Browsing by Subject "Consumer Search"

The dissertation consists of three chapters related to the low-price guarantee marketing strategy and energy efficiency analysis. The low-price guarantee is a marketing strategy in which firms promise to charge consumers the lowest price among their competitors. Chapter 1 addresses the research question "Does a Low-Price Guarantee Induce Lower Prices'' by looking into the retail gasoline industry in Quebec where there was a major branded firm which started a low-price guarantee back in 1996. Chapter 2 does a consumer welfare analysis of low-price guarantees to drive police indications and offers a new explanation of the firms' incentives to adopt a low-price guarantee. Chapter 3 develops the energy performance indicators (EPIs) to measure energy efficiency of the manufacturing plants in pulp, paper and paperboard industry.

Chapter 1 revisits the traditional view that a low-price guarantee results in higher prices by facilitating collusion. Using accurate market definitions and station-level data from the retail gasoline industry in Quebec, I conducted a descriptive analysis based on stations and price zones to compare the price and sales movement before and after the guarantee was adopted. I find that, contrary to the traditional view, the stores that offered the guarantee significantly decreased their prices and increased their sales. I also build a difference-in-difference model to quantify the decrease in posted price of the stores that offered the guarantee to be 0.7 cents per liter. While this change is significant, I do not find the response in comeptitors' prices to be significant. The sales of the stores that offered the guarantee increased significantly while the competitors' sales decreased significantly. However, the significance vanishes if I use the station clustered standard errors. Comparing my observations and the predictions of different theories of modeling low-price guarantees, I conclude the empirical evidence here supports that the low-price guarantee is a simple commitment device and induces lower prices.

Chapter 2 conducts a consumer welfare analysis of low-price guarantees to address the antitrust concerns and potential regulations from the government; explains the firms' potential incentives to adopt a low-price guarantee. Using station-level data from the retail gasoline industry in Quebec, I estimated consumers' demand of gasoline by a structural model with spatial competition incorporating the low-price guarantee as a commitment device, which allows firms to pre-commit to charge the lowest price among their competitors. The counterfactual analysis under the Bertrand competition setting shows that the stores that offered the guarantee attracted a lot more consumers and decreased their posted price by 0.6 cents per liter. Although the matching stores suffered a decrease in profits from gasoline sales, they are incentivized to adopt the low-price guarantee to attract more consumers to visit the store likely increasing profits at attached convenience stores. Firms have strong incentives to adopt a low-price guarantee on the product that their consumers are most price-sensitive about, while earning a profit from the products that are not covered in the guarantee. I estimate that consumers earn about 0.3% more surplus when the low-price guarantee is in place, which suggests that the authorities should not be concerned and regulate low-price guarantees. In Appendix B, I also propose an empirical model to look into how low-price guarantees would change consumer search behavior and whether consumer search plays an important role in estimating consumer surplus accurately.

Chapter 3, joint with Gale Boyd, describes work with the pulp, paper, and paperboard (PP&PB) industry to provide a plant-level indicator of energy efficiency for facilities that produce various types of paper products in the United States. Organizations that implement strategic energy management programs undertake a set of activities that, if carried out properly, have the potential to deliver sustained energy savings. Energy performance benchmarking is a key activity of strategic energy management and one way to enable companies to set energy efficiency targets for manufacturing facilities. The opportunity to assess plant energy performance through a comparison with similar plants in its industry is a highly desirable and strategic method of benchmarking for industrial energy managers. However, access to energy performance data for conducting industry benchmarking is usually unavailable to most industrial energy managers. The U.S. Environmental Protection Agency (EPA), through its ENERGY STAR program, seeks to overcome this barrier through the development of manufacturing sector-based plant energy performance indicators (EPIs) that encourage U.S. industries to use energy more efficiently. In the development of the energy performance indicator tools, consideration is given to the role that performance-based indicators play in motivating change; the steps necessary for indicator development, from interacting with an industry in securing adequate data for the indicator; and actual application and use of an indicator when complete. How indicators are employed in EPA’s efforts to encourage industries to voluntarily improve their use of energy is discussed as well. The chapter describes the data and statistical methods used to construct the EPI for plants within selected segments of the pulp, paper, and paperboard industry: specifically pulp mills and integrated paper & paperboard mills. The individual equations are presented, as are the instructions for using those equations as implemented in an associated Microsoft Excel-based spreadsheet tool.

This dissertation considers monetization strategies in the context

of online product and display ad marketplaces.

The first chapter considers online marketplace platforms that trade-off

their fees from advertising with commissions from product sales. While

featuring advertised products can make search less efficient (lowering

transaction commissions), it incentivizes sellers to compete for better

placements via advertising (increasing advertising fees). We consider

this trade-off by modeling both sides of the platform. On the demand

side, we develop a joint model of browsing (impressions), clicking,

and purchase. On the supply side, we consider sellers' valuation and

advertising competition under various fee structures (CPM, CPC, CPA)

and ranking algorithms.

Using buyer, seller, and platform data from an online marketplace

where advertising dollars affect the order of seller items listed,

we explore various product ranking and ad pricing mechanisms. We find

that sorting items below the fifth position by expected sales revenue

while conducting a CPC auction in the top 5 positions yields the greatest

improvement in profits (181%) because this approach balances the

highest valuations from advertising in the top positions with the

transaction revenues in the lower positions.

The second chapter considers how a publisher should set reserve prices

for real-time bidding (RTB) auctions when selling display advertising

impressions through ad exchanges. Through a series of field experiments,

we show that a reserve price set based on an imputed demand curve

(in the absence of constraints) can increase publisher's revenues

by 32%, thereby affirming the importance of reserve price in maximizing

publisher's revenues. Further, we find that advertisers increase their

bids in response to an experimental increase in reserve price and

show this behavior is consistent with the use of a minimum impression

constraint to ensure advertising reach.

Based on this insight, we construct an advertiser bidding model and

use it to infer the overall demand curve for advertising as a function

of reserve prices. Using this constraint-based demand model, we solve

the publisher pricing problem. Incorporating the minimum impression

constraint into the reserve price setting process yields a 50% increase

over a solution that does not incorporate the constraint and an additional

increase in profits of 9 percentage points.