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Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Machine learning has been applied by more and more scholars in the field of quantitative investment, but traditional machine learning methods cannot provide high returns and strong stability at the same time. In this paper, a multimodal model based on reinforcement learning (RL) is constructed for the stock investment portfolio management task. Most of the previous methods based on RL have chosen the value-based RL methods. Policy gradient-based RL methods have been proven to be superior to value-based RL methods by a growing number of research. Commonly used policy gradient-based reinforcement learning methods are DDPG, TD3, SAC, and PPO. We conducted comparative experiments to select the most suitable method for the dataset in this paper. The final choice was DDPG. Furthermore, there will rarely be a way to refine the raw data before training the agent. The stock market has a large amount of data, and the data are complex. If the raw stock market data are fed directly to the agent, the agent cannot learn the information in the data efficiently and quickly. We use state representation learning (SRL) to process the raw stock data and then feed the processed data to the agent. It is not enough to train the agent using only stock data; we also added comment text data and image data. The comment text data comes from investors' comments on stock bars. Image data are derived from pictures that can represent the overall direction of the market. We conducted experiments on three datasets and compared our proposed model with 11 other methods. We set up three evaluation indicators in the paper. Taken together, our proposed model works best. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid approach that integrates fuzzy multi-criteria decisionmaking with multi-objective mathematical optimization to address the investment management problem in the Iranian capital market under interval uncertainty. To achieve this, we first employ the fuzzy SWARA method to assess the global importance of the criteria weights. Subsequently, we develop a fuzzy EDAS method to rank the active industries in the Iranian capital market, including basic metals, chemical products, investment services, metal ore mining, financing, insurance, pension funds, and social security. Next, we present a mathematical model to determine the optimal investment amount for each ranked alternative. According to the numerical results, the most critical criteria for evaluating different investment areas are access to financial resources, distribution networks, and raw materials. The highest optimal share of investment is associated with Fars 1, while the lowest value pertains to Gharn 1. When solving the model under conditions of uncertainty, we observe that increasing parameter Γ1 from small to large values decreases the value of the first objective function for the most efficient Pareto member. However, when Γ1 exceeds 10, the value of the first objective function stabilizes. Additionally, the third objective function shows an increasing trend as the parameter Γ3 decreases. The results obtained can serve as a managerial tool for stakeholders involved in research participation. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid approach that integrates fuzzy multi-criteria decision-making with multi-objective mathematical optimization to address the investment management problem in the Iranian capital market under interval uncertainty. To achieve this, we first employ the fuzzy SWARA method to assess the global importance of the criteria weights. Subsequently, we develop a fuzzy EDAS method to rank the active industries in the Iranian capital market, including basic metals, chemical products, investment services, metal ore mining, financing, insurance, pension funds, and social security. Next, we present a mathematical model to determine the optimal investment amount for each ranked alternative. According to the numerical results, the most critical criteria for evaluating different investment areas are access to financial resources, distribution networks, and raw materials. The highest optimal share of investment is associated with Fars 1, while the lowest value pertains to Gharn 1. When solving the model under conditions of uncertainty, we observe that increasing parameter ⌈1 from small to large values decreases the value of the first objective function for the most efficient Pareto member. However, when ⌈1 exceeds 10, the value of the first objective function stabilizes. Additionally, the third objective function shows an increasing trend as the parameter ⌈3 decreases. The results obtained can serve as a managerial tool for stakeholders involved in research participation. [ABSTRACT FROM AUTHOR]

The Association of Southeast Asian Nations (ASEAN) region has been experiencing a vibrant economy with heavy investment in higher education as an economic development driver. Being home to over 630 million people and more than 7,000 higher education institutions (HEIs) and over 12 million students, it was critical to evaluate the role of cross-border higher education in the region. This study aimed to investigate the factors and motivations contributing to the success and efficacy of cross-border higher education in the ASEAN region. Additionally, it sought to examine the impact of cross-border education on the development of global citizenship. A quantitative study was conducted using secondary data from the repositories of the World Bank and UNESCO Institute for Statistics (UIS). Data was analyzed using descriptive visualizations and regression analysis. Results indicated variations in HEIs investments, with Brunei having the least. Many students moved from the ASEAN region to seek higher education in other regions, with Vietnam having the highest number of 137,022 students. The majority of these ASEAN countries have more than 10,000 higher education students' abroad. The United States, Australia, and Japan were the significant destinies of students from the ASEAN region. Government expenditure on tertiary education, gross domestic product (GDP), tertiary school enrolment, and GDP growth rate were found to have a significant influence on cross-border higher education mobility. Policy recommendations were the development of international collaborations, cross-border partnerships, and cross-national harmonization to enhance the partnership and mobility of higher education students in the ASEAN region. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Common prosperity is an important goal of China's modernization efforts, and narrowing the income gap among different regions and populations is crucial to achieving common prosperity. The construction of digital infrastructure has significantly boosted productivity and facilitated the diffusion of technology in less developed regions, leading to notable changes in labor employment and the income gap, which aligns with the goal of common prosperity. This paper explores the mechanism through which digital infrastructure influences common prosperity with a focus on employment, using panel data from 30 provinces in China between 2011 and 2021 for an empirical test. The research finds that digital infrastructure significantly promotes common prosperity. By expanding employment and increasing labor remuneration, the influence of digital infrastructure on common prosperity exhibits regional heterogeneity and a nonlinear threshold effect. The research suggests that the government should enhance investment in and construction of digital infrastructure, reduce the digital divide through policy support in rural areas, promote digital employment and skills training, and encourage industrial integration and enterprise participation. [ABSTRACT FROM AUTHOR]

Investment plays an increasing role in promoting economic diversification, and this only succeeds if it is managed effectively. Economic diversification is a crucial feature of supportable progress, as divergence improves economic steadiness and support to surge GDP and encourages organisational and long standing change not only in the budget but also in extra columns of expansion such as communal establishments and proportions. Nevertheless, there is no accord on the consequences in the literature review for the reason that of several influences, for example the employment of dissimilar variable quantity, methods, KSA countries, and time periods. Thus, this work provides detailed insight into the current and future trends and shifts of the Saudi economy. The paper conducts a measurement and analysis of the Saudi economic diversification in light of Vision 2030, the findings of which are used to develop and propose a study framework for developing a dynamic economy.

