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Purpose- Social sustainability, especially in rural areas, is one of the most important goals of policymakers, planners and managers. However, social sustainability in local communities, such as villages, can be challenged through environmental instabilities. Accordingly, the purpose of this study is to analyze the tensions and social dangers in rural areas of Neyshabur, one of the provinces of Iran. Design/methodology/approach- In order to measure the relationship between the independent variable of drought and the dependent variable of social tension, 24 variables were identified in the context of drought, existing tensions and social damage caused by water scarcity in the study area. The required information was collected from documentary studies and also through interviews and questionnaires. One-sample t-test, Pearson correlation, single-variable regression, and VIKOR model were used to analyze the data. Findings- The results show that there is a relationship between water deficit deduced from drought and 22 social unsustainability variables. Based on the results of the regression test and the amount of obtained beta, respectively, the greatest effects of water shortages deduced from drought was on intensifying rural poverty (0.932), increasing living expenses (0.931), and the destruction of small crop and small cultivation (0.924). Also, the results of the VIKOR model showed that there is a difference between the studied villages in terms of the severity of social tensions. Originality/value- This study has been promising to focus on the effects of drought and water scarcity as an environmental unsustainability in shaping and exacerbating tensions and social injuries. Therefore, the results of this study can be effective in recognizing the social impacts of environmental changes in geographical areas and countries facing environmental changes.

One of the most important aspects of investment is determining the “optimal investment portfolio”. To date, scientific research has been conducted to determine the optimal portfolio with “artificial intelligence” and “Fuzzy logic”. However, we determine the optimal portfolio based on Dynamic Stochastic General Equilibrium (DSGE) model. On the other hand, several factors affect returns, which is one of the most important issues in investment decision-makings, and various models have been developed to analyze the return of “capital” and “other assets”. In this regard, some of the most important models include linear and non-linear models, artificial neural network models, Fama–French model, Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model, and optimal stable model. All of these models are indicative of the use of quantitative methods and models in the investment industry. One of the causes of using these models is developing the financial economy. In fact, the development of financial economy has more increased with the concept of “portfolio optimization”. In fact, the portfolio optimization and diversification concept is the basis of developing and expanding classical finance and financial decision-making. Financial markets, especially the capital market, can have a great deal of relevance to other sectors of the economy. In the present study, we design and calibrate a new Keynesian DSGE model in relation to the optimal investment portfolio and effectiveness of shocks (e.g., productivity and foreign exchange earnings fluctuation) on macroeconomics variables.

Chief executive officers (CEO), as the central pillar directing companies at the capital market level, plays a critical role in making investment decisions to de-crease agency costs and maximize shareholders’ wealth; however, their psycho-logical attitudes and perceptions lead to different investment functions of these companies in a competitive market. Accordingly, this study aimed to detect the propositional arrays of the investment functions using Q analysis in order to identify the CEOs’ mental typology in distinguishing investment functions. The present study was carried out with the participation of 13 CEOs from Tehran Stock Exchange companies during a one-year period (2018-2019). The study encompassed two different phases. In the first phase, content analysis was used to identify the phrase Q of the CEOs’ investment functions. In the second phase, Q analysis was adopted to typify the CEOs’ investment functions, which was based on the subjective cognition of the target population and contributed to the development of the approaches in line with the research objectives. The results confirmed the existence of three mental patterns in the CEOs regarding the in-vestment functions in the capital market. These mental patterns were ‘investment function in stock market indices’ as the first mental pattern, ‘investment function in risk control’ as the second mental pattern, ‘strategic investment function’ as the third mental pat-tern. The study results revealed different types of investment functions among the CEOs’ of stock exchange companies and thus contributed to the development of financial theories from the perspective of CEOs’ cognition.

This study examines the criterion of value at risk from another perspective and presents a new type of mean-value at Risk model. To solve the portfolio optimization problem in Tehran Stock Exchange, we use NSGA II, MOACO, and MOABC algorithms and then compare the mean-pVaR model with the mean-SV model. Given that, finding the best answer is very important in meta-heuristic methods, we use the concept of dominance in the discussion of multi-objective optimization to find the best answers and show that, at low iterations, the performance of the NSGA II algorithm is better than the MOABC and MOACO algorithms in solving the portfolio optimization problem. As the iteration increases, the performance of the algorithms improves, but the rate of improvement is not the same, in a way, the performance of the MOABC algorithm is better than that of the NSGA II and MOACO algorithms. Then, to compare the performance of the “mean-percentage of Value at Risk” model and the “mean-semi variance” model, we examine both models in the standard mean-variance model and show that the mean-pVaR model, compared to the mean-SV model, Has better performance in stock portfolio optimization.

