Beneficiary Foci Types and Performance Appeals in Green Advertising

In green advertising, the message focus is often associated with one of two benefits: the self-benefit focus and the other-benefit focus. However, determining which of the two benefit foci is more effective in generating positive consumer responses is still debatable. To explain the complexity of the mixed findings, we have explored advertising appeals that influence the perception of the environmental performance of the product, or green performance perception. Specifically, we have examined the self- and other-benefit types with three performance-based appeals (before, after, and before–after appeals) in relation to perceived green performance and brand attitudes. A 2 × 3 ANOVA of perceived green performance with data from 390 participants reveals a significant two-way interaction. Results from comparing the three types of performance-based appeals indicate that, regardless of the beneficiary foci type, the before–after appeal works best in generating greater perceived green performance, which, in turn, leads to positive brand attitudes. When promoting the green benefit of others, we recommend using before-appeals to enhance a product’s green performance perceptions and after-appeals for self-benefit-focused advertisements; if not, before–after appeals are used

Exploring Hedonic and Utilitarian Aspects Through Perceived Warmth in Human-Designed Vs. AI-Generated Fashion

Among various ways in which artificial intelligence (AI) is used in the fashion industry, its utilization in design has sparked public discussion about the potential replacement of human designers by AI. Along with this critical question, it is imminent to examine how consumers would respond to designs by AI. The purpose of this study is to explore consumers’ perceptions toward a fashion product labeled as generated by an AI system, comparing it to the same product labeled as designed by a human designer. Specifically, drawing from existing literature, we examine if the design source affects consumers’ perceptions of a product to be more hedonic or utilitarian, with perceived warmth as a mediating factor

Will the Scarcity of AI-Designed Clothing Influence Consumers to Purchase?

This study explores how perceived scarcity of AI-designed clothing influences purchase intention, mediated by perceived monetary value. Fashion involvement\u27s moderating role is also examined. Participants (N = 311), sourced from Amazon Mechanical Turk, watched an AI clothing design video, and evaluated a jacket that is designed by AI. Responses on perceived scarcity, monetary value, purchase intentions, and fashion involvement were collected using Likert scales. Analyzing data with SPSS 28.0 and the PROCESS Macro Model 8 with 5,000 bootstrap samples suggested that although the scarcity of an AI-designed clothing alone may not significantly increase purchase intentions, fashion brands can leverage the perception of scarcity if the product can be perceived as of good value for the money. The effect will be particularly stronger if the brands’ target consumers tend to have low involvement in fashion

The Relationship Between Self-Sexualization and Sexually Objectified Experience

Will women who use their sexuality as a source of power, empowering themselves through self-sexualization, experience negative consequences resulting from sexually objectifying experiences? This study explored the relationship between self-sexualization and sexually objectifying experiences, which leads to body shame, with age as a moderator. An online questionnaire was created to measure the four variables (self-empowering sexualization, general self-sexualization, sexually objectified experiences; body shame). A total of 308 female respondents participated through MTurk, and the data were analyzed with SEM. The findings showed that not all self-sexualizing women experienced a negative consequence from sexually objectified experiences; the use of self-sexualization for power was not related to negative consequences. However, young women were at greater risk from self-sexualization because regardless of differences in self-sexualization, self-sexualization can not only lead to more sexual objectification but also directly lead to a feeling of body shame even in the absence of sexual objectification

Performance Appeals, Environmental Knowledge, and Emotions for Green Advertising

This study aims to investigate the effect of the green performance appeals in an advertisement on purchase intentions, which are mediated by anticipated positive emotions (i.e., happiness and hope). This study also explores that the mediation model is moderated by individuals’ environmental knowledge. Three experimental conditions were utilized in which three types of green performance appeals (before, after, before–after appeal) were presented in the advertisement of a mock denim brand. Web-based online survey data (N = 201; Amazon MTurk) were analyzed by using ANOVA and PROCESS procedure using SPSS 23.0. The results of this study indicated that when the green-message of fashion products used after-use and before-after appeals, the effect of the green-message can increase individuals’ anticipated happiness and hope, leading to purchase intentions. This strategy of message-appeals especially works for people with low environmental knowledge

