Skip to main content
Log in

Structural equation model for construction equipment selection and contractor competitive advantages

  • Construction Management
  • Published:
KSCE Journal of Civil Engineering Aims and scope Submit manuscript

Abstract

The selection and use of appropriate construction equipment contributes to operational efficiency and contractor competitive advantages. However, numerous factors are involved in the selection of suitable construction equipment. A review of the existing literature revealed a lack of research on the causal relationships between construction equipment selection factors and contractor competitive advantages. Therefore, this study attempted to identify the selection factors through a survey of contractors’ opinions on the levels of importance of the factors that are relevant to construction equipment selection and competitive advantages. The survey data were analyzed using Structural Equation Modeling (SEM). The results suggest the following six major selection factors and their respective weights of relative importance: compatibility with site characteristics (25%), services and maintenance (19%), costs (15%), safety and environmental effects (14%), ease of acquisition (14%), and technology and innovation (13%). These selection factors influence contractor competitive advantages in terms of financial stability, corporate image and reputation, bidding opportunity, and technical capacity, and their weights of relative importance are 31%, 25%, 22%, and 22%, respectively. The findings of this study shed light on the causal relationships between the selection of appropriate construction equipment and contractor competitive advantages.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Alkass, S. and Harris, F. (1988). “Expert system for earthmoving equipment selection in road construction.” Journal of Construction Engineering and Management, Vol. 114, No. 3, pp. 426–440, DOI: 10.1061/(ASCE)0733-9364(1988)114:3(426).

    Article  Google Scholar 

  • Alkass, S., Arouian, A., and Moselhi, O. (1993). “Computer-aided equipment selection for transporting and placing concrete equipment.” Journal of Construction Engineering and Management, Vol. 119, No. 3, pp. 445–465, DOI: 10.1061/(ASCE)0733-9364(1993)119:3(445).

    Article  Google Scholar 

  • Alkass, S., El-Moslmani, K., and AlHusseinm, M. (2003). “A computer model for selecting equipment for earthmoving operations using queuing theory.” Construction Informatics Digital Library, retrieved at: http://itc.scix.net/data/works/att/w78-2003-1.content.pdf

    Google Scholar 

  • Arbuckle, J. L. (2011). IBM SPSS amos 20 user’s guide, U.S.A., IBM Corporation.

    Google Scholar 

  • Babbie, E. (1989). The practice of social research, 5th Ed., Wadsworth Publishing, Belmont, CA.

    Google Scholar 

  • Blundon, G. H. (1980). Comparison of methods for evaluating construction equipment acquisition, MSc Thesis, Concordia University, Quebec, Canada.

    Google Scholar 

  • Burt, C., Caccetta, L., Hill, S., and Welgama, P. (2005). “Models for mining equipment selection.” Proceedings of the MODSIM 2005 International Congress on Modelling and Simulation, pp. 1730–1736, retrieved at: http://www.mssanz.org.au/modsim05/papers/burt.pdf

    Google Scholar 

  • Chan, F. T. S., Lp, R. W. L., and Lau, H. (2001). “Integration of expert system with analytic hierarchy process for the design of material handling equipment selection system.” Journal of Materials Processing Technology, Vol. 116, Nos. 2–3, pp. 137–145, DOI: 10.1016/S0924-0136(01)01038-X.

    Article  Google Scholar 

  • Dalalah, D., AL-Oqla, F., and Hayajneh, M. (2010). “Application of the Analytic Hierarchy Process (AHP) in multi-criteria analysis of the selection of cranes.” Jordan Journal of Mechanical and Industrial Engineering, Vol. 4, No. 5, pp. 567–578, retrieved at: http://jjmie.hu.edu.jo/files/v4n5/Application%20of%20the%20Analytic%20Hierarchy%20Process.pdf

    Google Scholar 

  • Day, D. A. and Benjamin, N. B. H. (1991). Construction equipment guide, John Willey & Son, Inc., New York, NY.

    Google Scholar 

  • Diamantopoulos, A. and Siguaw, J. A. (2000). Introduction LISREL: A guide for the uninitiated, Sage Publication London.

    Book  Google Scholar 

  • Gate, M. and Scarpa, A. (1980). “Criteria for the selection of construction equipment.” Journal of Construction Division, Vol. 106, No. 2, pp. 207–219.

    Article  Google Scholar 

  • Hair, J. F., Jr., Black, W. C., Babin, B. J., and Anderson, R. E. (2010). Multivariate data analysis, 7th Ed., Person Prentice Hall, NJ.

