مطالب

This study attempts to examine Tom Wolfe’s The Electric Kool-Aid Acid Test in the light of the ideas of Michel Foucault, specifically the notions of normalization, institutions, and surveillance that tackle the relationships among power, institutions, and literature. The analysis posits that, in the context of the 1960s, the American government took advantage of all the institutions which were supposed to guarantee the freedom of individuals to curtail their freedom. Seeking to create a normal, ordinary, and homogeneous society, these administrations have employed the police, law, prison, and other overlapping institutions that work in tandem to create circuits of institutions which guarantee to reduce  human beings to simpletons who are docile, meek, and ready to fit in place properly. The normality and ordinariness favored by the authorities are also implemented since the novel starts by depicting free individuals whose identities hinge on their being abnormal while it ends when their movement is shattered, and the protagonist is seen as a simpleton serving the forced labor sentence of the judges of both the government and normality. Freedom emerges as a mirage than truth as there seems to be no outside through which individuals can live outside the domination of controlling apparatuses.

This study examines the political and economic factors influencing the decision of investors in the stock exchange. For this purpose, first, by using the Meta Synthesis method, the factors affecting investment decisions were extracted from previous researches and then, using Delphi technique, the identified features were evaluated and approved by experts. Then, using DEMATEL method, the relationships between the factors were analyzed, and finally, the sequence and rank of each factor were determined based on the Interpretive Structural Modeling method. Based on the results obtained from the DEMATEL method, "Foreign political news and revolutionaries" and "International economic revolutionaries" are the most influential factor on other factors and "Predicting the country's economic situation in the future" is the most influential factor among other factors. Also, the results of the Interpretive Structural model approach show that Political factors such as the "Comments of political officials", "Iran's political relations with other countries" and "Internal Security and Stability" have the greatest impact on investment decisions.

The stock market is one of the main components of the economy, and various factors cause fluctuations in it, one of which is the effect of investors' behavior. Therefore, present study seeks to answer the question of whether the feelings and sentiments of investors might intensify the fluctuations in the Tehran Stock Exchange or not. To answer this question, at first, in order to quantify sentiments, as non-abstract variables, the Equity Market Sentiment Index (EMSI) was used that investors are classified in 5 categories of completely risk-averse, risk-averse, neutral-risk, risk-taking and completely risk-taking. Using GARCHi-in-Mean, results indicate that the sentiments of investors will result in greater fluctuations in the Tehran Stock Exchange. Hence, if fluctuation is considered an indicator of market risk, the excitement associated with an abnormal rise in volumes will increase that risk.

Portfolio optimization which means choosing the right stocks based on the highest return and lowest risk, is one of the most effective steps in making optimal investment decisions. Deciding which stock is in a better position compared to other stocks and deserves to be selected and placed in one's investment portfolio and how to allocate capital between these stocks, are complex issues. Theoretically, the issue of choosing a portfolio in the case of minimizing risk in the case of fixed returns can be solved by using mathematical formulas and through a quadratic equation; but in practice and in the real world, due to the large number of choices in capital markets, the mathematical approach used to solve this model, requires extensive calculations and planning. Considering that the behavior of the stock market does not follow a linear pattern, the common linear methods cannot be used and useful in describing this behavior. In this research, portfolio optimization using the gray wolf algorithm and the Markowitz model based on CO-GARCH modeling has been investigated. The statistical population of the current research included the information of 698 companies from the companies admitted to the Tehran Stock Exchange for the period of 2011 to 2020. First, the optimal investment model is presented based on the gray wolf algorithm, and After extracting the optimal model, the efficiency of the gray wolf algorithm is compared with the Markowitz model based on CO-GARCH modeling.

As we are looking for knowledge of stock future returns in portfolio optimization, we are practically faced with two principal concepts: Uncertainty and Information about variables. This paper attempts to introduce a pragmatic bi-objective investment model based on uncertainty, instead of probability space and information theory, instead of variance and other moments as a risk measure for portfolio optimization. Not only is uncertainty space expected to be more in line with investment theory, but also, applying and learning this approach seems more straightforward and practical for novice investors. The proposed model simultaneously maximizes the uncertain mean of stock returns and minimizes uncertain entropy as a measure of portfolio risk. The uncertain zigzag distribution has been used for variables to avoid the complexity of fitting distributions for data. This uncertain mean-entropy portfolio optimization (UMEPO) has been solved by three meta-heuristic methods of multi-objective optimization: NSGA-II, MOPS, and MOICA. Finally, it was observed that the optimal portfolio obtained from the proposed model has a higher return and a lower entropy as a risk measure compared to the same model in the probability space.

Improving the competitiveness of businesses through investment in industrial parks is one of the challenges that managers face for economic development. This study has been done with the aim of identifying, determining relationships and providing a structural model of investment to competitive advantage in industrial parks. The data have been analyzed in two parts, qualitative and quantitative. In the qualitative part, the variables of the model were extracted using the method of content analysis and coding and confirmed by the fuzzy Delphi method, and in the quantitative part, the hierarchical structure model was presented. The statistical population of the research is 25 experts who were selected by non-probability purposeful and snowball sampling and answered the pairwise comparison questionnaire. The findings of the qualitative section showed that the model has eight variables including "infrastructure investment", "motivational investment", "economical investment", "institutional investment", "environmental investment", "support investment", "Political investment" and "competitiveness". The findings of the quantitative section showed that the structural model has six levels, that "political investment" and "infrastructure investment" have the most influence in the model and are in the first priority. We conclude that in order to competitive advantage, managers should pay more attention to technical and informational infrastructure, as well as appropriate policies and providing regulations.

Background: Market strategy design involves the analysis of market position, identification of market opportunities, and understanding the strengths and weaknesses of an organization. It aims to create favorable competitive conditions by defining different market segments. In recent years, researchers have made efforts to develop models that can effectively determine ideal marketing strategies and promote their alignment and synergy at the organizational level.Objective: This study aims to design a comprehensive marketing strategy development and alignment model, which has been relatively understudied in academic research.Method: The present research builds upon the Strategic Reference Points (SRP, S) theory and utilizes thematic analysis to formulate a new framework and strategic reference points for an industry-specific marketing strategy. It also addresses the coordination between marketing strategies at both the business and corporate levels, employing the Delta model.Findings: A thematic network analysis was conducted based on interviews with industry experts. The research findings identified key dimensions of strategic reference points and provided theoretical and operational definitions of the power industry concept. These dimensions, namely "customer engagement" and "switching costs," were incorporated into the final model design. Leveraging the Delta model, the study resulted in the formulation of the Lock-in marketing strategy model. The research findings and the proposed model offer valuable insights and practical strategies to overcome current industry challenges, enhance agility, and facilitate effective decision-making in the field.