collaboration with commercial banks and microfinance banks, continue to enforce inclusion exercise in all rural communities, ensuring that women, youths, farmers, traders in the informal sector, are captured by the financial system. Also, Central Bank Nigeria should set up financial inclusion compliance committee at the Local Government levels, with a State Monitoring unit to ensure compliance.

Deep reinforcement learning (DRL) has achieved significant results in many Machine Learning (ML) benchmarks. In this short survey we provide an overview of DRL applied to trading on financial markets, including a short meta-analysis using Google Scholar, with an emphasis on using hierarchy for dividing the problem space as well as using model-based RL to learn a world model of the trading environment which can be used for prediction. In addition, multiple risk measures are defined and discussed, which not only provide a way of quantifying the performance of various algorithms, but they can also act as (dense) reward-shaping mechanisms for the agent. We discuss in detail the various state representations used for financial markets, which we consider critical for the success and efficiency of such DRL agents. The market in focus for this survey is the cryptocurrency market.

In light of the worldwide spreading requirements related to the disclosure of non-financial information, which are aligning to the Sustainable Development Goals (SDGs) developed by the United Nations (UN) in 2015, the study aims to analyse the influence of sustainability and other non-financial reporting on companies’ engagement in earnings management practices, through a pre-post adoption of European Directive 2014/95/EU comparative analysis for firms listed on the Bucharest Stock Exchange (BSE) in the period 2015-2019. To conduct the investigation, the research involves the assessment and analysis of three earnings management metrics resulted by running multiple linear regression models on a sample of 31 companies listed on BSE. Research findings emphasise a decrease in the use of income smoothing practices by sampled companies in the post-adoption period 2017-2019, compared to the period preceding the implementation of the EU directive related to mandatory disclosure of non-financial information, 2015-2016. Thus, firms characterised by a higher transparency in terms of sustainability reporting are less inclined to engage in earnings management practices. This research complements the literature in the field of sustainability reporting and earnings management, providing empirical evidence on the significance and impact of publishing non-financial information.

Online transactions are becoming more popular in present situation where the globe is facing an unknown disease COVID-19. Now authorities of Countries requested peoples to use cashless transaction as far as possible. Practically it is not always possible to use it in all transactions. Since number of such cashless transactions have been increasing during lockdown period due to COVID-19, fraudulent transactions are also increasing in a rapid way. Fraud can be analysed by viewing a series of customer transactions data that was done in his/her previous transactions. Normally banks or other transaction authorities warned their customers about the transaction If any deviation is noticed by them from available patterns. These authorities think that it is possibly of fraudulent transaction. For detection of fraud during COVID-19, banks and credit card companies are applying various methods such as data mining , decision tree, rule based mining, neural network, fuzzy clustering approach and machine learning methods. These approaches is try to find out normal usage pattern of customers based on their past activities. The objective of this paper is to find out such fraud transactions during such unmanageable situation.Digital payment schemes are often threatened by fraudulent activities. Detecting fraud transaction in during money transfer may save customers from financial loss. Mobile based money transactions are focused in this paper for fraud detection. A Deep Learning (DL) framework is suggested in this paper that monitors and detects fraudulent activities. Implementing and applying recurrent neural network on PaySim generated synthetic financial dataset, deceptive transactions are identified. The proposed method is capable to detect deceptive transactions with an accuracy of 99.87%, F1-Score of 0.99 and MSE of 0.01.

Over the past decade, the credit quality of loan portfolios across most countries in the world remained relatively stable until the financial crises hit the global economy in 2007–2008. In this paper I discuss, the relationship between non-performing loans and economic landscape. Since 2008, nonperforming loans have been an increasingly hot topic in the international scene, due to their important and rising volume and their impact on the economy as a whole, on the banking system and on its credit supply. Since then, average bank asset quality deteriorated sharply due to the global economic recession. Yet the deterioration of loan performance was very uneven across countries. I am interested in explaining these differences in bank asset quality across countries and over time. In this paper, I therefore study the empirical determinants of non-performing loan (NPL) ratios using a data set for EU countries covering the past decade. The paper assumes that the spatial organization of banking systems and the geographical distribution of comercial banks branches, ATMs and GDP growth are major factors influencing the effectiveness in credit system. The aim of this paper is to construct a continuous and quantifiable model, which will demonstrate a role of economic condition, technology, competition, policy, business climate in Financial Stability. Main hypotheses suggests, that GDP growth, interest rate, new business, FDI, ATMs and geographical distribution of branches have an influences on NPL (non-performing loans).

This paper aims to quantify the effect of the deadly novel coronavirus (COVID-19) pandemic outbreak on Chinese stock market performance. Shanghai Stock Exchange Composite Index and its component sector indices are examined in this study. The pandemic is represented by a lockdown dummy, new COVID-19 cases and a dummy for 3 February 2020. First, descriptive analysis is performed on these indices to compare their performances before and during the lockdown period. Next, regression analysis with Exponential Generalized Autoregressive Conditional Heteroscedasticity specification is estimated to quantify the pandemic effect on the Chinese stock market. This paper finds that health care, information technology and telecommunication services sectors were relatively more pandemic-resistant, while other sectors were more severely hurt by the pandemic outbreak. The extent to which each sector was affected by pandemic and sentiments in other financial and commodity markets were reported in details in this paper. The findings of this paper are resourceful for investors to avoid huge loss amid pandemic outburst and the China Securities Regulatory Commission in handling future pandemic occurrence to cool down excessive market sentiments.

This paper proposes a game-theoretic framework for quantifying effects of strategic bidding behavior of load aggregators (LAs) on wholesale electricity market equilibrium. The independent system operator (ISO) employs double-sided auction design to settle transactions in the wholesale electricity market. Generating companies (GENCOs) and LAs submit their bids to the ISO in the economic model of supply function equilibrium. Under the smart grid paradigm, a LA participates in the electricity market on behalf of end-consumers to minimize their total payment for purchasing electricity. In this paper, bi-level programming (BLP) method is employed to determine optimal bidding strategy of self-interested market participants. In the upper level, the profit of intended market participant is maximized and in the lower level, the ISO clears the market via a bid-based security constrained economic dispatch (SCED). Also, competition of GENCOs and LAs is modeled as a non-cooperative game. To examine the effects of strategic bidding behavior of LAs on market equilibrium, the proposed model is applied to the IEEE 9-bus and the IEEE 30-bus test systems. According to numerical results, to allow the LAs to behave strategically along with the GENCOs makes the former better off and the latter worse off, while the net effect of this on total social welfare turns out to be case-contingent.

