Search results

Artificial intelligence (AI) has gained significant momentum in recent years. Among AI-infused systems, one prominent application is context-aware systems. Although the fusion of AI and context awareness has given birth to personalized and timely AI-powered context-aware systems, several challenges still remain. Given the “black box” nature of AI, the authors propose that human–AI collaboration is essential for AI-powered context-aware services to eliminate uncertainty and evolve. To this end, this study aims to advance a research agenda for facilitators and outcomes of human–AI collaboration in AI-powered context-aware services.

Synthesizing the extant literature on AI and context awareness, the authors advance a theoretical framework that not only differentiates among the three phases of AI-powered context-aware services (i.e. context acquisition, context interpretation and context application) but also outlines plausible research directions for each stage.

The authors delve into the role of human–AI collaboration and derive future research questions from two directions, namely, the effects of AI-powered context-aware services design on human–AI collaboration and the impact of human–AI collaboration.

This study contributes to the extant literature by identifying knowledge gaps in human–AI collaboration for AI-powered context-aware services and putting forth research directions accordingly. In turn, their proposed framework yields actionable guidance for AI-powered context-aware service designers and practitioners.

The purpose of this paper is to examine how different types of user experience in TikTok impact purchase intention via commitment to the influencer and commitment to the platform, with customer type included to determine moderating effects. Three types of user experience are considered: information experience, entertainment experience and parasocial-relationship-based experience.

This study collected 458 valid questionnaires from TikTok users, employing the structural equation modeling approach to examine the proposed research model.

Information experience, entertainment experience and parasocial-relationship-based experience are found to critically stimulate user commitment to the influencer and commitment to the platform, in turn driving TikTok-based purchase intention. Tests incorporating customer type reveal that commitment to the influencer more strongly influences the purchase intention of repeat customers, with commitment to the platform more likely to stimulate purchase intention among potential customers.

On a theoretical level, the paper is among the first to examine TikTok-based user purchase intention with customer type as a moderator. On a practical level, the results can guide marketers to effectively promote products using TikTok and inspire TikTok managers to develop customized strategies to stimulate initial and repeat sales.

TikTok is moving to the stage of commercialization and monetization by introducing e-commerce features. Although this move should cultivate particularly fertile ground for companies to sell products, TikTok user purchase behavior has yet to receive sufficient research attention, with little currently known about their purchase motivations. The current study uncovers the significant antecedents of users' purchase intention through TikTok, and further reveals the motivational differences among potential and repeat customers.

This study aims at unpacking the multiplicity of the sitting activity in public spaces through the lens of actor-network theory. In line with previous urban research focussing on outdoor activities, such empirical investigation aims to show the importance of the physical aspects of spaces, including seating, in supporting sitting activities as a way of encouraging the use of public space.

This study adopts the overlap between actor–network theory and affordances. It utilises ethnographic research involving frequent users in Dahiyat Al Hussein Park in Amman-Jordan. Data were gathered on the different seat–user relations and the translated sitting activity networks.

Analysis demonstrates different cases of alignment, misalignment and realignment between what is intended and experienced, and where these relations are maintained, disrupted or changed. These findings reveal the multiplicity of sitting activities; this is significant for understanding how they are maintained.

The research suggests a new way of conceptualising the relationship between the physical environment and users and an approach for examining sitting activities. Some studies have applied actor–network theory and/or the concept of “affordance” by highlighting relations between the object and its user and how they create sitting activities. However, only few studies have problematised the multiplicity of sitting when considering seating uses.

Jarring events, be they global crises such as COVID-19 or technological events such as the Cambridge Analytica data incident, have bullwhip effects on billions of people's daily lives. Such “shocks” vary in their characteristics. While some shocks cause, for example, widespread adoption of information systems (IS) as diverse as Netflix and Teams, others lead users to stop using IS, such as Facebook. To offer insights into the multifaceted ways shocks influence user behavior, this study aims to assess the status quo of shock-related literature in the IS discipline and develop a taxonomy that paves the path for future IS research on shocks.

This study conducted a literature review (N = 70) to assess the status quo of shock-related research in the IS discipline. Through a qualitative study based on users who experienced shocks (N = 39), it confirmed the findings of previous literature in an illustrative IS research context. Integrating the findings of the literature review and qualitative study, this study informs a taxonomy of shocks impacting IS use.

