Entrepreneurial marketing orientation of the Polish and Finnish SMEs and its environmental determinants

Abstract

Purpose

The entrepreneurial marketing orientation (EMO) has been studied primarily in developed countries. The past research has focused on entrepreneurial marketing dimensions and their relationship with selected small- and medium-sized firm (SME) activities, strategic orientations or performance. Scholars have not paid enough attention to the EMO determinants. This study aims to investigate whether the SMEs originating from different countries, including the post-transition market, differ in their entrepreneurial marketing approach and checks its external determinants connected with environmental turbulence.

Design/methodology/approach

A total of 219 Polish and 81 Finnish manufacturing SMEs, serving mainly business-to-business clients, were surveyed using the mixed-mode computer assisted telephone interview/computer assisted web interview method between 2020 and 2021. Structural equation modelling, multigroup confirmatory factor analysis analysis, analysis of variance and T-tests were applied.

Findings

The metric and partial scalar invariance of the EMO scale used in Finland and Poland was found. The authors showed that Finnish firms represent a more robust entrepreneurial posture in marketing than Polish ones. The export market turbulence and the perceived crisis influence are the environmental determinants of EMO level, while the industry technological development level is not.

Research limitations/implications

The conducted analyses allowed to identify EMO determinants, verify the entrepreneurial marketing measurement concept in a new country (Finland) and show the differences in EMO between SMEs from a less and more developed country.

Originality/value

The existing literature lacks empirical data on the external EMO determinants and inter-country comparisons. This study shows the differences in EMO level of companies from different country backgrounds and points to the market turbulence as its determinant.

Citation

Kowalik, I., Danik, L. and Pleśniak, A. (2022), "Entrepreneurial marketing orientation of the Polish and Finnish SMEs and its environmental determinants", Journal of Business & Industrial Marketing, Vol. 37 No. 13, pp. 167-181. https://doi.org/10.1108/JBIM-07-2021-0333

1. Introduction

Over the past three decades, numerous studies on the marketing/entrepreneurship interface have emphasized entrepreneurial marketing (EM) as a concept that reflects the idiosyncrasies of marketing in small- and medium-sized firms (SMEs) (Hills et al., 2008; Jones and Rowley, 2011; Eggers et al., 2020). Opposite to the classic marketing approach comprising deliberate and carefully planned market segmenting, positioning and using 4 P tools (Kotler, 1967), EM is defined as “the proactive identification and exploitation of opportunities for acquiring and retaining profitable customers through innovative approaches to risk management, resource leveraging and value creation” (Morris et al., 2002, p. 5). As SMEs face both uncertain market conditions and constrained resources and, in their case, the loss or gain of a single customer may change the future, EM is said to be a significant determinant of their growth and survival (Becherer et al., 2012).

The building blocks of EM recognised in previous studies include proactiveness, opportunity-focus, propensity to innovate, calculated risk-taking, customer intensity, exploiting markets, resource leveraging and value creation. In general, the marketing capabilities of entrepreneurially oriented firms are worth analysing as they may determine market success (Sadiku-Dushi et al., 2019; Hagen et al., 2019). As researchers recognise different entrepreneurial marketing orientation (EMO) characteristics, the available studies differ in the considered number, specificity and interdependence of the EMO dimensions (Sadiku-Dushi et al., 2019). The review of research showed that the overall building of EM is still not defined.

Moreover, social and cultural context may influence the way the EMO dimensions are defined and understood, and according to the international entrepreneurship literature, the firm's geographical location may affect its export activity and the number of foreign market entries as well (Leppäaho et al., 2018; Zander et al., 2015). Because of the need to research different social and cultural contexts (Bilkey, 1985; Leppäaho et al., 2018), we chose to examine firms with diverse economic backgrounds, i.e. Polish, post-transition economy setting, and the Finnish, mature market setting.

Although the studies on entrepreneurship agree that the environmental factors and entrepreneurs' characteristics determine their activities (Cuervo, 2005), extensive research showing the environmental turbulences’ influence on EMO is missing. Moreover, the studies of its determinants in emerging and transition economies' settings are limited (Yadav and Bansal, 2021).

To partially fill research gaps, we will concentrate on the external determinants of EMO and compare the marketing orientation of SMEs operating in manufacturing industries, on local and international markets, originating from the post-transition and mature country. The study aims to examine the impact of external determinants connected with environmental turbulence on the EMO of SMEs originating from one post-transition and one mature market. The findings will contribute to the research on SMEs’ marketing activity threefold. We test whether there is a similar understanding of EM concept in varied country settings. In addition, we check the environmental determinants of EM, and we validate the EMO scale in two countries. To sum up, we shed more light on SME approach to marketing.

We applied multigroup confirmatory factor analysis, structural equation modeling, analysis of variance (ANOVA) and T-tests to assess the measurement invariance and determine the relationships between variables.

The structure of the study includes, first, a literature review concerning the EM concept and its application in diverse country settings and next – the description of the EM determinants, which leads to hypotheses development in Section 2, testing and presentation of results in the third section. It is followed by discussing the findings with the literature presented in Section 4. The conclusions and implications concerning SME activity on industrial markets close the study (Section 5).

2. Background and hypotheses

2.1 The entrepreneurial marketing orientation in diverse country settings

As Toghraee et al. (2017) and Sadiku-Dushi et al. (2019) showed, there is substantial heterogeneity of approaches among studies concerning the intersection of marketing and entrepreneurship. Thus, they recommended improving the quantitative research on this topic by using uniform definitions and measurements of the EM concept. Among the frequently mentioned ones is the description by Whalen et al. (2016, p. 7), treating the EM as “a combination of innovative, proactive, and risk-taking activities that create, communicate, and deliver value to and by customers, entrepreneurs, marketers, their partners, and society at large”. It allows treating the EM as a set of entrepreneurship issues framed in marketing or viewed through a theoretical marketing lens (Hansen and Eggers, 2010). Many authors accept that marketing, especially the entrepreneurial, is a strategic response to environmental change (Peterson, 2020; Miles et al., 2015; Deacon and Harris, 2011; Covin and Slevin, 1989), which makes it interesting to study its environmental determinants in more detail.

