جستجوی مقالات مرتبط با کلیدواژه « تصمیم گیری چند معیاره » در نشریات گروه « مدیریت »

In the digital age, blockchain technology is recognized as an operational innovation that is rapidly joining the field of supply chain and humanitarian logistics. Hence, blockchain technology has the potential to fundamentally change the field of humanitarian aid, but still relatively little research has been published aimed at improving understanding of the various barriers to blockchain adoption in humanitarian logistics. The aim of this research is to provide an integrated framework for evaluating the barriers to blockchain adoption in the field of humanitarian logistics. To assess the barriers, integrated approach has been applied in three phases. In the first phase of this approach, based on the literature, 10 barriers to the adoption of blockchain in humanitarian logistics are identified and evaluated using the FMEA method. In the second phase, using the opinions of experts, the weights of the three factors are calculated. Then, in the third phase and according to the outputs of the previous phases, obstacles are prioritized using the proposed Z-ARAS method. In addition to assigning different weights to the three factors considering uncertainty and reliability in barriers is also considered in this approach through the theory of Z numbers. The proposed approach of current study was implemented in the evaluation of blockchain adoption barriers in humanitarian logistics. According to the results, the most critical barriers concern with integrating issues, risk of cyber-attacks, and technology risks. The results shown the capability and superiority of the proposed approach compared to other traditional methods such as FMEA and Fuzzy ARAS.

In the context of the Fourth Industrial Revolution, advanced technologies are reshaping production and business models across various industries, offering new opportunities for enhanced competitiveness but also introducing challenges in terms of adoption and optimization (Wong et al., 2020; Khan et al., 2021). Notably, the convergence of advanced technology and humanitarian logistics is crucial, especially in addressing natural and man-made disasters (Ar et al., 2020; Dubey et al., 2020). This necessitates effective management and the combination of humanitarian logistics with blockchain technology, although this integration comes with multifaceted challenges (Baharmand et al., 2021).
To address these challenges, we explore the Failure Modes and Effects Analysis (FMEA) method as a systematic approach to identify and assess barriers and risks. Traditional FMEA approaches rely on subjective evaluations, which introduce uncertainty into the results. In this context, our research aims to introduce an innovative approach that addresses these limitations by integrating the ARAS method and Z-numbers theory. This approach allows for more reliable prioritization of barriers related to blockchain technology adoption in humanitarian logistics, enhancing the robustness and effectiveness of decision-making processes. In this extended abstract, we present our method and compare its outcomes with traditional approaches to prioritize barriers and risks in blockchain technology adoption within humanitarian logistics. Also, the barriers to blockchain technology adoption in humanitarian logistics and how to prioritize these barriers are among the main research questions.

