Download or swipe left: The role of complexity,future-oriented emotions and feature overload

With the intense competition in the mobile applications (apps) market, it is imperative for app providers to understand how visual stimuli from their apps can create a positive first impression and enhance the app download rates. In the present study, the mechanism through which visual complexity influences mobile app download intention is examined. Using a combination of convenience and snowball sampling, 218 participants were recruited to take part in a single-group post-test only quasi-experimental design. The findings of the study showed that visual complexity influences mobile app download intentions through the mediating role of two future-oriented emotions (i.e. hope and anticipated regret). Additionally, the study showed that the indirect effect of visual complexity on download intentions was moderated by feature overload with the importance of visual complexity significantly reducing as perceptions of feature overload increases. The proposed model explained 46% variance in the intentions to download a mobile app. The findings not only provide practical insights for mobile app developers and publishers but also theoretical insights on consumer decision making in the pre-use context of mobile apps.     

Examining the antecedents and consequences of mobile app engagement

Understanding how and why consumers engage with mobile apps is critical to the success of ubiquitous mobile marketing. This study proposed and tested a structural model to investigate the antecedents and consequences of mobile app engagement. Results show that time convenience, interactivity, and compatibility positively influenced mobile app engagement, in turn leading to strong relationship commitment and self-brand connections. Furthermore, informational and experiential mobile apps moderated the effects of time convenience, interactivity, and compatibility on mobile app engagement. Theoretical and practical implications for effective app engagement strategies are discussed.     

Facilitation of consumer loyalty toward branded applications: The dual-route perspective

Although many brands develop mobile applications (apps) to build relationships with consumers, most branded apps fail to retain consumers’ loyalty. This study examines the facilitation of consumer loyalty toward branded apps (continuance intention, in-app purchase intention, and word-of-mouth intention) from the dual-route perspective. One route is the affective (relationship) route, where brand benefits (functional benefits, experiential benefits, symbolic benefits, and monetary benefits) drive parasocial interactions between consumers and the brand, which, in turn, influences branded app loyalty. The other route is the utility route, where system characteristics (system quality and information quality) affect perceived usefulness, which, in turn, facilitates branded app loyalty. An online survey was conducted, and the research model was empirically tested using partial least squares structural equation modeling. The findings support the dual-route perspective according to which both affective and utilitarian paths facilitate branded app loyalty. The key theoretical contribution of this study is that it moves beyond the utilitarian path and finds the affective (relationship) path to give a more complete picture of the facilitation of consumer loyalty in the branded app context. A strategy is provided to suggest to practitioners how to design branded apps to facilitate consumer loyalty.     

Identifying relevant segments of AI applications adopters – Expanding the UTAUT2’s variables

Artificial intelligence (AI) is a future-defining technology, and AI applications are becoming mainstream in the developed world. Many consumers are adopting and using AI-based apps, devices, and services in their everyday lives. However, research examining consumer behavior in using AI apps is scant. We examine critical factors in AI app adoption by extending and validating a well-established unified theory of adoption and use of technology, UTAUT2. We also explore the possibility of unobserved heterogeneity in consumers’ behavior, including potentially relevant segments of AI app adopters. To augment the knowledge of end users’ engagement and relevant segments, we have added two new antecedent variables into UTAUT2: technology fear and consumer trust. Prediction-orientated segmentation was used on 740 valid responses collected using a pre-tested survey instrument. The results show five segments with different behaviors that were influenced by the variables of the proposed model. Once known, the profiles were used to propose apps to AI developers to improve consumer engagement. The moderating effects of the added variables—technology fear and consumer trust—are also shown. Finally, we discuss the theoretical and managerial implications of our findings and propose priorities for future research.     

