Analysis on pure e-commerce congestion effect,productivity effect and profitability in China

This paper examines the relationship of e-commerce congestion effect, productivity effect and profit generation in China. The technique of Data Envelopment Analysis (DEA) is used to measure returns to scale and total factor productivity in e-commerce. The results show that e-commerce firms achieve productivity growth but suffer from input congestion. Congestion weakens profitability and leads to negative returns of inputs to outputs. This finding offers a new insight to explain the determinants of profit change. This research enriches production theory of internet companies, and helps managers strengthen their profitability by measuring the existence of congestion and eliminating input congestion resources.     

Congestion, ownership, region of operation, and scale: Their impact on bus operator performance in Norway

The goal of this paper is to determine the impact that inputs such as fuel consumption and total number of workers employed have on operators’ efficiency in the Norwegian bus industry. Further, we investigate operations characteristics that are associated with the inefficient use of inputs in bus operations. This information is highly relevant for the subsidizers (decision-makers) since resource inefficiency leads to greater costs (ceteris paribus). We use Data Envelopment Analysis (DEA) to explore these issues. The results suggest that there is, in general, a potential for input saving in the sector of about 21%. No significant differences were found between urban and bus rural operators with respect to efficiency scores; neither were there any performance differences with respect to ownership. This latter result deviates from previous international studies, and can likely be explained by the lack of competition in the Norwegian bus industry. A particularly interesting result suggests a formidable degree of input congestion in the Norwegian bus industry, which is in contrast to previous international studies on such congestion.     

Congestion in the Chinese automobile and textile industries revisited

This paper re-examines a problem of congested inputs in the Chinese automobile and textile industries, which was identified by Cooper et al. [Cooper WW, Deng H, Gu B, Li S, Thrall RM. Using DEA to improve the management of congestion in Chinese industries (1981-1997). Socio-Economic Planning Sciences 2001;35:227-242]. Since these authors employed a single approach in measuring congestion, it is worth exploring whether alternative procedures would yield very different outcomes. Indeed, the measurement of congestion is an area where there has been much theoretical debate but relatively little empirical work. After examining the theoretical properties of the two main approaches currently available, those of Färe et al. [Färe R, Grosskopf S, Lovell CAK. The measurement of efficiency of production. Boston: Kluwer-Nijhoff; 1985] and Cooper et al., we use the data set assembled by Cooper et al. for the period 1981-1997 to compare and contrast the measurements of congestion generated by these alternative approaches. We find that the results are strikingly different, especially in terms of the amount of congestion identified. Finally, we discuss the new approach to measuring congestion proposed by Tone and Sahoo [Tone K, Sahoo BK. Degree of scale economies and congestion: a unified DEA approach. European Journal of Operational Research 2004;158:755-772].     

Productivity Growth, Efficiency and Outsourcing in Manufacturing and Service Industries

This paper is a survey of recent contributions to, and developments of, the relationship between outsourcing, efficiency and productivity growth in manufacturing and services. The objective is to provide a thorough and up–to–date survey that provides a significant discussion on data, as well as on the core methods of measuring efficiency and productivity. First, the readers are introduced to the measurement of partial and total factor productivity growth. Different parametric and non–parametric approaches to the productivity measurement in the context of static, dynamic and firm–specific modelling are discussed. Second, we survey the econometric approach to efficiency analysis. The issues of modelling, distributional assumptions and estimation methods are discussed assuming that cross–sectional or panel data are available. Third, the relationship between outsourcing and productivity growth in manufacturing and services is discussed. The correspondence between a number of hypotheses and empirical findings are examined. Examples of varieties of relevant empirical applications, their findings and implications are presented. Fourth, measurement of inputs and outputs in manufacturing and services are discussed. Finally, to promote useful research, a number of factors important to the analysis of outsourcing, efficiency and productivity growth in the service sector are summarised.     

