Strategic Approach to Configurational Analysis of Entrepreneurial Orientation, Strategic Networking, and SME Performance within Emerging Markets of Selected Southeast European Countries

Abstract

The beneficial relationship of entrepreneurial orientation with performance has been extensively acknowledged in the literature. However, empirical evidence is not straightforward and requires consideration of the interplay of different variables, context, and rationales through which this causal complexity of the performance-enhancing mechanism of entrepreneurial orientation influences firm performance. In this paper we examine the way the entrepreneurial behavior of the organization unfolds and affects performance through specific configurations resulting from the simultaneous interaction of strategic networking and dynamic environment in the setting of Southeast European SMEs. We apply hierarchical regression to a sample of 963 small and medium-sized enterprises. Empirical findings provide support for applying the configurational approach and show that companies of high entrepreneurial orientation and high strategic networking operating in a dynamic environment achieve the highest effect on a business performance. Research results further indicate that strategic networking is a mechanism that achieves the greatest efficiency in a dynamic environment and with the presence of a firm’s entrepreneurial orientation. According to the research results, implications for research and practice are suggested.

1. Introduction

Entrepreneurial orientation (EO) is one of the leading theoretically and empirically examined constructs in the domain of entrepreneurship and strategy-making process literature, and it still continues to be a vibrant research area (Wales et al. 2021; Putniņš and Sauka 2020; Covin and Wales 2019). Generally, entrepreneurship as an activity involves the discovery, evaluation, and exploitation of opportunities to introduce new sources of value, such as products, services, processes, and business models, through organizing efforts that previously had not existed (Shane and Venkataraman 2000; Venkataraman 1997). It is precisely the characteristics of creativity, innovation, risk, and intention to grow that are crucial for the differentiation of, for example, startups, as a typical representative of an entrepreneurial venture, from other newly established entities. Following that hallmark, entrepreneurial orientation as an organizational attribute represents entrepreneurial behavior of the organization, which is manifested through decision-making styles, methods, practices, and managerial philosophies (Covin and Lumpkin 2011; Wiklund and Shepherd 2005). The most commonly used theoretical construction of EO is that which is composed of three dimensions of the entrepreneurial activity: innovativeness, proactiveness, and risk taking (Migliori et al. 2019; Fuentes-Fuentes et al. 2015; Rauch et al. 2009; Covin and Slevin 1989). Its relationship with performance has been widely present in research, and study findings mainly indicate that EO is commonly associated with superior firm performance (Morić Milovanović et al. 2021b; Putniņš and Sauka 2020; Rauch et al. 2009; Wiklund and Shepherd 2005; Wiklund 1999). However, the empirical evidence is not straightforward. Some studies also found an insignificant relationship (Messersmith and Wales 2013; Chaston and Sadler-Smith 2012; George et al. 2001; Covin and Slevin 1989) and even a negative relationship (Hart 1992). Moreover, empirical results show that EO–performance link is more complex and contingent upon different variables, context, and rationales through which EO influences firm performance (Luu and Ngo 2019; Lumpkin and Dess 2001). Therefore, the causal complexity of the performance-enhancing mechanism of entrepreneurial orientation still represents an open research question.

In order to more precisely explain the relationship of EO to performance, several models have been used. The universal direct effect model (Wiklund 1999; Zahra and Covin 1995) assumes that EO is directly and invariably beneficial to performance, while the contingency two-way interaction model explores the relationship between EO and a special characteristic of the external environment or EO’s relationship with internal organizational characteristics. For example, Wiklund and Shepherd (2005) found that entrepreneurial orientation leads to relatively high business performance in a non-dynamic environment. Meta-analysis conducted by Rauch et al. (2009) shows that the EO–performance link is less positive in small companies than in large ones. Lee and Chu (2013) in their study reveal that EO will lead to improved performance when company possesses valuable rare resources and capabilities. In accordance with the resource-based view of the firm, each firm’s resource bundle is unique and specific to the firm, and consequently not capable of easy imitation, thereby creating a firm’s competitive advantage and a long-term sustainable advantage. However, relying solely on the effect of one of the factors does not provide the full potential in explaining the possible effect that EO can have on performance. Finally, the configurational three-way interaction model offers a more comprehensive understanding of EO implications on performance (Morić Milovanović et al. 2021b; Wiklund and Shepherd 2005; Lumpkin and Dess 1996).

This paper examines the significance of the EO–performance relationship through modeling direct and indirect effect; specifically, it tests the relevance of the universal effect model, the contingency approach, and the configurational approach in explaining the link between entrepreneurial orientation and small business performance in the context of Southeast European SMEs, thereby adding the contextual dimension of Southeast European SMEs to the interpretation of research results and potential theoretical relationships of variables. Precisely, this study uses a direct, two-way, and three-way interaction approach to model the relationship between EO and performance. Several contingency models have been constructed to examine the moderating effect of environmental dynamism and strategic networking on the relationship of EO and performance. Generally, network configurations received less attention in the EO–performance literature. Strategic networking pertains to intentionally constructed relationships and activities among network partners that are collaborating to achieve the set goals (Hilmersson and Hilmersson 2021; Antoldi and Cerrato 2020; Möller and Svahn 2003). Long-term implications of networking relationships can be regarded as a key determinant of contemporary entrepreneurial activities and critical for maintaining a competitive position in the market (Schoonjans et al. 2013; Sedmak et al. 2011; Watson 2007). Previous research evidence suggests that network configurations can be a beneficial mechanism for achieving a positive influence on EO and performance (Kusumawardhani et al. 2009; Parida and Westerberg 2009). Therefore, we expect that the relationship between EO and performance is moderated by strategic networking. Furthermore, a three-way configurational model structures the simultaneous joint effect of EO, environmental dynamism, and strategic networking on the performance. We test these effects on the sample of 963 small and medium-sized firms operating in the Southeast Europe, suggesting greater explanatory power of the configurational approach in studying the impact of entrepreneurial orientation on firm performance and in the setting of Southeast European SMEs.

