حبیب زارع احمدآبادی

Public budget allocation refers to the process by which governments determine how to distribute their financial resources among various social needs and priorities. It is a complex and multifaceted process that involves decisions with profound consequences for citizens' welfare and the overall functioning of society. Budget allocation influences the amount and quality of public services such as healthcare, education, and infrastructure and can also affect economic development and the distribution of wealth within a country. In recent years, there has been a growing interest in examining how public budgets are allocated and whether current methods and priorities align with societal needs and values. Continuous fluctuations in budget allocation policies in Iran, especially in critical areas such as education and healthcare, have led to regional inequalities. To address this issue, a planned and sustainable approach to credit distribution is required—one based on the actual needs of each province and aimed at balanced development. In this context, the present study aims to propose a performance-based planning model tailored to the nature of the problem for the distribution of provincial capital credits. The objective is to achieve macroeconomic and social goals, including reducing income inequality, alleviating deprivation, increasing production and employment, lowering unemployment rates, and enhancing social well-being, all based on the performance of the provinces.

The approach used in this research is mathematical modeling based on a conceptual framework that applies data envelopment analysis (DEA) in a novel way. As a case study, the model has been tested in the education and healthcare sectors. In the proposed model, specific values of deviation in variable values (delta) are determined by experts based on national and provincial credit distribution policies. Additionally, the allocation of budgetary resources is determined based on the performance evaluation and ranking of provinces to achieve predefined goals.

The implementation of the model using 1401 data demonstrates its efficiency compared to conventional and previous capital credit distribution methods employed by Iran's Planning and Budget Organization. The results indicate that the proposed method not only enhances accountability for achieving set goals but also facilitates continuous improvement by enabling provinces to learn from past experiences and make informed decisions for future activities.One of the most significant features of this model is its adaptability to budgetary changes. The model’s inputs can always be modified based on new policies, ensuring its relevance and applicability over time.

The proposed two-phase approach begins with the DEA model to align with the nature of the problem and assess provincial performance. In the second phase, a credit change management approach is employed for sensitivity analysis. A key distinguishing feature of this model is the expert-driven determination of delta values based on national and provincial credit distribution policies. Additionally, each province’s optimal share of total allocated credits can be calculated and received, providing policymakers with a crucial tool to enhance the efficiency of provinces and guide them toward an optimal state.

Due to the contradictions of lean and agile approaches and meanwhile, their synergy, choosing, combining, and implementing these approaches with specific goals, strategies, and limitations is a key challenge for supply chain managers. The current research aimed to develop a dynamic system for implementing lean and agile approaches in the supply chain.

 THEORETICAL FRAMEWORK:

Supply chain management includes the planning and management of all activities involved in the supply chain and is considered a vital factor in the competitiveness of organizations. Lean and agile approaches are among the popular approaches in supply chain management. Lean philosophy seeks to eliminate waste and reduce costs based on more output with fewer resources according to customers' needs. Governing lean thinking and principles in the value stream is called lean supply chain management. Quick response to changes in demand, in terms of volume and variety, is called agility. The concept of this approach refers to choosing the right strategy in conditions of uncertainty and providing products and services to customers at the right time and place. Empowering new competencies to respond quickly and effectively to the market is called agile supply chain management. These two approaches have different drivers, prerequisites, and strategies, and each one pursues a specific goal.

The present study is in the category of qualitative-quantitative research. Based on the stages of research in the conceptual development stage, the model is placed in the category of qualitative research. At this stage, by content analysis of the research background, factors affecting the selection of agile and lean approaches have been identified. This stage includes four main steps: problem definition, data collection, analysis, and presentation of the final model. In the quantitative stage, using the system dynamics method, using the factors obtained from the first stage and lean and agile strategies, a model has been presented to evaluate the performance and choose the appropriate strategies in different conditions. Causal models and state flow have been drawn and model evaluation tests, structure evaluation, and sensitivity analysis have been done to confirm the model validity. Finally, different scenarios have been simulated and analyzed in this model. The information required for modeling and simulating the model has been collected from the Yazd Rubber Industries Complex.

