Desirable Inputs Research Articles

A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia

Data envelopment analysis (DEA) is generally used to evaluate past performance and multi objective linear programming (MOLP) is often used to plan for future performance goals. In this study, we establish an equivalence relationship between MOLP problems and combined-oriented DEA models using a direction distance function designed to account for desirable and undesirable inputs and outputs together with uncontrollable variables. This equivalence model can be effectively used to support interactive processes and performance measures designed to establish future performance goals while taking into account the preferences of decision makers (DMs). In particular, it allows DMs to consider different efficiency improvement strategies when subject to budgetary restrictions. The applicability of the proposed method and the efficacy of the procedures and algorithms are demonstrated using a case study where the performance of high schools in the City of Philadelphia is evaluated.

Performance Evaluation of Combined Biomedical Waste Treatment Plants with Specific Focus on Incinerators Using Data Envelope Analysis in Uttar Pradesh, India

AbstractAssessing the accurate performance of incinerators is imperative for policymakers to chalk out appropriate solid waste management plans. Being a treatment facility, with high capacity to destroy hazardous waste, incinerators also have the disadvantage of producing toxic ash and polluted air during the incineration process. It is, therefore, required to develop a model, which considers not only desirable inputs and outputs (I/O) but also the undesirable I/O to assess the relative performance of incinerators. This study illustrates the use of data envelopment analysis (DEA) to assess the performance of 14 common biomedical waste (BMW) treatment plants, i.e., incinerators (government- and private-owned facilities) in the state of Uttar Pradesh (UP), India, using the 2013 data obtained from the state’s pollution control agency. These 14 plants receive waste from 5,301 healthcare facilities (HCFs) and hospitals, with a total of 84,751 beds. A Charnes-Cooper-Rhodes (CCR) DEA model with two inputs and fo...

Measuring Japanese bank performance: a dynamic network DEA approach

A dynamic two-stage network model of production incorporating financial regulatory constraints is developed and estimated for Japanese commercial banks. In the first stage of production bank managers use three desirable inputs (labor, physical capital, and equity capital) to produce two intermediate outputs-deposits and other raised funds. The first stage is constrained by the level of non-performing loans produced in a preceding period. In the second stage, the bank managers use the first stage intermediate outputs to produce desirable outputs of loans and securities investments and an undesirable output of non-performing loans. The dynamic framework allows resources to be allocated over time to maximize the production of desirable outputs and simultaneously minimize the production of undesirable outputs.

Undesirable Outputs’ Presence in Centralized Resource Allocation Model

Data envelopment analysis (DEA) is a common nonparametric technique to measure the relative efficiency scores of the individual homogenous decision making units (DMUs). One aspect of the DEA literature has recently been introduced as a centralized resource allocation (CRA) which aims at optimizing the combined resource consumption by all DMUs in an organization rather than considering the consumption individually through DMUs. Conventional DEA models and CRA model have been basically formulated on desirable inputs and outputs. The objective of this paper is to present new CRA models to assess the overall efficiency of a system consisting of DMUs by using directional distance function when DMUs produce desirable and undesirable outputs. This paper initially reviewed a couple of DEA approaches for measuring the efficiency scores of DMUs when some outputs are undesirable. Then, based upon these theoretical foundations, we develop the CRA model when undesirable outputs are considered in the evaluation. Finally, we apply a short numerical illustration to show how our proposed model can be applied.

Development of Traffic Inputs for Mechanistic–Empirical Pavement Design Guide in Michigan

Characterizing traffic and developing accurate and desirable traffic inputs for the new Mechanistic–Empirical Pavement Design Guide (MEPDG) are critical but challenging activities. The purpose of this study was to develop a process for characterizing traffic inputs in support of the new MEPDG for the state of Michigan. These traffic characteristics include monthly distribution factors, hourly distribution factors, truck traffic classifications, axle groups per vehicle, and axle load distributions for different axle configurations. Axle weight and vehicle classification data were obtained from 44 weigh-in-motion and classification stations located throughout the state of Michigan to develop Level 1 (site-specific) traffic inputs. Cluster analyses were conducted to group sites with similar characteristics for development of Level 2 (regional) inputs. Finally, data from all sites were averaged to establish the statewide Level 3 inputs. The effects of the developed hierarchical traffic inputs on the predicted performance of rigid pavements were investigated with the MEPDG models. An algorithm based on discriminant analysis was developed to acquire the appropriate Level 2 traffic characteristic inputs for pavement design. For pavement analysis and design, it is recognized that site-specific data should be used wherever available. For projects in which site-specific data are not available, it is necessary to know whether Level 2 or Level 3 data are acceptable at a minimum for design. The MEPDG was used to investigate the impact of traffic input levels on predicted pavement performance for rigid pavements. The results of the analysis showed that for pavement design in Michigan, statewide averages should be used instead of MEPDG Level 3 data.

