http://www.smallbusinessinstitute.biz A B S T R A C T Keywords: Journal of Small Business Strategy 2021, Vol. 31, No. 03, 33-46 ISSN: 1081-8510 (Print) 2380-1751 (Online) ©Copyright 2021 Small Business Institute® w w w. j s b s . o rg Introduction Florida Institute of Technology, College of Business, 150 W University Blvd, Melbourne, FL 32901, USA, jreed2017@fit.edu Strategic agility in the SME: Use it before you lose it Strategic agility, SME, Firm age, Firm size, Environmental turbulence APA Citation Information: Reed, J. (2021). Strategic agility in the SME: Use it before you lose it. Journal of Small Business Strategy, 31(3), 33-46. Strategic agility is a relatively new construct in the field of strategic management which applies the notion of agility (flexibility and speed) to business strategy (Doz & Kosonen, 2008a; Long, 2000). According to Doz and Kosonen (2008a; 2008b; 2010), strategically agile firms are able to change direction quickly through their heightened sensitivity to strategic developments (strategic sensitivity), making bold and fast decisions (leadership unity), and re- deploying resources rapidly (resource fluidity). Strategic agility is therefore a type of dynamic capability, enabling firms to reconfigure their resources and capabilities to ad- dress rapidly changing environments (Teece et al., 2016; Teece et al., 1997). Over the past decade, more than two dozen journal articles have been published on strategic agility, creating a vibrant research stream in strategic management. Much of the conceptual work builds upon Doz and Kosonen (2008a; 2008b). Weber and Tarba (2014), in their introduc- tion to a special section of California Management Review on strategic agility, define it as “the ability of management to constantly and rapidly sense and respond to a changing environment by intentionally making strategic moves and consequently adapting the necessary organizational config- uration for successful implementation” (p. 7). Other articles in the same publication discuss how strategic agility enables multinational enterprises to operate across emerging and es- tablished markets (Fourne et al., 2014), how different types of mergers and acquisitions enhance strategic agility (Bru- eller et al., 2014), and how leadership is central to managing the paradox between the long-term view of strategy and the short-term view of agility (Lewis et al., 2014). Vecchiato (2015) explores linkages between strategic foresight, first mover advantages, and strategic agility. Jacoby and Shaw (2016) use an athletics analogy to describe strategic agility in the U.S. military. They define strategic agility as the “ca- pacity at the global or theater level to rapidly assess complex and unpredictable security challenges and opportunities and to decide and respond quickly, effectively, and efficiently” (p. 36). Kumkale (2016) argues that strategic agility is a tool for creating competitive advantage. Kwon et al. (2018) find strategic agility to be characteristic of successful Ko- This empirical study investigates strategic agility and its relationships with firm age, firm size, and firm performance in SMEs. The Doz and Kosonen three-factor model of strategic agility is operationalized and tested in 30 firms from multiple industries located in the Space Coast region of Florida. It is found that strategic agility decreases as firms grow older but not as firms grow larger. Strategic agil- ity and firm performance are also found to be related as moderated by environmental turbulence. Specifically, performance increases with strategic agility in high turbulence but decreases with strategic agility in low turbulence. This finding is consistent with the view that dynamic capabilities like strategic agility bear a cost which may be unnecessary in stable environments. Overall, the study suggests that SMEs may benefit from strategic agility if it used while they still have it, that is, when they are young. Jonathan Reed http://www.smallbusinessinstitute.biz http://www.jsbs.org 34 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 rean founders, and Ivory and Brooks (2018) find strategic agility to be involved in managing the paradox of corporate sustainability. Relevant to the present study, Arbussa et al. (2017) are interested in strategic agility in small firms. They conduct a longitudinal case study of a temporary work- force services company in Spain and find two of Doz and Kosonen’s (2008a; 2008b) three dimensions present. But is changing strategy good for the bottom line? On one hand, firms which are strategically agile may be able to outmaneuver their rivals in competitive environments, earn- ing economic rents. On the other hand, changing strategy too often may lead to little market traction and unnecessary cost. Researchers have begun to empirically investigate the effect of strategic agility on firm performance, and the re- sults so far appear mixed. Ojha (2008) finds a negative rela- tionship between strategic agility and financial performance in medium-to-large sized U.S. manufacturing firms. Shin et al. (2015) find no relationship between strategic agility and financial performance in Korean manufacturers. Two very recent studies find positive relationships between strategic agility and firm performance in the Turkish accommodation industry (Kale et al., 2019) and German electronics firms (Clauss et al., 2019). Other researchers find interesting re- lationships between strategic agility and intellectual capital, competitive capabilities, and other constructs but not direct- ly with firm performance (Al-Azzam et al., 2017; Junni et al., 2015; Khoshnood & Nematizadeh, 2017; Ofoegbu & Akanbi, 2012). Assuming the different empirical findings are not ex- plained methodologically, one might ask what contingency factors are involved in strategic agility. Unfortunately, little research has been conducted on the antecedents and mod- erators of strategic agility. This study addresses this gap by investigating the effects of firm age, firm size, and environ- mental turbulence on strategic agility and its relationship with firm performance. Small and medium-sized Enterpris- es (SMEs) were selected for the study as the SME and en- trepreneurship literature suggest small and young firms are agile. The Space Coast region of Florida was selected as the context for the study due to its recent environmental tur- bulence. Multiple industries in this region were examined as the previous empirical studies were all single-industry based. Literature Review and Hypotheses The concept