Mobile apps usage and dynamic capabilities: A structural equation model of SMEs in Lagos,Nigeria

Significant knowledge exists regarding the application of dynamic capability (DC) frameworks in large firms, but their impact on smaller organisations is yet to be fully researched. This study surveyed 1162 small and medium sized enterprises (SMEs) in Lagos in an effort to understand how SMEs in developing country contexts use mobile apps to enhance their businesses through DCs. Through the use of the covariance-based structural equation modelling (SEM) technique, the study explored the fitness of a conceptual formative model for SMEs. The model assembled 7 latent variables namely: mobile app usage, adaptive capability, absorptive capability, innovative capability, opportunity sensing ability, opportunity shaping ability and opportunity seizing ability. Subsequently, 15 hypotheses aimed at testing the relationships between the latent variables were developed and tested. The findings revealed that mobile app usage increases the adaptive, absorptive and innovative capabilities of SMEs. Absorptive capabilities help SMEs to maximise opportunities, while innovative capabilities negatively influence SMEs’ tendency to maximise opportunities. The results failed to establish a direct relationship between mobile app usage and SMEs’ ability to maximise opportunities. The research outcomes indicate that SMEs in Lagos respond to opportunities innovatively but they seldom exhibit innovation in order to create opportunities. The heterogeneous nature of SMEs complicates any clear-cut narrative as to how SMEs in Lagos should employ mobile apps to create and maximise opportunities. However, mobile apps could induce innovation and, as such, impact significantly when developed and applied to the contextual requirements of SMEs. The research revealed the untapped potential of SMEs’ mobile app usage in Lagos.     

Cross-Compiling Android Applications to iOS and Windows Phone 7

Android is currently leading the smartphone segment in terms of market share since its introduction in 2007. Android applications are written in Java using an API designed for mobile apps. Other smartphone platforms, such as Apple’s iOS or Microsoft’s Windows Phone 7, differ greatly in their native application programming model. App developers who want to publish their applications for different platforms are required to re-implement the application using the respective native SDK. In this paper we describe a cross-compilation approach, whereby Android applications are cross-compiled to C for iOS and to C# for Windows Phone 7. We describe different aspects of our cross-compiler, from byte code level cross-compilation to API mapping. A prototype of our cross-compiler called XMLVM is available under an Open Source license.     

AdaptiveMutate: a technique for privacy preservation

Mobile apps are known to be rich sources for gathering privacy-sensitive information about smartphone users. Despite the presence of encryption, passive network adversaries who have access to the network infrastructure can eavesdrop on the traffic and therefore fingerprint a user’s app by means of packet-level traffic analysis. Since it is difficult to prevent the adversaries from accessing the network, providing secrecy in hostile environments becomes a serious concern.In this study, we propose AdaptiveMutate, a privacy-leak thwarting technique to defend against the statistical traffic analysis of apps. First, we present a method for the identification of mobile apps using traffic analysis. Further, we propose a confusion system in which we obfuscate packet lengths, and/or inter-arrival time information leaked by the mobile traffic to make it hard for intruders to differentiate between the altered app traffic and the actual one using statistical analysis. Our aim is to shape one class of app traffic to obscure its features with the minimum overhead. Our system strives to dynamically maximize its efficiency by matching each app with the corresponding most dissimilar app. Also, AdaptiveMutate has an adaptive capability that allows it to choose the most suitable feature to mutate, depending on the type of apps analyzed and the classifier used, if known.We evaluate the efficiency of our model by conducting a comprehensive simulation analysis that mutates different apps to each other using AdaptiveMutate. We conclude that our algorithm is most efficient when we mutate a feature of one app to its most dissimilar one in another app. When applying the identification technique, we achieve a classification accuracy of 91.1%. Then, using our obfuscation technique, we are able to reduce this accuracy to 7%. Also, we test our algorithm against a recently published approach for mobile apps classification and we are able to reduce its accuracy from 94.8% to 17.9%. Additionally, we analyze the tradeoff between the shaping cost and traffic privacy protection, specifically, the associated overhead and the feasibility for real-time implementation.     

