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Che Ibrahim, C K I, Costello, S B and Wilkinson, S (2015) A Fuzzy Approach to Developing Scales for Performance Levels of Alliance Team Integration Assessment. Journal of Construction Engineering and Management, 141(05).

  • Type: Journal Article
  • Keywords: Fuzzy; Scales; Assessment; Performance; Team integration; Project alliance; Quantitative methods;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000958
  • Abstract:
    Understanding the level of team integration in alliance projects, and how it changes over time, is key to maintaining consistently high levels of integration, and therefore performance, in highly complex projects. In response to the need to integrate teams, the Alliance Team Integration Performance Index (ATIPI), which combines seven weighted key indicators (KIs) and a set of corresponding quantitative measures (QMs) for measuring the team integration in alliance projects, was developed as part of previous research. However, the subjectivity inherent in assessing such performance requires the establishment of well-defined performance scales to ensure consistency and reliability when assessing performance. In order to address this gap in the body of knowledge, 17 recognized experts in the field of project alliancing participated in a questionnaire survey to help develop the performance scales. A systematic procedure based on fuzzy set theory, namely, the modified horizontal approach, was then applied to the survey outputs to establish a range of performance scales for each QM within five levels of performance, namely, poor, average, good, very good, and excellent. The established performance scales have shown that a high threshold score is essential for achieving an excellent performance and this reflects how critical it is for alliance teams to perform and integrate at the highest level to succeed in highly complex projects. The establishment of the performance scales contributes to the final step in converting the ATIPI from a conceptual model into a fully working assessment model. Finally, a numerical example is presented to demonstrate the application of the proposed ATIPI.