The remainder of the paper starts with a review of the theoretical background and developing the hypotheses. Following that, the next sections present the research methodology, empirical data, and results. In the final section, we discuss our findings and derive conclusions, where the implications for research and practices, as well as limitations are highlighted.

2. Literature Review and Hypotheses

2.1. Entrepreneurial Orientation and Performance

Entrepreneurial orientation represents an approach to the strategy-making process reflected in decision-making styles, methods, practices, and managerial philosophies, which are inherent to entrepreneurial behavior (Wales et al. 2021; Covin and Lumpkin 2011; Ireland et al. 2009; Wiklund and Shepherd 2005). As an organizational phenomenon, it implies the attributes of proactiveness, innovativeness, and risk taking (Covin and Slevin 1989; Miller 1983), which make companies entrepreneurial. By manifesting in this way, it actually shows how a firm operates rather than what it does (Lumpkin and Dess 1996). EO is a highly represented and fruitful area of research in the domain of entrepreneurship and strategy-making process literature, both theoretically and empirically (Wales et al. 2021; Balasubramanian et al. 2020; Ferreira et al. 2019; Migliori et al. 2019; Saeed et al. 2014; Rauch et al. 2009; Covin and Slevin 1989; Miller 1983).

As an organizational attribute, entrepreneurial orientation is conceptually and empirically most confirmed through the understanding of the three dimensions of the manifestation of entrepreneurial activity: innovativeness, proactiveness, and risk taking (Guzmán et al. 2020; Migliori et al. 2019; Amin et al. 2016; Fuentes-Fuentes et al. 2015; Rauch et al. 2009; Covin and Slevin 1989; Miller 1983). However, certain scholars propose some additional dimensions of EO in order to highlight the multidimensionality of the construct to capture EO (Campos and Valenzuela 2013; Lee and Chu 2013; Zulkifli et al. 2013; Wang 2008; Lumpkin and Dess 1996). The essential dimension that characterizes a firm’s entrepreneurial orientation is innovativeness. Innovativeness refers to a firm´s propensity to create and exploit new products, markets, technologies, or business models through the process of learning and experimentation, which may result in better market position and significantly improved business performance (De Vincenzi and Cunha 2021; Ngoc Mai et al. 2019; Saunila et al. 2014; Leiponen 2000). Closely related to innovation is the dimension of proactiveness. Proactiveness is described as active engagement in searching for new opportunities (Lumpkin and Dess 1996) and thus contributes to achieving a greater degree of innovativeness. In line with entrepreneurial behavior, there is also a risk-taking dimension, which is reflected in the readiness to exploit opportunities with uncertain but also higher returns (Miller 1983).

The eelationship between EO and business performance has been widely present in the research literature. Various studies have shown a significant positive impact on company performance (Milovanović et al. 2016; Khedhaouria et al. 2015; Casillas and Moreno 2010; Wiklund 1999; Zahra and Covin 1995), and such a relationship is confirmed in different national contexts, encompassing nations other than the US and Europe (Semrau et al. 2016; Milovanović and Wittine 2014; Kraus et al. 2012; Rauch et al. 2009). Innovativeness and proactivity in modern global and intensively dynamic business environments are certainly desirable features of organizational activity. Finding new sources of value creation in the context of new products, management concepts, and business models means resilience in unpredictable and turbulent economic conditions, such as the pandemic caused by coronavirus disease (COVID-19) (Azazz and Elshaer 2022; Elshaer 2022; Liu et al. 2022; Jialu et al. 2021). Therefore, it is reasonable to expect that each of the three components of entrepreneurial orientation has a positive effect on Southeast European SMEs’ performance; thus:

Hypothesis 1 (H1).

Entrepreneurial orientation has a universal positive effect on performance of Southeast Europe SMEs.

2.2. The Configurational Approach to the Relationship between Entrepreneurial Orientation and Performance

However, the empirical findings imply that the relationship between EO and performance is more complex and context-dependent (Lumpkin and Dess 1996). For example, Rauch et al. (2009) shows that the EO–performance link is less positive in small companies than in large ones. Therefore, it is reasonable to believe that the nature of such a relationship and its strength may depend on the specifics of the external environment and internal organizational characteristics, which has also been empirically examined and confirmed by a plethora of studies linking entrepreneurial orientation and environment (Zahra and Covin 1995; Covin and Slevin 1989), cultural and macroeconomic contingencies (Semrau et al. 2016; Saeed et al. 2014; Arbaugh et al. 2005), firm size (Rauch et al. 2009), financial resources (Wiklund and Shepherd 2005), cooperative principles (Guzmán et al. 2020), and leadership (Engelen et al. 2015). Meta-analyses of entrepreneurial orientation and business performance conducted by Rauch et al. (2009) included an assessment of potential internal and environmental moderators affecting this relationship and a recommendation for assessing the additional moderators. The meta-analysis by Saeed et al. (2014) also revealed the effect of moderators such as national-level factors, economic, political, and regulatory factors on performance implications of entrepreneurial orientation. Considering the impact of moderators on the performance implications certainly provides a potentially greater coverage of the mechanism of action of EO and useful implications for practitioners, because the application of the entrepreneurial approach is risky and financially demanding.

