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This study explores whether religion plays an important role in corporate poverty alleviation. Religious atmosphere affects managers' attitude towards corporate social responsibility (CSR) and then influences corporate poverty alleviation. This study first examines the impact of religious atmosphere on corporate poverty alleviation and then investigates whether formal institutions, such as law enforcement environments and ownership, influence the relationship between religious atmosphere and corporate poverty alleviation behavior.

In 2016, the Chinese government initiated a nationwide campaign aiming to eliminate poverty in China by 2020. The authors conduct empirical tests with data on Chinese listed firms from 2016 to 2020. The religious atmosphere is measured by the number of Buddhist monasteries and Taoist temples within a certain radius around Chinese listed firms' registered addresses. The authors adopt the ordinary least squares (OLS) method for regression and take the two-stage least squares (2SLS) method to address the endogeneity issue.

The results show a positive relationship between religious atmosphere and corporate poverty alleviation donations. Law enforcement attenuates the positive association between the religious atmosphere and corporate poverty alleviation donations. Religion and corporate poverty alleviation donations have a more positive association for non-state-owned enterprises (non-SOEs) than for state-owned enterprises (SOEs).

The authors' findings have important implications. First, this study inspires incorporating the ethical value of traditional culture, such as religion, into CSR. Second, the findings imply that informal institutions have a greater impact on corporate decision-making when formal institutions are weak, suggesting that informal institutions should be emphasized when promoting CSR in countries where formal institutions are relatively weak. The study investigates only religious influence on corporate poverty alleviation based on Buddhism and Taoism, but the authors do not examine the impacts of other religions. Future research may examine the relationships between other religions and corporate poverty alleviation in China.

This study illustrates the positive role played by religion in promoting CSR by relating religious atmosphere to corporate poverty alleviation. It fills the research gap between religion and CSR and also contributes to the literature on determinants of corporate poverty alleviation.

The development of e-grocery allows people to purchase food online and benefit from home delivery service. Nevertheless, a high rate of failed deliveries due to the customer’s absence causes significant loss of logistics efficiency, especially for perishable food. The purpose of this paper is to propose an innovative approach to use customer-related data to optimize e-grocery home delivery. The approach estimates the absence probability of a customer by mining electricity consumption data, in order to improve the success rate of delivery and optimize transportation.

The methodological approach consists of two stages: a data mining stage that estimates absence probabilities, and an optimization stage to optimize transportation.

Computational experiments reveal that the proposed approach could reduce the total travel distance by 3-20 percent, and theoretically increase the success rate of first-round delivery approximately by18-26 percent.

The proposed approach combines two attractive research streams on data mining and transportation planning to provide a solution for e-commerce logistics.

This study gives an insight to e-grocery retailers and carriers on how to use customer-related data to improve home delivery effectiveness and efficiency.

The proposed approach can be used to reduce environmental footprint generated by freight distribution in a city, and to improve customers’ experience on online shopping.

Being an experimental study, this work demonstrates the effectiveness of data-driven innovative solutions to e-grocery home delivery problem. The paper also provides a methodological approach to this line of research.

Aiding employment is an important poverty reduction strategy in many countries’ social welfare systems, as this strategy can help empower the recipients with a better living standard, development and social inclusion. The purpose of this paper is to identify the most significant individual and systematic variables for the employment status of low-income groups in urban China.

The data of this study are drawn from “Social Policy Support System for Poverty-stricken Families in Urban and Rural China 2015” report. The Ministry of Civil Affairs of the People’s Republic of China appointed and funded the Institute of Social Science Survey (ISSS) at Peking University to deliver the related project and organize a research team to write the report. Multiple binary logistic regression analysis is adopted to identify both individual and systematic factors that affect the employment status among low-income groups in urban China.

According to the results of the binary logistic regression model, individual factors, including: gender; householder status; education; and self-rated health status, play a significant role in determining the employment status of low-income groups in urban China. Clearly, the impacts of individual factors are more influential to marginal families than to families entitled to receive Basic Living Allowance. In contrast, compared with marginal families, systematic factors are more influential to families entitled to receive Basic Living Allowance.

This study highlights the importance of precise poverty reduction strategy and the issue of “welfare dependence” among low-income groups in urban China. Policy recommendations derived from the findings are hence given, including: the promotion of family-friendly policies; the introduction of a smart healthcare system; the establishment of a Basic Living Allowance adjustment mechanism; and the provision of related social services.

