morteza abbasi

Maturity models are valuable ways to help manufacturing organizations develop their collaboration. However, there is a lack of empirical work on developing a strategic alliance maturity model with clear guidelines. So, there is no model to measure the maturity of a strategic alliance with an evaluation tool that can deal with the inaccuracy caused by human judgment and the inherent uncertainty of the evaluation. This research created a strategic alliance maturity model based on a weighted Fuzzy Inference System (FIS) through a clear and precise procedure and developed a multi-method approach, including literature review, interviews, focus groups, and case studies, from model design to model evaluation.  In this research, to obtain the weight of the model’s dimensions, the Fuzzy Data Envelopment Analysis (FDEA) technique has been used, which has suitable capabilities for this purpose. The proposed model has been evaluated and validated through a case study. The results of the present study show that this approach provides a strong and practical diagnostic tool based on a set of strategic alliance maturity indicators. By using the results of this model and analyzing the gaps for the first time, an action plan can be prescribed to increase the maturity level of the strategic alliance.

An approach for simulating the initiation of slugs in horizontal pipes is proposed in this research. An analogy is established between the algorithms for solving single-phase problems with discontinuity (Riemann problems) and two-phase slug flow (having a discontinuity in the interface), employing a unique algorithm to solve the conservation equations. Numerical solutions to equations for two-fluid dynamics with transient behavior are obtained by applying a group of conservative shock-capturing techniques. The benefit of utilizing this approach is that the creation of slugs can be computed directly according to the solutions of the differential equations governing the flow field; hence, the location of the interface can be found instantly and without simulation, and the slug regime can be captured automatically. Furthermore, the slug can be captured with low computational cost using a conservative shock-capturing method compared to methods like finite volume. It is demonstrated that the two-fluid model may describe the development of instabilities in stratified flow that give rise to slugs when the mathematical character of the model is hyperbolic. Additionally, the results of numerical modeling and experimental analysis coincide well with the location of slug start. This approach can forecast the flow pattern map and the change from stratified to wavy, and then eventually, slug flow.

This article investigates the selection of a cooperation model with suppliers and the continuous monitoring of the collaboration strategy over time by tracking the supplier's performance. A multiple fuzzy profile monitoring model is proposed and implemented in two stages to oversee the supplier’s unforeseen costs. In the first stage, criteria and indicators for evaluating the delivery process and quality are identified based on literature reviews and expert opinions from industry leaders. In the second stage, a two-phase monitoring approach is adopted. First, using the T² method, the model’s parameters based on successive differences are calculated and separately monitored for the multiple fuzzy profiles of delivery and quality processes. In the second phase, the likelihood ratio method is applied to track the profiles over time, enabling the control chart to signal any warning in the shortest possible time. In the final stage, the results from the fuzzy profiles of delivery and quality processes, combined with artificial intelligence and the fuzzy inference system tool, are used to monitor unforeseen costs, make decisions regarding the supplier, and assess the adopted strategy. This model has been implemented in Iran's automotive industry, specifically within Iran Khodro Company and its gearbox parts supplier, Niromoharkeh Company.

application of Reliability can be seen in many industrial, communication, In the early stages of system design, many system features such as reliability, weight, cost, and etc are associated with uncertainty due to various reasons such as lifespan, operational conditions, etc. Since the use of the probabilistic approach in solving reliability problems has limitations and can only be used in quantitative analysis of information and in many cases does not produce useful and sufficient results for experts, therefore the use of the approach Fuzzy is much more efficient for solving reliability optimization problems. One of the ways to optimize the reliability is to allocate redundancy. When using redundant components in a subsystem, how the redundant components are used is particular importance. In reliability-redundancy allocation problems, the reliability of components is not known in advance and is considered as a decision variable. In the current research, the reliability-redundancy allocation problem has been investigated with two active and cold-standby redundancy strategies and the triangular fuzzy number approach has been used in using the parameters of probability functions and reliability calculation in two model problems and an industrial system. Genetic algorithm has been used to solve the problem. In the implementation of the genetic algorithm, the the random, tournament and roulette wheel methods has been used to select parents and different types of mutation and crossover operators have been used to produce children. The results are more efficient than the results obtained from solving the deterministic model.

