Asia Pacific Management Review 13(3) (2008) 583-599
www.apmr.management.ncku.edu.tw
Selection of Competitive Advantages in TQM Implementation Using Fuzzy AHP and Sensitivity Analysis Ming Lang Tseng*, Yuan Hsu Lin Department of Business Administration, Ming-Dao University, Taiwan Accepted 11 March 2008
Abstract This study examines the total quality management implementation in an organizational system in order to provide a framework in the selection of competitive advantages under uncertainty. The application of fuzzy analytic hierarchy process, based methodology, proves to be efficient in handling the decision criteria and fuzzy data involved in the selection of alternatives. Linguistic comparisons given by the consulted professionals and experts for each comparison facilitated the construction of fuzzy pairwise comparison matrices. A problem, having a hierarchy of four stages and containing different criteria and attributes, demonstrates the implementation of the system. The study decision criteria include effective leadership, people management, customer focus, strategic plan and process management, whereas the competitive advantages are cost, quality, delivery and flexibility. The research findings, as applicable to PCB manufacturing systems, suggest that the adoption of flexibility as a major competitive advantage with a higher uncertainty and delivery with a lower uncertainty. Keywords: Total quality management (TQM), competitive advantage, fuzzy analytic hierarchy process (FAHP), sensitivity analysis 1. Introduction1 For printed circuit board (PCB) manufacturing companies, one starting point to achieving high competency in the market involves the selection of competitive advantages. This task appears to be a multi-attribute decision-making (MADM) problem which depends on a broad comparison of TQM implementation in the industry. Different and conflicting selection criteria make the process more complicated and risky for its inherent direct impact on the trend of strategy and policy implementation. Therefore, this research focuses on developing a framework to aid a firm in choosing its competitive advantage. Since most of the PCB manufacturers depend on TQM implementation to reach its target competitive advantage (Ghobadian and Gallear, 2001), the consequences of poor decision making becomes critical. Any deficiency in the selection process can lead to excessive delays or additional management costs. Hence, PCB manufacturers need to pay more attention to its management strategy or policy implementation. TQM is often regarded as a philosophy that aims to achieve customer satisfaction through a set of criteria, such as strategic planning, effective leadership, people management, process management and customer focus in the organization. Some studies on firms show achievement of positive results owing to their implementation of a TQM program (Flynn, et al., 1995; Forza and Filippini, 1998; Kaynak, 2003; Tseng et al., 2006). Although there are several approaches and models suggested for TQM implementation (Dale, 1999; Fuentes*
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Fuents et al., 2004; Prajogo and Sohal, 2006), management still faces the challenge of environment uncertainty, intensive competition and conflicting selection decisions in the issue of imperative TQM implementation. This study considers no qualitative constrains and assumes all management polices capable of improving manufacturing performance through TQM implementation. Various literature and expert opinions were reviewed in the formulation of the study problem. This study considers several decision criteria in TQM implementation, namely, effective leadership, people management, customer focus, strategic plan and process management (Samson and Terziovski, 1999; Fuentes-Fuents et al, 2004; Jung and Wang, 2006; Tseng et al., 2007). These criteria may vary, depending on the need of the manufacturers, and their preferences and management strategy. In many cases, translating company priorities into useful criteria remains a challenge because needs are often expressed as a general qualitative concepts; criteria should be evaluated quantitatively. Current business scenario calls for an effective methodology for competitive advantage selection. In tackling MADM problems in real situations, the analytical hierarchy process (AHP) is a widely used approach (Satty, 1980). AHP can handle twelve types of problems: deciding priorities, generating alternatives, choosing best alternatives, deciding demands, allocating resources, forecasting results or evaluating risks, measuring performance, designing systems, making systems stable, optimizing, planning, and resolving conflicts (Satty, 1980). Dyer and Forman (1992) show that AHP has many advantages which include its capacity to: (a) combine tangible and intangible characteristics of questions, (b) focus on a group objective rather than individual, and (c) continue brainstorm and obtain better responses. However, disadvantages involve (a) expression of problem out of environment uncertainty (Belton and Gear, 1983), (b) deuce deficiency resulting from hierarchies (Millet and Harker, 1990), and (c) possibility of linguistic error