Organizational ambidexterity in young SMEs? The incompatibility of entrepreneurial orientation and process improvement

ABSTRACT

Organizational ambidexterity describes firms’ ability to pursue exploration and exploitation strategies simultaneously. It is, however, unclear if young SMEs should seek to develop organizations with this ability or if they are better off focusing on just one strategy. To shed light on this matter, this paper investigates the interaction between entrepreneurial orientation (EO) (organic organizing) and process improvement (mechanistic organizing) in relation to firm growth in young SMEs (small and medium-sized enterprises). We hypothesize that both types of strategies can produce growth for young SMEs but that, due to their incompatibility, young SMEs do not have the resources needed to successfully pursue them both. We test these hypotheses on a sample of 257 young Danish SMEs. Our results confirm that both EO and process improvement have a positive effect on firm growth. The results further show that while process improvement has a considerable positive effect in low EO firms, for high EO firms, this effect is minimal. Thus, high EO firms may waste important resources by putting too much effort into process improvement initiatives.

KEYWORDS:

• Entrepreneurial orientation
• process improvement
• firm growth
• small and medium-sized enterprises
• ambidexterity
• organic organizing
• Mechanistic organizing

Introduction

Growth is among the most important factors for young SMEs (small and medium-sized enterprises) in order to survive and prosper (Chandler and Hanks 1993; Rauch et al. 2009; Wiklund and Shepherd 2005). Evidence suggests that in order to be profitable, firms have to grow to a minimum threshold, which varies across industries and over time (Audretsch 1994; Williamson 1981). While pursuing growth, young SMEs typically struggle to balance between being entrepreneurial (opportunity-seeking and adaptable) and efficient (time and costs) (Chen et al. 2015; Cosh, Fu, and Hughes 2012; Dess, Lumpkin, and Covin 1997; March 1991; Rust, Moorman, and Dickson 2002; Terziovski 2010). To achieve the benefits of both strategies, firms may seek to develop ‘organisational ambidexterity’, i.e. the ability to respond to market demands in a cost- and time-efficient manner while also being flexible enough to pursue opportunities and adapt to changes in the environment (Adler, Goldoftas, and Levine 1999; Gibson and Birkinshaw 2004; Tushman and O’Reilly 1996). Organizational ambidexterity has, however, so far mainly been explored in relation to larger firms, while it remains unclear to what extent this knowledge applies to SMEs (Wenke, Zapkau, and Schwens 2021).

To shed light on this matter, we investigate the combined effects of entrepreneurial orientation (EO) and process improvement. Specifically, EO is defined as a strategic orientation founded on the dimensions of risk-taking, innovativeness, proactiveness, competitive aggressiveness, and autonomy (Hughes and Morgan 2007; Wiklund and Shepherd 2003, 2005). Process improvement, on the other hand, is defined as the ability to formalize and restructure processes to reduce time and costs while ensuring a consistent quality (Juran and Godfrey 1999; Klassen and Menor 2007; Powell 1995). While developing organizational ambidexterity that allows firms to combine the two strategies appears to be a feasible path for larger firms, we argue that this is not the case for many SMEs, in particular young ones. Specifically, the incompatibility of organic (i.e. EO) and mechanistic organizing (i.e. process improvement) implies a significant demand for resources to pursue both strategies.

In this context, ‘resource exhaustion’ theory explains how EO can make firms too explorative, thereby exhausting its resources and leading to firm failure (Covin and Wales 2019; Gali et al. 2023; Hughes et al. 2021). We theorize that young SMEs risk another type of ‘resource exhaustion’ if attempting to pursue both EO and process improvement strategies, namely one related to the organizational resources needed to manage both modes. Specifically, we argue that young SMEs’ more limited knowledge and formal management structures make shifts in focus between EO and process improvement less feasible (i.e. contextual ambidexterity), while their constraints regarding staffing make it difficult to implement separate units focusing on EO and process improvement respectively (i.e. structural ambidexterity). In other words, the additional resources a young SME would need to manage organizational ambidexterity counter the benefits that may be obtained from pursuing both strategies.

We test our hypotheses on a sample of young (2–12 years old) Danish SMEs (N = 257) (Reuber and Fischer 2002; Steffens, Davidsson, and Fitzsimmons 2009). Our argument for focusing on young SMEs is that such firms, as compared to more established firms, are more often in the process of deciding on the balance between process efficiency (time and costs) and process flexibility (adaptability and innovativeness). Specifically, some studies suggest many young SMEs take an aggressive stance in rapidly changing environments in order to establish and renew their competitive positions (Lumpkin and Dess 1996; Rauch et al. 2009) and that, in particular, young SMEs benefit from the relative lack of bureaucracy that exists within their larger counterparts (Cohen and Klepper 1996; Kamien and Schwartz 1975). On the other hand, some degree of process efficiency is needed to be competitive in time and cost dimensions. Thus, we expect that the challenge of balancing organic and mechanistic aspects of organizational strategies is more vividly displayed in this type of context.

Through the study above, this paper contributes to the limited knowledge about organizational ambidexterity in SMEs and connects two largely disparate areas of research, i.e. entrepreneurship and process improvement literature. Although the literature includes much debate concerning the incompatibility between organic and mechanistic organizing (Burns and Stalker 1961; Dust et al. 2014), there is a lack of empirical studies on younger firms. Thus, our study provides new knowledge on the topic through its focus on start-up firms. From a more general perspective, our study contributes to the understanding of the boundaries of EO in relation to the effect of a process improvement focus. The other way around, we contribute to understanding the boundaries of process improvement by showing that process improvement will have little effect in firms dominated by creativity, flexibility, and opportunity-seeking.

Theoretical foundations

Growth in young SMEs

Different factors influence growth in SMEs, which can be divided into internal and external factors. Internal factors include industry, size, age, and strategic orientation (Freel 2004; Schlichter, Klyver, and Haug 2018; Storey 1989; Wiklund and Shepherd 2005), whilst external factors focus on environmental dynamism (Carroll and Hannan 2000, Davidsson and Delmar 2006; Jovanovic 1982) and environmental hostility (Dess and Robinson 1984; Wiklund 1998). In relation to the internal factors of SMEs, previous research has established that the maturity of the industry influences firm growth, where there seems to be agreement that higher maturity of the industry leads to lower rates of firm growth (Davidsson, Achtenhagen, and Naldi 2005; Lumpkin and Dess 2001; Rauch et al. 2009). However, although the arguments about how size and age impact firm growth are somewhat related, the findings of prior studies point in different directions (Audretsch 2004; Carroll and Hannan 2000; Gilbert, Audretsch, and McDougall 2004; Rauch et al. 2009). Another relevant aspect in relation to young SMEs is that such firms are typically more entrepreneurial (Lumpkin and Dess 1996; Rauch et al. 2009) – and that EO has been shown to have a positive impact on firm growth (Messersmith and Wales 2011; Moreno and Casillas 2008; Rauch et al. 2009).

