IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v118y2017icp28-43.html
   My bibliography  Save this article

Technology diffusion: Shift happens — The case of iOS and Android handsets

Author

Listed:
  • Dutta, Amitava
  • Puvvala, Abhinay
  • Roy, Rahul
  • Seetharaman, Priya

Abstract

The diffusion of technology artifacts is often marked by abrupt events and incremental evolutionary moves, resulting in shifts in diffusion parameters as well as the underlying mechanics. In this paper, we model the diffusion of Android and iOS based handsets, where new models and operating system versions are released periodically. We relax a common assumption in IT diffusion studies, of holding diffusion parameters constant, and find that there are clear breaks in their values at specific points in time. Using the system dynamics methodology, we then develop and calibrate a causal model of the underlying mechanics. Significant events during evolution of the two platforms are matched temporally with the observed breaks, and the changing mechanics of diffusion across the breakpoints are identified using this causal structure. We find that iOS and Android handset diffusion patterns, although superficially similar, were driven by different mechanics. Our study contributes to the IT diffusion literature by (i) establishing the need to test for, and model, shifts in diffusion parameters over the horizon of interest (ii) offering a method to identify changes in diffusion mechanisms accompanying these shifts and (iii) demonstrating that similar temporal diffusion patterns need not imply similar underlying mechanics.

