رضا یوسفی زنوز

The research purpose is responding to the human resources compensation risk in Iran's insurance industry. By systematically studying the literature and interviewing 15 experts based on the snowball sampling , risks were identified and after screening based on the fuzzy Delphi, Fuzzy cognitive mapping has been used to respond to risk. the inflexibility of compensation was identified as the most central element of the cognitive risk mapping. In the next , the effect of different risk control policies on map elements was investigated in three scenarios. After controlling one factor and its lack of influence on the whole map, finally with the policy of controlling the key elements , seven key elements with the highest degree of centrality include inflexibility of compensation, lack of employee satisfaction, lack of transparency, internal and external inequality, and non-alignment of payment. And performance, the imbalance between short and long-term incentives and the non-compensation of extra-role behaviors of employees selected and with the aim of fully controlling these elements, values corresponding to these elements were considered equal to zero in the initial state vector. results show that by controlling key elements of mapping, whole mapping undergoes changes and risk of human resources compensation is reduced.

The COVID-19 pandemic has posed a significant challenge to the COVID-19 vaccine supply chain that need to be resolved for a successful exit from the pandemic. It is essential to identify and evaluate the risks associated with the vaccine supply chain. We propose a new measure for quantifying the resilience of the vaccine supply chain in Iran. To evaluate the resilience of the vaccine supply chain, we use a Bayesian network to consider the vulnerability and recoverability indices as well as the associated disruption propagation. This approach enables managers to measure the resilience of the supply chain and identify the reasons for performance decline due to the ripple effect. Our results show that outbreak risks, lack of access to vaccine suppliers, low efficacy of the vaccine against new variants, inaccurate prediction of vaccine demand, and failure to choose the right suppliers are the risks likely to have a high impact on the disruption of the vaccine supply chain. Our approach provides a useful tool for evaluating the resilience of the vaccine supply chain and identifying the critical risks. It can be used by decision-makers to mitigate the impact of disruptions and improve overall resilience of the vaccine supply chain.

Supply chain sustainability is necessary for businesses today, so organizations pay attention to social and environmental goals in addition to economic goals. Therefore, to ensure the realization of these goals, measuring the sustainability efficiency of the supply chain is considered inevitable. The problem of assessing the performance of supply chain sustainability, on the one hand, is affected by the inherent conflicts of interest among sustainability goals, which increase the complexity of the problem, and on the other hand, it should be configured in a way that can simultaneously provide sufficient knowledge of the efficiency of overall supply chain sustainability and sustainability goals. In this study, a combined mathematical model of data envelopment analysis and game theory is presented to evaluate the sustainability efficiency of the supply chain and the efficiency of sustainability goals by considering the trade-offs among sustainability goals. The trade-offs among sustainability goals are formulated using the Nash bargaining game in such a way that the ability to provide simultaneous results is related to the overall efficiency of supply chain sustainability and the efficiency of each sustainability goal. The proposed model was evaluated under a case study for appraising the efficiency of supply chain sustainability of an Iranian pharmaceutical company. The results of the model implementation indicate that the proposed model is firstly capable of simultaneously providing efficiency values of supply chain sustainability and each sustainability goal, and secondly, it provides the necessary and sufficient knowledge in comparison of these values for efficient and inefficient products.

Over the last years, extensive research has been done in the field of blockchain technology and there are a growing number of areas to which blockchain is being applied, creating broad knowledge in this field. Classifying the subfields and identifying new topics and research trends in the area of blockchain would be of significant help to researchers. The present study aims to review and categorize studies on blockchain technology, identify subfields, and achieve a coherent view of its research process. using bibliometric analyses. The data used in this research has been collected from 423 articles in the Scopus database. Then, the bibliographic coupling analysis and keyword co-occurrence have been performed.According to the findings of this study, researches on blockchain technology are divided into 5 clusters: 1. Computer systems, 2. Financial sciences, 3. Smart contracts, 4. Data management and authentication, and 5. Electronic cash. In recent years, topics such as machine learning, trust, deep learning, risk assessment, edge computing, Ethereum, and consensus have drawn the attention of the research community. This research provides a comprehensive classification of the main concepts and topics discussed in blockchain-related research, designated to help researchers in this field choose a line of research.

