Competitive incentives for manufacturing flexibility

International Journal ofProduction Economics, 28 ( 1992) 35-45 Elsevier

35

Competitive incentives for manufacturing flexibility

Matthew A. Walle? and David P. Christyb

“Department of Business Logistics, heal College of Business Administration, Pennsylvania State University, University Park, PA 16802, USA bDepartment ofManagement Science, Smeal College of Business Administration, Pennsylvania State University, University Park, PA 16802, USA

(Received 12 August 199 1; accepted in revised form 17 February 1992 )

Abstract

A game theoretic model is used in this paper to analyze firms incentives to acquire product flexibility. The degree of product flexibility is determined by the cost a firm must incur to produce a new product. The model helps to identify characteristics of industries which are likely to encourage product flexibility strategies. The model suggests that firms in industries where the ratio of price to variable cost is high are likely to expend more effort to increase product flexibility. This hypothesis is then tested empirically.

1. Overview

This paper presents an analysis of incentives to invest in product flexibility, or the ability to produce new products. To operationalize this concept, the degree of product flexibility is defined as the cost that a firm must incur if it chooses to produce a new product. The less it costs a firm to produce a new product, the more “product flexible” is the firm. The model presented here investigates a situation where two firms use product differentiation as a basis for competition in a market. The results are intui- tive; the model suggests how the degree of product flexibility affects the outcomes of competition. One of the results shows that when market potential is high and/or the unit cost of production is low, tirms are likely to be in a prisoners’ dilemma situation, and thus have more incentives to increase product flexibility. A prisoners’

Correspondence to: Matthew A. Waller, Department of Busi- ness Logistics, Smeal College of Business Administration, Pennsylvania State University, University Park, PA 16802, USA.

dilemma exists when firms are in an unfavorable position because of their inability to make bind- ing commitments. An amiable analytical characteristic of this model is that for a given market demand and a given unit production cost the market equilibria depend entirely on the degree of product flexibility.

The results of the model may help a firm determine if product flexibility is likely to become an “order-winning” criterion in their industry. An “order-winning” criterion is a characteristic for which the firm is awarded orders over competing firms in the market [ 11.

Suppose a firm has several plants that produce products that compete in distinctly different industries (i.e., each plant produces a different product) and the firm has funds to acquire flexible manufacturing technology (FMT) for only one of the plants. Which of the plants should probably receive the highest priority for being equipped with FMT? The results in this study help to address this question. The model helps to identify which of the industries is most likely to have product flexibility become an order-winning criterion.

09255273/92/$05.00 0 1992 Elsevier Science Publishers B.V. All rights reserved.

36 M.A. Walier, D.P. Christy / Competitive incentives for manufacturingjlexibility

In Section 2 the literature is reviewed on flexible manufacturing technology (FMT), including typology of flexibility and analytical models of flexibility. This review is used to develop a con- ceptual link to the model that follows. Section 2.1 is an overview of what is meant by flexible manufacturing technology. Figure 1 classifies the analytical models which are reviewed in Section 2.3. In Section 3 the analytical model is defined and Nash equilibria are characterized in terms of rel- evant parameters of the model. A hypothesis suggested by the analytical model is discussed in Section 4.1 In Section 4.2 the source of the data used in the correlation analysis is described. Sec- tion 4.3 contains the results of the hypothesis test. Conclusions and discussion comprise Section 5.

2. Review of the literature

2.1. Flexible manufacturing technology

Flexible manufacturing technologies include automated guided vehicles, automated materials handling, computer aided design, computer aided manufacture, flexible manufacturing systems and computer integrated manufacturing. These FMTs require very high initial investments. Therefore, a decision to acquire them is both risky and strategic in nature.

Not long ago, the only form of automation with high initial investments were fixed-automation dedicated systems with the promise of economies of scale. Today a variety of FMTs are sought in order to gain economies of scope, namely, ef- ficiency brought about by production variety [ 2 1. The ability to utilize economies of scope comes from the promise of flexibility offered by FMTs.

