二元学习与创新绩效的作用机制——组织内部协作网络的调节作用

组织学习是驱动企业创新、实现技术追赶与超越追赶的关键因素,如何合理组织企业的利用式和探索式学习是企业构建研发体系的关键问题。学界对二元学习是否有利于企业的创新绩效存在截然不同的观点。同时,组织内部的情境因素是影响组织二元学习和创新绩效关系的最根本因素,组织内部研发协作网络是二元学习的重要载体。基于美国半导体行业企业十年间的专利数据,实证研究发现,不同维度的二元学习对企业创新绩效具有不同的影响,联合二元学习能够积极影响企业的创新绩效,平衡二元学习则会降低企业的创新绩效;内部研发协作网络密度在二元学习和创新绩效的关系中具有显著的调节作用,企业的内部协作网络密度越高,联合二元学习对企业创新绩效的积极影响越弱,平衡二元学习对创新绩效的负影响则加剧。     

国家创新型城市效率评价研究——基于两阶段DEA模型

采用共享投入型两阶段数据包络分析（DEA）模型,并构建多环节的创新型城市评价指标体系,对长三角地区创新型城市的创新效率进行评价。结果表明:在未来国家创新型城市建设过程中,相关城市不仅要考虑科技创新,还应考虑经济效益、社会效益和生态效益;在资金投入方面,需要构建金融创新体系,深化资本市场的建设,提升对创新创业的支持力度,强化科技金融服务能力;在创新型城市的建设过程中,应加快产业结构的调整,鼓励自主创业和创新型中小企业的发展,加快推进城市的生态文明建设。     

中国省域碳排放的空间特征及影响因素

通过核密度分布和莫兰指数对中国2000—2015年30省份碳排放强度的动态趋势及集聚特征进行测度,并利用空间杜宾模型对其主要影响因素进行分析。结果显示:（1）中国30省份碳排放强度呈下降趋势,新常态以来低碳步伐加快;（2）碳排放强度的空间集聚性具有高水平集中、低水平集聚特征,空间溢出效应不断增强;（3）本省经济规模、产业结构对本省碳排放强度具有显著的正向影响,专利产出具有显著的负向影响;相邻省份的外商投资规模及能源消费结构变化对本省碳排放具有显著的空间溢出作用。因此,未来中国加快产业结构调整幅度、优化相邻省份间的产业空间布局以及大力发展绿色技术进步是中国促进区域低碳转型的主要方向,同时生态城镇化以及继续改善外商直接投资质量也是减排潜力因子,省域间的减排空间溢出效果不容忽视。     

Social capital in Croatia: measurement and regional distribution

By using partial least squares path modeling, this paper develops a complex index of social capital, selects Croatia as the case for testing and validating the index, and investigates the regional distribution of social capital. The social capital index is defined as a complex hierarchical structured construct of third-order with social trust, participation, and civism as its core dimensions. The main results indicate that civism is the most important cause of social capital followed by active participation and social trust. As far as the regional distribution of social capital is concerned, there are statistically significant differences across the Croatian regions. Although the lowest or below the national average level of social capital and its dimensions can be mostly found in the least developed regions (with the exception of the capital), the highest level of social capital and its particular dimensions is not achieved in the most developed regions.     

Sensitivity,uncertainty, and decision analyses in the prioritization of research

The evaluation of hazards from complex, large scale, technologically advanced systems often requires the construction of computer implemented mathematical models. These models are used to evaluate the safety of the systems and to evaluate the consequences of modifications to the systems. These evaluations, however, are normally surrounded by significant uncertainties related to the uncertainty inherent in natural phenomena such as the weather and those related to uncertainties in the parameters and models used in the evaluation.

Another use of these models is to evaluate strategies for improving information used in the modeling process itself. While sensitivity analysis is useful in defining variables in the model that are important, uncertainty analysis provides a tool for assessing the importance of uncertainty about these variables. A third complementary technique, is decision analysis. It provides a methodology for explicitly evaluating and ranking potential improvements to the model. Its use in the development of information gathering strategies for a nuclear waste repository are discussed in this paper.     

