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Aggression is a destructive experience in terms of social and public health. The purpose of this paper is to determine the role of depressive mood, premenstrual dysphoric disorder (PMDD) and premenstrual syndrome (PMS) in adolescent girls’ aggression.

In a cross-sectional study, 510 girl students were selected by multistage cluster sampling from Lahijan and Sangar high schools (Northern Iran) in the 2017–2018 academic year, and each of them responded to the short version of Beck Depression Inventory (BDI-13), Premenstrual Symptoms Screening Tool and Ahvaz Aggression Inventory. Data were analyzed by point-biserial and Pearson’s correlation coefficients, univariate analysis of covariance in the form of 2 × 3 factorial design and Hochberg’s GT2 post hoc test.

The questionnaires of 475 students were returned correctly (survey validity=93 percent). The results of ANCOVA after adjustment for confounding variables such as age and physical illness history revealed that the existence of main effect for depressive mood (F=31.50, df=1, p<0.0001) and PMS and PMDD diagnoses (F=11.39, df=2, p<0.0001) were associated with increased aggression. However, there was no significant interaction effect on aggression levels (p>0.05). Additionally, post hoc tests revealed no significant differences between the diagnosis of PMS and PMDD in terms of aggression (p>0.05).

The present study has some limitations. Depressive mood and diagnoses of PMS and PMDD were defined through relying on the self-report data and cut points suggested by the questionnaires. Obviously, change of measurement tools or even cut points reduces the results reliability and repeatability. Furthermore, the research plan does not allow us to infer causal relations and does not provide information about the direction of the relationship between depression symptoms, PMS and PMDD diagnoses, and aggression. Finally, the present study is relied on high schools’ data, and the results cannot be generalized to other adolescent girls.

Despite the limitations of this study, its findings offer new insights into the factors influencing the perpetration of aggression in Iranian adolescent girls. Depressed adolescent girls and those receiving a PMS or PMDD diagnosis are more likely to develop aggression. These findings can be used in high schools to design educational and health-based interventions in order to reduce and prevent anger and resentment in adolescent girls.

Despite the undoubted role of knowledge in the small family business (FB) in the restaurant and fast-food industry, there are some main challenges in the knowledge-sharing (KS) orientation for promoting their business. This study tries to recognise and explore the drivers influencing these enterprises' KS processes.

The authors applied combined exploratory and confirmatory analysis in two studies. In the first study, by the Delphi method, the 22 experts consisting of managers, FB owners and academic professors explore and forecast significant items and drivers. The second study is a confirmatory factor analysis (CFA) for validating the first study's indicators using the survey collected amongst 218 restaurants and fast foods employees.

The findings indicate 23 indicators in three main drivers of individual, organisational and technological, are critical for KS in small FBs in the investigated industry.

This research supports the understanding of knowledge management and the FB and contributes to recognising the influential factors for KS amongst small and medium-sized family businesses in the food-related industry. Also, by identifying and ranking the most significant factors, this research will help entrepreneurs facilitate FB entrepreneurship. Finally, the results provide practical implications for current and future KM and FB decision-makers.

Given the competitive environment and complicated relationships in supply chains in the modern era, it is important to take into account internal and external risks. In addition, proper methods must be designed to evaluate these risks correctly. The purpose of this paper is to provide a suitable map based on the artificial neural network technique to assess and classify the risk levels of retailers who have interconnected rules in the downstream of the supply chain.

In this research, a model for risk assessment with a hexagonal grid and 2D self-organizing map was applied.

According to the results, the model used in the study can provide a basis for classification of retailers based on the specified risk levels defined by the experts and risk managers of the company. Also with the model’s visual output, managers can have a better understanding of the distribution of the risk level of retailers.

The proposed methodology can be adopted by managers to assess the risk of members involved in the supply chain, helping them to formulate the risk mitigation strategies based on the risk levels.

As a part of the risk management process, organizations can use this developed method to reduce the existing risks imposed by the members or customers on the company.

This study aims to show that management with big data analytics capability can achieve more advantages of the global sourcing process. Furthermore, this study using its conceptual attitude model aims to show that big data analytics management capability leads to an increase in firm performance by the mediating role of integration.

Using an online questionnaire, 158 managers from 13 Iranian companies taking advantage of the global sourcing process were surveyed. The validity of the hypotheses was evaluated using partial least squares based on structural equation modeling (PLS method).

The results of the study showed that big data analytics management capability has a positive impact on global sourcing and firm performance directly, and by the mediating role of integration.

Previous studies have carefully addressed the role of big data and big data analytics in firms. However, this is among a few studies addressing the role of big data analytics capability, especially management capability, in improving firms’ performance. The results of this study shed light on the fact that how global sourcing takes the best advantage of big data analytics management capability for better accomplishment of organizations’ duties. The results of this study also disclose how big data analytics management capability helps organizations with their performance and bring benefits to their units.

