Role of Cultural Factors on Entrepreneurship Across the Diverse Economic Stages: Insights from GEM and GLOBE Data

2.1 Empirical Literature on Culture and Entrepreneurship

For the study of culture, the initial classification distinguishes between individualist and collectivist cultures (Hofstede, 1980, 1994, 2011; Schwartz, 1999). Hofstede (1980) defines culture as “the collective programming of the mind distinguishing members of a group or category of people from others” (Hofstede, 1980). In this context, culture’s outer layers typically encompass rituals, heroes, and symbols, while its core lies in its values (Hofstede & McCrae, 2004). The literature on culture’s influence on entrepreneurship can be broadly categorized into two streams: psychological and institutional (Davidsson, 1995).

In the psychological perspective, social and cultural contexts significantly shape individual psychology and behavior. Culture acts as a potent guide within specific cultural settings (Afsar et al., 2021; Hofstede, 1980), influencing the values and behaviors of individuals in one country. Entrepreneurship-friendly cultures encourage greater exploration of entrepreneurial potentials and promote increased entrepreneurial activities (Ben Youssef et al., 2021; McGrath et al., 1992; Mueller & Thomas, 2001).

In the institutional perspective, culture is considered an informal institution in line with the institutional economic theory proposed by North (2005). This framework provides a valid basis for studying the environmental factors influencing new business creation (Díaz-Casero et al., 2012). A supportive culture contributes to social legitimation, increasing the value and recognition of entrepreneurial careers, thus fostering a favorable institutional environment. Moreover, various institutional conditions, such as a competitive market, private property protection, and an effective educational system, facilitate entrepreneurial activities.

2.2 Empirical Literature on Economy and Entrepreneurship

Entrepreneurship is the driving force of the economy, characterized by the pursuit of profits through problem solving in uncertain situations. It also fuels innovation by introducing new products and processes (Acs & Audretsch, 1990, 2003). Entrepreneurship’s contribution to economic growth lies in its job creation, competitive stimulation, knowledge dissemination, and diversification of businesses (Angulo-Guerrero et al., 2017; Wennekers & Thurik, 1999).

It is widely recognized that macroeconomic variables are interconnected, indicating complex relationships and interdependencies among them. Thereafter, the relation between the economy and entrepreneurship is not simply linear. In the early or middle stages of economic development, entrepreneurial activity may be negatively correlated with economic improvement, as individuals transition from self-employment to wage employment (Nikolaev et al., 2018; Pinillos & Reyes, 2011). Conversely, increased income can foster more startup activities (Acs, 2006). This often leads to a U-shaped relationship between economic activity and entrepreneurship in the global economy (Carree et al., 2002, 2007; Sternberg & Wennekers, 2005).

However, it is apparent that countries with similar economic development exhibit substantial variations in their entrepreneurial activity dynamics and patterns (Pinillos & Reyes, 2011; van Stel et al., 2005). The impact of different types of entrepreneurship on economic growth is also hugely different (Angulo-Guerrero et al., 2017; Wennekers & Thurik, 1999), all of which complicate their relationship.

2.3 Entrepreneurial Activities: Opportunity vs Necessity

Regarding entrepreneurial motivation, the GEM distinguishes between two types of entrepreneurship: opportunity-driven entrepreneurial activity and necessity-driven entrepreneurial activity (Reynolds et al., 2002). Opportunity entrepreneurs initiate businesses to pursue market opportunities or just self-actualization, while necessity entrepreneurs are compelled to start businesses due to factors such as unemployment or dissatisfaction with their prior employment.

Opportunity entrepreneurs are typically more proactive and motivated to start businesses in their areas of expertise, while necessity entrepreneurs often start businesses out of necessity rather than choice. This distinction is significant because entrepreneurs driven by opportunity tend to make more substantial economic contributions, including longer business survival, greater growth, and stronger aspirations. The ratio of opportunity-driven to necessity-driven entrepreneurship (OPP/NEC) is an ideal indicator of entrepreneurship quality and contribution (Acs, 2006; Angulo-Guerrero et al., 2017; Nikolaev et al., 2018). In this study, we aim to shed light on these differences by the number of entrepreneurship (total entrepreneurial activity (TEA)) and the composition of entrepreneurial activities (OPP/NEC).

In essence, explaining these different entrepreneurial motivations goes beyond economic factors alone (Frederking, 2004). Previous research has linked variations in entrepreneurial activity to economic stages and cultural values but often overlooked the interaction between them (Morales et al., 2019). To better understand the motivation of entrepreneurship, cultures, economy, and in particular their interaction effects are investigated in the current study.

