基于AHP与DEA方法的创新效率研究

企业的技术创新能力是现代经济社会进步与发展的重要标志。在企业创新效率评价中,数据包络分析法(DEA)具有无需对输入和输出指标的计量单位或量纲进行统一,也不需要事先确定属性之间的相对权重等优势,已经被大量应用于创新效率的评价。但DEA方法只凭借客观数据,并未考虑决策的主观因素,在传统应用时有所限制。为了解决DEA方法在实际应用中的局限,使效率评价更加贴合实际要求,本文将AHP和DEA相结合,以重庆市八类企业为研究对象,通过首先引入AHP方法对相关指标进行筛选,确立符合地区现状的评价体系,再利用DEA评价其创新能力的技术效率、纯技术效率、规模效率情况,最后为当地政府的相关政策制定提供建议。     

电力生产、跨省交易与能源环境效率

将电力生产作为先行于其他社会生产的生产环节,在考虑规模越来越大的电力跨省交易和非期望产出(二氧化碳排放、工业废气总排放量、工业废水总排放量等)的基础上,使用非参数网络数据包络分析模型测算了2000—2012年中国省域能源环境效率。结果表明:与考虑电力生产和跨省交易的网络DEA模型相比,利用传统DEA方法会高估电力输入省的能源环境效率、低估电力输出省的能源环境效率。指出调整电力生产布局和跨省输送网络可以有效提高地区的能源环境效率。     

基于DEA-Tobit模型的马铃薯生产效率分析——以甘肃省定西市为例

随着社会的进步和农村经济的发展,农业生产效率已成为制约农民收入、造成农村落后的关键因素。中国是马铃薯的生产大国,其生产效率的提高对我国马铃薯产业的持续发展和保障我国的粮食安全有着很重要的意义。研究基于2014年对甘肃省定西市样本农户马铃薯种植的调查数据,采用DEA模型测算农户种植马铃薯的生产效率,并利用Tobit模型对影响马铃薯生产效率的因素进行分析。研究表明:农户生产马铃薯的综合技术效率较低,规模效率成为制约其生产效率提升的瓶颈;家庭纯收入、马铃薯的种植比例和引进新品种3个变量在0.01水平下对生产效率的影响达到显著;户主的年纪在0.05水平下对生产效率的影响达到显著;马铃薯的收购价格、农户是否参加合作社和种植培训、离农贸市场距离与马铃薯的生产效率间存在不显著的正相关关系。基于以上调研提出了鼓励土地流转、提高生产技术水平、加大农民生产技能培训力度、多方面增加农民收入和合理布局农产品贸易市场等政策性建议。     

Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm

In this paper, we propose a method for improving the accuracy of the estimation of interregional input–output tables, by combining the RAS method and the real-coded Genetic Algorithm (GA); these are simple representative methods for the estimation of an interregional input–output table. By comparing the performance evaluation results obtained using the proposed method, the RAS method, and Simulated Annealing, we verified that the combination of the genetic algorithm and the RAS method can enhance the estimation accuracy of an interregional input–output table. In addition, performance is further enhanced by adjusting GA parameters.     

Structural change and blurred sectoral boundaries: assessing the extent to which knowledge-intensive business services satisfy manufacturing final demand in Western countries

This paper focuses on the vertical integration of knowledge-intensive business services (KIBS) into manufacturing sectors, using a subsystem approach to input–output analysis. It aims at correctly assessing the process of structural change that has occurred in the four main European countries (France, Germany, Italy and the UK) over time (1995–2005). It does not focus on KIBS sectors per se, but on their function as carriers and sources of knowledge which influences the performance of sectors, value chains and clusters across industries and within countries. The analysis shows that KIBS’ contribution to satisfying the final demand of manufacturing is in general largely underestimated; that KIBS vertical integration into manufacturing has increased over time in all the countries investigated except the UK; and that the extent to which manufacturing sectors outsource to KIBS is significantly affected by their technological intensity.     

