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Ahadzie, D K, Proverbs, D G, Olomolaiye, P O and Ankrah, N (2009) Towards developing competency-based measures for project managers in mass house building projects in developing countries. Construction Management and Economics, 27(01), 89–102.

Al-Kharashi, A and Skitmore, M (2009) Causes of delays in Saudi Arabian public sector construction projects. Construction Management and Economics, 27(01), 3–23.

Bageis, A S and Fortune, C (2009) Factors affecting the bid/no bid decision in the Saudi Arabian construction contractors. Construction Management and Economics, 27(01), 53–71.

  • Type: Journal Article
  • Keywords: Bid/no bid decision; decision making; project selection
  • ISBN/ISSN: 0144-6193
  • URL: https://doi.org/10.1080/01446190802596220
  • Abstract:
    The bid/no bid decision requires an understanding of a company's assessment in relation to factors affecting the decision. Different companies might have different assessment values. The aim is to investigate how bid/no bid decisions are influenced by different characteristics of contractors. Various factors are identified and then analysed in order to investigate their influence and relative significance. A questionnaire survey was used to identify and rank the factors affecting the bidding decision and then analyse them in terms of differences between the returned responses with respect to the differing respondent characteristics. The findings have established the ranking order of the factors affecting the bid/no bid decision and identified their weights of importance. In addition, the influence of these characteristics upon the different weights of importance given by the survey respondents is found to be statistically significant. The most influential characteristics that affected their assessment of the weight of importance are contractor size, classification status of the contractor and the main client type. Different contractors' characteristics should be reflected in the way that the bid/no bid decisions are modelled. Also, the data collected should be categorized with regards to contractors' characteristics before starting the data analysis and modelling processes.

Burford, N K and Smith, F W (1999) Developing a new military shelter system: a case study in innovation. Building Research & Information, 27(01), 35–55.

Daget, Y T and Zhang, H (2019) Decision-making model for the evaluation of industrialized housing systems in Ethiopia. Engineering, Construction and Architectural Management, 27(01), 296–320.

Du, J, Jing, H, Castro-Lacouture, D and Sugumaran, V (2019) Multi-agent simulation for managing design changes in prefabricated construction projects. Engineering, Construction and Architectural Management, 27(01), 270–95.

Durdyev, S, Hosseini, M R, Martek, I, Ismail, S and Arashpour, M (2019) Barriers to the use of integrated project delivery (IPD): a quantified model for Malaysia. Engineering, Construction and Architectural Management, 27(01), 186–204.

Han, J, Rapoport, A and Fong, P S (2019) Incentive structures in multi-partner project teams. Engineering, Construction and Architectural Management, 27(01), 49–65.

Hossain, L (2009) Communications and coordination in construction projects. Construction Management and Economics, 27(01), 25–39.

Hwang, B, Zhao, X and Lim, J (2019) Job satisfaction of project managers in green construction projects. Engineering, Construction and Architectural Management, 27(01), 205–26.

Lam, P T I and Wong, F W H (2009) Improving building project performance: how buildability benchmarking can help. Construction Management and Economics, 27(01), 41–52.

Leaman, A and Bordass, B (1999) Productivity in buildings: the 'killer' variables. Building Research & Information, 27(01), 4–19.

Liao, X, Lee, C Y and Chong, H (2019) Contractual practices between the consultant and employer in Chinese BIM-enabled construction projects. Engineering, Construction and Architectural Management, 27(01), 227–44.

Liu, S, Jin, H, Liu, C, Xie, B and Mills, A (2019) Government compensation and costs of non-competition guarantee for PPP rental retirement villages. Engineering, Construction and Architectural Management, 27(01), 128–49.

Mahamadu, A, Manu, P, Mahdjoubi, L, Booth, C, Aigbavboa, C and Abanda, F (2019) The importance of BIM capability assessment. Engineering, Construction and Architectural Management, 27(01), 24–48.

Moohialdin, A S M, Lamari, F, Miska, M and Trigunarsyah, B (2019) Construction worker productivity in hot and humid weather conditions. Engineering, Construction and Architectural Management, 27(01), 83–108.

Ozyurt, B, Dikmen, I and Birgonul, M T (2019) Clustering of host countries to facilitate learning between similar international construction markets. Engineering, Construction and Architectural Management, 27(01), 66–82.

Papamichael, K (1999) Application of information technologies in building design decisions. Building Research & Information, 27(01), 20–34.

Sang, L, Xia, D, Ni, G, Cui, Q, Wang, J and Wang, W (2019) Influence mechanism of job satisfaction and positive affect on knowledge sharing among project members. Engineering, Construction and Architectural Management, 27(01), 245–69.

Sarhan, J G, Xia, B, Fawzia, S, Karim, A, Olanipekun, A O and Coffey, V (2019) Framework for the implementation of lean construction strategies using the interpretive structural modelling (ISM) technique. Engineering, Construction and Architectural Management, 27(01), 1–23.

Sezer, A A and Bröchner, J (2019) Site managers’ ICT tools for monitoring resources in refurbishment. Engineering, Construction and Architectural Management, 27(01), 109–27.

Wang, D, Fu, H and Fang, S (2019) The efficacy of trust for the governance of uncertainty and opportunism in megaprojects. Engineering, Construction and Architectural Management, 27(01), 150–67.

Wang, Y, Liu, J, Zuo, J and Rameezdeen, R (2019) Ways to improve the project management efficiency in a centralized public procurement system. Engineering, Construction and Architectural Management, 27(01), 168–85.

Yun, S and Caldas, C H (2009) Analysing decision variables that influence preliminary feasibility studies using data mining techniques. Construction Management and Economics, 27(01), 73–87.