The impact of key internal factors on firm performance: An empirical study of...
Acar, Ahmet C
Journal of Small Business Management; Oct 1993; 31, 4; ABI/INFORM Global
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the "internal environment." This research focuses on the internal environment and statistically controls for most industry-specific factors by limiting itself to two mature industries. The casting and machinery manufacturing industries studied here are both mature industries in that their real annual growth rates are less than 10 percent, their products and services are well-known by most users, and they have stable competitive structure and technology (Zeithaml and Fry as cited in Bracker and Pearson 1986, 507). Moreover, the effects of location or the local environment are largely eliminated as all firms are located in the same metropolitan area. Nevertheless, we include a dummy variable, firm's industry (casting or machinery manufacturing), to account for possible industry effects.
Internal Environment
In this research we examine the internal environment of the small firm in terms of five groups of factors: owner/ manager experience, age of firm, production competencies, marketing competencies, management competencies, and strategy.
Although the person at the center of the small firm bears the prime responsibility for the small firm's fortunes, systematic data on only one personality trait, experience of the owner/manager in the given industry, are available for the sample firms. This research does not address the impact of other CEO personality traits or entrepreneurial talents. However, the especially low frequency of entrepreneurs in mature industries (Schollhammer and Kuriloff 1979), and the limited impact of CEO personality in stable environments (Miller and Toulouse 1986) reduces the significance of this data shortcoming.
We examined the impact the age of firm has on performance. There are conflicting findings on the relationship
between firm age and performance. While some studies have associated higher performance with increased age (Birley and Westhead 1990, Bracker and Pearson 1986), others have suggested an opposite relationship (Begley and Boyd 1986, Kemelgor 1985).
Production competencies allow the firm to: manufacture a broad range of products, including specialty and high quality items; build a reputation in the industry; and reduce operating costs, which act as key factors to achieve competitiveness (Conant, Mowka, and Vara-darajan 1990; Dess and Davis 1984). However, most small firms experience problems due to inadequate product design and quality, and outdated machinery (O'Farrell and Hitchens 1988a, 1988b). In this research a total of seven surrogate variables are used to measure the production-related competencies of a firm. Site and building quality reflects sufficiency of existing structure, and the need for and feasibility of physical improvements. Technology measures suitability of machinery and knowledge of technologies and production know-how. Engineering and design shows the main parameters of operations and processes used, tools and fixtures, technical and cost-related feasibility of designs. Quality assurance covers defective and reject rates, inspection procedures and equipment, and overall quality orientation. Purchasing indicates the number of suppliers, knowledge of markets concerning suppliers, quality, reliability, prices, and payment terms. Repair and maintenance involves idle time due to break-downs and repairs, maintenance procedures, adherence to manufacturers blueprints, and stock of spare parts. Inventory management measures inventory levels for inputs and outputs, control procedures, lot-sizing, and frequency of orders.
Marketing competencies in pricing, advertising, promotion, distribution, after-
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sale (customer) service, and sales force quality determine effectiveness of the firm's response to targeted market segments, as well as its access to alternative product/market positions (Khan and Rocha 1982; e Sa and Hambrick 1989; Conant, Mokwa, Varadarajan 1990; Dess and Davis 1984). In this research, marketing-related competencies are introduced through four surrogate variables. Advertising and promotion covers type, mix, and cost-effectiveness of advertising and promotion activities. Distribution measures ownership of transportation facilities, and type, mix, and cost-effectiveness of distribution activities. Pricing reflects competency in cost estimation and pricing, knowledge of market prices, and alternative pricing policies. The fourth variable is a binary variable which shows availability of & full-time sales force.
The sophistication of the strategic planning process has been cited as a primary factor that strengthens financial performance in small firms (Bracker and Pearson 1986). Small firms are encouraged to have an informal planning process with little emphasis on structured objective-setting (Robinson and Pierce 1983), and a time horizon of less than two years (Barreyre 1977, Digman 1986). Not surprisingly, accounting and cash flow management, as short-term planning and control measures, were cited among the most critical factors for small business success (Khan and Rocha 1982, Robinson and Pierce 1984, Welsch and White 1981, Chaganti and Chaganti 1983). In this research three factors make up the framework for evaluating the general management skills of a firm. Cash and financial management covers separation of private and business finances, cash flow projections and control, and use of financial statements. Managerial and cost accounting reflects the type of financial records utilized, ef-
fectiveness of cost accounting, and use of outside accounting services. Cost structure measures shares of fixed material and labor costs, cost/value added ratio, and profit margin.
A firm's choice of strategies (Porter 1980) will determine the product/ market segments it competes in. In this research, we take three dimensions of the product/market structure as indicators of the company's strategic choices. Product diversification, is measured using a variant of the Herfindahl's index (Wernerfelt and Montgomery 1986):
i- (JlPf/fcp.r
where Pt shows the percentage of the total sales revenue due to product (product line) i. (A firm with a single product will have a diversification value of zero, while values close to 1 will show high levels of product diversification.) Product dependency measures focus on specific products (product lines) and is specified as max { P,, P2, P3, ... , Pm }, where Pi is defined as above. (A firm with only one product [product line] will have a dependency value of 1, showing complete focus on one product.) The third strategy variable is a binary variable indicating the scope of firm's markets (local/regional = 1; national/international = 2). The ability to compete in national (and international) markets, as opposed to local or regional, is taken as a sign of distinctive competencies needed to satisfy the demands of more competitive markets.
