Smaller less “glamorous” firms are more prevalent in the U.S. economy than high technology companies. These small firms are known for their inability to erect barriers to imitation, making the development of competitive advantage difficult. In our paper, we study the relationship between firm resources and firm strategies. Based on the contention that the quality of a firm’s strategy cannot be judged independently of the firm resources upon which it is based (Barney & Zajac, 1994), we examine the relationship between firm resources and strategies in a cross-section of over 250 small firms. Our findings indicate that small less glamorous firms should follow strategies that bring them closer to their customers, rather than innovation strategies that may be more appropriate for their high technology counterparts.

Small, non-high technology firms face dramatic shifts in their competitive landscape, brought on by changes in global competition and new technologies. These changes directly influence a small firm’s resource profile, strategic options and future performance. Although significant research attention currently focuses on the strategies and performance of fast growth high technology firms, these firms comprise a comparatively small proportion of firms in the US economy. Instead, smaller, less “glamorous” firms are far more prevalent (Dennis & Dunkelberg, 2000). US statistics from 1992 show small businesses accounted for 88% of the construction output, 74% of the service output, 62% of trade, 51% of finance, insurance, and real estate, 25% of manufacturing and mining, and 24% of transportation and communication output (Acs, 1999:7). An Organization for Economic Cooperation and Development (OECD) 1997 synthesis report estimated that about 60% of small and medium-sized companies in the OECD countries operate in mature conventional industries, another 30% operate in mature, global industries, and only up to 15% operate in emerging niche industries such as the high technology sector (OECD, 1997).

These small, non-high technology firms compete in business sectors that are notorious for their high failure rates (The State of Small Business, 1995). In addition, they have fewer opportunities to erect barriers to imitation, which means that they typically lack the capabilities or firm resources that can lead to competitive advantage (Zahra & Bogner, 2000). Therefore, for continued growth or better performance, their imperative is to develop unique bundles of resources that can distinguish their base of competition (Chandler & Hanks, 1994; Brush & Chaganti, 1998), and create strategies that result in customer loyalty (Carter, Stearns, Reynolds & Miller, 1994).

In this paper, we examine the fit between firm resource profiles and strategies in small firms. In essence, we argue that the quality of a firm’s strategy cannot be judged independently of the firm resources upon which it is based (Barney & Zajac, 1994). This is a contingency perspective, in that firm strategies are posited to “fit” with their corresponding internal capabilities or resources (Venkataraman & Camillus, 1984). While a significant body of work in the entrepreneurial domain illustrates that firm strategies are contingent on certain external factors such as the environment (Covin & Slevin, 1989), or industry (McDougall, Covin, Robinson, & Herron, 1994; Carter et al., 1994), less work has been done that examines specific internal factors and their link to firm strategy.

This is the purpose of our paper. We study the relationship between firm resources and firm strategies. To do this, we build on earlier studies that argue for the importance of the owner/ founder resources (Cooper, Gimeno-Gascon, & Woo, 1994) and organizational resources (Ropo & Hunt, 1995), as well as work that documents the relationship between resources and particular strategies (Chandler & Hanks, 1994; Brush & Chaganti, 1998). We focus exclusively on two specific strategy types: quality/customer service, and innovation, and their relationship to human and organizational resources or capital. We employ a structural equation modeling technique, which permits us to analyze the relationship between resource bundles and strategy types using multiple dependent variables. In the following sections, we develop hypotheses suggesting that there are positive and significant relationships between firm resources and firm strategies. We then describe our methodology, and present our findings and conclusions.

Firms build competitive advantage by utilizing unique sets of resources. Resources are heterogeneous, and typically include all assets, capabilities, processes and knowledge controlled by a firm that enables it to conceive of and implement strategies to improve effectiveness (Barney, 1991). Small firms competing in highly populated industrial sectors may be unable to differentiate their strategies due to low barriers to entry. Furthermore, small firms may have insufficient or inaccessible resources, which may limit the range of feasible strategic alternatives (Hofer & Sandberg, 1987). In these cases, the human capital resources, such as the personal experience, connections or commitment of the entrepreneur and employees (Cooper, Willard & Woo, 1994; Cooper & Artz, 1995), or organizational resources comprised of systems and policies (Ropo & Hunt, 1995) may have a more direct impact on a small firms strategic options and strategic choice. Moreover, a central premise of Penrose (1959) is that the manager’s expectations and judgments will ultimately determine the firm’s growth pattern. This premise is supported by Chandler and Hanks (1994), who found that firms with higher and broader levels of resource-based capabilities grew faster than those that did not.

