Utilisation of interpretive structural modelling method in the analysis of interrelationship of vendor performance factors

Transcription

1 260 Int. J. Business Performance Management, Vol. 12, No. 3, 2011 Utilisation of interpretive structural modelling method in the analysis of interrelationship of vendor performance factors Ya-Ti Lin* Institute of Management of Technology, National Chiao Tung University, No University Road, Hsinchu 300, Taiwan Fax: *Corresponding author Chia-Li Lin Department of Resort and Leisure Management, Taiwan Hospitalty and Tourism College, No. 268, Chungshin St., Fengshan, Shoufeng, Hualien, Taiwan Fax: Hsiao-Cheng Yu Institute of Management of Technology, National Chiao Tung University, No University Road, Hsinchu 300, Taiwan Fax: Gwo-Hshiung Tzeng Department of Business and Entrepreneurial Administration, Kainan University, No. 1 Kainan Road, Luchu Shiang, Taoyuan 338, Taiwan Fax: ghtzeng@mail.knu.edu.tw Abstract: Vendor performance is a crucial factor affecting the success of outsourcing operations today. It is essential to understand the interrelationship in a complex performance analysis framework, for it helps to identify the root causes that affect other criteria as well as the overall performance. The purpose and contribution of this paper is to propose the use of interpretive structural modelling (ISM) method to provide an understanding of the causal interrelationship in the complex vendor performance evaluation framework, and in return, enables the firms to make analysis and improvements more accurately and efficient. A case study is conducted to analyse the causal interrelationship of a wafer-testing vendor s performance in Taiwan s Copyright 2011 Inderscience Enterprises Ltd.

2 Utilisation of interpretive structural modelling method 261 semiconductor industry to present the proposed procedure. The proposed ISM method of this research is not only useful for distinguishing the causal interrelationship in a complex problem but also able to be extended to support other quantitative multiple-criteria decision-making methods in obtaining the weights of each evaluation criterion. Keywords: outsourcing; interpretive structural modelling; ISM; wafer-testing. Reference to this paper should be made as follows: Lin, Y-T., Lin, C-L., Yu, H.C. and Tzeng, G-H. (2011) Utilisation of interpretive structural modelling method in the analysis of interrelationship of vendor performance factors, Int. J. Business Performance Management, Vol. 12, No. 3, pp Biographical notes: Ya-Ti Lin received his PhD from the Institute of Management of Technology, National Chiao Tung University, Taiwan. He has ten years of experience in the procurement field of semiconductor industry of Taiwan. Chia-Li Lin is an Assistant Professor at the Department of Resort and Leisure Management, Taiwan Hospitalty and Tourism College. Hsiao-Cheng Yu is a Professor at the Institute of Management of Technology, National Chiao Tung University, Taiwan. Gwo-Hshiung Tzeng is a Distinguished Chair Professor at the Department of Business and Entrepreneurial Administration, Kainan University, Taiwan. 1 Introduction Since outsourcing operation has become a mainstream business model, performance analysis and improvement have been considered the critical elements in manufacturing management today (Bailey et al., 2002). Various firms choose to focus on aspects that create most values to the business; therefore, they tend to release non-core manufacturing processes to outside vender. The major benefits of the outsourcing operations are cost reduction, quality and service performance improvement (Sharpe, 1997; Bailey et al., 2002; Barthélemy, 2001; Loh and Venkatraman, 1992; Quinn, 1999; Lei and Hitt, 1995; Bengtsson, 2008; Caputo and Zirpoli, 2002; Bilgen and Ozkarahan, 2004). Outsourcing and supply chain management will greatly influence the profit of a firm, impact on timeto-market, and affect the firm s product cost and quality. Consequently, in order to make an appropriate outsourcing performance analysis and corresponding improvement, it is crucial for a firm to enhance the overall performance in outsourcing operation. An abundance of researches have been conducted in proposing the use of performance evaluation models or methods such as analytic hierarchy process (AHP), data envelopment analysis (DEA), analytic network process (ANP) and extended fuzzy approaches to improve performance (Yang et al., 2008; Onut et al., 2009; Shyur and Shih, 2006; Chen et al., 2006; Wu and Lee, 2007; Lee, 2009; Ha and Krishnan, 2008; Wu et al., 2009; Degraeve et al., 2000). Past researches focus on establishing the performance evaluation model, obtaining the weights of all evaluation and summarising the final

