Browsing by Author "Lee, Garim"

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    Congruence Effects in Online Customer Reviews: The Mediating Role of Perceived Information Relevance
    (2020-05) Lee, Garim
    Research addressing the message appeals of online customer reviews has arisen to deepen our understanding of consumer decision-making in online retail environments. Prior research suggests that there are two types of message appeals: emotional and rational (Huang et al., 2013; Kotler & Keller, 2008; Liu et al., 2018; Wu & Wang, 2011). The former can elicit consumers’ emotions to induce purchase willingness, whereas the latter appeals to their cognition and reasoning highlighting product functions and practical benefits. Retailing research (e.g., Kang & Park-Poaps, 2010) to date has widely explored consumers’ shopping orientations, which are largely originated from hedonic and utilitarian conceptions. However, the congruence effect between a message appeal of online customer reviews and shopping orientation has not been sufficiently established. To address this research gap, the purposes of this study were (a) to investigate how a congruence between a message appeal of online reviews and shopping orientation affects perceived relevance of information presented in an online customer review and, in turn, leads to consumers’ purchase intention and (b) to examine the role of cumulative customer satisfaction and overall perceived risk in directly affecting purchase intention as well as in moderating the relationship between perceived relevance and purchase intention. A 2 (message appeal of online customer reviews: emotional vs. rational) x 2 (shopping orientation: hedonic vs. utilitarian) between-subjects experiment was conducted with 227 U.S. participants through Amazon Mechanical Turk. The results confirmed the congruence effect between a message appeal of online customer reviews and shopping orientation, ultimately leading to purchase intention. The participants who had a hedonic (vs. utilitarian) shopping orientation perceived a higher congruence when they viewed an emotional (vs. rational) review than a rational (vs. emotional) one. The relationship between perceived congruence and purchase intention was partially mediated by perceived information relevance. Contrary to the hypothesis, the participants were more willing to purchase a product that has a relevant review when they had been less (vs. more) satisfied with an e-tailer over time. However, both direct and indirect effects of perceived risk were found to be insignificant. The results of this study contribute to the literature on electronic word-of-mouth (eWOM) by providing empirical evidence of congruence effects in online customer reviews. In addition, this study extends the findings of prior research by confirming the role of perceived information relevance. This study offers actionable guidelines to practitioners in ways to increase perceived information relevance.
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    Data supporting: Automated Object Detection in Mobile Eye-Tracking Research: Comparing Manual Coding with Tag Detection, Shape Detection, Matching, and Machine Learning
    (2024-06-20) Segijn, Claire M.; Menheer, Pernu; Lee, Garim; Kim, Eunah; Olsen, David; Hofelich Mohr, Alicia; segijn@umn.edu; Segijn, Claire
    The goal of the current study is to compare the different methods for automated object detection (i.e., tag detection, shape detection, matching, and machine learning) with manual coding on different types of objects (i.e., static, dynamic, and dynamic with human interaction) and describe the advantages and limitations of each method. We tested the methods in an experiment that utilizes mobile eye tracking because of the importance of attention in communication science and the challenges this type of data poses to analyze different objects because visual parameters are consistently changing within and between participants. Python scripts, processed videos, R scripts, and processed data files are included for each method.
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    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.