تاثیر پذیرش فناوری تولید انعطاف پذیر بر بهره وری صنعت تولید مالزیایی

This paper investigates the influence of the adoption of Flexible Manufacturing Technology (FMT) on the Total factor Productivity Growth (TFPG) of Malaysia Manufacturing Industry. The Principal Component Analysis has been adopted to extract the most appropriate underlying dimensions of FMT to use in place of the eight FMT variables owing to the potential multicollinearity. The study has been conducted within FMT intensively adopted 16 three-digit industries that encompass 50 five-digit industries covering the years 2000–2005. The results obtained from the two situations, one, including the industry fixed effects dummy variables and the other without these, are contrasted. It is established that the model that included the industry fixed effect dummy variables has a greater explanatory power. The two principal components that account for the greater variation in FMT show positive and moderately significant relationship with TFPG. The study provides sufficient evidence to conclude that FMT has a direct and moderately significant relationship with TFPG.

The average gross domestic product (GDP) growth of Malaysia (5.5%) during 2000–2007 is lower than that (7.0) during 1990–2000. Malaysian Manufacturing sector GDP (13.0%) during 2000–2007 is much lower than the same (4.8%) for the period 1990–2000. These are some of the key indicators to the declining competitiveness of the Malaysian manufacturing industry over the period 2000–2007. It is widely believed that intensive regimes of contemporary manufacturing paradigms such as mass customisation, customerisation and instant customerisation can pave the way for a competitive manufacturing industry. The studies show that mass customisation is the core manufacturing paradigm. The studies also showed that the crucial determinant of the successful implementation of mass customisation is the abundant use of Flexible manufacturing Technology (FMT) (Wind and Rangaswamy, 2001 and Da Silveria and Fogliatto, 2005). Moreover, Malaysian Industrial Development Authority (MIDA) (MIDA, 2007) has recognised a number of promoted activities and products (for the development and production) for high technology establishments which makes them entitled to pioneer status or investment tax allowance under the promotion of Investment Act 1986. This includes FMT products such as, Computer process control systems/equipment, Process instrumentation, and Robotic equipment and Computer numerical control machine tools. The Ninth Malaysia Plan which is compiled by the Economic Planning Unit of the Prime Minister's Office presents the first five-year blueprint of the National Mission, outlining the policies and key programmes aimed at fulfilling the Mission's ‘Thrusts’ and objectives for the period 2006–2010. This aims to achieve changes in the structure and improved performance of the economy with every economic sector achieving higher value added and total factor productivity. The ‘Thrust 1’ of the Plan is aimed at making the economy more centred on human capital, particularly with increasing competition from globalisation and progressive market liberalisation. This states that, ‘Application of high technology and production of higher value added products will be given emphasis. Measures will be undertaken to migrate the electrical and electronics (E&E) industry towards high-technology and higher value added activities’. The empirical studies on FMT are clustered in the following areas; types of flexibility, types of FMT, procedure bias on investment appraisal of FMT, operational problems, market structure and competitiveness. Nonetheless, it is observed that the influence of FMT adoption on the competitiveness of the Malaysian manufacturing industry has not been adequately explored. Studies have revealed that due to the potential operational problems of FMT implementation, potential benefits of FMT might not be derived (Sharma, 2002, Gale et al., 2002 and Roller and Tombak, 1993). Moreover, Slagmulder and Bruggeman, 1992 and Fine and Freund, 1990 showed that due to ‘procedure bias on investment appraisal of FMT’, investments in FMT do not take place smoothly or effectively. Hence, additional studies need to be carried out to measure the extent to which FMT contributes to the productivity in the manufacturing industry. Evidently, only a few studies have examined the impact of specific technologies on the industry level productivity using less aggregated data. Berndt and Morrison (1995) examined the impact of high-tech investments on multifactor productivity (MFP) and three profitability measures. While the study found only limited evidence of a positive relationship between profitability and the share of high-tech capital in the total physical capital stock, it established that they were negatively correlated with MFP. Amato and Amato (2000) have investigated the impact of high-tech investments on MFP