Investment Efficiency Research Articles

The impact of construction of an integrated shell waste management site on social, economic, and environmental aspects in Cirebon, West Java

Abstract The concept of a blue economy encourages business growth and efficient investment while protecting the environment by making the most of spending and financing resources that will increase economic growth and improve people’s lives. Crab shell is one of the industrial wastes of the pasteurization of crab meat, which is growing along with the demand for exports. Direct stockpiling of crab shells creates an unpleasant odor and makes access difficult for collectors of crab shells. Therefore an Integrated Shell Waste Treatment Site (ISWTS) is very important to build to support the blue economy principle, where all economic operations are zero-waste, clean, and efficient. The purpose of the study is to examine the impacts of ISWTS development on the social, economic, and environmental aspects in the Cirebon Regency. Data was collected through focus group discussions and interviews with eight miniplant owners and one supplier of crab shells. Qualitative descriptive and triangulation were applied to analyze the increase in earnings in crab industry laborers, the impact of individual and group capabilities, the strength of partnership partners, and labor absorption. The result shows there is an increase in earnings, which can contribute to the fisheries sector to the Gross Regional Domestic Product (PDRB) in Cirebon Regency through the application of the website for making orders operated by laborers and customers. This business makes more strong connections among miniplants, dryer shells, and TPLCT side through labor absorption primarily to involved and utilize at TPLCTThe study findings show that the community supports the construction of the TPLCT because it employs many people, but the building must be carried out far from residential areas.

Prophet modeling for oil production forecasting in an enhanced oil recovery field

Accurate daily oil production forecasting is essential for efficient reservoir management and investment strategy. Forecasting oil production in enhanced oil recovery (EOR) and conformance-dominated fields is a complex process due to the nonlinear, voluminous, and often uncertain nature of reservoir parameters and hidden factors. As a result, conventional tools such as decline curve analysis frequently fail to accurately predict daily oil production in conformance-controlled areas. In contrast, machine learning works efficiently for large datasets, even if the parameter values are unknown. The current study employs a Prophet time series forecasting method for five oil production wells in an EOR applied field, but it fails to achieve the desired sweep efficiency. This study compares the results of conventional decline curve analysis (DCA) and popular autoregressive integrated moving average time series forecasting methods with the Prophet model. This is the first attempt to use Prophet for oil well production forecasting, where polymer flooding is used. In all, 60% of the data are used for training, and the remaining 40% are used for testing. The Prophet shows the best performance for all the wells. This study is also the first to handle shut-in data using the Prophet model for oil production. Well-2 achieves the highest accuracy after incorporating shut-in results, with an R2 score of 92%. The result shows that though the DCA performs reasonably well with higher linearity and trend stationary data, Prophet modeling shows superior results than conventional DCA for all EOR applied producing wells.

Research on Problems and Solutions of Quantitative Investment in the Chinese Market

Quantitative investment has gradually become increasingly important in the Chinese finance market in recent decades. It improves the efficiency of investment, reduces the risk of investment, enhances the liquidity of some market assets and provides new opportunities to accumulate wealth for investors. As a new investment method, it raises some problems which lead to the turmoil of the market when it keeps developing and gaining traction. This paper will review the current situation of quantitative investment in the Chinese market from its development history and the sizes of funds. This study shows that there are mainly four problems existing in the application of quantitative investment in China. Listed below are problems. The evident government intervention in the market has a negative impact on the fitting effectiveness of quantitative models. Some kinds of assets and commodities face poor liquidity and for them, quantitative investment strategies can hardly be conducted accurately. The accuracy of quantitative analysis can be unreliable for the financial data is sometimes incomplete and unreliable in the Chinese market. The high-frequency trading affects the stability of the whole market because of lack of market supervision. This paper also puts forward relevant countermeasures and suggestions according to these problems. This study has great significance to the healthy development of quantitative investment in the Chinese market.

