ali mohaghar

Blockchain technology, with its advantages such as reducing intermediaries, controlling costs, and increasing security, has garnered attention from the financial industry. This technology, besides centralizing banking processes, can help improve operational efficiency. This study aims to identify and analyze the drivers influencing the future of banking in Iran, with a focus on blockchain technology. The research is applied in terms of orientation and quantitative in terms of methodology. Two methods, fuzzy Delphi and Marcus, were used for data analysis. Initially, 29 drivers were extracted through a literature review and interviews with banking experts. Subsequently, nine drivers were selected for final prioritization using the Marcus method after distributing expert questionnaires and screening them with the fuzzy Delphi method. The final drivers were ranked through a questionnaire distribution. The perceived organizational benefits, the compatibility of blockchain technology with the IT systems of the banking sector, the development of RegTech in the country, and the regulatory approaches of lawmakers regarding digital financial technologies were, respectively, identified as the highest-priority drivers. The most important practical recommendations of the study include developing a tool to measure the benefits of blockchain technology, adopting a systemic view towards the implementation of new technologies, making necessary changes before transferring the technology to the banking sector, leveraging RegTech capacities to assess the risks of using digital financial technologies, and ensuring the integration of regulatory policies and comprehensive regulation.

The current research seeks to identify and prioritize factors affecting the maturity of knowledge-based companies in the food industry, focusing on the approach of the fourth-generation industry.

The current research is applied in terms of orientation and it is a quantitative study from the point of view of methodology. The theoretical population of the research is the specialists of organizational maturity and the fourth-generation industry in the food industry. Sampling in this research was done based on the expertise of experts in the field of research. In this research, the fuzzy Delphi method was used to screen the factors and Copras and Mabac techniques were used to prioritize the screened factors. Interviews with focus groups were also used to provide practical suggestions.

The present research was carried out in several stages. In the first step, factors affecting the maturity of knowledge-based companies in the food industry were extracted through literature review and interviews with experts. To screen the factors, expert questionnaires were distributed among the experts, and the experts expressed their opinions about each of the factors in the form of a five-degree fuzzy spectrum. 10 factors had a favorable defuzzified number and were selected for final prioritization. Screened factors were evaluated by distributing priority questionnaires and Copras and Mabac techniques. The experts expressed their opinions in the form of a spectrum of 10 point on four indicators. The priority factors were: governance of data-driven decision-making culture, the use of new learning methods in the organization, the use of cloud platforms in the organization, the use of smart machines and equipment in the company, and innovation policies in the organization.

Originality/Value: 

Practical research proposals were developed based on the most important factors. Some suggestions were: the use of data-driven technologies such as business intelligence and big data to strengthen data-driven decision-making, the use of a hybrid approach in training and the application of new technologies in the field of training such as Metaverse, the use of Internet of Things and blockchain technologies to automate and intelligentize processes and finally Moving towards an open innovation policy.

The food industry is one of the vital industries for the health and well-being of society. The aim of the current research is to provide a model of factors affecting organizational maturity in knowledge-based companies of the food industry in Iran with the approach of the fourth-generation industry. The research consists of two qualitative and quantitative parts, in the first part, the main and secondary factors of the model were obtained through metacomposition. In the second part, the relationships between the main factors were determined through cross impact analysis.

The current research is applied in terms of orientation and is a mixed study in terms of methodology. Also, the current research is a pragmatic study in terms of philosophical foundations and exploratory research in terms of the goal. The theoretical population of the research is the experts of the food industry and the sampling was mainly done in a judgmental and purposeful way. In the judgmental sampling method, cases and samples are selected based on the expertise of experts. In this research, the meta-synthesis method was used to extract factors and the cross-impact analysis was used to determine the relationships between the main factors. Validation of articles was done by CASP tool. The extracted articles were screened step by step to identify the most qualitative articles for study.In this research, meta-synthesis method was used to extract factors and cross impact analysis technique was used to determine the relationships between the main factors. In order to get experts' opinions about the relationships between the research factors, influence evaluation questionnaires were used. The experts were asked to express their opinions on a scale of 0 to 3. Also, to measure the validity of the meta-synthesis part, the Lawshe content coefficient was used, and the Kappa coefficient was used to measure the reliability of the codings. Validity and reliability values in this research were appropriate.

This research was done in two steps. In the first step, factors affecting organizational maturity were extracted using a systematic background review and meta-combination method. The output was 6 main factors and 27 secondary factors. The main factors affecting organizational maturity were: structural factors, training and learning, technological factors, factors related to the nature of governance, factors related to innovation, and factors related to decision-making. In the following, these factors were evaluated with the approach of structural analysis of cross impact analysis. The results of this technique showed that decision-making, structural and governance factors are effeinfluential variables. Also, technological and innovative factors were evaluated as impressionable variables.

