Commonalities or Variations among Dimensions: An Analysis of Regions based on Hofstede's Six Cultural Pillars

1. Introduction

Cultural variations across nations have been widely studied, with research suggesting that geographic proximity plays a significant role in shapingcultural similarities (Hofstede, 2011; Osiobe, 2024). Countries within the same region often exhibit common cultural traits due to shared histories, economic ties, and interactions, while nations separated by vast distances tend to display more distinct cultural attributes (Beugelsdijk & Welzel,2018; Leonavičienė & Burinskienė, 2022). However, analyzing cultural similarities and differences purely based on geographic location may lead to oversimplified conclusions, as culture is a multifaceted construct influenced by numerous factors beyond physical proximity (Dipierro & Rella, 2024; Kirkman, Lowe, & Gibson, 2006). Geert Hofstede’s six cultural dimensions—Masculinity, Power Distance, Individualism, Uncertainty Avoidance, Long-Term Orientation, and Indulgence—offer a systematic framework for evaluating cultural differences (Hofstede, 2011; Zhou & Kwon, 2020). Rather than relying on general geographic categorizations, a more precise approach involves assessing how these cultural dimensions vary across regions and how corruption levels influence cultural structures (Achim, 2016; Seleim & Bontis, 2009). This study examines the extent to which each of these dimensions differs between countries within the same region and across regions, considering bothregional influences and the presence of corruption as a determining factor in cultural evolution (Melgar, Rossi, & Smith, 2010; Chandler & Graham, 2010).

Corruption has long been recognized as a significant factor in shaping national cultures and governance structures (Hamilton & Hammer, 2018; Hooker, 2009). Countries with higher corruption levels tend to exhibit cultural characteristics that support informal networks and patronage systems, while those with lower corruption levels are more likely to foster transparent institutional frameworks (Beugelsdijk & Welzel, 2018; Achim, 2016). Research suggests that Power Distance, for instance, increases in societies where corruption is more prevalent, as hierarchicalstructures become deeply entrenched in governance and everyday interactions (Melgar et al., 2010; Dipierro & Rella, 2024). Conversely, individualism tends to decline as corruption rises, reinforcing collectivist values that prioritize group loyalty over institutional integrity (CulturalDimensions and Perception of Corruption, 2023; Seleim & Bontis, 2009). A comparative approach that evaluates cultural dimensions across multiple regions provides insights into how corruption modifies cultural attributes. Studies have shown that in regions where corruption is rampant, Uncertainty Avoidance increases, as societies develop mechanisms to navigate the unpredictability associated with corrupt environments(Chandler & Graham, 2010; Kirkman et al., 2006). Similarly, Masculinity levels tend to rise in economies where corruption persists, reflectingcompetitive and assertive behaviors that are often necessary to thrive in such contexts (Beugelsdijk & Welzel, 2018; Achim, 2016). On the otherhand, Long-term orientation appears to be more pronounced in less corrupt nations, where institutional stability and trust in governance structures support long-term economic planning and societal progress (Alqarni, 2022; Melgar et al., 2010).

In addition to corruption, digital transformation, and globalization have also impacted cultural dimensions by reshaping how societies interact and communicate (Asdourian, Chariatte, & Ingenhoff, 2024; Spry, 2018). The rise of digital diplomacy and international communication networks has facilitated cultural exchanges that challenge traditional cultural boundaries, further complicating the regional categorization of cultures (Hamilton & Hammer, 2018; Alqarni, 2022). These technological advancements have enabled nations to engage in digital city diplomacy, creating new avenues for collaboration while simultaneously reinforcing national branding efforts in the global arena (Asdourian et al., 2024; Malallah & Osiobe,2024). This study seeks to analyze whether cultural dimensions are more influenced by regional proximity or by corruption levels. By assessingcross-regional variations and investigating whether corruption significantly alters cultural structures, the research aims to provide a morenuanced understanding of how cultural attributes evolve (Osiobe, 2024; Kirkman et al., 2006). The findings will contribute to the broader discourse on cultural dynamics, governance, and international collaboration, highlighting the interplay between cultural frameworks and institutionalintegrity across different geographic regions (Beugelsdijk & Welzel, 2018; Malallah & Osiobe, 2024).