Indonesian crypto asset owners are expanding despite the government's ban. Crypto assets are too risky for Indonesian investors. This study uses the Theory of Planned Behavior and exogenous variables like financial literacy, trust, and government regulation to determine the causes of the intention to invest in crypto assets. Exogenous variables and behavioral intentions were moderated by gender. The study employs a quantitative approach, collecting data through a questionnaire survey of 149 adults over the age of 17 who have invested in non-crypto assets. SmartPLS was used to analyze research data. Financial literacy and trust, according to the study's findings, have an impact on the intention to invest in crypto assets. Gender can moderate the relationship between belief and behavioral intention. Women are more likely than men to invest in crypto assets due to the block chain system's security, transparency, and ease of use. This research is expected to help the government address the risks associated with investing in crypto assets by increasing transaction security with futures clearing and monitoring by using third parties as depositors. It also governs the laws governing crypto exchanges' liability to their investors.

This study aims to determine the cash sales accounting information system that is suitable for online store applications. Using qualitative methods with the object of research, namely the online stores. Sources of data obtained from several online stores. Data collection methods used are semi-structured interviews, observation, and document analysis. From the analysis and design of the buying and selling cycle information system in online business development, it was found that the development of information systems is a very important stage in the efficiency and effectiveness of the buying and selling cycle. By implementing a good and correct accounting information system design on an online store, it can facilitate the recording and minimize the occurrence of errors/loss of data. In addition, with a good information system design, the division of tasks between various sections becomes clear.

The main purpose of study is to identify the impact of COVID-19 pandemic on the green financing of banks and non-bank financial institutions (NBFIs) in an emerging economy such as Bangladesh. Also, this study shows the green banking activities of the banks and NBFIs during the pandemic. To analyze the impact of the pandemic on green financing, secondary data were obtained from the quarterly and annual reports of Bangladesh Bank (BB) on green financing as well as the annual reports and websites of 61 banks and 34 NBFIs in Bangladesh for the period 2021–2019. Subsequently, the study deployed dependent t-test statistics, growth rate (year-on-year), descriptive statistics, relative percentage changes, and varying tables and graphs to analyze the obtained secondary data. The empirical findings revealed that during the COVID-19 pandemic, there was an increase in green finance for all banks and NBFIs compared to before the epidemic, indicating that the pandemic had no negative impact on the total green finance growth of all banks and NBFIs. On the other hand, compared to the pre-pandemic period, bank-wise growth in green financing was higher for state-owned commercial banks (SOCBs), specialized banks (SDBs), and private commercial banks (PCBs) but lower for foreign-owned commercial banks (FCBs) during the COVID-19 epidemic. This suggests that the pandemic does not affect the expansion of green finance by SOCBs, SDBs and PCBs but significantly impacted the growth of green financing by FCBs. Furthermore, the research findings showed that the total outstanding and classified loans within the green finance investment decrease for both banks and NBFIs during the COVID-19 pandemic. The results indicated that the Bangladeshi banks’ level of automation towards green banking were satisfactory during the pandemic. Therefore, major policy implications for the green economic recovery by the government, BB, and managers of the banks and financial institutions in emerging economies like Bangladesh were discussed.

Many studies in the current literature annotate patterns in stock prices and use computer vision models to learn and recognize these patterns from stock price-action chart images. Additionally, current literature also use Long Short-Term Memory Networks to predict prices from continuous dollar amount data. In this study, we combine the two techniques. We annotate the consolidation breakouts for a given stock price data, and we use continuous stock price data to predict consolidation breakouts. Unlike computer vision models that look at the image of a stock price action, we explore using the convolution operation on raw dollar values to predict consolidation breakouts under a supervised learning problem setting. Unlike LSTMs that predict stock prices given continuous stock data, we use the continuous stock data to classify a given price window as breakout or not. Finally, we do a regularization study to see the effect of L₁, L₂, and Elastic Net regularization. We hope that combining regression and classification shed more light on stock market prediction studies.

This study compared the performance of five Family Generalized Auto-Regressive Conditional Heteroscedastic (fGARCH) models (sGARCH, gjrGARCH, iGARCH, TGARCH and NGARCH) in the presence of high positive autocorrelation. To achieve this, financial time series was simulated with autocorrelated coefficients as ρ = (0.8, 0.85, 0.9, 0.95, 0.99), at different time series lengths (as 250, 500, 750, 1000, 1250, 1500) and each trial was repeated 1000 times carried out in R environment using rugarch package. And the performance of the preferred model was judged using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Results from the simulation revealed that these GARCH models performances varies with the different autocorrelation values and at different time series lengths. But in the overall, NGARCH model dominates with 62.5% and 59.3% using RMSE and MAE respectively. We therefore recommended that investors, financial analysts and researchers interested in stock prices and asset return should adapt NGARCH model when there is high positive autocorrelation in the financial time series data.

This research contributes to the overall debate on education for sustainable development (ESD) by shed- ding lights on the contributing role of formal education to the contemporaneous dynamics of literacy, labor market participation and poverty reduction in Africa, with a focus on Burkina Faso. The study uses a semi-parametric recursive trivariate probit modeling approach, and data from the 2014 National Survey on Household Living Conditions in Burkina Faso. The results show that the embraced systemic approach in this analysis is statistically signicant as shown by the 95% condence intervals on the three correlation coeffcients in the model. Furthermore, education does improve literacy skills, however improved literacy skills in itself does not guaranty active labor market participation in Burkina Faso. Active labor market participation seem to be affected by labor market rates of return, and individual reservation wage (or income). When labor market rate of return is short of high literacy skilled individuals' reservation wage, then the natural response is a choice of inactivity in the labor market, by the later group. Simultaneously however, it is found that active labor market participation leads to poverty reduction; therefore, in addition to new industrial policies for structural transformation of the economy, policy makers in Burkina Faso should consider education and minimum wage reforms to give highly literate household members the incentive to be active in the labor market.

The influence and importance of research and development (R&D) for business sustainability have gained increasing interests, especially in the high-tech sector. However, the efforts of R&D might cause complex and mixed impacts on the financial results considering the associated expenses. Thus, this study aims to examine how R&D efforts may influence business to improve its financial performance considering the dual objectives: the gross and the net profitability. This research integrated a rough-set-based soft computing technique and multiple criteria decision-making (MCDM) methods to explore this complex and yet valuable issue. A group of public listed companies from Taiwan, all in the semiconductor sector, was analyzed as a case study. Initially, more than 30 variables were considered, and the adopted soft computing technique retrieved 14 core attributes—for the dual profitability objectives—to form the evaluation model. The importance of R&D for pursuing superior financial prospects is confirmed, and the empirical case demonstrates how to guide an individual company to plan for improvements to achieve its long-term sustainability by this hybrid approach.