In the qualitative stage and after content analysis by reviewing articles and zigzag coding, 106 codes from 31 studies were identified as open codes. In this study, it was done. By repeatedly reviewing the identified primary codes and comparing them, the codes with common content and concepts were classified under one concept. In this way, 40 subgroups were extracted. Finally, these codes were classified into 17 groups and 4 general levels of environmental, organization-related, product-related, and functional factors. After extracting the influencing factors on the selection of lean and agile approaches, the flow model has been presented and evaluated in Vansim software. After obtaining the valid model, by changing different variables and scenario analysis, approaches have been analyzed in three different scenarios. A comparison of selected scenarios and policies for each condition shows that, as a strategic strategy, eliminating waste is a priority in all scenarios.

CONCLUSIONS & SUGGESTIONS:

The current research has theoretical and practical implications. This research is a response to the need for a systematic and comprehensive framework of vital factors in choosing appropriate agile and lean approaches. In this article, the knowledge available in the literature about the agile and lean approach in the supply chain is organized to develop a model for choosing appropriate approaches. On the other hand, organizations do not need fixed degrees of leanness or agility in different situations. The presented dynamic model can examine specific strategies of lean and agile approaches in different conditions and finally provide certain degrees of lean and agility. In the situation that in previous studies, the combination of these two approaches is usually discussed and less attention is paid to the effect of conditions on the level of leanness and agility. Although this study tried to present a dynamic model for choosing lean and agile strategies with a comprehensive look at all conditions, due to the existence of other approaches such as resilient and green, future studies may examine other effective factors and strategies to present a more comprehensive model.

Currently, the world is living in the era of the fourth industrial revolution. Although this era provides many opportunities for companies and organizations due to technological advances, it also presents many challenges. One of these challenges is the need for a set of new competencies that occur due to the transformation of the nature of jobs through digitalization in Industry 4.0. Hence, the purpose of the current research is to identify the skills needed in Industry 4.0 and provide a cognitive analysis of it. This research is classified as applied research and employs an exploratory mix method approach regarding data collection. The statistical population for this research includes experts in the steel industry (middle to upper managers). A sample of 10 experts from this sector were selected to complete the questionnaire, using a purposeful sampling method. Then, using the opinions of 10 experts of the steel industry in Yazd province, the collected data have been analyzed through the methods of intuitive fuzzy TOPSIS and intuitive fuzzy cognitive map. The competencies of Industry 4.0 in the steel industry were prioritized through intuitive fuzzy TOPSIS and the relationships between measures to improve competencies were explained using the intuitive fuzzy cognitive mapping method. The obtained findings indicate that the index of willingness of managers and owners of companies to move towards intelligentization and the creation of smart factories is more central than other measures, and as a result, more attention should be paid to it. Also, in the prioritization of competencies, it was found that customer-oriented competency has the highest priority.

this research, with the aim of evaluating the green innovation ecosystem and the way of green science and technology policy of selected European countries in order to ensure that Europe is moving towards minimizing Carbon, holistic sustainable development, and the green, innovative and competitive economy are on the move. This research is trying to provide a set of useful input, mediator and output indicators to determine the model indicating the stages affecting the performance of the green innovation ecosystem of the selected countries by examining the background of similar research. By collecting the available data through data banks, and preparing the ground for mathematical modeling, the mathematical model was designed by combining methods of network data envelopment analysis and game theory with the help of Lingo software to combine relative efficiency in functional areas and create a Calculate the final weighted score to evaluate the performance of the green innovation ecosystem for EU member states. The results indicate that according to the designed conceptual model including four stages of knowledge creation and development, knowledge implementation, financial and economic transformations and environmental protection, with the change in the performance of countries in the stage of financial and economic transformations, efficiency The total number of countries increases significantly;

