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Impact of enterprise information systems on selected key performance indicators in construction project management: An empirical study


Business results and enterprise performance depends on various factors. First of all, there are primarily human resources and their knowledge, skills and competencies. Managerial decisions supported by progressive technology are other important factor. These decisions are often done based on reports and analyses with help of enterprise information systems.

The proper complementation of new technology and management system can be achieved a significant impact on key performance indicators and results of enterprises and projects. Implementation of new technology such as enterprise information system should be an asset for the enterprise. Cost and profit are one of the elementary key performance indicators. Measurement of its impact on business results are very important for construction project management. There is assumption, that exploitation of enterprise information system has effects on cost and profit in construction project management. Research discusses issue of enterprise information system impact on key performance indicators in construction project management. Research sample included results of construction projects in Slovak construction industry. Main objective of research was set as confirmation of hypotheses, that enterprise information system has impact on selected key performance indicators like cost and profit.

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  1. Venkrbec, V., & Klanšek, U. (2016). Software-based support to decision-making process regarding the selection of concrete suppliers. In Advanced and trends in engineering sciences and technologies II—Proceedings of the 2nd International Conference on Engineering and Technologies, ESaT, 29th June 2016, Vysoké Tatry (pp. 1–6).

  2. Ljevo, Ž., Vukomanović, M., & Rustempašić, N. (2017). Analysing significance of key quality factors for management of construction projects. Gradevinar, 69(5), 359–366.

    Google Scholar 

  3. Radziszewska-Zielina, E., & Sroka, B. (2018). Planning repetitive construction projects considering technological constraints. Open Engineering, 8(1), 500–505.

    Article  Google Scholar 

  4. Ying, F., & Tookey, J. (2017). Key performance indicator for managing construction logistics performance. In LC3 2017 Volume II—Proceedings of the 25th Annual Conference of the International Group for Lean Construction, Heraklion, Greece (pp. 869–876).

  5. Neely, A., Adams, C., & Kenerley, M. (2002). The performance prism: The scorecard for measuring and management business success. London: Prentice-Hall.

    Google Scholar 

  6. Constructing Excellence. (2007). Industry performance report 2007—Based on the UK construction industry key performance indicators. London.

  7. Bashekal, B. C., & Tumutegyereize, M. (2011). Measuring the performance of contractors in government construction projects in developing countries: Uganda’s context: Uganda Management Institute, Kampala. Kampala: Public Procurement and Disposal of Public assets Authority.

    Google Scholar 

  8. Humaidi, N., & Said, N. (2011). The influence of project life cycle and key performance indicators in project management performance: Comparison between ICT and construction project. In The 2nd International Conference on Construction and Project Management IPEDR (Vol. 15). Singapore: IACSIT Press.

  9. Barone, D., Jiang, L., Amyot, D., & Mylopoulos, J. (2011). Reasoning with key performance indicators. In Business Information Processing (Vol. 23).

  10. Kaplan, R. S., & Norton, D. P. (1996). Balanced scorecard: translating strategy into action. Brighton: Harvard Business School Press.

    Google Scholar 

  11. Sibiya, M., Aigbavboa, C., & Thwala, W. (2015). Construction Projects’ Key Performance Indicators: A case of the South Africa Construction Industry. In CCREM 2015.

  12. Enshassil, A., Mohamed, S., & Abushaban, S. (2009). Factors affecting the performance of construction projects in the Gaza strip, Gaza.

  13. Novak, M., & Završki, I. (2012). Mihić.: Managing information in construction business enterprises. E-gfos - Electronic Journal of the Faculty of Civil Engineering, Osijek, 5, 95–104.

    Article  Google Scholar 

  14. Kršák, B., & Kyšeľa, K. (2016). The use of social media and internet data-mining for the tourist industry. Journal of Tourism & Hospitality, 5, 1–3.

    Google Scholar 

  15. Kolarić, S., & Vukomanovoć, M. (2017). Potential of BIM and ERP integration in contractor construction companies. In Conference Proceedings: 13th International Conference Organization, Technology and Management in Construction, Zagreb (pp. 669–673). ISBN 978-953-8168-21-5.

  16. Radziszewska-Zielina, E. (2016). Analysis of the profitability of investment in renewable energy sources on the example of a semi-detached house. In E3S Web of Conferences—1st International Conference on the Sustainable Energy and Environment Development (Vol. 10).

