Efficiency evaluation of banks in China: A dynamic two-stage slacks-based measure approach

Operational processes of banks in China can be divided into productivity and profitability stages. Within this, non-performing loans can be treated as a carry-over variable, an undesirable output of the profitability stage in the previous period but an input to the profitability stage in the current period. Using this framework, this paper proposes a dynamic two-stage slacks-based measure model to evaluate the efficiencies of Chinese banks. Based on the proposed model, the measures of stage, period and period stage efficiencies are defined. The proposed approach is applied to evaluate the operational efficiency of banks in China during 2008–2012. Key findings are that banks in China show both technical and scale inefficiency during 2008–2012, which results from the inefficiencies of both the productivity stage and profitability stage; city-owned commercial banks are more overall technically efficient than state-owned commercial banks and joint-stock commercial banks although state-owned commercial banks show best practice for pure technical efficiency, and city-owned commercial banks perform better than joint-stock commercial banks for pure technical efficiency.     

C239. The continued fraction for lnr( z): a stieljes conjecture

Estimation in logistic-normal models for correlated and overdispersed binomial data is complicated by the numerical evaluation of often intractable likelihood functions. Penalized quasilikelihood (PQL) estimators of fixed effects and variance components are known to be seriously biased for binary data. A simple correction procedure has been proposed to improve the performance of the PQL estimators. The proposed method is illustrated by analyzing infectious disease data. Its performance is compared, by means of simulations, with that of the Bayes approach using the Gibbs sampler.     

Testing for mean and variance differences with samples from distributions that may be non-normal with unequal variances

The problem of comparing several samples to decide whether the means and/or variances are significantly different is considered. It is shown that with very non-normal distributions even a very robust test to compare the means has poor properties when the distributions have different variances, and therefore a new testing scheme is proposed. This starts by using an exact randomization test for any significant difference (in means or variances) between the samples. If a non-significant result is obtained then testing stops. Otherwise, an approximate randomization test for mean differences (but allowing for variance differences) is carried out, together with a bootstrap procedure to assess whether this test is reliable. A randomization version of Levene's test is also carried out for differences in variation between samples. The five possible conclusions are then that (i) there is no evidence of any differences, (ii) evidence for mean differences only, (iii) evidence for variance differences only, (iv) evidence for mean and variance differences, or (v) evidence for some indeterminate differences. A simulation experiment to assess the properties of the proposed scheme is described. From this it is concluded that the scheme is useful as a robust, conservative method for comparing samples in cases where they may be from very non-normal distributions.     

Establishing safety stocks for master production schedules

The basic master production scheduling problem assumes that periodic demands are known with certainty. Uncertainty in the forecasts arc typically accommodated afterwards by adding safety stocks to a schedule. Two popular methods for establishing safety stocks are: (1) the constant cycle service level method; and (2) the constant safety stock method. This paper outlines these methods and then develops a third method which results in optimal safety stocks. The paper includes an experimental investigation aimed at comparing performances of the three safety stock methods. The constant safety stock method is shown to perform within one or two per cent of optimal, while the constant cycle service level method performs worse under most conditions. Shorter lead times, variable order interval lengths, and time-dependent forecast errors all adversely affect the performances of the non-optimal methods. An operations manager could use these results to evaluate the appropriateness of the methods for his master production scheduling environment.     

Efficiency decomposition in network data envelopment analysis with slacks-based measures

Conventional data envelopment analysis (DEA) treats the production system as a black box when measuring efficiency, ignoring its internal structure. By taking the operations of the component processes of the system into consideration, several network DEA models have been developed. Of these, the slacks-based measure (SBM) approach has attracted much attention for its ability to provide suitable efficiency measures, especially for weakly efficient production units. This paper proposes a general SBM model for network systems, and is able to decompose the system efficiency into a weighted average of the process efficiencies. This relationship holds for all types of network structure. An example shows that the network model has stronger discriminating power than the conventional black-box model, and the system efficiency is indeed a weighted average of the process efficiencies. The decomposition of the system efficiency helps identify key factors to improve the performance of a production unit.     

Benchmarking of maintenance and outage repair in an electricity distribution company using the value-based DEA method

Benchmarking of electricity distribution utilities has been widely used as a means to contribute for the adoption or reinforcement of enhanced competitiveness and innovation practices to optimize costs, increase customer satisfaction, improve corporate image and maximize profits. The purpose of this paper is to present a benchmarking study for the maintenance and outage repair activity carried out by a Portuguese electricity distribution company, EDP Distribuição (EDP-D), using the value-based DEA method, which builds on links between data envelopment analysis (DEA) and multiple criteria decision analysis (MCDA). This study illustrates the impact of the incorporation of managerial preferences in the classification and ranking of 40 network areas served by EDP-D, confronting the results with a previous study based on a BCC DEA model. In order to deal with the underlying uncertainty, the value-based DEA method for performance evaluation is adapted to include the concept of super-efficiency. Besides identifying best practices, sources of inefficiency, gaps relatively to best practices and opportunities for improvement, this analysis supports the introduction of corrective measures and informs decisions about future goals.     

新常态视角下装备制造业技术效率研究

新常态下提质增效是装备制造业发展的新模式。通过突破传统投入指标,引入能源指标,更全面、客观地反映装备制造业全行业和子行业技术效率与投入冗余的实际水平。以辽宁省为例进行实证分析,结果表明:通过引入能源指标的DEA技术效率测算值反映出普遍存在子行业的纯技术效率高于规模效率现象,但辽宁省装备制造业全行业技术效率仍是非DEA有效; 纯技术效率值为1的子行业,投入冗余差值比均为0; 金属制造业是七个子行业中技术效率和投入冗余表现最差的行业,而通信制造业表现最好。该研究进一步客观地展现各子行业资源利用及投入冗余的差异。     

惩罚函数型回归及应用

函数数据分析方法近年来成为研究热点,本文用函数数据分析方法研究了我国农村居民消费的有关问题,首先用B-样条基将函数数据平滑,然后建立了农村居民消费支出关于消费价格指数的函数型线性回归模型.结果表明,1月到10月CPI对农村居民消费具有推动作用,而11月到12月CPI对农村居民消费具有抑制作用.     

大数据中的管理问题: 基于大数据的资源观

作为重要的战略资源,大数据中包含诸多关键的管理问题． 文章首先评述了基于不同视角对大数据的认识． 然后,从管理的视角看大数据,指出大数据是一类重要的战略性信息资源,并从复杂性、决策有用性、高速增长性、价值稀疏性、可重复开采性和功能多样性等6 个方面探究了大数据资源的管理特征． 最后,提炼并探讨了大数据资源的获取问题、加工问题、应用问题、产权问题、产业问题和法规问题等6 个方面的关键管理问题