Objectives: To employ a drug supply chain information system to optimize drug management practices, reducing costs and improving efficiency in financial and asset management. Methods: A digital artificial intelligence + vendor managed inventory (AI+VMI)-based systemfor drug supply chain information management in hospitals has been established. The system enables digitalization and intelligentization of purchasing plans, reconciliations, and consumption settlements while generating purchase, sales, inventory reports as well as various query reports. The indicators for evaluating the effectiveness before and after project implementation encompass drug loss reporting, inventory discrepancies, inter-hospital medication retrieval frequency, drug expenditure, and cloud pharmacy service utilization. Results: The successful implementation of this system has reduced the hospital inventory rate to approximately 20% and decreased the average annual inventory error rate from 0.425? to 0.025?, significantly boosting drug supply chain efficiency by 42.4%. It has also minimized errors in drug application, allocation, and distribution while increasing adverse reaction reports. Drug management across multiple hospital districts has been standardized, leading to improved access to medicines and enhanced patient satisfaction. Conclusion: The AI+VMI system improves drug supply chain management by ensuring security, reducing costs, enhancing efficiency and safety of drug management, and elevating the professional competence and service level of pharmaceutical personnel. [ABSTRACT FROM AUTHOR]

Online-to-offline (O2O) retailing offers unique opportunities for customizable assembled products with spare parts. Customers can browse and configure their desired product online, selecting from various components. Imperfect production, where a certain percentage of products have defects, can be amplified in the manufacturing system. Stricter carbon emission regulations put pressure on manufacturers to minimize waste. This creates a tension between discarding imperfect products, generating emissions, and potentially offering them at a discount through the O2O channel, which could raise quality concerns for consumers. In this study, an imperfect single-stage production process is examined, incorporating manufacturing–remanufacturing within a single stage for assembled products containing various spare parts. The study explores an investment scenario aimed at enhancing the environmental sustainability of the product. Additionally, two carbon emissions regulation strategies, specifically carbon cap-and-trade regulation and carbon taxation, are evaluated for their effectiveness in mitigating carbon footprints. The identification of waste, particularly in the form of defective items, is achieved through automated inspection techniques. The demand for spare parts associated with the assembled products is intricately linked to the selling prices set across diverse channels. Finally, the total profit of the manufacturing system is maximized with the optimized value of the selling prices, order quantity, backorder quantity, and investments in autonomated inspection, setup cost, and green technology. Numerical illustrations show that system profit was optimized when the defective rate followed a triangular distribution under carbon cap-and-trade regulation and when green technology investment helped to enhance retailer profit by 18.12 % , whereas autonomated inspection increased retailer profit by 10.27 % . [ABSTRACT FROM AUTHOR]

Based on the theoretical basis of Myers (1977) and Ohlson (1995), this study explored the effect of R&D expenses as a company's exploratory activities and advertising expenses as an activity that utilizes existing capabilities on corporate value. As a way for companies to explore new capabilities, the effect of R&D expenses on corporate value is examined, and as a method for strengthening existing capabilities and strengthening market competitiveness, the effect of advertising expenses on corporate value is considered. The empirical analysis subjects of this study are companies listed on the Korean stock market from 2011 to 2021. Ultimately, the number of sample data used in the empirical analysis of this study is 9,220 firm-year, and all are extracted from the KIS-VALUE DATABASE. In an empirical analysis using a regression model, the relationship between R&D and advertising R&D expenses on corporate value is investigated. The results of the regression analysis showed that both R&D expenses and advertising expenses had a positive effect on corporate value. An increase in R&D expenses increases corporate value by increasing future growth opportunities beyond a company's present value, and an increase in advertising expenses maximizes product or service value and enhances corporate value by strengthening market competitiveness. In addition, it is found that the impact of R&D expenses on corporate value is greater than that of advertising expenses, indicating the importance of R&D as a company's exploratory activities. These results provide important implications for corporate strategic management. Companies can achieve corporate value improvement through strategic investment and management of R&D and advertising expenses. Companies can strengthen their competitiveness through R&D as a future exploration activity and through advertising to create results in the existing market. [ABSTRACT FROM AUTHOR]

This study focuses on compressor station investments in Germany's natural gas infrastructure, offering insights applicable to machinery, energy, and maintenance cost-driven decisions. A life cycle cost (LCC) analysis can guide investment choices; however, uncertainties in input data and future developments pose risks. The LCC-based studies encounter questions impacting their results and optimal selections. These uncertainties may lead to misallocations, emphasizing the need for careful consideration of investment decisions to avoid potential consequences and efficiently allocate limited funds. Various measures are available to mitigate the uncertainties and risks in LCC analyses. Recognized measures are deterministic and probabilistic. Seven case studies on investments in the natural gas infrastructure in Germany were analyzed in this context. In addition to the executed case studies, a case study from a scientific journal (published in 2001) was included in the analysis. The case studies were conducted by transmission system operators from 2005-2015, and a retrospective view made it possible to recognize whether the best options (due to the LCC analysis) were identified. Simulations were conducted with generated models using real historical input data such as energy costs. The re-calculation of the net present value or better discounted cumulated expenditure with real input data shows that the LCC analysis results are significantly dependent on the reliability of the input data and the prediction of their development. Therefore, validating the results using appropriate measures is mandatory. This study illustrates how sensitivity analysis can be used as a deterministic method to evaluate the LCC analysis results. A company's success is increasingly determined by its sustainability. A pure LCC analysis is insufficient, so social, ecological, and economic sustainability assessments must be conducted. This study demonstrates the effectiveness of the weighted scoring method for sustainability assessments. Although this study relates to LCC in Germany's natural gas infrastructure, the suggested process can be adopted for other investment projects comprising capital and operational expenditures. [ABSTRACT FROM AUTHOR]

