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Many buildings fail to meet user expectations, causing a performance gap. Pre-occupancy evaluation (PrOE) is believed to have the potential to close the gap. It enables designers to obtain end-user feedback in the design phase and improve the design for better performance. However, PrOE implementation faces challenges due to still maturing knowledgebase. This study aims to understand the state-of-the-art knowledge of PrOE, thereby identifying future research needs to advance the domain.

A systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework was conducted. A thorough search in five databases and Google Scholar retrieved 90 articles, with 30 selected for systematic review after eliminating duplicates and irrelevant articles. Bibliometric analyses were performed using VOSviewer and Biblioshiny on the article metadata, and thematic analyses were conducted on their contents.

PrOE is a vehicle for engaging building end-users in the design phase to address the credibility gap caused by the discrepancies between the expected and actual performance of buildings. PrOE has gained limited applications in healthcare, residential, office and educational building design for two broad purposes: design management and marketing. Using virtual reality technologies for PrOE has demonstrated significant benefits. Yet, the PrOE domain needs to mature in multiple perspectives to serve its intended purpose effectively.

This study identifies four knowledge gaps for future research to advance the PrOE domain: (1) developing a holistic PrOE framework, integrating comprehensive performance evaluation criteria, useable at different stages of the design phase and multi-criteria decision algorithms, (2) developing a mixed reality tool, embodying the holistic PrOE framework, (3) formulating a PrOE framework for adaptive reuse of buildings and (4) managing uncertainties in user requirements during the lifecycle in PrOE decisions.

Users often struggle to select choosing among similar online services. To help them make informed decisions, it is important to establish a service reputation measurement mechanism. User-provided feedback ratings serve as a primary source of information for this mechanism, and ensuring the credibility of user feedback is crucial for a reliable reputation measurement. Most of the previous studies use passive detection to identify false feedback without creating incentives for honest reporting. Therefore, this study aims to develop a reputation measure for online services that can provide incentives for users to report honestly.

In this paper, the authors present a method that uses a peer prediction mechanism to evaluate user credibility, which evaluates users’ credibility with their reports by applying the strictly proper scoring rule. Considering the heterogeneity among users, the authors measure user similarity, identify similar users as peers to assess credibility and calculate service reputation using an improved expectation-maximization algorithm based on user credibility.

Theoretical analysis and experimental results verify that the proposed method motivates truthful reporting, effectively identifies malicious users and achieves high service rating accuracy.

The proposed method has significant practical value in evaluating the authenticity of user feedback and promoting honest reporting.

We investigate the joint impacts of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of reviews and attitude toward the product/service reviewed.

We performed three studies to test our research model, presenting participants with scenarios involving product reviews and prior users' helpful and unhelpful votes across experimental settings.

A high helpfulness ratio boosts users’ trust and influences behaviors in both positive and negative reviews. This effect is more pronounced in attribute-based reviews than emotion-based ones. Unlike the ratio effect, helpfulness magnitude significantly impacts only negative attribute-based reviews.

Future research should investigate voting systems in various online contexts, such as Facebook post likes, Twitter microblog thumb-ups and up-votes for article comments on platforms like The New York Times.

Our findings have significant implications for voting system-providers implementing information techniques on third-party review platforms, participatory sites emphasizing user-generated content and online retailers prioritizing product awareness and reputation.

This study addresses an identified need; that is, the helpfulness votes as an additional trust cue and the joint effects of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of customers in reviews and their consequential attitude toward the product/service reviewed.

Fitness games, as a medium that combines playfulness and usefulness for exercise, face challenges in sustaining long-term user engagement. Currently, there is limited research exploring factors influencing users' continued intention to use from the perspective of user experience. Therefore, this study aims to investigate the priority of various user experience attributes of fitness games in promoting users' sustained engagement and to construct a user behavior model, offering theoretical guidance for designers and businesses.

This study distributed 441 survey questionnaires and, based on the fundamental characteristics of external games, established a model for users' continued intention to use external games. It explores the impact of various gaming elements on users' continued intention to use fitness games and the relationships between these elements.

The study indicates that usefulness, functional quality, and ease of use directly influence players' intention to continue playing external games. Social interactions, technical quality, and playfulness do not have an impact on the continued intention to use.

This research breaks away from the bias of previous studies overly focusing on playfulness in games. It fills the research gap regarding the continued intention to use fitness games and provides insights into the design and operation of fitness games.

This study examined how people assess health information from AI and improve their diagnostic ability to identify health misinformation. The proposed model was designed to test a cognitive heuristic theory in misinformation discernment.

We proposed the heuristic-systematic model to assess health misinformation processing in the algorithmic context. Using the Analysis of Moment Structure (AMOS) 26 software, we tested fairness/transparency/accountability (FAccT) as constructs that influence the heuristic evaluation and systematic discernment of misinformation by users. To test moderating and mediating effects, PROCESS Macro Model 4 was used.

The effect of AI-generated misinformation on people’s perceptions of the veracity of health information may differ according to whether they process misinformation heuristically or systematically. Heuristic processing is significantly associated with the diagnosticity of misinformation. There is a greater chance that misinformation will be correctly diagnosed and checked, if misinformation aligns with users’ heuristics or is validated by the diagnosticity they perceive.

When exposed to misinformation through algorithmic recommendations, users’ perceived diagnosticity of misinformation can be predicted accurately from their understanding of normative values. This perceived diagnosticity would then positively influence the accuracy and credibility of the misinformation.