Does banking competition increase corporate labor income share? Evidence from China

This paper investigates the impact of banking competition on corporate labor income share in China. Utilizing hand-collected unique data on bank branches within a certain distance of firms and a large sample of Chinese A-share list firms spanning the period 2000–2022, we find that banking competition significantly boosts corporate labor income share. A 10 percent increase in banking competition, the corporate labor income share increases by 0.06 percent on average. The results remain robust after replacing proxies, changing estimation methods, controlling for other shocks, and addressing endogenous concerns. Easing financing constraints, improving investment efficiency, and enhancing human capital are three essential channels through which banking competition promotes corporate labor income share. We also find that the impact of banking competition on corporate labor income share is more pronounced for firms with higher external financing dependence, higher financing gaps, more investment opportunities, higher governance efficiency, and higher information asymmetry. Our findings highlight the significance of enhancing banking competition to promote income distribution, foster common prosperity, and drive high-quality economic development.

Portfolio Optimization Strategies: New Approaches Based on Machine Learning Forecasting

This study provides an in-depth discussion and comprehensive review of the latest applications of machine learning techniques in the field of portfolio optimization. The article begins with an overview of traditional portfolio optimization theory and its limitations, and then focuses on how machine learning predictive models, which have flourished in recent years, can provide new perspectives and tools for solving the problems of non-linearity, dynamics and uncertainty in investment decision-making. This paper provides a detailed overview of the application practices of various machine learning algorithms (e.g., deep learning, reinforcement learning, integrated learning, etc.) in the areas of asset return prediction, risk assessment, and optimal weight allocation, and analyses their advantages and challenges compared to traditional methods. The analysis of relevant research cases reveals the significant effect of machine learning predictions in increasing expected portfolio returns, reducing risk exposure, and achieving effective diversification. The study also explores possible future trends and potential research directions for machine learning in portfolio optimization, highlighting the importance of combining domain knowledge with big data-driven intelligent investment decisions. This review aims to provide financial scholars and practitioners with a new way of thinking about portfolio optimization, and to promote the combination of theoretical research and practical operation in the fields of financial engineering and investment management, so as to achieve more accurate and efficient investment decisions.

Do Bill Shocks Induce Energy Efficiency Investments?

Do Bill Shocks Induce Energy Efficiency Investments?

Tax-avoidance Effect on Investment Inefficiency: An Examination of Agency Theory

Tax-avoidance activity in firms potentially increases investment inefficiency, arguably due to agency problems in firms. Further, this relationship shows country-wide variation. Using the data of 336 Indian firms from 2011 to 2021, this article examines the tax avoidance and investment efficiency relationship in the Indian context. It also provides empirical evidence for the agency argument on the tax avoidance-investment efficiency relationship. Estimates using the two-step system generalized methods of moments approach show that tax avoidance in Indian firms is positively associated with investment inefficiency, and the agency problem augments this relationship. The findings have significant policy implications for policymakers and firms. JEL Codes: G30, G32, G34

기업의 ESG 성과가 기업가치에 미치는 영향 : 최고경영자 특성을 중심으로

[Purpose] It analyzes how ESG management (environment, society, and governance) affects corporate value and analyzes whether these correlations differ according to the CEO’s personal characteristics to further confirm the CEO’s role in ESG activities. Through this, it is intended to present a new perspective on the characteristics of managers and provide an opportunity to increase the importance of ESG activities. [Methodology] This study collected data from 2,469 companies listed on the Korea Exchange from 2020 to 2022. The data included ESG activity metrics, demographic characteristics of managers, overconfidence, and capabilities. Using multiple regression analysis, the relationship between managerial characteristics and ESG activities was examined. [Findings] The results indicate that managers with higher levels of overconfidence tend to participate more actively in ESG activities. Additionally, the higher the managerial capability, the more vigorous the ESG activities, which positively influenced corporate value. [Implications] This study suggests that companies can actively introduce and effectively perform ESG management to improve corporate value. In particular, managers with excellent abilities can actively implement ESG management to improve the corporate image, improve the company’s sustainable management, and maintain the company’s long －term competitive advantage. It can help companies and investors recognize this fact. In the future, more efficient ESG management and investment strategies will be established in consideration of the characteristics of the CEO in the management and investment process.

Impact of Internal Control and Audit Quality on Corporate Investment Efficiency - Focus on Chinese Listed Companies

Impact of Internal Control and Audit Quality on Corporate Investment Efficiency - Focus on Chinese Listed Companies

Financial management, efficiency, and care quality: A systematic review in the context of Health 4.0.

