Although faced with a quickly changing business environment, better performing firm can still develop and maintain a competitive advantage. This study applies the dual analysis in data envelopment analysis to consider performance improvement of the Asian lead frame firms, since this can indicate how the associated factors should be adjusted so that input wastages and/or output shortfalls can be eliminated. The advantages of this study are that it can not only provide a practical framework for performance improvement for the lead frame industry, but also the management practices obtained can be used as a reference for the management of lead frame firms during their expansion strategies and the current global financial crisis.
Performance evaluation is an important issue for managers, since it can be used as a reference in decision making with regard to budget distribution and/or performance improvement for business units. Performance is conventionally defined either as organizational inputs or outputs, or as a relationship between these, usually stated as efficiency. Because the evaluation characteristics are generally multi-dimensional, there is no appropriate aggregation schema for them, and the basic problem of performance measurement is how to evaluate the relative performance of business units. To overcome this difficulty, data envelopment analysis (DEA) is a widely utilized technique for such evaluations within a group of decision making units (DMUs), and is often found in the management literature (for example, Bottl et al., 2009, Chang and Chen, 2008, Chen, 2007, Cook and Zhu, 2007, Hwang and Chang, 2003, Kao and Hung, 2008, Kao and Hwang, 2008, Liu and Wang, 2008, Paradi et al., 2002, Shin and Sohn, 2004, Tseng et al., 2009, Wang, 2005 and Wang et al., 2008).
DEA is a mathematical programming approach for measuring the relative efficiencies within a group of business units, such as bank branches, hospitals, schools, and so on. The relative efficiency of a unit within the DEA framework is defined as the ratio of multiple weighted outputs to multiple weighted inputs. Given the restriction that no DMU can exceed 100% efficiency, the weights are chosen to give as much efficiency as possible with regard to a specific business unit. If the efficiency score of a DMU is equal to one, then it is classified as efficient, and inefficient otherwise.
There are two types of DEA measurements, radial and non-radial, that can be utilized to obtain the alternative targets of inputs and outputs for inefficient DMUs in order to eliminate inefficiency. A radial measurement gives a dual variable to associate with the normalizing equation in the DEA model, meaning that the adjustment proportions of all inputs or outputs are the same for efficiency improvement. For a non-radial measurement, the normalizing equation is decomposed in order to be associated with different dual variables, and thus the adjustment proportions of factors do not need to be the same. In a DEA evaluation, a by-product is that the dual variables can indicate how the associated factors should be adjusted so that input wastages and/or output shortfalls can be eliminated. Consequently, the dual analysis is a widely utilized tool for inefficient DMUs to eliminate inefficiency.
Based on the excellent performance of the upstream design sector and the wafer fabrication sector, the production value and market share of Taiwan in the semiconductor foundry and assembly/testing industries are both number one worldwide. Since the lead frame is a main component in the assembly/testing industry and Taiwan is an important target market for the lead frame manufacturers, many firms are located in Asia, which has become the main production district of the lead frame industry. To enhance the competitiveness of a firm, any effort for performance improvement should first be considered. Consequently, an investigation of the efficiency improvement of Asian lead frame firms is carried out with the aim of finding out what targets should be set for specific factors, so that inefficient firms can improve. Therefore, this study applies dual analysis to obtain the alternative targets of factors for inefficient business units, through the radial and non-radial measurements, so that they can know what issues to work on in order to eliminate inefficiency and enhance competitiveness.
Performance evaluation is one of the most serious concerns for managers, since it can be used as a reference in decision making with regard to performance improvement. As a by-product, the dual variables in DEA can provide an insight into how the business unit being evaluated can be improved as far as an efficiency score is concerned. There are two types of DEA models, radial and non-radial, that can be utilized to obtain the improvement targets of specific factors for inefficient units. Consequently, managers can set better targets through a comparison of the total cost investments by different measurement models.
This study contributes dual analysis to the performance improvement of the Asian lead frame firms. Although there are a lot of user-specified approaches that can be used to specify the αr values in solving the non-radial DEA model, the contributions of this study are that it cannot only provide a practical framework for performance improvement in the lead frame industry, but also the performance improvement suggestions derived from this study can be used by other lead frame related firms during the current global financial crisis.