The frequent occurrence of mega project accidents has created an issue of risk management and has made its solution highly valued. In the case that the owner is at a regulatory disadvantage, insurance institution can provide a new pattern for risk management of mega projects. The purpose of this paper is to study the impact of insurance institution's participation in mega project risk management on the decision-making of all participants and the promotion of the overall effectiveness of collaborative risk management of all participants. By constructing a tripartite evolutionary game model between the insurance institution, supervision unit and contractor, the conditions of the behavior evolution process of each participant and the important parameters affecting the change in behavior strategies are analyzed. The results indicate that the participation of insurance institution can promote the risk management investment of the supervision unit and contractor, and punitive measures can make participants pay more attention to the losses caused by the occurrence of risks In order to encourage insurance institution to participate in risk management of mega projects, incentive measures need to be taken to dispel their concerns cost surrounding costs. This study is helpful to reduce the probability of risk occurrence so as to realize the sustainable development of mega projects and provides management suggestions for insurance institution to participate in risk management. [ABSTRACT FROM AUTHOR]

Background and Objectives: Investment has become a paramount concern for various individuals, particularly investors, in today's financial landscape. Cryptocurrencies, encompassing various types, hold a unique position among investors, with Bitcoin being the most prominent. Additionally, Bitcoin serves as the foundation for some other cryptocurrencies. Given the critical nature of investment decisions, diverse methods have been employed, ranging from traditional statistical approaches to machine learning and deep learning techniques. However, among these methods, the Generative Adversarial Network (GAN) model has not been utilized in the cryptocurrency market. This article aims to explore the applicability of the GAN model for predicting short-term Bitcoin prices. Methods: In this article, we employ the GAN model to predict short-term Bitcoin prices. Moreover, Data for this study has been collected from a diverse set of sources, including technical data, fundamental data, technical indicators, as well as additional data such as the number of tweets and Google Trends. In this research, we also evaluate the model's accuracy using the RMSE, MAE and MAPE metrics. Results: The results obtained from the experiments indicate that the GAN model can be effectively utilized in the cryptocurrency market for short-term price prediction. Conclusion: In conclusion, the results of this study suggest that the GAN model exhibits promise in predicting short-term prices in the cryptocurrency market, affirming its potential utility within this domain. These insights can provide investors and analysts with enhanced knowledge for making more informed investment decisions, while also paving the way for comparative analyses against alternative models operating in this dynamic field. [ABSTRACT FROM AUTHOR]

Group decision-making in capital investment involves a collaborative process where multiple stakeholders contribute their perspectives, insights, and expertise to evaluate investment opportunities and make informed decisions. This process's practical and methodological aims can vary depending on the organization's goals, industry, and market conditions. Researching capital investment group decision-making is motivated by several factors, such as optimizing investment decisions, enhancing performance, managing risk, adapting to changing conditions, and building knowledge and expertise. The investment decision relates to the distribution of financial resources. Investors select the most appropriate investment opportunities based on risk profiles, investment aims, and expected returns. Fuzzy multicriteria group decision-making in capital investment extends the traditional decision-making process to accommodate multiple criteria that are often uncertain, vague, or subjective in nature. This paper aims to suggest a technique known as the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (fuzzy TOPSIS) for group decision-making about investment in the respective vehicle. The fuzzy TOPSIS technique represents a decision for experts, which is multicriteria and includes an aggregated decision-making process. This paper shows the application of this method when choosing the best alternative, considering the choice of vehicle. [ABSTRACT FROM AUTHOR]

This work presents a study of the processes of digitalization of the economy in the context of assessing the role of investments in the development of digital technologies as the key drivers of the development of information systems management. Theoretical aspects of the formation and development of information systems are considered, their classification and general characteristics are given, general trends of transformation of information systems under the influence of digital technologies are established, and directions and volumes of investments in the digital economy from the position of their impact on the development of information systems are determined. The research methodology is based on the systemic approach and is characterised by the "blurring of the boundaries" of certain research spheres within such concepts as "digital economy", "information system", and "venture investment and start-ups". The methodological tools of this study include analysis and synthesis, specific historical methods, expert analyses, observation, and generalisation. This research is a stage in substantiating the connection between the factors of investments in the digital economy and the reflection of their impact on the management and development of information systems. The empirical study of the connection between the considered processes and justification of the key trends and directions for their development form a theoretical basis for mathematical models that are aimed at determining concrete sets of factors of investment effect on the designated range of the elements of the digital economy with further reflection of this effect in the form of economic results of companies' activities. [ABSTRACT FROM AUTHOR]

This paper shows that the American Inventor's Protection Act, which introduced the disclosure of patent applications after 18 months, that is, before a grant decision is taken and, hence, before it is known whether the respective technology will receive legal protection, is associated with a reduction of family firms' research and development (R&D) investment. This suggests that early disclosure of patent applications is perceived as a threat to family firms' innovation activity and discourages their R&D investment. This finding deserves our attention because family firms account for a large share of the US economy, and a reduction in their R&D investment can have long‐term consequences. [ABSTRACT FROM AUTHOR]

The rise of deep learning in the financial field has led to the integration of artificial intelligence and investment, providing users with intelligent investment decisions. However, the data volume of financial market continues to expand, traditional data processing methods can no longer meet the needs of efficiency and accuracy. This article focuses on deep reinforcement learning algorithms and delves into key issues such as stock price prediction, investment portfolios, and algorithmic trading. By comparing and analyzing the experimental results, not only was the performance of the model evaluated, but also the actual effect of the algorithm output was deeply explored. At the same time, drawing on Kubernetes container orchestration and microservice technology, a high concurrency and high-performance distributed financial data analysis system was constructed. This system not only meets the needs of users for real-time data analysis and deep learning, but also provides more reasonable investment suggestions for users. The contribution of this article lies in introducing deep reinforcement learning to solve nonlinear data problems in the financial field, proposing intelligent asset management methods, and designing a feasible intelligent financial asset management system, providing new ideas and practical experience for the further development of financial data analysis platforms. [ABSTRACT FROM AUTHOR]

Cuban Residents Abroad (CRA) have the potential to significantly contribute to Cuba's economy through tourism and remittances. CRA constitute a large diaspora, with strong ties to Cuba. Their travel to the island, even if primarily to visit family, has a notable economic impact, especially on private and local economies. Remittances from CRA are also substantial, representing a top source of foreign earnings for Cuba, though recently limited by US restrictions. However, various obstacles still hinder CRA's full economic participation, including outdated policies, limited travel services catering to CRA, and complicated remittance channels. The Cuban government could boost CRA contributions by facilitating their travel, investment, and remittances through updated policies, expanded local initiatives, allowance of more private sector participation, and overall reintegration of CRA into economic life. Balancing CRA participation with equitable development remains a challenge. [ABSTRACT FROM AUTHOR]

