Dynamic Efficiency Measurement Research Articles

The haemodynamic effects of crystalloid and colloid volume resuscitation on primary, derived and efficiency variables in post-CABG patients

BackgroundRecent studies in haemodynamic management have focused on fluid management and assessed its effects in terms of increase in cardiac output based on fluid challenges or variations in pulse pressure caused by cyclical positive pressure ventilation. The theoretical scope may be characterised as Starling-oriented. This approach ignores the actual events of right-sided excitation and left-sided response which is consistently described in a Guyton-oriented model of the cardiovascular system.AimBased on data from a previous study, we aim to elucidate the primary response to crystalloid and colloid fluids in terms of cardiac output, mean blood pressure and right atrial pressure as well as derived and efficiency variables defined in terms of Guyton venous return physiology.MethodRe-analyses of previously published data.ResultsCardiac output invariably increased on infusion of crystalloid and colloid solutions, whereas static and dynamic efficiency measures declined in spite of increasing pressure gradient for venous return.DiscussionWe argue that primary as well as derived and efficiency measures should be reported and discussed when haemodynamic studies are reported involving fluid administrations.

Airline dynamic efficiency measures with a Dynamic RAM with unified natural & managerial disposability

In this paper, we propose a Dynamic Range Adjusted Measure with unified natural & managerial disposability to evaluate the dynamic efficiency of 29 airlines during 2009–2015. In a dynamic period, the new model can judge automatically whether the airline should be under natural disposability or managerial disposability in the premise of optimizing the overall efficiency. We get some findings: 1. Scandinavian has the highest overall efficiency among these 29 airlines while Norwegian's overall efficiency is the least. 2. Improving undesirable outputs is not the most urgent work of these airlines. 3. In order to optimize the overall efficiency, most airlines should be under managerial disposability. 4. Most airlines' efficiencies have no obvious fluctuation in this period.

The Measurement of Dynamic Operational Efficiency in East Lake High-tech Zone Technology Business Incubation Network

The purpose of this paper is to examine the impact and success of a high-tech zone business incubation network project on its participants. The study aims to consider the impact of the project in terms of developing and supporting entrepreneurial activity in the East Lake of Wuhan. It seeks to establish and enhance existing technology business incubation literature and contribute to the field by identifying “good” practice and considering the measurement of success within such projects. This study employs an individual case study methodology which evaluates all aspects of the east lake high-tech zone technology business incubation network dynamically. A range of qualitative and quantitative methods are utilized to capture the views of aspiring entrepreneurs. In addition, the case study method is recognized as the most effective research strategy to capture the “rich” experience of complex project.

The Measurement of Dynamic Operational Efficiency in East Lake High-tech Zone Technology Business Incubation Network

The purpose of this paper is to examine the impact and success of a high-tech zone business incubation network project on its participants. The study aims to consider the impact of the project in terms of developing and supporting entrepreneurial activity in the East Lake of Wuhan. It seeks to establish and enhance existing technology business incubation literature and contribute to the field by identifying “good” practice and considering the measurement of success within such projects. This study employs an individual case study methodology which evaluates all aspects of the east lake high-tech zone technology business incubation network dynamically. A range of qualitative and quantitative methods are utilized to capture the views of aspiring entrepreneurs. In addition, the case study method is recognized as the most effective research strategy to capture the “rich” experience of complex project.

Dynamic Oil-in-Water Concentration Acquisition on a Pilot-Scaled Offshore Water-Oil Separation Facility.

This article is a feasibility study on using fluorescence-based oil-in-water (OiW) monitors for on-line dynamic efficiency measurement of a deoiling hydrocyclone. Dynamic measurements are crucial in the design and validation of dynamic models of the hydrocyclones, and to our knowledge, no dynamic OiW analysis of hydrocyclones has been carried out. Previous studies have extensively studied the steady state efficiency perspective of hydrocyclones, and have related them to different key parameters, such as the pressure drop ratio (PDR), inlet flow rate, and the flow-spilt. Through our study, we were able to measure the dynamics of the hydrocyclone’s efficiency response to step changes in the inlet flow rate with high accuracy. This is a breakthrough in the modelling, control, and monitoring of hydrocyclones.