Practical suggestions of the research were developed based on the influencing factors. Some suggestions were: the use of data-driven technologies such as business intelligence and big data to strengthen data-driven decision-making, paying attention to the compatibility and integration of technologies and information systems in knowledge-based companies in the food industry, and the use of technologies such as blockchain to improve governance and improve the transparency of knowledge-based companies in the food industry. By using technologies such as big data, a large amount of data can be collected and analyzed, and based on that, many risks and threats can be identified and managed. Business intelligence can be used to classify and predict key variables. Blockchain is also a key technology to enhance transparency and develop smart contracts. It should not be forgotten that the fourth-generation technologies are mainly integrated and systemic, so before the introduction of new technology, attention should be paid to system adaptation.

Considering the necessity of flexibility in the supply chain to manage uncertainties, this research aims to design and explain a flexibility process model for the financial supply chain in Iran's car leasing industry. 

The research method is a mixed-methods exploratory approach. First, 21 qualitative interviews were conducted. Using grounded theory, a financial supply chain flexibility model for Iran's automotive leasing industry was developed, comprising 24 sub-categories within six main categories. Next, 260 questionnaires were distributed and completed in automotive leasing companies in Iran. Structural equation modeling was then employed to conduct a path analysis of the hypotheses concerning the relationships among the model dimensions, and the validation of the model was assessed in the study.

Based on the data analysis, the causal conditions of flexibility include "expectations related to customers," "factors related to suppliers," and "motivations related to financing." The contextual factors contain "legal-regulatory factors," "financial-economic factors," "environmental factors," and "cultural-social factors." The intervening factors of financial supply chain flexibility include "ownership and shareholders of leasing companies," "communication and IT-related factors," "industry systems and infrastructure," and "transportation and logistics." The phenomenon of financial flexibility in the supply chain was defined as "financing solutions," "effective communication of supply chain elements," "factors related to the ability to credit," and "proper risk management." Additionally, the strategies for the flexibility of the financial supply chain cover "innovation and development of new products," "development of sales network and after-sales services," "development of training and service skills," and "development of cooperation between supply chains." The consequences of financial flexibility in the supply chain of leasing companies encompass "increasing the production of automotive products," "increasing the level of access to services," "easier access to financial resources," "improving the circulation of financial information," and "increasing the efficiency of the supply chain." In the quantitative part of the research, based on the results of structural equation modeling and path analysis, it was found that intervening factors affect the antecedents and strategies of flexibility. The antecedents of flexibility have an impact on attention to flexibility. Besides, dimensions such as contextual factors, attention to flexibility, and intervening factors significantly affect strategies for financial flexibility in the supply chain, which ultimately affect the consequences of financial flexibility.

To enhance the flexibility of the financial supply chain, it is advisable for companies to draw insights from successful product development experiences. Additionally, efficient management of after-sales services, building trust and establishing effective communication with customers, and upgrading employees' knowledge, experience, and skills to align with industry developments are essential factors for fostering financial flexibility in the leasing industry.

This research models and simulates the development of transmission capacity considering electricity supply and demand dynamics. After presenting a causal loop diagram and designing a stock and flow diagram, the model's validity is confirmed using validation methods for system dynamics models. The analysis then proceeds to scenarios for the total electricity demand in Iran. Firstly, the country's electricity demand structure is broken into industrial, household, agricultural, and other sectors. By studying consumption trends in each sector, linear and nonlinear regression are used to predict total electricity demand. Next, three scenarios - optimistic, moderate, and pessimistic - are defined in terms of electricity demand, and the required transmission capacity is calculated and designed for 400, 230, 132, and 63-66 kilovolt substations to cover and meet future electricity demand over twenty years. The research findings over a 20-year horizon indicate that in the moderate scenario, where electricity demand increases by 90 percent, the transmission capacity needs to increase by 106 percent to meet the demand. In the optimistic scenario, where electricity demand increases by 71 percent, the transmission capacity needs to increase by 85 percent. In the pessimistic scenario, where electricity demand increases by 110 percent, the transmission capacity needs to increase by 126 percent.

With the advancement of Industry 4.0, customer preferences are continuously evolving, and product life cycles are becoming shorter. Consequently, new product development (NPD) processes have become indispensable for companies. Achieving sustainable industries necessitates a process where emerging risks are mitigated. In other words, integrating risk management concepts into the NPD process can significantly improve organizational performance. The primary goal of this research is to develop a framework for risk management within the NPD process specifically tailored for fast-moving consumer goods (FMCG).

Initially, relevant research on NPD was reviewed, defining the concepts of NPD process, risk, and FMCG to clearly articulate the problem statement and the need for risk management in this domain. This section was presented in two main parts: theoretical literature and empirical literature. Subsequently, a detailed review of 18 risk management models was conducted, selected from a pool of 95 articles, to identify prominent studies in this area.

