CO2 emissions reduction of Chinese light manufacturing industries:a novel RAM-based global Malmquist-Luenberger productivity index

Climate change has become one of the most challenging issues facing the world. Chinese government has realized the importance of energy conservation and prevention of the climate changes for sustainable development of China's economy and set targets for CO2 emissions reduction in China. In China industry contributes 84.2% of the total CO2 emissions, especially manufacturing industries. Data envelopment analysis (DEA) and Malmquist productivity (MP) index are the widely used mathematical techniques to address the relative efficiency and productivity of a group of homogenous decision making units, e.g. industries or countries. However, in many real applications, especially those related to energy efficiency, there are often undesirable outputs, e.g. the pollutions, waste and CO2 emissions, which are produced inevitably with desirable outputs in the production. This paper introduces a novel Malmquist-Luenberger productivity (MLP) index based on directional distance function (DDF) to address the issue of productivity evolution of DMUs in the presence of undesirable outputs. The new RAM (Range-adjusted measure)-based global MLP index has been applied to evaluate CO2 emissions reduction in Chinese light manufacturing industries. Recommendations for policy makers have been discussed

A global cost Malmquist productivity index using data envelopment analysis

This paper proposes a global cost Malmquist productivity index, new cost Malmquist productivity index, that is circular and that gives a single measure of productivity change. The index is inspired by the global Malmquist productivity index as extended to productivity measurement. Decomposition of the proposed cost Malmquist productivity index is presented. Numerical results are presented for an example taken from the literature to illustrate the proposed algorithm.

Efficiency and productivity analysis of global not-for-profit microfinance institutions:data envelopment analysis approach

Microfinance has been regarded as the one of the effective solutions in poverty alleviation efforts globally. Its growth has been driven by not‐for‐profit microfinance institutions in the form of non‐governmental organization, credit unions, cooperatives and others. Microfinance sits at the unique position between social welfare programme and financial institutions as it faces dual objectives of outreach to the poor and financial sustainability. Due to its unique dual objectives, it is imperative to undertake a comprehensive performance and productivity assessment as microfinance institutions currently hold an important roles in improving the lives of the poor globally. This thesis thus has multi‐faceted objectives: firstly, it seeks to propose a comprehensive performance measurement that can evaluate these objectives comprehensively, as opposed to current focus on trade‐offs between microfinance dual objectives and shortsighted focus on financial indicator, yet proficient to track microfinance performance and total factor productivity over time. It therefore proposes Data Envelopment Analysis (DEA) as adept measurement for microfinance institutions globally, especially using hyperbolic, non‐oriented DEA model due to its benchmarking capability and DEA‐based Circular Malmquist Index in measuring total factor productivity under condition of unbalanced data, such as the case with microfinance. This thesis also proposes Social‐Financial Efficiency Matrix as a performance monitoring tool for microfinance. Secondly, this thesis seeks to provide thought‐provoking empirical evidence to the performance comparison between Islamic and conventional microfinance. Thirdly, it seeks to explore the relationship between loan methodology and microfinance efficiency in six different regions globally, in contributing to the search of an adept loan method that can boost efficiency. Fourthly, it seeks to analyse microfinance productivity globally in times of crisis, i.e. evaluating its resilience toward external shocks, so that improvement can be proposed for the future

Operational research:methods and applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order