Dynamic efficiency of German dairy farms under uncertainty

Output and price uncertainty determines the optimal allocation of variable inputs, and by the same token, firms' long-term adjustment of quasi-fixed factors. Dynamic efficiency measures, however, have thus far ignored uncertainty. To address this gap we present a model for dynamic efficiency measurement that combines a shadow cost approach with a stochastic dynamic cost-minimisation. We apply this model to western German dairy farm-level data from 1996-2010. We find that farms are more efficient in the long-run factor adjustment compared to the short-run, though they exhibit sensitivity to uncertainty. Neglecting uncertainty will overestimate average inefficiency and thus farms may appear seemingly inefficient.

Dynamic efficiency of German dairy farms under uncertainty

Output and price uncertainty determines the optimal allocation of variable inputs, and by the same token, firms' long-term adjustment of quasi-fixed factors. Dynamic efficiency measures, however, have thus far ignored uncertainty. To address this gap we present a model for dynamic efficiency measurement that combines a shadow cost approach with a stochastic dynamic cost-minimisation. We apply this model to western German dairy farm-level data from 1996-2010. We find that farms are more efficient in the long-run factor adjustment compared to the short-run, though they exhibit sensitivity to uncertainty. Neglecting uncertainty will overestimate average inefficiency and thus farms may appear seemingly inefficient.

A dynamic network efficiency measurement of airports performance considering sustainable development concept: A fuzzy dynamic network-DEA approach

In this paper, sustainability of airports is considered through a multi-perspective, multi-system, and multi-process operation. It is explored how an extension of fuzzy dynamic network performance measurement approach helps to determine the efficiency performance of an airport system. In this way, a three-pronged approach is intended which considers the internal functions of an airport, functions affecting the community and functions related to the passengers simultaneously. This novel combination makes it possible to have a comprehensive evaluation of airports' performance. Besides, fuzzy extension of SBM dynamic network approach makes it possible to deal better with the vagueness of variables during analysis. So, this extension is valuable from both technical and conceptual aspects which in turn provide useful information and insights for the future design of holistic strategies connected with sustainable development of airports where ever they are.

Dynamic efficiency in Lithuanian cereal farms

Lithuanian family farms are subject to both production and investment support under the Common Agricultural Policy. As a result, there have been structural changes in the sector. Therefore, it is important to analyse farm performance from an adjustment cost perspective. The dynamic efficiency measures encompass multi-temporal cost minimisation. This paper addresses the following problem: what are the key trends in dynamic efficiency and what are the implications thereof on further development of cereal farming in Lithuania? The present paper aims to identify the prospective paths for development of Lithuanian cereal farms by analysing their dynamic efficiency. Data Envelopment Analysis is applied to calculate technical efficiency scores under different assumptions regarding returns to scale. The results indicate pure technical inefficiency remained as the main source of the overall technical inefficiency with scale inefficiency increasing throughout 2004–2014. A more detailed analysis showed that it was smaller farms that suffered from losses in the pure technical efficiency to the highest extent. The exit of the smaller cereal and oilseed farms, therefore, has likely contributed to the decreasing technical inefficiency, yet it has dampened scale efficiency.

The adjustment-cost model of the firm: Duality and productive efficiency

We present the theoretical foundation for an adjustment cost technology that supports the intertemporal production decision making behavior using the directional distance function. Dynamic input efficiency measures are developed that can separate out the impact of variable and dynamic factors inefficiency levels. An approach to implement this theory in a nonparametric fashion is developed and applied to an unbalanced panel of Dutch glasshouse firms. The application finds overuse of all variable inputs and overcapitalization of installations, the overall dynamic efficiency gain of 16% remains possible, with allocative inefficiencies indicating underinvestment in structures and installations. A comparison of static and dynamic efficiency measures finds that the static overall cost inefficiency is overestimated with technical inefficiency being overstated and allocative inefficiency being understated.