The results indicated that while these articles examined specific phases or steps of the five-phase risk management models, often introducing variations, none of them comprehensively covered all activities and phases. Employing the meta-synthesis method and utilizing Sandelowski and Barroso's seven-step model, while considering the shortcomings and strengths of the reviewed models, a novel risk management model was proposed for enhancing the NPD process. This model consists of six steps and introduces the implementation details of the stages, steps, and sub-steps. Beyond incorporating the strengths of existing models, this model also addresses their deficiencies. Its innovation lies in its in-depth articulation of the risk process steps and its focused attention on improving the path for determining risk response strategies. The FMCG industry's impact on this model is evident in the independence of risk management and risk monitoring. This research was derived from existing models and grounded in the meta-synthesis method. It was further refined through consultations with risk management experts, FMCG specialists, and a case study of the current product status at Golrang Company. The key criteria for assessing the validity and reliability of the measures were examined. Validity assessment was initially conducted through an extensive review of the literature. Subsequently, the identified components and indicators were evaluated by experts in this field and received final approval. Additionally, two sets of interviews were conducted to gather the necessary data. The first set of interviews aimed to identify existing risks within the NPD process. The second set focused on determining response strategies for each prioritized risk.

The feedback loop is a critical factor for FMCG products, as ignoring feedback and failing to adjust the development process can lead to a product's competitive decline. Experts emphasize the need for independent risk management and risk monitoring in FMCG due to the high perishability of these products. Lost opportunities can result in irreparable losses, highlighting the critical importance of speed in risk management for FMCG. Given the short life cycle of these products, any delay in decision-making can lead to significant losses. Therefore, rapid risk management is essential for these products. To achieve the desired outcomes, developing data collection and analysis systems for assessing risks associated with these products is imperative.

In the Industry 4.0 era, many pioneering industries are leveraging emerging technologies such as the Internet of Things (IoT) as solutions in the digital age. One of the largest and most active industries in Iran is the food industry, which stands to benefit significantly from these advancements. Achieving a sustainable competitive advantage is often possible at the level of the supply chain, where companies use information and communication technologies, such as IoT, to coordinate information, finances, and materials among supply chain actors. This research aimed to identify the key success factors (KSFs) for implementing IoT in the food supply chain. Firstly, through a systematic literature review, the KSFs for IoT implementation in the food supply chain were identified. To develop a measurement model, confirmatory factor analysis using structural equation modeling was employed, making the research applied-descriptive. A questionnaire was designed and completed by 142 members of the "Amadeh Laziz" supply chain (a case study), who were selected using a stratified random sampling method. Confirmatory factor analysis and LISREL 8.83 were then used to validate the proposed model. Finally, the cause-and-effect relationship between KSFs in IoT implementation in the food supply chain was analyzed using Grey DEMATEL. Based on the confirmatory factor analysis findings, the KSFs in implementing IoT in the food supply chain were identified as technical, economic, legal, cultural and social, security, applicability of IoT throughout the supply chain, and implementation of IoT applications. Thus, the measurement model included eight factors and 27 measures. According to the cause-and-effect relationship findings, "Implementation of IoT applications" and "Economic" factors were found to be mostly influenced, while "Applicability of IoT throughout the supply chain" and "Technical" factors were recognized as the most influential. The results of this research can guide food producers and technology policymakers in their supply chains and help avoid trial and error in IoT implementation by leveraging global and national experiences.

One of the challenges faced by managers in the field of social networks in virtual space is the lack of understanding of the reasons for the decrease or increase in the number of users across various social networks in cyberspace. Despite the appropriate capabilities of some domestic social networks, their popularity is much lower compared to foreign-based networks. Research conducted in the field of social networks has mainly focused on pathology and the identification of positive and negative effects. Additionally, most of these studies have been conducted on foreign social networks such as Instagram. On the other hand, the research has only focused on certain factors and has not taken a comprehensive look at all the effective factors. The main question of the current research is: What are the most important factors affecting the use of internal social networks in Iran's virtual space?

The primary goal of this research is to identify and prioritize the factors affecting the use of internal social networks in Iran's virtual space. To achieve this, fuzzy Delphi, best-worst fuzzy, and COCOSO methods were employed to rank these factors. All three methods are part of quantitative techniques and utilize judgmental quantitative data for analysis and prioritization. The fuzzy Delphi method was used to screen the research factors, while the COCOSO technique was employed to rank the factors affecting the use of internal social networks in Iran's virtual space. The weight of the evaluation indicators for the research factors was also calculated using the fuzzy best-worst technique. Due to the quantitative nature of the techniques used in this research, it adopts a multi-method quantitative methodology. Furthermore, given the practical implications of the research findings for internal social networks, this study has a practical orientation. Data were collected using two interview tools and a questionnaire. Factors affecting the use of internal social networks were extracted from an analytical review of studies on social media and social networks. Subsequently, to evaluate these factors, three questionnaires—fuzzy screening, pairwise comparison, and COCOSO priority assessment—were distributed among experts. Screening questionnaires were evaluated using the fuzzy Delphi method; pairwise comparison questionnaires were assessed with the best-worst fuzzy method, and priority evaluation questionnaires were analyzed using the COCOSO method.