Knowledge management is considered a strategic necessity, ensuring long-term superiority for organizations and communities through the effective utilization of human and informational capital. Organizational knowledge management is recognized as one of the fundamental components for the success of organizations in the information age. Effective implementation of knowledge management leads to improved performance and processes. However, this requires a precise understanding of knowledge management concepts, especially its fundamental stage of deployment and implementation, as well as a thorough comprehension of its essential components. Green Knowledge Management (GKM) is a novel approach to knowledge management that emphasizes the creation, sharing, and application of knowledge related to environmental issues. Its main objective is to assist organizations and communities in achieving sustainable development by enhancing awareness and knowledge in the environmental domain. The lack of requisite skills among individuals and organizations can pose a significant challenge for implementing green knowledge management, as individuals must possess the necessary skills to create, share, and apply knowledge related to environmental issues. In addition to the aforementioned challenge, the absence of appropriate infrastructure for implementing green knowledge management, such as a lack of access to information and communication technologies, can hinder the implementation of green knowledge management. The research aims to present a suitable framework for evaluating the performance and efficiency of green knowledge management in European Union member countries as decision-making units. This is achieved by employing the Data Envelopment Analysis (DEA) technique while considering the inputs of the number of researchers and the amount of capital allocated for the development and management of green knowledge. Additionally, green technology is considered the tangible output of applying green knowledge, marking its first application in this context.
To develop a performance evaluation model based on green knowledge management, relevant research in this field was first utilized to identify the essential components. Subsequently, the European Union member countries were evaluated based on the extracted themes and sub-components using the combined Network Data Envelopment Analysis (NDEA) and Slacks-Based Measure (SBM) technique. Data from 27 European Union member countries were extracted from official databases and, after normalization, analyzed using a quantitative model.
The research findings indicate that for the implementation of knowledge management, six essential factors must be considered: the total number of personnel in research and development as input variables, the number of green patents, the number of academic publications in environmental innovation, and the level of awareness of sustainable development as intermediate variables, and finally, the level of environmental technology serves as the ultimate output variable. According to the results of the proposed model, Austria, Belgium, Bulgaria, Croatia, Cyprus, Greece, Italy, and Spain are identified as efficient countries in the knowledge creation domain within the European Union. In contrast, Cyprus, Germany, Malta, Slovakia, and Spain are recognized as efficient countries in the domain of knowledge application. It is noteworthy that while countries such as Luxembourg and the Netherlands have the highest number of researchers and the greatest level of environmental investment as input resources, Cyprus, Italy, and Greece achieved the highest output while simultaneously utilizing the lowest levels of these input variables. Consequently, these countries demonstrated superior performance in effectively utilizing green knowledge for sustainable development and were recognized as the most efficient countries. The performance gap for inefficient countries indicates the extent of change required for each variable to achieve an efficient state. Therefore, the performance gap for each input variable was calculated for each evaluated country, with the smallest difference corresponding to the number of research and development personnel. Additionally, the combined gap of the intermediate variables was reported for each country, with the smallest difference pertaining to academic publications in the field of environmental innovation.
To effectively utilize the integrated model of Network Data Envelopment Analysis and Slacks-Based Measure Data Envelopment Analysis for evaluating the performance of green knowledge management in European Union member countries, the input variables should include the number of research and development personnel as well as the amount of green investment. The intermediate variables include the number of green patents, the number of academic publications related to environmental innovation, and the level of awareness regarding sustainable development management. Finally, the output variable is the level of development of environmental technologies. The utilization of the introduced model is recommended for evaluating the performance of green knowledge management in organizations or across different countries.

The purpose of this research is to design the excellence model of reproductive companies in the context of academic entrepreneurship ecosystem. The approach of the current research is qualitative, and the seven-step metacombination method of Sandelowski and Barroso was used. The statistical community of the research includes all the resources related to the academic entrepreneurship ecosystem and reproductive companies published from the scientific database in the period of 1390-1400 solar and 2000 to 2021 AD. Therefore, taking into account the degree of relevance to the research topic, primary sources were screened and 55 sources were selected, and coding was done on the concepts extracted from them. In total, 24 subcategories and 6 main categories were categorized. Finally, the identified codes were classified based on the content analysis approach of Strauss and Corbin's three-stage coding (open, central and selective). The identified components include environmental, organizational, educational, research, business and managerial factors. The results were presented in the form of a conceptual model for a better understanding of the excellence model of reproductive companies in the context of the academic entrepreneurship ecosystem.