Other internal issues for SMEs concern that young SMEs often struggle with the liability of newness and the liability of smallness. The liability of smallness (Aldrich and Auster 1986) is concerned with limited internal resources as a result of firm size. In this context, the liability of newness affects the possibilities of increasing these, as it limits the external legitimacy and access to funds. If such challenges are overcome and growth is created, more organizational structure is needed to manage the larger organization – i.e. a functional structuring of the organization (Blili and Raymond 1993; Kyobe 2004). Common problems of resource allocation emerge because individuals in smaller firms have to manage different tasks, which often complicates the transition phase into a functionally structured organization (Ates et al. 2013). In this context, the central challenge concerns exploiting the strengths of the small organization by enhancing flexibility and creativity (Anderson and Eshima 2013; Love and Roper 2015; Man, Lau, and Chan 2002) whilst at the same time transitioning into a more formalized organizational structure (Hoffman et al. 1998; Miles et al. 1978; Sine et al. 2006).

With regard to the external factors relevant to growth in SMEs, the literature has discussed how environmental dynamism and environmental hostility influence firm growth. Specifically, while environmental dynamism is claimed to have a positive effect on firm growth in SMEs because of their flexibility and opportunity-seeking characteristics (Chandler and Hanks 1994; Covin and Slevin 1991; Zahra 1993), environmental hostility is claimed to have the opposite effect (Wiklund 1998).

Organising: organic versus mechanistic

To understand what makes firms entrepreneurial or process efficient, respectively, the focus may be turned to the distinction between organic and mechanistic organizing. Specifically, organic organizations are characterized by being flexible and emphasizing a high degree of autonomy, which in turn enables creative thinking (Kreiser and Davis 2010; Salehi and Arbatani 2013). In other words, employees in an organic organization are characterized as having more general competencies, which ensures a fast allocation of resources to new tasks and job assignments, making the organization more flexible (Cosh, Fu, and Hughes 2012; Miller and Toulouse 1986; Sagiv et al. 2010; Ward 2004). Thus, organic organizations invest in human capital in order to be prepared for future events, thereby supporting an organizational ability to adapt to its surroundings and create opportunities. This produces a cultural pattern of identifying and adapting creative solutions in a changing environment.

Firms that are organically organized typically achieve competitive benefits related to flexibility, creativity and risk-taking. Such firms are adaptable to changes in their environment, which is a particularly relevant characteristic for SMEs, as they often compete more on their flexibility than on costs (Dibrell, Davis, and Craig 2008; Wolff and Pett 2006). Furthermore, SMEs are often actors with low power and on whom few companies have high dependencies. Therefore, they have few opportunities to shape and form their context and are instead formed and shaped by it, making adaptability even more important. Additionally, it is well established that creativity concerns the ability to create and differentiate, making it an important element for firm growth (Hughes and Morgan 2007; Khan 1986). As EO emphasizes autonomy and creative thinking, as well as a focus on opportunity-seeking enabled by organizational flexibility (Hughes and Morgan 2007), we argue that EO is a suitable proxy for this approach.

On the other hand, mechanistic organizations have formalized processes and clear definitions of responsibilities, hierarchy, and procedures. Every part of the organization is well-defined and specialized, which in turn ensures efficiency and less friction (Sine et al. 2006). In a more specialized environment, the resources become less mobile but more efficient. The organization tends to focus on time and cost reductions, thereby emphasizing a more reactive approach to its surroundings. Within a mechanistic organization, there is a cultural pattern of ‘doing things right’ (Powell 1995; Reed, Lemak, and Montgomery 1996), driven by a continuous approach of identifying and adapting best practices. Thus, mechanistic organizing involves process simplification and formalization to create an organization characterized by predictability and efficiency (Powell 1995; Terziovski 2010). This implies that employees are responsible for fewer and more clearly defined tasks, which leads to faster decision-making and more area-specific knowledge (Ates et al. 2013; Blili and Raymond 1993; Kyobe 2004). Firms with such a focus on process efficiency often achieve competitive benefits related to time and cost reductions (Juran and Godfrey 1999; Klassen and Menor 2007; Powell 1995; Reed, Lemak, and Montgomery 1996).

It should be noted that mechanistic organizing has been attributed to different types of characteristics. Specifically, some literature associates mechanistic organizing with being bureaucratic, conservative, or risk-averse (e.g. Covin and Slevin 1988; Khandwalla 1977), while others associate this type of organizing with a focus on cost and time efficiency (e.g. Schroeder et al. 2008). As stated by Schroeder et al. (2008), ‘the mechanistic structure fits simple and stable tasks and promotes efficiency, whereas the organic structure fits complex and uncertain tasks and supports adaptability’. As business process improvement programmes focus on standardization (i.e. simplification) of processes in terms of activities and responsibilities to reduce costs and time cycles, it appears to be a suitable proxy for the latter perception of mechanistic organizing – that is, when the mechanistic organization is a result of seeking cost and time efficiency, as opposed to being bureaucratic, conservative, and risk-averse.

Accordingly, there are two distinct approaches to achieving growth, organic versus mechanistic organizing, for which basic characteristics are summarized in Figure 1 (based on dimensions by Burns and Stalker 1961). These characteristics are later further discussed under the development of hypotheses in the subsequent sections.

Figure 1. Characteristics of organic vs mechanistic organizing.

Organisational ambidexterity

Having outlined the contrast between organic and mechanistic organizing, an obvious question is if these may be combined. This is captured by the concept of ‘organisational ambidexterity’, which describes an organization’s ability to respond to market demands in a cost and time-efficient manner while also being flexible enough to quickly adapt to changes in the environment (Adler, Goldoftas, and Levine 1999; Gibson and Birkinshaw 2004; Tushman and O’Reilly 1996). In other words, ambidextrous organizations are capable of simultaneously engaging in exploration (i.e”.search, variation, experimentation and innovation”) and exploitation (i.e”.refinement, efficiency, selection and implementation”) (March 1991, 71). According to the literature, exploration, exploitation, and ambidexterity all have positive effects on firm performance (Junni et al. 2013; Mathias, McKenny, and Cook 2018). Furthermore, it has been theorized that ambidexterity would generally lead to better performance than focusing on either exploration or exploitation (e.g. Tushman and O’Reilly 1996).