The present research was conducted in three stages. In the first step, 24 factors were extracted through literature review and interviews with experts. In the next step, these factors were screened by distributing expert questionnaires and employing the fuzzy Delphi method. Eight factors had a defuzzified score higher than 0.7 and were selected for final ranking. Finally, the screened factors were ranked through the distribution of priority questionnaires and the COCOSO method. The prioritized factors included: the variety of services provided by the social network, users' trust in the social network, users' privacy and security, and social networks' monetization policies.

The current research seeks to identify and prioritize factors affecting the use of internal social networks in Iran. Most of the research conducted in this field pertains to foreign social networks such as Instagram. Conversely, previous studies have only considered certain variables, and the factors have not been comprehensively investigated and evaluated. The present research was conducted in three stages. In the first step, 24 factors were extracted through literature review and interviews with experts. The interviews with some experts were conducted to enrich the list prepared from the literature. Despite utilizing qualitative methods for thematic analysis, since most of the methods employed in this research were quantitative in nature, it is classified as a quantitative study in terms of methodology. Seven factors were added to this list by experts. Eight factors were in good condition in terms of their defuzzified scores and were selected for final ranking. The screened factors were evaluated and ranked using the COCOSO method. According to the scores of the final factors, the diversity of services provided by the desired social network, users' trust in the desired social network, users' privacy and security, and the social network's income generation policies were prioritized, respectively. Practical research proposals were developed based on the most important factors. Some practical suggestions include developing a specific business model, gaining users' trust, establishing regulations, creating a specific revenue plan, and paying attention to technology ethics.

Sustainable development is defined as development that meets the needs of the present generation without compromising the ability of future generations to meet their own needs. It encompasses economic, social, and environmental dimensions that must be considered simultaneously. With the increasing importance of sustainable development, many companies worldwide are motivated, either proactively or reactively, to collect their used products. In such circumstances, establishing a reverse logistics network based on sustainable development is essential. The decision to outsource logistics has gained significance due to the need to avoid fixed costs, heavy investment, and achieve economic advantages, with many companies recognizing the potential benefits of high-quality logistics services.

This research presents a mixed integer programming model for planning reverse logistics outsourcing in the assembly cycle of the automotive industry, focusing on a cost-oriented objective function. The research scope includes the assembly cycle of production lines, specifically prioritizing high-volume car manufacturers (light vehicles), and focuses on the Saipa Automotive Industrial Group, including the Ryan Saipa Leasing Group. The research period spans from 1389 to 1398 in the Iranian calendar. Variables such as non-commercial receivables, total assets, operating profit, net profit, and market value were evaluated using MATLAB software based on published statistics from Saipa.

The research findings indicate that among the variables of non-commercial receivables, total assets, operating profit, net profit, and market value, net profit to operating profit and sales (operating income) are of significant importance. The highest amount of non-commercial receivables for Saipa occurred in 1398 during the summer, while the highest total assets were recorded in 1392 during the summer. The highest operating profit was observed in 1398 during the winter, and the highest net profit was in 1390 during the spring. The degree of data convergence was calculated in the regression charts of sales (operating income) to operating profit and net profit to operating profit for the years 1389-1398. The degree of data convergence in the regression chart of sales to operating profit based on the conceptual model in 1398 was 0.9895, and for net profit to operating profit in 1398, it was 0.9961. The regression rate for the conceptual model in the test phase was 0.79, and in the overall processing stage, it was also 0.79. The histogram error rate was calculated for all three stages of learning, validation, and testing, with an error rate of 0.002375, which is acceptable due to its proximity to zero. Comparing these results with other studies shows an improvement in the regression and error rate in the analysis of the objective function.

Based on the calculated weight of the criteria in two-way assembly line balancing issues, it can be concluded that the decision team pays special attention to strategic issues in addition to production issues. The production rate of the line, which is the inverse of the production cycle time, affects the company's market share in the long term and increases its market share.

Adopting an integrated production, maintenance, and quality policy in production systems is of great importance due to their interconnected influence. Consequently, investigating these aspects in isolation may yield an infeasible solution. This paper aims to address the joint optimal policy of production, maintenance, and quality in a two-machine-single-product production system with an intermediate buffer and final product storage. The production machines have degradation levels from as-good-as-new to the breakdown state. The failures increase the production machine's degradation level, and maintenance activities change the status to the initial state. Also, the quality of the final product depends on the level of degradation of the machines and the correlation between the degradation level of the production machines and the product's quality in the case that high degradation of the previous production machines leads to a high probability to produce wastage by the following machines is considered. The production system studied in this research has been modeled using the agent-based simulation, and the Reinforcement Learning (RL) algorithm has obtained the optimal integrated policy. The goal is to find an integrated optimal policy that minimizes production costs, maintenance costs, inventory costs, lost orders, breakdown of production machines, and low-quality production. The meta-heuristic technique evaluates the joint policy obtained by the decision-maker agent. The results show that the acquired joint policy by the RL algorithm offers acceptable performance and can be applied to the autonomous real-time decision-making process in manufacturing systems.

