Firms offer products or services through different strategies. How to optimally price and bundle products is one of the most fundamental questions facing firms when consumers in the market are heterogeneous in their valuations for products. The pricing and bundling problems become more complicated when competition exists or the product is offered through different platforms. Chapter 1 of my dissertation focuses on the quality-differentiated firms’ bundling strategy for their core and add-on products. Motivated by firms’ distinct bundling practices, I build an analytical model to explain the firms’ optimal strategy. I find the critical role of competition and cost-to-quality ratio in driving the asymmetric firm’s bundling and pricing strategy. When there is more competition from the inferior firm, the superior firm has stronger incentive to bundle its add-on, even when the add-on product is costly.

Further in this direction, to study the firm’s pricing and bundling strategy when the product is offered through different mediums, chapter 2 of my dissertation focuses on the content publisher’s optimal strategy when the content can be offered in digital, physical, or a bundle of mediums. I develop an analytical model and find that offering digital medium only or offering bundle and digital medium can be optimal under different market conditions. Surprisingly, I find consumer surplus and social welfare may decrease as the proportion of digital-savvy consumers increases.

To further study the complementarity and substitutability of platforms, chapter 3 of my dissertation studies how firms should run their targeted advertising on different online platforms, i.e. social media and traditional platform. Specifically, I measure the effectiveness of targeted advertising on social media, relative to that on a traditional platform, on consumers’ ultimate conversions. I measure the interaction effects of the two platforms by using case-control design and post-regularized choice models. I find that targeting across platforms is positively associated with the ultimate conversion for the lower funnel, but there is no measurable synergistic effect for the upper funnel consumers.

Why do software firms sell more than one version of software to consumers? In the first chapter, I develop an analytical game theory model to examine a monopolist software firm's motivation of adopting a versioning strategy. We show that consumers' heterogeneity in requirements for software functionality and consumers' disutility from under-provisioning of software functionality are sufficient conditions for a software firm to adopt versioning strategy.

Why do deals have different discount rates on a daily-deal website? In the second chapter, I develop a two-period model to capture the strategic interaction between a daily-deal publisher and a merchant who wants to offer a deal to consumers on the publisher's website. I show that a merchant's optimal discount rate strategy and participation decision depends on the trade-offs between four effects - advertising, sampling, cannibalization and revenue sharing. Moreover, I recommend that a daily-deal publisher should take into account a merchant's marginal cost, proportion of informed consumers and consumer characteristics in formulating an appropriately customized revenue sharing contract for the merchant.

Do consumers benefit from using an online retailer's recommender system? In the third chapter, I develop an analytical framework to examine the optimal recommender system strategy of an online multi-product retailer and the effect of the recommender system on consumer surplus. I find that when the recommender system is relatively accurate, the retailer will recommend products that are never a perfect match to the recipients of the recommendations. I also find that improving the precision of a relatively accurate recommender system leads to a reduction in consumer surplus.