Efficiency Analysis Of Zakat Institutions In Indonesia: Data Development Analysis (DEA) And Free Disposal Hull (FDH) Approaches

This study aimed at assessing the efficiency of zakat organizations in Indonesia by the use of non-parametric efficiency measurement methods. In addition, a cluster analysis based on the affiliation type was also used to assess the efficiency of Zakat organizations. A quantitative approach with the DEA and FDH methods was applied to this research, during which the latest data from the financial reports of each Zakat Institution have been utilized. This period ranges from 2014 to 2018 for the 14 Zakat Institutions. Based on the results, Zakat Institutions have equal efficiency between DEA and FDH methods if the clusters of government, corporation, and social community are combined. Research data on measuring efficiency show that the DEA method contributes 21% of all Decision-Making Units (DMU) to the total, while the FDH method contributes 25%. The research is one of the first studies to focus on the efficiency of the Zakat Institutions and its associated clusters: government, corporation, and social community. This research can be useful for Zakat Institutions in the form of critical application evaluation considering the research input variables, such as salaries, operational costs, and cost of socialization, and research output variables, for example zakat fund, zakat distribution taking maqasid sharia aspects into consideration

Stochastic non-parametric efficiency measurement and yardstick competition in electricity regulation

Stochastic non-parametric efficiency measurement constructs production or cost frontiers that incorporate both inefficiency and stochastic error. This results in a closer envelopment of the mean performance of the companies in the sample and diminishes the effect of extreme outliers. This paper uses the Land, Lovell and Thore (1993) model incorporating information on the covariance structure of inputs and outputs to study efficiency across a panel of 14 electricity distribution companies in the UK during the 1990s. The purpose is to revisit the 1999 distribution price control review carried out by the UK regulator. The regulator’s benchmarking is contrasted with the stochastic nonparametric efficiency results and with other comparative efficiency models offering close envelopment of the data. Some conclusions are offered about the possible regulated price effects in the UK case

A new efficiency evaluation approach with rough data: An application to Indian fertilizer

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In the world of chaos, nothing is certain. In such an unpredictable world, measuring the efficiency of any individual is inevitable. In a conventional data envelopment analysis (DEA) model, exact input and output quantity data are needed to measure the relative efficiencies of homogeneous decision-making units (DMUs). However, in many real-world applications, the exact knowledge of data might not be available. The rough set theory allows for handling this type of situation. This paper tries to construct a rough DEA model by combining conventional DEA and rough set theory using optimistic and pessimistic confidence values of rough variables, all of which help provide a way to quantify uncertainty. In the proposed method, the same set of constraints (production possibility sets) is employed to build a unified production frontier for all DMUs that can be used to properly assess each DMU's performance in the presence of rough input and output data. Besides, a ranking system is presented based on the approaches that have been proposed. In the presence of uncertain conditions, this article investigates the efficiency of the Indian fertilizer supply chain for over a decade. The results of the proposed models are compared to the existing DEA models, demonstrating how decision-makers can increase the supply chain performance of Indian fertilizer industries

The role of multiplier bounds in fuzzy data envelopment analysis

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The non-Archimedean epsilon ε is commonly considered as a lower bound for the dual input weights and output weights in multiplier data envelopment analysis (DEA) models. The amount of ε can be effectively used to differentiate between strongly and weakly efficient decision making units (DMUs). The problem of weak dominance particularly occurs when the reference set is fully or partially defined in terms of fuzzy numbers. In this paper, we propose a new four-step fuzzy DEA method to re-shape weakly efficient frontiers along with revisiting the efficiency score of DMUs in terms of perturbing the weakly efficient frontier. This approach eliminates the non-zero slacks in fuzzy DEA while keeping the strongly efficient frontiers unaltered. In comparing our proposed algorithm to an existing method in the recent literature we show three important flaws in their approach that our method addresses. Finally, we present a numerical example in banking with a combination of crisp and fuzzy data to illustrate the efficacy and advantages of the proposed approach

Hybrid rough set and data envelopment analysis approach to technology prioritisation

The complexity and speed of change in technological systems pose new challenges to technology management. Particular attention should be given to the issue of modelling the uncertainty of assessments and creating rules for determining the weights of the technology assessment criteria. The article aims to present a comprehensive hybrid technology prioritisation model based on the Data Envelopment Analysis and the concept of Rough Sets. The technology prioritisation process that uses the proposed model includes three consecutive stages: (i) the formulation of technology assessment matrix, (ii) the removal of the criteria redundancy based on indiscernibility relation defined in the Rough Set Theory, (iii) the development of rough variables and prioritisation using the DEA super-efficiency model. The combination of DEA and RS is a unique proposal to classify and rank objects based on the tabular representation of their conditional attributes under circumstances of uncertainty. Application of the developed hybrid model to the real data of the technology foresight project “NT FOR Podlaskie 2020” positively verified the assumed effects of its use. The obtained results allow a more objective and rational justification of the chosen technology, simplification of interpretation and better authentication of results from the perspective of decision-makers. First published online 8 May 202

