Focusing events critically influence governmental policy agendas by catalyzing response-oriented agenda setting, a key instrument for addressing emergent public issues. Although their role is acknowledged, the mechanisms that trigger such agenda setting remain underexplored, particularly in non-Western contexts. In this study, we systematically analyzed 40 Chinese focusing events (2018-2023) using the multiple streams framework and qualitative comparative analysis to identify causal pathways that activate response-oriented agenda setting. Our findings reveal four distinct models-clear-pointing, problem-driven, high-level-driven, and composite-demonstrating that agenda setting arises from the convergence of the problem, policy, and political streams, adapted to China's political ecosystem. These insights refine the multiple streams framework and offer evidence-based guidance for policymakers managing focusing events. This study advances the understanding of agenda setting dynamics in non-Western contexts, highlighting the interplay among societal pressures, the exercise of power, and policy communities in shaping governmental responsiveness.
Public data resources may represent a new driver of agricultural transformation. Using county-level panel data from China covering the period 2010-2020, this paper treats the launch of government open-data platforms as an exogenous shock to evaluate the effects of data openness on agricultural production. The results reveal a nuanced pattern in which open public data reduce agricultural output while increasing productivity. The decline in output mainly reflects reductions in labor, land, and fertilizer use, whereas productivity gains have not yet fully compensated for these declines, highlighting transitional frictions in the shift from extensive to intensive production. Over time, however, the negative effect on output gradually weakens, suggesting that productivity improvements increasingly emerge as the sector adapts to modernization. Mechanism analysis further indicates that data openness affects agricultural enterprises through both extensive and intensive margins. On the extensive margin, data openness accelerates the exit of inefficient and noncompliant firms, thereby reducing the number of active enterprises and lowering input use. On the intensive margin, data openness improves agricultural total factor productivity by reducing the prevalence of zombie firms, increasing the scale and efficiency of new entrants, and strengthening the innovation capacity and industry-university-research collaboration of existing enterprises.
Online charitable donation has become a focus of modern philanthropy, yet the mechanisms underlying stable participation remain insufficiently understood. This gap highlights limitations in existing research, which typically investigates influencing factors in isolation through linear explanatory frameworks. To address this, this study employs agent-based modeling (ABM) to explore how varying intensities and combinations of four widely recognized mechanisms-algorithmic recommendation, information transparency, instant feedback, and social recognition-influence online donation behavior. A NetLogo-based simulation involving 500 heterogeneous agents was conducted across 81 mechanism combinations, with 30 repeated runs for each combination to ensure robustness. Results reveal that: (1) donation emerges only when multiple mechanisms operate in combination; (2) high-intensity triadic combinations form the minimum emergent unit; (3) donation engagement becomes more stable when more mechanisms operate jointly as configurations. These findings contribute to the literature in three ways: (1) theoretically, by extending Bekkers and Wiepking's mechanism framework through the lens of configurational interdependence; (2) methodologically, by applying the ABM approach to online philanthropy; and (3) practically, by providing insights for the design of complementary platform mechanisms that foster sustained donor participation.
The existing literature on volunteering largely focuses on volunteers' characteristics and motivations, with comparatively less attention to how volunteers are managed. Moreover, much of the research on volunteer management relies on frameworks drawn from Human Resource Management (HRM). This article presents findings from a scoping review of key volunteer management literature, supplemented by a critical thematic analysis, to advance understanding of this domain. We first argue that volunteers and paid employees are motivated by fundamentally different factors, requiring distinct management approaches. We then show how these differences complicate the direct application of traditional HRM practices to volunteer management. Next, we identify non-HRM volunteer management practices widely supported in the literature, followed by a discussion of underutilized HRM practices that could strengthen management in nonprofit organizations (NPOs). Finally, we propose context-sensitive recommendations that emphasize tailored, person-centered, and empowering strategies, moving beyond conventional HRM paradigms to better align with volunteers' unique characteristics and motivations.
Public value embodies citizens' expectations and preferences for government, representing the optimal manifestation of people-centered governance. However, most research has primarily analyzed PV's conceptualization and structure from a governmental perspective, paying insufficient attention to citizens' perceived public value (PPV). To address this gap, this study constructs a citizen-centric 'pyramid model' of PPV. Drawing on existing domestic and international micro- and macro-level structural models of PV, the model is developed and rigorously validated using established psychological scale development techniques. All indicators meet model construction criteria, and the proposed three-tiered PPV model (comprising micro, meso, and macro levels) demonstrates excellent fit. This pyramid model provides a foundational framework for understanding PV structure from citizens' perspectives, thereby advancing both PV theory and its practical application.