Suggested Citation

  • Dutta, Amitava & Puvvala, Abhinay & Roy, Rahul & Seetharaman, Priya, 2017. "Technology diffusion: Shift happens — The case of iOS and Android handsets," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 28-43.
  • Handle: RePEc:eee:tefoso:v:118:y:2017:i:c:p:28-43
    DOI: 10.1016/j.techfore.2017.01.024
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162517301129
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2017.01.024?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lakka, Spyridoula & Michalakelis, Christos & Varoutas, Dimitris & Martakos, Draculis, 2013. "Competitive dynamics in the operating systems market: Modeling and policy implications," Technological Forecasting and Social Change, Elsevier, vol. 80(1), pages 88-105.
    2. Sangin Park, 2004. "Quantitative Analysis of Network Externalities in Competing Technologies: The VCR Case," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 937-945, November.
    3. Donald W. K. Andrews, 2003. "Tests for Parameter Instability and Structural Change with Unknown Change Point: A Corrigendum," Econometrica, Econometric Society, vol. 71(1), pages 395-397, January.
    4. Ahmet Ilker Soydan & M. Atilla Oner, 2012. "Timely Resource Allocation Between R&D And Marketing: A System Dynamics View," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 1-38.
    5. Charlotte C. Greenan, 2015. "Diffusion of innovations in dynamic networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 147-166, January.
    6. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    7. Anjana Susarla & Jeong-Ha Oh & Yong Tan, 2012. "Social Networks and the Diffusion of User-Generated Content: Evidence from YouTube," Information Systems Research, INFORMS, vol. 23(1), pages 23-41, March.
    8. Jushan Bai & Pierre Perron, 2003. "Critical values for multiple structural change tests," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 72-78, June.
    9. Lakka, Spyridoula & Michalakelis, Christos & Varoutas, Dimitris & Martakos, Draculis, 2012. "Exploring the determinants of the OSS market potential: The case of the Apache web server," Telecommunications Policy, Elsevier, vol. 36(1), pages 51-68.
    10. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    11. Economides, Nicholas, 1996. "Network externalities, complementarities, and invitations to enter," European Journal of Political Economy, Elsevier, vol. 12(2), pages 211-233, September.
    12. Sharon G. Levin & Paula E. Stephan & Anne E. Winkler, 2012. "Innovation in academe: the diffusion of information technologies," Applied Economics, Taylor & Francis Journals, vol. 44(14), pages 1765-1782, May.
    13. Hsu, Chin-Lung & Lu, Hsi-Peng & Hsu, Huei-Hsia, 2007. "Adoption of the mobile Internet: An empirical study of multimedia message service (MMS)," Omega, Elsevier, vol. 35(6), pages 715-726, December.
    14. Kauffman, Robert J. & Techatassanasoontorn, Angsana A., 2009. "Understanding early diffusion of digital wireless phones," Telecommunications Policy, Elsevier, vol. 33(8), pages 432-450, September.
    15. Oliva, Rogelio, 2003. "Model calibration as a testing strategy for system dynamics models," European Journal of Operational Research, Elsevier, vol. 151(3), pages 552-568, December.
    16. Mark Paich & John D. Sterman, 1993. "Boom, Bust, and Failures to Learn in Experimental Markets," Management Science, INFORMS, vol. 39(12), pages 1439-1458, December.
    17. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
    18. Evans David S. & Schmalensee Richard, 2010. "Failure to Launch: Critical Mass in Platform Businesses," Review of Network Economics, De Gruyter, vol. 9(4), pages 1-28, December.
    19. Christoph H. Loch & Bernardo A. Huberman, 1999. "A Punctuated-Equilibrium Model of Technology Diffusion," Management Science, INFORMS, vol. 45(2), pages 160-177, February.
    20. Casey, Thomas R. & Töyli, Juuso, 2012. "Mobile voice diffusion and service competition: A system dynamic analysis of regulatory policy," Telecommunications Policy, Elsevier, vol. 36(3), pages 162-174.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kraus, Sascha & Kumar, Satish & Lim, Weng Marc & Kaur, Jaspreet & Sharma, Anuj & Schiavone, Francesco, 2023. "From moon landing to metaverse: Tracing the evolution of Technological Forecasting and Social Change," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    2. Benedict Bender, 2020. "The Impact of Integration on Application Success and Customer Satisfaction in Mobile Device Platforms," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(6), pages 515-533, December.
    3. Andrijana Horvat & Vincenzo Fogliano & Pieternel A Luning, 2020. "Modifying the Bass diffusion model to study adoption of radical new foods–The case of edible insects in the Netherlands," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-23, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Navid Ghaffarzadegan & Richard C. Larson, 2018. "SD meets OR: a new synergy to address policy problems," System Dynamics Review, System Dynamics Society, vol. 34(1-2), pages 327-353, January.
    2. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    3. Grajek, Michał & Kretschmer, Tobias, 2012. "Identifying critical mass in the global cellular telephony market," International Journal of Industrial Organization, Elsevier, vol. 30(6), pages 496-507.
    4. Emanuele Giovannetti & Mohsen Hamoudia, 2022. "The interaction between direct and indirect network externalities in the early diffusion of mobile social networking," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 617-642, December.
    5. Derbyshire, James & Giovannetti, Emanuele, 2017. "Understanding the failure to understand New Product Development failures: Mitigating the uncertainty associated with innovating new products by combining scenario planning and forecasting," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 334-344.
    6. Franses, Philip Hans, 2021. "Modeling box office revenues of motion pictures✰," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    7. Lakka, Spyridoula & Michalakelis, Christos & Varoutas, Dimitris & Martakos, Draculis, 2012. "Exploring the determinants of the OSS market potential: The case of the Apache web server," Telecommunications Policy, Elsevier, vol. 36(1), pages 51-68.
    8. Scaglione, Miriam & Giovannetti, Emanuele & Hamoudia, Mohsen, 2015. "The diffusion of mobile social networking: Exploring adoption externalities in four G7 countries," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1159-1170.
    9. Berrin Aytac & S. Wu, 2013. "Characterization of demand for short life-cycle technology products," Annals of Operations Research, Springer, vol. 203(1), pages 255-277, March.
    10. Day Yang Liu & Wen Chun Tsai & Pei Leen Liu & Chung Yi Fang, 2021. "Determinants of sales revenue in innovation diffusion effects of Taiwan sports lottery during the FIFA World Cup 2018," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(4), pages 43-58, June.
    11. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    12. Vincenzo Vignieri, 2021. "Crowdsourcing as a mode of open innovation: Exploring drivers of success of a multisided platform through system dynamics modelling," Systems Research and Behavioral Science, Wiley Blackwell, vol. 38(1), pages 108-124, January.
    13. Cowan, Kelly R. & Daim, Tugrul U., 2011. "Review of technology acquisition and adoption research in the energy sector," Technology in Society, Elsevier, vol. 33(3), pages 183-199.
    14. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    15. Mercure, Jean-François, 2018. "Fashion, fads and the popularity of choices: Micro-foundations for diffusion consumer theory," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 194-207.
    16. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    17. Kivi, Antero & Smura, Timo & Töyli, Juuso, 2012. "Technology product evolution and the diffusion of new product features," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 107-126.
    18. Stefan N. Groesser & Niklas Jovy, 2016. "Business model analysis using computational modeling: a strategy tool for exploration and decision-making," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 27(1), pages 61-88, February.
    19. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    20. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:118:y:2017:i:c:p:28-43. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.