نشریه مدیریت بحران
سال یازدهم شماره 2 (پیاپی 22، پاییز و زمستان 1401)

One of the ways to reduce disasters facing a society is to invest in promoting national resilience. The aim of this study was to design a model of collective resilience in global crises. The present study was a qualitative study that was conducted by data foundation method. Participants in this study included 16 experts in the field of management and public health who were selected by purposive sampling. Data collection method was semi-structured interview. Data were analyzed in three stages of open, axial and selective coding. Data validation was performed by the participants using the verification method. Based on the research findings, the central category of the model is national resilience in global crises (improving organizational strength, increasing adaptability and ability to face risk). Causal conditions have two categories (personality traits and collective characteristics). The strategies in question are: (offensive, defensive, review and contingency). Background conditions also include: (ancillary skills and hospitalization conditions of the community). Interventional conditions (economic and political) also affect strategies and ultimately lead to consequences (infrastructure-cultural, social and individual).The resilience approach in global crises such as coronary heart disease ensures our ability to adapt to new and emerging events and to reduce the risk of exposure and to recover quickly from the effects of the events. based on the findings of the present study, health managers in the country as well as all members of society can use this model for collective resilience in the face of global crises.

The purpose of this study is to present a conceptual model using interpretive structural modeling in order to achieve an organizational crisis management model with a human resource management system approach in the Iranian Red Crescent population. The present study is a survey and the method used to present the model and analyze the data is interpretive structural modeling. For this purpose, library study and opinions of experts in the field of crisis management and human resource management have been used. Modeling is done in two stages. In the first stage, 30 indicators were identified in library studies and in 3 stages, using Delphi method with the opinions of 15 experts consisting of population managers and experts in the field of human resources, 3 indicators were removed and 27 indicators were finalized. From a questionnaire with the opinions of 13 university professors in the field of management of the organization; Structural self-interaction matrices, initial achievement and final achievement matrices were extracted. The results show that in the stage of determining the level, 27 indicators are located in five levels and by categorizing the criteria using motivational power and dependence; Key, dependent and link variables are represented using the MICMAC method.

A crisis is an accident occurs suddenly as a result of natural and human events and actions and causes hardship and damage to a human community or society, and eliminating it requires emergency and extraordinary actions and operations and depends on identifying the crisis and raising awareness at the right time. In this context, the best and most effective way to attract social collaboration is through a new combination of different ideas and forms of cooperation and creating an entirely new approach to a social issue called social innovation. This study seeks to identify the dimensions of social innovation based on public participation in the event of the COVID-19 crisis. This research has practical objectives in which the grounded theory strategy has been used qualitatively. In this study, experts from the statistical community were selected from the Ministry of Health and Medical Education. Exploratory analysis method has also been used to identify the effective factors in social innovation. Based on the analysis of research data, the categories including: effectiveness of public participation, investment to attract participation, management ability, networking ability, general policymaking ability, necessary cultural and educational infrastructure, the existence of capable legal organizations to solve executive problems, facilitate Coordination, control, containment and mitigation of the effects of the crisis were identified as the eight main factors in social innovation based on the public participation and the government. The COVID-19 pandemic proved that government institutions and the structure of the health system in all countries were insufficient to respond to such a widespread crisis. The results of this study enable policymakers to have a model for social innovation in order to maintain and ensure the health of society, especially in times of crisis, by attracting public participation.

The importance of supply chain management in health is not hidden from anyone. Therefore, medical centers and hospitals in times of natural disasters and crises, if located correctly, can further control the loss of life. The purpose of this study is to configure the sustainable supply chain of the health care sector to determine the appropriate routing of medical facilities. This study uses a three-level mathematical model including suppliers, medical centers and demand points (areas of Tehran), the conditions of uncertainty in the form of different scenarios by optimization method in which medical service centers in Different scenarios are disrupted. The application of this model was investigated by a case study taken from the data of Tehran Emergency Center. Numerical results indicate the correctness and logic of the results of the mathematical model. In this case, this model can be studied and compared for different networks under disruption. Finally, the results of the implementation of the model and experiments of analysis of facility routing sensitivities along with demand points and its limitations are presented.

