Vol. 7(16), pp. 1522-1535, 28 April, 2013

DOI: 10.5897/AJBM12.1366 ISSN 1993-8233 © 2013 Academic Journals

http://www.academicjournals.org/AJBM

African Journal of Business Management

Full Length Research Paper

Strategic management practices and corporate entrepreneurship: A cluster analysis of financial and business services firms in South Africa

McEdward Murimbika and Boris Urban*

Graduate School of Business, University of the Witwatersrand, 2 St Davids Place, Parktown, Johannesburg, South Africa. 2196

Accepted 24 April, 2013

As emerging economies become more market-based, it is necessary for reformed enterprises to undergo an entrepreneurial transformation at the organizational level in order to adapt to the transitioning institutional environment and maintain competitiveness in both local and global markets. This study combines the research domains of strategic management and corporate innovation by examining the impact of strategic management practices on entrepreneurial orientation (EO). Recognizing the importance of internal business processes that enable firm entrepreneurial behavior, it is hypothesized that higher levels of EO are positively associated with the strategic management practices of (1) locus of planning, (2) scanning intensity, (3) planning flexibility, (4) planning horizon, and (5) strategy and financial control attributes. Cluster analyses and empirical testing take place in an African emerging market context on a sample of 219 financial and business services firms. The results provide support for the positive impact that the different strategic management practices have on EO. A practical consideration is for mangers to leverage the strategic management practices so that the firm’s position on the conservative-entrepreneurial continuum is increased by its propensity to be innovative, proactive, and be willing to take risks when confronted by uncertainty. Key words: Entrepreneurial orientation, strategic management, scanning, planning, controls.

INTRODUCTION Organizations are continually seeking to re-orientate themselves to become strategically innovative where pre-vious literature and empirical findings point to corporate innovation as an important element in organizational renewal and economic development (Ucbasaran et al., 2009). One major characteristic of firms in emerging markets is that established firms are being transformed into market-oriented enterprises. As the economy is becoming more market-based, it is necessary for these

reformed enterprises to undergo an entrepreneurial transformation at the organizational level in order to adapt to the transitioning institutional environment and maintain competitiveness in both local and global markets (Ghorbani et al., 2012; Peng, 2003).

Since innovation is essential for economic develop-ment, a theory of economic development requires not simply a ‘theory of the firm’ but a ‘theory of the innovating firm’ (Lazonick, 2008). It is through the interaction of the

*Corresponding author. E-mail: boris.urban@wits.ac.za. Tel: +27 11 717 3762.

innovative enterprise and the developmental state that entrepreneurial activity inserts itself into the economic system to contribute to the process of economic development. However, most research on the innovating firm has concentrated on developed market economies, despite that the emerging economies are growing at a rate comparably better than the developed economies. An estimated 40% of the global economy is now situated in the emerging economies especially in the BRIC (Brazil, Russia, India, and China) nations. South Africa which remains a highly significant regional, political and economic player in sub-Saharan Africa (SSA) has recently acceded to the BRIC cooperation mechanism, reflecting its growing international influence (Carmody, 2012).

The present business environment is filled with many contradictions (Phelps, 2009) where the dominant logic (Bettis and Prahalad, 1995) of a firm previously considered optimal may well be inappropriate. One way of creating a dynamic dominant logic is to make entrepreneurship the basis upon which the organization is conceptualized (Morris et al., 2008). Entrepreneurship and its relationship with strategy is studied extensively within organizations and has been conceptualized as a fundamental posture, instrumentally important to strategic innovation, particularly under shifting external environ-mental conditions (Ireland and Webb, 2007; Knight, 1997; Schweitzer et al., 2011).

Recent years have seen considerable work at the inter-face between entrepreneurship and strategy (Latham, 2009; Meyer and Heppard, 2000; Newbert et al., 2007). All of these studies address entrepreneurial behaviors that are strategic, yet their definitional differences are subject to debate, and the relationships among them remain unspecified (Schindehutte and Morris, 2009; Turkay et al., 2012). Despite these definitional contro-versies what emerges is that the integration of entrepre-neurship with strategy relies on the critical aspects of entrepreneurial strategy and a strategy for entrepre-neurship (Kuratko and Audretsch, 2009; Morris et al., 2008). Furthermore, a growing body of literature demon-strates that a sustainable competitive advantage and wealth creation are at the core of both entrepreneurship and strategic management (Ireland, 2007; Jiao and Robinson, 2011; Morris and Kuratko, 2002; Venkatraman and Sarasvathy, 2001).

Research reveals there is a growing focus on the nexus between strategic management practices, corporate entrepreneurship, innovation orientation and entrepre-neurial orientation (EO) of a firm (Covin et al., 2006; Dobny, 2010; Hitt et al., 2001; Ireland et al., 2009; Morris et al., 2008), with linkages between entrepreneurship; and strategic firm level practices and outcomes are increasingly corroborated in several studies (Covin et al., 2006; Kuratko and Audretsch, 2009). EO is concep-tualized as organizational-level making methods applied

Murimbika and Urban 1523 by business leaders in pursuit of proactiveness, innova-tiveness and risk-taking propensity (Covin and Slevin, 1986, 1989, 1991; Khandwalla, 1977; Miller, 1983).