of agility in a business context has its roots in manufacturing. Researchers at the Iacocca Institute (Nagel, 1992; Nagel, & Dove 1991) are most often cited as the first to use the term “agile manufacturing” in a study sponsored by the U.S. Office of Naval Research. They ar- gue that agility rather than mass production represented the future for 21st century manufacturing (Gunasekaran, 2001). Over time, the concept extended from manufacturing into supply chain management (Dove, 1996; Yusuf et al., 2004) and information technology (Lu & Ramamurthy, 2011; Sambamurthy et al., 2003), where the ability to reconfigure the suppliers and systems underlying manufacturing would be beneficial. Strategic Agility The first use of the term “strategic agility” is found in Roth (1996) although it was still used in a manufacturing context. Roth defines strategic agility as “the capability to create the right products at the right place at the right time at the right price” (p. 30). Long (2000) is the first to address strategic agility in the strategic management sense. He de- fines strategic agility as “not only maintaining the flexibility to respond quickly to changing circumstances and emerging opportunities but also concentrating on a clear strategic pur- pose” (p. 38). The concept of strategic agility is more thoroughly de- veloped by Doz and Kosonen (2008a, 2008b, 2010). They propose that strategic agility is comprised of three dimen- sions: strategic sensitivity, leadership unity, and resource fluidity. Strategic sensitivity represents an intense awareness of external trends combined with an internally participative strategy process. It is proactive in nature, involving an open strategy process, heightened strategic alertness, and a future orientation. Leadership unity (also called collective com- mitment) allows the top management team to make bold decisions fast once a new strategic situation is perceived. It involves mutual dependency, collaboration, and an inte- grative leadership style on the part of the CEO. Resource fluidity is the internal capability to reconfigure capabilities and redeploy resources quickly once a new strategic direc- tion is determined. It involves the alignment of strategy and structure, flexible business models, and modular systems and structures which can be reorganized quickly. According to Doz and Kosonen, all three dimensions are required for a firm to be strategically agile. “In short, the formulation is Agility = Sensitivity x Unity x Fluidity” (Doz & Kosonen, 2008b, p. 111). Doz and Kosonen (2010) provide a framework of five underlying determinants for each of the three dimensions. Each determinant is a type of leadership action that enhanc- es strategic agility. Anticipating, for example, enhances stra- tegic sensitivity by exploring concepts for how customers might use future products and services. Dialoguing enhanc- es leadership unity by sharing strategic assumptions and hy- potheses across the leadership team. Decoupling enhances 35 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 resource fluidity by allowing organizational elements to op- erate in a coordinated but autonomous fashion. Hamalainen, Kosonen, and Doz (2012) illustrate the application of the framework to the public sector. Here, three antitheses of the strategic agility dimensions are identified: strategic atrophy, diverging commitments, and resource imprisonment. Most recently, Doz (2020) examines the framework from a hu- man resources perspective. Firm age and firm size are both noted here as working against strategic agility. “Natural evolution leads to growing strategic rigidity as a company ages” and “achieving strategic sensitivity is even harder in the context of a large organization” (p. 3). This study follows Doz and Kosonen (2008a; 2008b; 2010; 2020) by defining strategic agility as the firm’s capa- bility to dynamically change its plan for achieving sustained competitive advantage through its strategic sensitivity, lead- ership unity, and resource fluidity, by operationalizing their strategic agility framework, and by examining the effects of firm age and firm size more closely. Contingency Factors Turning to the contingency factors related to strategic agility, the entrepreneurship literature supports the rele- vance of firm age. Young firms, almost by definition, are entrepreneurial. Gunter (2012) defines entrepreneurs as “in- dividuals who, in an uncertain environment, recognize op- portunities that most fail to see, and create ventures to profit by exploiting these opportunities” (p 387). Kirzner (1997) defines entrepreneurial alertness as an attitude of receptive- ness to available (but hitherto overlooked) opportunities. At the firm level, entrepreneurial orientation (autonomy, innovativeness, risk taking, proactiveness, and competitive aggressiveness) has been shown to be related to firm per- formance, particularly under conditions of environmental change (Covin & Slevin, 1989; Lumpkin & Dess, 1996). These concepts are similar to the strategic sensitivity dimen- sion of strategic agility. Young firms, led by entrepreneurs with high entrepreneurial alertness and high entrepreneurial orientation, may be quicker to recognize and exploit new opportunities than older firms. These similarities between entrepreneurship and strategic agility suggest that younger firms may be more strategically agile than older firms. This leads to the first hypothesis. Hypothesis 1. Firm age is related to strategic agility such that as SME firms become older, they become less strategi- cally agile. The SME literature suggests firm size is related to stra- tegic agility. Small firms, due to their fewer resources and investments, are almost inherently flexible. Small firms are found to be better than larger firms at adjusting their pro- duction output (Fiegenbaum & Karnani, 1991) and custom- izing their products (Ebben & Johnson, 2005) to meet fluc- tuating market demand. Forbes (2005) finds small firms to be faster at making major decisions. Small firms are found to make greater use of informal versus formal plans (Allred et al., 2007). SMEs are less bureaucratic, enabling their managers to react quickly to new situations, stay closer to their customers, and adapt more rapidly to changing tastes (Garcia-Morales et al., 2007). These concepts are similar to the leadership unity and resource fluidity dimensions of strategic agility. From a theory perspective, SMEs are less path dependent (Arthur et al., 1987) and less constrained by the smaller asset stocks they have