Wind as a major source of renewable energy has received tremendous attentions due to its unique features to reduce carbon emission and also to keep the environment safe. Nevertheless, to use wind energy properly, the environmental circumstances and geographical location related to wind intensity should be considered as a priority. Different factors may affect the selection of a suitable location for developments of wind power plants; thus, these factors should be considered concurrently to identify the optimum location of wind plants.

In this study, first, basic data envelopment analysis (DEA) was used, then dual DEA was used and, finally, Anderson Petersen (AP) model of dual DEA was selected to prioritize cities or decision-making units (DMUs). Numerical Taxonomy (NT) method was also used to assess the validity of AP dual model in DEA. The prescribed approach was applied for five cities in East Azerbaijan province of Iran.

The results indicate that wind power as a renewable energy can be harnessed in few cities, and the ranking by DEA illustrated that the city of Tabriz is the first priority.

Low environmental degradation effects in comparison to other methods and the ability to utilization at a widespread level include the benefits of using wind energy in the generation of electricity. In this regard, the study of relevant potentials and finding suitable locations for the deployment of wind energy utilization equipment are essential. Using DEA method helps us to choose optimal locations according to different criteria.

Wind energy is justifiable in reducing social costs in comparison with fossil fuel plants, which includes negative effects, and its electricity can be used as a sustainable energy in the country's economic, social and cultural development.

For identifying the most proper location for development of wind power plants in Iran, DEA is applied for the first time to prioritize the suitable locations for installations of wind turbines among five different cities in the East Azerbaijan region. A number of crucial factors including land price, distance to power, rate of natural hazards, wind speed and topography are considered for location optimization of wind turbines for the first time. Also, to validate the results of DEA method, NT method is used to assess the validity of AP dual model in DEA.

Despite the expansion of women's entrepreneurial activities and its positive effects on the economic development of societies, women still face numerous difficulties in starting and running a business compared to men, especially in developing countries because of gender discrimination in the field. The cultural context in societies is a significant factor affecting the status of entrepreneurship among the Iranian women. Therefore, the present research is an attempt to identify the challenges affecting entrepreneurship among Iranian women. The results obtained from 30 semi-structured interviews with women entrepreneurs and women with entrepreneurial roles showed that sociocultural challenges faced by women entrepreneurs are classified into: “the society's perception of entrepreneurship among women,” “women's social security,” and “common family norms governing a society.”

The purpose of this paper is to develop a theoretical model to explain the impact of big data analytics capabilities (BDAC) on company’s supply chain sustainability (CSCS). The secondary objective of the study is to assess the relationship between different dimensions of supply chain sustainability and companies’ BDAC.

This research was carried out by conducting a survey among 234 pharmaceutical companies in Iran (a case study of Iran), using a standard questionnaire of BDAC and United Nations (UN) online self-assessment on supply chain sustainability. However, the respond of managers of 188 companies were usable in this research. Smart PLS3 was used to employ partial least squares method to examine the validity and reliability of the measurement and structural model.

The results of this study demonstrate that BDAC have a strong impact on both pharmaceutical supply chain sustainability, and the dimensions including vision, engage and internal. It is found that the relationships between BDAC and the other dimensions of supply chain sustainability including expect, scope and goals are not significant but positive.

Research on the relationship between BDAC and CSCS, especially in the pharmaceutical supply chain, is scanty, and this gap is highlighted in developing countries and the pharmaceutical supply chain that plays a prominent role in public health. This paper discusses several important barriers to forming a sustainable supply chain and strong BDA capabilities.

This paper could be a guide to managers and consultants who are involved in big data analytics and sustainable development. Since UN urges companies do the online self-assessment, the results of this paper would be attractive and useful for UN global compact specialists.

No study has directly measured the relation between BDAC and CSCS and different dimensions of CSCS, using a comprehensive survey throughout all pharmaceutical companies in Iran. Moreover, this research assesses the different dimensions of BDA capabilities and supply chain sustainability. This paper represents the facts about situation of sustainability of pharmaceutical supply chain and BDAC in these companies, and discloses several related issues that are serious barriers to forming a sustainable supply chain and strong BDAC. In addition, this paper provided academic support for UN questionnaire about CSCS and used it in the survey.

The success of e-commerce websites depends on their effective communication and influence on their users. At first glance, the users are impressed by the website design and, if inspired, they would continue their operations on the website. This paper aims to evaluate the effects of visual aesthetic of the Web pages on users’ behavior in online shopping environment. In particular, the paper aims to evaluate the elements of visual aesthetic on the organism variables (i.e. “satisfaction,” “arousal,” “perceived on-line service quality” and “trust”) and measure them on the users’ response (i.e. purchase, comparison and re-visit).