3 262 Y-T. Lin et al. score. However, few of them discussed on how the performance evaluation dimensions and criteria affect each other, as well as how to improve the performance from the implication of the causal interrelationship amongst all dimensions. Therefore, the purpose of this paper is to provide a better understanding in determining the interrelationship of each performance index inside a comprehensive performance evaluation framework and provide improvement strategy accordingly by utilising Warfield s interpretive structural modelling (ISM) method. To better present this method, a case study is conducted, as a demonstration, to analyse the overall performance of a wafer-testing outsourcing vendor, which provides outsourcing services to most companies in Taiwan s semiconductor industry. The semiconductor industry has evolved along with the worldwide outsourcing trend and thereby transforming their manufacturing strategy, releasing many of the non-core manufacturing steps to outsourced subcontractors (Frederix, 1996; OhUallachain, 1997). The wafer-testing step tests the function and performance of the ICs. If wafer-testing companies fail to distinguish between effective and defective ICs, effective ICs may be scrapped and result in an increase in cost wastage. Furthermore, in a worse case scenario, if the wafer-testing companies fail to detect defective ICs, but instead, erroneously sending them for IC packaging and delivering to customers, then not only is packaging cost will be wasted, but more importantly, the potential loss in the reputation of company and business will be substantially damaging. Since integrated device manufacturing (IDM) companies and IC design houses focus on their core business functions, the demand of wafer-testing outsourcing services from professional wafer-testing houses has increased (Lee, 2006). The reason to use the semiconductor industry in Taiwan as an empirical case study is that it can be considered a global paragon (Chu et al., 2005), particularly when the professional wafer-testing houses in Taiwan, such as ASE, SPIL, KYEC and Ardentech, have 60% of the worldwide market share (IDB, 2007). Figure 1 depicts how the research was conducted. Figure 1 Research flow Research Research purpose, purpose, motivation motivation and and objective: utilizing ISM method to objective: utilizing ISM method to analyze the interrelationship of analyze the interrelationship of vendor performance evaluation vendor performance evaluation Literature Literature review review and and interviews interviews for establishing the vendor for establishing the vendor performance evaluation performance evaluation dimensions and criteria dimensions and criteria Conduct Conduct a a case case study study to to demonstrate the analysis demonstrate the analysis procedure procedure Discussion Discussion and and analysis analysis of of the the research research results results Literature review for the ISM Literature review for the ISM method method Conclusions Conclusions

4 Utilisation of interpretive structural modelling method Literature review on vendor performance evaluation criteria and the ISM method 2.1 The suitable vendor performance evaluation dimensions and criteria for the case study In order to ensure the performance of outsourcing vendors, the purchaser needs to establish a suitable framework to evaluate its vendors. The structure of one suitable framework must embrace the related criteria, which usually involved with the satisfaction of the purchaser (Lee and Billington, 1992). Dickson (1966) is known to be the pioneer to validate 23 criteria for assessing a vendor s performance, while Skinner (1969) is said to be the first to use the four dimensions of cost, quality, delivery and flexibility to evaluate a supplier s performance. Weber et al. (1991) have reviewed 74 academic papers as well as analysing the criteria used for vendor evaluation. They have discovered that net price was the most discussed criterion, followed by delivery and quality based on Dickson s well known study. Many researchers, afterwards, not only utilise these four dimensions, cost price, quality, delivery and flexibility (service) to evaluate vendor performance, but they also set a step forward with vendor selection issue (Lin and Lee, 2005; Leong et al., 1990; Krajewski and Ritzman, 1999; Ha and Krishnan, 2008; Wu et al., 2009; Towill, 1997). From the literature review, usable evaluation dimensions are collected and to be used for the case study in Section 3. In order to determine the best suitable performance evaluation criteria for every dimension, further interviews with the experts from the semiconductor industry in Taiwan are also conducted to screen for the suitable dimensions and criteria from the collection of literature reviews. Finally, by integrating them, this research summarises and constructs a performance evaluation structure using the four dimensions and 14 criteria that are most suitable for the vendor performance analysis of wafer-testing outsourcing. The four dimensions include delivery management capability (D), quality management capability (Q), integrated service capability (S), and price (P). Since different cases may have different sub-criteria for the performance evaluation, experts of the industry are interviewed to obtain the most suitable sub-criteria from each dimension, and in return, to better fit the characteristics of the case study that this research would conduct. After discussing with the experts, it is concluded that the dimension of delivery management capability (D) should include three criteria: accuracy of delivered contents (D 1 ); on-time delivery (D 2 ); and delivery adjustment flexibility (D 3 ). The dimension of quality management capability (Q) includes four criteria: correctness of testing data (Q 1 ); quality abnormal rate (Q 2 ); capability to prevent repeated error (Q 3 ); and error judgment rate (Q 4 ). The dimension of integrated service capability (S) includes four criteria: response-time for customers request (S 1 ); efficiency of engineering support (S 2 ); fulfilling customers special requests (S 3 ); and customer service for information platform (S 4 ). The dimension of price (P) includes three criteria: testing P (P 1 ); compensation rate for broken wafers (P 2 ); and acceptance criteria (P 3 ). These details of the dimensions and criteria are listed below in Table 1. These dimensions and criteria are utilised in setting up an evaluation hierarchy for evaluating the performance and its causal relation of the outsourcing vendor.

