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There is a close relationship between economic growth and energy consumption. Price is one of the most important parameters which affect energy demand and consumption. Thus, investigating the factors which affect the pricing of different forms of energy is very important. The purpose of this study is to identify and rank the most important factors that influence the pricing of renewable energy in Iran. In this study, we use Analytic Network Process to combine social, economic and environmental aspects in order to provide a comprehensive view about the most important factors affecting renewable energy pricing in Iran. The results show that in 1392, economic, financial & technical factors are respectively the most important factors in pricing of renewable energies in Iran.    

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According to great number of experts, having a distinct positioning regarding other competitors in one or more cases, are Critical factors of industrial success. These CSFs can create a golden and exceptional opportunity to gain a competitive advantage. Therefore, main goal of this study is to identify and prioritize CSFs in lubricants industry of Iran. Research method is practical use and as data collecting method is descriptive – survey. Interviews and questionnaires used to collect data in research population which is Iran lubricants industry experts. In this study, Thompson and Strickland models has been used to identify these factors. This model define critical success factors in seven different dimension and sets indicators for each one. Based on those factors and network analysis process a questionnaire has been prepared and has been placed at the disposal of industry experts. Obtained data were analyzed by using "super decision" software and five factors of " experience in product innovation", "technical knowledge", "production quality", "access to raw materials and additives", "access to skilled labor" were identified as critical success factors in this industry.  Therefore successful companies in this field can gain the competitive advantages investing on these factors.

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Supplier development refers to the purchaser activities to improve supplier performance in the areas of quality, cost, time of ordering to delivery, service, reliability, and promotion of suppliers knowledge which positively affects the operational and business performance of purchaser. The present study deals with suppliers' development strategies including enhancement of suppliers’ quality improvement systems, data exchange with suppliers in the areas of quality, suppliers’ process improvement, suppliers’ productivity enhancement and contribute to the development of the suppliers’ product by the Balanced Scorecard (BSC) approach, Analytic Network Process (ANP) and Revised Decision Making Trial and Evaluation Laboratory (Revised DEMATEL) techniques. The population of the current research consists of the foundry companies having more than 200 subject as human resources in Iran which manufacture the automobile parts. The research findings have shown that financial perspective (0.5417) ,  learning and growth perspective (0.0688) are respectively the most important and the least important dimensions to improve organization performance. in addition , information exchange with suppliers in the areas of quality (0.30) and suppliers' productivity increasing (0.11) are respectively the most and least important strategies in suppliers' development.

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In both the quality improvement and the design of a product, primarily the engineering characteristics affecting product performance are identified and improved to optimize customer needs (CNs). Especially, the limited resources, increased market competition and product complexity require a customer-driven quality management and product development system to achieve higher customer satisfaction. Quality Function Deployment (QFD) and its House of Quality (HOQ) are used as powerful tools for improving product design and quality, and procuring a customer-driven quality system. In this study, an integrated framework based on fuzzy-QFD and a goal programming model was proposed to determine the technical requirements (TRs) to be considered in designing a product. The coefficients of the mathematical model were obtained from a fuzzy analytic network process (ANP) approach. Furthermore, the proposed analytic procedure should take into account the multi-objective nature of the problem, and thus, incorporate other goals such as cost, extendibility, technological feasibility and competitiveness of TRs. Finally, the model, a zero–one goal programming methodology, includes the important levels of TRs deriven using the fuzzy ANP, cost budget, feasibility level, extendibility level , and competitiveness level as system constraints to determine the TRs to be considered in designing the product. An application for YEKTA washing machine powder in PAKNAM Company (Tehran, Iran) producing detergent products was presented to illustrate the proposed framework.