3.1 Theoretical Background

In this study, we adopt a psychological perspective to conceptualize culture as a collection of behaviors and customs embraced collectively by specific groups, setting them apart from other populations. These cultural practices play a significant role in shaping individuals’ behaviors, particularly in the context of entrepreneurship, through their psychological and motivational effects. In line with this perspective, we employ the MHT, also known as Herzberg’s two-factor theory (Herzberg, 1966), to investigate the influence of cultural factors on the entrepreneurial activities across different economic stages. The MHT posits that job satisfaction is influenced by two distinct categories of factors: motivation factors and hygiene factors.

Motivation factors are linked to an individual’s desire for self-growth and self-actualization, leading to job satisfaction, while hygiene factors are primarily concerned with the need to avoid unpleasantness (Herzberg, 1976, 2017; Hur, 2018). At the core of the MHT lies the distinction between these two types of factors: motivation and hygiene. Herzberg characterized motivation factors as intrinsic to the job itself, while hygiene factors are extrinsic to the job environment (Alshmemri et al., 2017). Accordingly, motivation factors solely serve to enhance job satisfaction. When fulfilled, they inspire satisfaction, while their absence does not lead to dissatisfaction. Conversely, hygiene factors exclusively work to diminish job dissatisfaction. When met, they prevent dissatisfaction, but their presence does not bring forward satisfaction (Alshmemri et al., 2017; Kotni & Karumuri, 2018). Importantly, these two factors run parallel to each other rather than representing opposite ends of a single dimension.

3.2 Hypotheses Development

The literature on the culture, economy, and entrepreneurship (Cressy, 2000; Kan & Tsai, 2006; Pinillos & Reyes, 2011; Zhao et al., 2012) reveals that cultural factors affect entrepreneurial motivations differently.

Aligned with the MHT, the motivation culture emphasizes intrinsic factors, making entrepreneurship a means for seizing opportunities. Individuals are motivated to explore more entrepreneurial opportunities, prioritize self-actualization over short-term profit, and place a greater emphasis on future interests. Moreover, people tend to manage their time conscientiously, striving for greater task efficiency while prioritizing the future (Bortolotti et al., 2015). While this intrinsic motivation may not necessarily result in a higher quantity of nascent entrepreneurship, it is expected to stimulate opportunity-driven entrepreneurship. This, in turn, should lead to greater entrepreneurship satisfaction and enhance the quality of entrepreneurial endeavors. Accordingly, we formulate the following hypothesis:

For countries characterized by high hygiene culture, these values such as obedience to authority, power structures, gender inequality, loyalty to collective interests, and the importance of traditional family and parent–child bonds are prioritized and interpersonal relationships take precedence (Zhao et al., 2012). On the one hand, individuals are more attuned to external conditions and social networks. Their interpersonal relationships are often built within stable, established social structures and networks. When necessarily starting new businesses, they can draw significant social and emotional support from extended family structures. On the other hand, for the avoidance of dissatisfaction, people tend to conform to established norms and seek stability in both their work and personal lives, and are reluctant to change the status quo or seize the new-found opportunities. These hygiene factors are expected to promote the number, while worsen the quality of entrepreneurial activities. Accordingly, we formulate the following hypothesis:

In less-developed economies, entrepreneurs often start businesses out of necessity, driven by factors such as the need for income generation and employment opportunities (Fernández-Serrano et al., 2018; Naude et al., 2008; Nikolaev et al., 2018; Wennekers et al., 2005). These individuals may face limited job prospects in the formal sector, leading them to create their own businesses for survival. With higher economic stages, there tends to be a shift in entrepreneurial motivations. Necessity-driven entrepreneurship may decline as formal employment opportunities increase. In more developed economies, entrepreneurs may be more driven by improvement-related motives, such as a desire for innovation, growth, and market success. These individuals may have more opportunities to pursue entrepreneurial ventures as a choice rather than a necessity. Therefore, we formulate the following hypotheses:

Given that both culture and economy significantly influence entrepreneurial activities, the interdependence between them has been documented (Fernández-Serrano et al., 2018; Mueller et al., 2002). Therefore, the current study tests the interaction effects of cultures and economy on entrepreneurial activities.

In the circumstance of motivation culture with the developed economy, the desires for high performance, future orientation, and market success correspond to factors like the nature of the work, achievement, recognition, and responsibility. Entrepreneurs in these settings are likely to be motivated by the intrinsic rewards associated with the work itself and self-improvement or self-actualization in more developed economies. On the other hand, as economies develop, basic survival factors like stable employment and adequate income become less of a concern. Dissatisfaction of entrepreneurship derived from power distance and collectivism in hygiene cultures makes people more cautious and less risk-taking, which hinders the pursuit of starting business. Accordingly, entrepreneurship is a choice rather than a necessity. On this basis, we formulate the following hypothesis:

Both motivation culture and hygiene culture concurrently influence the performance of entrepreneurial activities, operating within specific social contexts. Furthermore, there may exist an interaction effect between them on entrepreneurial activities. This interaction can either foster or hinder economic development.