Structuring the impact of individual variables on business performance has been covered in the literature through a contingency two-interaction model between EO and a special characteristic of the external environment or connecting EO and internal organizational characteristics (Morić Milovanović et al. 2021b). Zahra and Covin (1995) in their study demonstrated a greater positive impact of EO on performance in hostile environments compared to more benign environments. Furthermore, Lee and Chu (2013) reveal that EO will lead to improved performance when a company possesses valuable rare resources and capabilities. Nevertheless, solely relying on the effect of one of the factors, environmental or internal characteristics, does not provide the full potential in explaining the possible effect that EO can have on performance. A model that structures the joint effect of EO and both the external environment and internal organizational characteristics is a three-way interaction model, which simultaneously arranges the relationships of internal organizational characteristics and environmental characteristics into configurations. The strength of the EO–performance link depends on such a joint relationship of variables and thus provides a more complete and clear perspective of the explanation of the mechanism of action of EO on performance. Such an approach represents the configurational approach introduced by Lumpkin and Dess (1996).

In the remainder of the paper, we develop hypotheses concerning the performance implications of EO and firstly examine the significance of the two-way contingency approach model between EO and an environmental dynamism, as well as EO and strategic networking. Next, we hypothesize the simultaneous interactive relationships of EO, strategic networking, and environmental dynamism using the configurational model on a sample of Southeast European SMEs.

2.2.1. The Interaction of Entrepreneurial Orientation and Environmental Dynamism

The environment is one of the most researched contextual variables by researchers in the strategic management and organization theory literature (Wang et al. 2021; Rauch et al. 2009; Child 1972). The impact of the environment can be perceived through the degree of dynamism of the challenges facing the company in the external environment within which it operates. It represents the rate of change in market conditions and industry settings (Soto-Acosta et al. 2018). Generally, in stable and more predictable business environments, firms will not benefit from opportunity-seeking and risky behaviors as much as firms operating in a dynamic environment. A dynamic environment implies a great amount of uncertainty and complexity of environmental factors, such as markets, competitors, technologies, and business models (Dyduch et al. 2021; Chirico and Bau’ 2014; Baum and Wally 2003). Such a distinctly volatile environment represents a fruitful ground for spotting, creating, and launching new opportunities and imposes a constant need for a high level of innovation, i.e., finding new sources of value in order for the firm to maintain a competitive position in the market (Musawa and Ahmad 2019). It can be concluded that firm´s entrepreneurial behavior in such conditions is necessary and that it has a strong positive relationship with performance.

Empirical research confirms the above and suggests that EO’s impact on business performance is stronger in a highly dynamic, uncertain, and hostile environment (Morić Milovanović et al. 2021a; Bauweraerts 2018; Chirico and Bau’ 2014; Wiklund and Shepherd 2005). Furthermore, Zahra (1993) found a negative relationship linking entrepreneurship and performance in the context of firms operating in solid and more predictable environments. Bauweraerts (2018), in the empirical setting of private family firms, suggested that the best fit between family management, entrepreneurial orientation, and performance is achieved in conditions when EO and environmental dynamism are low. Entrepreneurial behavior entails very risky activities, requiring the investment of significant financial and other resources, a willingness to make changes, and an appropriate response. In the static environment, it is less likely for firms to take advantage of such strategies. Therefore, we formulate our next hypothesis:

Hypothesis 2 (H2).

Relationship between entrepreneurial orientation and performance of Southeast Europe SMEs is moderated by environmental dynamism.

2.2.2. The Interaction of Entrepreneurial Orientation and Strategic Networking

Entrepreneurial orientation, as a strategy-making process that implies innovativeness, proactiveness, and risk-taking activities of the company in order to achieve competitiveness and a position ahead of the competitors, entails a multitude of resources at its disposal, and it can therefore be argued that EO is a resource-consuming strategy (Teng 2007; Wiklund and Shepherd 2005). According to the resource-based view (Penrose 1959), a firm’s competitiveness can be explained by the possession of valuable resources which, due to their characteristics, such as rarity, imperfect imitativeness, and non- substitutability, provide a certain barrier and potential to create greater profitability (Barney 1991). Creating such an advantage is a difficult task for small businesses compared to large ones, and the scarcity of resources is one of their main challenges in the efforts they make to maintain market position and increase growth prospects in the future. This also applies to new ventures, whose lack of legitimacy is associated with difficulties in achieving efficient resource exchange, which increases the likelihood of their organizational failure and mortality (Tornikoski and Newbert 2007; Shane and Foo 1999). This resource restriction can act as a limitation for companies in creating entrepreneurial strategies and designing future actions, and therefore, access to resources is especially important for facilitating EO. According to Jarillo (1989), “the essence of entrepreneurship lies in the ability and willingness to use external resources”. It is the pursuit of entrepreneurial behavior that affords companies a greater ability to access resources, as well as their organization (Li et al. 2011), and it appears that companies which are successful in obtaining resources through establishing various relationships with external stakeholders will achieve greater effectiveness of EO, i.e., a stronger impact on performance (Hilmersson and Hilmersson 2021; Antoldi and Cerrato 2020).