Although the literature suggests that entrepreneurship and strategic management constructs relate to one another in many conceptual ways, firms that concentrate on either competitiveness (strategy) or opportunity generation (entrepreneurship) to the exclusion of the other leads to the increased probability of firm stagnation, decline, and ineffectiveness and possible complete failure (Hitt et al., 2001). This means that firms need to look inward for strategic opportunities (Rodríguez-Ponce and Pedraja-Rejas, 2012) and adopt strategic management practices that promote an entrepreneurial posture that simultaneously captures existing organizational com-petitive advantages while at the same time explore future needs that will ensure sustainable competitiveness. Literature supports the notion that central to an organi-zational entrepreneurial posture is the organization’s ability to be innovative, proactive and undertake risk-taking behavior which are all potentially affected by its strategic management practices (Berghman, 2012; Ireland et al., (2007); Covin and Kuratko, 2008; Lumpkin and Dess, 2005).

Despite the positive shifts acknowledging the interrelatedness between strategy and entrepreneurship, there is a noticeable dearth of empirical research that specifically combines strategic management and EO, which focuses deliberately on strategic management practices (Ireland et al., 2003; Wiklund and Shepherd, 2005), particularly in an emerging market context. Under-standing of emerging markets is rather fragmented with existing entrepreneurship research focusing almost exclusively on North American and European contexts. In fact, a systematic review of seven top international entrepreneurship journals reveals that less than half of one per cent of the articles from 1990 to 2006 addressed entrepreneurship in emerging markets (Bruton et al., 2008). It has been shown in other domains, such as strategy, that researchers should not assume that findings in a developed economy will be equally appli-cable to an emerging economy (Burton et al., 2008; Peng, 2003). Clearly there is a need to develop an understanding of these strategic entrepreneurship differences and their impacts.

Investigating the impact of strategic management practices on EO is important in understanding how firms promote sustainable growth and build a competitive advantage in a globalized hypercompetitive and dynamic environment (Brown and Eisenhardt, 2000; Sirmon et al., 2007). Building in this research direction the focus of this article is on the set of strategic management practices and organizational locations from which entrepreneurial behavior and processes may emerge (Smith et al., 2008; Zahra et al., 1999). While several firms may be entrepreneurial in one or a few respects, few are

1524 Afr. J. Bus. Manage. entrepreneurial throughout the spectrum (Morris et al., 2008). Recognizing the importance of internal business processes that enable entrepreneurial behavior (Covin and Slevin, 1991), the paper is designed to explain higher levels of EO as a result of the impact of the strategic management practices of (1) locus of planning, (2) scanning intensity, (3) planning flexibility, (4) planning horizon, and (5) strategy and financial control attributes.

This study has important academic, practitioner and policy implications as it assists in understanding how much emphasis is placed on entrepreneurial activities by successful firms in an emerging market and what strategic management practices are best implemented to achieve increased levels of EO. Firm entrepreneurial orientation and strategic management At the level of the business enterprise, the collective character of the innovation process reflects the reliance of the entrepreneur on the skills and efforts of other enterprise participants in the exercise of strategic control, the management of organizational integration, and the mobilization of financial commitment. Consequently, cor-porate entrepreneurship (CE), as an internal organiza-tional transformation and resource configuration mecha-nism, is a very important mediator that determines whether firms can realize the benefits derived from different resources and capital (Yiu and Lau, 2008).

There is growing literature that attempts to link the strategic management and entrepreneurship constructs (Covin et al., 2006; Dess et al., 2003; Wang, 2008), where some researchers (Meyer and Heppard, 2000) argue that the two constructs are inseparable; while others (McGrath and MacMillan, 2000) argue that strategists must exploit an entrepreneurial mind-set to sense opportunities, mobilize resources, and act to exploit opportunities.

Covin and Kuratko (2008) discuss strategic entrepre-neurship within the realm of CE, where strategic entre-preneurship is conceptualized as the integration of entre-preneurial (opportunity-seeking behavior) and strategic (advantage-seeking behavior) perspectives in developing and taking actions designed to create wealth. Additionally, strategic entrepreneurship has been conceptualized as a value-creating union in which a balance is sought between exploration and exploitation (Ireland et al., 2003), and which centers on the notion of an opportunity space and a paradigm built around forms, flows, and functions. Companies engaging in some level of entre-preneurial activity do not always integrate those activities into their core strategies. While corporate venturing entails company’s involvement in the creation of new business, strategic entrepreneurship corresponds to a broader array of entrepreneurial initiatives, which involve

organizational consequential innovations adopted to pursue competitive advantage (Morris et al., 2008).

The success of an entrepreneurship strategy is more probable when a firm has the skills required to structure (accumulate and strategically divest), bundle (success-fully combine), and advantage (mobilize and deploy) its resources (Sirmon et al., 2007). This would indicate that there are many different routes to achieve high entre-preneurial performance. One such route, where entrepre-neurship is manifested across the organization by implementing a particular strategy is entrepreneurial orientation (EO).

Research provides theoretical support for the EO construct, in both the fields of entrepreneurship and strategic management (Marino et al., 2002). Extensive research confirms the three dimensions of EO, as innovativeness, risk taking, and proactiveness (Lumpkin and Dess, 1996; Covin and Slevin, 1989, 1991). These dimensions have been extensively documented, and according to Lumpkin and Dess (1996), all the dimensions are central to understanding the entre-preneurial process, although they may occur in different combinations, depending on type of entrepreneurial opportunity the firm pursues. Covin et al. (2006) configure EO as a formative construct and propose that as a construct EO cannot be decomposed into its constituent elements, that is firms can only be labeled as entre-preneurial if they simultaneously exhibit risk taking, innovativeness, and proactiveness.