It is well known that that there is an intrinsic link between the financial and energy sectors, which can be analyzed through their spillover effects, which are measures of how the shocks to returns in different assets affect each other’s subsequent volatility in both spot and futures markets. Financial derivatives, which are not only highly representative of the underlying indices, but can also be traded on both the spot and futures markets, include Exchange Traded Funds (ETFs), a tradable spot index whose aim is to replicate the return of an underlying benchmark index. When ETF futures are not available to examine spillover effects, “generated regressors” are useful for constructing both Financial ETF futures and Energy ETF futures. The purpose of the paper is to investigate the co-volatility spillovers within and across the US energy and financial sectors in both spot and futures markets, by using “generated regressors” and a multivariate conditional volatility model, namely Diagonal BEKK. The daily data used are from 1998/12/23 to 2016/4/22. The data set is analyzed in its entirety, and are also subdivided into three distinct subsets. The empirical results show there is a significant relationship between the Financial ETF and Energy ETF in the spot and futures markets. Therefore, financial and energy ETFs are suitable for constructing a financial portfolio from an optimal risk management perspective, and also for dynamic hedging purposes.

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.

In this study, we examine the relationship of bank level lending and borrowing decisions and the risk preferences on the dynamics of the interbank lending We develop an agent-based model that incorporates individual bank decisions using the temporal difference reinforcement learning algorithm with empirical data of 6600 S. banks. The model can successfully replicate the key characteristics of interbank lending and borrowing relationships documented in the recent literatur A key finding of this study is that risk preferences at individual bank level can lead to unique interbank market structures which are suggestive of the capacity that the market responds to surprising

The use of improved agricultural technologies has been reported as the major strategy to increase agricultural production, increased household incomes and addressing poverty. However, adoption of such improved technologies by smallholder coffee farmers has been slow and this has contributed to the low coffee productivity in the country and the poor performance of the coffee sub sector. The study was meant to examine the effect of institutional factors including extension services, access to market and access to credit on technology adoption among smallholder coffee farmers in Kanungu District, Uganda. The study collected both quantitative and qualitative data from 289 smallholder coffee farmers and 8 key informants respectively in major coffee growing sub counties in Kanungu district. The study revealed that access to extension services and access to market have a positive significant influence on agricultural technology adoption while access to market has no significant influence on agricultural technology adoption. The study concluded that there is a positive significant relationship between institutional factors and technology adoption among smallholder coffee farmers in Kanungu district.

Artificial Intelligence (AI) stands as an emerging technology poised to reshape various facets of our daily lives, with a particularly noteworthy influence on the labor market. In Morocco, AI adoption has commenced in diverse sectors, including finance, insurance, and telecommunications, opening up fresh avenues for employment. Nevertheless, this technological shift also ushers in challenges for Moroccan workers, necessitating training and upskilling to effectively engage with AI-driven systems. Within this article, we delve into the burgeoning impact of AI on the Moroccan economy and job landscape, delving into both the opportunities and obstacles that accompany its proliferation. Furthermore, we explore strategies that authorities and businesses can employ to harness the benefits of AI while mitigating its potential adverse effects on Morocco's workforce.

Descriptive research design was used to select 200 respondents (i.e., 100 from each study places) following purposive sampling technique on two study areas (Market; Living). Personal observation and interview with retailers were done to triangulate the collected data from the formal survey. The collected data was analyzed using SPSS version 20 software program. Descriptive statistical measurements, Index and multinomial regression model was calculated to assess the relationship between customers point of emphasis during packaged water buying and respondents demographic variables. Majority of the respondent who frequently purchase packaged water generated a monthly income between 5000 and 10000 Birr. Television and radio was ranked first compare to other Media. Living place customers were more health concerned as compared to market place customers. Market place customer’s primarily give emphasis to price of packaged water. Almost all (97%) customers did not have the awareness towards packaged water standards. Only 86(43%) of the total respondents checked the chemical composition, of which 74(85%) of the respondents did not understand it. Customers sex, educational level and health status showed significant relationship with choice of packaged water quality -1.42(p<0.05), price -2.45(P<0.01) and health status -1.80(P<0.05) in market place and living places, respectively.

This study investigates the impact of global financial crisis and the present COVID-19 pandemic on daily and weekly Crude oil futures using four variants of ARMA-GARCH models: ARMA-sGARCH, ARMA-eGARCH, ARMA-TGARCH and ARMA- aPARCH with dummy variables We also investigated the persistence, half-life and backtesting of the models. This study therefore seeks to contribute to the body of literature on the impact of global financial crisis and the present COVID-19 pandemic on crude oil futures market. This investigation of the impact of global financial crisis and the COVID-19 on crude oil futures has not been much studied at present. We obtained and analyzed the daily and weekly crude oil futures from secondary sources. Daily crude oil futures used in this study covers the period from the 4th January 2000 to 27th April 2020 while the weekly crude oil futures covered from 2ndJanuary 2000 to 26th April 2020 . The global financial crisis period covered from 2nd July 2007 to 31st March 2009 and the current COVID-19 pandemic covered from 1st January 2020 to 27th April, 2020. The study used both student t and skewed student t innovations with AIC, goodness-of-test fit and backtesting to select the best model. Most of the estimated ARMA-GARCH models are supported by skewed student t distribution while most of the ARMA-GARCH models exhibited high persistence values in the presence of global financial crisis and the COVID-19 pandemic. In the overall, the estimated ARMA(1,0)-eGARCH(2,1) and ARMA(1,0)-eGARCH(2,2) model for daily crude oil futures and weekly crude oil futures respectively have been significantly impacted by the global financial crisis and the Present COVID-19 pandemic while the preferred estimated models also passed the goodness-of-test fit and backtesting.This study recommends shareholders and investors should think outside the box as crude oil futures tend to be affected by global financial crisis and COVID-19 pandemic while countries also that depend mostly on crude oil are encouraged to diversify their economy in other to survive and be sustained during financial and health crisis.

In the context of the economic and political uncertainty associated with the 2019-nCoV pandemic, it is necessary to determine the socio-psychological factors involved in the transformation of the behavior of insurance consumers under the influence of a biogenic threat. This study measures financial anxiety and its impact on the insurance behavior of Russian citizens. The correlation, comparative, and regression analyses of the financial anxiety of Russian citizens cover three stages of observation: before the start of the 2019 nCoV pandemic (“FA up to 19 nCoV; N = 766), during the period of quarantine measures announced in Russia in March 2020 (“FA 19-nCoV-1”; N = 856), and after the relaxation of quarantine measures at the end of April 2020 (“FA 19-nCoV-2”; N = 963).Psychological analysis data were obtained from the online survey “Financial anxiety (in the context of insurance)”. The questionnaire is psychometrically reliable and easy to use. It includes five measurement scales: MR1—Physical manifestations of financial incentive anxiety, MR2—With money shortages and financial uncertainty, MR3—The value of insurance coverage, MP4—Financial Confidence, and MR5—Perception of insurance and investment risks. It was found that Russian citizens consider it important to have insurance coverage for a “rainy day”, and they showed confidence in the insurance market during the biogenic crisis. However, unfortunately, during the 19-nCoV-1 and 19-nCoV-2 periods, Russian citizens did not feel financially secure, unlike in the period before 19-nCoV. Women showed high scores for physical manifestations of financial anxiety and low financial confidence in the future, in contrast to men, regardless of the observation period.

