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THE RELATION OF TRAITS, COMPETENCIES, MOTIVATION,
STRATEGY, AND STRUCTURE TO VENTURE GROWTH
J. Robert Baum, University of Maryland
The purpose of this study was to test contemporary entrepreneurship performance models. The models integrate personal, organizational, and industry concepts in a variety of configurations. I combined several models and measured common concepts with 22 variables that had persistent theoretical attention, consistent empirical association, or strong practitioner support for association with performance. Data from 363 growth-stage entrepreneurs and their associates were used with LISREL structural equation modeling to find that specific competencies, growth-oriented motivation, specific business strategies, and organization structure were significant direct antecedents of venture growth. Traits, general competencies, and local industry structure were mediated by the direct antecedents.
INTRODUCTION AND OVERVIEW
Entrepreneurs and entrepreneurship researchers and instructors are confronted with a large array of possible causes of entrepreneurship performance. To clarify the causes and their relationships, Gartner (1985), Sandberg (1986), McDougal, Robinson, and DeNisi (1992), Herron and Robinson (1993), and Naffziger, Hornsby, and Kuratko (1994), and others proposed entrepreneurship performance models with direct, mediation, and interaction configurations of an array of concepts. I used a large sample field study to evaluate a mediation configuration of 6 concepts that appeared repeatedly in the models. The concepts are: traits, competencies, motivation, strategy, organization structure, and industry structure.
The purpose was: 1) to identify measurable variables that embody the concepts, 2) to find the most significant direct performance-related concepts, and 3) to explore the permutation of mediation paths among the concepts. I wanted to provide empirical guidance for entrepreneurship performance model researchers, entrepreneurship instructors, and growth-oriented entrepreneurs.
I followed Gartner, Bird, and Starr (1992), who defined entrepreneurs as those who initiate, energize and guide the process of venture emergence. Focusing on emergence as an indicator of entrepreneurship, I identified entrepreneurs as those founders and buyers who had grown, or intended to grow, their companies and who were active managers with financial control. Thus, I excluded "lifestyle" founders and included buyers who transformed businesses into value-adding entities (Carland, Hoy, Boulton, and Carland, 1984). Consistent with the focus on emergence, I used venture growth as the indicator of performance.
Thirty-three (33) variables that articulated the 6 concepts that I studied were identified in a review of leadership, motivation, strategic management, and entrepreneurship studies. Interviews with 31 entrepreneurs identified additional candidate variables and guided assessment and selection of 22. I proposed direct relations between the 22 variables and venture growth and formed a mediation model that had paths that were consistent with theory, empirical research, and interviewee intuition.
A pretested questionnaire was circulated to CEOs of 849 firms from a single fragmented industry. Three-hundred seventy-four (374) CEOs (44%) responded. Associates of the CEOs provided data that were used with PRELIS 2 and LISREL 8 routines to configure a validated measurement model. Self-reported performance data were validated with a credit rating service. Three-hundred sixty-three (363) of the respondents qualified as growth-stage "entrepreneurs", and their responses were used with LISREL 8 structural equation modeling to test the proposals and the exploratory model.
ENTREPRENEURSHIP PERFORMANCE MODELS
Gartner (1985) emphasized individual behavior in his entrepreneurship performance model but proposed that entrepreneurship outcomes are an interaction of the individual, the organization, and the environment. Sandberg (1986) elaborated this view through an archival study of 17 firms; he found that industry structure and strategy had strong effects upon performance, while biographical characteristics of the entrepreneur (age, education, tenure) had weak effects. Subsequent research offered support for the importance of the interaction among industry structure and strategy for performance (Kunkel & Hofer, 1993; McDougall, Robinson, & DeNisi, 1992; Sandberg & Hofer, 1987).
Herron and Robinson (1993) proposed an entrepreneurship performance model that integrated more elaborate personal dimensions (skills, motivation) with organizational and industry dimensions. The model was based upon theory about the interaction of personal ability, motivation, and situation (Hollenbeck & Whitener, 1988). Naffziger, Hornsby, and Kuratko (1994) presented an integrated model of entrepreneurship performance that included individual differences, personal environment, business environment, ideas, vision, goals, behavior, and strategy.