The government environmental information disclosure (GEID) is a policy innovation designed to enhance transparency and public participation in environmental governance. Previous studies have focused on its positive effects on environmental governance but have overlooked the analysis of factors influencing the implementation of GEID. GEID is a form of digital public service within the context of bureaucracy and public participation. Drawing upon institutional theory and the resource-based view, this paper examines the configurational pathways that drive the implementation of GEID, with a particular emphasis on the dimensions of institutional pressures and government resources. We employed multi-period Qualitative Comparative Analysis (QCA) to explore the evolution in configurational pathways, particularly the impacts of the Central Inspection of Environmental Protection (CIEP) in China. In the early period, the GEID was primarily driven by institutional pressures, while after the implementation of CIEP, it relied on a combination of institutional pressures and government resources. Financial resources and intergovernmental mimetics had a significant impact, particularly regarding the sustainability of fiscal supply during policy implementation. In the later period, normative pressure and the government's human resources became increasingly important. This underscores the importance of public participation and the professionalization of civil servants in digital environmental governance.
Governments have long turned to volunteers to help provide public services. From volunteers on citizen advisory boards to park clean-ups to restocking books in libraries, government agencies rely on volunteers to provide insights and service. At a time when the government workforce is being shrunk in the United States and there is increased pressure on governments to do more with less across the world, the study of how volunteers are used in government is more important than ever. As such, we review the research on government volunteering across levels of government at the federal, state, and local levels, with an emphasis on what we know about the composition of government volunteers and how they are managed. The public sector is distinct from other volunteering contexts and faces different trends, challenges, and accountabilities that should be considered in tailoring volunteer management practices. We identify avenues for future research and highlight implications for practice. We call for governments to use strategic volunteer management tailored to the government context and centering government volunteers to provide them with meaningful experiences that foster retention.
Target setting functions as a starting point and a pivotal mechanism in government performance management, particularly within China's institutional framework of 'target-driven governance.' Scholars have examined the positive effects and potential risks of target setting; however, exploration of its coordinating role remains limited. This study focuses on the Environmental Kuznets Curve (EKC) phenomenon in China, investigating how governmental target setting shapes this curve and exploring the underlying coordinating mechanisms behind such target setting practices, using Chinese provincial panel data. Results indicate that environmental target setting has shaped EKC in China's provincial areas, thereby demonstrating the coordinating role inherent in target setting practices. Heterogeneity analysis shows that environmental target setting strongly coordinates the environment and economy in developing regions, whereas nonregulatory factors dominate inverse U-curve turning points in developed areas. This demonstrates that the coordinating role of target setting is conditionally transformative. This study addresses the research gap in the role of target setting mechanisms within coordinated governance frameworks using China's environmental governance practices as an analytical entry point. These empirical findings strengthen institutional frameworks for green development and outline a practical pathway for aligning target setting strategies with the Sustainable Development Goals.
Voice behavior-civil servants' speaking up with ideas, concerns, and suggestions-is pivotal for public organizations' adaptive capacity and service performance during crises, strengthening organizational learning and responsive policy implementation under uncertainty, yet the mechanisms enabling civil servants to voice under extreme demands remain underexplored. Drawing on Job Demands-Resources theory, this study examined how social support fostered Chinese civil servants' voice behavior during the pandemic through public service motivation (PSM) and how work stress shaped this effect. Survey data collected from Shandong were analyzed through structural equation modeling, Bootstrap tests and Sobel tests. Findings indicate that social support exerts a positive influence on voice behavior and increases voice by strengthening PSM. Work stress weakens the conversion of PSM into voice, while additional analyses indicate that moderate stress can activate motivated speaking up, whereas high stress suppresses it. The study also detects spatial heterogeneity between urban districts and rural counties, suggesting that administrative context conditions the effectiveness of supportive ties. This research contributes to clarify the motivational channel through which social support ties correspond to voice behavior among local civil servants, and highlight actionable levers for public managers-strengthening relational and organizational support while monitoring stress-to sustain constructive input and organizational resilience.
This study examines how state policies shape rural entrepreneurship in China, focusing on their interaction with informal institutions such as kinship networks. Grounded in governance literature, we empirically examine the interaction between state-led initiatives (i.e. rural welfare systems, transport infrastructure, higher education expansion, and rural financial institutions) and local, informal institutions (specifically, kinship networks) regarding entrepreneurial activities in rural South China. Our results using field data from 83 villages across 11 Chinese provinces reveal that welfare systems and transport infrastructure negatively moderate the influence of informal institutions on entrepreneurial activities, while the effects of state-led rural financial institutions and higher education are insignificant. This study contradicts previous rural governance theories by highlighting tensions between formal policy initiatives and informal institutions, offering empirical insights into local governance transitions. The findings contribute to public administration by revealing how state policies can simultaneously enable and constrain rural entrepreneurship, informing adaptive governance strategies. The results underscore the connection between effective governance and contextual fit and details institutional fit dynamics that should inform future research on rural development.