The former studies of EM in developing (Astuti and Balqiah, 2020), small and open economies countries (Andersson and Evers, 2015; Yang and Gabrielsson, 2017), and mature economies (Hagen et al., 2019) provide evidence of the viability of this concept in different economic settings. The mentioned studies testify to customer intimacy, selective responsiveness to foreign market needs, resource leveraging and value co-creation as the common EM strategies used by the studied SMEs. However, companies operating in different markets may vary in understanding the dimensions of EM and perceiving their usefulness because the macroeconomic, financial and institutional environment presents other challenges, risks, and uncertainties and provides them with access to additional resources and opportunities (Cuervo, 2005). The differences in applying the EM approach are visible in the studies on internationalized SMEs. For example, the earlier Polish studies showed (Kowalik et al., 2017; Kowalik, 2020; Baranowska-Prokop and Sikora, 2014) that SMEs from post-transition markets choose a distinctive approach to international marketing. They combine high proactiveness with incremental innovations, a low-risk approach to marketing, and a strong focus on customer responsiveness. Unlike Polish companies, the SMEs from Italy attach greater importance to market intelligence generation, market exploitation, and responsiveness to competitors, putting more stress on the architectural marketing capabilities that later contribute to their international performance (Giampaoli et al., 2020). On the other hand, in the studies by Falahat et al. (2020), SMEs from emerging markets combined the entrepreneurial features and market orientation elements to succeed in foreign markets. Therefore, the EM behaviours and attitudes seem to have different importance depending on the country. However, it is still unexplored how the dimensions of EM are understood in different countries. Thus, to be able to conduct inter-country comparisons, it is necessary to validate the EMO measurement tool in different country settings. As the previous studies do not give evidence allowing us to set hypotheses about the differences between Polish and Finnish companies regarding external determinants of their EMO approach, the comparison of the results for our two subsamples will be exploratory, to provide background for further studies.

Moreover, as was mentioned, the EM determinants are still underexplored (Peterson, 2020). As marketing is generally context-oriented and, therefore, the external conditions are expected to strongly influence EMO (Morris et al., 2002; Becherer and Helms, 2016), we will concentrate on them in this study. The external environment includes variables such as demand and supply complexity, changing bargaining power of suppliers/competitors and buyers, the availability of adequate substitutes, aggressive competitors' activity, technological trends' dynamics, instability in economic conditions and the character of regulatory policies. Measuring the degree to which the environment changes rapidly, becomes hostile and gets complex helps capture these aspects (Morris et al., 2002). The external factors forming the external EMO environment can also be classified as economic, political and socio-cultural, creating the institutional environment (Shane, 2007; Jafari Sadeghi et al., 2019).

The determinants of entrepreneurial behavior and decision-making mostly (although still very seldom) discussed in the literature are the country's environment and the uncertainty caused by environmental turbulence. The country's environment may affect entrepreneurship in developing formal and informal institutions, infrastructure and market conditions. The perceptions of entrepreneurship, the economic development level and ease of market entry influence entrepreneurial activities (Peterson, 2020).

2.2 Environmental turbulence and entrepreneurial marketing

Environmental turbulence is defined as the magnitude of changes in major environmental factors' levels and the unpredictable nature of those factors' future levels (Hanvanich, 2006). These factors can be divided into market and technological turbulence. The former is related to the changing clients' preferences, while the latter stems from technologies' availability, forcing companies to innovate (Hina et al., 2021). Turbulent market conditions may render companies' resources and core capabilities useless and meaningless (Khouroh et al., 2020). On the other hand, as the contingency theory claims, the ability to fit the resources within the turbulent market environment leads to better organisational performance (Pleshko, 2007; Whalen et al., 2016). According to contingency research, technology, structure and culture represent the organisational response variables to the turbulent environment (Venkatraman and Prescott, 1990; Birkinshaw et al., 2002). In line with Volberda (1996), higher degrees of environmental turbulence would require higher organisational technological, structural and cultural responsiveness levels.

Some studies show that the fit of the firm's technology, structure and culture with the level of environmental turbulence of its task environment is positively associated with firm performance (Volberda et al., 2012). It is also known that the fit between the international EM strategies and the contingencies of the organisation leads to improved performance of quickly developing firms, such as International New Ventures (Hallbäck and Gabrielsson, 2013; Khouroh et al., 2020). Therefore, the EM approach is especially useful in unstable conditions (Kottika et al., 2020) characteristic of the international export markets. It allows companies to leverage resources in various ways and seek new opportunities to create value for customers innovatively. Companies with a high EMO level learn and introduce changes rapidly and mitigate risks through alliances (Morris et al., 2002), which supports their survival (Morrish, 2011) or business recovery after a crisis (Morrish and Jones, 2020). However, not all the elements of EMO are equally crucial for the firm's success in different market conditions. As shown in a longitudinal study on the sample of Finnish companies, while customer orientation supports the firm's performance in the time of economic upturn, such a relationship was not observed in the time of financial crisis, when the competitor orientation and inter-functional coordination play an essential role (Huhtala et al., 2014).

According to Schumpeter (1934), the primary sources of entrepreneurial opportunity are technological change, regulatory and political environment changes and socio-demographic change. Rapid market changes may force companies, especially those small and suffering from shortages of resources, to take a more entrepreneurial approach to the market (Khouroh et al., 2020; Schindehutte et al., 2000). In markets with high turbulence, the new customers' product needs differ from current customers. Furthermore, in highly volatile markets, existing customers frequently change their product preferences or are constantly looking for new products. Companies must adapt to new customers' changing needs and preferences (Hanvanich, 2006). In the turbulent market and technological conditions, companies must gather accurate and reliable information by scanning the environment, acting innovatively, taking risks and acting proactively to satisfy customers (Wang and Fang, 2012; Roper and Tapinos, 2016; Freel, 2005). Considering the above, we can assume that market turbulence stimulates an EMO.