Links between EO and strategic management prove the direct effect of EO on strategic learning capability, and mediating effects for structural organicity, market responsiveness, and strategy formation (Anderson et al., 2009). Considering the vast literature and empirical evidence on EO, the point of view is adopted which relies on a firm’s behavior perspective to understand entre-preneurship and that firm-level behavior that can be managed by the creation of appropriate strategic practices (Sirmon et al., 2007).

Studies focused on explaining strategic and organi-zational processes that expedite entrepreneurial behavior (Guth and Ginsburg, 1990; Wiklund and Shepherd, 2005) have revealed five dimensions of strategic management practices as the most relevant to create and encourage an EO. These dimensions are scanning intensity, locus of planning, planning flexibility, planning horizon and control attributes (Barringer and Bluedorn, 1999). The dimensions are based on extant literature and theories which include the resource-based view (RBV), the knowledge based view (KBV) and the organizational learning (OL) pers-pective.

Consistent with the strategic entrepreneurship concept (Ireland et al., 2003; Ireland and Webb, 2007), it is argued that firms with higher levels of EO would reflect consistent behavior required to enact an entrepreneur-ship strategy as captured through the above mentioned

strategic management practices. Building on past research and in line with theoretical underpinnings, each of the strategic management dimensions are scrutinized and hypothesized to have a positive influence on EO.

Environmental scanning intensity

Environmental scanning intensity denotes organizational preparedness to manage risk and to be proactive. Strategic competence and intensity in environmental scanning would insure that managers deploy the right kind of knowledge and resources to cope with uncertainty better than competitors (Alvarez and Barney, 2005). Consequently, scanning is an essential strategic planning activity undertaken by managers to effectively steer their organizations towards sustainable competitive advantage in a fast-changing environment (Pacheco-de-Almeida and Zemsky, 2007). The importance of environmental scanning intensity, particularly the need for managers to have current and reliable strategic information required to recognize and exploit opportunities as well as the need to cope with uncertainty and be proactive, leads to the first hypothesis.

Hypothesis 1: Strategic environmental scanning intensity will be positively related to higher levels of EO.

Locus of planning

A deep locus of planning indicates organization-wide, high level of employee involvement, while a shallow locus of planning denotes exclusivity in the strategic planning process. Deep locus of planning is best exhibited through an organizational culture of participative management (Barney, 1986; Whetten and Cameron, 2002). Studies have shown that a significant number of companies have attributed their improvements in performance directly to the institution of participative management and teams in the workplace (Cohen and Bailey, 1997). Furthermore, in today’s complex business environment, deep locus of planning is essential for organizations confronting turbulence and dynamism (Antoncic and Hisrich, 2004; Urban, 2010). A deep locus of planning allows for key strategic concerns to emerge and gain formal recognition in an environment where the organization is an open market for innovation and risk-taking (Morris et al., 2008). Based on these theoretical underpinnings, the second hypothesis proposes that:

Hypothesis 2: Deep strategic locus of planning will be positively related to higher levels of EO.

Planning flexibility

Entrepreneurship and strategic management studies

Murimbika and Urban 1525 have successfully demonstrated the link between plan-ning flexibility and improved competitiveness (Wiklund and Shepherd, 2005). Planning flexibility enables entre-preneurial organizations to fine-tune their plans in real time in response to changing environmental challenges and adjust to take advantage of existing and emerging strategic opportunities. A high degree of planning flexi-bility allows an organization to be strategically responsive to environmental adjustments thereby allowing oppor-tunity recognition and exploitation in pursuit of a sus-tainable competitive advantage. The need for strategic planning flexibility in entrepreneurial organizations leads to the third hypothesis. Hypothesis 3: Strategic management flexibility will be positively related to higher levels of EO. Planning horizon An organization’s planning horizon is the length of the time that managers consider in future planning (Das, 1987). It is imperative that organizations would have a portfolio of plans with horizons relative to short-term and long-term strategies running concurrently (Capon et al., 1987). Short horizons (less than five years) are presumably ideal for entrepreneurial organizations com-peting in a turbulent hypercompetitive environment where product and services cycles are characteristically short. A short planning horizon combined with intensive environ-mental scanning and a high degree of organizational planning flexibility creates a fertile ground for an entrepreneurial organization to be responsive to oppor-tunities emerging from environmental changes and develop appropriate product and service innovations to sustain competitiveness. The fourth hypothesis reflects a relationship where it is expected that: Hypothesis 4: A short-term strategic management planning horizon (less than five years) will be positively related to higher levels of EO. Control attributes Both strategic and financial controls can be present simultaneously in an organization (Barringer and Bluedorn, 1999), yet they can have different influences on organizational innovation practices. Entrepreneurial organizations that reward creativity encourage proactive-ness and do not punish failure should have controls consistent with such practices (Morris et al., 2008). Here controls are consistent with the entrepreneurial process, which relies on viable innovation where time lag between innovation payoffs is not a limiting factor to employees especially those involved in product or process innovation