One of the characteristics of the fourth industrial revolution is the creation of production intelligence through real-time data to make accurate and timely decisions. Therefore, data-driven statistical process control is expected to significantly contribute to the advancement of intelligent manufacturing. For this reason, statistical process control has become one of the most widely used tools to maintain an acceptable level of quality characteristics in the era of Industry 4.0. In this article, organizational readiness factors for the establishment of intelligent statistical process control in the age of the fourth industrial revolution in the gas industry were investigated. For this purpose, after identifying the control structure of the intelligent statistical process of applying the literature review, 12 factors of organizational readiness in order to achieve this goal were presented in the form of a framework. Then the relationship and sequence of these factors were determined by fuzzy interpretive structural modeling. Next, the obtained model was verified using the structured equation modeling approach. The presented model can be a guide for the gas industry in implementing an intelligent statistical process control system to provide better services and less defects.

The application of supply chain management within the construction industry presents significant challenges due to the transient nature of construction projects, high levels of customization, low repeatability of activities, absence of a production line, and interdependent relationships among activities. Construction supply chains are intricate systems, where the final performance results from numerous decisions made across multiple independent companies. Interactions among supply chain stakeholders and the unique characteristics of each project create complex phenomena with multiple interconnected elements and variables. The Viable System Model (VSM), rooted in organizational cybernetics, provides a structured approach to addressing complex and unstructured problems. This structured approach allows analysts to gain in-depth insights into the functional issues of the existing system and understand how to modify the system design to adapt to internal and external disruptions.MethodologyDespite the extensive capabilities of the Viable System Model as a diagnostic tool for assessing organizational structure and achieving viability, a systematic and distinct methodology for its application is lacking. Researchers in VSM often do not employ a specific methodology for systems analysis. In this study, we propose a methodology for applying the VSM as a diagnostic tool for organizations, derived from a review of theoretical foundations and practical requirements of VSM. Building on Jackson's methodology outlined in his book "System Thinking, Creative Holism for Managers," we have developed a methodology by integrating Jackson's approach with case study research. This methodology includes stages such as designing a diagnostic framework, selecting case studies, identifying systems, conducting system diagnosis, and validating the model. We applied this methodology to diagnose the supply chain of an Iranian petrochemical construction project, resulting in the development of a viable system model. The validity of the research methodology and findings was confirmed through expert participation and the application of multiple qualitative criteria.ResultsFollowing the selection of a case study and the identification of systems, we investigated the existence and function of five subsystems and communication channels within the focal system using a case study approach to gather information and develop the viable system model. Data was collected through semi-structured interviews conducted at various managerial and technical levels within a prominent project-oriented company in Iran's petrochemical industry. These interviews lasted between 45 and 60 minutes each. Data collection methods also included observation and document examination. The research involved a semi-structured interview with 18 individuals to explore complications within each of the five systems. Subsequently, the collected data was adapted to the model's requirements, and findings were extracted through intra-case analysis and coding. This process led to model development and the identification of weaknesses within the construction supply chain from the perspective of the five systems and communication channels, with a focus on achieving viability.ConclusionsThe developed model highlights weaknesses and bottlenecks within the focal system, shedding light on the most significant issues. A critical issue identified in the case study is the evident lack of coherence within System 4 and System 5. The results reveal that the incoherence of System 5, divided between parts of the company at level 0 and the parent company at a higher recursion level outside the focal system, results in defects within the communication channels related to this system, including C14 (Connection of System 4 with System 5), C9 (Algedonic channel), and C16 (Connection of System 5 with the homeostatic loop of Systems 3 and 4). Additionally, System 4, which is jointly managed by a segment of the company and the project management consultant, leads to disruptions in channels related to this system, particularly C13 (Homeostatic loop between Systems 3 and 4), C14 (Communication between System 4 and System 5), and C15 (Homeostat of System 4 with the future environment). Concerning common errors, the dominant error is E5, attributed to the lack of coherence between Systems 4 and 5 and the weak performance of System 2. This error largely stems from inconsistencies between the two operational units responsible for the engineering phase and the construction and installation phase. To achieve viability within the focal system, several measures should be taken, including the establishment of centralized Systems 4 and 5 within the company and strengthening communication channels with incomplete or insufficient capacity. These channels include the connection between System 4 and System 5 (C14), the Algedonic channel (C9), the connection of System 5 with the homeostatic loop of Systems 3 and 4 (C16), the homeostatic loop of System 3 and System 4 (C13), and the homeostat of System 4 with the future environment (C15). A crucial homeostatic link involves the communication and interaction between System 3 and System 4 (C13) to establish dynamic communication between the current project environment and its future. However, the interaction between these two systems is currently conflicting and misaligned due to the lack of coherence within System 4 and differences in functionality between System 3's perspective on the current state and System 4's perspective on the future state. Balancing the emphasis on System 4 and the future with the daily operations of the supply chain's operational units within System 1 is essential to avoid supply chain disruptions or inefficiencies. The lack of coherence within System 4 also affects the performance of other systems, particularly System 5, as well as the stability of System 4 in relation to the future environment. Inadequate information about the future environment can hinder informed decision-making within the system. By addressing these points within the model, the construction project's supply chain can move toward viability and better adapt to changes in the project environment. This research represents one of the limited studies in the implementation of VSM within the construction project environment.