accumulated (Dier- ickx & Cool, 1989). They may therefore be more flexible than larger firms anchored by their past decisions and capi- tal investments. Given the flexibility of small firms and the similarities between flexibility and strategic agility, smaller firms may be more strategically agile than larger firms. This leads to the next hypothesis. Hypothesis 2. Firm size is related to strategic agility such that as SME firms become larger, they become less strate- gically agile. The relationship between strategic agility and firm per- formance is supported by the literature on dynamic capabil- ities. Dynamic capabilities lead to competitive advantage through the ability to acquire or reconfigure resources and competencies quickly, especially in rapidly changing envi- ronments (Eisenhardt & Martin, 2000; Teece et al., 1997). Strategic agility is a type of dynamic capability in which the firm’s strategy is the resource or competency dynami- cally changed. Teece (2009) describes dynamic capabilities in terms of sensing, seizing, and transforming, three com- ponents similar in nature to strategic agility’s three dimen- sions. This leads to the third hypothesis. Hypothesis 3. Strategic agility is related to firm perfor- mance such that as SME firms become more strategically agile, their performance improves. However, strategic agility may not be as critical in stable environments as in conditions of environmental tur- bulence. Stable environments allow an existing strategy to be changed slowly or not at all if firm performance is deemed acceptable. Environmental turbulence challenges an existing strategy with environmental complexity, rapid change, novel challenges, and unpredictability (Ansoff et al., 1984/2019). Ansoff argues that strategic responsiveness 36 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 must be matched to the level of environmental turbulence. Similarly, in the supply chain, stable environments place pressure on operational efficiency for enhanced competi- tiveness while unstable environments reward an agile sup- ply chain (Yusuf et al., 2004). High environmental turbu- lence may therefore enhance the effect of strategic agility on firm performance. This leads to the fourth and final hy- pothesis. Hypothesis 4. Environmental turbulence moderates the re- lationship between strategic agility and firm performance in SME firms. Figure 1 summarizes the four hypotheses in the form of a conceptual model relating strategic agility, contingency factors, and firm performance. Figure 1. Hypothesized Relationships between Firm Age, Firm Size, Strategic Agility and Firm Performance Construct Validity As this is the first study to operationalize strategic agil- ity following Doz and Kosonen (2010), it is important to assess the validity of the construct. One way of doing this is to compare strategic agility to like-constructs. Convergent validity is demonstrated when a construct is shown to cor- relate with a similar, established construct (Cooper & Schin- dler, 2014). Organizational alignment was selected for this purpose. Organizational alignment is the degree to which an organization’s strategy, structure, and culture cooperate to achieve the same desired goals (Nadler & Tushman, 1989; Powell, 1992; Quiros, 2009; Semler, 1997). As this appears conceptually similar to strategic agility (the alignment of strategic sensitivity, leadership unity, and resource fluidity), a positive relationship between the two constructs would support convergent validity for strategic agility. Criterion validity is demonstrated when a construct is shown to correlate with real-world outcomes (Sullivan et al., 2009). Strategy change was selected for this purpose. An organization may be strategically agile yet choose not to change its strategy during a given period of time. However, firms that are strategically agile may be expected to actually change their strategy more frequently. Strategy change is not a latent construct but rather a real-world event that may be measured objectively. A positive relationship between strategic agility and strategy change would therefore sup- port criterion validity for strategic agility. Note that organi- zational alignment and strategy change are not positioned as hypotheses as they are used for construct validation prior to hypothesis testing. Method Context The Space Coast region of the State of Florida in the United States was selected as the context for the study. This region is on Florida’s east coast and is comprised primarily of Brevard County, including the Palm Bay–Melbourne– Titusville Metropolitan Statistical Area (MSA). One of the reasons this region was selected is its high industry diversi- ty. According to Florida Gulf Coast University (2018), the Palm Bay-Melbourne-Titusville MSA ranked second in the state at the end of 2018 as an industrially diversified econo- my. High industry diversity is desirable for a multi-industry study. Another reason was that the region suffered econom- ically from the combined effects of the national recession from 2007 to 2009 followed closely by the retirement of NASA’s space shuttle program at the Kennedy Space Cen- ter from 2010 to 2011. Unemployment in Brevard Coun- ty ran 1 - 3% higher than the national average from late 2009 to 2013, then rebounded and has been lower than the national average since early 2015 (Space Coast Economic 37 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 Development Commission, 2018; 2019). These economic conditions represent a form of environmental turbulence suitable for the study. According to the Dun & Bradstreet (D&B) Hoovers database, there are a total of 1,709 companies in six select- ed industry sectors in this region which are independent, for-profit, with 10 or more employees (D&B Hoovers, 2018). From this population, stratified random sampling was used to generate a sample frame of 249 firms. A survey questionnaire was developed for data collection purposes and pretested and refined with seven firms from four indus- tries. Questionnaires were sent by postal mail to the CEO of each firm and responses were accepted on-line or by return mail. 34 responses were received (13.7% response rate), of which 30 were usable. The low response rate was likely due to the CEO level of the survey (Bednar & Westphal, 2006) and the request for financial and other information which may be considered sensitive, especially for small firms (Dess & Robinson, 1984). Table 1 summarizes the over- all population, sample frame, and responses by firm size. While no responses