Efficiency, Flexibility, Or Both

Strategic Management Journal Strat. Mgmt. J., 26: 1249–1259 (2005) Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/smj.503

EFFICIENCY, FLEXIBILITY, OR BOTH? EVIDENCE LINKING STRATEGY TO PERFORMANCE IN SMALL FIRMS JAY J. EBBEN* and ALEC C. JOHNSON Department of Entrepreneurship, University of St. Thomas, St. Paul, Minnesota, U.S.A.

This paper analyzes small firm performance in relation to efficiency and flexibility strategies. Using configuration theory, the authors propose that small firms that pursue efficiency strategies or flexibility strategies outperform those that attempt to pursue both. Additionally, size is used as a configurational attribute to develop competing hypotheses on whether efficiency strategies or flexibility strategies are better suited for small firm performance. In two samples of 200 and 144 privately-held small firms, firms that mixed efficiency and flexibility strategies significantly underperformed. No significant performance differences were found between firms utilizing only efficiency strategies and those utilizing only flexibility strategies. Copyright  2005 John Wiley & Sons, Ltd.

Advancing knowledge on strategy in small firms is an essential task because these firms play a vital role in world economies (e.g., Sherman, 1999), yet face significant disadvantages in the marketplace in terms of managerial expertise, access to capital, bargaining power with suppliers and buyers, and experience curve effects (e.g., Forbes and Milliken, 1999; Pissarides, 1999; Dean, Brown, and Bamford, 1998; Rajan and Zingales, 1995; Holmes and Dunstan, 1994). Progress in this area of the entrepreneurship literature has been made in recent years with studies on topics such as product-market strategies, outsourcing strategies, and market entry strategies to name a few (e.g., Carter et al., 1994; Tsai, MacMillan, and Low, 1991; Jarillo, 1989; Sandberg and Hofer, 1987). Conclusions have generally been made that strategy does indeed impact firm performance and that Keywords: entrepreneurship; small business; strategy; performance; efficiency; flexibility *Correspondence to: Jay J. Ebben, Department of Entrepreneurship, University of St. Thomas, St. Paul, MN 55105, U.S.A. E-mail: [email protected]

Copyright  2005 John Wiley & Sons, Ltd.

strategy functions differently in small firms than in large ones (e.g., Fiegenbaum and Karnani, 1991; Jarillo, 1989). One aspect of small firm strategy that has not received much attention is how product offering relates to operational strategy and firm performance. This paper examines this concept with regard to three choices firms can make: to offer only standard products, to offer only made-to-order products, or to offer both standard and madeto-order products. Previous literature has proposed that these choices dictate operational strategy (Chrisman, Bauerschmidt, and Hofer, 1998; Randolph and Dess, 1984), as firms that offer only standard products must compete on organizational efficiency, firms that offer only made-toorder products must compete on their flexibility to meet individual customer needs, and firms that offer both must attempt to be both efficient and flexible (e.g., Filley and Aldag, 1980). It has also been proposed that the technology, labor, control system, and organizational structure requirements to achieve efficiency conflict with those required

Received 8 October 2003 Final revision received 6 June 2005

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to achieve flexibility, and it is therefore difficult for firms to achieve both efficiency and flexibility (e.g., Fiegenbaum and Karnani, 1991; Filley and Aldag, 1980). While these strategies and their implications have been discussed in the organizational theory and operations management literature, little has been done empirically to investigate how these concepts apply to the management of small firms. This study advances the literature by developing these concepts using organization theory and by testing hypotheses regarding the relationship between these strategies and firm performance in a large sample of small, privately-held manufacturing firms. The results suggest that small firms that pursue either efficiency or flexibility strategies are able to achieve optimal performance, while firms that attempt to mix efficiency and flexibility strategies significantly underperform. The implications for small firm management and future research are discussed.