Roadside units are crucial elements of intelligent transportation systems that provide vehicle–vehicle and vehicle–equipment information communication. Due to the high cost of installation, the deployment of roadside units is the most critical. Aim of this study is developing a model to optimize of roadside units placement to achieve maximum coverage. A multi–objective mathematical model presented, based on the three main parameters. These parameters are traffic volume, incident rate and adjacency to important centers, which determine for alternative points. The maximum coverage problem is NP–hard. Consequently, conventional mathematical methods are not accurate for large scale problem. A meta–heuristic method based on the greedy algorithm was developed which conciders marking points as definitive–select or non–selectable. Result of the model were evaluated through testing of three scenarios, 200, 500 and 1000 meters coverage in District 5 of Tehran by using MATLAB and the best one, 1000 meters was chosen with 71% coverage. Observations showed the effect of various parameters such as equipment coverage radius, number of equipment and budget on the results of distribution. This algorithm makes it possible to solve the problem on a large scale by using the geolocation of the candidate points.

Highly unstable social and economic ecosystems have inevitably resulted in severe momentums and adverse environmental changes. To overcome the mentioned challenge and also increase their competitiveness, most businesses have accepted a resilience approach. Moreover, the presence of so called techno-social Complex Systems has given rise to serious challenges in developing Business Plans. To have accurate planning for the business, social issues, technical processes, and their correlation should be simultaneously addressed. In this work, following a comprehensive review of the previous efforts, a more detailed and sophisticated explanation of how techno-social factors impact  resilience Business model will be investigated. In other words, we aim to develop an improved Business model  model for companies dealing with the mentioned challenges.

Meta-Synthesis method have been used for gathering necessary resources. A complete review of all related references has been carried out. 78 outstanding articles have been selected from all the papers published since 2000. The study and analysis of these 78 references has built the framework of our work.

In this work 85 sub-codes, indicating the impacts on resilience business model, have been successfully extracted. Using these codes and their proximity in definition, 21 core themes were defined in the next part. Finally, the developed themes have been categorized into four main elements of Business Model Ontology: customer, management, infrastructure, financial flows, and recommended value.

The finally presented model, enjoying simultaneous analysis of social parameters and corporate technical processes, has shown to provide more generality in modeling. The model would be a great help for senior managers to desing resilient  business model. In addition, this model can efficiently be used in thorough assessment of resilience in techno-social companies.

The purpose of this study is to provide a model to explain the functions of the Project Management Office (PMO) of City Knowledge (CK) and prioritize their functions based on the importance-performance status.

The method of this research, In terms of purpose, is functional. In terms of data collection tools, it is descriptive (non-experimental). According to comprehensive literature review regarding to PMO functions, 28 main functions of the CK are identified. Questionnaires are designed and distributed among managers, consultants, facilitators and senior experts of City of Knowledge after content validity and reliability. The data are analyzed using structural equation modeling after measuring the construct validity by exploratory factor analysis. Then the best-worst method is used to prioritize the functions and sub-functions of the model. Then, the performance of each functions is obtained by conducting a survey of experts in the PMO of City of Knowledge. Finally, the functions of the PMO are prioritized using the importance‐performance analysis.

Based on the research findings, 7 functions with 28 sub-functions explain the conceptual model of the research. Also, based on the findings of  the importance‐performance analysis , design and documentation of project management system in the form of process diagrams, procedures and instructions, uniform formats and standard formats, transparency and clarity of information provided in project planning and organization, providing training services in the field of concepts Processes-Methods and tools of project management, design and development and deployment of project management information systems in the organization, participation in evaluating the performance of project managers, and project management teams are the first priority of improvemen.

Originality/Value:

 In this study, a model for assessing the prioritize of functions of the PMO to create an innovation center is presented. The proposed framework could be a good guideline for universities' policymakers to proceed with development projects and be a suitable model for others to benchmark development plans.

Nowadays, quality management is an important field for organizations, including the banking system, which faces fierce competition. Organizational Excellence Models serve as guides to help organizations improve their quality. The main aim of this study was to investigate the dynamic relationships between the approaches and criteria of the EFQM organizational excellence model and optimize the simulation of these relationships. To do this, we first identified the common approaches in the organizational excellence model and clustered them using the fuzzy clustering method. Next, we used the systems dynamics method of causal rings to discover the dynamic relationships between these approaches. Finally, using data from the banking system in Iran, we simulated cases and optimized the growth rate of organizational excellence in the sample over 20 years (2018-2019).

