Bye-Bye Bundles: The Unbundling of Music in Digital Channels

Elberse, Anita

doi:10.1509/jmkg.74.3.107

Cited by 150 publications

(74 citation statements)

References 55 publications

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“…Our focus on dynamics and complementary goods in a two-sided market as opposed to examining related goods of the same type makes both our methodology and result very different from other empirical work on bundling related to content industries like music and cable TV, where studies have demonstrated that mixed bundling can actually reduce revenues and profitability compared to pure bundling [Crawford, 2008, Elberse, 2010; in contrast, we find that dynamics make bundling more profitable.…”

Section: Related Literaturecontrasting

confidence: 66%

The Dynamic Effects of Bundling as a Product Strategy

Derdenger

Kumar²

2013

Marketing Science

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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.

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Section: Related Literaturecontrasting

confidence: 66%

The Dynamic Effects of Bundling as a Product Strategy

Derdenger

Kumar²

2013

Marketing Science

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“…Second, the digitization of music allows the unbundling of albums and in the digital world customers download singles increasingly. This means that the downloads are not as rewarding as previous CD sales were (Elberse 2010). To address these two problems, there are a number of new distribution concepts, one of which is Music as a Service (MaaS).…”

Section: Introductionmentioning

confidence: 99%

Pricing of Content Services – An Empirical Investigation of Music as a Service

Doerr¹,

Benlian²,

Vetter³

et al. 2010

Lecture Notes in Business Information Processing

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In the last years new concepts of digital music distribution have been developed. One of them is Music as a Service, which provides music streaming over the internet as a service -without transferring ownership for the content. This differentiates Music as a Service from Download to Own, which is used by music download platforms predominantly and is the most widely studied concept in academic research. The aim of this paper is to receive first research implications about customers' attitudes towards MaaS.Based on an empirical survey of 132 Music as a Service users, this research explores the effects of product configurations on consumers' utility and their willingness to pay (WTP) for premium offers. We can show that next to price, contract duration and music quality as the most important product attributes, there is a high WTP for overcoming insufficient mobile internet coverage.

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“…As a discipline, Marketing has relied more on IT, Economics and CS for its data analytics. From channel choice to prices and recommendation systems, music bundling and online reviews, and social networks, interdisciplinary researchers have conducted impactful analytics research [19,28]. Many different sources of data have been used, and there has been substantive mastery of the collection and analysis of Web data.…”

Section: Creating the Policy Analytics Fusionmentioning

confidence: 99%