By Norman Bennett,2014-08-08 02:14
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    Strategy Fit with Fuzzy Logic: A Case Study for Taiwanese


     Chao-Chin Kan Wen-Chuan Tsai

    Southern Taiwan University Southern Taiwan University


    This article proposes a crucial strategy fit combining strategic business units and supply chain operation strategy in line with Taiwanese companies operational management by fuzzy logic. The

    feedstock of strategic business units and supply chain operation include Five-forces, product life cycle, and primary activities and support activities, respectively. A framework of strategy fit has been produced which formed the basis of case study in four Taiwanese companies. Some of the more significant findings were that: The competitive intension of Five-forces in companies A1-A4 were H, M, H, and M, respectively. And the product life cycle of companies A1-A4 were maturity, growth, maturity, and growth stages, respectively. Therefore, companies A1 and A3 adopted efficient strategy

    and companies A2 and A4 used responsive and efficient strategy. Moreover, the four Taiwanese

    companies can depend on the activities of eight parts to achieve the lowest cost goal with efficient strategy, and respond quickly to demand goal with responsive strategy.

    Keywords: strategic business units, supply chain operation strategy, Five-forces, product life cycle

     Fuzzy logic


    This research explores and expands Fishers (1997) Supply Chain approach that Taiwanese companies

    should combine supply chain operation strategy to the stages of product life cycle (PLC), which depend on Five-forces analysis to recognize competitive statue of strategic business units (SBUs) because many Taiwanese companies, especially, small to medium sized enterprises, have difficultly with strategic thinking (Kan and Tsai, 2007) so that these companies are neither strategic planning nor considered strategy fit. Chopra and Meindl (2001) refer to “strategy fit, as both SBUs and supply

    chain operation strategy have to support each other, to achieve organizational goals. SBUs are designed to provide the capabilities that the supply chain operation strategy aims to build. A company‟s success

    or failure is thus closely linked to the following keys: The competitive strategy in SBUs and supply chain operation strategy must fit together to form a coordinated overall strategy and help an organization reach its strategy goal. The different functions in a company must appropriately structure their processes and resources to be able to execute these strategies successfully (Chopra and Meindl, 2001).

     Crisp logic involves two values such as SBUs level/supply chain operation level and competition/cooperation. Such logic has two main concepts: the concept of contradiction, a thing cannot be itself and something else; and the concept of excluding the middle: a thing is one of two mutually exclusive things. This idea has been criticized in the management field, with the advice that


leaders should consider “Both/And” rather than “Either/Or. Kosko (1999) points out that the definition

    of a system boundary neither belongs to the system nor perfectly not belongs to the system. Instead, it should belong to some degree of a system. Similarly, a novel thinking logic combines some degree of the SBUs level and supply chain operation level. Anderson (1994) mentions that fuzzy logic includes three main elements: fuzzy sets, membership functions and production rules. Fuzzy sets have variable boundaries between 0 and 1 as a membership function. Production rules are a list of fuzzy logic if-then statements that represent human knowledge and describe the proper behavior of the system being controlled (Kosko, 1999). Moreover, Akcakaya et al. (2000) explain that one of the simplest and best

    ways to represent uncertainty is to specify a range of possible values as triangular fuzzy numbers (TFN) (Bojadziev and Bojadziev, 1997).

     The fuzzy logic controls (FLC) methodology has been developed mainly for the needs of industrial engineering. The if-then inferential rules are used to replace conventional mathematical models, because it is almost impossible when complex phenomena are under study, and the presented methodology creates fuzzy logic models reflecting a given situation in reality and offers solution leading to suggestion for action (Bojadziev and Bojadziev, 1997). As Kaplan and Norton (1996) point out, a strategy can be described as a series of hypotheses about cause-effect relationships by means of if-then declarations. Therefore, fuzzy if-then rules and TFN were applied in this research for combining SBUs level and supply chain operation level to achieve strategy goals successfully in organizations. 2. THE NATURE OF FIVE-FORCES AND SUPPLY CHAIN OPERATION

    2.1 Five-forces analysis

    Porter‟s framework for industry analysis generalized the supply-demand analysis in three respects. First,

    it relaxed the assumptions of both large numbers and homogeneity, namely, existing competitors. Second, it shifted from two-stage vertical chains suppliers and buyers, to three-stage chains suppliers, rivals, and buyers. Third, it considered potential entrants and substitutes, and direct rivals. Porter (1985) points out that competitive strategy is a dimension of essential concern to managers. Competitive strategy, therefore, seeks a favourable competitive position in an industry, which is the fundamental arena where competition occurs. Porter proposed the Five-forces model, which helps to realize its competitors and its own position, and to translate this analysis into a competitive strategy including differentiation, cost leadership, focus, share, emergent, and innovation strategy for a business.

