{"title":"Competitive Strategies of Public Procurement Bidders","authors":"D. Sozaeva, K. Gonchar","doi":"10.37791/2687-0657-2022-16-3-91-104","DOIUrl":null,"url":null,"abstract":"The active promotion by the Government of the Russian Federation of measures to support small and medium-sized businesses through the system of state and municipal procurement from 2022 (the obligation to purchase at least 25% of their needs and small and medium-sized businesses instead of 15% from 2014 to 2021 [1]) has led to actualization of questions about barriers to entry into the state order markets. The purpose of the study is to create a “competition map” on the basis of which an entrepreneur entering the public procurement market will be able to determine in which industry and regional markets it is more efficient to work, taking into account the current level of competition. To achieve the stated goal, the following tasks were implemented: the results of the procurement activities of all Russian regions for 2020 and 2021 were analyzed in the format of a competition matrix: the participation of suppliers from each Russian region in procurements announced in each of the regions was evaluated, the probability of winning was determined depending on the combination participant-region”, as well as “region-object of procurement”. During the study, statistical tools were used to work with average data on competition and key factors and measurements that have a correlation. The sources of information were 3,976,711 notices and their corresponding public procurement protocols from the open data of the EIS ftp server for 2020 and 2021, collected and processed by a program written in Python using the PostgreSQL 12 database. Based on the results of the research, recommendations were given to procurement participants on which regional and industry markets it is more efficient to participate in procurement, and where the maximum probability of winning is guaranteed.","PeriodicalId":269031,"journal":{"name":"Journal of Modern Competition","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Modern Competition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37791/2687-0657-2022-16-3-91-104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The active promotion by the Government of the Russian Federation of measures to support small and medium-sized businesses through the system of state and municipal procurement from 2022 (the obligation to purchase at least 25% of their needs and small and medium-sized businesses instead of 15% from 2014 to 2021 [1]) has led to actualization of questions about barriers to entry into the state order markets. The purpose of the study is to create a “competition map” on the basis of which an entrepreneur entering the public procurement market will be able to determine in which industry and regional markets it is more efficient to work, taking into account the current level of competition. To achieve the stated goal, the following tasks were implemented: the results of the procurement activities of all Russian regions for 2020 and 2021 were analyzed in the format of a competition matrix: the participation of suppliers from each Russian region in procurements announced in each of the regions was evaluated, the probability of winning was determined depending on the combination participant-region”, as well as “region-object of procurement”. During the study, statistical tools were used to work with average data on competition and key factors and measurements that have a correlation. The sources of information were 3,976,711 notices and their corresponding public procurement protocols from the open data of the EIS ftp server for 2020 and 2021, collected and processed by a program written in Python using the PostgreSQL 12 database. Based on the results of the research, recommendations were given to procurement participants on which regional and industry markets it is more efficient to participate in procurement, and where the maximum probability of winning is guaranteed.