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This paper studies tax-minimizing investment, whereby firms tilt capital purchases toward year-end to reduce taxes. We use this pattern to characterize how taxes affect investment behavior. We exploit variation in firm tax positions from administrative data to confirm that tax minimization causes spikes. Spikes increase when firms face financial constraints or higher option values of waiting. Cumulative investment does not completely reverse after spikes. We develop an investment model with tax asymmetries to rationalize these patterns. Both depreciation motives (later investments face lower effective tax rates) and option value motives (tax asymmetry implies time-varying opportunities to minimize taxes) are necessary to fit the data. (JEL G31, G38, H25) [ABSTRACT FROM AUTHOR]

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.)

This article introduces a new holding horizon measure of active management and examines its relation to future risk-adjusted fund performance (alpha). Our measure reveals a wide cross-sectional dispersion in mutual fund investment horizons, and shows that long-horizon funds exhibit positive future long-term alphas by holding stocks with superior long-term fundamentals. Further, stocks largely held by long-horizon funds outperform stocks largely held by short-horizon funds by more than $ 3\% $ annually, adjusted for risk, over the following 5-year period. We also find a clientele effect: to reduce liquidity costs, long-horizon funds attract more long-term investors through share classes that carry load fees. [ABSTRACT FROM AUTHOR]

We examine diseconomies of scale for two different investment approaches: quantitative and fundamental. Using separate account (SA) data where the investment approach is self-identified, we find that fundamental SAs exhibit greater diseconomies of scale than quantitative SAs. Looking at liquidity costs, we find that quantitative SAs hold more diversified portfolios of higher liquidity stocks than fundamental SAs, thereby reducing their expected liquidity costs. We also find that consistent with lower information processing/hierarchy costs, the speed of information diffusion is higher for quant SAs. Accounting for these differences helps to explain the differences in diseconomies of scale. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this comparative quantitative study is to examine hypotheses regarding the impact of asset management and intellectual capital (IC) on the financial performance of the construction sector in the ASEAN-5 throughout 2019–2022 with enterprise resource planning (ERP) as a mediator variable. Design/methodology/approach: A final sample of 65 construction industries listed on stock exchanges during 2019 and 2022 in ASEAN-5 (Indonesia, Philippines, Malaysia, Thailand and Singapore) was selected using the purposive sampling method. This research employs market-to-book value (MBV) as a measure of IC. The study also used path analysis, the Sobel test and analysis of variance test (ANOVA). Findings: The findings demonstrate that asset management, intellectual capital and ERP have a significant and favorable impact on return on asset (ROA). Additionally, the asset management and IC of the ERP display weak and substantial outcomes. The implementation of ERP was also shown not to operate as a mediating factor. The ANOVA results on financial performance indicate significant differences for the year 2019. Furthermore, the use of various ERP software types demonstrates a comparable impact on enhancing financial performance. Originality/value: This is the first study that utilizes ERP to mediate management asset and IC on financial performance. The ASEAN-5 construction sector is representative of developing nations' economic condition, offering the possibility to avoid the global economic collapse in 2023 and recover despite economic volatility. [ABSTRACT FROM AUTHOR]

Narrative inquiry has gained traction in applied linguistics as a complementary approach to positivistic research, focusing on the subjectivities of individuals' lived experiences and using stories as data, analytical tools, and reporting practice. Although numerous methodologically oriented publications on narrative inquiry in the field reflect its vitality, scholars have raised questions about the complexity and ambiguity underlying what exactly constitutes narrative inquiry. While methodological diversity within narrative inquiry can signal innovation, it can also create uncertainty for novice and experienced scholars engaging with the methodology for the first time. To address these concerns, we conducted a systematic methodological synthesis of narrative inquiry studies in applied linguistics published from 2012 to 2022. Specifically, we searched 12 top‐tier applied linguistics journals and developed a corpus of 291 articles. We coded our corpus according to four areas: (a) theoretical framing, (b) demographic characteristics, (c) methodological design, and (d) reporting of ethics, researcher positionality, and funding status. We discuss our results in light of previous thematic reviews of narrative inquiry in applied linguistics, and we offer empirically grounded recommendations for scholars engaging with narrative inquiry. Our study responds to calls for greater methodological transparency in applied linguistics in general and methodological investment in narrative inquiry in particular. [ABSTRACT FROM AUTHOR]

