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User diversity has been discussed in many fields of study for decades. Nevertheless, some cohorts are rarely included in mainstream research. According to the concept of universal design of research (UDR), people with disabilities should be more often included in participant pools. There is, however, a need for certain methodological considerations to achieve UDR.

The suggested guidelines are based upon existing guidelines and research in addition to key takeaways from studies conducted by the authors over the past 15 years. Six studies are used to show how the guidelines can be applied in research involving three example cohorts, namely people with dyslexia, aphasia and intellectual disability.

Extensive guidelines are needed to increase user inclusion in mainstream studies and support researchers in conducting purposeful and ethical research. The suggested guidelines should be examined for other cohorts to ensure that all types of user needs are accommodated.

This study contributes with methodological approaches to enhance inclusion of all types of participants in mainstream research.

The main contribution is The seven principles of UDR, a further development of the original principles for UDR.

Despite the promising development and marketing potential of the metaverse, our understanding of how realistic metaverse environments impact user engagement and behaviours remains limited. This study investigates the role of perceived realism in influencing user engagement, thereby affecting external search behaviour and visit intentions.

We surveyed 270 active metaverse users to test the research model. The data were analysed using partial least squares structural equation modelling (PLS-SEM).

The results of our study show that three dimensions of realism – avatar involvement, perceptual pervasiveness and social realism – significantly enhance user engagement, which in turn influences external search behaviour and visit intention. In contrast, simulation realism and freedom of choice have minimal effects on absorption and dedication.

This study highlights the role of perceived realism in enhancing user engagement with the metaverse and its impact on physical world behaviours. It contributes to metaverse literature by demonstrating that engagement within the metaverse significantly influences physical world behaviours, including visit intentions and external search behaviours.

This study offers practical guidance for developers to enhance user engagement in metaverse environments. Specifically, our findings advocate for visual and audio quality enhancements, greater persuasiveness of virtual spaces, improved avatar representativeness and a closer alignment of metaverse activities with real-life events.

This study advances the theoretical understanding of perceived realism by examining how its dimensions – such as visual and audio quality, avatar representativeness and alignment with real-life events – impact user engagement in the metaverse. It also explores how this engagement influences offline behaviours, thus bridging the gap between virtual and real-world interactions.

The television (TV) content ecosystem has shifted from traditional broadcasting systems to dedicated content producers and over-the-top (OTT) services. However, less empirical effort has been paid to the actual behaviors of the mobile users who watch TV content when explaining the impact of OTT service and mobile network profiles in watching TV content. This study aims to investigate the impact of gratifications and attitude formed by mobile TV users on actual mobile TV watching behaviors, as well as the moderating impacts of paid OTT service subscriptions and mobile network profiles, based on gratification theory, cognition–affect–behavioral (CAB) framework, sunk cost effect and walled-garden effect.

This study employs the generalized linear model (GLM) with generalized estimating equations (GEE) to test hypothesized relationships. A total of 338 mobile phone users who have been watching TV content using a mobile phone participated in the survey. The moderating variables, 4 types of paid streaming platform subscriptions, were classified based on the walled gardens formed by mobile telecom services.

The study’s results revealed that obtained gratifications and opportunity constructs substantially influenced a mobile phone user’s attitude and behaviors. Additionally, mobile network profiles and the degree of access to paid platform services played significant moderating roles in the relationship between users’ attitudes and behavior.

This research enriches the existing OTT service literature and is one of the pioneering studies investigating the walled-garden effect’s role in mobile phone users’ actual watching behaviors, offering valuable practical implications for the OTT platform providers.

The manuscript aims to introduce the managerial practice of content recycling – that is, a firm's recycling of its posts on social media platforms. I define and distinguish the phenomenon from related ones and offer propositions for future research to test empirically.

Review of the practitioner literature, in-situ observations with content managers, and a survey of content managers and Facebook users.

Managers recycle their posts to recoup the costs of content. Under some conditions, recycled content may yield more benefits than costs.

I define the phenomenon of content recycling and differentiate it from related terms. I offer propositions for future research.

I inform managers of the benefits and costs of recycling content and conditions under which benefits may override costs.

The research is novel and helps develop a common managerial practice.