    In any industry, whether it is domestic or international, a product or a service, the rules of competition are embraced in five competitive forces. Power of buyers (POB) influence the prices that companies face to the substitution threat (ST) and also impact cost and investment, because of powerful buyers who require costly service. The bargaining power of suppliers decides the costs of raw materials and just in time inputs. However, in order to fit the strategy development of this research, the name of this feature has been changed from “bargaining power of suppliers” to cooperation power of

    suppliers (CPOS). Rivalry among existing competitors (RA) impacts prices and the costs of

    competing, such as advertising. Threat of new entrants (TNE) imposes a limit on prices, and shapes the investment required to prohibit new entrants. According to these factors, a company can decide what stage of PLC it belongs to. The PLC dimension allows a company to consider multiple strategic issues


associated with each PLC stage as shown in Table 1.

    Table 1. The competitive environment (Source: Porter, 1985, p.6)

Rivalry determinants Threat of new entrants Industry growth Product differences Fixed (or storage) costs/ Variable costs High profits Price competition Learning curve Diversity of competitors Technological requirements Brand identity Economies of scale Switching costs Access to distribution Concentration and balance Absolute cost advantages Informational complexity Brand identity Corporate stakes Access to necessary inputs Exit barriers Proprietary low-cost product design Intermittent overcapacity Government policy Expected retaliation Switching costs Determinants of cooperation power of supplier Determinants of substitution threat Supplier volume Relative price performance of substitutes Presence of substitute inputs Rate of R&D in revenue Risk of forward integration Technological development Supplier concentration Switching costs Differentiation of inputs Buyer propensity to substitutes Cost relative to total purchases in the industry Impact of inputs on cost or differentiation Switching costs of suppliers and firms in the industry Determinants of buyer power Bargaining leverage Price sensitivity Buyer volume Product differences Threat of backward integration Price/Total purchases Substitute products Brand identity Buyer information Impact on quality/performance Buyer concentration versus firm concentration Buyer profits Buyer switching costs relative to firm switching costs Decision makers‟ incentives Pull-through

2.2 Rethinking the Five-forces model

    Recently, e-business shows that there is a wide management field involved in enterprise resource planning (ERP) and customer relationship management, so that there emerges a crucial idea, mutual

    trust and beneficence”, in terms of supply chain management (Chopra and Meindl, 2001) rather than Porters competition thinking model. Porters (2001) article, Strategy and the Internet, noted that the

    Internet brings negative and positive relationships that impact the Five-forces model. Regarding one of the Five-forces, “bargaining power of suppliers, according to Kalakota and Robinsons (1999) view of

    e-business and Harlands (1996) article, Supply Chain Management: Relationship, Chains, Networks,

    obviously, firms should think more in terms of mutual trust and suppliers have shifted from hostile

    relationships to cooperative relationships, rather than only paying attention to the bargaining power of suppliers.

     Similarly, Relationship Marketing (RM) not only focuses on keeping customers but also pays attention to attracting customers by creating long-term positive relationships and mutual trust (Gummesson, 1994). ERP highlights the effective integration of the organizations internal resources

    and the cooperation of external stakeholders thereby enhancing competitive advantage (Hammer and James, 1993). RM and ERP may be applied to adjust two of the Five-forces, bargaining power of

    buyers and rivalry among existing firms, respectively. From the discussion above, let us rethink how managers can apply the Five-forces model in strategy-making processes. However, Porter (2001) still


    emphasizes widely adaptation in academia and management practice the Five-forces rather than the Internet. Therefore, this research emphasizes both: the industry level with Five-forces analysis in order to ensure that stages of PLC in the market posture are acknowledged and their impact on strategy determined for supply chain operation (Boddy and Paton, 1998).

    2.3 Supply chain operation

    The organization‟s capabilities and competences must be comprehended before any form of strategy can be pursued. These factors indicate that the assessment of capability must consider the overall balance of resources which are deployed in the various activities of the organization, as well as the quantity or quality of the different resource inputs.