The authors test the effect of expenditure decentralization and fiscal equalization on short- and long-run economic growth and estimate two-step generalized method of moment (GMM) simultaneous equations models, using panel data for China and India for the period 1985 to 2005. The authors estimate two simultaneous equations: a growth equation and equalization equation and find that expenditure decentralization has a negative and statistically significant effect at conventional levels on short-run economic growth for both China and India. However, the authors also find that this result is sensitive to the set of included explanatory variables. This leads the authors to conclude that expenditure decentralization has no effect on short-run economic growth for either country. The authors also find that expenditure decentralization has a positive and statistically significant effect on fiscal equalization for both countries but find no evidence that fiscal equalization affects short-run economic growth for either China or India. In contrast, the authors find that expenditure decentralization has a positive effect on long-run economic growth in the case of India, but not in the case of China. Finally, the authors report evidence that fiscal equalization has no effect on long-run economic growth in the case of China; however, the authors find that equalization has a positive and statistically significant at conventional levels effect on long-run economic growth in India.

The authors estimate two-step GMM simultaneous equations models, using panel data for China and India for the period 1985 to 2005. To examine the effect of fiscal decentralization (FD) policies on economic growth in China and India, the authors estimate two equations: a growth equation and an equalization equation. For the growth equation, the authors adopt a production-function-based model that is widely used in the empirical literature on growth; however, the authors do make some compromises with this specification due to the unavailability of certain data. For the equalization equation, the authors include variables that economic theory and empirical evidence suggest influence fiscal disparities among subnational governments which in turn influence the demand for horizontal fiscal equalization (HFE). To the extent possible, the authors employ the same econometric specification, variable constructions and sample periods for both China and India. The authors believe this strategy provides a more rigorous test of the FD hypothesis.

The authors find that expenditure decentralization has a negative and statistically significant effect at conventional levels on short-run economic growth for both China and India. However, the authors also find that this result is sensitive to the set of included explanatory variables. This leads to conclude that expenditure decentralization has no effect on short-run economic growth for either country. The authors also find that expenditure decentralization has a positive and statistically significant effect on fiscal equalization for both countries but find no evidence that fiscal equalization affects short-run economic growth for either China or India. In contrast, the authors find that expenditure decentralization has a positive effect on long-run economic growth in the case of India, but not in the case of China. Finally, the authors report evidence that fiscal equalization has no effect on long-run economic growth in the case of China; however, the authors find that equalization has a positive and statistically significant at conventional levels effect on long-run economic growth in India.

Due to the importance of FD policies, especially to many developing countries that are currently pursuing decentralization reforms, future research should examine the effect of FD on economic growth for other countries. Furthermore, although it would be difficult to do so, future research should examine whether FD promotes political stability on ethnically diverse countries.

To the best of the authors’ knowledge, no one has examined the effect of FD policies on India's growth experience. What is more is that this is also the first of its kind to have a comprehensive empirical investigation into these two major developing countries with very interesting similarities and differences in FD policies. It is thus of great importance to examine the effect of expenditure decentralization and HFE on economic growth in China and India.

There are certain differences in the production products of enterprises. What are the impacts of product differentiation on the iron and steel industry? Based on the macro background of CO₂ emission reduction, this paper aims to analyze the economic benefits and environmental changes of the iron and steel industry under the dual influence of CO₂ emission reduction policy and product differentiation policy.

Taking the basic data of iron and steel industry in six regions of China as an example, this paper constructed an extended two-stage dynamic game model to analyze the impact of product differentiation and carbon tax policy on the production, economic indicators and CO₂ emission levels for the overall industry and regional enterprises.

As the CO₂ emission reduction target increased, the unit carbon tax and total tax increased, whereas the macro-environmental losses, social welfare, consumer surplus and outputs decrease. Emission reduction pressures and other economic indicators showed obvious regional differences. Differentiated products promoted various indicators of enterprises and industries; higher degrees of product differentiation resulted in greater promoting effects on economic indicators.

This paper constructed multiple emission reduction and production backgrounds, and discusses the impact of the comprehensive implementation of these policies, which has been practically absent in previous studies. The results of this study are consistent with the current industrial policy for stable production and environmental protection, and also provides a reference for the formulation of detailed policies in the future.

This paper reviews the literature on zombie firms to provide a holistic view by delineating their formation, impact, widespread nature, prevention and policy implications.

This paper uses a systematic literature review methodology, in which 76 papers published in journals ranked on the Australian Business Deans Council (ABDC) 2022 list were reviewed. The study period was from 2000 to 2022.

Among the main findings, the widespread problems of zombie firms were evident. The authors found that consistent support, either in the form of government grants or a weak financial framework, was responsible for their formation. The suboptimal performance of factors of production, depressed job creation, low innovation and overall negative impact on economic activity are the consequences of zombification. This can be controlled by ensuring better bankruptcy codes, focused on government assistance, technology use and better due diligence by banks.

