In recent years, many areas of China have suffered from serious haze pollution, which greatly affects human health and daily life. It is of policy importance to understand the factors that influence the spatial concentration of PM_2.5. Based on data from 74 cities with PM_2.5 monitoring stations in 2013 and 2014, this study presents the overall haze situation in China and explores the determinants of PM_2.5 using a random-effects model, as well as a set of OLS regressions. The results indicate that PM_2.5 is significantly correlated with the industrial proportion, the number of motor vehicles, and household gas consumption, while public financial expenditure on energy saving and environmental protection does not show statistically significant effects. The analysis implies that China should adjust its economic structure and optimizes environmental governance to effectively respond to haze pollution.

Based on the collaborative governance framework, this paper proposes four starting conditions that affect the establishment of intergovernmental collaboration: power imbalance, resource imbalance, prehistory of collaboration and participation of superior levels of government. The interaction of these conditions is tested with collaborative practice among local governments in China to control air pollution. The qualitative comparative analysis results show that wheel-shaped, umbrella-shaped and fan-shaped modes promote collaboration. Non-participation of superior levels of government and strong–strong competition modes inhibit collaboration. External leadership and internal leadership play important roles in the initiation of interlocal collaboration.

Although performance targets imposed by high levels of governments are an important vertical result-oriented influence on local governments’ policy adoption, no studies have examined the impacts of performance targets on policy processes. Using the adoption of atmospheric pollutant emission standards by Chinese provinces in the 2000 to 2015 period, this study runs spatial autoregression models to investigate the effects of mandatory performance targets on environmental policy adoption processes in China. The results show that top-down performance targets can drive the adoption of atmospheric pollutant emission standards in Chinese provinces. Furthermore, the influence of vertical environmental performance targets on the adoption of local atmospheric pollutant emission standards is stronger in Chinese provinces that have adopted more similar standards in the previous period. The results show that top-down performance management shapes the policy adoption processes and policy adoption of Chinese provinces under vertical result-oriented performance target pressure is path-dependent.

China relies on the total pollutant emission control and environmental target responsibility system to curb environmental pollution and improve energy conversation. How the central government breaks down environmental targets among provincial governments lies at the core, but little research has been done to explore the determinants of environmental target-setting empirically. This work models the decomposition process of environmental targets by focusing on the roles of historical performance and provinces’ political status. With the method of hierarchical linear model, data on five kinds of environmental obligatory targets (energy consumption per unit GDP and other four kinds of pollutants) during China’s “12th Five-year Plan” period is used to test the hypotheses. The results show that provincial historical structural performance is negatively significantly correlated with their environmental target levels, while the effects of historical scale performance and intensity performance are not significant. Besides, provinces with higher political rankings tend to be allocated higher targets, which is in accordance with the model effect hypothesis rather than the bargaining effect hypothesis.

Gaming behaviors are challenges to governments’ performance measurement systems. This paper presents a theory of the ways in which participatory management and goal ambiguity shape gaming behaviors in performance management. Using survey data from China, this study empirically shows that in high-incentive performance measurement systems, township government cadres’ participation in goal-setting has a significant positive effect on their gaming behaviors; cadres’ perceived goal ambiguity has a significant negative effect on their gaming behaviors; and participatory management affects gaming behaviors through goal ambiguity. This study’s findings reveal that in the context of high pressure and intense competition, gaining more useful information from participation in goal-setting and developing a deeper understanding of the evaluative goals requested by superiors may allow township government cadres to identify loopholes in performance measurement systems and seize opportunities for gaming. These findings imply that a comprehensive management strategy should be used to limit gaming behaviors.

In an era of economic globalization and informatization, public institutions worldwide are required to provide higher quality of public service in response to demands from citizens. However, differ...