The present study aimed to systematically review the recent researches in the field of leisure time physical activity using managerial approach. This study was a secondary study that has been done in systematic review method. In doing so, firstly to determine the inclusion and exclusion criteria, an evaluation form was prepared and its face validity was then confirmed by 5 experts in the field of sport and leisure management. In the initial search for data collection, based on pre-determined key words, 831 articles were recognized between 2005 to 2018-time period. Considering the research inclusion criteria, 101 articles were analyzed. In sum, 280 textual propositions were identified. Afterwards the detected textual propositions were summarized into the 185 items. In the next step, these 185 propositions were divided into four categories: a- motivators, b- concepts or barriers, c- outcomes, d- the change-needed fields. So, it is suggested to key decision makers to have a comprehend attention on issues contributed to providing participation necessities for all segments of the population (i.e. vulnerable groups) by promoting inter-organizational collaborations.

Due to the presence of human resource in all parts of an organization, risks related to the human resources can be extended to all organizational activities and disrupt the implementation of the organization’s plans. Accordingly, and considering the major research gap in the field of human resource risk, the aim of this study is identifying and prioritizing human resource risks in the Iranian insurance industry. After systematic study of literature and finding 59 related articles, and through interviewing 15 experts in the Iranian insurance industry, human resource risks are identified, screened, and prioritized using thematic analyses, fuzzy Delphi and network analyses. The findings demonstrate that human resource risks in Iranian insurance industry consists of recruitment, compensation, training, performance appraisal and nonfunctional risks; among which the importance of recruitment risks is higher than other risks. Thus, recruiting the right human resource will pave the way to development of Iranian insurance industry.

Climate change and environmental impacts of economic activities, have forced supply chains to implement green policies and reduce environmental impacts and destruction to achieve competiete advantage. One approach to achive simultaneously to the economic and envitonmental objectives is to design closed loop supply chain networks (CLSCN) that integrate reverse logistics into their forward paths. In this paper, a bi-objective mixed integer linear programming model was developed for the CLSCN problem. The first objective is to minimize the cost function and the second objective function tries to minimize the time of transferring products from manufacturers to the distributors. Lp Metric and ε -constraint methods were utilized to solve the model. A numerical example was presented to show the applicability of the model and also sensitivity analysis was done. In this model two parameters of cost and demand are uncertain, in order to deal with uncertain parameters a robust optimization approach was utilizec. Multi objective particle swarm optimization (MOPSO) was used to solve the model in lare scales ad the solutions were compared with the solutions that obtained by exact methods. the findings of this research can help decision makers and executives to design efficient closed loop supply chains.

As one of the most significant issues in working environments, the concept of “envy among employees” exerts a considerable influence on employees’ feelings. As a negative feeling, enviousness has not sufficiently been researched from an academic point of view. The purpose of this research was to identify and prioritize the effective factors (individual and organizational) on employee envy. This research is developmental-applied in terms of purpose and can be categorized based on the nature and method of descriptive group. Also, based on the type of data, it can be considered as a “survey –case” one. The statistical population of this research includes 10 academic and organizational experts with educational degree related to or experienced in human resource management and organizational behavior. According to the theoretical framework and the review of literature, 19 factors (9 personal factors and 10 organizational) were identified as influencing the concept of envy among employees. Then, DEMATEL technique is used to prioritize the identified factors. To do so, after measuring average of influence and the influence of the identified factorsAnd the factors that R + J were higher than the average (7 personal and 7 organizational factors) were selected. In the next step and in order to prioritize the selected factors, ANP technique is used. The results showed that in individual dimension, negative social comparison in the first rank, conscious cognitive assessment of other’s better future in the second rank and awareness of other’s abilities were put in the third rank. Also in organizational dimension, low level of fairness and justice in organization ranked first, performance evaluation ranked second and leadermember interaction ranked thirdر With regard to the results, it can be argued that the experts in human resource management should prepare themselves to face any kind of envy on behalf of employees and have ability to change envy to competition and motivation.

Over the past decades, organization‘s ambidexterity has been considered as a new managerial topic, pointing to the organization's ability to simultaneously address two inadequate organizational objectives, exploitation and exploration. However, organizations need different resources to achieve ambidexterity, the most important of which are human resources or organization staff that can help organizations achieve their goals. Therefore, this research seeks to identify and prioritize the factors affecting the ambidexterity of employees. This research is applied in terms of purpose and in terms of the nature and method of descriptive-survey. 21 factors were extracted from the research literature as factors affecting employees' ambiguity and Delphi and fuzzy and ISM methods were used to analyze the information. Delphi and ISM questionnaires were distributed in two stages among 15 managers and human resources experts of commercial banks in Tehran. In the first stage, after analyzing the data by Delphi method, 7 factors were removed from the 21 identified factors and finally 14 the factor was identified as the most important factors.The identified factors were then re-assigned to managers and experts through the ISM questionnaire to prioritize the factors. Thus, factors were prioritized at 8 levels, with personality traits that are internal individual factors being identified as the most influential factors, and human resource flexibility and external motivation being structural organizational factors being identified as the most influential factors

The overall responsibility of any organization lies with its strategic leaders or senior management team and organizational performance is influenced by their strategic choices, in other words, the organization is the reflection of its top executives. The current dynamics of the business environment and technological advances have put organizations at odds with various stakeholder groups that sometimes have conflicting demands. Therefore, this study aimed to identify the capabilities required for strategic leaders to satisfy different organizational stakeholders in Iranian airlines.