While early theoretical work on the concept of flexibility can be found in literature [ 3 1, practi- cal concerns about flexibility arose when the competitiveness of the United States in international trade started to become a serious issue. Japanese companies continue to lead in the use of flexibility in manufacturing [ 4 1.

An important strategic contribution of FMT is the manufacturing flexibility it offers. However, since manufacturing flexibility is a relatively

complex concept, several authors have devised typologies of manufacturing flexibility [ 35-7 1.

2.2. Typologies offlexibility

Slack [6] identified five different types of manufacturing flexibility. New productflexibility is the ability to make something novel, product mix flexibility is the ability to switch between different products, qualityflexibility is the ability to change quality level, volume flexibility is the ability to change the volume of output, and delivery flexibility is the ability to change delivery dates.

Stigler [ 31 defined what many researchers today call volume flexibility. According to his def- inition, flexibility is the second derivative of the average cost function. A flexible firm has a relatively flat average cost curve. Therefore, at output levels which differ significantly from the minimum cost level of production, the loss is not as significant as would be the case for a firm with an average cost curve that is less flat (i.e., low flexibility). Thus, volume flexibility means that for a given change in volume there is a relatively minor change in average cost. This type of flexibility could be acquired to deal with uncertainty in the quantity demanded or to make strategic moves that were previously impossible.

Jones and Ostroy [ 5 ] presented one of the most general papers on flexibility. They defined flexibility as “ . ..the cost, or possibility, of moving to various second period positions” where flexibility is a “ . ..property of initial positions”.

Swamidass [ 7 ] defined flexibility according to various process contingencies. Three divisions of process contingencies, high-volume/low-variety, mid-volume/mid-variety, and low-volume/high- variety, are defined and the different types of flexibility required in each are explained. His typology of flexibility is supported through case studies that are presented in his research. In general, he defined flexibility as follows: “Manufac- turing flexibility refers to the capacity of a manufacturing system to adapt successfully to changing environmental conditions and process requirements. It refers to the ability of the pro-

M.A. Wailer, D.P. Christy /Competitive incentives for manufacturingjlexibility 37

duction system to cope with the instability in- duced by the environment.”

Many researchers are interested in the implications of flexibility on the firm. When is flexibility valuable? When is it appropriate for firms to try to increase their flexibility? Which of the firm’s manufacturing processes should be given priority for resources which will increase flexibility? Analytical models of flexibility attempt to address these questions.

2.3. Analytical models offlexibility

The model in this paper complements the work of Fine and Freund [ 8 ] whose analytical model was used to investigate product flexibility. They modeled a firm that chose among various com- binations of fixed and flexible capacity for the production of two products before demand information is received. They assumed that the cost of flexible capacity was more than the cost of dedicated capacity. One of the results of their study indicated that in some cases a product should be manufactured on a combination of FMT and dedicated equipment. The part of the demand that is stable can be manufactured on the dedicated equipment and the part of demand that is volatile can be manufactured on the FMT. Their model also illustrated that when demand is negatively correlated between two products, greater risk stimulates the need for FMT. How- ever, because of certain assumptions used in de- veloping their model, the results indicated that FMT will never be acquired when the demands of two products are perfectly positively correlated. They also showed that the need for FMT does not always increase as the level of risk increases.

Caulkins and Fine [ 9 ] extended the work of Fine and Freund to allow firms to carry inventory using a stochastic dynamic programming model. This is important since firms can realist- ically deal with uncertainty in demand by holding inventory. They showed that flexible capacity can be valuable even when there is no uncertainty about demand. The model in this paper also illustrates this. However, their model in-

dicated that determining the value of flexibility when firms are allowed to hold inventory is dif- ficult. Part of the difficulty arises from their lind- ing that investing in FMT and holding inventory may be substitutes, complements or neither. That is, it is not necessarily true that firms can simply hold inventory instead of investing in FMT to deal with uncertainty. Their analysis indicated that FMT may be more useful in dealing with uncertainty between products and that inventory may be more useful in dealing with uncertainty between periods. In contrast to Fine and Freund [ 8 1, Caulkins and Fine [ 9 ] found that it may not be optimal to use dedicated equipment to manufacture the part of demand that is stable and to use the FMT to manufacture the part of demand that is volatile.

