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You searched for +publisher:"University of Southern California" +contributor:("Yang, Sha"). Showing records 1 – 3 of 3 total matches.

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University of Southern California

1. Lu, Shijie. Essays on online advertising markets.

Degree: PhD, Business Administration, 2015, University of Southern California

My dissertation examines novel interactions between consumers and advertisers enabled by Internet platforms with new targeting technologies in online advertising markets. As paid‐search and display become two most prevalent forms of online advertising, this dissertation empirically investigates the consumer and advertiser interactions in these two online advertising markets. ❧ In my first essay, I examine the determinant of competition and its impact on click‐volume and cost‐per‐clicks in paid‐search advertising. I regard each keyword as a market and measure the competition by the number of ads on the paid‐search listings. I build an integrative model of the number entrant advertisers, the realized click‐volume and cost‐per‐clicks of each entrant. The proposed model is applied to data of keywords associated with digital camera/video and accessories. Results indicate that the number of competing ads has a significant impact on baseline click‐volume, decay factor, and value‐per‐click. These findings help search advertisers assess the impact of competition on their entry decisions and advertising profitability. The proposed framework can also provide profit implications to the search host regarding two polices: raising the decay factor by encouraging consumers to engage in more in‐depth search/click‐through, and providing coupons to advertisers. ❧ As Internet advertising infomediaries now provide rich competition‐related information, search advertisers are becoming more strategic in their keyword decisions. In the second essay, I explore whether positive or negative spillover effects occur in advertisers’ keyword entry decisions, which lead to assimilation or differentiation in their keyword choices. I develop a model of advertisers’ keyword decisions based on the incomplete‐information and simultaneous‐move game with two novel extensions: (i) I allow the strategic interactions to vary with advertisement positions to reflect consumers’ top‐down search pattern; and (ii) I infer potential entrants of a keyword by modeling the advertisers’ keyword consideration process to capture their limited capacity in analyzing all existing keywords. Using a panel dataset of laptop‐related keywords mainly used by 28 manufacturers, retailers, and comparison websites that advertise on Google, I find both assimilation and differentiation tendencies, which vary across firm types and the expected ranking of competing firms. A counterfactual simulation suggests that the more accurate competition information provided by infomediaries leads to a market‐expansion effect. ❧ Behavioral targeting, displaying personalized advertisements based on consumers’ past online behaviors, has become a popular practice in the online advertising industry. Yet, empirical research on behavioral targeting remains relatively nascent. The final essay studies the impact of targeting level on three key players (users, advertisers, and the advertising host) in behaviorally targeted display advertising. The targeting level is defined as an inverse scale of the number… Advisors/Committee Members: Yang, Sha (Committee Chair), Dukes, Anthony (Committee Member), Shum, Matthew (Committee Member), Yang, Botao (Committee Member).

Subjects/Keywords: online advertising; Internet marketing; paid search; competition; generalized second-price auction; entry; incomplete-information game; infomediary; behavioral targeting; Bayesian estimation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lu, S. (2015). Essays on online advertising markets. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/548697/rec/2472

Chicago Manual of Style (16th Edition):

Lu, Shijie. “Essays on online advertising markets.” 2015. Doctoral Dissertation, University of Southern California. Accessed October 30, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/548697/rec/2472.

MLA Handbook (7th Edition):

Lu, Shijie. “Essays on online advertising markets.” 2015. Web. 30 Oct 2020.

Vancouver:

Lu S. Essays on online advertising markets. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2020 Oct 30]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/548697/rec/2472.

Council of Science Editors:

Lu S. Essays on online advertising markets. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/548697/rec/2472


University of Southern California

2. Sheng, Shuyang. A structural econometric analysis of network and social interaction models.

Degree: PhD, Economics, 2013, University of Southern California

Social and economic networks play an important role in shaping individuals' behaviors. In this dissertation, we provide a structural econometric analysis of network-related models, including network formation models and social interaction models. In the analysis of network formation models, the goal is to identify and estimate the underlying utility parameters using observed data on network structure, i.e., who is linked with whom. We consider a game-theoretic model of network formation and use pairwise stability, introduced by Jackson and Wolinsky (1996) as the equilibrium condition. The parameters are not point identified when there are only multiple equilibria. We leave the equilibrium selection completely unrestricted and use partial identification. Following Ciliberto and Tamer (2009), we derive bounds on the probability of observing a network. These bounds, however, are computationally infeasible if networks are large. To overcome this computational problem, we propose a novel method based on subnetworks. A subnetwork is the restriction of a network to a subset of the individuals. We derive bounds on the probability of observing a subnetwork, considering only the pairwise stability of the subnetwork rather than the entire network. Under mild assumptions, these subnetwork bounds are computationally feasible as long as we consider only small subnetworks. ❧ As for the social interaction models, we focus on a special case where individuals interact because they can learn from their neighbors about a new technology. We follow the literature on nonparametric identification and provide conditions under which the structural functions and average learning effects in this model can be nonparametrically identified. Advisors/Committee Members: Ridder, Geert (Committee Chair), Strauss, John A. (Committee Member), Moon, Hyungsik Roger (Committee Member), Yang, Sha (Committee Member).

