EFFICIENCY ANALYSIS IN SPARE PART RETAIL USING DATA ENVELOPMENT ANALYSIS

The retail business sector contributes a large per capita to Indonesia so this sector has a vital role in the Indonesian economy. The retail business in Indonesia is growing day by day, and business competition is showing quite rapid development, especially on spare part retail businesses in Padang. The sales of spare parts from year to year do not increase significantly. The number of players entering this market makes competition is building up. One of them is the spare parts retailer who has established business since 1974 and already has five branch stores in Padang. In the current conditions, the potential of spare parts retail business has not realized and has not organized optimally. It is necessary to measure efficiency to determine the performance of spare parts retail business processes, so players in this business can improve their business and can compete with other competitors. Based on the problems that have been explained, it is needed an efficiency analysis on the spare parts retail business to measure the efficiency level of the company, so the company can implement improvement to improve the efficiency level and can through market competition. Efficiency analysis was conducted on one spare part retailer that already has five spare part retail branches in Padang using Data Envelopment Analysis method, which uses an input-oriented BCC model. This model was chosen because the retail business is a dynamic sector, so changing in input or output does not affect the other linearly. In other words, changing the values of input does not cause a change in outputs in the same amount. The inputs used in this study are the size of the land, number of employees, number of deliveries, total costs. The output used in this study is a number of customers and number of sales. The results of relative efficiency analysis represent that four retails have been operating relatively efficiently in period one and period two, namely retail 1, 2, 3, and 4, while retail 5 is relatively inefficient. Then, in period three, the number of retailers relatively efficiently is decreased to two retailers, namely retail 2 and 4, while retail 1, 3, and 5, were relatively inefficient. Input factor that dominant contributes to the level of efficiency spare part retail, namely the size of land, number of deliveries, and total costs

Evaluating The Performance Of Animal Shelters: An Application Of Data Envelopment Analysis

The focus of this thesis is the application of data envelopment analysis to understand and evaluate the performance of diverse animal welfare organizations across the United States. The results include identification of the most efficient animal welfare organizations, at least among those that post statistics on their operations, and a discussion of various partnerships that may improve the performance of the more inefficient organizations. The Humane Society of the United States estimates that there are 4000 - 6000 independently-run animal shelters across the United States, with an estimated 6-8 million companion animals entering them each year. Unfortunately, more than half of these animals are euthanized. The methods shared in this research illustrate how data envelopment analysis may help shelters improve these statistics through evaluation and cooperation. Data envelopment analysis (DEA) is based on the principle that the efficiency of an organization depends on its ability to transform its inputs into the desired outputs. The result of a DEA model is a single measure that summarizes the relative efficiency of each decision making unit (DMU) when compared with similar organizations. The DEA linear program defines an efficiency frontier with the most efficient animal shelters that are put into the model that envelops the other DMUs. Individual efficiency scores are calculated by determining how close each DMU is to reaching the frontier. The results shared in this research focus on the performance of 15 animal shelters. Lack of standardized data regarding individual animal shelter performance limited the ability to review a larger number of shelters and provide more robust results. Various programs are in place within the United States to improve the collection and availability of individual shelter performance. Specifically, the Asilomar Accords provide a strong framework for doing this and could significantly reduce euthanasia of companion animals if more shelters would adopt the practice of collecting and reporting their data in this format. It is demonstrated in this research that combining performance data with financial data within the data envelopment analysis technique can be powerful in helping shelters identify how to better deliver results. The addition of data from other organizations will make the results even more robust and useful for each shelter involved

Nigerian Banks' Efficiency Performance- A post 2004 Banking Reforms Evaluation

This study investigated the Nigerian Banks’ Efficiency Performance. The period studied was 2005-2009.In addition to the above, the extent of the effect of the bank’s fixed assets, operating expenses and total deposit on their efficiency was investigated. The effect of the bank’s efficiency on their profitability was also examined. In recent years emphasis is now on using frontier analysis methods in measuring bank efficiency instead of using financial ratios .In frontier analysis, the institutions that perform better relative to a particular standard are separated from those that perform poorly. Such separation is done either by applying a parametric or non parametric frontier analysis to firms within the financial services industry.This study employed the Non parametric Data Envelopment Analysis (DEA)under the assumptions of Constant return to scale (CRS),Variable Return to Scale (VRS) and Scale Efficiency(SE) to estimate the efficiency scores of the banks .A bank with a score of 1 is efficient, while a score below 1 means the bank is inefficient. The tests of the four hypotheses were carried out using Vector autoregressive Analysis (VAR). The findings of the study revealed that GTB was the most efficient bank and it has the least reduction in inputs (4.93%) needed to produce the same amount of output. Moreover it remained efficient throughout the years 2006-2009.Overall, the worst performers are Unity bank, Afribank and UBA. Also the banks did not achieve full efficiency under the CRS, VRS and SE in any of the five years. The findings on the hypothesis tested revealed that fixed assets have a negative relationship with efficiency, operating expenses has no long run relationship with the efficiency variable and total deposit does not affect efficiency. Lastly, efficiency has a positive significant relationship with profitability. This study therefore recommend that the banks that are not efficient should study the operations of GTB the best performer to see if could be adopted to improve their efficiency and the banks should moderate their use of inputs as they could have used fewer amount of inputs to achieve the same level of output. Finally, the acquisition of fixed assets should be reasonable. This is to prevent it from reaching a point where it will impact negatively on the bank’s efficiency

Polyhedral attributes of production possibility sets in data envelopment analysis, with applications to sensitivity analysis and cross-evaluation methodologies

In this thesis we study some critical problems in the area of Data Envelopment Analysis (DEA) within the unifying framework of polyhedral characteristics of the production possibility sets and efficiency frontiers of important DEA models. Recent developments in DEA have made it possible to identify the efficient frontier explicitly. This thesis builds on these developments to make the following contributions. We establish theoretical results on the efficiency classifications of surfaces of the boundaries of the production possibility sets. These systematise existing research in the field and fill in many gaps. Our main results provide necessary and sufficient conditions for characterising fully-dimensional efficient surfaces. In addition, the new theoretical framework leads us to discover and address inconsistencies in the related literature. Next we study the sensitivity of efficiency classifications of Decision Making Units (DMUs) to data perturbations. In contrast to existing approaches, we study the effects of arbitrary data perturbations on the efficiency classifications of all DMUs. Theoretical constructs based on the polyhedral nature of production possibility sets lead to identifying a Conditional Stability Region for each DMU within which its data can be perturbed without affecting the efficiency classification of any other DMU. Finally, we develop a new methodology for cross-evaluation in DEA which replaces the traditional approach of peer evaluation by evaluating DMUs across all possible weights obtained from our explicit identification of the DEA production possibility set. The new approach eliminates some major flaws and weaknesses of the traditional approach and produces more meaningful results. Moreover, a set of extensions to the new approach lead to tools that allow identification of DMUs with unrealistic efficiency scores as well as the identification of under-achieving DMUs, a concept that is introduced here