Nevertheless, as Wang et al. (2021) noted, these conditions represent a double-edged sword, as entrepreneurs may perceive environmental turbulence as an opportunity or a threat. Companies, especially with limited resources, sensing the environment as unpredictable, may concentrate on their primary market and engage in less innovative activities, not increasing the risk (Wang et al., 2021; Hanvanich, 2006). Therefore, the turbulence may require strengthening some EMO dimensions and making the other less relevant than in more stable conditions. Such a relationship was observed by Wang et al. (2013), who have shown that market turbulence, technological turbulence and competitive intensity are positively related to responsive market orientation. However, the turbulence is negatively associated with the proactive market orientation, which includes the generation, distribution and use of market knowledge related to the potential future needs of customers (Jaworski et al., 2000). As there are many measures of EMO and the turbulence factors may differ, the relationship between environmental conditions and EMO requires further studies. Thus, it becomes interesting to examine whether and how the market turbulence affects the various dimensions of EMO.

The COVID-19 pandemic crisis in 2020–2021 caused significant market turbulence. It harmed international trade by causing both short-term problems, such as the temporary closure of non-essential manufacturing facilities, cargo shipping disruption and cost escalation, the instability of demand, export restrictions on some products and the reduction of some import restrictions, as well as long-term consequences, such as losing trust in single-sourcing strategies, which led to supplier diversification (Gruszczyński, 2020; Kerr, 2020). Given the unprecedented diversity of product, source, and destination changes in trade flows, consumers, businesses and governments faced increased uncertainty and adjustment costs, as well as a greater need and incentive to implement new or intensified risk mitigation strategies (Arriola et al., 2021). However, the COVID-19 crises affected different industries and companies to varying degrees (Vet et al., 2021). It led us to test whether perceptions of situation as threatening can affect EMO and to verify the following hypothesis:

H1.

Perceiving environmental turbulence as harmful is positively related to entrepreneurial marketing.

SMEs operating in foreign markets suffer from liabilities of smallness (Hannan and Freeman, 1984), similar to those active in the local markets. However, to a much greater extent, they suffer from the liability of newness (Stinchcombe, 1972) and foreignness (Hymer, 1976), making the foreign market environment less friendly and less predictable than the local one. The application of EM can reduce these liabilities (Weerawardena et al., 2019). Moreover, being active in foreign markets is related to a more significant uncertainty resulting from facing different cultures, regulations (Felzensztein et al., 2020) or other market conditions, which again requires an entrepreneurial approach (Whalen et al., 2016).

Export activity of an SME implies that it operates in a more turbulent environment than others, as the international market environment is characterized by higher turbulence, uncertainty, complexity (Panizzon et al., 2020; Olabode et al., 2018) and vulnerability to external shocks. Such shocks could have been observed when the COVID-19 pandemic-related problems took down international logistics solutions. The research conducted before crises also shows that export markets tend to be more turbulent. In the study of Indian high-tech International New Ventures, the international market turbulence indicator’s mean equaled 5.71 on the 1–7 scale (Buccieri et al., 2021). In the study on exporters from the Philippines, the mean indicator of environmental turbulence equaled 3.96 on the 1–5 scale (Souchon et al., 2012) while the mean evaluation of export market turbulence in the study on Portuguese exporters equaled 4.72 on the 1–7 scale (Lisboa et al., 2013). Functioning in the dynamic export markets requires constantly adapting to changing customer preferences. For example, during the pandemic, the Polish exporters faced the breaking up of foreign-market distribution chains. They had to quickly replace these chain members to match the needs of end customers (Wedziuk, 2020). To find out more about the relationship between the export market turbulence and EM, we have verified if:

H2.

The export market turbulence is positively related to entrepreneurial marketing.

Moreover, it seems that in those more advanced markets in technology development, the adoption of EM may be more widespread. The customers usually do not know what new technology they need or lack the necessary expertise to explain their technology needs. Thus, the company is responsible for discovering unexpressed customer requirements and satisfying them, which requires a proactive approach (Narver et al., 2004; Wang et al., 2013).

The entrepreneurial firms selling technologically sophisticated products often are ahead of the market, offering products of unrealised potential. The technology enthusiasts are already buying the product, but they constitute a market segment that is too small to assure a firm's survival. It requires the firms to cross the chasm that Moore (2008) described. The EM strategies (Sullivan Mort et al., 2012) in such a situation are used to win the mainstream customers' attention and convince them to purchase the high-tech products (Weerawardena et al., 2019). The traditional marketing approach may be insufficient because of the more significant technological turbulence of the high-technology markets. Thus, in this study, we would like to verify the following:

H3.

The technology turbulence in an industry is positively related to entrepreneurial marketing.

3. Research method

3.1 Sample and data gathering

The data for the study were collected from the Polish firms between January and February 2021 using the mixed-mode method, including 219 interviews, collected with the computer assisted telephone interview/computer assisted web interview technique by an independent market research company from Warsaw. The data for the second subsample were collected from the Finnish firms between December 2020 and January 2021 using the CAWI technique, including the same survey questions as in the Polish subsample, translated into Finnish. The stratified sampling method was used for the Polish subsample, with subgroups defined by the sections of economic activity, size of the company (small- and medium-sized firms) and firms' age. To enter the sample, the companies had to belong to the manufacturing sections of economic activity classification, including the following industries: production of metal constructions and their parts, production of plastic packaging goods, production of artificial-fibre goods for the building industry, production of electricity distribution and control mechanisms, production of measuring, navigation and control equipment, production of electric lighting equipment, production of machinery for food, tobacco and drinks' processing and others. Moreover, they had to be established not earlier than 1990, not due to a merger of other firms. They could not be a branch of other foreign-based companies and had a 0–50% foreign ownership share. The population meeting the above criteria in the purchased Bisnode database was 1,395, of which 807 firms were drawn by a randomised algorithm, giving each of the firms an equal chance to participate in the study. Of this group, 211 firms refused to participate, 46 stopped answering the questionnaire without finishing, 228 firms agreed to participate, but at times beyond the study, 75 did not meet the other selection criteria. The response rate (a quotient of the sum of partially and fully completed interviews and the size of the selected population) was 0.42.

