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User review is a significant component of mobile app markets such as the Google Play Store, App Store, Microsoft Store and others. Users submit their reviews for downloaded apps on these sites in the form of star ratings and text reviews. Apps can contain huge volumes of feedback, making it difficult for the user and the developer to skim through thousands of such reviews to get an insight into usage and impact of such apps. Thus, the current study aims to assess the usage and satisfaction among users of the Mendeley’s Android app vs iOS app.

The analytics are performed by using Appbot analytics software which captured, monitored, measured and analyzed the review results for a particular period. Appbot provides easy-to-understand insights of an app using artificial intelligence algorithm tools.

The findings of the study reveal strong inclination, adoption and usage of Mendeley’s Android app compared to that of iOS among users.

The value of this research is in getting an insight of the pattern/behavior of users towards using apps on different platforms (Android vs iOS) and provides valuable results for the app developers in monitoring usage and enhancing features for the satisfaction of users. Without mobile app analytics, one will be blindly trying out different things without any evidence to back up their experiments.

The purpose of this paper is to address how New York University Shanghai Library utilizes WeChat to support students’ research and information needs. WeChat is a mobile text and voice messaging communication service developed in China. Released in 2011, it currently has over 355 million users worldwide. The paper explores the information exchanges and interactions as well: what are students asking and what they can gain from this app; and features of the app are explored: WeChat can send files, support video-chat and group and voice messaging. By examining the opportunities and challenges of this app, the paper offers best practices to maximize WeChat as a library virtual service.

The design approach of this paper is to analyze the information exchanges and interactions from participants. By collecting and analyzing the responses, the paper presents the opportunities of the app in supporting patrons who are often mobile and also how the app can be used for student engagement that is beyond reference services.

From virtual reference to social media outreach, this paper finds that the app can offer a wide range of support and service through the library. Based on the positive daily interactions in the app, the research notes that the app can be utilized in many contexts: to support virtual service, to create student engagement, to promote library services and to create an online community of student users.

This paper introduces in the context of an American institution and how this app can be utilized to support virtual reference and student engagement. The most important feature of this work is to demonstrate how to use this app to promote and to provide library services remotely. The paper introduces an alternative virtual reference service that can be utilized in any university setting.

This exploratory study examines and comprehends the relative importance of mobile app attributes from a consumer perspective. Both quantitative and qualitative analysis approaches explore users' behavior and attitudes toward the priorities of mobile app attributes and preferences, identifying correlations between attributes and aggregating individual attributes into groups.

Online convenience sampling and snowball sampling resulted in 417 valid responses. The numerical data are analyzed using the relative to an identified distribution (RIDIT) scoring system and gray relational analysis (GRA), and qualitative responses are investigated using text-mining techniques.

This study finds enhanced nuances of user preferences and provides data-driven insights that might help app developers and marketers create a distinct app that will add value to consumers. The latent semantic analysis indicates relationship structure among the attributes, and text-based cluster analysis determines the subsets of attributes that represent the unique functions of the mobile app.

This study reveals the essential components of mobile apps, paying particular attention to the consumer value component, which boosts user approval and encourages prolonged use. Overall, the results demonstrate that developers must concentrate on its functional, technical and esthetic features to make an app more exciting and practical for potential users.

Most scholarly research on apps has focused on their technological merits, aesthetics and usability from the user's perspective. A post-adoption multi-attribute app analysis using both structured and unstructured data is conducted in this study.

This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.

This paper aims to investigate textual characteristics of customer reviews that motivate companies to respond (sentiment negativity and sentiment deviation) and how aspects of these company responses (response intensity, length and tailoring) affect subsequent customer review quality (comprehensiveness and readability) over time.

Leveraging a large data set from a leading app website (Shopify), the authors combine text mining, natural language processing (NLP) and big data analysis to examine the antecedents and outcomes of online company responses to reviews.

This study finds that companies are more likely to respond to reviews with more negative sentiment and higher sentiment deviation scores. Furthermore, while longer company responses improve review comprehensiveness over time, they do not have a significant influence on review readability; meanwhile, more tailored company responses improve readability but not comprehensiveness over time. In addition, the intensity (volume) of company responses does not affect subsequent review quality in either comprehensiveness or readability.

This paper expands on the understanding of online company responses within the digital marketplace – specifically, apps – and provides a new and broader perspective on the motivations and effects of online company responses to customer reviews. The study also extends beyond the short-term focus of prior works and adds to literature on long-term effects of online company responses to subsequent reviews. The findings provide valuable insights for companies (especially those with apps) to enhance their online communication strategies and customer engagement.