1526 Afr. J. Bus. Manage. that takes a long time to reach their market (Goold and Campbell, 1994). Therefore, indicators such as market share, customer retention, firm reputation, corporate social responsibility, customer satisfaction, patent registration, and attaining quality control targets are all valid measures of performance from a strategic control (non-financial) perspective of an entrepreneurial firm (Antoncic and Hisrich, 2003). Accordingly, a hypothesis is formulated which captures the strategic nature of control in relation to EO. Hypothesis 5a: A higher degree of emphasis on strategic controls will be positively related to higher levels of EO. Financial controls are probably the most common form of performance measurement across all business organi-zations. Theoretically, financial control attributes measure firms’ performance in terms of objective indicators such as returns on assets (ROA), and return on investment (ROI), etc. However, high degrees of financial control are congruent with competencies most valued primarily in conservative organizations. The sole use of financial controls is biased towards short-term profitability at the expense of long-term growth (Hitt et al., 2000, 2001). It follows, therefore, that for entrepreneurial organizations, if strategic practices such as long-term planning and planning flexibility are organic and more responsive to a hypercompetitive environment, performance measures should also be adjustable to support the organization’s planning process. To ensure that financial controls are conducive towards fostering EO, additional indicators are included in this study measuring not only importance of financial controls but also satisfaction with financial controls (Johnson et al., 1993). Consequently, the concern with financial control included a multiplicative formula where the degree of importance and satisfaction with objective financial controls is evaluated in relation to EO. This observation leads to the following and final hypothesis of this study.

Hypothesis 5b: A higher degree of importance and level of satisfaction with financial controls will be positively related to higher levels of EO. Conceptual development

Based on the aforementioned theoretical perspectives, a conceptual model is developed which displays the hypothesized links between the study variables (Figure 1).

Additional variables are included in this model as moderating and control variables based on past findings indicating the importance of their inclusion. First in terms of the business environment, three characteristics of the firm’s external environment are included which are

discussed extensively in the literature: dynamism, hostility, and heterogeneity. Theory on the environment and its effect on firms and their competitive strategies is well documented (Allen and Stearns, 2004; Preece et al., 1998; Uzkurt et al., 2012; Zahra and Bogner, 1999), where all three environmental dimensions are important for EO when considering: (a) the rate of change in industry life cycles, new products, and technology and customer preferences which have increased expo-nentially; (b) industrial boundaries which are blurring as industries converge or overlap; (c) competitive advantage depends on identifying new and emerging opportunities in the marketplace where traditional strategic thinking based on stable industries has long ceased to be as effective (Ireland and Hitt, 1999).

Secondly, business demographics were included in the model where indicators such as firms’ age has been reported to influence EO, for instance older firms are more bureaucratic and therefore less entrepreneurially oriented (Zahra, 1991). The same argument applies to a firm’s size where larger organizations respond differently to competitive environment given their assumed slow-ness (Durand and Courderoy, 2001). Moreover, the sub-industry classification in which a firm operates potentially influences and shapes its environment and therefore levels of EO (Covin and Slevin, 1991).

It must also be noted that the relationship between entrepreneurship and firms’ performance has been the subject of considerable discussion and debate for several decades (Lumpkin and Dess, 1996; Wiklund and Shepherd, 2003). Most researchers report that there is a positive relationship between EO and firms’ profitability and growth (Covin and Slevin, 1991; Lumpkin and Dess, 1996). Although this study does not directly measure or analyze the effect of EO on firms’ performance (indicated as broken lines in the model), strategic and financial controls are accounted for since literature indicates that above-average returns and a sustainable competitive advantage are often achieved as a result of the functions and processes of strategic and financial controls (Keh et al., 2007; Wiklund and Shepard, 2005). RESEARCH DESIGN AND METHODS

Data collection and sampling characteristics

The study followed an explanatory design and used a quantitative approach. An online survey was administered to respondents at senior managerial levels, in a single industry. The context of the study is the South African financial and business services sector. By focusing on a single industry sector, a greater homogeneity of context is achieved which addresses the concerns of broad applicability versus perfect suitability for narrower groups. Studies across industries often produce results that apply to all while they at the same time apply to none (Davidsson, 2004), since they only capture a tiny fraction of each firms’ manifestation of EO. Consequently the focus was on a single industry.

Murimbika and Urban 1527

Figure 1. Conceptual model and hypotheses indicating the influence of strategic management practices and control variables on EO.

Moreover, considering the important issue about sampling, in general, is not statistical but theoretical representativeness, that is,

the elements in the sample represents the type of phenomenon that the theory makes statements about (Davidsson, 2004); a convenience sampling frame based on the financial and business services industry in the Gauteng Province was used. The financial and business services industrial sector as a unit of analysis is based on the Standard Industrial Classification (SIC) (Statistics South Africa, 2010), which classifies financial and business services sector as specializing in financial intermediation, insurance, real-estate activities, research and development and business services.

The financial services subsector consists of corporations including depository institutions, non-depository credit institutions, security and commodity brokers, dealers, exchange and services, insurance carriers, agents, brokers and services, holding and other investment houses. The business services subsectors consiss of commercial legal services, accounting, bookkeeping and auditing activities; tax consultancy; market research and public-opinion research; business and management consultancy firms (Govern-

ment of Republic of South Africa, 2010a, 2010b, 2010c; Johannesburg Securities Exchange, 2009).