The approach of this research is inductive and in terms of research orientation it is an applied researches. The study was conducted by using a qualitative method through the thematic analysis of semi-structured interviews with 17 strategic leaders of airlines (CEO, Board of Directors and Chief Executive Officers). Purposeful judgment and snowball methods were used for sampling. QSR Nvivo software was used to analyze the data derived from the interviews and the reliability of the coding of the interviews was assessed by using in-subject percentage agreement method.

as a result of analyzing the data from the interviews, 4 main themes are: strategic leadership skills, individual attributes, interpersonal behavioral skills, management skills, and 24 Sub-themes and 61 concepts for strategic keadership with stakeholders approach was identified.

in the present study, in order to satisfy different stakeholders by top management team, the fourfold pattern of strategic leadership was presented.

Millions of people encounter coronary artery disease annually, and this disease constitutes a large number of patients. Although considerable progress has been made in medical science, but the early detection of this disease is still a challenging issue. The aim of this paper is to describe developing a fuzzy expert system that will help to detect CAD at an early stage. Rules were extracted with the aid of doctors and fuzzy approach was taken to cope with the present uncertainty in the medical domain. The results indicate a high level of correct detection of normal and abnormal groups of people. The suggested methodology can help the doctors in medical diagnosis.

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Crowdfunding Platforms are transformed to Websites by which people will be able either to back financially new Ideas or to try to seek investment (Fundraising) for their products and services. Whereas in recent years this kind of investment is highly advertised in press circles and many success stories are reported in this kind of investments, many people have referred to these newly developed platforms (websites) and many projects have been launched on these various sites. In spite of dramatic growth of the turnout of the people in the role of investors or in the role of investment attractors, the percentage of successful projects in absorbing complete investment has experienced decreasing growth. The works, which have been conducted with regards to prediction of successful projects, are merely concentrated on optimization of prediction models to improve the prediction procedures, but in these studies the prediction scenarios are not dealt with. But we should consider this fact that without identification and definition of prediction scenarios, we couldn’t reach to the main goal of this undertaking which is to present effective suggestions for success improvement of the launching of crowd funding projects. In this paper, the main objective is to suggest some proposals based on the available information regarding the status of the projects through success prediction of launched projects by means of Business Intelligence: (BI). To realize this, in this paper by using business intelligence features, initially, we have presented a comprehensive model for prediction issues in target business based on Key Performance Indicator: (KPI). Then, according to extracted requests from the model, we gathered a large amount of data from the Kick Start website which consist of the project records, user records, temporal data and projects users profile in famous social media. In the next step, by consideration of extracted model, based on business intelligence, we implemented the corresponding model by means of data analysis for prediction and evaluation of the financial pledges of the implemented projects. Our practical results show that prediction models can predict effectively the success of the projects and also they can suggest, by means of identification of projects success factors, proposals in order to improve the success probability of the projects

Since any organization can’t do all the right things in the way of ýdevelopment and maturity in a short time, the models for evaluating ýthe maturity of e-HRM provide the indicators for assessing e-HRM, ýby these indices, current maturity of the organization is assessed and is ýplanned to achieve the desired level of maturity.ý
The aim of this study is to identify and rank the indicators and criteria ýto assess the maturity of E-HRMþ.þý This research is applied and ýdescriptive-survey. Fuzzy delphi method was used to identify ýindicators and criteria and fuzzy analytic hierarchy process (AHP ýfuzzy) was used for prioritize and determine the importance of ýindices.ý
The end result of this research is e-HRM maturity assessment indices in ýthree phases and seven components, so the first phase of transactional ýand replication include communication, automation, and application, ýsecond phase, enhanced include Software Analysis and Coordination ýsoftware and third phase, transformational include creation and ýalignment, in continue the relevant indicators and their importance was ýpresentedý

