Effective contracting for high operational performance in projects

Maria Kapsali, Kurt Roehrich, Pervaiz Akhtar

Research output: Contribution to journalArticle

3 Citations (Scopus)
75 Downloads (Pure)


The purpose of this paper is to examine combinations of contract clauses in order to ascertain which combinations correlate to high operational performance (OP).

Two hypotheses were formulated from contracting theory and tested on data collected from 45 projects. Fuzzy set qualitative comparative analysis was used and validated with multiple regression and simulation.

The hypotheses were tested to determine whether combinations of classical, relational, and/or associational contract clauses correlate to high OP. The results show that whereas high OP correlates to combinations of relational and associational contract clauses, classical and relational clauses should not be combined.

Research limitations/implications
Directions are proposed to guide future research in order to produce a more nuanced testing of contractual complementarity.

Practical implications
The managerial implications of the findings include a more thorough understanding of the use of contract clauses and of which clauses managers should combine to achieve high OP.

This study contributes to the theory of contractual incompleteness and complementarity, specifically in the context of project contracting. The analysis produced two theoretical implications: first, that better performing contracts are created when combining relational and associational contract clauses; and second, that in projects, relational and classical contract clauses are not complementary with regards to realizing high OP.
Original languageEnglish
Pages (from-to)294-325
Number of pages32
JournalInternational Journal of Operations & Production Management
Issue number2
Early online date4 Feb 2019
Publication statusPublished - 4 Feb 2019


  • Classicjavascript:void(0);al and relational contracts
  • Contract clauses
  • Operational performance
  • Projects

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Strategy and Management
  • Management of Technology and Innovation

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