Emerging Internet of things (IoT) technologies are enhancing the value of traceability information in reshaping organic food consumption behaviours. However, the best ways to measure consumers’ perceptions of the quality of traceability information remains uninvestigated. This paper explores the perceived quality of traceability information through the available literature on perceived information quality, principal-agency theory, and cue utilisation theory. Specifically, we examine how traceability information influences purchase intentions of organic foods. We conducted an online survey and collected 361 valid samples from organic milk consumers in China. Our structural equation modelling analysis led to the following key findings: first, the perceived quality of traceability information positively influences purchase intention towards organic food; second, perceived uncertainty partially mediates the main effect; and, finally, the importance of product information positively moderates the relationship between perceived uncertainty and purchase intention.

Background: The internet enables consumers to evaluate products before purchase based on feedback submitted by like-minded individuals. Displaying reviews allows customers to assess comparable experiences and encourages trust, increased sales, and brand positivity. Customers use reviews to inform decision making, whereas organizations use reviews to predict future sales. Prior studies have focused on manufactured products, with little attention being paid to health care services. In particular, whether patients prefer to use websites to discuss doctors’ reputation has so far remained unanswered. Objective: This study aims to investigate how patient propensity to post treatment experiences changes based on doctors’ online reputation (medical quality and service attitude) in delivering outpatient care services. Further, this study examines the moderating effects of hospitals’ (organizational) online reputation and disease severity. Methods: Fractional logistic regression was conducted on data collected from 7183 active doctors in a Chinese online health community to obtain empirical results. Results: Our findings show that patients prefer to share treatment experiences for doctors who have a higher medical quality and service attitude (βservice attitude=.233; P<.001 and βmedical quality=.052; P<.001) and who work in hospitals with a higher online reputation (β=.001; P<.001). Patients are more likely to share experiences of doctors who treat less severe diseases, as opposed to those treating severe diseases (β=−.004; P=.009). In addition, hospitals’ online reputation positively (negatively) moderates the relationship between medical quality (service attitude) and patient propensity to post treatment experiences, whereas the moderating effects of disease severity on doctors’ online reputation are negative. Conclusions: Our research contributes to both theory and practice by extending the current understanding of the impact of individual reputation on consumer behavior. We investigate the moderating effects of organizational reputation and consumer characteristics in online health communities.

Background: Mobile health applications are being increasingly used for people’s health management. The different uses of mobile health applications lead to different health outcomes. Although active usage of mobile health applications is shown to be linked to the effectiveness of mobile health services, the factors that influence people’s active usage of mobile health applications are not well studied. Objective: This paper aims to examine the antecedents of active usage of mobile health applications. Methods: Grounded on the 3-factor theory, we proposed 10 attributes of mobile health applications that influence the active usage of mobile health applications through consumers’ satisfaction and dissatisfaction. We classified these 10 attributes into 3 categories (ie, excitement attributes, performance attributes, and basic attributes). Using the survey method, 494 valid responses were collected and analyzed using structural equation modeling. Results: Our analysis results revealed that both consumer satisfaction (β=0.351, t=6.299, P<.001) and dissatisfaction (β=–0.251, t=5.119, P<.001) significantly influenced active usage. With regard to the effect of attributes, excitement attributes (β=0.525, t=12.861, P<.001) and performance attributes (β=0.297, t=6.508, P<.001) positively influenced consumer satisfaction, while performance attributes (β=–0.231, t=3.729, P<.001) and basic attributes (β=–0.412, t=7.132, P<.001) negatively influenced consumer dissatisfaction. The results of the analysis confirmed our proposed hypotheses. Conclusions: Our study provides a novel perspective to study the active usage of mobile health applications. By categorizing the attributes of mobile health applications into 3 categories, the differential effects of different attributes can be tested. Meanwhile, consumer satisfaction and dissatisfaction are confirmed to be independent from each other.

Background: China has achieved nearly universal coverage of the Social Basic Medical Insurance (SBMI), which aims to reduce the disease burden and improve the utilization of health services. We investigated the association between China’s health insurance schemes and health service utilization of middle-aged and older adults at different quantiles, and then explored whether the SBMI could help reduce the underutilization of health services among the middle-aged and older adults in China. Methods: Survey data of middle-aged and older adults were drawn from the China Health and Retirement Longitudinal Study (CHARLS). A linear quantile mixed regression model was utilized to provide a comprehensive understanding of the relationship between SBMI and health service utilization, which was measured by the total medical expenditure. We took the New Rural Cooperative Medical Scheme (NCMS) as the reference level and examined the associations of the Urban Employee Basic Medical Insurance (UEBMI) and the Urban Resident Basic Medical Insurance (URBMI) with health service utilization. Results: The quantile regression analysis revealed a significant positive association between URBMI and health service utilization at the 0.75 (β = 1.608, p < 0.01), 0.8 (β = 1.578, p < 0.01), 0.85 (β = 1.473, p < 0.01), 0.9 (β = 1.403, p < 0.01) and 0.95 (β = 1.152, p < 0.01) quantiles, and also a significant positive association between UEBMI and health service utilization at the 0.85 (β = 1.196, p < 0.01), 0.9 (β = 1.070, p < 0.01) and 0.95 (β = 0.736, p < 0.01) quantiles. Results showed that URBMI was significantly associated with an improvement in inpatient health service utilization of the middle-aged and older adults, and a significant positive association between UEBMI and inpatient health service utilization was observed at 0.1 (β = 0.559, p < 0.01), 0.25 (β = 0.420, p < 0.05), 0.5 (β = 0.352, p < 0.05), and 0.75 (β = 0.306, p < 0.05) quantiles. Conclusions: Inequity in health service utilization exists among the middle-aged and older adults across urban and rural Chinese areas, and it can be explained by the different reimbursement benefits of SBMI types.