Nowadays, in most countries of the world, small and medium industries play various roles in social, industrial and service arenas. An e-business is a system that is created with the aim of satisfying customers and facilitating the fulfillment of their orders using the Internet. Advances in technology offer countless opportunities for rapid market access nationally and internationally to small and medium-sized enterprises. Accordingly, infrastructures should be provided by the government to make it easier to use the facilities, and the relevant agencies should work together to create a safe and comfortable environment, away from strict regulations. In this way, the ground will be prepared for the development of the economy, the training of specialized man power and the employment of experts in organizations. The aim of this research is to develop the electronic businesses of small and medium enterprises in Yazd Province in the field of ceramic tiles using the fuzzy cognition mapping approach. Based on the nature of the research, responses are found to the questions ‘What factors are effective in the development of e-businesses of small and medium enterprises in the Iranian ceramic tile industry?’ and ‘What is the degree of effectiveness, influence and centrality of the factors?’

This study is descriptive in type. From a methodological point of view, it is based on the mixed research method, which was done in four stages. In the first stage, based on the results of a library study on the theoretical foundations and research background, the basic conceptual framework of electronic business in the ceramic tile industry was extracted. For this purpose, two statistical populations were sampled the first of which consisted of eight experts in the field of business management in Yazd Province. They were randomly selected and interviewed. At this stage, 18 factors were obtained by reviewing the literature and the research background, as a result of which a number of factors were removed, merged or added from the prepared list. Finally, 15 factors were approved by the experts. The second sample included 35 online sellers of ceramic tiles in Yazd Province who were selected to participate in the construction of the model. In the second stage of the qualitative modeling process, the causal map of the experts was extracted and analyzed. Then, fuzzy cognitive mapping was drawn by the Ucinet6 software. In the fourth stage, the degree of centrality, the effectiveness of specific factors, and the scenarios for the development of e-business in small and medium enterprises in Yazd Province were simulated in a case study of the ceramic tile industry, and the results were checked with the soft FCMapper1 software. The data and the scenarios were analyzed using the fuzzy cognitive mapping technique, and the research model was designed through social network analysis.

According to the research findings, the factors affecting the development of e-business in small and medium enterprises in Yazd Province (with a focus on the ceramic tile industry) include leadership and management factors, technical requirements, financial infrastructure, organizational image, product and service, supply chain, customer satisfaction, competitors and partners, suppliers, political and legal infrastructures, marketing and advertising, after-sales service, customer trust, investment, and organizational culture. Based on the degree of centrality, what tops the list is leadership and management factors as well as products and services. Also, the results of the analysis of the second scenario indicate that, since the managers of the ceramic tile industry try to have better leadership and management and do not take legal, political and legal infrastructures into account, they cannot hope for the progress and development of their business. In other words, management and leadership along with legal, political and legal infrastructures can lead to the development of businesses in the ceramic tile industry. According to the results of the third scenario, if we develop the product and service factor but do not pay attention to the value chain, the majority of the factors change in a negative direction, but the rate of change is less than that in the second scenario.

Finally, based on the results of this study, there are suggestions made for the development of electronic businesses in the ceramic tile industry, including the attendance of managers in various courses of management and leadership skills and market study. The accurate knowledge of customer needs is also pointed out in order to provide the products and services that are more tailored to the tastes of customers and, as a result, their satisfaction is guaranteed as much as possible.

The influence of the fourth industrial revolution on the construction industry has led to the introduction of the concept of "Construction 4.0" and the purpose of the present study was to analyze the formation of this phenomenon in Iran in a twenty-year time period through futures study. The present qualitative and descriptive research was designed with an exploratory futures study approach. In order to achieve the objectives of the research, an initial list of key drivers affecting the formation of Construction 4.0 was extracted from research records and written scientific sources, and then, by forming an expert group with the Delphi approach, they were prioritized. In the scenario-writing stage, using the methodology of the Global Business Network (GBN), four scenarios of possible futures in this field were set while creating an intersection between the uncertainties of two key drivers. The prioritization of the identified drivers in the field of creating the phenomenon of Construction 4.0 in Iran indicates that the two key factors in this field are: "Scientific cooperation of the country with the developed world" and "Technological advances in new areas". Quadruple scenarios resulting from the intersection of these two uncertainties were identified with the metaphors of Sea, Spring, Marsh, and River. It is necessary for the policy makers to strengthen scientific and technological interactions with advanced countries in this matter (such as Germany), to support start-up and innovative companies, and focus on strengthening the other identified main drivers.