5 264 Y-T. Lin et al. Table 1 The criteria for wafer test vendor selection Dimensions/criteria Accuracy of delivered contents (D 1 ) on time delivery (D 2 ) Delivery adjustment flexibility (D 3 ) Explanation of the criterion Dimension D: delivery management capability The vendor needs to deliver correct quantity and item to the customer The vendor needs to deliver tested wafers on time The vendor can provide the flexibility to adjust the production priority and schedule according to customer s adjustment Dimension Q: quality management capability Correctness of testing data (Q 1 ) The vendor needs to provide correct testing information and results to the customer Quality abnormal rate (Q 2 ) The abnormal rate, including wafer damage, scratched, data error and etc. Capability to prevent repeated error (Q 3 ) Error judgment rate (Q 4 ) Response time for customers request (S 1 ) Efficiency of engineering support (S 2 ) Fulfil customers special requests (S 3 ) Customer information service platform (S 4 ) Testing price (P 1 ) Compensation rate for wafer damage (P 2 ) Acceptance criteria (P 3 ) The vendor needs to have the capability to prevent repeated quality abnormal issue Error judgment on effective and defective ICs Dimension S: integrated service capability Response time of the vendor s response to customers requests The vendor needs to fulfil customers engineering demand, including testing program development, tester adjustment, and related engineering processes Except the normal request from customers, the wafer-testing vendor should fulfil other special demands, such as manufacturing process priority change, special price request, delivery plan change, extra engineering service or extra engineering resource to support a specific case The customer information system is an interface between the vendor and customer, which can provide manufacturing status, delivery, and some related information immediately. This system should be very stable and easy to use. Dimension P: price Testing price per wafer or per hour, and other related expense The compensation rate for abnormal yield loss or damage Are the acceptance criteria reasonable and acceptable? 2.2 The ISM method ISM method has been proposed by Warfield (1974a, 1974b, 1976) as a computer assisted methodology (Sharma et al., 1995; Agarwal et al., 2007; Huang et al., 2005). It is used to derive an understanding of the interrelationships amongst complex elements, and allow a set of different, yet directly related, elements to be structured into a comprehensive systemic model (Fontela, 2003). The theory of ISM is based on discrete mathematics,

