This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

Displaying 1 - 2 of 2
Filtering by

Clear all filters

154454-Thumbnail Image.png
Description
In two independent and thematically connected chapters, I investigate consumers' willingness to pay a price premium in response to product development that entails prosocial attributes (PATs), those that allude to the reduction of negative externalities to benefit society, and to an innovative participatory pricing design called 'Pay-What-You-Want' (PWYW) pricing, a

In two independent and thematically connected chapters, I investigate consumers' willingness to pay a price premium in response to product development that entails prosocial attributes (PATs), those that allude to the reduction of negative externalities to benefit society, and to an innovative participatory pricing design called 'Pay-What-You-Want' (PWYW) pricing, a mechanism that relinquishes the determination of payments in exchange for private goods to the consumers themselves partly relying on their prosocial preferences to drive positive payments. First, I propose a novel statistical approach built on the choice based contingent valuation technique to estimate incremental willingness to pay (IWTP) for PATs that accounts for consumer heterogeneity, dependence in the decision making processes, and incentive compatibility. I validate the approach by estimating IWTP for a variety of PATs and contrast the theoretical and managerial benefits of using the proposed approach over extant techniques used in the literature for this purpose. Second, I propose a general and flexible statistical modeling framework for estimating PWYW payments that exceed zero. It relies on the joint estimation of three types of consumer decision processes namely, the consumer propensity to default to an explicit price recommendation, the propensity to pay a least legitimate price, and the payment of a freely-chosen non-zero payment. Of particular interest is the model's ability to account for a wide variety of design constraints such as the setting of price bounds, explicit price recommendations, and the provision of a menu of discrete prices to choose from. I validate the approach by estimating PWYW payments for a variety of products such as music licenses, snacks, and sports tickets. I specifically examine and report the differential impact of three managerially controllable variables namely, 'payment anonymity', 'information on payment recipients' and 'information of product value/quality'.
ContributorsChristopher, Ranjit M (Author) / Wiles, Michael (Thesis advisor) / Ketcham, Jonathan (Committee member) / Park, Sungho (Committee member) / Arizona State University (Publisher)
Created2016
155939-Thumbnail Image.png
Description
Total digital media advertising spending of $72.5 billion surpassed total television Ad spending of $71.3 billion for the first time ever in 2016. Approximately $39 billion, or 54% of the digital media advertising spend, involved pre-programmed software that purchased Ads on behalf of a buyer in Real-Time Bidding (RTB) settings.

Total digital media advertising spending of $72.5 billion surpassed total television Ad spending of $71.3 billion for the first time ever in 2016. Approximately $39 billion, or 54% of the digital media advertising spend, involved pre-programmed software that purchased Ads on behalf of a buyer in Real-Time Bidding (RTB) settings. A major concern for Ad buyers is sub-optimal spending in RTB settings owing to biases in the attribution of customer conversions to Ad impressions. The purpose of this research is twofold. First, identify and propose a novel experimental design and analysis plan for to handling a previously unidentified and unaddressed source of endogeneity: count/quality simultaneity bias (CQB). Second, conduct a field study using data for Ad response rates, cost, and observed consumer behavior to solve for the profit maximizing daily Ad frequency per customer. One large online retailer provided data for Ad impressions, bid costs, response rates, revenue per visit, and operating costs for 153,561 unique users over 23 days. Unique visitors were randomly assigned to one of seven treatment groups with one, two, three, four, five, and six impressions per day limits as well as a final condition with no daily impression cap. Ordinary least square models (OLS) were fit to the data and a non-linear relationship between Ad impressions and site visits demonstrating declining marginal effect of Ad impression on site visits after an optimal point. The results of the field study confirmed the existence of negative CQB and demonstrated how my novel experimental design and analysis can reduce the negative bias in the estimate of impression quantity on customer response. Second, managers interested in improving the efficiency of advertising spend should restrict display advertising to only the highest quality inventory through specific site targeting and by leveraging direct buys and private marketplace deals. This strategy ensures that subsequent impressions are not of lower quality by restricting the pool of possible impressions from a homogenous set of high quality inventory.
ContributorsFay, Bradley (Author) / Mokwa, Michael P. (Thesis advisor) / Park, Sungho (Thesis advisor) / Han, Sang-Pil (Committee member) / Christopher, Ranjit M (Committee member) / Arizona State University (Publisher)
Created2017