This article introduces the concept of a Natural Dividend and describes the three types of rent that combine to produce it: a differential rent, a regulatory rent, and a locational rent. Each of these rents is associated with a classical economist (Ricardo, Marx and George, respectively), and each is shown to be a product of nature, society and/or the political authorities that manage nature on our behalf. Because the Natural Dividend is a windfall derived from our regulation of commonly held (and immobile) natural resources, it can be taxed at a higher level without distorting any underlying investment decisions. [ABSTRACT FROM AUTHOR]

This study addresses the dearth of research on what enables firms' performance in the context of Industry 4.0 (I4.0). We investigate how I4.0 shapes the effects of firm investments over time and whether the effects of people and equipment depend on innovative management approaches. A longitudinal multi-sector study is conducted of 157 export-oriented, manufacturing firms in a European Union member state (Slovenia) over a 14-year period (in total, consisting of 1791 total observations). The findings suggest that firms which invest more in technology complement these costs by making investments in people, which over time leads to a higher firm performance. The I4.0 phase moderates this mediated relationship in that firms more advanced with respect to engaging in I4.0 tend to lower their human resources costs despite investing in technology while still showing a superior firm performance. This indicates the substitution effect of technology vis-à-vis human resources. The moderation of management innovation proved to be weaker, calling for a detailed look at its nuances across the studied levels. Taken together, our paper contributes in advancing the stream of research focused on internal factors and processes specifically related to firm investments and management processes, thereby leading to the outcomes of new technology use and capitalization. The findings highlight the link between I4.0 and technology management, and innovation, and complements the existing research on the link between management innovation and performance by contextualizing it within I4.0's new technology and socio-economic changes. [ABSTRACT FROM AUTHOR]

The Local Public Service Agency is part of the local government unit, with a legal status not separate from the local government, which has a flexible financial management pattern in the form of flexibility to apply fair business practices to improve and develop services, as an exception to the provisions of financial management in general. The flexibility of financial management includes revenue and expenditure management, cash management, debt management, tariff determination, employee procurement, procurement of goods and services, and investment management. The pattern of flexible financial management still refers to the regulations that have been set, namely the Sumbawa Regent Regulation Number 5-year 2020 concerning guidelines for financial management of the regional public service agencies within the Sumbawa government. Regulations or policies that have been established by the Sumbawa Regency government to be implemented and adhered to in implementing BLUD financial management policies at Puskesmas are expected to improve and develop health services with transparency and accountability. Based on the description, the research problem is how far is the financial management of the Regional Public Service Agency (BLUD) at Puskesmas in the Sumbawa Regency region based on the Sumbawa Regent Regulation Number 5 of 2020 concerning guidelines for financial management of regional public service agencies within the scope of the Sumbawa Regency. Researchers used a qualitative descriptive method approach using interview and observation tools to collect data both directly and through document review. The data obtained were analyzed using Likert scale categorization, which consists of Very Good, Good, and Less Good. The findings of the research provided an overview that public policy evaluation is closely related to the level of compliance and readiness of Human Resources in conducting the financial management of the Regional Public Service Agency (BLUD) at Puskesmas in Sumbawa. The results of this study can complement Wiliam Dunn's opinion or theory on public policy evaluation to emphasize the level of compliance and readiness of Human Resources in conducting public policy evaluations, which not only focus on the values and objectives but also the targets of a policy. [ABSTRACT FROM AUTHOR]

