جستجوی مقالات مرتبط با کلیدواژه « Steel Industry » در نشریات گروه « مدیریت »

Given the dependencies of key economic sectors, the global steel demand is expected to increase. Therefore, pursuing multiple strategies and aligning with global market developments is essential to enhance and achieve competitiveness in this industry. One of the development approaches in the steel industry, like other technology-based industries adapting to advancements in new technologies, is using a technology transfer approach. This industry is one of the largest and most important industries in the world and plays a very important role in many economic sectors. It can be significantly recognized in global markets as one of the main and powerful players by improving its competitiveness. The main objective of this research is to evaluate the competitiveness model in the steel industry with a technology transfer approach.

This research is applied considering its objective and follows a descriptive survey methodology for data collection. The statistical population of this research includes managers and employees of companies active in the country's steel industry. The data collection tool in this research was a questionnaire distributed randomly among the population. Ultimately, 384 questionnaires suitable for data analysis were collected. The gathered data were analyzed through the structural equation approach and with the help of Smart-PLS software. The model validation in this research was formed comprehensively with an interpretive-structural modeling approach.

The results showed that among the influencing factors, internal factors have the highest impact on competitiveness, while among the contextual factors, political and legal factors have the most significant effect. Additionally, the strategy of investment and cooperation was identified as the most effective for improving competitiveness, potentially yielding important economic, social, and organizational benefits for companies in the steel sector. Consequently, it is suggested that these companies enhance the selection and purchasing power of domestic and foreign customers by diversifying their product offerings, including related and complementary products, to cater to a wide range of needs within the industry.

The petrochemical industry is not in a favorable condition in this regard, and the volume and lines of products and derivatives in the industry are limited despite the available potential. Support from official, governmental, and legislative institutions for stakeholders and investors in the steel sector is crucial. By providing appropriate facilities and subsidies, these institutions can encourage and motivate active and potential investors to expand their production activities. Additionally, it is essential to reduce cumbersome and discouraging laws related to investment and exports. One of the most important drivers for increasing competitiveness among companies in the steel industry is the presence of a supportive atmosphere and attitude from senior company managers. The industry needs to step towards attracting, transferring, and developing existing technologies. Therefore, the presence of expert and capable managers with an entrepreneurial orientation in new technologies can be a crucial factor in developing the steel industry.

Efficient supply chain as well as the proper management of its components play an important role in supply chain productivity. The steel industry is one of the mother industries and needs to further enhance its chain productivity. The purpose of the present study is to identify key factors affecting the productivity of national steel supply chain. In order to identify the factors affecting steel supply chain productivity, the SCOR model has been used and its indices have been validated by CVR and CVI forms as well as by steel industry experts, based on which the designed questionnaire was distributed among the managers and experts of the steel industry and the data were collected. Finally, the data analysis was performed using confirmatory factor analysis with structural equations and PLS software. The factors affecting supply chain productivity were confirmed by 30 indices and 6 factors.The results revealed that all 6 factors influence steel supply chain efficiency, however, among these factors, the enabler’s factor

Supply chain management is a modern organizational management mode that organizes and plans information, capital flow, and business partnerships in the supply chain and requires complete business and market information (Quinn et al., 2012). However, the cost of acquiring supply chain companies and product information by traditional methods is very high. Information technology provides the power for companies to implement supply chain management and share the supply chain easily, and all companies in the supply chain can create value through information management (Shawaki et al., 2023). The utilization of intelligent approaches to predict prices and demand quantities enhances supplier delivery performance. It also refines demand forecasting accuracy, improves factory planning precision, forecasts demand for new products, and minimizes supplier risks, transportation costs, inventory, operational expenses, and time (Tirklai et al., 2021). In supply chain management, accurate forecasting of demand reflects the price. It is a critical issue that can reduce inventory costs and achieve the desired service level (Zouqaq et al., 2020). Intelligent supply chain pricing approaches can help supply chain companies to adapt the quality of their product offerings in supply chain management according to the knowledge gained (Kotsiopoulos et al., 2021). Identifying and modeling steel market fluctuations is very important in the steel industry and supply chain management. Considering the vertical chain in this industry and the interaction between the players of this industry, game theory has been used to model the optimal price. Neural network models were employed to replicate the game, as interaction and repeated gameplay are required for achieving balance among players. Taking into account Iran's unique circumstances, notably its confrontations with substantial sanctions in the metal industry, the sanctions variable was integrated as an adjusting factor in the pricing model for this sector.