in responding to the AHP questionnaire (Jang, 1991). Despite its popularity and simplicity in concept, this method lacks the ability to adequately handle the inherent uncertainty and imprecision associated with quantifying decision maker’s perception. In the traditional formulation of the AHP, human’s judgments are represented as exact numbers. In many practical cases, the human preference is uncertain and decision makers might be reluctant or unable to assign exact numerical values to the comparison judgments. To improve the AHP method and to facilitate TQM implementation criteria selection, this study employs a fuzzy AHP approach which uses triangular fuzzy numbers to represent the comparison judgments of decision makers (Chang, 1996; Kang and Lee, 2006). The fuzzy set theory resembles human reasoning in its use of approximate information and uncertainty to generate decisions. It has the advantage of mathematically representing uncertainty and vagueness, and of providing formalized tools for dealing with the imprecision intrinsic to many problems. The approach finds basis on the work of Van Laarhoven and Pedrycz (1983) and Buckley (1985). These studies apply fuzzy set theory in AHP to overcome linguistic uncertainty in multiple attribute decision making (MADM), where cardinality represents linguistic intensity for fuzzy arithmetic, known as FAHP. In addition, Herrera et al. (1995) present a linguistic order-weighted averaging operator based on the definition provided by Yager (1988) and on the convex combination of linguistic labels defined by Delgado et al. (1993) to resolve uncertainty in MADM problem. Each method has its own individual advantages. Linguistic information coupled with cardinal labels report the final results in concrete numbers. The linguistic information combined with linguistic labels reflects original linguistic opinions, but with final results presented in notional words. To concretely express research data to readers, the cardinal label set was adopted. The applied FAHP uses the triangular fuzzy numbers as a pairwise comparison scale in deriving the priorities of the selection criteria and attributes. However, five types of fuzzy membership function exists in tackling fuzzy numbers, namely, triangular function,
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trapezoidal function, S function, Z function, and PI function. With reference to the design of a questionnaire reporting the intensity of an interviewee opinion in one point, Hsu et al. (2003) shows that triangular function is better than others types. Therefore, the triangular fuzzy number was employed. This research adopts the method proposed by Netherlands’s scholar van Laarhoven and Pedrycg (1983), Chang’s extent analysis (1996) and Sheu (2004), where the fuzzy comparing judgment is represented by triangular fuzzy numbers. The weight vectors, with respect to each element under a certain criterion, was developed using the principle of the comparison of fuzzy numbers. Of critical importance in this process is the appropriateness of management criteria to its planned level of effort in reaching the competitive advantage. The overall objective of this study is to identify the competitive advantage in the TQM implementation of the empirical study firms in uncertainty. Specifically, it aims to apply an FAHP method that will facilitate the competitive advantage selection process and to perform a series of sensitivity analysis. This study utilizes critical information from a group of experts in the industry in developing the applied method. In particular, the developed approach can adequately handle the inherent uncertainty and imprecision of the human decision making process and can provide the flexibility and robustness needed for the decision maker to understand the decision priorities. These merits will help facilitate its use in making effective real-life decisions. The remainder of the paper is organized as follows. Section 2 discusses the literature review. Section 3 contains the methodology. Section 4 presents the numerical result and Section 5 gives the research findings. 2. Literature review This section identifies the theoretical background considered in this study’s objectives. TQM in strategic plan, effective leadership, customer focus, people management and process management are presented as a strategic, decision making perspective to improve present performance. This review also covers criteria identification in order to describe the decisionmaking process (FAHP) and criteria in enhancing such. 2.1 Fuzzy analytic hierarchy process Researchers propose various FAHP methods. The use of FAHP concepts in these methods provides a systematic approach to the alternative selection and justification problem. The earliest work in FAHP, accomplished by van Laarhoven and Pedrycz (1983), compares fuzzy ratios described by triangular membership functions. On the other hand, Buckley (1985) determines fuzzy priorities of comparison ratios whose membership functions are trapezoidal. Stam et al. (1996) explore how developed artificial intelligence techniques can be used to determine or approximate the preference ratings in AHP and conclude that the feed-forward