This review serves as a reference point for future researchers as a cohesive and holistic study presenting a full picture of the problem, so that the proposed solutions are robust and tenable.

This review is among the initial attempts to comprehensively study published work on zombie firms in terms of analyzing their region-specific nature, with an emphasis on definition, causes, impact and prevention.

This paper aims to provide a driving behavior scoring model to decide the personalized automobile premium for each driver.

Driving behavior scoring model.

The driving behavior scoring model could effectively reflect the risk level of driver’s safe driving.

A driving behavior scoring model for UBI.

The purpose of the study is to analyze changes in land use, specifically residential area expansion, in South Tangerang City and identify the factors that influence land use change.

The study used remote sensing methods in ArcGIS 10.8 for data analysis and processing, including spatial analysis and identification of land use changes. The study analyzed satellite images from 2010 and 2020 to identify changes in land use in South Tangerang City over the ten-year period.

The study found that the most significant land use changes in South Tangerang City between 2010 and 2020 were the reduction of mixed plantation area and the expansion of residential areas. The study identified the development of small townships by private developers as the main factor that influenced land use change in South Tangerang City.

The study has several limitations, including a focus on only one aspect of land use change (i.e. residential area expansion), limited scope of the study area (South Tangerang City) and a reliance on remote sensing methods for data analysis.

The findings of the study can be used by policymakers and city planners to develop sustainable land use planning strategies that balance the need for urban development with environmental and social concerns. By understanding the factors that drive land use changes in South Tangerang City, policymakers can develop policies that encourage sustainable urban growth and development while preserving natural resources and protecting the environment.

The study has social implications as the expansion of residential areas in South Tangerang City indicates a growing demand for housing in the area. The study highlights the importance of developing affordable and sustainable housing solutions to meet the needs of the growing population in South Tangerang City. Additionally, the study emphasizes the importance of understanding the social and economic factors that drive land use change and their implications for the well-being of local communities.

The residential area development in South Tangerang City is driven by private developers who make small independent cities that have all facilities in one area. These small cities attract people to reside and also drive high population growth in South Tangerang City, considering it is a buffer city of Jakarta that has good infrastructure development.

The aim of this study is to investigate the impact of local political uncertainty on the asymmetric cost behavior (i.e. cost stickiness) for listed firms in China.

In this study, the authors manually collect the turnover data of prefecture-city officials as a measure of exogenous fluctuations in political uncertainty and obtain firm-level financial information from the China Stock Market Accounting Research (CSMAR) database. To perform the analysis, the authors augment the traditional cost stickiness model by including the interaction terms of the prefecture-city official turnover, and firm-level and prefecture-city level control variables.

The authors find that political turnover leads to a higher degree of cost stickiness, implying that firms retain slack resources when political uncertainty is high. Moreover, the effect of political turnover on cost stickiness is more pronounced for firms residing in regions with weaker institutional environments, and firms that are privately owned and with smaller size. The authors further provide evidence that policy uncertainty and the threat of losing political connection are two underlying channels. Overall, this study documents that the local political process is an important channel that influences corporate operational decisions.

This study provides the first piece of evidence on the relation between political uncertainty and cost stickiness at the local government level. Moreover, the authors propose and demonstrate two underlying channels through which political uncertainty affects firms' asymmetric cost behavior.

The interruption event will seriously affect the normal operation of urban rail transit lines,causing a large number of passengers to be stranded in the station and even making the train stranded in the interval between stations. This study aims to reduce the impact of interrupt events and improve service levels.

To address this issue, this paper considers the constraints of train operation safety, capacity and dynamic passenger flow demand. It proposes a method for adjusting small loops during interruption events and constructs a train operation adjustment model with the objective of minimizing the total passenger waiting time. This model enables the rapid development of train operation plans in interruption scenarios, coordinating train scheduling and line resources to minimize passenger travel time and mitigate the impact of interruptions. Regarding the proposed train operation adjustment model, an improved genetic algorithm (GA) is designed to solve it.

The model and algorithm are applied to a case study of interruption events on Beijing Subway Line 5. The results indicate that after solving the constructed model, the train departure intervals can be maintained between 1.5 min and 3 min. This ensures both the safety of train operations on the line and a good match with passengers’ travel demands, effectively reducing the total passenger waiting time and improving the service level of the urban rail transit system during interruptions. Compared to the GA algorithm, the algorithm proposed in this paper demonstrates faster convergence speed and better computational results.

This study explicitly outlines the adjustment method of using short-turn operation during operational interruptions, with train departure times and station stop times as decision variables. It takes into full consideration safety constraints on train operations, train capacity constraints and dynamic passenger demand. It has constructed a train schedule optimization model with the goal of minimizing the total waiting time for all passengers in the system.