Measurement of Technical Efficiency Using the Dea and Sfa Methods: A Case Study on Malaysian Transport Manufacturing Industry

Abstract

and make it difficult for them to decide on the best courses of action to be taken to improve the industry's TE. TE is widely used as an indicator to gauge the efficiency level of a company or an industry (Mahadevan, 2004) and it has been used successfully to measure said levels in various organisations and industries (Cullinane et al., 2006). In general, approaches to measuring TE can be classified into two, namely, parametric, and non-parametric (Jarboui et al., 2012).An example of a parametric approach is the Stochastic Frontier Analysis (SFA), which evaluates the cost, profit, or production functions based on the input, output, and environmental parameters (Aigner et al., 1977). In the estimation, the effects of random errors and inefficiencies are considered immaterial Abstract: At present, there is limited research on the state of the transport manufacturing industry in Malaysia. This article presents an analysis on the technical efficiency (TE) of the Malaysian transport manufacturing industry using the established parametric and non-parametric approaches of Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), respectively based on Department of Statistics Malaysia (DoSM) data of 611 firms between 2005 and 2010. The results showed that within the DEA approach, the Variable Return to Scale (VRS) model gave higher average efficiency than the Constant Return to Scale (CRS) model, whereas the Translog function was found to be superior to the Cobb-Douglas function in the SFA approach. Overall, high efficiency values were found in both the parametric and non-parametric methods and the results were consistent. Spearman's coefficients showed weak correlations between the DEA and SFA approaches, with inconsistencies among the samples. Limited comparisons, however, could be made based on subsectors. Although inconsistencies were found in both approaches to identify firms with best and worst performances, the methods could still be useful in measuring TE through a careful selection of the input and output variables, depending on the context, objectives, and environment of the measurement.

Technical efficiency in the Malaysian electric and electronic manufacturing industry: A stochastic frontier analysis approach

“…Examining this relationship in relation to an efficiency frontier holds significant interest for government and investment agencies, economists, and management professionals.The extent of technical inefficiency is captured by the difference between the efficiency frontier and the actual input-output relationship. Studies on TE have been conducted widely in various areas, such as the Indian manufacturing sector (Singh, Ashraf, & Ashish, 2019) carrot production (Abunyuwah, Yenibehit, & Ahiale, 2019) the Malaysian transportation industry (Hashim, Mohamed, Fahmy-Abdullah, & Sieng, 2021) and the Chinese energy industry (Wanke, Tan, Antunes, & Hadi-Vencheh, 2020) and agricultural production (Huang, Xu, & Guo, 2021). This evidence indicates that TE has been recognised as a relevant indicator for evaluating production efficiency and identifying weighted input that enhances efficiency.…”