Understanding user behavior with new mobile applications

2007 ◽  
Vol 16 (4) ◽  
pp. 393-412 ◽  
Author(s):  
Raquel Benbunan-Fich ◽  
Alberto Benbunan
Keyword(s):  
Mobile Applications ◽  
User Behavior

scholarly journals Quality and Use of Mobile Applications for Transportation Service: Influence on Satisfaction

2021 ◽  
pp. 21-42
Author(s):  
Claudia Leticia Preciado-Ortiz
Keyword(s):  
Mobile Applications ◽  
Mobile Application ◽  
Structural Equation ◽  
User Behavior ◽  
Research Work ◽  
Equation Modeling ◽  
Transportation Industry ◽  
Transportation Service ◽  
Intention To Continue

The main objective of this research work was to analyze the factors that influence satisfaction and the intention to continue with the use of mobile transport applications in young university students from Guadalajara, Jalisco, Mexico. The approach was quantitative. 144 valid responses were used, and partial least squares structural equation modeling (PLS-SEM) was used to test the model. The software employing was the SmartPLS 3. The results indicate that the quality of the design, the quality of the information and the quality of the system are predictors of influence on satisfaction. Companies that offer individual passenger transport through a mobile application have increased in recent years, generating strong competition both between existing brands and with established traditional taxis. This study provides new and recent information for marketing managers and academics on application user behavior in the transportation industry.

scholarly journals Explaining user experience in mobile gaming applications: an fsQCA approach

2019 ◽  
Vol 29 (2) ◽  
pp. 293-314 ◽  
Author(s):  
Ilias O. Pappas ◽  
Patrick Mikalef ◽  
Michail N. Giannakos ◽  
Panos E. Kourouthanassis
Keyword(s):  
Complexity Theory ◽  
Mobile Applications ◽  
Positive Emotions ◽  
User Behavior ◽  
Qualitative Comparative Analysis ◽  
Mobile Games ◽  
Content Type ◽  
Content Quality ◽  
Intention To Adopt ◽  
Research Propositions

Purpose In the complex ecosystem of mobile applications multiple factors have been used to explain users’ behavior, without though focusing on how different combinations of variables may affect user behavior. The purpose of this paper is to show how price value, game content quality, positive and negative emotions, gender and gameplay time interact with each other to predict high intention to download mobile games. Design/methodology/approach Building on complexity theory, the authors present a conceptual model followed by research propositions. The propositions are empirically validated through configurational analysis, employing fuzzy-set qualitative comparative analysis (fsQCA) on 531 active users of mobile games. Findings Findings identify ten solutions that explain high intention to download mobile games. Alternative paths are identified depending on the gender and the time users spend playing mobiles games. The authors highlight the role of price value and game content quality, as well as that of positive emotions, which are always core factors when present. Originality/value To identify complex interactions among the variables of interest, fsQCA is employed, differentiating from traditional studies using variance-based methods, leading to multiple solutions explaining the same outcome. None of the variables explains the intention to download on its own, but only when they combine with each other. The authors extend existing knowledge on how price value, game content quality, emotions, gender and gameplay time combine to lead to high intention to download mobile games; and present a methodology for how to bridge complexity theory with fsQCA, improving our understanding of intention to adopt mobile applications.

scholarly journals Growth, Adoption, and Use of Mobile E-Commerce

2014 ◽  
Vol 104 (5) ◽  
pp. 489-494 ◽  
Author(s):  
Liran Einav ◽  
Jonathan Levin ◽  
Igor Popov ◽  
Neel Sundaresan
Keyword(s):  
Mobile Applications ◽  
User Behavior ◽  
Internet Site ◽  
Internet Commerce ◽  
Early Adopters ◽  
The Core ◽  
Mobile Shopping ◽  
Internet Platform ◽  
Early Effects ◽  
Sustained Increase

We document some early effects of how mobile devices might change Internet and retail commerce. We present three main findings based on an analysis of eBay's mobile shopping application and core Internet platform. First, early adopters of mobile e-commerce applications appear to be people who already were relatively heavy Internet commerce users. Second, adoption of the mobile shopping application is associated with both an immediate and sustained increase in total platform purchasing, with little evidence of substitution from the core platform. Third, differences in user behavior across the mobile applications and the regular Internet site are not yet so dramatic.