An analysis of the relationship between bank efficiency and access to banking services in South Africa

The primary objective of this study is to investigate the nature of the relationship between bank efficiency gains and access to banking services in South Africa. The importance of making such an enquiry arises from the fact that various studies have identified access to financial services as an important vehicle for lifting the poor out of poverty. In particular, there is concern that banks` appetite for better scores on efficiency has the potential of reducing access to services for consumers particularly the low-income clients. The study attempted to answer two central research questions: Firstly, does the quest for banks to improve efficiency preclude access to banking services for some group of consumers? Secondly, do bank efficiency gains necessarily translate to improved accessibility to banking services? The researcher applied a two-stage methodology approach. In the first stage, the Hicks-Moorsteen aggregator functions were used to generate and decompose total factor productivity (TFP) into several efficiency measures for a panel of eight South African banks. First stage results revealed that the average banking sector total factor productivity efficiency (TFPE) was 59 percent implying that the observed TFP was 41 percent short of the maximum TFP possible using the available technology. A further comparison of performance revealed that large banks were better performing than small banks in terms of TFPE. Apart from estimating and decomposing TFP indices we needed to determine if there was a statistically significant change in the TFPE of South African banking system as a result of the global financial crisis. A general analysis of the generated scores showed that TFPE clearly decreased during 2008-2009, the period that coincided with the global financial crisis. We then used the Fixed Effects Model (FEM) in the second-stage analysis to examine the link between banking sector TFPE and access. The FEM was utilised to take account of bankspecific heterogeneity. The obtained results indicated existence of a positive and significant relationship between banking efficiency and access to banking services. This study suggests that banking sector efficiency plays a crucial role in promoting access to bank services in South Africa. We therefore underscore the need for all banks to attain and maintain high efficiency in order to augment government efforts towards improving accessibility for the unbanked South African people. We also found evidence similar to that reached by Kablan (2010) that an increase in the rural population is associated with a reduction in access to bank services. From this result, we speculated that banks are somewhat biased against providing their services to the general rural populace. Since the rural-population variable exerted the greatest marginal impact on access we suggested that perhaps investment in rural infrastructure would help broaden access and so improve financial inclusion on a larger scale. Finally we also investigated the link between banking sector efficiency and unemployment in South Africa. Of paramount importance in the second stage analysis was that we found a negative and significant association between banking sector efficiency and unemployment indicating that employment is influenced, inter alia, by the efficiency with which banks operate

Comparative evaluation of public universities in Malaysia using data envelopment analysis

Applications of Data Envelopment Analysis (DEA) for the assessment of performance of universities have been widely reported in the literature. Often the number of universities under the assessment is relatively small compared to the number of performance measures (inputs and outputs) used in the analysis, which leads to a low discriminating power of DEA models on efficiency scores. The main objective of this thesis is the development of improved DEA models that overcome the above difficulty, using a sample of public universities in Malaysia as an illustrative application. The proposed new approach combines the recently introduced Hybrid returns to scale (HRS) model with the use of additional information about the functioning of universities stated in the form of production trade-offs. The new model developed in this thesis, called Hybrid returns to scale model with trade-offs (HRSTO), is applied to a sample of eighteen universities, which is considered to be a very small sample for the DEA methodology. Our results show that, in contrast with standard DEA models, the new model is perfectly suitable for such samples and discriminates well between good and bad performers. The proposed combined use of HRS model with production trade-offs is a novel methodology that can be used in other applications of DEA. Overall, the thesis makes several contributions of the theory and practice of DEA. First, for the first time, it is shown that the higher education sector satisfies the assumptions and can be modelled using the proposed HRSTO model. Second, also for the first time, it is shown that production trade-offs can be assessed for such applications and the methodology of their assessment has been developed and used in the thesis. Third, it is demonstrated that the HRSTO model significantly improves the discriminating power of analysis compared to standard DEA models, which is particularly important for small data sets. Fourth, it is concluded that the HRS model is further improved if production trade-offs are used. Fifth, by experimenting with different specific values of production trade-offs, it is shown that even the most conservative estimates of trade-offs notably improve the model. Finally, our results contribute to the more general discussion of the performance of universities in Malaysia and identification of the best performers among them

Fishing for solutions. Environmental and operational assessment of selected Galician fisheries and their products

Fishing is the only hunting activity which is still maintained on an industrial level to sustain worldwide food demand. Currently, worldwide fisheries are suffering a series of hazards linked to overexploitation and increasing human demand for protein, causing a wide range of environmental impacts on marine ecosystems, such as stock depletion or ecosystem disruption. Moreover, the fishing industry has grown to an extent where the environmental burdens associated with on board and on land operational activities, such as fuel consumption by vessels or wastewater generated by canning factories, are also becoming important environmental concerns. From a regional perspective, Galicia (NW Spain), the main fishing region in the European Union (EU) in terms of landed fish and economic turnover, does not escape these global threats. Additionally, Galicia supplies the rest of Spain and other EU countries with important amounts of fresh and processed seafood