Eliciting consumer preferences in the presence of free alternatives

and whether the net effect will be positive or negative. Content owners will only be able to use a free, ad-based model as a tool to reach previously inactive consumers and, thereby, ef-fectively segment the market if those factors that will create a lift will dominate over the oth-er factors. An ad-based soth-ervice will only work as a market segmentation tool if it is capable of attracting users who have not been using commercial download services before. If factors that will shift preferences towards ad-based services (e.g., a positive affect and a reduced WTP for incumbents) dominate consumer decision-making and a majority of consumers feel that they can maximize their rent in an ad-funded store, ad-based services will cannibalize customers from incumbents. Assuming that utility-maximizing consumers take into account the behavioral factors discussed, the degree to which a shift occurs will depend on the degree of substitutability between an ad-based service and the incumbent offers. If the two types of business models (pay vs. free models) are too close in their intrinsic value, consumers who had previously been paying for downloading music will abandon the incumbent in favor of the ad-based model. Therefore, the effect of the factors that might shift consumer choice will depend on the degree of substitutability.

Although it would be of interest to test the effect of each of the factors discussed above separately, it is of foremost importance to empirically identify the net effect of those factors that create a lift or shift in the total number of adopters of commercial download offers, re-spectively, as theory does not provide unambiguous predictions about the magnitude of the effects.

1983). CBC mimics real purchase situations more accurately than do traditional rating- or ranking-based conjoint approaches, leading to the assumption that CBC provides more accu-rate responses (Toubia, Hauser, and Simester 2004). An example that was used in our appli-cation to the music market is displayed in Figure 2.

>>> Figure 2 about here <<<

Because the level of analysis is not an individual track or album but is, rather, the busi-ness model, the choice tasks required the respondents to indicate what type of download store would be most preferable. Within one choice set this does not allow for modeling the possi-bility that some consumers might choose to make purchases using different types of business models or to purchase CDs as well. Although we view it as a reasonable assumption that, in general, consumers focus on one type of store or business model, our model also accommo-dates the consideration of multiple business models across several consecutive choice sets.

3.1. Attributes and attribute levels

We decompose music download services and their respective business models into their main characteristics, which we assume to be price, advertising intensity, restrictions through DRM, and catalog size (Table 1). The selection of attributes and levels is based on insights we gained from three sources. (1) We conducted interviews with focus groups prior to the main data collection process that dealt with issues of legally downloading music from the Internet to gain qualitative insights into consumer preferences. (2) We interviewed experts from the industry to learn about the attributes that the managers perceive to be important. (3) To en-sure that no major facet was omitted, we reviewed articles in the popular press and comments that were posted by users in the online versions of relevant articles.

>>> Table 1 about here <<<

3.1.1. Price. The research question requires special consideration of the price variable in the design and estimation of the model. The subscription model, on the one hand, is associated with a monthly subscription fee that is not related to individual titles and does not entitle con-sumers to permanently keep any tracks that were downloaded through the service. The DST model, on the other hand, charges a fee for every track purchased. Thus, the interpretation of a price variable depends on the respective business model. We therefore introduce an alterna-tive-specific variable for price that we term pricesub (pricedst) for the subscription model (DST model). Pricesub (pricedst) is only shown to the respondent if it occurs for an alternative that represents the subscription model (DST model). The specific valuation of a respondent for either business model is thus captured in the corresponding price coefficient. The five levels for the respective price variables (Table 1) enclose the price range that can be observed in the market. To accommodate advertising-funded offerings that are free of charge, the price of € 0 is included as the minimum level.

3.1.2. Advertising. To capture consumer preferences with regard to advertising, we use four attribute levels: no advertising, banner on the site, banner and obligatory disclosure of prefer-ences and personal information, and advertising embedded in music files. These attribute levels capture the options that are generally available for content distributors.

3.1.3. Digital rights management. Due to the fact that restrictions imposed by DRM strongly affect the utility of a music download (Sinha, Machado, and Sellman 2010;

Sundararajan 2004), we include DRM and adapt this attribute to the specific requirements of the respective business models. For the DST model, we incorporate DRM on four different attribute levels. In the case of a subscription-based service, downloads without DRM are not an option because this would render a sustainable business model infeasible due to potential arbitrage. Thus, the attribute level with the highest utility is that at which downloads can be

3.1.4. Catalog size. The utility that consumers associate with a download store is likely to depend on the number of different titles offered by that particular store (Sinha and Mandel 2008). This assumption follows the rationale that consumers do not want to cover their de-mand for music downloads at several different download shops but instead prefer a one-stop-shop that provides a comprehensive selection of artists and titles. We thus include a variable that captures the perceived size of the catalog on four levels (small, medium, large, compre-hensive).

Based on these attributes and attribute levels, we constructed conjoint choice sets consist-ing of three stimuli and a no-choice-option; we used a randomized computer-generated de-sign that accounts for minimal overlap, level balance, and orthogonality (Huber and Zwerina 1996). So as not to overstrain the respondents’ cognitive resources, we assigned eight choice sets to each respondent. Seven of these were used for estimation; one hold-out set (Figure 2) was deployed to test the predictive validity of our model.

3.2. Covariates

Several covariates were included to help characterize respondents and the resulting segments because the estimation is enriched with information that is not directly contained in the choice behavior. The questionnaire covered aspects that relate primarily to three conceptual domains. (1) The “theory of planned behavior” has proven powerful in explaining and help-ing us to understand future behavior, includhelp-ing the adoption of innovations (Ajzen 1991; Tay-lor and Todd 1995)—hence, the theory’s constructs attitude (towards DST and subscription models, respectively), perceived behavioral control, and subjective norm (to adopt any com-mercial download store) are included. (2) Rogers (2004) identified several product character-istics that determine whether an innovation is likely to be adopted. Based on previous re-search (Taylor and Todd 1995), we include these innovation criteria as the perceived degree of relative advantage, complexity, and compatibility of commercial downloads. Note that

these variables do not pertain to specific download stores but rather to the concept of obtain-ing music from commercial download stores. We extend these variables via constructs that pertain to the perceived risk of adopting a download service, the perceived critical mass (Van Slyke et al. 2007), and consumers’ price sensitivity (Ofir 2004). (3) We control for music usage habits by asking respondents to indicate, for example, how much time they spend on listening to music, their budget for music purchases, and how important they view the oppor-tunity to permanently keep the tracks. Because the choice of a legal download service will probably be affected by the likelihood of an individual’s engaging in illegal file-sharing that, however, is hard to measure, we computed a measure that relates the number of files stored on a computer to the annual downloading budget. We use this measure as a proxy of the in-clination to use the computer to consume music that was obtained from other sources. These may include illegitimate file-sharing as well as files copied from previously purchased CDs.

A list of all items can be found in the Appendix.