Measuring Transaction Costs in Public Sector Contracting Through Machine Learning and Contract Text.

Transaction cost (TC) theoretical constructs are central to research throughout the social sciences, yet key concepts, such as measurability and asset specificity, often defy systematic empirical measurement. In government contracting research, empirical measurements of key TC theoretical constructs...

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Publicado en:Public Administration Review Vol. 86; no. 1; pp. 199 - 217
Autores principales: Potoski, Matthew, Lund‐Sørensen, Bjarke, Petersen, Ole Helby
Formato: Artículo
Publicado: Wiley-Blackwell Jan/Feb2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Measuring Transaction Costs in Public Sector Contracting Through Machine Learning and Contract Text.
      aug:
        au:
          Potoski, Matthew
          Lund‐Sørensen, Bjarke
          Petersen, Ole Helby
        affil:
          Bren School of Environmental Science and Management, University of California, Santa Barbara California,, USA
          Department of Social Sciences and Business, Roskilde University, Roskilde, Denmark
      su:
        European Union
        Public administration
        Transaction costs
        Machine learning
        Public contracts
        Legal documents
        Statistics
        Government purchasing
        Acquisition of data
      sug:
        subj:
          Public administration
          European Union
          Other General Government Support
          Transaction costs
          Machine learning
          Public contracts
          Legal documents
          Statistics
          Government purchasing
          Acquisition of data
      keyword:
        contract management
        machine learning
        transaction costs
        contract management
        machine learning
        transaction costs
      ab: Transaction cost (TC) theoretical constructs are central to research throughout the social sciences, yet key concepts, such as measurability and asset specificity, often defy systematic empirical measurement. In government contracting research, empirical measurements of key TC theoretical constructs are limited to the International City/County Management Association's surveys of US municipal and county governments. We present a preregistered method using machine learning algorithms to generate product‐level TC measures from contract text data and a government contract manager survey. We verify the algorithms' out‐of‐sample performance and use them to generate TC measures for additional products from corresponding contract text data. The result is a publicly available database of new TC measures for 176 diverse products and services covered in the European Union's Common Procurement Directives. These new measures facilitate the application of the TC framework across public management, including research on government contracting, collaboration, networks, and governance.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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