درخت حوزه‌های تخصصی

INTRODUCTION: An earthquake is a major natural disaster with widespread and great effects on human life and nature. Taking care of the basic needs of earthquake victims is an essential step that should be addressed immediately. Moreover, the evaluation of various problems after disasters, especially earthquakes, is of crucial importance for the affected people. The management of humanitarian aid and public assistance among these affected people is considered one of the most important post-earthquake concerns. Therefore, the present study was conducted to evaluate the post-earthquake challenges and strengths of providing humanitarian aid services in Sisakht, Yasuj, in February 2019. METHODS: This qualitative case study was conducted from March 2019 to July 2020. The studied population consisted of 20 participants including medical staff (n=10), clergy (n=2), crisis managers (n=4), and military personnel (n=4). The required data were collected through observation and semi-structured interviews, which continued until data saturation. To evaluate the reliability of the data, the strategies recommended by Guba were used. The data were analyzed by conventional content analysis based on the method proposed by Graneheim and Lundman. FINDINGS: The advantages and strengths of this study included humanitarian cooperation and coordination, as well as the timely presence of relief and rescue teams and law enforcement agencies from the post-earthquake first hours, which had a great impact on reducing the suffering of people. The challenges in providing post-earthquake services included health, medical, management, geographical, and spatial concerns and issues related to the earthquake victims (relief goods distribution problem and inappropriate information dissemination as the main challenges). CONCLUSION: Effective and appropriate management policies regarding the management of providing post-earthquake services and elimination of the structural and managerial obstacles can improve the operation and management of humanitarian aid.

Many studies have been conducted in the field of bankruptcy prediction; But in most of them only financial ratios are used. However, in Iran, many non-financial factors affect bankruptcy. The main purpose of this study is to develop a mathematical model in which financial and non-financial indicators such as management and economics factors are used to predict bankruptcy. In this study, 44 variables that had the greatest impact on bankruptcy forecast were selected and with confirmatory factor analysis, a questionnaire was developed and sent to experts in the fields of management, accounting and economics to rank the impact of these variables. The statistical sample of the study includes 200 bankrupt and non-bankrupt companies listed in the period 2009-2018. After collecting the questionnaires using the OLS regression estimation method, the variables that had a factor load of less than 0.5 were eliminated and in the final model 9 main variables. The research model identified 95% of bankrupt companies and 93% of non-bankrupt companies with 95.4% confidence. Then, for verification, two hypotheses were developed and the model of this research was compared with two existing models. The ability to distinguish bankrupt companies from non-bankrupt ones by our proposed model was 6% more accurate than the Pourheidari et al. model, and 9.4% more accurate than Altman’s model.

Automotive industry particularly, commercial automotive industry, ranks as a key industry in the economic growth. The necessity of investigating the research & development(R & D) activities of digital marketing and innovation in the form of a dynamic system in automotive industry based on the 3 variables: empowerment of supply network, of product innovation, and of digital marketing is quite undisputed. The present research has been done with a view to identifying and evaluating the cause-and-effect interdependent relations governing the variables of R & D of digital marketing and innovation in commercial automotive industry. The research is typically applied, and has been done using the descriptive-survey method. The research community consisted of 50 experts; all with acceptable academic backgrounds and years of experience as executive managers and marketeers in the R & D of automotive industry. To analyze the data, the views of some elected experts on automotive industry, along with Delphi fuzzy and Dematel method were applied. Our findings showed that the variable “Intensity of R & D of digital marketing and innovation” has the most effect on the other variables. The variable “Empowerment of supply network” with the score of 3,25 has the largest amount of interaction with the other variables. Also, the variable “ Empowerment of R & D in digital marketing and innovation” with the score of 1,08 has the smallest amount of interaction with the other variables.