Blockchain technology is gaining traction in supply chains due to its diverse applications and unique advantages. As supply chains face increasing disruptions, blockchain technology adoption can address challenges and enhance performance (Akhavan & Philsoophian, 2022; Hald & Kinra, 2019). Blockchain structures data into interconnected blocks, ensuring the security and transparency of transactions (Akhavan & Namvar, 2021; Azizi et al., 2021). Blockchain technology is appealing for supply chains due to four main characteristics: encouraging data sharing, minimizing fraudulent transactions, ensuring data immutability, and providing asset security (Babich & Hilary, 2020; Cole, Stevenson, & Aitken, 2019; Rahimi, Akhavan, Philsofian, & Darabi, 2022).
Research on blockchain applications in humanitarian logistics primarily focuses on motivations, such as improved collaboration, transparency, trust, cost reduction, intermediary removal, and shared participation (Baharmand, Maghsoudi, et al., 2021; Seyedsayamdost & Vanderwal, 2020). However, more research is needed in this area (Sahebi, Masoomi, & Ghorbani, 2020). Existing studies have identified barriers to blockchain adoption in humanitarian supply chains, including financial constraints, senior management support, organizational readiness, technological complexity, infrastructure, technology compatibility, and regulatory issues (Baharmand & Comes, 2019).
Multi-criteria decision-making methods (MCDM) have been used to improve FMEA's performance (Ghoushchi et al., 2021; Ghoushchi et al., 2022). These approaches often combine FMEA with methods like GRA, BWM, TOPSIS, and AHP in various fuzzy environments. Such integrated methods have been proposed for barrer identification in the context of blockchain adoption (Li, Li, Sun, & Wang, 2018; Lo & Liou, 2018; Kolios, Umofia, & Shafiee, 2017; Carpitella, Certa, Izquierdo, & La Fata, 2018; Sayyadi Tooranloo & Ayatollah, 2017). Additionally, unified methods like MOORA have been applied to address specific challenges in different contexts (Jafarzadeh Ghoushchi, Memarpour Ghiaci, et al., 2022).
The literature indicates a gap in research on blockchain applications in humanitarian logistics, as most studies focus on business supply chains. Using insights from business supply chains to inform decisions in humanitarian logistics can be misleading, given their fundamental differences (Baharmand, Saeed, Comes, & Lauras, 2021). Consequently, this study aims to address these gaps by proposing an extended FMEA approach based on MCDM methods to identify and prioritize barriers to blockchain adoption in humanitarian logistics, using Z-numbers theory.

The proposed approach of this research is presented, utilizing FMEA and Z-ARAS methods for barrier assessment. The proposed approach consists of three phases. In the first phase, barriers are identified, and the values of the criteria are scored by the FMEA team using linguistic variables from Z-number theory. In the second phase, considering the differences in the importance of criteria, the weight of each criterion is determined based on expert opinions as triangular fuzzy numbers. In the third phase, based on the results of the first and second phases, barrier prioritization is performed while taking into account the criterion weights, using the Z-ARAS method. Unlike the conventional fuzzy ARAS method, the Z-ARAS method can consider uncertainty and reliability for each criterion concerning the options. In this method, after determining the decision matrix, which comprises fuzzy numbers and reliability values (Z-numbers), these values are transformed into triangular fuzzy numbers, and then the Z-ARAS method is executed.

Humanitarian logistics is a relatively new area of research. The impact of humanitarian logistics is crucial, as it saves lives and improves conditions. Research has shown that effective humanitarian logistics is a key driver for the performance of humanitarian organizations. Currently, there exists a significant gap in humanitarian logistics research, particularly in developing countries, between theoretical research and practical implementation.
The adoption of blockchain technology will play a pivotal role in the future development of humanitarian logistics. Therefore, the identification and prioritization of barriers to adopting blockchain technology in humanitarian logistics have gained increasing importance. In this study, an enhanced approach to FMEA is proposed using the Z-ARAS method. Based on the results obtained, "Integration Issues," "Cybersecurity Risks," and "Technology Risks" have been chosen as critical barriers to blockchain technology adoption in humanitarian logistics and are given priority for mitigation and resource allocation. The use of this enhanced approach has addressed some of the limitations of the conventional FMEA method, such as not providing a complete ranking of options. While the developed FMEA approach using the Z-ARAS method is a promising and reliable method, it has limitations. This model may be complex for decision-makers, and it is expected that software tools will be developed to assist decision-makers using this enhanced approach. Additionally, the interaction and impact of barriers were not discussed in this study. Future work can analyze the interplay between barriers to identify critical barriers. Furthermore, researchers can consider multi-criteria decision-making methods like PIPRECIA, SWARA, BWM, and others to determine the importance and weights of criteria. Developing the FMEA method using multi-criteria decision-making methods such as MARCOS, EDAS, CoCoSo, and others for ranking barriers in uncertain environments, including pythagorean, q-rung, and spherical fuzzy scenarios, is also suggested for future studies. Regardless of the issue used for implementing the proposed approach in this research, this approach can be applied to identify and analyze risks and failure modes in various scenarios.

