Matching markets in the digital age
http://science.sciencemag.org/content/352/6289/1056.full
With the new advances in technology and enterprise within the age of information technology, the concept of matching markets is applicable and viewable in every nuance of interaction between consumer to goods and services. From the diverse and exhaustive range of mobile applications, to the imposed goods and services of the digital age, digital markets impose the ability to create markets of interaction between buyers and sellers as well as an inherent network structure that helps create exchange and diffusion of information.
A grand example of matching markets at work in the digital world can be extracted from the recent year’s great increase in ride-sharing applications and services. Ride-sharing services offer opportunities, extrapolated from the advantages of the digital markets, for both consumers and drivers to be able to find perfect matching based upon costs, prices and personal evaluations. The ride-share market is the epitome of what economists have outlined as being matching markets in such that consumers who use services such as Uber, Lyft or Hitch, actually care about what driver they receive and transact with, and thus place their own individual evaluations toward the service and driver at hand. A consumer is able to evaluate a driver based on his or her price, location and any other unique feature such as vehicle and driver age. Drivers similarly are able to place evaluations on consumers based on compensation, past ratings and reviews, and willingness to carry out the proposed trip. Previous use of taxi services has been decentralized and often the matching process required burdensome amounts of consumer labor which was often difficult and time-consuming. The implementation and rise of ride-sharing services has improved matching efficiency by not only benefiting the diffusion of information between buyers and sellers but also providing the relevant data necessary to create a match in the exchanges. Ride-sharing services in metropolitan areas or large cities often provide much lower costs and much more convenience for the consumer, and also provide background information on the drivers in the area to help consumers make a decision. This pertains to the creation of values by the customer for their ride and their driver with deeming factors such as time of day, length of ride, reviews, prices and so forth.
The surge in goods and services from the current digital age, specifically with ride-share services, exemplifies the concept and establishments of matching markets. When users attempt to create rides and find drivers, bipartite sets between rider and driver are created. In conjunction, each consumer comes in with his or her own evaluation for the ride and then driver based on intrinsic market clearing prices at hand that would derive from various external factors. Depending on the specific service used, perfect matching may or may not exist in certain situations. This leads into the notion of the matching theorem, to which no perfect matching is the result of a constricted set between buyers and sellers. In the case of the ride-sharing services, there may be more riders who only value a less amount of sellers, and thus perfect matching cannot exist to meet the necessary needs and desires of each consumer. However, usually the process of consumers creating their own valuations of drivers and rides alike illustrates the process of optimal assigning and underlying market clearing prices for rides that would allow riders to find their version of the best ride available.