morteza bazrafshan

In this research, a conceptual model for identifying and prioritizing the factors affecting the success of gas projects in the South Pars field in Iran using a multi-criteria decision-making approach and foundational data theory is presented. For this purpose, first, using the Delphi method, Paying attention to the technical challenges and contractual requirements of the project and ensuring customer satisfaction, Paying attention to the challenges in decision-making in the project closing phase and headquarters challenges, the support of senior managers and management. Release of guarantees, proper management of resources and risk management, correct planning and no change in the organization's strategy and attitude during the closing phase, having a coded operational plan for transfer and operation and updating the organization's current information management system, the desired performance of stakeholders and its effects on the quality of the launch. Then, using the best-worst method, while determining the best and worst criteria, the index of attention to the project completion phase and the consequences of the facility operation period are considered as the best criteria and the index of proper resource management and risk management are considered as the worst criteria. Finally, the importance of the criteria has been calculated. The second variable is the measure of technical challenges and contractual requirements of the project and ensuring customer satisfaction on the success of offshore gas projects is ranked first using the best-worst method with a weight of 0.219.

Tourism destinations are getting more complex. Increasing uncertainty and environmental changes are among the most important ones that tourism destinations have to deal with to maintain their competitive advantage. Preferably innovation, flexibility, responsiveness, and redefinition of market opportunities can be considered as the new techniques for gaining the advantages. These techniques are focused on the effective use of knowledge, skills, and the experience of key actors, known as learning in the literature. Although the learning (organization) concept is spread in various settings such as cities (learning cities), or universities (learning universities), little research has been done in tourism. Thus, this research aims to provide a model for the development of Learning Tourism Destinations in Yazd. Based on qualitative methods, the researchers did a thematic analysis of the interviews with 14 tourism experts and an Interpretive Structural Model analysis of 12 experts’ questionnaires. The proposed model is composed of four levels in which there is sustainability at the highest level. In the second level of the model, there are futurism, system thinking, and human resource management empowerment. The third level of the model is composed of adaptive management, coordination and participation, cultural exchange, responsibility, innovation and creativity, and environmental intelligence. At the lowest level, there are factors of competitive intelligence, technological intelligence, research and development, intellectual capital, and knowledge management. The results of the research can be used as a model for transforming learning cities into learning tourism destinations.

Organizations are forced to adapt themselves to the ever-increasing advances in knowledge and technology in order to survive in this changing environment. They are to take fundamental measures and changes based on innovation, flexibility, responsiveness, creative redefinition of the market and new opportunities, and resources to gain a competitive advantage. These changes are focused on effective use of the knowledge-based capital, which is achieved by creating a learning organization. This article is to present a model for transforming hotels into learning organizations. Therefore, by compiling interview questions based on theoretical literature and obtaining experts' opinions with thematic analysis method, indicators and factors of the learning hotel for the Iranian hotel industry is presented. The model is composed of 61 basic concepts, 11 organizing concepts, and 3 comprehensive concepts including the drivers, the factors, and the consequences of the learning hotel.

In this research, a framework for optimizing the oil condensate supply chain is designed using mathematical programming and simulation. Based on this framework, investment and operating costs and greenhouse gas emissions for oil and gas transmission lines can be minimized to meet pressure and transmission network needs. We can also minimize the production of pollutants in the related parts of the chain. By applying a real case study, all possible decisions are taken into account to consider the environmental aspects of the supply chain. Therefore, the structure and decisions of the supply chain are generally based on two objective functions, including the reduction of transportation and maintenance costs and pollution in treatment plants and distribution centers. The results showed that using the proposed model reduces costs by 31% and greenhouse gas emissions by 51%. There will also be an 8% increase in the capacity of fields and refineries and a 65% increase in exports. Using the results obtained from solving the model, it is possible to determine the share of each oil product in the total price and each part of the chain in the production of greenhouse gases. According to the results, oil is the most expensive and oils are the least expensive. In addition, refineries have the most impact and storage tanks have the least impact on environmental pollution.

Cost efficiency in which cost coefficients are given for some inputs (cost coefficients can be different for disparate decision-making units (DMUs)) is one of the most important concepts in data envelopment analysis (DEA) to analyze the performance. Moreover, in some occasions, the cost performance and changes of input measures should be addressed while the convexity property is violated. Therefore, in this paper, first a DEA model is provided to assess cost efficiency based on the free disposal hull (FDH) model. Then, by considering cost and technical efficiencies achieved, a multi-objective problem called the inverse FDH cost model is presented to determine input values based on output changes while the cost and technical efficiency levels are preserved. The multi-objective problem is computed applying two approaches. Also, a dataset from the literature is presented to show the performance of the proposed method. For this purpose, we used the data of six banks in different countries. We added 2% to the outputs and analyzed the inputs with two models. In the first model, we used cost coefficients for weights, and in the second model, we used the same weights. Contrary to forecasts, some entries have decreased and others have increased. But from the results, we have noticed that the first model is more realistic because most of the solutions have increased in this model.