The ability to obtain external resources is critical for the exploitation of entrepreneurial activities and their transformation into performance results (Kim et al. 2017). Resource dependence theory proposes two ways for firms to obtain these resources: engaging with their environment and creating different forms of interorganizations (Brouthers et al. 2015; Singh et al. 2011). To achieve such interaction with potential partners, companies rely on networking practices. Through various network linkages, a venture can obtain different kinds of scarce and valuable resources, such as specialized knowledge, access to innovative technology, access to scarce raw materials, human resources, and innovative financial technologies, and this can empower firms in pursuing innovative, proactive, and risk-taking strategies (Karami and Tang 2019). By joining the network, companies are able to reduce production costs, achieve greater flexibility and efficiency in conducting business processes, better absorb market uncertainties (Schoonjans et al. 2013; Sedmak et al. 2011), and achieve economies of scope and scale (Watson 2007), thus increasing the likelihood of achieving a higher degree of EO efficiency, as this reduces the risk inherent in entrepreneurial behavior.

Due to the nature of modern business processes, the establishment and management of network relationships is imposed as a “modus operandi”, and long-term implications of such relationships are critical to maintaining a competitive position in the market. Strategic networking refers to a set of relationships which can be described as intentionally constructed activities among network actors that are purposefully collaborating towards certain goals (Hilmersson and Hilmersson 2021; Möller and Svahn 2003). Unlike emergent networks, these networks are focused on a specific context of strategically intentional actor interactions (Möller and Rajala 2007). Some general antecedents that can be linked to the success of a strategic network are trust, commitment, reputation, communication, and cooperation (Milovanović et al. 2020; Chang and Harwood 2001). All of these factors have been empirically confirmed to significantly contribute to strategic network performance (Milovanović et al. 2020; Schoonjans et al. 2013; Konsti-Laakso et al. 2012; Lee et al. 2010; Stanko et al. 2007; Chang and Harwood 2001). Furthermore, digital technologies provide a wide range of innovation opportunities in the modalities of entrepreneurial activities and emphasize openness, interaction, and networking as key determinants of contemporary entrepreneurial activities, such as the open innovation paradigm (De Vincenzi and Cunha 2021; Chesbrough 2003) and the concept of co-creation (Takahashi and Takahashi 2021; Ramaswamy and Ozcan 2018).

Prior empirical evidence suggests that network relationships can be a mechanism for achieving a higher degree of EO and performance (Kusumawardhani et al. 2009; Parida and Westerberg 2009; Sirmon et al. 2007; Lerner et al. 1997) and therefore points to the premise that the strategic networking processes affect the strength of the EO–performance relationship. However, empirical evidence is not consistent, and the results of existing research put forward some contradictory insights as well. Strategic networking has also been recognized as a cause of a firm’s underperformance, mostly because of the network partner’s opportunistic behavior (Parida et al. 2010; Miles et al. 1999) due to the unbalanced relations of the networking partners, especially if one company is significantly larger. Therefore, we propose that strategic networking may serve as a contingency that shapes the relationship between EO and performance and set forth the following hypothesis:

Hypothesis 3 (H3).

Relationship between entrepreneurial orientation and performance of Southeast Europe SMEs is moderated by strategic networking.

2.2.3. The Configuration of Entrepreneurial Orientation, Strategic Networking, and Environmental Dynamism

In order to more precisely explain the impact of EO on performance, in addition to the moderating impact of external environment dynamics and strategic networking, we will test the interaction of all three variables, applying a configurational approach (Wiklund and Shepherd 2005; Lumpkin and Dess 1996). The configurational approach implies a three-way interaction model that structures the joint influence of several variables in configurations, i.e., EO and the observed factors of internal and external environment. With the purpose of obtaining a clearer and more comprehensive picture of the implications of EO on performance, it is necessary to consider complex combinations of variables in simultaneous interaction, because different contexts have different effects. Therefore, in explaining the variations of EO implications on performance, it is necessary to consider how EO and strategic networking activities make an impact within different contexts, i.e., different dynamics of the external environment.

According to the configurational approach, the firm’s potential to achieve higher performance arises in situations where the firm is aligned on many constructs (Linton and Kask 2017; Ketchen et al. 1993). This implies the compliance of certain characteristics of the organization with those of the environment. It can be assumed that companies that are more successful in aligning these characteristics will achieve better business results. Entrepreneurially oriented strategies are inherently risky and very resource-intensive. As suggested in the previous section, a failure to align the firm’s EO with the dynamics of the environment may result in unfavorable performance impact, such as in the situation of implementing entrepreneurially oriented strategies in a stable and benign environment. Similarly, the acquisition of resources from the external partners through networking practices, as a fundamental feature of entrepreneurial behavior and the way of unfolding the exploitation of entrepreneurial strategy (Kim et al. 2017; Shane 2000), has its drawbacks, i.e., it carries a certain level of hazard. Empirical research suggests that in the circumstances of networking with suppliers, firms can encounter a “lock-in effect” as a consequence of increased dependency on a certain supplier. Furthermore, significant reliance on customers, in searching for the innovative opportunities, may constrain a firm’s innovativeness (Parida et al. 2010). Therefore, it can be assumed that companies operating in a dynamic environment will achieve more benefit and better performance if they pursue EO and are successful in strategic networking practices. In a dynamic environment of rapid change, ever shorter product life cycle, and significantly rapid changes in customer preferences, it is desirable to achieve such relationships, while in a stable environment, it can pose additional risks and jeopardize performance. Therefore, we formulate the following hypotheses:

Hypothesis 4 (H4).

