Browsing by Subject "Consumer Behavior"

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    The Dark Side Of Luxury Consumption: Psychological And Social Consequences Of Using Luxury Goods
    (2015-06) Wang, Yajin
    Prior research has examined people's attitudes, preferences, and motivations for desiring luxury goods, but we know little about what happens when consumers actually use luxury products. My dissertation examines the psychological and behavioral effects of luxury consumption, and asks the question: Does using a luxury product influence the way a person feels and behaves?
  • Thumbnail Image
    Item
    Investigating Consumer Responses to AI- versus Human-Designed Fashion Products: A Mind Perception Theory Perspective
    (2023-05) Lee, Garim
    Generative AI, which creates original content based on input data, is becoming prevalent in the consumer environment. The fashion industry can benefit from generative AI, making the overall product design process more efficient and cost and time effective. However, not many studies have investigated how consumers evaluate AI-designed fashion products. The theorization of how consumers perceive AI in the fashion design process is also not yet sufficient. Building on mind perception theory, this study aims to fill the research gaps by examining how consumers evaluate AI’s mental and intentional abilities and respond to AI-designed versus human-designed fashion products.Consumers’ negative bias toward AI-designed (vs. human-designed) fashion products is confirmed across the two online experiments (Study 1: n=289; Study 2: n=289). Such effects are explained by perceived experience, perceived agency, and perceived design expertise, while the roles of perceived agency and design expertise are especially prominent. The advantageous effects of humans over AI as design entity are generally confirmed across different product types in the same product categories and perceived threats from AI. Finally, incorporating human aspects when introducing products designed through AI-assisted processes alleviates consumers’ negative responses. Varying levels of human aspects in AI applications (AI vs. humanized AI designer vs. human-AI collaboration) lead to different ratings between mind perception, perceived design expertise, and consumer responses. The study contributes to the understanding of the applications of generative AI in retail, focusing on the fashion design process. The theoretical and practical implications are provided drawn from the study findings.
  • Thumbnail Image
    Item
    Optimal Pricing with New Models of Consumer Behavior
    (2015-09) Liu, Yan
    Revenue management is a commonly used practice in many industries, such as airlines, hotels, fashion, and car rentals. It takes advantage of customers' different valuations for a product or products and charges different prices to different customers to extract customers' surplus. In revenue management, most literature assumes that customers are myopic and will buy immediately if the price is low and leave otherwise. In recent years there has been much research involving strategic customers who have the ability to predict future prices and thus make a purchase at the price that maximizes their utility. In Chapter 2 and 3, I will study a different type of customer behavior, which we call patient customer behavior. A patient customer will wait up to some fixed number of time periods for the price of the product to fall below his or her valuation at which point the customer will make a purchase. If the price does not fall below a patient customer's valuation at any time during those periods, then that customer will leave without buying. Chapter 4 describes a learning and pricing problem in which the seller does not know the fraction of patient customers. In practice, customers may wish to search for product information before making purchase decisions. That is, they may wish to research the product or products under consideration. This research behavior will introduce costs to customers, which may include time cost, travel cost, and mental processing cost. Since such research costs could be part of a customer's utility, they may affect a customer's purchasing behavior and thus the firm's strategy. However, most literature in revenue management does not consider the existence of customers' search cost. In Chapter 5, I consider a pricing problem in which customers face uncertainty about whether they will like certain products. Those customers can incur research costs to learn product information. In summary, I will focus on deriving optimal pricing decisions for companies that face customer behavior that is more complex than typically assumed in traditional models.
