Diffusion of a new product under network effects: the US DVD market

Inceoglu, Firat; Park, Minsoo

doi:10.1080/00036846.2010.498358

Cited by 9 publications

(6 citation statements)

References 14 publications

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“…First, empirical research on system markets has focused on detecting the indirect network effects of various entertainment products, including DVDs (Inceoglu & Park, 2011), computer hardware and software (Frels, Shervani, & Srivastava, 2003), CDs (Basu, Mazumdar, & Raj, 2003), VCRs (Park, 2004), and home video games (Chintagunta, Nair, & Sukumar, 2009). To date, direct network effects have been rarely considered (e.g.…”

Section: Introductionmentioning

confidence: 99%

Platform adoption in system markets: The roles of preference heterogeneity and consumer expectations

Steiner

Wiegand

Eggert

et al. 2016

International Journal of Research in Marketing

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Section: Introductionmentioning

confidence: 99%

Platform adoption in system markets: The roles of preference heterogeneity and consumer expectations

Steiner

Wiegand

Eggert

et al. 2016

International Journal of Research in Marketing

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“…Recent studies have criticized earlier research that examined demand-side effects without controlling for the endogeneity of title availability (e.g., Dubé, Hitsch & Chintagunta, 2010;Gretz, 2010;Inceoglu & Park, 2011;Zhu & Iansiti, 2012;Kim, Prince & Qiu, 2014). In a reanalysis of the data from nine consumer electronic product categories, Stremersch et al (2007) compared the relative importance of the supply and demand effects.…”

Section: Attributes Of Ine Softwarementioning

confidence: 99%

“…They concluded that software availability typically followed hardware sales, while 'the reverse almost never happens' (Stremersch et al, 2007, p. 68). However, more recent studies focusing on specific categories have found evidence supporting the existence of demand effects in the markets for home video games (e.g., Corts & Lederman, 2009;Dubé, Hitsch & Chintagunta, 2010;Gretz, 2010;Zhu & Iansiti, 2012;Kim, Prince & Qiu, 2014) and DVD players (e.g., Inceoglu & Park, 2011).…”

Section: Attributes Of Ine Softwarementioning

confidence: 99%

“…For example, the value of a CD player is a function of the number of CDs that can be used with that player (Basu, Mazumdar & Raj, 2003). Similarly, the value of a DVD player depends on the number of movies available in the DVD format (Inceoglu and Park, 2011), and the value of gaming hardware depends on the number of available games (Shankar & Bayus, 2003). Given this interdependence between hardware and complementary products, the customer's hardware adoption decision depends on the benefits of the product bundle, which consists of the hardware plus any software that the adopter plans to use with that hardware (Gupta, Jain & Sawhney, 1999).…”

Section: Introductionmentioning

confidence: 99%

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The Adoption of Electronic Innovations with Indirect Network Externalities that Compete with Standalone Physical Products

Kawakami¹,

Parry²

2015

Creat Innov Manage

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The authors consider how a change in product form impacts the adoption decision for an innovative product based on digital technology. Examples of changes in product form often arise in products that feature indirect network externalities, such as MP3 players, PDAs and e-readers. Existing research suggests that, for innovations with indirect network externalities, the consumer's hardware adoption decision is influenced by the availability of complementary products. However, these studies of complementary products tend to focus on products that exist only as complementary products, such as DVDs, CDs, and video games. This research focuses on the case of an innovative hardware product that uses digital complementary products that compete with standalone versions of the same products. The authors argue that high levels of experience with a standalone product that competes with an innovative hardware/software bundle should increase the consumer's appreciation of (1) the utilitarian benefits of the hardware/software bundle and (2) the hedonic benefits of the standalone product, some of which may not be transferable to the electronic hardware. An analysis of data collected from 549 potential adopters of e-readers in Japan support these hypotheses. The findings have important implications for the design and marketing of digital innovations that involve a change in product form.

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“…The interacting mechanism of indirect network effects can be represented explicitly by using two simultaneous equations: The purchase probability for the main product is expressed as a function of the availability of complementary goods, which, in turn, is specified as a function of the number of consumers using the main product. This technique has been used to examine indirect network effects for digital TVs (Gupta, Jain, and Sawhney, 1999), CD players (Le Nagard‐Assayag and Manceau, 2001), video recorders/DVD players (Inceoglu and Park, 2003; Karaca‐Mandic, 2004; Ohashi, 2003), and personal digital assistants (Nair, Chintagunta, and Dubé, 2004).…”

Section: Review Of the Diffusion‐modeling And The Utility‐based Approachmentioning

confidence: 99%

Sales Forecasting in High-Technology Markets: A Utility-Based Approach

Decker

Gnibba-Yukawa

2010

Journal of Product Innovation Management

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Accurate sales projections are of vital importance to the profitability and long-term survival of high-tech companies. This is especially true in the growth stage of product innovation, because major investments and marketing decisions are made in this phase. By examining recent empirical studies focusing on consumer behavior in high-technology markets, several factors are identified that can affect individual buying decisions and aggregate sales, namely, interpersonal communication, democratization of innovation, direct and indirect network effects, forward-looking behavior, and consumer heterogeneity. Against this background the diffusion-modeling and the utility-based approach are reviewed in terms of their basic conception and their applicability to the markets concerned. Based on this investigation a sales forecasting model for high-tech products, specifically in the growth stage, is developed. The model has a utility-theoretic background and a logistic structure. Since data are scarce in this early stage of the product life cycle two versions of the new approach are discussed, an extended version considering forward-looking behavior and a more parsimonious (''myopic'') one. The performance of the new model is demonstrated using real sales data on the CD player, the DVD player/recorder, and the digital camera market. The empirical comparisons include alternative specifications of the Bass diffusion model as well as a proportional hazard model and consist of two steps. First, the models are checked as to whether they are able to represent the sales data at all. It is shown that both versions of the proposed model are at least equivalent, if not superior, to the models used as benchmarks in terms of fit. In the next step, the models are applied to predict future sales in the three markets. The resulting forecasts show that the proposed model performs significantly better than its benchmarks. Its parsimony enables reliable predictions, even in cases, where only short time series are available for parameter estimation. The model is able to anticipate decreasing diffusion rates as they occur at the end of the growth stage and, thus, helps to avoid overoptimistic sales forecasts, which may cause severe economic damages. The new approach is easy to calibrate and can be applied without specialized econometric expertise.

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Diffusion of a new product under network effects: the US DVD market

Cited by 9 publications

References 14 publications

Platform adoption in system markets: The roles of preference heterogeneity and consumer expectations

Platform adoption in system markets: The roles of preference heterogeneity and consumer expectations

The Adoption of Electronic Innovations with Indirect Network Externalities that Compete with Standalone Physical Products

Sales Forecasting in High-Technology Markets: A Utility-Based Approach

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