The ability to monitor supplier performance is a critical capability to maintain a strong organization-supplier relationship, especially for organizations where the supplier plays a significant role in their end product and market retention. In this article, a multi-variable multi-profile monitoring model is presented, taking into account the risk conditions in two stages for monitoring the quality of parts and supplier products. In the first step, the criteria and indicators for evaluating the quality process as well as the risk function are extracted according to the library resources and the opinion of experts and elites of the relevant industry. In the next phase, in the first phase of monitoring, using the Hotelling’s  Statistic Based on the Successive Differences, the parameters of the model are calculated and monitored, and in the second phase, the likelihood ratio method is used to monitor the supplier's quality process over time, so that if the presence of a warning will show the control chart in the shortest possible time. This model has been implemented in the automotive industry of Iran Khodro Company and the supplier of gearbox parts by Niro Travezah Company.

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

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

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

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

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

The growth and development of defence industries are essential to improve deterrence and national security. One way to develop such industries is to acquire technology-based firms that, in addition to improving the ability to manufacture new products, can help them meet their operational and strategic goals. Since the valuation of such firms is considered one of the complexities of acquisition, this paper aims to propose a model for their valuation according to the ecosystem of defence industries.

Design/methodology/approach: 

To create the model, first the literature in this field has been investigated. Also, the comments and proposals of senior managers, technical designers and experts, economic and financial specialists, and R&D experts in the defence industries have been surveyed and then, the valuation criteria for technology-based firms have been identified using the fuzzy screening technique. Next, by using the fuzzy Analytic Hierarchy Process (AHP), the relative importance coefficients for components, criteria, and subcriteria have been determined, and the valuation model has been developed. Finally, the function of estimating the value of technology-based firms that can be acquired in the Department of Defense (DOD) has been formulated. The study was carried out at the end of 2022 in DOD strategic organizations.

Since knowledge and intellectual properties are the most significant pillars and competitive advantages of technology-based firms, the results showed that the “intangible assets” criterion is the most significant one for the valuation of firms by a weight of 0.449. Following the criterion are the tangible assets, and the major risks with a weight of 0.351, and 0.20, respectively. In this study, the strategic role and importance of technology-based firms for the defence industries, their synergy with these industries, the protection requirements, as well as the stability and durability of the technology-based firms in the condition of disruption were introduced as specific criteria in the valuation model for the firms. Also, the result of the sensitivity analysis indicated that the ranking of options is the most sensitive subject to changes in the importance and weight of intangible assets and the main risk.

Research limitations/implications:

 One of the limitations of the research is that this study was not conducted in a specific defence industry such as electronics and radar, energy-rich materials, chemical, air, or marine industries, and was comprehensively planned in all industries. Since tangible, and intangible assets or even risks may be different in each of such industries, this issue leads to the cautious use of the model in each of these specialized areas. Another limitation was the research statistical population, which only included university professors, senior managers and financial managers of defence industries. Although using the opinions of capital market valuation experts venture capitalists and expert valuation experts of the country's innovation and knowledge ecosystem for further validation of the model and criteria statistics and to specify the specific conditions of valuation in the defence environment, seemed useful, there were limitations in their assessment.

Originality/value: 

Proposing a hybrid model including tangible and intangible assets and considering risks, and also considering the key criteria of the defence sector such as strategic importance, synergy stability and durability of firms, as well as providing functions for estimating the value of technology- base firms that can be acquired in DOD are considered as the two of the most important aspects of contributions and innovations of this research. The current model provides a systematic and scientific plan for defence industry managers and experts who can use it in the valuation of companies that can be acquired in the defence industry and be sure that their interests are taken into account.