One approach to ambidexterity is ‘contextual ambidexterity’, which may be described as ‘building a set of processes or systems that enable and encourage [managers] to make their own judgements about how to divide their time between conflicting demands for alignment and adaptability’ (Gibson and Birkinshaw 2004, 211). Exploration and exploitation are, however, fundamentally different activities, for which reason contextual ambidexterity can be challenging and produce tensions in organizational units that pursue both these activities (March 1991; Smith and Tushman 2005). For such reasons, several researchers argue that firms would often be better off by structurally separating exploration and exploitation in different business units, i.e. ‘structural ambidexterity’ (Heracleous et al. 2017; O’Reilly and Tushman 2008; Tushman and O’Reilly 1996).

In the context of SMEs, it is unclear if any form of organizational ambidexterity is more beneficial than focusing on either exploration or exploitation (Wenke, Zapkau, and Schwens 2021). Specifically, most literature has a larger firm focus, and it is unclear to what extent this knowledge applies to SMEs (Wenke, Zapkau, and Schwens 2021). Furthermore, among the few studies focusing on SMEs, there is conflicting empirical evidence on this matter, as some studies show ambidexterity to be superior to exploration and exploitation in SMEs (e.g. McDermott and Prajogo 2012), while others do not find support that ambidexterity is beneficial for SMEs (e.g. Bierly and Daly 2007).

Hypothesis development

Organic structuring and firm growth

The EO-performance relationship has been thoroughly supported by prior research (e.g. Covin and Slevin 1986; Hult, Ketchen, and Nichols 2003; Lee, Lee, and Pennings 2001, Wiklund and Shepherd 2011; Lumpkin and Dess 1996; Moreno and Casillas 2008), although the magnitude and significance of the relationship vary across studies (Rauch et al. 2009). Thus, EO is considered an essential characteristic and a prerequisite for growth. The literature conceptualizes EO as a five-dimensional construct that entails innovativeness, risk-taking, proactiveness, competitive aggressiveness and autonomy (Hughes and Morgan 2007).

Innovativeness concerns the predisposition to engage in creative and experimental activities that relate to the development of new products, services, or processes. By adding new features to a given product or service, the firm creates a market entrance or expands existing market potential, which is crucial for growth. Therefore, SMEs need to improve their products and services by enhancing and rethinking these. This innovative nature consequently acts as a prerequisite for SMEs in order to increase market share and, subsequently, grow.

Risk-taking concerns the ability to act decisively and boldly in an environment characterized by high uncertainty. As SMEs need to be the frontrunners with innovative solutions, a derived effect of risk-taking is that a firm wanders into new territory, whether it is the application of new technology, services, or processes. Miller and Friesen (1982) argue that doing nothing at all or being slow to act often results in a higher risk than acting on opportunities that might not pay off.

Proactiveness concerns the ability to be forward-looking and to introduce products and services ahead of competitors, thereby anticipating future demands. It is SMEs’ ability to act on market possibilities and maintain awareness of market developments.

Competitive aggressiveness concerns SMEs’ efforts to compete against their competitors, and it is closely related to the aforementioned proactiveness. The main difference between the two dimensions is that whilst proactiveness concerns the ability to foresee opportunities in the market, competitive aggressiveness concerns the ability to handle threats from competitors.

Finally, autonomy concerns the organizational freedom given to employees. It expresses the degree to which the EO is dependent on the CEO. If an SME has a high level of autonomy, the members of the organization are capable of and encouraged to bring forth new ideas, thereby enabling the firm to adapt more quickly to its environment (Grewal and Tansuhaj 2001). Furthermore, a high level of autonomy will arguably utilize the other dimensions of the EO construct more.

To sum up, we argue that most successful SMEs are characterized by (1) an ability to be innovative in terms of products, services or processes; (2) a willingness to take risks in order to explore new ventures; (3) an ability to anticipate future demands and act proactively; (4) an ability to handle threats from competitors and thus position the firm in the market accordingly; and (5) an autonomous organizational structure that enables employees to bring forth new ideas in order to adapt to the firm’s environment. We expect all five EO dimensions to impact SME growth in a similar direction with no unique opposite effects. Based on the findings by Lomberg et al. (2017) that shared variance across EO dimensions explained a rather significant part of firm performance (particularly for firms across sectors), as well as the recommendation of Kreiser et al. (2002) to prioritize simplicity over potential detailed accuracy, we conceptualize EO as a unified conceptual entity (Covin and Slevin 1989; Miller 1983).

As EO is a well-established theoretical construct which has been associated with performance and growth (Covin and Wales 2019; Eshima and Anderson 2016), we formally state the following hypothesis:

H1:

(baseline): EO is positively associated with firm growth in young SMEs

Mechanistic structuring and firm growth: process improvement

Another way for SMEs to grow is to achieve time and cost efficiency through simpler and more formalized processes using best practices, specialization, and automation (Bessant and Tidd 2007; Prakash and Gupta 2008; Wolff and Pett 2006). However, questions have been raised about the relationship between process improvement and performance, as this has produced different results. Specifically, it has been argued that process improvement has a positive effect on growth, as it increases firms‘ capacity and quality (Gunday et al. 2011; Hervas-Oliver, Sempere-Ripoll, and Boronat-Moll 1988; Wolff and Pett 2006). However, the magnitude of the effect varies in the literature, going from no significant effect to a strong positive effect (Freel 2004; Ittner and Larcker 1997).

Besides being able to service customers faster, process time reductions can also reduce costs. Specifically, reductions in the time used to handle customer orders, the overall product or service delivery time and the development time of new products and services can reduce the number of man-hours used (Powell 1995; Reed, Lemak, and Montgomery 1996; Terziovski 2010). Other means for process efficiency concern reductions of paperwork and time wasted (Powell 1995; Terziovski 2010). Specifically, reductions of paperwork and time wasted in organizations concern eliminating unnecessary processes and reducing bureaucracy. The implied cost reductions from such initiatives enable firms to gain competitive advantages by delivering products and services faster and at a lower cost.

