this paper introduces discretionary imprecise data in data envelopment analysis (dea) and discusses the efficiency evaluation of decision making units (dmus) with non-discretionary imprecise data. then, suggests a method for evaluation the efficiency of dmus with non-discretionary imprecise data. when some inputs and outputs are imprecise and non-discretionary, the dea model becomes non-linear ...

Nowadays, with respect to knowledge growth about enterprise sustainability, sustainable supplier selection is considered a vital factor in sustainable supply chain management. On the other hand, usually in real problems, the data are imprecise. One method that is helpful for the evaluation and selection of the sustainable supplier and has the ability to use a variety of data types is data envel...

The performance assessment of supply chains including sustainability dimensions of economic, environmental and social is a significant aspect for managers and decision makers. Furthermore, imprecise data are presented in many real world applications. Therefore, the current paper proposes an approach based on data envelopment analysis (DEA) to analyze the revenue efficiency of sustainable supply...

recently, farzipoor saen [journal of the operational research society, 60(11), 1575–1582 (2009)] proposed a method based on data envelopment analysis to identify optimistic efficient suppliers in the presence of nondiscretionary factors-imprecise data. this short communication aims at showing a computational error in computing the value of preference intensity parameter in farzipoor saen’s [1] ...

spurred by intensifying competition in global markets, most companies have been increasingly implementing supply chain management (scm) and information systems (is) practices. as well, globalization policies have created a more intensive competition amongst manufacturers; in additional the priority of supply over demand, market competition and importance of some factor such as quality, accounta...

This paper introduces discretionary imprecise data in Data Envelopment Analysis (DEA) and discusses the efficiency evaluation of Decision Making Units (DMUs) with non-discretionary imprecise data. Then, suggests a method for evaluation the efficiency of DMUs with non-discretionary imprecise data. When some inputs and outputs are imprecise and non-discretionary, the DEA model becomes non-linear ...

Technology-based sustainability enhancement is a key approach for industrial sustainability realization. However, identification of effective technologies for any industrial system could be very challenging. If the available data and information about the industrial system and technologies are incomplete, imprecise, and uncertain, then technology identification could be very difficult. In this ...

data envelopment analysis (dea) is a widely recognized approach for evaluating the efficiencies of decision making units (dmus). because of easy and successful application and case studies, dea has gained much attention and widespread use by business and academy researchers. the conventional dea models (e.g. bcc and ccr) make an assumption that input and output data are exact values on a ratio ...

In the environment of business‐to‐business e‐commerce, Buyers and sellers in mature industrial markets can turn single transactions into long-term beneficial relationships by a deeper understanding of the complex connection between the two and buyers and sellers are uncertain about their roles. A “must-do” for the sellers, in particular, is to understand patterns of investment and reward,...

data envelopment analysis (dea) is a method for measuring the relative efficiencies of a set of decision-making units (dmus) that use multiple inputs to produce multiple outputs. in this paper, we study the measurement of dmu performances in dea in situations where input and/or output values are given as imprecise data. by imprecise data we mean situations where we only know that the actual val...