A new method for measuring congestion in data envelopment analysis

In data envelopment analysis (DEA), there are two principal methods for identifying and measuring congestion: Those of Färe et al. [Färe R, Grosskopf S. When can slacks be used to identify congestion. An answer to W. W. Cooper, L. Seiford, J. Zhu. Socio-Economic Planning Sciences 2001;35:1–10] and Cooper et al. [Cooper WW, Deng H, Huang ZM, Li SX. A one-model approach to congestion in data envelopment analysis. Socio-Economic Planning Sciences 2002;36:231–8]. In the present paper, we focus on the latter work in proposing a new method that requires considerably less computation. Then, by proving a selected theorem, we show that our proposed methodology is indeed equivalent to that of Cooper et al.     

A novel method for computing single output for DEA with application in hospital efficiency

There are two main methods for measuring the efficiency of decision-making units (DMUs): data envelopment analysis (DEA) and stochastic frontier analysis (SFA). Each of these methods has advantages and disadvantages. DEA is more popular in the literature due to its simplicity, as it does not require any pre-assumption and can be used for measuring the efficiency of DMUs with multiple inputs and multiple outputs, whereas SFA is a parametric approach that is applicable to multiple inputs and a single output. Since many applied studies feature multiple output variables, SFA cannot be used in such cases. In this research, a unique method to transform multiple outputs to a virtual single output is proposed. We are thus able to obtain efficiency scores from calculated virtual single output by the proposed method that are close (or even the same depending on targeted parameters at the expense of computation time and resources) to the efficiency scores obtained from multiple outputs of DEA. This will enable us to use SFA with a virtual single output. The proposed method is validated using a simulation study, and its usefulness is demonstrated with real application by using a hospital dataset from Turkey.     

Using DEA to improve the management of congestion in Chinese industries (1981–1997)

Congestion is said to be present when increases in inputs result in output reductions. An “iron rice bowl” policy instituted in China shortly after the revolution led by Mao Tze Tung resulted in congestion that ultimately led to bankruptcy in the textile industry, and near bankruptcy in other industries. A major policy shift away from the “iron rice bowl policy” in 1990 led to massive layoffs and increasing social tensions. Were these massive layoffs necessary? Extensions of data envelopment analysis models effected in the present paper identified inefficiencies in the management of congestion. Using textiles and automobiles for illustration, it is shown how elimination of such managerial inefficiencies could have led to output augmentation without reducing employment. Thus, even in the presence of congestion, it proved to be possible to identify additional (managerial) inefficiencies that provided opportunities for improvement. In the heavily congested textile industry, these output augmentations could have been accompanied by reductions in the amounts of capital used (as an added bonus). In any case, we show how to identify and evaluate new types of efficiency—viz., the efficiency with which needed (or desired) inefficiencies are managed.     

Weak congestion in output additive data envelopment analysis

Our earlier work [Wei QL, Yan H. Congestion and returns to scale in data envelopment analysis. European Journal of Operational Research 2004;153:641–60] discussed necessary and sufficient conditions for the existence of congestion together with aspects of returns to scale under an output-oriented DEA framework. In line with this work, the current paper investigates the issue of “weak congestion”, wherein congestion occurs when the reduction of selected inputs causes some, rather than all, outputs to increase, without a worsening of others. We define output efficiency for decision making units under a series of typical DEA output additive models. Based on this definition, we offer necessary and sufficient conditions for the existence of weak congestion. Numerical examples are provided for purposes of illustration.     

Improving discrimination in data envelopment analysis: some practical suggestions

In some contexts data envelopment analysis (DEA) gives poor discrimination on the performance of units. While this may reflect genuine uniformity of performance between units, it may also reflect lack of sufficient observations or other factors limiting discrimination on performance between units. In this paper, we present an overview of the main approaches that can be used to improve the discrimination of DEA. This includes simple methods such as the aggregation of inputs or outputs, the use of longitudinal data, more advanced methods such as the use of weight restrictions, production trade-offs and unobserved units, and a relatively new method based on the use of selective proportionality between the inputs and outputs.     

Measuring scale efficiency from a parametric hyperbolic distance function

This paper shows how scale efficiency can be measured from an arbitrary parametric hyperbolic distance function with multiple outputs and multiple inputs. It extends the methods introduced by Ray (J Product Anal 11:183–194, 1998), and Balk (J Product Anal 15:159–183, 2001) and Ray (2003) that measure scale efficiency from a single-output multi-input distance function and from a multi-output and multi-input distance function, respectively. The method developed in the present paper is different from Ray’s and Balk’s in that it allows for simultaneous contraction of inputs and expansion of outputs. Theorems applicable to an arbitrary parametric hyperbolic distance function are introduced first, and then their uses in measuring scale efficiency are illustrated with the translog functional form.     

