Telematics and Informatics最新文献

As one of the most prevalent types of memes, visual memes often transcend individual cultures and languages and reach broad online communities of disparate actors. However, how the intrinsic factors of visual memes shape cross-cultural diffusion and whether visual memes can positively promote digital cultural globalization remains unclear. To answer these questions, we identified 1147 visual memes with 11,729 instances from four online communities on Instagram and Douban and manually annotated the memes in three dimensions, i.e., form, content, and emotion. Then, regression and structural causal models were designed to investigate the intrinsic factors affecting cross-cultural diffusion. Empirical results reveal that memes expressing focused and positive emotions, conveying universal topics, sourcing from films, using short captions, and featuring African or Caucasian roles are more likely to attain cross-cultural diffusion. In contrast, the memes featuring female or Asian roles are just the opposite. Moreover, the structural analysis of emotions, topics, and social identities suggests that although the dominance of Western culture and male groups persists in cross-cultural memes, visual memes have the potential to challenge the hegemonic power structures. From the prism of cross-cultural diffusion, the connotation of memes is enriched—expressive repertoires using multimodal discourses that can act as bridges between different cultures and languages. In summary, this research uncovered the effects of the intrinsic factors of visual memes on cross-cultural diffusion using regression and causal models for the first time and can help perform effective memetic engagement across different communities and cultures.

E-participation diffusion is influenced by the interactions of multiple contextual factors. This study examines how societal dynamics and governance (i.e., national culture, economic prosperity, human capital, population size, online trust, and regulation) interact to produce high and low levels of e-participation diffusion. The study uses fuzzy-set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) on a dataset of 88 countries collected from multiple sources. FsQCA reveals three paths for high e-participation diffusion (each includes either high online trust or high regulation combined with at least one additional condition) and a single path combining low online trust and regulation for low e-participation diffusion. NCA identifies that regulation, online trust, human capital, and economic prosperity are necessary conditions for high e-participation diffusion, while no necessary condition is identified for low e-participation diffusion. Uncovering casual mechanisms leading to high and low e-participation diffusion, the study contributes to the conversation on technology-mediated participatory governance interactions and guides decision makers in formulating targeted strategies to promote e-participation diffusion.

With the commercialization of ChatGPT, generative artificial intelligence (AI) has been applied almost everywhere in our lives. However, even though generative AI has become a daily technology that anyone can use, most non-majors need to know the process and reason for the results because it can be misused due to lack of sufficient knowledge and misunderstanding. Therefore, this study investigated users’ preferences for when, what, and how generative AI should provide explanations about the process of generating and the reasoning behind the results, using conjoint method and mixed logit analysis. The results show that users are most sensitive to the timing of providing eXplainable AI (XAI), and that users want additional information only when they ask for explanations during the process of using generative AI. The results of this study will help shape the XAI design of future generative AI from a user perspective and improve usability.

Internet of Things (IoT) technology has been integrated into a diverse array of products, including watches, glasses, lighting systems, and home services, and has garnered widespread consumer acceptance. While the overall IoT market has reached a stage of maturity, the adoption of wearable devices, a key subset of IoT technologies, lags behind. Recognizing the need to identify potential demand for these wearable devices, this study leverages data from the 2019 MCR survey (N=3,922) and employs five machine learning algorithms for analysis. Among these, the random forest model demonstrates the highest accuracy in predicting consumer adoption of wearable devices. Based on this model, 17 major predictors influencing adoption have been identified. The study’s findings suggest that women in their 10 s and 20 s are the most likely potential core consumers for wearable devices. These individuals are characterized by a high expenditure-to-income ratio and stringent consumption standards that take into account product quality, price, design, shopping efficiency, and brand reputation. This research contributes to the expansion of the advertising marketing literature by being among the first to employ machine learning techniques for consumer targeting strategies in the wearable device sector.

With the ceaseless flourishing of network information technologies, mobile social media have recently gained tremendous popularity and infiltrated people’s quotidian digitized lives in mainland China. Leveraging motivation theory and expectation disconfirmation approach, the principle aim of the current study is to systematically examine the dynamic influences from multidimensional perceived benefits (functional benefits, psychosocial benefits, and hedonic benefits) on WeChat users’ cumulative satisfaction, as well as to comprehensively evaluate the impact stemming from cumulative satisfaction alongside their stickiness on electronic word-of-mouth engagement (eWOM). Data were gathered utilizing an online survey from 689 active WeChat users in mainland China, and subsequently analyzed employing structure equation modeling. The pivotal findings demonstrate that functional benefits, psychosocial benefits, and hedonic benefits positively influence WeChat users’ cumulative satisfaction. Additionally, the empirical investigation discovers that WeChat users’ cumulative satisfaction and their stickiness significantly affect eWOM engagement. Additionally, the mediating role of stickiness between cumulative satisfaction and eWOM is identified. These obtained results illuminate and provide novel evidence on how mobile social media could drive users and heighten their cumulative satisfaction and stickiness which consequently would propel users’ engagement in making comments on specific products or services in contemporary mobile-saturated environments.

