The aim of this research is to examine the mediating effects of self-congruity between destination brand personality, to revisit intention and heed the moderating effects of gender between self-congruity. Therefore, data were collected through a survey from 226 Chinese outbound tourists in Glasgow city, United Kingdom and was analyzed to provide evidence. Based on the results, the analysis of partial least squares structural equation modeling (PLS-SEM) using the Smart PLS 3.0 program indicated that self-congruity was mediated partially through destination brand personality and revisit intention. In tourism destination, Aaker five dimension of brand personality model was particularly adapted into practice. However, the model failed to perform an actual self-congruity to mediate all five dimensions (i.e., sincerity, excitement, competence, excitement, sophistication and ruggedness) of destination brand personality and revisit intention. The results revealed that the ideal self-congruity is a mediating effect between destination brand personality (i.e., sincerity and excitement) and revisit intention. Moreover, this study also reported that the moderating role of gender has no effects on self-congruity and revisit intention. No difference was observed between female and male Chinese tourists who rely more on destination brand personality over self-congruity when the impact of symbolic destination brand benefits on their intention to revisit Glasgow was considered. Findings further offer specific implications for both theoretical insight and marketing practice in context of tourism destinations in Glasgow.

Computer vision–based weed detection plays a critical role in agricultural robotics, enabling accurate, selective weeding. These systems operate on resource-constrained embedded platforms, which introduces a significant trade-off between accuracy and efficiency. This study presents a comparative evaluation of six detection models (YOLOv11n, YOLOv11s, SSD-Lite, NanoDet, Faster R-CNN, RT-DETR) for agro-robotic applications, measuring precision, recall, mAP@0.5, and runtime on low-power hard-ware. NanoDet achieved the highest detection accuracy (precision 98.6%, recall 94.2%, mAP@0.5 97.7%). YOLOv11s demonstrated similar performance (mAP@0.5: 96.1%) but required more computation. YOLOv11n provides the most favourable balance between accuracy and throughput (mAP@0.5: 94.6%, 207 FPS on a workstation). On Raspberry Pi 5, light models achieved 3–5 FPS. RT-DETR and Faster R-CNN exhibited high latency (3112–6500 ms/frame), which prevents real-time operation. NanoDet excelled in detection, while YOLOv11n provides the best balance between accuracy and efficiency for limited devices.

Transportation is associated with all aspects of the nation’s growth. Nowadays, sustainability is one of the primary goals of many urban transportation systems. Over the past, many innovative initiatives have been undertaken to achieve a safe, efficient, and sustainable transport system. Besides, natural environment, social wellbeing, and economic prosperity depend on sound transportation systems. In Malaysia, Penang is well-known as an industrial and medical hub. In recent years, the state has experienced rapid economic growth. However, without proper development planning for the transportation system and infrastructure, the growth for sustainable development will be jeopardised. Heavy congestions due to increasing car dependency lead to psychological stress for the travellers. There are limited studies on sustainable transportations in Penang. Therefore, this study will explore the current transportation system in Penang, including the Penang Transport Master Plan. To address the aim of the research, we adopt an inductive cross-organisational semi-structured interview to explore the current level of sustainability within Penang transportation system. From this case study, the initial findings indicate Penang is in dire need for a robust, sustainable transport system which can include rail transports and integration of different modes of transport. Moreover, the result also shows that the behaviour and attitude of Penangites towards public transportation needs to be changed. This study suggests a series of long term and short term solutions to enhance the performance of the transportation system in Penang. The balance alignment between the economic, social and environmental themes of sustainability will overcome the issues faced by the current transportation system in Penang.

Inclusive higher education in Indonesia still faces significant challenges in providing accessible digital communication for students with low vision. Learning Management Systems (LMS) are not only repositories of course content but also key mediated communication channels where lecturers, institutions, and students exchange information and feedback. When these platforms are inaccessible, the problem becomes communication inequality that restricts students’ rights to receive and express information. This study explores accessibility barriers experienced by low vision students in universities across Bandung Raya, focusing on their interaction with LMS interfaces, messages, and media formats. Using a constructivist paradigm and an intrinsic case study approach, data were collected through semi-structured interviews and analyzed with Miles and Huberman’s interactive model. Findings reveal three main communication-related accessibility issues: inconsistent visual layout and low-contrast interfaces, inadequate keyboard-based navigation, and the absence of screen reader integration and alternative formats such as audio or transcripts. Viewed through inclusive communication and the social model of disability, these barriers act as structural “noise” in mediated interaction. The study argues that LMS accessibility must be treated as a central component of inclusive digital communication, requiring user-informed design, assistive communication technologies, and participatory testing with low vision students as co-designers.