When choosing auction mechanisms sellers can decide how much information to reveal to buyers regarding the quality of the goods sold. Using a field experiment in a market for wholesale automobile auctions we are able to measure the effects of information on auction outcomes. We create random assignments of information about quality, and manipulate the availability of information over time. Our results suggest that, as the theoretical literature generally predicts, more information increases expected revenues. Furthermore, by measuring the effects on different quality grades of automobiles it seems like the increase in revenues are due to more competition for any given vehicle. Finally, we quantify the value of gathering information and releasing it to potential buyers in this setup. JEL classifications C93, D44, D82, L15.

Chapter 1 examines the strategic conditions that drive entrepreneurial innovators to pursue novel innovation rather than innovation that is closer to existing technologies. To an increasing extent, startups commercialize innovation in a cooperative setup. Because radical breakthrough innovation is more difficult to communicate than its incremental counterpart, entrepreneurial innovators may avoid breakthrough innovation for which the cost of developing credible information is exceedingly high. In the context of the Orphan Drug Act (ODA), this study uses a difference-in-difference approach to measure whether entrepreneurs are more likely to bring novel innovations to the market when the policy change unexpectedly lowers the cost of obtaining information that will convince investors through a small market test. Using a new measure of the novelty of innovation and a detailed panel dataset of therapeutic molecules, this empirical study finds that biotech startups bring more breakthrough drugs to markets affected by ODA. This research also finds that in ODA-affected areas, entrepreneurs hold novel projects longer before contracting with partners and aim to generate more revenue streams from pursuing novel innovation. Taken together, the results of this study suggest that the cost of convincing investors prevents entrepreneurs from marketing novel innovation and that a public policy can moderate inefficiency in the “market for ideas” by decreasing communication costs.

In Chapter 2, I study the impact of complementary assets on the form of partnership between innovative startups and established firms seeking technology commercialization. As startups develop complementary assets, the small innovating firms increasingly take active parts in advanced-stage development processes, which enables small firms to better convince partners of the prospect of innovations. At the same time, the new asset acquisition makes them less dependent on the partnership with established firms. In the context of ODA, I find that biotech firms are more likely to engage in partnership during clinical trial stage rather than during pre-clinical stage. The delay of partnership suggests that startup firms advance their innovations further so that they can convey rich information on the prospect of drugs to potential partners. I find evidence that the propensity of licensing increases in a group of molecules disproportionately impacted by ODA. Lastly, this study documents that the relationship between licensing and drug approval outcomes becomes less tight, although the approval of novel drugs appears to still heavily depend on the commercialization capabilities of licensing partners.

In Chapter 3, I study how ODA affects the timing and the feature of investments of venture capitalists (VCs). VCs invest in innovations at nascent stage, which inherently incorporates huge risks. Because it is difficult to valuate the prospect of novel technologies at the early development stage, however, VCs may be herded into finance advanced-stage projects for which an archive of scientific knowledge and commercial performances necessary for a correct valuation is available. An institutional change can steer the investors toward supporting new innovations at early stage, by providing more information necessary to valuate the young projects. In the context of ODA, I find that VCs are more likely to invest in early-stage technologies. To reduce the risk of failure, moreover, firms invest in a team rather than putting a huge amount into a round being a sole investor. Finally, I document that the exit performances of VC-backed startups do not get worse as a result of VCs investing into early-stage innovations. It suggests that VCs are enabled to make fully-informed decisions thanks to information provided by ODA, rather than merely speculate on risky and highly uncertain projects.

Chapter one examines the effects of bundling social incentives with promotions. When

using these “social promotions,” a firm must decide whether or not to require customers to

share the promotion on social media with friends. On the one hand, this requirement may make

it easier for the firm to get the word out. On the other hand, this requirement may inconvenience

customers and lower their propensity to purchase. To conduct valid inference on this trade-off

between the costs and benefits, I devise novel empirical strategies that flexibly accommodate

the amount of information available to a firm. Through a field experiment on a Chinese online

grocery site, randomized both at the city and individual level, I find that social promotions

can serve as an effective growth strategy. The social obligation can benefit a firm through two

channels. First, the customers who do share add additional value through both new customer

acquisition and existing customer retention. Second, the firm does not lose profit from the

customers who choose not to purchase the promoted products when forced to share (but would

otherwise purchase the promoted products without mandatory sharing); they contribute instead

by purchasing other substitutes from the same site. Furthermore, different types of customers

respond to the social incentive differently and I present results on customer heterogeneity.

Chapter two expands on the targeting question in social promotions. This paper examines

how a firm should target a social incentive on top of a standard promotion, i.e. also requiring

the customer to share the promotion with friends on social media to qualify for the discounts.

A major challenge in this targeting question is that the targeting decision on a focal customer

also affects how many leads will be generated. Therefore, tackling this targeting question

requires a different framework compared with that of standard targeting. This paper compare

a few targeting schemes, including a post-experiment strategy based on an “effective” profit

idea and two contextual bandits that balance exploration and exploitation real time, namely

LinUCB and LinTS.We find that in our offline simulations, the two contextual bandits perform

similarly and better than post-experiment targeting. Targeting the social incentive to certain

type of customers can significantly increase firm profitability.

Chapter three discusses an empirical case study on bundle design and pricing. Unlike what

conventional bundle pricing theory suggests, we find that on the largest Chinese e-commerce

platform Taobao.com, a bundle tends to cost more than purchasing each bundle item from the

same online market separately. These bundle premiums are prevalent in multiple product categories,

such as digital cameras, iPads, cell-phones, and video game consoles. Conservatively

speaking, in the digital single-lens reflex cameras market, “premiumed bundles” account for

30% of the market share. Furthermore, the magnitude of the premium is also beyond that of rational

expectation. For example, for Canon 700D bundles, the average premium is 17 USD, or

4% the base good price. These bundle premiums can have significant implications for consumer

welfare and platform design. This paper systematically documents these empirical regularities.