The purpose of this study is to examine the driving model of determinant factors that affects the performance of small and micro enterprises empirical evidence from Amhara Region, Ethiopia. The study used primary and secondary data from manufacturing, construction, urban agriculture, trade, and service entrepreneurs found in Bahirdar, Dessie & Gonder Cities using a purposive sampling technique. It also used the descriptive research design with a self-administered survey questionnaire. The Statistical analysis tools, SPSS and Amos, software were applied to analyze the data. Multiple regression model results revealed that access to credit, initial capital, working premises, industry category, market linkage, ICT adoption have a positive relationship and a major impact on the Amhara region's enterprise performance. Hence, the outcome variable, enterprise performance, is highly affected by all predicted variables. As the study finding shows, a lack of access to credit, , market linkage, working premises), initial capital, and information communication Technology problems are critical challenges of SMEs. The Regional Government, TVED Bureau, Micro Finance Institutions, , should take corrective action to provide sufficient credit and long-term loans to protect inflation. Moreover, this study proposed a sustainable cluster management approach that solves their challenges in an integrated way.

Banking sector is generally taken out of sample while the sustainability performance, and the financial performance are compared with each other. The core aim of this study is to analyze the effect of the declarations made in the cope of sustainability reports on the financial performance in the banking sector. Seven banks were included in the study which were placed at least one time in BIST Sustainability Index in between 2010-2017 years. Environment, human resources, product liability and community involvement were determined as sustainability criteria and return on assets, return on equity and net interest margin were determined as financial performance criteria. Non-Parametric Statistic Tests and Panel Data Analysis were used for analysis and types, and the sizes of banks were selected as dummy variables. As a result, it is found that the declarations of sustainability reports have a significant effect only on return on assets and have no significant effect on return on equity and net interest margin. And also, when we analyzed the relationship of sustainability criteria and return on assets, we found that the declarations about environment and human resources have negative effects on return on assets.

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.

Considering the impact of religiosity on the perceptions regarding life quality, in this paper we focus on the effects of the appurtenance to a religion on the standard of living in several economically developing countries (Turkey, Ukraine, Senegal and Morocco). The data have been collected using a survey carried out in 2012 and the empirical analysis was based on non-parametric tests and multinomial logistic regression. The results indicate there are differences between religious persons and atheists regarding gender, marital status, perceptions of daily life and standards of living. Females and officially married people or single people tend to be more religious. A person claiming to belong to a religion has 2-4-fold more chances to achieve a considerable improvement in the standards of living as compared to an atheist. Moreover, religious people from the analyzed countries are more optimistic about their life overall. Taking into account the sample’s characteristics and the countries chosen, we can claim that the results obtained are truly cross-cultural in nature. Moreover, most of the conclusions reached would be to some extent relevant to other developing economies of Eastern Europe, North Africa and Middle East.

The authors propose in this study to evaluate financial performance applications for stock prices of the Indonesian Stock Exchange in manufacturing companies. The method of research used here is a quantitative descriptive method. In that statement, Indonesian Stock Exchange manufacturing companies between 2016 and 2018 are the population use in this research, using the sampling technique Purpose Sampling. This research uses secondary data from 2016 to 2018, the financial reports of Indonesian Stock Exchange manufacturing companies. The Indonesian stock exchange web site has been provided with all data sources at https://www.idx.co.id, and searching for www.google.id. Our analysis shows that book value prices and the net profit margin affect stock prices. The value of financial performance at the Indonesian Stock Bourses manufacturing companies' cost amounts to 64.5 percent, while other factors not listed in this study account for 35.4 percent.

The relationship between economic growth, growth volatility and financial sector development continues to attract attention in the theoretical and empirical literature. Over time, some studies hypothesize that finance has a causal linear relationship with growth. Recently several other authors contradict this claim and argue that the relationship that exists between finance and growth is nonlinear. We investigate these claims for Nigeria for the period between 1970 and 2015, using semi-parametric econometric methods, Hansen sample splitting techniques and threshold estimator. We observed no evidence of ‘Too much finance’ as claimed by many researchers in recent times. We show that the relationship between financial development and economic growth is U-shaped. This is equally true for the relationship between financial development and growth volatility. We also discuss policy implications of our findings and recommend financial innovations and decentralization of stock exchanges to boost access to financial services, in addition, improved regulation to enhance financial market efficiency.

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.

There has been rampant fold-ups, merger and acquisitions occurring in the Ghanaian banking industry. Then, the questions arise: Is the Ghanaian Financial System in Crisis? This study was conducted to find answers to these problems unsolved with prior literature. A sample of seventy customers of the Royal Bank, 8 employees of the Royal Bank and 2 managers of the Royal Bank were selected for a case-survey. The study also monitored the Trend of the Ghanaian Financial System through the reading and monitoring of daily news on the Financial System and reports of banks. The data from the field and the secondary data from news and reports were analysed symmetrically. The study drew on Minsky’s Financial Crisis Theory to explain the phenomenon in the Ghanaian economy and to draw predictions of what would happen in other developing economies. The study found out that: (1) The Ghanaian financial system is fragile and it holds true for most developing economies; (2) The financial system suffers greatly when the confidence level of customers falls significantly; (3) Management information systems raises the confidence level of customers (borrowers and lenders) such that there is a greater fall and impact in times of instability in the economy; (4) The higher the level of MIS adoption in an unstable economy, the more fragile the Financial System becomes and (5) A higher adoption of Management Information Systems in a Fragile Financial System indirectly contributes to Financial Crisis of the Financial System.

Time irreversibility, i.e. the lack of invariance of the statistical properties of a system under time reversal, is a fundamental property of all systems operating out of equilibrium. Time reversal symmetry is associated with important statistical and physical properties and is related to the predictability of the system generating the time series. Over the past fifteen years, various methods to quantify time irreversibility in time series have been proposed, but these can be computationally expensive. Here we propose a new method, based on permutation entropy, which is essentially parameter-free, temporally local, yields straightforward statistical tests, and has fast convergence properties. We apply this method to the study of financial time series, showing that stocks and indices present a rich irreversibility dynamics. We illustrate the comparative methodological advantages of our method with respect to a recently proposed method based on visibility graphs, and discuss the implications of our results for financial data analysis and interpretation.