This article investigates the intersection between innovation, Health 4.0, and financial management in the healthcare industry, emphasizing the importance of operational efficiency and quality of care. The study aims to analyze how financial management processes in healthcare relate to Health 4.0 and enhance care quality. It begins with a thorough theoretical grounding, proposing a framework that connects Health 4.0 with financial management practices. A systematic review of the literature was conducted, identifying trends, challenges, and opportunities in the financial management of Health 4.0. The results highlight selected articles on responsible innovation, Health 4.0 technologies, investments in health, hospital efficiency, performance forecasting, and high-cost patient management. These articles were clustered into "Data Analysis and Machine Learning in Healthcare" and "Health Management and Sustainability," providing a categorized understanding of the topics. The study reveals that Health 4.0 offers significant opportunities for process efficiency and cost reduction without compromising service quality. It highlights strategic advantages in addressing contemporary healthcare challenges by optimizing processes, improving financial projections, and incorporating advanced technologies efficiently. The successful implementation of Health 4.0 can lead to substantial improvements in service quality, adding value to patients and driving local economic development. This article offers valuable insights for healthcare professionals and managers, emphasizing the transformative potential of Health 4.0 and outlining strategies for its effective implementation. The clustering of articles provides a clearer understanding of current research in Health 4.0, contributing significantly to the field and guiding future research directions.

Debt maturity, governance and investment efficiency: new evidence from emerging market

PurposeThis study investigates the combined influence of corporate governance (CG) and debt maturity (DM) on the investment inefficiency among non-financial 506 NSE-listed firms in India between 2009 and 2022. Additionally, this study also investigates the moderating effect of short-term debt (STD) maturity concerning the relationship between CG and investment inefficiency.Design/methodology/approachUtilizing the residuals extracted from the Biddle et al. (2009) investment model, three different forms of investment inefficiency (investment inefficiency, overinvestment and underinvestment) were measured. To measure the internal governance of firms, a new corporate governance index (CGI) was developed using 65 new governance stipulations, whereas STD was measured as short-term debt divided by total debt. Interaction effects between CG and DM were also estimated. Employing CGI and STD along with firm-specific control variables, many pooled regression models were estimated. Endogeneity issues were addressed through two-stage least squares. Robustness checks were also conducted using the two-step system GMM, alternative measures of dependent and independent variables.FindingsThe findings demonstrate that higher CG and shortened DM increase investment efficiency. This evidence implies that firm-level governance and short-term debt reduce information asymmetry and increase management oversight. Additionally, the evidence suggested that shortened DM and CG complement one another to increase investment efficiency, suggesting companies that utilize STD to a greater (lesser) extent demonstrate a greater (lesser) impact of CG in reducing investment inefficiency.Practical implicationsThis work first advocates the establishment and implementation of robust corporate governance mechanisms to control agency conflicts, moral hazard, adverse selection and limit opportunistic behavior of managers for improving investment efficiency. Second, since interaction effects suggest a complementarity between CG and DM, it is advocated that STDs can be used to achieve optimal investment choices to control moral hazards and adverse selection and discourage suboptimal investment levels.Originality/valueThis work provides new evidence concerning the effects of CG and DM on various forms of corporate investment efficiency (investment inefficiency, overinvestment and underinvestment, using alternate measures) in an emerging economy like India having a unique institutional framework and macroeconomic environment using a newly developed firm-specific CG index for a large sample of companies using recent data.

Majority-of-the-minority shareholder votes and investment efficiency

In an environment where concentrated share ownership is the norm, we ask whether Majority-of-the-Minority (MoM) votes curb controlling shareholder overreach and investment inefficiency. We consider MoM votes on controller-based related party transactions in China. Such votes give minority parties potential veto power. We report strong association between shareholder disapprovals on controller-based investment related MoM proposals and the underlying entity's investment plans. This association is robust to a battery of tests, including assessment of pre-vote consultation between minority and controlling shareholders and an exogenous regulatory shock. We also report increased likelihood of informal securities enforcements in the year following MoM shareholder disapproval.

Do regional tax incentive policies improve productivity?