Measuring dynamic efficiency of highway maintenance operations

In this paper we discuss a dynamic efficiency measurement model for evaluating the performance of highway maintenance policies where the inter-temporal dependencies between consumption of inputs (i.e., maintenance budget) and realization of outputs (i.e., improvement in road condition) are explicitly captured. We build on a micro representation of pavement deterioration and renewal processes and study the impact of the allocation of scarce maintenance budgets over time. We provide a measure of efficiency that contrasts the optimized budget allocations to the actual ones. The developed model is then applied to an empirical dataset of pavement condition and maintenance expenditures over the years 2002 to 2008 corresponding to seventeen miles of interstate highway that lay in one of the counties in the state of Virginia, USA. The policies that were found through optimization showed that road authorities should give higher priorities to preventive maintenance than corrective maintenance. In essence, by applying preventive maintenance, the road authorities can effectively decrease the need for future corrective maintenance while spending less overall.

Reviewing the literature on non-parametric dynamic efficiency measurement: state-of-the-art

Much of the literature on static efficiency measurement models assumes that the inputs are fully used for producing outputs in the same period, with the result that no time interdependence exists between the input utilization and output realizations for a production unit in consecutive periods. A review of the literature on non-parametric dynamic efficiency models identifies five key factors of the inter-temporal dependence between input and output levels over different periods: (i) production delays; (ii) inventories (inventories of exogenous inputs or inventories of intermediate and final products); (iii) capital or generally quasi-fixed factors (and associated embodied technological change, vintage specific capital); (iv) adjustment costs; and (v) incremental improvement and learning models (disembodied technological change). This paper reviews the literature and finds that the dynamic issues associated with adjustment costs and capital have received considerable attention in the literature, whereas the dynamic issues associated with inventories have received less attention. The paper concludes with suggestions for future research such as relaxing the perfect anticipation/knowledge assumption for future variables, prices, and states. Moreover, Dynamic Network Data Envelopment Analysis has provided a unifying framework for some dynamic factors, but further development of these models is necessary including meaningful applications.

Measuring dynamic efficiency under uncertainty

In this paper we develop a theoretical model that links dynamic efficiency measurement and optimal investment under uncertainty. It is widely acknowledged that uncertainty has an impact on the optimal factor use of a profit maximizing firm. This is particularly true for the optimal adjustment of the firm’s capital stock. While uncertainty has been considered in the static efficiency measurement literature it has been ignored so far in the context of dynamic efficiency measurement. This paper targets at closing this gap. For that purpose we take up a dynamic efficiency model which embeds a stochastic intertemporal duality model into a shadow cost framework and allows for measuring technical and allocative inefficiency. We derive hypotheses on how uncertainty affects the measurement of efficiency. The factor demand equations, which we derive, may serve as a starting point for an empirical validation of these hypotheses.

Measurement of Dynamic Efficiency: A Directional Distance Function Parametric Approach

This research proposes a parametric estimation of the structural dynamic efficiency measures proposed in 2009 by Silva and Oude Lansink. Overall, technical and allocative efficiency measurements are derived based on a directional distance function and the duality between this function and the optimal value function. The applicability of the parametric proposal is illustrated by assessing dynamic efficiency ratings for a sample of Dutch dairy farms observed from 1995 to 2005. Dynamic efficiency ratings indicate the possibility to achieve long‐run cost savings on the order of 12% that are mainly to be accomplished through a reduction in input use.

A Reduced‐Form Model for Dynamic Efficiency Measurement: Application to Dairy Farms in Germany and The Netherlands

The stochastic distance function model is extended to allow for the inefficiency component of the error term to be autocorrelated, as implied by a dynamic model of firm behavior. The autocorrelation parameter can then be interpreted as a measure of the persistence of inefficiency. The model is viewed from a state‐space perspective, and Kalman filtering techniques are proposed for estimation. The model is applied to two panels of dairy farms from Germany and the Netherlands. The results suggest a very high degree of persistence of inefficiency through time.