Performance of Southeast Europe SMEs is explained by configurations of entrepreneurial orientation, strategic networking, and environmental dynamism.

Hypothesis 4a (H4a).

Performance of Southeast Europe SMEs is highest for firms with a high degree of entrepreneurial orientation and high degree of strategic networking and in dynamic environment than for other configurations.

Hypothesis 4b (H4b).

Performance of Southeast Europe SMEs is lowest for firms with a high entrepreneurial orientation, low degree of strategic networking, and in stable environment than for other configurations.

3. Research Method

3.1. Research Design

The purpose of this research is to test the EO–performance relationship through the contingency model and the configurational model with the simultaneous joint effect of EO, environmental dynamism, and strategic networking on a large sample of Southeast European SMEs. In accordance with the research purpose, a quantitative research design will be applied. As an analytical method for testing whether the universal, contingency, or configurational models best fit the data, moderated (hierarchical) linear regression analysis was used. In hierarchical linear regression analysis, control, main, and moderating variables were first added, followed by the two-way and three-way interactions, respectively. Variables used in the analysis were mean-centered because many research papers imply it can improve the interpretability of the results. Results have been further tested by several robustness tests, including multicollinearity, heteroscedasticity, and autocorrelation, where there was an absence of non-response bias and common method bias, as well.

3.2. Sample

The sampling frame was taken from the databases of consulting companies operating in the former Yugoslav countries (Slovenia, Croatia, Serbia, Bosnia and Herzegovina, Monte Negro, and North Macedonia), where a random sample of small and medium-sized firms was taken. The European Union definition of small and medium-sized enterprises was followed, meaning that firms were classified as follows: micro firms with less than 10 employees, small firms with 10–49 employees, and medium-sized firms with 50–249 employees. The online questionnaire was sent to the email addresses of owners and CEOs of the firms where the questionnaire was accompanied by a letter describing the purpose of the study. The questionnaire was translated from English to each official language of the observed countries, and then translated back into English to ensure that accuracy and compliance were not compromised by potential errors due to language differences. In total, 9000 firms were contacted during the period from December 2019 until April 2020, out of which 963 responded and correctly filled out an email questionnaire, which corresponds to a response rate of 10.7%. Out of 963 firms that were willing to participate in this research, 403 were micro firms (41.8%), 392 were small firms (40.7%), while 168 were medium-sized firms (17.5%). When analyzing the sample according to the industry sector, the majority of the firms operated in the wholesale/retail sector (22%), manufacturing sector (20%), and construction sector (13%). Sample demographic analysis reveals that 71% of the respondents were either firm owners or firm directors, 83% had bachelor’s degree or higher (MBA/master/PhD), and 74% worked for the firm for more than 7 years. Detailed sample demographics are shown in

Table 1. Demographics: firm and entrepreneurs’ characteristics (n = 963).

Variable	Frequency	Percentage	Variable	Frequency	Percentage
Size			Education
Micro	403	42%	Elementary school	6	1%
Small	392	41%	High school	162	17%
Medium	168	17%	Bachelor	528	55%
Role			MBA/Master	210	22%
Owner	509	53%	Doctorate	57	6%
Director	175	18%	Experience
Management	217	23%	<1 year	27	3%
Other	62	6%	1–4 years	134	14%
Gender			5–7 years	91	9%
Male	640	66%	>7 years	711	74%
Female	323	34%

.

3.3. Variables and Measures

Business performance was measured by a modified instrument developed by Gupta and Govindarajan (1984), where the respondents were asked to indicate on a seven-point Likert-type scale the extent to which sales growth rate, market share, and market development are important for their business. Afterwards, respondents were asked to indicate on another seven-point Likert-type scale the extent of satisfaction with the achieved performance of these three indicators. To minimize the potential of the individual bias, Naman and Slevin’s (1993) approach has been adapted where ‘importance’ scores were mathematically adjusted to sum up to 1. These ‘importance’ scores were then multiplied by the ‘satisfaction’ scores to compute the weighted average performance index. The computed performance index has a mean of 4.76, a standard deviation of 1.17, a range of 6.00, and a Cronbach’s α value of 0.89. A seven-point Likert-type question scale developed by Covin and Slevin (1989) was used for measuring entrepreneurial orientation (EO). The EO score has a mean of 4.26, a standard deviation of 1.00, a range of 5.73, and a Cronbach’s α value of 0.71. As when measuring EO, five different seven-point Likert-type question scales were used to measure strategic networking (SN). More precisely, Allen and Meyer’s (1990) scale was used for measuring commitment, Garbarino and Johnson’s (1999) scale for measuring trust, Hansen et al. (2008) scale for measuring reputation, Sivadas and Dwyer’s (2000) scale for measuring communication, and Eriksson and Pesamaa’s (2007) scale for measuring cooperation. The strategic networking score has a mean of 5.27, a standard deviation of 0.92, a range of 5.60, and a Cronbach’s α value of 0.76. In the same manner, environmental dynamism (DYN) was measured using Miller and Friesen’s (1982) seven-point Likert-type question scale, where the ED score has a mean of 3.73, a standard deviation of 1.22, a range of 6.00, and a Cronbach’s α value of 0.66. The size of the firm and industry could potentially affect the overall performance, considering various organizational and environmental contexts in which the firm operates (Wiklund and Shepherd 2005). Moreover, different cultural and contextual country-specific factors could potentially influence the firm’s performance as well, which is why these three variables (country, firm size, and industry) were included as control variables. In order to determine the firm size, respondents were asked to state the number of their employees, and based on the provided answers, were further classified according to the EU definition of SME as a micro firm, a small firm, or a medium-sized firm. Similar to the firm size, in order to determine the main industry in which the firm operates, respondents were asked to choose among the following industries: agriculture, manufacturing, construction, transportation/communications, wholesale/retail, tourism/hospitality, financial services, and other.

