{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"Detecting Fraud in Public Procurement","metadata":[{"label":"dc.description.sponsorship","value":"This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree."},{"label":"dc.format","value":"Monograph"},{"label":"dc.format.medium","value":"Electronic Resource"},{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/77411"},{"label":"dc.language.iso","value":"en_US"},{"label":"dc.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.abstract","value":"Fraud in public procurement is a big problem in public sector all over the world, and is very difficult to detect in empirical studies. Common fraud schemes include corruption, collusive bidding, failure to provide the required quality, and false statements, etc. In this paper, I employed game theory, machine learning, and statistical methods to detect fraud risk in Federal Procurement Contract Data, and studied the relationship of fraud, competition and contract types. In the first section, I studied a procurement game and found that if the firms' types are close enough to each other, their strategies regarding whether or not to engage in fraud would tend to be similar. Based on this proposition, in the second section, I implemented One-Class Support Vector Machine method to train the historical data of contractors with fraud records, and developed a classifier. Then I used the classifier to classify and analyze the Federal Procurement Data. In the last section, I applied Logit Regression to the classification outcomes, and the result shows that competition has a small positive relationship with fraud risk. In addition, performance based contracts and flexible-price contracts are more inclined to fraud."},{"label":"dcterms.available","value":"2017-09-20T16:52:38Z"},{"label":"dcterms.contributor","value":"Tan, Wei."},{"label":"dcterms.creator","value":"Wang, Yajun"},{"label":"dcterms.dateAccepted","value":"2017-09-20T16:52:38Z"},{"label":"dcterms.dateSubmitted","value":"2017-09-20T16:52:38Z"},{"label":"dcterms.description","value":"Department of Economics"},{"label":"dcterms.extent","value":"25 pg."},{"label":"dcterms.format","value":"Monograph"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/77411"},{"label":"dcterms.issued","value":"2016-12-01"},{"label":"dcterms.language","value":"en_US"},{"label":"dcterms.provenance","value":"Made available in DSpace on 2017-09-20T16:52:38Z (GMT). No. of bitstreams: 1\nWang_grad.sunysb_0771E_12996.pdf: 304954 bytes, checksum: 3bd20d8c613a4a4684a2a6ed391e1ecd (MD5)\n  Previous issue date:    1"},{"label":"dcterms.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.subject","value":"FPDS, public procurement, SVM"},{"label":"dcterms.title","value":"Detecting Fraud in Public Procurement"},{"label":"dcterms.type","value":"Dissertation"},{"label":"dc.type","value":"Dissertation"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/69%2F46%2F21%2F69462102326450485342913492925347365180/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/69%2F46%2F21%2F69462102326450485342913492925347365180","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}