Using the stimulus–organism–response (S-O-R) framework, the authors first assessed direct and indirect effects of visual aesthetics of e-commerce websites on customer responses. Then, the Visual Aesthetics of Websites Inventory (VisAWI) method was used to examine the effects of four dimensions (i.e. craftsmanship, simplicity, diversity and colorfulness) on users’ perceived website aesthetics. To do so, DigiKala.com, a famous Iranian e-commerce website was selected and the questionnaires were distributed among its users.

The study results revealed that the website aesthetics in the S-O-R evaluation had the greatest direct impact on “perceived quality of online services,” “trust,” “satisfaction” and “arousal,” respectively. These variables also indirectly affected “shopping,” “revisit” and “comparison to similar products on other websites.” Regarding the evaluations based on the VisAWI, the component “craftsmanship” played the most central role in expressing the website aesthetics, followed by the variables “simplicity,” “diversity” and “colorfulness,” respectively.

Although the considerable effect of Web aesthetics on customers’ purchase behavior has been identified in previous research, it has not been accurately measured. Furthermore, studies on Web aesthetics are mostly limited to information systems’ users and do not concern consumers. Therefore, considering the increasing growth in online shopping and the significance of Web aesthetics to online consumers, investigating how consumers respond to Web aesthetics is of vital importance.

The main purpose of the present study was to improve and develop previously proposed models for Iran telecommunication networks. It should be noted that the six-dimensional (6D) sustainability model used in this study will be a useful and comprehensive model for industries. Since, the new dimension of IT along with the five well-known economic, social, environmental, technical and institutional aspects of organizations is considered to have great impacts on supply chain sustainability; the proposed framework can be practical.

According to the related literature review, there are two research streams in supply chain management. The first stream is exploratory research, seeking out conceptual discussions in this area. The second one is associated with mathematical models and techniques, aiming to set decision-making rules in this regard (Agrell et al., 2004). In this study, evaluation was performed using the FMEA method as an analytical technique based on the principle of pre-occurrence prevention to identify potential failure factors in sensitive systems (Mohammadfam and Kianfari, 2008).

After identifying the risks and causes of the incidence and effects and consequences of risks, preventive and risk control measures and advisory strategies were presented. Customers with 45.76% share in critical risks are threatening to maintain supply chain in these companies. During this study, it was found that 33.9% of the main source of supply chain critical risks was customers, constituting 45.76% of such risks, accompanied by organization, having a 38.88% share of critical risk generation. The study findings also revealed that 33.9% of critical risks were mainly (equally) related to economic and technical aspects of supply chain sustainability in telecommunication networks. Moreover, as a newly-introduced sixth dimension, IT represented 10.17% of critical risks threatening supply chain sustainability in such networks. Critical risks are mainly related to the economic and technical aspects (equally) with the sustainability of the telecommunication networks supply chain. Also, as a new finding and the sixth dimension, 10.17% of the critical risks that threaten the sustainability of the telecommunication networks supply chain have the information technology dimension.

The internet and fixed and mobile data services are provided by several private companies in Iran, which are relatively similar in terms of their supply chains. In order to manage the sustainability of Iran's telecommunication supply chain, telecommunication networks affiliated to Iran Telecommunication Company (ITC), operating in the field of data and internet services and fixed telephone were selected in 31 provinces. The intended networks were also providing an important part of the country's needs including Mobile Telecommunication Company of Iran, a subsidiary of Iran's telecommunication networks, as one of the top companies in this industry. Accordingly, all the networks studied in this study needed to be identified with regard to communication sustainability risks, since they provide management solutions to each other by segregating risks. In this study, 68 managers and 72 experts participated in different work teams of telecommunication networks.

This paper aims to present a smart, sustainable supply chain practices structure on the basis of the relational view.

A method based on fuzzy cognitive map was applied to construct a relational map to introduce and implement such relational methods. Considering this relational map as a guideline, observations into particular methods and ways of applying relational methods to attain sustainable development goals across organizations has been introduced.

Primary outcomes provided a series of relational methods for the purpose of giving advice to those organizations and their suppliers for smart, sustainable supply chain. Reliance between relational methods were examined and assessed under seven meaningful groups: economic internet of things (IoT), green internet of things, social internet of things, economic supply chain, green supply chain, social supply chain and other variables.

This study guides managers toward an improved perception of the connection among IoT instances and sustainable supply to modeling smart, sustainable supply chain. Managers can determine the practices that need more focus along with the practices that are less relevant. Thus, this will help managers in the decision-making process and to organize their decisions by planning and calculating the relative importance and influence of smart, sustainable practices on each other and on the company’s smart, sustainable program.

To the best of the authors’ knowledge, this is the first approach that promptly examines and determines the interdependencies between relational methods and constructs a relational map for the purpose to introduce and analyze smart, sustainable supply chain.