Research

The goal of the current study is to compare 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 posed by this type of data when analyzing different objects because visual parameters are consistently changing within and between participants. Machine learning was found to be the most reliable method to detect all types of objects and was slightly more conservative compared to manual coding. Feature-based matching worked well for static objects. We discuss the advantages and challenges of each method along with key considerations for researchers depending on their research objective, the type of object, and the object detection method they will use.

The fashion industry can benefit from generative AI because the AI-assisted design process has the potential to be more efficient and cost- and time-effective. Under the mind perception theory, this study examines how consumers evaluate AI's experiential and intentional abilities and respond to AI-designed versus human-designed fashion products. The results of the three online experiments indicate that human-designed products are generally more favorably evaluated than AI-designed ones. Such preference was mainly because people ascribe a better intentional capacity to act and plan to humans than AI, which makes them believe humans have better design expertise. The preference for human design over AI design was found regardless of one's tendency to perceive AI threats. The receptivity to the AI design is increased for highly functional (vs. self-expressive) products, but such a moderating effect of product type may not hold in intra-product comparisons. Incorporating human elements into the AI-assisted design process when introducing the products can alleviate the negative responses, but the effectiveness can vary depending on the levels of human elements. This study contributes to the literature by finding the perceptual superiority of human design and suggesting the potential of changing negative bias toward AI design.

Generative Artificial Intelligence (AI) empowers the AI design process. Then, how do consumers respond to AI-designed fashion products? Building on schema theory, this research investigated the extent to which AI-designed clothing is perceived as authentic through three online experiments. Study 1 (n=121) and Study 2 (n=161) showed consumers generally respond more favorably to human-designed (vs. AI-designed) clothing, which is driven by perceived authenticity and expected product quality. Study 3 (n=156) confirmed that negative responses toward AI-designed clothing can be mitigated when consumers have the option to provide input to customize the design because it enhances perceived authenticity. Study findings offer a theoretical understanding of how and why consumers respond to AI-designed products and practical guidelines for retailers.

Developments in digital technologies have extended the abilities of marketers to collect, process, and share consumer data to optimize personalized messages across media in real time, a strategy known as synced advertising. Previous research has found promising effects related to synced advertising. At the same time, consumer knowledge appears to be low, and informing consumers could increase their critical attitudes towards synced ads. Our eye-tracking lab study (N = 163) showed that informing consumers on synced advertising helps them to understand and increase their knowledge about this new marketing strategy. Moreover, this strategy increases recall of the product mentioned on TV as well as perceived surveillance. Finally, we found that all participants closed the synced ad with an average of 6.5 s and fixated on it for an average of 1.3 s. This study contributes to the growing literature on synced advertising by empirically investigating the impact of consumer knowledge on the tensions and opportunities of this new marketing strategy.

With exponential technology advancement and innovation, consumers can now receive synchronized advertising across media simultaneously. However, programmatic advertising technologies allow not only the same brand but also competitor brands to be synchronized across media. Based on the concept of repetition from the multi-layered concept of relatedness, this research investigated the effects of synced brand versus competitor brand with an online scenario-based experiment (Study 1; N=122) and an online task experiment (Study 2; N=227). The results showed a positive effect of synced brand on brand attitude and purchase intention but only in the scenario-based studies. This research is, to our knowledge, the first to empirically show that synced advertising with the same brand versus a competitor brand may lead to favorable consumer responses. The findings contribute to more academic thinking towards the effects of personalized advertising frameworks and provide insights to advertising practitioners regarding the impact of cross-media personalization strategies. 

Voice Assistants (VA) are increasingly penetrating consumers’ daily lives. This study aimed to investigate the effects of synthetic vs. human voice on users’ perception of the voice, social judgments of the VA, and attitudes towards VAs. Drawing from CASA(Computers-as-socialactors) framework and social perception literature, we developed a theoretical model that explains the psychological underlying mechanism of the voice effects. Through two online experiments, we rejected our initial hypotheses that human voice would increase users’ perception and evaluation of the VAs. Instead, our findings support that the VAs were favored when they spoke with a synthetic voice only when the users engaged in functional tasks. There was no difference between the voices for social tasks. A further investigation revealed that participants perceived the synthetic voice to be more fluent when VA responds to functional tasks. This enhanced perception of fluency increased competence perception and attitudes. The findings imply that VAs should not be designed to closely resemble humans. Rather, consideration of usage contexts and consumer expectations should be prioritized in developing most likable VAs.

Purpose: This study examines how the locus of agency of brands' artificial intelligence (AI)–powered voice assistants (VAs) could lead to brand loyalty through perceived control, flow and consumer happiness under the moderating influences of brand image and voice congruity.