Drawing upon the concepts and configurations that appear in common in extant entrepreneurship performance models, I formed the Entrepreneurship Performance Test Model that is shown in Figure 1 on the next page. As described below, propositions about direct relationships between concepts and venture growth (shown as P1 to P6) were based upon a research review and interviews. An explanation of the paths among the concepts is offered in "Relationships Among Performance Concepts".
RESEARCH REVIEW, INTERVIEWS, AND PROPOSITIONS
Following a review of performance relationships identified in 4 research domains, I interviewed 31 architectural woodwork industry entrepreneurs. The purpose of the two-hour structured interviews was: 1) to verify the relevance and measurement possibilities of 33 performance antecedents that were identified in the research review, and 2) to discover other likely antecedents.
Table 1 on the next page shows the results of the research review and the interview assessment. The source of each of the possible antecedents (research review or pilot study) is shown, as well as the percent of interviewees who felt that an antecedent was important for entrepreneurship performance. The 22 variables that were selected for the test of the Entrepreneurship Performance Model received support from more than 50% of the interviewees, as well as indications that the concept was measurable. A summary of the research review and interviews follows.
Personality traits are human predispositions that are stable across time and setting. Traits ought to be particularly important in the entrepreneurship situation where few, or unclear, inhibiting organizational cues or constraints are present (Bird, 1989). Indeed, some personality traits of successful entrepreneurs have been identified (achievement needs, locus of control, risk propensity, etc.), but for the most part, these traits also characterize successful managers and leaders of mature businesses and produce weak relationships with venture performance (Begley & Boyd, 1987; Low & MacMillan, 1988). Thus, I explored leadership research in search of traits that may be more powerful or may have been overlooked.
Stogdill (1948), Locke (1993), Locke, Kirkpatrick, Wheeler, Schneider, Niles, Goldstein, Welsh, & Chah (1991), and Yukl (1989) offer consistent support for an array of traits/motives that associate with manager/leader performance: tenacity, positive mood, ambition, goal-striving, high energy, high honesty/integrity, self-confidence and creativity. Many of these traits/motives align with the entrepreneurship archetype (Bird, 1989, 1992), so they were identified in Table 1 as potential venture growth-related variables.
Additional trait variables were suggested by the interviewees: money-seeking, status-seeking, fear of failure, and passion for work. Only "high energy", "creativity", and "fear of failure" were not considered important for entrepreneurship performance by more than half of the interviewees. The interviewees had difficulty distinguishing between "tenacity", "ambition", and "goal striving", so these variables were combined. Many participants felt that honesty/integrity and self-confidence are concepts that are difficult to test accurately with self-reports.
Proposition 1: Traits: tenacity, positive mood, money-seeking, status-seeking, and passion for work will have significant positive relationships with venture growth.
Competencies are sufficient knowledge, skills, and/or abilities to meet a need such as effective job performance. Boyatzis' (1982) performed a comprehensive study of over 2000 managers and identified and assessed over a hundred potential competencies. Other theorists have presented models of leadership and management that reveal general agreement with Boyatzis' (1982) configuration (Locke et al. 1991; Yukl, 1989).
Entrepreneurship competency studies (Chandler & Jansen, 1992; Herron & Robinson, 1990) developed skill/ability clusters that are similar to those found in management/leadership theory; however, two additional skills appeared: 1) opportunity, and 2) self-management. Based upon these studies, I formed the array of nine entrepreneurship competencies that appear in Table 1: knowledge, cognitive ability, self-management, administration, human resource, decision skill, leadership, opportunity recognition, and opportunity development.
Many participants suggested that human relations and administration practices are embedded in leadership in their intimate companies; thus, I combined these competencies as "organization skill". Cognitive ability was not discussed, although it was tested in the questionnaire. Although self-management competency received support from most interviewees, most felt that it was difficult to measure accurately. To maintain construct simplicity, I combined the skills of finding and implementing opportunities into one concept, opportunity skill. The interviewees discussed knowledge competency, a specific ability or skill, in terms of technical skill and industry experience. The two variables received enthusiastic support, so they were separated for analysis.