One of the elements of the success of any production organization is the optimization of the product distribution channel. Because it affects all the activities of the organization in order to provide the services needed by the customers. Elements such as inventory, marketing decisions, and pricing are effective in optimizing the distribution channel. Although the investigation of these factors alone leads to optimization, but their simultaneous optimization creates global optimal, which has rarely been addressed in past studies. Therefore, this article seeks to present an integrated model for the simultaneous optimization of supply chain elements in the distribution channel. The proposed model is a bi-objective model in which decisions related to marketing; pricing and inventory control are considered. Two internal and external suppliers have been used. In this study, the first objective function seeks to maximize profit and the second objective function is the utility resulting from customer satisfaction. The presented model has been implemented in the supply chain network of Etka chain stores. Inventory management in distribution centers as well as marketing parameters, including product pricing in channels, choosing the best channel for each product, the amount of sales of each product in each channel and finally the amount of discount for products It has been checked in different channels in the proposed model and then it has been solved by LP metric method by GAMS and NSGA2 algorithm. Which shows that the genetic algorithm of NSGA2 in high dimensions provides the desired results in a more appropriate time.

Background and

Thirst is one of the most common problems in patients undergoing hemodialysis, which stimulates the patient to consume more fluids, causes weight gain between two dialysis, reduces quality of life, and leads to many other problems. Therefore, due to the necessity of using thirst management methods, the aim of this study was to determine the effect of ice chip containing menthol on the thirst of patients undergoing hemodialysis.

In this clinical trial study, 60 patients of Birjand dialysis centers were selected considering study criteria using convenience sampling. The patients were randomly assigned to the control and experimental groups. The experimental group consumed 12 pieces of ice chips containing menthol every day for one week and the control group did not receive any intervention. Questionnaires of intensity of thirst, discomfort of thirst, duration of thirst, and dry mouth were completed before each dialysis session during the week before the intervention and during the intervention, and the volume of fluids consumed was measured and recorded in a daily checklist. Data were analyzed using SPSS V15  applying independent t-test, paired t-test, x2 and Fisher exact test at the significance level of P<0.05.

The results showed that in the experimental group, the mean score of duration of thirst, intensity of thirst, dry mouth, thirst discomfort, volume of fluids consumed, and number of thirsts had a significant decrease after the intervention compared to before it (P= 0.0001). The mean score changes of thirst duration, thirst intensity, dry mouth, thirst distress, fluid consumption, and number of thirsts in the experimental group were significantly higher than the control group (P=0.0001).

Considering the effect of ice chip containing menthol on the thirst of dialysis patients, the use of this simple, applicable, and low-cost method is recommended for thirst management.

This research proposes a multi-objective and robust model considering both cost and risks related to the environment (water consumption and environmental pollution), social responsibility (working conditions and employee health), operations (change in demand and return rates), and disruption (accs and diseases such as COVID-19) in the supply chain, using horizontal collaboration to deal with it.

In this research, mixed-integer linear programming and robust optimization technique have been used for closed-loop supply chain network design and a multi-objective method has been developed to solve the problem and create Pareto spaces.

The results of the calculations show the effect of failure probability on the capacity of the facility, the total cost of the network and the degree of collaboration between members of the supply chain to deal with the risk. Also, the amount of cost required for allocation to reliable and unreliable facilities and also creating a suitable Pareto space for deciding on the optimal choice of facilities, capacity and flow between them and iron and steel production technology, according to sustainability and social responsibility indicators, are other research findings.

Originality/Value:

 In this study, for the first time, the design of a robust, sustainable, and resilient network of iron and steel under different risks has been studied. Horizontal collaboration has been used as a new approach to deal with risk and solution method for multi-objective problems has been developed. Using the results of this study, the decision-maker can make informed decisions about the supply chain under risk conditions by considering suitability for each of the objectives.

Outsourcing has been the most common method of cooperation. Today, issues such as increased competition, limited resources, technological complications, uncertainty about the future and increased costs have caused organizations to reconsider their management model and turn to new strategies. In such a situation, strategic alliances can replace outsourcing. The purpose of this article is to design a model to evaluate the current state of an outsourcing and to investigate the possibility of developing it into a strategic alliance. For this purpose, in this research, by studying the literature on the subject, examining examples of strategic alliances and also interviewing experts, a list of effective criteria on the formation of a strategic alliance was prepared and categorized into 6 dimensions. Then, using the content validity ratio method, unnecessary criteria were identified in this list. After that, using fuzzy data envelopment analysis without explicit input method, the best combination of weights for essential criteria was obtained. In the next step, by specifying the minimum values for the formation of a strategic alliance for each of the criteria and dimensions of the model, it is possible to compare the current state of the contractor with the minimum value necessary for the formation of a strategic alliance. Results indicates that through this comparison, organizations can identify their weak points in order to become a strategic ally and plan to improve these criteria and, as a result, succeed in developing strategic allies.