LITERATURE REVIEW Early literature on organizations proposed that there is a trade-off firms can make between efficiency and flexibility due to competing organizational and operational requirements in terms of technology, organizational structure, operating processes, and labor. Stigler (1939) introduced this trade-off, arguing that the technology needed to operate with low costs is entirely different from that required to meet changing demand. Thompson and Bates (1957) followed this, proposing that firms with flexibility goals do not invest in heavy, specialized capital equipment because it inhibits the ability to shift from one goal to the next. These authors also noted that flexibility goals require skilled direct labor, stating that ‘front-line flexibility requires the exercise of judgment, and hence experience is a major basis for functional and hierarchical differentiation’ (Thompson and Bates, 1957: 331). Woodward (1965) classified manufacturing production technologies as unit/small batch and large batch/mass production, finding that large batch/mass production firms focused on efficiencies, while unit/small batch firms were flexible in meeting customer needs. Filley and Aldag built on this previous work along with their own observations to assert that a clear distinction exists, in that ‘the survival of Copyright  2005 John Wiley & Sons, Ltd.

organizations seems to depend, on the one hand, upon creating efficiency of operations, or on the other hand, producing an outcome which is relatively made-to-order’ (Filley and Aldag, 1980: 305). These researchers concluded that firms operating with an efficiency strategy produce different types of products and utilize different technologies, organizational structures, control systems, and employees than those that operate with a ‘made-to-order’ strategy. More recently, Fiegenbaum and Karnani (1991) examined these concepts in terms of flexibility in output volume, finding an interaction effect between variation in output volume and firm size on performance. This paper integrates Filley and Aldag’s (1980) and Fiegenbaum and Karnani’s (1991) work to propose that the key to efficiency and flexibility strategies does not only come from the ability to meet variation in quantity of product provided, but also from the variation in types of products that are offered. In this regard, flexibility refers to a firm’s ability to provide made-to-order products that are unique to individual customers or groups of customers. These efficiency and flexibility classifications of small firms are different from some of the more popular typologies that have been established in the literature. For instance, it is different from Porter’s (1980) low cost and differentiation, in which firms execute a differentiation strategy via marketing or innovation rather than customization. Products that are differentiated still may be standardized and conducive to mass production and distribution (White, 1986), which are in essence efficiency strategies. Differentiation via marketing might also be less relevant to small firms, as they may not have the marketing dollars necessary to pursue this strategy. This is not meant to imply that other typologies are not useful in small-firm strategy research, but the efficiency and flexibility classifications may provide an alternative perspective that reveals new insights into small firm behavior and performance.

THEORY DEVELOPMENT Configuration theory and small-firm performance In small firms, where selection of strategy is critical for survival given the disadvantages they face, an investigation of these operational strategies Strat. Mgmt. J., 26: 1249–1259 (2005)

Efficiency and Flexibility Strategies of Small Firms seems especially relevant. Configuration theorists have long held that operational strategy is central to organizational outcomes (Chandler, 1962) and that congruence among strategy, technology, organizational structure, and operating processes are key in the overall effectiveness of a firm (Fry and Smith, 1987; White 1986). Different strategies are expected to require different structures (Miller, Droge, and Toulouse, 1988; Filley and Aldag, 1980), which must ‘respond to the particular control and coordinative problems created by the strategies that are ultimately selected’ (Miller et al., 1988: 545). Empirical studies regarding configuration have consistently found evidence that fit among organizational characteristics is an important predictor of firm performance (e.g., Slater and Olson, 2000; Ketchen et al., 1997; Priem, 1994; White, 1986). Because each operational strategy calls for a particular configuration of organizational aspects (see Table 1), efficiency and flexibility can be viewed as pure or ideal configurations, while a combination of efficiency and flexibility would require a hybrid configuration (Doty, Glick, and Huber, 1993). Since the configurational dimensions for efficiency and flexibility conflict, firms that operate with this hybrid configuration will not have consistent organizational attributes and will experience difficulty achieving either efficiency or flexibility in their operations. This will likely result in an inability to effectively maintain low costs or effectively meet end-customer needs, and Table 1.

