This study conducts research on retailers’ behavioral intentions and behavior in adopting e-commerce platforms (ECPs) and uses the unified theory of acceptance and use of technology (UTAUT2) model as well as add other factors such as Personalization Platform, Seamless Interaction. The findings show that Effort Expectancy, Social Influence, Hedonic Motivation, Retailers’ Capacity, Integration Strategies have a positive impact on retailers’ behavioral intention of adopting ECPs and Performance Expectancy has a negative impact on retailers’ behavioral intention of adopting ECPs. At the same time, Behavioral Intention, Facilitating Conditions have a positive impact on retailers’ behavior adopting ECPs and Seamless Interaction has a negative impact on retailers’ behavior adopting ECPs. With important implications, these findings are proposed to relevant parties, helping retailers and ECPs suppliers identify factors affecting retailers’ behavioral intention and behavior in adopting ECPs in Vietnam.

Given its insular geographic location, Taiwan inherently benefits from a natural advantage in developing its shipping industry, positioning it as a critical sector for the nation’s economic advancement. The shipping industry operates within a highly competitive maritime market, wherein ocean freight forwarders provide services on a global scale, thus classifying them within the international transportation and logistics industry. The global competition from logistics peers renders the services highly substitutable. This study breaks new ground by integrating the SERVQUAL scale with advanced methodologies such as the Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) to assess and enhance service quality in the shipping industry. By segmenting the five dimensions of SERVQUAL, the study delineates 19 specific evaluation indicators. The expert questionnaires developed and analyzed through AHP and DEMATEL reveal a previously unidentified link between specific service quality dimensions and customer satisfaction. The findings from this analysis offer crucial insights into the critical success factors (CSFs) of service quality and their causal interrelationships, thereby establishing a model for service standards. By leveraging the identified CSFs and understanding the causal relationships among these key factors, ocean freight forwarders can enhance and optimize their value propositions and resources. This proactive approach is expected to significantly improve service quality, fortify core competitiveness, and elevate customer support and satisfaction levels, ultimately leading to an increased market share and ensuring sustainable business operations.

To achieve the electrification of private vehicles, it is urgent to develop public charging infrastructure. However, choosing the most beneficial type of public charging infrastructure for the development of a country or region remains challenging. The municipal decision’s implementation requires considering various perspectives. An important aspect of energy development involves effectively integrating and evaluating public charging infrastructure. While car charging facilities have been thoroughly studied, motorcycle charging facilities have been neglected despite motorcycles being a vital mode of transportation in many countries. The study created a hybrid decision-making model to evaluate electric motorcycle charging infrastructure. Firstly, a framework for evaluating electric motorcycle charging infrastructure was effectively constructed through a literature survey and expert experience. Secondly, decision-makers’ opinions were gathered and integrated using Bayesian BWM to reach a group consensus. Thirdly, the performance of the alternative solutions was evaluated by exploring the gaps between them and the aspiration level through modified VIKOR. An empirical analysis was conducted using examples of regions/countries with very high rates of motorcycle ownership worldwide. Finally, comparative and sensitivity analyses were conducted to demonstrate the practicality of the proposed model. The study’s findings will aid in addressing municipal issues and achieving low-carbon development objectives in the area.

Artificial Intelligence (AI) has become a pivotal force in transforming the retail industry, particularly in the online shopping environment. This study investigates the impact of various AI applications—such as personalized recommendations, chatbots, predictive analytics, and social media engagement—on consumer buying behaviors. Employing a quantitative research design, data was collected from 760 respondents through a structured online survey. The snowball sampling technique facilitated the recruitment of participants, focusing on diverse demographics and their interactions with AI technologies in online retail. The findings reveal that AI-driven personalization significantly enhances consumer purchase intentions and satisfaction. Multiple regression analysis shows that AI personalization (β = 0.35, p < 0.001) has the most substantial impact on purchase intention, followed by chatbot effectiveness (β = 0.25, p < 0.001), predictive analytics (β = 0.20, p < 0.001), and social media engagement (β = 0.15, p < 0.01). Similarly, AI personalization (β = 0.30, p < 0.001), predictive analytics (β = 0.25, p < 0.001), and chatbot effectiveness (β = 0.20, p < 0.001) significantly influence consumer satisfaction. The hierarchical regression analysis underscores the importance of ethical considerations, showing that ethical and transparent use of AI increases consumer trust and engagement. Model 1 explains 45% of the variance in consumer behavior (R² = 0.45, F = 154.75, p < 0.001), while Model 2, incorporating ethical concerns, explains an additional 10% (R² = 0.55, F = 98.25, p < 0.001). This study highlights the necessity for retailers to leverage AI technologies ethically and effectively to gain a competitive edge, improve customer satisfaction, and drive long-term success. Future research should explore the long-term impacts of AI on consumer behavior and the integration of emerging technologies such as augmented reality and the Internet of Things (IoT) in retail.

Students from different cultures possess varying levels of skills in learning, remembering, and understanding concepts. Some terms and their explanations may seem easy for one group of students but difficult for another. Therefore, delivering educational content that aligns with student’s learning capabilities is a challenging task based on cultural orientations. This study addresses the learning challenges by developing a Thesaurus Glossary E-learning (TGE) framework method. This study introduces the TGE method which is a multi-language tool with visual associations that adapts to students’ capabilities. It also examines cultural differences and native languages, particularly aiding Arab Native to visualize appropriate terms (thesaurus) and their explanations (glossary) based on students’ learning capabilities. TGE learns from students’ term selection behavior and displays terms at a simple or advanced level that matches their learning ability. Additionally, TGE demonstrated its effectiveness as an e-learning tool, accessible to all students anytime and anywhere. The study analyzed 314 records related to student performance, out of which 114 students were surveyed to evaluate the effectiveness of the TGE method. This work presents TGE as a novel e-learning tool designed to enhance conceptual thinking within the context of modern educational practices during the digital transformation. TGE is based on artificial intelligence algorithms and associative rules that simulate the human brain, establishing logical connections between related key terms and sketching associations among diverse facets of a situation. An experiment was conducted at a private university in the Sultanate of Oman to assess the effectiveness of the proposed TGE tool. TGE was integrated with selected subjects in information systems and used by the students as a resource for e-learning methods and materials. The results show that 85% of students who used TGE improved their performance by 19%. We believe this work could establish a new smart e-learning teaching method and attract modern and digital universities to enhance student learning outcomes linked with conceptual thinking.