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As absolute poverty in China, measured by the current standard, is being eliminated, the focus of future poverty reduction projects will necessarily shift to addressing relative poverty. Contiguous poverty areas have been identified in Hebei province around Beijing and Tianjin (HABT), and this is not conducive to the coordinated development of the Beijing-Tianjin-Hebei region. The dynamic identification of relative poverty at the county level within the region must be the basis for formulating scientific strategies for poverty reduction. Night light (NTL) data can reveal socio-economic information and reflect human activities, and has a wide range of other applications for evaluating and identifying poverty. For this reason, NPP/VIIRS (Visible Infrared Imaging Radiometer Suite equipped on the Suomi National Polar orbiting Partnership satellite) NTL data from 2012 to 2020 were corrected, and NTL data for HABT were obtained. A multidimensional relative poverty index (MRPI) that assesses being “free from worries over food and clothing and having access to compulsory education, basic medical services, and safe housing” using social statistical data was created with the analytic hierarchy process and entropy weight method. A panel regression model with fixed effects was established for MRPI and corrected NPP/VIIRS NTL data. The R2 of fitting was 0.6578 and confirmed a strong correlation between MRPI and corrected NPP/VIIRS NTL data. Based on this, the MRPI estimation model was constructed based on the MRPI and corrected NPP/VIIRS NTL data, and passed the accuracy test. Finally, using the national list of poverty counties, it was verified that, at the county scale, the corrected NPP/VIIRS NTL data could effectively identify areas of relative poverty. This study lays the foundation for the use of NPP/VIIRS NTL data in the identification of areas of relative poverty. It provides a feasible method and data reference for analyzing relative poverty at a smaller scale. The dynamic identification of areas of relative poverty can also provide a basis for formulating scientific poverty reduction strategies.

This study hypothesizes that employees’ positive perceptions of corporate social responsibility (CSR) activities at the individual level have a negative effect on employee deviance—a negative job-related behavior—and that anomie plays a mediating role in this relationship. In order to verify the relationship, this study conducts an empirical analysis with a questionnaire survey on employees of firms that implement CSR activities at the company level. Based on Social identity theory, this study examines the causal relationship between the employees’ perceptions of CSR activities and their deviance, and mechanisms by which anomie decreases in the process. The findings are as follows. First, employees’ perceptions of CSR activities had a negative effect on employee deviance. Second, employees’ perceptions of CSR activities had a negative effect on anomie. Third, anomie had a positive effect on employee deviance. Fourth, anomie fully mediated the relationship between employees’ perceptions of CSR activities and employee deviance. This study is the first to document this relationship, which has great practical and academic significance, as it indicates the importance for companies to consider employees’ perceptions of CSR activities. In addition, the study identifies the mediating role of anomie as mentioned above. The results suggest that methodological considerations of CSR awareness enhancement at the company level be discussed more in depth, helping top management and middle managers understand that enhancing employees’ positive perceptions of CSR activities should be the first priority for reducing collective normlessness under the pressure of goal attainment and resolving ethical conflicts among employees.

Abstract Motivated by the practical application of information and communication technologies (ICT)-based innovations in environmental and social responsibility (ESR) investment, this study investigates a sustainable power supply chain that consists of a traditional energy power generation firm (TEF), a renewable energy power generation firm (REF) and a downstream power distributor (PD). Each supply chain member can invest in ESR to achieve energy conservation and emission reduction, and thereby gain economic benefits. To achieve higher power level for better ESR investment, the TEF may actively form an alliance with the REF or the PD, or not, which leads to three different alliance strategies, i.e., Strategy HA, Strategy VA, and Strategy NA, respectively. The results show that NA is the equilibrium strategy when the TEF’s investment cost is low while the PD’s investment cost is medium. However, when the TEF’s investment cost is medium while the PD’s investment cost is low, VA is the equilibrium strategy. Moreover, when the investment cost of the TEF and the REF are both low, HA is the equilibrium strategy. In the other cost intervals, the three power firms will not invest in ESR simultaneously, and consequently the alliance strategy has no effect on the revenue allocation. Therefore, the TEF forms no alliance with either the REF or the PD. By comparison with the unaligned case, we find that alliance not only benefits the TEF, but also the other firms in the power supply chain as well as the whole society resulting from the improved ESR investment, which achieves a “win-win-win” situation.