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therefore an inability to establish a competitive advantage. Following this logic, Tushman and O’Reilly (1999) suggested that a firm can only provide both standard and made-to-order outputs effectively if they are pursued in physically separate entities, with different organization structures, systems, rewards, and competencies; in other words, two divisions with ‘pure’ configurations. While this may be feasible for large firms, small firms generally have more limited resources (Cooper, Gimeno-Gascon, and Woo, 1994) and expertise (Forbes and Milliken, 1999). Because of this, the task of separating the organization into divisions that effectively follow different strategies may be more demanding and complex than most small firms can handle. Therefore, small firms that attempt to mix efficiency and flexibility strategies will likely be at a disadvantage to other firms, which should result in lower performance. Hypothesis 1: Small firms that follow an efficiency strategy and small firms that follow a flexibility strategy will outperform small firms that mix these strategies. Performance of flexibility vs. efficiency strategies in small firms Firm size is an important contextual variable in configuration, so congruence between strategy, configuration, and size may influence firm performance. It is therefore important to ask whether an

Characteristics of efficiency and flexibility firms

Operational aspect

Efficiency firms

Flexibility firms

Technology

Specialized equipment, heavy fixed assets

General-purpose equipment

Production processes

Long product runs

Unit or small batch production

Organization design

Mechanistic

Organic

Direct labor

Unskilled

Skilled decision-makers

Control systems

Feedforward

Feedback

Copyright  2005 John Wiley & Sons, Ltd.

Cite Lowson (2001), Thompson (1967), Thompson and Bates (1957) Zipkin (2001), Filley and Aldag (1980), Woodward (1965) Filley and Aldag (1980), Thompson and Bates (1957) Lowson (2001), Filley and Aldag (1980), Thompson and Bates (1957) Morgan (1992), Filley and Aldag (1980), Thompson (1967) Strat. Mgmt. J., 26: 1249–1259 (2005)

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efficiency strategy is more appropriate for small firms than a flexibility strategy, or vice versa. Given the differences between large and small firms, conventional wisdom might predict that flexibility strategies are more appropriate for small firms, but arguments can be made on both sides.

in efficiency firms for optimal performance. This leads to the first of two competing hypotheses:

A flexibility perspective

An efficiency perspective

Much of the early entrepreneurship literature prescribed that small firms should pursue niche strategies. This conventional view contended that small firms cannot compete directly with larger firms on economies of scale, so they are better off serving narrow market segments not reached by larger competitors (Broom and Longenecker, 1979; Katz, 1970), and targeting market segments that demand customized products and high levels of customer service that might be difficult for larger firms to provide (Cohn and Lindberg, 1972). The population ecology literature also points to smaller-scale niche strategies with the concept of resource partitioning (Carroll, 1985), which suggests that opportunities exist for small firms to serve smaller, specialized niches that are not fulfilled by large generalist firms (Wholey and Brittain, 1986). Based on certain characteristics of small firms, flexibility strategies do seem to fit. First, small firms do not have access to the same financial resources as larger firms and are many times undercapitalized (Cooper et al., 1994; Rajan and Zingales, 1995). This results in a lack of financial resources that hinders large fixed-asset investment (Jarillo, 1989), which is important for optimal performance in efficiency firms. Past research has also shown that this lack of financing is a key barrier to growth (Binks and Ennew, 1996; Stancill, 1986), so small firms may have difficulty achieving the economies of scale required to be successful with efficiency strategies. Second, small firms are generally less bureaucratic, structured, and diversified than larger firms (Forbes and Milliken, 1999), so they can be more responsive to individual customer needs in providing made-to-order products and services, which can be a significant competitive advantage (Cohn and Lindberg, 1972). Finally, small firms generally have fewer formal systems and procedures in place and perform fewer planning activities (Busenitz and Barney, 1997), so they are ill equipped to plan for and implement feedforward control systems, which are necessary