The present study reports a critical review of NIO's business model, considering the evolving landscape of the electric vehicle market and servicing. The objective of this study is to develop a comprehensive framework that facilitates the identification of key elements characterizing a company's business model and highlights ongoing transformations, crucial for adaptation and survival in a rapidly changing environmental context. Focusing on the case study of NIO, a relatively young Chinese original equipment manufacturer (OEM) specializing in high-tech electric cars, the research delves into the challenging scenario of the Chinese electric vehicle market, which has recently faced a bubble in 2023. The market proliferation, supply chain disruptions, and price wars triggered by Tesla have resulted in a survival struggle for numerous automotive startups, leaving larger companies with increasing market shares. Despite facing adversities, NIO managed to secure a promising segment, catering to premium-range battery electric vehicles (BEVs), establishing a competitive advantage through differentiation. By pursuing ambitious investments, the company aims to create economies of scope and achieve cost leadership, venturing into new market sectors and vertically integrating the production chain. Given NIO's agility in adapting to market conditions, aggressive entry into new segments, and a strategic vision for the future, it serves as an excellent candidate for testing and validating the proposed framework. The research sheds light on NIO's trajectory and offers insights into its potential for sustained growth in the dynamic electric vehicle market.

Since the early 21st century, the globalization trend and technological innovations have changed the ways and speed of market growth. Rapid market expansion and the pressure for firms to achieve sustainable business growth via mergers and acquisitions have become the norms for acquiring the necessary competencies, expanding market shares and business integrations. This study explains the factors that correlate to the IJM's financial performance based on the market dynamics in recent years. This case study is a qualitative approach employing systematic review and content analysis. As a result, firms begin to diversify or venture into the business segments that might be related to or complement their core businesses, intentionally or unintentionally, which eventually evolved into the conglomerate form. This case study provides a financial performance analysis of IJM Corporation Berhad's success and challenges from its conglomerate business model. The fact that a well-diversified firm will have better risk management in the event of an economic downturn is also a primary driver for firms to embark on a corporate diversification strategy. This case study reveals IJM's conglomerate model has been successful during its rapid business growth; however, it has shown signs of diminishing in recent years.

The World economy after global crisis of 2008–2009 entered a restructuring era. It defines relevance of researches of its directions and patterns. The principles of determinism and systemic analysis are methodological basis of article. In research were used the methods of processing Big Date, as of continuous changes and the symmetric analysis of macroeconomic indicators according to databases of the IMF, WB, BIS, the Central banks and treasuries. As a result of the research it is proved that depth and globalism of recessionary processes are caused by a combination of crisis of world financial system and civilization problems. Intrinsic signs of risks in the modern economy caused by the duality of the nature of global crises have been identified. There are analyzes: the deficit of resources of the international financial institutions, a negative role of a fixed rate of Yuan, a big share of derivatives and off-balance obligations of banks, use of SPV in structures of deals, growth of debt obligations, trade wars, slowdown in the growth of the Chinese economy, aggravation of contradictions between global and national finances. The thesis is reasonable that deglobalization and dedollarization deepened this conflict, started the rollback mechanism from achievements of globalization, led to tariff wars. By means of a systematization it is proved the key directions of the restructuring of global economy: legal basis, leadership and reserve currency. On the basis of SWOT-analysis of the USA and China it was concluded that the question of leadership of one country should be excluded, but slow transition to use SDR (with a basket from 15–20 currencies) as a reserve.

Electric Vehicles (EVs) are increasing the interdependence of transportation policies and the electricity market. EMMEV (Electricity Market Model with Electric Vehicles) is an experimental agent-based model that analyses how carbon reduction policy in transportation may increase number of Electric Vehicles and how does that would influence on the electricity price. Agents are ESCOs (Energy Service Providers) which can distribute fuels and their objective is to maximize their profit. In this paper, EMMEV is used to analyze the impacts of the LCFS (Low Carbon Fuel Standard), a performance-based policy instrument, on electricity prices and EV sales. The agents in EMMEV/regulated parties in LCFS should meet a certain CI (Carbon Intensity) target for their distributed fuel. In case, they cannot meet the target, they should buy credit to compensate for their shortfall and if they exceed, they can sell their excess. The results, considering the assumptions and limitations of the model, show that the banking strategy of the agents contributing in the LCFS might have negative impact on penetration of EVs, unless there is a regular Credit Clearance to trade credits. It is also shown that the electricity price as result of implementing the LCFS and increasing number of EVs has increased between 2–3 percent depending on banking strategy.

There have been many discussions on the globalisation of SMEs, but it is true that there is not enough academic achievement after such the study of Born global (BG) ventures. The internationalisation of SMEs (Small and Medium Enterprises) is not easy because they lack resources or capabilities compared to multinational corporations. This study investigated the role of government in assisting the internationalisation of SMEs. In particular, SMEs lacked the ability to acquire market-oriented information, so we’ve established the scheme of efficient information support system for the internationalisation of SMEs. In other words, we proposed an information analysis system through the establishment of a relational database constructed for market-oriented information support. KISTI (Korea Institute of Science and Technology Information), which is one of the government-funded research institutes in the Republic of Korea, provided information support to the SMEs dealing with hydrazine related products. This study suggests this case for the market-oriented information support of the government in the internationalisation of SMEs. The research on information support of the government is meaningful in that it suggests a way to support SMEs in practical level.

This research suggests a multi-stakeholder framework to increase the use of fintech in Africa, which would help the continent boost its financial inclusion and reach its Sustainable Development Goals (SDGs). The study evaluates previous research and frameworks that have been created to aid in the adoption of fintech by several stakeholders in developing nations, some of which have been tested in African nations with limited success. To begin with, the study suggests the use of the World Bank’s Maximising Finance for Development (MFD) approach through the prioritization of national ownership, creation of an enabling environment for private sector investment, partnering with multilateral development banks and other stakeholders, fostering innovation and digital literacy, and focusing on cost-effective, non-government guaranteed financing. In the same vein, in line with the G20’s High-Level Principles for Digital Financial Inclusion, the adoption of financial technologies and digital financial services in Africa can be promoted through the creation of a country-specific strategy. Each government can create a regulatory environment that encourages innovation and competition, improve its digital infrastructure, increase its digital literacy and awareness, and collaborate with private sector stakeholders to expand financial inclusion. Furthermore, The Better Than Cash Alliance’s strategy to increase fintech adoption can also be implemented through partnership with businesses, international organizations, and other nations. By joining the Alliance, countries can enact rules and regulations that facilitate fintech adoption, promote awareness and education, and design and execute national digital payment infrastructure with the help of fintech companies. Finally, the mSTAR initiative suggests collaborating with USAID, in order to provide support to underrepresented populations, incorporate digital financial services, increase public-private collaboration, and educate and train policymakers, practitioners, and technologists. By implementing these strategies, African nations can accelerate the adoption of fintech solutions and increase financial inclusion.

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.

