سخنران های کلیدی

 | تاریخ ارسال: ۱۳۹۷/۳/۳۰ | 

Title: How Harmless is Convexification for Nonparametric Cost Function Estimates?
Kristiaan Kerstens & Ignace Van de Woestyne

Prof. Kristiaan Kerstens
CNRS-LEM (UMR 9221)
IESEG School of Management

Email: K.kerstens@ieseg.fr



 

Abstract: This contribution focuses on testing the empirical impact of the convexity assumption in estimating costs using nonparametric specifications of technology and cost functions. Apart from reviewing the scant available evidence, the empirical results based on two publicly available data sets reveal the effect of the convexity axiom on cost function estimates: cost estimates based on convex technologies turn out to be on average between 21% and 38% lower than those computed on nonconvex technologies. These differences are statistically significant when comparing kernel densities and can be illustrated using sections of the cost function estimates along some output dimension. Finally, also the characterization of returns to scale and economies of scale using production and cost functions for individual units yields conflicting results for between 19% and 31% of individual observations. The theoretical known potential impact as well as these empirical results should make us reconsider convexity in empirical production analysis: clearly, convexity is not harmless.


Title : Planning and Budgeting (Applications of Decision Making Models in Planning and Budgeting for Executive Managers)

Dr. Mohammad Khodabakhshi   
Associate Professor in Operations Research  
Department of Mathematics
Shahid Beheshti University, Tehran, Iran
Email: 
mkhbakhshi@yahoo.com
 

Title : A Survey on Models and Methods for Solving Fuzzy Data Envelopment Analysis

Dr. Ali Ebrahimnejad   
Associate Professor  in Operations Research  
Department of Mathematics, Islamic Azad University, Qaemshahr, Iran


 

Abstract: 

There is an extensive literature in data envelopment analysis (DEA) aimed at evaluating the relative efficiency of a set of decision-making units (DMUs). Conventional DEA models use definite and precise data while real-life problems often consist of some ambiguous and vague information, such as linguistic terms. Fuzzy sets theory can be effectively used to handle data ambiguity and vagueness in DEA problems. In this contribution a taxonomy and review of the fuzzy DEA (FDEA) methods are provided. The solution approaches are divided into several groups. A mathematical description of each approach is provided and followed by a brief review of the most widely cited literature relevant to each approach. The main advantages and disadvantages of each approach are discussed. In addition to existing approaches, a new category to group the pioneering papers that do not fall into any of the existing classifications is introduced.



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دانشکدۀ علوم ریاضی و کامپیوتر

تاریخ های مهم

  • فراخوان اول: ۲۰-۱۲-۹۶
  • مهلت ارسال مقالۀ: ۲۵-۰۳-۹۷
  • ​تمدید مهلت ارسال مقاله: 31-۰4-۹۷
  • اعلام نتایج داوری مقالات: 20-۰5-۹۷
  • مهلت ثبت‌نام: 25-۰5-۹۷
  • تمدید مهلت ثبت نام: 31-05-97
  • مهلت ثبت‌نام با تأخیر (با هزینۀ اضافی): ۹۷-06-05
  • تاریخ برگزاری: ۱۴ و ۱۵ شهریور  ۱۳۹۷

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