Contrary to the more conventional perspective, there is reason to believe that small firms may be better off with efficiency strategies. The most compelling reason to believe this is that organizing to meet individual customer needs and fluctuating demand is very complex (Swaminathan, 2001; Filley and Aldag, 1980). Because of the uncertainty of demand and costs for individual projects, production scheduling and pricing are difficult but necessary to keep costs from getting out of control and to maintain adequate margins. Additionally, with the uncertainty involved in product attributes and volume demand, flexibility firms operate in a much more turbulent environment by nature (Vickery, Droge, and Germain, 1999). Since small firms are generally assumed to have less sophisticated management expertise (Pissarides, 1999; Forbes and Milliken, 1999), they may not be able to effectively manage these difficult internal and external environments. Efficiency strategies, on the other hand, may be less complicated to manage. Efficiency firms provide products of a prescribed quality at predictable levels of demand (Vickery, Droge, and Markland, 1997). These firms generally provide only a few products that are the core offerings of the firm, which combined with predictable demand allows for simpler production scheduling, inventory levels, and delivery. This results in more accurate cost estimates, so pricing to maintain profitable margins is less complicated than in flexibility firms. This leads to the second competing hypothesis:

Copyright  2005 John Wiley & Sons, Ltd.

Hypothesis 2a: Small firms that utilize a flexibility strategy will outperform small firms that utilize an efficiency strategy.

Hypothesis 2b: Small firms that utilize an efficiency strategy will outperform small firms that utilize a flexibility strategy.

METHODS Sample The sample of firms was selected from a database owned by Fintel, LLC, that contains financial data Strat. Mgmt. J., 26: 1249–1259 (2005)

Efficiency and Flexibility Strategies of Small Firms Table 2.

Descriptive statistics and correlations

Sample Survey (144 firms)

Variable

1. 2. 3. 4. 5. 6. 7. Website (200 firms) 1. 2. 3. 4. ∗∗

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Mean

S.D.

1

ROIC 0.133 0.167 ROE 0.172 0.224 0.935∗∗ ROA 0.086 0.106 0.924∗∗ Size 5,312,243 4,872,835 −0.029 Age 41.93 29.29 −0.133 Family 0.434 0.497 0.102 CEO 17.75 11.40 0.000 ROIC 0.141 0.162 ROE 0.179 0.208 0.957∗∗ ROA 0.087 0.101 0.947∗∗ Size 5,268,259 4,245,381 −0.018

2

0.844∗∗ −0.009 −0.110 0.097 0.002 0.899∗∗ 0.014

3

4

−0.056 −0.122 0.230∗∗ 0.076 −0.079 −0.048 −0.045

5

−0.219∗∗ 0.008

6

0.033

−0.047

p < 0.01

on privately held firms from over 900 SIC codes. A random sample of 600 manufacturing firms with SIC codes between 20 and 39 was selected. All of these firms had less than $20 million in sales, which is consistent with other researchers’ definition of small firms (e.g., Daily and Dalton, 1993; d’Ambroise and Muldowney, 1988). These 600 firms were contacted by phone and 319 indicated interest in participating in the study. Of these 319 firms, 200 firms had website information available on firm products and services and 144 firms responded to a survey of top managers regarding firm operations and strategy (see Table 2 for descriptives). Ninety-one firms had website information available and responded to the survey. Measures The independent construct, firm strategy, was measured via survey response and website analysis. The survey was designed to examine expected product and operational aspects of firms that utilize efficiency and flexibility strategies. Eight questions were developed regarding these aspects and answered on a six-point semantic-differential format. Since the Fintel database included financial data from year-end 1997, the survey questions asked about firm operations during that year. For each question, firms scored on a continuum from flexibility to efficiency (1 to 6), with questions one, three, four, and six reverse-scored. The response rate for the survey was 45.1 percent. Internal consistency of the eight questions was examined using a principal components analysis with Varimax rotation. Seven of the eight questions Copyright  2005 John Wiley & Sons, Ltd.

