783 resultados para Data envelopment analysis-DEA


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The efficiency of the construction industry is analyzed based on provinces panel data in China in this paper. The Mean Number of Employee and the Mean Completed Investment are used as inputs. The Mean Actual Sales of Commercial Houses and the Mean Net Profit are used as outputs. Data Envelopment Analysis (DEA) model is used to measure the efficiency of the construction industry. Shanghai and Zhejiang are found technically efficient. Shandong is scale efficient but technology efficiency is lower. There are two provinces are decreasing returns to scale and other provinces are increasing returns to scale. On the whole, the technology efficiency of the construction industry of China is lower. Based on the conclusions, the paper proposes some suggestions to improve the efficiency of the construction industry in China.

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There is much concern about the social and environmental impacts caused by the economic growth of nations. Thus, to evaluate the socio-economic performance of nations, economists have increasingly addressed matters related to social welfare and the environment. It is within the scope of this context that this work discusses the performance of countries in the BRICS group regarding sustainable development. The objective of this study regards evaluating the efficiency of these countries in transforming productive resources and technological innovation into sustainable development. The proposed objective was achieved by using econometric tools as well as the data envelopment analysis method to then create economic, environmental, and social efficiency rankings for the BRICS countries, which enabled to carry out comparative analyses on the sustainable development of those countries. The results of such assessments can be of interest for more specific scientific explorations.

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This paper analyses the relationship between productive efficiency and online-social-networks (OSN) in Spanish telecommunications firms. A data-envelopment-analysis (DEA) is used and several indicators of business ?social Media? activities are incorporated. A super-efficiency analysis and bootstrapping techniques are performed to increase the model?s robustness and accuracy. Then, a logistic regression model is applied to characterise factors and drivers of good performance in OSN. Results reveal the company?s ability to absorb and utilise OSNs as a key factor in improving the productive efficiency. This paper presents a model for assessing the strategic performance of the presence and activity in OSN.

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Data envelopment analysis (DEA) is defined based on observed units and by finding the distance of each unit to the border of estimated production possibility set (PPS). The convexity is one of the underlying assumptions of the PPS. This paper shows some difficulties of using standard DEA models in the presence of input-ratios and/or output-ratios. The paper defines a new convexity assumption when data includes a ratio variable. Then it proposes a series of modified DEA models which are capable to rectify this problem.

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Since the original Data Envelopment Analysis (DEA) study by Charnes et al. [Measuring the efficiency of decision-making units. European Journal of Operational Research 1978;2(6):429–44], there has been rapid and continuous growth in the field. As a result, a considerable amount of published research has appeared, with a significant portion focused on DEA applications of efficiency and productivity in both public and private sector activities. While several bibliographic collections have been reported, a comprehensive listing and analysis of DEA research covering its first 30 years of history is not available. This paper thus presents an extensive, if not nearly complete, listing of DEA research covering theoretical developments as well as “real-world” applications from inception to the year 2007. A listing of the most utilized/relevant journals, a keyword analysis, and selected statistics are presented.

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This paper is drawn from the use of data envelopment analysis (DEA) in helping a Portuguese bank to manage the performance of its branches. The bank wanted to set targets for the branches on such variables as growth in number of clients, growth in funds deposited and so on. Such variables can take positive and negative values but apart from some exceptions, traditional DEA models have hitherto been restricted to non-negative data. We report on the development of a model to handle unrestricted data in a DEA framework and illustrate the use of this model on data from the bank concerned.

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Data Envelopment Analysis (DEA) is a nonparametric method for measuring the efficiency of a set of decision making units such as firms or public sector agencies, first introduced into the operational research and management science literature by Charnes, Cooper, and Rhodes (CCR) [Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444]. The original DEA models were applicable only to technologies characterized by positive inputs/outputs. In subsequent literature there have been various approaches to enable DEA to deal with negative data. In this paper, we propose a semi-oriented radial measure, which permits the presence of variables which can take both negative and positive values. The model is applied to data on a notional effluent processing system to compare the results with those yielded by two alternative methods for dealing with negative data in DEA: The modified slacks-based model suggested by Sharp et al. [Sharp, J.A., Liu, W.B., Meng, W., 2006. A modified slacks-based measure model for data envelopment analysis with ‘natural’ negative outputs and inputs. Journal of Operational Research Society 57 (11) 1–6] and the range directional model developed by Portela et al. [Portela, M.C.A.S., Thanassoulis, E., Simpson, G., 2004. A directional distance approach to deal with negative data in DEA: An application to bank branches. Journal of Operational Research Society 55 (10) 1111–1121]. A further example explores the advantages of using the new model.

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As student numbers in higher education in the UK have expanded during recent years, it has become increasingly important to understand its cost structure. This study applies Data Envelopment Analysis (DEA) to higher education institutions in England to assess their cost structure, efficiency and productivity. The paper complements an earlier study that used parametric methods to analyse the same panel data. Interestingly, DEA provides estimates of subject-specific unit costs that are in the same ballpark as those provided by the parametric methods. The paper then extends the previous analysis and finds that further student number increases of the order of 20–27% are feasible through exploiting operating and scale efficiency gains and also adjusting student mix. Finally the paper uses a Malmquist index approach to assess productivity change in the UK higher education. The results reveal that for a majority of institutions productivity has actually decreased during the study period.

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This paper suggests a data envelopment analysis (DEA) model for selecting the most efficient alternative in advanced manufacturing technology in the presence of both cardinal and ordinal data. The paper explains the problem of using an iterative method for finding the most efficient alternative and proposes a new DEA model without the need of solving a series of LPs. A numerical example illustrates the model, and an application in technology selection with multi-inputs/multi-outputs shows the usefulness of the proposed approach. © 2012 Springer-Verlag London Limited.