The purpose of this research is to identify and investigate the relationship between the barriers to the implementation of the circular economy and Industry 4.0 in the supply chain in one of the polluting industries of the country (Yazd Glass Complex). In order to identify the barriers and categorize the barriers, the Meta-Synthesis approach was used, and in the quantitative part, in order to present the pattern of relationships between these barriers and their prioritization, the combined method of Fuzzy DEMATEL- ANP (FDANP) was used. The findings of the qualitative section included the identification of 24 obstacles in 5 dimensions. In the quantitative part, the findings showed that economic, infrastructural and technical-legal barriers are considered as causal dimensions that affect human resources and organizational-management (Effect) dimensions. Also, the obstacles of lack of expertise and knowledge of employees regarding the circular economy and Industry 4.0; Fear of unemployment and resistance to organizational and process changes and lack of funds and financial tools for training and research and development and operations are the most important obstacles in the implementation of the circular economy and Industry 4.0 in the supply chain of polluting industries such as the glass industry.

Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society and address the environmental and economic challenges related to managing organizational operations. This research aims to analyze the factors enabling the implementation of circular economy and Industry 4.0 in the supply chain of Yazd glass factories. In the initial phase of the research, a review of various articles was conducted using the meta-synthesis method to identify and categorize relevant enablers. This process resulted in the identification of 15 enablers categorized into four dimensions: economic, human resources, organizational management, and infrastructure. In the subsequent step, the Fuzzy DEMATEL technique was employed to examine the cause-and-effect relationships. The findings indicate that, within the economic dimension, the most influential enablers are "budget allocation for the implementation of circular economy and Industry 4.0" and "stimulation of demand for circular products." In the human resources dimension, "training and development of employees" and "organizational culture" play crucial roles. In the organizational-management dimension, "support and commitment of senior management" and "cooperation and networking with supply chain partners (industrial coexistence)" are highly significant. Lastly, within the infrastructure dimension, "development of information technology standards and infrastructures" and "security and protection of intellectual property rights" are considered the most effective enablers for the implementation of circular economy and Industry 4.0 in the Yazd glass factories. The results indicate that the Ardakan glass factories of Yazd should prioritize attention to economic and infrastructural enablers when implementing circular economy and Industry 4.0.

Concerns related to environmental issues on the one hand and limited resources available for different organizations on the other hand make it mandatory to pay attention to productivity and quality management of products and services, especially among small and medium- sized enterprises. The purpose of this research was to explain the relationship among factors affecting employee productivity, quality management and environmental management. The statistical population of this research is managers, employees, and supervisors of small and medium-sized companies in Yazd province, which are active in 5 industrial branches (chemical-cellulose, food, clothing, textile, mineral, metal-electrical). The data collection instrument in this research was a questionnaire. Initially, using the questionnaire of the pair-wise comparisons of identified factors and presenting a conceptual model of the study through the interpretive structural modeling, the opinions of nine managers of small and medium-sized companies in Yazd province were sought. Then, in order to fit the obtained model, using the structural equation modeling approach and Smart PLS3 software, 400 questionnaires were distributed among the employees and supervisors of small and medium-sized enterprises in Yazd province through available sampling procedure, of which 265 questionnaires returned. The results of the analyses showed that the culture of cooperation, leadership and performance feedback has a positive significant effect on customer focus and training. Also, it was revealed that training and focusing on the customer has a positive significant effect on innovativeness, environmental policies and strategies, environmental investment, defined processes and organization and management support.