loaded on a single factor, and the question that did not load was discarded from subsequent analysis. Coefficient alpha was 0.86 on the remaining seven questions, indicating that they were indeed measuring the same construct. Response scores for the seven questions were added together to represent strategy for each firm and adjusted to a range of 0 to 35, with lower scores representing flexibility and higher scores representing efficiency. Only two firms left one of the eight questions blank; rather than deleting these firms, the missing data were replaced with the mean response by the firm to the other items in the survey. For the website measure of strategy, a search was made for websites of the 319 firms and 200 were found that had enough information available to evaluate the strategy of the firm. Three raters examined these websites and provided their opinions on whether each firm was using an efficiency strategy, using a flexibility strategy, or mixing strategies. One of the three raters was deemed the ‘blind’ rater and was not familiar with the hypotheses of the paper. The criteria for strategy classification were specified in advance, based on the principle that efficiency firms only provide standard products, flexibility firms only provide made-to-order products, and mix firms provide both standard and made-to-order products. Every available page on each firm’s website (Company History, Products and Services, etc.) had to be examined. Coefficient alpha between the three raters’ strategy classifications was 0.85, signaling high interrater reliability, and there did not appear to be systematic differences between the ‘blind’ rater’s and ‘non-blind’ raters’ responses. Based on rater classifications, the 200 firms were coded as Strat. Mgmt. J., 26: 1249–1259 (2005)

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1 = flexibility, 2 = mix, or 3 = efficiency, resulting in 66 flexibility, 50 mix, and 84 efficiency firms. Convergent validity was demonstrated between the survey responses and website classifications using several methods. Correlation between the measures was 0.612 and significant at a 0.01 level, and the two measures loaded on a single factor that explained 81 percent of the variance in cases using a rotated principal components analysis. Also, when cut-off points were established so that firms scoring below 11 on the survey were classified as flexibility, firms scoring between 11 and 16 on the survey were classified as mix, and firms scoring above 16 were classified as efficiency, coefficient alpha between survey and website classifications was 0.80. As additional evidence of convergence, the groups of firms as classified by website responded to the survey significantly differently. For the 91 firms with both website and survey data, Table 3.

31 were classified as flexibility by website, 25 were classified as mix, and 35 were classified as efficiency. The mean overall survey score for the 31 firms classified as flexibility was 7.58, for the 25 mix firms was 12.36, and for the 35 efficiency firms was 20.89 (all three mean differences were significant at a 0.01 level). On individual survey questions, firms classified as flexibility scored significantly lower than those classified as efficiency on all seven questions used in the analysis, while mix firms scored in between on six of them (see Table 3). Mix firms scored significantly lower than efficiency firms at a 0.05 or 0.01 level on all seven questions and significantly higher than flexibility firms at a 0.05 or 0.01 level on four of the seven questions. The dependent construct, firm performance, was captured using three measures: return on invested capital (ROIC), return on equity (ROE), and return on assets (ROA). These measures were taken from year-end 1997 data in the Fintel database and

Survey responses by website classification of strategy Mean Response

t-valuea,b

Eff.

Mix

Flex.

(E vs. F)

4.11

2.28

1.61

6.100∗∗

4.77

3.20

1.90

7.335∗∗

3.03

2.00

2.39

1.623+

3.98

2.92

2.65

2.977∗∗

4.54

3.44

2.97

3.994∗∗

4.06

2.56

1.65

6.453∗∗

3.49

2.68

1.42

5.580∗∗

Question (scores range from 1 to 6)

1 = Our company provided only made-to-order products and services to customer groups or individual customers. 6 = Our company provided standard products to all of our customers. 1 = Our products were priced based on the modifications that were required by customers. 6 = We invoiced our customers using a set price list. 1 = We utilized short products runs in manufacturing or produced in single unit batches. 6 = We utilized long product runs in manufacturing. 1 = Our manufacturing line employees were frequently required to perform unique tasks or alter products. 6 = Our manufacturing line employees performed standard tasks in completing the production/assembly of products. 1 = Our manufacturing materials inputs varied greatly with production runs or were specially ordered for particular production runs. 6 = Our manufacturing materials inputs did not vary greatly with production runs. 1 = Customers often asked for modification in products when ordering or they ordered products specifically modified for their market segment. 6 = Customers ordered our products from established descriptions or catalogs without product modification. 1 = We manufactured products after they were ordered. 6 = We manufactured products and placed them in inventory for later sale. d.f. = 6 3 One-tail tests + p < 0.10; ∗∗ p < 0.01 a

b

Copyright  2005 John Wiley & Sons, Ltd.