and Price Cost margin. This study established that there was a positive impact from high-tech investments regardless of whether or not the specification includes industry effects dummy variables to account for the differences in technological opportunity among industries. According to Henricsson and Ericsson, 2005, Wysokinska, 2004 and Porter, 1990, productivity is the only relevant measure of competitiveness. Zhi et al. (2003) showed that there were three productivity concepts currently adopted to measure the productivity in the manufacturing industry. Chau, 1993 and Oulton and O' Mahony, 1994 emphasised on the unresolved academic debate over whether MFP and Total Factor Productivity Growth (TFP) are the same. On account of this, the present study adopts a widely recognised productivity measure, growth of TFP (TFPG). A number of studies have been conducted in the manufacturing industry of Malaysia that adopted TFPG to measure productivity at industry level. Menon (1998) studied TFPG of foreign and domestic firms in the Malaysian manufacturing industry. Tham, 1997, Choong and Tham, 1995 and Fatimah and Mohd, 2004 adopted TFPG to examine the influence of trade policies and industry characteristics on the productivity growth of the Malaysian manufacturing industry. Abdullah and Hussein (1993) adopted TFPG to examine the productivity growth of the Malaysian resource based industries. These studies indicate that TFPG has been used in Malaysia to measure productivity growth in the manufacturing industry. Moreover, Elsadig (Elsadig, 2006a, Elsadig, 2006b, Elsadig, 2006c, Elsadig, 2007, Elsadig, 2008a and Elsadig, 2008b), estimate TFPG contribution to Malaysia's manufacturing in relation to input driven, positive and negative externalities, such as the impact of information and communications technology, human capital, foreign direct investment, carbon dioxide emissions and Biochemical Oxygen demand emissions. The purpose of this paper is to examine the influence of FMT adoption on TFPG in selected manufacturing industries of Malaysia. This adds to the previous literature by focusing more narrowly on the influence of adoption of FMT on productivity. This study developed inclusion criteria and selected FMT intensively adopted 16 MSIC three-digit industries and 50 MSIC five-digit industries included within them. All secondary data required for the study came from the Annual Surveys of Manufacturing Industries (ASMI) during 2000–2005 and Economic census data maintained by the Department of Statistics Malaysia (DOS). Another novelty in this study is that prior similar studies have been carried out at the four-digit level whereas the present study is carried out at five-digit level. The present study contributes to the previous studies by considering less aggregated data and also by considering TFPG in place of MFP. This study also considers a higher number of specific FMT variables such as, Computer Numerical Control machine tools, Numerical Controlled Machine Tools (NC), Robotics (ROB), Programmable Logic Controllers (PLC), Automated Inspections (INS), Automated Storage and Retrieval Systems (ASR), Computer Aided Design (CAD) and Local Area Networks (LAN). In order to overcome multicollinearity among FMT variables, the study extracts three underlying dimensions of FMT by adopting Principal Component Analysis. They are namely; ‘process control’ technologies, ‘production and quality control’ technologies and the ‘general control’ technology. The study adopts a questionnaire survey to compute the degree of adoption of FMT among the selected 50 five-digit industries. The present study considers eight types of FMT instead of five specific technologies, evidently the maximum number considered in a prior study. The study covers only six years from 2000 to 2005 due to the limitation of data availability. The fact is that the DOS follows the MSIC 2000 in classifying industries for the collection and publication of data. The Annual Survey of Manufacturing Industries (ASMI) reports from 2000 onwards have been prepared according to this classification and up to 1999 according to the older version of the MSIC. The older classification system is so different that more than 30% of the MSIC five digit industries (classified according to MSIC 2000) considered in this study is neither listed nor coded or described differently in ASMI reports published up to 1999 which were based on older classification system. Hence, the earliest year that was considered for this study is 2000. Since ASMI 2006 which publishes data for the reference year 2005 was released in early June 2008, the latest year considered is 2005. This has been done by Amato and Amato (2000) too in their study on impact of high-tech investments in profitably and productivity have considered only five years. Since the data for six year have been reviewed the total number of resultant observations (cases) available for this study was 300 (6 × 50 = 300).