Open innovation has been discussed in the management of innovation literature over past decade, which has led to the increasing recognition of its benefits, including the use knowledge inputs accelerate domestic innovation and expanding the market for using innovation in small and medium company. The purpose of this study is to investigate the factors affecting or being affected in a comprehensive model of open innovation for gold industry of Iran and to explain the relationship between these factors. The present research is of qualitative type with exploratory-explanatory nature in which the systematic review of research literature, meta-synthesis approach and content analysis have been used. Based on the seven steps of meta-synthesis after passing through several layers of evaluation: 54 articles, out of 3151 initial ones, were chosen careful content review and identifying desired variables and semantic units. In regard, 25 concept codes were extracted and after examining their validation by help subject matter experts, the relationships between them were also induced from scientific texts and drawn in a conceptual framework. Then, in order to implement the identified framework in the gold industry of Iran, semi-structured interviews with the experts the gold industry of Iran were designed and conducted, which led to the identification of 11 new and specific factors for the gold industry. By merging and categorizing the factors, 34 final categories were identified and by examining relationships between them, open innovation model in gold industry of Iran was developed and important influential and influential factors were identified in model.

The factors used in the foresight of any system vary from country to country, society, culture, politics and even time. Identifying and planning for influential factors in any industry is of particular importance. By identifying influential indicators, planners and policymakers determine which indicators are prioritized. Also, to move towards the main goal of organizations, identifying these indicators will help policymakers and planners to invest and optimize the most important indicators.The main purpose of this study is to identify the political factors affecting the future of the rail transport system in the freight sector. In this research, the identification of political factors of the rail transportation system in the freight sector has been done using a combination of library, field and Delphi studies and Micmac software has been used in the analysis. The three stages of this research have sought to present the most important political factors affecting the future of rail transportation in Iran. In the first step, all factors were identified. In the second stage, using the Delphi method, a consensus was reached in three consecutive periods, and in the third stage, using Micmac software, eleven factors in three categories were presented as the most important drivers for the future of the rail freight transportation system.
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Resource management is one of the most important practices in sustainability. Resource management, due to the scarcity of resources, requires attention and scientific-based organizing. Manufacturing industries are among the largest centers of resource consumption, especially natural resources. Therefore, different industries need to be committed to the principles of sustainable development in meeting their needs. Hence, the purpose of this study is to provide a model of resource management in sustainable supply chain in the selected industries. To do so, first, resource management indicators in the sustainable supply chain have been identified based on the previous studies and the experts’ opinions, and then, a model of indicators have provided in order to show their importance in the different industry by applying three methods of K-average, principal component analysis and random forests. In order to gather data, a survey-based questionnaire is used. The results demonstrate that environmental management and cross-functional cooperation indicators in the automotive industry are the most important indicators. In ceramic tile industry, social issues and human resource management indicators are important but, in the steel industry, social issues and environmental management indicators were important. In the foodstuffs industry, quality management, cross-functional cooperation indicators and human resource management have great importance. In addition, in the textile industry, the quality management indicator was the most important one. The results obtained from the various industries provide practical suggestions for prioritizing improvement practices for resource utilization for having sustainable supply chain.

The purpose of this paper is to identify the enablers of Industry 4.0 supply chain sustainability and further attempt to propose a research framework to bridge the theoretical gaps. At first, the enablers that influence the adoption of sustainability capability were identified through the review of domestic and foreign articles using the meta-combination method. After identification, the enablers were compared through a questionnaire and provided to 12 experts in the field of tile manufacturing industries in Yazd province. Using the information obtained from the questionnaire and its analysis through the combined method of DEMATEL-Fuzzy Network Analysis Process, a model was ultimately presented. The research results of the meta-combination section identified 114 open codes, 26 central codes, and finally 7 selective codes. The selected codes include organizational, production system, environmental, product, economic, technological, and social factors, which were analyzed using the combined method of Fuzzy Dematel-ANP. The relations and importance of these enablers were examined, and It was determined that the "technology" dimension is the most influential, the "product" dimension is the most susceptible, and the "economic" dimension is the most important dimension.

The issue of open innovation has been widely discussed in the innovation management literature in recent decades, which leads to their increasing recognition, including accelerating the internal innovations of companies and expanding the market to take advantage of external innovations in small and medium enterprises. For this purpose, at first, a systematic review of the literature was done in order to achieve a properly enough research background and then a sample of 54 articles was chosen and examined by using Systematic review approach. After the identification of the related variables, the relations between them were examined and drawn as a conceptual framework based on the research background. Then, in order to adapt the identified framework to reality, interviews with experts were done and after verification, several new variables, such as the degree of variability of managers, the culture of monopoly of knowledge, and competence; were added to the new framework and with the final identification of 32 categories, the relevant questionnaire was developed and distributed among stakeholders. Finally, by extracting the results and using the fuzzy mapping technique and also two soft wares of FCMapper and Pajek, a correlation model was designed between the factors and by analyzing the relevant results, effective scenarios were identified in the research. The results of this study showed that if we focus on the three factors of trust-building in cooperation and partnership, strengthening the appropriability regime and also empowering managers, we can see the improvement of open innovation process and a consequent positive impact on the company performance as well as innovative performance in Yazd gold industry.