Strat. Mgmt. J., 26: 1249–1259 (2005)

Efficiency and Flexibility Strategies of Small Firms

Fiegenbaum and Karnani, 1991), and size has been argued to be an important control variable in entrepreneurship research regarding firm performance (e.g., Murphy, Trailer, and Hill, 1996). Firm size was defined as the log of 1997 sales revenues, which was obtained from the Fintel database. Log values were used to obtain normal distributions for this measure, consistent with other empirical studies (e.g., Garg, Walters, and Priem, 2003). For the survey sample, firm age, family ownership, and the tenure of the current CEO were obtained in the survey and included in regression as control variables. All three of these constructs have been linked to various firm outcomes, including performance (e.g., Randøy and Goel, 2003; Hambrick, 1991; Randolph and Sapienza, 1991). Firm age was taken as the log of the number of years since inception, family ownership was coded as 0 = No and 1 = Yes, and tenure of the current CEO was measured as the number of years the current CEO had been in his or her position.

are common measures utilized in the strategy and entrepreneurship literature (e.g., Robinson, 1999). Adjustments were made to these data to reduce the influence of outliers using the Winsor technique at the 5th and 95th percentiles. This technique has been recommended for accurate regression model estimates (Kennedy, Lakonishok, and Shaw, 1992) and used in empirical analyses in the management literature (e.g., Miller and Parkhe, 2002; Berger, 1993). In an additional data adjustment, calculations for ROIC and ROE were eliminated when invested capital and/or equity for a firm was negative, as these negative denominators would result in a misleading measure of performance. While there are bias concerns with this method, it resulted in minimal loss of data. For the 200 firms with website data, this left 199 firms with an ROIC measure, 194 firms with an ROE measure, and all 200 firms with an ROA measure. For the 144 firms with survey data, this left 144 firms with an ROIC measure, 142 firms with an ROE measure, and all 144 firms with an ROA measure. Industry was used as a control variable for three reasons. First, size, growth, and concentration of a particular industry are likely to affect individual firm performance within that industry (e.g., Schmalensee, 1985). Second, controlling for industry helps to control for environmental effects, such as hostility, complexity, and dynamism (Naman and Slevin, 1993). Third, controlling for industry helps to control for firm goals (Bromiley, 1991; Fiegenbaum and Thomas, 1988). Industry was controlled using a dummy variable for each 2-digit SIC code. Firm size was also used as a control, as several studies have linked size to performance (e.g., Table 4.

ANALYSIS AND RESULTS Two sets of analyses provide evidence of support for Hypothesis 1 but no evidence of support for Hypothesis 2a or 2b. The first set of analyses compared firm strategy as measured by survey to firm performance on the sample of 144 (see Tables 4 and 5 for results). ANOVA and t-tests showed significant differences in performance between firms classified as non-mix and those classified as mix at a 0.10 level. Regression analyses revealed stronger relationships when controlling for firm size, age, industry, family ownership, and CEO tenure, with

Mean performance comparisons

Measure

ROICb ROEb ROAb ROICc ROEc ROAc

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t-testsa

Mean

t-testsa

Mean

Mix

Non-mix

d.f.

t

Eff.

Flex.

d.f.

t

0.093 0.116 0.060 0.091 0.120 0.056

0.143 0.186 0.092 0.158 0.203 0.098

142 140 142 197 192 198

1.467+ 1.510+ 1.483+ 2.579∗∗ 2.799∗∗ 2.556∗∗

0.153 0.201 0.100 0.152 0.194 0.092

0.133 0.172 0.085 0.166 0.215 0.104

112 111 112 147 143 148

0.653 0.699 0.780 0.617 0.583 0.492

a

One-tail tests 144 surveyed firms c 200 website firms + p < 0.10; ∗∗ p < 0.01 b

Copyright  2005 John Wiley & Sons, Ltd.

