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Optimization on the Efficiency of the Construction Sector Companies in Malaysia With Data Envelopment Analysis Model

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  • Lim Shun Jinn*

    (Centre for Bio-Diversity Research , Department of Physical and Mathematical Science, Faculty of Science, Universiti Tunku Abdul Rahman, Kampar Campus, Jalan Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia)

  • Lam Weng Hoe

    (Centre for Mathematical Sciences, Centre for Business and Management , Department of Physical and Mathematical Science, Faculty of Science, Universiti Tunku Abdul Rahman, Kampar Campus, Jalan Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia)

  • Lam Weng Siew

    (Centre for Mathematical Sciences, Centre for Business and Management , Department of Physical and Mathematical Science, Faculty of Science, Universiti Tunku Abdul Rahman, Kampar Campus, Jalan Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia)

Abstract

Construction industry contributes to the growth of economy in Malaysia. Therefore, efficiency is important to measure how well the construction company is performing in utilizing the resources to generate outcomes. The aim of this research is to evaluate the efficiency of the listed construction sectors companies in Malaysia with Data Envelopment Analysis model. In this study, BREM, DKLS, ECONBHD, HSL, KERJAYA, MELATI, MLGLOBAL, PTARAS, PUNCAK, SUNCON and ZECON are ranked as efficient companies which achieve 100% efficiency score. This study is significant because it helps to identify the efficient companies that serve as benchmark to other inefficient companies for further improvement.

Suggested Citation

  • Lim Shun Jinn* & Lam Weng Hoe & Lam Weng Siew, 2018. "Optimization on the Efficiency of the Construction Sector Companies in Malaysia With Data Envelopment Analysis Model," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 893-898:6.
    • Handle: RePEc:arp:tjssrr:2018:p:893-898
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    References listed on IDEAS

    as
    1. Piyu Yue, 1992. "Data envelopment analysis and commercial bank performance: a primer with applications to Missouri banks," Review, Federal Reserve Bank of St. Louis, issue Jan, pages 31-45.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
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