This paper adds to a growing literature on the willingness to pay (WTP) for internet services. We surveyed 5,200 respondents across four demographically diverse United States (US) states, and developed a curve-fitting WTP estimation technique that builds on existing conjoint analysis models. We find that users are willing to pay an extra $1.13 per month for a 1 megabits per second (Mbps) faster internet and $45.52 per month for better connection quality. We document a strong non-linearity: a given speed increment generates the most value for users with the slowest internet but confers negligible value on users with the fastest internet. Specifically, improving speed from 1 Mbps to 25 Mbps creates 2.32 times more value than improving from 25 Mbps to 100 Mbps. A similar non-linearity arises in terms of internet quality. We report large WTP discrepancies by income levels and employment status. The results corroborate that internet subsidies are most impactful if they first assist users with the poorest internet access. In this sense, subsidizing the right population could be as important as – if not more important than – raising funds to subsidize internet access.

From both scholarly and public debate there is no clear-cut answer to the question of how social media use (SMU) coincides with mental health and body image. To explain mixed results, we suggest that the active–passive dichotomy should be further specified by the content types one creates or is exposed to (i.e., authentic, edited, intimate, and positive). This study focused on (self-)photo sharing, given the popular focus on appearance on social media. We designed a cross-sectional study to examine how various types of visual active self-presentation, and exposure thereto, coincide with mental health and body image among 408 adolescents (M = 14.07, SD = 1.64; 48.8 % female). Results demonstrated that it is not about being either active or passive on social media, but rather the content types one creates, or sees, that are important to understand how SMU behaviors coincide with mental health and body image. Social media behaviors do not uniformly relate to all mental health and body image indicators. Altogether, the current study emphasized that we should move away from the active–passive frequency dichotomy and follow a more detailed communication-centered approach emphasizing the content types.

While the global gaming industry has become a significant economic force, surpassing the film and music industries in market size, it has not achieved the same level of universality as its entertainment counterparts. Previous literature has mainly focused on gaming motivation, addiction, and regulation, ignoring non-game players and their barriers. Therefore, this study explores why people are hesitant to play digital games and investigates the factors that contribute to this resistance. The current study incorporates Crawford and Godbey’s (1987) leisure barriers into Innovation Resistance Theory. Of the seven barriers identified, this study categorizes four as intrapersonal, two as interpersonal, and one as a structural barrier. Further, it explores the differences between non-game players by categorizing them into those without any digital gaming experience (NG-N) and those with previous digital gaming experience (NG-F). The findings of this study suggest that perceived incompetence and negative social perception are the main barriers to playing digital games. As for the group analysis, there is a statistically significant difference between NG-N and NG-F players. These results provide valuable insights for both gaming industry, and regulatory bodies to create a better environment for the gaming ecosystem and expand its potential user base.

Images have become integral to consumers’ sharing of consumption experiences due to their abilities of carrying rich and vivid information. Drawing from the perspective of information theory and the elaboration likelihood model (ELM), this study investigates impacts of visual information and visual appearance of user-generated photos (UGPs) on customers’ perceived review helpfulness. We utilize deep learning techniques to calculate the breadth and depth of photos (visual information), and evaluate the aesthetic value of the photos (visual appearance). By collecting a substantial amount of review, reviewer and restaurant information from the Yelp platform, our results demonstrate that the visual breadth and visual depth of review photos have a significant positive impact on review helpfulness. Notably, reviewer status and review length moderate these effects. These insights offer valuable strategies for both restaurant managers and online restaurant platforms regarding UGP management.

While artificial intelligence’s (AI) promise for fake online review detection has been investigated, other questions have emerged with ChatGPT’s introduction, a generative AI platform. This research provides a much-needed investigation into consumer reactions to reviews perceived to be generated by ChatGPT vs. a human. Results from three studies in TripAdvisor hotel review and Yelp restaurant review contexts revealed that consumers rate reviews as less useful, trustworthy, and authentic if they perceived ChatGPT generated them. Further, the findings were robust regardless of review valence and even when participants were informed the reviewer possessed a TripAdvisor Expert badge. These findings’ theoretical and practical implications are discussed, along with limitations.