A comparative performance evaluation of Taiwan's high-tech industries

Chen, Chung‐Jen; Yeh, Quey Jen

doi:10.1504/ijbpm.2005.006241

Cited by 18 publications

(13 citation statements)

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“…Similar results could also be obtained when an alternative parametric programming approach is conducted (Hong et al, 2002;Chen and Yeh, 2005). The results also show that the crisis of subprime mortgage and financial tsunami would depreciate costs, allocative and technical efficiency in Taiwanese biotechnological company.…”

Section: Discussionsupporting

confidence: 71%

“…They found that the companies located in regional agglomerations grow faster than isolated in regional ones, and biotech companies spun-off from universities have a better performance than that of start-ups. Finally, Chen and Yeh (2005) applied DEA to analyze the comparative performance of six high-tech industries currently developed in Taiwan. The results indicate that semiconductor and computer industries have the best performance, while the biotech operates at a worst level. In detail, the biotech industry reveals a lowest average scale efficiency scores, but a highest pure technical efficiency scores among the six industries.…”

Section: Asian Economic and Financial Reviewmentioning

confidence: 99%

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Using DEA and Malmquist Productivity Index to Analyze the Operational Efficiency of Taiwan Biotechnological Industry

Liu

2017

Asian Economic and Financial Review

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Article HistoryThis study employs data envelopment analysis (DEA) method and Malmquist productivity index (MPI) to reexamine the change of operational efficiency for both individual firm and whole biotechnological industry. Concerning the whole industry, lower efficiency of the industry is mostly caused by pure technological inefficiency. When applying the sense of total factor productivity (TFP) index, the changes of TFP in biotechnological industry is most accounted for the efficiency changes rather than technological charges. These results benefit to biotechnology industry managers and regulators through the provision of useful guidelines for management control within the competitive biotechnological industry and market.Contribution/ Originality: This study contributes in the existing literature with employing DEA and MPI to reexamine the change of operational efficiency for biotechnological industry in Taiwan. Concerning the whole industry, lower efficiency of industry is mostly caused by pure technological inefficiency. The changes of TFP is mostly accounted for the efficiency changes.

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Section: Discussionsupporting

confidence: 71%

Section: Asian Economic and Financial Reviewmentioning

confidence: 99%

Using DEA and Malmquist Productivity Index to Analyze the Operational Efficiency of Taiwan Biotechnological Industry

Liu

2017

Asian Economic and Financial Review

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“…For example, Oum and Yue (1994) use DEA efficiency scores with a Tobit model to analyses the influence of certain variables on the performance of European railways as did Kerstens (1996), who evaluates the performance of French urban transit companies. Chen and Yeh (2005) applied DEA to analyze the comparative performance of the six high-tech manufacturing industries currently developed in Taiwan. The results show that the semiconductor and computer industries are the best performers, but the biotech industry has the worst performance.…”

Section: Literature Reviewmentioning

confidence: 99%

From instrumentalism to realism in accounting

Enachi

Andone

2015

JEFS

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This study investigates the technical efficiency for each industry in the Malaysian manufacturing sector is estimated by using Data Envelopment Analysis (DEA). In order to pursue a balance of innovation between long-term and short-term performance strategy, we integrate the Balance Scorecard (BSC) approach with DEA. Furthermore, this paper looks at the determinants of efficiency using the Tobit regression model. In measuring the level of firms' efficiency and innovation, the wood and wood based products industry is emphasized due to its importance in the economic growth of manufacturing sector. In the wood and wood based products industry, the highest level of technical efficiency was achieved by two sub-sectors i.e. veneer sheets and plywood and laminboard, particle board and other panels board, with the mean value of technical efficiency of 1.081 and 1.097 respectively. Generally, the majority of the manufacturing firms are operating technical inefficiently. The distribution of DEA and DEA-BCS technical efficiency in Malaysian Manufacturing Industries show that most of the industries have the average technical efficiency scores greater than 1.05 with only 7 industries (13.21%) in DEA-BSC model operating at or near to the most optimal productions. © 2015 The Authors. This is an open access article under the terms of the Creative Commons Attribution License 4.0, which allows use, distribution and reproduction in any medium, provided the original work is properly cited. DOI: http://dx.doi.org/10.18533/jefs.v3i03.109 IntroductionPrevious research acceded that there are myriad of definitions and usage of the term innovation (Jain, 2010). Although formal definitions of innovation appear diverse, one common element in all definition of innovation is novelty. For the purpose of this study, innovation is defined as "the commercially successful exploitation of new technologies, ideas or methods through the introduction of new products or process, or through the improvement of existing ones.There is clear evidence that innovation play a crucial role to long term profitability and growth in firms (Freel, 2000). There can be little doubt that today's firms must be able to move in the world of innovation. The successful firms will be firms which fully understand innovative business differs from non innovative business and is able to respond accordingly thereby successfully "being innovative".The importance of manufacturing sector in contributing to Malaysian economic growth is not deniable. With this rapid expansion of the manufacturing sector in the last three decades has transformed Malaysia from an Innovation and technical efficiency … Munisamy et al., JEFS (2015), 03(04), 50-67Journal of Economic and Financial Studies. Page 51agricultural based economy to a rapidly industrializing country (Ministry of International Trade and Industry, 2008) During the period of 1996 to 2005, the trade and economic policy undertook progressive liberalization to achieve the long-term objectives of freer and open trade as well as stren...

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“…DEA allows researchers to avoid specification of a given functional form or error structure, and many researchers have focused on estimating the technical efficiency and scale efficiency of DMUs by utilizing this technique (Oral and Yolalan, 1990 [8]; Favero and Papi, 1995 [9]; Schaffnit, Rosen and Paradi, 1997 [10]; Fukuyama, Guerra and Weber, 1999 [11]). The DEA model used to evaluate the efficiency in the semi-conductor industry is found in Liu and Wang (2008) [12], Chen and Chen (2007) [13], and Chen and Yeh (2005) [14], while Schaffnit, Rosen and Paradi (1997) [10] present a best practice analysis of bank branches based on a DEA assurance region (DEA-AR) model containing output multiplier constraints, with standard transaction and maintenance times, in order to evaluate allocative efficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

A Comparison of Three-Stage DEA and Artificial Neural Network on the Operational Efficiency of Semi-Conductor Firms in Taiwan

Liu¹,

Chen²,

Chiu³

et al. 2013

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In this study, the data envelopment analysis (DEA), three-stage DEA (3SDEA) and artificial neural network (ANN) are employed to measure the technical efficiency of 29 semi-conductor firms in Taiwan. Estimated results show that there are significant differences in efficiency scores among DEA, 3SDEA and ANN analysis. The advanced setting of the three stages mechanism of DEA does show some changes in the efficiency scores between DEA and ANN approaches. We further find that the environmental factor is still a significant variable to explain technical efficiency in Taiwan, irrespective of whether a DEA, 3SDEA or ANN approach is used.

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A comparative performance evaluation of Taiwan's high-tech industries

Cited by 18 publications

References 0 publications

Using DEA and Malmquist Productivity Index to Analyze the Operational Efficiency of Taiwan Biotechnological Industry

Using DEA and Malmquist Productivity Index to Analyze the Operational Efficiency of Taiwan Biotechnological Industry

From instrumentalism to realism in accounting

A Comparison of Three-Stage DEA and Artificial Neural Network on the Operational Efficiency of Semi-Conductor Firms in Taiwan

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