In the current competitive market of automobile in Iran and the world, business partners play a key role in the success or failure of any organization. In fact, the survival, growth and development of businesses will depend on determining a strategic business partner. Therefore, choosing an experienced business partner is essential and requires the use of a precise decision-making method. In this paper, a multi-criteria decision-making method with the purpose of evaluating business partners is presented. This evaluation and ranking method is able to identify the interaction between criteria and consider it in the ranking process. At first, 22 variables corresponding to the conditions of the Iranian automobile industry were selected as criteria and 15 Chinese automobile companies were selected as alternatives. Then, Shannon's entropy technique was applied for weighting the criteria. Finally, the alternatives were ranked by the Choquet integral method. Next, the proposed technique was validated through comparison with TOPSIS method and the results were analyzed and compared. The results of the implementation of introduced technique indicate that the combination of Choquet integral decision-making method and Shannon's entropy is a simple, novel and also practical method and will be applicable in the real world.

In the field of transportation in the distribution network, route optimization is of great importance because it can reduce costs, increase efficiency, and improve service quality. In this paper, a new method to optimize the transportation route in the distribution network using fuzzy AHP multi-criteria decision making is introduced. First, using the fuzzy AHP method, various criteria such as distance and time, cost and service quality are evaluated. Then, by using the matrix of integrated fuzzy comparisons of the criteria, the preference of each criterion over the other is determined. In the next step, in order to improve the accuracy and efficiency, the sub-criteria related to each criterion are evaluated. Using the matrix of integrated fuzzy comparisons of sub-criteria and the normalization method, the degree of preference of each sub-criteria is determined and we rank them. According to the results obtained from the preference of criteria and sub-criteria, different transportation routes can be improved and optimized based on preferences and normalization of preferences. The results show that the use of fuzzy AHP multi-criteria decision-making in the optimization of the transportation route in the distribution network leads to improved efficiency and reduced costs, and ultimately increases the quality of services.

This study was conducted to design a performance evaluation model for high school principals of Tehran using fuzzy logic.

In this applied research, the mixed approach method with two statistical populations has been executed. In the qualitative section, 20 experts, and in the quantitative section, for the purpose of selecting districts and schools in the city of Tehran, 5 districts (2, 3, 4, 3, 6 and 12) were selected. The statistical population is consisted of 150 individuals from the Tehran Ministry of Education and school principals, teachers and parent associations of the districts, estimated from the entire population census. The data collection tools in the qualitative part were semi-structured interviews for determining the components and indicators using Pseudo fuzzy and quasi TOPSIS-fuzzy methods. In the quantitative part, the mentioned components and indicators were utilized to design a questionnaire. With the implementation of Multi Source Feedback and Performance Significance Analysis, the performance of principals was assessed.

Exploited from books, 97 indicators in the form of 5 main components were identified and with the approval of experts, 26 final indicators were confirmed. Next, the weights of the indicators were determined using Best-Worst Method, DEMATEL and Network Analysis Process. For establishing the questionnaire, content and structure validation was used. The content validation was confirmed by the experts and for assessing structure validation, two convergent and divergent validity criteria were created, leading to a variance mean of 0.980, representing high convergence of the structure.

The qualitative results indicate that the components of personality traits and communication skills had the most weight. The quantitative results show that the main indicator of personality traits and communication skills has the highest rank and priorities among the five indicators, while the decision-making skills indicator has achieved the lowest weight and priority.

The main purpose of this study is to Measuring the efficiency of technological units in strategic industrial by regional development aspect. To achieve this goal, first define the criteria for regional development and after weighing these criteria, define the indicators for measuring the efficiency in terms of regional development and finally extract the units efficiency.Research

This research, from the perspective of research orientation, is applied and based on quantitative and qualitative methods. The research strategy is descriptive-survey, from the perspective of the purpose, descriptive, from the perspective of time horizon, cross-sectional and from the perspective of the method of data collection from interviews and documentary studies. The fuzzy Delphi method has been used to determine the criteria for regional development, the fuzzy hierarchical analysis method has been used to weight the criteria, and the fuzzy TOPSIS method has been used to rank the performance indicators. Finally, the efficiency of the units was obtained by Data Envelopment Analysis method.