This is a practical study. The research time frame for predicting steel prices and calculating the sanctions index spans from 2011 to 2020, with quarterly data. The MATLAB software was used.

Three Bayesian neural networks, support vectors, and Grassberg's anti-diffusion were used to predict the price of steel. The results showed that the Grossberg anti-diffusion model is more accurate in predicting steel prices. Next, the predicted price entered the game theory process and the Nash equilibrium point of the model was determined. According to the country's specific conditions, the sanctions variable was introduced in the game theory model. The results showed that the inclusion of sanctions in the model led to price increases and production reductions within the steel industry. The present study delved into price fluctuations resulting from shifts in supply and demand, particularly in the context of sanctions. The findings reveal that a reduction in supply coupled with escalated sanctions led to substantial price hikes, surpassing the impact of supply changes. Consequently, steel exhibits a heightened susceptibility to input constraints, where any disruption in its supply chain triggers significant price spikes, thus unsettling the market. This amplifies the sensitivity of supply chain management for steel. Consequently, a systemic and dynamic approach is essential for market regulation policies, raw material supply, transportation strategies, and warehousing considerations. It should be noted that the use of intelligent approaches and machine learning can play a significant role in coordinating such issues.

Considering that Stackelberg's approach was used in the current research, the sequence of players' entry into the game holds significance with respect to the Nash equilibrium. The development of market entry monitoring rules and regulations in this industry should be investigated because the steel industry is one of the industries that face high entry and exit costs. As a result, Policymakers and industry managers should monitor the entry and exit of players within this sector. They should endeavor to establish norms and regulations governing interactions among market participants to foster a structured and well-defined competitive environment.

An organization that does not have creativity and innovation cannot survive and will disappear from the scene over time. Therefore, organizations are constantly looking for ways to strengthen creativity and innovation and remove its obstacles in the organization. Companies that have an active approach to innovation and can use it effectively are among the first to offer better, faster, and cheaper solutions than their competitors. Therefore, the aim of this research is to present the innovation model of the country's steel industry. The research method in this article is descriptive-correlation and variance-covariance matrix analysis. This research was done in the library and in the field. The research model was extracted by analyzing, analyzing and interpreting interviews conducted with Iran's steel industry experts using the theme analysis method and four rounds of the Delphi method. Finally, by using 316 questionnaires received from the country's steel industry, a measurement and structural model was discussed to measure the relationships between variables and also to validate the developed model. According to the findings of structural equation modeling, in the studied steel companies, among the dimensions of the presented model, the most important dimensions are respectively related to "technical and technological innovation", "product innovation", "organizational innovation", "system innovation", "law innovation". ", "financial innovation", "economic innovation" and "marketing innovation".

Achieving excellence is gradual and will be achieved mostly in the light of acceptance and institutionalization of a set of characteristics such as values, methodologies, standards and quality management tools. Organizational excellence models are used as powerful tools to measure the success rate of systems deployment in different organizations. Organizational culture and employee behaviour is the main concern in the workplace to achieve organizational effectiveness. Therefore, cultural characteristics are necessary to maintain and strengthen organizational culture. Despite the existence of extensive independent and various research in the field of organizational culture, organizational transformation, and organizational excellence, few cases of research in this field deal with the transformation of organizational culture based on excellence. For this purpose, this study aims to propose a model of excellence-oriented culture transformation in the steel industry.

Design/methodology/approach:

 This research is typically qualitative and based on GTM data. In terms of its purpose, it is an applied research. The research population included all specialists, experts, experts and managers in the field of human resources in the steel industry. Non-probability sampling was applied purposefully and according to the theoretical saturation index. The literature has been reviewed and the references have been collected using a library method, and field study has been applied to conduct the research. Using in-depth and semi-structured interviews, field observations and document review, necessary information for this study has been collected and by using Maxqda18 software, their categories, themes and relationships have been identified. Also, in this study, the Kendall coefficient has been calculated using the Delphi method, for which, a questionnaire has been made and it has been validated using the Delphi method and obtaining the coefficients.

Findings indicated that the transformation model of excellence-oriented organizational culture is created from causal conditions including technological factors, individual factors and organizational factors, which benefit from new technology, for which, aligning goals is also the basis. Also, intervening conditions including factors related to society and organizational justice help to create strategies such as economic-political factors, implementing laws and regulations, and evaluating and providing feedback, which ultimately lead to consequences such as personal growth, organizational development, and social development. Based on the data obtained from the Delphi rounds and different parts of the questionnaire in each round, the minimum, maximum, average, mean and deviation statistical indices were calculated.

