Human Behavior and Emerging Technologies最新文献

Globally and in South Africa, the beauty industry, which includes high-involvement products such as skincare, fragrance, makeup, and haircare products, is experiencing robust growth, something partially attributed to the rapidly growing influence of beauty social media influencers. While increased attention is being paid to social media influencer marketing in academic literature, most of these studies focus on the characteristics of the social media influencer rather than on the content that they deliver. Moreover, there is a paucity of studies that specifically consider YouTube vlogs in relation to beauty products and Generation Y female consumers. The purpose of this research was to determine the perceived value and purchase influence of beauty vlog content on YouTube amongst Generation Y female (females born from 1986 to 2005) consumers from the emerging market perspective of South Africa. The study adopted an explanatory research design, whereby data were collected using an electronic questionnaire from 340 Generation Y female consumers. The results of the path analysis indicate that the beauty vlog content dimensions of informativeness, entertainment, and credibility collectively account for 72% of the variability in Generation Y female consumers’ perceived value of beauty vlog content on YouTube. In turn, this perceived value, along with its predictors, accounts for almost 50% of the variance in the purchase influence of such vlogs amongst Generation Y female consumers. These findings confirm the salience of beauty brands engaging with YouTube beauty vloggers when targeting Generation Y female consumers. Moreover, when choosing which beauty vloggers to engage with, the results highlight the need to seek out those with a proven track record for delivering informative and interesting beauty product content and who consistently exercise a high degree of integrity in their beauty product review vlogs.

Employee monitoring software enables employers to oversee their workforce, even when working remotely. While it has the potential to enhance efficiency, productivity, and profitability within an organization, there are also significant risks associated with its adoption, such as violations of privacy, security intrusions, and lack of transparency. Although recent research thoroughly discusses the role of employers in the ethical use of monitoring, the role of monitoring software vendors has yet to be explored. Therefore, this research is aimed at exploring vendors’ current involvement in mitigating the risks of employee monitoring software. To achieve this, a content analysis was conducted on 15 websites selling employee monitoring software to examine how vendors address these risks. Given the lack of relevant literature and the possible reluctance of vendors to discuss the risks in surveys or interviews, content analysis enables a systematic review of the available software and the portrayal of employee monitoring on their websites. The findings show that risk-mitigating features are uncommon in the solutions offered by these companies. Furthermore, vendors tend to misrepresent and under-represent the risks of monitoring tools on their webpages compared to the benefits. With insights from this study, policymakers and advocates can develop new measures to promote the ethical use of employee monitoring. These measures could include establishing a knowledge center to provide general, evidence-based information about risks and benefits as an objective third party.

Attending to the phone while interacting face-to-face with another person, a behaviour known as phubbing, can be detrimental to the phubbed person’s psychological wellbeing. Recent research revealed that phubbing friends and partners indirectly affected the phubbed individual’s wellbeing. The aim of this study was to investigate the effect of children’s phubbing on parents’ psychological wellbeing; not the effect of parents’ phubbing on children’s psychological wellbeing, which has been the focus of most of current research. Two hundred and sixty six (266) parents of smartphone users participated in a web survey. The questionnaire measured parents’ experience of being phubbed by their children, psychological wellbeing, relationship satisfaction, loneliness, and self-esteem. The analysis showed a significant indirect effect of children’s phubbing on parents’ psychological wellbeing through the mediating roles of relationship satisfaction and loneliness. Children’s phubbing increased parents’ feelings of loneliness, and this rise in levels of loneliness worsened parents’ psychological wellbeing. Similarly, children’s phubbing decreased parents’ relationship satisfaction with their children, and this decrease in feelings of relationship satisfaction worsened parents’ psychological wellbeing. Additionally, children’s phubbing affected parents’ psychological wellbeing through the mediating roles of relationship satisfaction and loneliness in sequence (chain effect). As children’s phubbing increased parents’ feelings of loneliness, parents’ relationship satisfaction with their children dropped. The lowering of feelings of relationship satisfaction worsened parents’ psychological wellbeing. A moderated mediation analysis revealed that children’s phubbing decreased parents’ relationship satisfaction with their children, especially for parents who are low on self-esteem. This study is one of the first that offers insights into how children’s phubbing and parents’ psychological wellbeing are related.