    A widely adopted method for contributing to a companys relative cost position and creating a

    basis of differentiation is the supply chain operation. The supply chain operation divides a firm into two categories: primary activities and support activities. Primary activities combine “inbound

    logistics, “operations,” “outbound logistics,” “marketing and sales, and “service. Support activities

    include human resource management” and “firm infrastructure”. Based on what is identified above,

    this research divides the activities of the supply chain operation into eight parts: product design, pricing, manufacturing, inventory, lead time, supplier, transportation and service, which will be explained in Table 3. Basically, an effective supply chain operation strategy has to notice the nature of the demand in a company. Product features and the customer segment being served need adjustment as a product goes through its life cycle. A product passes through an S-shape as introduction, growth, maturity and decline occur because of the process of innovation and diffusion of a new product (Kotler, 1972).

    The introduction phase is characterized by the difficulty of overcoming customer inertia and stimulating hard demand for the new product. Marginal profits are often high, and time is of the essence for getting sales. Capturing the market is more important than the consideration of the cost factor. Rapid growth happens as many consumers rush into the market when the product has demonstrated itself successful. Penetration of the product‟s potential consumers is ultimately gained, so the rapid growth stops and levels out to a basic rate of growth. In other words, when products gradually develop into the maturity stage of PLC, demand is more sure; marginal profits often lower, and competitors increase, so price is an essential factor in customers‟ selection. Finally, growth will ultimately stay steady or even decrease when new substitute products emerge.

    The PLC has encountered some criticism, for example, it is often not clear what stage of PLC an industry is in. Companies can influence the shape of the growth curve by means of product innovation and repositioning and sometimes industries omit maturity by passing through from growth to decline. However, Miller (1998) asserts that the PLC provides a useful framework for SBUs‟ strategy formulation because it provides a summary for numerous strategic situations. If a firm is, therefore, to maintain strategy fit, its supply chain operation strategy must evolve as its products enter different phases (Chopra and Meindl, 2001).

    Fisher (1997) classifies products into two categories: primarily functional and primarily innovative. Each category needs a distinctly different kind of supply chain operation strategy. When it


is a functional product or in the maturity stage of PLC, it requires an “efficient supply chain operation

    strategy” because it has to reduce cost to boost competitive advantage. Conversely, when it is an innovative product or in the introduction stage of PLC, it requires a “responsive supply chain operation

    strategy” because it has to quickly respond to customers needs as shown in Table 2. Basically, a

    responsive supply chain operation strategy is able to respond to wide ranges of quantities demanded, meet short lead times, and meet a very high service level. On the other hand, an efficient supply chain operation strategy focuses on the cost of making and delivering a product to the customer. Moreover, Table 3 shows the activities of the supply chain operation under efficient and responsive strategies.

    Table 2. Supply chain operation strategy match with the stage of PLC

    (Source: Adapted from Fisher, 1997, p.109)

    Innovative products Functional products

    (Introduction stage of Growth stage of PLC (Maturity and decline

    PLC) stage of PLC)

    Responsive supply match mismatch mismatch

    chain strategy

    Responsive and mismatch match mismatch

    efficient supply chain


    Efficient supply chain mismatch mismatch match


    Table 3. Comparison of efficient and responsive supply chain operation strategies

    (Source: Adapted from Fisher, 1997, p.108)

     Efficient supply chain operation Responsive supply chain operation

    strategy strategy

    Primary goal Supply demand at the lowest cost Respond quickly to demand

    Product design activity Maximize performance at a minimum Create modularity to allow

    product cost postponement of product


    Pricing activity Lower margins because price is a prime Higher margins, as price is not a

    customer drive prime customer driver

    Manufacturing activity Lower costs through high utilization Maintain capacity flexibility to meet

    unexpected demand

    Inventory activity Minimize inventory to lower cost Maintain buffer inventory to meet

    unexpected demand

    Lead time activity Reduce but not at the expense of costs Aggressively reduce even if the costs

    are significant

    Supplier activity Select based on cost and quality Select based on speed, flexibility, and


    Transportation activity Greater reliance on low cost modes Greater reliance on responsive modes

    Service activity Select based on lower cost Service quality is just in time

    Besides Fisher‟s (1997) efficient strategy, this research proposes three complementary strategies: liquidation, innovation, and divestiture, when products are located in the maturity and decline stage, a company has to consider other strategies. They are introduced as follows. Liquidation: A company tries to obtain tangible values through gradually selling its assets. Innovation: Innovation, according to the degree of intrinsical newness, three different kinds of

    innovation can be identified, i.e. nominal, incremental, and radical. Radical innovation is a high degree of intrinsical newness. In general, when companies discover that their products are in the declining


    stage of the S-shape, as a way of enhancing their competitive advantage. An incremental innovation involves a lower degree of intrinsical newness as the organization refines. A nominal innovation is an innovation in name only, i.e., a new use of an existing computer system is only new for the organization concerned at that moment. Therefore, an innovative company encourages learning which brings continuous adjustment to its market, organization and technology innovation, in order to fit as environmental forces and markets tend to decline.