Programming is becoming increasingly common in mathematics degrees as it is a desirable skill for new graduates. However, research shows that its use is mostly restricted to computational or modelling tasks. This paper reports a study on students' perceptions of and difficulties with Lean, an interactive theorem prover introduced as part of a transition to proof first-year module. The data consist of first-year university mathematics students' questionnaire responses (n = 99) and sections of 37 semi-structured interviews with students from the same cohort. Findings highlight students' difficulties with syntactic and strategic knowledge, in line with similar research on programming, and how conceptual knowledge is discussed in terms of conceptual-mathematics and conceptual-programming. Moreover, some students share how the experience with Lean changed their perception of mathematics by contributing to the epistemological shift from school to university, which is necessary for students to be successful. However, many students failed to engage with Lean due to its difficult syntax and because they perceived programming to be disconnected from the activity of proving and not worth the time investment needed to become proficient with this tool. We conclude with some reflections on the implications of this study for university teaching and suggestions for future research. [ABSTRACT FROM AUTHOR]

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 purpose of the study is to study the impact of responsible investment on the banking performance in the small and medium banks. This study used the secondary data by using 129 banks from 2018 t0 2023 and the OLS are utilised as a regression. The study utilized the statistical software STATA to test the relation among the variables. We found a positive and significant correlation between the responsible investments on the banking performance. Finally, appropriate recommendations were presented to improve the quality responsible investment on the banking performance in Asian Banks. The study concluded that the impact of investment on the performance of banks utilizing the statistical analysis program shows that there is a statistically important influence of investment on the bank performance of the financial institution. Hence, it is the responsibility of the institution to distinguish among the several investment options, with the goal of starting an investment construction in the institution that is composed and in accordance with the economic limits, and capable of enhancing its goals. In light of the findings extended, the study obtainable a number of references, the most significant of which is the essential for banks in specific and firms in overall to strengthen investment processes in the field of information technology payable to its significance in enhancing services and raising bank performance. The findings of the study will support decision-makers recognize the significance of investment part. The next are the most significant results. We find that the values of banks' investments are mostly from investments. [ABSTRACT FROM AUTHOR]

This paper seeks to highlight and address some of the key questions and challenges facing investment management companies navigating a geopolitical and economic landscape that continues to experience significant regulatory change. Managing the complexities of regulatory changes requires a strategic, integrated approach. By staying informed, leveraging technology, prioritising investor protection, engaging effectively with the board and ensuring robust governance and operational resilience, investment management companies can effectively overcome these challenges and maintain compliance in an ever-changing regulatory environment. [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]

The COVID-19 pandemic hit the world in late 2019, bringing many human activities to a halt. Several phenomena occurred as a result of these difficult conditions. Due to the rapid development of technology and the use of technology to earn income is new to some people, many people are exposed to fraud that occurs in the field of financial technology. This study aims to find out how people's financial literacy index, how they choose to invest, and how their financial literacy affects investment decisions. Since the millennial generation is the majority of productive age in Indonesia, this research targets the millennial generation. This research is limited to the Bandung City area because there are differences in Regional Minimum Wage (UMR) and investment decision-making behavior between cities. This verification quantitative research uses purposive sampling method with a total sample size of 1,275,520 people. Data was collected using an online questionnaire and the SPSS program was used to analyze the data of 400 respondents to find out how the level of financial literacy affects investment decisions and to identify all factors that affect financial literacy. The three factors used to measure the effect of financial literacy are financial knowledge, behavior and attitude. Descriptive statistics, normality, heteroscedasticity, multicollinearity and multiple linear regressions were the SPSS tests performed. This study found that financial knowledge, behavior and attitude together have a significant influence simultaneously on investment decisions. In addition, this study also found that financial knowledge, behavior and attitude each have a partially significant influence on investment decisions. [ABSTRACT FROM AUTHOR]