To expound the causal relationship between economic development and entrepreneurship, we employ panel data analysis incorporating gross domestic product (GDP) data with a one-period lag. This method allows us to explore the temporal dynamics and discern the influence of prior economic conditions on the subsequent entrepreneurial landscape, enhancing the understanding of the interplay between economic development and entrepreneurial activities over time.

Specific combinations of cultural factors can resonate with one another, exerting a pronounced impact on entrepreneurial activities, while other combinations may dampen each other’s influence, limiting their mutual effects. The intricate relationship between specific combinations of cultural factors and their impact on entrepreneurship, subsequently affecting economic development and leading to distinguishable economic outcomes among countries. On the basis of this assessment, we formulate the following hypothesis:

4.1 Measurements of Cultural Factors

Within the framework of MHT, motivational factors encompass achievement, recognition, the nature of the work itself, responsibility, opportunities for advancement, and the potential for personal growth. In contrast, hygiene factors encompass aspects related to company policies and administration, relationships with supervisors, interpersonal relations among colleagues, working conditions, and salary (Castillo-Palacio et al., 2017; Herzberg, 2017).

In this study, we use data from the GLOBE project, which identifies nine cultural dimensions across 62 countries. GLOBE was designed to understand the relationship between national culture and leadership attributes and offers a substantial sample size. To ensure data consistency and balance with GEM entrepreneurship data, culture data from 54 countries are adopted.

Statistically, factor analysis is a commonly employed technique to eliminate redundant variables from survey data and reduce the number of variables into a smaller set of dimensions, especially when certain variables cannot be directly measured. Before conducting factor analysis, the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s sphericity test are performed. The results indicate a KMO value of 0.678, which is larger than the acceptable threshold of 0.5, and the P-value is significantly smaller than 0.05. These results demonstrate that the data are structurally suitable for factor analysis (Table 1). Initially, the analysis involves combining the nine cultural practice variables from GLOBE and applying the principal component extraction method with varimax rotation. This process results in the extraction of three factors.

The dimension of institutional collectivism exhibits nearly equal loadings on two factors (Factor 1: 0.546; Factor 3: 0.588). This finding is consistent with much of the previous literature, which has also shown that its relationship with entrepreneurial performance is not significant (Hayton et al., 2002). As a result, it was excluded from further analyses. By using the remaining eight components, we extracted three factors with eigenvalues greater than one, collectively explaining 79.5% of the total variance (Table 2). We employed orthogonal rotation (Varimax) with Kaiser normalization, and the factor loadings are presented in Table 3. The rotation process successfully converged in five iterations, with the original order of responses rearranged to reflect the factor structure.

Factor 1 includes future orientation, performance orientation, and uncertainty avoidance, which represent motivational factors related to achievement, advancement, future growth, and responsibility (Alshmemri et al., 2017).

Factor 2 includes in-group collectivism, gender egalitarianism (with a negative coefficient), and power distance, which are associated with hygiene factors in interpersonal relationships with supervisors, family, and opposite-sex interactions (Alshmemri et al., 2017).

Factor 3, labeled as humanity factor, includes human orientation and assertiveness (with a negative coefficient). Notably, no previous literature provides support for its relationship with entrepreneurship and the economy. Pearson correlation results also confirm the absence of correlations between the humanity factor, entrepreneurial activities, and economic stages (Table 6). Consequently, it is not included in the current study.

Similar to Gusfield’s perspective on tradition and modernity, we contend that motivation culture and hygiene culture are two separate factors that exist independently of each other, rather than being part of a single bipolar continuum (Dacin et al., 2019; Gusfield, 1967). In each country, both motivation and hygiene factors coexist at the national level, implying that the presence of one does not necessarily preclude the existence of the other, and vice versa.

4.2 Baseline Empirical Models

To estimate the regression results, we employ equation (1) to assess both the direct and the interaction effects of culture, economic development, and entrepreneurial activities. In addition, equation (2) is used to examine these relations by lagging one period of the GDP per capita. All variables are measured with “i” as the unit of observation in each country, “t” as the unit of observation in each year, and “t−1” as the unit of observation lagged one period.

4.3 Variables Description

4.4 Data Analysis

To analyze the data, various statistical methods and tests were employed to analyze and interpret the data, helping to draw meaningful conclusions from the research findings. They are as follows:

1. One-way analysis of variance (ANOVA): Used to assess the significance of differences in culture, economy, and entrepreneurship across the five economic stages and four quadrant groups of culture combination.