Having the ability to choose a marketing strategy, use economic information and understand ways to increase the competitiveness of small and medium enterprises is vital. Therefore, the purpose of this research is to investigate the position of marketing based on social media in SMEs of Lorestan province under the conditions of the Corona crisis from the point of view of their managers and owners. This research is based on the applied goal and based on the descriptive-correlation method. The size of the statistical population was estimated using Cochran's formula of 197 managers and owners of SMEs in Lorestan province. A closed questionnaire was used to collect information. In order to check the content validity of the questionnaire according to the professors of the entrepreneurship department of Ilam University and to measure the reliability, Cronbach's alpha coefficient was used, the average of which was 0.85 for the study variables and indicates the reliability of the research tool. In order to analyze the data, community mean comparison tests (one-group t), Pearson correlation, multiple regression, simple linear regression and regression path analysis were used. According to the findings, the mean variable of the intention to use social media based marketing in the conditions of the corona crisis was calculated to be 3.75 and above the average, as well as the variables of motivation to use social media based marketing, the skill of using the media. Social factors in the direction of marketing and understanding the usefulness of social media based marketing explained 32% of the changes in the intention to use social media based marketing in the conditions of the Corona crisis, in addition to the intention to use social media based marketing as well. It had a significant relationship with the amount of marketing based on social media.

The events that occur suddenly as a result of natural and human actions and impose hardship on society are called Disasters. In recent years, due to changes in the Earth's climate, the number of natural crises, including earthquakes, floods, storms, etc been increasing. Thus, the need for disaster management and planning is felt more than ever. In this research, the aim is to model and solve the problem of locating local warehouses and allocating and controlling the inventory of normal and perishable items in post-crisis conditions. Because in the real world, the demand for affected areas for any reason, such as the severity of damage to areas and people, the possibility of aftershocks with higher intensity and in a short time after the initial earthquake, and the rate of death is not certain. In addition, in most of the conditions, the budget is not clear for the managers and it depends on the severity of the crisis, the support of humanitarian organizations, and public donations. S the budget is uncertain. Therefore, we considered uncertain demand and budget in this research. For this problem, a mixed-integer linear mathematical model has been developed. To solve the problem, GAMS software and the electromagnetic algorithm have been used for small-sized and large-sized problems, respectively. Numerical results on different examples show the efficiency of the proposed algorithm in terms of time and the quality of results.

When a disaster occurs, collecting and sharing disaster information about affected areas is one of the most important activities in order to optimal decision making for relief operations. Also because the infrastructures are destroyed or damaged after a disaster, WSNs and UAVs can be used to receive online data from the affected areas. This results in making a lot of data with high rates of production through social networks as well as mobile phones of affected people in affected areas as well as WSNs and UAVs which indicates the necessity of Big Data. On the other hand cloud computing is a service, independent of device and location where computing can be performed at high speed and this shows the need for cloud computing as well. In other words these two technologies provide real-time data analysis not just for emergency situation identification in the affected areas but also to rescue the affected people. In this paper we try to provide a comprehensive analysis of application of Big Data, Cloud Computing, Wireless Sensor Networks (WSN) and Unmanned Aerial Vehicles (UAV) in relief problems.

