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This paper aims to develop a causal feedback structure that explains the dynamics of entrepreneurship development in Iran’s photovoltaic (PV) technological innovation system (TIS) to design effective policy interventions for fostering PV innovation.

This study adopts the system dynamics approach to develop the causal structure model. The methodology follows a systematic method to elicit the causal structure from qualitative data gathered by interviewing several stakeholders with extensive knowledge about different aspects of Iran’s PV TIS.

Lack of technological knowledge and financial resources within Iranian PV panel-producing firms are the main barriers to entrepreneurship development in Iran’s PV TIS. This study proposes two policy enforcement mechanisms to tackle these problems. The proposed feedback mechanisms contribute to the domestic PV market size and knowledge transfer from public research organizations to the PV industry.

The proposed policy mechanisms aid Iranian policymakers in designing effective policy interventions stimulating innovation in Iran’s PV industry.

The main contributions of this study include conceptualizing the causal structure capturing entrepreneurship dynamics in emerging PV TIS and proposing policy mechanisms fostering entrepreneurship and innovation in PV sectors.

There is usually a considerable shortage of resources and a lack of accurate data about the demand amount in a post-disaster situation. This paper aims to model the distribution and redistribution of relief items. When the new data on demand and resources become available the redistribution of previously delivered items may be necessary due to severe shortages in some locations and surplus inventory in other areas.

The presented model includes a vehicle routing problem in the first period and some network flow structures for succeeding periods of each run. Thereby, it can produce itineraries and loading plans for each vehicle in all periods when it is run in a rolling horizon manner. The fairness in distribution is sought by minimizing the maximum shortage of commodities among the affected areas while considering operational costs. Besides, equity of welfare in different periods is taken into account.

The proposed model is evaluated by a realistic case study. The results show that redistribution and multi-period planning can improve efficiency and fairness in supply after the occurrence of a disaster.

This paper proposes an operational model for distribution and redistribution of relief items considering the differences of items characteristics. The model integrates two well-known structures, vehicle routing problem with pickup and delivery and network flow problem to take their advantages. To get more practical results, the model relaxes some simplifying assumptions commonly used in disaster relief studies. Furthermore, the model is used in a realistic case study.

This study aims to differential diagnosis of some diseases using classification methods to support effective medical treatment. For this purpose, different classification methods based on data, experts’ knowledge and both are considered in some cases. Besides, feature reduction and some clustering methods are used to improve their performance.

First, the performances of classification methods are evaluated for differential diagnosis of different diseases. Then, experts' knowledge is utilized to modify the Bayesian networks' structures. Analyses of the results show that using experts' knowledge is more effective than other algorithms for increasing the accuracy of Bayesian network classification. A total of ten different diseases are used for testing, taken from the Machine Learning Repository datasets of the University of California at Irvine (UCI).

The proposed method improves both the computation time and accuracy of the classification methods used in this paper. Bayesian networks based on experts' knowledge achieve a maximum average accuracy of 87 percent, with a minimum standard deviation average of 0.04 over the sample datasets among all classification methods.

The proposed methodology can be applied to perform disease differential diagnosis analysis.

This study presents the usefulness of experts' knowledge in the diagnosis while proposing an adopted improvement method for classifications. Besides, the Bayesian network based on experts' knowledge is useful for different diseases neglected by previous papers.

The purpose of this paper is to develop a prescriptive portfolio selection (PPS) model based on a compromise between the idea of “fast” and “slow” thinking proposed by Kahneman.

“Fast” thinking is effortless and comfortable for investors, while “slow” thinking may result in better performance. These two systems are related to the first two types of analysis in the decision theory: descriptive, normative and prescriptive analysis. However, to compromise between “fast” and “slow” thinking, “overconfidence” is used as a weighting parameter. A case study including a sample of 161 active investors in Tehran Stock Exchange (TSE) is provided. Moreover, the feasibility and optimality of the model are discussed.

Results show that the PPS recommendations are efficient with a shift from the mean-variance efficient frontier; investors prefer PPS portfolios over the advisor recommendations; and investors have no significant preference between PPS and their own expectations.

Two assumptions of this study include: first, investors follow their “fast” system of thinking by themselves. Second, the investors’ “slow” system of thinking is represented by advisor recommendations which are simple expected value of risk and return. Therefore, considering these two assumptions for any application is the main limitation of this study. Moreover, the authors did not have access to more investors in TSE or other financial markets.

This is the first study that includes overconfidence in modeling portfolio selection for the purpose of achieving a portfolio that has a reasonable performance and one that investors are comfortable with.

The aim of this study is to identify the status of managing gray literature (GL) in medical science libraries in terms of three dimensions, collection development, organization and dissemination.

In this survey study, a structured questionnaire was used. The questionnaire consisted of 30 questions and consisted of six sections (demographic characteristics, the use of the term GL, types of GL, collection development, organization and dissemination). In total, 50 librarians from 15 medical science libraries participated in this study. The questionnaires were distributed manually to librarians by visiting libraries. All the librarians filled in the questionnaires. It should be noted that descriptive statistics and Excel and SPSS software were used for data analysis.