2. Bivariate correlation: Conducted to identify the significance of relationships among the variables, which justify the necessity of following regression analysis.

3. Panel data regression: The panel data regression of fixed effect is applied to confirm the direct and interaction effects. To control the endogeneity between the economy and entrepreneurship, a fixed effects panel regression is adopted, with the individual effects of year and country controlled, with and without one-period lag on GDP per capita. To mitigate multicollinearity, relevant variables in the interaction models were standardized. To overcome the impact of autocorrelation, national level clustered standard errors are used.

4. Dummy variable regression: Employed as a robust test to verify the relations, and the dummy variable of high or low level of economy is included, which is rather persistent compared with yearly changing GDP per capita.

5. Visualization: Interaction effects were visualized using figures, following the methods of Dawson and Richter (2006)^[2].

6. Culture Map: Created to demonstrate the distribution of countries (regions) in the quadrant distribution diagram.

5.1 Comparative Analysis Across Economic Stages

Table 4 shows the descriptive statistics of all the variables. Table 5 shows the results of One-way ANOVA at different economic stages, indicating statistically significant differences in entrepreneurial framework, motivation culture, hygiene culture, and entrepreneurial activities across various economic stages. This suggests that different economic stages play a significant role in shaping these variables, highlighting the importance of considering economic context when studying the relation between culture and entrepreneurship.

As economy advances, the number of TEA decrease from 24.89 in factor-driven economies to 8.05 in innovation-driven economies (F = 7.36, P ≤ 0.01). Conversely, the ratio of OPP/NEC significantly increases from 2.03 to 5.06 (F = 6.15, P ≤ 0.01). At the same time, motivation culture increases from 4.08 to 4.20 (F = 3.60, P ≤ 0.01), while hygiene culture drops from 2.80 to 2.05 (F = 6.06, P ≤ 0.01). In addition, a preliminary analysis of Pearson correlation between the variables is conducted.

5.2 Pearson Correlation

The Pearson correlation matrix in Table 6 reveals some significant relationships among the variables. Notably, there is a negative correlation (−0.225, P ≤ 0.05) between TEA and OPP/NEC, indicating that as the number of TEA worsen the ratio of OPP/NEC. TEA exhibits a negative correlation (−0.563, P ≤ 0.01) with the economy. Conversely, there is a positive correlation (0.542, P ≤ 0.01) between OPP/NEC and the economy. These results align with the previous research, which suggests that opportunity-driven entrepreneurship is more beneficial for economic growth due to its higher motivation and innovation, while necessity-driven entrepreneurship may be less conducive to economic development (Acs, 2006; Pinillos & Reyes, 2011). Is there a possibility that economic development contains the necessity-driven entrepreneurship, while promoting opportunity-driven entrepreneurship?

The correlation results indicate that motivation culture is positively correlated with OPP/NEC (0.453, P ≤ 0.01), economic stages (0.235, P ≤ 0.05), and economic development (0.365, P ≤ 0.05). However, there is no significant correlation between motivation culture and TEA (−0.126, P > 0.1). On the other hand, hygiene culture is positively correlated with TEA (0.359, P ≤ 0.05) but negatively correlated with almost all other variables, including a strong negative correlation with OPP/NEC (−0.578, P ≤ 0.01), economic stages (−0.571, P ≤ 0.01), and economic development (−0.689, P ≤ 0.01). This aligns with the ANOVA results, suggesting that hygiene culture may be associated with higher TEA but less favorable for opportunity-driven entrepreneurship (OPP/NEC) and other factors.

While the Pearson correlation analysis serves to ascertain the existence and strength of relationships between variables, it primarily captures associations rather than providing insights into causal effects. These data show that there are significant variations and close relations between entrepreneurial and cultural variables across different economic stages. However, to delineate and substantiate the causal relations among the variables, the need of regression models becomes imperative. Regression analysis enables a systematic examination of the causal relation by elucidating the impact of one or more independent variables on a dependent variable, thereby providing a more refined understanding of the intricate relationship within the studied variables.

Before that, one thing needs to be stated that the correlation matrix shows that there is no multicollinearity issue among the variables, as no single correlation value exceeds the threshold of + or −0.70. This indicates that the variables in the study are not highly correlated with each other, ensuring the robustness of the subsequent regression analyses. Moreover, taking the results of ANOVA and Pearson correlation, the entrepreneurial framework is also highly related to most variables, including TEA and OPP/NEC, thereby it should be controlled in the following regression models.