Proposition 2: Competencies: cognitive ability, organization skill, decision skill, opportunity skill, industry experience, and technical skill will have significant positive relationships with venture growth.
Motivation refers to factors within an individual, other than knowledge, which energize, direct, and sustain behavior (Locke & Latham, 1990). Entrepreneurial motivation is manifested in the entrepreneur's vision and goals, and it bears upon planning and behavior (Bird, 1989).
Vision is the motivation dimension that refers to a cognitive structure or image of a desired future state. Management, leadership, and entrepreneurship theorists make frequent mention of the importance of vision for business success (Bennis & Nanus, 1985; Collins & Lazier, 1992; Filion, 1991); however, little empirical research exists. Social cognitive theory's concept of self-efficacy has demonstrated strong associations with performance (Bandura, 1986). Goal theory, which suggests that specific challenging goals lead to high performance (Locke & Latham, 1990), has demonstrated more scientific validity than any other motivation theory and has the greatest scope (Landy & Becker, 1987). Entrepreneurship researchers cite goal theory as a possible explanation for entrepreneurial behavior (Gartner, Bird, and Starr (1992). Thus, vision, self-efficacy, and growth-goal setting appear as likely venture growth-related variables in Table 1.
The interview discussions about business vision exposed a general awareness of the concept andstrong general support for its value as a management tool. Although the interviewees were not as confident about their goal-setting views as they were about vision-setting, there was universal support for the notion that specific challenging personal goals enhance company performance. Ten (10) interviewees practiced formal goal-setting with performance feedback for employees. Self-efficacy was strongly supported with responses to the question, "Is it important to believe that you have the skill and drive to make your current goal?".
Proposition 3: Motivation variables: vision, self-efficacy, and growth goal-setting will have significant positive relationships with venture growth.
Business strategies are the plans for achievement of overarching and operating level goals. They consist of intended operating and marketing scope, plans for application of resources, plans for development of competitive advantage, and the interrelation of all three (Porter, 1980). As shown in Table 1, I used dimensions from Miles and Snow's (1978) strategy typology as the basis for the strategy variables because the typology is defined in terms of continuous, internally consistent dimensions that appear in the archetypical entrepreneur role (Bird, 1989). Four of the dimensions are: 1) market domain (product, customer, and geographic market stability and breadth), 2) product and marketing response to opportunity, 3) production flexibility (high flexibility vs. mechanized efficiency [low cost]), and 4) production focus (innovation of product and market). Consistent with the practice of entrepreneurship researchers, I included investment level among the business strategies that may relate with venture growth (Kunkel & Hofer, 1993).
Excepting "challenging projects", the strategy dimensions received support from the entrepreneurs as concepts that were important for venture growth. Market domain was dropped as a study concept because the interviewees had difficulty comparing the stability and breadth of their competitors' market with their own. Miles and Snow's (1978) "product and marketing response to opportunity" was renamed "innovation" consistent with suggestions made during the interviews. The entrepreneurs felt that "production flexibility" and "production focus" were not distinct, so the concepts were combined and identified as "production focus". The interviewee responses to questions about innovation and production focus were similar, thus the variables were combined as "innovation/production focus". The interviewees suggested that high price, high quality, and exceptional service normally appear together as a strategy and this was included as a study variable. Personal marketing, the strategy that includes heroic efforts to be in touch with significant customers, was strongly supported.
Proposition 4: Strategies: innovation/production focus, price/quality/service, and personal marketing will have significant positive relationships with venture growth.
Organization structure encompasses the lines of authority, channels of communication, and the information that flows within a firm (Chandler, 1962). Miles and Snow (1978) found that "formalization of planning and communication" and "centralization of authority" were distinct organizational structure continua (part of the "administrative problem"); thus, "formalization" and "vertical distance" were included as variables that probably relate with venture growth.
