With the rapid growth of the smartphone and tablet market, mobile application (App) industry that provides a variety of functional devices is also growing at a striking speed. Product life cycle (PLC) theory, which has a long history, has been applied to a great number of industries and products and is widely used in the management domain. In this study, we apply classical PLC theory to mobile Apps on Apple smartphone and tablet devices (Apple App Store). Instead of trying to utilize often-unavailable sales or download volume data, we use open-access App daily download rankings as an indicator to characterize the normalized dynamic market popularity of an App. We also use this ranking information to generate an App life cycle model. By using this model, we compare paid and free Apps from 20 different categories. Our results show that Apps across various categories have different kinds of life cycles and exhibit various unique and unpredictable characteristics. Furthermore, as large-scale heterogeneous data (e.g., user App ratings, App hardware/software requirements, or App version updates) become available and are attached to each target App, an important contribution of this paper is that we perform in-depth studies to explore how such data correlate and affect the App life cycle. Using different regression techniques (i.e., logistic, ordinary least squares, and partial least squares), we built different models to investigate these relationships. The results indicate that some explicit and latent independent variables are more important than others for the characterization of App life cycle. In addition, we find that life cycle analysis for different App categories requires different tailored regression models, confirming that inner-category App life cycles are more predictable and comparable than App life cycles across different categories.
This study proposes the establishment of a knowledge-system ontology in the nursing field. It uses advanced data mining techniques, digital publishing technologies, and new media concepts to comprehensively integrate and deepen nursing knowledge and to aggregate sources of knowledge in specialized technical fields. This study applies all forms of media and transmission channels, such as personal computers and mobile devices, to establish a knowledge-transmission system that provides knowledge services such as knowledge search, update retrieval, evaluation, questions and answers (Q&As), online viewing, information subscription, expert services, push notifications, review forums, and online learning. In doing so, this study creates an authoritative and foundational knowledge service engine for the nursing field, which provides convenient, flexible, and comprehensive knowledge services to members of the nursing industry in a digital format.