Roller and Tombak [ 10 ] emphasized the importance of other firms’ decisions in their model, as is done in the model in this paper. Their research looked at the strategic implications of the choice between a FMT and dedicated equipment. In their model, the FMT could manufacture a higher variety of products than the dedicated equipment but the FMT was more expensive. They modeled a two-stage game between two firms. In stage 1 firms simultaneously committed to a production technology, and in the second period they simultaneously choose output. Their result indicated that firms will tend to adopt FMT when the size of the market is large and when the difference between the fixed costs of FMT and dedicated equipment is low. Welfare implications were also investigated in their research. They found that consumers are in the best position when both firms acquire FMT and in the worst position when both firms acquire dedicated equipment. This is so because FMT means lower prices because of increased competition. However, they found that firms are in the best position when both firms acquire dedicated equipment and in the worst position when both firms acquire FMT for the same reason that consumers are in the best position when both firms acquire FMT. Thus, when both firms acquiring FMT constitutes an equilibrium, these firms are in a prisoners’ dilemma. Their model suggested

38 M.A. Wailer, D.P. Christy /Competitive incentives for manufacturing flexibility

that one way firms can break the prisoners’ dilemma is to standardize their products, that is, make them closer substitutes.

Tombak and DeMeyer’s [ 111 research is similar to the model in this paper in that they ana- lyzed the situations in which firms would be most likely to want to invest in FMT. Their model emphasized the importance of uncertainty in inputs and outputs if firms’ decisions to acquire FMT while it ignored the role of the decisions of other firms. They performed two simple statistical tests of the hypotheses suggested by their analytical model. Based on their model, their first hypothesis was that firms acquire FMT to manage the uncertainty in their inputs. Their second hypothesis was that firms acquire FMT to deal with uncertainty in their outputs. Their empirical study suggested that firms that implement FMT are planning on narrowing or standardizing their product lines. This result is interesting in light of the research of Roller and Tombak [ lo]. (Recall the research of Roller and Tombak suggested that firms may be able to break out of the prisoners’ dilemma by standardizing their products. )

Kulatilaka and Marks [ 12 ] modeled the value of input flexibility, namely, the ability to switch between a labor intensive mode of production and a capital intensive mode of production. In their model, the firm chose a technology, negoti- ated the price with the supplier of the input, and then chose input quantities. They showed that in some circumstances the value of flexibility can be negative. Similarly, Hiebert [ 13 ] showed that as demand variability increases, the value of flexibility and the optimal level of flexibility may not increase.

Kulatilaka [ 14 ] developed a dynamic and stochastic model to analyze the option value of flexibility that arises due to the hypothesis that firms with flexibility are better at dealing with uncertainty. This model was a significant contribution to the theory which is intended to help under- stand phenomena associated with the acquisi- tion of FMT and has important managerial implications. It showed how capital budgeting techniques can be modified to deal with the

problems that FMT introduce into the investment decision. It also illustrated the fact that the design and investment justification stages need to be concurrent. For a literature review 2nd classification of approaches to planning ano J U I’. tifying flexible manufacturing technologies see Ref. [15].

Many of the analytical models may be model- ing similar types of flexibility and yet label them differently. Figure 1 lists each of the analytical models just reviewed and indicates the type of flexibility studied using Slack’s typology.

Five of the seven models in Fig. 1 emphasize the use of flexibility for dealing with uncertainty. However, the decisions of other firms in an industry can and should be of great significance to a firm in making decisions about flexibility. Only two of the seven models taken into account the strategic interaction of firms. The model developed in this paper studies product mix flexibility; it is simply called product flexibility. It emphasizes the role of the strategic interaction of firms in decisions about flexibility.

While the phenomena Fine and Freund model is very similar to the phenomena that is modeled in this paper, their model emphasizes the importance of risk and this model emphasizes the importance of the decisions of other firms in the industry. This is important since it is the decisions of other firms that help to create new order-winning criteria.