The Extraction of Technical Coefficients from Input and Output Data

Presumably, input-output coefficients reflect technology, and these coefficients measure the input requirements per unit of product. This concept has been extended to consumption theory, where it models expenditure shares. Input-output coefficients are extracted from the national accounts of an economy, by taking average proportions between inputs and outputs. Since the latter represent all sorts of inefficiencies, this practice blurs the measurement of technology. Input requirements are better measured by minimal proportions between inputs and outputs. This approach separates the measurement of technology from that of productive efficiency.     

Measuring Intersectoral Technology Spillovers: Estimates from the European and US Patent Office Databases

This paper presents several new methods for measuring intersectoral knowledge spillovers, and applies these methods in an analysis of productivity growth in manufacturing for a cross-country, cross-sectional sample for the 1980s. It is argued that existing methods of measuring such intersectoral knowledge spillovers are mostly aimed at measuring so-called crent spillovers'. The methods developed here are aimed at measuring knowledge spillovers—an additional aspect of the spillover process. The empirical analysis shows that there are indeed differences between these two types of spillover measure.     

Optimum,market and second-best land use patterns in a von Thünen city with congestion

This paper constructs a von Thünen type model with traffic congestion and two production inputs. A comparison between optimum and market land use patterns is presented. The second-best problem in which congestion tolls are not allowed is also considered. The policy variable in the analysis is the allocation of land between production and transportation. The result is examined in a cost-benefit analysis based on market rent.     

Simulation decomposition for environmental sustainability: Enhanced decision-making in carbon footprint analysis

Environmental sustainability problems frequently require the need for decision-making in situations containing considerable uncertainty. Monte Carlo simulation methods have been used in a wide array of environmental planning settings to incorporate these uncertain features. Simulation-generated outputs are commonly displayed as probability distributions. Recently simulation decomposition (SD) has enhanced the visualization of the cause-effect relationships of multi-variable combinations of inputs on the corresponding simulated outputs. SD partitions sub-distributions of the Monte Carlo outputs by pre-classifying selected input variables into states, grouping combinations of these states into scenarios, and then collecting simulated outputs attributable to each multi-variable input scenario. Since it is a straightforward task to visually project the contribution of the subdivided scenarios onto the overall output, SD can illuminate previously unidentified connections between the multi-variable combinations of inputs on the outputs. SD is generalizable to any Monte Carlo method with negligible additional computational overhead and, therefore, can be readily extended into most environmental analyses that use simulation models. This study demonstrates the efficacy of SD for environmental sustainability decision-making on a carbon footprint analysis case for wooden pallets.     

A new methodology to measure efficiencies of inputs (outputs) of decision making units in Data Envelopment Analysis with application to agriculture

This paper aims at developing a new methodology to measure and decompose global DMU efficiency into efficiency of inputs (or outputs). The basic idea rests on the fact that global DMU's efficiency score might be misleading when managers proceed to reallocate their inputs or redefine their outputs. Literature provides a basic measure for global DMU's efficiency score. A revised model was developed for measuring efficiencies of global DMUs and their inputs (or outputs) efficiency components, based on a hypothesis of virtual DMUs. The present paper suggests a method for measuring global DMU efficiency simultaneously with its efficiencies of inputs components, that we call Input decomposition DEA model (ID-DEA), and its efficiencies of outputs components, that we call output decomposition DEA model (OD-DEA). These twin models differ from Supper efficiency model (SE-DEA) and Common Set Weights model (CSW-DEA). The twin models (ID-DEA, OD-DEA) were applied to agricultural farms, and the results gave different efficiency scores of inputs (or outputs), and at the same time, global DMU's efficiency score was given by the Charnes, Cooper and Rhodes (Charnes et al., 1978) [1], CCR78 model. The rationale of our new hypothesis and model is the fact that managers don't have the same information level about all inputs and outputs that constraint them to manage resources by the (global) efficiency scores. Then each input/output has a different reality depending on the manager's decision in relationship to information available at the time of decision. This paper decomposes global DMU's efficiency into input (or output) components' efficiencies. Each component will have its score instead of a global DMU score. These findings would improve management decision making about reallocating inputs and redefining outputs. Concerning policy implications of the DEA twin models, they help policy makers to assess, ameliorate and reorient their strategies and execute programs towards enhancing the best practices and minimising losses.     