Based on student responses to a set of customized questionnaires, this study aims to present evidence that while student evaluations of instructors and courses remain consistent, a designated mobile app enhances perceived online learning experience.

This study addresses quality assurance issues in accelerated online graduate-level education by identifying factors that influence nontraditional adult student preferences for using mobile applications (apps).

It is evident that affordability and functionality are the two most important determinants of nontraditional student preferences for app-based learning, followed by mobility and ease of purchase.

These findings underscore the potential of app learning to bolster positive perceptions of online education. Findings of this study imply that integrating additional app learning tools can be used as a quality assurance mechanism and enhance nontraditional students’ satisfaction through improving their perceived online learning experience.

Hoping to increase the productivity of their employees, firms provide and expect their employees to use approved mobile apps. However, despite an intuitive appeal, the relationship between information technology usage and productivity is still seen as paradoxical. This study examines the relationship between employees' experience and engagement with business mobile apps provided by employers and its effects on employee work productivity.

Data from respondents who use employer-provided business apps were used to test the hypotheses. Measurement-corrected latent scores extracted from the PLS measurement evaluation were used in regression-centric assessment using PROCESS.

Results indicate that employee-users’ experience-based attributions of the business app, i.e. customization, performance quality and compatibility, have positive effects on productivity mediated by participation intensity. Further, work type (retail vs non-retail) and the depth of the employee user’s experience moderate experience-based attributions' indirect effects on productivity.

Unlike previous studies delving into this topic, this study focuses solely on the mediation and moderation effects for hypothesis testing. Specifically, this study investigates effects conditional on work type (retail vs non-retail), which the authors believe has significant implications for retailing. These findings have interesting implications for both future research and managers.

This study attempts to discover effective strategies for mobile commerce applications (apps) to grow their consumer base by releasing app strategic updates. Drawing on the landscape search model from strategy research, this study conceptualizes mobile app update strategy as three interdependent decisions, i.e. what business elements are changed in an app strategic update, how substantial the changes are and when strategic updates are released relative to the competitive environment.

Using a field data set of 1,500 strategic updates of seven rival apps in the mobile travel market, this study integrated fuzzy set qualitative comparative analysis (fsQCA) with econometric analysis to analyze how app strategic update decisions interdependently influence app performance.

This study identified three effective and one ineffective mobile app update strategies from the mixed-method analysis, which verified the complex interdependency of app strategic update decisions. A general takeaway from these strategies is that a complex strategy problem on the mobile platform must be solved with respect to the constraints and capabilities of mobile technology.

This study moves beyond a linear view of the relationship between app update frequency and app performance and provides a holistic view of how and why app strategic update decisions mutually influence one another in their impact on app performance. This work makes contributions by identifying interdependency as a conceptual bridge between strategy and mobile app literature and developing an empirically testable version of the landscape search model.

Consumers are increasingly embracing innovative technologies for enhanced experiences. This study delves into the banking consumer brand experience through the lens of augmented reality (AR). The focus is on mobile augmented reality applications within financial institutions, which contribute to a more enjoyable and immersive customer experience. Specifically, the research highlights the utilisation of mobile augmented reality applications by a Pakistani bank and examines its influence on consumer loyalty and sustained engagement, with a particular emphasis on the AR brand experience.

The authors conducted a comparative study between married and unmarried consumers with sample sizes of 178 and 172, respectively. The results were analysed through structural equation modelling using SmartPLS.

The study's outcomes show that AR brand experience for the unmarried sample category is positive and higher than a married one. This is an excellent opportunity for the banking sector in Pakistan to invest more in innovative technologies.

The current study investigates the brand experience in the banking sector from the perspective of AR technology which contributes to the AR literature.

The aim of this study was to observe how a user’s individual factors in a commercial weight-loss treatment app affect their perceived usefulness of its features and how they relate to each other.

The information was obtained from an online survey with a sample of 412 users from a branded app for a commercial weight-loss treatment using body mass index (BMI), self-efficacy, social support and perceived usefulness as variables.

Users with higher self-efficacy perceived the app’s features as more useful. However, BMI was not a factor except for the psycho-emotional support features, which individuals with obesity perceived as more useful. Likewise, it was found that there weren’t any significant differences in self-efficacy based on their BMI. Lastly, it was found that social support could not be used as a factor to predict self-efficacy.

This study helps understand how individual factors for behavioural change may affect the perceived usefulness of a weight-loss app. Furthermore, the significance of self-efficacy as an influencing factor provides useful information for companies and app developers alike when developing their branded apps.

This study contributes to the body of knowledge on factors affecting user perceptions of weight-loss apps. It also adds to the literature of branded apps as complimentary resources for companies, which has not been studied in detail.