مطالب

This study was conducted to determine the stock portfolio with the best return and low-risk investments using momentum-contrarian strategies (MCSs). The momentum-Contrarian strategy is one of the well-known models to construct the portfolio which suggests buying the stocks with the best performance (the winner stocks) and selling the stocks with the worst performance (the loser stocks). The optimal values of the portfolio's objective function and the weight of all assets in the portfolio that are not necessarily the same are calculated by defining a nonlinear multivariate optimization model combined with momentum-contrarian strategies (MCSs). The return information of companies listed on the Tehran Stock Exchange from 2014 to 2019 was used to select the best optimal portfolio. The results confirmed the stability in the profitability of the contrarian optimal portfolio with minimum risk compared to other optimal portfolios. Furthermore, through MATLAB software the optimal weight of assets in the optimal portfolio is calculated based on statistical data.

This research, in line with the strategy of the World Customs Organization, order to provide a structural model for improving the ethics and administrative health of employees based on the use of information technology in customs affairs with a combined approach of fundamental theory and interpretive structural modeling to understand how information technology affects ethics and Administrative health and investigating the power of influence and the degree of dependence of the variables of ethics and administrative health of employees in the form of drawing a comprehensive structuring model. In the implementation of this research, a mixed method was used in the qualitative part of the foundation's data theory according to the research needs and structured interviews were used to collect data. To collect data in a qualitative method, with the help of Maxqda software, research findings through the opinions of 13 experts in three stages of open-centered and selective coding in the form of 6 categories affecting the ethics and administrative health of employees in the form of the Strauss paradigm model and Corbin and it was expressed theoretically. After building the theory, in the quantitative stage, interpretive structural modeling has been used in order to understand the relationship between the variables and the leveling of the promotion of ethics and administrative health of Iran Customs. The results of the research show that the variable "use of smart technologies" is the first level variable in the promotion of ethics and health, and the variables "Analysis of the situation of manpower and customs processes, ethical characteristics of employees and laws and management of information technology and human resources" » is the second level variable. And the variables of "conditions and structure of the organization and the requirements and infrastructure of information technology" are the variables of the third level.

Modern organizations’ strategy is reducing inventory, production cycle time, transportation cost, quality cost, while increasing competitiveness to maximize its benefits. Supply chain management, as part of an organization’s strategy, involves several stakeholders with different interests, each controlling part of the chain and pursuing different goals. This paper presents a comprehensive multi-level model of a supply chain consisting of several simultaneous stakeholders in a systematic way. The developed model first, consider the various transportation factors, such as distribution of goods for various members of the supply chain to achieves the lowest transportation cost at different levels, for both transporting parts and products. The model also provides lowest costs of purchase and production by considering the costs of maintenance, supply shortages and shortage, for all the involved parties. In addition, a competition in the context of a game to select the optimal situation between the stakeholders of the supply chain has been considered to make the best decision in terms of a participatory game by considering different scenarios. Through applying the principles of the game theory, various scenarios were developed to optimize the benefits of parties and to achieve the optimal design. The results of a numerical example showed that the answer provided by the game theory for the value of the objective function was less than the answers of the transport problem, despite the deficit penalty. Therefore, it can be concluded that game theory can achieve a better answer by considering the conditions of alliance between participants in a collaborative game.

In recent years, industrial clusters have received considerable attention from economists and industry analysts because they are seen as the main reason for certain economic regions' economic growth and success. For many Industrial States Organization, the selection of industrial clusters has become a critical strategic consideration due to the Budget allocation priority. In this paper, an extended qualitative flexible multiple (QUALIFLEX) methods is used to solve problems regarding the priority among this cluster using probability hesitant fuzzy information, which can lead to allocating the budget for industrial clusters more effectively. For more accuracy, we have applied a Hesitant fuzzy Topsis for prioritizing. Both rankings have been aggregated by the Copeland method. From our research results, the Larestan Muscat is of great importance, and Abade Inlaid Wood, Citrus packaging, Shiraz Marquetry, and Niriz stone have ranked respectively.

Social networks advertisements can be employed as a powerful means of communication to achieve goals such as sales, profitability and reinforcing brand image. Organizations managers have established a department titled “public relations” in their organizations, through which they communicate with individuals inside and outside the organization, so that they can fulfill their goals at lower costs and within shorter time by informing and persuading those individuals. In this regards, the present study is aimed at evaluating the extent to which public relations of private organizations employ social networks to introduce their products and services. Research population consists of managers and public relation experts of private sector’s organizations in Yazd, Iran. The present study takes a survey method and is regarded as field-work research. Sampling method is based probability and availability. Due to the limited population, 76 individuals were selected as the sample through limited population formula. Data was analyzed via Smart-PLS. results reveal that public relations of private organizations employ social networks at an optimal and acceptable level to introduce their products and services. Hence the hypothesis of the study is confirmed.

In modern times many militant atheist thinkers and activists have tried to promote the idea that religions, as well as religious ways of life, are one of the main, if not the main source of evil in the social arena. Some other non-believer scholars, while taking a respectful approach towards religions and religious people, maintaining that it is more rational for people and communities to adopt a non-religious outlook on life and become members of the community of non-believers. In this paper, I do not take issue with the militant non-believers. The reason is that their approach to religion is so ideologically driven that it leaves not much room for proper rational discussions; it only invites some polemical replies. My aim here is, instead, to enter into a dialogue with those non-believer scholars who view religion in a measured and rational way. My intention is to critically assess the claims of this latter group of scholars and explain why, contrary to what they suggest, certain interpretations of religion, and in particular, the Islamic faith, can provide them with better alternatives than their atheist outlooks. The arguments of this paper are mostly in reply to the views expressed by Professor Shearmur in his paper on critical rationalism and religion.

