Data envelopment analysis is a method for evaluating the relative efficiency of a collection of decision making units. The DEA classic models calculate each unit’s efficiency in the best condition, meaning that finds a weight that the DMU is at its maximum efficiency. In this paper, utilizing the directional distance function model in the presence of undesirable outputs, the efficiency of each ...

one of the important issues in data envelopment analysis (dea) is sensitivity analysis. heretofore the existent studies have considered the data modification of inputs and outputs in one or multiple dmus. in this paper the number of dmus is increased and a stability region is obtained in  by applying defining hyperplanes in which if the added dmu (only one dmu) is in this region then all of the...

the problem of utilizing undesirable (bad) outputs in dea models often need replacing the assumption of free disposability of outputs by weak disposability of outputs. the kuosmanen technology is the only correct representation of the fully convex technology exhibiting weak disposability of bad and good outputs. also, there are some specific features of non-radial data envelopment analysis (dea...

This study began with an observation of the financial performance banks in assessing efficiency commercial Indonesia 2016 period and found inefficiency problems BUKU I based on values (BOPO) as indicator bank efficiency. is analysis measurement using quantitative secondary data obtained from balance sheet income statement for each sample (DMU) - 2017 a math-ematical model (linear program) Non-P...

in recent years, virtual communities have been significantly popular and almost all of them are targeted for business profitability. in our study, the profitability of these communities for businesses has been analyzed from a commercial perspective. the study considers virtual community as a business model which can have a great impact on consumer purchase decision process. with respect to refe...

This paper proposes a new method based on the ideal input vector to estimate inputs of a given decision making unit (DMU) when some or all of its outputs are increased to maintain its current efficiency level. In other words, this paper studied the following question: How much would be the increase in the inputs of the DMU if the decision maker increases certain outputs to a particular unit in ...

The traditional model upgrading paradigm for retrieval requires recomputing all gallery embeddings before deploying the new (dubbed as "backfilling"), which is quite expensive and time-consuming considering billions of instances in industrial applications. BCT presents first step towards backward-compatible upgrades to get rid backfilling. It workable but leaves a dilemma between feature discri...