The objective of this paper was to evaluate the influence of the degree of adoption of Flexible Manufacturing Technology on the productivity of the manufacturing industry of Malaysia. The types of Flexible Manufacturing Technology considered are namely, Computer Numerical Control Machine Tools, Numerical Controlled Machine Tools, Robotics, Programmable Logic Controllers, Automated Inspections, Automated Storage and Retrieval Systems, Computer Aided Design and Local Area Networks. The presence of multicollinearity among the eight types of Flexible Manufacturing Technology necessitated the use of three PCs to substitute the individual Flexible Manufacturing Technology variables. The Flexible Manufacturing Technology variables load onto PCs as follows: Local Area Networks, Computer Aided Design, Programmable Logic Controllers and Computer Numerical Control Machine Tools load onto PC1; Automated Storage and Retrieval Systems, Automated Inspections and Robotics load onto PC2 and Numerical Controlled Machine Tools only loads onto PC3. The three Principal Components (PCs) were labelled so that they best describe their respective constituents; PC1-‘process control’ technologies, PC2-‘production and quality control’ technologies and the PC3-‘general control’ technology. In this study, two separate models for total factor productivity growth were solved for two situations: one included the Industry Fixed Effects Dummy Variables and the other excluded it. One of the important contributions of the present study is that it reveals, regarding the models specified to study the impacts of Flexible Manufacturing Technology, that by including an industry fixed dummy variable to account for the differences in technological opportunity among different industries, the credibility of the models can be increased at least marginally. The most significant finding of the study is that the change in PC1 shows a significant and positive correlation with total factor productivity growth whereas the change in PC2 shows a marginally significant and positive relationship with total factor productivity growth. This indicates that the increase in process control technologies and production and quality control technologies have direct influences on total factor productivity growth of the Flexible Manufacturing Technology intensively adopted sub sector of the manufacturing industry. In contrast, the change in PC3 shows a highly insignificant and negative relationship with total factor productivity growth. Since both PC1 and PC2 together account for (53%) greater variation and PC3 account for (12%) relatively smaller variation among the eight Flexible Manufacturing Technology, it can be concluded that a high degree of Flexible Manufacturing Technology adoption enhances total factor productivity growth of the Manufacturing Industry of Malaysia. This is in harmony with the a priori expectations regarding Flexible Manufacturing Technology but contrary to the findings of the studies by Berndt and Morrsison, 1995 and Amato and Amato, 2000. However, these studies are different from the present study due to reasons such as differences in technologies considered, non consideration of Industry Fixed Effects Dummy Variables, differences in countries considered and the differences in the explanatory variables considered. In this regard, the manufacturing sector has been the engine of economic growth since structural transformation took place in the Malaysian economy in 1987. The sustainability of higher economic growth continued to be driven by productivity through the enhancement of TFP. In this regard, TFP development strategies emphasised on the quality of the workforce, raw material, capital structure and technical progress. However, the instability of TFP contribution to manufacturing sector industries in terms of average annual growth rates are dependent on the inputs used in the production which were reported to be insufficient and of low quality. The starting point for policy recommendations is to offer policies that can help to overcome the following main problems of the manufacturing sector, especially the efficiency and productivity being input-driven rather than TFP productivity-driven. Meanwhile, for any industry to develop there must be a regular and consistent supply of raw materials. One of the main problems faced by the Malaysia's manufacturing sector industries is in the supply of raw materials. The manufacturing sector is dependent on imported raw materials, which form the largest component of cost in the Malaysian manufacturing sector. This can have serious adverse impact on the Malaysian Balance of Payments as shown in the Annual Report of Bank Negara (1991–2005) which reported that imported raw materials constituted 20% of the raw materials utilised by resource-based industries while non-resource-based industries as much as 60% of the required raw materials. In particular, leading industries in the manufacturing sector such as electronics and electrical machinery can have imported raw materials content as high as 70% of the total cost. For food manufacturing industries, the sources of supply of raw materials are 70% dependent on imported raw materials. The supply of raw material is not consistent and of low quality in most manufacturing sector industries in general and food manufacturing industries in particular. Besides, shortage of skilled labour also causes a serious