Maximum economies of scale in multi-sided platforms

Abstract

The objective of our study is three-fold: a) Study Congestion in a Network: Lot of literature exists on benefits of network/platforms and how it helps to grow business. For example, presence of plethora of articles on operating model of Uber, Facebook etc. and its advantages. This positive impact of platforms is known as network effects. However, very few literatures exist on talking about the negative impact of increased user base in a network, called congestion b) Define Maximum Economies of Scale: Enough literature exists on the concept of minimum economies of scale and how wider level of output reduces the per unit cost. However, there are possibilities where increase in data availability beyond certain point results in declining utility. This concept is called maximum economics of scale and we have explored in this study how it manifests in networks c) Identify Interplay of Behavioural and Economic Aspects of Congestion: Network congestion has been studied popularly with reference to telecom industry and mainly the economical aspect of it. However, behavioural aspect of choice overload leading to congestion in a platform has not been studied