  17. Kozlovska, M., Spisakova, M., & Mačková, D. (2016). Company size impact on construction management documents processing and using. In Advances and Trends in Engineering Sciences and Technologies—Proceedings of the International Conference on Engineering Sciences and Technologies, ESaT 2015 (pp. 299–304).

  18. Mesároš, P., Mandičák, T., Mesárošová, A., & Behún, M. (2016). Developing managerial and digital competencies trough BIM technologies in construction industry. In ICETA 2016—14th IEEE International Conference on Emerging eLearning Technologies and Applications, Proceedings (Vol. 14, pp. 217–222).

  19. Čarnický, Š. (2004). Manažérske informačné systémy podnikov. Bratislava: Ekonóm, ISBN 80-225-1822-0.

  20. Čarnický, Š., & Mesároš, P. (2009). Informačné systémy podnikov. Bratislava: Ekonóm, ISBN 978-80-225-2676-0.

  21. Devis, B., & Brabander, E. (2009). ARIS design platform: Getting started with BPM. Berlin: Springer.

    Google Scholar 

  22. Bourgeois, D. T. (2014). Information Systems for Business and Beyond. Washington, DC: Saylor Academy.

    Google Scholar 

  23. Berisha-Namani, M. (2010). The role of information systems in management decision making—An theoretical approach. Manager Journal, 12, 109–116.

    Google Scholar 

  24. Haag, S., & Cummings, M. (2006). Essentials of information systems. New York: McGraw-Hill.

    Google Scholar 

  25. Čarnický, Š. (2001). Strategická úloha informačných systémov. Acta oeconomica Cassoviensia, 5.

  26. Szilva, I., Caganova, D., Bawa, M., Pechanova, L., & Hornakova, N. (2018). Knowledge management perception in industrial enterprises within the CEE region. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 2nd EAI International Conference on ICT Infrastructures and Services for Smart Cities, IISSC 2017 and 2nd International Conference on Cloud, Networking for IoT Systems, CN4IoT 2017 (Vol. 189, pp. 66–75).

  27. Mesároš, P., & Mandičák, T. (2017). Impact of ICT on performance of construction companies in Slovakia. In IOP Conference Series: Materials Science and Engineering: WMCAUS 2017 (Vol. 24, pp. 1–9). Bristol: IOP Publishing. ISSN 1757-8981.

  28. Turban, E., et al. (2008). Information technology for management: Transforming organizations in the digital ecomonomy.

  29. Balaban, N., Belić, K., & Gudelj, M. (2011). Business process performance management: Theoretical and methodological approach and implementation. Management Information Systems, 6, 3–9.

    Google Scholar 

  30. Otley, D. (2003). Management control and performance management: Whence and wither? The British Accounting Review, 35, 309–326.

    Article  Google Scholar 

  31. Eckerson, W. (2007). Benchmark guide: Interpreting benchmark scores using TDWI’s maturity model.

  32. Neely, A. (2002). Business performance measurement: Theory and practice. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  33. Kokles, M., & Romanová, A. (2002). Informačný vek. 2. vyd. Bratislava: Sprint. ISBN 80-89085-09-1.

  34. Mesároš, P., Mandičák, T. (2017). Impact of ICT on performance of construction companies in Slovakia. In IOP Conference Series: Materials Science and Engineering: WMCAUS 2017 (Vol. 24, pp. 1–9). Bristol: IOP Publishing. ISSN 1757-8981.

  35. Ghasemi, A., & Zahedias, S. (2012). Normality tests for statistical analysis: A guide for non-statisticians. International Journal of Endocrinology and Metabolism, 10, 486–489.

    Article  Google Scholar 

  36. MacFarland, T. W., & Yates, J. M. (2016). Mann–Whitney U Test. Introduction to nonparametric statistics for the biological sciences using R. Berlin: Springer.

    Book  Google Scholar 

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The paper presents a partial research results of project VEGA 1/0828/17 “Research and application of knowledge-based systems for modeling cost and economic parameters in Building Information Modeling”. “This work was supported by the Slovak Research and Development Agency under the Contract No. APVV-17-0549”.

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Correspondence to Annamária Behúnová.

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Mesároš, P., Behúnová, A., Mandičák, T. et al. Impact of enterprise information systems on selected key performance indicators in construction project management: An empirical study. Wireless Netw 27, 1641–1648 (2021).

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  • Enterprise information system
  • Key performance indicators
  • Construction project management
  • Cost
  • Profit