The difficulty in transforming old industrial areas constitutes a significant factor contributing to regional development imbalances. Can regional tax incentives, as a crucial component of regional policies, polish the "rust belt" regions? This study leverages the inaugural Value-Added Tax (VAT) reform in China as an opportunity to explore the potential of regional tax incentives in achieving sustainable development in traditional industrial areas. Drawing upon a comprehensive industrial enterprise database, we employ a Propensity Score Matching-Difference in Differences (PSM-DID) approach to examine the efficacy of these tax incentives. Our findings reveal that: (1) Regional tax incentives primarily enhance firms productivity by stimulating investment in enterprises, yet they do not contribute to improved investment efficiency or spur innovation within firms. (2) Regional tax incentives have alleviated financing constraints for enterprises in old industrial bases, significantly enhancing the Total Factor Productivity (TFP) of firms with higher financing constraints. This policy has had an even stronger impact on improving the TFP of state-owned and monopolistic enterprises. (3) Regional tax incentives have impeded productivity growth by preventing the exit of low-efficiency firms and the entry of high-efficiency ones. These incentives also increased the likelihood of "zombie firms" forming and failed to promote endogenous economic growth in the Northeast region. Additionally, they have distorted the allocation of resources towards capital and technology-intensive industries in that area. In China's old industrial bases, regional tax incentives should be coordinated with market-oriented reforms; these regional tax incentive policies should also be further enriched.

How does carbon emissions trading scheme affect the investment efficiency of companies? Evidence from China

Carbon emissions trading scheme (ETS) will change the internal and external operating environment of related companies, increase new carbon reduction costs, and may affect their investment behavior and decision-making. This study constructs the policy effect evaluation model to evaluate the net effect of China's ETS pilot policy on the investment efficiency of related companies in high-carbon industries. This study indicates that: first, China's ETS pilot policy has reduced the inefficient investment of related companies by 11.40% during the sample period. Second, innovation ability plays an enhanced moderating effect in the inhibitory effect of China's ETS pilot policy on the inefficient investment of related companies in the short term, but the effect is weakened in the long-term. Third, the policy effect is relatively obvious for non-state-owned companies and companies with more institutional shareholdings. This research has important reference value for the continuous improvement of China's national carbon market, and the steady transformation from simple investment-driven to investment-efficiency-driven economic development in China.

Supply chain network, digital transformation, and investment efficiency

ABSTRACT In the modern digital era, firms’ position in the supply chain networks significantly impacts their investment decision-making. As businesses undergo digital transformation to enhance collaboration and supply chain efficiency, a research gap exists in understanding their combined influence on investment efficiency. Using Chinese public firms from 2008 to 2021 as a sample, we construct a supply chain network and analyse how supply chain network structures affect investment efficiency. Our results show that both supply chain network centrality and structural holes enhance firms’ investment efficiency. Mechanism analysis shows that corporate digital transformation moderates this relationship by mitigating financing constraints and agency costs. In addition, further results reveal that the effect of supply chain networks is stronger for non-state-owned firms, firms in low-marketization region, and firms in closer geographic proximity to their customer base. This study contributes to understanding the roles of supply chain networks and digital transformation in firms’ investment efficiency.

Environmental, social and governance (ESG) performance as a moderator in assessing the impact of government subsidies on underinvestment in China

In recent years, underinvestment has become common among subsidised enterprises in China. Stakeholder theory asserts that environmental, social and governance (ESG) performance forces enterprises to prioritise stakeholder needs by incorporating ESG principles into business operations, which in turn influences business investment decision-making. This study examines the impact of government subsidies on firm underinvestment and whether ESG performance plays a moderating role in this direct relationship. A dataset of 17,780 firm-year observations of A-share public firms in China for the period 2011–2021 was employed, and the data were analysed using the ordinary least squares regression model, fixed-effects regression model, propensity score matching difference-in-difference model, and instrumental variable approach. These results indicate that government subsidies mitigate firm underinvestment and tend to reduce underinvestment in firms with higher ESG performance. Moreover, the findings indicate that the performance in ESG factors influences the effect of government subsidies on the lack of investment in state-owned enterprises (SOEs), as opposed to non-SOEs. This effect is more noticeable in heavily polluting industries compared to non-heavily polluting industries. These findings imply that the government should promote the ESG performance of subsidised firms to enhance their overall corporate investment efficiency.