6 Utilisation of interpretive structural modelling method 265 graph theory, social sciences, group decision-making, and computer assistance (Warfield 1974a, 1974b, 1976). ISM has been proven as a more efficient method, for it can be implemented in a small expert group instead of making massive statistics in determining the interrelationship amongst elements (Wang and Hsieh, 2009). The DEcision MAking Trial and Evaluation Laboratory (DEMATEL) method is also designed for distinguishing the causal interrelationship in a complex problem. But the major difference is that DEMATEL method focuses on determine the strength of the interrelationship, which is more complicated than ISM. Therefore, ISM is more suitable to support in purely determining the causal interrelationship in a complex problem. Wang et al. (2008), Yang et al. (2008), Kannan et al. (2009) and Lee et al. (2010) have utilised the ISM method in their researches to investigate the interactions among their research subjects. They have concluded that ISM method should to be exploited to distinguish the interrelationship of the researched dimensions or criteria. The first step of ISM is to identify the variables relevant to the problems or issues. It then extends with a group problem-solving technique. A structural self-interaction matrix (SSIM) is then developed based on a pair-wise comparison of variables. The SSIM is formed by asking questions such as, Will element e i affect element e j? If the answer is yes, then π ij = 1. If the answer is no, then π ij = 0. SSIM can be described as below: e1 e2 en e1 0 π12 π1n e 2 π21 0 π 2n D = en πn1 πn2 0 The e i means the ith element, the π ij means the interrelationship between the ith and the jth elements, and D is an SSIM. After establishing the SSIM, it is converted into a reachability matrix, and that its transitivity is then checked using equations (1) and (2) (Huang et al., 2005): M = D+ I (1) * k k+ 1 M = M = M, k > 1 (2) where I is the unit matrix, k denotes the powers, and M * is the reachability matrix. Note that the reachability matrix is under the operations of the Boolean multiplication and addition (i.e., 1 1 = 1, = 1, 1 0 = 0, = = 1, 1 0 = 0 1 = 0). For example: M =, = 1 1 M 1 1 (3) 3 Empirical case study of the vendor performance analysis for wafer-testing outsourcing This section illustrates how to determine the causal relation of a vendor s performance by using an empirical case study in Taiwan s semiconductor industry. The evaluated vendor

7 266 Y-T. Lin et al. in this case study is an IPO company that provides pure wafer-testing service to most of the semiconductor companies in Taiwan. In order to make the research more practical and the case study more complete, a cross comparison between literature reviews and industry practices is strongly recommended (Chang, 2007). Therefore, the performance evaluation dimensions and criteria have been concluded in this case study by combining suggestions from the academic researches and the comments from experts in the industry. We begin with a literature review to understand the researches on outsourcing performance analysis and to obtain useable information that can be applied to this case study from Section 2. Next, consultations with the experts from the semiconductor industry of Taiwan are conducted to screen out the suitable performance evaluation dimensions and criteria from the literature review. Furthermore, these experts have also previewed the questionnaire for this case study and have provided their professional comments for the research results. It is important to know that this case study includes three parts. The first part is to utilise the ISM method to find out the relationship between cause and effect amongst dimensions and criteria. The second part is to analyse and study the results with the experts. Finally, improvement strategies are proposed to enhance the performance level based on the interrelations in each criterion. 3.1 Basic data description of the case study The experts of various background and experience have responded to the questionnaires. They include senior engineer/administrator, basic level managers, mid- to upper level managers, testing engineering, outsourcing production plan/management, purchasing, quality control and assurance of IC design houses and wafer foundry providers. Out of the 55 questionnaires issued, 34 of them are approved as valid, of which, 38.24% of the replies have been derived from the IC design companies, while 61.76% are from the wafer foundry providers. In terms of the function of the respondents, 35.29% of the questionnaires are derived from the field of testing engineering, 38.24% from outsourcing production plan/management, 5.88% from purchasing and 20.59% from quality control and assurance. 3.2 Applying the ISM method to determine the interrelation amongst dimensions and criteria In this step, the ISM method is applied to obtain the interrelationship amongst all evaluation dimensions and criteria. The performance evaluation dimensions include delivery management capability (D); quality management capability (Q); integrated service capability (S); price (P). The average value of the original interrelation data among all dimensions is collected from the questionnaires and is listed in Table 2. Table 2 Original interrelation matrix D Q S P D Q S P

8 Utilisation of interpretive structural modelling method 267 Based on the experts suggestion on setting a tighter definition, we have decided to set the threshold value to 0.8. If the value of the element inside the matrix is 0.8, the value will be counted as one. If the value of the element is <0.8, the value will be counted as zero. Then the interrelation matrix (D) and the matrix (M) can be obtained by using formula (1), as shown in Table 3 and Table 4. Table 3 Interrelation matrix (D) D Q S P D Q S P Table 4 Matrix (M) of all dimensions D Q S P D Q S P Table 5 Reachability matrix (M*) of all dimensions D Q S P D Q S 1* P Figure 2 Dimension interrelation structure (see online version for colours) Delivery Management Capability (D) Quality Management Capability (Q) Price (P) Integrated Service Capability (S) Finally, the reachability matrix can be obtained by using formula (2). The asterisk (*) indicates the derivative relation, which did not emerge in the original relation matrix. The correlation between every aspect is shown in Table 5 and Figure 2.