Based on this SIC classification, the original sample of firms was derived from an independent research firm’s database where 1347 Gauteng-based heterogeneous non-diversified, medium to large financial and business services firms were surveyed (FTT, 2011). These firms were further cross-screened against other independent institutional databases and listings including the Institute of Directors Southern Africa database (FTT, 2011); the Johannesburg Stock Exchange Global Classification System Database (2009); databases of the Johannesburg Chamber of Commerce and Industry (2008) and the Gauteng Chambers of Commerce (2011);

and the database of the corporate Who Owns Whom in South Africa Pty. Ltd. (2011).

Although regarded as a micro-level unit, the firm is an aggregate of different individuals and business activities, and the issues of relevance, size, size distributions, and heterogeneity need to be mentioned (Davidsson, 2004); particular as these issues were treated as control variables in this study. To reduce the confounding effects of diversification, the study limited the firms in the sample to those that generate at least 70% of their turnover from a single subsector in the financial and business services industry. Furthermore, focusing on medium to large corporations eliminated

the predictable size-related biases on some of the research variables. For example, smaller businesses exhibit characteristics of emergent strategy-formation patterns (Mintzberg, 1973), which may not apply to established corporate organizations (Covin et al., 2006).

Based on the selection criteria, a total of 1121 qualifying firms were coded into a database where a random numbers program was applied to randomly select 25% of the firms as the final sample.

This multi stage screening yielded a sample of 280 firms. Respondents included individual senior, middle and low-level managers from these firms, where at least two participants, each from either low or middle or top management, per sampled firm were invited to participate in the electronic survey. Responses from 219 firms out of the 280 sample firms were collected before the survey was closed.

Sample characteristics revealed that 33.5% (73) of firms were less than 15 years old and 66.5% (145) were more than 15 years old. The age distribution of the firms was skewed to the high end of the scale (older firms), which pulled the overall mean age to 33.8 years. Firm size, as operationalised through annual sales/income,

1528 Afr. J. Bus. Manage. revealed that 35.6% (78) of the firms were medium corporations (earning R5 million – R34, 999,999.00 annual income) and 64.4% (141) were large corporations (earning R35 million and above

annual income). The firms were also grouped into either the business (32.9%) or financial services (67.1%) sub-industry sectors. Scale development and measures The survey instrument sought to measure respondent’s attitudes and understanding of their organizational strategic management practices and levels of EO. As hypothetical constructs, attitude scales adapted for this study attempt to determine what individual respondents believe, perceive or feel about the scales on EO and strategic management practices of their respective firms. Attitude scales are suitable because they are effectively applicable toward self, others and a variety of other activities such as institutions, and situations relevant to strategic management practices and firm’s EO (Bouma and Atkinson, 1995).

The survey instrument carried three primary question typologies

and scales of measure. The dependent variable (EO) and the independent variables (strategic management practices and controls) were derived from and are supported by, a significant amount of literature. Table 1 indicates how the constructs were operationalised and measured. Scale validity and reliability

The survey instrument contained multi-items with overlapping measurement characteristics and exploratory factor analysis (EFA) was used to examine the factor structure and dimensionality of entrepreneurial orientation (innovativeness, risk-taking, proactive-ness), scanning intensity, locus of planning, planning flexibility, planning horizon, strategic control, financial control, and environ-mental uncertainty (turbulence, hostility, dynamism).

Principal component analysis yielded eight principle components with eigenvalue scores ranging between 13.15 to 1.14. The extraction of maximum likelihood factors further reduced the underlying factors with significant loadings to six. These emergent factors revealed significant interpretability and showed conceptual alignment to the theoretically derived constructs (Table 2). To test for reliability, Cronbach alphas (Cronbach, 1951) were calculated, which were all above 0.70 and average inter-item correlation coefficients ranged from 0.81 to0.91.

DATA ANALYSIS AND RESULTS

Acknowledging that EO in firms can be placed on a conceptual continuum of conservative firms (entrepre-neurship negative) on one side and entrepreneurial firms (entrepreneurship positive) on the other, cluster analysis was performed. Retaining only the significant factors with high loadings generated from factor analysis, research variables were computed by K-means analysis of variance from the standardized data set. Euclidean distance computation through STATISTICA established four distinct clusters (see Table 3) and the cluster means plots (not shown).

The sample data are gathered into four exclusive clusters (Table 4). The clusters were ranked and put through cluster comparison and validation. It emerged

that the similarities and distances between clusters relate to three key firm demographic factors: (i) age of firm [dichotomous classification of older /younger], (ii) firms’ size [dichotomous classification of large / medium], and (iii) firm’s sub industry [dichotomous classification of financial services / business services]. The cluster classifications are summarized in the stub-and-banner in Table 5. Reading from the characteristics of the clusters presented in Table 5, as anticipated, all firms with similar strategic and entrepreneurial dispositions clustered together. Analysis of characteristics of firms in each group allowed the researcher to name the cluster accor-ding to their position on the conceptual conservative-entrepreneurial continuum as: (1) Conservative; (2) Transitional; (3) Entrepreneurial; (4) Traditional. These exclusive clusters were also are expressed as a percentage of the total sample: (1) Conservative Firms (33.8%); (2) Transitional Firms (23.8%); (3) Entrepre-neurial Firms (29.8%); and Traditional Firms (12.6%). On the conceptual conservative-entrepreneurial continuum, traditional firms occupy the extreme entrepreneurship-negative end followed by conservative firms, while transitional firms were situated on the third spot followed on the other extreme end by entrepreneurial firms that exhibit entrepreneurship-positive characteristics.