The field of data envelopment analysis in the realm of data science and analytics focuses on examining and analyzing various aspects of data within a dataset. The main objective of this analysis is to investigate and analyze different and diverse dimensions of the data. Data envelopment analysis is employed to gain a better understanding of the data, enhance transparency, and achieve a deeper comprehension of patterns, relationships, and characteristics within the data. The primary goal of data envelopment analysis is to discover hidden and unknown information within the data and extract knowledge from it. By utilizing data envelopment analysis methods, one can observe and comprehend patterns, relationships, differences, and variations in the data, leading to the provision of new and potentially valuable insights regarding the data and its associated processes. Therefore, in this article, the bootstrap simulation process has been utilized to improve the accuracy of achieved performance. The main objective of this article is to present a framework for measuring the performance of evaluated units under the bootstrap scenario. To accomplish this, overall and stage-wise performance scores are separately determined for each unit through simulated values for inputs and outputs. Thus, the most significant innovation of this research is the presentation of a framework for determining the performance scores of interconnected units using bootstrap-data envelopment analysis. To demonstrate the proposed method, a real case study in the tomato supply chain network has been considered. According to the results, the accuracy of the employed method has been demonstrated.

In this paper, a framework for optimizing the oil condensate supply chain is modeled using mathematical planning to design and make strategic and tactical decisions. According to this framework, investment and operating costs for oil and gas transmission lines can be minimized to meet the pressure requirements and the transmission network. Also, we can minimize the production of pollutants in the chain-related sectors. In the case under study, all possible decisions are considered to consider the environmental aspects of the supply chain. Therefore, the structure and decisions of the supply chain are generally based on two objective functions, including reducing transmission and maintenance costs and pollution in treatment plants and distribution centers. The proposed model is 95% reliable, which is acceptable reliability, and can estimate goals with only 5% error. Using the proposed model will reduce costs by 31% and emissions by 51%. Also, there will be an 8% increase in the capacity of fields and refineries and an increase in exports by 65%. Using the results obtained from solving the model, we can determine the share of each petroleum product in the cost and each part of the chain in the production of greenhouse gases. According to the results, fuel oil has the highest and oils the lowest. In addition, refineries have the greatest impact, and storage tanks have the least impact on environmental pollution.

In the current situation, besides having to create jobs so as to help poverty reduce, there is a need for supplemental income for farmers. As the agriculture industry in Iran is dealing with different problems such as drought, it seems that a supplement income is required for the sustainability of agricultural activities and preservation of the rural population. This additional income arising from activities such as tourism can also create some new jobs. In this regard, the linkage between tourism and agriculture leads to the formation of agritourism. Agritourism is considered as both an opportunity for surviving agriculture in different regions and has different economic impacts (for local people); also, it is identified as an opportunity for growth and development. In this article, the purpose concerning previously conducted research and elite opinion poll (agricultural and touristic responsibles, specialists, and experts) is to determine and examine the factors influencing the development of agritourism. Hence, related variables were extracted by reviewing the related literature and considering the experts’ points of view and, firstly, 134 variables were recognized; These variables were reduced to 34 ones according to the experts’ opinion poll (by considering the conditions of region) during three stages. Then, 260 respondents’ responses (collected by a questionnaire) were analyzed using SPSS and LISREL software. Factors analysis (exploratory factor analysis and confirmatory factor analysis) results showed that there are 5 factors which are influencing the development of agritourism in Jahrom and forming the research model: 1- Intellectual infrastructure 2- physical infrastructure 3- Institutional factors 4- Promotion and development, and 5- competitiveness factors. All in all, the clearest results of the Coding method indicated that home-based business is the most important one resulting from agritourism

There is a need for supplementary income for farmers and employment creation to help alleviate poverty. Agritourism has been identified as an opportunity for growth and development as it has the potential to meet those needs. In this article, according to the literature review and opinion polls of experts (officials, experts, and experts in agriculture and tourism), the factors affecting the development of agritourism were identified and investigated. In the initial summary, 134 indices were extracted and reduced to 34 indices during the three stages of expert opinion polling. 260 experts answered the questions in this questionnaire. According to statistical analysis using SPSS and LISREL software, research questions were analyzed and the final model of this research consists of 1. Intellectual infrastructure, 2. Physical infrastructure, 3. Institutional factors, 4. Promotion and development factors, and 5. Competitiveness factors.

The purpose of this article is to investigate the relationship between five attitudes of competitive intelligence (warriors, assaults, actives, reactive and sleepers) and competitive advantage in hotels of Shiraz. The research is developmental- practical with quantitative approach and was done by use of Structural Equation Modeling. The society of this research were hotels managers of Shiraz in which by use of classified random sampling, 106 of them completed the questionnaire. The relationship between latent and observable variables was determined by confirmatory factor analysis. The results of model Goodness showed that the managers of Shiraz hotels have “warriors” and”assaults” attitudes. Thus, there is a significance relationship between these two attitudes and “cost reduction” and “differentiation” strategies. The findings can help the hotel managers to move toward competitive advantage by considering the importance of the above mentioned attitudes. other results shows in paper, also we indicate discussion and managerial conclusions for future studies and intereseted researchers.