9 268 Y-T. Lin et al. 3.3 The interrelation amongst criteria of each dimension By repeating the ISM calculation procedure introduced in Sub-Section 2.2 and 3.3 for all criteria of each dimension, the interrelationship map of each dimension and its criteria can be obtained accordingly. The following sub-sections elaborate the interrelationship of each dimension The dimension of delivery management capability (D) There are three criteria in the dimension of delivery management capability: accuracy of delivered contents (D 1 ), on time delivery (D 2 ), and delivery adjustment flexibility (D 3 ). Based on information provided in Table 6 and Figure 3, it is understood that the two criteria affecting on time delivery (D 2 ) are accuracy of delivered contents (D 1 ) and delivery adjustment flexibility (D 3 ). As a result, if the vendor wants to improve the D, it should increase the accuracy of delivered contents (D 1 ) and delivery adjustment flexibility (D 3 ) so the on time delivery (D 2 ), as well as the whole dimension, can be improved accordingly. Table 6 Impact relationship matrix (delivery management capability) D 1 D 2 D 3 D D D Figure 3 Dimension network structure (delivery management capability) Delivery Management Capability (D) Accuracy of delivered contents (D 1 ) On time delivery (D 2 ) Delivery adjustment flexibility (D 3 ) The dimension of quality management capability (Q) The four criteria of the dimension of quality management capability includes correctness of testing data (Q 1 ), quality abnormal rate (Q 2 ), capability to prevent repeated error (Q 3 ), and error judgment rate (Q 4 ). When looking at data in Table 7 and Figure 4, it is noted that the capability to prevent repeated error (Q 3 ) affects the correctness of testing data (Q 1 ), quality abnormal rate (Q 2 ) and error judgment rate (Q 4 ). Hence, the capability to

10 Utilisation of interpretive structural modelling method 269 prevent repeated error (Q 3 ) is considered the most critical factor. Additionally, correctness of testing data (Q 1 ), quality abnormal rate (Q 2 ) and error judgment rate (Q 4 ) also affect each other interactively. As a result, if the vendor wants to improve the quality management capability (Q), then it must improve the capability of preventing repeated error (Q 3 ), which is the most crucial criterion in this dimension, followed by correctness of testing data (Q 1 ), quality abnormal rate (Q 2 ) and error judgment rate (Q 4 ). Table 7 Impact relationship matrix (quality management capability) Q 1 Q 2 Q 3 Q 4 Q Q Q Q Figure 4 Dimension network structure (quality management capability) Quality Management Capability (Q) Correctness of testing data (Q 1 ) Quality abnormal rate (Q 2 ) Error judgment rate (Q 4 ) Capability to prevent repeated error (Q 3 ) The dimension of integrated service capability (S) There are four criteria to be addressed for the dimension of integrated service capability. They are: response time for customers request (S 1 ), efficiency of engineering support (S 2 ), fulfil customers special requests (S 3 ), and customer information service platform (S 4 ). From looking at Table 8 and Figure 5, this research has discovered that customer information service platform (S 4 ) affects the response time for customers request (S 1 ), efficiency of engineering support (S 2 ), and fulfilment of customers special requests (S 3 ). Hence, the customer information service platform (S 4 ) is the main criterion in affecting others. Response time for customers request (S 1 ), efficiency of engineering support (S 2 ), as well as fulfilling customers special requests (S 3 ), also affect each other interactively. As a result, if the vendor wants to improve the S, then improvement on the customer information service platform (S 4 ) must be made first, followed by the response time for customers request (S 1 ), efficiency of engineering support (S 2 ) and fulfil customers special requests (S 3 ). Additionally, the following four potential interrelations are also encountered during this stage of research: S 2 to S 1 ; S 1 to S 3 ; S 4 to S 2 and S 4 to S 3.