The same selection criteria were applied to choose the final sample of 81 Finnish SMEs, where there was a response rate of 0.41 (for detailed characteristics of subsamples, see Table 1).

3.2 Applied scales

We used a five-dimensional construct to measure the EMO, based on Fiore et al. (2013), which was adapted and tested in 2019 on a sample of Polish SME-exporters. The modified model included four dimensions of EMO: Proactive Orientation (P) (comprising items: 1. We continually engage in changing the way products/services are marketed in our business. 2. Our business is frequently one of the first among competitors to alter its marketing methods. 3. We consistently improve the approach to marketing our business); Opportunity Focus (OP) (items: 1. We pursue untapped market opportunities regardless of budgetary or staff constraints. 2. When new market opportunities arise, our business very quickly acts on them. 3. Our business excels at identifying marketing opportunities.); Customer Orientation (CO) (items: 1. We spend considerable resources to get to know our customers better. 2. In our business, employees contribute ideas to create value for customers. 3. Our business continuously tries to find new ways to create value for our customers.); and Low-risk Marketing (RM) (items: 1. Our marketing efforts tend to have a low level of risk for our business. 2. Our business typically incurs low costs in connection with new marketing activities.).

These dimensions are consistent with the description provided in Kowalik et al. (2020, p. 86), except that the CO dimension comprises item 1 from the original CO construct and items 2 and 3 from the original CO Value Creation construct. Thus, we evaluate the reflective measurement model comprising four EMO dimensions through confirmatory factor analysis for Poland and Finland.

Although the previous studies showed that the EMO model was successfully adapted to the Polish context, this does not mean that the same concepts may be measured in the same way everywhere. As Poland and Finland reflect different contexts and business environments, the cross-country comparability of the scales (measurement invariance) should be confirmed first. Respondents from different countries might understand the EMO dimensions differently; that is, the configuration of items and constructs is not the same across countries. In addition, they might react differently to scales' items. For example, respondents may agree almost with all statements in one country while choosing relatively neutral categories in another. If so, we cannot meaningfully compare the means of the EMO dimensions across the countries. That is why testing for measurement invariance is crucial while comparing two countries.

We expected that measurement invariance might not hold, first, due to cultural differences and, second, as companies in Poland and Finland operate in different conditions. To assess the measurement invariance, we used the multigroup confirmatory analysis. The psychometric properties of scales were evaluated based on F-L criteria (Fornell and Larcker, 1981) for composite reliability (CR) and convergent validity. The commonly used F-L measures are severely biased, having a high false-positive rate in detecting a discriminant validity problem (Rönkkö and Cho, 2020), and the nested model comparison-based approach proposed by Bagozzi et al. (1991) is tedious and labour-intensive for models estimated in groups. Thus, we decided to evaluate discriminant validity (whether inter-construct correlations differ significantly from 1.00) based on bootstrap confidence intervals (CI) for inter-construct correlations.

3.3 Applied measures

As outlined before, the turbulence in the environment may relate to market or technology changes. We chose to examine market turbulence by using two variables: the perceived crisis influence on the company's environment and the activity on the export market.

The first variable was the perceived crisis influence on the environment of a company’s activity, which was measured by asking the question, “Did the COVID-19 pandemic deteriorate or improve the situation in the environment of the company's functioning?” described on a seven-point Likert-type scale ranging from “1 – strongly deteriorated” to “7 – strongly improved”. In the whole sample, only 47 firms (15.7%) admitted that the pandemic did not change the situation, and only three firms (1%) admitted it “rather improved” the situation in their environment. In contrast, the rest (over 83%) said the crisis deteriorated the situation in their surroundings.

In our sample, the export market turbulence was assessed by the fact that the firms were conducting foreign sales and by the number of foreign markets in which the exporters were present. Half of the sample were exporters, and all of them had at least a 15% share of the export sales in total turnover. Among the 109 Polish exporters, only 15 admitted that their main export market is the Czech Republic, Slovakia or Ukraine. The remaining ones traded with countries of Western Europe. Among the 41 Finnish exporting firms, only 10 indicated Sweden or Norway as their main export markets. This shows that the culturally close countries were not the dominant export destinations, and thus, the psychic distance could contribute to export market turbulence in both subsamples.

Finally, as said before, technological turbulence is higher in industries with more advanced technical solutions, so we chose to assess the technological turbulence by the technology development level in the industry. It was measured using Eurostat's classification and dividing the sample into four groups of SMEs classified as low-tech, medium low-tech, medium high-tech and high-tech (Eurostat, 2018). In the sample, there were 21.3% of high-tech enterprises (comprising medium-high-technology or high-technology) and 78.7% low-tech ones (comprising low-technology or medium-low-technology).

4. Results

4.1 Measurement invariance and scale's properties

To test for measurement invariance, we estimated and compared three nested models. The configural model (Model 1) assumed that the same items load on each EMO dimension across countries. Then we tested for metric measurement invariance by constraining the loadings (measurement weights) to be the same across countries (Model 2). To test the scalar measurement invariance, we constrained both loadings and item intercepts equal across countries (Model 3, Table 2).

The fit indices indicate a good fit for the configural model (Model 1). Contrary to our expectations, the nested models' comparison indicates a good fit for Model 2 (metric invariance) as well, as the loss in fit (ΔIFI, ΔTLI) while moving from the configural to metric measurement invariance model is less than 0.01 and Δχ²(7) = 9,4 (p = 0.065). Therefore, the metric invariance model (Model 2) should be chosen. The scalar invariance model (Model 3) shows a significantly worse fit as compared with Model 2 (Δχ²(11) = 38.8, p < 0.001 and ΔIFI > 0.01) and should be rejected. The metric (weak) measurement invariance holds for all EMO dimensions but not the scalar (strong) measurement invariance.

