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How should physicians set prices for individual service and team-based service in the online environment? A view from the price difference (Preprint)


 BACKGROUND
 Price which has a significant effect on consumers’ exchanging value perception plays a decisive role in the product market. Different from the traditional medical market, the online medical market allows physicians considerable discretion in setting prices of their services, which begin to be paid close attention to. Physicians face a challenge with the introduction of various service styles. Some studies have begun to examine the role of price in the online medical service environment, however, limited studies have explored them in both individual and team-based contexts.
 
 
 OBJECTIVE
 Guided by transaction utility theory and price fairness, this study aims to investigate the influence of pricing strategy on service demands from the price difference perspective by focusing on two typical service models: individual service and team-based service. Moreover, team characteristics (response speed and team size) are also considered.
 
 
 METHODS
 The data collection was conducted in March 2018 and repeated in May 2018, and physicians who provide both individual service and team-based service are included in our study. Finally, a dataset consisting of 1,100 teams with 1,100 physician leaders from 14 departments such as obstetrics and gynaecology department were collected from an online medical platform in China were included.
 
 
 RESULTS
 Empirical results support most of our hypotheses. A negative influence of team-based price has been got (β = -0.282, p < 0.000). As a substitute service, higher individual service price will make patients turn to the team-based service (β = 0.164, p < 0.000). Moreover, individual service price negatively moderates the relationship between team-based service price and demands (β = -0.036, p < 0.05). By calculating the price difference between individual service price and team-based service price, we find a negative role of the price difference in affecting patient purchase decisions (β = -0.085, p < 0.05). Although we did not find a significant effect of team size, a quick response can attract more patients (β = 0.174, p = 0.05).
 
 
 CONCLUSIONS
 Price fairness provides a proper framework for understanding pricing strategy in individual and team-based service in an online environment. Understanding the effects of prices from a price difference perspective has both theoretical and practical contributions. Specifically, this study contributes to knowledge on price fairness, online medical platforms, and virtual teams, and provides management suggestions.