The source of strategy in small firms is more likely to arise from human capital resources, capabilities and competencies (Hitt & Reed, 2000). Critical resources, especially in small firms, are likely to be held by the individual entrepreneur(s) or their organization (Mosakowski, 1993; Pennings, Lee & van Witteloostuijn, 1998). While some studies do show equivocal relationships between individual aspects of human resources and performance (e.g., experience or education or psychological characteristics) (Cooper & Gimeno-Gascom, 1992), overall the human resources of the entrepreneur and team have a direct effect on the firm’s product/market strategies (Miller & Friesen, 1984). Hills and Narayana (1989) found success factors in high growth small firms included the quality of the product or service, having a good reputation with customers, the ability to respond to customer’s requests, and hard work and devotion to the business. Hence, in small firms, when human capital resources are both strong and related to customers, suppliers and service dimensions, the relationship between human resources and a strategy of quality/customer service is likely (Chandler & Hanks; 1994). Therefore, we propose

Hypothesis 1a: In small firms, greater levels of human capital have a positive and significant impact on the firm strategy of quality/customer service.

Relationships between human resources and innovation strategies also are suggested in a variety of studies. Companies pursuing an innovation strategy need creative and innovative employees, to maintain contact with customers (Chandler & Hanks, 1994). Given that entrepreneurial strategy is defined by agility, creativity and continuous innovation (Covin & Slevin, 1990), it follows that stronger human resources will be associated with innovation strategies. Relatedly, literature from innovation technology finds that many market driven innovations result from interactions with customers (von Hippel, 1981), while Aldrich and Zimmer (1986) found that linkages and relationships of entrepreneurs to customers were associated with the innovation process. Further, Bantel and Jackson (1989) found a strong relationship among innovation, top-management team education and functional expertise. Zahra and Bogner (2000) propose that the decisions regarding technology investment in research and development, and product upgrades are rooted in managerial perceptions and strategies for dealing with the environment. Hence, in small firms, where top managers are responsible for strategy, it follows that human capital will be related to innovation strategies. Therefore, we propose

Hypothesis 1b: In small firms, greater levels of human capital have a positive and significant impact on the firm’s strategy of innovation.

Organizational resources are referred to as the structure, processes and systems in organizations, which permit flows of information, training, and which motivate organizational members (Andrews, 1971). In a small company, organizational resources include the employees’ expertise, systems and policies (Ropo & Hunt, 1995), management systems (Bracker & Pearson, 1986; Brush & Chaganti, 1998), financial structures (Bygrave, 1992), planning and control systems (Bracker & Pearson, 1986), and culture and employee skills (Dollinger, 1995) of the firm. Presumably management systems, skills of employees and routines are essential in reaching customers or providing superior levels of service. Efficient small firms are more capable of providing quality customer service, while those that develop human capabilities in the form of skilled employees, are better able to respond to customer and market needs (Hitt & Reed, 2000). Furthermore, a positive relationship between resource-based capabilities, measured as employees trained and having expertise in providing superior customer service, was found by Chandler and Hanks (1994). Hence, we propose

Hypothesis 2a: In small firms, greater levels of organizational capital have a positive and significant impact on the firm strategy of quality/customer service

While it has been argued that less structure, ambiguity and open systems encourage innovation (Kanter, 1983), paradoxically, the development of systems, routines and policies would also appear to have a positive impact on a strategy of innovation. For example, it has been suggested that innovation strategies are supported by investment in research and development, obtaining copyrights, product upgrades, and other means of intellectual capital protection (Zahra & Bogner, 2000). Competencies or higher levels of organizational resources such as training of employees and their expertise are also associated with a strategy of innovation (Chandler & Hanks, 1994). Therefore, we propose

Hypothesis 2b: In small firms, greater levels of organizational capital have a positive and significant impact on the firm strategy of innovation.

