۱.
This research addresses the critical gap in Information Technology Governance (ITG) models specifically tailored for the successful implementation of Branchless Banking (BB). While ITG has been extensively studied, its application within the unique context of BB remains underexplored. This study proposes and validates an operational ITG model designed explicitly for BB implementation. Drawing upon a comprehensive literature review and insights from in-depth interviews with information security experts, this study identifies the key effects of ITG implementation on BB success. An operational model is developed and empirically validated using Partial Least Squares The structural modeling results demonstrate that ITG exerts a significantly more favorable and robust effect on BB success when mediated through Digital Transformation (DT). Furthermore, the core ITG framework components—Strategic Planning (SP), Risk Management (RM), and Quality Management (QM)—are found to have significant positive influences on the ITG framework itself. Crucially, ITG also exhibits a direct, positive, and significant impact on the successful implementation of BB. These findings underscore the necessity for banks to align their DT strategies with a robust ITG framework to effectively eliminate physical branches and digitize banking processes.
۲.
Industry 5.0 envisions a transformative industrial paradigm that goes beyond mere automation, emphasizing human-centricity, sustainability, and resilience. The convergence of Artificial Intelligence (AI), Internet of Things (IoT), and Blockchain forms a powerful technological foundation to achieve this vision, enabling intelligent, interconnected, and secure industrial operations. In this paper, we propose a comprehensive conceptual architecture for integrating these three technologies, facilitating seamless interaction between humans, machines, and decentralized systems. We conduct a systematic review of the existing literature, examining design patterns, practical use cases, adoption barriers, and key challenges. Additionally, we analyze real-world industrial implementations to extract insights, lessons learned, and best practices. Our findings highlight critical technical, governance, and scalability issues, including interoperability, data privacy, regulatory compliance, and infrastructure limitations. To address these challenges, we present a multiphase strategic roadmap for the deployment and adoption of AI–IoT–Blockchain convergence in human-centric industrial environments. Finally, we discuss emerging research directions, such as post-quantum blockchains, federated learning, autonomous economic agents, and resilient cyber-physical systems. Our analysis indicates that while the convergence of these technologies holds transformative potential for Industry 5.0, practical and scalable adoption requires careful system design, iterative prototyping, and robust policy frameworks. This study provides a structured reference for researchers, practitioners, and policymakers seeking to advance human-centric, sustainable, and technologically empowered industrial systems.
۳.
This study aims to identify and rank the key barriers hindering the adoption of Blockchain technology in the tourism industry, given its transformative potential and strategic relevance. The research utilized a mixed-method approach. First, barriers were identified through a comprehensive literature review and expert interviews. A sample of 22 experts in Blockchain and tourism was selected, and data were collected using a structured questionnaire. The Interpretive Structural Modeling (ISM) technique was employed to prioritize the barriers, and Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was used to analyze the causal relationships among them. The study identified 11 critical barriers to Blockchain adoption in tourism. Among these, "lack of knowledge, expertise, and human capital", "lack of standardization", "absence of government regulations", and "inadequate employee training and customer awareness" emerged as the most significant. Furthermore, "resistance to change and non-acceptance by companies" was found to have the highest level of interaction with other barriers, indicating its central role in the adoption process. This research contributes to the limited body of knowledge on Blockchain implementation in tourism by offering a systematic prioritization and relational mapping of adoption barriers. The findings provide strategic insights for policymakers, tourism stakeholders, and technology developers aiming to facilitate Blockchain integration in this sector.
۴.
In recent years, academic libraries have increasingly sought to enhance service quality and operational efficiency through the adoption of advanced technologies such as Radio Frequency Identification (RFID). Despite its well-documented benefits, the implementation of RFID systems faces numerous challenges. This study aims to identify and analyze the key barriers to RFID adoption in academic libraries in Iran. The research is applied in nature and employs a descriptive-survey methodology. Initially, potential barriers were extracted through a comprehensive literature review and previous studies. These were then validated via expert input using a structured questionnaire. Subsequently, to examine the interrelationships among the identified factors, a second questionnaire was administered, and the data were analyzed using Fuzzy Cognitive Mapping (FCM). The findings reveal that "High Implementation Cost," "Resistance to Change," and "Technical Issues" are among the most influential barriers in the RFID implementation process. These insights can support library managers and IT policymakers in developing more strategic and effective approaches for the successful integration of RFID technology in academic environments.
۵.
The aim of the present study was to investigate the impact of new marketing strategies and emerging technologies on the behavior of sports venue customers. This study was applied in terms of purpose and descriptive-correlational in terms of method. The statistical population included sports venue customers in Kermanshah and Kurdistan provinces, a sample of which was selected based on the random cluster sampling method. Data were collected using a marketing mix questionnaire and a researcher-made ICT questionnaire. The validity of the instruments was confirmed by experts and their reliability was confirmed using Cronbach's alpha coefficient. Data analysis was performed using path analysis and structural equation modeling. The results of the study showed that the marketing mix and ICT components have a positive and significant effect on attracting sports venue customers. Also, human factors, hardware infrastructure, and the service delivery process were identified as the most effective factors in shaping customer behavior and increasing their attraction. Accordingly, sports venue managers’ focus on digital transformation and implementing integrated marketing strategies can improve customer experience and strengthen long-term relationships with them.
۶.
This study compares three machine learning algorithms (Multilayer Perceptron Neural Network (MLP), Random Forest (RF), and Decision Tree (DT)) for modeling biodiesel production. For this purpose the synthesis methods (UIMS, MS, FPUI, PUI), the methanol to oil ratio (3:1 to 15:1) and reaction times (5–50 minutes), were considered as input parameters and the percentage of biodiesel production was considered as the output of the model. According to the results, the MLP model demonstrated superior predictive performance, with an R² score of 0.9800, RMSE of 3.28, and MAE of 2.35, significantly outperforming RF (R² = 0.8892) and DT (R² = 0.8500). Also, the neural network model represents that all parameters (reaction time, methanol to oil ratio, and synthesis method) hold nearly equal importance. Based on the neural network model, the optimal synthesis conditions are: the UIMS method, a reaction time of 47 minutes, and a methanol-to-oil ratio of 5.8:1, yielding a predicted conversion of 98%.