To test for partial scalar invariance (Ariely and Davidov, 2012) and to determine if any EMO dimensions meet scalar invariance, we released the intercepts for P3, CO1, CO2 and CO3, as these items displayed the most severe violations of this criterion and were the sources of Model 3 misfit. The partial scalar invariance model (Model 3a) reveals a good fit, which does not deteriorate compared with the metric invariance model (Δχ²(7) = 11.9, p = 0.103 and ΔIFI, ΔTLI < 0.01). Overall, the scalar invariance holds for Opportunity Focus and Low-risk Marketing, as all intercepts for constructs' items were constrained to be equal across the countries in Model 3a. Proactive orientation shows partial scalar invariance as two of three intercepts were constrained across countries. For Customer Orientation, the item intercepts were released, so only metric invariance is supported for this dimension. We can meaningfully compare between the countries both the means and the relationships between all EMO dimensions but CO. As for CO, we can compare the relationships with other EMO dimensions only.

Next, we evaluated the EMO dimensions properties. As it is visible from Table 3, the constructs making up the EMO model present high CR exceeding 0.7, indicating acceptable reliability and convergent validity (Fornell and Larcker, 1981) for Finland. When it comes to the Polish firms, all EMO dimensions proved reliable and showed composite validity, except for Customer Orientation, which was not reliable or valid.

Discriminant validity (whether inter-construct correlations differ significantly from 1.00) was assessed based on bootstrap CI (Rönkkö and Cho, 2020). The bias-corrected percentile CI calculated based on 2,000 replications did not contain the value of 1, meaning that correlations differed significantly from 1 (Table 4). The discriminant validity can be recognised for all the constructs (Bagozzi et al., 1991; Rönkkö and Cho, 2020).

Theoretical validity is achieved when convergent and discriminant validity exists. This is the case for all EMO dimensions for Finland and all EMO dimensions, but CO, for Poland.

4.2 Entrepreneurial marketing orientation of the Polish and Finnish small- and medium-sized firms

The EMO dimension achieving the highest values in the sample was Proactive Orientation, followed by Opportunity Focus (for Polish companies, the differences in average P and OP were relatively small, while for the Finnish ones, the average factor scores were4.5 for P and 3.9 for OP). Proactive Orientation and Opportunity Focus were also correlated to the highest degree among other EM dimensions. The least pronounced dimension of EM was RM, with an average value of 0.9 for Polish companies and 2.1 for Finnish ones.

The Finnish companies under study were more entrepreneurially oriented in their marketing than the Polish ones. Some EMO dimensions' average levels were significantly higher than in Polish SMEs (Table 5). The T-test for independent samples confirmed that the differences between Proactiveness and Low-risk Marketing were significant at the 0.05 level (for Proactiveness, t = 5.520, p < 0.001; for Risk-management, t = 13.246, P < 0.001). Unfortunately, because of the lack of scalar invariance, the meaningful comparisons of CO means among countries were impossible.

4.3 Environment turbulence and entrepreneurial marketing orientation

Most of the studied firms believed the COVID-19 crisis deteriorated their environment (80.4% of the Polish sample and 91.4% of the Finns). For the Polish sample, we obtained significant differences when comparing the EMO dimensions of the companies who perceived the crisis as detrimental and those who had a neutral or positive opinion about its influence. The results of T-tests showed that the Polish SMEs perceiving the situation as bad were significantly more proactive (T = 2.091, p = 0.038), more focused on opportunities (T = 2.298, p = 0.023) and less engaged in low-risk marketing (T = −2.653, p = 0.009) than the rest (Figure 1). As for Finland, the differences were not significant as the group of companies that had not perceived the impact of the pandemic as negative was small (n = 7). Thus, H1 was analysed only in the Polish subsample, and it was supported.

4.4 Export activity and entrepreneurial marketing orientation

When comparing the EMO of exporters and non-exporters, we used the independent samples T-tests and first checked the homogeneity of variance assumption. This allowed us to confirm whether the conditional distributions of EMO dimensions differ among exporters and non-exporters and, subsequently, if a relationship exists between exporting and the EMO (Figure 2).

In both countries, we found significant differences in EMO dimensions between non-exporters and exporters. The levels of Proactive Orientation (T_FIN = −7.061, p < 0.001; T_POL = −9.901, p < 0.001), Opportunity Focus (T_FIN = −6.990, p < 0.001; T_POL = −7.638, p < 0.001) and Customer Orientation (T_FIN = −2,815, p = 0.006; T_POL = −8.869, p < 0.001) were significantly higher in exporting companies, both in Finland and in Poland, than in the locally active ones. This evidence supports H2 for the abovementioned EMO dimensions. However, contrary to expectations, the exporters had a lower RM dimension (T_FIN = 5.120, p < 0.001; T_POL = 6.484, p < 0.001) in both countries.

Further, to analyse the impact of export market turbulence on EMO, we checked the correlation of the number of foreign markets with EM dimensions. There was a moderate positive correlation between Opportunity focus (0.319, p < 0.001) and a moderate negative one between Low-risk marketing (−0.279, p = 0.003) and the number of foreign markets in which the Polish firms were present. We found no correlation of EMO dimensions with their foreign activity scope for the Finnish firms.

4.5 Technology turbulence and entrepreneurial marketing orientation

Considering the different levels of technology development in SMEs from studied industries and their relation to EMO dimensions, we expect all EMO dimensions' levels to be higher in companies with higher technology levels according to H3. To test it, we conducted ANOVA analysis based on three groups, i.e. high, medium-high and medium-low tech firms. A low technology group was excluded from the analysis due to a small size (n = 3 and n = 2 for Poland and Finland, respectively). The homogeneity of variances assumption was met for all variables. However, as group sizes differed substantially, we used Welch's robust test of equality of means. The result has shown no significant differences among the group means for Proactive Orientation (F_FIN = 0.198, p = 0.824, F_POL=0.045, p = 0.956), nor for Opportunity Focus (F_FIN=0.741, p = 0.501, F_POL = 0.448, p = 0.643). Similarly, for Customer Orientation (F_FIN=0.924, p = 0.427, F_POL = 0.167, p = 0.847) and Low-risk Marketing (F_FIN = 0.274, p = 0.766, F_POL = 0.838, p = 0.442), the evidence has not supported H3 (see also: Figure 3).