Research limitations/implications: 

This research required the necessary equipment and participation of all human and material resources in the fields related to the subject of study. Some of the limitations were a long time to complete the research and problems of making tools and operationalizing the concepts due to their originality. This study has resulted in categories that can be tested quantitatively. Also, conducting experimental and semi-experimental studies according to the obtained components among the country's steel companies can be an opportunity for future study.

Practical implications: 

Based on the findings, the effective role of organizational culture must be seriously and deeply reviewed by the management of organizations, since organizations recognize the importance of knowledge and are looking for ways to create it. Hence, it is recommended to invest in research, development, workshops and skill training courses to increase the capacity of knowledge, and at the same time, try to create a culture with the characteristics of a learning organization.

Social implications: 

The researchers, while concentrating on the theoretical literature of transformation and culture and applied research in the field of organizational excellence and its drivers, have sought to design a comprehensive model of transformation of organizational culture based on excellence, which has greatly contributed to the local applied literature of management knowledge and facilitated the continuous movement of Iranian organizations in the path of organizational excellence.

Originality/value:

 In this study, a model was proposed to those organizations that identify and influence the components of organizational culture towards survival, stability and achieving organizational excellence.

Sustainable development is a new field that deals with socio-cultural policies and mechanisms, economic prosperity, trade and industry, protection of the environment and coexistence with nature, and attention to equal human rights in the domestic and international arenas. The purpose of this paper is to provide a favorable model for the sustainable development of the iron and steel industry using Grounded data approach. This research was conducted using a mixed method. In the qualitative phase, using the Grounded data technique, a model for sustainable development for the steel industry was designed and presented. In a quantitative phase, the structural equation technique was used to analyze the data and explain the relationship between the components. In collecting information, two library methods such as reading and reviewing books, articles, seminars, conferences were used to extract concepts. In the interview section, most of the concepts have been extracted, relying on university professors and industry experts. The components of the extracted concept diagram include: supply of raw materials, development projects, integrated materials management, energy, market, economic and political conditions of the country and human resources - education, finance, logistics, technology, macro-industry, community and environment - health. Therefore, one of the important ways to achieve sustainable development, effective management and support of this industry in the country, management of supply of raw materials and strategic materials, environmental protection, the importance of employment and optimal use of resources.

One of the challenges faced by the steel industry is supply chain management. Based on this, inthe present research, based on the three scenarios of non-cooperation and simultaneousmovement (Cournot), non-cooperation and sequential movement (Stackelberg) and cooperativebehavior (collusion) will be discussed in the steel supply chain.The research method is applied in terms of purpose. The research period is seasonal data from2011 to 2020 and the software used MATLAB softwareIn this paper, a hybrid model based on artificial neural networks and game theory was presentedto help steel industry activists in determining the price level and optimal production. To predictsteel prices, three Bayesian neural networks, support vectors and cross-emission anti-emissionwere used. The results indicate that the cross-emission model of Grossberg is more accurate inpredicting steel prices. Also, the results show that by moving from the Cournot game to theStackelberg game and from the Stackelberg game to the Collusion game In the supply chain, itwill increase the price in the steel industry by 6 dollars per ton and the amount of product supplywill be in the range of 1500 to 4000 tons In other words, with the increase in the level ofcollusion in the steel market, more products have been offered in the market and at the sametime, the price level of the product will also increase, which will reduce the welfare of steelconsumers in the market.

Proper economic policy-making and planning in any country requires recognizing the facilities and production capabilities and economic advantage of different regions of that country. The aim is to recognize the relative advantage of the upstream and downstream sub-sectors of the steel industry of Yazd province during the years 2004-2018 which used the spatial coefficient model. The results showed a value added for the spatial coefficient index, Yazd province had more production expertise in upstream industries than in the whole country and was also an exporter of added value in the desired activity. But the spatial value added index of the province in the downstream industries for the entire period, was less than one. According to the results, Yazd province has less production expertise in the activity in question than the whole country and is an importer of added value in this sector. Yazd province has been a supplier of steel raw materials for many years, due to lack of comprehensiveness of development projects from mining to high value-added final product, has always had the least benefit from the value added of this sector and A significant number of industrial and construction projects in the province, the required steel structures are supplied from outside the province. Provincial planners should decide on investment, resource allocation and budgeting according to the province's advantage in order to increase the province's value-added growth in the downstream part of the steel industry.