Using surveys of Amazon and Tmall Global users, this paper aims to empirically investigate the issue of platform technological selection. We explore the impact of switching costs on users’ intentions to use an app-enabled cross-border e-commerce (CBEC) platform based on an extended technology acceptance model (TAM). The results suggest that the higher the switching cost of a platform is, the greater the users’ satisfaction and intention to use this platform. Therefore, for the platform, a moderate switching cost will be beneficial for retaining users.

Based on the TAM, this paper takes the switching costs as the starting point and focuses on exploring the relationships among switching costs, perceived usefulness, perceived ease of use, perceived reliability, satisfaction and intention to use. Online surveys of users of Amazon and Tmall Global are adopted as the main instruments of this research. We collected a total of 408 valid responses from Amazon users and 490 from Tmall Global users. For the data analysis, this study conducts frequency analysis, a test analysis of the reliability and validity of the measures, correlation analysis, and path analysis using a structural equation model.

The results show that switching costs positively affect the users’ satisfaction and intentions to use a CBEC platform through perceived usefulness, perceived ease of use and perceived reliability.

The questionnaire respondents were predominantly Chinese due to the constraints of the survey conditions. In fact, China has a high penetration rate in CBEC, and Chinese users have rich experience using the Amazon and Tmall Global platforms.

The development of CBEC has ups and downs, and users frequently switch platforms. Considering how platforms can stand out from the crowd and retain users, we believe that a moderate increase in the switching cost of the platform is helpful for companies to address these problems, and the implications of the results are particularly valid for decision-makers of CBEC platforms and companies.

Amazon and Tmall Global are the two largest CBEC platforms in the world. Using these two companies as examples for comparison can effectively identify the differences between the platforms and the conclusions are representative. We suggest that platforms can improve user satisfaction and willingness to use by establishing VIP communities, issuing coupons, providing shipping services as well as convenient after-sale complaint channels, and improving the platform’s easy-to-use interface, as ways to further enable the platform to retain more users and stand out in fierce competition.

This paper addresses an interesting and practical issue related to the effects of introducing switching costs in an extended TAM applied to CBEC platforms.

This paper aims to investigate the extent of personal privacy concerns expressed by university students in Vietnam while using TikTok, the influence of peer interactions and social norms on privacy attitudes and behaviors and the strategies used by university students in Vietnam to mitigate privacy risks on TikTok.

A qualitative approach using semi-structured interviews was used to gather data on the following: the degree to which Vietnamese university students express concerns about their personal privacy while using TikTok; how peer interactions and social norms influence privacy attitudes and behaviors; and the strategies these students use to mitigate privacy risks on the platform.

Findings indicate that although university students exhibit a relatively low level of concern regarding their personal privacy on TikTok, peer influences and societal norms significantly shape their attitudes and behaviors on the platform. Moreover, students use several strategies to mitigate privacy risks, such as selective content sharing and refraining from engaging with unknown links.

These insights provide valuable implications for the development of targeted interventions and educational initiatives aimed at fostering a more privacy-conscious TikTok user community among university students in Vietnam.

This research fills a critical gap in the existing literature by focusing on the influence of social norms and peer influences on privacy attitudes and behaviors on social media platforms. While prior studies have explored various factors impacting privacy concerns on social media, the role of social dynamics has been understudied. Moreover, the research specifically addresses the lack of investigation into privacy concerns on TikTok, a platform rapidly gaining popularity among younger demographics.

As museums and other memory institutions continue to invest considerably in mass-digitising collections and participating in large search portals, it is essential to understand existing and potential users, their motivations and search needs to inform collections’ documentation. In this article, we discuss insights from a collaborative project with National Museums Scotland, set up to enhance the findability of collection images and inform documentation practices by understanding the collections users and their search terms.

The research involved interviews with National Museums Scotland staff, users and non-users of the Museums’ Search our Collections portal encompassing a concept mapping and card sort activity; online surveys and content analysis of user search queries.

The project revealed that participants are interested in searching the online collections by terms often not represented in collections metadata, including terms related to identity (their own but also others’) and social context (e.g. through seasonal and social events); emotional and sensory interests (e.g. visual characteristics) and narrative themes (e.g. on under-represented histories).