4. Results

Table 2. Means, S.D.s, and correlations (n = 963).

	Mean	S.D.	1	2	3	4	5	6	7	8	9	10	11
1. Country	3.29	1.45	1.00
2. Firm size	1.75	0.73	−0.038	1.00
3. Industry	4.86	2.20	0.065 *	−0.276 **	1.00
4. EO	4.26	1.00	−0.033	0.020	0.033	1.00
5. SN	5.27	0.92	0.098 **	0.000	0.058	0.445 **	1.00
6. DYN	3.73	1.22	−0.051	−0.078 *	−0.049	0.257 **	0.094 **	1.00
7. Performance	4.76	1.17	−0.037	0.101 **	−0.004	0.363 **	0.374 **	−0.091 **	1.00
8. EO × SN			0.005	−0.045	0.003	−0.113 **	−0.177 **	0.025	−0.095 **	1.00
9. EO × DYN			−0.022	−0.037	0.014	0.072 *	0.025	0.007	0.084 **	0.146 **	1.00
10. SN × DYN			−0.061	−0.059	0.058	0.026	−0.071 *	0.054	−0.057	0.224 **	0.454 **	1.00
11. EO × DYN × SN			−0.031	0.059	−0.056	0.205 **	0.216 **	0.390 **	0.095 **	0.002	−0.114 **	−0.147 **	1.00

Notes: * p < 0.05 (2-tailed); ** p < 0.01 level (2-tailed).

depicts values for mean, standard deviation, and correlation of the observed variables. The correlation coefficients among the observed independent variables are relatively modest, ranging from −0.276 to 0.454. Among independent variables, statistically significant positive correlation coefficients with performance include entrepreneurial orientation (0.363) and strategic networking (0.374), while environmental dynamism has a negative correlation (−0.091). When observing correlations between interaction terms and performance, it can be concluded that only the two-way interaction between SN and DYN is not statistically significant, while all the others are. More precisely, the correlation between performance and the two-way interaction of EO and SN (−0.095) is of negative character, while the two-way interaction of EO and DYN (0.084) and the three-way interaction between EO, SN, and DYN (0.095) show positive correlation.

Table 3. Business performance: universal, contingency, and configurational model (n = 963).

	Model 1 Control Variables		Model 2 Universal Model		Model 3 Contingency Model		Model 4 Configuration Model
	β	S.E.	β	S.E.	β	S.E.	β	S.E.
Control variables
Country	−0.028	0.026	−0.048 **	0.023	−0.050 **	0.023	−0.048 **	0.023
Firm size	0.173 ***	0.054	0.120 **	0.048	0.121 **	0.048	0.114 **	0.048
Industry	0.015	0.018	−0.007	0.016	−0.005	0.016	−0.005	0.016
Main variable
EO			0.339 ***	0.038	0.335 ***	0.038	0.332 ***	0.038
Moderating variables
Str. networking (SN)			0.343 ***	0.041	0.334 ***	0.041	0.322 ***	0.042
Dynamism (DYN)			−0.181 ***	0.028	−0.176 ***	0.028	−0.196 ***	0.031
2-way interactions
EO × SN					−0.005	0.033	−0.010	0.033
EO × DYN					0.082 ***	0.028	0.085 ***	0.028
SN × DYN					−0.074 **	0.032	−0.066 **	0.032
3-way interactions
EO × DYN × SN							0.041 *	0.023
R²	0.012 ***		0.232 ***		0.241 ***		0.243 ***
Adjusted R²	0.009 ***		0.228 ***		0.233 ***		0.235 ***
∆R²	0.012 ***		0.220 ***		0.008 ***		0.002 ***

Notes: * p < 0.10; ** p < 0.05; *** p < 0.01.

depicts four different hierarchical regression models where each of the models reflects results of the hypothesis testing. As control variables, country, firm size, and industry were added to Model 1. Independent variables (EO, SN, and DYN) were added to Model 2 (universal model), which provides the answer to Hypothesis 1. The two-way interaction terms were added to Model 3 (contingency model), which gives an answer to Hypotheses 2 and 3. Lastly, the three-way interaction term was added to Model 4 (configurational model), which provides the answer to Hypothesis 4.