5. Discussion and conclusions

Our study addressed the research gap concerning the external determinants of EM in different country contexts. We have shown that the understanding of the EM concept is similar in Poland and Finland, but there are differences in the EMO dimensions, indicating that market conditions are among their determinants. Operating in export markets and perceiving the market turbulence during a crisis as harmful are related to EMO. However, our study did not confirm the technology turbulence as the EMO determinant.

Thanks to the scale application, analysing the overall level of EM and demonstrating that Finnish companies exceed the Polish ones regarding Proactiveness and Low-risk Marketing was possible. This finding can be explained by functioning in the more developed market, demanding customers, and a more predictable business environment. Such an environment, during the crisis, allows for higher proactiveness in changing the marketing methods and provides for perceiving marketing as less risky. The Low-risk Marketing dimension concentrates on marketing activity connected with low cost and little risk. Thus, our results show that the Finnish firms perceive marketing activity as associated with lower risk than the SMEs from Poland. This is in line with the typical approach to EM, based on incremental improvements in promotional activities and low-cost, limited-range promotion (Gilmore, 2011). Our results show that this crucial feature of EM was sustained in Finland despite the crisis. We can suspect that the environment for SMEs in Finland provides them with a sense of security even in a crisis, so they do not need to change their approach to risk-taking in marketing. On the other hand, in the case of Polish enterprises, which operate on a much less developed market, factors limiting entrepreneurial activities, especially those involving risk, may be the lack of savings or easy access to capital allowing to make risky business decisions. In the study regarding the ease of getting a loan, Poland is ranked at the 89th place, while Finland is at the 12th place. The results referring to the availability of financial services also show that Finish companies are in much better positions than Polish ones (Poland is ranked 43rd, while Finland is ranked 10th) (Schwab, 2015). Finally, Poland's gross domestic product per capita is three times lower than in Finland (Worldbank, 2020). Entrepreneurs operating in such conditions are forced to take less risky decisions, as the wrong ones may be too costly for them. Avoiding risky decisions may be also explained by the uncertainty avoidance, which is exceptionally high in Poland (UAI of Hofstede = 93) compared with Finland, where this is slightly above the average (UAI of Hofstede = 59) (Hofstede Insights).

Regarding the market turbulence and EM, H1 has been supported. It has been shown in several studies summarised by Schindehutte et al. (2000) that the principal triggers for corporate entrepreneurship are aggressive competitor moves, changes in industry or market structure or regulatory threats. Zahra (1991) also identified that dynamism (instability of a firm's market because of changes) has a triggering effect on the firm's entrepreneurship (see also: Bocconcelli et al., 2018). Thus, despite the resource poverty of SMEs, a higher degree of entrepreneurial orientation in marketing may be expected in the circumstances of market turbulence, like the ones occurring during the crisis.

As for the specific EMO dimensions, some earlier findings (Niazi et al., 2019) showed a significant impact of market turbulence on market orientation, marketing orientation and innovation orientation. They showed that the higher the instability in customer demand, the higher the market information gathering, dissemination and response, which are the strategic marketing capabilities giving ground to the operational level success in marketing during crises. As the present study showed, Polish firms that perceived the situation as harmful were more proactive and focused on opportunities and disagreed with the statements describing their marketing efforts as risk-less and low cost. The crisis made implementing promotional and other marketing efforts more difficult. Thus, the typical feature of EM, which is low-cost marketing, became irrelevant in such hard times. In addition, we could compare the current study results with the results of other pre-crisis studies of the Polish SMEs when the EM dimensions were measured similarly (Kowalik, 2020). Compared with that study, the Low-risk Marketing dimension has changed into perceiving marketing as riskier (a three times lower mean score for this dimension). It shows that either SMEs replaced the low-cost promotion with a more risky and expensive one or perceived promotion as more costly. The study of Sundqvist et al. (2012) found, after researching over 700 Finnish exporters, that at times of crisis, risk-taking is the entrepreneurial behaviour that should be emphasised, together with innovativeness. Thus, in the present study, the perceived risk related to marketing activity was probably accepted to face the turbulent market's challenges.

The research by Qureshi et al. (2017) on 253 small and medium new technology-based firms in Turkey also confirmed that environmental turbulence enhanced the entrepreneurial and market orientation of the firms, which in turn led to a different approach to the marketing function.

Regarding the impact of export market turbulence on EM (H2), in both Finnish and Polish subsamples, the exporting SMEs tend to be more proactive, focused on opportunities and customer-oriented than those active only locally. In earlier studies, the environmental determinants of marketing decisions also included market turbulence, e.g. Yang and Gabrielsson’s (2017) qualitative study on high-tech early internationalizing firms from Finland. Other studies that support such a relationship in emerging-market firms (Purkayastha et al., 2021) also confirmed that internationalisation stimulates entrepreneurial orientation in India. Thus, perhaps the export market turbulence generates risk and uncertainty in the strategic planning process, reinforcing the need for a proactive approach, as in the study of Lindelöf and Löfsten (2006). The mean proactiveness level of the exporting SMEs in our sample was slightly lower than in the pre-crisis studies of Polish SMEs (a c.a.13% fall in 2021 Proactive Orientation's mean value). Thus, being proactive in marketing activity and exceeding the competitors' speed and frequency of new product launches and promotions proved to be the most consistent feature of SMEs’ marketing.

Similarly, a foreign market requires a higher degree of opportunity focus and market-sensing activities, making our results regarding the exporters understandable. According to Miocevic and Morgan (2018), the market-sensing capabilities belong to the absorptive operational capabilities necessary for export marketing success.

