Do Development Strategies Influence the Performance of Mobile Apps? Market Status Matters

Bei Luo, Xiaoke Zhang*, Lele Kang, Qiqi Jiang

*Corresponding author af dette arbejde

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

Abstrakt

There is substantial academic interest in modeling the determinants of mobile apps’ success. However, few relative researches explored the impact of development strategies and market status of mobile apps on their market performance. This paper adopted text mining technique and Boston Consulting Group (BCG) Matrix to measure the divergence of a development strategy and market status, respectively. Furthermore, we construct a multivariable linear regression model of performance of apps using data from five mobile platforms: Mumayi, Baidu mobile assistant, 360 mobile assistant, Eoemarket, and App China. The result shows that apps of Stars require convergent development strategies to attract potential consumers while more generally, the divergent development strategies benefit apps in other quadrants of the BCG Matrix, namely Cash Cows, Problem Children and Dogs.

OriginalsprogEngelsk
TitelHCI in Business, Government and Organizations. Information Systems and Analytics - 6th International Conference, HCIBGO 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings
RedaktørerFiona Fui-Hoon Nah, Keng Siau
Antal sider12
UdgivelsesstedCham
ForlagSpringer
Publikationsdato14 jun. 2019
Sider83-94
ISBN (Trykt)9783030223373
DOI
StatusUdgivet - 14 jun. 2019
Begivenhed6th International Conference on HCI in Business, Government, and Organizations, HCIBGO 2019 - Orlando, USA
Varighed: 26 jul. 201931 jul. 2019
Konferencens nummer: 6

Konference

Konference6th International Conference on HCI in Business, Government, and Organizations, HCIBGO 2019
Nummer6
LandUSA
ByOrlando
Periode26/07/201931/07/2019
AndetHeld as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind11589
ISSN0302-9743

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