Green Advertising Using Sick-, Well-, and Healed-Appeals

The purpose of this study was to examine the effects of sick, well, and healed appeals while examining the interaction effect of the saliency of environmental issues in the fashion industry on consumer responses. A 3 x 2 experimental study was conducted with the appeals (sick vs. well vs. healed appeals) and the salience for environmental issues in fashion (low vs. high) as independents and positive and negative anticipated emotions as mediators, leading to purchase intentions. A total of 195 usable responses were collected through MTurk. While all appeals worked well with consumers with high saliency through anticipated positive emotions, a sick appeal was not effective regardless of the consumer’s position on the saliency of environmental issues in the fashion industry. The findings suggest that markers should convince consumers in a positive manner and promote positive emotions that consumers will have from buying their environmentally sustainable fashion products

Can I Touch the Clothes on the Screen? The Touch Effect in Online Shopping

We examined the interplay effects of device types (touch vs. non-touch) and the tactile sensitivity (fur vs. woven) on the product attitudes mediated by the mental simulation for touch. The participants from MTurk were randomly assigned to one of two tactile conditions. Responses from those who used tablets (n=83, touch device) and laptops (n=96, non-touch device) were included in the analysis. The main effects of device types and tactile-sensitivity on the mental simulation for touch were significant. The interaction effect of device types and tactile sensitivity was also significant. Those participants seeing the less tactile-sensitive product showed greater mental simulation for touch when using a touch device (vs. non-touch device). However, those participants seeing the high tactile-sensitive product showed similar mental simulations for touch regardless of the device types. This indicates that using a touch device can strengthen the mental simulation for touch of a non-haptic centric product

AI-Designed Clothing and Perceived Values: What Can Move Consumers\u27 Minds With the AI-Designed Clothing?

This study investigates the perceived values of AI-designed clothing (quality, emotion, ease) and their impact on willingness to pay (WTP) and word-of-mouth (WOM), with the moderating effect of gender differences. A total of 314 respondents completed the survey via MTurk. Participants watched a video clip demonstrating how an AI system creates various clothing designs by altering garment elements (e.g., style, size). After watching the video clip, they were asked to answer a series of questions about the AI-designed clothing and themselves. The collected data were analyzed using AMOS 26.0. Results showed that, for male and female consumers, the quality value of AI-designed clothing led to enhanced WTP and WOM. However, emotional value and perceived ease of shopping appeared to be more crucial in increasing WTP and WOM for male than female consumers

The Effect of Touch Simulation in Virtual Reality Shopping

This study aims to explore the effect of touch simulation on virtual reality (VR) store satisfaction mediated by VR shopping self-efficacy and VR shopping pleasure. The moderation effects of the autotelic and instrumental need for touch between touch simulation and VR store satisfaction are also explored. Participants wear a head-mounted display VR device (Oculus Go) in a controlled laboratory environment, and their VR store experience is recorded as data. All participants’ responses (n = 58) are analyzed using SPSS 20.0 for descriptive statistics, reliability analysis, exploratory factor analysis, and the Process macro model analysis. The results show that touch simulation positively influences VR store satisfaction, which is mediated by the self-efficacy and by the dual path of the self-efficacy and the pleasure. Furthermore, the relation between touch simulation and pleasure is moderated by need for touch. For individuals with a high level of autotelic need for touch, the effect of touch simulation on the pleasure is heightened. However, instrumental need for touch does not moderate the path of touch simulation on the self-efficacy

Adaptive Torque Estimation for an IPMSM with Cross-Coupling and Parameter Variations

This paper presents a new adaptive torque estimation algorithm for an interior permanent magnet synchronous motor (IPMSM) with parameter variations and cross-coupling between d- and q-axis dynamics. All cross-coupled, time-varying, or uncertain terms that are not part of the nominal flux equations are included in two equivalent mutual inductances, which are described using the equivalent d- and q-axis back electromotive forces (EMFs). The proposed algorithm estimates the equivalent d- and q-axis back EMFs in a recursive and stability-guaranteed manner, in order to compute the equivalent mutual inductances between the d- and q-axes. Then, it provides a more accurate and adaptive torque equation by adding the correction terms obtained from the computed equivalent mutual inductances. Simulations and experiments demonstrate that torque estimation errors are remarkably reduced by capturing and compensating for the inherent cross-coupling effects and parameter variations adaptively, using the proposed algorithm.111Ysciescopu