The results of using the term GL showed that 68 per cent of librarians use the source name itself. Most GL in libraries were theses (94 per cent). Moreover, a review of the status of GL collection showed that 60 per cent of libraries had written instructions for providing these resources. A total of 62 per cent of librarians stated that there is a GL selection committee in their library and the librarian is the most important member of the collection department. A total of 40 per cent of libraries were weeding GL. The most common way of obtaining GL was through deposition. The analysis of the status of GL organization indicated that 80 per cent of libraries had GL organization. A total of 90 per cent of libraries had digitized GL, and that librarians played a large role in organizing such resources. Evaluation of the dissemination of GL showed that all libraries have enabled users to access GL. In most libraries, users were only allowed to use GL in the library, and it was not possible to copy GL. Students and faculty members were the most important users of GL. Informing through the library website and the parent organization was the most important way of informing about these resources.

GL is one of the most important resources in medical and non-medical academic libraries. In this study, for the first time, the status of GL management in Iranian libraries of medical sciences was investigated. The results of this study can be useful for policymakers and managers of medical and non-medical libraries.

Northwest Nigeria is mostly populated by the Hausa and Fulani ethnic groups. Social inclusions and gender equality are listed among the fundamental rights. They are essential for human being to put up their best efforts in resolving all difficulties without restraint. Nonetheless, these rights are frequently withheld in many nations within the African continent, owing to ignorance, religion and custom fanaticism. In spite of these constraints, the northern Nigeria is faced with security issues such as persistent cattle rustling which ultimately evolved into armed banditry, which have exacerbated some lingering issues that revolves around children and women. This study attempts to examine the nature of the crisis that may relates to gender-based issues in Zamfara state. The article relied mostly on secondary literature. Evidences proved that security difficulties have worsened the living circumstances of women and girls in the understudied state, thereby espousing women and girls to dangerous attacks and hard living.

Human resources are one of the most important and effective elements for companies. In other words, employees are a competitive advantage. This issue is more vital in the supply chains and production systems, because of high need for manpower in the different specification. Therefore, manpower planning is an important, essential and complex task. The purpose of this paper is to present a manpower planning model for production departments. The authors consider workforce with individual and hierarchical skills with skill substitution in the planning. Assuming workforce demand as a factor of uncertainty, a two-stage stochastic model is proposed.

To solve the proposed mixed-integer model in the real-world cases and large-scale problems, a Benders’ decomposition algorithm is introduced. Some test instances are solved, with scenarios generated by Monte Carlo method. For some test instances, to find the number of suitable scenarios, the authors use the sample average approximation method and to generate scenarios, the authors use Latin hypercube sampling method.

The results show a reasonable performance in terms of both quality and solution time. Finally, the paper concludes with some analysis of the results and suggestions for further research.

Researchers have attracted to other uncertainty factors such as costs and products demand in the literature, and have little attention to workforce demand as an uncertainty factor. Furthermore, most of the time, researchers assume that there is no difference between the education level and skill, while they are not necessarily equivalent. Hence, this paper enters these elements into decision making.

Multi‐point boundary value problems have important roles in the modelling of various problems in physics and engineering. This paper aims to present the solution of ordinary differential equations with multi‐point boundary value conditions by means of a semi‐numerical approach which is based on the homotopy analysis method.

The convergence of the obtained solution is expressed and some typical examples are employed to illustrate validity, effectiveness and flexibility of this procedure. This approach, in contrast to perturbation techniques, is valid even for systems without any small/large parameters and therefore it can be applied more widely than perturbation techniques, especially when there do not exist any small/large quantities.

Unlike other analytic techniques, this approach provides a convenient way to adjust and control the convergence of approximation series. Some applications will be briefly introduced.

The paper shows how an important boundary value problem is solved with a semi‐analytical method.

The study investigates the effects of energy resource efficiency on the triple themes of sustainable development (economic, social and environmental dimensions). We adopt a quantitative research method, and the required macroeconomic data were extracted from World Development Indicators for a period of 30 years (1991–2020). The extracted data were analysed using correlation analysis and linear regression. Ultimately, the estimations from the three models produced mixed results. Energy resource efficiency (EFF) exerts a significant positive effect on economic sustainability (ECS), a significant negative effect on social sustainability (SOS) and a significant negative effect on environmental sustainability (EVS). However, claims on government (COG) exerted an insignificant negative effect on ECS, an insignificant negative effect on SOS and a significant positive effect on environmental sustainability (EVS). In practical terms, the findings are consistent with previous empirical studies, and they also validate X-efficiency theory (XET) and resource curse theory (RCT). The study concludes with implications, limitations and further research directions.

This study aims to examine the determinants of retailer social responsibility (RSR) in Old Dhaka City and their impact on RSR practices.

A cross-sectional design was used to collect primary data from 180 retailers through a questionnaire survey. The study used partial least squares structural equation modeling to analyze the data and examine the relationships among the determinants of RSR.

The study found that economic and ethical factors positively and significantly affect RSR practices, while social and environmental factors negatively but not significantly affect RSR practices. Cultural factors were also found to positively and significantly affect RSR practices.

This study provides insights for retailers and policymakers to enhance their RSR practices by considering economic, ethical and cultural factors. The findings also contribute to the existing literature on stakeholder theory by highlighting the importance of considering multiple stakeholders in RSR practices.

This study provides insights into the determinants of RSR in a unique setting in associating stakeholder theory and in Bangladesh, which has received limited attention in the literature on RSR.