Abstract
“Mercado Publico” is a Chilean electronic platform used for purchasing processes by Chilean public organizations for the last two decades. The main aim of this study is to characterize the Chilean public procurement ecosystem by using social network analysis to detect the main communities of suppliers based on who awarded the tenders. To do this, we use a methodology that first represents the bidder-supplier relationship as a bipartite graph using purchase order information. Then we project the bipartite graph onto a monopartite graph of suppliers. We end by detecting the main supplier communities using a modularity algorithm. When we applied this methodology to the large tender segment in the Chilean public procurement market over a period of four years, we successfully detected the five largest communities and the micro and small companies which had the greatest rate of participation over time.
Highlights
Mercado Público is the public procurement system of the Chilean State and the largest electronic trading platform in Chile, through which most public goods and services are traded
BUSINESS UNDERSTANDING Table 3 shows the number of tenders, buy orders, besides of the organisms and suppliers which were present in the Chilean Public Market for the seven years period under study
WORKS As a result of the work, supplier communities were detected in the period under study, so we can conclude that it is possible to reconstruct the public procurement market
Summary
Mercado Público is the public procurement system of the Chilean State and the largest electronic trading platform in Chile, through which most public goods and services are traded. The operation of ‘‘Mercado Público’’ starts with the publication of a tender on the platform www.mercadopublico.cl, a procedure carried out independently by buyer agency where interested suppliers are invited to submit bids to provide goods or services in order for the buyer agency to select the most convenient offer according to the criteria established in the bidding rules. These rules establish the requirements, The associate editor coordinating the review of this manuscript and approving it for publication was Walter Didimo. Community detection techniques have been applied in different areas of knowledge, such as sociology, biology, information technology, and astronomy, and may have specific applications in social networks [14], communications networks [4], and grouping web clients with geographically similar interests to improve performance of dedicated web servers [17]
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