neural network formulation appears to be a powerful tool for analyzing discrete alternative MADM problems with imprecise or fuzzy ratio-scale preference judgments. Chang (1996) introduces a new FAHP approach, with the use of triangular fuzzy numbers for pairwise comparison scale, and the use of the extent analysis method for the synthetic extent values of the pairwise comparisons. Weck et al. (1997) present a method to evaluate different production cycle alternatives by including the mathematics of fuzzy logic to the classical AHP. Any production cycle evaluated in this manner yields a fuzzy set, which can be defuzzified by forming the surface center of gravity of any fuzzy set. Alternative production cycles investigated using this method can be ranked in terms of the main objective set. Kahraman et al. (2003) use a fuzzy objective and subjective method to obtain the weights in AHP and to make a fuzzy weighted evaluation. Deng (1999) presents a fuzzy approach for tackling qualitative MADM problems in a simple and straightforward manner. Lee, et al. (1999) provide a review of the basic ideas behind the AHP, which led them to introduce the concept of comparison interval and propose a methodology based on stochastic optimization 585
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to achieve global consistency and to accommodate the fuzzy nature of the comparison process. Cheng et al. (1999) proposes a new method for evaluating weapon systems through the use of AHP, based on linguistic variable weight. Zhu et al. (1999) discuss the extent analysis method and applications of FAHP. Chan et al. (2000) presents a technology selection algorithm to quantify both tangible and intangible benefits in a fuzzy environment. They describe an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations. By aggregating the hierarchy, the preferential weight of each alternative technology, the fuzzy appropriate index, can be determined. The fuzzy appropriate indices of different technologies can be ranked and preferential ranking orders of technologies be established. Several authors have explored the advantages of FAHP. Cheng et al. (2005) implement the FAHP method to help telecom carriers evaluate and plan their future broadband Metropolitan Area Network access strategy. Kahraman et al. (2003) present four fuzzy MADM approaches, including FAHP on a facility location selection problem. Bozdağ et al. (2003) implement FAHP to select the best computer-integrated-manufacturing system by taking into account both intangible and tangible factors. Kahraman et al. (2004) employ the FAHP to compare catering firms through customer satisfaction. Kulak and Kahraman (2005) compare the FAHP method and the fuzzy multi-attribute axiomatic design approach. 2.2 Total quality management The establishment of the Malcolm Baldrige National Quality Award (MBNQA) in 1987 as a statement of national intent to provide quality leadership resulted in the creation of similar quality awards and frameworks in other industrialized countries. Other key influencers (Juran, 1989; Gale and Klavans, 1985; Heller, 1994; Wilson and Collier, 2000; Lee et al., 2003) in the early days give significant contributions to the development of both the conceptual and practical sides of quality management. A number of research studies in TQM and quality awards systems led to a debate about the effectiveness of such awards criteria and of the various TQM elements (Samson and Terziovski, 1999; Taylor and Wright, 2003; Jung and Wang, 2006). Saraph et al. (1989) establishes eight factors; some of which are similar to those of Black and Porter (1996), and to the quality award categories. However, there certainly is not a clear agreement as to what the real factors of TQM are, and there will always be disagreements as to how to best cut the TQM cake into factors or elements. Black and Porter (1996) conduct factor analysis on a questionnaire administered to quality manager practitioners. From this, they established a list of ten factors that are described as critical to TQM. Samson and Terziovski (1999) examine the TQM practices and operation performance of a large number of manufacturing companies in order to determine the relationships between these practices, individually and collectively, and firm performance. The research uses a large database of 1200 Australian and New Zealand manufacturing organizations. The result shows that TQM practice intensity explains a significant proportion of variance in performance. Although their approach is sound and is similar to this study’s, the categories of leadership, people management, strategic plan, process management and customer focus were identified to be significant predictors of operational performance (Samson and Terziovski, 1999; Kaynak, 2003; Jung and Wang, 2006; Prajogo and Sohal, 2006). The TQM elements are based on literature review of historical development that satisfies content validity. 2.2.1 Leadership It is considered the major driver of TQM, which examines senior executive leadership and personal involvement in setting strategic directions, and building and maintaining an effective leadership system that can facilitate high organizational performance, individual development, and organizational learning (Waldman, 1994). TQM emphasizes the activities of senior 586
