مطالب

BACKGROUND: The present study was conducted with the aim to evaluate the performance of the applied science centers of the Iranian Red Crescent Society (IRCS) in crisis management. METHODS: In this descriptive-survey study, 167 out of 295 managers and experts of the applied science centers of the IRCS were selected on the basis of the Cochran formula. To examine the study variables, a questionnaire including 37 items and 2 parts evaluating performance and crisis management was employed. The financial, customer, internal processes, and growth and learning performances were measured in the performance assessment section, and the 6 dimensions of flexibility, inclusion, trust, risk perception, fairness, and consistency were measured in the crisis management part. The reliability, content validity, and construct validity of the questionnaires were confirmed by Cronbach’s alpha coefficient, a group of university professo BACKGROUND: The present study was conducted with the aim to evaluate the performance of the applied science centers of the Iranian Red Crescent Society (IRCS) in crisis management. METHODS: In this descriptive-survey study, 167 out of 295 managers and experts of the applied science centers of the IRCS were selected on the basis of the Cochran formula. To examine the study variables, a questionnaire including 37 items and 2 parts evaluating performance and crisis management was employed. The financial, customer, internal processes, and growth and learning performances were measured in the performance assessment section, and the 6 dimensions of flexibility, inclusion, trust, risk perception, fairness, and consistency were measured in the crisis management part. The reliability, content validity, and construct validity of the questionnaires were confirmed by Cronbach’s alpha coefficient, a group of university professors, and confirmatory factor analysis (CFA), respectively. Then, inferential statistical methods such as the Kolmogorov-Smirnov (K-S) test were used to ensure the normal distribution of data, and the structural equation model, Pearson correlation test, chi-square test, two-sample t-test, and one-sample t-test were used in the LISREL and SPSS software to test the hypotheses. RESULTS: The performance of the applied science centers of the IRCS in crisis management was higher than the average level based on the balanced scorecard (BSC) model. In addition, in terms of the 4 characteristics of financial performance, customer performance, internal process performance, and growth and learning performance, the crisis management performance of this organization was at a desirable level. CONCLUSION: It seems that policymakers, while maintaining the current situation, should plan for the development of crisis management, as well as for providing the ground for continuous improvement and better performance in this area. rs, and confirmatory factor analysis (CFA), respectively. Then, inferential statistical methods such as the Kolmogorov-Smirnov (K-S) test were used to ensure the normal distribution of data, and the structural equation model, Pearson correlation test, chi-square test, two-sample t-test, and one-sample t-test were used in the LISREL and SPSS software to test the hypotheses. RESULTS: The performance of the applied science centers of the IRCS in crisis management was higher than the average level based on the balanced scorecard (BSC) model. In addition, in terms of the 4 characteristics of financial performance, customer performance, internal process performance, and growth and learning performance, the crisis management performance of this organization was at a desirable level. CONCLUSION: It seems that policymakers, while maintaining the current situation, should plan for the development of crisis management, as well as for providing the ground for continuous improvement and better performance in this area.

Introduction: Because of the vulnerability of human settlements to natural disasters and damage caused by them, the study of the resilience of settlements has become critical in planning urban areas. The purpose of this paper is to evaluate resiliency of Baghershahr, a town with a population of 65000, locates in 4 km from Tehran city, against earthquake. Methods: The research data were collected by survey method (questionnaire tool) and also by using statistical documents and documentary reports. AHP technique has been used to determine the coefficient of importance of indicators and descriptive statistics methods have been used in data analysis. Findings: The study area has, on average, only 36.6% of the ideal conditions of resiliency. The figure in institutional dimension was 25.5%, indicating that this dimension has lowest resilience compared with other dimensions. After this, the physical dimension has a figure of 31.7%. In case of economic dimension, the figure was 40.5% of the ideal rate of resiliency and the highest level belongs to the social dimension, which was 45.4%. Conclusion: The studied area is an example of Iranian settlements with very low resiliency. On one hand, low level of the resiliency of Baghershahr is due to the threats caused from its vicinity to the oil and gas refinery complex, the thermal power plant, the sulfur industry, and the numerous plastic recycling workshops, the huge stores of petroleum products, gas and crude oil and crude oil pipelines. On the other hand, it is due to sudden formation and uncontrolled rapid growth of the town which has been accompanied by widespread migration of low-income classes over the past few decades.

BACKGROUND: Rural areas, usually when compared to other natural events, have the greatest vulnerability of human settlements. The aim of this study was to evaluate natural hazards as earthquakes, landslides, floods and identify high-risk zone in relation to the rural areas of the central township of Azna County, Iran. METHODS: Topographic and geology maps, elevation digital model, and seismic and meteorological data along with field studies to investigate the location of villages in terms of natural hazards of earthquakes, landslides, and flood were used. Then, effective factors were identified in each of the hazards, and grouped in separate layers. The Arc GIS software was used to develop and integrate maps; AHP model and paired comparison method were used to weight effective factors in expecting any of the natural hazards, and to compare the criteria one by one; fuzzy logic model was used to standardize the layers in Arc GIS software; and the overlay model index was used to integrate final layers of natural hazards and determine high-risk zones. RESULTS: 49 percent of villages in privacy due to the major and minor faults were in the zone of high earthquake risk. The risk of landslides in areas where rural areas were based, due to the low gradient very low and only 10% of the villages are at risk of landslides. 14% of the villages in the privacy due to the major rivers, flood risk and the risk of flooding is very high. Prioritization of rural areas in terms of natural hazards by using AHP model shows that the 8 villages were located in high-risk areas. CONCLUSION: Providing maps of potential natural hazards can be helpful in crisis management and identification of the high-risk settlements.