Data Collection

Our research was conducted in two phases. Initially we performed an exploratory study of 410 small ventures that were randomly identified from publicly available directories, according to industrial technology sector (Buckley & Brooke, 1992).¹ We received 76 completed questionnaires during the first research phase, giving us a response rate of 18.5%. The second survey employed the same technology-sector sampling criteria, but to improve our response rate, we identified trade associations and personally requested their assistance in obtaining a list of firms. Associations included: primary sector—the Farm Equipment and Irrigation Associations; secondary sector—National Barbecue Association and National Poultry and Food Distributors Association; tertiary sector—National Association of Personal Financial Advisors.

We mailed 1120 questionnaires in the second research phase, using the Dillman (1978) multiple-contact method. Fifty-nine questionnaires were returned with bad addresses, bringing the number surveyed to 1061. A second mailing was sent to all non-respondents, followed by reminder post-cards two weeks later. The second mailing resulted in 39 additional responses, providing us with 208 responses from this phase (or 19.6%). For the total survey, the overall response rate from both research phases was 19.3%, yielding 284 useable responses. T-tests were performed to determine the appropriateness of pooling the data from the two phases (n=76 and n=208). We found no significant differences between the two samples on key variables including 1994 sales, total number of employees, and age of firm.

Measures: Resources

In measuring resources, we used a five point Likert scale ranging from Highly Unfavorable to Highly Favorable with a defined neutral anchor. In all cases Highly Favorable was numerically coded at 5.0 while the Highly Unfavorable anchor was coded as 1.0 (i.e., large numbers denote greater favorability). Resource items were identified from previous sources (Chandler & Hanks, 1994) as well as conceptual work in entrepreneurship (Vesper, 1990).

Human Resources: According to prior research, human resources comprise a broad range of aspectst—he owner-founder’s achieved attributes (Becker, 1964), background in family characteristics, education, and experience (Cooper, 1981), as well as attitudes, motivations, skills and goals (Davidsson, 1989; Birley & Westhead, 1990; Brush & Chaganti, 1998). ² We created a latent variable for human capital, comprised of two distinctive attributes of human resources: interpersonal skills and business skills. Specific variable items for interpersonal skills were: team management, motivational skills and developing personal relationships, and for business skills: oral presentation skills, writing ability and problem-solving ability. All of these are attributes of the respondent who in our sample was either the owner or the senior executive. The individual measures comprising the latent variable were factor analyzed and checked for reliability. The scale for interpersonal skills demonstrated high internal validity with factor loadings at .73 or higher. Cronbach’s alpha was .79. For business skills, factor loadings were at .62 or greater, and Cronbach’s alpha was .61. Each of these alpha levels is above the acceptable threshold for reliability (Nunnally, 1970), indicating good internal validity and reliability of the measures comprising the latent variable.

Organization Resources: Organizational resources include systems, policies, culture and the knowledge of the organization members other than founders, as well as organizational routines and structures (Tomer, 1987; Dollinger, 1995; Greene & Brown, 1997). Again, we created a latent variable called organizational capital, comprised of three distinctive aspects of organizational resources: employee skills, financial access and organization attributes. Specific variable items for employee skills included: ability to form strategic alliances, multilingual staff, and employees with international experience. For financial access, we examined the organization’s access to debt finance and its access to equity capital. Finally, for organizational attributes we looked at high domestic profitability, customer service capabilities, operating efficiencies, cost structures, and product and service offerings of the firm. A five-point Likert scale was used for each item. Each observed variable was factor and reliability analyzed. For employee skills, factor loadings were .79 or higher, with a Cronbach’s alpha for the variable of .84. For financial access, factor loadings were .98 or higher with a Cronbach’s alpha for the variable of .94. For organizational attributes, factor loadings were .63 or higher with a Cronbach’s alpha of .89.