The use of text readability indicators and sentiment factors to asset pricing is practical in investment risk management yield pursuit. We analyzed the polarity of textual sentiment of Management Discussion and Analysis (MD&A) in 10-Ks for firms in the U.S. by constructing Sentiment Entropy, a new sentiment indicator based on L&M Dictionary, which captures the same characteristics of positive and negative emotions from the perspective of polarity. The empirical results show that the polarity of sentiments increases investment risk measured by return volatility, which differs from the traditional one-way emotion indicator. We found through a mediator effect test that emotional polarity significantly increases investment risk by stimulating large changes in trading volume, which is consistent with conventional wisdom. Challenging conventional findings, we find that positive and negative emotions in disclosures may have homogenous effects on the market, providing inspirations for understanding the role of textual sentiment on investor behavior. [ABSTRACT FROM AUTHOR]

The Constant Leverage covering strategy for the equity momentum portfolio (CLvg) developed in this project cannot mask its shortcomings by increasing leverage. It has to successfully forecast and avoid more losses than profits to perform better than the momentum portfolio. This approach is different from other covering strategies available in the literature that focus on increasing the right tail of the momentum returns distribution at a faster rate than they increase the left tail. The CLvg strategy only depends on past information and uses the daily volatility of the loser portfolio to determine episodes of high and low volatility. The daily volatility of the loser portfolio has a stronger relationship with large negative momentum returns than the daily volatility of the momentum portfolio. The daily volatility of the loser portfolio also has a weaker relationship with larger positive monthly returns, and it is more predictable because it has a higher volatility persistence. The negative effects of transaction costs on the CLvg strategy are measured using bid and ask prices reported by CRSP from 1992 to 2021. During this period, the stock market presented an average excess return of 9.19% and a Sharpe ratio of 0.61, and 9.74% of its returns were crashes, which is a better performance than the momentum portfolio. The CLvg adjusted by transaction costs presented excess returns of 16.93% and a Sharpe ratio of 0.84, and only 8.31% of its returns were crashes. [ABSTRACT FROM AUTHOR]

This study investigates the association among management fees, ESG scores, and investment performance of ESG funds in China. It explores the significance of comprehending the cost–benefit analysis and long-term yields associated with sustainable investing. The investigation specifically concentrates on China's open-end equity funds and uncovers some noteworthy discoveries. Initially, funds with higher management fees tend to yield greater returns, suggesting a potential validation for these fees. Nevertheless, when taking risk-adjusted metrics into account, these funds do not exhibit superior performance, indicating that the elevated fees may not necessarily result in enhanced performance after factoring in risk. Furthermore, the analysis discloses an adverse influence of ESG factors on fund performance. In general, the findings indicate that ESG funds in China do not impose higher management fees and do not ensure better returns but often produce superior risk-adjusted investment performance if their ESG scores are moderately higher. Exceptionally high ESG scores can end up with the worst risk-adjusted investment performance. [ABSTRACT FROM AUTHOR]

This study develops a novel periodic regime-switching model (the PRS model) to improve the forecasting of stock market volatility by accounting for the information from non-trading and trading periods, including regular trading and after-hour trading. Empirical analysis of the Taiwan Futures Exchange (TAIFEX) demonstrates the significant improvements of the PRS model in both in-sample and out-of-sample periods. Our results also show that the introduction of after-hour trading sessions has provided valuable information for volatility forecasting in subsequent regular trading sessions, emphasizing the importance of considering diverse information flows across different trading and non-trading times. The PRS model effectively captures the dynamics of non-trading and trading sessions and the influence of unusual news arrivals and jumps on market volatility, contributing to investment and risk management strategies. [ABSTRACT FROM AUTHOR]

In this study, we explore the negative impact of upstreamness on suppliers' investment quality and management earnings' forecast accuracy and investigate whether a shared auditor engaged by both a supplier and its major customers could mitigate these effects. Using a comprehensive dataset of multitier supply chains, we find that suppliers located further upstream tend to have lower investment efficiency and exhibit less accurate management earnings forecasts. However, our results also show that the presence of a shared auditor in the supplier-customer pair could alleviate these adverse impacts by enhancing the quality of information in the supply chain. Our findings shed light on the implications of upstreamness in the supply chain, such as reduced investment efficiency and increased management forecast errors and suggest a role for information quality in mitigating these consequences. Data Availability: All data are available from public sources mentioned in the text. [ABSTRACT FROM AUTHOR]

Renewable energy sources (RES) will play a key role in the transition to clean energy. Financial and socio-economic benefits determine the investment management in these energy sources. This article aims to indicate current energy policy goals, present socio-economic benefits resulting from renewable energy investments, and review further development directions in Poland. The research was carried out using desk research, case studies, and literature review methods to provide a broader economic context for RES investments. The scope of the research included both the Polish and the European Union contexts. The authors examined the Polish objectives of investment in renewable energy contained in strategic, planning, and other legal documents compared to EU targets, reviewed possible investments in renewable energy, and indicated wind farms and photovoltaic investments as the most effective ones from the point of view of further development which aims to meet the EU's goals by 2030. The authors also demonstrated a wide range of socio-economic benefits based on literature reviews, analysis of policy documents, and regulations regarding the energy sector, and examined a specific example of investment implementation and identified the ecosystem of beneficiaries and their benefits. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the concept and features of investment certificates of a mutual investment fund as a type of securities of collective investment schemes in Ukraine. The study is based on the current legislation of Ukraine, as well as scientific works in this area. The main method of the study is the method of analysis and synthesis, which allows, on the basis of a comprehensive analysis of numerous regulatory legal acts of Ukraine in the field of collective investment, to identify the features of investment certificates of a mutual investment fund. In addition, the rights of holders of this type of securities under Ukrainian legislation are structured using the method of systematization. As a result of the study, the author provides a comprehensive definition of investment certificates of a mutual investment fund which contains all the features of this type of securities. In addition, the rights of holders of investment certificates of a mutual fund are systematized. [ABSTRACT FROM AUTHOR]