A generalized model in presence undesirable factors

Many production processes yield both desirable factors(input/output) and undesirable ones. Efficiency measurment is usually based on the assumption that desirable inputs and undesirable outputs have to minimized and desirable outputs and undesirable inputs have to be maximized.So far, a number of UDEA(DEA in present undesirable factors) models have been developed: The UCCR, UBCC models and the UFDH model are well known as basic UDEA model. In this paper, we suggest a model call generalized UDEA(UGDEA)model,which can treat the above stated basic DEA models in a unified way. In addition,by establishing the theoretical properties on relationship among the UGDEA model and those UDEA models, we prove that the UGDEA model make it possible to calculate the efficiency of DMU incorporating various preference structures of decision makers.

Undesirable inputs and outputs in DEA models

Efficiency measurement in Data Envelopment Analysis (DEA) is usually based on the assumption that inputs have to be minimized and outputs have to be maximized. In some situations, undesirable (bad) inputs and outputs may be presented in the production process. In order to improve the performance of an inefficient Decision Making Unit (DMU) the undesirable outputs and desirable (good) inputs should be decreased while the desirable outputs and undesirable inputs should be increased. In this paper, we present a method to deal with such inputs and outputs in non-radial DEA models.

Equilibrium Earnings Management, Incentive Contracts, and Accounting Standards*

AbstractIn this paper, we model earnings management as a consequence of the interaction among self‐interested economic agents ‐ namely, the managers, the shareholders, and the regulators. In our model, a manager controls a stochastic production technology and makes periodic accounting reports about his or her performance; an owner chooses a compensation contract to induce desirable managerial inputs and reporting choices by the manager; and a regulatory body selects and enforces accounting standards to achieve certain social objectives. We show that various economic trade‐offs give rise to endogenous earnings management. Specifically, the owner may reduce agency costs by designing a compensation contract that tolerates some earnings management because such a contract allocates the compensation risk more efficiently. The earnings‐management activity produces accounting reports that deviate from those prescribed by accounting standards. Given such reports, the valuation of the firm may be nonlinear and s‐shaped, thereby recognizing the manager's reporting incentives. We also explore policy implications, noting that (1) the regulator may find enforcing a zero‐tolerance policy ‐ no earnings management allowed ‐ economically undesirable; and (2) when selecting the optimal accounting standard, valuation concerns may conflict with stewardship concerns. We conclude that earnings management is better understood in a strategic context that involves various economic trade‐offs.

How good is your infant program? Use an observational method to find out

The proliferation of day care facilities for infants under 3 years of age has brought with it a growing concern with respect to the type and quality of care provided for infants and toddlers. That assurance of quality programming is crucial is suggested by a good deal of the literature on antecedents of high social-emotional and intellective competence in young children. For example, Watts, Barnett, and Halfar (1973) in their longitudinal ecological study of infant development have confirmed that highly competent 3-year olds, regardless of social class, have experienced markedly more interactions with adults in intellectually valuable activities. If limited financial or personnel resources exist, then certainly neither sophisticated nor lengthy measurement instruments can be used. Brevity, ease of use, specificity of developmentally desirable adult inputs, and sensitivity to caregiver differences in such inputs should be considered in choosing a method to evaluate programs with such financial constraints. If an observational method can highlight the kinds of experiences and the quality of interactions that go on between caregivers and babies, then it can be used as formative evaluation to improve program quality and to ensure the consistency of high-quality care. These methods do not have to be lengthy or complicated, but they should include teacher behaviors that reflect program goals. It is also important that input characteristics of "master" teachers of infants and toddlers be ascertained by means of such an instrument. In this manner the kinds, amounts, and qualities of adult care