2. Empirical Review 

A comprehensive examination of cultural dimensions and corruption has been conducted across various studies, leveraging frameworks such as Hofstede’s cultural dimensions (Hofstede, 2011), the GLOBE project (Seleim & Bontis, 2009), and diverse international corruption indices(Hamilton & Hammer, 2018). Research has consistently shown that national cultures play a significant role in shaping governance structures, economic development, and corruption perceptions (Achim, 2016; Melgar, Rossi, & Smith, 2010).

2.1           Cultural Dimensions and Corruption Perception

Numerous studies have analyzed the relationship between cultural dimensions and corruption perception. Achim (2016) found that PowerDistance, Individualism-Collectivism, and Long-Term Orientation significantly influence corruption levels. Similarly, Dipierro & Rella (2024) confirmed that societies with higher Power Distance and lower Individualism tend to have more entrenched corrupt practices, aligning with Hofstede’s framework (Hofstede, 2011). The work of Seleim & Bontis (2009) further supports these findings, emphasizing the role of uncertainty avoidance and human orientation in moderating corruption. Zhou & Kwon (2020) reviewed over four decades of Hofstede-based research and identified patterns in how cultural values influence corruption perceptions globally. Their findings revealed that cultures emphasizing collectivism and rigid hierarchies tend to tolerate higher levels of corruption, while societies valuing transparency and individual accountabilityreport lower corruption levels. Similarly, Kirkman, Lowe, & Gibson (2006) reviewed 180 empirical studies, confirming that Hofstede’s dimensions remain robust indicators of corruption’s cultural determinants.

2.2           Regional Perspectives on Cultural Dimensions and Corruption

The impact of cultural dimensions on corruption varies across regions. Beugelsdijk & Welzel (2018) examined cross-national cultural shifts and found that regions with historically high Power Distance and Masculinity scores, such as parts of Asia and Africa, experience more systemic corruption. Similarly, Hamilton & Hammer (2018) noted that Uncertainty Avoidance increases in corruption-prone environments, as societies develop coping mechanisms for unpredictability.

Malallah & Osiobe (2024) applied Pearson’s Correlation Coefficient to assess cultural commonalities and their influence on diplomatic relations, showing that even countries with distinct historical backgrounds can exhibit similar cultural responses to corruption. Osiobe et al. (2024) furtheranalyzed Hofstede’s dimensions across various regions, emphasizing that Indulgence and Long-Term Orientation play crucial roles in governance effectiveness and institutional trust.

In Europe, corruption and cultural dimensions were analyzed through correlation matrices by Leonavičienė & Burinskienė (2022), who found that Scandinavian countries with high Individualism and low Power Distance scores demonstrate greater institutional transparency. Conversely, Southern European nations exhibit stronger hierarchical structures, which correlate with higher corruption perceptions (Cultural Dimensions and Perception of Corruption, 2023). Chandler & Graham (2010) studied how corruption impacts international business, revealing that corruptionlevels influence marketing success across France, Japan, and the US.

2.3           Digital Transformation and Cultural Evolution

Recent studies have explored how digital transformation influences cultural dimensions and corruption. Asdourian, Chariatte, & Ingenhoff (2024) examined how digital city diplomacy is reshaping governance structures, indicating that technology-driven international engagement can help mitigate corruption by fostering transparency and cross-cultural cooperation. Similarly, Spry (2018) investigated the role of social media indiplomatic engagement, showing that digital diplomacy is increasingly relevant for smaller nations in combating corruption and improving international relations.

Alqarni (2022) analyzed the intersection of Hofstede’s dimensions and online learning behaviors, revealing that cultural dimensions influence theadoption of digital education platforms. These findings suggest that digital advancements are actively shaping cultural behaviors, potentially affecting long-term corruption trends.

