The community and home-based elderly care service system has been proved an effective pattern to mitigate the elderly care dilemma under the background of accelerating aging in China. In particular, the participation of social organizations in community and home-based elderly care service has powerfully fueled the multi-supply of elderly care. As the industry of the elderly care service is in the ascendant, the management lags behind, resulting in the waste of significant social resources. Therefore, performance evaluation is proposed to resolve this problem. However, a systematic framework for evaluating performance of community and home-based elderly care service centers (CECSCs) is absent. To overcome this limitation, the SBM-DEA model is introduced in this paper to evaluate the performance of CECSCs. 186 social organizations in Nanjing were employed as an empirical study to develop the systematic framework for performance evaluation. Through holistic analysis of previous studies and interviews with experts, a systematic framework with 33 indicators of six dimensions (i.e., financial management, hardware facilities, team building, service management, service object and organization construction) was developed. Then, Sensitivity Analysis is used to screen the direction of performance optimization and specific suggestions were put forward for government, industrial associations and CECSCs to implement. The empirical study shows the proposed framework using SBM-DEA and sensitivity analysis is viable for conducting performance evaluation and improvement of CECSCs, which is conducive to the sustainable development of CECSCs.

Economic efficiency is the key issue of sustainable development in urban agglomerations. To date, more attention has been paid to the estimates of productivity gains from urban agglomerations. Differing from the previous studies, this paper focuses on the influencing factors and mechanisms of the economic efficiency of urban agglomerations, and check the effects of three different externalities (industrial specialization, industrial diversity and industrial competition) on the economic efficiency of urban agglomerations. The selected samples are multiple urban agglomerations, and the economic efficiency of urban agglomerations includes single factor productivity and total factor productivity. China’s top 10 urban agglomerations are selected as the case study and their differences in economic efficiency are portrayed comparatively. Firstly, a theoretical analysis framework for three different externalities effect mechanisms on the economic efficiency of urban agglomerations is incorporated. Secondly, economic efficiency measurement index system composes of labor productivity, capital productivity, land productivity and total factor productivity, and the impact of various factors on the economic efficiency of urban agglomerations is tested. The results confirm some phenomena (MAR externality, Jacobs externality and Porter externality) discussed or mentioned in the literature and some new findings regarding the urban agglomerations, derive policy implications for improving economic efficiency and enhancing the sustainability of urban agglomerations, and suggest some potentials for improving the limitations of the research.

The innovation activities of new generation of employees have the characteristics of double network embeddedness, and the degree of psychological contract fulfilment is an important factor that affects their innovation performance. Based on the attributes of internal network embeddedness and external network embeddedness, this paper builds a hypothesis model of the relationship between network embeddedness, psychological contract and innovation performance. It explores the impact and mechanism of network embeddedness on the innovation performance of new generation of employees and the mediating role of the psychological contract. Empirical research shows that network embeddedness has a positive effect on the innovation performance of new generation of employees. The psychological contract has a mediating role in network embeddedness on innovation performance of new generation of employees. These conclusions continue and deepen the research on network embeddedness and innovation performance and further enrich and expand the application of social networks in the research of individual innovation performance of new generation of employees.

Policy uncertainties have always played a critical role in shaping economic outcomes, as evidenced by the recent sluggish economic growth in many countries. Green economic efficiency (GEE) is a comprehensive index to measure economic, social, and environmental development. This paper uses the slack-based measurement (SBM) directional distance function and Luenberger productivity indicator to measure the static GEE and dynamic green total factor productivity (GTFP) of China's urban agglomerations from 2003 to 2020 under constraints of resources and environment. In order to clarify the driving mechanisms of GEE and GTFP, this paper adds the factor of economic policy uncertainty (EPU). The results show that there is a positive correlation between EPU with GEE and GTFP. The possible reason is that the market mechanism plays a decisive role in improved GEE and GTFP. Therefore, policymakers should give better play to the government's macro-control role, and play the decisive role of the market mechanism in the environmental governance system to improve GEE and GTFP in a targeted manner.

Environmental productivity comprehensively measures economic growth and environmental quality. Environmental innovation is considered to be the key to solving economic and environmental problems. Therefore, discussing the impact of environmental innovation on environmental productivity will reveal its economic and environmental effects. This paper measures environmental productivity by value added per unit of pollution emissions (four types of emissions are used) using panel data of 10 Chinese urban agglomerations from 2003 to 2016 to analyze the spatial correlation of environmental productivity, and constructs a spatial panel data model to empirically test the impact of environmental innovation on environmental productivity. It was found that environmental productivity measured by value added per unit of carbon dioxide emissions (gross domestic product (GDP)/CO2) had a significant positive spatial spillover effect, and measured by value added per unit of sulfur dioxide emissions (GDP/SO2), smoke (dust) emissions (GDP/SDE), and industrial sewage emissions (GDP/IS) had a significant negative spatial spillover effect. Environmental innovation has a significant negative inhibitory effect on environmental productivity measured by GDP/SDE and GDP/IS, but no obvious effect measured by GDP/CO2 and GDP/SO2. Control variables such as economic development level, industrial agglomeration, foreign direct investment, and endowment structure factor also show significant differences in environmental productivity measured by value added per unit of pollution emissions. In addition, there are significant differences in direct effects of explanatory variables on environmental productivity of local regions and indirect effects on neighboring regions. These differences are also related to the types of pollution emissions. Therefore, policymakers should set different policies for different types of pollution and encourage different types of environmental innovation, so as to achieve reduced pollution emissions and improved environmental productivity.