This study proposes a domain-aligned framework for computational social science. It leverages Large Language Models (LLMs) to simulate social perception by grounding analysis in China's Common Prosperity agenda. A dual-track design is adopted, combining expert-led qualitative interviews with structured questionnaires. This process yields a corpus enriched with attitude labels and expert reasoning chains. These annotations enhance interpretability and subgroup fidelity, enabling both micro-level inference and macro-level distribution modeling. Several base LLMs are fine-tuned on this corpus and evaluated under a unified six-task pipeline. This pipeline covers social background and interview dialogue simulation, as well as the simulation of attitudes and survey answers at both individual and group levels. Across all tasks, the domain-aligned models are found to consistently outperform state-of-the-art general-purpose LLMs. These models excel in preserving heterogeneity, recovering latent signals in minority groups, and reproducing empirical distributions with low Wasserstein distance. These results demonstrate that LLMs trained on small but semantically rich corpora, are effective instruments for perception modeling and population-level inference, highlighting the potential for future research to deepen domain alignment and integrate LLM-based simulations more systematically with empirical social data.
Scholars widely regard digital governance as a path to good governance in China. However, the perception gap between political elites and mass in China has not yet been systematically explored. Based on a large-scale online national survey (N = 3,822), this study divides perceptions of digital governance into preference and satisfaction and applies an individual-contextual model to explain the perception gap. The findings reveal that there is consensus between political elites and mass in their preferences, but a significant divide exists in their satisfaction, with elites reporting higher satisfaction. Individual factors significantly shape both preference and satisfaction. There are heterogeneous effects in key individual factors and contextual factors. Low-income political elites report the highest level of satisfaction with digital governance among other subgroups. In cities where the digital governance system is more well-developed, the satisfaction gap is the narrowest, because elite satisfaction decreases more sharply during the process of constructing the digital governance system. By contrast, in cities with higher-quality digital governance services, the satisfaction gap widens-driven by the faster increase in elite satisfaction. These findings provide new insights into the perception gap between elites and mass, with important implications for the legitimacy of digital governance in China.
Public Data Openness (PDO) is a pivotal governance initiative, but its effect on a city's ability to withstand crises remains a key concern. This study addresses this question by examining the impact of PDO on Urban Resilience (UR). Using urban panel data and enterprise registration information from China, we construct a multi-period Difference-in-Differences (DID) model that leverages the PDO policy as a quasi-natural experiment. Our findings demonstrate that PDO significantly enhances UR, an effect particularly pronounced in coastal, central, and non-resource-based cities. The mechanism analysis reveals that PDO strengthens UR by fostering technological innovation and entrepreneurial dynamism. We also identify a positive spatial spillover effect, with the benefits of PDO extending to neighboring regions. This research contributes to the literature by providing robust causal evidence on how data-driven governance enhances UR and revealing the specific mechanisms and spatial dynamics at play.
Prior research has pointed to the interaction effect between formal and informal institutions in public goods provision, but the mechanism remains under-investigated. This paper contributes to the research agenda by analyzing both field observations and panel surveys collected in rural China. Employing a mixed-method approach with qualitative analyses and a comparative study, this paper finds synergic interactions between resources invested from formal institutions and local lineage groups in uni-surname villages, leading to successful public goods provision. Conversely, in multi-surname villages characterized by subnetworks and factions, governance from formal institutions does not resonate with informal institutions, and thus public goods provision fails. Results underscore that governance from formal institutions alone is insufficient for the provision of public goods in rural China. The internal synergy of informal institutions is equally pivotal for community well-being. These findings advance our understanding of the interplay among government investment, local network structures, and public goods provision in rural settings.
This paper examines the impact of official turnover on land allocation to pollution-intensive industries using panel data from 282 prefecture-level cities and above in China between 2007 and 2020. The findings indicate that official turnover increases the proportion of land allocated to pollution-intensive industries by 1.7 percentage points, an effect that remains robust across a series of sensitivity checks. Further analysis reveals that pressure to promote economic growth amplifies this effect, whereas pressures related to environmental protection and fiscal constraints mitigate the effect. Additionally, the positive impact of official turnover on land allocation is observed only in the year of turnover and the subsequent year, suggesting that the effect is driven primarily by the behavior of successor officials. These results underscore the importance of institutional constraints on successor governance during periods of political transition.