Based on the findings, we further theorise the semantic gap in online museum collection metadata. To bridge this gap and cater to how users search, we argue for a paradigm shift in documentation practices: suggesting practitioners should not only view collection images as information but also tap into their rich potential for enabling social and affective connections.

This study aims to examine the factors influencing trust toward mobile health applications (mhealth apps) among young consumers. By building on the socio-technical systems framework and self-congruence theory, the authors develop and examine a conceptual model of the trusting intentions of young consumers toward mhealth apps.

The data for the study was collected from a sample of 285 young consumers via an online survey by using a purposive sampling method. All the respondents were existing users of health apps and resided in the urban areas of the country. The sample comprised 53% male respondents and 47% female respondents. Subsequently, the data was analyzed using the structural equation modeling technique.

The findings revealed that psychological factors like self-congruence and technical factors such as flow experience and perceived playfulness aid in building trust among young mhealth app users, which in turn influences the purchase intention and user loyalty toward the application. Social factors like perceived critical mass and social influence did not significantly impact trust.

The data was collected from Generation Z, recognized as the most influential consumer demographic worldwide, primarily involved in mhealth app usage. Nonetheless, it is essential to understand that these findings might only partially apply to a specific user group. In addition, the study did not focus on any specific mhealth applications. Hence, it is prudent to exercise caution when generalizing these results to the broader population.

This study advances the comprehension of socio-technical elements in establishing trust, subsequently impacting purchase intentions and loyalty among young users in the context of mhealth apps. In addition, it expands the socio-technical framework by incorporating a psychological factor that could influence trust and purchase intentions toward mhealth apps. Furthermore, the post hoc findings reinforce this comprehension by identifying the moderating effects of operating system type and gender. These insights could provide valuable guidance for developing tailored marketing strategies targeting the young consumer base.

To address the shortcomings of existing academic user information needs identification methods, such as low efficiency and high subjectivity, this study aims to propose an automated method of identifying online academic user information needs.

This study’s method consists of two main parts: the first is the automatic classification of academic user information needs based on the bidirectional encoder representations from transformers (BERT) model. The second is the key content extraction of academic user information needs based on the improved MDERank key phrase extraction (KPE) algorithm. Finally, the applicability and effectiveness of the method are verified by an example of identifying the information needs of academic users in the field of materials science.

Experimental results show that the BERT-based information needs classification model achieved the highest weighted average F1 score of 91.61%. The improved MDERank KPE algorithm achieves the highest F1 score of 61%. The empirical analysis results reveal that the information needs of the categories “methods,” “experimental phenomena” and “experimental materials” are relatively high in the materials science field.

This study provides a solution for automated identification of academic user information needs. It helps online academic resource platforms to better understand their users’ information needs, which in turn facilitates the platform’s academic resource organization and services.

China’s healthcare system is being burdened by the increasing prevalence of chronic diseases. Therefore, this study investigated the health service requirements of mobile health applications (mHealth apps) users in Hangzhou, China. This study aimed to propose suggestions and theoretical references to improve mHealth apps and promote their development, thereby meeting public medical and health needs and creating an efficient medical service system.

We constructed a model of health service demands using a literature review, network survey, and semi-structured interviews. We analyzed the demand attributes using the Kano model and Better-Worse index and obtained the priority ranking of demands.

The results revealed 25 demand elements in four dimensions: must-be (M), one-dimensional (O), attractive (A), and indifferent (I) requirements. The findings suggest that mHealth app developers can optimize health services by categorizing and managing health services, focusing on middle-aged users, enhancing the professionalism of health service providers, and improving the feedback mechanism.

Studies on mHealth apps user demands, particularly on health service needs, remain scarce. This study employed a mixed-methods approach, integrating both qualitative and quantitative research techniques, to establish a priority ranking of user health service needs for mHealth apps. The study offers recommendations and theoretical references to optimize and improve mHealth app services.

1. Construct a better health service requirements model for mHealth app users.

2. Obtain the prioritization of demand elements in the model.

3. Propose some management suggestions to improve mHealth apps.

Construct a better health service requirements model for mHealth app users.

Obtain the prioritization of demand elements in the model.

Propose some management suggestions to improve mHealth apps.