In recent years, responsiveness in the Supply Chain Network (SCN) has been considered to improve competitiveness because customers are the most significant part of a supply chain, and promptly meeting customer demand is substantial. In this article, to deal with the technological risks, the Reinforcement Policy (RP) before the disruption and the Assets-Sharing (AS) policy before and after the disruption has been used as Resilience Policies for Disruption (RPD). Also, the responsiveness of the network, as well as the risks associated with AS, have been considered in mathematical modeling. In addition, Lateral Sending (LS), delivery time deviations, and penalties for lost sales for increasing customer satisfaction in the cost objective function are considered responsiveness policies. A solution method has been developed based on the augmented ɛ-constraint to solve the model. Finally, the results show an improvement in cost by up to 14% and responsiveness by up to 17% by using the proposed policies, as well as the effectiveness of the developed technique to cope with the Multi-Objective (MO) model.

The purpose of this study is to present a new mathematical model to design a supply network by considering the strategic alliance and the relationships between the supply chain members under uncertainty. This study attempts to create a suitable decision-making environment for managers to optimize the network and make appropriate strategic decisions accordingly. Since the mathematical model of network design has computational complexity, providing a suitable solution method for the proposed model is another goal of this research.
As this paper is an applied study, a new mixed-integer linear programming model (MILP) has been presented. The robust optimization method has been used to deal with uncertainty risks such as the risk of changing sales and the return of products. In the mathematical model, strategic alliance levels and the level of risk for each of the partners are considered. The model has two objectives; minimizing the cost, and minimizing the risk of establishing a strategic alliance. The optimal location of the facilities, the selection of production methods, the capacity of facilities, the selection of colleagues, the level of strategic alliance, and their control level have been determined in the presented mathematical model. Considering the computational complexity of the mathematical model, The Benders decomposition method has been applied, and a solution for the proposed mathematical model has been developed and localized by using acceleration mechanisms.
The results show the effectiveness of strategic alliances in reducing the costs of the production and distribution network of goods. The quantification of the concepts related to the strategic alliance in the supply chain, and the establishment of a trade-off between the risk and benefits of the strategic alliance are other research findings. Considering the different levels of strategic alliance and risk for each partner, the results of the current research show that a strategic alliance reduces the cost, and this cost reduction depends on the risk level of the partners. In addition, the computational results show the efficiency of the accelerated Benders decomposition algorithm for solving mathematical models in large-scale problems. In some problems that the Gams software is not able to provide the right answer in the appropriate time, the algorithm based on benders methods provided acceptable answers in a shorter time frame.
Applying the industry data shows the effectiveness of the model in creating a decision-making environment for managers and decision-makers. Also, the results show the appropriate performance of the solution method. Therefore, the finding of this research indicates a new research viewpoint in the field of network design under strategic alliance for the production and distribution of products.

Many producers and large commerce companies must manage their suppliers and reduce or merge them. Most methods mentioned in the literature are qualitative. Therefore, the aim of this research is to present a three-objective nonlinear mixed integer programming model including minimizing the cost of allocating parts to suppliers, minimizing the cost of interactions between suppliers, and minimizing management complexity. The innovation of this research is to simultaneously consider the grouping of parts and allocation to suppliers based on the required operational capabilities of the parts and the capabilities available to suppliers and the tiering of suppliers. This model was evaluated with a case study in the electric motor industry and solved with the method of goal attainment, the validation of the results has also been done.