The influential physicist Richard Feynman became interested in the relationship between religion and science during a mid-career phase. He proposed that their interface was embroiled in unresolvable difficulties. He felt that science demanded an attitude of uncertainty for its claims, while religion contrarily required certain belief in its core doctrines. Though possessing several non-contradictory dimensions, Feynman felt that the nature of the truth claims of science and religion suffered from insurmountable elemental conflicts. This was by contrast to Karl Popper, the leading critical rationalist of the 20th century, who argued that there could be no tension between science and religion. This paper will argue that the ‘Feynman Problem’ is not as insoluble as it appears. Rather, several solutions exist within critical rationalism. Two will be presented-the first revolves around the conjectural basis of knowledge and is already a well characterised critical rationalist notion. The second is a novel solution based on the separate categorisation of psychological, pragmatic, and epistemological attitudes to religion and science. Karl Popper’s view of religion-science dissimilarity was a minimalist point of departure for critical rationalists, who have developed increasingly sophisticated frameworks for investigating the relationship between faith and reason. Critical rationalism represents an equally inspirational methodology for the pursuit of scientific and religious truth. Though both Feynman and Popper’s views on religion were underdeveloped, they foreshadowed the religion-science frameworks advocated by many late 20th century scientists, especially in the form of New Atheism and Gould’s NOMA theory. 

Organizational DNA expresses a method of investigation, thinking, reflection and thought about organizations, which examines the patterns of organizations, management practices, leadership style and other concepts related to the organization. Organizational DNA uses very diverse approaches to understand and recognize the organization, instead of organizational models and forms, by examining issues such as teamwork, decision-making, and development and improvement of human resources as separate or at least independent variables. In this research, by using the theoretical framework and using quantitative and qualitative methods, it has been done to identify the dominant DNA in Tocafulad Holding companies and determine the relationship model of hidden components using covariance analysis. The statistical population includes 435 employees of Isfahan Tokafulad companies and 6 company experts who used a mixed or mixed design to conduct the research. The technique of structural equations has been used to improve the model and evaluate the components and indicators to check and identify the model. In order to answer the research question, the steps are: 1) presentation of the conceptual model of the relationship between the corporate DNA and the investigated components, 2) quantitative evaluation of the components and indicators of the model, 3) determining the mutual influence of the hidden variables and the obvious variables of the model and 4) the relationship Between the apparent variables of the components with each other and the verification of the initial conceptual model has been carried out and then the model has been improved and finally the dominant DNA has been determined. The research showed that semantic DNA with a factor load of 0.93 is the dominant DNA in 4 out of 6 companies under investigation. It was also found that planning and payment system are the least important and change processes are the most important in line with the improvement model. In the improved model based on covariance analysis, the mutual effects of payment system and planning with mission, leadership style with teamwork, performance management with decision-making, interpersonal relations with change processes and change processes with work group should be considered.

There has not been presented any comprehensive index for Corporate Governance in spite of its crucial role in resolution and responsiveness. Although diverse methods have been sought for measuring the Corporate Governance in the previous studies, in this study, a comprehensive index is proposed for measuring Corporate Governance taking other indexes into account through mathematical equations. For testing the designed model’s functionality, a set of data related to 149 firms from 2014 to 2019 has been used jointly, too. To do so, a questionnaire, which asks the experts their idea about the weight and significance of the criteria of measuring the Corporate Governance of the firm, is made and distributed and the weight and significance of the criteria were determined through one method of multi-criteria decision model (Shannon Entropy). To measure the changeable hidden relationship which exists in this study of the Corporate Governance, provided with the measurement items, a confirmatory factorial analysis was taken, too; results show that the supposed model has been a proper index for Corporate Governance. This mixed index includes criteria such as the board of directors' size, independence, meetings, and its education, the CEO's permanence, the size, independence, financial specialty, financial experience, tenure and the meetings of the auditors hip committee, ownership concentration, organizational ownership, governmental ownership, deals with the dependent persons, the quality of the disclosure, proper information and weaknesses if the internal controls,

The purpose of this study was to present an optimal model Predicting Future Cash Flows optimized neural network with genetic (ANN+GA) and particle swarm algorithms (ANN+PSO). In this study, due to the nonlinear relationship among accounting information, we have tried to predict future cash flows by combining artificial intelligence algorithms. Variables of accruals components and operating cash flows were employed to investigate this prediction; therefore, the data of 137 companies listed in Tehran Stock Exchange during (2009-2017) were analysed. The results of this study showed that both neural network models optimized by genetic and particle swarm algorithms with all variables presented in this study (with 15 predictor variables) are able to provide an optimal model Predicting Future Cash Flows. The results of fitting models also showed that neural network optimized with particle swarm algorithm (ANN+PSO) has lower error coefficient (better efficiency and higher prediction accuracy) than neural network optimized with ge-netic algorithms (ANN+GA).