Strat. Mgmt. J., 26: 1249–1259 (2005)

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J. J. Ebben and A. C. Johnson Results of regression analysesa

Ind. variables

Intercept Log sales SICb Firm age Family-ownedc CEO tenure Strategyd F R2 Adj. R 2

144 surveyed firms

200 website firms

Model 1: ROIC

Model 2: ROE

Model 3: ROA

Model 1: ROIC

Model 2: ROE

Model 3: ROA

0.013 (0.304) 0.051 (0.047) — −0.151∗ (0.064) −0.003 (0.032) 0.001 (0.001) 0.078∗ (0.038) 1.192 0.188 0.030

−0.066 (0.413) 0.079 (0.063) — −0.207∗ (0.087) −0.011 (0.043) 0.001 (0.002) 0.114∗ (0.052) 1.056 0.173 0.009

0.140 (0.195) 0.010 (0.030) — −0.086∗ (0.041) −0.010 (0.020) −0.001 (0.001) 0.047∗ (0.024) 1.058 0.171 0.009

0.021 (0.241) 0.012 (0.037) — n/a

−0.084 (0.313) 0.031 (0.048) — n/a

0.104 (0.150) −0.007 (0.023) — n/a

n/a

n/a

n/a

n/a

n/a

n/a

0.067∗∗ (0.027) 1.879∗ 0.166 0.078

0.088∗∗ (0.035) 1.968∗∗ 0.177 0.087

0.042∗∗ (0.017) 1.494∗ 0.136 0.045

a

Standard errors are in parentheses SIC 31 significant at 0.05 for surveyed firms, SIC 30 and 31 sig. at 0.05 for website firms c 0 = no; 1 = yes d 0 = mix; 1 = non-mix ∗ p < 0.05; ∗∗ p < 0.10 b

non-mix strategy having a positive and significant impact on performance at a 0.05 level. No significant differences in the performance of firms classified as efficiency and those classified as flexibility were found in this sample. The second set of analyses using the website measures of strategy on the sample of 200 provided even stronger support for Hypothesis 1. ANOVA and t-tests showed that firms classified as non-mix as well as those classified as efficiency and flexibility separately performed significantly greater than firms classified as mix at a 0.01 level. Regression analyses supported these results when controlling for size and industry, with non-mix strategy having a positive and significant impact on all three measures of performance at a 0.01 level. No significant differences were found between the performance of efficiency and flexibility firms.

DISCUSSION The findings in this study are significant for the small-firm strategy literature, as they indicate that efficiency and flexibility may be appropriate classifications of small-firm strategy and provide a Copyright  2005 John Wiley & Sons, Ltd.

new area of focus for entrepreneurship strategy research. The results seem significantly strong considering the use of two separate measures of strategy on two overlapping samples. Although the findings using the website measure of strategy may be questioned, as this measure was taken in 2002 (5 years after the measure of performance), it is contended that the 2002 website measure is representative of 1997 strategy for three reasons. First, the convergence with the survey measure of strategy, which asked about firm operations in 1997, provides validation. Second, based on the minimum age of firms in the sample, 6 years, as well as the median age, 33 years, it appears that the majority of these firms are well established and therefore subject to inertial constraints that would prevent them from changing strategy significantly (Hannan and Freeman, 1984). Third, follow-up phone interviews with a random sample of 10 firms indicated that these firms were operating in 2002 with the same strategy as in 1997. In fact, all 10 interviewees responded enthusiastically that their firm had not changed its strategy at all since well before 1997, with some stating that their firm was operating today exactly the way it has been for the past 40 or 50 years. Strat. Mgmt. J., 26: 1249–1259 (2005)