Measures: Strategies

To measure the implementation strategies adopted by the firm, we drew on existing strategy measures developed by Chandler and Hanks (1994). While Chandler and Hanks originally examined three distinctive implementation strategies,³ in our analysis, only two strategies, quality/customer service, and innovation showed satisfactory reliability levels. Therefore, we eliminated the third strategy due to low reliability.

Quality/Customer Service Strategy: High quality and its commensurate customer service is a popular differentiation implementation strategy (Porter, 1995). We measured this strategy by examining four distinctive components: quality control, satisfaction of customer needs, highest quality, and superior service. The measure was factor and reliability analyzed. Factor loadings were a minimum of .74 and Cronbach’s alpha was .84, well above the minimum threshold set for reliability (Nunnally, 1970).

Innovation Strategy: We also examined the firm’s innovation strategy. We looked at the firm’s product or service development/innovation, innovative marketing, and technological superiority. The measure was factor and reliability analyzed with minimum factor loadings of .72 and a Cronbach’s alpha of .62. Table 1 presents the correlation matrix for the observed independent variables and their mean, standard deviation and reliability alphas.⁴

To best capture the theoretical interdependencies between resources and strategies, we analyzed the data using Structural Equation Modeling (AMOS 4.0 statistical package). This procedure allows for simultaneous analysis of more then one dependent variable. We developed a latent variable for human capital, based on the two observed variables, interpersonal skills and business skills and for the latent variable organizational capital based on three observed variables, employee skills, financial access and organizational factors. Latent variables are hypothetical constructs that combine two or more observed variables. As such, indicators that measure a latent variable should exhibit convergent validity, indicated by their correlation (Kline, 1998). For quality/customer service strategy and innovation strategy, we used observed variables.

To insure that the model fits the data well, we used multiple fit criteria to rule out measuring biases inherent in the various methods (Hair, Anderson, Tatham & Black, 1995). The chi-square divided by the degrees of freedom was .68, which is under the suggested ratio of two, for the hypothesized indirect model, and the p-value was .64, which is greater than the suggested .05 (Schumacker & Lomax, 1996). The model’s adjusted goodness of fit (AGFI) was .98, indicating a good fit with the data. The normed fit index (NFI) was .99, well above the .90 acceptable level (Hair, et al., 1995). The root-mean-square residual was a very acceptable .09 for the indirect model indicating a low difference between the observed and model-implied covariances. Hotelling’s critical N was 1287, well over the 200 mark considered acceptable thus indicating that the data fit very will with the model (Schumacker & Lomax, 1996). Table 2 shows the multiple fit statistics for the model.

In hypotheses 1 and 2, we make predictions about the specific paths in the model. To test these hypotheses, we examined the path coefficients and the critical ratios. In hypothesis 1a, we predicted a positive and significant relationship between human capital and the firm strategy of quality/customer service. The critical ratio for this path is 2.37 indicating strong support for this hypothesis at the z £ .01 level. In hypothesis 1b, we predicted a positive and significant relationship between human capital and the firm strategy of innovation. We found support for this hypothesis as well, with the critical ratio at 2.1 and z £ .05 level. For hypothesis 2a, in which we predicted a positive and significant relationship between organizational capital and the firm strategy of quality/customer, we also found strong support with the critical ratio at 3.62 and a significant z score at the z £ .001 level. In hypothesis 2b, we predicted a positive and significant relationship between organizational resources and the firm strategy of innovation. This hypothesis was not supported, as the critical ratio was .62, well under the necessary criteria for support. Table 3 shows the path coefficients and the critical ratios for the independent variables in the model. Figure 1 presents the model.

Our study sought to examine the fit between firm resource profiles and strategies in small firms. We tested for the effect of two types of capital (i.e., human and organizational) on two types of strategies (i.e., quality/customer service and innovation). We found significant effects of both human capital and organizational capital on quality/customer service strategy. The effect of human capital on innovation strategy also was significant, however, the relationship between organizational capital and innovation strategy was not. Given the context of the study—small, low growth companies—these results suggest that small companies should align their human and organizational capital to a strategy of quality/ customer service.

