The COVID-19 pandemic has forced people to limit their physical interactions, which has led to unprecedented growth in mobile health live streaming (MHLS). Such practices have been facilitated by the rapid development of consumers’ willingness to pay for MHLS. However, few efforts appear in the literature to understand this change. This study aims to integrate the theory of planned behavior with compatibility to clarify payment motivations for MHLS during the COVID-19 pandemic in China. Accordingly, the current study used a web-based, self-reported questionnaire to collect data from 506 Chinese consumers. Of the 535 distributed questionnaires, we received 505 valid responses, yielding an effective rate of 94.3%. The valid responses were analyzed using structural equation modeling, and the associated hypotheses were tested using partial least squares regression. The results showed that attitude, self-efficacy, preferred lifestyle, information quality, and interactive immersion (but not subjective norms) significantly predicted consumers’ willngness to pay (WTP). In addition, attitude partially mediated the association between preferred lifestyle, information quality, and WTP, respectively, while the mediating role in the relationship between interactive immersion and WTP was not confirmed. These findings can be used to formulate effective marketing strategies to benefit MHLS services and mobile payment technology in the country.

As mobile healthcare services entered the public sight with high frequency during the COVID-19 pandemic, patients are increasingly recognizing the effectiveness of mobile medical consultation (MMC). Earlier studies have investigated what influences continuance intention (CI) towards MMC, but few studies have scrutinized it from the perspective of patients’ psychological distance. We formulated a framework to examine the psychological factors influencing CI towards MMC by integrating the information systems continuance model and psychological distance theory. The framework was validated using the partial least squares structural equation modeling (PLS-SEM) approach and data from 475 MMC users in China. The empirical results revealed that immediacy, telepresence, intimacy, and substitutability were significant predictors of CI, while satisfaction mediated these pathways. Pandemic-induced anxiety positively moderated the effect of immediacy on satisfaction and the effect of satisfaction on CI. Practical implementations for MMC healthcare practitioners, designers, and marketers are drawn.

Field strength is a typical indicator of air access network signals, and the prediction of field strength has important reference significance for the estimation of aerial access network signals. However, many factors affecting the field strength, such as path, terrain, sunshine, and climate, increase the computational complexity, which greatly increases the difficulty of establishing an accurate prediction system. After persistent research by researchers in recent years, the ITU‐R P.1546 model has gradually become a point‐to‐surface forecasting method for ground services recommended by ITU for ground operations in the frequency range of 30 MHz~3000 MHz. In view of the characteristics of electromagnetic signal propagation in mountainous environment, the influence of diffraction is also considered in this paper. Based on more accurate scene information such as actual terrain, the prediction calculation of electromagnetic signal propagation in a mountainous environment is proposed by using the corrected ITU‐R P.1546 model. In addition, the influence of the actual terrain is taken into account to correct the relevant parameters, and the predicted results are compared with the measured data. The results indicate that field strength prediction results of the ITU‐R P.1546 model based on the diffraction effect correction proposed in this paper in specific physical areas have better performance than those of the traditional ITU‐R P.1546 model. Among them, the determination coefficient between the measured data and the predicted results is 0.87, the average error is 5.097 dBμV/m, and the root mean square error is 6.6228 dBμV/m, which proves that the ITU‐R P.1546 model based on the corrected model is effective in the prediction of electromagnetic field intensity in the actual mountainous environment.

Mobile health livestreaming has rapidly grown and become a popular platform for consumers to receive sustainable health consultation services. However, the factors influencing consumer engagement in this context still need clarification. To address this gap, we propose a framework based on dual-process theory, which suggests that cognitive mechanism and affective mechanism are two pathways that can cultivate consumer engagement in mobile health livestreaming. Using data from 499 Chinese consumers and the partial least squares structural equation modeling (PLS-SEM) approach, we empirically corroborated our framework. The results show that perceived intelligence significantly predicts consumer engagement, while concentration is positively associated with consumer engagement. Our results also indicate that concentration moderates the relationship between perceived intelligence and consumer engagement. In addition, mobile health livestreaming features can activate the two mechanisms. Perceived synchronicity and perceived vicariousness have a significant influence on perceived intelligence, while arousal and affinity are positively associated with concentration. This study carries considerable implications for the industry in support of promotional policies to engage consumers in mobile health livestreaming.