Collation of Decision Support System (DSS) Models used for Bid Decisions in Construction Industry

  • Mandanna B
  • et al.
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Abstract

The past researches on key elements responsible for the successful completion of the project showed the importance of assessment and accounting of various types of risks during the bid decision process. If the contractor invests his productive time in only those projects which are meeting the organization’s goals and targets, then the chances of submitting a competitive bid is more. In order to select such appropriate projects, the measure of the effect of numerous factors on bid decision is essential. This research highlights the numerous reasons that influences the bid decisions of contractors and the contribution of these factors towards the construction of Decision Support System Models (DSS). In order to identify the factors influencing the bid decisions, past literature studies were conducted and a strong focus was given to methods such as questionnaire survey, structured and semi-structured interviews were used. The construction of the models was done after taking the opinions of contractors. From the past research it can be noted that the main factors such as client’s financial capability, contractor’s financial capability, past experience of the contractors in similar projects etc., were considered across the globe. This complex and dynamic nature of bid decision making demands a robust decision support system which can be implemented collectively at least in a construction industry within a country. Moreover, the bid decision is more of subjective in nature. So, addressing this with only quantitative models which considers past bid data, recently applied strategy etc., may not be adequate to forecast the dynamic phenomenon. This strongly proposes the requirement for development of a Qualitative model to take care of subjective decision-making situation.

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APA

Mandanna, B. S., & Holla, Dr. B. R. K. (2020). Collation of Decision Support System (DSS) Models used for Bid Decisions in Construction Industry. International Journal of Recent Technology and Engineering (IJRTE), 8(6), 11–22. https://doi.org/10.35940/ijrte.f6981.038620

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