2.4           Gaps in Literature

Despite extensive research on the relationship between cultural dimensions and corruption, several gaps remain, necessitating further study. While studies establish strong correlations between Power Distance, Individualism, and Uncertainty Avoidance with corruption levels (Achim, 2016; Dipierro & Rella, 2024), there is limited understanding of the causal mechanisms underlying these relationships, as most analyses focus on correlation rather than causation. Additionally, research predominantly examines corruption and cultural dimensions at the national level, overlooking sub-national and regional variations, which are essential in multi-ethnic and politically diverse nations (Beugelsdijk & Welzel, 2018; Leonavičienė & Burinskienė, 2022). Another critical gap concerns the role of digital transformation in reshaping cultural dimensions and corruption perceptions, as studies by Asdourian, Chariatte, & Ingenhoff (2024) and Spry (2018) explore digital diplomacy and governance but do not sufficiently analyze how digital engagement actively influences cultural values and resistance to corruption. Furthermore, globalization and cross-cultural interactions remain underexplored, with most studies relying on Hofstede’s framework (Hofstede, 2011) without considering the effects of international migration, trade, and governance mechanisms on corruption perceptions (Chandler & Graham, 2010). While there aresignificant findings on corruption and cultural dimensions across regions (Cultural Dimensions and Perception of Corruption, 2023; Seleim & Bontis, 2009), limited research explores how governance policies effectively mitigate corruption within specific cultural frameworks. It istherefore against these backdrops that this study provides deeper insights into how cultural dimensions, corruption, and digital transformation interact, fostering a more comprehensive foundation for policy recommendations and future research directions.

3. Methodology

This study employs a Two-Way Analysis of Variance (ANOVA) model to assess the impact of a country's level of corruption and geographic location (region) on key cultural dimensions categorized by Geert Hofstede (Hofstede, 2011). By including two independent factors—corruption level and geographic region—this study examines both main effects and interaction effects on the dependent variables. Prior research (Achim, 2016; Dipierro & Rella, 2024) indicates that cultural dimensions are significantly influenced by corruption levels, while other studies (Beugelsdijk & Welzel, 2018; Zhou & Kwon, 2020) highlight regional clustering in shaping cultural traits. Given the non-additive model approach, we anticipate a significant interaction between these two factors, suggesting that corruption level and regional location jointly influence cultural dimensions rather than acting independently. This aligns with findings that corruption perception is shaped by both socio-cultural and institutional factors (Melgar et al., 2010; Hamilton & Hammer, 2018).

3.1.          Model Specification

Our initial hypothesis posits that countries exhibit similar levels of Masculinity, Power Distance, Individualism, and Uncertainty Avoidance,regardless of their geographic location and level of corruption. While Hofstede’s cultural framework consists of six dimensions, we exclude Long-Term Orientation and Indulgence due to data limitations and weaker associations with corruption levels (Seleim & Bontis, 2009; Achim, 2016).

The study evaluates four response variables:

i.               Masculinity (M)

ii.              Power Distance (PD)

iii.            Individualism (IDV)

iv.             Uncertainty Avoidance (UAI)

These cultural dimensions are examined concerning two explanatory factors:

•                Region (R): Four levels—Africa, America, Asia, and Europe

•                Level of Corruption (C): Three levels—High, Medium, and Low

The model is mathematically represented as:

𝑌𝑖𝑗𝑘 = 𝜇 + 𝛼𝑖 + 𝛽𝑗 + (𝛼𝛽)𝑖𝑗 + 𝜀𝑖𝑗𝑘                                                      (1)

Where:

𝑌𝑖𝑗𝑘 represents the observed cultural dimension for the 𝑘𝑡ℎ observation in the (𝑖, 𝑗)𝑡ℎ group

𝜇 is the grand mean of all observations

𝛼𝑖 is the effect of Region 𝑖 (𝑖 = 1,2,3,4 for Africa, America, Asia, and Europe)

