Abstract
In the technology and design industries, one product builds on another: A smart television enhances a smart phone. However, due to complementary features, the utility that is gained by owning both products from the same firm is greater than the sum of the two products’ utility if purchased from separate firms. Aftermarkets suggest that the margins of the second product would increase. Instead, we show that the firms’ complementary utility offset each other, which results in reduced prices. Further, consumer purchase behavior is a function of the product release order; given a different release schedule, some consumers would purchase from a different company.
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Notes
We use the term ‘psychological factors’ to describe purchase decisions that are driven by non-concrete benefits. We do not mean the term negatively. We simply mean that purchases that are driven by psychological factors might be more driven by the marketing department than by the engineering department.
See Sect. 5 for more examples from different industries.
For a literature review of aftermarkets, see Ellison (2005).
Some bonus utility would be costly for the firm to avoid even if the firms did not want to provide it. For instance, software firms could choose to have very different user interfaces across products instead of similar interfaces. The firms would likely always choose to have similar interfaces when targeting similar consumers, as this would: require less effort for the design team; result in fewer support calls as consumers would be more familiar with the product; and would be in their customers’ best interest.
In particular, a two-period model of switching cost with: (1) myopic consumers; (2) forward looking firms; and (3) full independence of product preferences (Villas-Boas, 2015) It is important to note, however, that even when there is a convergence in the outcomes of the models, the outcomes are driven by different underpinnings.
Product A is simply the product that is released first, while product B is the product that is released second.
The assumption of myopic consumers, which is standard in the switching cost and path dependence literature (see, for instance, Cabral & Villas-Boas, 2005; Dubé et al., 2009), is reasonable, since many of the applications for which the paper is relevant are durable goods (see Sect. 5 for details), in which case consumers are not always aware of future releases of new products, developments of product categories, and, most importantly, the nature and extent of integration between a company’s line of products (a source of bonus utility). Nonetheless, in Sect. 4 we explore the equilibrium behavior when consumers are sophisticated, and we show that our main results that are reported in this section remain qualitatively unaffected.
Our model does not consider the potential for pirated goods or open-source alternatives (to be clear, we do not consider piracy and open-source alternatives to be the same thing only that they might act on the model in a similar way). Many of our example products are durable goods where piracy is difficult and open-source alternatives are scarce. Nonetheless, in software both do exist. For simplicity, we are ignoring these alternatives.
Using quadratic transport costs, we find no qualitative difference in our main result: Similar to the model that is presented here, the final prices for the model with quadratic costs are \(p_{1A}^* = p_{2A}^* = c_A + t_A - \mu \), and \(p_{1B}^* = p_{2B}^* = c_B + t_B\). The indifferent consumer final solutions in Eqs. (1), (2), and (3) are identical regardless of whether the transport costs are specified linearly or quadratically.
In our baseline model, firms choose prices for both markets at the beginning of the game. In Sect. 3, we demonstrate the robustness of this assumption by considering a two-period market, whereby firms decide on prices in the market for product A in the first period and for product B in the second period. The results from the two-period analysis corroborate those that are presented in this section.
The first-period price reduction is not obvious given \(\Omega \) and \(\Phi \) in Eq. (6). However, \(\Omega + \Phi \) simplifies to \(2t_A\). Therefore, given the remainder of the price equation, the firms are net charging a lower price in market A. This holds true both for a simple average of market A prices and for a market-share-weighted average of prices as more consumers will purchase from the less expensive firm.
For more information, see https://www.cnet.com/news/smartthings-to-control-samsungs-smart-appliances/.
Sampling plays a role in this behavior as well. The purchaser gains more information as a result of the first purchase (e.g. book) and will be more informed when purchasing the second good. Bonus utility increases the likelihood the purchaser will buy the second good from the same producer. However, if the purchaser did not like the first good, this may encourage them to purchase the second good from a different producer.
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The authors are extremely grateful to the Editor, Lawrence J. White, and the anonymous referees for their extremely helpful feedback. The authors thank Southern Economics Conference participants, Leif Lundmark, and Dustin White for their valuable feedback.
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Akhundjanov, S.B., Smith, B.O. & St. Brown, M. Path Dependence as a Path to Consumer Surplus and Loyalty. Rev Ind Organ 63, 1–20 (2023). https://doi.org/10.1007/s11151-023-09904-2
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DOI: https://doi.org/10.1007/s11151-023-09904-2