Roller and Tombak’s model is similar to the model in this paper in that it emphasizes the importance of the decisions of other firms. How- ever, the model in this paper does not directly model the decision to invest in FMT. Instead it characterizes the situation in which firms would be most likely to want to increase their product flexibility, whether it be by acquiring FMT or by some other means.

While the model in this paper looks at a single aspect of flexibility, we see our contribution in the same light Fine and Freund saw theirs: “We view our analysis as contributing to the theory necessary to develop realistic models for com- plete analysis of FMS investment decisions.” [ 8 ]

M.A. Wailer, D.P. Christy /Competitive incentives for manufacturingjlexibility 39

Fme 8

Freund

.(1990)

Caulkms a

Fine (1988)

product-

mix

flex.

product prod- flex. wth

llexible producton cost UC~IO” and respect to product

capaL%y tlexlblllty flex flex. process flex saps uex

Yes

Tombak 8 Kulatilaka 8 Roller 8

DeMeyer Marks Hiebert Kulatilaka Tombak

(1968) (1988) (1989) (1988) (1990) This Model

volume

and

input’

flex

InpUt’

flex

product-mix

volume and mput’ product- product-

flex. flex. mix flex. mix flex

yes “0 Yes Yes “0 “0

‘Input flexiblllty was not defined in any of the typologles. We will

call It Input flexibility for convience. Input flexibility IS the ability to

deal with variations m inputs.

Fig. 1. Classification of the analytical models of flexibility.

3. An analytical model of flexibility

3.1. The model

A situation is investigated where two firms compete in a market with product differentiation. It is assumed that all product development costs have been incurred in the past. Thus, the degree of product flexibility is only affected by costs associated with the manufacturing process due to switching from producing z to producing m. It is assumed that in period one both firms (firm’ and fit&) are producing product z because that is the only product demanded by the consumers. In period two consumers’ demand changes such that they prefer product m, al- though z is a close substitute, in the following way: If both firm’ and lit-m* produce only z in period two, then the inverse demand they face is given

by

P(X) =a-bx, (1)

where

P(x) = inverse demand function or price per unit as a function of quantity,

X = quantity of the product demanded, a = intercept of the inverse demand func-

tion, also known as the market potential or maximum potential price per unit,

b = slope of the inverse demand function. In this situation the firms choose quantities si-

multaneously, and therefore we get the Coumot (Nash) equilibrium. If Firm’ (firm*) produces n and firm* (firm’ ) produces z, then firm’ (firm* ) faces the inverse demand in Eq. ( 1) like a monopolist; firm* (firm’ ) faces the residual demand and optimizes. This situation implies that consumers prefer m in period two, and will therefore first purchase rn until the market has cleared. They will then purchase z at the market clearing price, based on the residual demand.

Neither firm knows whether or not the other firm is going to switch to producing m. If a firm switches to producing m, then it must incur a cost S. When s is large the firm is not product flexible and when s is small the firm is product flexible.

40 M.A. Wailer, D.P. Christy / Competitive incentives for manufacturingjlexibility

If both firms produce z in the second period, then firm”s profit is given by

n&= [a-b(x, +x;!)]xi -CX[, (2)

and firm *‘s profit is given by

n&= [a-b(x, +x2)1x* -cxz, (3)

where

$I = profit to firm ’ producing i when firm’ is producingj,

= profit to firm’ for producingj when firm’ is producing i,

X1 = quantity of z produced by firm’,

X, = quantity of z produced by firm2, c = variable production cost. (x1 and x2 may represent the quantity of z or m which ever is implied by the context. )

3.2. Outcomes of competition

A Nash equilibrium [ 161 is a situation in which each firm is optimizing given what the other firms are doing. A Cournot equilibrium is the Nash equilibrium of a game in which each firm produces an optimal quantity given the quantity produced by the other firm. The Cour- not (Nash) equilibrium of this game is

7r;:=7c;;=(a-c)*/9b. (4)

