Telematics and Informatics最新文献

The current 3G and 4G telecom technologies present challenges in the form of network congestion, low average revenue per user and limited applications across different industries. This is driving the need for faster adoption and implementation of 5G technologies. Researchers have largely focused on the technical aspects of 5G and its adoption on the demand side, while the focus on the supply side—business implications, enablers and barriers to adoption for the telecom service providers (TSPs)—is limited. A supply side perspective on 5G adoption in developing economies needs more attention as their ecosystem of technology deployment is different from that of developed economies. India being one of the prominent developing countries and the second largest telecom market in the world, with 5G adoption at a nascent stage, is an apt case for studying enablers and barriers. Thus, this exploratory study focuses on identifying the factors for adoption of 5G by TSPs. The study makes theoretical contributions to literature by identifying seven unique factors and eight unique subfactors and proposing a new 5G adoption model for TSPs. Recommendations are provided to aid policy and decision-makers in designing policy interventions and strategies for faster 5G adoption from the supply side of the diverse ecosystem.

COVID-19 infodemics are intertwined with the dynamic development of the pandemic. During infodemics, the challenges and difficulties are to reveal the dynamic evolution of public’s engagement to fake news rebuttals information and break through the bottleneck of previous static research. Motivated by this, fake news rebuttals engagement index (FNREI) is proposed to state the public engagement towards COVID-19 related fake news rebuttals. A total of 19,603 fake news rebuttals microblogs from Weibo are divided into four categories by latent dirichlet allocation (LDA): “status and confirmed cases of COVID-19″, ”transmission mode and living conditions of coronavirus“, ”prevention and detection of COVID-19″ and “overseas fake news and derivative events”. Time-varying parameter vector auto-regressive model (TVP-VAR) is used to explore the time-varying impact of the COVID-19 life cycle and the appearance of virus mutation (Delta, Omicron) on four categories of FNREI time series. The research results suggest that under the impact of different major events during the COVID-19 life cycle, the public's engagement to different categories of COVID-19 related fake news has different priorities, its duration and intensity is dynamically changing. This study explores the evolution of individuals’ engagement to fake news rebuttals information during the COVID-19 and provides a basis for improving fake news governance effectiveness.

Broadband connectivity is regarded as generally having a positive macroeconomic effect, but we lack evidence as to how it affects key economic activity metrics, such as firm creation, at a very local level. This analysis models the impact of broadband Next Generation Access (NGA) on new business creation at the local level over the 2011–2015 period in England, United Kingdom, using high-resolution panel data. After controlling for a range of factors, we find that faster broadband speeds brought by NGA technologies have a positive effect on the rate of business growth. We find that in England between 2011 and 2015, on average a one percentage increase in download speeds is associated with a 0.0574 percentage point increase in the annual growth rate of business establishments. The primary hypothesised mechanism behind the estimated relationship is the enabling effect that faster broadband speeds have on innovative business models based on new digital technologies and services. Entrepreneurs either sought appropriate locations that offer high quality broadband infrastructure (contributing to new business establishment growth), or potentially enjoyed a competitive advantage (resulting in a higher survival rate). The findings of this study suggest that aspiring to reach universal high–capacity broadband connectivity is economically desirable, especially as the costs of delivering broadband services decline.

With the rise of the internet and social media, many people find their news online, often only incidentally. Burgeoning research in this line of inquiry has explored the connection between incidental exposure to news (INE) and participatory political behaviors. However, certain peculiarities still need to be addressed in this area. Working with panel survey data from the United States, in this study, we uncover the relationship between incidental news exposure and political consumerism as well as nuances thereof. While there is a positive connection between overall INE and consumerism, our findings reveal that different effects emerge depending on the place of incidental exposure (on social media, traditional media, or online), thus highlighting that the focus on social media INE applied in many studies needs to be broadened. Furthermore, we find differences between those who boycott and buycott, challenging the traditional composition of the political consumerism measurement.