Towards a General Managerial Framework for Performance Measurement: A Comprehensive Highway Maintenance Application

This paper describes the application of Data Envelopment Analysis (DEA) to a highway maintenance setting, using measures of inputs, outputs and outcomes reported by New Zealand local authorities. A general framework of performance measurement is developed and illustrated through application to the highway setting. The framework encompasses a performance pyramid embodying multiple-perspectives of the organisation with a structure of measures linking critical success factors to process drivers, methods of data analysis and influencing factors such as professional culture. Distinctions between measures of outcome, output and input enable finer partitioning of analyses into managerial notions of efficiency, effectiveness and economy. The impact of environmental factors on efficiency is explored through two approaches suggested in the literature.     

A Note on the Technical and Allocative Efficiency of Local Exchange Carriers in the United States

The issue explored is whether incentive regulation of local exchange carriers in the United States has resulted in an increase in efficiency. After providing an overview of the nature of incentive regulation, the methodology for measuring the effects of incentive regulation on efficiency is reviewed. This methodology is data envelopment analysis and allows for the measurement of both technical efficiency and allocative efficiency of individual local exchange carriers. The results of empirically implementing the DEA approach indicate that there is little change in technical efficiency. In fact average technical efficiency in 1988 was the same as in 2001. Next, while outputs continued to grow at about their historical rate across LECs, the sizeable increase in the two types of capital increased inputs well above their historical average rates for some LECs leading to short run allocative inefficiency. On average, however, allocative efficiency shows no identifiable trend between 1988 and 2001. Finally, in the aggregate, total economic efficiency does not demonstrate any trend between 1988 and 2001.     

Assessing the effects of measurement errors on the estimation of production functions

This article explores to what extent the poor results that are often found when estimating parameters of production functions can be attributed to measurement errors, due to the use of common price deflators across firms. Because of the lack of detailed micro‐economic data, econometricians have to rely on industry‐wide deflators when computing outputs and intermediate inputs. A unique feature of the longitudinal data used in this paper is that it reports firm‐level prices. This allows for a comparative assessment of production function parameters where the outputs and intermediate inputs are computed using both firm‐specific prices and industry‐wide deflators. The empirical results presented in this paper show that the use of common deflators across firms leads to lower scale estimates, mainly because of a large downward bias in the estimated coefficients for labour. Copyright © 2006 John Wiley & Sons, Ltd.     

Airlines’ strategic interactions and airport pricing in a dynamic bottleneck model of congestion

This paper analyzes efficient pricing at a congested airport dominated by a single firm. Unlike much of the previous literature, we combine a dynamic bottleneck model of congestion and a vertical structure model that explicitly considers the role of airlines and passengers. We show that a Stackelberg leader interacting with a competitive fringe partially internalizes congestion, and that there are various toll regimes that induce the welfare maximizing outcome, widening the set of choices for regulators. In particular, charging the congestion toll that would apply for fully competitive carriers and that ignores any internalization, to both the leader and the fringe, yields the first-best outcome.     

职住平衡的研究回顾及观点综述

就业-居住平衡是西方城市规划界在与"城市病"做斗争的过程中形成的一种规划理念,并在20世纪80年代的美国转变为一些地方政府解决交通拥堵和空气污染的政策.从就业-居住平衡的涵义和测度开始,简要回顾了这一理念的形成和发展过程及其政策转向,重点梳理了西方学者对就业-居住平衡政策有效性和实现途径的不同观点,总结出其对中国城市空间结构研究和城市规划的启示,以期引起国内学者对这一问题的研究和讨论,共同为中国城市在市场化过程中的空间结构调整探索出一条具有中国特色的道路.