The high speed of technology progress and the importance of obtaining the new ones have made under- and undeveloped countries look for technology transfer from technology- owned countries in order to remove their weaknesses and obtain competitive advantages. In this connection, the approach of the developed countries willing to maintain technology or its transfer to the countries having the same political and economic interests, have caused the technology transfer and its effective methods to become one of the important issues of the present decade. To obtain and transfer various technologies from developed countries to the target ones, different solutions can be considered. Generally, the selection of the most effective way in this respect is made based on different (and sometimes contradictory) criteria as well as a lot of sub ones.
In this research, considering the technology levels of wind turbine manufacturing in Iran and also the approach of the other countries with respect to it, the customary methods of technology transfer are determined based on the views of the experts and the companies manufacturing turbine parts. Then, the importance of criteria, sub criteria, and technology transfer options are verified by using the analytic hierarchy process method (AHP); finally the best option for implementing in wind power industry in Iran is selected. The results of this study can be used by the country decision makers in order to design and manufacture the wind turbines.
In this research, considering the technology levels of wind turbine manufacturing in Iran and the approach of the other countries with respect to it, the customary methods of technology transfer are determined based on the views of the experts and the companies manufacturing turbine parts. Then, the criteria relative importance, sub criteria, and technology transfer options are specified by using the analytic hierarchy process method (AHP); finally the best option for implementing in wind power industry in Iran is selected. The results of this study can be used decision makers in order to design and manufacture the wind turbines.

In order to gain more illicit profit, some traders in the stock market try to make a targeted impact on prices by placing fake orders and false advertising. Due to the high customer population, it is not possible to discover these frauds using traditional methods. The present study seeks to provide a system for preventing the frauds in future market-trading coins based on Bayesian classifier model for Iran Mercantile Exchange. The proposed model has polynomial time complexity and high accuracy because of considering important dependencies among different features of data. The primary labeling of data has been done by Kmeans clustering. The test of model shows 94.55 percent similarity between model's output and labeled data. Using this system can helps to identify the fraudulent from non-fraudulent traders.

Hospital information systems play an important role in improving coordination between different sectors of a hospital and increasing the efficiency of its managerial processes. Despite great advantages of these systems, many hospitals have encountered some obstacles at the implementation stage that deviate the systems from their primary goals. These events caused the hospital information systems to fail. The aim of this paper is to present a model for identification of these events and categorize them and finally prioritize them in order to manage or hinder their occurrence.
Firstly, by reviewing the related literature, we identified the risks that possibly can occur in this area. After extracting the risks, their consequences have been quantified by means of expert judgment. Experts were selected from Milad hospital. Then the risk's priorities have been determined by applying fuzzy analytic hierarchy process. The reliability and the validity of the related questionnaire have been determined
Between four identified factors, the highest scores were related to the managerial factors with the weight of 0.84 while the organizational factors gained the lowest score by the weight of 0.01. After multiplying the probability of each risk factor to its consequence, the priorities changed.
Employing qualified personnel in the field of health information systems, providing necessary trainings to them and preparing technical infrastructure before the implementation of the system along with the assignment of the required resources, and paying special attention to interpersonal relationships are very crucial in the reduction of failure risk of hospital information system implementation project.

The main target of this research is providing a decision making model to identify the target groups for energy subsidy reform using artificial neural network approach.
Family expenditures on electricity, gas, telephone and cell phone are used as the inputs to the artificial neural network model and the Probit model developed as a benchmark. The sample being studied in this research are divided into two groups: eligible and non-eligible to receive subsidies. The artificial neural network used in the research is the multilayer perceptron which has used the Levenberg-Marquardt method to train the data.Acooring to the results, there exists a statistically meaningful relation between the families’ expenditure on the chosen services and their belonging to different income levels as eligible or non-eligible groups for receiving subsidies. Moreover, families with higher expenditures on selected services have higher incomes.The outcome of this study reveals that the two models used for classifying the target groups have similar results in classifying the families into eligible and non-eligible groups for receiving subsidies

Banking and financial services are important parts of the service industry. Quality of service in the banking industry has a close relationship with customer satisfaction service system. Banks could create competitive advantage by increasing customer satisfaction and reduce costs in today's competitive environment. This paper presents a decision-making model to obtain optimum tasks assignement to personnels in workflow process of housing facilities for the purposes of minimization the average processing time of orders entered into workflow (average time) and also personnel operating costs to minimize banking workflow preocess (operating costs) which it would reduced the waiting times for customers and ultimately higher satisfaction level for the customers. This is a non-linear multi-objective optimization problem and with respect the nature of the variables would be define in a discrete integer space. Since the problems is in NP-hard problems in class, solving the optimization problem has been conducted using non-dominate Sorting Genetic Algorithm II.