were received from large firms (500 or more employees), the distribution of responses from very small to medium-sized firms was good, providing sufficient range in the sample to study the effects of firm size. Table 1 Firm size distribution of population, sample frame, and responses Firm Size Number Employees Pop. Count Pop. Percent Strat Factor Sample Frame Count Sample Frame Percent Response Count Response Percent Large 500+ 3 0.2% 100% 3 1.2% 0 0.0% Medium 100 - 499 59 3.5% 100% 59 23.7% 7 23.3% Small 2 50 - 99 143 8.4% 35% 58 23.3% 4 13.3% Small 1 20 - 49 518 30.3% 10% 67 26.9% 8 26.7% Very Small < 20 986 57.7% 5% 62 24.9% 11 36.7% Total 1709 100% 249 100% 30 100% Table 2 summarizes the population, sample frame, and responses by industry sector. The construction and profes- sional services sectors had the most responses while health/ social and accommodation/food had the fewest. Comparing the response percentages to the sample frame percentages indicates potential response bias by industry, suggesting the use of industry sector as a control variable relative to bias as well as traditional industry effects (Groves, 2006; Rumelt, 1991). Table 2 Industry sector distribution of population, sample frame, and responses Industry Sector NAICS Pop. Count Pop. Percent Sample Frame Count Sample Frame Percent Response Count* Response Percent Construction 23 314 18.4% 45 18.1% 8 26.7% Manufacturing 31, 32, 33 196 11.5% 38 15.3% 5 16.7% Retail Trade 44, 45 199 11.6% 27 10.8% 4 13.3% Professional Services 54 194 11.4% 34 13.7% 8 26.7% Health/Social 62 289 16.9% 34 13.7% 1 3.3% Accomodation/Food 72 517 30.3% 71 28.5% 2 6.7% Total 1709 100% 249 100% 28 100% *Two responses did not report their industry 38 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 The operationalization of each variable used in the study is discussed below. Firm Age The age of a firm is commonly measured as the num- ber of years since its founding (Autio et al., 2000; U.S. Small Business Administration, 2012). For independent firms, founding is defined as the year of its legal incorpo- ration. For branches or divisions of a larger firm, founding is defined as the year of the establishment of the outlet. The age of the firm was calculated as the current year minus the founding year. Firm Size Firm size may be measured in several ways including the number of employees, annual revenue, and assets. Num- ber of employees was used in this study due to less sensi- tivity to its reporting by small, private firms. No distinction was made between full-time or part-time status. Strategic Agility A 10-item scale derived from Doz and Kosonen (2010) was used to measure strategic agility, and is provided in Ap- pendix A. Each item was measured on a 7-point Likert-type scale ranging from Strongly Disagree (1) to Strongly Agree (7). The measures for each individual dimension were av- eraged to provide a composite value for the dimension. As Doz and Kosonen require all three dimensions to be pres- ent to achieve strategic agility, indicating an interaction between the dimensions, the three composite values were multiplied together to arrive at the final value for strategic agility. This value ranged from 1 to 343. Environmental Turbulence “Environmental turbulence is a combined measure of the changeability and predictability of the firm’s environ- ment” (Ansoff et al., 1984/2019, p. 80). Four items derived from Ansoff et al. were used to measure environmental tur- bulence on a 5-point Likert-type scale ranging from Very Low (1) to Very High (5). These items measured the envi- ronment’s complexity, novelty, speed of change, and fre- quency of shifts. The average of the items was calculated as the composite value for environmental turbulence. The scale is provided in Appendix A. Firm Performance Firm performance was measured as revenue growth, profitability, and subjective performance against objectives. Of these, profitability (return on sales) was found to be the most simple and reliable measure across firms of different ages, sizes, and industries, and was used as the dependent variable for the study. This is consistent with Powell’s (1992) study of the relationship between organizational alignment and firm performance. Profitability was measured in ranges (< 0%, 0 – 5%, 5 – 10%, 10 – 15%, 15 – 20%, 20 – 25%, > 25%) to reduce respondent concerns regarding the release of sensitive information. Organizational Alignment Organizational alignment was measured using four items derived from Semler (1997) to measure the pairwise consistency or fit between strategic goals, tactics, structure, cultural values and norms, and the external environment. The degree of alignment for each pair was measured on a 7-point Likert-type scale ranging from Strongly Disagree (1) to Strongly Agree (7). The average of the items was cal- culated as the composite value for organizational alignment. The scale is provided in Appendix A. Strategy Change Three original items were used to measure the degree to which a firm actually changed its strategy during the last three years. Using a 5-point scale, the items measured the frequency of strategy change (ranging from None to Con- tinually), the degree of change (ranging from Very Minor to Very Major), and the speed of change (ranging from No Time At All to Years). The average of the three items was calculated as the composite value for strategy change. Industry Industry was measured as a nominal value correspond- ing to each industry sector. As a categorical variable, it then was encoded using dummy variables for the construction and professional services industries with higher response counts, and the remaining industries were grouped into a third “other” category, for use in regression analysis (Cohen et al., 2015). Analysis The two primary forms of analysis were factor anal- ysis and multiple regression. Confirmatory Factor Analy- sis (CFA) was used to validate the ten survey items used 39 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 to measure strategic agility. Factors were extracted using principal component analysis, as shown by Table 3. The top three components, presumably corresponding to the three dimensions of strategic agility, met the rule-of-thumb crite- ria for Eigenvalues > 1.0 and together accounted for 63.4% of the average variance explained. Table 4 provides the fac- tor loadings of the survey items, showing clean loadings for most items on the components. CFA and Cronbach’s alpha were used to test the in- ternal reliability of all five latent constructs in the study, as