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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 propose a comprehensive theoretical framework to explain the different diffusion dynamics of a technology realized under an open source (OS) regime vs a technology realized under a closed-proprietary (CP) regime.

Following a systematic combining approach, theoretical predictions derived from literature on diffusion of innovation and on open innovation were matched with empirical observations derived from a case study of two mobile operation systems, which were released under different technological regimes.

This paper proposes a theoretical framework and a set of original theoretical propositions that can help to explain the differences in the diffusion dynamics of technologies that are released under different regimes (i.e. CP vs OS).

This paper provides managers a better understanding of the diffusion dynamics of technologies released according to an open innovation strategy. In addition, the empirical case study improves the understanding of an important industry (the MOS industry) that has not been fully investigated from the innovation diffusion perspective. Nevertheless, the efficacy and generalizability of the theoretical framework proposed in this paper require future empirical tests.

This paper makes an original contribution to the open innovation and innovation diffusion literature by linking, in a conceptual model, three antecedents of the diffusion of a new technology that previous literature has considered only separately: the regime under which the technology is released (OS vs CP), the contingencies related to the characteristics of the technology and to the network of its adopters, and the resulting barriers to adoption.

The purpose of this paper is to propose practical and usable interactions that will allow more informed, risk-aware comparisons for individuals during app selections. The authors include an explicit argument for the role of human decision-making during app selection and close with a discussion of the strengths of a Bayesian approach to evaluating privacy and security interventions.

The authors focused on the risk communication in mobile marketplace’s realm, examining how risk indicators can help people choose more secure and privacy-preserving apps. Combining canonical findings in risk perception with previous work in usable security, the authors designed indicators for each app to enable decisions that prioritize risk avoidance. Specifically, the authors performed a natural experiment with N = 60 participants, where they asked them to select applications on Android tablets with accurate real-time marketplace data.

In the aggregate, the authors found that app selections changed to be more risk-averse in the presence of a user-centered multi-level warning system using visual indicators that enabled a click-thru to the more detailed risk and permissions information.

Privacy research in the laboratory is often in conflict with privacy decision-making in the marketplace, resulting in a privacy paradox. To better understand this, the authors implemented a research design based on clinical experimental approaches, testing the interaction in a noisy, confounded field environment.

This paper aims to investigate Google’s top developers’ apps with trust badges to see if they warrant an additional level of trust and confidence from consumers, as stated by Google.

Risky app permissions and in-app purchases (IAP) from Google’s top developers and traditional developers were investigated in several Google Play top app categories, including Editor’s Choice apps. Analysis was performed between categories and developer types.

Overall, Google’s top developers’ apps request more risky permissions and IAP than do traditional developers. Other results indicate that free apps are more dangerous than paid apps and star ratings do not signify safe apps.

Because of a limited number of Google’s top developers and Editor’s Choice apps, conclusions are drawn from a small sample of apps and not the entire market.

Google’s top developers’ apps are suited well for increasing revenue for Google and developers at the consumer’s expense. Consumers should be wary of top developer trust badges.

As the lure for “top free” and “top developer” software is strong among consumers, this research contributes to societal welfare in that it makes consumers aware that Google top developer app trust badges and free apps are more dangerous than traditional developer and paid apps, as they request risky permissions at a much higher frequency. Therefore, consumers should be very careful when downloading apps that are advertised as “top free” or “top developer”.

Google’s top developers’ apps and Editors’ Choice apps have not been investigated from the perspective of permissions and IAP before.

The proliferation of mobile phones with integrated sensors makes large scale sensing possible at low cost. During mobile sensing, data mostly contain sensitive information of users such as their real-time location. When such information are not effectively secured, users’ privacy can be violated due to eavesdropping and information disclosure. In this paper, we demonstrated the possibility of unauthorized access to location information of a user during sensing due to the ineffective security mechanisms in most sensing applications. We analyzed 40 apps downloaded from Google Play Store and results showed a 100% success rate in traffic interception and disclosure of sensitive information of users. As a countermeasure, a security scheme which ensures encryption and authentication of sensed data using Advanced Encryption Standard 256-Galois Counter Mode was proposed. End-to-end security of location and motion data from smartphone sensors are ensured using the proposed security scheme. Security analysis of the proposed scheme showed it to be effective in protecting Android based sensor data against eavesdropping, information disclosure and data modification.

Mobile applications, or apps, are an increasingly important part of omnichannel retailing. While the adoption and usage of apps for marketing purposes has grown exponentially over the past few years, there is little academic research in this area. The purpose of this paper is to examine how the mobile phone platform (Android vs Apple iOS), interest in the app and recency of store visit affect consumers’ likelihood to use the apps for purchasing and information-sharing activities.

The paper tests a model by analysing survey data collected from customers of a major US retailer using partial least squares regression.

The analysis finds that the level of interest in a retail app is positively related to the consumer's intention to engage in both purchasing and information-sharing activities. In addition, the recency of the consumer's last visit to the retail store has a moderating effect on both types of activities; the more recent the last visit, the larger the effect-size of interest in the app on intention to share information and make a purchase.

While marketing and advertising managers may have suspected that Apple iOS users are more receptive to retail mobile apps, this study provides empirical support for the proposition. In addition, the moderating effect of recency of visit suggests that in-store promotions may be effective in increasing usage of the retailer's mobile apps.

This study is among the first in the academic literature to examine predictors of mobile app usage for purchasing and information sharing. It fills a gap in the literature, while at the same time providing actionable information for practitioners.