In today highly competitive and changing business environment, systematic analysis of performance of the organization for determining the rate of success, detecting the deviations and their causes and exploring new ideas or finding the modification solutions, has been the principal concern of managers and organizations. The evaluation of the financial efficiency and using the financial indicators are one of the most common approaches in this way. Given the importance and urgency of this issue, in this study financial efficiency of the pharmaceutical companies listed in Tehran Stock Exchange that are working in the field of production of pharmaceutical products has been assessed and evaluated. Therefore, and in order to overcome limitations of financial ratios in this study to assess the financial efficiency of statistical sample of firms through using financial ratios, has been used the integrated approach of Data Envelopment Analysis and Balanced Scorecard (DEA-BSC).
Based on this approach and to overcome the challenges in selecting optimum combination of financial ratios, the Balanced Scorecard approach has been applied. For this purpose, the four key perspectives (financial, stakeholders, processes and growth) are considered as the basis for an explanation of the proposed financial ratios. In order to choose the right financial ratios, a panel of industry experts (experts in the field of financial and pharmaceutical fields) formed and through monitoring their specialized comments, in each perspective three ratios were selected as an indicator of financial performance measurement and then were weighted. This process will cause the appropriate influence of each indicator according to its importance in the statistical sample companies. In addition, the suitable type of data envelopment analysis approach that is consistent with the nature of the study have been selected and used. Finally, by doing the mathematical calculations and solving the relevant equations through using the operations research software (GAMS), the financial performance of each company of the statistical sample of the research was estimated and according to this basis the companies were ranked.

Risk is inherent and inseparable part of life and business. Always uncertainty condition arising from incomplete information and data or ungovernable variables, associated with opportunities and threats.Nowadays many organizations and companies have relied heavily on information systems and information security management has transformed to an important organizational topics. And due to the fact that the use of information systems security may be created some risks, an effective risk management process, will result in a successful security program. Risk management includes risk identification process, risk assessment and risk-reduction efforts to acceptable levels. The objective of this research is to prioritize information security risks, in order to provide a mechanism to enhance the security of enterprise information. To this end, a model has been presented for organizational information security risk assessment using the fuzzy AHP and Bayesian networks. In the assessment process, risks impact by fuzzy AHP and risks probability by Bayesian networks have calculated and finally The risks Prioritized. The findings suggest In the case study, the risk of lack of knowledge and lack of proper training in the field of information security, have the highest priority and attention is needed most.

Most organizations need to information systems to survive and thrive. therefore they should seriously protect their information assets. Creating structured and justifiable exchanges between cost, security and mission control systems security risks is essential. This is important in the planning and development of such systems. Initial Appropriate decisions can reduce costs and increase ease of control risk. The first step in the risk management process is the identification of risk. The purpose of this study is identify the most important enterprise information security risks.From the point of view purpose, The study is application and of view research methods, is descriptive. In this study, a model is presented to identify information security risks, according to ISO 27002 and cobit 4 and study the documents and using by fuzzy Delphi method and opinions of experts, which includes 10 of the IT professionals of the Bank, have been presented. in this template 6 factors and 20 subfactors of information security risk factors have been identified for the Bank.

An important phenomenon in supply chain management, known as bullwhip effect, suggests that demand variability increases as one moves up a supply chain. In this paper, we investigate the influence of advanced and traditional methods to forecasting lumpy demand on the occurrence of bullwhip effect. Knowing the fact that neural networks can better model and forecast the nonlinear and chaotic behavior of lumpy demands in comparison with traditional and usual methods such as exponential smoothing, this paper efficiently employs neural networks as the main core in the proposed forecasting system. Further with the help of a numerical example it is shown that utilization of neural networks was more beneficial and successful in comparison to other forecasting techniques in terms of reduction in bullwhip phenomenon.

This paper presents a model predictive control (MPC) approach for production and inventory control systems. Model predictive control previously has been successfully applied to supply chain problems; however most systems that have been proposed so far possess no information on future demand. The incorporation of a forecasting methodology in an MPC framework can promote the efficiency of control actions by providing more insights in the future demands. In this paper, we investigate the applicability of advanced and traditional methods to forecasting lumpy demand at supply chains. Neural networks can be better model for forecast the nonlinear and chaotic behavior of lumpy demands in comparison with traditional and usual methods such as exponential smoothing. This paper efficiently employs neural networks as the main core in the proposed control design. To highlight efficiency of the proposed method, real datasets are used for investigation and comparison studies.