Due to global threats such as pandemics and wars affecting supply chains, redesigning the supplier network with circular criteria, cost reduction and proper supplier backup to reduce supply risk is a an importtant need in today's industrial society. To address this issue, this paper developed a multi-objective model with conflicting objectives to design a circular reliable supplier network considering knowledge sharing capability, backup, skills, reliable cooperation networks, cost, capacity, order allocation, and circular criteria for a modular product. The proposed model for network design simultaneously considers the following key factors: 1) circular criteria, 2) cooperation network and historical records between suppliers, 3) skills, 4) ability to share knowledge and experience, and 5) cost and backup suppliers. The model was evaluated with the numerical study of the simulated data as well as with the real data of the electro-optical camera, and it was validated with the precise method of augmented epsilon constraint method and LPmetric and the exact solution of small-scale problems, and the sensitivity analysis was also performed.; Therefore, first a modular product was selected and the number of modules was determined by clustering. Then, the parameters and variables were determined and after formulating and solving the model, the model was validated and the results, teams and optimal order allocation were determined. From the results of solving the model with artificial data, the main team (1, 2, 3, 4 and 15) and the support team (4, 8 and 9) were obtained. Also, according to the results of solving the model with real data, the main team (1, 2, 3, 8, 9 and 10) and the support team (4) were obtained. The results showed that, based on all the assumptionsو this approach, suggests the network of optimal circular reliable suppliers in two main and supporting groups with the lowest cost, the most knowledge sharing and reliability and circular criteria. The results are in line with the needs of modern industrial society. At the end, suggestions for future research were presented.

This paper aims to propose a systematic view of how Circular Supply Chain Management (CSCM) captures and evolves the state-of-the-art advances in this field. Multiple analyzes have been performed with two tools of VOSviewer and open-source R-package ‘bibliometrix”. Also, a network and bibliometric analysis of the Co-Occurrence, Co-Authorship, and Co-Citation has been made on CSCM using bibliometric and scientometrics methods on the literature available on the Web of Science and Scopus databases.

Design/methodology/approach:

 Bibliometric, network structure, and descriptive analysis have been used to investigate publications on the subject of circular supply chain management. For this purpose, a systematic review has been performed using the Prisma review protocol. After defining the research objectives and questions, the relevant keywords for the sources and database and search codes have been used for an online search. Then, the initial search has been conducted. The next step involved screening the study results. 116 published articles have been selected from Scopus for analysis. The potential papers were then downloaded in CSV format for bibliometric analysis and synthesis. The final data for this research has been selected from 2010 to 2021. All the data was exported in CSV format to the Bibliometrix and Vosviewer software for data analysis. Also, Co-Authorship, word Co-Occurrence, and Co-Citation analysis have been generated using VOSviewer.

This study analyzed the annual publication trends, the most productive authors, the most cited articles, the most productive affiliations, the most important journals, the most productive countries, and keywords. Collaboration, co-occurrence, co-authors, co-citation, and historiographical analysis were also performed in this study. Findings indicated that "Perona, M" and "Mina, H" with six and five articles were the most productive authors in the development of this field. Also, Geissdoerfer's article was the most cited article with 231 citations, and it can be considered a pioneering work in the field of CSCM development. Farooq's article was also the most cited local article. Govindan et al.'s (2020) article were the most important in co-citation analysis. Great Britain and Italy were the most productive countries with 70 and 66 publications. Cambridge University was the most productive university in England. The "Journal of Cleaner Production" and "Sustainability" were the most visited journal with 24 and 8 articles. The most dominant keywords were "circular economy" and "circular supply chain". The main keywords shared in the most advanced cluster were "circular economy", "circular supply chain", and "supply chain". The main common keywords in cluster 2 included "supply chain management" and "circular supply chain management", and the main common keywords in cluster 3 included "sustainability, and “closed loop supply chain". Also, major cooperated countries included Great Britain, Italy, and China. Strong cooperation between Iran and Denmark, China and Australia, and Britain, and India was also observed. A significant number of articles were written by Iranian researchers, and the number of citations received by foreign researchers was higher. The authorship of the articles included two, one, and three authors, respectively. The results indicated the existence of the development of CSCM with quantitative modeling approaches, proficient algorithms, optimization techniques, and integrated multi-criteria decision-making techniques. Also, CSCM research must identify enablers, drivers, Critical Success Factors (CSF), obstacles and barriers, innovative frameworks, and circular business models.