5.3 Panel Data Regression

To explore the interaction between culture, economy, and entrepreneurial activities, panel data regression was conducted. The results of the Hausman test indicated that the data met the assumptions necessary for employing fixed effects in the model, affirming the appropriateness for the panel data analysis. Since the economic stages from the GCR are an ordinal variable and not available as panel data, LnGDP per capita is used as a proxy for economic development. This adjustment allows for a quantitative representation of economic development levels, facilitating a more nuanced analysis within the given data constraints. While recognizing that national culture evolves over the long term, the cross-sectional culture data from GLOBE are employed in a panel regression analysis because the national culture remains comparatively stable in the short term. To be specific, national level clustered standard errors are used to overcome the impact of autocorrelation.

The results of panel regression analyses in Tables 7 and 8 show the relationships between cultural factors, economic development, and entrepreneurial activities. Notably: Model 1 to Model 10 in Table 7, TEA is the dependent variable, while from Model 11 to Model 20 in Table 8, OPP/NEC is the dependent variable.

Entrepreneurial framework is taken as control variable in the current study, and Models 1 and 11 show that it makes a negative and significant impact (−0.176, P ≤ 0.1) on TEA, whereas it makes a positive impact (0.217, P ≤ 0.01) on OPP/NEC respectively, as expected.

In Model 2 (TEA) and Model 12 (OPP/NEC), introducing cultural factors alongside control variables reveals that hygiene culture significantly encourages TEA (0.404, P ≤ 0.01), while discouraging OPP/NEC (−0.460, P ≤ 0.1). Motivation culture positively influences OPP/NEC (0.246, P ≤ 0.01), while no impact on TEA. Since economy can explain the motivation of entrepreneurship, which may account for its variation. In Models 3–5, 13–15, economic development is introduced together with or without culture factors.

Economy has a negative and statistically significant impact on TEA (0.608, P ≤ 0.01) in Model 3, while they have a positive and statistically significant impact on OPP/NEC (0.510, P ≤ 0.01) in Model 13.

Model 4 reveals an intriguing shift: the significant promoting effect of hygiene factors on TEA, seen in Model 2, disappears when economic development is considered. Instead, economic development’s containing effect on TEA becomes more pronounced (from −0.608 to –0.627), overshadowing the influence of hygiene factors (from 0.404 to −0.025). In contrast, when explaining OPP/NEC in Model 14, the effects of motivation and hygiene factors remain consistent with that in Model 12 (from 0.246 to 0.238 and −0.460 to −0.262, respectively).

These results highlight the dynamic relationship between cultural factors, economic development, and entrepreneurial activities. Thereafter, their interaction effects are postulated that there are interaction of economy and two cultures, as well as interaction between two cultures themselves on entrepreneurship. Models 5 and 15 are applied to check the former, while Models 6 and 16 are applied to check the latter.

The positive interaction effect of motivation culture in Model 5 (0.237, P ≤ 0.05) shows its reduction of economic development’s containment on TEA, while hygiene culture does not. The interaction effect is visualized in Figure 1. On the contrary, the negative interaction effect of hygiene culture in Model 15 (−0.276, P ≤ 0.01) shows its offsetting effect on economic development’ s promotion on OPP/NEC, while motivation culture does not, as shown in Figure 2. In Model 6, the negative interaction effect of two cultures (−0.179, P ≤ 0.05) shows motivation culture’s reducing effect on hygiene culture’s encouragement on TEA. On the contrary, the negative interaction effect (−0.351, P ≤ 0.01) in Model 16 demonstrates the reducing effect of hygiene culture on the promotion of motivation culture on OPP/NEC. These interaction effects of cultures themselves are illustrated in Figures 3 and 4.

Figure 1

The interaction effect between motivation culture and economic development on TEA.

Figure 2

The interaction effect between hygiene culture and economic development on OPP/NEC.

Figure 3

The interaction effect between motivation culture and hygiene culture on TEA.

Figure 4

The interaction effect between motivation culture and hygiene culture on OPP/NEC.

In Models 7–10 and Models 17–20, the lagging of GDP per capita by one period is implemented to mitigate endogeneity concerns between the economy and entrepreneurship. This adjustment results in a reduction of the sample size from 292 to 219. The regression results have been checked, and it can be safely stated that there are no noticeable changes observed in the direction or relations between culture, economy, and entrepreneurship.

5.4 Robust Test

To establish more direct insights into the relationships among culture, economic level, and entrepreneurship, a robust examination was conducted, incorporating a dummy variable representing economic levels. In accordance with the GCR 2017–2018, countries or regions were categorized into three distinct economic stages – factor driven, efficiency driven, and innovation driven – along with two transitional states. This classification, based on both GDP and the driving force for development, exhibits greater stability compared to relying solely on annual GDP per capita. For our investigation, we designated countries or regions of stages 1 and 2 and the transitional state as low-level economies, coded as “0,” while those of stage 3 and its transitional state were categorized as high-level economies, coded as “1.” The results of the dummy variable regression analysis are presented in Table 9.