Table 6 presents the EO statistical characteristics of each cluster. Cluster 1 (Conservative firms) showed typical conservative business organisational traits such as risk averse, low proactivity and low innovativeness (low entrepreneurship). Cluster 2 (Transitional firms) group exhibits conservative characteristics but with leaning towards entrepreneurial traits such as average innovativeness, risk-tolerance and proactiveness. Cluster 3 (Entrepreneurial firms) exhibits high entrepreneurial characteristics that support innovativeness, risk-taking and proactiveness. Cluster 4 (Traditional firms) grouped firms exhibit highest levels of risk avoidance, relative absence of innovativeness and reactive posture in their strategy management approach. The traditional firms also exhibit relatively low attention to organized strategic management approach, a key characteristic that sepa-rates them from the conservative cluster.

To make further sense of the clusters, analysis of variance (ANOVA) was conducted on the emergent clusters against the EO sub-dimensions and the EO variable (not shown), followed by a post hoc Scheffe’s test conducted on the cluster data to confirm the significance of the cluster group mean differences. The test results were significant at the p < 0.05 level, indicating that the differences in mean scores amongst all possible combinations of cluster categories differed significantly from one another (not shown).

To test the hypotheses correlations coefficients bet-ween the strategic management practices and EO were calculated across cluster groups (Table 7). Strategic scanning intensity was positively related to EO, producing

Murimbika and Urban 1529 Table 1. Research instrument scales and corresponding literature support.

Scale Description Literature support

EO [innovation, risk-taking and proactiveness scales] (9 items).

The EO scale collected data using nine items on the three sub-dimensions assessing a firm’s tendency toward innovation, degree of risk-taking, and proactiveness. The average of these ratings generated a mean score of EO index. The higher the index, the more the entrepreneurial the firm is on a conceptual conservative-entrepreneurial continuum. Respondents used a seven-point Likert scale, where 1= complete agreement with statement on left side of scale and 7 = complete agreement with statement on right side of scale.

Khandwalla (1977); Ginsberg (1985); Miller and Friesen (1983); Miller (1983); Covin and Slevin (1989); Knight, (1997); Lumpkin and Dess, (1996); Barringer and Bluedorn, (1999); Kreiser et al. (2002); Wiklund and Shepherd (2003, 2005).

Scanning intensity scale (10 items).

This scale measures the effort dedicated to environmental scanning and depth of the scanning process. A combined mean score of scanning effort and scanning frequency provides the overall scanning intensity index. The higher the index, the higher the perceived level of scanning intensity. This study used four post hoc variables to measure scanning intensity: (i) routine gathering of information, (ii) specialised scanning (iii) scanning effort variable, and (iv) overall scanning intensity. Responses were collected using the same seven-point Likert scale, as for EO.

Miller and Friesen (1982); Bhuian et al. (2005).

Locus of planning scale (15 items).

This scale measured the extent to which employees from different hierarchical levels are involved in strategic planning processes of goal formation, environmental scanning, strategy formulation, strategy implementation, and evaluation and control. By combining the subscale mean scores of distributed decision authority (5-items) and participation in decisions (5-items), a new hierarchical variable was established - authority participation. Similarly, for the subscale of locus of planning (5-items), a mean score represented the planning effort variable. Responses were collectedusing a seven-point Likert scale, similar to EO.

Miller (1983); Boyd and Reuning-Elliot (1998); Slater, Olson and Hult (2006); Anderson (2004).

Planning flexibility scale (9 items).

Planning flexibility refers to organizational capability to change and respond quickly to changing environmental conditions. The mean score, averaged across all nine items, was used to assess the degree of planning flexibility in the organization. The higher the score, the more flexible the strategic planning process. Responses were collectedusing a seven-point Likert scale, as in EO.

Barringer and Bluedorn (1999); Entrialgo et al. (2000); Hoskisson, et al. (2008).

Planning horizon scale

Planning horizon scale measures the future time that decision makers consider in strategic planning. An average score for each hierarchical level’s planning horizon was calculated for the board of directors, top, middle and low management planning horizons.The responses were further consolidated into dichotomous categories of below five years and more than five years planning horizons. Only the mean score of top management’s long planning horizon (above 5 years) was applied in further analysis. Respondents useda seven-point Likert scale, similar to EO.

Barringer and Bluedorn (1999); Hoskisson et al. (2008).

Strategic Control Scale

This scale measuredstrategic (nonfinancial) performance attributes. The average score of six items measuring strategic performance attributes determined the strategic control variable. Items were based on the following subjective strategic criteria: market share, reputation, internal communications and improvements in customer satisfaction. Respondents used a seven-point Likert scale, where 1= unimportant and 7 = important.

Hoskisson et al. (2008); Naman and Slevin (1993); Barringer and Bluedorn (1999).

1530 Afr. J. Bus. Manage. Table 1. Contd.

Financial control Scale

Respondents were asked to indicate: Importance of objective evaluation of performance; Satisfaction with objective evaluation of performance;

Importance x Satisfaction with objective evaluation of performance. Evaluation was based on the degree of importance of the following financial objective performance criteria: an objective measure of return on assets (ROA), return on investment (ROI), cash flow, operating profit and sales growth rate. These five items measuring objective financial performance attributes were averaged to obtain aconsolidatedfinancial controls variable.