Quality of accounting information presented in the form of financial reports issued by the government must be reliable in making decisions. This information is an important consideration for managers to determine how to develop operating activities and avoid risks that can bring losses. This research was conducted with quantitative methods. The population is all regional financial and asset management revenue offices (DPPKAD) as the agency that manages the finances of all districts and cities in North Sulawesi. A sample of 116 civil servants in the regional revenue, financial and asset management services. Data analysis used Structural Equation Model (SEM) modeling with Partial Least Square (PLS) approach. The results showed that the Average Variance Extracted (AVE) value of the variable used was more than 0.5 and the composite reliability (CR) value was more than 0.7. The results of the first, second and third hypothesis testing showed a value of α < 0.05, so the hypothesis was accepted. The results of this study indicate that environmental uncertainty has a positive and significant effect on the quality of accounting information systems, information technology has a positive and significant effect on the quality of accounting information systems. Likewise, leadership has a positive and significant effect on the quality of accounting information systems. [ABSTRACT FROM AUTHOR]

In recent years, smart agriculture has gained strength due to the application of industry 4.0 technologies in agriculture. As a result, efforts are increasing in proposing artificial vision applications to solvemany problems. However, many of these applications are developed separately. Many academic works have proposed solutions integrating image classification techniques through IoT platforms. For this reason, this paper aims to answer the following research questions: (1)What are themain problems to be solvedwith smart farming IoT platforms that incorporate images? (2) What are the main strategies for incorporating image classification methods in smart agriculture IoT platforms? and (3) What are the main image acquisition, preprocessing, transmission, and classification technologies used in smart agriculture IoT platforms? This study adopts a Systematic Literature Review (SLR) approach. We searched Scopus, Web of Science, IEEE Xplore, and Springer Link databases from January 2018 to July 2022. Fromwhich we could identify five domains corresponding to (1) disease and pest detection, (2) crop growth and health monitoring, (3) irrigation and crop protectionmanagement, (4) intrusion detection, and (5) fruits and plant counting. There are three types of strategies to integrate image data into smart agriculture IoT platforms: (1) classification process in the edge, (2) classification process in the cloud, and (3) classification process combined. The main advantage of the first is obtaining data in real-time, and its main disadvantage is the cost of implementation. On the other hand, the main advantage of the second is the ability to process high-resolution images, and its main disadvantage is the need for high-bandwidth connectivity. Finally, themixed strategy can significantly benefit infrastructure investment, butmostworks are experimental. © 2024 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. [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]

Individual investors, particularly US domiciled, are becoming more aware of how taxes are impacting their portfolio's returns. As a result, wealth managers need to more frequently explain their portfolio-management decisions in terms of both investment management and tax management. Wealth managers can use the concept known as tax alpha in conjunction with their existing performance-attribution framework to explain a client's after-tax performance. They may find, however, that the framework requires their making several assumptions with no clear guidance about how to specify them. In this article, we enumerate the challenges specific to after-tax attribution and the details of the required assumptions. We propose two frameworks a wealth manager could use to provide transparency around an after-tax attribution calculation. For each framework, we explain how the manager may transparently satisfy the required assumptions. Although our frameworks are robust, we also discuss specific areas in which different approaches could be adopted, specifically related to the handling of securities not in the client's benchmark. Finally, we illustrate our frameworks with detailed examples illustrating how wealth managers can apply them in practice. [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.

This paper examines the impact of management myopia on the investment behavior of green investors using A‐share listed companies from 2004 to 2020 in China. The research reveals that management myopia significantly inhibits the investment behavior of green investors. Through corporate reputation and the development of green technologies, management myopia affects the investment intentions of green investors. Environmental project subsidies do not mitigate the negative impact of management myopia on green investment intentions. Interestingly, compared to environmentally friendly projects categorized under "profit‐related" and "reward" headings, subsidies in the form of environmental project grants exacerbate the inhibitory effect of management myopia on green investment. [ABSTRACT FROM AUTHOR]

Hedge fund managers' risk-taking choices are influenced by their compensation structure. We differ from most studies that focus on incentive fees and the high-water mark by examining how management fees affect managers' risk-taking. Our simple model shows that managers' risk-taking is negatively related to their future management fees. Using fund-level data, we find that future management fees are the dominant component of managers' total compensation. When the contribution of future management fees increases, managers reduce risk-taking to increase survival probabilities. Moreover, funds with higher decreasing returns to scale are more sensitive to future management fees and reduce risk-taking even more. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

Copyright of Forensic Science & Technology is the property of Institute of Forensic Science, Ministry of Public Security 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.)