Nowadays, organizations need an efficient supply chain and proper supply chain management to face global competition. The steel industry is considered the most strategic industrial good in the world because of its large impact on the economic and industrial development of countries. Paying attention to the supply chain of this industry, as the fundamental industry is crucial because of its key role in the national economy and the welfare of communities. This research aims to provide a dynamic system model for the country's steel supply chain to help policymakers and managers to have more effective management in the industry. To present the model, causal rings are drawn by the association of steel industry experts and then modeled by VENSIM. Following are the required tests for model validation. Scenario-based simulation results show that a ±20% change in the two model parameters that reflect technology growth and investment coefficient will have a significant impact on the achievement of the goals.

The purpose of this study is to design a green human resource management model in the steel industry. The statistical population of the research is the West Asian Steel Company. This research is applied and mixed methods (qualitative-quantitative) in terms of purpose and data collection method, respectively. Interview method was used to design the research model. To this end, the initial research model was designed following conducting 22 interviews. To evaluate the validity in the qualitative part, triangulation, member checking and pairwise methods were used, and to confirm the reliability, the retest method was utilized. In the quantitative section, a questionnaire appropriate to the model was developed to confirm the designed model based on the interviews, and this model was examined using the structural equation method. In the quantitative section, the statistical population included 987 individuals, and the sample size was determined to be 686 individuals based on the Krejcie and Morgan table. Content validity method was used to assess the validity of the questionnaire and Cronbach's alpha was used to determine the reliability of the questionnaire. The results of the structural equation model conducted by AMOS software confirmed the designed model. The results showed that green human resource management on individual, organizational, group consequences and due to the need to internalize and change the attitude of employees and managers of West Asia steel company in the field of environmental issues, the most important way to change the attitude in the company is training and increasing knowledge in the field of environment

Marketing capacity is a mechanism that enables organizations to implement their strategies in a competitive environment. Using these capabilities, organizations can improve their performance in today's competitive environment by using their physical resources and intellectual and strategic assets. The purpose of this study is to present a model of marketing capacity in the Khuzestan steel industry and its impact on the company's performance in developing open innovation.

The method of the present study is a combination that was performed in two qualitative and quantitative stages using data theory of the foundation. Qualitative stage data were collected through interviews with 15 experts in the field of marketing who were selected through purposive sampling and analyzed with Maxqda software. Qualitative data analysis software.

The results obtained from the analysis of theoretical foundations and research interviews, led to the final model of marketing capacity, which has 10 main categories of product, distribution network, market, customer, competitor analysis, advertising, brand, management strategies, and technological strategies. And training. Analysis of competitors, customers and products in the role of "underlying factors" of the market in the role of "environmental conditions", advertising, brand, distribution network, management strategies, technological strategies and training in the role of "strategies and strategies" and marketing capacity in the role of the "main category" and the company's performance in the role of "consequence" have been identified. The researcher-made marketing capacities that resulted from the results of the qualitative sector and in the quantitative sector, considering the importance of open innovation to be a market leader in the steel industry, the company's performance was measured based on open innovation. Was analyzed. Findings indicated a good fit of the proposed model.

The purpose of this study is to provide a model to identify the factors and components of sustainable development of the iron and steel industry using grounded data and fuzzy DEMATEL techniques.

The present study is descriptive in terms of purpose (qualitative and quantitative), exploratory in terms of identifying components, and cross-sectional in terms of time. The study population in the qualitative section included senior managers and academics with a history of sustainable development and in the quantitative section, the statistical population included senior industry managers and university professors. To determine the priority of components, two groups were formed. Statistical sample, in the qualitative stage, was formed using purposive judgmental sampling of 15 university and industry experts to extract a conceptual model to localize the model and check the content validity of the model and factors by grounded data technique. In the quantitative stage, due to the use of research techniques in operations and the fuzzy DEMATEL method to prioritize and identify the most effective and influential model factors, seven experts were selected from seniors of the community. Industry and university professors were selected. These people had master's and Ph.D. degrees and more than 15 years of work experience. In order to collect information by reviewing the research literature and consulting experts, the factors were identified by the grounded data technique. It was also used to collect the necessary data during the research through interviews and a pairwise comparison questionnaire. The validity of the assessment tool in the qualitative part, which is the use of semi-structured interviews, was done through face validity and observing the interview protocols, and in the quantitative part, Cronbach's alpha was used to assess the validity of the questionnaire. According to this method, the reliability of all research variables was more than 0.7. The number of statistical samples of the research included 15 interviewees in the first qualitative part (using grounded data) and seven in the quantitative part (Fuzzy DEMATEL).

