Mixed input and output orientations of Data Envelopment Analysis with Linear Fractional Programming and Least Distance Measures

Dar, Qaiser Farooq; Padi, Tirupathi Rao; Tali, Arif Muhammad

doi:10.19139/soic.v4i4.225

Cited by 5 publications

(6 citation statements)

References 8 publications

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“…Y1 (order picking cycle time) and Y2 are the output variables (order prepared for shipment per man-hour). The CRS Primal model was utilized as the DEA model to determine the relative efficiency of each DMU [21,22]. The variable calculation for each DMU is illustrated in the mathematical models below:…”

Section: Resultsmentioning

confidence: 99%

Improving Efficiency for Retail Warehouse Using Data Envelopment Analysis

Kusrini¹,

Prakoso²,

Hidayatuloh³

2022

MMEP

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Warehouse has an important role in supply chain management and has many complex activities that require special attention. This study aims to improve warehouse efficiency performance. Data Envelopment Analysis (DEA) method is employed to obtain the level of efficiency and benchmarking on five indicators, namely financial, productivity, utilization, quality, and cycle time along with five business processes in warehousing, i.e. receiving, put away, storage, order picking, and shipping. The decision making unit is a warehouse in four retailers in Yogyakarta province, in Indonesia. The input and output variables are selected based on the highest priority weight using the Analytical Hierarchy Process (AHP). The most important variable for receiving is productivity (receipt per man-hour), variable for put away is cycle time (put away cycle time), variable for storage is utilization (% location and cube occupied), variable for order picking is cycle time (order picking cycle time) and variable for shipping is productivity (order prepared for shipment per man-hour). The research results show that the benchmarking model with DEA can be used to increase warehouse efficiency performance by up to 22% by increasing receiving and shipping productivity, increasing storage utilization and reducing cycle time at put away and order picking.

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Section: Resultsmentioning

confidence: 99%

Improving Efficiency for Retail Warehouse Using Data Envelopment Analysis

Kusrini¹,

Prakoso²,

Hidayatuloh³

2022

MMEP

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“…In order to overcome such critiques, many types of research have sought the DEA to construct HDI, which is an optimization technique that evaluates the efficiency of DMUs through multiple outputs and multiple inputs on the weighted input and output ratios' strength (Dar et al, 2016). However, missing data is a continuing challenge in DEA applications, mostly, to insufficient coverage of significant input and/or output variables, or failure of DMUs to report needed statistics (Kuosmanen, 2014).…”

Section: Discussionmentioning

confidence: 99%

“…• yin is DMUn ' s i th output and wi is its corresponding weight, where i = 1,2,…, I output • xjn is DMUn ' s j th input and vj is its corresponding weight, where j = 1,2,…, J inputs and • wi and vj are the decision variables for this model This model is an optimization technique that evaluates the efficiency of DMUs through a set of inputs and sets of outputs on the weighted input and output ratio strength, whereas the DEA frontier is obtained through linear fractional programming (Dar et al, 2016). In general, DEA has assisted in creating CIs; as it doesn't require weights that are previously agreed upon or weights that are uniquely set.…”

Section: Composite Indicators Through Data Envelopment Analysismentioning

confidence: 99%

Modified Human Development Index using Data Envelopment Analysis Approach

Salama¹,

Hamed²,

Rashwan³

2022

Journal of Mathematics and Statistics

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Composite Indicator is considered the mathematical aggregation which has wide usage for monitoring performances, conducting benchmarks, analyzing policies, and communicating publicly. Human Development Index (HDI) is the most popular index which measures human development through average achievement in its main dimensions: Health status, education status, and living standard but it is faced with several critiques, positive and negative. Moreover, HDI was tested to have a positive and significant correlation with natural resource abundance. Therefore, based on Mathematical Programming approaches, previously tested for Composite Indicators' development, this research proposes a new calculated HDI using a Data Envelopment Analysis approach based on the Goal Programming model; including missing values' estimation. This new proposed HDI was validated through Sensitivity Analysis of Normalization and Weighting methods; in addition to Wilcoxon Signed Rank Test. The first test shows a positive high correlation between the proposed HDIs and the United Nations HDI. Those tests ensure that HDI rankings are highly correlated and that they are unchanged given the different normalization and weighting techniques. Moreover, they reflect that the paired sample mean is not the same. This highlights the advantageous property of the proposed HDI; preserving both the advantages of Goal Programming and Data Envelopment Analysis approaches, in addition to others.

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“…The CCR and BBC model of DEA are categorized as radial measure efficiency because both are dealing directly with the inputs and outputs of a DUM [22]. These models can solve by using either input orientation at a fixed level of output or output orientation at a fixed level of input or mixed-orientation varying both input and outputs at an optimal level [23]. A non-oriented and non-radial measure of efficiency was proposed by [24], which is not dealing with the inputs and outputs of DMU directly but dealing with input excesses and output shortfall called slack based measure (SBM) of efficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of International Trade on Central Bank Efficiency: An Application of DEA and Tobit Regression Analysis

Dar

Ahn

Dar³

2021

Stat., optim. inf. comput.

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The purpose of this study is to introduce a novel methodology to measure the central bank efficiency. The data envelopment analysis (DEA) applies in the combination of three input and two output variables characterizing the economic balance in international trade. Super-efficiency DEA model is applied for ranking & comparing the efficiency of different central banks. In contrast, the Malmquist productivity index (MPI) is used to measure the productivity change over the period of time. Further, the study is extended to quantify the impact of international trade dimension on the efficiency of the central bank by using Tobit regression analysis. Finally, based on our data analysis, we reported that the efficiency changes over the period of time and the total productivity changes significantly due to the technology shift as compared to efficiency change. Additionally, it is also observed that the central bank efficiency is impacted dramatically by the export level of the country as compared to import level, average exchange rate and GDP. It implies that the export level of the country significantly influences the performances of the central bank.

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Mixed input and output orientations of Data Envelopment Analysis with Linear Fractional Programming and Least Distance Measures

Cited by 5 publications

References 8 publications

Improving Efficiency for Retail Warehouse Using Data Envelopment Analysis

Improving Efficiency for Retail Warehouse Using Data Envelopment Analysis

Modified Human Development Index using Data Envelopment Analysis Approach

The Impact of International Trade on Central Bank Efficiency: An Application of DEA and Tobit Regression Analysis

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