The asset management industry is becoming a systemic feature of global finance, yet has evaded regulators' efforts to designate its largest firms as systemically important institutions. How has this been achieved? We use as our example BlackRock's running commentary on the evolving plans of both prudential (banking) and securities (market) regulators in the period from 2008 to 2018. We show how asset managers engaged in successful recognitional politics, based on a decade-long struggle to influence how they were seen across the regulatory divide. James C. Scott's most recent thoughts on legibility codes provide us with our conceptual language of shape-shifters and chameleons. Two distinct strategies were simultaneously in play. As a shape-shifter, BlackRock repeatedly changed form in its self-presentation to prudential regulators concerned with systemic risk, so they could not be certain what they were looking at. As a chameleon, it invited securities regulators to maintain their authority over the asset management industry, so it could increasingly blend into the supposedly safe category of market-based finance. [ABSTRACT FROM AUTHOR]

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]

Learning and resolving uncertainty should be important components of management decisions, but not every type of uncertainty is equally important to resolve. For rare, threatened, and endangered species, information may be limited and there is often great urgency to halt potential population declines. Therefore, the most important uncertainties are those that would lead to different decisions intended to improve outcomes for species of interest. The New England cottontail (Sylvilagus transitionalis) is an endemic species to the northeastern United States and is listed as a species of special concern, threatened, or endangered in all states in its current range. States within the historical New England cottontail range have made substantial investments in habitat management, captive breeding, and research, but considerable demographic, management, and monitoring uncertainties remain. Connecticut is the geographic core of the current range of the species and therefore has been the focus of many management efforts, including improving habitat, creating new habitat patches, removing eastern cottontails (Sylvilagus floridanus), and releasing captive‐bred New England cottontails. We used a value of information analysis to identify the optimal management decision given current uncertainty and to evaluate how sources of uncertainty might lead to changes in management decisions. Given the current understanding of the New England cottontail in Connecticut, we identified the optimal management decision as improving existing habitat patches without monitoring for the species and managers could expect a 3.4% increase in populations if decision‐making uncertainty could be fully resolved. Multiple sources of uncertainty influenced results, but variation in New England cottontail density and the response of the species to the removal of eastern cottontails were most likely to result in changes to management decisions. At lower New England cottontail densities, releasing captive‐bred individuals competed with improving habitat as the optimal management action. Accounting for the value of information benefits New England cottontail management by guiding research efforts toward information that is most beneficial for decision‐makers and providing insights into parameter thresholds that would lead to changes in management decisions. [ABSTRACT FROM AUTHOR]

The policy performance of implementing Risk-Based Business Licensing through the Online Single Submission-Risk Based Approach (OSS-RBA) system in Kuningan Regency is still experiencing obstacles because Kuningan Regency does not yet have a Detailed Spatial Plan (RDTR) which has an impact on hampering the process of basic requirements in the form of Conformity of Space Utilization Activities (KKPR), Environmental Approval and Building Construction Approval (PBG). Therefore, it is necessary to evaluate the business licensing policy so that the aim of the policy, namely improving the investment ecosystem through issuing business permits more effectively and simply, can be achieved. This research uses qualitative methods with data collection and analysis techniques through observation, interviews with service officers and the community as well as documentation studies. Based on the results of research using William N Dunn's evaluation theory with 6 main criteria, it was concluded that the implementation of risk-based business licensing policies in Kuningan Regency has not met effectiveness, efficiency, adequacy, alignment and accuracy in encouraging ease of business licensing even though the responsiveness is quite good with the increasing number of permits. Micro and Small Enterprises (IUMK) in Kuningan Regency. To increase the effectiveness of implementing this policy, the Kuningan Regency government issued a regional policy so that the business licensing public service process in Kuningan Regency continues to run well. [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]

