Journal of System Management(JSM)

Industry 4.0 includes an important regeneration of production and management systems within manufacturing, where the majority of the procedures will be entirely or partially automated. However, there are insufficient research studies related to machines tool operation optimization considering the effective criteria for reliability in industry 4.0 to enable plants to measure their own conditions and to make future strategies for their activities in this field. Thus, this article proposes a decision-making model using a combination of DEMATEL, ANP and Shannon Entropy, and VIKOR methods with fuzzy features in cellular production systems, considering the effective criteria for reliability in Industry 4.0. Use of fuzzy features aims to bring the problem closer to the real world in this study. The efficiency of proposed model has been validated in a large automotive parts manufacturing plant as a case study. Based on the results, the most critical machine in the category of automatic lathe machines is Machine3, and the ordinary lathe machines is Machine31. Sensitivity analysis shows that changing the weights of criteria affects the individual prioritization of machines but does not have any impact on their overall prioritization. This prioritization has a high level of alignment in terms of priority and accuracy with the perspectives of experts and decision-making teams. The selected critical machine is a sensitive machine in plant and cannot be replaced throughout its equipment lifetime. Finally, practical recommendations for Machines Tool Operation Optimization have been provided in Industry 4.0.

Effective supply chain management (SCM) enhances organizational performance by optimizing resource allocation, reducing costs, and increasing customer satisfaction through streamlined operations and cross-functional collaboration. This leads to improved inventory management, higher service levels, and a competitive edge. Sales and operations planning (S&OP) plays a vital role in aligning demand forecasts with supply capabilities, fostering visibility and proactive decision-making. This minimizes inventory costs and improves responsiveness to market changes, supporting strategic goals and long-term success. Despite its importance, a gap remains in systematic literature reviews that categorize trends and challenges in S&OP. Addressing this gap aids supply chain managers in identifying and understanding current challenges and trends, facilitating informed decision-making. This study conducted a comprehensive systematic literature review, examining 295 studies and selecting 66 relevant articles published between 2012 and 2023 using screening methods coupled with TOPSIS and ANP techniques. The results reveal that most studies focus on optimization models for S&OP, employing optimization techniques, simulation, heuristic methods, artificial intelligence, machine learning, statistical approaches, and qualitative models. The research identified key S&OP planning issues and various models for addressing them. It also highlights emerging trends, such as the increasing use of machine learning and artificial intelligence to improve demand forecasting and decision support systems. Additionally, the growing focus on sustainability in supply chains, including reducing carbon emissions and minimizing waste, is being integrated into S&OP models. However, challenges persist, including dependence on accurate and reliable data, data quality issues, and organizational resistance to change. The complexity of S&OP processes also presents obstacles. This review provides insights into S&OP models, trends, and challenges, and offers future research directions, emphasizing AI integration, sustainability, and hybrid modeling approaches. Addressing these challenges can enhance alignment between sales, production, and inventory, ultimately improving business performance.

The main problem of most companies is the short life of brands. The brand life cycle is used by many business managers and plays a very vital role in determining strategies. Considering propulsions and inhibitors that strengthen or hinder this type of marketing, entrepreneurial marketing (EM) is one of the new topics of the brand life cycle management. An accepted framework for EM and identification of effective factors for brand cycle management is not available. Therefore, the purpose of this article for solving the above mentioned problem is to design an EM model for brand life cycle management. This is how this paper contributes in this regard. The necessity of this research is the short life of brands and the waste of economic and social capital. This current research has qualitative approach and is descriptive-exploratory in data process with conceptual qualitative analysis methodology. The tool applied in this research are interviews |(semi-structured) and the population of this paper includes managers, marketing and brand experts in the field of chemicals, medicine and facilities industries in Eshtehard industrial zone of Tehran, Iran. The target community have been selected by snowball sampling method. Interviews extracted data has been classified by Open, axial and selective codes and were analyzed by Maxqda software. After investigating of codes by experts and eliminating items less than critical amount of 0.62 (according to Lawche formula), finally 166 codes and 23 components as propulsion and 84 codes and 16 components as inhibitors of EM were identified and categorized for brand life cycle management. The conceptual model of this paper has been reached from the review of the research background and interviews with the experts and by the final investigations, we reached to the conclusion that propulsion and inhibitors are affecting on entrepreneurial marketing and consequently on brand life cycle management. The results of this research shows that entrepreneurial marketing is a suitable solution to manage the brand life cycle and prevent the early decline of brands.