summarized by Table 5. Strategic sensitivity and resource fluidity did not quite meet the rule-of-thumb minimum of .70 for coefficient alpha (Nunally, 1978). Strategic sensi- tivity also did not meet the rule-of-thumb minimum of .60 for one of its factor loadings. However, the Average Vari- ance Explained (AVE) and Composite Reliability (CR) of the constructs did meet the rule-of-thumb minimums of .50 and .80 respectively (Fornell & Larcker, 1981; Netemeyer et al., 2003). Table 3 Principal component analysis for strategic agility Initial Eigenvalues Component Total Variance % 1 3.336 33.364 33.364 2 1.845 18.446 51.809 3 1.164 11.635 63.445 4 811 8.115 71.560 5 695 6.954 78.513 6 684 6.845 85.358 7 609 6.094 91.452 8 439 4.386 95.838 9 291 2.905 98.744 10 126 1.256 100.000 Table 4 Loading of survey items on strategic agility components Component Item 1 2 3 SENSE1 .529 -.182 .458 SENSE2 .161 .395 .789 SENSE3 .047 .206 .885 UNITY1 .715 -.145 .202 UNITY2 .869 .084 .084 UNITY3 .751 .277 -.154 UNITY4 .627 .242 .133 FLUID1 -.036 .808 .054 FLUID2 .059 .699 .241 FLUID3 .197 .670 .133 Varimax rotation with Kaiser normalization Table 5 Reliability of latent variables Construct Cronbach’s Alpha Range of Factor Loadings* Average Variance Explained Composite Reliability Environmental Turbulence .766 .653 - .852 .593 .852 Organizational Alignment .769 .701 - .847 .596 .855 Strategic Sensitivity .695 .536 - .894 .626 .827 Leadership Unity .764 .667 - .896 .587 .849 Resource Fluidity .637 .751 - .800 .592 .813 *Unrotated Results and Discussion The means, standard deviations, and correlations are reported in Table 6. Firm age and firm size are positive- ly correlated with one another, as would be expected. Firm age and strategic agility are negatively correlated, support- ing H1. Firm size and strategic agility are not significantly correlated. Strategic agility is strongly positively correlat- ed with both organizational alignment and strategy change (p < .01), supporting the anticipated construct validity of strategic agility. None of the variables show a statistically significant correlation with firm performance. The results of the regression analysis of strategic agility on firm age and firm size are shown in Table 7. Hi- erarchical regression was used to model industry control variables first, followed by the addition of firm age and firm size. Model 1 shows that industry alone accounts for 16.5% of the variance in strategic agility. Model 2 shows that firm age is still negatively related to strategic agility under in- dustry control, adding 8.8% to the proportion of variance explained. Hypothesis 1 is therefore supported. Model 3 shows that firm size is not significantly related to strategic agility, providing no support for Hypothesis 2. Model 4 shows that the relationship between firm age and strategic agility is independent of firm size as well as industry. 40 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 The results of the regression analysis of firm perfor- mance on strategic agility and environmental turbulence are shown in Table 8. Model 1 shows that the industry controls account for only 4.4% of the variance in firm performance, and Model 2 shows that adding strategic agility has little effect. Hypothesis 3 was therefore not supported. Model 3 shows that adding environmental turbulence has little ef- fect. However, Model 4 shows that the interaction between strategic agility and environmental turbulence is statistical- ly significant and adds 10.5% to the proportion of variance explained. This supports Hypothesis 4. Figure 2 graphically depicts the moderating effect of environmental turbulence. Under high turbulence (3.97), as strategic agility increases, so does firm performance. Under low turbulence (2.78), as strategic agility increases, per- formance actually decreases, suggesting that firms may be penalized for their strategic agility in stable environments. Probing the interaction (Hayes, 2018) at multiple levels of turbulence shows that the point at which the relationship be- tween strategic agility and performance switches between positive and negative is approximately 3.4 on the 5-point turbulence scale ranging from Very Low (1) to Very High (5). Table 6 Descriptive statistics and pearson correlations Variable Mean (S.D.) AGE SIZE AGILITY TURB PERF ALIGN CHANGE CTRDUM SRVDUM AGE 26.33 (16.15) 1 SIZE 72.87 (93.02) .441** 1 AGILITY 136.80 (58.30) -.434** -.042 1 TURB 3.37 (0.60) -.092 .061 .253 1 PERF 3.97 (1.73) .050 -.183 .064 -.123 1 ALIGN 5.58 (0.84) -.332* .066 .589*** .255 -.200 1 CHANGE 2.34 (0.85) -.403** .109 .486*** .334* -.047 .449** 1 CTRDUM 0.27 (0.45) .315* .019 -.355* -.029 -.210 -.175 -.368** 1 SRVDUM 0.27 (0.45) -.359* -.064 -.313* .068 .056 .305 -.038 -.364** 1 *p <.10, **p < .05, ***p < .01 (2-tailed) Table 7 Relationships of firm age and firm size with strategic agility Dependent Var: AGILITY Independent Vars Model 1 Controls Model 2 AGE Model 3 SIZE Model 4 AGE and SIZE CTRDUM -.278 -.209 -.248 -.193 SRVDUM .212 .120 .210 .109 AGE -.325* -.397* SIZE -.024 .143 R2 .165 .253 .166 .269 ΔR2 .088 .001 .016 Std. Error 55.222 53.236 56.256 53.704 Sig. .088 .052 .188 .087 Values are standardized coefficients *p < .10, **p < .05, ***p < .01 41 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 The performance penalty for strategic agility in stable environments is consistent with Winter’s (2003) view that dynamic capabilities are not always warranted given their greater cost in comparison to ordinary capabilities (rou- tines) and ad hoc problem solving. According to Winter, dynamic capabilities involve a carrying cost for the special- ized resources which enable it to change lower-order ca- pabilities. Firms without dynamic capabilities can still ac- complish change through ad hoc problem solving, the costs of which generally disappear when there is no problem to solve. Therefore, when the need for change is sparse, the added cost of dynamic capabilities may not be matched by corresponding benefits. In summary, the hypothesis that firm age is negatively related to strategic agility (H1) was supported by the study. As firms became older, they became less strategically agile. This is consistent with prior research in the areas of path dependency, asset stock accumulation, and structural inertia Table 8 Relationships between strategic agility, environmental turbulence, and firm performance Dependent Var: AGILITY Independent Vars Model 1 Controls Model 2 AGILTY Model 3 TURB Model 4 AGILTYxTURB CTRDUM -.218 -.220 -.210 -.229 SRVDUM -.023 -.022 -.021 -.008 AGILITY -.008 .030 -2.029 TURB -.135 -1.078* AGILITYxTURB 2.483* R2 .044 044 .061 .167 ΔR2 .000 .017 .105 Std. Error 1.754 1.788 1.807 1.738 Sig. .542 .752 .800 .462 Values are standardized coefficients *p < .10, **p < .05, ***p < .01 Figure 2. Plot of Moderating Effect of Environmental Turbulence 42 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 (Barney, 1991; Dierickx & Cool, 1989; Hannan & Freeman, 1984). The hypothesis that firm size is negatively related to strategic agility (H2) was not supported, despite the cor- relation found between firm age and size. While surprising, previous studies have also found the effects of firm age and firm size to be separate and independent (Esteve-Perez & Manez-Castillejo, 2006; Freeman et al., 1983; Gopalakrish- nan & Bierly, 2006). The hypothesis that strategic agility was unconditionally related to firm performance (Hypothe- sis 3) was also not supported. However, the hypothesis that environmental turbulence positively moderates the relation- ship between strategic agility and performance (Hypothe- sis 4) was supported. As firms became more strategically agile, they performed better in turbulent environments and worse in stable environments. This negative impact in low turbulence might be called the “Winter effect” after Sidney Winter, who argued that dynamic capabilities are expected to carry additional costs that may be an unnecessary burden in low turbulence (Collis, 1994; Winter, 2003). This finding may also help explain the mixed results in prior research on the relationship between strategic agility and firm perfor- mance. Implications, Limitations, and Future Research This study contributes to theory in two ways. First, it operationalizes the Doz and Kosonen (2010) framework de- scribing strategic agility and finds it to be valid both inter- nally through CFA and externally through convergence with similar constructs. The resulting scale may prove useful to researchers investigating strategic agility and may lead to more consistent findings in the future. Second, two contin- gency factors related to strategic agility are identified. Firm age is found to be an antecedent of strategic agility, and en- vironmental turbulence is found to be a moderator of the re- lationship between strategic agility and performance. These findings help to “build out” our conceptual understanding of the role of strategic agility. The study also has two significant managerial implica- tions. Young firms may be able to leverage strategic agili- ty as a source of competitive advantage, particularly when competing against older firms. However, they should bear in mind that they may lose strategic agility as they grow older. That is, they should use it before they lose it. Firms may therefore wish to use the scale to monitor their strate- gic agility and to maintain it through exercise or develop it through training. Second, firms may enhance their per- formance by matching their level of strategic agility with the level of turbulence in their environment. High strate- gic agility appears to pay off in high turbulence, whereas low strategic agility appears to pay off in low turbulence. This suggests that the ability to dynamically adjust strategic agility is a useful second-order dynamic capability (Winter, 2003). There are several limitations in the study. The gen- eralizability of the results is limited by the focus on firms located in a specific region of one state. The results may therefore not apply to other geographies which are mark- edly different in industry mix or environmental factors. The study is also limited by its small sample size. While statis- tically significant results are found, stronger relationships and results involving firm size may be found with a greater number of firms. Finally, the study is limited by the use of single-rater survey data as opposed to multiple, more objec- tive sources of data. While the behavioral nature of strate- gic agility requires a questionnaire, some constructs such as firm performance and environmental turbulence might be collected from public filings or industry databases. Multiple raters for each firm might also be used to reduce bias and increase the sample size. Each of these limitations warrants additional research. The study should also be expanded to include large firms. Large firms generally have greater resources, more products and services, larger market share, economies of scale, and other advantages over SME firms (Penrose, 1959). However, these advantages may become disadvan- tages when it comes to strategic agility. Large firms may not be able to shift their resources or market focus as easily or quickly as small firms. Grantham et al. (2007) argue that the agility of large corporations is limited by their real estate, human resources, and IT investments. While firm size was included in this study, it remains to be seen if the findings extend to firms with one thousand or ten thousand employ- ees and revenues measured in billions. Finally, the longitudinal study of strategic agility is recommended. By measuring and tracking the strategic agility of one or more firms over time, causal relationships may be identified in how the capability is developed, lost, and linked to outcomes. Unfortunately, unless archival data is used, it may take years for the longitudinal study of stra- tegic agility to witness the results of strategic change. References Al-Azzam, Z. F., Irtaimeh, H. J., & Khaddam, A. A. H. (2017). Examining the mediating effect of strategic agility in the relationship between intellectual capital and organizational excellence in Jordan service sector. Journal of Business, 6(1), 7-15. Allred, A., Addams, H., & Chakraborty, G. (2007). Is in- formal planning the key to the success of the Inc. 500? Journal of Small Business Strategy, 18(1), 95-104. 