Modern Research in Decision Making

Abstract Quality 4.0 is an emerging research topic and refers to how to adopt quality management in the fourth industrial revolution era, which today's organizations can use as a strategy for competition and progress in the market. This research aims to investigate the barriers to applying Quality 4.0. Therefore, in the first step, the obstacles to applying Quality 4.0 were identified by reviewing the literature. In the second step, identifying barriers is localized using Fuzzy Delphi Method (FDM). The approved barriers are prioritized in the last effort using the Bayesian best-worst method (BWM). The case study of this research is Shahr-e Ketab Institute, and the expert panel included eight senior managers of this organization. Using the literature, 23 barriers to applying Quality 4.0 are identified. According to the results of FDM, seven barriers were confirmed. Based on the results of the Bayesian BWM, the cost of deploying Quality 4.0 infrastructures is recognized as a more critical barrier. Lack of trained and qualified human resources and digital integration are ranked second and third, respectively. The results of this research are of particular importance because it plays a significant role in helping stakeholders understand the barriers to implementing Quality 4.0.

Abstract Today, by adopting a circular approach, organizations can reduce the flow of materials, products, and environmental waste caused by supply chain practices. Therefore, circular supply chain management is one of the appropriate methods to reduce issues such as pollution, resource depletion, and environmental problems. Despite these advantages, the implementation of the circular economy in the supply chain faces numerous challenges. The purpose of this research is to identify and prioritize the challenges of implementing circular supply chain management in Premium Band Company. In terms of results, this research is considered part of applied-developmental research. In the first stage of the research, the challenges of implementing the circular economy were identified and categorized using a systematic approach. This involved reviewing literature and articles published from 2000 to 2022 and employing the qualitative content analysis method. This process resulted in the design of a model, which included 33 challenges across six dimensions: legal and regulatory, market, social, organizational, technological, and financial and economic challenges. In the second stage, the importance of these challenges was determined using the Hesitant Fuzzy Topsis method, based on the opinions of 10 experts from Premium Band Company through a questionnaire. The findings reveal that challenges such as a lack of financial resources, insufficient budget, inadequate support and commitment from top management, absence of a circular supply chain management structure, and a shortage of skilled labor are the most significant obstacles in the implementation of circular supply chain management.

Abstract In general, information technology has a sustainable nature, and in line with preserving the environment, it can advance programs that protect the interests of future generations. On the other hand, the presence of acute viral diseases in different periods has caused many human and financial losses in the world. Sustainable information technology can have a great impact on the management and control of acute viral diseases, which human power alone seems to be insufficient. Therefore, the purpose of this research is to design a management and control model using sustainable information technology for acute viral diseases. In the current research, it is an applied research that developed a conceptual and process model by using the qualitative method of theme analysis and the formation of a panel of experts. The data collection tool is an unstructured questionnaire for interviewing experts who include the medical community, university faculty members, and knowledge-based managers. Sampling continued using the targeted method until reaching theoretical saturation with the number of 26 interviews. The results presented a model with four sub-themes including: sustainable value (social, economic, environmental), management and control of viral diseases (planning, organization, control and monitoring), information management (data collection, information dissemination, reporting and data analysis). ) and finally led to sustainable information technology factors (sustainable performance, attitude, technology, policy and implementation). In the process model, the main components of the algorithmic model include identifying, designing, organizing and storing information. Therefore, it can be said that by using the management and control model implementation during

Abstract With the emergence industry 4.0, many industrial and service sectors have moved towards using it to improve their effectiveness and efficiency. This transformation has been done slowly in Iran's healthcare sector, so it is necessary to identify the factors affecting its acceptance. The requirement to start this movement is to accept it. Considering the existing research gaps, this research has been conducted to identify, model and analyze the scenario of Industry 4.0 acceptance factors in Iran's healthcare supply chain. This research was done in 2 stages with a mixed approach. The first stage with a qualitative approach seeks to identify acceptance factors and the second stage with a quantitative approach seeks to model and analyze their scenarios. The statistical population in both stages are experts in the healthcare supply chain and sampling methods is judgmental and snowball. In the first stage, semi-structured interviews and thematic analysis were used, and in the second stage, a researcher-made questionnaire and fuzzy cognitive map were used. The results of the first stage show 23 acceptance factors, which were classified into 4 categories: "personality factors", "organizational behavior", "organizational hardware" and "management". The results of the second phase indicate that "emotional intelligence", "organizational culture", "social responsibility" and "stakeholders' awareness of I4.0 technologies" are drivers and "organizational openness" is the recipient. The results of the analysis of forward and backward scenarios show the importance of "effective change management", "trust", "stakeholders' awareness of I4.0 technologies", "financial capability" and "optimism towards technology".

Abstract Managers and investors always tend to predict the results of their decisions and investments based on expectations and existing conditions. Undoubtedly, for this purpose, they need a correct analysis of the current situation and predict future events. Therefore, the aim of the current research is to provide a dynamic model for predicting possible financial crises. In order to achieve the purpose of the research, first, by using the content analysis, 25 indicators were identified from the categories of macroeconomic indicators, industry factors, company characteristics, political, cultural, and behavioral events. Then, by using multivariable regression algorithm, smart ant colony algorithms and particle swarm optimization, and using the combined data of 173 companies accepted in Tehran Stock Exchange from 2010 to 2020, the proposed model was tested. The findings based on the regression method showed that some internal and external criteria had a significant impact on the financial crisis of companies. the findings showed that in terms of efficiency, the optimization method of ants is the most efficient in the problem of predicting the financial crisis. Finally, it was found that the information of independent variables can predict the financial crisis of companies. The findings of the research also show that up to five years before the financial crisis, it is possible to predict the financial crisis in companies with relatively high accuracy, but as the financial crisis subsides, due to the decrease in the clarity and accuracy of the financial sector forecasting indicators, the predictive ability of the model also decreases.

Abstract Social media marketing is a relatively new concept in discussion of the Internet marketing and the digital markets, and considering that most companies do marketing in this type of media based on trial and error, their main problem is not having a comprehensive model. In order to properly use this space and the tools available in it,is necessary to formulate a comprehensive social media marketing model by helping to know the main components affecting it.
This research is practical in terms of purpose and in terms of collection method is meta-synthesis which was carried out with the help of Sandofsky and Barso's seven-step method. The statistical population includes existing literature and documents and articles between 2011 and 2022, which was conducted as a purposeful sampling based on entry and exit criteria and using the verification form tool. The analysis was done with the help of MAXQDA software and based on open coding, axial coding and creating classes. Validity was also confirmed with the help of internal validity and experts' point of view, and finally a comprehensive framework and useful roadmap was presented, which has 99 open codes, 21 core codes, and 3 main dimensions, including internal environment factors, external environment factors, and shared environment factors. Due to the fact that the research done on social media marketing has been done heterogeneously in certain electronic businesses and on certain variables, more variables and businesses were included in this article and it also has innovation in the research method and content.