It seems surprising that the Customer Orientation dimension was significantly higher in exporting SMEs than locally active ones. However, Eggers and Kraus (2011), who studied the behaviour of SMEs from Silicon Valley during the economic crisis, discovered that customer intimacy became more critical during the recession than entrepreneurial behaviour. The firms surveyed during the crisis were customer- and entrepreneur-oriented, but they concentrated on customer responsiveness, not innovativeness. Our findings suggest that the studied firms started adjusting CO to the changing situation's needs, especially to the demanding foreign markets (Hills et al., 2008). It can also be explained with greater competitive intensity in foreign markets. Companies must consider changing customer needs in highly competitive markets (Lusch and Laczniak, 1987). On the other hand, exporting companies can lack customer knowledge, leading to more time and energy spent researching them than domestic customers.

We have found that the EMO increases with the greater foreign activity scope. Specifically, the Opportunity focus of the Polish firms increased with the number of foreign markets, which testifies to a greater level of entrepreneurial alertness necessary in the varying circumstances of new countries (Kontinen and Ojala, 2011). In addition, the perceived risk of marketing activity correlated with the increased geographic scope. These results testify to foreign market turbulences leading to the increased need to monitor market niches, but at the same time, promotional activities tend to become riskier (Morgan et al., 2004; Morgan et al., 2012).

Finally, we found no support for H3 concerning the relation between technology development level in the industry and EM, contrary to some earlier findings (Yang and Gabrielsson, 2017). The dimensions making up the entrepreneurial posture in marketing are not dependent on the type of industry in which the studied companies operate. According to the Global Entrepreneurship Monitor, the total early entrepreneurial activity shares in the specific industries are highly diverse when comparing the countries participating in that study (Global Entrepreneurship Research Association, 2021). In Poland, 27.6% of total early entrepreneurial activity starts in manufacturing and processing industries (the so-called Transforming sector). On the other hand, in Scandinavian countries, the share of this activity in manufacturing industries is much lower (Norway – 16.3%; Sweden – 13.6%), whereas it is 23.2% in the UK. This gives an idea that the entrepreneurial intentions are not connected with the industry type but rather with different factors. Sciascia et al. (2014) studied entrepreneurial orientation and its impact on performance in low- and medium-tech industries in Italy and found no connection between the EO and industry type.

On the other hand, Wang et al. (2021) found that technological turbulence was negatively related to the proactive market orientation of 308 companies across a wide range of industries. They explained that uncertainty of technological turbulence made managers avoid the risk associated with proactive market orientation due to their limited resources and newness. A similar situation may have occurred in our sample, especially in the Polish high-tech SMEs. However, the results concerning the relationship between the proactiveness dimension of EMO and industry type were insignificant because of a small number of studied firms operating in high-tech branches (21%).

According to Lumpkin and Dess (2001), it is the stage of the industry life cycle and not its technology level that tends to favour one type of entrepreneurial orientation over another. The performance of firms in the early stages of industry development is better when their strategy making is proactively oriented. These authors found that proactiveness – a response to opportunities – is an appropriate mode for firms in dynamic environments or in growth stage industries where conditions are rapidly changing and opportunities for advancement are numerous. However, such domains may not favour competitive aggressiveness (another dimension of entrepreneurship). So, considering the turbulence of the environment, we can explain that proactiveness and opportunity focus were necessary for all branches of industry in our study, regardless of the technology development level. That is why we did not find significant differences concerning these dimensions in different branches.

Summing up, we demonstrated that the EMO dimensions are influenced by environmental turbulence, which testifies to the studied business-to-business (B2B) firms' marketing responsiveness. In addition, we were able to compare the actual levels of proactiveness, opportunity focus and low-risk marketing concerning the Polish manufacturing SMEs, with a pre-crisis study. The comparison showed a vivid change of risk-taking and opportunity focus, testifying to the firms' efforts to maintain a strategic fit with the external conditions, in line with the contingency theory of management (Venkatraman and Prescott, 1990).

5.1 Implications of study

Our study has several research implications. Firstly, it showed that entrepreneurs from diverse economic backgrounds understand the EM concept similarly. Thus, it is possible to apply it in different country contexts (e.g. Poland, Finland, and the USA, as Fiore et al. (2013) showed). The metric and partial scalar invariance of the EMO scale was proved, suggesting that Proactiveness, Opportunity Focus and Low-risk Marketing are the EM dimensions understood similarly by respondents from Poland and Finland. It evidences that the same EMO measurement tools may be used in different countries, and meaningfully compared.

Moreover, we found that the level of EMO dimensions differed between Polish and Finnish SMEs. This finding indicates that EM is dependent on the local context, which should be taken into account both when researching this phenomenon and when discussing it. Findings from one country are not representative of other populations. Furthermore, our study shows that operating in foreign markets and crisis conditions determine the entrepreneurial approach to marketing, thus starting a new trend in research. It is worth conducting further research to deepen the knowledge on the identified relationships and to identify further external determinants of EMO, allowing decision-makers to better support the development of such attitudes among entrepreneurs.

The data used in our study were collected during the COVID-19 pandemic. Meanwhile, companies, especially European ones, are facing another crisis caused by the multidimensional and hard-to-predict consequences of the Russian assault on Ukraine. Therefore, our findings on the relationship between market turbulence and marketing orientation may be of particular value to policymakers and business practitioners.

As we observed significant differences in EMO dimensions between Finnish and Polish companies operating on the B2B market, policymakers should make efforts to provide Polish SMEs with a stable, supporting environment, strengthening their proactive attitudes in the domestic and export markets. Especially at market turbulence, when the marketing activities may be perceived as more costly and risky, the institutional support should concentrate on SME marketing. Moreover, as exporting SMEs need to be highly entrepreneurial, the education programmes should strengthen both the marketing and entrepreneurial qualities in future business people to support the country’s export success.