Dynamic DEA models with network structure: An application for Iranian airlines

Efficiency estimation of interdependent divisions within a company or assessing the interrelated processes in a production system provides insights for improving the operational performance. Recent developments in network data envelopment analysis (NDEA) models enable decision making units (DMUs) to be informed of inefficient processes within the system. The NDEA model assesses the processes of the system in a specific moment and ignores the dynamic effects within the production processes. Thus, without considering the temporal dimension of production processes, biased efficiency measurement will be obtained that provides misleading information to DMUs. For evaluating the performance of a DMU with interrelated processes during specified multiple periods, this paper proposes a relational dynamic NDEA (DNDEA) model which measures the efficiencies of the system and its internal processes over the time, simultaneously. To illustrate the capability of the proposed model, this study for the first time measures the efficiency of eight Iranian airlines in several periods connected to each other by carry over flows. The actual data is gathered in three periods from 2010 to 2012 and the results are compared with the dynamic DEA and network DEA models in the same time span.     

Efficiency and productivity changes in Greek airports during the crisis years 2010–2014

The aim of this study is to evaluate the operating efficiency and productivity changes of the Greek airports, during the first years of the severe economic crisis in Greece (2010–2014), by using two methods: Data Envelopment Analysis (DEA) and Malmquist Productivity index (MPI). Findings have shown that, despite the dramatic effects of the economic crisis on the socio-economic life of the country, overall airport efficiency and productivity improved, mainly due to exogenous factors such as international tourism growth. The MPI reveals that over the period of the study, airports have experienced an annual average increase in total factor productivity (TFP) of 0.9% (an increase of 3.6% over the examined period). On examining the components of this productivity change, it becomes evident that this is due to the combination of both positive (a slight progress) annual average technology change (0.5%) and technical efficiency change (0.4%). The results also indicate that 65.8% of airports have an increase in average TFP during the period 2010–2014, ranging between 0.4% and 20%. However, as Greek airports operate at poor levels of efficiency, there is still considerable space for improvements in most of the airports.     

The relevance of commuting zones for regional spending efficiency

We use data envelopment analysis (DEA) efficiency scores to show that clustering municipalities into encompassing regional clusters improves spending efficiency of single stand-alone municipalities. We propose a new geographic aggregation based on municipalities-to-municipalities commuting flows, defined using hierarchical cluster analysis. Our example for Portugal shows that from an output-oriented perspective between 83% and 98% of municipalities would increase their efficiency scores, while from an input-oriented perspective between 86% and 98% of municipalities would also be better off in terms of efficiency. Then using a linear regression model, we find that population increases positively affects the efficient scores (via scale economies). Also, increases in the share of high-educated and poorer residents leads to higher efficiency scores.     

基于DEA模型的山东省农地利用经济效益分析

山东省农地面积较广,利用类型丰富,农地的合理利用对推进山东省农业经济发展及土地资源的可持续发展具有重要意义。文章阐述了山东省农地利用状况,从自然因素、土地投入、农业土地利用结构、农业从业人员素质、农产品市场意识及经营手段等方面探讨影响农地利用经济效益的因素,通过构建DEA模型,对农地利用经济效益进行应用分析,并提出加大农业用地投入和建设、优化农业用地结构和规模、强化市场经营意识和管理等提高山东省农地利用经济效益的对策建议,以期为山东省土地合理规划利用提供理论依据。     

基于因子分析和DEA模型的现代光伏农业技术经济性综合评价研究

发展现代光伏农业是推进现代农业可持续发展的重要途径，对现代光伏农业进行技术经济性综合评价有较强的现实意义，为此，建立了因子分析法和DEA相结合的现代光伏农业技术经济性综合评价模型。首先，利用因子分析法对评价指标进行了降维处理；然后，根据DEA模型需要对指标数据进行了标准化处理；最后，利用DEA模型完成了对50亩智能农业大棚各经营方案的评价，结果表明：将光伏发电和温室大棚种植相结合具有良好的技术经济效益。