Human Behavior and Emerging Technologies最新文献

The significance of social media content in consumers’ decision-making journeys has acquired substantial attention among scholars and business practitioners in recent times. However, the exploration of how marketing strategies should design social media content to influence behavioral intentions remains fairly inadequate, particularly within the tourism industry. This study is aimed at developing a model that includes the moderating, mediating, and configuration effects of tourism-related content (TRC) dimensions on TikTok to predict enjoyment and behavioral intention. This study employs a hybrid approach of structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA) to test hypotheses and propositions using a sample of 319 participants who have experience watching TRC on TikTok and have the intention to visit the destinations presented in the content. The results from SEM confirm that content reliability and understandability significantly influence perceived enjoyment. Furthermore, visit intention is predicted to increase through the contributions of content understandability and perceived enjoyment. Insights from the mediating effect reveal that perceived enjoyment serves as a fully mediating factor between content understandability and visit intention. Moreover, the moderating effects of gender and frequency of use exhibit significant differences in their impacts on perceived enjoyment and visit intention. The outcomes of fsQCA confirm that various configurations of TRC dimensions and enjoyment provide valuable insights for designing content-marketing strategies. The consideration of different combinations of these constructs can impact behavioral intentions. This research makes significant contributions to both theory and marketing practice, as the comprehensive discussion of the combinations of configurations provides amplified insights into this study’s findings.

With the growing prevalence of online social interactions, it is crucial to understand how the social dimension affects well-being. This study investigates the relationship between the Need for Online Social Feedback (NfOSF) and individuals’ well-being, considering the moderating role of perceived online reputation. A total of 1398 participants, predominantly female, aged 14 to 61, completed an online questionnaire. The results revealed an M-shaped pattern, indicating that both dissatisfaction and excessive satisfaction with online reputation were associated with lower well-being. For those dissatisfied with their reputation, a high desire for social feedback correlated with reduced well-being, as validation from the social environment, was lacking. Similarly, individuals with fully satisfying reputations experienced frustration in their pursuit of online social feedback. In this case, the “Fame” dimension of the NfOSF scale exhibited a negative association with well-being, highlighting the impact of grandiose expectations. The findings underscore the subjective nature of this relationship, emphasizing the role of individual characteristics and social context.

Continuous usage behavior among millennials is crucial, yet factors influencing this behavior are not well understood. This study integrates human-computer interaction and marketing research to investigate the relationship between persuasive dialogue support (PDS), attitudinal loyalty (AL), and continuous-use intention (CI) in the context of WhatsApp. The study also examines the moderating role of four cultural dimensions: uncertainty avoidance (UA), power distance (PD), masculinity (MAS), and individualism (IND) in these relationships. Data was collected from 287 WhatsApp users in four countries, and the proposed theoretical model was tested using structural equation modelling (SEM-PLS). The results indicate that PDS has a direct positive impact on AL, which in turn leads to CI. The study also found that cultural differences can moderate the relationship between PDS and AL and between AL and CI. Therefore, app developers need to consider cultural differences when designing their products and implement persuasive design aspects to boost user loyalty and intention to use. To ensure optimal app performance in diverse cultural settings, developers should strike an appropriate balance between universal design principles and culturally sensitive adaptation. However, the study’s limitations, such as reliance on self-reported data and a relatively small sample size, suggest the need for future research to expand its scope to include participants from a broader range of cultural backgrounds.

This contribution analyzes the self-perception and political biases of OpenAI’s Large Language Model ChatGPT. Considering the first small-scale reports and studies that have emerged, claiming that ChatGPT is politically biased towards progressive and libertarian points of view, this contribution is aimed at providing further clarity on this subject. Although the concept of political bias and affiliation is hard to define, lacking an agreed-upon measure for its quantification, this contribution attempts to examine this issue by having ChatGPT respond to questions on commonly used measures of political bias. In addition, further measures for personality traits that have previously been linked to political affiliations were examined. More specifically, ChatGPT was asked to answer the questions posed by the political compass test as well as similar questionnaires that are specific to the respective politics of the G7 member states. These eight tests were repeated ten times each and indicate that ChatGPT seems to hold a bias towards progressive views. The political compass test revealed a bias towards progressive and libertarian views, supporting the claims of prior research. The political questionnaires for the G7 member states indicated a bias towards progressive views but no significant bias between authoritarian and libertarian views, contradicting the findings of prior reports. In addition, ChatGPT’s Big Five personality traits were tested using the OCEAN test, and its personality type was queried using the Myers-Briggs Type Indicator (MBTI) test. Finally, the maliciousness of ChatGPT was evaluated using the Dark Factor test. These three tests were also repeated ten times each, revealing that ChatGPT perceives itself as highly open and agreeable, has the Myers-Briggs personality type ENFJ, and is among the test-takers with the least pronounced dark traits.