Hoskisson et al. (2008); Naman and Slevin (1993); Barringer and Bluedorn (1999); Zahra (1996).

Environmental Uncertainty Scale (12 items).

Higher levels of turbulence, hostility, and dynamism create higher levels of uncertainty and unpredictability. Collectively these dimensions indicated the measure of environmental uncertainty, with 12 items using a 7-point Likert-type response format (1=strongly disagree, 4 = neutral and 7 = strongly agree).

Khandwalla (1977); Miller and Friesen (1983), (1984); Zahra (1991); Naman and Slevin (1993); Wiklund and Shepherd (2005).

Table 2. Eigenvalues extraction of six principal components and factor reliabilities.

Factor Eigen% Total value Cumulative % variance Cronbach’s Alpha

1Locus of planning 13.15 43.84 43.84 0.81

2. Strategic control 5.02 16.74 60.58 0.92

3. Planning flexibility/horizon 2.45 8.17 68.75 0.83

4. Environmental uncertainty 1.44 4.80 73.54 0.73

5. Financial control 1.18 3.95 77.49 0.87

6. Scanning intensity 1.14 3.79 81.28 0.91

Table 3. Euclidean distances in terms of firm entrepreneurial orientation.

Cluster No. 1 No. 2 No. 3 No. 4

Conservatives {1} 0.00 0.96 2.07 0.73

Transitional {2} 0.98 0.00 0.37 0.92

Entrepreneurial {3} 1.44 0.61 0.00 1.76

Traditional {4} 0.86 0.96 1.33 0.00

Note: Cluster distances are below-diagonal and squared distances are above-

diagonal.

Table 4. Frequency analysis of clusters identified.

Cluster category Count Cumulative count Per cent Cumulative per cent

1 51 51 33.77 33.77

2 36 87 23.84 57.62

3 45 132 29.80 87.42

4 19 151 12.58 100.00

Missing 0 151 0.00 100.00

significant correlation coefficients ranging from r = .0.60 to r = 0.75 (p < 0.05), and providing support for hypo-thesis 1. Locus of planning measuring distribution of

decision authority and participation in decisions produced positive and negative significant correlation coefficients (p< 0.05), ranging from r = 0.81 to r = -0.17, providing

Murimbika and Urban 1531

Table 5. Cluster frequencies and stub-and-banner summaries.

Factor Cluster 1 Cluster 2 Cluster 3 Cluster 4 Total

Firm category:

Firm large 6 5 6 4 21

Firm medium 2 2 2 2 8

Firm large younger 0 4 4 0 8

Firm medium younger 0 5 19* (42.2) 1 25

Firm large older 36* (70.6) 15

* (41.6) 9 7 67

Firm medium older 4 2 1 0 7

Firm large younger 2 0 0 3 5

Firm medium younger 1 3 4 2 10

Firm category: total 51 36 45 19 151

Age of firm:

Less than 15 years 3 12* (33.3) 27

* (60.0) 6 48

More than 15 years 48* (94.1) 24

*(66.7) 18

*(40.0) 13

*(68.4) 103

Age of firm: total 51 36 45 19 151

Size classification:

Large corporation 44* (86.3) 24

* (66.7) 19

* (42.2) 14

* (73.7) 101

Medium corporation 7 12* (33.3) 26

* (57.8) 5 50

Size classification: total 51 36 45 19 151

Sub-industry classification:

Business services 8 16* (44.4) 31

* (69.9) 7 62

Financial services 43* (84.3) 20

* (55.6) 14

* (31.1) 12

* (63.2) 89

Sub-industry classification: Total 51 36 45 19 151

Notes:*= Significant summaries with counts >10 and corresponding percentages in parenthesis.

Table 6. Descriptive statistics for entrepreneurial orientation sub-dimensions along each cluster group.

Cluster P* P* P* I* I* I* R* R* R* EO* EO* EO*

Mean N SD Mean N SD Mean N SD Mean N SD

1. Conservative 3.27 51 .88 3.22 51 .93 2.88 51 .97 3.17 51 .83

2. Transitional 5.23 36 1.11 4.85 36 1.47 5.19 36 1.62 5.10 36 1.00

3. Entrepreneurial 6.07 45 .68 6.16 45 .64 6.16 45 .76 6.12 45 .62

4. Traditional 4.26 19 1.25 4.30 19 1.14 3.95 19 1.43 4.20 19 1.02

All groups 4.70 151 1.49 4.62 151 1.58 4.54 151 1.79 4.64 151 1.47

Notes: N = 151 (no missing data in the dependent variable list for this analysis). *P = Proactiveness; *I = Innovativeness; *R = Risk-taking. *EO = Entrepreneurial Orientation.

partial support for hypothesis 2. Planning horizon and flexibility were positively related to EO, producing significant correlation coefficients ranging from r = .0.72 to r = 0.26 (p < 0.05), providing support for hypotheses 3 and 4. Strategic control was positively related to EO, producing a significant correlation coefficient (r = 0.78; p < 0.05), and providing support for hypothesis 5a. Financial control was negatively related to EO, producing a significant correlation coefficient of r = -0.43 (p < 0.05),

and providing support for hypothesis 5b. Additionally, performance variables were to some degree inter-correlated and produced significant coefficients with the dependent variable – EO. DISCUSSION AND CONCLUSION The study has contributed to a growing body of literature

1532 Afr. J. Bus. Manage.

Table 7. Correlation analysis for strategic management practices for all cluster groups in terms of entrepreneurial orientation.