Mobile devices (smartphones, tables etc.) have become the de facto means of accessing the internet. While traditional Web browsing is still quite popular, significant interaction takes place via native mobile apps that can be downloaded either freely or at a cost. This has opened the door to a number of issues related to privacy protection since the smartphone stores and processes personal data. The purpose of this paper is to examine the extent of access to personal data, required by the most popular mobile apps available in Google Play store. In addition, it is examined whether the relevant procedure is in accordance with the provisions of the new EU Regulation.

The paper examines more than a thousand mobile apps, available from the Google Play store, with respect to the extent of the requests for access to personal data. In particular, for each available category in Google Play store, the most popular mobile apps have been examined both for free and paid apps. In addition, the permissions required by free and paid mobile apps are compared. Furthermore, a correlation analysis is carried out aiming to reveal any correlation between the extent of required access to personal data and the popularity and the rating of each mobile app.

The findings of this paper suggest that the majority of examined mobile apps require access to personal data to a high extent. In addition, it is found that free mobile apps request access to personal data in a higher extent compared to the relevant requests by paid apps, which indicates strongly that the business model of free mobile apps is based on personal data exploitation. The most popular types of access permissions are revealed for both free and paid apps. In addition, important questions are raised in relation to user awareness and behavior, data minimization and purpose limitation for free and paid mobile apps.

In this study, the process and the extent of access to personal data through mobile apps are analyzed. Although several studies analyzed relevant issues in the past, the originality of this research is mainly based on the following facts: first, this work took into account the recent Regulation of the EU in relation to personal data (GDPR); second, the authors analyzed a high number of the most popular mobile apps (more than a thousand); and third, the authors compare and analyze the different approaches followed between free and paid mobile apps.

This study was conducted to identify, summarise, analyse and categorise mobile device applications (Apps), relevant to the construction industry and to explore their uses and exposure levels.

The research method involved reviewing literature and searching for Apps. The construction Apps were found by developing key phrases. These key phrases were used to develop search strategies, which were then used to find the construction Apps. The Apps found were categorised based on the similarity of their uses.

The 136 Apps identified were summarised, analysed, and categorised into 11 groups of distinct construction operations and tasks. The “Design and Drawing Apps”, “Measurement and Estimation Apps”, “Management Apps”, “All Round Apps” and “Construction Site Apps” recorded 29, 28, 26, 21 and 11 numbers of Apps, respectively. The Autodesk Sketchbook, GPS Field Area Measure, MagicPlan, Measure and TSheets were the top five in terms of the number of downloads. These Apps in terms of their exposure levels in the construction industry record 4.76%, 2.38%, 0.52%, 0.48% and 0.42%, respectively.

This paper provides a catalogue of the continuum of construction Apps for a wide variety of construction operations/activities which are available for construction professionals and provide guidance on their uses to assist in selecting appropriate Apps for specified operation/tasks/activities in the construction industry. Construction professionals may benefit from increased productivity, efficiency and ease of working.

The Web 3.0 has been hugely enabled by smartphones and new generation mobile applications. With the growing adoption of smartphones, the use of mobile applications has grown exponentially and so has the development of mobile applications. This study is an attempt to understand the issues and challenges faced in the mobile applications domain using discussions made on Twitter based on mining of user generated content.

The study uses 89,908 unique tweets to understand the nature of the discussions. These tweets are analyzed using descriptive, content and network analysis. Further using transaction cost economics, the findings are reviewed to develop practice insights about the ecosystem.

Findings indicate that the discussions are mostly skewed toward a positive polarity and positive user experiences. The tweeters are predominantly application developers who are interacting more with marketers and less with individual users.

Most of these applications are for individual use (B2C) and not for enterprise usage. There are very few individual users who contribute to these discussions. The predominant users are application reviewers or bloggers of review websites who use the recently developed applications and discuss their thoughts on the same.

The results may be useful in varied domains which are planning to expand their reach to a larger audience using mobile applications and for marketers who primarily focus on promotional content.

The domain of mobile applications on social media is still restricted to promotions and digital marketing and may solely be used for the purpose of link building by application developers. As such, the discussions could provide inputs towards mobile phone manufacturers and ecosystem providers on what are the real issues these communities are facing while developing these applications.

The study uses mixed research methodology for mining experiences in the domain of mobile application developers using social media analytics and transaction cost economics. The discussion on the findings provides inputs for policy-making and possible intervention areas.

Construction safety is a crucial aspect that has far-reaching impacts on economic development. But safety monitoring is often reliant on labor-based observations, which can be prone to errors and result in numerous fatalities annually. This study aims to address this issue by proposing a cloud-building information modeling (BIM)-based framework to provide real-time safety monitoring on construction sites to enhance safety practices and reduce fatalities.

This system integrates an automated safety tracking mobile app to detect hazardous locations on construction sites, a cloud-based BIM system for visualization of worker tracking on a virtual construction site and a Web interface to visualize and monitor site safety.

The study’s results indicate that implementing a comprehensive automated safety monitoring approach is feasible and suitable for general indoor construction site environments. Furthermore, the assessment of an advanced safety monitoring system has been successfully implemented, indicating its potential effectiveness in enhancing safety practices in construction sites.

By using this system, the construction industry can prevent accidents and fatalities, promote the adoption of new technologies and methods with minimal effort and cost and improve safety outcomes and productivity. This system can reduce workers’ compensation claims, insurance costs and legal penalties, benefiting all stakeholders involved.

To the best of the authors’ knowledge, this study represents the first attempt in Bangladesh to develop a mobile app-based technological solution aimed at reforming construction safety culture by using BIM technology. This has the potential to change the construction sector’s attitude toward accepting new technologies and cultures through its convenient choice of equipment.