43 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 Ansoff, H. I., Kipley, D., Lewis, A. O., Helm-Stevens, R., & Ansoff, R. (2019). Implanting Strategic Management (3rd ed). Palgrave MacMillan. (Original work pub- lished 1984) Arbussa, A., Bikfalvi, A., & Marques, P. (2017). Strategic agility-driven business model renewal: The case of an SME. Management Decision, 55(2), 271-293. Arthur, W. B., Ermoliev, Y. M., & Kaniovski, Y. M. (1987). Path-dependent processes and the emergence of mac- rostructure. European Journal of Operational Re- search, 30(3), 294-303. Autio, E., Sapienza, H. J., & Almeida, J. G. (2000). Effects of age at entry, knowledge intensity, and imitability on international growth. Academy of Management Jour- nal, 43(5), 909-924. Barney, J. B. (1991). Firm resources and sustained compet- itive advantage. Journal of Management, 17(1), 99- 120. Bednar, M. K., & Westphal, J. D. (2006). Surveying the corporate elite: Theoretical and practical guidance on improving response rates and response quality in top management survey questionnaires. Research Method- ology in Strategy and Management, 3, 37-55. Brueller, N. N., Carmeli, A., & Drori, I. (2014). How do dif- ferent types of mergers and acquisitions facilitate stra- tegic agility? California Management Review, 56(3), 39-57. Clauss, T., Abebe, M., Tangpong, C., & Hock, M. (2019). Strategic agility, business model innovation, and firm performance: An empirical investigation. IEEE Trans- actions on Engineering Management (Early Access), 1-18. DOI 10.1109/TEM.2019.2910381 Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2015). Ap- plied multiple regression/correlation analysis for the behavior sciences (3rd ed.). Routledge. Collis, D. J. (1994). Research note: How valuable are or- ganizational capabilities? Strategic Management Jour- nal, 15(S1), 143-152. Cooper, D. R., & Schindler, P. S. (2014). Business research methods. McGraw-Hill. Covin, J. G., & Slevin, D. P. (1989). Strategic management of small firms in hostile and benign environments. Strategic Management Journal, 10(1), 75-87. D&B Hoovers. (2018). D&B Hoovers: Accelerate the path from prospect to profitable relationship. https://www. dnb.com/products/marketing-sales/dnb-hoovers.html Dess, G. G., & Robinson, R. B., Jr. (1984). Measuring or- ganizational performance in the absence of objective measures: The case of the privately-held firm and con- glomerate business unit. Strategic Management Jour- nal, 5(3), 265-273. Dierickx, I., & Cool, K. (1989). Asset stock accumulation and sustainability of competitive advantage. Manage- ment Science, 35(12), 1504-1511. Dove, R. (1996). Agile supply-chain management. Automo- tive Production, 108(4), 16-17. Doz, Y. L., & Kosonen, M. (2008a). Fast strategy: How strategic agility will help you stay ahead of the game. Wharton School Publishing. Doz, Y. L., & Kosonen, M. (2008b). The dynamics of stra- tegic agility: Nokia’s rollercoaster experience. Califor- nia Management Review, 50(3), 95-118. Doz, Y. L., & Kosonen, M. (2010). Embedding strategic agility: A leadership agenda for accelerating business model renewal. Long Range Planning, 43(2-3), 370- 382. Doz, Y. (2020). Fostering strategic agility: How individual executives and human resource practices contribute. Human Resource Management Review, 30(1), 1-14. Ebben, J., & Johnson, A. (2005). Efficiency, flexibility, or both? Evidence linking strategy to performance in small firms. Strategic Management Journal, 26(13), 1249-1259. Eisenhardt, K., & Martin, J. (2000). Dynamic capabilities: What are they? Strategic Management Journal, 21(10- 11), 1105-1121. Esteve-Perez, S., & Manez-Castillejo, J. A. (2006). The resource-based theory of the firm and firm survival. Small Business Economics, 30(3), 231-249. Fiegenbaum, A., & Karnani, A. (1991). Output flexibility – a competitive advantage for small firms. Strategic Management Journal, 12(2), 101-114. Florida Gulf Coast University. (2019). FGCU industry di- versification index, 4th Quarter 2018. https://www. fgcu.edu/cob/reri/idp/ Forbes, D. (2005). Managerial determinants of decision speed in new ventures. Strategic Management Journal, 26(4), 355-366. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and mea- surement error. Journal of Marketing Research, 18(1), 39-50. Fourne, S. P. L., Jansen, J. J. P., & Mom, T. J. M. (2014). Strategic agility in MNEs: Managing tensions to cap- ture opportunities across emerging and established markets. California Management Review, 56(3), 13- 37. Freeman, J., Carroll, G. R., & Hannan, M. T. (1983). The liability of newness: Age dependence in organizational death rates. American Sociological Review, 48(5), 692- 710. Garcia-Morales, V. J., Llorens-Montes, F. J., & Verdu-Jo- 44 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 ver. (2007). Influence of personal mastery on organi- zational performance through organizational learning and innovation in large firms and SMEs. Technovation, 27(9), 547-568. Gopalakrishnan, S., & Bierly, P. E. (2006). The impact of firm size and age on knowledge strategies during prod- uct development: A study of the drug delivery indus- try. IEEE Transactions on Engineering Management, 53(1), 3-16. Grantham, C. E., Ware, J. P., & Williamson, C. (2007). Cor- porate agility: A revolutionary new model for compet- ing in flat world. AMACOM. Groves, R. M. (2006). Nonresponse rates and nonresponse bias in household surveys. Public Opinion Quarterly, 70(5), 646-675. Gunasekaran, A. (2001). Agile manufacturing: The 21st cen- tury competitive strategy. Elsevier. Gunter, F. R. (2012). A simple model of entrepreneurship for principles of economics courses. The Journal of Economic Education, 43(4), 386-396. Hamalainen, T., Kosonen, M., & Doz, Y. L. (2012). Stra- tegic agility in public management. (Working paper 2012/30/ST). INSEAD. Hannan, M. T., & Freeman, J. (1984). Structural inertia and organizational change. American Sociological Review, 49(2), 149-164. Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press. Ivory, S. B., & Brooks, S. B. (2018). Managing corporate sustainability with a paradoxical lens: Lessons from strategic agility. Journal of Business Ethics, 148(2), 347-361. Jacoby, C. H., Jr., & Shaw, R. L. (2016). Strategic agility theory and practice. Joint Forces Quarterly, 81, 34-42. Junni, P., Sarala, R. M., Tarba, S. Y., & Weber, Y. (2015). The role of strategic agility in acquisitions. British Journal of Management, 26(4), 596-616. Kale, E., Aknar, A., & Basar, O. (2019). Absorptive capacity and firm performance: The mediating role of strategic agility. International Journal of Hospitality Manage- ment, 78, 276-283. Khoshnood, N. T., & Nematizadeh, S. (2017). Strategic agility and its impact on the competitive capabilities in iranian private banks. International Journal of Busi- ness and Management, 12(2), 220-229. Kirzner, I. M. (1997). Entrepreneurial discovery and the competitive market process: An Austrian approach. Journal of Economic Literature, 35(1), 60-85. Kumkale, I. (2016). Organization’s tool for creating com- petitive advantage: Strategic agility. Balkan and Near Eastern Journal of Social Sciences, 2(03), 118-124. Kwon, S. J., Ryu, D., & Park, E. (2018). The influence of entrepreneurs’ strategic agility and