In the first stage of the qualitative section, the categories were summarized with Maxqda software and 6 main factors, 13 sub-factors, and 46 concepts were identified. Then, using the fuzzy DEMATEL technique, the 13 factors of importance, effectiveness, and susceptibility were extracted, respectively. The most influential included "macro-management of iron and steel industry, economic and political conditions, market management, financial management, integrated resource management, environment", respectively and the most influential of all was "society and production".

Based on the results obtained to achieve organizational productivity, the organization should pay attention to the factor of steel production in the sustainable development of the steel and iron industry. "Steel industry macro-management factor" is also the most influential factor in the sustainable development of the steel and iron industry.

This research has been done with the aim of determining the effects of investment policies for competitiveness in two qualitative and quantitative sections. In the qualitative part, the variables of the model were extracted through content analysis and semi-structured interviews with 20 steel industry experts who were selected purposefully and theoretically. Then, through a questionnaire, the experts made pairwise comparisons of the relationships between the variables of the model with the comprehensive structural-interpretive modeling method and the hierarchical structural model was formed in the quantitative part. Finally, the structural model created by the structural equation modeling method was validated by the data collected from 144 financial and investment managers of the steel industry. The findings of the qualitative part showed that the created model has 14 variables, which according to the findings of comprehensive structural-interpretive modeling, these variables are located in seven hierarchical levels, so that the three dimensions of "Establishment of standards in the industry", " "Government investment rules and regulations", "Competitive investment strategy" has more influence and guidance, and "Risk management" has the most influence. The results indicate that a higher level of government support and policies can improve the firm's transitory capital, which creates competitiveness, and the importance of these policies was highlighted.

Environmental pollution is a serious threats to global warming and human health, and most industries, especially the steel industry, are sources of environmental pollution, so reducing and controlling pollution from this industry has become particularly important in recent studies. Therefore, the purpose of this study is to identify the environmental criteria of Yazd steel industry in order to provide a causal model and analyze the relationships between them. In this study, first, by studying the thematic literature using the content analysis approach, the criteria that had a very low number of repetitions were removed from the list and interviewed with steel industry experts to localize and identify more practical criteria and 36 final environmental criteria were selected. A questionnaire was used to collect data and its validity and reliability were confirmed. Finally, a fuzzy cognitive mapping approach has been used to investigate the intensity of relationships and how the criteria affect and model design, and each of the criteria has been analyzed within the framework of this model. Accordingly, the criteria of green marketing, environmental design and environmental performance have the most influentiality, respectively, and the criteria of green marketing, green warehouse and building and environmental performance have the most impressionability in this industry, respectively.

Technological learning and the drive for innovation in different industries emphasize the role of companies, especially large companies, and the acquisition of knowledge from external sources. Given the large corporations on the one hand and the long-term historical partnerships with foreign large firms on the other, the country's steel industry is also a good place to study in this field. On the other hand, some of the industry's successes, such as sustainability under sanctions, the country's second-largest source of non-oil export earnings, and some recent breakthroughs, particularly in the registration of the PERED technology brand, show that learning efforts have been somewhat successful. This study, which examines the learning processes and outputs of the country's steel industry (especially in policy, engineering and large steel companies) in the post-revolutionary era, has attempted to use a qualitative (case study) approach for drawing the path of technological development in the industry. For this purpose, 18 interviews with executives and policymakers, academics, engineering firms and specialists from large steel companies were conducted. Analyzing the content of these interviews and using the analytical framework of the Windows of opportunities path to innovation in the industry is described. The results show that dependence on the path of incremental innovation and falling into the success trap, lack of focusing on technology development across the steel value chain and the lack of a proper national strategy for technology development are the most important factors that make the industry successful in innovation process in some aspects of value chain.

