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Development of hierarchical structure and analytical model of key factors for mobile app stickiness
Author(s) -
TsuenHo Hsu,
JiaWei Tang
Publication year - 2019
Publication title -
journal of innovation and knowledge
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.72
H-Index - 20
eISSN - 2530-7614
pISSN - 2444-569X
DOI - 10.1016/j.jik.2019.01.006
Subject(s) - computer science , key (lock) , promotion (chess) , loyalty , social media , mobile apps , function (biology) , incentive , entertainment , value (mathematics) , business model , world wide web , marketing , advertising , knowledge management , business , computer security , evolutionary biology , machine learning , politics , art , political science , economics , law , visual arts , biology , microeconomics
Mobile apps (applications) provide services such as information dissemination, knowledge promotion, social media integration, and online shopping, all of which are platforms that enable the strengthening of communication and foster interaction between firms and consumers. The related pieces of literature on the continuous use of mobile apps have noted that apps must have convenience, unique value, social value, incentives, entertainment, and other such qualities to attract continuous usage by customers. As such, stickiness has become the key factor in the business success of apps. For businesses managing mobile apps, the topics of how to design content for mobile device users, how to measure media value and returns, and how to capture the attention of users and make them willing to spend more time using the application are all worthy of exploration. This study proposes the analytical model for mobile app stickiness to measure the significance of various influencing factors of the hierarchical structure and to measure the performance of mobile apps. The study explored key factors that affected user stickiness while examining usage statistics to develop management strategies geared toward mobile app stickiness to improve customer/user loyalty. The proposed model can function as a tool for app planners in measuring user stickiness and app performance while serving as reference for future studies into app stickiness and real-life applications. It can also clarify the influence of key factors influencing app stickiness, which can help app planners develop appropriate strategies and function as a reference point for future improvement and optimization strategies.

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