احمد توکلی

INTRODUCTION: Increasing the incidence of natural disasters around the world has led to increased concerns about the social and economic development of developed countries. Natural disasters are inevitable, but they can be taken to reduce their negative impacts on countries. Organizations involved in managing these crises must regulate their supply chain and make the necessary changes to improve the performance of the humanitarian supply chain. METHODS: Data analysis by partial least squares method (PLS) was performed using smart-pls2 software and a researcher-made questionnaire with 25 questions that examined six structures. In this research, 320 questionnaires have been distributed. In the statistical population of the survey, there are military centers, fire brigades, Omer Crescent population, emergency 115, crisis management and renovation committee in the parliament, governorate, municipalities, supply chain managers, Active practitioners in this field, subject specialists (reference persons and perpetrators in this field), and other members of the organizations involved in rescue and rescue operations in Tehran (randomly selected from the 22 areas). Eventually, 193 people were involved in relief and rescue operations. The reliability of the model has been investigated and verified through three ways of evaluating factor load coefficients, Cronbach's alpha coefficients, composite reliability (CR). The average variance extracted (AVE) values are greater than 0.5, and CR values are larger than AVEs. That means convergent validity. Also, the mean of the AVE for each structure is greater than 0.50 and this is a sign of convergent validity. FINDINGS: For the model, GOF is 0.56; that means the model has a great fit. The statistics above show that the proposed model is suitable for data collection. In general, the proposed model confirms the relationship between the use of information technology, mutual trust, flexibility, agility, adaptability and performance of the humanitarian supply chain. Fit statistics have four indicators: Goodness of Fitness (GFI) of 0.92, Fitted Goodness Index (AGFI) of 0.9, Root RMSEA error of 0.04, and 360.88 x 360 times. Finally, the ratio of k2 to the degree of freedom for 1.38 is obtained, indicating the good of fitness of the model fit with the data. With the aid of p-values and T-Values 8 hypotheses were confirmed in this modeling. CONCLUSION: The results show that the agility and flexibility of organizations in the humanitarian supply chain are related to the use of information technology and organizational trust, which in turn affects performance.

The shadow economy (SE) is a pathological normalcy, not only in developing countries but also in developed ones, causing disagreeable distortions in the real economy. The causes of the shadow economy can be traced back to actors who operate outside the formal sector to reap the benefits. The way these actors work can both affect the quality of governance and affect it. The right to comment and accountability, political stability and non-violence, government efficiency, the quality of governance laws, the rule of law and the control of corruption are indicators of governance evaluation in this regard. Therefore, in this study, using Hishao causality method, the causal relationship between these indicators with the shadow economy in Iran during the years 1995 to 2017 has been investigated. Findings show that government efficiency, rule of law and control of corruption have a two-way relationship with the shadow economy and the indicators of the right to comment and accountability, political stability and non-violence and the quality of governance laws have a one-way relationship with it.

In this paper, an economic decisions-making model based on mathematics in order to optimize the costs of investment in accordance with innovative technology of human resources recruitment introduced and in the next section, the economic impact of the Internet recruitment technologies has been examined. In order to fulfill these demands classic economic order quantity model of have developed as cover unique cost of recruiting activities such as human resource management and coordination related to it. Therefore, using this method calculated the required minimum of recruitment level and consequently optimal investment in online recruitment technology has been resulted. The findings suggest that optimal investment costs near the minimum level of recruitment is rapidly increasing but the stunning developments in efficient technologies in recruitment system and lack of awareness of this minimum level of employment has caused total number of employees is more than the required minimum level. In this article, how to use this model in a research sample of online recruitment websites in Iran entitled “Iran recruitment” its potential as a tool for decision-making in the field of optimal investment for managers appeared.