In this study, 8 regional development criteria appropriate to the research topic were introduced. Then, the weight of these criteria was determined and 22 input indices and 22 output indices of technology units were ranked with these criteria. Finally, 18 units ranked in terms of efficiency.

Saffron and dairy production industrial companies had the highest efficiency rank in terms of regional development.

The multitude of projects and the complexity of making decisions about them, as well as planning and allocating the organization's limited resources to the selected projects, are the main challenges that many project-oriented organizations face. Considering all organizational aspects in obtaining projects is the most key point in the success of project-oriented organizations. For this reason, choosing a portfolio of projects in a way that can meet the goals and strategy of the organization, in addition to considering the organizational limitations, is very vital. For this reason, in this research, while emphasizing the implementation of the portfolio management process in organizations, a two-stage model is presented for evaluating and prioritizing projects to form an optimal portfolio. By examining the life cycle of projects, first, 12 influential indicators in the evaluation of projects are extracted with the help of previous research, and after the confirmation of 8 important indicators by experts, they are analyzed with the help of fuzzyDematel technique, and the weight of each indicator is determined. In the next step, the proposed projects are evaluated and prioritized using the fuzzy TOPSIS technique. Finally, taking into account the capabilities, assets and limitations of the organization, the optimal portfolio of projects is formed and approved by the decision makers. By implementing the above model in a construction company active in public and private projects, it was found that the analysis of relationships between indicators helps a lot to choose the optimal portfolio and prepares the ground for achieving the set goals.

Developing countries like Iran face increasing energy demands due to population growth and economic expansion. The country has numerous renewable energy resources that account for the majority of its total energy supply. As fossil fuel resources are running out, the government plans to increase its renewable energy share. Many studies have already been conducted on renewable resources. However, the interdependence between the criteria used to evaluate renewable resources has not been considered. This paper presents a planning, decision-making, and policy framework for renewable energy based on the Analytical Network Process (ANP). ANP is a multi-criteria analysis method and provides a tool for determining the relative importance of all criteria that affect the decision objective. This process allows us to identify dependencies and include them in the multi-criteria evaluation and decision-making method from the point of view of a group of experts and professionals on the subject. The case study of this research is related to the country of Iran, and strategic criteria such as technology, economy, environmental, political and social impacts are calculated and priorities for renewable energy are set and analyzed. The results of this study show that solar energy is at the top of energy alternatives for the country. Such studies help countries to make the best use of their renewable energy sources

One of the most important issues in the field of sustainable supply chain that affects the environment is the amount of contamination generated by the supply chain facilities. Failure to pay attention to this issue will have many economic, social and environmental consequences. Therefore, this research addresses this issue. In this study, a novel model for design of sustainable supply chain network is proposed where only environmentally friendly facilities can operate and others should be repaired or renovated. Furthermore, in order to increase the development and improve the living and social conditions of the people, in the proposed model, location of manufacturers is selected from among less developed regions with greater growth potential. To calculate the growth potential of the regions, criteria such as proximity to neighboring countries with higher GDP, unemployment rate, number of mines, etc. are considered and integrated with multi-criteria decision-making techniques. The methodology of this research is that first, the scores are calculated for each region by the decision-making methods, and then the problem including these scores is optimized. The modeling includes two stages of calculating the growth potential score of each region with multi-criteria decision-making techniques and then formulating a sustainable supply chain network problem. Finally, performance of the proposed model and reduction of environmental impacts to improve the sustainability of logistics systems are investigated and illustrated in a case study. In order to validate the model, several different sensitivity analyzes are presented. The results of computational analysis show efficiency and effectiveness of the model.