As one of the dark sides of smartphone use, phubbing (i.e., snubbing others during face-to-face interactions by using their smartphones) has drawn increased attention in recent years. A growing literature on phubbing has widely examined psychological and social problems related to phubbing. However, very little is known about how certain psychological states and outcomes—mainly loneliness and life satisfaction—occur in relation to phubbing. This study examined the relationships between loneliness, problematic smartphone use, phubbing, and life satisfaction, particularly within friendships. For this study, college students (N = 513; 188 men, 323 women, and two others) aged 18 to 29 (M_age = 19.85 years) completed self-report measures online. Structural equation modeling was used to measure the model, and the relationships of this study were conducted via SPSS and AMOS. As expected, the model yielded a good fit, and the findings showed that loneliness positively and indirectly predicted the enactment of friend phubbing through its influence on problematic smartphone use, which negatively predicted life satisfaction.

The multiplication of fractions was generally considered easy, but it became challenging when presented as a nonroutine problem. One solution to these challenges was integrating technology into learning. Therefore, the study is aimed at proposing a hybrid module as a solution. The design in this research was a didactical design research. The study involved 56 participants, aged 13–18 years, mainly female students from the Sasak tribe in an Indonesian junior high school. Researchers employed fraction comprehension tests, in-depth interviews, and a hybrid hypothesis module as primary instruments. For learning outcomes, NVivo-12-assisted thematic analysis was used, and for learning obstacles, retrospective-based qualitative analysis was used. The study findings revealed several factors that caused learning obstacles, including conceptual ontogenic, epistemological factors, and students’ restricted Internet access. The hybrid hypothesis module proved effective in assisting students by providing additional problem contexts and scaffolding, addressing previous learning obstacles. After implementation, there was a redesign of the hybrid module in the form of additional scaffolding to help students construct the concepts studied. This research concluded that the application of technology in the form of hybrid modules was able to minimize barriers to student learning.

In recent years, the effective enhancement of information communication effect through governmental social media in has emerged as a universally concerned issue on government governance within the social media era. As Generation Z represents the primary and frequent users of social media, understanding the factors influencing their behaviors regarding information seeking and avoidance on governmental social media platforms is essential (in China, the principal governmental social media platform is government microblogging). Employing the grounded theory methodology, 31 participants of Chinese Generation Z were recruited for the present study, and data were collected using an in-depth interview. The results showed that the factors influencing the information-seeking behavior of Generation Z towards government microblogging mainly include heuristic seeking factors (personal preference, emotional value, and following hot topics), systematic seeking factors (task demand and expert recommendation), and defensive seeking factors (defending stance, authority seeking, and impression management). The factors influencing the information avoidance behavior of Generation Z towards government microblogging mainly include heuristic avoidance factors (clickbait titles, content layout, excessive length, and high redundancy), systematic avoidance factors (selective ignorance and terminological density), and resource-limited avoidance factors (demand scarcity, time scarcity, and vitality scarcity). This study contributes to a more comprehensive understanding of the government microblogging information behavior of Generation Z. Implications for government microblogging governance, strategy recommendations, and indicates directions for future research are discussed.

In recent years, the smartphone has become ubiquitous in everyone’s lives. The smartphone has both positive and negative impacts on the users. Although addiction has been extensively studied, not much has been done to examine the association between neurofunctional regional activation and problematic smartphone use. This review, therefore, is systematically aimed at understanding the different neurofunctional regional activation differences related to smartphone addiction. The systematic review was done in four stages as follows: (1) identifying the techniques/instruments used in the literature (database search), (2) identifying relevant literature, (3) identifying criteria for inclusion and exclusion, and (4) acquiring full-text papers. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to conduct the systematic review. The literature was searched using the following databases: PubMed, Science Direct, Taylor & Francis, and Springer Link. The inclusion requirements were met by 7 articles out of 28896. The study on smartphone addiction with a focus on neurofunctional regional activation is limited. This review sheds light on neurofunctional regional activation associated with problematic smartphone usage. This will open the door to focused interventions and well-informed approaches to digital well-being in our technologically advanced society.

The importance of Digital Self-Efficacy is likely to grow as digital technology becomes increasingly widespread. To succeed in today’s digital world, it is essential for people to have a strong belief in their ability to effectively use digital technologies. Therefore, it is necessary for researchers to have adequate instruments to measure them in different populations. The Digital Self-Efficacy Scale offers an innovative technology-independent approach. It provides a multidimensional assessment grounded in the DigComp framework, allowing adaptability and facilitating comparison across diverse demographics. This study examined the validity and reliability of the Spanish-adapted version of the Digital Self-Efficacy for Equatorian workers. The results from a sample of 471 participants, with a gender-balanced distribution (43.74% female and 55.41% male) and a mean age of 34 years, showed that this translated 19-item scale is a valid and reliable measure of this construct. Nomological network analysis with SEM showed that Digital Self-Efficacy had a positive and significant association with task-technology fit and the use of technology. This suggests that workers with higher levels of Digital Self-Efficacy are more likely to use technology effectively and efficiently and that they are more likely to find technology that is a good fit for their tasks.