Technical Efficiency Evaluation: Study on Malaysian Electrical and Electronics Firms

Fahmy-Abdullah, Mohd; Sieng, Lai Wei; Isa, Hamdan Muhammad; Malaysia, Malaysia Jabatan Perangkaan

doi:10.21315/aamj2019.24.2.1

Cited by 5 publications

(8 citation statements)

References 31 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Accordingly, the literature on productivity or firm efficiency has predominantly identified tangible assets, such as capital (or fixed assets), labour, land, raw materials, and energy (fuel), as standard determinants of productivity (Battese & Coelli, 1988;1992;Cornwell et al, 1990;Cuesta, 2000;Radam et al, 2008;Kim et al, 2009). Moving away from the general production function, some studies have considered additional quality-based inputs to investigate technical efficiency, such as human capital (education and skill levels, expenditure on training; see Fahmy- Abdullah et al, 2019), expenditures on R&D (see Schmidt and Sickles, 1984;Dilling-Hansen et al, 2003;Pattnayak and Chadha, 2008;Badunenko et al, 2008;Barassa et al, 2019) and information and communication technology (ICT).…”

Section: Firm Ownership and Productivity: Theoretical Considerationsmentioning

confidence: 99%

“…Previous studies conducted on productivity and technical efficiency in the Malaysian manufacturing sector (Abdullah & Hussein, 1993;Tham, 1997;Mahadevan, 2001;Oguchi et al, 2002;Jajri & Ismail, 2006;Khalifah et al, 2008;Radam et al, 2008;Kim et al, 2009;See & Coelli, 2012Amin et al, 2017;Fahmy-Abdullah et al, 2019) have focused largely on firm size, and firm age effects, with limited studies on productivity comparisons by firm ownership (foreign versus local; see Menon, 1998;Oguchi et al, 2002;Okamoto, 1994;Khalifah et al, 2008;Khalifah & Adam, 2009;Khalifah, 2013;Dogan et al, 2013). Most of the productivity studies related to ownership in the Malaysian manufacturing sector are for earlier years, and therefore considerably dated; 1983-1990(Okamoto, 1994), 1988-1992 (Menon, 1998);1992-1996(Oguchi et al, 2002, 2000-2004(Khalifah & Adam, 2009Khalifah, 2013).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Firm Ownership and Technical Efficiency: Production Frontier Analysis of Malaysian Manufacturing

Suntherasegarun¹,

Devadason

2023

IJIE

View full text Add to dashboard Cite

Using a new micro-based dataset of 8,472 firms covering 19 industries, this paper employs a stochastic production frontier analysis to compare time-varying technical efficiencies of foreign firms vis-à-vis local firms for the 2014 to 2019 period. The empirical findings indicate that on average, foreign firms are only marginally more (technically) efficient than local firms even after controlling for other firm characteristics. The productivity levels between foreign firms and local firms are also somewhat comparable for ‘catalytic’ industries, electrical and electronics, machinery, and chemicals. Together these results confirm that the high productivity gaps between the foreign firms and local firms in the Malaysian manufacturing sector seem to be a thing of the past.

show abstract

Section: Firm Ownership and Productivity: Theoretical Considerationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Firm Ownership and Technical Efficiency: Production Frontier Analysis of Malaysian Manufacturing

Suntherasegarun¹,

Devadason

2023

IJIE

View full text Add to dashboard Cite

show abstract

“…Overall, the average annual growth of this firm is -0.4% (MITI 2013; NAP 2014) while this industry is one of the industries that can increase the total factor productivity (TFP) as highlighted in the National Key Result Areas (NKRA). In fact, the efficiency level of the industry should be high in preparation for changes in the efficiency of new techniques and technologies as well as the emergence of new operations (Fahmy-Abdullah et al 2019a;Idris et al 2019;Sabli et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Efficiency Assessment of Transport Manufacturing Firms using a Stochastic Frontier Analysis Approach

Jofree¹,

Hashim²,

Fahmy-Abdullah³

et al. 2021

JSM

View full text Add to dashboard Cite

This paper aims to analyze the level of technical efficiency and determinants of technical inefficiency of transport manufacturing firms in Malaysia using Stochastic Frontier Analysis (SFA) approach from 2005 to 2010. Through SFA approach, hypothesis test is conducted in order to select Cobb-Douglas or Translog production function and testing the effects of technical inefficiencies. While the determining factors that been taken into account include the capital-labor ratio, training expenses, education level ratio, wage rate, information and communication technology expenditure, and firm size. Hypothesis test results show that the Cobb-Douglas production function is rejected. While the test for the effect of technical inefficiency shows its existence. Training expenses, secondary and tertiary education level ratios, wage rates and information and communication technology expenses are significant determinants for transportation manufacturing firms. However, the capital-labor ratio was found that it has reduced the level of technical efficiency. The implications of these results show that firms need to focus on investing in human capital, information technology and increase motivation among employees such as rising wage rates and reducing the use of capital appropriate to the technology.

show abstract

“…In recent years, the rapid development of the global transport industry has led to an increase in research on the level of efficiency in the transport and logistics industry. Examples include the works of Jarboui et al (2013), Chang and Tovar (2014), Gonzalez (2015), Rhee and Kim (2015), and Fahmy-Abdullah et al (2019).…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, conflicting results from the various approaches used in the studies could confuse policymakers in the transport industry to these parameters (Boame, 2004). As SFA considers the problem structure and evaluates the performance determinants and factors (Cullinane et al, 2006;Fahmy-Abdullah et al, 2019, Latif et al, 2019, the method is flexible and suitable for use in the hypothesis-testing of parameters in economic theories (Coelli, 1996;Coelli et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

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

Hashim¹,

JOFREE²,

Fahmy-Abdullah³

et al. 2021

JBSD

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Technical Efficiency Evaluation: Study on Malaysian Electrical and Electronics Firms

Cited by 5 publications

References 31 publications

Firm Ownership and Technical Efficiency: Production Frontier Analysis of Malaysian Manufacturing

Firm Ownership and Technical Efficiency: Production Frontier Analysis of Malaysian Manufacturing

Efficiency Assessment of Transport Manufacturing Firms using a Stochastic Frontier Analysis Approach

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

Contact Info

Product

Resources

About