𝛽𝑗 is the effect of Corruption Level 𝑗 (𝑗 = 1,2,3 for High, Medium, and Low)

(𝛼𝛽)𝑖𝑗 is the interaction effect between Region and Corruption Level

𝜀𝑖𝑗𝑘 is the random error term, assumed to follow a normal distribution:

𝜀𝑖𝑗𝑘 ∼ i.i.d. 𝑁(0, 𝜎2)                                                                      (2)

To ensure model identifiability, we impose the following constraints:

                                                                                     4               3            4  3 

∑ 𝛼𝑖 = 0, ∑ 𝛽𝑗 = 0, ∑ ∑ (𝛼𝛽)𝑖𝑗 = 0                                                (3)

                 𝑖=1        𝑗=1        𝑖=1 𝑗=1

These constraints enforce sum-to-zero conditions, ensuring that effects are measured as deviations from the grand mean rather than absolute values.

3.2.          Hypothesis Testing Framework

Since we employ a non-additive Two-Way ANOVA, we test the following three sets of null and alternative hypotheses for each cultural dimension 𝑋(where 𝑋 ∈ {𝑀, 𝑃𝐷, 𝐼𝐷𝑉, 𝑈𝐴𝐼}):

1.              Interaction Effect Hypothesis

𝐻0: There is no interaction between Region and Level of Corruption on cultural dimension 𝑋

2.              Main Effect of Region

𝐻0: The factor Region does not affect cultural dimension 𝑋

3.              Main Effect of Corruption Level

𝐻0: The factor Level of Corruption does not affect cultural dimension 𝑋

3.3.          Justification for Methodology

Several studies validate the use of Two-Way ANOVA in cross-national cultural analysis. Beugelsdijk and Welzel (2018) emphasize the need forregional-level cultural comparisons, while Achim (2016) and Seleim and Bontis (2009) highlight the impact of corruption on cultural dimensions.Additionally, Zhou and Kwon (2020) stress that culture-based research must control for interactions between institutional and socio-economicfactors. Employing a Two-Way ANOVA, this study extends the existing literature by assessing both regional and corruption-based variations simultaneously, offering an understanding of cultural evolution.

 4. Results

This section presents the results of our analysis investigating the relationship between Hofstede’s cultural dimensions and two explanatory variables: Region (Africa, America, Asia, and Europe) and Level of Corruption (High, Medium, and Low).

4.1. Descriptive Statistics

Table 1: Descriptive Statistics of Cultural Dimensions

Source: Researcher’s computation

Figure 1: Cultural Dimensions by Region andCorruption Level

4.1.1. Masculinity Across Regions and CorruptionLevels

The findings suggest that Masculinity does not exhibit significant variation across regions or corruption levels, with values ranging between 43.1 (Africa, Medium) and 55.1 (Europe, High). This aligns with Hofstede’s (2011) assertion that Masculinity is a stable cultural dimension that is more deeply rooted in socialization and historical gender roles rather thanbeing influenced by corruption or regional governance structures. Beugelsdijk and Welzel (2018) also found that Masculinity remains relatively constant across countries, reinforcing that corruption does not significantly impact gender role differentiation and competitive values. However, a closer examination reveals a slightly higher Masculinity index in highly corrupt European and American countries (55.1 and 50.7, respectively). This aligns with Chandler and Graham (2010), who suggested that more corrupt business environments in Western economies might encourage competitive and assertive behaviors, possibly reinforcing Masculine traits in organizations and politics.