Formalization increases the quality of the products and services, and it reduces the price of producing these. The improvement of the quality of products and services is created by formalizing internal processes to create more homogeneous products and services with fewer mistakes at a higher pace (Powell 1995; Terziovski 2010). By formalizing processes, firms adopt a more specialized mindset that will enhance the performance and quality of individual tasks. Specialization offers steeper learning curves, optimizing the efficiency of the individuals, and is a natural transition as the firm grows and functional departments form (Audretsch 2001). This organizational development and specialization increase the scalability of different job functions, enhancing the effect of process improvements by having more people doing the same tasks (Salehi and Arbatani 2013). Formalization will, therefore, have a direct effect on SME performance based on the impact of organizational growth, as well as enhance the output of internal processes.

Formalized organizational structures are claimed to have a positive impact on performance, especially in more stable environments (Burns and Stalker 1961; Sine et al. 2006). This includes higher role formalization, functional specialization, and administrative intensity, which are claimed to have a positive effect on the performance of young SMEs, even in a dynamic environment (Sine et al. 2006). This has a number of explanations. Firstly, role formalization reduces role ambiguity (Fernhaber and Patel 2012; Tang et al. 2008), which is a common phenomenon in young SMEs. Furthermore, role formalization can enable faster decision-making at a lower cost due to an increased understanding based on decision authority. This is enabled by the clarification of competencies and, therefore, the ability to present the decision to the most knowledgeable person. Faster decision-making has a positive effect on SMEs in volatile environments (Eisenhardt and Schoonhoven 1990). Functional specialization can also enhance performance, as it supports organizational growth and specialization. Lastly, administrative intensity is important for the development of the organization’s processes. Higher administrative intensity is preferable in order to align processes and thus increase the reproducibility of products and services.

As the abovementioned perspective arguably adds to the positive relationship between process improvement and firm growth in SMEs, we state the following hypothesis:

H2:

Process improvement is positively associated with firm growth in young SMEs

Process improvement versus EO

While the literature shows the benefits of EO and process improvement strategies, respectively, the question is if it is feasible for young SMEs to combine these to achieve the benefits associated with both strategies. Specifically, there are some significant challenges related to managing the incompatibility of these two strategies, which subsequently are illustrated using Burns and Stalker’s 1961 dimensions of organizing, i.e. decision-making, processes, and investment approaches.

With regard to decision-making, there is a trade-off between creativity and process formalization. Specifically, several studies show that a highly formal organizational structure inhibits creative thinking, as it creates boundaries for creative thinking and disempowerment of employees (Cosh, Fu, and Hughes 2012; Dess, Lumpkin, and Covin 1997; Miller 2011; Miller and Toulouse 1986; Sagiv et al. 2010; Ward 2004). Structural organizing is also associated with a stronger hierarchical organization, where more layers of management are present, and decisions are consequently concentrated at a higher management level, ensuring a more homogenous decision-making process better aligned with the overall firm strategy. This limits the effect of employees’ autonomy and, thus, their ability to make creative solutions at lower hierarchical levels. In other words, striving for a creative environment and simultaneously standardizing and formalizing processes seems counterproductive.

With regard to processes, there is a trade-off between flexibility and formalization (Chen et al. 2015; Dess and Robinson 1984; Patel 2011; Terziovski 2010). Flexibility creates value through situational adaptation to threats and opportunities. On the other hand, formalization creates value by supporting best practices, indicating that ‘one size fits all’, and emphasizing speed, quality and continuity. Tools used for generating formalization (e.g. some IT systems, standards and business process modelling) often limit the possibilities of deviating from procedures (Hage and Aiken 1967; Van de Ven, Ganco, and Hinings 2013). Formalization leads to increased specialization of employees, consequently affecting the quality of the individual’s output positively, but at the same time affecting the mobility of the workforce negatively. This mechanism is the opposite of what is found in less formalized organizations, which tend to be more flexible and have fewer specialists and more generalists. While formalization entails a focus on making the processes more homogenous and trying to find the best way of improving services or products to the customer, flexibility moves in the opposite direction, trying to apply a contingency approach to the processes by focusing both on the individual performing the task, as well as the circumstances around the process. The contradictory characteristics of the two approaches mean that the combination would only provide confusion and wasted time and resources.

With regard to investment approaches, there is a trade-off between risk-taking and cost reduction (Levinthal and March 1993; March 1991; Rust, Moorman, and Dickson 2002). In search of new opportunities, organizations that are taking risks have more focus on activities and investments that strengthen the ability to act more proactively. A cost reduction approach has a more reactive nature, as it focuses on improving the current state of the organization. Thus, the cost-reduction approach does not play well with the characteristics of risk-taking behaviour. Basically, the fundamentals surrounding the perspectives are completely different. While these two perspectives do not directly contradict each other, the mindset of applying one or the other does. The cost reduction perspective focuses on reducing uncertainty and minimizing cost, whilst risk-taking focuses on investments in uncertain environments with the intent of future gain.

As mentioned previously, firms may attempt to mitigate the conflicts described above by developing either contextual or structural ambidexterity. With regard to contextual ambidexterity, the literature has pointed to the fact that exploration and exploitation are fundamentally different activities and that pursuing both these activities can be challenging and will often result in organizational tensions (March 1991; Smith and Tushman 2005). This may be even harder for SMEs because they do not have adequate knowledge to operate in both modes or the management structure to control such shifts of focus. To avoid such issues, pursuing such activities in different business units could be the answer, i.e. structural ambidexterity (Heracleous et al. 2017; Tushman and O’Reilly 1996). While this approach is feasible in larger organizations, it is harder to implement in SMEs, as they are much more constrained regarding staffing such separate units (Lubatkin et al. 2006; Voss and Voss 2013). In other words, maintaining two such architectures appears to be challenging for SMEs (O’Reilly and Tushman 2013).

As indicated above, developing organizational ambidexterity requires significant organizational resources, as opposed to pursuing an EO or process improvement strategy exclusively. Given the limited resources of young SMEs, such endeavours could have a resource-exhausting effect that counters the benefits achieved from being ambidextrous. In other words, we speculate that another type of resource exhaustion could be at play, as compared to the theory by Gali et al. (2023). Specifically, while Gali et al. (2023) showed how EO can generate unsustainable amounts of entrepreneurial entropy, we hypothesize that attempts to pursue EO and process simultaneously for young SMEs could have a similar resource-exhausting effect. Accordingly, we argue that the relationship between EO and firm growth will be negatively moderated by process improvement in young SMEs, as stated in the hypothesis:

H3:

Process improvement negatively moderates the relationship between EO and firm growth in young SMEs

The theoretical model of the study is shown in Figure 2.

