IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v200y2025ics0148296325004643.html

Secret power of the product ecosystem: A network perspective from the case of Apple

Author

Listed:
  • Chang, Jung-Hua

Abstract

From a network theory perspective, this study examines the Apple product ecosystem, conceptualized as a network of products connected through native applications. It investigates how this ecosystem influences users’ ecosystem loyalty intention and brand identification through customer value (functional, emotional, and social value) and switching costs (transition and sunk costs). Empirical results demonstrate that both the product tie degree and ecosystem density significantly affect customer value and switching costs. Furthermore, the study reveals that the product ecosystem indirectly impacts ecosystem loyalty intention and brand identification differently through these factors. Importantly, it confirms that switching costs exert a stronger influence than customer value within the ecosystem. These findings contribute to advancing research on product ecosystems and network theory and provide practical implications for marketers aiming to enhance customer retention and brand engagement through interconnected product strategies.

Suggested Citation

  • Chang, Jung-Hua, 2025. "Secret power of the product ecosystem: A network perspective from the case of Apple," Journal of Business Research, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:jbrese:v:200:y:2025:i:c:s0148296325004643
    DOI: 10.1016/j.jbusres.2025.115641
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296325004643
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2025.115641?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    2. 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.
    3. Yifan Dou & Marius F. Niculescu & D. J. Wu, 2013. "Engineering Optimal Network Effects via Social Media Features and Seeding in Markets for Digital Goods and Services," Information Systems Research, INFORMS, vol. 24(1), pages 164-185, March.
    4. Baohong Sun & Jinhong Xie & H. Henry Cao, 2004. "Product Strategy for Innovators in Markets with Network Effects," Marketing Science, INFORMS, vol. 23(2), pages 243-254, October.
    5. Ma, Ruijing & Wang, Weisha, 2021. "Smile or pity? Examine the impact of emoticon valence on customer satisfaction and purchase intention," Journal of Business Research, Elsevier, vol. 134(C), pages 443-456.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Büyükdağ, Naci & Kitapci, Olgun, 2021. "Antecedents of consumer-brand identification in terms of belonging brands," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    8. Luyan Su & Ying Li & Wenli Li, 2019. "Understanding Consumers’ Purchase Intention for Online Paid Knowledge: A Customer Value Perspective," Sustainability, MDPI, vol. 11(19), pages 1-19, September.
    9. Chengli Shu & Kevin Z. Zhou & Yazhen Xiao & Shanxing Gao, 2016. "How Green Management Influences Product Innovation in China: The Role of Institutional Benefits," Journal of Business Ethics, Springer, vol. 133(3), pages 471-485, February.
    10. Loureiro, Sandra Maria Correia & Friedmann, Enav & Breazeale, Michael & Middendorf, Ivo, 2023. "How can brands encourage consumers to donate data to a data-driven social partnership? An examination of hedonic vs. functional categories," Journal of Business Research, Elsevier, vol. 164(C).
    11. Sheth, Jagdish N. & Newman, Bruce I. & Gross, Barbara L., 1991. "Why we buy what we buy: A theory of consumption values," Journal of Business Research, Elsevier, vol. 22(2), pages 159-170, March.
    12. Sullivan, Yulia W. & Kim, Dan J., 2018. "Assessing the effects of consumers’ product evaluations and trust on repurchase intention in e-commerce environments," International Journal of Information Management, Elsevier, vol. 39(C), pages 199-219.
    13. Aron Culotta & Jennifer Cutler, 2016. "Mining Brand Perceptions from Twitter Social Networks," Marketing Science, INFORMS, vol. 35(3), pages 343-362, May.
    14. Christophe Van den Bulte & Stefan Stremersch, 2004. "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test," Marketing Science, INFORMS, vol. 23(4), pages 530-544, July.
    15. Henderson, Geraldine R. & Iacobucci, Dawn & Calder, Bobby J., 1998. "Brand diagnostics: Mapping branding effects using consumer associative networks," European Journal of Operational Research, Elsevier, vol. 111(2), pages 306-327, December.
    16. He, Hongwei & Li, Yan & Harris, Lloyd, 2012. "Social identity perspective on brand loyalty," Journal of Business Research, Elsevier, vol. 65(5), pages 648-657.
    17. Sabine Matook & Susan A Brown & Johanna Rolf, 2015. "Forming an intention to act on recommendations given via online social networks," European Journal of Information Systems, Taylor & Francis Journals, vol. 24(1), pages 76-92, January.
    18. Jones, Michael A. & Mothersbaugh, David L. & Beatty, Sharon E., 2002. "Why customers stay: measuring the underlying dimensions of services switching costs and managing their differential strategic outcomes," Journal of Business Research, Elsevier, vol. 55(6), pages 441-450, June.
    Full references (including those not matched with items on IDEAS)