Mobile Technology: Opportunity for Entrepreneurship

The recent extraordinary growth of smart phones and tablets gives rise to the mobile application market. It opens up opportunity for new type of entrepreneurs to tap into the fast-growing mobile application market, bypassing the incumbent operators and requiring minimal capitals. Therefore, focus should be given to promoting these mobile entrepreneurs in order to change Thailand from a ‘consumer’ to a ‘producer’ of ICT technologies. This paper reviews recent trends on mobile technology in the mobile ecosystem and mobile application market. It then identifies emerging opportunity for business entrepreneurs. Furthermore, the measures being implemented by Mobile Technology for Thailand ( $\text{ MT}^{2})$ , an alliance from government, business and education sectors for promotion of mobile application industry, are explained. Specifically, it consists of human resource development, entrepreneur incubation and marketing support. It is expected that by focusing on inspiring a new generation of mobile application developers into entrepreneurship, incubating them into successful business and promoting their mobile app to the world market, Thailand could become a regional hub for mobile application industry in the near future.     

Systematic evaluation of mobile fitness apps: Apps as the Tutor,Recorder, Game Companion,and Cheerleader

Mobile fitness applications are innovating the ways in which smartphone users self-manage their health. Prior research found that app functions may impact app efficacy. However, research to date has not sought to systematically investigate how different combinations of app functions impact user response to apps, especially adoption intent. This article describes two studies on mobile fitness app characteristics and user attitudes. Study One used content analysis and hierarchical cluster analysis on 98 iPhone fitness apps and identified four app clusters: “Tutor”, “Recorder”, “Game Companion”, and “Cheerleader.” Tracking was the predominant function in current market, but tracking-focused Recorder apps received lowest user ratings among all app clusters. Users favored Tutor apps that combine exercise education and tracking, and Game Companion apps that combine gamification, tracking, and social functions. Function combinations, rather than standalone functions, impact app success. Following a Reasoned Action Approach, Study Two found various effects of individual differences (age, gender, BMI, eHealth literacy, smartphone experience, function preference) on user attitude toward different fitness app types. A comparison between two studies demonstrated a mismatch between market offerings and user needs regarding app functions. Implications of results for mobile fitness app design to improve consumer health and for theories are discussed.     

The role of regulatory focus in decision making of mobile app download: A study of Chinese college students

This paper aims to map out college consumers’ decision making process in mobile application download. Regulatory focus (RF) is examined as an important factor affecting gratifications sought (GS) and information processing (IP), app selection style and the ultimate mobile app download behavior. Results show that RF has effects on hedonic GS, and heuristic IP and systematic IP. Hedonic GS positively predicts equally both heuristic processing and systematic processing. Both heuristic processing and systematic processing predict selection style. Although selection style does not affect download app type diversity, impulsive style consumers are more likely to download the app. The study also shows college consumers in general have high likelihood in downloading an app after they considered it. Hedonic GS mediates the relation between RF and both heuristic processing and systematic processing. Systematic processing mediates hedonic GS and selection style. Hence mobile app download decision involves both heuristic and systematic processing.     

Mobile city applications for Brussels citizens: Smart City trends,challenges and a reality check

This article combines quantitative and qualitative methods to take a first look at the app economy and mobile services landscape in the City and Region of Brussels, capital of Belgium and Europe. By scraping the iTunes App Store and Google Play market places we get a view on platform distribution, pricing, public vs. commercial, adoption, appreciation and popular categories of Brussels apps aimed at citizens, as well as a view on the app economy in the city. This data is then complemented by qualitative expert interviews with actors in the field, such as cities, interest groups and developers. In the context of the current debate surrounding what constitutes a Smart City and the importance of smartphones and mobile in this area, we perform a reality check, using Brussels as a case. We find that the laggard position Brussels is currently in could be an opportunity to leapfrog in the field of mobile services, but that a focused vision and clear mobile strategy, while thinking of the city as a local innovation platform built on open data, is quintessential to achieving this.     