This study identifies different ways that shocks influence user behavior. The taxonomy reveals that IS research could profit from considering environmental, private and work shocks and shedding light on positive shocks. IS research could also benefit from examining the urgency of shocks, as there are indications that this influences how and when individuals react to a specific shock.

Findings complement previous rational explanations for user behavior by showing technology use can be influenced by shocks. This study offers a foundation for forward-looking research that connects jarring events to patterns of technology use.

Smartphone apps collect users' personal information, which triggers privacy concerns for app users. Consequently, app users restrict apps from accessing their personal information. This may impact the effectiveness of in-app advertising. However, research has not yet demonstrated what factors impact app users' decisions to use apps with restricted permissions. This study is aimed to bridge this gap.

Using a quantitative research method, the authors collected the data from 384 app users via a structured questionnaire. The data were analysed using AMOS and fuzzy-set qualitative comparative analysis (fsQCA).

The findings suggest privacy concerns and risks have a significant positive effect on app usage with restricted permissions, whilst reputation, trust and perceived benefits have significant negative impact on it. Some app-related factors, such as the number of apps installed and type of apps, also impact app usage with restricted permissions.

Based on the findings, the authors provided several implications for app stores, app developers and app marketers.

This study examines the factors that influence smartphone users' decisions to use apps with restricted permission requests. By doing this, the authors' study contributes to the consumer behaviour literature in the context of smartphone app usage. Also, by explaining the underlying mechanisms through which the principles of communication privacy management theory operate in smartphone app context, the authors' research contributes to the communication privacy management theory.

It is becoming easier for end-users to modify their information system, sometimes against the wishes of management or the original manufacturer. In the mobile device context, “modding”, “jailbreaking” or “rooting” allows a mobile phone user to select operating software and network providers other than those mandated by the original provider. Prior studies have theorised that modders and non-modders possess different perspectives on the relationship between them and their device provider. However, these differences have not been empirically demonstrated in prior work. This paper aims to test theoretical pathways to explain the behavioural relationship effects of security within the modding context.

This study models four relationship conceptualisations from prior research. The study tests this model using a survey of 464 mobile device users to compare the user attitudes of modders and non-modders.

Modder and non-modder relationships differ. Both groups value security, but in different ways: modder relationships are governed by satisfaction and commitment, while non-modder relationships are governed more by trust.

To the best of the authors’ knowledge, this is the first study to empirically demonstrate the relationship differences between IS modifiers and non-modifiers. Most published work has focused on IS that are unmodified. Incorporating device modification may improve behavioural understanding of end-users.

Researchers in information studies have examined fictional depictions of libraries in various mediums because these images can reflect and influence real-life experiences and attitudes. Video games, despite being relatively overlooked, are increasingly culturally relevant and can indicate library users' real needs and desires. This study investigates the ways in which video games depict characters using libraries to seek and use information.

A qualitative content analysis approach incorporating methods from information studies and game studies was applied. Tancheva's (2005) semiotic analysis of fictional libraries and Carr's (2019) textual approach provided the framing for the unique aspects of video games and their meanings. Carroll (2021)'s character analysis and Chatman (1996)'s theory on insiders–outsiders dynamic underpinned the data collection and analysis. The purposive sample included 15 video games released since 2010.

Video games depict game characters visiting libraries to solve short-term problems, to gain knowledge to improve themselves or to bond with others. Protagonists are often depicted as adventurers or outsiders who must adapt to unfamiliar places and situations to achieve their wider objectives. In these games, libraries provide useful documents, spaces or helpful guides and intellectuals who assist the protagonists. As outsiders, the protagonists seek information in libraries to help them learn about their environments and to immerse themselves in the local histories and cultures in their worlds. Overall, these depictions highlight both short- and long-term benefits of library use.

As with existing studies, the ways in which fictional library use appear in video games can suggest real needs and desires among library users. The findings from this study emphasise the importance of library services and spaces that help users both address short-term problems and immerse themselves in local concerns, with longer-term goals. Applying different research methods or lenses to analysing video games could deepen our understanding of what library users think and feel when they seek and use information in libraries.

With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed.

In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked.

Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR.

In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.