Today, manufacturing companies must address the increasing trend of smart manufacturing (SM) to maintain their competitiveness. Concurrently, small and medium enterprises (SMEs), which constitute the backbone of numerous production economies, are endeavoring to comprehend the complexities associated with implementing this advanced production system. However, many of these enterprises are hesitant to adopt SM due to insufficient human and financial resources. The transformation of a company's existing system into smart production systems, as opposed to implementing smart manufacturing from the outset, necessitates greater financial and temporal investment. Consequently, it is imperative to consider and integrate effective requirements for smart production systems during the design phase. This study aims to identify these requirements, ascertain their significance, and comprehend the contextual relationships among them. To achieve this, a systematic review method is employed to identify the requirements, followed by the Intuitionistic Fuzzy Multiplicative Best-Worst Method (IFMBWM) to determine their weights. Finally, the TISM method is utilized to understand the interrelationships and compare the levels obtained with the results of the best-worst method. The results indicated that the effective requirements can be categorized into eight main criteria. The highest and most fundamental criterion is the requirement for digitalization and real-time data connection. The second criterion is automation, followed by smart communication with beneficiaries as the third. Overall, small and medium-sized enterprises should prioritize information technology and artificial intelligence requirements to advance towards smart production systems.

Introduction and Objective: A growing body of research has highlighted that the capability for organizational learning is the singular competitive advantage that enables organizations to thrive in today’s turbulent environment. The primary objective of this study is to design a conceptual model for leading learning organizations within higher education institutions in Fars Province. Research Methodology: This research is developmental in nature, employing a qualitative design through thematic analysis and semi-structured interviews. Participants were selected using purposeful sampling and the concept of theoretical saturation, resulting in a sample of 25 faculty members and specialists in higher education. To obtain the credibility and validity of the data, two methods were used: participant review and expert review by non-participants in the research. Reliability was determined using the Holistic coefficient, which was found to be 0.87. To achieve transferability, interviews and consultations were conducted with 25 specialists, and to ensure dependability, all details of the research were meticulously recorded at every stage. Findings: The research findings indicate that the conceptual framework for learning organization leadership in higher education institutions in Fars Province encompasses four main dimensions: structural perspective, which includes flexibility, simplification, decentralization, and technology focus; contextual perspective, featuring policy-making, network expansion, strategic thinking, and culture focus; transformational perspective, characterized by leader mentorship, customer orientation, team trust, Magnificent Leader, and leader pragmatism; and knowledge-centered perspective, which supports knowledge production, knowledge sharing, and a belief in science. Research and Conclusion: Identifying the key components influencing leadership in learning organizations within higher education institutions is essential. By prioritizing these elements in the strategic planning of higher education management, it can pave the way for a broader adoption of this leadership style nationwide.

The food packaging industry has been investigated as a case study in this study.The present study was conducted based on interpretive philosophy and with an inductive approach. Also, the present study is an applied-developmental study in terms of objective, and it is a non-experimental (descriptive) research in terms of data collection method. A qualitative research design was used to achieve the research objective. In this study, population includes professors of management and food industry managers. Purposeful sampling (snowball method) was used and theoretical saturation was achieved with 20 participants. The participants of this research include theoretical experts (university professors) and experimental experts (food industry managers). A semi-structured interview and a decision matrix-based questionnaire were used to collect data. The results of qualitative coding were validated with the Holsti method (0.717) and Cohen's Kappa (κ) (0.659). The validity of the questionnaire was confirmed by the formal method and the reliability of the questionnaire was also confirmed by estimating the internal correlation coefficient (0.815). Analysis and coding of the text of the interviews was done using the theme analysis method in MaxQDA 20. Also, structural-interpretive modeling method and MicMac can be used to determine relationships between constructs and model design in the second part. According to the results, the investigated factors and components were grouped in seven levels. These components are: Level 7 components including business resources, digital transformation leadership and digital/sustainable foresight, Level 6 components, including digital/sustainable innovation strategies, the components of level 5, including the use of new technologies in processes and operations, core digital/sustainable capabilities, and employees' digital experience, level 4 components of the model, including a new approach to food packaging industry processes, improving sustainable food packaging functions, and designing innovative food packaging, the level 3 components, including the alignment of the digital/sustainable innovation strategy with Digital/Sustainable Capability and Business Sustainability in the Digital Age, the level 2 components, including the component of improving customer experience (digital/sustainable), and finally, the “consequences of digital transformation” component with an sustainability-driven innovation approach in the food industry.