基于数字证书的自有APP签名保护方案

为应对移动应用(APP)盗版、仿冒、篡改风险,保证自有APP来源可信、内容完 整,本文提出了一套基于数字证书的APP签名保护与安全控制技术方案,实现了对 自有应用进行签名认证和全流程安全管控。该方案规范了自有APP的签名证书,明 确了正版标识;采用可信副署签名技术,加强代码保护,实现被篡改应用可识别可 追溯;通过中央监控平台,及时发现并限制异常应用,实现了APP的全流程实时安全管控。     

Untangling the effect of cognitive trust and perceived value on health-related information seeking,sharing and psychological well-being: Motivations sought perspective

Previous literature has documented that mobile application utilization increased exponentially throughout the ongoing COVID-19 epidemic. To comprehend the possible antecedents of individuals’ psychological well-being, this research invokes motivation theory and associated literature on perceived assessment (cognitive trust, perceived value, and perceived threat) to comprehensively investigate the determinants of factors influencing mobile app users’ health-related information behaviors and psychological outcomes. Data were gathered collected from 898 users of mobile apps, and this article adopted structural equation modeling (SEM) to evaluate the hypothesis generation model. Obtained findings demonstrated that cognitive trust and perceived value positively impacted seeking and sharing health-related information, which subsequently benefited individuals’ psychological well-being during the public health crisis. Furthermore, perceived threat exerted a negative impact on seeking and sharing health-related information. These results contribute to existing studies on psychological well-being by broadening the antecedence domain of information practices and revealing the underlying psychological mechanism behind this dynamic process. This study could also benefit practitioners by providing insights into embedded system and mobile app development, which would play a pivotal role in enhancing user experiences that optimize psychological well-being.     

Automatic labeling of mobile apps by the type of psychological needs they satisfy

App usage is now a ubiquitous phenomenon, but little is known about what types of psychological needs are met by which apps. We proposed a method to label automatically mobile apps in terms of whether and to what extent they can satisfy users’ particular psychological needs. First, using the grounded theory approach, we conducted semi-structured in-depth interviews to identify types of needs associated with app usage. Substantive and theoretical coding of the data from the interviews as well as data from samples of app reviews yielded eight types of psychological needs app users had: utilitarian, low-cost, security, health, hedonic, social, cognitive, and self-actualization needs. Second, using the needs corpus (words and phrases) generated above, a classifier was trained using latent Dirichlet allocation (LDA) and support vector machine (SVM) algorithms to filter reviews in terms of whether they included needs-related comments. The classifier showed good performance. Finally, Labeled-LDA was used to automatically provide each review with multiple labels of the types of needs mentioned and the apps were analyzed for the different types of needs they satisfied.     

Consumer preferences of attributes of mobile payment services in South Korea

The widespread diffusion of mobile devices has led to a new method of value transfer that retains the features of mobile devices: mobile payments. Many researchers have investigated consumers’ responses to mobile payment services, which is a key indicator of the success of a service, and have examined determinants of consumer adoption. Although many studies have addressed consumer adoption of mobile payment services, only the general and abstract factors affecting adoption (e.g., perceived usefulness) have been intensively investigated. However, these studies have rarely examined the idiosyncratic and concrete aspects of mobile payment services. To improve our understanding of why consumers adopt certain mobile payment services, this study investigated consumers’ evaluations of the explicit attributes of the services. Three hundred seventy-three consumers of mobile payment services participated in an online conjoint survey. Their preference structure was generated from a conjoint analysis including five service attributes (mobile payment platform, assurance policy, mileage program, authentication method, and affiliated stores), which were identified through a literature review and focus group discussion. The results showed that an assurance policy is the most critical factor influencing consumers’ choices, and a mileage program is considered to be as imperative as the platform. We also compared the findings by two consumer clusters (safety seekers vs. platform adherers), which were classified by preference. Because this study examines concrete and specific attributes of mobile payment services beyond abstract and general adoption factors, it provides insights into consumers’ actual adoption of services.     

Zone-it before IT zones you: a location-based digital notice board to build community while preserving privacy

The current success of ephemeral communication apps such as Snapchat points to the growing awareness among users about online ‘biographic mining’ through information technology by advertisers, companies and government agencies. Based on the literature, we argue that location-based services (LBS) can be the answer to preserving privacy, on the condition that they target trusted communities of anonymous users and that the communication is transient. The paper describes in three steps the development of an app fulfilling these conditions. From the interdisciplinary exchange between digital anthropologists, GIScientists and ICT engineers resulted Zone-it, a virtual notice board for self-zoning, permitting the user to start location-based interactions under certain categories. We present the results of a user survey that determined the app's functionalities. The functionalities offer a way for LBS to invert the purpose of social media such as Facebook by shifting attention from person-based to goal-oriented communication. The paper discusses why this move away from ‘faces’ to ‘places’ meets the purpose of community-building, rather than jeopardising it.     