The dummy regression results align with the panel data regression (5.3), demonstrating remarkable consistency, with one exception observed in Model 26. In this model, the interaction effects between motivation/hygiene culture and the economy level on OPP/NEC prove to be statistically significant (0.338, P ≤ 0.01; −0.310, P ≤ 0.1), while the corresponding interaction effect of motivation culture in Model 15 (0.071, P ≥ 0.1) is not significant. Nevertheless, this divergence does not compromise the overall robustness and reliability of the results obtained from the panel data regression.

5.5 Map of Culture Distribution

As mentioned previously, motivation culture and hygiene culture are two discrete dimensions that are independent of each other. Within each country, both motivation and hygiene factors coexist at the national level. To visually illustrate the cultural scores and their impact, countries are categorized culturally into four combinations using the medians of the motivational factor (4.00) and hygiene factor (2.37) as reference points. This classification results in a quadrant distribution diagram, which can visualize how countries fall within the motivation-hygiene framework, as displayed in Figure 5.

Countries in Quadrant I are featured with high motivation (mean = 4.20) and high hygiene culture (mean = 2.63), such as China, India, and Philippines. Countries or regions in Quadrant II are featured with low motivation (mean = 3.67) and high hygiene culture (mean = 2.62), such as Thailand, Spain, and Turkey. Countries in Quadrant III are featured with low motivation (mean = 3.60) and low hygiene culture (mean = 2.16), such as Qatar, Bolivia, and Namibia. Countries in Quadrant IV are featured with high motivation (mean = 4.43) and low hygiene (mean = 1.86), such as Denmark, the United States, and Switzerland.

ANOVA was conducted to examine the differences in variables among the four quadrant groups, particularly to assess the impact of different cultural combinations on economic development. The results, as shown in Table 10, demonstrate that the four groups exhibit significantly different performances in GDP per capita and reach different economic stages, with all P-values less than 0.05. Countries or regions in Quadrant IV tend to perform the best in terms of economic development.

6.1 Hypotheses of Direct Effects Tested

Taking the coeffects of Pearson correlation between motivation culture and TEA (−0.126, P ≥ 0.1), and OPP/NEC (0.453, P ≤ 0.01 ) in Table 6, and the regression results of Model 2 (0.088, P ≥ 0.01) and Model 12 (0.246, P ≤ 0.01) in Tables 7 and 8, countries with high motivation culture exhibits no difference in TEA, yet significantly high OPP/NEC. H1a is partially true.

This implies that the motivational influence exerted by motivation culture is particularly pronounced in fostering opportunities rather than necessitated entrepreneurial endeavors. As per the Herzberg theory stated that motivational factors are intrinsic to the job and entrepreneurial activities (Alshmemri et al., 2017; Galanakis & Peramatzis, 2022; Herzberg, 2005). In this study, motivation culture, assessed through performance, future orientation, and uncertainty avoidance reflects a cultural environment that promotes individual freedom, personal achievement, self-expression, subjective well-being, and self-actualization. These factors are conducive to entrepreneurship, particularly opportunity-driven entrepreneurship.

Taking the coeffects of Pearson correlation between hygiene culture and TEA (0.359, P ≤ 0.05), and OPP/NEC (−0.578, P ≤ 0.01), and the regression results of Model 2 (0.404, P ≤ 0.01) and Model 12 (−0.460, P ≤ 0.01), it can be safe to say that hygiene culture positively correlated with TEA, while negatively correlated with OPP/NEC. H1b is versified.

Hygiene factors, measured by in-group collectivism, gender egalitarianism, and power distance in the current study, are extrinsic to the job (Alshmemri et al., 2017; Galanakis & Peramatzis, 2022). Countries with high hygiene culture prioritize concepts like obedience to power, authority, and loyalty to collective interests. It is noted to say individuals in this culture can benefit from strong interpersonal relationships, often grounded in family kinship, providing substantial social and emotional support, when they start business. Conversely, opportunity-seeking entrepreneurial activities marked by elements of risk, the pursuit of opportunities, and alterations to individuals’ established status quo are inherently incongruent with the settings of hygiene culture. Such endeavors are perceived as discordant with the principles of hygiene culture, and perceived as unpleasant behavior, thus causing the decline of OPP/NEC.