Studies have displayed that the favorable image of a psychotherapist increases the therapy outcome by encouraging the self-disclosure of clients. Recently, in a situation where AI psychotherapy chatbots were actively employed, this study examines how the degree of anthropomorphism in profile pictures of AI psychotherapy chatbots (company logo, robot character, human character, real human photo) affects user self-disclosure. Furthermore, this study verifies that the relationship between anthropomorphism and self-disclosure is mediated by the user’s liking and mind perception towards the chatbot. The study found that the anthropomorphism of the psychotherapy chatbot profile picture did not directly affect the user’s self-disclosure, and the higher the degree of anthropomorphism of the profile picture, the more self-disclosure when the user had a favorable feeling for the chatbot. On the other hand, when the user perceived the chatbot to have thoughts and emotions, the higher the degree of anthropomorphism of the profile picture, the lower the degree of self-disclosure. This study has significance in examining the user’s perception according to the chatbot profile picture given the situation in which a psychotherapy chatbot will be used in the actual market.

Esports has been boosted by the proliferation of gamified social live streaming (SLS) platforms over the past few years. While previous research has recognized the complexity of gamification, limited scholarship has examined gamification effectiveness in terms of consumer loyalty in esports. Through the lens of technology acceptance model (TAM), the current study surveyed esports consumers of two SLS platforms (n = 583) to explore the relationships between gamification dimensions, TAM determinants, and SLS platform loyalty. We examined the structural model on both aggregate and segment-specific levels and revealed the existence of unobserved heterogeneity in the model’s paths and observations. The findings provided unique insights into gamification effectiveness and esports consumer heterogeneity. Theoretical and managerial implications were discussed accordingly.

Narratives play a critical role in health communication and promotion on social media. This study aimed to identify the features of popular social media narratives that generate emotional support and engage users in cancer communication. We conducted a content analysis of popular breast cancer narratives (N = 410) by five influential breast cancer non-profit organizations on Facebook. Based on a theoretical framework grounded in narrative communication research, we analyzed these narratives in the following dimensions: narrative content (e.g., character attributes, events, and mood), narrative form (e.g., perspective and length), literary techniques (e.g., imperatives, metaphors, and celebrity appeals), and visual elements (e.g., the color pink, events, and vividness). Negative binomial and linear regressions were conducted to examine the relationships between narrative characteristics and three types of social media engagement: affective, cognitive, and behavioral engagement. Results showed that cancer stories that were longer, less emotionally intensive, told from the cancer survivor’s perspective, with gender identity–related information, describing the act of providing social support, explicitly requesting engagement and/or donation, and using more vivid forms of visuals such as linked images tended to be more engaging. However, different narrative features were associated with the three engagement outcomes differently. This study provides a framework for understanding how health communicators can leverage social media to share cancer narratives to reach and engage the intended audience.

Short video applications are becoming a new form of entertainment and diversion for social media users. However, the underlying reasons why people are immersed in and continue to use current short-form video applications still need to be investigated in depth. This study examines the dual drivers (flow experience and cognitive lock-in) and their antecedents of sustained use of short-form social media based on flow theory and status quo bias theory. The model proposed in this study was tested by analyzing data from a sample of 365 users. The results indicate that flow experience and cognitive lock-in positively influence continued intention to use. In addition, recommended information characteristics (self-referencing and serendipity) significantly affect flow experience, while recommendation information vividness has insignificant effects on flow experience. Also, sunk costs, network externalities, and habits positively affect cognitive lock-in. This study explains the two-factor driven path of short-video users’ continuous usage intention, as well as provides some valuable insights into the sustainable development of short video platforms.

Social bots exacerbate emotional chaos and network disorder during sudden public opinion outbreaks. Drawing on information ecology theory, we analyze how social bots as information person characteristics influence information characteristics represented by topic tendency and sentiment spreading and environmental characteristics represented by information diffusion and network influence, and further discuss the conditional role played by social bots in public opinion dynamics. By comparing different machine learning models, the study selects the XGBoost model with the highest accuracy to identify the type of social bots with specific automation features in the Chinese context. Meanwhile, based on the representative public health emergency, the study uses a large-scale social media dataset (N = 328539) to explore how social bots affect multi-dimensional public opinion dynamics in the information ecosystem. It was found that the information published by social bots and human users has an entirely different dissemination mechanism, and social bots have a significant impact on topic tendency, sentiment spreading, information diffusion, and network influence in cyberspace. Moreover, social bots also play an important moderating role in the information diffusion and network influence of affective information. Relevant findings provide a practical reference for the recognition and prevention of social bots, and help emergency management departments to stabilize public sentiments by intervening in the behavior of social bots, weakening the influence of negative public opinion, and promoting the management of public opinions in emergencies and the maintenance of network order.