The purpose of this research was to make and provide a model for developing the competence of the leadership of the steel industry managers. The methodology of this research was applied and exploratory in terms of the purpose and data gathering method was mixed. In qualitative stage, after a deep interview, data gathering has been done based on the Grounded Theory and by using a questionnaire of 12 questions. It was in accordance with the systematic approach of Strauss and Corbin. After coding process, 180 initial propositions or concepts were identified according to open coding and 32 categories were derived from their combination, which were the origin of the axial coding. After that, Six main components or dimensions of the model were designed. Finally the systematic model of the leadership competency development of the steel industry managers was designed. The statistical population of the research in the qualitative stage included all experts of the steel industry that were interviewed according to non-probability sampling and the snowball technique. 21 persons  were selected and the deep interviews were done. In the second stage, sample size was 155 and after statistical analysis and structural equations, the fitting of the designed model was verified by using the PLS software.

Technology development has been recognized as a major factor in the long-term national boom. In this regard, it is necessary to stimulate innovation in order to maintain a position in global competition. The necessity of designing and evaluating any innovation policy requires looking for ways to measure and compare the technological capability of different countries. This paper investigates and estimates the technology gap in Iran's steel industry with 13 selected countries to assess the technological capability of the world's top steel producers. The purpose of the present study is to identify the extent of technology gap, its causes, and provide solutions to overcome this technology gap. For this purpose, based on econometric method, two categories of inputs (raw materials, energy consumption and manpower) and outputs (total steel production) in the period 2009-2014 were collected through different databases, and then the data were analyzed through Frontier41 and GAMS soft wares. Results based on estimating the technological frontiers of each group of countries and comparing them with existing technology meta-frontier indicate that Iran has the largest technology gap in the steel industry compared to the selected countries,so based on literature review, some solutions has been provided at the end of the paper.

Considering the vital role of Environmental factors alongside industries’ efforts on effective and efficient use of resources as well as nowadays’ social issues, lead to serious attention to sustainable development. On the other hand, the intensity and necessity of environmental considerations in the steel industry, which has decades of history in Iran, has always been emphasized. Therefore, this paper aims to elaborate the underlying factors of steel industry sustainable development. To this aim, based on prior studies and interviewing experts, the underlying extracted factors scrutinized through ISM approach in order to develop a coherent structure. In the following, the structured factors clustered by MICMAC analysis. In addition, their mutual affects and importance weights, derived by employing ANP on the ISM developed structure. Findings depict that inventory, occupational accidents, human safety and welfare are the most effecting factors of steel industry sustainable development.

Marketing plays an important role in determining the strategic goals and the outcomes of the company's performance. Regarding the importance of the steel industry as the second non-oil export industry in the country, this study tries to identify, categorize and model the affecting factors on marketing in the major steel companies by using the qualitative research method. According to 30 interviews with experts in the steel industry in the year 1396 AH, 16 major categories were identified based on the Paradigmatic Model of grounded theory that have been structured in the form of six dimensions. Strategic management as the causal conditions, corporate social responsibility, market orientation and internal marketing as intervening conditions, appropriate investment as the underlying condition were identified. Territory, supply chain management, logistics and transportation, appropriate scale of production, production technology, proper interaction with customers, productivity, price, and product as the interactive dimensions have been identified. Strategic marketing as ‘central phenomenon’, and the performance and brand equity as ‘consequent dimensional’ have also been identified. In the quantitative section, the obtained model by the distribution of 384 questionnaires, was tested by structural equation modeling and the position of the variables was tested by t-test. The results showed that position of the variables of the strategic management, territory, supply chain management, investment, corporate social responsibility, logistics and internal marketing are not suitable. Also, in ranking of affecting factors on strategic marketing, it was specified that strategic management, market orientation and product quality are the most important factors.

Many products are produced in networks of firms connected to each other by transactions. From a supply network perspective, the relative position of individual firms with respect to one another affects both strategy and behavior. Despite the importance of such networks little is known about relationship patterns and structural complexity of them. Social network analysis (SNA) approach is a proper method for modelling and understanding structural attributes of such networks. Hence, this study identifies those centrality measures of SNA highly related with supply network efficiency, using buyer-supplier relationship data collected from 45 steel companies in Iran. In a multistage procedure, a DEA model (BCC-input oriented) is used to calculate firm level efficiencies and SNA is applied to measure centrality metrics in supply network. Then, these variables are applied in data panel regression with constant effects to identify those variables most relevant to productive efficiency. The results indicated productive efficiency has positive association with in- degree and betweenness centrality and negative association with out-degree centrality in logistic flow network. Also, in the contractual relationship network, productive efficiency has positive association with degree centrality and negative association with eigenvector Researches in the literature have confirmed although not without exceptions