Due to increasing environmental regulations and restrictions, and increasing social awareness, in order to meet sustainable development goals, government oversight of environmental and social issues in organizations has become stricter. Therefore the aim of this study is criteria identification and sustainable iron ore supplier ranking of Isfahan Steel Company using a new multi-criteria decision-making method, named MARCOS. This research is applicative which performed by qualitative- quantitative method. The statistical population of this study was the raw material purchasing experts, which ten experts were selected by purposive sampling. In the qualitative part, the criteria were identified by thematic analysis. Then, AHP method has been used to calculate the weight of criteria and finally, using MARCOS method, ranking and evaluation of seven major suppliers of iron ore with emphasis on sustainability principles has been done by MATLAB 2019a software. Based on the results, fifteen criteria have been identified in three sectors: economic, social and environmental, which after calculating the weight of the criteria, quality, delivery, and social responsibility, and reliability, adherence to laws, pollution control and distance were more important. It should be noted that the criteria identified in this study were in good agreement with available literatures. Also, the results obtained from MARCOS method were consistent with the results of TOPSIS, COPRAS, VIKOR and SAW methods.

Studies show that there is a significant relationship between human resource strategies and the overall strategy of the organization. Also, the degree of coordination between human resource strategies and the organization's strategy affects the overall performance of the organization. The purpose of this study is to investigate the correlation between the dimensions of the model of alignment of human resource strategies with the strategy of the organization in the field of succession management in the National Iranian Oil Company. The sample members are 120 managers that, knowing the subject matter, also have been appointed to supervisory / managerial positions. The research tool is a researcher-made questionnaire that was extracted based on the standard process and based on a qualitative analysis and then its standardization steps were performed during quantitative research, then, The collected data were analyzed with SMARTPLS software. Findings indicate that The highest correlation coefficient was related to the strategy variables with the interventionist conditions with a correlation coefficient of 0.603, also significant at the level of 0.01., and The lowest correlation coefficient obtained with the main category variable with contextual factors with a correlation coefficient of 0.107, which is not significant at the level of 0.05 .

Research and development (R&D) department is an essential and critical section for all organizations, which are eager to actively participate in markets and strategies on R&D management. Today’s investment in this field has been approved and all organizations are aware of its role to increase competitive risk. Improving R&D departments and promoting the efficiency of companies can help a country to move toward knowledge-based economy and also assist to stop illogical exchange currency flow to foreign countries against import of technology transfer from them. A problem in a domestic market is the lack of the R&D strategy to produce new products and promote the customer’s satisfaction level in industrial companies. The objective of this research is to introduce a two-phase decision-making approach to assess R&D strategies in automotive battery industries stressing on the customer’s satisfaction parameter. In the first section, the practical strategies on R&D management and the effective indices of the customer’s satisfaction on R&D strategies are recognized. In the second section, weighting coefficients related to customer’s satisfaction indices are reached by utilizing the fuzzy best-worst method (FBWM) as an effective multi-criteria decision-making (MCDM) method. Moreover, the weight of any individual strategy and their final prioritization is calculated using the analytical method of the interval-valued triangular fuzzy - gray relation analysis (IVTFN-GRA). Based on the results gained from the proposed FBWM, three effective factors in evaluating R&D strategies in an automotive battery industry are recognized. Finally, among the existing strategies, the joint R&D strategy with 0.375 rate is selected

Technology-based companies have a good capacity to enter foreign markets due to their technological advantages. The purpose of this study is to provide a decision-making method to prioritize foreign entry modes. Therefore, the research method is a combination of qualitative approach in criteria identification and quantitative approach in prioritizing criteria and entry modes. Frist, by reviewing the research background, influential components on entry mode choice have been identified, including internal factors (organization and its products), and external factors (internal market and foreign market). Then, using the best-worst method the effective criteria for entering foreign markets are ranked. The results show that “product differentiation” and “networking” are the most important ones for these firms. the experts’ view. This is in line with the technological advantage of these companies and on the other hand the limited resources of small and medium companies for foreign investment. Second, from the perspective of a technology-based company with extensive international activities in the field of advanced machinery, entry modes are prioritized using TOPSIS. The results showed that the first choice is the establishment of a wholly owned subsidiary. Actually for the company that has gone through the early stages of internationalization, this method is preferred, both for providing protection of the company's proprietary technology, provides the basis for exports to neighboring countries; also it can indicate that export restrictions from the origin of Iran, increases the orientation of firms towards more risky entry methods.