The study was conducted with the aim of offering a social media-based digital marketing model for the development of foreign trade. This is an applied-developmental research in nature, following a mixed-method approach in terms of data. Information was gathered through library research, and data collection was conducted via fieldwork. In the qualitative section, the variables, components, and indicators of the model were identified and extracted using content analysis. The qualitative statistical population consisted of 17 marketing managers from exporting companies in the detergent, cosmetic, and hygiene product sectors, selected through non-probability, purposive, and theoretical sampling using the snowball technique. The quantitative statistical population included 151 managers, experts, and marketing experts randomly selected based on stratified sampling. Data collection was done through fieldwork, and the tool for gathering data was a researcher-made questionnaire. The qualitative content analysis results identified the model variables as: “Social Media Trade Strategy in International Markets”, “Marketing Communications in Social Media in International Markets”, “Social Messaging Strategy in Social Media in International Markets”, “Marketing Actions in Social Media in International Markets”, “Customer Value Creation in Social Media”, and “Export Trade Development”. Interpretive-structural modeling was used to generate the model, and the findings from this section indicate that the structural model consists of five levels, with “Social Media Trade Strategy in International Markets” and “Marketing Actions in Social Media in International Markets” being the most influential and independent variables. The variables “Marketing Communications in Social Media in International Markets” and “Social Messaging Strategy in Social Media in International Markets” are interconnected, and finally, “Customer Value Creation in Social Media” is the most dependent and affected variable, with a sequential effect on the others. Subsequently, the relationships within the generated model were tested using SEM. The validation findings demonstrated on export development were positively and significantly confirmed in the model. The results of this study suggest that to enhance social media marketing for export development, customer value creation should be strengthened through marketing communications and the implementation of social media marketing.

Compilation and approval of the transformation and excellence document of Islamic Azad University and emphasizing the transformational turn from cultural and educational inefficiency to an educational, cultural and identity community in the document and emphasizing the role of influencers in this transformation, adopting a strategic and management model in line with creating a platform for education and has put social education in front of Islamic Azad University. In this regard, this article, which has been written by using a qualitative approach based on documentary studies and extracting statistical data from monitoring and buffer systems, aims to answer the question that the application of culture gardening model in Azad University How has Islamic been able to increase the role of influencers and reduce tenure in this university and in the process of social education? The results and findings of the present applied research, which is based on the evaluation and comparison of the influence status of student institutions (centers, Islamic organizations of academics and publications) in The cultural achievements of the academic years 2021-2022 and 2023-2024 have been obtained, indicating the increasing role of the influence pole of student institutions in units of the Islamic Azad University and the reduction of tenure in this university, as this will provide the basis and necessary arrangements for the realization of the ministry stage in the process of social education and training. The entry of students into the field of participation and responsibility and special attention to their agency in cultural programs has been provided

This study identifies and ranks the obstacles to implementing Total Quality Management (TQM) in small and medium-sized enterprises (SMEs), with a focus on the food industry. The aim is to understand the key barriers hindering the adoption of TQM in this sector. The research is applied and descriptive, using a survey approach. Data were collected from managers in the quality control and assurance departments of food industry SMEs, selected through snowball sampling, via a structured questionnaire. The study applies the Group Best-Worst Method (GBWM) to prioritize these obstacles. The results show that “Lack of commitment and involvement of senior management” ranked as the most significant barrier with an importance coefficient of 0.299, followed by “Senior management instability” (0.117) and “High rate of organizational turnover” (0.117). In addition, the consistency ratio of less than 0.1 indicates high validity of the results. This research provides practical insights for overcoming TQM barriers in SMEs, contributing to the development of TQM strategies in food industry SMEs, especially in developing countries.