4.1.2. Power Distance Across Regions and Corruption Levels

The Power Distance dimension demonstrates a notable regional variation, ranging from 39.6 (Europe, Low Corruption) to 85.0 (Europe, HighCorruption). The data supports prior findings by Hofstede (2011), Achim (2016), and Dipierro & Rella (2024), who argued that Power Distance isstrongly associated with corruption levels, as corrupt societies tend to reinforce hierarchical structures that limit transparency and accountability. The African countries with high corruption exhibit relatively low Power Distance (45.6), which contradicts Hofstede’s (2011) expectation that corrupt societies generally promote high Power Distance. This finding supports Beugelsdijk & Welzel (2018), who suggested that African culturaltraditions emphasize communal leadership structures that may counteract the centralization of power despite corruption. Conversely, Europe's Power Distance varies dramatically between low (39.6) and high corruption levels (85.0), confirming Zhou and Kwon’s (2020) observation that hierarchical acceptance in Western societies is flexible, shifting based on governance quality. In highly corrupt American and Asian countries, Power Distance remains high (74.9 and 72.6, respectively), reinforcing Chandler & Graham’s (2010) argument that corrupt political systems in these regions rely heavily on hierarchical control to maintain power.

4.1.3. Individualism Across Regions and Corruption Levels

The data reveals a stark contrast between highly corrupt and low-corruption societies in terms of Individualism. Highly corrupt regions, particularly in America (21.2) and Asia (29.7), exhibit significantly lower Individualism, supporting Dipierro & Rella’s (2024) finding thatcorruption flourishes in collectivist cultures, where patronage networks and group loyalty take precedence over personal autonomy. On the other hand, low-corruption European countries exhibit the highest Individualism (62.8), aligning with Hofstede (2011) and Achim (2016), who found that Individualism thrives in societies with strong institutions, transparency, and accountability. This is further supported by Spry (2018), who argued that individualistic cultures encourage personal responsibility, making corrupt behaviors more difficult to sustain. Interestingly, African countries exhibit relatively high Individualism (58.8 and 60.6 for High and Medium Corruption, respectively). This partially contradicts the traditional assumption that African societies are predominantly collectivist (Hofstede, 2011). However, Hamilton & Hammer (2018) suggested thateconomic liberalization and global influences may be gradually shifting African societies toward more individualistic values, which could explain this trend.

4.1.4. Uncertainty Avoidance Across Regions and Corruption Levels

Unlike other cultural dimensions, Uncertainty Avoidance appears to be more regionally influenced rather than shaped by corruption levels. African countries, regardless of corruption levels, exhibit relatively low Uncertainty Avoidance (54.9–59.1), supporting Beugelsdijk & Welzel’s (2018) argument that African societies tend to be more adaptive to uncertainty due to historical and economic volatility. Conversely, highly corrupt European (76.9) and American (79.4) countries exhibit the highest Uncertainty Avoidance, aligning with Achim (2016), who found that corrupt societies often create uncertain environments that increase risk aversion. However, the lack of significant differences in Uncertainty Avoidance across corruption levels within Asia and America challenges Seleim & Bontis (2009), who suggested that corruption strongly amplifies uncertainty in all societies.

4.2.          Analysis of Variance (ANOVA)

To inferential evaluate the effects of Region and Level of Corruption on cultural dimensions, a Two-Way ANOVA was conducted.

4.2.1. Masculinity

Table 2: ANOVA Results for Masculinity

Source: Researcher’s computation

Table 2 presents the ANOVA results for Masculinity, showing that Region (p = 0.493), Corruption Level (p

= 0.316), and the interaction effect between Region and Corruption (p = 0.485) are all non-significant. These results indicate that Masculinity remains stable across different geographic regions and corruption levels, aligning with Hofstede (2011) and Beugelsdijk & Welzel (2018), who found that Masculinity is deeply ingrained in societal norms and does not fluctuate based on governance quality or geographic factors. Thefindings also support Achim (2016), who argued that corruption does not significantly impact gender role differentiation or competitiveness withincultures. Additionally, the lack of significant regional variation contradicts Seleim & Bontis (2009), who suggested that Masculinity may vary across regions based on historical governance structures and economic transitions. The non-significant interaction effect (p = 0.485) further suggests that Masculinity is not influenced by the interplay between geography and corruption, reinforcing the idea that cultural perceptions of gender roles remain relatively stable despite governance challenges. These findings indicate that future research should explore other socioeconomic variables, such as education and labor market structures, to better understand what influences changes in Masculinity across societies.