Budget investments are a necessary prerequisite for investment development of the state. In the EU member countries, budgetary investment contributes to the implementation of profitable or non-profitable, but socially significant projects, which enable the activation of investment processes, both at the macro and micro levels. The need to use budget investments as a stimulus for economic growth determines the need for an in-depth study of the theoretical and applied principles of their implementation, as well as substantiation of the prospects for reforming the management of budget investments in Ukraine in the context of international experience. Based on the analysis of domestic experience and the generalization of foreign practice, the components and key principles of budget investment management are defined, which emphasize the need for cooperation at all levels of government in the context of coordination, facilitation, and institutionalization. A set of measures to reform the management of budgetary investments in Ukraine is proposed, based on the use of an information model, which, in contrast to the known ones, provides for the improvement of planning (through the development of a national strategy and/or plan of budgetary investments, the use of medium-term fiscal frameworks, the introduction of budgeting based on results, the introduction of preliminary assessment of budgetary investments and the introduction of their independent expertise), distribution (for the implementation of the strategic goals of post-war infrastructure restoration, the development of the green and digital economy and ensuring social and economic stability) and use (on the basis of the introduction of repeated technical and economic substantiation, the introduction of accrual accounting, timely and full financing and control of implementation) of budget investments, which enables the implementation of only the most high-priority state investment projects that have clear technical characteristics, have undergone a thorough approval and selection procedure, are financially accessible and to a large extent ensure economic growth and public welfare. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVE: A strong and effective health management workforce (HMW) is essential to underpin the comprehensive health care services provided by health care organizations. The fast-growing nature of healthcare systems suggests the required competencies for HMW continue to evolve. Hence, an up to date understanding of management competency requirements is important to the productivity and sustainability of the healthcare system. Before any investment in management competency development, understanding the current health service management workforce development strategies is one of the key steps. There has been no integrated review on the development efforts for HMW in the Asia Pacific region. The objective of this scoping review is to identify and confirm the key strategies that have been used in developing the health management workforce in the Asia Pacific region. MATERIALS AND METHODS: A scoping review of the literature was conducted between May and August 2022 using the following databases: Medline, Ovid Emcare, CINAHL, Scopus, and Web of Science, to retrieve original research articles demonstrating development efforts for HMW in the Asia Pacific regions. The review was guided by the PRISMA-ScR (2018) checklist [23]. RESULTS: The scoping review identified four different development strategies for HMW in Asia Pacific region: i) Organisational informal professional development programs, ii) Competency assessment and identification of gaps in knowledge and skills of HMW, iii) Confirming competencies and developing competency framework and iv) Formal education and training. Among these four development strategies, organisational informal professional development programs and competency assessment and the identification of gaps in knowledge and skills of HMW were the main strategies implemented for HMW in the Asia Pacific region. The review also highlighted a relatively low level of government or system level development strategies for HMW in the Asia Pacific region. CONCLUSION: The review concluded that the existing development strategies and efforts for HMW are not evenly implemented within the Asia Pacific region. Political will and policy direction are important and plays a vital role in the competency development of HMW. It is also critical to provide multilevel commitment from system and organisational level together with identifying and addressing the bottlenecks in the development strategies by considering organisation types, management levels and positions, practical training methods, motivation of participants, and other contextual factors. [ABSTRACT FROM AUTHOR]

Featured Application: The outcome of this study has the potential to open a new direction to optimise the success of asset management and of financial markets in general. The new focus is not algorithms, but the non-conscious mind in humans. In the world of finance, considerable attention is given to improving machine learning techniques to predict the future of stock markets. However, for obvious reasons, this turns out to be an unsolvable mission, most likely because the real world is not driven by algorithms but by human beings. In response to this, the present study has its focus on raw affective responses in actual asset managers during their decision making regarding controlled financial scenarios. Nineteen asset managers were invited and asked to make sell/buy decisions related to visual presentations of three different price developments of different assets. The three scenarios were "crash", "stable" and "gain". Parallel to their decision making, startle reflex modulation (SRM) was used to measure non-conscious affective responses without demanding any respective explicit responses (no conscious language processing involved). Interestingly, two further factors were introduced. First, all participants had to make their decisions once while being informed that 0% prior investments (low exposure) have been made into the presented assets, and once being informed that a large investment consisting of 25% of ones' overall portfolio has been made prior to making the decision (high exposure). Second, the factor experience was included dividing all participants into two groups, one with low experience and the other with high experience. First, across both these extra factors, it was found that "crash" scenarios resulted in the most negative affective responses. The most positive affective responses were found for "gain" scenarios, while the "stable" condition was in between. Interestingly, the factor of prior investment (i.e., exposure) had an effect. Non-conscious affective responses during decision making related to the "stable" condition varied as a function of "exposure". In the low exposure condition, affective responses to decision making during the "stable" scenario were most negative, even more negative than in "crash" scenarios. The factor experience also had an effect, but due to the small sample size, no significant interaction occurred. However, t-tests revealed the same significant effects in the experienced group as found in the 0% prior investment condition. To our knowledge, this is the first empirical investigation measuring non-conscious affective responses during decision making in the context of asset management. Thus, this study might form an interesting basis for new strategies to explore non-conscious human brain functions instead of inventing new algorithms to make asset management more successful. [ABSTRACT FROM AUTHOR]

The article deals with the financial management of construction companies in the Czech Republic during 2014-2021, i.e., an 8-year period. Since the data collection also provided information on the years of the COVID-19 pandemic crisis, the paper focuses on the financial management of construction companies during this period. Financial management means the management of companies' assets, i.e., fixed and current assets and the management of financial resources that cover these assets. Financial resources are divided into own and external resources. Liquidity is also related to the issue of financial management where current liquidity including all current assets to cover short-term liabilities is taken into account. The paper is divided into two parts: the former analyses the period until the COVID-19 pandemic crisis i.e., 2017-2019, and the latter analyses the period during the years of the COVID-19 pandemic crisis i.e., 2020-2021. The aggregate data for the entire period under study is also recorded. An important outcome of the paper is highlighting the possible differences in the financial management of construction companies before and after the COVID-19 pandemic crisis. The methods used in the research described in the article are closely related to those used in financial analysis, in particular the basic vertical analysis method and the ratio indicator method, where the current ratio is taken into account. [ABSTRACT FROM AUTHOR]