Taken the results of one-way ANOVA in Table 5, it is found that the TEA falls with improving the economic conditions from 24.89 at stage 1 to 8.05 at stage 3, while OPP/NEC, which keeps increasing from 2.03 to 5.06. With the economic development, the number of TEA decreases from factor-driven economies to innovation-driven economies (F = 7.36, P ≤ 0.01), while motivation culture increases (F = 3.60, P ≤ 0.01). Pearson correlation coeffects of TEA with economic stages (−0.464, P ≤ 0.01), GPD per capita (−0.563, P ≤ 0.01) while OPP/NEC with economic stages (0.485, P ≤ 0.01), GPD per capita (0.542, P ≤ 0.01) show that economic development negatively affects TEA and positively promotes OPP/NEC. The regression results of Model 3 (−0.608, P ≤ 0.01) and Model 13 (0.510, P ≤ 0.01) further validate this relationship. Both H2a and H2b are confirmed.

It is shown that in less economically developed countries, self-employment and entrepreneurship, particularly necessity-driven entrepreneurship, play a significant role in job creation and market development. As economies progress toward innovation-driven stages, larger firms and stable wage employment opportunities become more prevalent, leading to a decrease in new business startups (TEA). Instead, individuals may engage in entrepreneurship for self-actualization and growth, facilitating the promotion of high-quality entrepreneurial endeavors and contributing to the rise of OPP/NEC.

6.2 Hypotheses of Interaction Effects Tested

The results from panel regression with fixed effects in Tables 7 and 8 provide insights into the interaction effects between cultural factors and economic stages on entrepreneurship. As the results in Model 5 show, the positive interaction effect of motivation culture in Model 5 (0.237, P ≤ 0.05) demonstrates its reduction of economic development’s containment on TEA. According to the results in Model 15, the interaction effect of motivation culture (0.071, P ≥ 0.1) does not exist. Thereafter, H3a that the containment of economy on TEA can be mitigated by motivation culture is proved, while its promotion of economy’s encouragement on OPP/NEC is not supported. Therefore, motivation culture should not be overstressed, because it may offset the reducing effects of economy on TEA, causing more people to start their own business blindly, while not promoting the quality of entrepreneurship. H3a is partially supported.

Interestingly, the results in Model 5 do not support the interaction effect of hygiene culture’s interaction effects with economy on TEA (−0.087, P ≥ 0.1). However, according to the results in Model 15, the worsening effect of hygiene culture with economy on OPP/NEC exists (−0.276, P ≤ 0.01). Thereafter, H3b that the containment of economy on TEA is not worsened by hygiene culture, while its promotion of economy on OPP/NEC is reduced by hygiene culture. Seemingly, with the development of economy, hygiene culture factors like in-group collectivism and power distance should not be encouraged, because they may offset the promoting effects of economy on OPP/NEC. H3b is partially supported.

The results concerning the interaction effects of motivation culture and hygiene culture are complex. Results of culture interaction effects shown in Models 6 and 16 are profound. Within Model 6, the negative interaction effect (−0.179, P ≤ 0.05) between cultures illustrates the mitigating impact of motivation culture on the stimulation of hygiene culture to TEA. Conversely, in Model 16, the observed negative interaction effect (−0.351, P ≤ 0.01) shows the bad influence of hygiene culture on motivation culture’s fostering effect on OPP/NEC; thus, H4 is confirmed. This phenomenon can be explained by the fact that motivation culture, characterized by a higher level of performance orientation and uncertainty avoidance, may create lower incentives for risky endeavors such as innovation and entrepreneurship, which is exacerbated in cultures with high power distance and strong emphasis on family boundaries (Achim et al., 2021).

The incorporation of a one-period lag on GDP per capita in the panel regression framework emerges as a widely used strategy for confronting and alleviating endogeneity concerns (Nathaniel et al., 2021; Sadorsky, 2010; Teles & Cesar Mussolini, 2014). This congruence of results between Models 7–10 and 17–20 with one-period lag on GDP per capita and Models 3–6 and 13–16 without lagging, per se, provides a compelling argument for the reliability and resilience of this method. While acknowledging that a one-period lag on GDP per capita may not comprehensively address all aspects of the endogeneity concerns associated with the economy and entrepreneurship, its utilization reaffirms the stability and coherence of the observed results. Economic development with one-period lag consistently demonstrates its containing effect on TEA, as in Models 7–10 (−0.586, P ≤ 0.01; −0.640, P ≤ 0.01; −0.724, P ≤ 0.01; −0.622, P ≤ 0.01) and promoting effect on OPP/NEC, as in Models 17–20 (0.438, P ≤ 0.01; 0.240, P ≤ 0.05; 0.317, P ≤ 0.01; 0.246, P ≤ 0.01). Therefore, H5 is substantiated.