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A part of management of solid waste related to site selection for healthy landfill. some method and technique delivered for site selecting. Among them analytic network process (ANP), a multi-criteria decision-making technique have some priority that can be a proper model for site selection because represents a framework with a bidirectional relationship. the ANP allows for complex interrelationships among decision levels and attributes. The ANP feedback approach replaces hierarchies with networks in which the relationships between levels are not easily represented as higher or lower, dominant or subordinate,direct or indirect. The elements of a cluster may influence some or all the elements of any other cluster.therefor. This paper addresses the problem of solid waste location selection using the analytic network process (ANP), a multi-criteria decision-making technique. The ANP technique enables us to consider both qualitative and quantitative criteria as well as the interdependencies and feedbacks. Selection of the appropriate landfill site is a complex problem and requires an extensive evaluation process considering the requirements of public sector, governmental, environmental objectives, etc. A number of criteria (social, environmental and technical) and their sub-criteria were considered for sitting a landfill on the Qucahn as the case study. The process of site selection was performed through some steps that will be discussed throughout the paper in detail. Finally, the suitable land units for landfill were selected.

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One of the common problems in manufacturing firms is selecting the best manufacturing system with regard to firm capabilities, market situation, competitors and political and economical issues. Just-In-Time system is one of the best manufacturing systems, which has many benefits. In contrast; implementation of this system is very difficult because of various constraints. Therefore, manufacturing managers encounter the problem of using or not using this system in their firm. In this article, a decision making model based on Analytic Network Process (ANP) is presented for analyzing this problem in a printing factory for finding the appropriate manufacturing strategy. To sum up, the decision making criteria were determined by studying the literature, relevant articles and using Nominal Group Technique among the experts. Then, the related decision making model was prepared by expert interviews. Finally, the best strategy was selected by paircomparison and solving the model.

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Suitability analysis is a prerequisite for sustainable agricultural production and it involves evaluation of the environmental parameters. The development and creation of appropriate points for this land use without considering environmental capability will result in the appearance of several ecological, economic, and social problems. The Multi-Criteria Decision Making (MCDM) Models were used for solving such problems. Takestan-Qazvin region is one of the biomes that have difficulties due to lack of a systematic administration on environmental resources. This research was done in the framework of the ecological model and by using multicriteria decision making methods such as Analytic Network Process (ANP), Simple Additive Weighting (SAW) and Vlse Kriterijumska Optimizacija I Kompromisno Resenje - Analytical Hierarchy Process (VIKOR-AHP)in GIS environment with the aim of choosing the suitable locations for agricultural land use in Takestan-Qazvin Plain. However, the purpose of this study was twofold: first, it was aimed at determining the ecological capability of agricultural land use by using ANP and SAW methods. Second, the suitable agricultural alternatives in this region were ranked using the integrated VIKOR and AHP models. In these methods, the ratings and the weights of the criteria are known precisely. Ecological factors such as physical and biological parameters and economic - social factors were chosen as the major criteria affecting the agriculture land use. The research indicated that north parts of the study area were not suitable for agricultural development. Finally, the conclusion showed that the application of decision making models could be useful in environmental capacity evaluation of agricultural land use.

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Agricultural sector plays a fundamental role in development, especially in developing countries. Investment in targeted agribusinesses can develop and improve agricultural value chains. Because of capital shortages and different investment requirements of the sector, the capital allocation has become an important decision-making issue for managers and investors of the agricultural sector in recent years. Investors have many alternative investment options in the agriculture sector and factors such as return on investment, investor expertise and interest, government policies, and the comparative advantages of each region can affect the direction of the capital to different agricultural subsectors. The main objective of this study was to investigate investment priorities in the livestock and poultry value chains of Khorasan Razavi Province in Iran. This paper employs the Analytic Network Process (ANP) model for agribusiness investment decisions, which is one of the important Multi-Criteria Decision-Making (MCDM) methods. The contribution of this research is that it ranks agribusiness activities on the livestock and poultry value chains and determines the most important areas for investment direction. The results show that “government policies and laws” are the most important factor for business selection in the livestock and poultry subsectors. Furthermore, livestock and poultry feed businesses contribute the most to the progress of the value chains. Therefore, stability in policy-making and appropriate legislation to support agricultural businesses can be effective in this regard.