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The aim of this article is to investigate the impact of supply chain risk on the buying behavior of active companies in Mobarakeh Steel Complex (MSC). This study, is of mixed type in terms of the nature and type of the data, is fundamental and applied in terms of the purpose, is descriptive in terms of implementation, and is exploratory in terms of method. The study was carried out in two stages using qualitative and quantitative methods. In the qualitative stage, case study was used as the research methodology. The statistical population included the purchase managers from MSC and its suppliers, from which snowball sampling method was used to select 20 managers for interviews. Interview was used as the data collection tool, and the qualitative data analysis was carried out using the qualitative content analysis method. The analysis was performed using open, central and selective coding methods along with providing documentary evidence. In the quantitative stage, descriptive research method was applied to determine the size of the sample using Karjesi and Morgan's sampling table. Among more than 80 active supplier companies, a sample of 66 companies was selected, of which 62 completed questionnaires were obtained. The data analysis showed that there is a significant relationship between the risk of foreign suppliers and the buying behavior of industrial customers. In addition, the results of the study indicated that in the steel industry, communication systems and environmental factors have less impact than other factors, since suppliers are more concerned about price and quality, which are the main priorities of MSC.

Nowdays, technology progress and development of the industry 4.00, and the new approach in idustry that concentrate in earning money from the knowledge-based economy, has resulted in designing knowledge management strategy based on the open innovation model. The main objective of this paper is to introduce a framework for knowledge management aligned with the model of open innovation at the enterprise level. To this end, the literature of the last 50 years on the WoS database is reviewed, and 34 articles were selected (out of 256 articles ) by the meta-synthesis method. By reviewing and analyzing their content, 55 codes, 16 themes, and 4 categories were extracted. These categories are: 1) creating technological infrastructure and knowledge management infrastructure, 2) Finding the common knowledge base and incorporating the ambidextrous approach for corporate learning, 3) supporting intellectual property and protecting shared knowledge, and 4) continuous improvement of organizational knowledge management performance. The first three categories can lead to the fourth. The results can be used to improve and adapt the knowledge management system in firms that focus on open innovation. It can be used as a criterion for evaluating the knowledge management system of companies seeking support in designing government incentives to encourage open innovation.

Organizational excellence is not an unknown concept in management and organization; in addition, developing novel models, differences between the 2020 model and the old model of EFQM, and different firms’ efforts to develop customized OEM methodology all indicate the dynamics and importance of focusing on this fundamental concept. Therefore, in the present study, an attempt was made to configure and test organizational excellence methodology in Iran’s oil industry.

This research was conducted by using Multi-Grounded Theory (MGT), a complementary and extended method of Grounded Theory (GT), that provides a comprehensive framework to develop distinctive theories. To validate the results, expert surveys were used in a separate stage. The result verified the validity of the acquired results and appropriateness of the final model from the perspective of understandability, comprehensiveness, applicability, and innovation.

Analyzing the gathered data by reviewing more than 70 models developed over the last 40 years and conducting interviews with 22 experts selected through a combination of purposive and snowball sampling methods led to the development of a model with seven criteria, 32 subcriteria, and 102 concepts which improve the excellence of Iran’s oil industry in terms of "Strategic leadership and management development", "Management of organizational capital", "Organizational diplomacy", "Operation and customers", "Results of managerial and supportive processes", "Stakeholders results", and "Value chain results".

The obtained results of the present study can be applied in developing a roadmap for organizational excellence, evaluating and determining plans to improve Iran’s oil industry.

Long-term delays to complete residential units, due to lack of adequate and punctual financing, is considered as a developer's problem, in the process of housing production. In this regard, the present study, with the consideration of the challenges that obstacle the efficient pre-sale of residential units, aims to determine the pre-sale policies of housing by providing a model based on the system dynamics approach in order to provide sufficient and punctual financial resources, reduce delays in completion, reduce opportunity cost and to achieve a balance between developers’ and buyers’ profit. After making a dynamic model and validating it, 48 scenarios consisting of the states of five lever variables were simulated and after analyzing the results, improvement policies which include four alternatives were extracted. The results indicate that to produce the residential units with average prices, whether the percentage offered of area for initial pre-sale is 0/3, the initial pre-sale discount coefficient relative to the price of the completed unit is 0/06 and the down payment coefficient is 0/3, from which the mentioned variables will lead to a significant reduction in completion delays and opportunity cost, and also will balance the profit of both developers and buyers.

Experience has shown that for the development and growth of any country in different dimensions, imitation of many non-indigenous models does not meet the needs of that society. The different conditions of each country in philosophical and epistemological foundations, reveal the need to design an appropriate model, taking into account social, cultural, scientific, economic and political conditions. Beliefs and values, especially in religious societies, modify and shape attitudes and behaviors. The purpose of this study is to design and explain the model of human qualitative growth as the foundation of human beliefs and values.