The combined interactive effects of cultural factors are further illustrated by classifying 54 countries or regions into quadrant distribution based on motivation and hygiene scores, as shown in Figure 5. Analyzing the results of one-way ANOVA in Table 10 among countries in quadrant cultural distribution, we observe that countries in Quadrants I and IV share a high motivation culture. However, their corresponding OPP/NEC and TEA levels vary significantly. Similarly, countries in Quadrants I and II share a high hygiene culture, and their OPP/NEC and TEA levels follow similar patterns, with high TEA and low OPP/NEC. Regarding entrepreneurial activities, countries/regions in Quadrant IV exhibit the lowest TEA and the highest rate of OPP/NEC. In other words, countries or regions in Quadrant IV achieve the highest performance in both economic development and entrepreneurial quality. Therefore, H6, which pertains to the influence of cultural combinations on economic development and entrepreneurial activities, is supported. In essence, these findings pertaining to H6 also underscore the statistical rigor and consistency in the results of the panel regression analysis and one-way ANOVA.

Figure 5

Countries/regions in motivation-hygiene quadrant distribution diagram.

7.1 Contribution

First, theoretically, the MHT is employed to examine the relations between culture, economy, and entrepreneurial activities, which fills the theoretical gap of clarifying the cultural roles in entrepreneurial activities.

Second, the culture data from GLOBE project (2007) are converted into motivation culture and hygiene culture. Five economic stages from GCR (2018) and the panel data of GDP per capita (2011–2018) are used to represent economic stages and development, respectively, which makes the present study more comprehensive and robust.

Third, from the perspective of statistic methods, apart from the bivariate correlation and one-way ANOVA, the panel data regression of fixed effect, with national-level clustered standard errors, are used to overcome the impact of autocorrelation. The dummy variable regression as a robust examination was conducted, by incorporating the dummy variable of high/low economy.

Finally, to demonstrate the interaction effects of economy, cultures, and different entrepreneurial activities, two-way interaction effects are plotted. Plus, a culture map is drawn according to the culture scores of 54 countries (regions) to demonstrate their distribution in the quadrant distribution diagram globally.

7.2 Policy Implication

Motivational factors and hygienic elements assume distinct roles throughout entrepreneurial endeavors, exhibiting varying significance across different economic stages. There are no universal rules of cultural practices and entrepreneurial activities for different countries to pursue. Hence, without specifying the economic stages, it would be too simplistic to draw the conclusion that the hygiene culture stimulates the necessity-driven entrepreneurship or motivation culture promotes opportunity-driven entrepreneurship. Similarly, even though the economic development’s confinement on TEA and encouragement of OPP/NEC have been testified, this relationship can be elucidated only within the contextual framework of two types of cultures.

Some findings of this research show the facts that, i.e., low economic stage countries, if featured by high hygiene culture, such as high in-group collectivism, and power distance can create many entrepreneurial activities, mostly necessity-driven ones. With the continual economic development, their entrepreneurial activities (TEA) decrease sequentially, while few of them can be transformed into opportunity driven if there is no high motivation culture, such as poor future orientation and poor performance. In contrast, high economic stage countries, if featured by high motivation culture and low hygiene culture, by stressing self-actualization, good performance, and uncertainty avoidance without caring about power distance and collective confinement, can bring about opportunity-driven entrepreneurship and enhance entrepreneurial quality, and more importantly, they make positive feedback on entrepreneurship and innovation, which brings forward the promotion of economy sequentially. However, Motivation Culture should not be overstressed in developed economy, because it may offset the reducing effects of economy on TEA, causing more unqualified people to make the decision of starting business.

7.3 Limitations and Future Research

This study has several limitations that should be acknowledged and considered for future research. First, the data of culture and entrepreneurial activities used in this study were obtained from two independent databases, which led to the collected data unbalanced. Even though the sample size in this study reaches 292, it is still relatively small for entrepreneurship study. Also, in view of the possible endogeneity between economy and entrepreneurship, one-period lag on GDP per capita was adopted in the panel regression to alleviate endogeneity concerns. However, there is still a risk of endogeneity due to simultaneous causality, which makes the generalization of the findings more cautious and further studies are needed.

Understanding these dynamics between culture, economy, and entrepreneurship is crucial for policymakers, researchers, and entrepreneurs themselves, as it emphasizes the need to consider both motivational and environmental factors when fostering entrepreneurial ecosystems. While Herzberg’s MHT has been extensively studied in the context of job satisfaction, its applications in culture and entrepreneurial motivation are quite novel. Future research is needed to justify and confirm this theoretical attempt in the related areas for a more comprehensive understanding.

This research attempts to shed some light on the effects of interaction between culture and economy on entrepreneurship. However, all of them are complex, multifaceted, and interrelated. Future research can delve into their relationships from new perspective, like the mediating effect of entrepreneurship on culture and economic development, with the hope of exploring more intriguing relationships among them.