Predicting numeric ratings for Google apps using text features and ensemble learning

Application (app) ratings are feedback provided voluntarily by users and serve as important evaluation criteria for apps. However, these ratings can often be biased owing to insufficient or missing votes. Additionally, significant differences have been observed between numeric ratings and user reviews. This study aims to predict the numeric ratings of Google apps using machine learning classifiers. It exploits numeric app ratings provided by users as training data and returns authentic mobile app ratings by analyzing user reviews. An ensemble learning model is proposed for this purpose that considers term frequency/inverse document frequency (TF/IDF) features. Three TF/IDF features, including unigrams, bigrams, and trigrams, were used. The dataset was scraped from the Google Play store, extracting data from 14 different app categories. Biased and unbiased user ratings were discriminated using TextBlob analysis to formulate the ground truth, from which the classifier prediction accuracy was then evaluated. The results demonstrate the high potential for machine learning-based classifiers to predict authentic numeric ratings based on actual user reviews.     

运用XD与HBuilderX在Android平台的智能手机App设计及应用

随着智能手机时代的到来,大多数人的生活方式已经改变,如今,智能手机已成为人们工作的一部分,并在他们的工作中起着重要作用。作为移动互联网行业的关键领域,智能手机在互联网行业中变得越来越重要。人们一直在密切关注智能手机App设计的用户体验。以智能手机App为核心的用户体验构建设计是智能手机应用程序设计的核心和关键点,也是使得用户需求得以满足的重要方式。智能手机App的存在时间相对较短。其开发过程缺少完整的设计过程和理论支持。如何给用户提供良好体验的App设计就显得非常重要。针对此问题,一方面,需要从逻辑设计入手考虑用户体验。另一方面,通过调查来分析用户体验,进行有效的图形设计。在手机App层出不穷的新时期,要合理设计智能手机的应用程序,以增强用户体验。     

Repackaging Attack on Android Banking Applications and Its Countermeasures

Although anyone can easily publish Android applications (or apps) in an app marketplace according to an open policy, decompiling the apps is also easy due to the structural characteristics of the app building process, making them very vulnerable to forgery or modification attacks. In particular, users may suffer direct financial loss if this vulnerability is exploited in security-critical private and business applications, such as online banking. In this paper, some of the major Android-based smartphone banking apps in Korea being distributed on either the Android Market or the third party market were tested to verify whether a money transfer could be made to an unintended recipient. The experimental results with real Android banking apps showed that an attack of this kind is possible without having to illegally obtain any of the sender’s personal information, such as the senders public key certificate, the password to their bank account, or their security card. In addition, the cause of this vulnerability is analyzed and some technical countermeasures are discussed.     

Religion-focused dating apps: A Q methodology study on the uses of mutual

Dating apps have become an increasingly viable option for individuals seeking interpersonal romantic relationships. While there is significant research regarding user motivation on dating apps such as Bumble, Tinder, and Match.com, there is no published research that discusses the motivations of Mutual app users. Developed as a dating app to target members of The Church of Jesus Christ of Latter-Day Saints, Mutual allows users to find potential mates who share their religious background and specify their relationship readiness (from “Into Dating I Guess” to “Ready for a Ring”). This research aims to illuminate the various motivations, attitudes, and opinions of Mutual app users through Q methodology, which identifies perceptual groups among homogeneous populations through a factor analysis of participants’ agreement with similar statements regarding Mutual use. Findings indicated four factor groups: the Relationship Readies (i.e., those serious about dating), the Swipeaholics (i.e., those looking for entertainment), the Faithless (i.e., those who felt pressured to use Mutual), and the Eligible Optimists (i.e., those who saw the app as a convenient, entertaining way to date). Different from other research on dating apps, this study indicates that people may use a niche religion-focused dating app to find individuals with similar moral values or due to external pressure from others. Results warrant further investigation into niche dating apps.