DSpace Community:
https://dspace.ewha.ac.kr/handle/2015.oak/241411
2024-03-29T09:20:05Z
-
When digital celebrity talks to you: How human-like virtual influencers satisfy consumer's experience through social presence on social media endorsements
https://dspace.ewha.ac.kr/handle/2015.oak/267790
Title: When digital celebrity talks to you: How human-like virtual influencers satisfy consumer's experience through social presence on social media endorsements
Ewha Authors: 박민정
Abstract: Retailers are employing non-human endorsers as alternatives to traditional celebrities in digital marketing. We seek to identify the aspects of human-like virtual influencer endorsements that create a positive consumer experience. Using a survey of 364 female Instagram users in South Korea, we find that virtual influencers’ perceived anthropomorphism positively influences satisfaction. Social presence does not mediate the association between perceived anthropomorphism and satisfaction. Further perceived enjoyment, perceived usefulness, flow, and credibility play a significant role in the relationship among perceived anthropomorphism, social presence, and satisfaction. This study offers practical insights into collaborative advertising for retail marketers utilizing virtual celebrities. © 2023 Elsevier Ltd
2024-01-01T00:00:00Z
-
Augmented reality in delivering experiential values: moderating role of task complexity
https://dspace.ewha.ac.kr/handle/2015.oak/267008
Title: Augmented reality in delivering experiential values: moderating role of task complexity
Ewha Authors: 박민정
Abstract: This study examined if greater experiential values are provided when shopping via an AR mobile app compared to shopping via a general mobile website without AR. The mediating role of experiential values between the two shopping methods and customer loyalty as well as the moderating effect of task complexity between the two shopping methods and experiential values were further investigated. An exciting eyewear retailer’s mobile site and mobile app embedded with AR features were used. A total of 302 usable respondents participated in the study. Shoppers exposed to an AR function perceived greater aesthetics, escapism, enjoyment, and efficiency than those exposed to a non-AR mobile site. Also, compared to shoppers exposed to a general non-AR mobile site, shoppers exposed to an AR mobile app showed greater customer loyalty through the four experiential values. Task complexity modified the effects of AR on consumers’ perceived escapism and efficiency experiential values. This research fills the gap in the literature by investigating AR’s experiential values in connection with customer loyalty by comparing an AR-embedded mobile app with a general mobile site without an AR feature. The additional examination of task complexity also contributes to a complete understanding of AR experiential benefits considering consumers’ perceptions about AR operation task complexity. © 2024, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
2024-01-01T00:00:00Z
-
Development of a fabric classification system using drapability and tactile characteristics
https://dspace.ewha.ac.kr/handle/2015.oak/267001
Title: Development of a fabric classification system using drapability and tactile characteristics
Ewha Authors: 윤창상
Abstract: When producing clothing using virtual fitting technology or purchasing textile and clothing products online, it is challenging to make judgments or communicate information about sensory characteristics, such as drapability and tactile sensations, as there are no clear objective indicators for these factors. Therefore, the study aims to develop a classification system for the sensory properties of fabrics using drapability and tactile characteristics as quantitative indicators. The developed system was verified through subjective evaluations by an expert group, and it was found to be meaningful in reflecting classification levels in practice. The drapability and tactile sensation (softness; TS7) of the fabric were classified using fuzzy c-means cluster analysis, and the results were confirmed through a subjective evaluation by experts. The classification system was then used to predict the classification group, constituted by drapability and tactile characteristics, from mechanical properties using an artificial neural network. The network was trained on 534 fabric samples for drapability and tactile sensation (softness), and it correctly predicted 202 samples out of 243 validation data, with a forecasting accuracy of 83.5%. The developed classification system enables predictions and judgments about subjective characteristics like fabric drapability and tactile sensation based on the mechanical property values of various samples. © 2024, The Author(s).
2024-01-01T00:00:00Z
-
Multidimensional analysis for fabric drapability
https://dspace.ewha.ac.kr/handle/2015.oak/266614
Title: Multidimensional analysis for fabric drapability
Ewha Authors: 윤창상
Abstract: This study analyzed fabric drapability in one, two, and three dimensions to provide an assessment method reflecting real conditions. One-dimensional analysis of drapability involved observing the fabric movement by reciprocating motion. The movement appeared differently depending on the fabric characteristics, and the shape and location of the node showed differently, which were considered to be influenced by the weight of the sample along with the drape coefficient. Two-dimensional analysis identified the significant factors for the drape information. This examination confirmed that, even if drape factors were similar, differences in draped shape were observed based on the factors related to node shapes. Three-dimensional analysis, using a 3D scanner, involved the use of the mean distances between draped samples and the standard truncated cone, their standard deviation, and the coefficient of variation. The coefficient of variation was high in the groups wherein the shape of the drape was irregular. In the 3D analysis, the distances between samples and the standard truncated cone were expressed in colors to intuitively deliver the drape information. To determine a factor that could indicate drapability among the factors derived from each dimension, the existing drape coefficient was employed for correlation analysis. Three pairs of samples with similar drape coefficients but different drape shapes were selected to verify the above results. In conclusion, one-dimensional node location, two-dimensional standard deviation of node severity, and three-dimensional coefficient of variation were shown to effectively demonstrate the drape characteristic that the drape coefficient could not indicate. © 2023, The Korean Society of Clothing and Textiles.
2023-01-01T00:00:00Z