If both firms produce m, then the profit functions are as in Eqs. (2) and (3) with s sub- tracted. Thus the Cournot (Nash) equilibrium is given by

Zl* x2* mm= mm- - (a-c)2/9b-s, (5)

where K ‘* ??*,n = profit to firm ’ for producing m when firm*

is producing m, P$$,, = profit to firm2 for producing m when firm’

is producing m. (The * indicates that this is a Nash equilibrium. )

If firm’ is producing m and firm* is producing z, then the profit function for firm’ is given by

7t’ mm = (a-bx,)x, -CXt -3,

and optimization yields

n$&= (a-c)2/4b-s.

(6)

(7)

Now firm2 optimizes on the residual demand, where this residual demand is given by

~~~~i~~=~(x) =Q-h(xY +X2)> (8)

where x7 is the argument that maximizes Eq. (6). Hence, firm 2’s profit function is given by

n&,= [a-b(x:S_Xz)]X*-CX*. (9)

Firm 2’s optimization of Eq. (9 ) yields

x2,*,= (a-c)*/16b. (10)

If firm ’ is producing z and firm2 is producing m, then profit functions are derived in a similar manner.

3.3. Production decision

The decision to produce m or z in the second period can be viewed as a simultaneous game which can be described by the strategic form in Fig. 2. This means that both firms must make their decision simultaneously.

From Fig. 2 we see that (z,z) is an equilibrium when

niT-ng=>O and K~;--_~~>O. (11)

For the model developed in this section we can rewrite Eq. ( 11) as

s> 5(a-c)2/36b. (12)

The intercept of the demand function, a, is defined as the market potential. Hence, when the market potential is low or the variable cost of production is high firms are more likely to “cooperate” and not incurs. This would indicate that firms in markets with low market potential or high variable production costs are less likely to seek product flexibility since they are less likely to incur s.

Similarly, the conditions for (m,m) to be an equilibrium for the game in Fig. 2 are

x’* -Jr’* mm rm>O and n~&,-n~Z>O. (13)

These conditions imply that

s<7(a-c)2/144b. (14)

Here, when the market potential is high or the

M.A. Wailer, D.P. Christy /Competitive incentives for manufacturingflexibility 41

FIRM 1

m

FIRM 2 m

Fig. 2. General strategic form of the production decision. The entries in the zz cell represent the payoffs to the firms if firm 1 chooses z and firm 2 chooses z. Similarly, if firm 1 chooses tn and firm 2 chooses z, then the payoffs to the firms are found in cell mz. The choice of m and z is simultaneous for both firms.

FIRM 2

t

FIRM 1

m

L m

(a-c) * (a-c) 2 VBb

(a-Q2 Jb-s

(a-C)2 ’ lhb

(a-C)2 (a-$ -%--S’--S 9b

Fig. 3. Strategic form of the production decision for this game. and, hence, is the Nash equilibrium.

variable cost of production is low, firms are not likely to “cooperate”, and thus incur s. This can also be interpreted as: firms with more product flexibility are more likely to incur s. A prisoner’s dilemma is a situation where each firm chooses a strategy that makes it better off no matter what the other firm does and these strategies give each player a lower payoff than they would get if they

When Eq. (14) holds, m is a dominant strategy for both firms

cooperated. Note that when Eq. ( 14) holds we have a prisoner’s dilemma (see Fig. 3 ) .

When Eq. (14) holds, wt is a dominant strategy for both firms despite the result that if each firm played z, each would be better off. The problem is that given one firm is playing z, the other firm is better off playing m. Thus, it is not an equilibrium. Also, when Eq. ( 14) holds firms

42 M.A. Wukr, D.P. Christy / Competitive incentives for manufacturingjlexihility

are more likely to seek product flexibility because they incur s in equilibrium.

The previous two equilibria identified by Eqs. ( 12 ) and ( 14) were unique when they held. That is, if one of the above equilibria held, then the other did not hold. However, when (z,m) is an equilibrium so is (m,z) and vice versa. In fact, (m,z) and (z,m) are equilibria when

7(a-C)2/144b<s<5(a-c)2/36b. (15)

A hypothesis suggested by this model is now empirically investigated. The purpose of the empirical test is not to verify the model, since it is not really possible to do that. The purpose of the test is to see if there is any statistical evidence that the model should be rejected.

4. Empirical analysis

4.1. Hypothesis

Equation ( 14) holds when (a- c)/b is relatively high. When Eq. ( 14) holds, (m,wt) is the unique equilibrium and when (m,m) is an equilibrium, firms incur s. Thus, these firms would like to decrease s since they incur it in equilibrium. Decreasing s is equivalent to increasing product flexibility. Therefore, the model developed here suggests the following hypothesis: H,: Firms in industries where (a-c) /b is rela-