Research limitations/implications:

 The papers were merely reviewed in the form of scientific and English language journal articles. Other datasets and conference papers, reports, and books can be considered for future study, but they were not included in the structural literature review.

Practical implications: 

CSCM is rapidly developing in supply chain sustainability and can operate as a guide for companies. To apply CSCM, three questions need to be answered:  i) which business/supply chain models should companies choose (closed loop or circular)?; ii) how does it cover supply chain operations to achieve a zero-waste perspective?; and iii) how does the company redesign its supply chain and implement a circular supply chain?

Social implications: 

The application of the results of this study and circular supply chain indicators have positive effects on the sustainability and circular economy.

Originality/value:

 This research is one of the early attempts to analyze the structure of social networks in CSCM using bibliometric and scientometric methods. In previous studies relevant to CSCM, mainly the structured literature review, content analysis, and integrated framework have been used, and few studies have addressed CSCM using bibliometric analysis. In this paper, the R-software was used for the first time as a tool for bibliometric data statistics (open-source R-package tool ‘Bibliometrix’ supplemented by VOS viewer, which is used for clustering and data visualization). Also, the results of the analysis of the two software were compared.

In this study, comprehensive numerical simulations were conducted to examine laminar pulsatile developing flows through flat channels. The developing velocity fields and the hydrodynamic entry length were explored for the Reynolds numbers from 20 to 200, and the low and intermediate non-dimensional pulsation frequency or the Womersley number (1.08 ≤Wo≤ 8.86). For all simulations, the pulsating amplification factor was considered from zero to one, (0 ≤A≤ 1), and to achieve more practical and relevant outcomes, time-dependent parabolic inlet velocity profiles were applied. The outcomes reveal that for the higher values of the pulsation frequency or the Womersley number (6 ≤ Wo ≤ 8.66), the maximum pulsatile entranced length during a cycle is close to the inlet length of the mean component of the flow. On the other hand, for the rest of the Womersley number range (1.08 ≤ Wo < 6), and high amplification factor (0.5 ≤ A), the value of the entrance length increases and is significantly different from the development length of the steady component. Moreover, the results demonstrate that the entry length correlates with the Womersley number through a power-law function, whilst it has linear correlations with the Reynolds number and the amplification factor. Further, using the result of the accomplished numerical study, a practical correlation of the entrance length is offered to be used in the design phase for any type of pulsatile flow through the flat channels.

This paper presents a framework to prioritize the supply chain strategies (SCS) according to all involved criteria, including objectives, process characteristics, product types, and environmental and demand conditions, to gain competitive advantages. This process has been done for the entire SC and upstream, downstream companies, and the focal companies of SC separately. Literature review and nominal group technique were used to identify customized criteria and SC strategies. Fuzzy Multiple Criteria Decision-Making techniques, including FDEMATEL and FANP, were used to structure the causal diagram and prioritize the entire and each section of SC. The case study is an industrial electronic supply chain (ESC) that produces condition monitoring devices. This is the first study on SC strategies for the entire SC and each section separately and implemented in an ESC. In addition, this is one of the few studies on flexibility requirements evaluation in supply chain strategies.

Internet businesses have a large share of global and domestic markets, which are both small and large markets, and they operate from any stratum in Internet businesses, which can be small and limited activities or extensive activities such as company activities and or international holdings. With the increase in the activity of internet businesses and the growth of their market share, the possibility of anti-competitive actions by some of these businesses or the claim of anti-competitive practices by competitors or other persons will increase. In this situation, due to the specific requirements of the e-commerce field and its emerging nature in Iran, the application of competition law rules on the performance of internet businesses will face new challenges. This article, with a descriptive and analytical method, tries to examine the concept of ethics and philosophy of ethics, business ethics, the differences between ethical requirements and legal requirements, the concept of advertising and its importance, and ethical issues in electronic commerce from the perspective of protecting consumer rights and examining the status of protection It has the rights of consumers in advertising in the law of electronic commerce. The results show that since it is desirable to improve the efficiency and well-being of consumers in any market, in principle, competition regulations can be applied in all markets, unless a specific market is excluded from the scope of these regulations for a justified reason.

