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The impact of superstar and non-superstar software on hardware sales: the moderating role of hardware lifecycle

Author

Listed:
  • Richard T. Gretz

    (The University of Texas at San Antonio One UTSA Circle)

  • Ashwin Malshe

    (The University of Texas at San Antonio One UTSA Circle)

  • Carlos Bauer

    (The University of Alabama)

  • Suman Basuroy

    (The University of Texas at San Antonio One UTSA Circle)

Abstract

In the context of two-sided markets, we propose hardware lifecycle as a key moderator of the impact of superstar and non-superstar software on hardware adoption. A hardware’s earlier adopters are less price sensitive and have a higher preference for exciting and challenging software. In contrast, later adopters are more price sensitive and prefer simplicity in software. Superstar software tend to be more expensive and more complex compared to non-superstars. Therefore, earlier (later) adopters prefer superstars (non-superstars), which leads to higher impact of superstars (non-superstars) on hardware adoption in the early (later) stages of the hardware lifecycle. Using monthly data over a 12-year timeframe (1995–2007) from the home video game industry, we find that both superstar and non-superstar software impact hardware demand, but they matter at different points in the hardware lifecycle. Superstars are most influential when hardware is new, and this influence declines as hardware ages. In contrast, non-superstar software has a positive impact on hardware demand later in the hardware lifecycle, and this impact increases with hardware age. Findings reveal that eventually the amount of available non-superstar software impacts hardware adoption more than the amount of available superstar software. We provide several managerial implications based on these findings.

Suggested Citation

  • Richard T. Gretz & Ashwin Malshe & Carlos Bauer & Suman Basuroy, 2019. "The impact of superstar and non-superstar software on hardware sales: the moderating role of hardware lifecycle," Journal of the Academy of Marketing Science, Springer, vol. 47(3), pages 394-416, May.
    • Handle: RePEc:spr:joamsc:v:47:y:2019:i:3:d:10.1007_s11747-019-00631-3
    DOI: 10.1007/s11747-019-00631-3
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