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Emrouznejad et al. (2010) proposed a Semi-Oriented Radial Measure (SORM) model for assessing the efficiency of Decision Making Units (DMUs) by Data Envelopment Analysis (DEA) with negative data. This paper provides a necessary and sufficient condition for boundedness of the input and output oriented SORM models.

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介绍了VCSTalk的具体设计和实现架构,并展示了它用于评价若干开源软件项目中的开发人员效率的一个具体实例.

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应用数据包络分析(Data Envelopment Analysis,DEA)模型对我国自然灾害的区域脆弱性水平进行研究,在区域灾害系统理论的组织框架下,从区域自然灾害危险性、区域承灾体暴露性和区域自然灾害损失度三个方面构建了区域自然灾害系统的DEA投入产出模型,并利用模型得出的区域自然灾害成灾效率对区域自然灾害的脆弱性进行模拟反映,对我国自然灾害脆弱性的区域分异特征进行分析。研究发现:我国自然灾害脆弱性的整体水平较高,地域格局为西部>中部>东部,且脆弱性水平与地区经济水平具有明显的负相关关系,经济发达地区的脆弱性相对较低。

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O presente trabalho, além de dar a conhecer o grupo BCP e de caracterizar as minhas atuais funções no seio de uma agência do Millennium bcp, tem como objetivo analisar se a nova abordagem comercial aos clientes, que este banco se encontra a implementar, permite melhorar a eficiência das suas agências. A eficiência é analisada através do estudo da produtividade técnica, com recurso à técnica de programação linear: Data Envelopment Analysis – DEA, na abordagem do modelo BCC, com orientação output. Considerou-se como variáveis input: o número de empregados, os gastos com pessoal e o total dos gastos operacionais, e como variáveis output: o número de contactos telefónicos, o número de transações e o número de vendas. Foram analisadas 109 agências, 9 que já implementaram a nova abordagem comercial e 100 que ainda utilizam a abordagem comercial tradicional. Verificou-se que até ao ano 2011, as agências que implementaram a nova abordagem comercial detinham um nível de eficiência significativamente inferior ao das agências que utilizam a abordagem comercial tradicional. Em 2012, ano em que foi implementada a nova abordagem comercial nas 9 agências, verificou-se que estas conseguiram melhorar significativamente o seu nível de eficiência, enquanto as agências que continuaram a usar a abordagem comercial tradicional diminuíram-no ligeiramente.

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This study examines the efficiency of search engine advertising strategies employed by firms. The research setting is the online retailing industry, which is characterized by extensive use of Web technologies and high competition for market share and profitability. For Internet retailers, search engines are increasingly serving as an information gateway for many decision-making tasks. In particular, Search engine advertising (SEA) has opened a new marketing channel for retailers to attract new customers and improve their performance. In addition to natural (organic) search marketing strategies, search engine advertisers compete for top advertisement slots provided by search brokers such as Google and Yahoo! through keyword auctions. The rationale being that greater visibility on a search engine during a keyword search will capture customers' interest in a business and its product or service offerings. Search engines account for most online activities today. Compared with the slow growth of traditional marketing channels, online search volumes continue to grow at a steady rate. According to the Search Engine Marketing Professional Organization, spending on search engine marketing by North American firms in 2008 was estimated at $13.5 billion. Despite the significant role SEA plays in Web retailing, scholarly research on the topic is limited. Prior studies in SEA have focused on search engine auction mechanism design. In contrast, research on the business value of SEA has been limited by the lack of empirical data on search advertising practices. Recent advances in search and retail technologies have created datarich environments that enable new research opportunities at the interface of marketing and information technology. This research uses extensive data from Web retailing and Google-based search advertising and evaluates Web retailers' use of resources, search advertising techniques, and other relevant factors that contribute to business performance across different metrics. The methods used include Data Envelopment Analysis (DEA), data mining, and multivariate statistics. This research contributes to empirical research by analyzing several Web retail firms in different industry sectors and product categories. One of the key findings is that the dynamics of sponsored search advertising vary between multi-channel and Web-only retailers. While the key performance metrics for multi-channel retailers include measures such as online sales, conversion rate (CR), c1ick-through-rate (CTR), and impressions, the key performance metrics for Web-only retailers focus on organic and sponsored ad ranks. These results provide a useful contribution to our organizational level understanding of search engine advertising strategies, both for multi-channel and Web-only retailers. These results also contribute to current knowledge in technology-driven marketing strategies and provide managers with a better understanding of sponsored search advertising and its impact on various performance metrics in Web retailing.

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The present study examines the level of pure technical and scale efficiencies of cassava production system including its sub-processes (that is production and processing stages) of 278 cassava farmers/processors from three regions of Delta State, Nigeria by applying Two-Stage Data Envelopment Analysis (DEA) approach. Results reveal that pure technical efficiency (PTE) is significantly lower at the production stage 0.41 vs 0.55 for the processing stage, but scale efficiency (SE) is high at both stages (0.84 and 0.87), implying that productivity can be improved substantially by reallocation of resources and adjusting operation size. The socio-economic determinants exert differential impacts on PTE and SE at each stage. Overall, education, experience and main occupation as farmer significantly improve SE while subsistence pressure reduces it. Extension contact significantly improves SE at the processing stage but reduces PTE and SE overall. Inverse size-PTE and size-SE relationships exist in cassava production system. In other words, large/medium farms are technically and scale inefficient. Gender gap exists in performance. Male farmers are technically efficient at processing stage but scale inefficient overall. Farmers in northern region are technically efficient. Investments in education, extension services and infrastructure are suggested as policy options to improve the cassava sector in Nigeria.