Figure 2. Theoretical model.

Methodology

Data and sample

The firms studied in this survey were young SMEs in Denmark. Two types of data were collected: survey data and register data. The survey data were based on a survey conducted by the professional survey provider Epinion in January 2016. These data were paired with register data from Navne & Numre Erhverv, which is a large firm database containing data from all Danish firms. We selected firms that (1) are from 2 to 12 years old (Reuber and Fischer 2002; Steffens, Davidsson, and Fitzsimmons 2009), (2) have three to 250 employees, (3) are not subsidiaries, and (4) have recorded financial statements. With regard to the first, this was based on the argument that, in order to make the growth measure comparable, at least two years of register data are needed. Furthermore, this enables a robustness test of the growth variable based on register data. The argument for excluding firms with fewer than three employees was that there is a high number of inactive firms in this group. The questions in the survey were answered by the CEOs of the firms who, in the case of SMEs, have greater insights into the firm’s functioning and orientation (Covin and Slevin 1989).

Based on the above sampling criteria, we identified a population of 7143 firms. Based on random sampling, we contacted 1255 firms and received 604 answers, giving a response rate of approximately 48%. We reduced the size of this sample through missing value analysis. Specifically, we removed 77 cases because of missing register data and 209 cases because of failure to answer more than 10% of the questions in both the EO, process improvement and the growth constructs. This left 318 cases, which we tested using missing value analysis (Harms et al. 2010) to establish whether the missing values were random. The analysis concluded that the missing values in the EO construct were random but that they were not random in the process improvement construct. This made us remove further cases with missing values, leaving a final number of 257 cases.

Measures

Firm growth is the dependent variable of the study. Several methods currently exist for the measurement of firm growth. In this study, we use a growth construct consisting of three items: sales, market share and employees (Anderson and Eshima 2013). These items were estimated for the last three years and measured on a five-point Likert scale, ranging from very high to very low (Cronbach’s alpha = .766). Although a self-reported growth measure has some weaknesses, for SMEs, in particular, the managerial perception of success or failure has a strong influence on the motivational level of firms (Dess and Robinson 1984), which makes it possible to compare firms across industries (Achtenhagen, Naldi, and Melin 2010). We, thereby, limit industry bias, as compared to if we had measured the change in growth for the specific firm (Davidsson and Delmar 1997). It should be noted that the use of multiple growth variables (Davidsson 1991) has been argued to provide a better overall variable because growth varies from industry to industry. This measure has, for a long time, been used as a base for evaluating relative firm growth within the management literature (Covin and Slevin 1989; Lawrence and Lorsch 1967; Tan and Peng 2003).

The first independent variable is EO. EO was originally defined as consisting of three core dimensions: risk-taking, innovativeness and proactiveness (Covin and Slevin 1989; Miller 1983) – which have been supported by the studies by, e.g. Rauch et al. (2009); Lisboa et al. (2016). Lumpkin and Dess 1996; 2001) subsequently advocated for there being two additional dimensions: competitive aggressiveness and autonomy. Competitive aggressiveness focuses on how to deal with threats from the environment, separating it from proactiveness, which focuses more on seeking out opportunities. The autonomy dimension captures how well the mindset of the owner is transferred to the organization – making it capable of making decisions and carrying out tasks (Hughes and Morgan 2007). In this study, we investigate EO as an 18-item construct under the categories of risk-taking, innovativeness, proactiveness, competitive aggressiveness and autonomy (Hughes and Morgan 2007). These 18 items are measured on a 5-point Likert scale ranging from very high to very low (Cronbach’s alpha = .810).

The second independent variable is process improvement. Process improvement is measured as a 5-item construct based on Powell (1995), which has achieved wide acceptance in the literature. The items concern the degree to which the firm had reduced (1) order processing cycle time, (2) new product development cycle time, (3) overall product development cycle time, (4) paperwork, and (5) time and costs in all internal processes. These five items were measured using a 5-point Likert scale ranging from totally agree to totally disagree (Cronbach’s alpha = .703).

Additionally, we employed a set of control variables, which also could explain the relationship between independent variables and dependent variables. These include firm size, firm age, and industry. Data on firm size, firm age and industry were drawn from register data from Navne & Numre Erhverv. We controlled for these variables because prior studies indicate they are related to both EO and process improvement (Greiner 1998; Laforet 2013; Rauch et al. 2009). Firstly, firm size is suggested to influence growth (Hall and Weiss 1967; Wiklund and Shepherd 2005). Specifically, size influences the impact of the EO-performance relationship in the sense that it has a greater impact in smaller organizations, while on the other hand, firm size is expected to have a positive effect on the relationship between process improvement and performance based on economies of scale. Secondly, firm age is known to influence growth and profitability (Almus and Nerlinger 1999; Coad, Segarra, and Teruel 2016). Specifically, whilst the EO-performance relationship is expected to be negatively affected by age, the process improvement-performance relationship seems to be positively affected. Thirdly, the industry seems to affect both types of relationships based on the difference in industry dynamics (Almus and Nerlinger 1999; Tanriverdi 2006; Wieder et al. 2006), which is partly due to different levels of training, human capital, and absorptive capacity. In this context, we divided the firms into the following industry categories: manufacturing, retail, service, transport, public utilities, and financial (Harter, Schmidt, and Hayes 2002; Harter, Schmidt, and Killham 2003).

Data analysis strategy

The hypotheses were tested using hierarchical linear regression models. We examined the main effect of EO and process improvement on SME growth, together with their interaction effect.

In the hierarchical regression model, the variables are introduced sequentially in order to establish whether the different main effects and interaction(s) account for a statistically significant difference in the total explained variance. The sequential order is control variables, independent variables, and interaction variables. We use two-way interaction plots for interpreting the results of the interaction effects (Aiken and West 1991).

Results

Descriptive results

The results, as shown in Table 1, indicate that there is a positive correlation between the dependent variable and both independent variables, i.e. EO and SME growth (r = .20 p < .01) and process improvement and SME growth (r = .26 p < .01). Furthermore, a positive correlation was found between EO and process improvement, suggesting some relationship between the two independent variables (r = .23 p < .01).

Table 1. Means, standard deviations and correlations.