The research aspired to determine the effecting determinants of the implementation of Fourth Industrial Revolution (4IR) technologies in the manufacturing industry, examining how 4IR readiness (R) acts as a mediator to facilitate the process of 4IR adaptation (ADP) in Bangladesh. Employing the extended technology–organization–environment (TOE) framework, the research method integrated both quantitative approaches and structured surveys using random sampling approaches to explore the specific determinants that influence the adoption of 4IR technologies. A total of 500 organizations were approached with an online questionnaire, yielding 370 completed responses, a response rate of 74%. After ensuring the reliability and validity of the findings, the structural equation model was analyzed using SmartPLS 4.0 and SPSS 29 with structural equation modeling (SEM). A statistically significant positive correlation was observed among technology readiness (TR), government support (GS), and technology innovation decision-making (TIDM) on 4IR R, as well as 4IR R on 4IR ADP based on the findings. Practical implications were discussed with a focus on strategic recommendations for policymakers and industry leaders to enhance the structural and supportive infrastructure necessary for 4IR integration. To extend the R and flexibility of the manufacturing sector in anticipation of the 4IR, policymakers must urgently contemplate the expansion of government aid and the formation of expert consulting groups. The originality of this study applied in its ADP of the TOE framework to the context of a developing country, specifically targeting the R factors that facilitate technological ADP in Bangladesh. Unlike traditional models that focus solely on technological adoption, this extended model integrates organizational and environmental factors, offering a comprehensive view of industry R. The findings highlighted the significant positive correlations between technology infrastructure R, governmental support, and decision-making processes in technology innovation, which distinguish this model by its specific ADP to the developmental and economic conditions in a developing economy like Bangladesh.

Medical service digitalization not only simplifies the work of professionals but also facilitates communication with patients. However, how medical providers can implement digital transformation with limited resources and invest in digital technologies to achieve the best benefits is yet unknown. In this study, a review of the literature related to the orthodontic process and interviews with relevant orthodontics digital transformation stakeholders were conducted. Content analysis was subsequently performed to construct an evaluation framework for the digital transformation of the orthodontic service. Next, this study conducted questionnaire design, DRA model construction, and DEMATEL analysis. This research constructed an evaluation framework of the digital transformation of four procedures, namely, clinical evaluation (CE), therapeutic communication (TC), treatment procedures (TPs), and patient tracking (PT). Taking Taiwan as a case, a total of 88 valid questionnaires were obtained from orthodontic digital transformation stakeholders. The results of the DRA-NRM show that the healthcare digital transformation process in Taiwan starts at CE and that the project needs policy support or business transformation. Next, the TC project is considered to be the most important stage of the medical digitalization transformation and requires a full investment of resources. In the subsequent TP phase, marketing efforts need to be stepped up to convince stakeholders of the benefits of medical digitization. Finally, PT can be postponed during digitalization until sufficient support and resource inputs are available. This study makes strategic recommendations for orthodontic digital conversion and establishes a plan and future direction for the digital transformation of healthcare services.

This paper introduces a neural network-based model designed for classifying emotional states by leveraging multimodal physiological signals. The model utilizes data from the AMIGOS and SEED-V databases. The AMIGOS database integrates inputs from electroencephalogram (EEG), electrocardiogram (ECG), and galvanic skin response (GSR) to analyze emotional responses, while the SEED-V database continuously updates EEG signals. We implemented a sequential neural network architecture featuring two hidden layers, which underwent substantial hyperparameter tuning to achieve optimal performance. Our model’s effectiveness was tested through binary classification tasks focusing on arousal and valence, as well as a more complex four-class classification that delineates emotional quadrants for the emotional tags: happy, sad, neutral, and disgust. In these varied scenarios, the model consistently demonstrated accuracy levels ranging from 79% to 86% in the AMIGOS database and up to 97% in SEED-V. A notable aspect of our approach is the model’s ability to accurately recognize emotions without the need for extensive signal preprocessing, a common challenge in multimodal emotion analysis. This feature enhances the practical applicability of our model in real-world scenarios where rapid and efficient emotion recognition is essential.

TikTok, a popular social media network, has gained an immense worldwide following because of its entertaining short video format. The main aim of this study was to understand the dynamic association between the variables TikTok addiction, impulsivity, digital maturity, and morality in young adults. For this purpose, a quantitative study with a correlational research design was adopted. Purposive sampling was used to select 423 TikTok users from private universities, with 209 males and 214 females included. The data was collected through the TikTok Addiction Scale, which has been adapted from the Social Media Addiction Scale (Sahin, 2018), the Barratt Impulsiveness Scale Version 11 (Barratt et al., 1995), the multidimensional Digital Maturity Inventory (Laaber et al., 2023), and the Moral Character Questionnaire (Furr et al., 2022). The results showed a strong significant positive relationship between TikTok addiction and impulsivity, but significant negative correlation with digital maturity and morality. Impulsivity had a strong significant negative relationship with digital maturity and morality, whereas digital maturity had a strong positive relationship with morality. The results of this study can be helpful in raising awareness about the adverse effects of TikTok addiction and in promoting digital literacy through workshops or seminars.