Control variables (country, firm size, and industry) explain 1.2% of performance variation (p < 0.01). The universal effect of EO, SN, and DYN accounts for an additional 22% of the variation in performance (p < 0.01), where all three variables are statically significant; however, EO (β = 0.339, p < 0.01) and SN (β = 0.343, p < 0.01) have a positive effect on performance, while DYN (β = −0.181, p < 0.01) does not. Therefore, there is enough evidence to confirm Hypothesis 1, that EO has a universal positive effect on the performance of Southeast Europe SMEs. The contingency model explains an additional 0.8% of performance variation (p < 0.01), where only the two-way interaction between EO and SN is not statistically significant, while the two-way interaction between EO and DYN is statistically positively significant (β = 0.082, p < 0.01) and the two-way interaction between SN and DYN is statistically negatively significant (β = −0.074, p < 0.05). Therefore, it can be argued that Hypothesis 2 is supported, while Hypothesis 3 is not. Stated differently, there is enough evidence to support the claim that the relationship between entrepreneurial orientation and performance of Southeast Europe SMEs is moderated by the environmental dynamism (H2). On the other hand, there is not enough evidence to support the claim that the relationship between entrepreneurial orientation and performance of Southeast Europe SMEs is moderated by strategic networking (H3). Figures 2 and 4 provide additional evidence to support previous statements, supporting Hypothesis 2, while negating Hypothesis 3. The configuration model, when including the three-way interaction term between EO, SN, and DYN, accounts for an additional 0.02% of performance variation (p < 0.01). Furthermore, the three-way interaction term has a statistically significant positive effect on performance (β = 0.041, p < 0.10), confirming Hypothesis 4. Stated differently, there is enough evidence to support the claim that the performance of Southeast Europe SMEs is explained by configurations of entrepreneurial orientation, strategic networking, and environmental dynamism.

To better understand the obtained results, we have plotted both two-way (Figures 2–4) and three-way (Figure 1) interaction effects. As outlined by Cohen et al. (2014), whose procedure we have followed, while entering the range of EO values, the values of SN and DYN were set at one standard deviation above the mean and one standard deviation below the mean. As a result of this procedure, Figure 1 depicts illustration of the three-way interaction effect of EO, SN, and DYN on performance under the four observed conditions.

As depicted in Figure 1, all lines slope upward, meaning that performance increases with the increase in EO regardless of the levels of SN or DYN, further confirming Hypothesis 1. What is important to point out is the fact that although performance increases with increasing EO for all configurations, it increases at a faster rate for those firms operating in a dynamic environment and with a high degree of SN compared to all other combinations of SN and DYN, thus supporting Hypothesis 4a. This means that there is enough evidence to support the claim that the performance of Southeast Europe SMEs is highest among firms with a high degree of entrepreneurial orientation and strategic networking operating in a dynamic environment compared to other configurations. However, Figure 1 does not provide support for Hypothesis 4b since the lowest performing configuration is for firms with a high degree of EO and a low degree of SN operating in a dynamic environment. Therefore, there is not enough support to claim that the performance of Southeast Europe SMEs is lowest among firms with a high entrepreneurial orientation and a low degree of strategic networking operating in a stable environment compared to other configurations.

Figure 2 provides additional evidence that the interaction effect between EO and DYN exists when placed in the relationship with small firm performance. Moreover, Figure 3 provides additional support that the interaction effect exists between SN and DYN but is of negative value. Lastly, Figure 4 provides further evidence that there is no interaction effect between EO and SN.

5. Discussion and Conclusions

5.1. Implications for Research

Entrepreneurial orientation as an organizational-level phenomenon is conceived as an entrepreneurial behavior and a dimension of a firm’s strategic posture (Lumpkin and Dess 1996; Covin and Slevin 1991). Characterized primarily by the propensity to constantly create and exploit new opportunities, a forward-looking perspective by active engagement in searching for innovative opportunities, and a readiness to exploit opportunities with uncertain returns, entrepreneurial orientation appears relevant for the competitiveness of firms operating in a dynamic, complex, and challenging environment. Its beneficial relationship with performance is a well-researched topic in the literature and is confirmed by many empirical studies concerning various contexts. In exploring its relationship with a firm´s performance, critical contingencies have been examined by strategic management researchers, including external environment and internal organizational variables, primarily through contingency two-way and configurational three-way models. While the contingency model does not provide a sufficiently satisfactory insight into the implications of the effect of the complex EO phenomenon on performance, a more complete understanding of small business performance can be obtained through observing the joint simultaneous effect of variables through the three-way contingency model.

The main purpose of this study was to examine the relationship of EO with the performance and the way it unfolds further through the contingency model, as well as the concomitant effect of strategic networking and environmental dynamism, through the configurational model in the context of Southeast European SMEs. By integrating the configuration approach, our study extends the understanding of the specific configurations resulting from the simultaneous interaction of strategic networking and dynamic environment in the setting of Southeast European SMEs. Generally, network configurations received less attention in the EO–performance literature, and prior research suggests that network configurations can be a beneficial mechanism for EO and performance.