This research tries to answer these three questions. 1- What structures and components does human quality development have? 2- What is the effect of these components on each other? 3- And finally, what is the dynamic model of human quality growth? Therefore, the research method in this article is a qualitative method of content analysis and interpretive epistemology and phenomenology. The statistical population of this research is thirty-five relevant and valid researches.

By conducting this research, the effective components on human qualitative growth and how they are affected and effective, and then the dynamic model governing the dynamic system of human qualitative growth have been developed. The dynamic system of human development is a multidimensional concept, the components of which, with their dynamic relationships, interact and intensify. The phenomenon of human qualitative development organizes the system of beliefs and values of the individual and shapes beliefs and values.

The Internet of things (IoT) is a new technology that expanding rapidly and has led to the emergence of new services in the banking industry. Although IoT is an emerging technology in Iran, it is expected to become a paradigm in the future. IoT applications in banking have helped to provide high quality and fast responses to customers anytime, anywhere. This research aims to identify and prioritize IoT applications in the Iranian banking industry based on business continuity indicators. First, based on the comprehensive literature review and practical experiences, IoT applications in the banking industry are identified. Then, each indicator's weight was calculated using the Grey Decision-making trial and evaluation laboratory (DEMATEL). Finally, IoT-based applications in the Iranian banking industry have prioritized using the multi-attribute utility theory (MAUT). Due to the unstable economic conditions for the financial sector, business continuity indicators are employed in this study. Also, the reason for using MAUT is to consider the utility of banking experts for performing IoT banking services. According to results, IoT-based services in the banking industry, including Transmit instant reports, smart ATMs, non-contact electronic payments, and electronic checks, are identified for Iranian banks. Then, These appropriate services are prioritized with the capabilities of Iranian banks.

Latecomer firms have a significant technological gap with their international competitors. To fill this technological gap, these companies have to follow the path of technological catch-up. For technological catch-up, the latecomer firm needs to acquire new capabilities or upgrade its existing capabilities in each of the of the catch-up steps. Existing research background introduces higher-order/ dynamic capabilities as a factor in creating or upgrading firm capabilities in 4 steps: 1. Sensing, 2. Learning, 3. Integrating, 4. Coordinating. At each stage, several mechanisms must be used that have been neglected in previous research. This study intends to identify these mechanisms by separating the steps for the path from the level of duplicative imitation to the level of creative imitation through a case study in the country's automobile industry (in Iran Khodro). For this purpose, semi-structured interview tools and theme analysis methods were used, and 11 technological capabilities and 20 mechanisms for capability development were extracted. Among them, 4 mechanisms were in sensing stage, 8 mechanisms were in learning stage, 3 mechanisms were in Integrating stage and 5 mechanisms were in Coordinating stage. The final results were drawn as a conceptual model and approved by a panel of experts.

Along with the competitive behavior of producers, consumers’ behavior significantly influences the market structure. The temporal resolution of recursively repetitive interactions between producer firms and consumers creates and shapes the structure of the market and defines the firms' market shares. In order to explore this issue, we require a comprehensive model considering the behaviors of both sides, such that the variation of the parameters of the model reflects the competitive policies of the producers and the diversity and differences among the spirits of the consumers. The proposed model of this paper is based on these viewpoints and, by variation of its parameters, the effects of consumers’ behavior and moods on producers’ market shares are simulated. The developed model includes two sub-models. The first is based on the theory of differential games to represent the competitive behaviors of producers. The second is agent-based which is developed through learning and choice pattern to illustrate the consumers’ behavior in an oligopoly market. In a numerical example of this model, producers apply their policies in 5 intervals such that between any two intervals of policy application, consumers buy and consume goods in 5 subintervals through which the consumers have the opportunity to learn and gain new experience. In this example, it is observed that the tendency of consumers towards new experiences, the degree of relative importance, that the consumer attaches to their high level of desires, the duration or opportunity of learning and gaining new experience and the delay in the policy implementation, all together, affect the market shares of producers. It is also shown that from perspective of this model, market shares do not change dramatically compared to their initial conditions in the case of belief-based learning; but, in the case of reinforcement learning, consumer behavior becomes more random. In case of belief-based learning, it is expected that as the number of consumers seeking new experience decreases, the market shares diverge. Similarly, increasing in the degree of optimization in the random selection law, in both belief-based and reinforcement learning cases, leads to the increasing of the divergence in market shares. Here, the number of sub-intervals indicates the required time for producers to implement their new market policies. As the number of sub-intervals increases or decreases, convergence of market shares increases, under both types of learning. Delays in the implementation of policies by a producer, in the case of belief-based learning will be in its favor; and, in the case of reinforcement learning such delay will be in adverse of that producer. The presented model of this paper can be used by firms to test their competitive policies, by looking at different scenarios related to environmental conditions and the behavior of consumers prior to deployment of those policies.