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Although user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.

The authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.

The authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.

This study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.

This article aims to reveal the factors influencing the sustainable development of mobile e-commerce from both user and operational perspectives. It fills the gap in qualitative research on the sustainable development of artificial intelligence (AI) technology in mobile e-commerce based on the grounded theory. This study provides valuable insights and inspiration for sustainable development in this field and lays the theoretical foundation and research reference for future studies.

Based on the grounded theory (GT), interview method was used to conduct the study.

The impact of AI applications on mobile e-commerce is mainly reflected in three stages of the customer shopping process. They are pre-shopping, mid-shopping and after-shopping AI services and each of the three stages has its own separate dimensions that need attention. The study and its persistence aspects are discussed.

The results of this study can provide forward-looking suggestions and paths for the construction and optimization of future e-commerce platforms, contribute to the sustainable development of e-commerce and contribute to the sustainable and healthy growth of the social economy.

This study proposes sustainable development measures for the application of AI in mobile e-commerce, from operation to supervision, which is an important reference for promoting coordinated and rapid socio-economic development.

This research aims to examine some nudges for creating psychological ownership in order to reduce misbehaviors, consequently encouraging subsequent users to demonstrate stewardship behaviors.

This research examined the sentiment of tweets (Study 1) to explore user experience and conducted two experiments (Studies 2 and 3) to test the hypotheses.

The misbehavior of the previous user in relation to the subsequent user's stewardship behavior was moderated by nudges based on self-investment and local identity. Perceived responsibility mediated the relationship between misbehavior and stewardship behavior as a result of nudges.

The findings of this study provide a framework for the transition from misbehavior to stewardship behavior in PMVs.

The main objective of this study is to investigate the factors that influence the adoption intention of cloud computing services among individual users using the extended theory of planned behavior.

A purposive sampling technique was used to collect a total of 339 data points, which were analyzed using SmartPLS to derive variance-based structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA).

The results obtained from PLS-SEM indicate that attitude towards cloud computing, subjective norms, perceived behavioral control, perceived security, cost-effectiveness, and performance expectancy all have a positive and significant impact on the adoption intention of cloud computing services among individual users. On the other hand, the findings from fsQCA provide a clear interpretation and deeper insights into the adoption intention of individual users of cloud computing services by revealing the complex relationships between multiple combinations of antecedents. This helps to understand the reasons for individual users' adoption intention in emerging countries.

This study offers valuable insights to cloud service providers and cyber entrepreneurs on how to promote cloud computing services to individual users in developing countries. It helps these organizations understand their priorities for encouraging cloud computing adoption among individual users from emerging countries. Additionally, policymakers can also understand their role in creating a comfortable and flexible cloud computing access environment for individual users.

This study has contributed to the increasingly growing empirical literature on cloud computing adoption and demonstrates the effectiveness of the proposed theoretical framework in identifying the potential reasons for the slow growth of cloud computing services adoption in the developing world.

This study aims to argue that user’s continued use behavior is contingent upon two perceptions (i.e. the app and the provider). This study examines the moderating effects of user’s perceptions of apps and providers on the effects of security and privacy concerns and investigate whether assurance mechanisms decrease such concerns.

This study conducts a scenario-based survey with 694 mobile cloud computing (MCC) app users to understand their perceptions and behaviors.

This study finds that while perceived value of data transfer to the cloud moderates the effects of security and privacy concerns on continued use behavior, trust only moderates the effect of privacy concerns. This study also finds that perceived effectiveness of security and privacy intervention impacts privacy concerns but does not decrease security concerns.

Prior mobile app studies mainly focused on mobile apps and did not investigate the perceptions of app providers along with app features in the same study. Furthermore, International Organization for Standardization 27018 certification and privacy policy notification are the interventions that exhibit data assurance mechanisms. However, it is unknown whether these interventions are able to decrease users’ security and privacy concerns after using MCC apps.

The purpose of this paper is to understand how users behave and evaluate how systems with users are essential for interactive information retrieval (IIR) research. User study methodology serves as a primary approach to answering IIR research questions. In addition to designing user study procedures, understanding the limitations of varying study designs and discussing solutions to the limitations is also critical for improving the methods and advancing the knowledge in IIR.

Given this unresolved gap, we apply the faceted framework developed by Liu and Shah (2019) in systematically reviewing 131 IIR user studies recently published (2016–2021) on multiple IR and information science venues.

Our study achieve three goals: (1) extracting and synthesizing the reported limitations on multiple aspects of user study (e.g. recruitment, tasks, study procedures, system interfaces, data analysis methods) under associated facets; (2) summarizing the reported solutions to the limitations; (3) clarifying the connections between types of limitations and types of solutions.