As for the managerial implications, we confirmed other findings supporting the paramount role of proactiveness as an entrepreneurial feature. It also applies to marketing, and the need to continuously improve marketing methods is unquestioned even during crisis times. To meet the challenges of a turbulent environment, Rašković (2021) recommends “harnessing the transformative potential of adversity through continuous learning and entrepreneurial thinking”, which is evident also from the current study. Another valuable part of managing SMEs in crisis is to perceive the environmental turbulence realistically. The firms in our study who were aware of the harmful effects of the situation on their environment managed to maintain a relatively high level of EMO despite difficulties and uncertainty. This finding indirectly supports the contingency theory and the importance of strategic fit.

The conclusions concerning technological turbulence show that industry type is not a decisive factor for entrepreneurship development. Growth opportunities can be found in low- and high-tech industries, regardless of environmental constraints.

Finally, the differences in customer orientation between the Polish exporting and non-exporting B2B SMEs should be underlined. It can indicate Polish entrepreneurs' similarities to the Russian managers studied by Gulakova et al. (2019), who still lack a proper customer orientation. As customer orientation is of extraordinary importance in the B2B relationships (Singh and Koshy, 2011; Gould et al., 2016; Li-Wei et al., 2017), Polish B2B SMEs, especially the non-exporting ones, should work on its improvement.

5.2 Study limitations

Although our study provided interesting results, it is not free from limitations. First of all, we cannot exclude that some of the relationships we have studied are reciprocal (for example: being an exporter forces the companies to be more entrepreneurial, but on the other hand, more entrepreneurial companies may decide to enter foreign markets). The sample covers SMEs originating from two countries only. More longitudinal studies in diverse country settings would be required to understand better the relationships discussed above. Moreover, future studies covering the same firms could show if environmental changes led to improved performance. As the quantitative methods do not explain these relationships in greater detail, in-depth qualitative studies could help better understand such phenomena.

Figures

Figure 1

Comparison of EMO dimensions in firms perceiving the crisis as harmful and the others, 95% confidence intervals for means

Figure 2

Comparison of EMO dimensions in exporters and non-exporters, 95% confidence intervals for means

Figure 3

Comparison of EMO dimensions in industry branches with different levels of technology, 95% confidence intervals for means

Table 1

Sample composition

Finnish sample (n = 81)		Polish sample 2021 (n = 219)
50% – exporters	50% − non-exporters	50% − exporters	50% − non-exporters
64% − small companies	36% − medium-sized companies	62% − small companies	38% − medium-sized companies
23% − serving both B2B and B2C markets	77% − operated exclusively on the B2B market	32% − serving both B2B and B2C markets	68% − serving B2B market only
21% − low or medium-tech	79% − medium-high or high-tech	78.5% - low- or medium-tech	21.5% − medium-high-tech or high-tech

Source: Own study

Table 2

Measurement models fit and test of measurement invariance

	Model fit indices							Measurement invariance
Model	χ2	df	IFI	TLI	CFI	RMSEA	SRMR	Δχ2	Δdf	ΔIFI	ΔTLI
1. Configural model	150.7	76	0.966	0.949	0.965	0.057	0.055
2. Metric invariance	164.0	83	0.963	0.950	0.962	0.057	0.068	13.3	7	0.006	0.000
3. Scalar invariance	202.9	94	0.949	0.940	0.949	0.062	0.070	38.8	11	0.018	0.009
3a. Partial scalar invariance*	176.0	90	0.960	0.951	0.960	0.057	0.068	11.9	7	0.006	−0.001

Notes:

Measurement invariance model comparisons: 2 v 1, 3 v 2 and 3a v 2. IFI: Incremental Fit Index, TLI: Tucker–Lewis Index, CFI: Comparative Fit Index, RMSEA: root mean squared error of approximation, SRMS: standardised root mean squared residual.

*The constraints of intercepts for items P3, CO1, CO2 and CO3 were released

Table 3

Scales' properties

Item		Construct	Poland			Finland
			Estimate	CR	AVE	Estimate	CR	AVE
P1	←	P	0.899	0.928	0.811	0.933	0.931	0.818
P2	←	P	0.860			0.811
P3	←	P	0.941			0.962
OP1	←	OP	0.977	0.914	0.780	0.963	0.924	0.803
OP2	←	OP	0.823			0.856
OP3	←	OP	0.842			0.865
RM1	←	RM	0.930	0.740	0.599	0.974	0.761	0.631
RM2	←	RM	0.578			0.560
CO1	←	CO	0.547	0.566	0.311	0.730	0.829	0.628
CO2	←	CO	0.680			0.998
CO3	←	CO	0.414			0.596

Note:

The measurement model was estimated assuming partial scalar invariance (Model 3a)

Source: Own study

Table 4

Discriminant validity assessment

Correlation			Poland			Finland
			Estimate	90% CI		Estimate	90% CI
P	↔	OP	0.522	0.420	0.609	0.699	0.574	0.794
CO	↔	OP	0.515	0.372	0.648	0.319	0.129	0.495
CO	↔	P	0.366	0.206	0.510	0.223	0.052	0.407
P	↔	RM	−0.445	−0.551	−0.319	−0.476	−0.659	−0.281
CO	↔	RM	−0.476	−0.622	−0.311	−0.308	−0.483	−0.126
OP	↔	RM	−0.887	−0.943	−0.816	−0.821	−0.921	−0.731

Note:

CI – the bootstrap confidence interval calculated using the bias-corrected percentile method

Source: Own study

Table 5

Descriptive statistics of the EMO dimensions

EMO dimension	Poland (N = 219)				Finland (N = 81)
	Minimum	Maximum	Mean	SD	Minimum	Maximum	Mean	SD
Proactive orientation (P)	2.45	5.94	3.916	0.877	2.56	6.11	4.551	0.907
Opportunity focus (OP)	1.54	6.29	3.652	0.994	1.41	5.98	3.879	0.991
Customer Orientation (CO)	1.60	3.53	2.480	0.442	2.29	5.34	3.807	0.846
Low-risk marketing (RM)	−0.58	2.02	0.862	0.670	0.62	3.64	2.065	0.769

Notes:

Factor scores are calculated as a weighted sum of items. The factor score weights are calculated based on a matrix of covariances among items and a matrix of covariances between items and EMO dimensions

Source: Own study