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

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 (nonsuperstars), 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)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(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.

Sustaining Complement Quality for Digital Product Platforms: A Case Study of the Philips Hue Ecosystem

“…Our findings suggest that a relational and dynamic conceptualization of complement quality is particularly important for studying digital product ecosystems. Prior research that operationalized complement quality through single measurements of user or expert ratings (Binken and Stremersch, 2009; Cennamo et al, 2018; Gretz et al, 2019) was primarily focused on earlier generations of video game consoles and games. These were less subject to dynamics of complement quality as these platforms and complements were only updated through discrete next‐generation of the ecosystem and did not allow for continuous updating.…”

“…Prior research juxtaposed platform quality against (indirect) network effects as separate competitive forces (e.g., McIntyre, 2011; Tellis, Yin, and Niraj, 2009). The few studies on complement quality and network effects only studied complement quality as a driver for platform growth (e.g., Binken and Stremersch, 2009; Gretz et al, 2019). Our study suggests that quality might also have a negative influence on network effects: quality problems of complements can make them less attractive for users.…”

“…Complements differ in the value they provide for the platform ecosystem. Some complements are “superstars” that generate high sales, thereby stimulating platform growth (Binken and Stremersch, 2009; Gretz et al, 2019). Furthermore, when users experience high‐quality complements, they may also buy other complementary products because they anticipate that their quality will be high too (Cennamo and Santalo, 2019).…”

“…Complement quality refers to the functionality that a specific complement adds to a platform and how smoothly it interoperates with the platform core (Cennamo, Ozalp, and Kretschmer, 2018; Cennamo and Santalo, 2019). The few available empirical studies on complement quality treated it as a fixed characteristic, as, for instance, reflected in an average customer review score (Binken and Stremersch, 2009; Cennamo, 2018; Gretz, Malshe, Bauer, and Basuroy, 2019). Other studies documented how platform owners can ensure complement quality at the time of their introduction (e.g., Ghazawneh and Henfridsson, 2013; Tiwana, 2015a).…”

Platform Exploitation: When Service Agents Defect with Customers from Online Service Platforms

“…Very little research has discussed platform exploitation, a gap with important implications for building theory about relationships between platforms and their ecosystem members (e.g., service agents) (Eckhardt et al 2019). Previous platform and two-sided market research take a perspective that largely emphasizes the symbiotic relationship of the two sides-for example, how ecosystem members and platforms help each other (Gretz et al 2019;Luo et al 2021). However, our research introduces a perspective that stresses the friction between the two.…”