The interviewees felt that both organization structure variables were probably important for venture growth, but there was disagreement about the direction of the force. Some interviewees claimed that formal, tightly controlled companies can grow faster because no time is wasted reaching consensus. However, more interviewees felt that highly formal firms with great vertical distance would grow more slowly because customers would not be served well. I follow the more popular view.
Proposition 5: Organization Structure: formalization and vertical distance will have significant negative relationships with venture growth.
Local Industry Structure
Industry structure refers to industry level market characteristics such as product differentiation, barriers to entry, number of buyers and sellers, cost structures, and the degree of vertical integration. Industry forces have been shown to distinguish industries and to have pervasive affects upon individual firms across industries (Yasai-Ardekani, 1986). Sandberg (1986) and Kunkel and Hofer (1993) have found industry structure to be an important determinant of entrepreneurship performance. Although I studied a single industry, its competitive behavior was fragmented regionally. Thus, I included two variables that indicate local industry structure (local market concentration and relative supplier, customer, and competitor power).
In general, the interviewees felt that local industry structure was important for growth of individual firms; however, they felt that local industry characteristics affect profits more than growth. A typical view was that when a few large firms dominate a market, cooperation will enable higher prices and profits; smaller firms may be able to grow more quickly. Arguments were made for the opposite view; however, I propose that:
Proposition 6: Local industry structure: local industry concentration and local industry participant size will have positive relationships with venture growth.
In addition to the control afforded by studying a single industry, I controlled for organization size. Hundreds of studies have shown that size is an important determinant of organization process (Pugh, Hickson, Hinings & Turner, 1968).
Relationships Among Performance Concepts
Possible mediation paths among entrepreneurship performance antecedent categories exist. Theorists' propositions and my intuition guided the configuration of exploratory mediation paths shown on and below the diagonal in Figure 2.
The limited success that entrepreneur personality researchers have had may be explained by analysis of mediation paths through competencies, motivation, strategy, and structure. Indeed, Boyatzis (1982) suggested that personality is manifested in knowledge, skill, and ability, and Locke and Latham (1990) suggest that goals mediate traits and performance. Bird (1989), in her discussion of strategic vision and goals, suggested that vision and goals are an integration of personality and entrepreneurial ability. Taken together, there is reason to explore a permutation of mediation paths from traits.
The path from competencies to motivation is consistent with Bandura's (1986) suggestion that self-efficacy is affected by experience and skills. The paths from competencies to strategy rest upon the intuitive notion that ability affects thinking and action. A path from motivation to strategy is included. This is consistent with goal theory's position that task strategy is a mediator of the goal to performance relation (Locke & Latham, 1990), and Bandura's (1986) assertion that motivation is a codeterminant (with environment) of behavior (strategic behavior). Additionally, entrepreneurship theorists have posited that business vision affects strategy (Bird, 1989; Filion, 1991). A bidirectional path is shown between strategy and local industry structure to reflect a portion of the interaction findings of Sandberg and Hofer (1987), and McDougall, Robinson, and DeNisi (1992).
Field Study Participants
The survey population was all of the CEOs of architectural woodwork companies (849). The industry manufactures wood products for high-end residential, commercial, and industrial buildings (part of SIC 2431); it is fragmented and turbulent. Three-hundred seventy-four (374) CEOs (44%) and 189 associates participated.
The questionnaire contained six sections: (1) self-reported demographic data, (2) self-reported personal and industry practice information, (3) decision choices among alternate solutions to three industry specific scenarios, (4) self-reported individual difference data, (5) ability test responses, and (6) sales, employment, and profit information for 1990 to 1993.
Table 2 on the next page shows the 22 variables that were selected and summarizes the measures of each that were employed in the questionnaire. Cognitive ability was measured with a 19 question test. Respondents' vision statements were evaluated by two experts for brevity, clarity, degree of abstraction, challenge, future orientation, and reference to product, market and strategy. Following the advice of Chandler and Hanks (1993) about performance reporting format, four years of data were collected. Actual growth goals and self-efficacy about the goals were measured. All other antecedents were measured with 123 Likert response format statements, 10 point scales, or forced choice items.