Conversational agents (CAs) are effective tools for health behavior change, yet little research investigates the mechanisms through which they work. Following the Computer as Social Actors (CASA) paradigm, we suggest that agents are perceived as human-like actors and hence influence behavior much as human coaches might. As such, agents should be designed to resemble ideal interaction patterns, for example, by resembling their users. In this registered report, we evaluated this paradigm by testing the impact of customization on similarity and reciprocity, which in turn were hypothesized to improve perceptions of the agent and compliance with the agent’s recommendations to complete a cognitive training exercise. In an online study, 2437 participants were randomly assigned to one of two surface-level CA customization conditions (present/absent) and to one of two deep-level CA customization conditions (present/absent) in a between-subject experimental design. As part of a conversation flow with a CA, participants assigned to the present surface- and/or deep-level customization conditions were able to choose their preferred CA based on the four personality summaries and/or choose their CA’s gender (male/female/agender robotic), avatar (choice between seven avatars corresponding to the chosen gender), and name. While the ability to customize increased similarity to the user and the perceptions of customizability, our findings show that customization did not impact experience or compliance. However, the perceived customizability of the agent was linked to increases in the likeability and usefulness of the agent. We conclude that our work finds no negative effects of customization; yet, its impact on the relationship between the agent and its user is complex and can benefit from more research as merited by its applicability to public health. As aging and ill populations increase the burden on health systems worldwide, CAs have the potential to transform the landscape of accessible care.

Consumers’ willingness to pay a price premium is pivotal for assessing brand value and competitive advantage. Yet, limited and scattered research has focused on how combining brand emotion, strength, and brand loyalty can influence consumers’ willingness to accept a price premium. The present study examines the role of brand attachment, brand strength, and brand loyalty in determining consumers’ willingness to pay a price premium and explores their interplay using a serial mediation model within a unified framework, specifically focusing on home appliance brands. Data from 323 valid questionnaires collected from Algerian households were analyzed using PLS-SEM. Results demonstrate that consumers’ willingness to pay a price premium is significantly and positively influenced by brand strength, brand attachment, and brand loyalty. Furthermore, the relationship between brand strength and consumers’ willingness to pay a price premium is mediated positively by brand attachment and brand loyalty. Grounded on various theories and addressing gaps captured in previous studies, this research is considered pioneering in this field. This study significantly advances our understanding of how brand emotional bonds, brand relationships, and brand strength interplay to influence consumers’ willingness to pay a premium. The findings highlight the importance for brand managers to sustain robust brands to stimulate consumers’ opening to pay extra, thereby achieving and maintaining long-term success in a competitive market.

The integration of big data analytics in digital marketing has fundamentally transformed how organizations understand and influence consumer behavior. This systematic review explores the potential of big data to offer deep insights into consumer preferences and behaviors. The current literature on big data and consumer behavior showcases its potential in enhancing marketing and customer experiences. However, significant gaps exist, such as longitudinal studies on how continuous big data–driven personalization affects consumer trust and loyalty over time. Addressing these gaps will advance academic understanding and offer practical insights for optimizing marketing strategies and improving customer experiences ethically. Focusing on these areas will contribute to a holistic view of big data’s responsible use in digital marketing. By utilizing large datasets, businesses can now tailor their marketing strategies to individual consumers, enhancing customer satisfaction and engagement. Adopting the PRISMA methodology, this review synthesizes recent literature to evaluate the benefits of big data in digital marketing. The research was conducted through a rigorous five-stage process, encompassing the identification of key research questions, database searches, and the critical analysis of selected articles: (1) defining the initial topic, (2) developing the appropriate research questions, (3) identifying the necessary keywords, (4) identifying and searching databases, and finally (5) accessing and reading the articles. The databases that were searched were as follows: Scopus, Web of Science, Emerald Insight, Springer Link, and ScienceDirect. The articles that were selected were 19, in a total sum of 265 identified articles. The findings consolidate current knowledge on how big data analytics can optimize marketing strategies and consumer experiences. Ultimately, this review underscores the transformative potential of big data in digital marketing, highlighting its role in enhancing customer insights and driving more effective marketing strategies.