Topic Editors
Consumer Psychology and Business Applications
Topic Information
Dear Colleagues,
Consumer psychology, drawing on multi-disciplines including social psychology, marketing, behavioral economics, and other areas, is a science that understands consumers’ perceptions, beliefs, feelings, motivations, and thoughts as well as personality and social factors that influence their purchasing and consumption behavior. In the digital era, platforms change the consumer’s journey because consumers actively engage in the value co-creation process through social media platforms and omni-channels (Lim, 2023, Wang, 2021). Thus, interactive marketing becomes the new normal in contemporary consumer participatory culture with a wide application in business practices (Lim, 2023, Wang, 2023). Such knowledge helps marketers to develop marketing strategies, including product design and development, integrative and interactive marketing communications, and consumer activities on social media platforms.
Since every individual is a consumer, consumer psychology can be applied in every aspect of human life and every stage of the consumption process. Therefore, this special topic emphasizes the managerial implications and practical applications of psychological principles to business practices. We welcome submissions, including empirical, methodological, or conceptual papers that demonstrate innovative thinking, rigorous methodologies, and insightful contributions (Wang, 2022) with a focus on real-world decision making and practical implications. In particular, the focus of this special topic is on the application of consumer psychology (consumer perception, attitude, emotion and motivation, personality and psychographics, etc.) in the following suggested (but limited) topic areas:
- Consumer behavior in the digital age;
- E-commerce and E-word of mouth;
- Consumer experience and experiential marketing;
- Behavioral economics and decision making;
- Applied behavior analysis and predictive campaign analytics;
- Social media and interactive marketing;
- Value-concretion for brand management;
- Brand extension and new branding strategies;
- Artificial intelligence and generative ChatGPT application in business;
- Big data, predictive analysis, and customization;
- Virtual reality and augmented reality in marketing applications;
- Smart technology and Internet of Things in consumer life and business applications;
- Green marketing and sustainable consumption;
- Collaborative consumption in shared economy;
- Consumer experience and new retailing strategies;
- Positive psychology and social marketing applications;
- Consumer happiness and well-being;
- Brand community and fandom management;
- Consumer behavior in private vs. public situations;
- Social influences and peer impact on consumer behavior;
- Brand loyalty, brand engagement, and brand co-creation;
- New media and communications;
- Livestreaming and short-video marketing campaigns;
- Key opinion leaders and influencer marketing;
- Consumer behavior in social media platforms;
- Consumer involvement and risk taking;
- Defensive mechanism and consumption;
- Leisure activities, entertainment, and hedonic consumption;
- Tourism, hospitality, and travel management;
- Consumer experience in service industries;
- Stereotype-based expectations and consumer behavior;
- Consumer nostalgic feeling and business strategies;
- Emotions and impulsive consumption;
- Novelty-seeking behavior and brand switching;
- Luxury consumption and buying behavior;
- Fashion-consciousness and fashion marketing management;
- Organizational and B2B buying behavior;
- Buying and selling behavior in supply chain management and omni-channel marketing;
- Advertising and sales promotions;
- Customer engagement and service management;
- Emerging consumption patterns of millennials;
- Social change and consumer values;
- Product development and design in contemporary consumer culture;
- International and cross-cultural consumer behavior and consumption patterns;
- Methodological advancement and applications;
- Ethical considerations of consumer behavior and business practice.
Prof. Dr. Chenglu Wang
Prof. Dr. Henry F. L. Chung
Prof. Dr. Jin Sun
Prof. Dr. Yongge Niu
Dr. Liying Zhou
Topic Editors
Keywords
- consumer behavior and business strategies
- applied psychology in e-commerce and social media platforms
- predictive analytics and communications
- buying and selling behaviors in supply chains
- tourism and travel marketing
- sustainable consumption
- consumer happiness and well-being
Participating Journals
| Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC | |
|---|---|---|---|---|---|---|
Administrative Sciences
|
3.0 | 3.9 | 2011 | 20.6 Days | CHF 1400 | Submit |
Behavioral Sciences
|
2.6 | 3.0 | 2011 | 21.5 Days | CHF 2200 | Submit |
Journal of Theoretical and Applied Electronic Commerce Research
|
5.6 | 6.2 | 2006 | 38.4 Days | CHF 1000 | Submit |
MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication:
- Immediately share your ideas ahead of publication and establish your research priority;
- Protect your idea from being stolen with this time-stamped preprint article;
- Enhance the exposure and impact of your research;
- Receive feedback from your peers in advance;
- Have it indexed in Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.
Published Papers (4 papers)
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: The Positive Potential of Deepfake Technology: Evidence from a Study on Female Chinese College Students
Authors: Mengjiao Yin
Affiliation: Taihu University of Wuxi
Abstract: The advent of GAN has given rise to concerns within the academic community regarding the ethics of deepfake advertising. Existing studies on consumer perceptions of generative AI advertisements indicate a negative attitude towards the falsity inherent in deepfake advertising.
This study adopts a novel perspective. We recruited 200 female university students from the university to which the authors are affiliated and divided them into three experimental groups and one control group. The participants were invited to either watch or engage in the production of deepfake advertisements themselves.
Participants in the "Idol Experimental Group" used photographs of their idols (celebrities and stars they admire) as raw material, those in the "Relatives Experimental Group" used photographs of their loved ones (family members, partners, friends, etc.), and participants in the "Self Experimental Group" used their own photographs.
These images were fed into an open-source deepfake model called “roop” to replace the face of the female protagonist in a Chanel(brand name) advertisement with the faces from the provided photographs. Each experimental group was further divided in half, with one subset just providing photographs and observing the resulting deepfake advertisement created by the researchers, and the other subset actively creating the deepfake work under the guidance of the researchers. The control group, however, did not engage in any deepfake activities.
After the deepfake operation, participants from all four groups were asked to verbally express their attitude towards the brand for 30 seconds. Their statements were transcribed and subjected to both qualitative and quantitative content analysis. The quantitative analysis primarily measured the length of the output strings within the specified time. The qualitative analysis categorized attitudes into three components—cognition ("I think"), affect ("I feel"), and behavioral intention ("I intend to")—and deconstructed the length of the strings in these three dimensions, assigning weighted scores (behavioral intention > affect > cognition). The total score for each statement was then calculated and statistically compared.
The experimental results showed that the experimental groups exhibited a more positive brand attitude compared to the control group. Participants who actively engaged in creating deepfakes demonstrated a more positive brand attitude than those who only observed. Importantly, the positivity of brand attitude was independent of the participants' subjective perceptions of the generative effect (i.e., the perceived realism).
The innovative aspect of this study is the application of a controlled experimental method and the development of novel measurement indicators to substantiate the positive effects of deepfake advertising, Amidst a chorus of critical voices towards deepfake technology.
Certainly, the study does have its limitations. Due to constraints in computational resources, as well as difficulties inherent in the use of Google Colab for participants, such as issues with internet accessibility and the necessity for a certain level of technical knowledge, it was not feasible to recruit a large number of test subjects in China. This limitation may raise questions regarding the generalizability of the study's findings.
However, we believe that as deepfake technology matures, an increasing number of consumer interactive advertisements will be produced and integrated into social media H5 pages or specific features within apps. Therefore, this study holds practical significance for the future landscape of advertising and consumer interaction.
Additionally, to maintain stringent control over variables, the present study temporarily excluded the variable of gender, selecting females—who may possess stronger expressive abilities—as subjects for research. The examination of male responses is pending further experimental investigation to supplement the current findings.
Our research has progressed beyond the data analysis phase, and if the editorial office deem the study of significance, we are honored to expedite the submission of the full manuscript.