tively high are likely to expend more effort to increase product flexibility.

If the linear demand functions of the industries have the same slope, then for a given up- ward sloping supply curve, pl >,p2 if and only if a, 3 a2. Here, p, and p2 are points on two different inverse demand functions corresponding to an arbitrary level of demand; and a, is the intercept of the inverse demand function of the inverse demand corresponding to p1 and a2 is the intercept of the inverse demand function of the inverse demand corresponding to p2. As a result, H, can be rewritten as the following hypothesis: H,: Firms in industries where p/c is relatively

high are likely to expend more effort to increase product flexibility.

There are many obstacles to directly testing this

hypothesis. Most firms produce more than one product, hence, most firms would have multiple ps. The closest surrogate to the price to variable cost ratio is total revenue to total variable cost since total revenue/total variable cost = pq/vq =p/v. Of course, when there are several products and different quantities of the products are sold, the qs are not equal. As a result, this surrogate may be biased.

The next problem is to find a measure of a Iirm’s effort to increase its product flexibility. As was already mentioned, FMT often increases manufacturing flexibility [ 2,17-2 11. A measure of the degree of the use of FMT in manufacturing is used to measure a firm’s effort to increase its flexibility.

The two firm analytical model suggests that when the price to variable cost ratio is high that firms have more incentive to try to increase product flexibility. The real problem is that our model consists of only two firms. The question is “is there any evidence from industries with many firms that this hypothesis should be rejected?“. If there is evidence that it should be rejected, then the simplifying assumptions may not be leading us in a worth while direction. If there is no evidence that it should be rejected, then the model may be worth the insight that it is offering to un- derstand the phenomena. This evidence will be examined below.

4.2. Source of data

Yoon [ 22 ] surveyed Pennsylvania manufacturing firms; data was obtained from 190 firms for a 38% response rate. This data for five metal- working industries is used to test hypotheses on firms’ efforts to increase product flexibility. The five industries include primary metals, fabri- cated metal, metal-working machinery, trans- portation equipment, and precision instruments. The five industries were further divided into 90 smaller industries. That is, the five main industries were further separated according to their four digit SIC code. The number of responses that could be used in this study was 170. Appendix A shows the portion of Yoon’s survey employed in

h4.j Wailer, D.P. Christy /Competitive incentives for manufacturing flexibility 43

this study. A variable from the survey was used which was a mean of 11 items that measured the degree of utilization of FMT by firms; we call this variable COMCOR. COMCOR ranges from 1 to 5, where 5 represents the most use of FMT. The mean of COMCOR was 3.32 and the standard deviation was 0.63. For information on industry total revenue and variable costs, Manufacturing USA [24] was used.

Total variable cost was modeled as total materials costs for two reasons: First, materials costs typically represent about 60% of manufacturing costs, whereas labor represents only about 20%. Second, payroll cost data available for analysis includes the payroll for management, which is typically a fixed cost rather than a variable cost. The majority of the remainder of the labor cost is also relatively fixed.

In order to test our hypothesis we will investigate the relationship between the ratio of total revenue to total materials costs (independent variable ) and COMCOR (dependent variable ) . We will call the ratio of total revenue to total materials costs RATIO.

4.3. Result of the test of hypothesis

Simple correlation between COMCOR and RATIO showed a correlation of 0.156. However, our goal is to test the hypothesis. The fact that the correlation is relatively weak is unimportant since this is not being used for explanatory pur- poses. The hypothesis above was tested using a t- test and was significant at the 0.05 level.

5. Summary and conclusions

5.1. Summary

