TY - GEN
T1 - Canalization or increased diffusion? An empirical analysis on the impact of the recommendation system in the mobile app market
AU - Liu, Charles Zhechao
AU - Jozani, Mohsen M.
AU - Choo, Kim Kwang Raymond
N1 - Publisher Copyright:
© 2018 IEEE Computer Society. All rights reserved.
PY - 2018
Y1 - 2018
N2 - Online retailers have increasingly adopted product recommendation systems as an effective tool to improve product visibility and promote sales. This study examines the impact of the recommendation system in the popular Google Play mobile app store. By analyzing a 60-day panel dataset with 235,638 observations from 9,735 apps, we investigate how the characteristics of the recommended apps relative to those of the focal apps affect the adoption of mobile apps in this volatile market. Our results show that the relative strength of the recommended apps over the focal app plays a key role in influencing the outcome of recommendations. Moreover, the heterogeneity of the recommendations as represented by the diversity of the popularity of the recommended apps is positively associated with a more even distribution of revenue in the market. These findings provide insights for mobile app market operators to enhance the design of their recommendation systems.
AB - Online retailers have increasingly adopted product recommendation systems as an effective tool to improve product visibility and promote sales. This study examines the impact of the recommendation system in the popular Google Play mobile app store. By analyzing a 60-day panel dataset with 235,638 observations from 9,735 apps, we investigate how the characteristics of the recommended apps relative to those of the focal apps affect the adoption of mobile apps in this volatile market. Our results show that the relative strength of the recommended apps over the focal app plays a key role in influencing the outcome of recommendations. Moreover, the heterogeneity of the recommendations as represented by the diversity of the popularity of the recommended apps is positively associated with a more even distribution of revenue in the market. These findings provide insights for mobile app market operators to enhance the design of their recommendation systems.
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M3 - Conference contribution
AN - SCOPUS:85068180126
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 1432
EP - 1441
BT - Proceedings of the 51st Annual Hawaii International Conference on System Sciences, HICSS 2018
A2 - Bui, Tung X.
PB - IEEE Computer Society
T2 - 51st Annual Hawaii International Conference on System Sciences, HICSS 2018
Y2 - 2 January 2018 through 6 January 2018
ER -