dynamic capabili- ty on the opportunity pursuit process of new ventures: Evidence from South Korea. Academy of Strategic Management Journal, 17(1), 1-17. Lewis, M. W., Andriopoulos, C., & Smith, W. K. (2014). Paradoxical leadership to enable strategic agility. Cali- fornia Management Review, 56(3), 58-76. Long, C. (2000). You don’t have a strategic plan? – Good! Consulting to Management, 11(1), 35-42. Lu, Y., & Ramamurthy, K. (2011). Understanding the link between information technology capability and organi- zational agility: An empirical examination. MIS Quar- terly, 35(4), 931-954. Lumpkin, G. T., & Dess, G. G. (1996). Clarifying the en- trepreneurial orientation construct and linking it to performance. Academy of Management Review, 21(1), 135-172. Nadler, D. A., & Tushman, M. L. (1989). A model for di- agnosing organizational behavior: Applying a congru- ence perspective. In D. A. Nadler, M. L. Tushman, & C. O’Reilly (Eds.). The management of organizations: Strategies, tactics, analyses (pp. 91-106). Harper & Row. Nagel, R. N. (1992). 21st century manufacturing enterprise strategy report (AMEF N0001-92). Arlington, VA: Of- fice of Naval Research. Nagel, R. N., & Dove, R. (1991). 21st Century Manufactur- ing Enterprise Strategy: An industry-led view. Diane Publishing. Netemeyer, R. G., Bearden, W. O., & Sharma, S. (2003). Scaling Procedures: Issues and Applications. SAGE. Nunally, J. C. (1978). Psychometric theory. McGraw Hill. Ofoegbu, O. E., & Akanbi, P. A. (2012). The influence of strategic agility on the perceived performance of man- ufacturing firms in Nigeria. International Business & Economics Research Journal, 11(2), 153-160. Ojha, D. (2008). Impact of strategic agility on competitive capabilities and financial performance (Accession/ Order No. 3339487) [Doctoral dissertation, Clemson University]. ProQuest Dissertations and Theses. Penrose, E. T. (1959). The theory of the growth of the firm. John Wiley & Sons. Powell, T. C. (1992). Organizational alignment as competi- tive advantage. Strategic Management Journal, 13(2), 119-134. Quiros, I. (2009). Organizational alignment: A model to ex- plain the relationships between organizational relevant variables. International Journal of Organizational Analysis, 17(4), 285-305. 45 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 Roth, A. V. (1996). Achieving strategic agility through economies of knowledge. Strategy & Leadership, 24(2), 30-36. Rumelt, R. P. (1991). How much does industry matter? Strategic Management Journal, 12(3), 167-185. Sambamurthy, V., Bharadwaj, A., & Grover, V. (2003). Shaping agility through digital options: Reconceptual- izing the role of information technology in contempo- rary firms. MIS Quarterly, 27(2), 237-263. Semler, S. W. (1997). Systematic agreement: A theory of organizational alignment. Human Resource Develop- ment Quarterly, 8(1), 23-40. Shin, H., Lee, J., Kim, D., & Rhim, H. (2015). Strategic agility of Korean small and medium enterprises and its influence on operational and firm performance. Inter- national Journal of Production Economics, 168, 181- 196. Space Coast Economic Development Commission. (2019). Interactive data center. https://spacecoastedc.org/da- ta-downloads/dashboard/ Space Coast Economic Development Commission. (2018). Florida’s space coast named ‘turnaround of the year’ by SpaceNews. https://secure.spacecoastedc.org/np/ clients/spacecoastedc/news.jsp?news=122 Sullivan, L. E., Johnson, R. B., Mercado, C. C., & Terry, K. J. (2009). The SAGE glossary of the social and behav- ioral sciences (1st ed.). SAGE. Teece, D. J. (2009). Dynamic capabilities and strategic management. Oxford University Press. Teece, D. J., Peteraf, M., & Leih, S. (2016). Dynamic ca- pabilities and organizational agility: Risk, uncertain- ty, and strategy in the innovation economy. California management review, 58(4), 13-35. Teece, D., Pisano, G., & Shuen, A. (1997). Dynamic capa- bilities and strategic management. Strategic Manage- ment Journal, 18(7), 509-533. U.S. Small Business Administration (2012). Survival rates and firm age. https://www.sba.gov/advocacy/ small-business-facts-and-infographics Vecchiato, R. (2015). Creating value through foresight: First mover advantages and strategic agility. Technological Forecasting & Social Change, 101, 25-36. Weber, Y., & Tarba, S. Y. (2014). Strategic agility: A state of the art. California Management Review, 56(3), 5-12. Winter, S. G. (2003). Understanding dynamic capabilities. Strategic Management Journal, 24(10), 991-995. Yusuf, Y. Y., Gunasekaran, A., Adeleye, E. O., & Sivayo- ganathan, K. (2004). Agile supply chain capabilities: Determinants of competitive objectives. European Journal of Operational Research, 159(2), 379-392. 46 J. Reed Journal of Small Business Strategy / Vol. 31, No. 3 (2021) / 33-46 Appendix A – Latent Variable Scales Strategic Sensitivity 1. My organization anticipates future products and services needed by customers. 2. My organization uses experimenting (e.g., prototypes, pilots, in-market tests) to probe the future. 3. My organization considers a wide range of potential products and services by viewing our business in abstract terms. Leadership Unity 1. The leaders of my organization engage in open dialogue and welcome differences of opinion. 2. The leaders of my organization operate as an integrated, interdependent, value-creating team. 3. The leaders of my organization are aligned around a common interest through a compelling mission, aspirational vision, shared values, and emotion. 4. The leaders of my organization are caring and demonstrate empathy and compassion for others. Resource Fluidity 1. My organization’s underlying business systems and processes are modular and easily changed. 2. My organization uses multiple business models for different market segments or products. 3. My organization adopts new ways of doing business from other companies. Environmental Turbulence 1. How complex is your company’s external environment? 2. How rapidly do challenges evolve in the external environment? 3. How novel is each challenge in the external environment? 4. How frequently does the external environment shift between being stable and unstable? Organizational Alignment 1. There is a rational flowdown of goals within my organizational structure. 2. The cultural values of my organization are consistent with our strategic goals. 3. The cultural norms for behavior in my organization are consistent with our tactics. 4. There is good fit between the demands of the external environment and our strategic goals and tactics.