     Divestiture: When a division needs more resources to compete than the company can offer, an organization sells a product line or SBUs. The relationship between SBUs and supply chain operation

    strategy is shown in Figure 1.

    Strategic business units

     Introduction and Growth Maturity and Decline

     ; Quick response ; Innovation strategy

     ; Product capturing the market ; Differentiation strategy

     ; Share strategy ; Share and emergent strategy

     ; Pricing or lower cost strategy

     Supply chain operation strategy

    Responsiveness Efficiency




    ; Product design ; Lead time ; Pricing ; Supplier

     ; Manufacturing ; Transportation ; Inventory ; Service

    Figure 1. The relationship of strategic business units and supply chain operation strategy

2.4 Fuzzy logic

    The FLC systems include three primary procedures: fuzzification, inference and defuzzification: First, fuzzification uses linguistic variables. Linguistics variables have to be defined in order to all variables used in the if-then rules for input variables. Second, inference uses if-then rules. When all numerical input values have been transformed to linguistic values, the fuzzy inference step can recognize the rules that apply to the current situation and can compute the values of the output linguistic variables. Altrock (1997) points out that the computation of the fuzzy inference comprises two components: Aggregation: computation of the „if‟ part of the rules, and composition: computation

    of the „then‟ part of the rules.

     At the end of the fuzzy logic inference, the result is given as a linguistic variable value. Third, to use this value for comparisons or ranking, it has to be translated into a numerical value. This step is called defuzzification. Commonly, there are three methods of defuzzification. According to centre of area (COA), the most popular method, is quite natural from the point of view of common sense. Therefore, it will be used for defuzzification in the research. Hellendoorn and Thomas (1993) proposed that the centroid method calculates defuzzification via the following formula:

    ()xxdxˆx(iDS j()xdxˆx(i


    ˆA[L,M,H]as When a fuzzy number, however, is equal to one single triangular fuzzy number

    formula (1) be used to measure data of case study or five membership functions as formula (2) is used for defuzzification measuring of Five-forces., then the formula of defuzzification are respectively as follows: (H+M+L)/3 (1) DSj

    (The centroid value of very weakthe area of very weak according to its degree) + (The

    centroid value of weakthe area of weak according to its degree) + (The centroid value of

    moderatethe area of moderate according to its degree) + (The centroid value of

    strongthe area of strong according to its degree) + (The centroid value of very

    strongthe area of very strong according to its degree) (the area of very weak according

    to its degree + the area of weak according to its degree + the area of moderate according

    to its degree + the area of strong according to its degree + the area of very strong

    according to its degree) (2)

    As mention above, therefore, this research proposes that the framework of integrating SBUs and functions levels for strategy fit to fulfill strategy goal with fuzzy logic as shown in Figure 2.

     Competitive intensity of Five-forces

    Low (0-0.599~) Moderate (0.6 -0.749~) High (0.75 -1.0)

     Introduction stage Growth stage Maturity and decline stage

    Product life cycle (PLC)

    Supply chain Responsive strategy Responsive and Efficient, Liquidation,

    operation strategy efficient strategy Innovation, Divestiture


    Figure 2. Framework of strategy fit


    3.1 Relationship of Five-forces and PLC

    In Figure 2, it indicates that if Five-forces analysis yields the result “L of competitive intensity”, then

    SBUs are seen as in the introduction stage of PLC. SBUs in the growth stage of PLC, when Five-forces analysis, have “M of competitive intensity”. When SBUs are in the maturity and decline stage of PLC,

    if Five-forces analysis, they have “H of competitive intensity”.

    3.2 Rules of supply chain operation strategy

    All implementing activities in SBUs can be represented using a supply chain operation. Supply chain operation activities are, therefore, the discrete building blocks of competitive advantage. How each activity is performed, combined with its economics, will determine whether a company is high or low cost relative to competitors and its contribution to buyer needs and hence will lead to differentiation by responsive supply chain operation. The fuzzy if-then rules help to transform the competitive environment into characteristics of strategic thinking. Practically, senior managers can identify changes in the environment to perform supply chain operation strategy for promoting strategy goal in an organization by proper choice of fuzzy if-then rules as shown in Table 4.


