Designing a social responsibility assessment model with a network data envelopment analysis approach (Case study: public hospitals in Yazd province)
Article Type:
Case Study (دارای رتبه معتبر)

The returning of a patient to a health facility to get new services plays a significant role in creating brand identity which is a major factor of success for such an organization. On this basis, this study intends to evaluate the performance of state hospitals applying network data envelopment analysis.


Regarding the purpose, this article was applied and used descriptive-survey method. Data were gathered through assessing the organizational documentation as well as the viewpoints of experts and managers who were active in health areas. Data analysis was operated by using two-phased envelopment analysis and input-based network. Then, efficient and non-efficient hospitals were identified and eventually, data sensibility was analyzed considering the results of data envelopment analysis.


The results of input-based network data envelopment analysis show that none of the hospitals were efficient in phase 1 but in phase 2, merely 2 out of 13 hospitals were efficient. Additionally, in processes 1, 2, 3 and 4, only 2, 5, 1 and 4 hospitals were efficient respectively. Therefore, only 30% of the hospitals under study are efficient in phase 2. After examining the efficiency in the first and second phases and that of the network, the hospitals are ranked in a descending order (from the most to the least efficient).


Many theoretical and experimental researches have so far been conducted in order to reach a mathematical model of performance evaluation for hospitals. However, none has ever dealt with the social responsibility component of these health facilities. In this respect, the present research has not only introduced a model for performance evaluation and development of social responsibility, but also implemented the model in Yazd public hospitals as an example.

Journal of Management and Development Process, Volume:35 Issue: 3, 2022
221 to 259  
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