治理效能视角下公民参与公共服务的制度研究

公民参与公共服务的有序性和有效性并非直接相关,可以从有序性和有效性两个维度分析公民参与及其治理效能的关系.为提升治理效能,以程序性规则为核心的制度设计能更为充分地保障公民有序有效参与公共服务,实现公民与政府之间的良性互动与有序合作.基于全过程民主、程序性权利和共同体秩序等公民参与的程序性价值维度考量,再以环境保护领域中的公民参与为例,从公开公示机制、意见表达机制、回应吸纳机制、监督评价机制和责任追究机制等方面构建公民全过程参与制度,并探索公民参与的方法和策略.通过公民参与的程序性价值内化、方法创新与技术转型来推进治理体系和治理能力现代化.     

基于最新统计分类标准的数字经济发展水平测度

随着信息技术的发展,数字经济已经成为经济增长的"新引擎"。但由于缺乏权威的产业统计分类标准,学者们一直面临"数字经济研究缺乏数字依据"的尴尬境地。文章基于国家统计局公布并实施的《数字经济及其核心产业统计分类(2021)》中的分类标准,对各省份统计年鉴的数据进行重新整理,利用熵权法构建数字经济发展指数,测度了我国30个省份的数字经济发展水平,分析了各省份数字经济发展的差异以及时空特征。研究发现,2009—2019年我国数字经济产业发展迅猛,各项子产业都取得了长足的进步。相比较而言,数字要素驱动业发展速度略低于其他三个子产业;数字经济发展存在着明显的区域不平衡。东中部地区的数字经济发展状况明显优于西部地区,南方优于北方,而且区域不平衡有持续扩大趋势。     

Transformer in navigation: Diverse government roles for open innovation in China's high-speed rail

Based on a longitudinal case study of China's high-speed rail embedded in the emerging economy context, we focus on what role the government plays and how that matters to open innovation (OI) for competitive advantage. By linking the OI literature with the national political institutions literature to motivate our research question, we propose a statist-based OI view to differentiate diverse government roles, investigating how government adopts roles in a combined way to push OI in stages. Our findings suggest that government is an important strategic decision-maker for OI. Specifically, the government plays various roles as commander, protector, cultivator, and intermediator, reflecting state activism derived from national political institutions, to construct institutional-level OI for domestic OI activities, and inbound and outbound OI across national borders. We find government can deliberately and strategically use its diverse roles in a combined way to push OI for competitive advantage through the industrial evolutionary process over time. Our study contributes to the OI literature and integrates the strategic management literature with the study of OI to provide new insights to explain the origins of competitive advantage from the state perspective.     

Estimation of geodesic tortuosity and constrictivity in stationary random closed sets

We investigate the problem of estimating geodesic tortuosity and constrictivity as two structural characteristics of stationary random closed sets. They are of central importance for the analysis of effective transport properties in porous or composite materials. Loosely speaking, geodesic tortuosity measures the windedness of paths, whereas the notion of constrictivity captures the appearance of bottlenecks resulting from narrow passages within a given materials phase. We first provide mathematically precise definitions of these quantities and introduce appropriate estimators. Then, we show strong consistency of these estimators for unboundedly growing sampling windows. In order to apply our estimators to real data sets, the extent of edge effects needs to be controlled. This is illustrated using a model for a multiphase material that is incorporated in solid oxide fuel cells.     

Effects of mediator competence and mediation process on user satisfaction with child custody,finances, and property outcomes

This study draws on survey data from 205 family mediation service users concerning their satisfaction with the outcomes of mediation to address two research questions: (a) how satisfied are service users? and (b) what factors account for users' satisfaction with the outcome of child custody arrangements and the allocation of finances and property? Overall, users' level of satisfaction with outcomes was high. While the mediation process explained a significant variance in satisfaction with the outcomes for child custody and for finances and property, the mediator's perceived professional competence did not predict user satisfaction with the outcomes for either issue. This study contributes to our knowledge on the significance of mediators' process skill, specifically their calm and clear responses to the socioemotional needs of the mediated parties, on the service outcomes for both types of dispute. The implications for mediation training are discussed.     

Bayesian inference for stable Lévy–driven stochastic differential equations with high‐frequency data

In this paper, we consider parametric Bayesian inference for stochastic differential equations driven by a pure‐jump stable Lévy process, which is observed at high frequency. In most cases of practical interest, the likelihood function is not available; hence, we use a quasi‐likelihood and place an associated prior on the unknown parameters. It is shown under regularity conditions that there is a Bernstein–von Mises theorem associated to the posterior. We then develop a Markov chain Monte Carlo algorithm for Bayesian inference, and assisted with theoretical results, we show how to scale Metropolis–Hastings proposals when the frequency of the data grows, in order to prevent the acceptance ratio from going to zero in the large data limit. Our algorithm is presented on numerical examples that help verify our theoretical findings.     

An additive–multiplicative mean model for panel count data with dependent observation and dropout processes

This paper discusses regression analysis of panel count data with dependent observation and dropout processes. For the problem, a general mean model is presented that can allow both additive and multiplicative effects of covariates on the underlying point process. In addition, the proportional rates model and the accelerated failure time model are employed to describe possible covariate effects on the observation process and the dropout or follow‐up process, respectively. For estimation of regression parameters, some estimating equation‐based procedures are developed and the asymptotic properties of the proposed estimators are established. In addition, a resampling approach is proposed for estimating a covariance matrix of the proposed estimator and a model checking procedure is also provided. Results from an extensive simulation study indicate that the proposed methodology works well for practical situations, and it is applied to a motivating set of real data.