区域知识产权保护发展的空间格局及结构体系研究

以我国各省知识产权保护制度为研究对象，创新性地将探索性空间数据分析方法与社会网络分析方法相结合，基于地理邻近视角，验证了区域知识产权保护的空间相关性、空间集聚特征和空间溢出效应。同时，突破地理近邻效应的局限，解析区域知识产权保护的空间关联特征。结果表明：我国各省知识产权保护具有全局自相关性，相似地区间存在空间集聚效应，不同发展程度地区的空间关联性质不同；网络化后的区域知识产权保护各节点间联系紧密、网络结构稳定，并且可以确定核心行动者和边缘行动者角色；长三角、珠三角、环渤海等较发达地区与其它地区之间存在较多溢出关系。     

大数据能力对企业创新绩效的影响——IT-业务融合与双元环境的调节作用

基于动态能力理论和权变理论，以IT-业务融合、双元环境为调节变量，探究大数据能力与企业创新绩效间的作用关系，结果发现：大数据能力对创新绩效具有正向促进作用；IT-业务融合调节大数据能力与创新绩效的关系，IT-业务融合水平越高，大数据能力对创新绩效的正向影响就越显著；双元环境能够调节大数据能力与创新绩效间关系。其中，环境动态性在大数据能力与创新绩效关系间起正U型调节作用，而环境竞争性在大数据能力与创新绩效关系间起倒U型调节作用。从内外部情境视角解释大数据能力的创新转化，对中国企业大数据应用具有指导意义。     

Cluster Analysis for mixed data: An application to credit risk evaluation

Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative indicators. This paper highlights the relevance of both quantitative and qualitative features of applicants and proposes a new methodology based on mixed data clustering techniques. Indeed, cluster analysis may prove particularly useful in the estimation of credit risk. Traditionally, clustering concentrates only on quantitative or qualitative data at a time; however, since credit applicants are characterized by mixed personal features, a cluster analysis specific for mixed data can lead to discover particularly informative patterns, estimating the risk associated with credit granting.     

The Impact of Public Expenditure and International Trade on Agricultural Productivity in China

The “industry nurturing agriculture” reforms and World Trade Organization accession led to dramatic growth in public expenditure and international trade in China’s agricultural sector. This article aims to estimate the effects of public expenditure and trade on agricultural productivity in China for 2004–2015. A semi-parametric production function with shape constraints is introduced to derive more accurate productivity before the productivity determinants are analyzed with an emphasis on public expenditure and trade. The empirical result shows that public expenditure and exports can effectively improve agricultural productivity, while imports have no significant effects. Policy implications are discussed in the context of supply-side reforms.     

Economic interpretations of DEA

Research on productive efficiency at the firm level has developed as an important and active strand of research the last decades, both within operations research, management science and economics. Two apparently different definitions of efficiency are examined, but it is shown that when both estimation methods are based on solving linear programming problems the definitions of efficiency are identical. The purpose of the paper is to give the basic ideas of efficiency analyses using DEA as a tool for researchers not so familiar with efficiency analysis and DEA. The concept of shadow prices is given special attention.     

Labor market analysis through transformations and robust multivariate models

The work presents a robust approach to labor share analysis. The estimate of labor share presents various complexities related to the nature of the data sets to be analyzed. Typically, labor share is evaluated by using discriminant analysis and linear or generalized linear models, that do not take into account the presence of possible outliers. Moreover, the variables to be considered are often characterized by a high dimensional structure. The proposed approach has the objective of improving the estimation of the model using robust multivariate regression techniques and data transformation.     

Methodological Advances in DEA: A survey and an application for the Dutch electricity sector

We survey the methodological advances in DEA over the last 25 years and discuss the necessary conditions for a sound empirical application. We hope this survey will contribute to the further dissemination of DEA, the knowledge of its relative strengths and weaknesses, and the tools currently available for exploiting its full potential. Our main points are illustrated by the case of the DEA study used by the regulatory office of the Dutch electricity sector (Dienst Toezicht Elektriciteitswet; Dte) for setting price caps.     

The Performance of Service Industries in Canada: A Real Value Analysis

The performance of service industries in Canada has been lower than that of good industries over the last four decades, with noticeable exceptions such as for railways and telecommunication carriers. Service industries were less economically (and technically) efficient in that they generated less output value (quantity) per hour worked (level and growth) or per combined unit of labour and capital (multifactor productivity growth) than good industries. The relative output price of services declined slightly over time compared with goods. At the disaggregated level, changing relative output prices were substantial and proved to be an important factor explaining the relative satisfactory economic performance of many service industries despite their low technical performance. Nevertheless, the output share of service industries increased over that period, sustained, mainly, by the growing recourse of all firms to outsourcing of services.     

Identifying “best” applicants in recruiting using data envelopment analysis

Selecting the most promising candidates to fill an open position can be a difficult task when there are many applicants. Each applicant achieves certain performance levels in various categories and the resulting information can be overwhelming. We demonstrate how data envelopment analysis (DEA) can be used as a fair screening and sorting tool to support the candidate selection and decision-making process. Each applicant is viewed as an entity with multiple achievements. Without any a priori preference or information on the multiple achievements, DEA identifies the non-dominated solutions, which, in our case, represent the “best” candidates. A DEA-aided recruiting process was developed that (1) determines the performance levels of the “best” candidates relative to other applicants; (2) evaluates the degree of excellence of “best” candidates’ performance; (3) forms consistent tradeoff information on multiple recruiting criteria among search committee members, and, then, (4) clusters the applicants.