This tribute to Harry Markowitz provides an overview of Markowitz's far-reaching contributions to the theory and practice of investment management. The author details the introduction of portfolio selection from the initial 1952 Journal of Finance article to the 1959 book that provides a complete exposition of the concept through to the completed three volumes of Markowitz's last book that revisits portfolio selection after more than 50 years since its introduction. A discussion of Markowitz's work and influence on various aspects of modern investing is presented, including risk modeling, portfolio management, and simulation. Finally, the author shares his personal experiences and insights about who Markowitz was in life. [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]

Purpose: The aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management activities and to ascertain some substantial gaps related to them. Design/methodology/approach: For doing research synthesis, systematic literature review approach was applied considering research studies published within the time period, i.e. 1980–2020. This study attempted to accomplish a critical review of 59 studies out of 118 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioural finance domain-related explicitly to recognition-based heuristics and their effect on investment management activities. Findings: The survey and analysis suggest investors consistently rely on the recognition-based heuristic-driven biases when trading stocks, resulting in irrational decisions, and an investment strategy constructed by implementing the recognition-based heuristics, would not result in better returns to investors on a consistent basis. Institutional investors are less likely to be affected by these name-based behavioural biases in comparison to individual investors. However, under the context of ecological rationality, recognition-based heuristics work better and sometimes dominate the classical methods. The research scholars from the behavioural finance community have highlighted that recognition-based heuristics and their impact on investment management activities are high profile areas, needed to be explored further in the field of behavioural finance. The study of recognition-based heuristic-driven biases has been found to be insufficient in the context of emerging economies like Pakistan. Practical implications: The skilful understanding and knowledge of the recognition-based heuristic-driven biases will help the investors, financial institutions and policy-makers to overcome the adverse effect of these behavioural biases in the stock market. This article provides a detailed explanation of recognition-based heuristic-driven biases and their influence on investment management activities which could be very useful for finance practitioners' such as investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/ broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making its financial management strategies. Originality/value: Currently, no recent study exists, which reviews and evaluates the empirical research on recognition-based heuristic-driven biases displayed by investors. The current study is original in discussing the role of recognition-based heuristic-driven biases in investment management activities by means of research synthesis. This paper is useful to researchers, academicians, and those working in the area of behavioural finance in understanding the role that recognition-based heuristics plays in investment management activities. [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]

We proposed a method to reduce the data-mining bias[1] caused by the complexity of machine learning models and to increase their readability and transparency of the models, considering an investment situation in financial business as an example. By investment simulations with real financial data, we could confirm that our proposed method improved investment performance compared with the original random forest[2] even though decision rules were simplified and their number of them was reduced by our proposed method. [ABSTRACT FROM AUTHOR]

Changes to US wildfire policy in 2009 blurred the distinction between fires managed for resource benefits and fires with primarily suppression objectives, making management strategies difficult to track. Here, qualitative text is coded from a sample of 282 Wildland Fire Decision Support System Relative Risk Assessments completed on wildfires between 2010 and 2017 to examine the prevalence of different strategies and their associations with risk. Suppression is used most, associated with high risk. Managers discuss intent to suppress even when it is untenable. Monitoring, confine, or point protection are used much less commonly and when risk is low. The Southwest region discusses a diversity of strategies, leveraging landscape barriers from past management to support them; the Northwest discusses suppression or monitoring and rarely links strategy selection to barriers. Based on associations between physical barriers to fire spread, risk, and strategy, creating more barriers may provide a path forward to better implement fire policy. Study Implications: Systematic analysis of text data in wildfire decision documents provides insights into how fires are managed. Most wildfires are still aggressively suppressed despite federal fire policy promoting the use of fire to enhance resources. When managers discuss risk during wildfires, it is evident that physical barriers to fire spread (e.g. rivers, roads, trails, rocky scree), including mechanical fuel treatments, prescribed fires, and previous wildfires, are important factors in operational fire planning. However, management strategies promoting the use of wildfire to enhance ecological resiliency or reduce transmission of future fires to values are used sparingly. Southwest fire managers are relying on past wildfires, fuel treatments, and prescribed fires more so than the Northwest to engage in a full spectrum of fire management strategies. This finding suggests that, at least in some geographies, ongoing investments in fuels management will pay dividends in reducing risk and broadening opportunities to meet federal policy goals. [ABSTRACT FROM AUTHOR]

