IDEAS home Printed from https://ideas.repec.org/a/taf/conmgt/v32y2014i6p641-651.html
   My bibliography  Save this article

On information and communication technology and production cost in construction industry: evidence from the Netherlands

Author

Listed:
  • Arno J. Van der Vlist
  • Marien H. Vrolijk
  • Geert P.M.R. Dewulf

Abstract

The interplay between information and communication technology (ICT) and the competitiveness of construction firms is considered. More specifically, the question is whether firms that invest in information and communication technology have a production cost advantage. The economics literature hypothesizes that ICT brings about a production cost advantage, as ICT brings flexibility and improves the planning, organization and control of work. To test this proposition for the construction industry, a production cost function allowing for the inclusion of ICT is formulated. Using statistical nearest-neighbour matching methods it is possible to identify the effect of ICT on production costs thereby controlling for economic moderators. Data from a sample of Dutch construction firms reveal that those firms that installed ICT capital do have a production cost advantage. The results indicate further that firms need a minimum level of ICT capital to fully benefit from its production cost advantage.

Suggested Citation

  • Arno J. Van der Vlist & Marien H. Vrolijk & Geert P.M.R. Dewulf, 2014. "On information and communication technology and production cost in construction industry: evidence from the Netherlands," Construction Management and Economics, Taylor & Francis Journals, vol. 32(6), pages 641-651, June.
  • Handle: RePEc:taf:conmgt:v:32:y:2014:i:6:p:641-651
    DOI: 10.1080/01446193.2014.911932
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01446193.2014.911932
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/01446193.2014.911932?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
    2. Mattias Jacobsson & Henrik C.J. Linderoth, 2012. "User perceptions of ICT impacts in Swedish construction companies: ‘it’s fine, just as it is’," Construction Management and Economics, Taylor & Francis Journals, vol. 30(5), pages 339-357, February.
    3. Paola Giuri & Salvatore Torrisi & Natalia Zinovyeva, 2008. "ICT, skills, and organizational change: evidence from Italian manufacturing firms," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 17(1), pages 29-64, February.
    4. Mattias Jacobsson & Henrik Linderoth, 2010. "The influence of contextual elements, actors' frames of reference, and technology on the adoption and use of ICT in construction projects: a Swedish case study," Construction Management and Economics, Taylor & Francis Journals, vol. 28(1), pages 13-23.
    5. Simon Commander & Rupert Harrison & Naercio Menezes-Filho, 2011. "ICT and Productivity in Developing Countries: New Firm-Level Evidence from Brazil and India," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 528-541, May.
    6. Jiukun Dai & Paul Goodrum & William Maloney, 2007. "Analysis of craft workers' and foremen's perceptions of the factors affecting construction labour productivity," Construction Management and Economics, Taylor & Francis Journals, vol. 25(11), pages 1139-1152.
    7. Gary S. Hansen & Birger Wernerfelt, 1989. "Determinants of firm performance: The relative importance of economic and organizational factors," Strategic Management Journal, Wiley Blackwell, vol. 10(5), pages 399-411, September.
    8. Les Ruddock & Steven Ruddock, 2011. "Evaluation of trends in the UK construction industry using growth and productivity accounts," Construction Management and Economics, Taylor & Francis Journals, vol. 29(12), pages 1229-1239.
    9. Vachara Peansupap & Derek Walker, 2006. "Innovation diffusion at the implementation stage of a construction project: a case study of information communication technology," Construction Management and Economics, Taylor & Francis Journals, vol. 24(3), pages 321-332.
    10. Emrah Acar & Ismail Kocak & Yildiz Sey & David Arditi, 2005. "Use of information and communication technologies by small and medium-sized enterprises (SMEs) in building construction," Construction Management and Economics, Taylor & Francis Journals, vol. 23(7), pages 713-722.
    11. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    12. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    13. Mark Koetse & Arno Vlist & Henri Groot, 2006. "The Impact of Perceived Expectations and Uncertainty on Firm Investment," Small Business Economics, Springer, vol. 26(4), pages 365-376, May.