The study aims to examine the impact of various behavioral biases such are overconfidence, representativeness, availability, anchoring and herding, and their effects on individual investment decisions in the case-developed country context of China. To achieve this, data was meticulously gathered from 362 participants active in the Shanghai stock market. Employing advanced analytical tools, particularly the Smart PLS 3.3.2 software and structural equation modelling (SEM), this study rigorously scrutinized the intricate relationships between behavioral biases and investment decisions. The findings of this study notably reveal that all examined behavioral biases exert a significant positive impact on investment decisions within the Anxin, Haitong, Shanxi, and China Galaxy stock markets. Remarkably, no substantial disparities in the effects of these biases on stock market trading were observed among these markets. Importantly, these findings bear exceptional significance within the context of a developed country like China. The implications extend to a wide spectrum of stakeholders, including government entities, regulatory bodies, practitioners, the academic community, industry professionals, and researchers. Regulatory authorities can leverage these insights to refine their strategies, practitioners can fine-tune their investment advisory approaches, and academia and researchers can build upon these findings to deepen the understanding of behavioral finance in the realm of stock market investments. [ABSTRACT FROM AUTHOR]

Studyholism (SH) is a new potential clinical condition introduced in 2017 by Loscalzo and Giannini to refer to problematic overstudying, specifying that it might be associated with either high or low Study Engagement (SE). We aimed to analyze SH and SE's predictive role on academic resilience. We gathered 609 Indonesian youths, and we performed a path analysis model. Among the main findings, SH predicts a lack of academic resilience, while SE predicts higher academic resilience. However, SH and SE do not predict time spent studying, and GPA is negatively (although weakly) predicted by SH only. Hence, we provided support for the critical role of SH and SE in predicting students' academic success and for implementing preventive and clinical interventions to reduce SH and foster SE, given their impact on academic resilience, which, in turn, influences students' well-being and academic success. Finally, we recommend future research on Studyholism in non-Western countries. [ABSTRACT FROM AUTHOR]

This paper investigates the mechanisms of tax incentives and R&D investments on employment absorption, constructs a panel data model with a sample of 4,255 Chinese technology-based SMEs, and adopts a random effect model for empirical evidence after various tests. The research results show that tax incentives and R&D investments of technology-based SMEs positively affect their employment absorption. The positive effect not only exists in the current period but also remains valid in the next period. R&D investment, operating profit margin, and remuneration have more significant positive impacts on employment absorption, while we should pay attention to control and reduce overhead costs. Finally, this paper gives corresponding suggestions and countermeasures from three levels: government, enterprises, and society. [ABSTRACT FROM AUTHOR]

Imperfect external capital market and internal soft budget constraints are important reasons for the issue of enterprise financing constraints. This paper studies the impact of financing constraints and influencing factors of financing constraints in municipal infrastructure investment and construction for local governments by using the panel data from 2003 to 2018 in China. The results show that, first, there are great financing constraints in municipal infrastructure investment and construction for local government in China. Second, the increase of self-financing capacity and external financing capacity can reduce the level and uncertainty of financing constraints, thus improving the efficiency of municipal infrastructure investment and construction. Third, the expansion of the city scale may reduce the uncertainty of financing constraints, but improve the level of financing constraints thus reducing the efficiency of municipal infrastructure investment and construction. [ABSTRACT FROM AUTHOR]

As the financial condition of most individuals has taken the toll during the COVID-19 pandemic, this study aims to analyze varied risk perceptions owing to dynamic behavioral aspects ingrained in individuals. The study primarily incorporates the impact of COVID-19 induced risk perceptions on psychological bias and its aftermath on perceived investment performance, with gender differences being moderators in the aforesaid relationship. A mix of probability and non-probability sampling has been used to collect data from 1,133 respondents through a structured questionnaire. The partial least square structured equation modeling (PLS-SEM) has been employed as an estimation technique. The findings highlight that risk perception has been significant in affecting the heuristics and prospects. However, it is insignificant in directly impacting the perceived investment performance. However, psychological biases, proxied by heuristics and prospects, were found to mediate the relationship between risk perception and perceived investment performance. Practical implications suggest a judicious combination of risk, return, and behavioral portfolio to stimulate, and upscale investments thereby enhancing the investment momentum to reach pre-covid levels. At the same time, the relevance for society lies in the fact that they need to re-consider their investment portfolio to adjust for uncertainties like COVID-19. Future studies can embark on cross country research to investigate varied risk perception-investment performance relationships prevalent in respective economic settings. Also, studies can explore the variation in findings with respect to different classes of investors that is, experiences, first timers, institutional, influencers and others. [ABSTRACT FROM AUTHOR]

The investment decisions of managers of investment funds (especially equity investment funds) have an impression on the returns of individuals who have deposited their capital in these funds. Therefore, the issue of evaluating the performance of investment funds and their managers is imperative for investors. The research aims to investigate the effect of cross-sectional alpha dispersion on investors' evaluation of the performance of investment funds. We extract data regarding 31 equity investment funds from 2012 till 2022 and calculate the interquartile ratio of Jensen's alpha called "IQR" and "Performance-Flow Sensitivity" along with control variables. Then, the hypothesis test model was fitted using the multivariate regression analysis using the Generalized Least Squares method. Empirical findings show a negative and significant connection between the alpha dispersion of investment funds and performance-flow sensitivity. Based on the results, one credit increase in the standard deviation of alpha dispersion leads to a decrease of about 0.4% in the ratio of performance-flow sensitivity. Environments with high alpha dispersion of investment funds will targeted by unskilled managers to introduce themselves as successful and skilled managers to investors and mislead them. Therefore, when the alpha of investment funds has a higher dispersion, the type I error possibility investors will face increases. Individuals may consider an inefficient manager to be competent and skilled. We will provide some suggestions in this regard. [ABSTRACT FROM AUTHOR]