	Mean	S. D.	1	2	3	4	5	6	7	8	9	10
1. Growth	3,47	0,75	1	0,766
2. Process Innovation	3,35	0,70	.26**	1	0,703
3. Entrepreneurial Orientation	3,75	0,48	.20**	.23**	1	0,81
4. Manufacturing	0,15	0,36	−.13*	06	05	1
5. Retail	0,26	0,44	08	-,02	.16*	−.25**	1
6. Service	0,37	0,48	-,08	-,04	-,09	−.32**	−.46**	1
7. Transport and public utilities	0,12	0,32	07	-,08	-,07	−.15*	−.22**	−.28**	1
8. Financial	0,10	0,30	08	12	-,06	−.14*	.20**	−.26**	-,12	1
9. Numbers of employees	18,23	21,96	11	02	-,03	.13*	-,08	-,11	.13*	00	1
10. No. of months since start-up	66,92	14,96	−.13*	03	−.16*	01	07	00	−.15*	04	-,09	1

**Correlation is significant at the 0.01 level (2-tailed).

*Correlation is significant at the 0.05 level (2-tailed).

To test whether the observed statistical relationship may be caused by common method bias, we conducted Harman’s single-factor test. We found that no variable in the study accounts for more than 17% of the total variance, which indicates that common method bias is not a problem (Harman 1976). We found a negative correlation between growth and firm age (r = −.13 p < .05), whilst there is no significant relationship between process improvement and any of the other variables in the survey. There is a positive relationship between EO and two of the control variables. EO has a positive correlation with the retail industry (r = .16 p < .01) and a negative correlation with firm age (r = −.16 p < .01). The highest correlation between variables is below 0.7, which indicates no sign of multi-collinearity. To make sure multi-collinearity was not a problem, we conducted a variance inflation factor (VIF) test. The highest VIF value observed in the test was 4.601 in the moderator model and 1.306 in the standard model, which are both well below 10, suggesting that multi-collinearity was not a problem (O’Brien 2007).

Key results

It is apparent from Table 2 Model 2 that EO is positively related to firm growth. After controlling for the influences of firm age, firm size and industry, EO was significantly related to growth (β = .198, p < .001), explaining why an additional 3.4% of the variation is added to the 4% of the baseline model. Similarly, Table 2 Model 3 shows that process improvement is positively related to firm growth after controlling for firm age, firm size and industry (β = .271, p < .001). The effect of process improvement has a larger explanatory power on the variation, adding 7.1% to the baseline model. These results suggest that both independent variables are significantly and positively related to firm growth. By adding both independent variables to the model (Model 4), we raise the explanatory power of the model to 12.4%, which is 8.4% higher than the baseline model. In summary, we find evidence for accepting both Hypothesis 1 and Hypothesis 2.

Table 2. Regression models.

	Model 1	Model 2	Model 3	Model 4	Model 5
Number of months since start-up	−0.120 ϯ	−0,084	−0.125 *	−0,099	−0,092
Numbers of employees	0.117 ϯ	0.124 *	0.11 ϯ	0.116 ϯ	0.11 ϯ
Industry (reference is service)
Manufacturing	−0.091	−0.109	−0,1.7	−0.118 ϯ	−0.118 ϯ
Retail	0.114 ϯ	0.079	0.113 ϯ	0.089	0.089
Transportation and public utilities	0.061	0.068	0.077	0.080	0.091
Financial	0.106	0.109 ϯ	0.073	0.079	0.080
EO		0.198 ***		0.139 *	0.725 **
Process improvement			0.271 ***	0.238 ***	1.162 **
EO*Process improvement					−1.208 *
N respondents	257	257	257	257	257
Adjusted R Square	0.040	0.074	0.111	0.124	0.136
Adjusted R square change	0.040	0.034	0.071	0.084	0.096

^ϯp < .10.

*p < .05.

**p < .01.

***p < .001.

The significance levels are reported as two-tailed tests for control variables and as one-tailed tests for independent variables.

Model 5 shows a negative moderating effect of process improvement on the EO-firm growth relation (β = −1.208, p < .05), supporting Hypothesis 3. The final model (Model 5) explains a total of 13.6% of the variance, which is 1.2% higher than the full main effect model. The interaction plot in Figure 3 indicates that process improvement has a larger impact on firm growth than EO. The most interesting finding is that whilst SMEs with a low level of process improvement activities increased growth when they have high levels of EO, this is less so in the case of SMEs with high levels of process improvement. Furthermore, SMEs with high levels of process improvement outperform firms with low levels of process improvement, regardless of their level of EO.

Figure 3. Effects of EO and process improvement on SME growth.

Robustness tests

We originally theorized the five subdimensions of EO as a unidimensional construct due to expected shared variance (Lomberg et al. 2017) and expected similar effects of all five dimensions on SME growth (Kreiser, Marino, and Weaver 2002). However, to challenge these assumptions, we conducted several robustness tests. First, we ran similar regression analyses, including the five dimensions separately (See Table 3). This only revealed a significant positive association between proactiveness and SME growth, while the remaining subdimensions were insignificant. When the other subdimensions were considered isolated, together with the control variables, each of them was significantly associated with SME growth (risk-taking: r = .104; p < 0.05; innovativeness: r = .232; p < 0.001; autonomy: r = .105; p < 0.05), except competitive aggressiveness (r = −0.004; n.s.) (not reported in tables). This suggests, similar to Lomberg et al’.s (2016) results, that the subdimensions share explaining variance. Further on, when examining the interaction effects of the subdimensions and process innovation, the results are robust for risk-taking, innovativeness, proactiveness, and autonomy; however, not for competitive aggressiveness. Contrary to expectations, competitive aggressiveness has a negative association with SME growth when combined with low process innovation and only a marginal increasing growth when combined with high process innovation. Thus, competitive aggressiveness behaves differently together with process innovation compared to the other four dimensions that behave in a consistent manner.

Table 3. Regressions models: five separate dimensions of EO.

	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7
Controls	Yes	Yes	Yes	Yes	Yes	Yes	Yes
EO
Risk-taking	−.005	.014	.723**	0.06	.001	.008	0.28
Innovativeness	.113	.085	.069	.521*	.099	.107	.083
Proactiveness	.198**	.171*	.155*	.186*	.622**	.134*	.165*
Comp. agressiveness	−.060	−.062	−.056	−.060	−.048	−1.199***	−.067
Autonomy	.006	−.031	−.015	−.026	−.032	−.022	.576*
Process improvement		.222***	.826***	.731**	.844**	−.729***	.910***
Risk-taking*Process improvement			−.959**
Innovativeness*Process improvement				−.751*
Proactiveness*Process improvement					−.833*
Comp. agressiveness*Process improvement						1.536***
Autonomy*Process improvement							−1.019**
N respondents	257	257	257	257	257	257	257
Adjusted R Square	0.010	0.141	0.164	0.150	0.150	0.194	0.159
Adjusted R square change		0.041	0.023	0.009	0.009	0.053	0.018

^ϯp < .10 * p < .05** p < .01*** p < .001.

