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Public libraries are strong advocates of the development of accessibility for people with disabilities. Understanding the accessibility services needs of visually impaired patrons is highly beneficial for increasing satisfaction with public library services. The purpose of this research is to assess the service capabilities of visually impaired patrons in public libraries and to improve the accessibility of services provided by public libraries for visually impaired patrons.

This research adopts a mixed methods approach. Qualitative data collection involves interviews and surveys with 34 visually impaired individuals in China, applying grounded theory and expectancy theory. Quantitative analysis is then carried out using the Kano model.

The research reveals four types of accessibility service needs, with visually impaired patrons prioritizing value-added information services and self-service options. In addition, visually impaired patrons are also highly interested in the integration of assistive and innovative technologies within libraries.

By emphasizing a patron-centered approach, this research provides insights into innovative service approaches in public libraries that address the specific needs of visually impaired patrons and contribute essential strategies for bridging the digital divide.

The use of social media for sustainable information is important since it has the potential to influence people’s intentions and behaviour towards sustainability. As previous studies on social media and sustainable development have primarily focussed on Western viewpoints, this study presents a comprehensive Asian perspective by investigating the impact of social media on sustainable intention and behaviour amongst Malaysian and Indonesian undergraduate university students.

A campus-wide online survey was conducted with 953 students from Malaysia and Indonesia. The researchers collected data through an online questionnaire and a two-week quantitative survey of undergraduate students in Malaysia and Indonesia. Quantitative data were analysed by SmartPLS software and comparative studies were conducted.

The result of the survey indicated that Facebook and Instagram were mainly used by Malaysian students to obtain and communicate about sustainability information, whilst Instagram was mainly used by Indonesian students. The findings also discovered that social media usage and social media effectiveness and usefulness are statistically significant predictors of sustainable intention amongst the students in Malaysia and Indonesia. Sustainable intention is also a statistically significant predictor of sustainable behaviour amongst the students. Additionally, this study also found that Malaysian students appeared to have a high level of the effect of sustainable intention on sustainable behaviour and the effect of the effectiveness and usefulness of social media to sustainable intention compared to Indonesian students. On the contrary, their use of social media related to sustainable behaviour was relatively low compared to Indonesian students.

Overall, the findings can contribute to the presently scant empirical works that focus on social media’s influence on sustainability and sustainable development. Furthermore, the findings contribute to the growing body of knowledge related to sustainability communication and sustainable education, particularly in terms of the use of social media in the learning and teaching process. Future research could focus on studying postgraduate students and university students from other Asian countries. Moreover, using qualitative methods like in-depth interviews or focus group discussion and applying other theories might unveil further results.

Artificial intelligence (AI) has been touted as one of the viable solutions to address urban mobility issues. Despite a growing body of research on AI across various sectors, its use in the mobility sector remains underexplored. This study addresses this limitation by investigating AI applications and identifying the AI material properties and use cases that offer mobility-specific affordances.

Although AI applications in mobility are growing, academic research on the subject has yet to catch up. Therefore, we follow a systematic review and analysis of practitioner literature. We conducted a comprehensive search for relevant documents through Advanced Google and OECD databases and identified 173 sources. We selected 40 sources published between 2015 and 2022 and analysed the corpus of evidence through abductive qualitative analysis technique.

The analysis reveals that mobility organisations are implementing various AI technologies and systems such as cameras, sensors, IoT, computer vision, natural language processing, robotic process automation, machine learning, deep learning and neural networks. These technologies offer material properties for sensing mobility objects and events, comprehending mobility data, automating mobility activities and learning from mobility data. By exploiting these material properties, mobility organisations are integrating urban mobility management, personalising and automating urban mobility, enabling the smartification of infrastructure and asset management, developing better urban transport planning and management, and enabling automatic driving.

The study contributes a mid-range theory of the affordances of AI for mobility (AI4M) at the infrastructure, operation and service levels. This contribution extends the existing understanding of AI and offers an interconnected perspective of AI affordances for further research. For practitioners, the study provides insights on how to explore AI in alignment with organisational goals to collectively transform urban mobility to be affordable, efficient and sustainable.