As is consistent with previous findings, we expected the human capital of the entrepreneur to be related to quality/customer service strategy (Cooper & Gimeno-Gascon, 1992; Mosakowski, 1993). The ability of the small firm owner/founder to motivate employees, interact with employees and customers, and solve problems, is central in a small firm. However, our results suggest that with respect to a strategy of quality/customer service, the management team, or organizational capital is also critical. This means that firms choosing to compete using a strategy of quality or customer service should critically examine their resource profiles. Apparently, not only do the characteristics of the owner/founder matter, but the resource sets of the entire management team are important as well.

Conversely, we find that human capital positively affects innovation strategy, but that organizational capital is not significant. We were somewhat surprised that organizational capital, such as organizational efficiencies, policies, and high level of profits was not associated with a strategy of innovation. It is possible that resources important to an innovation strategy reside in the owner/ founder (e.g., creativity, technological expertise) rather than the organization. In addition, it is possible that for small companies pursuing innovation strategies, other resources (e.g., technical, or physical) are more crucial to strategy than are organizational resources (Zahra & Bogner, 2000).

Our findings contribute to the better understanding of the role of the resource base and the importance of resource deployment in the context of the small companies. Our findings confirm that small firms are not merely smaller versions of big businesses, the major distinguishing characteristic being their “resource poverty” (Welsh & White, 1981: 18). Instead, small firms, often operating in mature, fragmented industries, such as service, consumer products, or retail face different competitive challenges. For example, these sectors are known for their notoriously high failure rates. Small firms face severe limitations in terms of economic and technical resources, which limit their performance (Brouthers, Andriessen & Nicolaes, 1998). Under conditions of resource constraints, the majority of small firms, operating in what Kirchhoff (1994) refers to as the “economic core,” exhibit little capacity to pursue a high innovation strategy. The findings of our study suggest that even when human resources, (e.g., the managerial competencies of the small firm) are adequate, the pursuit of innovation strategy may be misaligned with the generally low levels of development of organizational capital (e.g., production, research and development, or marketing capabilities). In essence, organizational constraints may inhibit small firms in less glamorous industries, from successfully pursuing a strategy of innovation.

The findings from our study suggest that while small firms face unique challenges in crafting strategies that fit their resource bases, it is critical to match the firm’s resources with its desired implementation strategy. Indeed, finding this match, while important for all firms, may be more important for small firms in less glamorous industries, in that these firms are often operating in highly competitive arenas and have little ability to erect barriers to imitation and therefore obtain a competitive advantage. In addition, their “resource poverty” further constrains these firms from acquiring the needed resources through arm’s length market transactions. Therefore, these firms must pay critical attention to their resource strengths and match them carefully with their desired firm strategy.

Our study makes an important empirical contribution by emphasizing the contingent nature of resources and strategies. The relationship between distinctive competencies and strategies is an area that has been identified as in need of further research (Chrisman, Hofer & Bauerschmidt, 1999). Our findings highlight the necessity of achieving a fit between firm resources and strategies for small firms. Future research should extend this study by linking resources and strategies to firm performance.

This research has important ramifications for managers. Innovation strategies are often touted as the route to competitive advantage for small firms in high technology sectors. However, for small firms in less glamorous industrial sectors, a strategy of innovation does not fit as well with the firm’s overall resource profile. Therefore, as tempting as a strategy of innovation may be, firms such as those in our sample are well advised to focus on the human capital of the owner/founder and pursue a strategy of quality and customer service. In other words, small firms should carefully utilize the resource strengths of their owner/founder while focusing on their customers, as this is their real competitive strength.

1. Buckley and Brooke identified three technology sectors; primary, secondary and tertiary. Primary industries are considered to be environmental and agricultural businesses; secondary are food equipment and service organizations; tertiary are finance and service organizations.

2. One item, expertise in technology, was dropped from the scale due to low factor loadings.

3. Chandler and Hanks (1994) originally used three strategies, innovation, cost leadership, quality/customer service.

4. Variable operationalizations and factor loadings are available from the authors.

CONTACT: Linda F. Edelman, Bentley College, 175 Forest Street, Waltham, MA 02453; (T) 781-891-2530; (F) 781-894-4257; ledelman@btinternet.com

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