Subjects/Keywords: network formation; pairwise stability; multiple equilibria; partial identification; subnetworks; simulation; social interactions; Bayesian learning; nonparametric identification; nonadditive index models

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sheng, S. (2013). A structural econometric analysis of network and social interaction models. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/320029/rec/374

Chicago Manual of Style (16th Edition):

Sheng, Shuyang. “A structural econometric analysis of network and social interaction models.” 2013. Doctoral Dissertation, University of Southern California. Accessed October 30, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/320029/rec/374.

MLA Handbook (7th Edition):

Sheng, Shuyang. “A structural econometric analysis of network and social interaction models.” 2013. Web. 30 Oct 2020.

Vancouver:

Sheng S. A structural econometric analysis of network and social interaction models. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2020 Oct 30]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/320029/rec/374.

Council of Science Editors:

Sheng S. A structural econometric analysis of network and social interaction models. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/320029/rec/374


University of Southern California

3. Tsai, Jason. Protecting networks against diffusive attacks: game-theoretic resource allocation for contagion mitigation.

Degree: PhD, Computer Science, 2013, University of Southern California

Many real-world situations involve attempts to spread influence through a social network. For example, viral marketing is when a marketer selects a few people to receive some initial advertisement in the hopes that these `seeds' will spread the news. Even peacekeeping operations in one area have been shown to have a contagious effect on the neighboring vicinity. Each of these domains also features multiple parties seeking to maximize or mitigate a contagious effect by spreading its own influence among a select few seeds, naturally yielding an adversarial resource allocation problem. My work models the interconnected network of people as a graph and develops algorithms to optimize resource allocation in these networked competitive contagion scenarios. ❧ Game-theoretic resource allocation in the past has not considered domains with both a networked structure and contagion effects, rendering them unusable in critical domains such as rumor control, counterinsurgency, and crowd management. Networked domains without contagion effects already present computational challenges due to the large scale of the action space. To address this issue, my first contribution proposed efficient game-theoretic allocation algorithms for the graph-based urban road network domain. This work still provides the only polynomial-time algorithm for allocating vehicle checkpoints through a city, giving law enforcement officers an efficient tool to combat terrorists making their way to potential points of attack. Second, I have provided the first game-theoretic treatment for contagion mitigation in social networks and given practitioners the first principled techniques for such vital concerns as rumor control and counterinsurgency. Finally, I extended my work on game-theoretic contagion mitigation to address uncertainty about the network structure to find that, contrary to what evidence and intuition suggest, heuristic sampling approaches provide near-optimal solutions across a wide range of generative graph models and uncertainty models. Thus, despite extreme practical challenges in attaining accurate social network information, my techniques remain near-optimal across numerous forms of uncertainty in multiple synthetic and real-world graph structures. ❧ Beyond optimization of resource allocation, I have further studied contagion effects to understand the effectiveness of such resources. First, I created an evacuation simulation, ESCAPES, to explore the interaction of pedestrian fear contagion and authority fear mitigation during an evacuation. Second, using this simulator, I have advanced the frontier in contagion modeling by developing empirical evaluation methods for comparing and calibrating computational contagion models that are critical in crowd simulations and evacuation modeling. Finally, I have also conducted an examination of agent-human emotional contagion to inform the rising use of simulations for personnel training in emotionally-charged situations. Advisors/Committee Members: Tambe, Milind (Committee Chair), Marsella, Stacy C. (Committee Member), Yang, Sha (Committee Member), McCubbins, Mathew D. (Committee Member), Krishnamachari, Bhaskar (Committee Member), Bowring, Emma (Committee Member).

Subjects/Keywords: game theory; security; contagion; networks

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tsai, J. (2013). Protecting networks against diffusive attacks: game-theoretic resource allocation for contagion mitigation. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/283292/rec/5297

Chicago Manual of Style (16th Edition):

Tsai, Jason. “Protecting networks against diffusive attacks: game-theoretic resource allocation for contagion mitigation.” 2013. Doctoral Dissertation, University of Southern California. Accessed October 30, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/283292/rec/5297.

MLA Handbook (7th Edition):

Tsai, Jason. “Protecting networks against diffusive attacks: game-theoretic resource allocation for contagion mitigation.” 2013. Web. 30 Oct 2020.

Vancouver:

Tsai J. Protecting networks against diffusive attacks: game-theoretic resource allocation for contagion mitigation. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2020 Oct 30]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/283292/rec/5297.

Council of Science Editors:

Tsai J. Protecting networks against diffusive attacks: game-theoretic resource allocation for contagion mitigation. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/283292/rec/5297

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