Uncovering top-ranking factors for mobile apps through a multimethod approach

• Main Author: Picoto, Winnie
• Publication Date: 2019
• Other Authors: Duarte, Ricardo, Pinto, Inês
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10400.5/95911
• topic: Mobile Apps; App Success; Top Grossing App; fsQCA; Multivariate Logistic Regression

The increasing computational power of mobile devices and the advancements in network communications are enabling the emergence of new mobile services. Developers have created many mobile applications (mobile apps) to fulfill a wide range of personal and professional user needs. The present study aims to answer the following research question: what are the factors that influence an app's ranking and success? To answer this question, we define a set of antecedents that may explain the top rank of an app. We use a sample of 500 of Apple's top grossing apps to analyze the top 50 and bottom 50 apps. We then use a multivariate logistic regression to examine if factors such as user rating, category popularity, diversity as measured by the number of languages supported, package size, and release date are determinants of an app's success. We also apply a fuzzy-set qualitative comparative analysis (fsQCA) to find the existence of more causal paths for the mobile app's success. Multivariate results indicate that category popularity, diversity (number of languages supported), package size, and app release date are all factors that increase the probability that an app will be ranked inside the top 50. Nevertheless, contrary to our prediction, a high user rating is negatively associated with an app's success. The results of the fsQCA show that the importance of an app's attributes, functionalities, and longevity surpasses the importance of the user rating in explaining the app's success..