Disruption of the sleep cycle normal functioning of body system with a significant effect on various dimensions of human lives such as career-related variables. The objective of this study was to investigate the relationship between sleep quality and career adaptability with occupational burnout and to compare them among employees with low and normal sleep quality.

In terms of objective and nature, this study was an applied-descriptive, correlational, and causal-comparative study. The statistical population of the study included a private company in Tehran Province, Iran, where 286 people were selected using simple random sampling as the sample and after completing career adaptability, occupational burnout, and sleep quality scales, the relationship between variables was investigated.

The findings indicated a significant negative relationship between sleep quality and occupational burnout and its dimensions. Moreover, a significant positive relationship was found between career adaptability of people with normal sleep and low sleep (P < 0.0500) and people with normal sleep quality showed lower occupational burnout and higher career adaptability. In comparing female and male groups regarding career adaptability and occupational burnout, the results showed that a significant difference exists between them in emotional exhaustion; females obtained larger mean values compared to men and no significant difference was observed among the components.

Given the findings of this study, it can be concluded that sleep, in addition to decreasing occupational burnout, leads to higher career adaptability among employees.

Behavioral disorders in children cause helplessness in academic and behavioral performance and also reduce their efficiency. The aim of this study was to investigate the effectiveness of video-based attachment-based education on parental bonding of children with behavioral disorders.

The present study was a quasi-experimental study with a pretest and posttest design with a control group. The statistical population of this study includes children 10 to 12 years old with behavioral disorders (according to the diagnosis of child psychologists or child psychiatrists in Sari) and their parents (mother or father) who from July to December 1398 to counseling centers under the supervision of welfare They have been to Sari. A total of 20 samples (20 including children with one of their parents) in the form of 2 groups of 10 people were purposefully selected based on inclusion and exclusion criteria. Data collection tools included the parents' version of the Rutter Child Behavior Disorder Questionnaire (1994), the Goodenough Puppet Painting Test (1920), and the Pianta Child-Parent Relationship Scale (1994). Video feedback attachment training was provided to the experimental group in 10 sessions (three months, one week per week), while the control group received no training. data were analyzed using statistical methods including mean, standard deviation, and analysis of covariance and using SPSS software version 25.

The results of the analysis of covariance showed that attachment-based education through the video feedback method had a significant effect on parental bonding and its components in children with behavioral disorders (p <0.01).

In general, the results indicate the effect of attachment-based education training on video feedback, which can be used as an effective way to improve parental bonding of children with behavioral disorders.

The aim of study was to investigate the effectiveness of attachment-based training with video feedback method on parental bonding of children with behavioral disorder. The method of this research was quasi-experimental with pre-test and post-test design and control group. The statistical population of this study is children aged 10 to 12 years with behavioral disorders (according to the diagnosis of child psychologists or psychiatrists in Sari) and their parents who referred to counseling centers under the supervision of Sari Welfare. 20 people (20 children with one of their parents) in 2 groups of 10 people were selected as a purposive sampling method based on entry and exit criteria. Data collection tools included the Rutter Child Behavior Disorder Questionnaire (1994), the Goodenough Draw-a-Person test (1920), and the Pianta (1994) Parent-Child Bonding Questionnaire. Findings of the study using MANCOVA showed that there is a significant difference between the experimental and control groups in the post-test of research variables and attachment-based video feedback training has been able to improve parental bonding and its components in children with behavioral disorders. It is concluded that attachment-based training can be used as an effective way to improve parental bonding of children with behavioral disorders.