Eleven-hundred (1100) items of missing data were completed with information from a credit service, phone communication with respondents, and PRELIS 2 imputation (Joreskog & Sorbom, 1993). Five cases of data were unusable. The data were transformed to polychoric correlation matrices to enable theoretically pure processing of ordinal, censored, and non-continuous data. The entire response set was used to establish statistical, internal and concept validity.
Compared with the population of 849 architectural woodworkers, the respondents' companies had representative size, location, and trade association status; given the large sample and sufficient response rate, I claimed that the sample was statistically valid. Common source bias was checked with LISREL confirmatory factor analysis by linking a common latent variable with all of the measures. The resultant coefficient, LAMBDA = .16 (t = .42, p <.05), indicated that common variance was less than 3%. Univariate homogeneity testing (PRELIS 2 HT) and LISREL multiple sample analysis (MSA) exposed the similarity of the reporting distributions of the CEOs and the associates. However, several privately held personal characteristics remain unverified (cognitive ability and self-efficacy). The CEOs with and without matching associates (MAs) exhibited significant univariate and multivariate similarity in 105 out of 117 measures. Performance data validity was established with tests of matching data from Dun and Bradstreet (1994). Taken together, the data appear to be internally valid.
LISREL second order factor analysis (CFA) was used to establish construct validity and to explore reconfiguration of measures, variables, and concepts. The initial configuration of measures produced a "poor" fit [X2 (5833) = 12455; p <.00; GFI = .65; AGFI =.60; PNFI = .57; RMSR = .084; RMSEA = .075]. Thus, I eliminated measures that had: 1) insignificant parameter coefficients and item reliabilities, 2) significant but low parameter coefficients and dissimilar MA and CEO distributions, and 3) dissimilar "CEOs with MAs" and "CEOs without MAs" distributions. Twenty-six of 110 items were eliminated. As shown in Table 2, 14 variables were measured with composite reliability > .70; the rest were >.60. Convergent validity was established since all surviving measure coefficients were significant (t > 2.0). Discriminant validity was established by checking each bivariate correlation (ETA matrix) between the latent variables for the difference from perfect correlation (p = 1.00) at .05 significance).
The final measurement model was tested and found to have acceptable reliability, convergence of measures, and divergence of variables. The reconfiguration produced an improved SOFA "fit" [X2 (3347) = 7866; p < .00; GRI = .85; AGFI = .81; PNFI = .54; RMSR = 0.88; RMSEA = .104] and demonstrated a significant explanation of the covariance structure of the data compared with the independence model. Validity was established at the concept level with similar analyses.
Three-hundred sixty-three respondents qualified as "entrepreneurs". They controlled more than 50% of their company stock, devoted more than 40 hours per week to their business, reported that they had intended to "grow" their businesses sometime since founding, and had managed their businesses for less than 12 years.
LISREL 8 structural equation (SE) analysis was used to evaluate the direct relationships among the 21 variables and venture growth. The fit statistics show that the model was useful: X2 (3128) = 6921; p < .00; GRI = .87; AGFI = .82; PNFI = .54; RMSR = 0.088; RMSEA = .092. The coefficients are shown in Table 2; self-efficacy, technical skill, personal marketing, innovation/production focus, and passion for work had the strongest direct positive relationships with venture growth. Vision, organization skill, growth goals, opportunity skill, industry experience, and participant size had significant, but less powerful, positive relationships. Vertical distance and local industry concentration had significant negative relations with venture growth. Tenacity, money-seeking, status-seeking, positive affectivity, cognitive ability, and decision skill were personal characteristics that did not have significant direct relations with venture growth. Price/quality/service emphasis, formalization, and size were strategy, structure, and control variables that were not significant in the direct effects path model.
Propositions 3 and 4 were confirmed and partial support was found for propositions 1, 2, and 5. One of the "local industry structure" variables developed a significant coefficient that supported proposition 6, while a second developed a significant coefficient that did not provide support.