Dimension Variable Correlation coefficient

Scanning intensity

Routine gathering of opinions .60

Total scanning intensity .75

Specialised scanning effort .74

Scanning frequency .74

Locus of planning

Distributed decision authority .77

Participation in Decisions .67

Goal formation phase -.56

Scanning the business environment phase -.22

Formation -.57

Implementation -.17

Strategy evaluation -.48

Authority participation .81

Planning effort .56

Decision power .82

Planning flexibility Planning flexibility .71

Planning horizon

Board of directors planning horizon .49

Top management planning horizon .72

Middle management planning horizon .32

Low level management planning horizon .26

Strategic control Strategy controls .78

Financial control Financial controls -.43

Performance Importance of overall evaluation of performance .16

Importance*Satisfaction with overall evaluation of performance .23

Performance strategy

Importance of Subjective evaluation of performance .71

Satisfaction with overall evaluation of performance .20

Satisfaction with Subjective evaluation of performance .51

Importance of satisfaction with subjective evaluation of performance .71

Financial performance

Satisfaction with objective evaluation of performance -.13

Importance of satisfaction with objective evaluation of performance -.35

Importance of objective evaluation of performance -.43

Notes: N=151 (Case wise deletion of missing data); All correlations are significant at the p < 0 .05 level.

which demonstrates that various strategic management practices are key to higher levels of EO (Kuratko and Audretsch, 2009). The empirical evidence emanating from this study provides support for the hypotheses formulated insofar a significant and positive relationship is observed between EO and the strategic management practices of locus of planning, scanning intensity, plan-ning flexibility, planning horizon, financial control, and strategy control attributes.

Based on the cluster analysis it is clear that four distinct categories emerge when analyzing EO and strategic management practices along the conservative-entrepre-neurial continuum. The significance of this observation

lies in the verification of the conservative-entrepreneurial continuum that consists of four, and not two, distinct exclusive clusters.

The results indicate that scanning intensity has a positive relationship with a firm’s EO, which is in line with existing findings (Morris et al., 2008) which demonstrate environmental scanning as one of the most important issues for managers because of today’s high rate of environmental change. These results translate into practices that require firms to aggressively scan their environments to understand key events and trends, and to reduce uncertainty in the local and global environment so as to be able to react to change quickly (Brorstrom,

2002).

The findings further indicate that a deep locus of plan-ning is significantly associated with higher levels of EO. Literature reports that a deep locus of planning is accredited for facilitating opportunity recognition, identi-fication, acquisition, and deployment of firm resource to take advantage of opportunities as they emerge in the environment (Hornsby et al., 2002). Moreover, planning flexibility is a prerequisite for managers who want to develop methods and programs to increase levels of EO in their firms. A flexible system coupled with intense environmental scanning allows strategic plans to remain up to date and organic, which will permit a firm’s entrepreneurial initiatives to be strategically formulated rather than be planned in an ad hoc manner outside the parameters of a strategic plan.

Building on the notion that controls in entrepreneurial organizations should reward creativity in pursuit of oppor-tunities through innovation and stimulate proactiveness and risk-taking, two forms of controls, strategic and financial controls were found to have a significant impact on EO. This finding resonates with previous research that finds these two types of controls attributes are not oppo-sites of each other, and can be present simultaneously in an organization, yet influence EO independently (Barringer and Bluedorn, 1999).

A practical insight is for management is to understand and leverage the firm’s strategic management practices in a manner that influences the firm’s position on the conservative-entrepreneurial continuum, as concep-tualized in this study. Strategic actions would include increasing the firm’s propensity to be innovative, proactive to marketplace opportunities, and be willing to take risks when confronted by uncertainty. Increasing EO requires developing new products or services, introducing new and more efficient processes and procedures, or simply creating added value for customers. The point is that innovativeness must be perceived as a strategic requisite to avoid organizational complacency and inertia.

A deep and thorough understanding of EO is important not only for academic purposes but also because the subject has salience for practitioners and policy makers. These implications relate to the profitability and competi-tiveness of the firm as well as to the overall economic performance of industry and the national economy. As part of government’s initiatives in emerging countries, which is often to foster innovation, policies should encourage the diffusion, adoption and application of the very latest technologies, often the cornerstones of innovation, since a lot of potential exists in emerging countries to import and adapt technologies developed in industrialized countries (von Broembsen et al., 2005).

Considering the context of the study, research in Africa as a whole may be considered as valuable, as very few empirical studies have been previously conducted which focus on EO and strategy. The importance of further

Murimbika and Urban 1533 interrogating EO in an emerging country context seems justifiable, since such investigations allow researchers to compare and examine different EO and strategy links which firms use in similar environmental contexts. There is a need for further theorization and empirical analysis of these different contexts. This type of research is impor-tant considering that a multi-country study finds that intrapreneurship and independent entrepreneurship seem to be substitutes at the macro level. Large firms in high income countries tend to display more entrepreneurial behavior than large firms in low income countries (Bosma et al., 2010).

This study has several limitations. The cross-sectional nature of the study prevents any causal relationship between strategic management variables and EO to be drawn. A longitudinal study is required to provide further insights and causal inferences into the relationship between strategic management practices and EO levels. The study relies on perceptual data where responses may have been influenced by perceptual biases and cognitive limitations. REFERENCES

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