مقاله انگلیسی رایگان در مورد ارزيابي بهره وری حد واسط در تحليل پوششي داده ها بر اساس نظريه چشم انداز – الزویر ۲۰۱۹
مشخصات مقاله | |
ترجمه عنوان مقاله | ارزيابي بهره وری حد واسط در تحليل پوششي داده ها بر اساس نظريه چشم انداز |
عنوان انگلیسی مقاله | Cross-efficiency evaluation in data envelopment analysis based on prospect theory |
انتشار | مقاله سال ۲۰۱۹ |
تعداد صفحات مقاله انگلیسی | ۲۹ صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس میباشد |
نمایه (index) | Scopus – Master Journal List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
۳٫۶۳۲ در سال ۲۰۱۷ |
شاخص H_index | ۲۱۱ در سال ۲۰۱۹ |
شاخص SJR | ۲٫۴۳۷ در سال ۲۰۱۷ |
شناسه ISSN | ۰۳۷۷-۲۲۱۷ |
شاخص Quartile (چارک) | Q1 در سال ۲۰۱۷ |
رشته های مرتبط | مهندسی صنایع |
گرایش های مرتبط | برنامه ریزی و تحلیل سیستم ها |
نوع ارائه مقاله |
ژورنال |
مجله | مجله اروپایی تحقیق در عملیات – European Journal of Operational Research |
دانشگاه | Institutes of Science and Development – Chinese Academy of Sciences – China |
کلمات کلیدی | تحلیل پوششی داده ها، راندمان متقابل، نظریه چشم انداز، نگرش ریسک |
کلمات کلیدی انگلیسی | Data envelopment analysis، cross-efficiency، prospect theory، risk attitude |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.ejor.2018.07.046 |
کد محصول | E10788 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract
۱- Introduction ۲- Cross-efficiency evaluation ۳- Prospect theory ۴- Prospect cross-efficiency model for cross-efficiency evaluation ۵- An illustrative example ۶- Conclusions and discussions References |
بخشی از متن مقاله: |
Abstract Cross-efficiency evaluation in data envelopment analysis (DEA) is a useful tool in evaluating the performance of decision-making units (DMUs). It is generally assumed that decision makers (DMs) are completely rational in common cross-efficiency evaluation models, which fail to consider the DM’s risk attitude that plays an important role in the evaluation process. To fill this gap, we investigate the cross-efficiency evaluation in DEA based on prospect theory. First, we introduce a prospect value of the DMU to capture the non-rational psychological aspects of a DM under risk. Second, based on the prospect value, we propose a new cross-efficiency model termed the prospect cross-efficiency (PCE) model. Particularly, some existing cross-efficiency evaluation models can be deemed as the special cases of the PCE model with suitable adjustments of the parameters. Furthermore, this paper provides an empirical example to evaluate cross-efficiency with several selected universities directly managed by the Ministry of Education of China to illustrate the effectiveness of the PCE model in ranking DMUs. Introduction Cross-efficiency evaluation, developed by Sexton, Silkman, and Hogan (1986), has been widely accepted as a discriminative assessment tool for data envelopment analysis (DEA). It is generally used for distinguishing efficient decision-making units (DMUs) from one another (Despotis, 2002). Each DMU in cross-efficiency evaluation has a self-evaluated efficiency derived by its own set of optimal weights and n ۱ peer-evaluated efficiencies obtained by the optimal weights of other DMUs. Consequently, a final efficiency for ranking DMUs is aggregated based on n efficiencies. The major characteristics of cross-efficiency evaluation are the following: (1) ranking the DMUs in a unique order (Doyle & Green, 1995), (2) eliminating unrealistic weight schemes without predetermining any weight restrictions (Anderson, Hollingsworth, & Inman, 2002), and (3) effectively differentiating between good and poor performers among the DMUs (Boussofiane, Dyson, & Thanassoulis, 1991). Due to these advantages, cross-efficiency evaluation has been used in a variety of applications, including project ranking (Green, Doyle, & Cook, 1996), the measurement of the labour assignment in a cellular manufacturing system (Ertay & Ruan, 2005), sports rankings (Wu, Liang, & Chen, 2009), corporate philanthropic selection (Partovi, 2011), the supplier selection problem in public procurement (Falagario, Sciancalepore, Costantino, & Pietroforte, 2012), and portfolio selection (Lim, Oh, & Zhu, 2014; Mashayekhi & Omrani, 2016). Despite the many advantages and wide applications of cross-efficiency, its usefulness is possibly reduced by the non-uniqueness of the optimal weights (Doyle & Green, 1994). Specifically, the possible existence of multiple optimal weights in the evaluation leads to different sets of cross-efficiency scores for each DMU. |