Frontier analysis of the Philippine manufacturing efficiency

Eduardo S. Gayosa and Emilyn Cabanda

International Journal of Information and Decision Sciences, 2014, vol. 6, issue 1, 87-108

Abstract: This research investigates the efficiency of 100 firms from ten selected manufacturing industries in the Philippines over the period 1995-2004, using the two frontier models. The aim of this research is to evaluate and measure the technical efficiency of selected firms by applying the data envelopment analysis (DEA) and stochastic frontier analysis (SFA) approaches. A total of 1,000 pooled data are analysed using both DEA and SFA methods. New findings reveal that the average technical efficiency scores of DEA and SFA are 57.4% and 82.63, respectively, but no statistically significant correlation found. New results also suggest that older firms tend to be more technically inefficient than younger firms while larger firms tend to be more technically efficient than smaller firms. Significantly, this research has also found that an imposition of higher tariff rates can make firms to be technically inefficient. Overall, this research provides significant evidences on the usefulness of two frontier methods for evaluating manufacturing efficiency as alternative tools of performance measurement for managerial decision making.

Keywords: data envelopment analysis; DEA; stochastic frontier analysis; SFA; technical efficiency; manufacturing industry; Philippines; manufacturing efficiency; performance measurement. (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=59733 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijidsc:v:6:y:2014:i:1:p:87-108

Access Statistics for this article

More articles in International Journal of Information and Decision Sciences from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().