The aim of this study was to investigate the capability of value chain of industrial clusters and its ranking in Arak province. The ranking is based on the indicators and capabilities obtained using multi-criteria decision-making method. This research is descriptive and applied. Data were collected using experts' surveys and two questionnaires of pair comparisons and an index importance questionnaire for each industry and extracted data from statistical resources and official reports of relevant organizations. In this research, literature has been reviewed and then the indicators of industrial cluster formation have been studied. After interviewing the experts of flour, dairy, handmade carpets, agricultural equipment, poultry farming, handicrafts have been selected for prioritization. In data analysis, an ANP method, which is one of the multi-criteria decision-making methods, has been used to prioritize the mentioned industries for the formation of industrial clusters, and entropy method has been used to weigh the indicators in each industry. Super Decision software is used to solve multi-criteria decision-making model. Finally, industrial clusters of Golestan province were ranked as handmade carpet clusters, dairy clusters, poultry clusters, agricultural equipment clusters, flour clusters and handicraft clusters, respectively.

One of the most serious and practical discussions in most planning and management systems is choosing the right option. Economic, communication, industrial, social systems and Information processing methods, on the one hand, and subtle decision-making conditions, high ambiguities, and environmental complexities, on the other hand, have increased the need for this process, given the intense competition in the automotive industry. Therefore, leveling the factors affecting the quality of car parts for each car manufacturer is a big challenge considering the different goals and criteria that exist for that company. The aim of this research is to level the factors affecting the quality of mechanical parts of the car (engine) with a multi-criteria decision-making approach (MCDM ) using DEMATEL technique for the parts manufacturing company. In this study, using reference books and experts' opinions, the factors affecting the quality of automotive mechanical parts are identified and then using the Delphi method, the screened factors and the most important factors are then selected by DEMATEL method. These factors have been reviewed and finally leveled.

Studies show that there is a significant relationship between human resource strategies and the overall strategy of the organization. Also, the degree of coordination between human resource strategies and the organization's strategy affects the overall performance of the organization. The purpose of this study is to investigate the correlation between the dimensions of the model of alignment of human resource strategies with the strategy of the organization in the field of succession management in the National Iranian Oil Company. The level of analysis in this study was organizational and the sample members are 120 managers that, knowing the subject matter, also have been appointed to supervisory / managerial positions. The research tool is a researcher-made questionnaire that was extracted based on the standard process and based on a qualitative analysis and then its standardization steps were performed during quantitative research, then, the collected data were analyzed with SMARTPLS software. Findings indicate that the highest correlation coefficient was related to the strategy variables with the interventionist conditions with a correlation coefficient of 0.603, also significant at the level of 0.01., and the lowest correlation coefficient obtained with the main category variable with contextual factors with a correlation coefficient of 0.107, which is not significant at the level of 0.05.

Accurate understanding of knowledge requirements is one of the features of competitiveness mechanisms in the Organization. The existence of knowledge management entity in an organization emphasizes its importance on achieving sustainable competitive advantage. In this study, effective and key indicators to improve knowledge management strategy in the Tarasht power plant to achieve the organizational goals, by referring to similar internal and external studies, were identified. Then, by using efficient DEMATEL method, a framework of factors was identified along with the relationships of affectivity and cross-effectiveness. Finally, important and effective factors to improve the knowledge management strategy in the case study firm were identified. The statistical population of this study is the expert staff in the field of knowledge management in the organization. The main tool for data collection in this study is questionnaire. In this regard, after identifying the criteria of the subject, their causal relationships by experts were examined. Data by using DEMATEL method were analyzed. The results showed that most important factors are: teaching and learning, staff participation and human resource empowerment. Indicators of top management support, organizational structural infrastructure, information technology infrastructure and organizational culture are among the influential factors; and other factors such as education and learning, employee engagement, and goals and strategies are influential factors. The purpose of these factors is to enhance and improve the knowledge management strategy in the organization

