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Cited by 13Evolutionary Game Theory and CooperationDigital Platforms and EconomicsEvolution and Genetic Dynamics

The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.

The Effects of Developer Dynamics on Fitness in an Evolutionary Ecosystem Model of the App Store

Lim, Soo Ling, Bentley, Peter J., Ishikawa, Fuyuki·2016·IEEE Transactions on Evolutionary Computation
DOI 10.1109/tevc.2015.2494382
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Abstract

Natural ecosystems exhibit complex dynamics of interacting species. Man-made ecosystems exhibit similar dynamics and, in the case of mobile app stores, can be said to perform optimization as developers seek to maximize app downloads. This work aims to understand stability and instability within app store dynamics and how it affects fitness. The investigation is carried out with AppEco, a model of the iOS App Store, which was extended for this paper and updated to model the store from 2008 to 2014. AppEco models apps containing features, developers who build the apps, users who download apps according to their preferences, and an app store that presents apps to the users. It also models developers who use commonly observed strategies to build their apps: innovator, milker, optimizer, copycat, and flexible (the ability to choose any strategy). Results show that despite the success of the copycat strategy, there is a clear stable state for low proportion of copycats in developer populations, mirroring results in theoretical biology for producer-scrounger systems. The results also show that the best fitness is achieved when the evolutionary optimizer (as producer) and copycat (as scrounger) strategies coexist together in stable proportions.

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Citations

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Research works printed but not linked: 7

  1. lanfranchi, 2010, How to Successfully Market Your IPhone Application
  2. tesfatsion, 2015, Agent-Based Computational Economics (ACE)
  3. ray, 1991, An approach to the synthesis of life, Artificial Life II, 371
  4. lim, 2012, How to become a successful app developer? Lessons from the simulation of an app ecosystem, Proc Genet Evol Comput (GECCO), 129
  5. 10.1111/j.1600-0889.1983.tb00031.x · DOI
  6. lim, 2012, From natural to artificial ecosystems, Proc Frontiers Nat Comput, 15
  7. 10.1109/4235.956714 · DOI

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Metadata

Authors
Lim, S. L., Bentley, P. J., & Ishikawa, F.
Affiliations
  • University College London (GB)
  • National Institute of Informatics (JP)
ORCID
Venue
IEEE Transactions on Evolutionary Computation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2016-08
Volume
20
Issue
4
Pages
529-545
ISSN
  • 1089-778X (ISSN-L)
  • 1941-0026
DOI
10.1109/tevc.2015.2494382
OpenAlex
W2345110451
Cited by
13
References
42
Citations by year
2026: 1 · 2024: 1 · 2023: 3 · 2022: 3 · 2021: 1 · 2020: 1 · 2018: 1 · 2017: 1 · 2016: 1
FWCI
3.32
Type
journal article
Language
en
Open access
closed
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/OAPA.html (vor)
Locations
IEEE Transactions on Evolutionary Computation (publishedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Evolutionary Game Theory and Cooperation
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Platforms and Economics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
Keywords
iOS App Store, mobile app stores, developer strategies, milkers, evolutionary stability, coexistence, fitness, ecosystem dynamics

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