Our results confirm that regardless of environmental dynamics and the intensity of strategic networking, performance increases with the increased EO, which validates the findings from previous studies focused on researching the direct (universal) effects EO has on small firm performance (Bauweraerts 2018; Brouthers et al. 2015; Engelen et al. 2015). Considering the interaction between EO and environmental dynamism, the study results suggest a positive impact on firm performance. This finding is consistent with the findings of Dess et al. (1997). An interesting finding is that environmental dynamism perceived through the main-effects-only model leads to negative performance. However, the interaction effect of EO and environmental dynamism generates positive performance implications and indicates that the association between environmental dynamism and firm performance may depend on the firm’s entrepreneurial orientation. Concerning the moderating effect of strategic networking on the EO–performance relationship, a statistically insignificant result may indicate that the relationship between strategic networking and performance may be more complex, which has been further confirmed through the inclusion of the three-way configuration of EO, strategic networking, and environmental dynamism. The statistically significant and positive effect on performance suggests that the configurational model is more relevant than the contingency model. Moreover, the highest effect was achieved by companies of a high entrepreneurial orientation and high strategic networking operating in a dynamic environment. This finding is opposed to the finding of Wiklund and Shepherd (2005), whose empirical contribution suggests that the effect of EO on performance is higher in a stable environment. Contrary to our assumption, the performance effect was the smallest for firms with a high entrepreneurial orientation and low strategic networking doing business in a dynamic environment. According to the configurational model, strategic networking is a mechanism that achieves the greatest efficiency in a dynamic environment in the presence of a firm’s entrepreneurial orientation. Strategic networking practices also carry certain risks and shortcomings (Parida et al. 2010; Miles et al. 1999), so it can be assumed that they achieve a stronger effect over time when trust and commitment between partners is gained and when these relationships are at higher levels and more intensely present.

Our findings on the sample of Southeast European SMEs underscore the support for the configurational approach in explaining EO, strategic networking, and environmental dynamism implications on small business performance and generally confirm the relevance of the configurational approach and its greater explanatory power in studying the impact of EO on firm performance. Furthermore, the results highlight the critical importance of pursuing high entrepreneurial posture and strategic networking practices in the context of a dynamic and challenging environment. According to the obtained empirical results, strategic external relations that small and medium enterprises create with partners through various forms of strategic networking represent an effective mechanism for exploiting their entrepreneurial strategy in the context of high environmental dynamics. The aforementioned is similar to the results of Jiang et al. (2018), suggesting that acquiring valuable resources from network partners is an underlying mechanism by which EO contributes to firm performance. In the setting of high dynamism and rapid changes in the environment, the strategy of experimentation, innovation, and proactive and risky endeavors is effectively achieved through practices and different modalities of strategic networking. According to such results, we did not confirm that the combination of a low level of strategic networking and a stable environment achieved the lowest performance growth, which again confirms the mechanism of strategic networking as an effective means of implementing EO in a dynamic environment. These results suggest that EO can be regarded as a good strategy for small and medium businesses operating in a crisis or challenging periods, such as the Covid pandemic, which require innovation and the transformation of the current strategy and business model.

Furthermore, our findings point to the notion that strategic networking and environmental dynamics act simultaneously on the implications of EO on performance. Environmental dynamics revealed a negative impact on the performance in the universal model, while the configuration of high EO, low SN, and high environmental dynamics proved to be the combination that has the least favorable impact on performance. It can be concluded that performance may be enhanced through the alignment of strategic networking and dynamic environment. According to the obtained results of this research, it can be concluded that strategic networking is a variable in need of further research and validation in studying its relationship with entrepreneurial orientation and performance. Primarily this refers to the application of multivariate configuration methods in combination with the contingency of external variables in different contexts.

5.2. Implications for Practice

The study also provides practical implications for management. Generally, the results of our research confirm the positive effect of EO on the performance of small and medium-sized companies. Managers can benefit from pursuing innovative strategies, being proactive, and taking risky opportunities. In particular, this refers to the importance of developing and nurturing entrepreneurial behavior in a challenging and dynamic environment, which implies a readiness for creativity and experimentation and finding and exploiting new sources of value: products, services, business models, etc. Our results also indicate that applying a strategic networking practice is an effective mechanism for operationalizing an entrepreneurial strategy for small and medium-sized companies within the context of a dynamic environment. Furthermore, managers should pay attention to carefully designing relationships with external partners, especially to the processes of building a trust, commitment, reputation, communication, and cooperation, which, according to the results obtained, reduces the risk inherent to entrepreneurial behavior.

5.3. Limitations

Firstly, the sample of SMEs representing the Southeast European countries affects the generalization of the results. Secondly, the data collected are based on the subjective perception of respondents, where only one representative of the firm participated in the questionnaire. Future studies may consider the inclusion of several firm representatives in order to increase the validity of the obtained results. Furthermore, variables were measured based on subjective data. It can be assumed that the use of objective data would increase the validity of the research results. A non-response bias and common method bias analysis have been conducted in this study, and results showed that both a non-response bias and a common method bias were not present. Finally, some studies indicate that using objective data produces similar results concerning the EO–performance estimates as subjective self-reported measures (Rauch et al. 2009; Kale et al. 2002). In this study, we perceived EO as a unidimensional construct, while its conception as a multidimensional construct can provide additional insights into explaining its relationship to performance in different environmental conditions (Su et al. 2019). Firm performance was observed at one point in time, which represents another limitation. Future research should aim at performing a longitudinal study and increasing the model´s explanatory power.