The Dynamic Effects of Bundling as a Product Strategy

Abstract

Several key questions in bundling have not been empirically examined: Is mixed bundling more effective than pure bundling or pure components? Does correlation in consumer valuations make bundling more or less effective? Does bundling serve as a complement or substitute to network effects? To address these questions, we develop a consumer-choice model from micro-foundations to capture the essentials of our setting, the handheld video game market. We provide a framework to understand the dynamic, long-term impacts of bundling on demand. The primary explanation for the profitability of bundling relies on homogenization of consumer valuations for the bundle, allowing the firm to extract more surplus. We find bundling can be effective through a novel and previously unexamined mechanism of dynamic consumer segmentation, which operates independent of the homogenization effect, and can in fact be stronger when the homogenization effect is weaker. We also find that bundles are treated as separate products (distinct from component products) by consumers. Sales of both hardware and software components decrease in the absence of bundling, and consumers who had previously purchased bundles might delay purchases, resulting in lower revenues. We also find that mixed bundling dominates pure bundling and pure components in terms of both hardware and software revenues. Investigating the link between bundling and indirect network effects, we find that they act as substitute strategies, with a lower relative effectiveness for bundling when network effects are stronger.

Intertemporal Price Discrimination with Complementary Products: E-Books and E-Readers

“…It also includes demographics such as household income, age, family size, zip code, etc. 6 Consumers were re-sampled every year. There are 20,637 households and 72,619 book purchases.…”

“…It is weighted so that the distribution of the demographics matches that of the U.S. Internet user population. 6 The income and age information is in terms of groups. Consumers are categorized into three income groups and three age groups.…”

Economic Value of Celebrity Endorsements: Tiger Woods' Impact on Sales of Nike Golf Balls

“…Even consumer packaged goods can display signicant dynamics due to learning or inventory eects, as is well known from individual-level models estimated from household panels. Another important setting includes the purchase of technology products, which causes signicant interdependencies between hardware and software [Melnikov, 2013, Derdenger and Kumar, 2013, Derdenger, 2014. Thus, intertemporal eects are highly important across a wide variety of settings in marketing and economics, and our aim is to provide a method that enables a highly tractable approach to such settings, which includes incorporating both observable and unobservable states evolving over time, and the exibility to model evolution for each product separately, unlike the current state-of-the-art approach for aggregate data.…”

“…Due to its advance in dealing with a challenging problem, the approach has been recently used across a range of dynamic settings, including an investigation of how consumers tradeo between new and used cars [Schiraldi, 2011], the dynamic impacts of bundling as a product strategy Derdenger and Kumar [2013], and consumer hardware and software purchases in settings with technological tying [Derdenger, 2014], as well as in storable CPG goods with individual-level data [Hendel and Nevo, 2006a].…”

Some economics of the movie industry

“…This idea is relatively general and should apply beyond DVD sales. In fact, as Derdenger and Kumar () show, a similar phenomenon takes place in the video‐game industry (where games are bundled with game consoles).…”