Significance levels are reported as two-tailed tests for control variables and one-tailed tests for independent variables.

Second, we ran similar regression analyses, including the three original subdimensions suggested by Covin and Slevin (1989) as both a multidimensional construct (See Table 4, Model 1–5) and a unidimensional construct (See Table 4, Model 6–7). The results are robust compared to the original results.

Table 4. Regression models: three separate subdimensions of EO.

	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7
Controls	Yes	Yes	Yes	Yes	Yes	Yes	Yes
EO (unidimensional)						.247***	.969***
Risk-taking	−.006	.003	.729**	−.004	−.010
Innovativeness	.107	.075	.060	.519*	.091
Proactiveness	.194**	.162*	.148*	.178*	.677**
Process improvement		.218***	.835***	.736**	.868**		1.267***
Risk-taking*Process improvement			−.976**
Innovativeness*Process improvement				−.764*
Proactiveness*Process improvement					−.924*
EO (3 dimensions)* Process improvement							−1.415**
N respondents	257	257	257	257	257	257	257
Adjusted R Square	0.134	0.178	0.203	0.189	.190	0.095	0.168
Adjusted R square change		0.044	.025	0.011	.012		0.073

^ϯp < .10 * p < .05** p < .01*** p < .001.

Significance levels are reported as two-tailed tests for control variables and one-tailed tests for independent variables.

As described previously, we originally used all five scale items of the process improvement construct (Powell 1995). However, looking deeper into the items, it may be questioned whether a reduction of paperwork is essentially incompatible with entrepreneurial orientation. Thus, we eliminated the reduction of the paperwork item from the scale and ran similar regressions. The results of this analysis were robust (entrepreneurial orientation: r = .669; p < 0.05; process improvement: r = 1.084; p < 0.05; interaction term −1.081; p < 0.05) (See Model in Table 5). Looking at the items, it could also be argued that some items (items 1, 4 and 5) focus on internal processes while other items are focused on product development (items 2 and 3). The theoretical model proposed by Wales et al. (2023) suggests that product development cycle time facilitates new value creation and, by extension, growth, and, accordingly, is not tied to efficiency. While launching new products is costly, it simultaneously increases the potential to identify new avenues for growth. Accordingly, following the logic of Wales et al. (2023), one might speculate that processes which make a firm better at launching new products would support the EO-growth relationship; that is, an interaction term in the opposite direction as originally hypothesized. We therefore completed a split of the process improvement construct into an internal improvement component (entrepreneurial orientation: r = 1.004; p < 0.001; process improvement: r = 1.745; p < 0.001; interaction term −1.913; p < 0.001) and a product development improvement component (entrepreneurial orientation: r = .199; n.s.; process improvement: r = 0.329; n.s.; interaction term −0.129; n.s.) (See results in Model 2 and 4 in Table 5). For the internal improvement component, we also created a component without paperwork reduction (entrepreneurial orientation: r = .992; p < 0.001; process improvement: r = 1.739; p < 0.001; interaction term −1.853; p < 0.001) (See results in Model 3 in Table 5). The results are not only robust for the internal improvement component (both with and without the paperwork item) but have larger and more significant coefficients and more explained variance (adjusted R square increased from 0.136 to 0.151 and 0.159, respectively). On the other hand, the results for the product development improvement component are not robust. The direct effects of EO and process improvement are still in the correct direction and significant (r = .140; p < 0.05; r = 226; p < 0.001; not reported in the table), but the interaction term is insignificant, and less variance is explained (adjusted R square decrease from 0.136 to 0.125). In sum, it can be concluded the negative moderation of the effect of EO on growth by process improvement is primarily driven by the internal components of the process improvement construct.

Table 5. Regression models: various operationalization of process improvement.

	Model 1	Model 2	Model 3	Model 4
	Without paperwork (Item 1 + 2 + 3 + 5)	Internal processes (Item 1 + 4 + 5)	Internal processes with paperwork (Item 1 + 5)	Product development (Item 2 + 3)
Controls	Yes	Yes	Yes	Yes
EO	0.669*	1.004***	0.992***	0.199
Process improvement	1.084*	1.745***	1.739***	0.329
EO*Process improvement	−1.081*	−1.913***	−1.853***	−0.129
Adjusted R Square	0.139	0.151	0.159	0.125

^ϯp < .10 * p < .05** p < .01*** p < .001.

Significance levels are reported as two-tailed tests for control variables and one-tailed tests for independent variables.

Discussion

This study investigated the compatibility of organic and mechanistic organizing in relation to firm growth in young SMEs. Combining arguments from entrepreneurship and process improvement literature, we theorized that young SMEs benefit from both organic and mechanistic organizing but that pursuing both through ambidextrous organizing would not be beneficial. Specifically, the mechanistic view, as compared to the organic view, involves (1) predictability vs. creativity, (2) formalization vs. flexibility, and (3) cost reduction vs. risk-taking. While larger firms may have the resources to pursue both strategies, we argued that this is not the case for young SMEs. Specifically, SMEs generally have less internal knowledge and formal management structures, which makes it harder to successfully switch between exploration and exploitation modes (contextual ambidexterity), while their more limited size constrains them regarding staffing separate units for exploration and exploitation (structural ambidexterity) (Cao, Gedajlovic, and Zhang 2009; Voss and Voss 2013). Our results supported these arguments by showing that both organic and mechanistic organizing can be beneficial for young SMEs in achieving growth, but when employed together, they counter each other. Specifically, we found only minimal effects of process improvement in high EO firms, as compared to low EO firms.

Research contributions

Through the findings described above, our study provides several contributions. A central contribution relates to organizational ambidexterity in SMEs. Specifically, most studies on organizational ambidexterity focus on larger firms, while it remains unclear if ambidexterity is beneficial for SMEs (Wenke, Zapkau, and Schwens 2021). In this context, some studies suggest ambidexterity to be superior to exploration and exploitation in SMEs (e.g. McDermott and Prajogo 2012), whereas others do not support ambidexterity being beneficial for SMEs (e.g. Bierly and Daly 2007). While organizational ambidexterity may be beneficial in some types of SMEs, our study suggests that at least this is not the case for young SMEs in general. In other words, it could appear that organizational ambidexterity requires a certain level of maturity in terms of knowledge, organizational structure, and human resources that is not found in young SMEs.