Development of framework for realization and classification of static and dynamic energy efficiency measures

The increasing emphasis on energy management warrants an investigation to classify energy efficiency measures (EEMs) based on the characteristics that are responsible for achieving efficiency. As numerous measures have been developed over the years, this study is motivated by the fact that the successful implementation of EEMs requires an understanding of the formulation of EEMs and how their characteristics influence thermal comfort as well as energy consumption. In an integrated approach, the classification of EEMs is accomplished by means of analyzing the transient energy balances for components that have the most significant effects on energy consumption. The objectives of this study are to (a) create a framework for classifying EEMs based on their physical and inherent characteristics, (b) classify typical EEMs based on the suggested framework and (c) examine the application of control methodologies as EEMs. The procedure adopted for this study includes formulation of a general model based on differential equations describing the interactions between important components. It is determined that, based on their inherent characteristics, EEMs can be classified into static and dynamic categories. The results from simulation of several control methodologies, as EEMs, show that the dynamic types perform better as compared to their static counterparts. It is anticipated that the proposed framework for classification of EEMs can lead to development of more effective simulation tools, design, manufacturing, application and procedures for commissioning and retro-commissioning.

Dynamic Efficiency Measurement: Theory and Application

Nonparametric dynamic measures of production efficiency are developed in the context of an adjustment‐cost technology and intertemporal cost minimization. Bounds on each efficiency measure are derived for each firm using a nonparametric revealed preference approach. Long‐run efficiency measures indicate the relative efficiency of both variable and dynamic factors while short‐run measures of efficiency indicate whether variable inputs are employed efficiently in the production process. The efficiency measures are temporal in nature by describing the degree of efficiency of the firm at a particular point along its adjustment path. The empirical implementation is illustrated for a balanced panel of Pennsylvania dairy operators during 1986–1992.

Numerical simulation and analysis of fuzzy PID and PSD control methodologies as dynamic energy efficiency measures

Energy efficiency enhancement is achieved by utilizing control algorithms that reduce overshoots and undershoots as well as unnecessary fluctuations in the amount of energy input to energy consuming systems during transient operation periods. It is hypothesized that application of control methodologies with characteristics that change with time and according to the system dynamics, identified as dynamic energy efficiency measures (DEEM), achieves the desired enhancement. The objective of this study is to simulate and analyze the effects of fuzzy logic based tuning of proportional integral derivative (F-PID) and proportional sum derivative (F-PSD) controllers for a heating and cooling energy system while accounting for the dynamics of the major system components. The procedure to achieve the objective includes utilization of fuzzy logic rules to determine the PID and PSD controllers gain coefficients so that the control laws for regulating the heat exchangers heating or cooling energy inputs are determined in each time step of the operation period. The performances of the F-PID and F-PSD controllers are measured by means of two cost functions that are based on quadratic forms of the energy input and deviation from a set point temperature. It is found that application of the F-PID control algorithm, as a DEEM, results in lower costs for energy input and deviation from a set point temperature by 24% and 17% as compared to a PID and 13% and 8% as compared to a PSD, respectively. It is also shown that the F-PSD performance is better than that of the F-PID controller.

Measurement of Dynamic Efficiency in Production : An Application of Data Envelopment Analysis to Japanese Electric Utilities

The purpose of this paper is to measure productive efficiencies when a firm employs quasi-fixed inputs that cannot be instantaneously adjusted to their optimal levels. To this end, data envelopment analysis (DEA) is extended to a dynamic framework so that investment behavior can be modelled with the efficient production frontier. Based on the work of Nemoto and Goto (1999), we show how the efficiencies of quasi-fixed inputs and their adjustment processes are evaluated. An application to Japanese electric utilities over the 1981–1995 period delivers empirically plausible results and proves the usefulness of the procedure.

The Measurement of Dynamic Productive Efficiency

Measuring dynamic productive efficiency from observed input‐output data raises several new issues which are absent in the static production frontier studies. The adjustment cost approach is developed here as an interface between the static and the dynamic frontier studies, and the non‐parametric method of Farrell developed for static efficiency is extended for the specification of a dynamic production frontier.