The bibliography of user studies can be used by students and junior researchers who are new to user-centered IR studies as references for study design. Our results can facilitate the reflection and improvement on IR research methodology and serve as a checklist for evaluating customized IIR user studies in varying problem spaces.

To our knowledge, this work is the first study that systematically reviews the study limitations and solutions reported by IIR researchers in articles and empirically examines their connections to different study components.

Since the introduction of the outstanding web AI chat system, ChatGPT, it has caused a significant impact in both academia and the business world. Many studies have started to explore its potential applications in various fields. However, there is a lack of research from the perspective of user experience. To fill this theoretical gap and provide a theoretical basis for the operation and design of related services, this study plans to develop a set of evaluation scales for AI chat system user experience and explore the relationship between various factors and user satisfaction.

This study obtained 41 evaluation indicators through literature review and user research. Subsequently, these indicators were used as questionnaire items, combined with satisfaction metrics. A total of 515 questionnaires were distributed, and factor analysis and linear regression were employed to determine the specific elements influencing user experience and the user satisfaction model.

This study found that the factors influencing user experience are usefulness, accuracy, logical inference, interactivity, growth, anthropomorphism, convenience, credibility, ease of use, creativity, and security. Among these factors, only accuracy, anthropomorphism, creativity, and security indirectly influence satisfaction through usefulness, while the rest of the factors have a direct positive impact on user satisfaction.

This study provides constructive suggestions for the design and operation of related services and serves as a reference for future theoretical research in this area.

This study aims to identify user perception of different qualities of optical character recognition (OCR) in texts. The purpose of this paper is to study the effect of different quality OCR on users' subjective perception through an interactive information retrieval task with a collection of one digitized historical Finnish newspaper.

This study is based on the simulated work task model used in interactive information retrieval. Thirty-two users made searches to an article collection of Finnish newspaper Uusi Suometar 1869–1918 which consists of ca. 1.45 million autosegmented articles. The article search database had two versions of each article with different quality OCR. Each user performed six pre-formulated and six self-formulated short queries and evaluated subjectively the top 10 results using a graded relevance scale of 0–3. Users were not informed about the OCR quality differences of the otherwise identical articles.

The main result of the study is that improved OCR quality affects subjective user perception of historical newspaper articles positively: higher relevance scores are given to better-quality texts.

To the best of the authors’ knowledge, this simulated interactive work task experiment is the first one showing empirically that users' subjective relevance assessments are affected by a change in the quality of an optically read text.

This study focuses on perceived overload from environmental stimuli and individual psychology and behavioral interactions. It constructs a theoretical model with overload as the key stressor based on the stressor-strain-outcome (SSO) model. The authors argue that system feature overload (SFO), information overload, and social overload lead to two psychological strains: fear of missing out (FoMO) and fatigue among users of short video platforms, affecting their discontinuous usage intentions.

To test the hypotheses, the authors conducted a questionnaire survey on 412 users' short video platform usage and empirically tested the constructed model using the research tool SmartPLS 3.3.2.

The results of data analysis showed that most of the hypotheses were supported. Specifically, system feature overload, information overload and social overload all positively affected FoMO. However, SFO and information overload significantly affected fatigue. There was no significant relationship between social overload and fatigue. In addition, both FoMO and fatigue negatively influenced users' discontinuous usage intentions.

The current research on user behavior in information systems tends to focus on the influence in the positive direction and less on the negative direction. The research on discontinuous usage intention (DUI) is a very new research topic. This research studies the influencing factors of users' discontinuous behavior from the perspective of perceptual overload. It provides a unique view for future short video platform user behavior research, with significant theoretical contributions and essential practice for short video platform operators to improve services.

The PICCH research project contributes to opening a dialogue between cultural heritage archives and users. Hence, the users are identified and their information needs, the search strategies they apply and the search challenges they experience are uncovered.

A combination of questionnaires and interviews is used for collection of data. Questionnaire data were collected from users of three different audiovisual archives. Semi-structured interviews were conducted with two user groups: (1) scholars searching information for research projects and (2) archivists who perform their own scholarly work and search information on behalf of others.

The questionnaire results show that the archive users mainly have an academic background. Hence, scholars and archivists constitute the target group for in-depth interviews. The interviews reveal that their information needs are multi-faceted and match the information need typology by Ingwersen. The scholars mainly apply collection-specific search strategies but have in common primarily doing keyword searching, which they typically plan in advance. The archivists do less planning owing to their knowledge of the collections. All interviewees demonstrate domain knowledge, archival intelligence and artefactual literacy in their use and mastering of the archives. The search challenges they experience can be characterised as search system complexity challenges, material challenges and metadata challenges.

The paper provides a rare insight into the complexity of the search situation of cultural heritage archives, and the users’ multi-facetted information needs and hence contributes to the dialogue between the archives and the users.