This paper presents a framework for policy makers in China that identifies the relevant design variables and market objectives that play a role in the design and analysis of spot market. We outline the full extent of the design challenge through a discussion of interactions between design variables and how they act to market objectives, and the inter-linkages between the spot market design of energy and other products, the inter-linkages with market regulation at large. In fact, the energy market design has a trend of convergence. Policy makers can address the spot market design challenge by adopting a structured approach in which market objectives, design space variables, linkage between markets products and market regulation are explicitly considered.

Vulnerability State Graph (VSG) is an important method to analyze the security status of computer network, and it plays a guiding role for the establishment of network security policy. The knowledge base of vulnerability state graph is formally described by Description Logics (DLs) in this paper, an algorithm of network vulnerability state graph generation based on Description Logics is designed and realized and the effectiveness of the algorithm is showed by an experimental example.

Abstract Measuring regional differences in fossil energy consumption is the first step to the study of natural resource allocation and utilization. This paper employs annual and cumulative consumption Gini indexes as well as the deviation index to discuss regional differences in the per capita consumption of fossil energy and related products across 30 Chinese provinces from 1997 to 2013. The results show that Chinese inter-provincial Gini ratio of fossil energy consumption is below 0.3 in recent years, and change in per capita energy consumption is the key factor behind the decline in the overall Gini index. Unlike existing studies based only on annual flows of energy consumption, this paper also focuses on cumulative energy consumption. Moreover, decomposing annual and cumulative consumption Gini coefficients by type, group, and incremental variation is rarely seen in other studies. Based on the above positive analysis, the paper provides some policymaking suggestions.

Since the load ratio deflection range of existing electric energy monthly transaction schedules is small, the optimization space of integrative cost is limited and the electricity fairness constraint of impartial and open dispatching is not satisfied. For this status, this paper proposed a Gini coefficient constraint method. The method comprehensively considered the benefits of power plants, power grids and society, taking the integrative cost of monthly electricity generation as objective function. Based on the conventional constraints of the generation unit monthly load electricity, generating capacity and load ratio range, the Gini coefficient constraint between generation unit electricity deflections was introduced to ensure the electricity implementation fairness. A monthly trade schedule model under the restriction of impartial and open dispatching was built to meet the requirements of energy-saving generation dispatching. At the prerequisite of guaranteeing constraints such as generation unit electricity fairness, energy-saving and environmental protection, the scheduling results of the calculation example achieve the goal of the lowest integrative cost and win great social benefits, showing that this method is rational and effective.

Abstract Many developing countries rely on hydropower to improve energy access and to meet their growing demands for energy. However, the social justice concerns accompanying hydropower development are in danger of being overlooked. This study focuses on arguably the most pressing social problem associated with hydropower development, namely, the displacement and resettlement of communities. Employing a case study based approach, this study investigates the extent to which hydropower development-induced resettlement process and its impacts on the resettled households respond to three different tenets of energy justice, i.e., distributional, recognition, and procedural justice. Based on fieldwork conducted at the Hongjiang and Wanmipo Hydropower Stations in Hunan Province, China for two months in 2008, this paper demonstrates that although hydropower development generated significant economic and developmental benefits by alleviating power shortages, improving grid stability, and increasing local tax revenues, these benefits came at the cost of the social exclusion of more than 20,000 resettlers. Specifically, the resettled communities experienced 1) distributional injustice from hydropower due to the low affordability of electricity and water, reduced access to land and food, and an unbalanced distribution of costs and benefits from hydropower development; 2) recognition injustice due to the lack of fairness, transparency, and accountability on the part of the hydropower developer and at all levels of government in energy decision-making; and 3) procedural injustice due to the very limited participatory rights in the decision-making process before, during, and after resettlement and the lack of viable channels through which to seek redress and remedies.

China aims to reduce its carbon dioxide emissions and promote green growth. This study aims to examine the effect of banking sector performance indicators (banks assets and return on asset) and financial inclusion on renewable energy consumption, green growth, and carbon emissions for China from 1995 to 2020 using the ARDL approach. The long-run results suggest that bank assets increase renewable energy consumption and green growth. While return on assets also increases green growth and decreases carbon emission in the long run. Financial inclusion enhances renewable energy consumption and green growth, curbing CO2 emissions. Banking sector performance and financial inclusion have short-run effects on renewable energy consumption, green growth, and carbon dixoside emissions. The findings thus point to the need for policies that promote banking sector performance and financial inclusion to boost green growth and alleviate CO2 emissions.