  • Thumbnail Image
    Item
    The Rise of AI-powered Search Engines: Implications for Online Search Behavior and Search Advertising
    (2024-05) Garlough-Shah, Gabriel
    The emergence of AI-powered search engines (AIPSEs) present enormous opportunities and challenges for the future of research on search engine behavior and advertising alike. To address these opportunities and challenges, a multimethod study (survey and online observation) was conducted examining relationships surrounding perceptions of different technological affordances offered by AIPSEs and traditional search engines (TSEs), motivations for using each type of SE, behavioral intentions to use each in the future, and actual use behavior. Survey results show that participants perceive the technological affordances of AIPSEs and TSEs to be distinct in several facets, finding AIPSEs to be more cool, social, and responsive while finding that TSEs provide more variety and are easier to navigate. Online search observation results showed heavier reliance on TSEs than AIPSEs, more elaborative keyword use on AIPSEs, and heightened use of AIPSEs in advice-seeking circumstances, among other findings. These results offer both theoretical and practical implications.
  • Thumbnail Image
    Item
    Voice Shopping: The Effect of the Consumer-Voice Assistant Parasocial Relationship on the Consumer's Perception and Decision Making
    (2018-08) Whang, Claire
    The primary goal of this study was to investigate how shopping with voice assistants may be uniquely different from shopping on websites. This study focused on whether using different shopping mediums (i.e., voice assistant and websites) affects the way consumers evaluate the recommended product offered by the shopping medium. Based on the anthropomorphism literature and the parasocial interaction theory, the study proposed consumers to form a stronger parasocial relationship with a more humanlike shopping medium, which in turn influences consumers to evaluate the recommended product more positively. Specifically, consumers were expected to perceive voice assistants as more humanlike than websites because of the way voice assistants are designed (i.e., vocal conversation). Furthermore, the study aimed to understand the effect of two moderators, interaction style (task-oriented interaction vs. socially-oriented interaction) and product type (search product vs. experience product). To investigate the following questions, two experimental studies were conducted. Both studies recruited participants who are 18-36 years old and are familiar using voice assistants. Study 1 (N=85) utilized a 2 (shopping medium type: voice assistant vs. website) x 2 (interaction style: task-oriented vs. socially oriented) between-subject experiment factorial design. Participants were invited to the lab to interact with Amazon Echo or the Amazon website. Their interaction styles were manipulated using instructions that are focused on either socially-oriented interaction or task-oriented interaction. Study 2 (N=418) utilized a 2 (shopping medium type: voice assistant vs. website) x 2 (product type: experience product vs. search product) between-subject online experiment factorial design. Study 2 participants were recruited via Amazon MTurk. In Study 2, a hypothetical retailer was created instead of using currently available voice assistants and websites to eliminate the effect of preexisting relationships on the results. The recommended products were manipulated by two products with different search qualities and experience qualities. In both studies, the results of MANCOVA/MANOVA and PROCESS mediation analyses revealed that consumers evaluated products more positively when they were recommended by the shopping medium they formed a stronger parasocial relationship with. Consumers developed a stronger parasocial relationship with the shopping medium they perceived to be more humanlike. However, unlike hypothesized expectations, consumers perceived websites to be more humanlike than voice assistants, consecutively formed a stronger parasocial relationship with websites and evaluated products recommended by the websites more positively. The moderating effect of interaction style was not statistically significant, but the moderating effect of product type was statistically significant. Participants in the website condition evaluated the recommended experience product significantly more positively than participants in the voice assistant condition. Their evaluation of the recommended search product did not vary significantly between the website condition and the voice assistant condition. The findings suggest people may perceive voice assistants as an autonomous agent apart from their operating brands while perceiving websites to be inseparable from their operating brands (e.g., employee, product, CEO). In addition, although the proposed hypotheses were not supported, the findings still support the proposed model that suggested consumers be persuaded more by the more humanlike shopping medium because they form a stronger parasocial relationship with it. Further, the findings also suggest a recommended product’s search or experience qualities may critically influence the way consumers evaluate it. The research contributes to the anthropomorphism literature and parasocial interaction theory by confirming the causal relationship between humanlikeness and parasocial relationships. Further, the research provides knowledge related to utilizing voice assistants in the field of consumer behavior.