The Supply Chain Network Design (SCND) with perishability is an active research topic. The Agri-fresh Food Supply Chain (AFSC) is a relevant topic to SCND and this study aims to model a new AFSC for a real-world case study. Regarding the traditional AFSC, the geographically dispersed small farmers transport their product individually to market for selling. This leads to a higher transportation cost, which is the major cause of farmers’ low profitability. This paper formulates a traditional product movement model to represent the existing AFSC. The concept of sharing economic approach is employed by the aggregate and collaborative transportation of products to minimize transportation inefficiency. This paper proposes an aggregate product movement with the vehicle routing model to re-design an AFSC for a case study in Iran based on the data of ETKA Company-the largest domestic agri-fresh food supply chain. A four-echelon, multi-period, Mixed Integer Non-Linear Programming (MINLP) approach for the proposed location-inventory-routing model is formulated for perishable products via considering the clustering of farmers to minimize the total distribution cost.

Price return and P/E are two interesting factors for a lot of investors; The Bohmian quantum mechanics used referring to the time correlation of return and P/E of the stock market under consideration. In this study, we extend the quantum potential concept to determine the behaviour of P/E and also price return in two different industry of Tehran stock market during a time interval of April. 2008 to march 2019. The obtained results show that the quantum potential behaves in the same manner for P/E and price return, also confines the variations of the P/E and price return into a specific domain. Furthermore, a joint quantum potential as a function of return and P/E is derived by the probability distribution function (PDF) constructed by the real data of a given market. It serves as a suitable instrument to investigate the relationship between these variables. The resultant PDF and the corresponding joint quantum potential illustrate that where we have light points in joint quantum potential chart, the probability of those amount of P/E and price return are more than other points. In addition, because of the rectangular shape of the joint quantum potential chart we can say that these two variables behave as two independent variables in the Market.

Ecofeminist discourse is experiencing its peak importance with the rise of both feminism and ecocriticism to the summit of cultural and literary studies. Going back and revisiting authors and texts which helped shaping the current cultural forces through ecofeminist lenses may help us understand how nature and femininity both are viewed separately and together. As one of the most prominent and influential figures in horror and science fiction (and perhaps pop culture in general), Howard Phillips Lovecraft presents a thought-provoking portrait of women and femininity in his texts and since nature plays an integral role in worldview, femininity and nature almost blend into a single concept throughout his fiction. This paper intends to analyze the works of H. P. Lovecraft through Ecofeminist lenses and apply the Ecofeminist theory of Mother/Nature, developed by Catherine M. Roach, on Lovecraft’s life and fiction. The researchers intend to find a correlation between the idea of Bad Nature presented by Roach and the almost always evil representation of femininity in H. P. Lovecraft’s fiction.

This paper aims to analyze the impact of the traumatic experiences on the identity formation of Shaila Abdulla’s main character in Saffron Dreams and elaborates on how she manages to overcome her diverse emotional burdens. The author, who is concerned with Muslim women’s multiple identities and struggles in the American Diaspora, discusses the challenges of living in the increasing Islamophobic climate in the aftermath of 9/11 through the life of her heroine, Arissa Illahi, a Pakistani writer and artist, who loses her husband in the collapse of the World Trade Centre. Judith Herman’s conceptions of trauma and recovery are applied to discuss the impact of trauma on the identity formation of the character and how she succeeds to go through the process of healing. The paper also analyzes the literary strategies and narrative techniques in this feminist trauma narrative to indicate how the author has tried to represent what is originally marked by voicelessness. The results of the study demonstrates that although the traumatic event of 9/11 and its consequences has devastating effects on Arissa, she as an artist is able to utilize her psychological resources and to take advantage of familial ties to cope successfully with the traumatic experiences in her life, tolerate adversities, and even develop an optimistic view point about new possibilities for her future life. This paper supports the aim of contemporary feminist traumatology which is to make women’s trauma visible, give meaning to it, and ultimately create frameworks that promote the healing of trauma. Cathy Caruth, Judith Herman, and Laurie Vickroy are among the main theoreticians of the research.