Performance Measures and Data Limitations
Measurement of organizational performance is a challenging issue. Alternative measures of organizational performance have frequently been found to yield contradictory results (Lu-
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batkin and Schrieves 1986, Dubovsky and Varadarajan 1987). Performance measurement in small business research has its additional problems, mainly due to data availability and reliability problems. As experienced by many researchers, small firms are notorious for their inability and unwillingness to provide the desired information (Fiorito and La Forge 1986, Birley and Westhead 1990). Moreover, where available, use of objective financial data on small firms may even have misleading results (Cooper 1979). Consequently, most empirical studies on small business have resorted to rather subjective assessments of company performance (O'Neill, Saunders, and Hoffman 1987; Birley and Westhead 1990; Conant, Mowka, and Varadarajan 1990). Although five years is generally regarded as the appropriate period to examine performance and change in firms (Bracker and Pearson 1986), consistent and reliable longitudinal data are rarely available for small firms. Hence, most studies have had to rely on data for shorter periods or simply use cross-section data to evaluate change and performance. In this research we use two separate performance dimensions. The first dimension is the size of firm measured as the average number of workers. The second dimension is the proportional sales revenue increase a firm has over a period of three years.
Analysis
Due to space limitations in this article, we discuss the findings obtained from step-wise regression analysis run to examine the combinations of factors that explain the variance in firm size and sales performance. The results of other analyses run on the same sample of firms are reported elsewhere (Acar 1991).
Firm growth rate. In the first model, size of firm was regressed against all 20 competence and strategy variables de-
scribed above, with .05 taken as the significance limit for variable inclusion. As seen in table 1, three surrogate variables (accounting, technology, and purchasing) entered the regression model to account for 61 percent of the variance in size variable, and the resulting equation was significant at the .0001 level. Inclusion of accounting in the equation stressed the importance of management competencies, along with production competencies. It can be inferred from the equation that firms which possessed requisite technology and know-how, maintained an effective accounting system, and featured competence in procurement management recorded the highest number of employees.
Sales revenue performance. When a regression analysis was run for sales revenue increase with .05 as the limit for variable inclusion, no variables entered the step-wise regression equation. The limit was then relaxed to .10. The resulting regression equation (table 1) was significant at the .0268 level, and it accounted for 22 percent of the variance in sales revenue performance. Product diversification was the first variable to enter the equation, and its negative coefficient (significant at p < .05) indicated the undesirable nature of product diversification for this sample of small firms. Financial management appeared as a significant variable (p < .05) to contribute to sales performance. Consequently, the inference is that firms with lower degrees of product diversification and mastery of cash and financial management realized the highest proportional increase in sales revenue.
Interestingly, the dummy variable which indicated the firm's industry did not enter any of the regression equations although it had highly significant bivariate correlations with both performance measures. This observation suggested, at least for this sample of firms, that the firm-specific factors su-
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Table 1 SUMMARY OF REGRESSION RESULTS
Independent Variables / Coefficient Estimate / Dependent Variables Standard Error of Coefficient / Significance LevelSize of Firm'
Technology Accounting Purchasing (constant) / 3.884
1.621
1.754
-12.557 / .969
.667
.726
3.986 / .001 .025 .025 .005
Sales Revenue Increase2
Diversification / -1.250 / .578 / .042
Financial management (constant) / .219 1.174 / .106 .363 / .048 .004
'Multiple R = 'Multiple fl =
0.815, Adjusted R!-0.540, Adjusted ft2
= 0.613, p < 0.001; n = 96 firms. = 0.224, p < 0.027; n= 55 firms.
perseded the industry factors in explaining growth and sales performance variances among firms.
Conclusion
The measures of organizational competencies and strategic dimensions used in this study proved instrumental in explaining firm size and sales performance. The analysis provided a statistically significant regression model which explained 61 percent of the variance in sizes (employment levels) of the sample firms. Competencies in terms of technology and procurement management, and sound accounting practices emerged as the most relevant factors that were positively associated with size. The selected variables proved less powerful in explaining the variance in sales revenue performance. The regression model, which accounted for 22 percent of the variance, showed that firms with better cash/financial management skills enjoyed higher proportional increases in their sales revenues. The negative (and significant) coefficient that product diversification had in the regression model may be explained by the presence of unused capacity (excess resources) which typically results in 'forced' product diversification (Chatterjee and Wernerfelt 1991). In the case of the smaller and
"not-so-competitive" firms, product diversification appears as a means of survival rather than a deliberate strategic choice.
Contrary to the expectations, the firm's age and owner's experience were not significant factors to explain size or sales performance differentials. While the firm's industry had significant bivar-iate correlations with both performance measures, it did not enter any of the step-wise regression equations.
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