Efficiency and Flexibility Strategies of Small Firms This validation is important because it provides evidence that meaningful differences exist between small firms in terms of standard and made-to-order product offerings. Most importantly, the strong support for Hypothesis 1 along with the lack of support for Hypotheses 2a and 2b suggests that what matters most in regard to efficiency and flexibility strategies is not which one a small firm pursues, but that a small firm does not attempt to pursue both. This does not coincide with the conventional wisdom that small firms can better compete by providing unique or made-to-order products; instead, it supports configuration theory in that the strategy chosen is not as important as whether it allows for consistency in operations (e.g., Doty et al., 1993). The surveys provide some evidence of this, as it appears that firms offering only standard products configure in a manner related to efficiency, firms offering only made-toorder products configure in a manner related to flexibility, and firms offering standard and madeto-order products are somewhere in between. In addition to theoretical advancements, there is also merit to the methods utilized. The authors are unaware of other studies that have used website analysis to classify firm strategy, and while this may seem unorthodox to some researchers, its convergence with a second measure and the high interrater reliability indicate that this method is indeed valid. This is a method that could potentially be used to classify firm strategy for a large sample of firms. This study is also unique in utilizing a database containing financial data for privately held firms, which may make the results of this study more generalizable to the population of small firms than studies that have used secondary data on public small firms or business units of large corporations. In terms of practical application, the findings of this study have the potential to be significant for entrepreneurship education. Anecdotal evidence suggests that small firms mix strategies as a response to customer demand or in an attempt to increase sales volume by offering greater variety. For example, efficiency firms may begin mixing strategies if sales reps are repeatedly asked whether ‘special’ sizes or versions of products are possible. While this may seem like a good way to expand sales and grow, or as a strategic response to faltering sales, the evidence from this study suggests that this may actually be counterproductive in terms of the long-term health of the organization. If Copyright  2005 John Wiley & Sons, Ltd.

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entrepreneurs are taught to determine what operational strategy their firm should rely on (efficiency or flexibility), they can then organize accordingly and avoid mixing strategies. Limitations and future research The sample used for this study only included manufacturing firms for comparability within this study, and generalizability to the entire population of small firms should therefore be done with caution. Efficiency and flexibility strategies are fairly simple to identify in firms that manufacture products (standard vs. made-to-order), but may not be so simple to identify in retail or other types of firms. It is also possible that these strategy classifications are not appropriate for small firms outside of manufacturing, or that other results would be obtained for non-manufacturing sectors. However, there is no immediate reason to assume that either of these is the case and this should be addressed in subsequent research. A second limitation is the model used for this study. All efficiency and flexibility firms were lumped together and treated as adopting pure strategies, while mix firms were coded zero and treated as directly in between efficiency and flexibility firms. This ignores the true variance in strategy implementation, reducing the model’s predictive power. Future research should specify a more accurate model that addresses the degree to which a firm mixes strategies and at what point it begins to impact performance. Another topic that should be addressed in future research is how these strategies develop and change in small firms. It is likely that product and organization are intertwined, which conflicts with some of the traditional thinking that organization follows product (Randolph and Dess, 1984). What an entrepreneur sees as a need in the market may lead him or her toward a standard or madeto-order product, but the entrepreneur will also need to consider the organizational requirements involved when evaluating the overall opportunity. For instance, an entrepreneur may recognize an opportunity within an industry to provide either standard or made-to-order outputs, but that entrepreneur may view the capital requirements of an efficiency strategy as prohibitive and therefore opt to pursue a flexibility strategy. Likewise, there may be identifiable factors that influence strategic change as a firm develops. Strat. Mgmt. J., 26: 1249–1259 (2005)

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All in all, the authors believe that this study provides a significant step forward in entrepreneurial strategy research. Although classifying firms as efficiency, flexibility, and mix is relatively simple, it appears promising given the performance and organizational differences found in this study. If future research confirms and builds on the concepts and findings of this study, considerable advancements may be made in the field of entrepreneurship regarding organizational development.

ACKNOWLEDGEMENTS We would like to give special notice to Gerry George, Robert Pricer, Nancy Carter, Kenneth Wathne, Jan Heide, and Boris Neide for their integral support and insight, and thank the University of Wisconsin—Madison and the University of St. Thomas for providing us with exceptional resources for pursuing this study.

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