    Table 4. Rules of supply chain operation strategy

     If Five-forces belongs to „L‟ or „M‟ or „H‟, then the supply chain operation strategy is „responsive‟

    or „responsive and efficient‟ or „efficient or innovative or liquidation or divestiture‟.


    Yin (1994) argues that case studies, as experiments, are generalizable to theoretical propositions rather than populations, while being used with multiple-case studies, so it is used in this research. Three

    managers in each company have to pick an appropriate competitive intensity of each force from very low (VL), low (L), moderate (M), high (H), very high (VH) for Five-forces and membership function

    as shown in Figure 3 in four companies of the case study. When a company runs SBUs which have to recognize the competitive environment, the state of competition in which stage of PLC depends on Five-forces. Linguistic variables of Five-forces have to be defined for all variables which are used in the fuzzy “if-then” rules. Twelve senior managers from four companies confirmed the measurement of the Five-forces with TFN for any force in Five-forces. In turn, COA is used to compute competitive degree of each force with formula (2) and Figure 3 and located them into one of low (0-0.599~) or moderate (0.6-0.749~) or high (0.75-1.0). Finally, based on repeated combination formula n;r1C(where n = 3, r = 5), there are 21 possible rules to decide competitive intensity of Five-forces r

    with L, M, and H as shown in Table 5.


    Very low low Moderate high Very high


    Five-forces (Ff) 0 6 24 54 82 96 100

    Figure 3. The Membership function of Five-forces


    5.1 Competitive intensity of Five-forces for companies A1-A4

    Based on TFN in Table 6, company A1 obtained the average of Five-forces 91, 69, 85, 77, 88 and from Figure 3 got strong or weak degree of Five-forces, H=0.36, VH=0.64; M=0.46, H=0.54; H=0.79, VH=0.21; M=0.18, H=0.82; and H=0.57, VH=0.43, respectively. Finally, based on COA formula for

    12.40560.773;0.966888.64company A1, defuzzification of Five-forces were RA =; 0.852612.4056;8.64

    similarly, TNE = 0.6402, CPOS = 0.8015, ST = 0.6965, and POB = 0.8261, respectively.


    Table 5. Rules of competition intensity of Five-forces

    Possible rules Then If: Condition Competition intensity Rule1 H H H H H H Rule 2 H H H H M H Rule 3 H H H H L H Rule 4 H H H M M H Rule 5 H H H M L M Rule 6 H H H L L M Rule 7 H H M M M M Rule 8 H H M M L M Rule 9 H H L L L M Rule 10 H M M M M M Rule 11 H H M L L M Rule 12 H M M M L M Rule 13 H M M L L M Rule 14 M M M L L M Rule 15 M M M M L M Rule 16 M M M M M M Rule 17 H M L L L M Rule 18 H L L L L L Rule 19 M M L L L L Rule 20 M L L L L L Rule 21 L L L L L L

     Similarly, companies A2-A4 obtained the average of Five-forces, 70, 69, 72, 53, and 61; 96, 77,

    86, 81, and 83; 69, 53, 70, 77, and 61 and further from Figure 3 got strong or weak degree of Five-forces, A2= (M=0.43, H=0.57; M=0.46, H=0.54; M=0.36, H=0.64; W=0.03, M=0.97; M=0.75, H=0.25); A3= (VH=1; M=0.18, H=0.82; H=0.71, VH=0.29; M=0.04, H=0.96; H=0.93, VH=0.07); A4= (M=0.46, H=0.54; W=0.03, M=0.97; M=0.43, H=0.57; M=0.18, H=0.82; M=0.75, H=0.25), respectively. Finally, based on COA formula for company A2-A4, defuzzification of Five-forces were A2=0.6449, 0.6403, 0.6568, 0.5212, and 0.5936; A3=0.9669, 0.6965, 0.8107, 0.7494, and 0.7837; A4=0.6403, 0.5212, 0.6449, 0.6965, and 0.5936, respectively.