The model in this paper investigates firms’ incentives for product flexibility. The strategic interaction of firms was emphasized in the model since most models ignore this while emphasizing uncertainty. Game theory was the underlying technique used in the analytical model of flexibility. The model suggests that when the price to variable cost ratio is high, firms are likely to ex-

pend effort to increase product flexibility. The empirical test did not provide evidence that the hypothesis should be rejected.

5.2. Concluding discussion

There are two examples of high operating mar- gin industries where flexibility has become important. Both of these examples come from Swamidass [ 71. The motorcycle industry has high operating margins and high fixed costs. In the early 1980s Honda made 113 changes to its product line and Yamaha made 37 changes all within eighteen months. In this industry, product flexibility is clearly an order winning criterion.

The second example also comes from Swami- dass [ 7 1. It is General Electric’s locomotive plant in Pennsylvania. Again, this is an industry with high operating margins and high fixed costs. This plant installed a flexible manufacturing system that was capable of producing thousands of different motor frames using automatic tool changers.

Managers could use the results of this research to help determine which of their plants is most likely to have product flexibility become an order-winning criterion. Recall that an order winning criterion is a characteristic that may give the firm an advantage in the market. If a firm is in an industry with a relatively high ratio of total revenue to total materials costs, then it may be that flexibility is or will become an order-winning criterion. Inability to meet an order-winning criterion can be competitively devastating.

Many operations management issues are only studied from a tactical point of view when, in fact, the daily operational decisions made by operations managers affect the strategic position of a firm [ 24,25 1. This study has been an effort to analyze how product flexibility affect firms stra- tegically and competitively. Most research to this point has been concerned with describing flexibility. We looked for statistical evidence to reject our hypothesis and found none.

5.3. Future research

This research assumed that the cost that firms must incur to produce a new product was sym-

44 MA. Wailer, D.P. Christy / Competitive incentives for manufacturing flexibility

metric. That is, it was assumed that firms ini- tially are equivalent in terms of product flexibility. While this is a reasonable assumption, it would be interesting to investigate the situation where firms could invest in FMT to increase their product flexibility before they compete. That research would help to analyze ways in which FMT could be used offensively or as an order-winning criterion.

The model in this paper could also be extended to analyze welfare implications such as changes in producer’s and consumer’s surplus.

Appendix A

The section of Yoon’s ( 1988) survey employed to measure the dependent variable.

Computerization Below is a list of tasks typically performed in manufacturing firms. Please indicate by circling the appropriate number the extent to which com- puters, computerized machines, or computer-aided techniques are currently used in your plant for performing each of these tasks. 1 Not computerized at all 2 Slightly computerized 3 Moderately computerized 4 Mostly computerized 5 Completely computerized

N/A Does not apply to our plant

Manufacturing (COMCOR) (a) Product development

(b) Design and drafting (e.g., CAD)

(c) Production planning/engineering (e.g., specification of the production sequence or selection of tools by using computer aided process planning)

(d) Component manufactu~ng (e.g., molding, casting, forming, or heat treatment by using robots, computer-numerically controlled machines)

12345

N/A 12345

N/A 12345

N/A

12345 N/A

(e ) Assembly (e.g., welding, mechani- 12 3 4 5 cal pinning, adhesive bonding, or N/A wiring by using computerized equipment such as robots)

(f ) Scheduling (e.g., MRP II) 12345

N/A (g) Maintenance 12345

N/A (h) Materials handling (e.g., auto- 12345

0)

tj)

tk)

matic guided vehicles, automatic N/A storage and retrieval systems) Testing and inspection 12345

N/A Inventory controt 12345

N/A Quality assurance 12345

N/A

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ill

[21

[31

141

ISI

t61

171

[8l

i.91

[lOI

1111

[I41

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Competitive incentives for manufacturing flexibility