Perceived diagnosticity exerts a key role in fostering misinformation literacy, implying that improving people’s perceptions of misinformation and AI features is an efficient way to change their misinformation behavior.

Although there is broad agreement on the need to control and combat health misinformation, the magnitude of this problem remains unknown. It is essential to understand both users’ cognitive processes when it comes to identifying health misinformation and the diffusion mechanism from which such misinformation is framed and subsequently spread.

The mechanisms through which users process and spread misinformation have remained open-ended questions. This study provides theoretical insights and relevant recommendations that can make users and firms/institutions alike more resilient in protecting themselves from the detrimental impact of misinformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2023-0167

This study intended to identify and categorize the drivers of using online English learning resources (OELR) and to understand OELR's impacts.

The authors conducted an online survey, obtained complete responses from 157 OELR users and used structural equation modeling (SEM) for hypothesis testing.

Most utilitarian and hedonic drivers lead to positive perceptions of OELR, which in turn positively contribute to continuance intention (CI). Two counterintuitive findings were obtained. First, functionality was negatively related to the perception of ease of use. Second, perceived ease of use (PEOU) was not related to CI to use OELR.

This study has implications as follows: (1) complexity of the functions of OELR may deter rather than attract users, (2) ease of use of OELR is not directly positively related to CIs and (3) users may seek practical benefits (utilitarian) and experiential learning processes (hedonic) when using OELR.

The authors' study has theoretical significance by being the first to caution that excessive functionality or complexity in assisting learning tools would likely hinder further use of OELR. The practical significance of this finding is that the finding highlights two factors (perceived usefulness (PU) and perceived enjoyment) that could effectively increase OELR use.

Building on the “needs–affordances–features” framework, the authors explored how users are motivated by their needs to actualize the feature-enabled affordances and engage in the metaverse.

The data were collected through semi-structured and in-depth interviews with 35 participants. The authors applied thematic analysis to summarize the key features and affordances, supplemented by frequency analysis to explore the significance of the features. Sentiment analysis was employed to explicate the relationship between user affordance sentiments and engagement.

The key features of the metaverse portal components—hardware, software and content—afford user behaviors. The features of mechanics and physics engines are important for user engagement in the metaverse. The affordances are related to needs satisfaction and user engagement. Mental immersion was frequently mentioned by the participants, implying that it is significant to afford mental immersion in the metaverse.

The findings of the study provide a rich understanding for practitioners in the metaverse on how to use the features to afford user behaviors and engage them. The authors identified the key elements of user engagement that can be used to guide metaverse game designers.

This study provides a rich and systematic understanding of features, affordances, needs satisfaction and engagement in the metaverse. Going beyond a fragmented view, the findings conclude a research framework that weaves features, affordances, needs and engagement together.

The purpose of this study is to explore the interplay between electronic service quality, user experience (UX) and overall customer satisfaction. Additionally, it aims to assess the suitability of E-S-QUAL and UX metrics within the cultural context of Greece.

Data were collected from 310 Internet users based on their last online purchase from an e-retail website. To evaluate the conceptual model, the authors used partial least squares structural equation modeling (PLS-SEM).

The findings of this study validate the scales' reliability and validity in the realm of electronic commerce (e-commerce) in Greece. The findings also emphasize the favorable association between e-service quality and UX with overall satisfaction, while indicating that e-service quality plays a partial mediating role in the relationship between UX and customer satisfaction.

The authors' study enhances the existing theory by introducing a new multi-dimensional conceptual framework that illuminates the relative importance of the dimensions within the scales. Additionally, it offers valuable insights into the impacts of e-service quality and UX on overall satisfaction, providing managers and practitioners with a tool to evaluate the quality of their electronic services and make necessary adjustments to meet the needs of their customers.

Mobile learning has seen tremendous growth over the years. Like any other software application, usability is one of the key concerns in its successful implementation. There is a lack of study that provides a comprehensive overview of usability testing of mobile learning applications. Motivated by this a mapping study is conducted.

A systematic mapping study was conducted using 51 papers retrieved from the Scopus database published between 2005 and 2022 that reported on usability testing of mobile learning applications.

The key findings suggest that research is expected to expand in the near future. User-based testing is the commonly used method, while data are collected mainly through questionnaires, observation and interviews. Testing is mainly conducted in a controlled environment.

The study provides (1) an evidence-based discussion on usability testing of mobile learning applications, (2) an up-to-date map on state of the art on usability testing of mobile learning applications and (3) providing direction for further research to scientifically strengthen the field.

Facilitated by image retouch tools, social media influencers can digitally enhance their self-image in product recommendation posts. This paper proposes that image enhancement may serve as a cue for the audience to assess the authenticity of the influencer (“true to oneself”), which further affects the influencer's product recommendation effectiveness (i.e. attitudes toward the post and recommended product).

Experiment 1 examines the effect of image enhancement on consumers' perceived influencer authenticity and product recommendation effectiveness. Experiment 2 considers the moderating role of post type, examining the effects in informational versus storytelling posts.

Consumers perceived an influencer to be more authentic when the image is not enhanced; in turn, consumers reported more favorable attitudes toward the post and the recommended product upon reading the post. The effects are moderated by post type: the effect of image enhancement (through perceived influencer authenticity) exists in posts using an informational message format but is attenuated for those using a storytelling message format.

This research enriches the literature on authenticity cues by documenting a novel visual cue and contributes to influencer marketing by identifying a nuanced interactive effect between image enhancement and post type on recommendation effectiveness.