constraint on capital utilisation. Skilled labour is required to operate the new technologies embodied in new plants and equipment so that available capital stock may be utilised efficiently. Hence, skills training and the deepening of skills are of vital importance for the full utilisation of capital. Improvement of the quality of the local raw materials will help to improve the final product and enable it to compete in the international markets; and also help to reduce the dependency of the manufacturing sector industries on imported raw materials. These, if attained, could help the industries to become efficient, dynamic, and internationally competitive. Moreover, one of the major problems of Malaysia's manufacturing sector is that the sector is highly dependent on foreign direct investment FDI. The local small and medium scale industries have financial problems compared with the large-scale industries. Getting capital at the right time will save the production of these SMI's. Overcoming the financial problems of industries will improve the productivity of the sector. In addition, low technology has been identified as a major constraint facing the local small-scale industries (SMI's). The findings of this study are in line with the above-mentioned statement reflecting the relationship between the technological inputs and the scale of production of SMI's. Low technologies are adopted in the manufacturing processes, and manual handling of materials is applied, with low quality control. The first step for improving the productivity growth and efficiency of the manufacturing industries will be to modernise the technology used by small-scale industries to improve the quality of the manufacturing products, and change their production methods. This must be started right from the cultivation of agricultural raw material in order to reduce the harvesting loss, and also to get good raw material quality. The local large-scale industries, on the other hand, are dependent largely on imported technology. For a more sustainable development of the large-scale industries, this imported technology should be kept to a minimum in the short run, while in the long run efforts are made to produce all the technological inputs locally. This can be achieved by adopting the experience of industrial countries and by capitalising on the benefits of global information and communications technology and research done in this area through collaboration with the developed countries and their companies. Furthermore, the level of skilled labour employed would reflect on the level of technology adopted. Therefore, before any improvement on technological and material inputs, there is a need to reduce the number of unskilled labour that dominated the manufacturing sector, and increase the volume of skilled labour in the sector. Concomitant with technology enhancement and as industries become more capital intensive, the critical shortage of skilled manpower will continue for some time. A programme could be designed to upgrade labour standards and use high technology in production methods, through institutions involved in the area of technology skills training for local workers. Finally, since a direct relationship between the total factor productivity growth and the degree of investment in flexible manufacturing technology has been established, the policy makers can focus more on the promotion of investments in flexible manufacturing technology in formulating incentive schemes for the manufacturing industry. The threat of global competition and the changing demand of customers are forcing the Malaysian manufacturing industry to re-evaluate their existing operational and technological capability. The study recommends that managers make the manufacturing processes more efficient by adopting a high degree of flexible manufacturing technology despite their widely discussed operational problems and the unfavourable economic appraisals. FMT allows manufacturers to cope with the ever increasing changing demand of digitally connected 21st century customers. These new kind of customers are in a way becoming closer to the production floor and they expect more customization on the products they are buying. For example, companies such as Dell and BMW offer modular customization to their customers who order through their websites. Perhaps by incorporating these kind of customer values into the equation will help to shed some lights and arrive to a favorable economic appraisal for FMT investment in manufacturing. In its customary call for future research, the authors recommend studies that investigate the relationship of investments in FMT rather than the degree of adoption of FMT have with the total factor productivity growth of the manufacturing industry. Relating technology investments such as FMT to customer values (Sade et al., 2009) for example, is becoming more crucial as manufacturing concept of productivity moves toward the concept of customerisation. Further, it can be safely admitted that the accuracy of findings can be increased by considering investments in FMT rather than the degree of adoption of FMT. Hence, it is proposed that future studies need be undertaken in collaboration with the industry monitoring institutes of the state sector that makes establishments obligatory to divulge investments made in FMT to evaluate the impact of investments in FMT on total factor productivity growth.