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The liberalization of natural gas markets and the emergence of gas hubs in recent decades have shifted the natural gas trade from the regional to the global trade. The growth and maturity of these hubs have weakened the previously established relationship between the natural gas price and the prices of crude oil and petroleum products. Therefore, predicting the price of gas as a strategic commodity has become more important for different countries. Using the neural network method, this paper attempts to provide a model for the monthly prediction of natural gas price. Based on the time series data from 2012 to April 2019 as neural network input, this model predicts the prices in five hubs and natural gas exchange centers in Europe. Based on the R2 performance evaluation index of 98% in the neural network model fitted based on the aforementioned data series, the neural network model has an acceptable performance in predicting the natural gas price. The results of this study show that using the artificial neural network (ANN) method, the gas prices in the European gas hubs, which are located in European Country, can be predicted with a high accuracy.

Internationalization of businesses is considered as a key factor in economic development and growth of the economic entities. On the other hand, the ability of the system for endurance and reliability is inevitably dependent on the success that the system gains in communicating with the external environment; in other words, the sustainability of the system is entirely dependent on system capability for adaptation, change and responsiveness to the environment. Furthermore, Technology-based businesses are highly dynamic and use different internationalization patterns. A literature review shows that comprehensive studies have not been conducted despite the necessity of today's businesses to move toward sustainable internationalization. Therefore, this research examines existing patterns by presenting a model for sustainable internationalization in technology-based businesses. In the present study, 6 technology-based businesses in oil and gas industry have been investigated using a multi-case interview method. The validity and reliability of data collection tools have been confirmed. The results of the interviews performed during the two coding stages revealed that economic, environmental, social and technological factors are among the factors influencing the adoption of sustainable business internationalization strategies along with a focus on a sustainable business model. This study also presents different types of sustainable internationalization strategies and classifies the internationalization’s sustainability index into two categories of profitability and sustainability of relationships in the network.

Projects are affected by many internal and external factors. Such factors could be initiated domestically or internationally. The South Pars is a mega gas field in Iran which requires billions of dollars for development and gas extraction. Its development has taken a rather long time and gone through many challenges over the last two decades; due to several challenges, especially international barriers.In this research, the effects of sanctions on the expenditurs ofselected activities in developing of pars field between internal and foreign contractors is investigated. The main purpose of this research is to calculate the cost of selected activities of South Pars phases and compare the performance of internal contractors in sanctions conditions with foreign contractors in non-sanctions conditions.For this purpose, 18 activities which were similar in all of South Pars contracts,were selected.In these three sections, after applying relative indexes,global inflation, and technology by using inferential statistics, the total cost were considered among internal and foreign contractors. Based on the statistical analysis,there was no significant difference between the expenditures of selected activities performed by internal contractors and foreign contractors Under sanctions.

<strong>Abstract</strong> The motivation of this paper is the way in which the alternative fuel modes for public transport are analyzed. The aim is proposing a hybrid method to select the best fuel for public transport. The buses with old and new alternative fuels are considered in this paper. Several types of fuels are considered as alternative-fuel modes, e.g., conventional diesel, ultra-low-sulfur diesel fuel, bio-diesel fuel, and electric and gasoline hybrid engine. Moreover, many decision criteria categorized into performance, environmental, economical, infrastructure, technological, social, and risk are taken into consideration. The paper uses a hybrid multi-criteria decision analysis model to rank the fuel modes and/or choose the most efficient one. This hybrid method consists of rank order centroid method to assign the weights to the criteria, and additive ratio assessment technique to analyze the decision-making matrix. To demonstrate the applicability and flexibility of the model, a case study with data given by the experts from the respected fields is employed. The result presents that the liquefied propane gas (LPG) outperforms the other options in terms of the selected criteria.   <strong> </strong>

The purpose of the current work, conducted in 2017 and 2018, is to identify andprioritize the qualitative and quantitative factors affecting human resources(HR) valuation at National Iranian Oil Company and its subsidiaries. Using asnowball sampling method, 28 experts were selected from the head of humanresources, the head of finance, and some staff members of National IranianOil Company and its subsidiaries. In order to identify the dimensions andcomponents affecting human resources valuation, a comprehensive literaturereview at international and national levels, interviews with experts, andthree stages of distribution and collection of questionnaires using the FuzzyDelphi method were performed. Then, two phases of the paired comparisonquestionnaire were developed and provided for the experts to explain andevaluate the cause-and-effect relationships between the dimensions andthe components together. The specified components and dimensions wereprioritized using the Fuzzy DEMATEL method. Using the Fuzzy Delphimethod, 15 dimensions and 101 components influencing HR valuation wereidentified at National Iranian Oil Company and its affiliated companies.According to Pareto 20-80, 20 components were identified as the factorsinfluencing human resources valuation at National Iranian Oil Company andits subsidiaries, and using the Fuzzy DEMATEL method, 15 dimensionsand 20 specified components were prioritized. According to the resultsobtained, the most important dimension and component affecting humanresources valuation at National Iranian Oil Company and its subsidiaries arejob satisfaction, motivation, and perseverance in employees’ assignments.