Design/methodology/approach: This study conducted a 2 (locus of agency: high vs. low) by 2 (brand image-voice congruity: congruent vs. incongruent) between-subjects experimental design. MANOVA, ANOVA and structural equation modeling (SEM) were conducted to test the hypothesized model.

Findings: ANOVA results revealed that human-centric (vs. machine-centric) agency led to higher perceived control. The interaction effect was significant, indicating the importance of congruency between brand image and VAs' voices. SEM results confirmed that perceived control predicted brand loyalty fully mediated by flow experience and consumer happiness.

Originality/value: This study provides evidence that the positive technology paradigm could carve out a new path in existing literature on AI-powered devices by showing the potential of a smart device as a tool for improving consumer–brand relationships and enriching consumers' well-being.

Purpose: The recent surge of subscription box services calls for research to understand how consumers respond to curation services. This study aims to develop and test a theoretical model to predict consumer response to AI (vs. human). Particularly, we tested the role of stereotyping in shaping consumer perception of creativity in this context while considering the contextual moderators, shopping goals (hedonic vs. utilitarian) and product category (fashion vs. meal).

Design/methodology/approach: Two preliminary studies and the main study (total n=761) tested the assumptions and hypotheses of the study. Preliminary study 1 (n=511 Amazon mTurk, online survey) confirmed consumer stereotypes of humans and machines. Preliminary study 2, a single-factor between-subjects online experiment (recommender: human vs. AI), was conducted at a large Midwestern university in the U.S. (n=56). The main study was conducted as a 2(recommender: human vs. AI) × 2(product: fashion vs. meal) × 2(goal: utilitarian vs. hedonic) between-subjects online experiment (n=194, Amazon mTurk).

Findings: The results confirmed that consumers are more likely to follow recommendations made by a human more than recommendations made by AI and the perceived creativity of the recommender explained the effect. Significant differences across product categories and shopping goals of the consumers were observed, calling for attention to the context of consumption.

Originality: This study extends the understanding of consumers’ responses to recommendations in curation subscription services by highlighting the role of perceived creativity of humans versus AI.

Abstract

Purpose: Consumers support local businesses as an ethical choice. However, consumer ethics researchers have not paid much attention to local consumption, limiting the understanding of why consumers believe local consumption is ethical. To address this research gap, this study aims to develop and test the theoretical model for local consumption decisions by integrating moral foundations theory and local–global identity literature.

Design/Methodology/Approach: An online survey of US adult consumers (n=362) was conducted to test the theoretical model. A correlational structural equation model was used to analyze the data.

Findings: The results confirmed that consumers’ moral obligations to engage in local consumption are driven partially by pro-group moral foundations, and that this identity-based motivation is an intuitive predictor of local consumption behaviors. The findings of this study demonstrate that traditional ethical consumption frameworks that assume knowledge-based decision-making are not enough to explain local consumption, and provide arguments for the need to consider both moral intuitions and moral reasoning.

Originality/Value: This study synthesizes two isolated streams of literature and presents an integrated model to holistically explain consumer motivations for local business support. Local consumption was rarely investigated and its unique characteristics were not fully understood in the context of ethical consumption. This study specifically focuses on local consumption, advancing our knowledge of this understudied consumer behavior.

Abstract

This study explored the interaction of a message appeal of online reviews and shopping orientation on perceived congru- ence. The effects of perceived congruence, perceived information relevance, cumulative satisfaction, and perceived risk on purchase intention were also examined. The participants with hedonic (vs. utilitarian) shopping orientation perceived higher congruence when viewing an emotional (vs. rational) review than a rational (vs. emotional) review. Perceived information relevance mediated the effects of perceived congruence on purchase intention. Cumulative satisfaction positively affected purchase intention, while the effects of perceived risk were found to be insignificant. The findings contribute to the online review literature by providing evidence of congruence effects between consumers’ internal factors and review characteristics. The finding that perceived information relevance serves as an underlying mechanism of the congruence effects expands the existing knowledge of electronic word-of-mouth. Practitioners are recommended to find ways to increase perceived information relevance by tailoring to consumers’ shopping orientation and utilizing the message appeal of online reviews with web- site designs and algorithms.

Abstract

Despite the extensive research on the effects of storytelling in ads, studies have neglected to investigate fashion film series. The current research fills this gap, emphasizing the strengths of fashion film series. Previous studies on the effects of repeated exposure provide a framework to understand the superiority of film series (vs repeats). A 1-factor 3-level (fashion films: series vs. repeats vs. control) online experiment reveals that participants who viewed film series showed higher character empathy (marginally significant) and brand anthropomorphism than participants who viewed film repeats or viewed a film once (control condition). Moreover, character empathy mediated the relationship between fashion films and brand anthropomorphism. Furthermore, brand anthropomorphism is associated with brand love. The study shows that exposure to diverse stories about a character is more effective than repetitive stories in strengthening the consumer-brand relationship.