    Table 6. Competitive intensity of Five-forces for companies A1-A4

    Company Five-forces RA TNE CPOS ST POB A1 (82, 94, 98); 91 (44, 73, 91); 69 (68, 88, 97); 85 (54, 82, 96); 77 (80, 86, 97); 88 H=0.36 VH=0.64 M=0.46, H=0.54 H=0.79; VH=0.21 M=0.18, H=0.82 H=0.57, VH=0.43

    0.8526?H 0.6402?M 0.8015?H 0.6965?M 0.8261?H

    From rule 4, Five-forces?H

    A2 (54, 78, 87); 70 (44, 73, 91); 69 (55, 75, 87); 72 (24, 54, 82); 53 (33, 63, 87); 61 M=0.43, H=0.57 M=0.46, H=0.54 M=0.36, H=0.64 W=0.03, M=0.97 M=0.75, H=0.25

    0.6449?M 0.6403?M 0.6568?M 0.5212?L 0.5936?L

    From rule 14, Five-forces?M

    A3 (95, 96, 96); 96 (54, 82, 96); 77 (74, 87, 97); 86 (69, 81, 93); 81 (68, 87, 94); 83 VH=1 M=0.18, H=0.82 H=0.71, VH=0.29 M=0.04, H=0.96 H=0.93, VH=0.07

    0.96688?H 0.6965?M 0.8107?H 0.7494?M 0.7837?H

    From rule 4, Five-forces?H

    A4 (49, 69, 88); 69 (24, 54, 82); 53 (46, 73, 91); 70 (54, 82, 96); 77 (34, 63, 87); 61 M=0.46, H=0.54 W=0.03, M=0.97 M=0.43, H=0.57 M=0.18, H=0.82 M=0.75, H=0.25

    0.6403?M 0.5212?L 0.6449?M 0.6965?M 0.5936?L

    From rule 14, Five-forces?M

    The results of competitive intensity of Five-forces in companies A1-A4 were H, M, H, M, and H; M, M, M, L, and L; H, M, H, M, and H; M, L, M, M, and L. Therefore, company A1-A4 were based on if-then rules of 4, 14, 4, and 14, the competitive intensity of Five-forces in companies A1 was H; A2 was

    M; A3 was H and A4 was M, as shown in Table 6. From case study analysis, this research found that companies A1 and A3 should use efficient strategy, but companies A2 and A4 can adopt responsive


    and efficient strategy, because companies A1 and A3 belonged to maturity and decline stage, and companies A2 and A4 belonged to growth stage of PLC, as shown in Figure 4 and the strategic decision rule matrix as shown in Table 7.

     Competitive intensity of Five-forces

     Moderate (0.6 -0.749~) Low (0-0.599~) High (0.75 -1.0)

     Introduction stage Growth stage Maturity and Decline stage

     Product life cycle Companies A1 and A3 Companies A2 and A4 (PLC)

    Supply chain Responsive strategy Responsive and Efficient, Liquidation,

    operation strategy efficient strategy Innovation, Divestiture


    Figure 4. Results of strategy fit

    Table 7. The strategic decision rule matrix If-conditions And-condition Then-decision Input Output RA Company A1? Maturity and Decline CPOS The competitive intension of Five-forces Company A2? Growth in companies A1-A4 are belonged to H, Five-forces analysis Company A3? Maturity and M, H, and M, respectively. POB Decline TEN Company A4? Growth ST The competitive intension PLC of four companies are shown as A1 ? Efficient strategy or of Five-forces is shown as follows: (Innovative or Liquidation Supply chain operation follows: Company A1? Maturity and Decline or Divestiture) strategy Company A1? H Company A2? Growth A2 and A4 ? Responsive Company A2? M and efficient strategy Company A3? Maturity and Decline A3? Efficient strategy or Company A3? H Company A4? Growth (Innovative or Liquidation Company A4? M or Divestiture)

5.2 Discussion for companies A1-A4

    Company A1. The company has three development phases: the introduction phase (1986-1992), the development phase (1993-1997), and the current growth phase (1998 until now). In the first phase, in 1989, the president of company A1 was replaced in order to build a new leadership style which was conducive to competitive advantage in the auto parts industry. The company adopted a cost focus strategy for survival first, and used a development strategy of diversification in 1991. However, profit per share was decreasing while sales were increasing, because of severe competition in the auto parts industry in Taiwan. In the second phase, the PLC of company A1 belonged to the maturity stage, and further proposed an efficient supply chain operation strategy to reduce cost. Company A1, therefore, had a higher growth of sales and became the biggest auto lighting company in Taiwan (Ho, 2000, p.16). In the third phase, company A1 further aimed to create a short-cut channel to contact customers directly and to create good relationships. President Ho points out that the key success factors of our company are “people” and a main mission - how does the company boost “quality of people”? In other words,

    our company emphasizes organizational culture to cohere employees‟ belief, completes communication

    in different departments for promoting cooperation, encourages team learning, lean manufacturing and


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