Assessing and managing the impact of large-scale epidemics considering only the individual risk and severity of the disease is exceedingly difficult and could be extremely expensive. Economic consequences, infrastructure and service disruption, as well as the recovery speed, are just a few of the many dimensions along which to quantify the effect of an epidemic on society's fabric. Scenarios tell future stories that are likely to occur in the form of stories and provide alternative narratives about situations related to the future development of epidemics. Scenario writing is one of the best and most powerful tools for recognizing and examining the future of science, which can be used to identify and examine future environmental changes and uncertainties In terms of practical purpose, the present research has been done in terms of exploratory method at exploratory level and based on futures research and scenario approach. And reduction policies using effective indicators in the social resilience of Iran's metropolises with the sample case of Ahvaz metropolis with a future approach, provides research on the prevalence of epidemics. Propulsion forces are identified by a specific Delphi method, and then these factors are prioritized based on the degree of importance and uncertainty, and the most critical determinants are used, and Micmac software is used to write possible scenarios. According to the research findings, among these factors, inflation is the most key factor in the social resilience of the metropolis in the face of infectious diseases. Have been calculated.

In this article, the authors try to design a social capital promotion model for the branches of the Social Security Organization of Mazandaran Province during the corona outbreak. The research method is exploratory (qualitative-quantitative). The statistical population in the qualitative section was 30 university professors and executive elites in the field of management and in the quantitative section were 150 elites in the field of social security. In the qualitative part, using the snowball method of dreading theoretical saturation with 16 experts, in-depth interviews were conducted and in the quantitative part, to evaluate the model, a researcher-made questionnaire was distributed among 90 samples by relative cluster sampling method. The validity of the questionnaire was confirmed by the form-content method and its reliability was confirmed by Cronbach's alpha method. Data were analyzed by exploratory and confirmatory factor analysis using SPSS and AMOS software. The corona outbreak period has 18 dimensions as follows: causal variables (organizational transparency, competence, support, and social cohesion), contextual variables (innovative designs, development, and customer relationship management, organizational skills and management), intervention variables (Setting and maintaining policies to overcome constraints, optimal crisis management, efficient manpower and service delivery development), strategic variables (recognizing threats and challenges, innovative strategies, recognizing and financing), and outcome (increasing investment, Intensification of social interaction, deepening social satisfaction, comprehensive development of the organization). The results of the quantitative section showed that all the dimensions of the research model of the research were confirmed.

Awareness of modern developments and dynamics in different disciplines including management can dramatically contribute to the transcendence and prosperity of communities, facilitate facing crises and problems, and help accountability and complicated problem-solving skill. This applied study identified and evaluated the drivers of resilient management of businesses affected by the COVID-19 crisis using a mixed-methods (qualitative-quantitative) design. In the qualitative phase, the components of resilient management were identified with a systematic study of documents and using qualitative content analysis through three coding steps in the MAXQDA2020 software for a two-year time interval. These components were found to include organizational architecture, organizing to be accountable, suspicion and intuition, continuous assessment, delegation of authority, psychological safety, flexible groups, and rapid problem-solving capability. In the quantitative phase, the effectiveness of the components was determined by the structural equation modeling using a questionnaire in the PLS software package. The statistical population in this phase was composed of the managers and owners of businesses in selected cities. The sample size was estimated at 90 people by Cochran’s formula. The results show that all components influence the resilient management of businesses. The components of flexible groups, delegation of authority, organizational architecture, and suspicion and intuition are the least influential.

Among the institutions in charge of emergency management, the non-governmental organizations have a special place as efficient and complementary public sector institutions in achieving development goals. These organizations, and at the head of them the Red Crescent Society, play an effective and constructive role in successful management of emergency due to their capabilities such as the ability to create deep local connections, public awareness, flexibility and rapid response and thus their participation in crisis management leads to an improvement in the situation.Given the importance of this role, the article intends to study and analyze the function of NGOs in emergency management, based on the duties of the Iranian Red Crescent Society, using a descriptive-survey method and in order to provide a conventional model. For this, the expert members and groups of NGOs in the Iranian Red Crescent are considered as a statistical population. 381 people of them have been selected by stratified random sampling. Also, data were collected through a questionnaire and analyzed using structural equation testing. The validity and reliability of the tools have also been confirmed. Findings indicate that the role of NGOs on the tasks of the Red Crescent in emergency management is positive and significant and the proposed model has a good fit.