title: The Impact of the Internet on Health Consultation Market Concentration: An Econometric Analysis of Secondary Data.
abstract: Many markets have traditionally been dominated by a few best-selling products, and this is also the case for the health care industry. However, we do not know whether the market will be more or less concentrated when health care services are delivered online (known as E-consultation), nor do we know how to reduce the concentration of the E-consultation market.
  
  
  
  The aim of this study was to investigate the concentration of the E-consultation market and how to reduce its concentration through information disclosure mechanisms (online reputation and self-representation).
  
  
  
  We employed a secondary data econometric analysis using transaction data obtained from an E-consultation Website (haodf.com) for three diseases (infantile pneumonia, diabetes, and pancreatic cancer) from 2008 to 2015. We included 2439 doctors in the analysis.
  
  
  
  The E-consultation market largely follows the 20/80 principle, namely that approximately 80% of orders are fulfilled by nearly 20% of doctors. This is much higher than the offline health care market. Meanwhile, the market served by doctors with strong online reputations (beta=0.207, P<.001) or strong online self-representation (beta=0.386, P<.001) is less concentrated.
  
  
  
  When health care services are delivered online, the market will be more concentrated (known as the "Superstar" effect), indicating poor service efficiency for society as a whole. To reduce market concentration, E-consultation websites should provide important design elements such as ratings of doctors (user feedback), articles contributed by doctors, and free consultation services (online representation). A possible and important way to reduce the market concentration of the E-consultation market is to accumulate enough highly rated or highly self-represented doctors.
authors: E-commerce Institute, School of Business, East China University of Science and Technology, Shanghai, China.
authors: Jia
authors: 0000-0002-4422-2647
authors: J
authors: Li
authors: E-commerce Institute, School of Business, East China University of Science and Technology, Shanghai, China.
authors: Ya
authors: 0000-0002-7633-1127
authors: Y
authors: Zhang
authors: E-commerce Institute, School of Business, East China University of Science and Technology, Shanghai, China.
authors: Ling
authors: 0000-0002-9570-2587
authors: L
authors: Ma
authors: E-commerce Institute, School of Business, East China University of Science and Technology, Shanghai, China.
authors: Xuan
authors: 0000-0001-5370-937X
authors: X
authors: Liu
mesh_terms: D003625:Data Collection / Q000191:economics / Q000379:methods; D006801:Humans; D020407:Internet / Q000191:economics*; D017059:Models, Econometric; D012017:Referral and Consultation / Q000191:economics*
keywords: E-consultation; information asymmetry; long tail effect; market concentration; online reputation; self-representation; signaling theory; superstar effect