Copyright of TESAM Academy Journal is the property of Tesam Academy 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.)

Copyright of TESAM Academy Journal is the property of Tesam Academy 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.)

Copyright of Contabilidad y Dirección is the property of ACCID 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.)

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]

Based upon behavioral perspective and agency theory, this paper attempts to investigate the effect of CEO stock option pay on firms' risk‐taking investments in the restaurant sector. Specifically, this paper proposes that option‐loaded CEOs tend to make risky investments. In addition, we investigate how the prior stock performance of a firm and its CEOs' characteristics moderate this relationship. The findings of this paper show that option‐loaded CEOs are more likely to engage in risk‐taking investments. However, this positive main relationship is diminished when a firm has a good prior stock performance, when a CEO has a longer tenure, and when he or she becomes aged. Given the lack of empirical literature that explores the corporate governance in the hospitality literature, this study adds value to the existing research by further investigating the effect of CEO stock option pay scheme on restaurant firms' risk‐taking behavior. [ABSTRACT FROM AUTHOR]

Copyright of Corporate Management Review is the property of College of Management, National Chiao Tung University 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.)

The German economy began recovering at the beginning of 2024 and has developed better than initially expected. A sharp rise in construction investment, albeit more of a flash in the pan as a result of mild winter weather, along with strong goods exports helped the economy onto its recovery path and masked the disappointing development of private consumption, which sank unexpectedly. However, consumer sentiment has since brightened considerably: Following the recent special payments, employees in many sectors are now earning more on a permanent basis due to pay raises, which increases income security. In conjunction with the inflation rate now being stable at below the three-percent threshold, real wages are rising significantly. Added to this is the turnaround in interest rates initiated by the European Central Bank, which is making saving less attractive and loans more affordable. The UEFA European Men's Football Championship, which is being held in Germany this year, is also likely to boost consumption, albeit slightly. In addition to private consumption, foreign trade will prove to be the second mainstay of the German economy in the forecast period. On the one hand, imports are increasing as the domestic economy becomes stronger. On the other hand, the German export industry will also experience a significant boost, as industrial production is likely to pick up worldwide. Due to the high share of intermediate products and investment goods, exports "made in Germany" are particularly dependent on the global industry's economic situation. In Germany, too, industrial companies will begin investing more in their capacities from 2025 at the latest. Construction investment will then also rise again. Overall, the outlook is somewhat more positive than it was in the spring: Instead of stagnating, DIW Berlin now expects the German economy to grow by 0.3 percent in 2024 and by 1.3 percent in 2025. One risk factor for the forecast is that the full extent of the damage from the flooding in southern Germany is still unclear. In some places, production capacities could remain impaired for longer than expected. At the same time, it is also conceivable that repair and reconstruction work could increase economic output. Overall, however, the effects in one way or the other are likely to remain manageable. In addition, the tug-of-war over the next federal budget could once again become a factor contributing to uncertainty, possibly even more so than was already to be expected after the results of the EU elections in Germany. The global economy will also gain some momentum over the forecast period. The euro area is finally overcoming its weak phase for good and international trade is picking up speed. The interest rate turnaround in the major advanced economies will likely have a positive effect on residential construction and corporate investments from the second half of 2024. Overall, the global economy is expected to grow by 3.7 percent in 2024 and by 3.6 percent in 2025. [ABSTRACT FROM AUTHOR]