Financial capacity instruments are psychometric tools designed to evaluate individual decisional capacity based on financial decisions. As tests are complex and need special conditions for administration and evaluation, it is difficult to use them in daily geriatric clinics. Our scoping review objective was to evaluate existing financial capacity instruments from the perspective of simplicity and portability. We evaluated one English speaking knowledge database (Medline) using a dedicated MeSH terminology. The review yielded one independent instrument, The Semi-Structured Clinical Interview for Financial Capacity, that can be easy adapted for every-day clinical use. It is simple to understand and perform and do not need trained personnel for administration. It can be finalized in 15 minutes. Initially validated on 261 subjects (with different forms of cognitive impairment), it showed good accuracy and precision mainly in subjects with cognitive impairment. The test is less apt to detect early or fluctuating cognitive impairment. Simplicity, the main advantage of the test, allows gamification fact that increases portability. Familiar images (coins, money) that are used for performing simple tasks does not need complex translation and adaptation. In form of a game, the test is suitable for serial administration, increasing the chance for early capacity reduction detection. Results reflect a physician judgement related to the subjects’ capacity to understand and execute simple financial instructions and not financial proficiency scores. The main limitation of our review is that we investigated only one, English speaking, knowledge database. The scoping strategy generated a financial capacity instrument that can be used in geriatric clinics for early diagnostic of decisional capacity reduction. Further studies are needed to evaluate the reliability and validity of the test in conditions of serial administration and in populations having various financial experience.

The commitment of the EU to Corporate Social Responsibility (CSR) is projected in the EU law about annual reporting by businesses. Since EU member states further develop this framework by their own domestic laws, annual reporting with CSR information is not unified and just partially mandatory in the EU. Do all European businesses report CSR information and what public declaration to society do they provide with it? The main dual purpose of this paper is identifying the parameters of this annual reporting duty and studying the CSR information provided by the ten largest Czech companies in their annual statements for 2013-2017. Based on legislative research and the teleological interpretation, the current EU legislative framework with Czech particularities is presented and, via a case study exploring 50 annual reports, the data about the type, extent and depth of the CSR is dynamically and comparatively assessed. It appears that, at a minimum, large Czech businesses satisfy their legal duty and e-report on CSR in a similar extent, but in dramatically different quality. Employee matters and adherence to international standards are used as a public declaration to society more than the data on environmental protection, while social matters and R&D are played down.

: A strong financialtransaction is an important factor in organizational triumph and sustainability, and it is elucidated in the revised student handbook of the University that can be found on page 96 rules 1 to 5. This study assessed the registered students organizations' profile in terms of its type, registration, years of establishment, functions, and designations of student leaders and advisers. The financial practices or internal control system manages their organizational finances and the problems encountered by the student organizations and eventually proposed a manual of operation for students and youth organization's internal control system. This research used the descriptive design with the aid of questionnaire; data gathering through quota sampling from 57 student leaders and advisers of different student organizations of NEUST. Findings showed that most organizations had their constitution and by-laws but kept only as files and renewal requirements. Some provisions were not known to the officers, mostly were registered more than five years in operation; however, in terms of functions of officers and advisers, the results showed that some functions were not done by the officers who supposed to do it like the auditors who serve as treasurers also, the PRO as the record keeper and the presidents who handled finances and collections and as well as disbursements of funds. Generally, the organizations' financial activities were deemed to be "good", especially budgeting and cash receipt, due to the implementation of "no collection and no tuition fee policy". The researchers concluded that the absence of the proper internal control systems and manual of operation and lack of proper transfer of financial records from the previous sets of officers were the serious problems that should be addressed. Moreover, the student organizations' internal control system could still be improved if there is proper training and supervision in accounting operation.

This paper relies on accounting-based measures of country risk to investigate U.S. global banks' exposure to foreign country risk over the 2017 fiscal year as measured by the sum of cross-border risk, foreign office risk, and derivative risk claims. We achieve this using panel linear modeling methods with country level heterogeneity and time fixed effects, along with a constructed panel data of 284 observations on 71 countries distributed across 6 world regional blocks, and observed over 4 consecutive quarters starting from 4th quarter 2016 and ending with 3rd quarter 2017. The results show that on average, over the four quarters, a 1% increase in foreign banking sector's claims significantly increases U.S. global banks cross border risk exposure by 0.34%, while reducing derivative risk exposure by 0.22%, but have no significant impact on foreign office risk exposure. Similar results are observed with public sector claims which significantly increase banks' exposure to cross border risk by 0.21%, while reducing derivative risk exposure by 0.19%. Conversely however, non-bank financial sector claims are found to have no significant affect on cross-border risk exposure, but significantly reduce foreign office risk exposure by 0.09%, while increasing derivative risk exposure by 0.06%. These results indicate the presence of sectoral heterogeneities in U.S. banks' exposure to foreign counterparties' risk, and also that overall, over the course of 2017 the level of U.S. global banks' cross-border risk exposure increased, while their level of derivative risk exposure decreased, and the level of foreign office risk exposure remained relatively unchanged.

The aim of this study was to determine the impact of information technology in management of risks in the capital market-listed company is in Tehran Stock Exchange. The purpose of the present study is an applied descriptive approach. The target population for the survey, companies that from 2009 to the first half of 2015 have been a member of the Tehran Stock Exchange, through Cochranʼs sample size of 140 companies, respectively. We used cluster sampling method. In order to collect data from two questionnaires: risk management questionnaire Foakeh (2013) has 38 items and a standard questionnaire Chanvyas (2006) has 40 items, the whole five-item Likert scale questionnaire is above has been used. Data gathered through the questionnaire, sign the application was 21spss. For inferential analysis of the variables and to analyze the data from different statistical tests and regression was used Kolmogorov-Smirnov test. The results showed that information technology on risk management and its dimensions (primary market risk, market risk and the risk of secondary non-financial) impact.

Financial statement analysis is an analysis that uses analytical procedures to evaluate a company's financial health, risks, performance, and future growth potential. This article aims to find out the application of analysis of financial statements of PT. Astra Internasional, Tbk towards the decision-making of novice investors in the Indonesian capital market. This article is qualitative descriptive with literature studies. The results of this article can be concluded that the analysis of the financial statements of PT. Astra Internasional, Tbk can help novice investors in the Indonesian capital market in making investment decisions.

This study will investigate different signals and events/news that determined the stock market's movements. As we know, many factors affect the stock market on a daily, weekly, and monthly basis, e.g., rate of interest, exchange rate, and oil prices, etc. Our research will investigate the impact of daily events/news in the KSE-100 index due to several policies announced and events/news in the country because the daily movements in the stock market can be determined only by different signals and events/news. Time series data is collected daily for particular reasons from "The News" (Daily Newspaper, Sunday edition) from 2010 to 2019. The results of this study show that political and global news affects the stock market index ferociously. For investors, the investment in blue chips is not less than a safe haven. When day-to-day transactions are concerned, there is always a higher panic attack than the herd behaviour in the stock exchange. Investors tend to make prompt responses to negative rather than positive news, which makes them risk averters. Our finding also confirmed that the ARCH/GARCH model is better than the simple OLS method concerning stock market upheaval.