A User Behavior Based Trust Model for Mobile Applications

2008 ◽  
pp. 455-469 ◽  
Author(s):  
Zheng Yan ◽  
Valtteri Niemi ◽  
Yan Dong ◽  
Guoliang Yu
Keyword(s):  
Mobile Applications ◽  
User Behavior ◽  
Trust Model ◽  
Behavior Based

Developing Self-Adaptive Service-Oriented Mobile Applications: A Framework Based on Dynamic Deployment

2018 ◽  
Vol 28 (11n12) ◽  
pp. 1537-1558
Author(s):  
William Filisbino Passini ◽  
Frank José Affonso
Keyword(s):  
Mobile Applications ◽  
User Behavior ◽  
Third Party ◽  
Smart Devices ◽  
Mobile Environment ◽  
Adaptive Services ◽  
Service Oriented ◽  
Processing And Storage ◽  
Hybrid Devices ◽  
Self Adaptive

Today’s society is increasingly dependent on the use of mobile or smart devices (e.g. smartphones, tablets, hybrid devices, smart-TVs, smart-watches, among others), which have changed over these last 10 years the way people perform their daily tasks. In parallel, Internet of Things (IoT) systems have played a prominent position in this scenario, since they enable to exchange information among different types of devices and services (e.g. physical devices, vehicles, home appliances, sensors, among others). This scenario has boosted the demand for development of high-quality Mobile Applications (MobApps), which can be pre-installed on such devices during manufacturing platforms, or delivered as applications by the mobile stores or third parties. According to [1–3], mobile devices have some physical limitations (e.g. processing and storage) compared to personal computers. Thus, service-oriented MobApps have been a feasible alternative to overcome such limitations, improving the efficiency of the development life cycle of these applications with adoption of third-party components (e.g. software components, web services, and other mobile applications). In another perspective, it is also been noted a change in the user behavior of MobApps, which demand applications capable of operating in adverse conditions, maintaining their integrity of execution. Considering the relevance of such applications, this paper reports the extension of a framework to support the development of Self-adaptive Services-oriented MobApps (Self-MobApps), which enables modification of services at runtime [4] by means of a deployment dynamic approach. To show the feasibility of our framework, a case study for a smart restaurant was conducted in a mobile environment. The results of this study enable us to create a positive perspective on the contribution of our framework to the research communities involved.

HEPre: Click frequency prediction of applications based on heterogeneous information network embedding

2021 ◽  
pp. 1-16
Author(s):  
Chao Li ◽  
Yeyu Yan ◽  
Zhongying Zhao ◽  
Jun Luo ◽  
Qingtian Zeng
Keyword(s):  
Prediction Model ◽  
Mobile Applications ◽  
Mobile Application ◽  
User Behavior ◽  
Absolute Error ◽  
Research Direction ◽  
Information Network ◽  
Heterogeneous Information Network ◽  
Heterogeneous Information ◽  
Network Representation

Owing the continuous enrichment of mobile application resources, mobile applications carry almost all user behaviors and preferences. The analysis of user behavior regarding mobile terminals has become an important research direction. The frequency with which users click on mobile applications reflects their preferences to a certain extent. In this study, we propose a mobile application click-frequency prediction model based on heterogeneous information network representation. This model first constructs a heterogeneous information network between users’ mobile devices and mobile applications. To generate a meaningful sequence of network-embedded nodes, we perform a random walk on a specified meta-path. Finally, the prediction of users’ mobile application click frequency is completed using representation fusion and matrix factorization. Experiments show that our method outperforms other baseline methods in terms of the mean absolute error and root mean square error. Therefore, the application of a heterogeneous information network representation method to the prediction model is effective. This study is significant to the behavior research of mobile terminal users.

Mobile applications for client use: Ethical and legal considerations.

2019 ◽  
Vol 16 (2) ◽  
pp. 281-285 ◽  
Author(s):  
Amanda Edwards-Stewart ◽  
Cynthia Alexander ◽  
Christina M. Armstrong ◽  
Tim Hoyt ◽  
William O'Donohue
Keyword(s):  
Mobile Applications ◽  
Ethical And Legal Considerations
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