    Google Scholar 

  • Han, J., Park, H., Ock, J., and Jang, H. (2014). “An international competitiveness evaluation model in the global construction industry.” KSCE Journal of Civil Engineering, Published online August 30, 2014, DOI: 10.1007/s12205-012-0486-z.

    Google Scholar 

  • Harris, F. (1989). Modern construction equipment and methods, Longman Scientific & Technical, UK.

    Google Scholar 

  • Hassan, M.D.M. (2010). “A framework for selection of material handling equipment in manufacturing and logistics facilities.” Journal of Manufacturing Technology Management, Vol. 21, No. 2, pp. 246–268, DOI: 10.1108/17410381011014396.

    Article  Google Scholar 

  • Hoang, N. N. (2010). Competitiveness assessment model for construction companies, MSc Thesis, Applied Science (Building Engineering), Concordia University, Quebec, Canada.

    Google Scholar 

  • Hooper, D., Coughlan, J., and Mullen, M.R. (2008). “Structural equation modelling: guidelines for determining model fit.” Electronic Journal of Business Research Methods, Vol. 6, No. 1, pp. 53–60, retrieved at: http://arrow.dit.ie/cgi/viewcontent.cgi?article=1001&context=buschmanart

    Google Scholar 

  • Nunnally, J.C. (1967). Psychometric theory, McGraw-Hill, New York, NY.

    Google Scholar 

  • Orozco, F., Serpell, A., and Molenaar, K. (2011). “Competitiveness factors and indexes for construction companies: findings of Chile.” Revista de la Construccion, Vol. 10, No. 1, pp. 91–107, DOI: 10.4067/S0718-915X2011000100009.

    Article  Google Scholar 

  • Pongpeng, J. and Liston, J. (2003). “Contractor ability criteria: a view from the Thai construction industry.” Construction Management and Economics, Vol. 21 No. 3, pp. 267–282, DOI: 10.1080/0144619032000049647.

    Article  Google Scholar 

  • Samee, K. and Pongpeng, J. (2012). “Construction equipment selection: a common procedure.” Proceedings of the 2 nd International Symposium on Technology for Sustainability (ISTS 2012), 21–24 November 2012, The Swissotel Le Concorde, Bangkok, Thailand, pp. 281–284.

    Google Scholar 

  • Schermelleh-Engell, K. and Moosbrugger, H. (2003). “Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures.” Methods of Psychological Research-Online 2003, Vol. 8, No. 2, pp. 23–74, retrieved at: http://www.dgps.de/fachgruppen/methoden/mpr-online/issue20/art2/mpr130_13.pdf.

    Google Scholar 

  • Schumacker, R. E. and Lomax, R. G. (2010). A beginner’s guide to structural equation modeling, 3rd Ed., Taylor and Francis Group, New York, NY.

    Google Scholar 

  • Shapira, A. and Goldenberg, M. (2007). ““Soft” considerations in equipment selection for building.” Journal of Construction Engineering and Management, Vol. 133, No. 10, pp. 749–760, DOI: 10.1061/(ASCE)0733-9364(2007)133:10(749).

    Article  Google Scholar 

  • Shapira, A. and Schexnayder, C. J. (1999). “Selection of mobile cranes for building construction projects.” Construction Management and Economics, Vol. 17, No. 4, pp. 519–527, DOI: 10.1080/014461999371439.

    Article  Google Scholar 

  • SPSS training (1998). SPSS training series by IT services, Queensland University of Technology, Brisbane, Australia.

    Google Scholar 

  • Tan, Y., Shen, L. Y., Yam, M. C. H., and Lo, A. A. C. (2007). “Contractor key competitiveness indicators (KCIs): A Hong Kong study.” Surveying and Built Environment, Vol. 18, No. 2, pp. 33–46, retrieved at: http://www.hkis.org.hk/ufiles/200712-yongtan.pdf

    Google Scholar 

  • Ullman, J. B. (2001). “Structural equation modeling: reviewing the basics and moving forward.” Journal of Personality Assessment, Vol. 87, No. 1, pp. 35–50, DOI: 10.1207/s15327752jpa8701_03.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kattiya Samee.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Samee, K., Pongpeng, J. Structural equation model for construction equipment selection and contractor competitive advantages. KSCE J Civ Eng 20, 77–89 (2016). https://doi.org/10.1007/s12205-015-0632-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12205-015-0632-5

Keywords

Navigation