The influence of the emerging flow of the Fourth Industrial Revolution in the old construction industry has led to the formation of a new revolutionary flow in this field, which has been introduced to the world of science and technology in recent years as "Construction 4.0". The main question in this study is what are the drivers and areas affecting the formation of the phenomenon of construction 4.0 in Iran and which of them have more importance and priority.

To find a scientific answer to this question, a developmental, qualitative and descriptive research was designed. In the first step, an initial list of possible drivers of this phenomenon was compiled based on research records and valid scientific reports. Subsequently, with the formation of a meeting of experts, this list was refined based on the local requirements of the Iranian society. In the second phase of this study, which was conducted with the aim of prioritizing these drivers, with the participation of a number of experts, while performing two rounds of Delphi technique, these factors and areas were prioritized at three levels.

Two drivers "Scientific cooperation with the developed countries" and "Technological advances in new fields" were selected as the first priority,

The findings of this research can be used to draw a roadmap for our country to join the new construction 4.0 trend and guide strategic and operational plans for the success of the country's construction industry in this field.

This study evaluates the performance of Iran and 38 OECD countries by providing a DFM model with undesirable outputs. Comparing the changes in the rate of increase in output and the rate of decrease in inputs for the efficiency of decision units in DFM and CCR models is one of the objectives of this study. This research is applied research in terms of purpose and is descriptive research in terms of implementation. According to the review of the literature and research background of the employed Total labor force, Total primary energy consumption and Gross Capital Formation were considered as input, GDP was considered as a desirable output and total GHG emissions excluding LULUCF, was considered as an undesirable output. The results showed that inefficient countries should make the most change in the input of total primary energy consumption and the least change in the desirable output (GDP) in order to reach the efficiency frontier; therefore, considering energy consumption management can be effective in changing inefficient countries with poor performance in environmental sustainability, such as Iran into efficient ones. The analysis also showed that in order to improve the sustainability in Iran, policymakers should consider reducing energy consumption, increasing labor productivity, reducing greenhouse gas emissions and improving investment productivity and GDP. According to the research method, two modeling methods of evaluating the efficiency of countries in the field of sustainable development were compared and the advantages of DFM model in comparison to CCR were studied.

Social and cultural developments are one of the main goals of regional development. This research uses social research approaches as well as planning models that are designed based on the scenario, to study social and cultural development in Yazd province based on the national vision document. In the first step of the research, 33 factors were identified that these factors have somehow affected the process of social and cultural development in Yazd province. After conducting various interviews with experts, 9 key factors were identified from 33 factors based on upstream documents. Then, for each of the factors based on different scenarios, 18 favorable and unfavorable situations in the future of the province were identified. Then, by forming a matrix of cross-effects through MicMac software and also using the knowledge of social science experts in assessing the effects of the occurrence of each situation on the occurrence or non-occurrence of other situations in the province, using the capabilities of Scenario Wizard software. 6 scenarios with very high compatibility were extracted. The results show the identification of three factors, social justice, social capital and quality of life as the main and effective actors in the process of social and cultural development in Yazd province. The results also indicate that the current status of each of the factors identified in the study is not very appropriate. The possible scenarios formed in this study raise hopes for improving the development situation in the province.

