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Muhamad Azhar Nor Sabli · Mohd Fahmy-Abdullah · Lai Wei Sieng ·International Journal of Supply Chain Management ·2019

This aim of this study is to measure the technical efficiency score and identify the factors that affect the technical efficiency in plastic manufacturing firm in Malaysia for the year 2015 using the two stage Data Envelopment Analysis (DEA) method. The first stage involves calculating the efficiency score through the DEA using firm-level data, provided by the Department of Statistics, Malaysia. In the second stage, Tobit Regression Analysis was used to identify the significant factors affecting the efficiency of the plastic industry. The determining factors are the labor-ratio, training expenses, educational level ratios, wage rates, information and communications technology expenses and firm size. The results show that average efficiency score is moderate rate. Information and communication technology (ICT) expenditure, wage rate, research and development expenditure and education level are significant factors of the efficiency factor of a plastic product manufacturing firm. The implication of this decision suggests that firms need to emphasize significant factors to enhance firms' efficiency.

Muhammad Syafiq Abdul Latif · Mohd Fahmy-Abdullah · Lai Wei Sieng ·International Journal of Supply Chain Management ·2019

— Machinery manufacturing industry has been introduced since the beginning of the industrial era from European countries and developed until today. However, major challenges in machinery industry still driven by traditional production factors such as capital and labour that caused the industry still left out. Thus, the objective of the study are to analyse the level of TE and identifying determinant factors influenced to technical efficiency in the machinery manufacturing industry in Malaysia. The study was conducted by using the method of Data Envelopment Analysis (DEA) two stages. The first stage involves the calculation a score of efficiency through the DEA by using firm’s data while the second stage Regression Tobit Analysis used to identify significant factors influencing to technical efficiency in machinery industrial. This firm’s data are categorized into 3 subindustry 3-digit according to the Malaysian Standard Industrial Classifications which are consists of Manufacture of General-Purpose Machinery, Manufacture of Special Purpose Machinery and Manufacture of Installation Machinery Industrial and Equipment. A total of 636 machinery industry firms were involved in this study. Results showed the average efficiency score is at the medium level while the determinant factors were significant are wage rates, the standard of education and research and development (R&D). The implications of this study show that the machinery industry should focus their attention to the significant factors to improve the level of technical efficiency of the machinery industry.

Sulistiyo K. Ardiyono ·Economic Analysis and Policy ·2022 ·JEL: D22, L2, L6, L8

Numerous studies have explored the impact of the Covid-19 pandemic on firms’ financial performance, but the link between such performance and employment has rarely been estimated rigorously. Using the ASEAN-5 firms’ data from Q1-2018 to Q3-2021, this study shows how the pandemic affects firms’ revenue, cost, profitability, and employment heterogeneously across countries. It is argued that while revenue losses are the main challenge, widespread and prolonged restrictions in some countries have created extra complications in idle inventories and labour. In response to the revenue shocks, firms reduce their employment with an elasticity of around 0.10, indicating that a 10 per cent revenue decline is associated with a 1 per cent headcount reduction in the short run. A further examination using event analyses reveals that the path of labour adjustment is diverse across countries and industries, reflecting the degree of pandemic severity and countries’ structural issues.