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leadership, much like transformational leadership theory (Bass, 1985). The core issues in effective leadership construct include the creation of unity of purpose, organizational development for best practice, organizational structure, change of organization, continuous improvement of best practices, employee participation and environmental protection (Wilson and Collier, 2000). 2.2.2 People management In this aspect, the issue focuses on how well human resource practices tie into and align with the strategic directions of an organization. According to Garvin (1991), this comes down to a simple test - the voice of the people. This research emphasizes the understanding of employees, education and training of employees, communication channel with all employees, health and safety, and employee development and involvement (Prajogo and Sohal, 2006). The pairwise questions serve as the bottom line on people management because they capture the combined impact of TQM implementation. Commonly heard statements by management level such as “people are really everything” and “people are our critical resource” lead to an expectation of this variable in TQM implementation (Black and Porter, 1996). 2.2.3 Customer focus This element determines current and emerging customer requirements and expectations, provides effective customer relationship management, and determines customer satisfaction in the organization (Evans and Lindsay, 1995; Ahire et al., 1996). This research measures the extent to which customer related information is disseminated through monitoring customer complaint resolution, recognizing customer demand, attending to customer needs, considering customer feedback in products design and measuring customer satisfaction (Forza and Filippini, 1998; Chong and Rundus, 2004; Prajogo and Sohal, 2006). 2.2.4 Strategic planning It focuses on strategic and business planning, and deployment of plans, along with the attention to customer and operational performance requirements of the organization (Evans and Lindsay, 1995). The emphasis is on customer-driven quality and operational performance excellence, as these are the key strategic business issues integral to overall business planning. It is appropriate to distinguish between the TQM perspective of strategy and corporate strategy. The perspective strategy deals extensively with business unit strategy in the sense of ‘how to compete for a set of customers’. Corporate strategy deals with how to decide which customers to compete for the extent of a defined central purpose and mission in the organization (Wilson and Collier, 2000). 2.2.5 Process management TQM concerns organization designs, introduces products and services, integrates production and delivery requirements and manages the performance of suppliers (Evans and Lindsay, 1995). The core idea behind this principle is that organizations are sets of interlinked processes, and that improvement of these processes is the foundation of performance improvement (Deming, 1986). Deming saw sets of interlinked processes as systems, and his treatment of organizational systems is generally consistent with the use of this term in management theory. According to Dean and Bowen (1994), the intellectual turf represented by this category has been abandoned by management theorists and is currently occupied by industrial engineers. The measurement of this element is linked to product development of supplier, bilateral fluent processes from close corporation, self quality control of suppliers, well-established mechanism for product quality and clear operating procedures. Though there will always be debates about how to categorize elements of a holistic process and framework such as TQM, it is necessary to classify it to facilitate analysis. Since the most pervasive and 587
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universal method has been awards criteria such as the MBNQA, this study follows the TQM factors from the studies of Saraph et al. (1989), Black and Porter (1996), Evans and Lindsay (1995), and Samson and Terziovski, (1999). 2.3 Competitive advantages A common success theme of operations strategy lies on manufacturers’ choice of emphasis among key capabilities or competitive advantages. The preferred competitive advantage guides operations development and specifies how the operations function provides a firm with competitive advantage in the marketplace or tactical goal of the operational functions (Wheelwright and Bowen, 1996; Hills, 2000; Chenhall and Langfield-Smith, 1998). Once competitive advantages are chosen, they become the basis for making operational decisions in the marketplace (Ward et al., 1995; Margaret, 1996). Manufacturing strategy literature suggests four competitive advantages: low cost, quality, delivery, and flexibility (Skinner, 1974; Van Dierdonck and Miller, 1980; Hayes and Wheelwright, 1984). The character of each competitive priority is discussed as follows: Cost refers the production and distribution of a product or service at lowest expense. Lowering