11 270 Y-T. Lin et al. Table 8 Impact relationship matrix (integrated service capability) S 1 S 2 S 3 S 4 S * 0 S 2 1* S S 4 1 1* 1* 1 Figure 5 Dimension network structure (integrated service capability) Integrated Service Capability (S) Response time for customers request (S 1 ) Efficiency of engineering support (S 2 ) Customer information service platform (S 4 ) Fulfill customers special requests (S 3 ) Table 9 Impact relationship matrix (service) P 1 P 2 P 3 P P * P 3 1 1* 1 Figure 6 Dimension network structure Price (P) Testing price (P 1 ) Compensation rate for wafer damage (P 2 ) Acceptance criteria (P 3 ) The dimension of price (P) There are three criteria to be considered for this dimension: testing price (P 1 ), compensation rate for wafer damage (P 2 ), and acceptance criteria (P 3 ). Data from Table 9 and Figure 6 have shown that testing price (P 1 ), compensation rate for wafer damage

12 Utilisation of interpretive structural modelling method 271 (P 2 ), and acceptance criteria (P 3 ) affect each other interactively. As a result, improvements made to any one of these criteria will enhance the performance of price dimension accordingly. Furthermore, two potential interrelations are derived from and Table 9 and Figure 6, with one interrelation coming from compensation rate for broken wafer (P 2 ) to acceptance criteria (P 3 ), and vice versa. 3.4 Results and analysis of the case study Most of the traditional vendor performance analysis have provided insufficient amount of information regarding the understanding of the interrelationships of each dimension and its sub-criteria. However, ISM method resolves this limitation. Additional information received from the collected questionnaires via case study have provided better understanding regarding the causal interrelation of each performance measurement dimension and the criterion of current real practice. The cause and effect interrelation structure can help both customers and the vendor to generate corresponding improvement strategies. The elaborations are provided in the sub-sections as follow: The implication of the interrelationship for all evaluation dimensions From the case study, the researchers have discovered that the whole performance analysis framework can be separated into two groups, price and non-price. The non-price group includes delivery management (D), quality management (Q), and integrated service (S) capabilities. After calculating the ISM based on the replied questionnaires, it is noted that the price (P) does not affect the other three dimensions. Discussion with the experts also implies that the customers tend to separate the assessments of P and non-p dimensions. More specifically, the customers do not acknowledge that the P should be different based on different performance level of delivery management (D), quality management (Q), and integrated service (S) capabilities. The main reason of this phenomenon is that the customers deem that the non-p performance difference is not significant among vendors. Therefore, they are unwilling to pay higher prices in exchange for better performances. Instead, they force the vendors to compete in the non-price dimensions and select the most suitable one as the major supplier. Therefore, it is crucial for the vendors to identify methods on how to achieve better performances in the non-p dimensions. The interrelation map of the four dimensions based on the survey states that quality management capability (Q) and integrated service capability (S) can affect delivery management capability (D). Furthermore, the integrated service capability (S) can as also affect quality management capability (Q). The most interesting finding from the case study is that the integrated service capability (S) affects both delivery (D) and quality management capability (Q). After consulting with the experts regarding this phenomenon, we have realised that time-to-market is always a critical factor in the semiconductor business and industry. In order to meet the request, not only is the stable and agile manufacturing a requirement, but the numerous engineering supports, customised service, specific task force, dedicated supporting resources, as well as seamless information exchange, are also necessary. These extra demands are belonging to the dimension of integrated service capability (S). Therefore, the wafer-testing vendor is suggested to invest more resources to fulfil customers requirements, and in return, increase the satisfaction level and enhance the vendor s self-capability in coping with different challenges.