One of the main concepts in finance is portfolio diversification and optimization. Typically, investors use the risk and return approach to diversify their portfolios. However, risk spillovers and market connectivity should also be considered when making investment decisions, especially during times of crisis. The TVP-VAR approach is used in this study to analyze risk spillovers and connectivity between the S&P 500 index, green bond, real estate, oil market, and dollar index in the USA from 2016 to July 2022. The TVP-VAR model is a time-varying model that may consider current political and economic circumstances. As a result, investors can choose wisely when it comes to their portfolios. According to comparisons with other markets, the S&P 500 index and the real estate market are the two most significant sources of volatility in the system. In fact, they not only transmit greater volatility, but they also take it in more. After 2020, there will likely be a significant increase in the volatility of the real estate market and the S&P 500 index due to the COVID-19 epidemic. Additionally, as anticipated, other markets have an impact on the green bond market. It does not, however, transmit them. [ABSTRACT FROM AUTHOR]

Aim: The research aims to delineate and explain the state of bilateral relations between Australia and China in the context of the stability of the Indo-Pacific region. Methods: The main tools used to achieve the objectives mentioned above include the analysis of primary and secondary sources: literature, official statements, diplomatic and quantitative data from governmental sites, and statistical research. Results: Reliable and balanced bilateral relations between the People’s Republic of China, the most significant regional power, and Australia, the most influential Western outpost in the Indo-Pacific, are sine qua non condition of stability in the region. However, within the last decade, there was far too much uncertainty and hostility between the two parties to pass unnoticed: trade and investment restrictions on Chinese companies, not to mention political tensions due to unprecedented Chinese interference in Australia’s domestic affairs. The article analyzes bilateral Sino-Australian relations, including political, economic, and social dimensions, in the context of regional security issues. Conclusions: Relations between China and Australia are underpinned by their strong economic interdependence on the one hand and Australia’s security alliance with the U.S. on the other. While concerns over trade tensions may soon be over, Australia must accommodate the reality of China’s more active presence in the IndoPacific region. [ABSTRACT FROM AUTHOR]

This research investigates how corporate social responsibility (CSR) affects the connection between accounting conservatism and investment efficiency. The study focuses on a sample of 530 firms that are listed in the United States and covers the period from 2015 to 2019. We contribute to the literature by incorporating ESG performance scores to measure CSR, and by investigating the moderating effect of CSR on the conservatism-investment efficiency relationship. Our results show that environmental and governance metrics positively influence investment efficiency, while social performance indicators have a negative association. Moreover, the environmental performance indicator strengthens the relationship between conservative accounting and investment efficiency, while the governance indicator weakens this association. Overall, our study provides new insights into the interplay between conservative accounting, investment efficiency, and CSR and sheds light on the importance of considering CSR in investment decision-making. [ABSTRACT FROM AUTHOR]

Successful research-policy partnerships rely on shared vision, dedicated investment, and mutual benefits. To ensure the ongoing value of chronic disease prevention research, and support research translation and impact, Australia needs funding, university, and policy systems that incentivise and support emerging leaders to drive effective partnerships. [ABSTRACT FROM AUTHOR]

The wide-spread reporting of non-GAAP earnings suggests efficiency gains from doing so. By estimating a dynamic investment model, we examine the real implications of investors using both GAAP and non-GAAP earnings to value firms. When investors use the firm's GAAP earnings only, the firm's manager—who cares about current stock prices—underinvests, and his investment is sensitive to transitory earnings. Non-GAAP earnings can improve investment efficiency by adjusting for these transitory earnings, but can also hide inefficient investment by introducing opportunistic bias. Although non-GAAP earnings induce overinvestment, they dominate GAAP-only reporting. Counterfactual analysis reveals supplementing GAAP earnings with biased non-GAAP earnings increases firm value by 3.4 percent relative to GAAP-only reporting. Precluding bias reduces overinvestment and further increases firm value by 1 percent. Data Availability: Data are available from the sources cited in the text. JEL Classifications: E22; G31; G34; M40. [ABSTRACT FROM AUTHOR]

In the process of transnational investment management, the choice of entry mode is one of the key decisions, and creative assets will affect the choice of overseas market entry mode. However, few studies have analyzed how creative assets affect firms' overseas market entry patterns. This paper takes 480 overseas investment data of 134 Chinese listed enterprises from 2012 to 2019 as research samples and uses the Logistic model to study the influence of creative assets owned by enterprises on their choice of the joint venture and wholly owned modes. At the same time, we examine the formal and informal institutional distance between home and host countries, and the moderating effect of firms' own experience in the process of model selection. In addition, using the fuzzy-set qualitative comparative analysis (fsQCA) from the perspective of configuration to explore the different paths of overseas market entry mode. The research results indicate that marketing intensity and technical intensity of enterprises have a positive and significant impact on overseas investment patterns, that is, higher marketing intensity or technical intensity will prompt enterprises to preferentially choose wholly-owned mode. Formal institutional distance and experience can moderate the relationship between creativity and investment mode to some extent, while informal institutional distance has no significant moderating effect on creative assets and investment mode. Three configurations can induce firms to choose the wholly-owned mode, and only one configuration can induce firms to choose the joint venture mode. This study lays a theoretical foundation for enterprises to enter the overseas market. [ABSTRACT FROM AUTHOR]

Objective: The negative effects of Problematic Instagram Use (PIU) on selfevaluations of one's appearance (i.e., body-image satisfaction-dissatisfaction) are well-known, whereas less explored is its role on body-image investment dimensions. By adopting the Social Comparison and the Self-discrepancies theories as the framework, the present study hypothesized that PIU negatively affects body investment and appearance management behaviours through the serial mediating role of actual appearance comparison on Instagram (IG) and the need to conceal body flaws. Gender, age and trait appearance comparison were controlled for. Method: A convenience sample of 323 participants (F = 70.3%; Mage = 28.92 + 10.96) was recruited, and well-known self-report measures were administered online. Results: The structural model produced good fit indices [χ2/df = 2.36, RMSEA = 0.065 (0.053 - 0.077), CFI = 0.962, SRMR = 0.038], and the variables accounted for 79% and 32% of the variance in body investment and appearance management behaviours, respectively. PIU was associated with body investment both directly and indirectly, whereas it affected appearance management behaviours only via appearance comparison on Ig. The tested alternative model has a poorer fit than the hypothesized model, and the former fitted significantly worse than the proposed one. Conclusions: The present study represents a step toward a better understanding of the psychological mechanisms underlying the link between PIU and body image investment dimensions. [ABSTRACT FROM AUTHOR]