prices can increase demand for products or services, but it can also reduce profit margins if the product or service cannot be produced at a lower cost. Lowering cost can capture the competitive priority by placing an emphasis on reducing production costs and inventory while increasing equipment utilization and capacity utilization (Kathuria, 2000; Ward and Duray, 2000; Tseng and Chiu, 2004). Garvin (1991) points out that quality is multidimensional and that each of its dimensions can be used strategically to gain competitive advantage. The quality scale that is being used includes items related to the important quality aspect of process control and process management, specifically, high performance design on the future of superior features, close tolerance and great durability. Quality consistency refers to the frequency of meeting the design specifications. The flexibility scale intends to capture the importance of reducing costs associated with changing products or mix. In particular, the scale measures the relative emphasis placed on the capacity for lead-time and set-up time reductions, the ability to change priority of jobs on the shop floor, and the ability to change machine assignments on the shop floor (Ward and Duray, 2000). Delivery pertains to manufacturers’ emphasis on customer service as indicated by either delivery reliability or delivery speed. Delivery reliability refers to the ability to meet delivery schedule or promises, whereas delivery speed refers to the ability to react quickly to customer orders (Kathuria, 2000). 2.4 Rationale of research hierarchical structure The study problem finds application in the PCB manufacturing industry, where firms seek the best competitive advantage due to tough market condition. Critical to the implementation of a TQM strategy is taking into consideration all the possible important criteria which can affect in the selection of their competitive advantage. To aid in the determination of the different criteria, a decision-making group, consisting of management professionals in each strategic decision areas, was formed. The group discussed and decided among them the attributes associated with the criteria involved in selecting the competitive advantage in TQM implementation. A total of thirty (30) attributes were considered for the five (5) criteria available in TQM implementation. Figure 1 shows the hierarchy developed by the experts for the selection of the competitive advantage in TQM implementation. The following steps summarize the hierarchical structure:
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a. b. c. d. e.
Define the competitive advantage selection problem Identify the overall objectives Identify the criteria and attributes that must be satisfied to fulfill the overall objectives Identify the competitive advantage alternatives Structure the hierarchy by placing the objective at first level, criteria at second level, attributes at third level, and decision or selection of competitive advantage at fourth level Ultimately, the research motivation is based on wishing to contribute to knowledge about “What works might improve presence performance?” The research method is based on the selection of a competitive advantage in TQM implementation, due to the reliability and validity of the TQM factors were evaluated in the previous studies (Samson and Terziovski, 1999; Kaynak, 2003; Jung and Wang, 2006; Prajogo and Sohal, 2006).
Figure 1. Hierarchical structure for selection of competitive advantage in TQM implementation
3. Methodology After the construction of the hierarchy, the different priority weights of the each criteria, attributes and competitive advantage selection are calculated using the FAHP approach. The comparison of the importance or preference of one criterion, attribute or alternative over
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another was accomplished through the questionnaire filled out by the participating experts. Available research and current business scenario also aided in the decision making process. In synthesizing experts’ opinions, the geometric mean method proposed by Buckley (1985) was employed. In consideration of environmental uncertainty and simulation analysis, the algorithm of FAHP was based on relative research (Cheng and Mon, 1994). Algorithmic steps of the proposed FAHP method follows: Table1. Linguistic value table Fuzzy language Absolute important Demonstrated important Strong important Weak important Equal unimportant Intermediate values between the two adjacent judgments
Quantitative value 9 7 5 3 1 2,4,6,8
Step 1. Experts in PCB industry were invited to construct the TQM issue hierarchically. Based on the proposed hierarchy, a questionnaire was formulated to compare the different criteria pairwisely in their contribution toward achieving the goal of TQM implementation and then to compare detailed criteria pairwisely in their contribution toward attaining their upper-level criterion. Since five (5) criteria were used, five (5) different levels of evaluation were employed. Table 1 presents the linguistic values. Step 2. Set up fuzzy numbers in the all hierarchies. The triangular fuzzy membership function is given by. 0 x