13 272 Y-T. Lin et al The implication of the interrelationship for all evaluation criteria of each dimension In delivery management capability dimension (D) This study discovers that accuracy of delivered contents (D 1 ) and delivery adjustment flexibility (D 3 ) affect on-time delivery (D 2 ). Thus, the vendor is suggested to improve D 1 and D In quality management capability dimension (Q) The capability to prevent repeated error (Q 3 ) is identified as the key point in this dimension. This capability affects three other criteria within this dimension. The experts also concur in this phenomenon, particularly because the vendor can improve the quality continuously and effectively as long as the repeated error can be prevented. In order to improve this capability, suggestions are made to the vendor to implement knowledge management (KM) system and on job training, which will be helpful for the improvement. The other three criteria are not relatively critical; thus, the semiconductor companies can ask the vendor to focus on the capability of preventing repeated error (Q 3 ) as the top priority In the integrated service capability dimension (S) An interesting finding observed in this study is that the customer information platform (S 4 ) is the key point in this dimension. After clarifying with the experts, they have commented that most semiconductor companies have a strong demand of a powerful B2B information management system, by which to manage production and quality related items. The internal reason of this is from the request of timely and seamless information exchange. Efficient information exchange not only saves on communication time and prevents message misunderstanding, but it also provides all related information for further analysis and improvement. Therefore, the vendor is recommended to input more resource for enhancing the customer information platform to raise the satisfaction level In the price dimension (P) The researchers have discovered that all criteria affect each other. As a result, improvements made to any one of them will result in better performance in this dimension. For example, the vendor can either propose a cost reduction plan to the customer, or accept a tighter acceptance requirement to improve customers satisfaction level. 4 Conclusions Outsourcing vendor performance analysis and improvement are essential to the success of outsourcing operation. Past researches have focused on establishing the performance evaluation model, obtaining the weights of all evaluation criteria, as well as summarising the final score. However, few of them discussed on how the performance evaluation dimensions and criteria affect each other, and how to improve the performance from the

14 Utilisation of interpretive structural modelling method 273 implication of the causal interrelationship amongst all dimensions and criteria. This paper utilises a case study from the semiconductor industry in Taiwan to present the procedure of applying the ISM method in determining the causal interrelationship of each vendor performance evaluation dimension and criterion. Finally, four evaluation dimensions and fourteen criteria are suggested for this case study, and the analysis and corresponding improvement suggestions to the semiconductor companies and the outsourcing vendor are offered accordingly. Based on the research results, suggestions are made to the wafer-testing vendor to understand that customers do not believe the delivery management, quality management and integrated service capabilities are related to price, particularly since the performance difference amongst vendors is insignificant. Therefore, the vendor is suggested to enhance the three non-price dimensions and, consequently, generate and enlarge the difference of performance. It is then that the customers may be convinced to pay a higher price in exchange for a better outsourcing performance. In addition, ISM is presented as a practical technique in determining the causal interrelationship in a complex performance evaluation model. For example, ISM method identifies a phenomenon between price and other dimensions from the survey, which enables the customers and vendor to gain a better understanding of the real situation. The suggested method can be modified as required for different applications and territories of supply chain performance causal interrelationship analysis. It can also help the firms to have a better grasp on how to determine the key factors that affect the overall performance the most and take necessary improvements accordingly. In addition, the concluded performance evaluation dimensions and criteria can act as a reference to other practitioners in the industry. For future researches, this proposed solution may be extended in helping the AHP or ANP method to assess the total performance score of the researched subject more accurately. References Agarwal, A., Shankar, R. and Tiwari, M.K. (2007) Modeling agility of supply chain, Industrial Marketing Management, Vol. 36, No. 4, pp Bailey, W., Masson, R. and Raeside, R. (2002) Outsourcing in Edinburgh and the Lothians, European Journal of Purchasing & Supply Management, Vol. 8, No. 2, pp Barthélemy, J. (2001) The hidden costs of IT outsourcing, MIT Sloan Management Review, Vol. 42, No. 3, pp Bengtsson, L. (2008) Outsourcing manufacturing and its effect on engineering firm performance, International Journal of Technology Management, Vol. 44, Nos. 3 4, pp Bilgen, B. and Ozkarahan, I. (2004) Strategic tactical and operational production-distribution models: a review, International Journal of Technology Management, Vol. 28, No. 2, pp Caputo, M. and Zirpoli, F. (2002) Supplier involvement in automotive component design: outsourcing strategies and supply chain management, International Journal of Technology Management, Vol. 23, Nos. 1 3, pp Chang, S.C. (2007) Reverse electronic auctions: cases in Taiwan s high-tech industry, Technology in Society, Vol. 29, No. 4, pp Chen, C.T., Lin, C.T. and Huang, S.F. (2006) A fuzzy approach for supplier evaluation and selection in supply chain management, International Journal of Production Economics, Vol. 102, No. 2, pp

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