The objective of this research was to collect online data about the cultivation of 'ora-pro-nóbis' (OPN) in the Vale do Paraíba Paulista to support research planning and public policies. A questionnaire with 24 questions was created using a remote research management application and covered the cultivation, consumption and commercialization of OPN. Applied to the agroecology group Rede Agroflorestal do Vale do Paraíba (Rede) and food security group Roda de Saberes (ROSA), made up of farmers, producers and rural owners, agriculture, health and education professionals, we obtained 52 completed questionnaires with OPN valued for its high protein and nutritional content, as a traditional food widely used by 96% of respondents who keep few plants in backyards and farms (82%) for the consumption of 0.5-1, 0kg of leaves per month in fresh form (29%), green juice (22%), cakes and breads (21%) and sautéed with meat (17%). Research should focus on pruning management (67%), necessary to maintain the low size of the plants and prevent the spikes from increasing in size as the branches age. This research provided a current overview of the growing popular interest in the consumption of OPN, which justifies investments to improve management and expand the scale of production to also serve the food and pharmaceutical industries. [ABSTRACT FROM AUTHOR]

The REVM method is a modernized option of classical EVM method. The new method has been developed for applying in unstable condition of works implementation. When the works can be accidentally disturbed and the impact of random disruption factors on course and results of works must be taken into consideration. Next, Randomized Budgeted Duration to Completion and Randomized Budgeted Cost to Completion that is duration and cost of works remaining to execution after each inspection, as well as the Randomized Budgeted Duration at Completion and Randomized Budgeted Cost at Completion that is duration and cost of all works of the project completion after the site inspection. Moreover, the risk of durations and costs overrun of works are evaluated. It is important that input data required for the REVM method are the similar and are measured in the same way as in typical control of advancement works. But results of the application consist new decision information. Control of the investment under deterministic conditions, without taking into account the risk of disruptions, resulted in a final deviation from the planned budget of over 7%, and from the planned completion of the investment by almost 12%. Without analysing the factor related to disruptions at the investment implementation stage, the material and financial schedule was completely outdated. On the other hand, when controlling the investment under risk conditions and introducing organizational and technological changes adequate to the inspection reports, the final deviation from the planned budget was less than 2%, and slightly more than 2% from the planned completion date. Researches confirm that the results received by using the REVM method well reflect real situation of works implementation. [ABSTRACT FROM AUTHOR]

At the end of the 1990s, there existed a belief that a growing Canadian military involvement in the Caribbean region was unlikely if it was not associated with Canada's interest in Latin America (Klepak 1996). This view had such a large impact that today there is a dearth of information on Canada's military involvement in the Caribbean region. Lacking systematic investigation, two myths have perpetuated: first that Canada has no stake or interest in Caribbean security, insofar as those interests cannot be tied to Canada's interests in Latin America; and second, that all expressions of Canada's involvement in Caribbean security are simply extensions of US security interests in the region. Looking at Canada as part of the Anglosphere, this paper analyzes Canada's ongoing commitment in the Caribbean to preserving and expanding the political, social, economic, and ecological system that benefits Anglospheric capitalist accumulation and security objectives. Today, Jamaica is the host site for the Canadian Armed Forces Operation Support Hub in Latin America and the Caribbean (OSH-LAC), as Canada aims to position its long-term security partner as a regional sub-policeman of the region. OSH-LACs proximity to states like Haiti, a frequent site of Canadian intervention, should worry those concerned with Canada's increased global militarism and imperialism in the world more broadly. [ABSTRACT FROM AUTHOR]

Introduction: Lack of data about saline aquaculture in Pakistan has curtailed informed policy and investment decision making resulting in undervaluation of and underinvestment in the sector. Therefore, saline aquaculture in Pakistan is today an underdeveloped sector despite its potential as an alternative livelihood for the country's rural farmers. This study represents one of the initial exploratory investigations into saline aquaculture systems in Pakistan, aiming to comprehend the existing sectoral landscape, production challenges, post-harvest constraints, and the associated capacity and investment needs. Methods: The study employed purposive sampling to survey 121 low-income saline aquaculture farmers across five districts of Southern Punjab and Sindh provinces. The analysis was carried out using descriptive statistics. Results: The results revealed that the saline aquaculture sector is predominantly male-centric, with agricultural land utilized for both agriculture and aquaculture purposes. Ponds, which usually serve multiple functions, focus primarily on carp production, but adherence to good management practices remains limited. Farmers face various challenges, including the high costs of feed and seeds, freshwater scarcity, inadequate technical knowledge, and marketing issues. Discussion and conclusion: This study serves as a foundational assessment, addressing data and information gaps crucial for supporting the sustainable development of saline aquaculture in Pakistan. To facilitate such development, the study recommends initiating programs to strengthen technical skills in saline aquaculture, together with the establishment of hatcheries and breeding stations for saline-tolerant species, aiming to reduce dependence on freshwater species in saline pond environments. [ABSTRACT FROM AUTHOR]

In today's world where globalization is intensely experienced, differences in risk perception, developments in capital markets, and the negativities faced in the markets due to uncertainty are very important when researching the structures of the stock markets, and therefore determining current volatilities. One of the biggest problems encountered is the inability to price stocks effectively. Therefore, estimating and modeling volatility becomes crucial. The diversity of the portfolio, created by international investors in the financial markets and the sustainability of their investment decisions, are closely related to the volatility variable. However, the fact that financial markets are more fragile in developing countries increases the importance of volatility. There are many different methods in the literature when estimating volatility. Due to the inadequacy of traditional time series models in estimating volatility, conditional heteroskedasticity models are used with ARCH and GARCH class models being frequently used. In this study, the series of daily opening values of the ISE100 Index covering from 02.01.2003 to 30.09.2022 was estimated using ARCH/GARCH models for volatility with the aim to determine which model has the higher explanatory power. According to the findings, the GARCH(1,1) model gave more meaningful results in explaining the ISE100 return volatility. [ABSTRACT FROM AUTHOR]