    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. Surya Pathak & P. V. Sundar Balakrishnan, 2025. "The paradox of product scarcity: Catalyzing the speed of innovation diffusion," Journal of the Academy of Marketing Science, Springer, vol. 53(3), pages 804-824, May.
    2. Laciana, Carlos E. & Rovere, Santiago L. & Podestá, Guillermo P., 2013. "Exploring associations between micro-level models of innovation diffusion and emerging macro-level adoption patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1873-1884.
    3. Ravi Bapna & Akhmed Umyarov, 2015. "Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks," Management Science, INFORMS, vol. 61(8), pages 1902-1920, August.
    4. Nejad, Mohammad G. & Amini, Mehdi & Babakus, Emin, 2015. "Success Factors in Product Seeding: The Role of Homophily," Journal of Retailing, Elsevier, vol. 91(1), pages 68-88.
    5. Zhang, Honghong & Fam, Kim-Shyan & Goh, Tiong-Thye & Dai, Xin, 2018. "When are influentials equally influenceable? The strength of strong ties in new product adoption," Journal of Business Research, Elsevier, vol. 82(C), pages 160-170.
    6. Alzate, Miriam & Arce-Urriza, Marta & Cebollada, Javier, 2022. "Mining the text of online consumer reviews to analyze brand image and brand positioning," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    7. Alexei Parakhonyak & Nick Vikander, 2019. "Optimal Sales Schemes for Network Goods," Management Science, INFORMS, vol. 65(2), pages 819-841, February.
    8. repec:plo:pone00:0206736 is not listed on IDEAS
    9. Landsman, Vardit & Nitzan, Irit, 2020. "Cross-decision social effects in product adoption and defection decisions," International Journal of Research in Marketing, Elsevier, vol. 37(2), pages 213-235.
    10. Chandrasekaran, Deepa & Arts, Joep W.C. & Tellis, Gerard J. & Frambach, Ruud T., 2013. "Pricing in the international takeoff of new products," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 249-264.
    11. Yansong Hu & Christophe Van den Bulte, 2014. "Nonmonotonic Status Effects in New Product Adoption," Marketing Science, INFORMS, vol. 33(4), pages 509-533, July.
    12. Abedi, Vahideh Sadat & Eslami, Hossein, 2025. "Aggregate vs micromodels for forecasting the diffusion of new technologies," Technological Forecasting and Social Change, Elsevier, vol. 219(C).
    13. Yujuico, Emmanuel, 2015. "Considerations in the diffusion of a public traffic app for Metro Manila," Journal of Transport Geography, Elsevier, vol. 42(C), pages 48-56.
    14. Büyükdağ, Naci & Kitapci, Olgun, 2021. "Antecedents of consumer-brand identification in terms of belonging brands," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    15. Steven M. Shugan, 2005. "Brand Loyalty Programs: Are They Shams?," Marketing Science, INFORMS, vol. 24(2), pages 185-193.
    16. Bhukya, Ramulu & Paul, Justin, 2023. "Social influence research in consumer behavior: What we learned and what we need to learn? – A hybrid systematic literature review," Journal of Business Research, Elsevier, vol. 162(C).
    17. Carlson, Jamie & Rahman, Mohammad M. & Taylor, Alexander & Voola, Ranjit, 2019. "Feel the VIBE: Examining value-in-the-brand-page-experience and its impact on satisfaction and customer engagement behaviours in mobile social media," Journal of Retailing and Consumer Services, Elsevier, vol. 46(C), pages 149-162.
    18. Yeh, Ching-Hsuan & Wang, Yi-Shun & Yieh, Kaili, 2016. "Predicting smartphone brand loyalty: Consumer value and consumer-brand identification perspectives," International Journal of Information Management, Elsevier, vol. 36(3), pages 245-257.
    19. Yang Li & Dandan Yang & Yingying Liu, 2021. "The Effect of Message Framing on Consumers’ Intentions to Purchase Recycling-Aiding Products in China," Sustainability, MDPI, vol. 13(12), pages 1-17, June.
    20. Meyners, Jannik & Barrot, Christian & Becker, Jan U. & Bodapati, Anand V., 2017. "Reward-scrounging in customer referral programs," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 382-398.
    21. Tarnanidis, Theodore & Owusu-Frimpong, Nana & Nwankwo, Sonny & Omar, Maktoba, 2015. "Why we buy? Modeling consumer selection of referents," Journal of Retailing and Consumer Services, Elsevier, vol. 22(C), pages 24-36.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jbrese:v:200:y:2025:i:c:s0148296325004643. 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.elsevier.com/locate/jbusres .

    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.