In pursuit of a simple view of the results of the study, I used confirmatory factor analysis (ETA model) to aggregate the forces of the 21 variables. The best configuration consisted of factors that were consistent with the concepts studied here except that competencies were better described as "specific" and "general". The fit statistics were: X2 (119) = 459; p < .00; GRI = .90; AGFI = .80; PNFI = .46; RMSR = 0.066; RMSEA = .080. The variable to concept coefficients are shown in Table 2. Organization skill and decision skill did not enter the configuration of the array of concepts.
Using exploratory structural equation analysis of the multiple paths among the 7 concepts and between the concepts and venture growth, I found that the mediation configuration that is shown in Figure 2 produced an excellent fit: [X2 (173) = 396; p < .00; GRI = .94; AGFI = .90; PNFI = .76; RMSR = 0.066; RMSEA = .080]; only significant paths are shown. The concept to venture growth coefficients are shown in Table 2. Specific competencies, motivation, and business strategies had strong positive relationships with venture growth. Organization structure had significant negative relations. While traits, general competencies, and local industry structure did not have significant direct relations, they were all mediated strongly so that they had important indirect effects. As shown in Table 2, when direct and indirect effects are combined, all concepts exhibit significant relationships with venture growth.
DISCUSSION AND CONCLUSION
My findings suggest that contemporary entrepreneurship performance models can be opera-tionalized successfully with an array of personal, organizational, and industry variables from diverse research domains. My exploration of relationships among second order factors formed from 22 variables confirmed that a mediation configuration fit the data best. Thus, it appears that explanations of entrepreneurship performance that deal with only a few antecedent concepts are not sufficient; concepts from many domains of research combine to cause organization outcomes.
While it appears that a few personal variables are direct antecedents of venture growth (passion for work, organization and opportunity skill), most general traits and competencies operate through more specific concepts. The powerful concepts in my study were specific competencies, specific business strategies, and growth-specific motivation. This finding may help explain why entrepreneurship researchers were unable to show consistently significant relations between general traits and performance.
The study found significant direct relationships with venture growth for motivation variables (vision-setting, goal-setting, and self-efficacy); these variables have appeared rarely in entrepreneurship research; however, they may assist our understanding of venture performance. Similarly, traits that were seldom studied (tenacity, positive mood, status-seeking, and passion-for-work) produced significant total effects; they may be useful variables in future studies.
I found empirical support for the view that industry structure, organization structure, and business strategy are related. Specific strategies such as "continuous production innovation" and "persistent personal marketing" related directly with venture growth, but important indirect paths through organization structural variables existed. While local industry structure did not appear as a direct determinant of venture growth, it had significant total effects through business strategy and organization structure.
LISREL 8 and its preprocessor PRELIS 2 were used extensively as the statistical research tool. The results expose their ability to transform ordinal and non-normal continuous data and to analyze complex relations among many variables that are measured with large samples of data. Researchers have no need to compromise the treatment of ordinal and censored variables, to work with biased fit functions, to limit the number of variables, or to simplify the conceptualization of measurement, indicator, or reflection error. Thus, this study adds to the growing body of empirical research that demonstrates the versatility of LISREL analysis.
The concurrent correlation design of this study is an important limitation. Causality cannot be proven, although structural equation interpretations of causal models can be supported with concurrent data. A single industry was studied to eliminate the diverse effects that externalities (economic conditions, and zeitgeist) have upon different industries (Brush & Vanderwerf, 1992). However, effects observed in one industry may not generalize to oal research tool. The results expose their ability to transform ordinal and non-normal continuous data and to analyze complex relations among many variables that are measured with large samples of data. Researchers have no need to compromise the treatment of ordinal and censored variables, to work with biased fit functions, to limit the number of variables, or to simplify the conceptualization of measurement, indicator, or reflection error. Thus, this study adds to the growing body of empirical research that demonstrates the versatility of LISREL analysis.
The concurrent correlation design of this study is an important limitation. Causality cannot be proven, although structural equation interpretations of causal models can be supported with concurrent data. A single industry was studied to eliminate the diverse effects that externalities (economic conditions, and zeitgeist) have upon different industries (Brush & Vanderwerf, 1992). However, effects observed in one industry may not generalize to others.
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