Today, developing Medical tourism especially for developing countries is one of the sources of income. If any development in the body of tourism not within the strategic planning framework, and which does not consist of continuous control and preventive actions, will, in different dimensions, meet negative and irrecoverable impacts. Hence, the present study is to examine the position of medical tourism in Shiraz in order to formulate appropriate strategies for proper and comprehensive development. This research method is a combination of surveys and descriptive-analytics. 80 medical tourists and 20 medical tourism experts were selected as a random sample, and, for samples, strategic factors through questionnaires were distributed. Data collected were set in the framework of the Strategic SWOT model, and computational steps were computed using decision-making method based on Fuzzy-TOPSIS. Analysis of findings showed that according to the focus of the first, second, and third strategy obtained from combining Comments of sample groups, focus strategy to action is an aggressive one.

Technology transfer and the employees’ inclination to accept it is not always an easy process as they tend to be resistant to it. This paper intended to use leadership styles to present a model which could facilitate technology application by employees. The research was conducted in two phases: in phase one, technology acceptance criteria were identified and graded from the most relevant to the least relevant by ten experts selected from among Iranian university professors and defense industry specialists. Then, based on the acquired weights and by using Multimoora method, leadership styles indexes were prioritized. In the second phase, with the help of the same experts, indexes with higher grades were classified and relations among them were determined by applying interpretive structural modeling technique. Findings show that strategic leadership orientation, ability to establish leader communication and leader’s decisiveness are the most effective in facilitating employee’s technology acceptance.

One of the features of the new business world is increasing competition. Organizations that want to increase their market share or are able to adapt to such an environment must adapt to changing environmental conditions. Hence, many changes in business practices are taking shape. One of them is Business Process Reengineering (BPR), which Michael Hammer defines as business process redesign as a revolutionary way to achieve significant improvement. Because reengineering theory is a relatively new theory for improving business, its methods and approaches are still evolving, and since the application of reengineering concepts can take many forms, its methods are different because of the emphasis on certain factors in an engineering project. Again, it will be different for another project. Having such an idea in the present study, we decided to carry out a thorough analysis in the study organization in line with the desired topic. Therefore, while studying scientific methods, we paid attention to the analyzes and opinions of experts and specialists working in the mentioned system (through interviews and questionnaires), so that we can find a comprehensive and accurate knowledge of ongoing processes and correctly identify the factors affecting failure. Establish process reengineering systems to exploit them and select the most important of these factors and prioritize them according to their degree of importance. Then, among the various prioritization methods, we used the Analytic Hierarchy Process (AHP). Prioritization calculations were performed using the decision tree and the process analysis model. Important factors, indicators and sub-indicators were identified and prioritized, and this prioritization provided a tool for obtaining results and making suggestions, which is mentioned at the end of the discussion.

The existence of an active and prosperous capital market is always recognized as one of the signs of international development in the countries. The most important issue faced by investors in these markets is the decision to choose the appropriate securities for investment and formation of optimal portfolio. The rating of companies accepted in stock exchange is a complete mirror of their status and is a measure of investment. This will increase the competitiveness, development and market efficiency. In this research, the top 20 companies listed in Tehran Stock Exchange during the third quarter of 2015 are ranked according to financial ratios. In previous studies, optimal portfolio has been determined using data envelopment analysis models and multi-criteria decision making techniques, but the present study combines these two techniques to evaluate and determine the most efficient portfolio. Accordingly, the performance scores of each model are obtained using one of the data envelopment analysis model and then, the weight of each index is obtained using the network analysis process through multi-criteria decision-making techniques.