Fostering Investment Efficiency in Indonesian Firms: Empirical Evidence and Recommendations for Future Research

Objective –The purpose of this research is to review and examine the empirical evidence on investment efficiency in Indonesia.Design/methodology –This research employs bibliographic analysis. This research utilizes 30 articles published between 2015 and 2023 in internationally recognized Scopus journals and nationally recognized Sinta 2 journals.Results –This research identifies three categories of factors that impact investment efficiency namely financial, governance, and non-financial factors. Financial factors are essential in assessing investment effectiveness, while corporate governance factors can enhance a firm's investment decisions. Non-financial factors related to managerial personnel can also significantly impact a firm's investment efficiency. Future research on investment efficiency in Indonesia should incorporate diverse variables and external factors, conduct comparative studies with neighboring countries, and collaborate with industry stakeholders to bridge the gap between theory and practice.Research limitations/implications –This research focuses primarily on analyzing the literature on investment efficiency in Indonesia by using charting the field method. This research adds to the literature on the various factors that affect the investment efficiency of firms.Novelty/Originality –This research is the first to conduct a comprehensive literature review on investment efficiency in Indonesia. By systematically analyzing findings from various studies, this research offers a unique and thorough understanding of investment efficiency within the Indonesian context.

State management of public investment in road construction in Vietnam: Current situation and solutions

This study examines Vietnam’s state management of public investment in road construction. The development of road transport infrastructure is in extremely high demand as Vietnam undergoes an economic transition. Despite the fact that the effects of the COVID-19 pandemic have caused the economy to grow more slowly recently, public investment in the transport industry has increased significantly. Several modern, large-scale road works that have been finished and put into operation are having a significant positive impact on urbanization, connecting regions, and socioeconomic development. However, public investment in road transport construction still has a lot of issues that need to be fixed. The state’s weakness is one of the primary issues that reduces investment efficiency. This study analyzes the state management of public investment in road construction, according to the following contents: legal system and policies; formulation and implementation of public investment plans; inspection and supervision by state management agencies. The method of collecting secondary data and primary data (through sociological investigation) is used and combined with Statistical Package for the Social Sciences (SPSS) software to determine the influencing factors and find out the problems and their causes. Therefore, this study proposes a number of urgent and practical solutions to improve the state management of public investment in road construction and develop a synchronized road transport network.

Optimized green infrastructure planning at the city scale based on an interpretable machine learning model and multi-objective optimization algorithm: A case study of central Beijing, China

Green infrastructure (GI) has developed as a sustainable approach to the mitigation of urban floods. While machine learning (ML) models have exhibited advantages in urban flood simulation, their direct application to support the quantitative planning of GI at the city scale remains a challenge. To address this, an interpretable ML model based on support vector machine (SVM) and the Shapley additive explanations (SHAP) approach is integrated with the non-dominated sorting genetic algorithm-II (NSGA-II) in this study. The model is applied to the case of central Beijing, China, and demonstrates a robust performance with a high area under curve (AUC) value of 0.94. The results of the urban flood susceptibility assessment identify the urban-rural transition zone in the study area as being under a greater flood threat. Via model interpretation with SHAP, the dominant roles of GI and grey infrastructure (GrI) in preventing flood are revealed and the non-linear complementarity between the two is demonstrated to be more significant in study units with a GI proportion of less than 0.45. Supported by the NSGA-II-based optimization framework, optimal GI plans under different total implementations of GI are achieved, among which a solution with a 3.21% increase in the total GI area is selected as that with the best investment efficiency. The pattern of GI implementation is suggested to be dispersed and small-scale by model. This study provides a tool with broad application prospects, effectively integrating GI implementation with urban planning. The findings of this study not only provide important references for the determination of the priority areas of new ecological space in Beijing, but also provide areas that share similar characteristics with new insight into GI planning and the management of urban floods.

Evaluation of market transformation efficiency of urban investment and development companies based on the three-stage DEA model

Evaluation of market transformation efficiency of urban investment and development companies based on the three-stage DEA model