E-consultation is considerably significant in today’s highly competitive environment in reducing medical costs, improving operational efficiency and effectiveness, enhancing the equity of medical resources, and meeting customers’ satisfaction. However, the prosperity of e-consultation depends on doctors’ consistent participation and continued contribution. In addition, receiving a monetary return may be deemed as one of the major factors for doctors to stay on e-consultation platforms and provide the needed online services. This study investigates how a physician can achieve economic success in the online consultation market from the perspective of signaling theory. A secondary data econometric analysis using transaction data obtained from an e-consultation Website (haodf.com) was conducted. The obtained results indicate that both seller signals (knowledge contribution) and market signals (reputation), which are observable from the Website, may positively affect physicians’ income. In fact, the two types of online signals are the substitutes for each other; in addition, the impacts of both seller signals (knowledge contribution) and market signals (reputation) obtained from the Website were negatively moderated (weakened) by the offline signals (status). This study contributes to the literature by making a clear distinction between the online and offline signals, as well as between the seller signals and market signals. This study also provides practical implications, indicating that knowledge contribution and reputation are two important factors for physicians to increase their online income.

Introduction: The key step in changing health behavior is understanding why users continue to use fitness apps. Therefore, we intend to investigate the users’ intention to continue using social fitness-tracking apps. Materials and Methods: We identify two major forces driving continuous behavior. Expectation confirmation is the internal driving force and social comparison is the external driving force. A survey was conducted to test this proposed research model. We obtained 211 valid questionnaires. Results: Our results indicate that activity amount ranking (p < 0.001) and activity frequency ranking (p < 0.001) positively affect confirmation and that confirmation (p < 0.001) also positively affects the continuous intention of individuals using fitness-tracking apps. In addition, the impact of activity amount ranking and activity frequency ranking on continuous intention is moderated by expectation confirmation. Meanwhile, as the upward comparison tendency increases, the positive effect of confirmation on continuous intention decreases (p < 0.001). Conclusions: Social rank expectation and confirmation are the primary driving forces of continuous intention in individuals using fitness-tracking apps. Social rank is a meaningful and straightforward measurement individuals can use to evaluate their activity performance. An upward comparison tendency weakens the effect of confirmation on continuous intention.

The purpose of this paper is to investigate the moderating effect of disease risk in terms of the major signals (i.e. status, reputation and self-representation) on the e-consultation platforms. In this study, the proposed research hypotheses are tested using the transaction data collected from xywy.com (in Need of Therapy). In fact, xywy.com is one the leading e-consultation service websites in China that provides a platform for the interactions between the physicians and patients (Yu et al., 2016, Peng et al., 2015). Generally speaking, it has all the needed design elements and in other words, a standard e-consultation website should have such items/components as physician homepage, physician review, free consultation, paid consultation and recommendation systems. The obtained results reveal that all attributes including status, reputation and self-representation have a positive impact on physician’s online order volume. Moreover, there is a positive moderating effect of disease risk onto the online reputation, indicating a higher effect exists for the diseases with high risk. However, the effect of offline status and online self-representation is not moderated by the disease risk, indicating market signals (online reputation) may have a stronger predictive power than seller signals (offline status and online self- representation), and therefore market signals are more effective when/if the disease risk is high. E-consultation has gradually become a significant trend to provide the healthcare services, in the emerging economy such as China because of shortage of medical resources but having an adequate access in internet usage. The impacts of signals on the health care market have been validated by previous studies. However, the research focusing on the moderating effect of signaling environment in the health care industry is still lacking. As a result, the value of this research helps to bridge the aforementioned research gap.