    14. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hui Zhang & Yuyao Qian & Liying Yu & Zheng Wang, 2020. "Integrated Development of Information Technology and the Real Economy in China Based on Provincial Panel Data," Sustainability, MDPI, vol. 12(17), pages 1-17, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Flores, Carlos A. & Mitnik, Oscar A., 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," IZA Discussion Papers 4451, Institute of Labor Economics (IZA).
    2. Patricia M. Danzon & Andrew Epstein & Sean Nicholson, 2007. "Mergers and acquisitions in the pharmaceutical and biotech industries," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 28(4-5), pages 307-328.
    3. Jochen Kluve & Boris Augurzky, 2007. "Assessing the performance of matching algorithms when selection into treatment is strong," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 533-557.
    4. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    5. Théo Nicolas, 2019. "How Do Short-term Financial Constraints Affect SMEs’ Long-Term Investment: Evidence from the Working Capital Channel," Working papers 731, Banque de France.
    6. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
    7. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Mar 2024.
    8. Gustavo Canavire-Bacarreza & Luis Castro Peñarrieta & Darwin Ugarte Ontiveros, 2021. "Outliers in Semi-Parametric Estimation of Treatment Effects," Econometrics, MDPI, vol. 9(2), pages 1-32, April.
    9. Paolo Casini & Olivia Riera & Paulo Santos Monteiro, 2014. "Labor market effects of improved access to credit among the poor: evidence from Cape Verde," Working Papers of LICOS - Centre for Institutions and Economic Performance 484951, KU Leuven, Faculty of Economics and Business (FEB), LICOS - Centre for Institutions and Economic Performance.
    10. Steven Lehrer & Gregory Kordas, 2013. "Matching using semiparametric propensity scores," Empirical Economics, Springer, vol. 44(1), pages 13-45, February.
    11. Jones A.M & Rice N, 2009. "Econometric Evaluation of Health Policies," Health, Econometrics and Data Group (HEDG) Working Papers 09/09, HEDG, c/o Department of Economics, University of York.
    12. Bruno Cirillo & Stefano Brusoni & Giovanni Valentini, 2014. "The Rejuvenation of Inventors Through Corporate Spinouts," Organization Science, INFORMS, vol. 25(6), pages 1764-1784, December.
    13. Sokbae Lee & Yoon-Jae Whang, 2009. "Nonparametric Tests of Conditional Treatment Effects," Cowles Foundation Discussion Papers 1740, Cowles Foundation for Research in Economics, Yale University.
    14. Zeqin Liu & Zongwu Cai & Ying Fang & Ming Lin, 2019. "Statistical Analysis and Evaluation of Macroeconomic Policies: A Selective Review," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201904, University of Kansas, Department of Economics, revised Mar 2019.
    15. Martin Huber & Michael Lechner & Andreas Steinmayr, 2015. "Radius matching on the propensity score with bias adjustment: tuning parameters and finite sample behaviour," Empirical Economics, Springer, vol. 49(1), pages 1-31, August.
    16. Brett R. Gordon & Florian Zettelmeyer & Neha Bhargava & Dan Chapsky, 2019. "A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook," Marketing Science, INFORMS, vol. 38(2), pages 193-225, March.
    17. Michael Lechner, 2004. "Sequential Matching Estimation of Dynamic Causal Models," University of St. Gallen Department of Economics working paper series 2004 2004-06, Department of Economics, University of St. Gallen.
    18. Erlend E. Bø & Elin Halvorsen & Thor O. Thoresen, 2019. "Heterogeneity of the Carnegie Effect," Journal of Human Resources, University of Wisconsin Press, vol. 54(3), pages 726-759.
    19. Paweł Strawiński, 2012. "Small sample properties of matching with caliper," Working Papers 2012-13, Faculty of Economic Sciences, University of Warsaw.
    20. Flores-Lagunes, Alfonso & Gonzalez, Arturo & Neumann, Todd C., 2007. "Estimating the Effects of Length of Exposure to a Training Program: The Case of Job Corps," IZA Discussion Papers 2846, Institute of Labor Economics (IZA).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:conmgt:v:32:y:2014:i:6:p:641-651. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RCME20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.