Second, the study extended resource exhaustion theory (Gali et al. 2023) by suggesting a different type of EO-related exhaustion. Specifically, while existing research has pointed to the risk of EO behaviour exhausting a firm’s resources (Covin and Wales 2019; Gali et al. 2023; Hughes et al. 2021), we theorized that attempting to combine EO with process improvement, particularly its internal component as opposed to it product development component (Wales et al. 2023), could have a similar effect. We argued that this would be particularly present in young SMEs, given the scarcity of resources in such firms. In other words, the resources demanded to develop organizational ambidexterity will counter the benefits of pursuing both strategies.

Third, our results show that boundary conditions of EO are influenced negatively by the characteristics of mechanistic organizations, i.e. an emphasis on predictability over creativity, formalization over creativity and cost reduction over risk-taking. Specifically, process standardization can have a negative impact on creativity, as it limits employees’ drive to find ‘new ways’; formalization reduces opportunities for adopting contingency approaches and changes the focus from searching for creative solutions to adopting best practices; and a cost reduction focus negatively impacts risk-taking behaviour given the financial uncertainties associated with this.

Fourth, our study shows that process improvement has a much greater positive effect on growth in low EO environments than in high EO environments. The explanation may be that the characteristics of organic organizations negate some of the positive effects of process improvement. Firstly, creativity will counter standardized and formalized processes, as it emphasizes a bottom-up approach. Secondly, flexibility implies less standardization and will, therefore, lower the quality, speed and consistency of the firm’s products and processes. Based on a more voluntary approach to processes in the firm, flexibility will limit the options for economies of scale by process optimization. Lastly, risk-taking allows the movement of financial resources towards riskier investments and making numerous changes that negate the effect of cost reduction caused by optimizing processes.

Finally, our study elaborates on the contrast between organic and mechanistic organizing, which was introduced by Burns and Stalker (1961) and later discussed in contemporary organizational research. Specifically, we investigated this contrast in the context of young SMEs, where we expected this contrast to be particularly visible. Thus, our study contributes to a stream of literature that seeks to better understand extant organizational theory in the context of smaller firms (Aldrich 1999; Shane 2003). Hereunder, our study makes several contributions.

Limitations and future research

Our study also has some limitations. First, because of the size of the firms, the data submitted to the public databases were more limited, given lower requirements than for larger firms. This makes it harder to validate the reported measures with register data. Second, the high number of firms that, for various reasons, were not willing or able to complete the full questionnaire reduced the statistical power and eliminated important variance. Third, it was not possible to separate firms operating in growth markets from those operating in mature markets, which may have influenced the results slightly.

Next, it could be speculated that the emphasis on EO or process improvement is particularly associated with different growth stages or dynamic states (Churchill and Lewis 1983; Greiner 1998; Levie and Lichtenstein 2010). In this context, however, it should be noted that the term process improvement, as it is defined in the process improvement literature (Juran and Godfrey 1999; Klassen and Menor 2007; Powell 1995), has a clear focus on time and cost efficiency. On the other hand, although growth stages or states also involve increased formalization and structuring, these do not necessarily have a focus on time and cost efficiency. In other words, flexibility and innovation may still be emphasized over time and cost efficiency as an organization becomes more formalized and mature. Nevertheless, a relevant way to progress from our study for future research is to study how lifecycle stages or states influence the balance between EO and process improvement.

Growth stages and dynamic states may also affect the compatibility of EO and process improvement modes. Specifically, while our study shows that these modes are generally incompatible in young SMEs, it could be speculated that when such SMEs reach a certain size and level of maturity, organizational ambidexterity may become a more feasible path. Thus, identifying such conditions should be a focus of future research. Furthermore, there is also room for a deeper understanding of why EO and process improvement appear to be incompatible strategies in young SMEs. As argued, this may relate to SMEs having less knowledge, less formal management structures, and fewer resources. Since such constraints are related to whether contextual or structural ambidexterity is pursued, the effects of both of these strategies in SMEs are also worth exploring. In this context, our results pointed towards different types of process improvements (i.e. internal-focused versus product development-focused) varying in terms of how they can be combined with EO. Future research might look further into why this is the case or investigate other types of process improvements and their compatibility with EO.

Finally, our robustness tests also revealed some unexpected results regarding the importance of competitive aggressiveness of SMEs, particularly in combination with process innovations. While speculations may provide some potential insights into why competitive aggressiveness seems to be a distinct subdimension of EO when explaining SME growth, further research is needed.

In summary, we identify the following areas that future research could explore: (1) clarify if an emphasis on EO or process improvement is associated with different growth stages or dynamic states; (2) clarify the conditions for EO and process improvement being compatible strategies in relation to growth stages or dynamic states; (3) improve the understanding of the which types of organizational ambidexterity SMEs pursue and their effects; (4) clarify the compatibility of different types of process improvements with EO in SMEs; and (5) improve the understanding of the role of competitive aggressiveness in SMEs with high EO when explaining their growth.

Implication for practice

Our results inform SMEs about the difficulties of balancing entrepreneurial and efficiency focuses. We showed that young SMEs should apply one of the two strategies to achieve firm growth, while following both simultaneously is most likely not worth the effort. Specifically, according to previous studies, process improvement projects can be costly and often fail to achieve their objectives (Bakotic and Krnic 2017; Huang, Lee, and Chiu 2015). The lack of synergies when focusing both on EO and process improvement is often overlooked. Accordingly, when guided by most prior research, many SMEs might wrongly assume that following both strategies simultaneously might be an effective way to grow when, in reality, they do not benefit from the extra effort. Thus, our study may steer young SMEs away from attempts to employ an organic and mechanistic strategy at the same time but focus on only one of these. Which of the two strategies to pursue obviously depends on the firm’s capabilities and competitive environment.

Conclusion

Young SMEs can pursue different organizing strategies in order to secure firm growth. In this context, it is commonly accepted that both organic and mechanistic organizing strategies can support SMEs to achieve growth. However, in this paper, we showed that it is important to consider the incompatibilities of these two organizing strategies. Specifically, we showed that for young SMEs, it is likely not to be worth the efforts and risks involved in attempting to utilize both strategies, as they counter each other. Thus, a focus on one of the two strategies seems to be most beneficial with regard to achieving growth.

Disclosure statement

No potential conflict of interest was reported by the author(s).