A creator platform utilizes marketing tools and pricing policies to maximize customer acquisition and revenue, with trade-offs among the creators, their audience, and the platform itself. In chapter “Referral Program Design”, we focus on how a platform can leverage a referral program to acquire new subscribers and maximize profit, and quantify the financial consequences of referral marketing with a structural model. The return from implementing a referral program for the creator is a function of the size of the monetary reward for successful referrals, and the price charged for new subscriptions. We find a substantial contribution of applying referral marketing to creators’ revenue, but this varies for specific types of content with different referral effectiveness and operation costs. Further, we document inverted-U shaped relationships for profit and demand as the size of referral rewards increase. Using counterfactual analysis, we highlight the disparity of profit-optimizing referral marketing design between creators and the platform since creators focus on short term profit while the platform focuses on long run user base growth. In chapter “Platform Commission Design”, we study the impact of platform commission changes on creators’ pricing decisions and quality. The same creator platform underwent significant adjustments to its commission policy. In August 2019, the platform increased its commission from 5% to 20% for all creators, and later allowed eligible creators to revert to the original 5% commission. Using a difference-in-differences approach, we examine the consequences of subsidizing eligible creators with a lower commission, and find a significant price increase induced by the commission cut, which contrasts sharply with classic prediction from third-degree price discrimination. If the initial commission increase altered market concentration, the subsequent reduction in commission could incentivize some creators to raise prices in order to reveal their status as high-quality content providers. This study suggests that changes in commission should be approached with caution due to their irreversible effects. Increasing commission while discriminating against a segment of creators shifts content and price distribution, potentially disadvantaging subscribers and reducing their welfare.

The concept of “genuine hospitality” extends beyond the mere provision of tangible offerings and hospitable behaviors by the host. It requires true hospitableness on the part of the service providers themselves. However, like humans, can AI also serve as a provider capable of embodying hospitableness? This dissertation seeks to establish a comprehensive theoretical framework called the Consciousness Attribution Model of AI Hospitableness (CAMAH) which encompasses three interconnected aspects: (1) the mechanism of consciousness attribution by consumers towards AI-enabled service providers, (2) the necessity of such attributions in recognizing the symbolic value of AI hospitableness, and (3) a nuanced comparison between human and AI providers concerning their capacity to deliver genuine hospitability. Structured into three scholarly essays, this dissertation first undertakes a philosophical and conceptual exploration, culminating in the proposition of CAMAH. Extending the theoretical foundations established in Essay 1, the subsequent essays (2 and 3) delve into empirical investigations within specific service technology domains, focusing on service robots and AI avatars equipped with self-service technologies, respectively. The significance of this dissertation lies in its identification of a necessary condition for AI service providers to be recognized as hospitable hosts capable of imparting hospitality-oriented, symbolic value, while clearly delineating the key boundaries that distinguish AI service providers—notwithstanding their potential to equip with anthropomorphic behaviors/forms—to human counterparts. / Tourism and Sport

The formation of a consumer's brand related schemas results from prior exposure to brand information through advertising, product experience and other sources. A framework based on categorization theory, priming and the advertising/evidence interaction research, investigates the effect of arousal of schema based expectations on consumer evaluative judgments. The two step model in advertising/evidence interaction research suggests that advertising at first arouses tentative expectations because of the partisan nature of the source. In the second step, the credibility of such ad-induced expectations are evaluated using available evidence in the form of product search and experience to influence evaluative judgments of quality. Priming increases the accessibility of a conceptual category, thereby increasing the likelihood of the use of that category to encode new information. The main argument, is that priming with a brand/logo (well known brand prime, unknown brand prime or no prime) activates brand based schemas and arouses expectations similar to ad-based expectations about the brand. The focus of this research is to show that schema based expectations aroused through priming, in conjunction with evidence about product performance (which may be ambiguous or unambiguous), influence brand evaluations and judgments of quality. Priming effects are predicted to be similar for repeat purchase and expensive durable products. Higher levels of attitude and intentions are predicted with "well known brand primes" than an "unknown brand prime". Information processing differences between concept driven (or top-down) and data driven (or bottom-up) processes are also predicted. Data collected from student samples shows support for the main hypothesis--that schema-based expectations aroused through priming interacts with product evidence on quality judgments. The effect is however strongest for unknown brand primes than well known brand primes showing that priming with unknown brand primes may be more successful. Subjects showed equal levels of satisfaction of information provided across the two product classes. Attitudes were also more positive with "well known primes" than with "unknown brand primes". Surprisingly, unambiguous product evidence did not lead to greater confidence in judgments than ambiguous evidence. Partial support was found for information processing differences across the prime and evidence conditions.

Thesis (Ph. D.)--University of Oregon, 2007. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 249-257). Also available for download via the World Wide Web; free to University of Oregon users.

Thesis PlanB (M.S.)--University of Wisconsin--Stout, 2008. / Includes bibliographical references.

Thesis (M. Sc.)--University of Hong Kong, 2005. / Also available in print.

Thesis (Ph.D.)--University of Hong Kong, 2002. / Includes bibliographical references. Also available in print.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1969. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 357-368).

Thesis (MBus)--University of South Australia, 1996

Thesis (Ph. D.)--University of Iowa, 2007. / Thesis supervisor: Nick Street. Includes bibliographical references (leaves 109-116).