Industrial energy and environment efficiency evaluation become especially crucial as industrial sectors play a key role in CO2 emission reduction and energy consumption. This study adopts the additive range-adjusted measure data envelope analysis (RAM-DEA) model to estimate the low-carbon economy efficiency of Chinese industrial sectors in 2001–2013. In addition, the CO2 emission intensity miti...

Many production activities generate undesirable byproducts in conjunction with the desirable outputs they produce. The present study uses an output distance function approach and its duality with the revenue function to estimate the marginal abatement cost of CO2 emissions from a sample of thermal plants in India. Two sets of exercises have been undertaken. The marginal abatement cost is first ...

Abstract The question of how to properly model production systems with unintended outputs has proven both controversial and particular interest the productivity efficiency community. paper explains why some arguments put forward in these controversies are hardly convincing for industrial other processes. Among things, there is a lack clear conceptual labelling different types joint production, ...

There are two typical sub-processes in bank production– deposit generation and loan generation. Aiming to open the black box of input-output production of banks, and provide comprehensive and accurate assessment on the efficiency of each stage, this paper proposes a two-stage network model with bad outputs and supper efficiency (US-NSBM). Empirical comparisons show that the US-NSBM may be promi...

This paper explores a relatively new methodology, the directional distance function method, to analyze productivity growth. The method explicitly evaluates the role undesirable outputs of the economy, such as carbon dioxide and other green-house gases, have on the frontier production process which we specify as a piece-wise linear and convex boundary function. We decompose productivity growth i...

In many practical situations the outputs of a plant are not measured exactly, but are corrupted by quantization errors. Often the effect of the quantization error is neglected in the control design phase, which can lead to undesirable effects like limit cycles and even chaotic behavior once the controller has been implemented. In this paper we present a method based on 11 optimal control that m...

The purpose of this contribution1 is to set up a language to evaluate the results of concerted action among interdependent agents against predetermined properties that we can recognise as desirable from a deontic point of view. Unlike the standard view of logics to reason about coalitionally rational action, the capacity of a set of agents to take a rational decision will be restricted to what ...

This paper uses a fully nonparametric approach to estimate efficiency measures for primary care units incorporating the effect of (exogenous) environmental factors. This methodology allows us to account for different types of variables (continuous and discrete) describing the main characteristics of patients served by those providers. In addition, we use an extension of this nonparametric appro...

Many studies have measured productivity change and efficiency when an undesirable output is a by-product. We flexibly treat the bad as a technology shifter of an input distance function and model a system of nonlinear equations subject to endogeneity. Theory dictates that we impose monotonicity on all inputs, outputs, and the bad. Since a Bayesian full-information likelihood approach can easily...