Inference for quantile measures of kurtosis,peakedness, and tail weight

Insight into measures of peakedness, heavy-tailedness, and kurtosis can be gained by studying Ruppert’s ratios of interquantile ranges. They are not only monotone in Horn’s measure of peakedness when applied to the central portion of the population, but also monotone in the practical tail-index of Morgenthaler and Tukey, when applied to the tails. Non-parametric confidence intervals are found for Ruppert’s ratios, and sample sizes required to obtain such intervals for a pre-specified relative width and level are provided. In addition, the empirical power of distribution-free tests for peakedness and bimodality are found for some symmetric distributions.     

How to Evaluate Government Performance while Building a Rule of Law Government in China*

Building a law-based government is a central element of the comprehensive framework for promoting the rule of law in China, while using evaluation to catalyze growth is in line with the incentive principle of management studies. Since China started to implement reform and opening up over thirty years ago, rule of law development and organizational evaluation have gone through several stages, each with different characteristics. Efforts to build a law-based government have met with success, but what the country now has is essentially still goal-oriented assessment. At present, this suffers from the lack of a clear goal orientation or definition of functions, an imperfect technical system and unsound motivation mechanisms, not to mention the practical problems of each government department going its own way, duplicating evaluations or being left rudderless. Drawing on a combination of value rationality and instrumental rationality and using government performance evaluation to promote the building of a law-based government not only conforms to the spirit of the rule of law and value rationality in government performance, but also strengthens the role of evaluation as an instrument for organizational management. Therefore, we need to create new evaluation theories, expand public participation, introducing diversified evaluating entities, improve technical systems, strengthen institutional buildup, and foster a performance-based culture. In addition, replacing goal-oriented assessment with performance evaluation will help the emergence of a new discipline—the performance evaluation of rule of law government, thus promoting multidisciplinary efforts to integrate and create new public administration theories in China.     

Practical procedures to deal with common support problems in matching estimation

This paper assesses the performance of common estimators adjusting for differences in covariates, such as matching and regression, when faced with the so-called common support problems. It also shows how different procedures suggested in the literature affect the properties of such estimators. Based on an empirical Monte Carlo simulation design, a lack of common support is found to increase the root-mean-squared error of all investigated parametric and semiparametric estimators. Dropping observations that are off support usually improves their performance, although the magnitude of the improvement depends on the particular method used.     

An Extended Single‐index Model with Missing Response at Random

An extended single‐index model is considered when responses are missing at random. A three‐step estimation procedure is developed to define an estimator for the single‐index parameter vector by a joint estimating equation. The proposed estimator is shown to be asymptotically normal. An algorithm for computing this estimator is proposed. This algorithm only involves one‐dimensional nonparametric smoothers, thereby avoiding the data sparsity problem caused by high model dimensionality. Some simulation studies are conducted to investigate the finite sample performances of the proposed estimators.     

Work performance and tax compliance in flat and progressive tax systems

Different tax systems, and their impact on work motivation and tax compliance are significant issues in contemporary political and economic debates. The proportional feature of a flat tax system is assumed to lead to higher performance, while the fairness of the redistributive progressive tax system is assumed to result in higher tax compliance. However, empirical findings on the topic are inconclusive. Both work performance and tax compliance under different tax systems were examined in an experiment, with special attention devoted to the effect of a change in tax systems. A flat tax system was supposed to induce greater work performance, whereas a progressive tax system was expected to increase tax compliance based on fairness perceptions, allowing for the opposite effect due to higher complexity. Furthermore, it was assumed that performance and tax payments would be influenced by motives of self-interest. The design included 20 rounds with a real-effort task in each round, determining participants’ experimental income. Participants (N = 191) made decisions about their tax payments from round-to-round in four different experimental conditions: (1) a flat tax system, (2) a progressive tax system, (3) starting with a flat and changing to a progressive, and (4) starting with a progressive and changing to a flat tax system. Results indicate higher work performance in a progressive system. However, a change from a progressive tax system to a flat system led to increased tax compliance.