In the present research, the non-uniform magnetic field effect on separation phenomenon in divergent channels was investigated numerically. The governing equations, including continuity and momentum equations, were presented and simplified for the laminar, steady, and incompressible flow; then, a non-uniform magnetic field was applied to the flow. Hence, the finite volume method using the OpenFOAM CFD toolbox was employed and a code for 3-D divergent channel flow under a non-uniform magnetic field developed. The effect of non-uniform magnetic field intensity on the boundary layer separation phenomenon on the divergent channel wall was investigated. The results show that the separation in the flow without applying a magnetic field occurs in Re=250 on the channel's upper (lower) wall. By applying the magnetic field and increasing the Hartmann, the boundary layer separation was delayed and in Ha equals 4, the separation is completely deleted and not observed. Under the same conditions, near the sidewalls, the separation occurs sooner than the channel entrance. Furthermore, by reducing the Reynolds to 208.33, the separation occurs late. In a 3-D channel that has a width ten times bigger than its height, the separation points far from the side walls are almost the same as a 2-D channel.

To address problems in product development, decisions about product architecture and supply chain, and specially supplier network, are usually sequenced. This study aims to propose a model considering the product architecture and the supplier network at the same time in the early stages of product design for two optimization goals: i) to increase the weight of the supplier cooperation network; and to minimize the total cost of transactions and the proposed modules’ cost. The relationship between suppliers and within and between modules has been also considered in the early stages of design. The cost of interactions has been estimated, using clustering to obtain the Design Structure Matrix (DSM). The proposed solution was examined in an artificial network and on the electro-optical camera. This research aims to minimize interaction costs and maximize suppliers’ collaboration networks.

In the first step, a DSM was developed for Product Architecture. Then the mathematical optimization MO_MINLP with a two objective model was developed. The proposed model was solved by GAMS software using Weighted Sum, LP metric, and augmented epsilon constraint methods. Consequently, the results were compared and a sensitivity analysis was performed.

The model aimed to minimize costs, including the total cost of internal and external transactions. The module proposed cost and maximized the weight of the supplier cooperation network. To evaluate the model, an artificial numerical problem and a real problem on the electrooptical camera were studied. The experimental results confirmed that the proposed model can effectively design supplier networks and assign modules to the best suppliers. The analysis of the results indicated that considering the transactions cost and supplier cooperation network simultaneously in a bi-objective model more effectively optimizes and designs the supplier network. The model’s solution results implied reduced redesign and rework with minimum cost. The results also highlighted: i) Simultaneous consideration of product architecture and supplier network in the form of a team and network of suppliers. ii) Nonlinear bi-objective model: to increase the weight of the supplier cooperation network; and to minimize the total cost of internal and external interactions for the realization of product modules for the main manufacturer and the module proposed cost by the supplier, taking into account the skills and capacity and supporting suppliers. iii) Considering the relationship between suppliers and within and between modules iv) Assisting in the selection of the right supplier in the early stages of design v) Estimation of the cost of interactions, using DSM clustering. Research limitations/implications: In the case study, the most critical limitation in collecting necessary information and developing a computational model was the lack of historical data for product architecture and parameters. Practical implications: Applying the proposed approach reduced the cost of product design and its associated operations. Practitioners can use this approach in selecting the best supplier and modules. The proposed approach reduced rework and redesign and supplier network costs in early product design processes. Social implications: Implementation of the proposed approach decreased social costs by reduced rework and redesign and supplier network costs in early product design processes. Such an achievement was also related to the social network of suppliers.

The proposed mathematical model innovatively integrated product architecture and supplier network using MO_MINLP and used the results to optimize a typical industrial product.

Increasing attention to the closed-loop supply chain and considering forward /reverse logistics has led to the presentation of various mathematical models in this field. This paper first presents a robust model for a supply chain network with forward /reverse flow approach, and then uses the experiment design method to determine the effect of each of the robust modeling parameters and the parameters of cost, production rate, return of products in the top and bottom level. this paper presents a new robust optimized model for the supply chain network.design The use of robust mathematical design and experimental modeling at the same time, which is done for the first time in this paper, has caused: 1) to increase the speed of achieving optimal answers, 2) to help the decision maker in the appropriate choice of model parameters in a structured way. The report and the presented results, according to the information of iron and steel industry, show the efficiency of using experimental design in order to reduce the time of solving the mathematical model and providing guidelines to the decision maker in the strategic area of supply chain.