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Combining balanced scorecard with data envelopment analysis to conduct performance diagnosis for Taiwanese LED manufacturers

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  • Chih-Hsuan Wang
  • Yu-Wei Chien

Abstract

Light emitting diode (LED) is a popular component to replace the traditional lighting source or advertising sign display. In 2014, high-brightness LED has a strong growth in backlight display, mobile appliances, automotive devices and outdoor illumination. However, emerging technologies in compound materials, epitaxying, packaging and new entrants result in a scale-based economy and intensively competitive environment. Inspired by the concept of business analytics, this paper proposes a novel framework to conduct corporate diagnosis for Taiwanese LED manufacturers: (1) balanced scorecard is fused with data envelopment analysis to address the impact of operational efficiency on performance outcomes, (2) financial and non-financial indicators are incorporated into the process of performance measurement, (3) the intricate causalities between key performance indicators (KPIs) and multiple outcomes (i.e. earnings per share and return on equity) are captured and (4) managerial insights are provided to indicate adaptive adjustment on significant KPIs. More importantly, a data-set comprising representative Taiwanese LED companies spanned from 2010 to 2014 is used to justify the validity of the proposed framework.

Suggested Citation

  • Chih-Hsuan Wang & Yu-Wei Chien, 2016. "Combining balanced scorecard with data envelopment analysis to conduct performance diagnosis for Taiwanese LED manufacturers," International Journal of Production Research, Taylor & Francis Journals, vol. 54(17), pages 5169-5181, September.
  • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:17:p:5169-5181
    DOI: 10.1080/00207543.2016.1156780
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    Cited by:

    1. Ehsan Pourjavad & Rene V. Mayorga, 2019. "A comparative study and measuring performance of manufacturing systems with Mamdani fuzzy inference system," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1085-1097, March.
    2. Arnab Mitra & Arnav Jain & Avinash Kishore & Pravin Kumar, 2022. "A Comparative Study of Demand Forecasting Models for a Multi-Channel Retail Company: A Novel Hybrid Machine Learning Approach," SN Operations Research Forum, Springer, vol. 3(4), pages 1-22, December.

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