Abstract The main goal of this research is identifing the factors influencing the future of the rail transportation system in the freight sector. In this research, identifing the factors for the rail transportation system in the freight sector using a combination of library and developmental purpose, PESTEL model, Delphi method and SMART PLS software has been used in the analysis. The three stages of this research seek to present the most important factors affecting the future of rail freight in Iran. In the first stage, all factors were identified. In the second stage, consensus was reached using the Delphi method in three consecutive periods.In the third stage, based on the opinion of experts and the use of smartPLS software, out of 168 factors identified, 76 factors are considered more important as the main effective factors in Iran's 50-year foresight which were classified into 8 main categories. Identifying and planning for the factors that affect this industry is of particular importance. By identifying indicators, planners and policymakers will determine which indicators we are important. The indicators also warn policymakers and planners if we want to move towards total goal, which indicators should we turn into the optimal indicator.

The growing need of the society for food, the reduction of food resources and nutritional imbalance, the environmental damage in the food industry, the water shortage crisis and the changing climate, the urgent need to address the major environmental consequences and move towards sustainable development in this sector is essential. The main purpose of this research is to design a model of sustainable innovation for small and medium businesses in the food industry. In this research, by comprehensive review of research literature and interviews with experts and managers in the field of food industry and using thematic analysis method, important factors and variables in sustainability innovation in small and medium businesses were identified and extracted.Then, interpretive structural modeling was used to determine the priorities and relationships between the factors. Finally, the analytic network process was used to determine the weight of each factor. The results indicate that government policy, green social pressure and green culture of society are the most important factors in the formation of sustainable innovation. And government should focus on green strategies formulatin, organizational capabilities reinforcement and acquisition of economic competencies between firms.

Economic activities use and depend on natural resources, and the nature of their processes is such that they potentially pollute the environment. Therefore, environmental evaluation practices in various industries, including the steel industries, should be reviewed. The purpose of this study is to identify the environmental indicators of performance excellence model of Yazd Steel Industries and design the relationships between them through fuzzy cognitive map. This study is applied in terms of purpose and descriptive-survey in terms of type and data collection. At first, with the meta-synthesis approach, 40 articles were reviewed as samples and in order to identify complementary indicators, environmental activists in the steel industry were interviewed, in which 269 environmental indicators, 36 concepts and 9 categories of performance excellence model were identified. In order to collect data and examine the relationship between environmental concepts, industrial and academic experts have completed the questionnaires and with the fuzzy cognitive map technique and FCMapper and Pajek softwares, a linking model between factors and scenario making has been designed. The research findings from the designed fuzzy cognitive map show 157 relationships between 36 concepts, of which six scenarios are obtained in two ways, backward scenario and forward scenario.

Policy, science, and innovation policy indicators are important to provide the information needed to support evidence-based policy, as well as to provide effective monitoring and evaluation capabilities for policies. Also, due to the great complexity of the system of science, technology and innovation, designing a comprehensive model for policy-making in this area is one of the major concerns of policy makers and decision makers. The main purpose of this study is to design a linking model between the factors affecting the appropriate policy-making of the phenomenon of science, technology and innovation, as well as how the factors affect. By comprehensively reviewing the research background, a conceptual framework was extracted from the effective and shaping factors of science, technology and innovation policy. The current status and importance of these factors were questioned using a 56-item questionnaire. Using the data obtained from the questionnaire and SPSS software, Pearson simple correlation matrix was extracted and used as input of FCMapper software. Then, by entering the output of FCMapper software in Pajek software, a fuzzy cognitive map is drawn. According to the obtained results, the employment factor in the field of policy-making was identified as the most important factor among other factors. Finally, the most important forward and backward scenarios for science, technology and innovation policy-making in the science and technology corridor of Yazd province are examined.

The k-nearest neighbor's algorithm (KNN) is one of the most widely used and useful nonparametric classification algorithms. The classification mechanism of this algorithm involves computing the distance between new instances and the instances whole classes are known. When the dataset contains non-numerical (ordinal and nominal) attributes, the performance of the algorithm can be significantly affected by how this distance is measured. In this paper, we attempt to improve the performance of the KNN algorithm by presenting a new solution for computing the distance of non-numerical traits. For this purpose, the Particle Swarm Optimization (PSO) algorithm is used. The task of this algorithm is to determine the best value of the distance between two states in a non-integer trait so that the accuracy of the KNN algorithm is increased. UCI University Learning Repository Data is used to test this idea. The results obtained from the proposed algorithm are compared with several other improved algorithms and show the useful improvement of this mechanism.