This paper examines the effect of chronotype on the delinquent credit card payments and stock market participation through preference channels. Using an online survey of 455 individuals who have been working for 3 to 8 years in companies in mainland China, the results reveal that morningness is negatively associated with delinquent credit card payments. Morningness also indirectly predicts delinquent credit card payments through time preference, but this relationship only exists when individuals’ monthly income is at low and average level. On the other hand, financial risk preference accounts for the effect of morningness on stock market participation. Consequently, an additional finding is that morningness is positively associated with financial risk preference, which contradicts previous finding in the literature. Finally, based on the empirical evidence, we discuss the plausible mechanisms that may drive these relationships and the implications for theory and practice. The current study contributes to the literature by examining the links between circadian typology and particular financial behaviours of experienced workers.

In areas with strongly seasonal climates, local people often use complex strategies to manage agricultural production shortages, including diverse activities such as hunting, selling and consuming non-agricultural products, and wage labor. We surveyed all the households in a village in northern Laos to evaluate how such livelihood activities varied during years with differing agricultural production conditions. We compared two years with normal rice production conditions (2010, 2012) and one year with a severe rice shortage (2011) due to a rodent outbreak. Earning wages inside and outside the village was the most important activity for mitigating rice shortages, followed by selling livestock and using/selling non-timber forest products. Villagers also borrowed rice from a village rice bank. Most cash income was earned from selling rice. We concluded that a balance of traditional risk management activities under the swidden system (e.g., raising livestock) with the more recent rice bank system and wages from the market economy will be critical for the sustainable development of mountain villages in northern Laos. Permanent crops and monocultures tend to make local livelihoods more dependent on a single crop, but maintaining the traditional swidden system will help local people to manage agricultural production shortages.

The striving for sustainable development has become the goal of actions undertaken not only by representatives of public authorities and institutions representing this sector, but also representatives of private entities who are increasingly recognizing the benefits and sources of long-term development based on the principles and objectives of sustainable development. These are mainly based on the pursuit of synergy in the three basic areas of activities, i.e., in the economic, social, and environmental dimensions as well as in the maintenance of natural resources. The implementation of these activities is connected with the necessity of incurring financial expenditures, which the government (public sector) does not have in the required value. Therefore, in the process of sustainable development for which the government is responsible, the active participation of the financial sector (banks) is necessary. Achieving results within the alliance of the concept of sustainable development requires the setting of a kind of contract, the parties of which are the government, society, and financial institutions. The purpose of the conducted research is to indicate by which means the government and the financial sector can stimulate economic growth towards its sustainable development.

Forest certification is considered a viable market-based policy instrument to promote forest sustainability. It has an important role of play in meeting the objective of modern forestry development in China, which is to sustain ecological and environmental benefits of forests. To understand differences in attitudes, opinions, and interests in forest certification, this study segmented respondents of a landowner’s survey in Shandong, China based on their level of interest in participating in forest certification under different program requirements. Multivariate cluster analysis revealed three distinct groups: likely-, potential-, and unlikely-landowners. We further examined the heterogeneity of these groups in terms of their demographics, ownership characteristics, management objectives, and perceived benefits and challenges with adopting forest certification. The results suggested the necessity of differentiating landowners in formulating and designing specific motivation-based incentives and tailor outreach efforts and communication strategies to improve their interests in forest certification. Findings are useful and interesting to forest policymakers interested in promoting forest certification among landowners in China and other countries facing similar circumstances.

China combines green energy and industrial policy in its power market reform with various policy initiatives, including price support scheme for electricity from renewable sources and subsidies in the push for broader use of greener energy. This study focuses on the impacts of power market reform on the stock price volatility of listed power companies: 1) we use the Iterative Cumulative Sums of Squares (ICSS) algorithm to identify structural break points in stock prices; 2) we analyze the characteristics of stock price volatility based on the GARCH model; 3) we report the impact of power regulation on stock price fluctuations based on the Autoregressive Distributed Lag (ARDL) model. The result suggests three structural breaks in China’s power stock price volatility were related to the promulgation of power market reform policies. We find that industrial policies promote the reduction of power stock price fluctuations and its impact on power stock price volatility is consistent in the long run. However, our study also indicates the recent policies related to renewable energy do not have a very significant impact on the power stock market.

The quality of an educational system is reflected not only in the instructive performances of the educational actors, but also in the degree in which it ensures an adequate professional integration. The undergraduate of today, the graduate of tomorrow needs an as accurate as possible information regarding the labour market, which cannot be achieved only by individual means, but also by resorting to carrier counselling services. The motivation of this research is closely connected to the improvement of the level of communication between the two aspects – on the one hand the academic one, by its finite products, and the economic one, on the other hand – and the opportunities that the cooperation between the two aspects might offer: adjusting the demand-supply ratio on the labor market and above all, stopping massive emigration of young graduates of higher education.

Does the choice of proxy for stock market development matter? This paper suggests that the growth effect of stock market development is sensitive to the choice of proxy and using alternative financial development indicators have practically no influence on the results. We found that using either the stock market capitalization to GDP ratio or the stock market returns; have a positive and significant effect on growth. However, we cannot make same conclusion when one uses either the ratio of total value of trades on the major stock exchanges to GDP or stock market turnover ratio to proxy for stock market development as the coefficient on these variables were found to be statistically insignificant. The indexes extracted from principal component analysis confirm the sensitivity of the effect to the choice of proxy. This finding suggest that stock market development is a conceptual terms, thus, representing it with single indicators make it impossible to identify which stock market development indicators have a significant positive growth effects.

This paper analyzes if the Financial Fair Play (FFP) regulations set by UEFA have influenced the auditing fees charged to the football clubs. In addition, it explores the determinants of audit fees. We use a two-sample t test with equal variances to determine whether differences are present. After this, we carry out a panel data regression with clubs fix effect to estimate the determinants of audit fees in football clubs. Our findings reveal an increase of audit fees after the implementation of FFP regulations. On top of that, audit fees are explained by the presence of foreign investors if the audit firm is one of the Big4 and if the auditor is a woman. The regulation change has an impact on the audit fees charged by auditors for their services. However, this increase can be compensated across future years given the improving financial situation of clubs; therefore, the auditors’ risk diminishes and subsequent audit fees may be reduced. UEFA should monitor audit fees as well as the quality of the audit reports, which have become crucial to obtaining the license to participate in UEFA competitions.

The paper investigated the components of savings accumulation in Nigeria over the period 1980 to 2017. Secondary data were collated from World Development Index (WDI). In evaluating the objectives, the study employed the Auto Regressive Distributive Lag (ARDL) and Vector Error Correction Model (VECM) estimation methods. The key findings of the study show that the components of savings identified in literature understudied in the paper specifically, GDP per capita, foreign direct investment, financial deepening, interest rate, inflation rate exchange rate significantly influence savings accumulation in Nigeria either in short run, long run or both. Financial deepening was found statistically significant but influences savings negatively. Inflation rate was statistically insignificant although negative. The result from the VECM causality test revealed that short run and long run causal relationship exist between savings and the afore mentioned components in Nigeria. Hence, the study recommends careful manipulation of the identified savings components in a manner that they will not yield a counterproductive result in the economy rather contribute to the growth of savings and ultimately, the growth of Nigeria economy as a whole. It further recommends that the Nigerian government through its financial institutions encourage savings from both small and big savers which to large extent will assuage the perceived undeserved influence of financial deepening on savings accumulation.

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.

For automobile insurance, it has long been implied that when a policyholder made at least one claim in the prior year, the subsequent premium is likely to increase. When this happens, the policyholder may seek to switch to another insurance company to possibly avoid paying for a higher premium. In such situations, insurers may be faced with the challenges of policyholder retention by keeping premiums low in the face of competition. In this paper, we seek to find empirical evidence of possible association between policyholder switching after a claim and the associated change in premium. In accomplishing this goal, we employ the method of association rule learning, a data mining technique that has its origins in marketing for analyzing and understanding consumer purchase behavior. We apply this unique technique in two stages. In the first stage, we identify policyholder and vehicle characteristics that affect the size of the claim and resulting change in premium regardless of policy switch. In the second stage, together with policyholder and vehicle characteristics, we identify the association among the size of the claim, the level of premium increase and policy switch. This empirical process is often challenging to insurers because they are unable to observe the new premium for those policyholders who switched. However, we used a 9-year claims data for the entire Singapore automobile insurance market that allowed us to track information before and after the switch. Our results provide evidence of a strong association among the size of the claim, the level of premium increase and policy switch. We attribute this to the possible inefficiency of the insurance market because of the lack of sharing and exchange of claims history among the companies.

Of course, now we know that quantum mechanics has been a fundamental structure of our world since our universe came into being. However, it has been only a century since the experimental and theoretical discovery of quantum mechanics and its extensions into many implications and applications. In particular, there are implications across many disciplines that most likely will affect education, health, security, etc. Examples are given of the need for starting education as early as possible in schools, the use of nano-robots to deliver drugs targeted to specific molecular sites, to developing new cryptographic systems to safeguard our privacy.

The study's motivation is to gauge the nexus between economic policy uncertainty and financial innovation for the period 2004M1 to 2018M12 in BRIC nations. For establishing a long-run cointegration study applied Autoregressive Distributed Lagged (ARDL) and asymmetry effects of economic policy uncertainty investigated following nonlinear framework known as NARDL. Furthermore, directional causality is established by performing a non-granger causality test. Cointegration test results of Fpss, Wpss, and tBDM confirmed the long-run association between EPU and financial innovation. On the other hand, the Wald test results proved asymmetry effects furring from EPU to financial innovation both in the long-run and short-run. Referring to asymmetry effects that positive and negative shocks in financial innovation, the study revealed that negative linkage between shocks in EPU and financial innovation in the long-run but short-run effects are insignificant. Furthermore, financial innovation measured by R&D investment exhibits positive linked with shocks in EPU, implying that uncertainty induces innovation in the economy. Refers to directional causality estimation, the study revealed evidence supporting the feedback hypothesis between EPU and financial innovation in all sample countries.

In the context of economic and political uncertainty associated with the 2019-nCoV pandemic, it is necessary to determine the socio-psychological factors in the transformation of the behavior of insurance consumers under the influence of the biogenic threat. This study is devoted to measuring financial anxiety and its impact on the insurance behavior of Russian citizens. Correlation, comparative and regression analyzes of financial anxiety of Russian citizens cover three stages of observation: before the start of the 2019 nCoV pandemic (“FA up to 19 nCoV; N = 766), during the period of quarantine measures announced in Russia in March 2020 (“ FA 19- nCoV-1 "; N = 856) and after the relaxation of quarantine measures at the end of April 2020 (" FA 19-nCoV-2 "; N = 963). Psychological analysis data were obtained from the online survey "Financial anxiety (in the context of insurance)". The questionnaire is psychometrically reliable and easy to use, including 5 measurement scales: MR1. Physical manifestations of financial incentive anxiety, MR2. With money shortages and financial uncertainty, MR3. The value of insurance coverage, MP4. Financial Confidence, MR5. Perception of insurance and investment risks. Russian citizens considered it important to have insurance coverage on a “rainy day” and showed confidence in the insurance market during the biogenic crisis. But, unfortunately, Russian citizens during the 19-nCoV-1 and 19-nCoV-2 periods did not feel financially secure in the future, unlike the period before 19-nCoV. ”Women showed high scores for physical manifestations of financial anxiety and low financial confidence in the future, in contrast to men, regardless of the observation period.

The purpose of this study is to examine the driving model of determinant factors that affects the performance of small and micro enterprises empirical evidence from Amhara Region, Ethiopia. The study used primary and secondary data from manufacturing, construction, urban agriculture, trade, and service entrepreneurs found in Bahirdar, Dessie & Gonder Cities using a purposive sampling technique. It also used the descriptive research design with a self-administered survey questionnaire. The Statistical analysis tools, SPSS and Amos, software were applied to analyze the data. Multiple regression model results revealed that access to credit, initial capital, working premises, industry category, market linkage, ICT adoption have a positive relationship and a major impact on the Amhara region's enterprise performance. Hence, the outcome variable, enterprise performance, is highly affected by all predicted variables. As the study finding shows, a lack of access to credit, , market linkage, working premises), initial capital, and information communication Technology problems are critical challenges of SMEs. The Regional Government, TVED Bureau, Micro Finance Institutions, , should take corrective action to provide sufficient credit and long-term loans to protect inflation. Moreover, this study proposed a sustainable cluster management approach that solves their challenges in an integrated way.

This is a theoretical and empirical article. In the first part, an original definition of the cross-border market for cultural services has been developed, based on classic market definitions. The structure and conditions of functioning for this market have also been presented. The next part of the article discusses the supply side of the cross-border market of cultural services for the two twin towns: Cieszyn (Poland) and Český Těšín (Czech Republic). Next, based on the surveys conducted, the participation of residents of both towns in the most important cultural events organised by cultural institutions on both sides of the border was examined.

The idea of the current research started from noticing a major gap in the customer behavior literature - researchers scarcely analyzed the impact of scandals on the customer purchase decision in the case of celebrity endorsement. Using a quantitative approach based on questionnaires, 101 people were asked about their opinions, the goals being to find out if people are influenced by the celebrity scandals, if people tend to have different reactions in terms of consumer purchase decision when it comes to various different negative actions carried on by the endorsers - will a murder upset the customers more than an infidelity scandal? - and if there are any differences in treating Romanian and foreign celebrities once they would enter into such a scandal.