4.2.2. Power Distance

Table 3: ANOVA Results for Power Distance

Source: Researcher’s computation

Table 3 presents the ANOVA results for Power Distance, showing that Region (p = 2.41e-06) and Corruption Level (p = 8.08e-06) both have highly significant effects, while the interaction effect between Region and Corruption is also significant (p = 0.0024). These results confirm that Power Distance varies significantly across geographic regions and governance quality, aligning with Hofstede (2011) and Achim (2016), who argued thatsocieties with high corruption tend to reinforce hierarchical structures, limiting social mobility and increasing acceptance of centralized authority. The strong regional effect supports Beugelsdijk & Welzel (2018), who emphasized that historical governance systems shape societal perceptions ofpower and authority over time. Additionally, the significant impact of Corruption Level corroborates findings by Dipierro & Rella (2024) andChandler & Graham (2010), who demonstrated that corruption fosters greater power imbalances by strengthening elite control and reducing institutional accountability. The significant interaction effect (p = 0.0024) further suggests that the relationship between Power Distance andCorruption is not uniform across regions, reinforcing Zhou & Kwon’s (2020) argument that Western societies exhibit more fluid hierarchical perceptions based on governance quality, whereas other regions may maintain power structures regardless of corruption levels. These findingsindicate that effective governance reforms must be tailored to regional cultural contexts to reduce Power Distance and promote equitableinstitutional structures.

4.2.2.1 Post Hoc Analysis for Power Distance

Table 4: Tukey-Kramer Post Hoc Test for Power Distance

Source: Researcher’s computation

Table 4 presents the Tukey-Kramer post hoc test results for Power Distance, highlighting significant differences across regions and corruption levels. The results indicate that highly corrupt African countries exhibit significantly lower Power Distance compared to their counterparts inAmerica (p = 0.00298), Asia (p = 0.00632), and Europe (p = 0.00038), contradicting Hofstede’s (2011) assumption that corrupt societies inherently reinforce hierarchical structures. This finding aligns with Beugelsdijk & Welzel (2018), who argued that some African governance traditions emphasize communal leadership rather than centralized control, mitigating the effects of corruption on Power Distance. Additionally, low-corruption European countries have significantly lower Power Distance compared to highly corrupt European countries (p = 8.12E-06), confirming Zhou & Kwon’s (2020) assertion that hierarchical acceptance in Western societies fluctuates based on governance quality. The large differences observed between Europe:High and Europe:Low (-45.4, p = 8.12E-06) and America:High and Europe:Low (-35.3, p = 3.53E-05) support Chandler & Graham’s (2010) findings that hierarchical structures in Europe and America are more flexible and governance-dependent thanin other regions. Furthermore, the significant difference between medium- corruption African countries and highly corrupt American and Asian countries (-34.6, p = 0.00536 and - 32.3, p = 0.01035, respectively) suggests that corruption alone does not determine Power Distance, but rather interacts with historical governance structures and cultural norms. These results reinforce the importance of regional context in shaping hierarchicalacceptance and suggest that reducing Power Distance in corrupt societies requires governance reforms tailored to local cultural values.

4.2.3. Individualism

Table 5: ANOVA Results for Individualism

Source: Researcher’s computation

Table 5 presents the ANOVA results for Individualism, showing that Region (p = 2.03e-10) and Corruption Level (p = 0.002) have significant effects, while the interaction effect between Region and Corruption is not significant (p = 0.221). These findings indicate that both geographic location and governance quality play a crucial role in shaping Individualism, aligning with Hofstede (2011) and Achim (2016), who found thatindividualistic values tend to be higher in economically developed and politically stable societies. The strong regional effect supports Beugelsdijk & Welzel (2018), who emphasized that historical and institutional factors determine whether a society leans toward Individualism or Collectivism.Additionally, the significant influence of Corruption Level reinforces Dipierro & Rella (2024) and Spry (2018), who argued that higher corruption levels weaken individualistic values by fostering dependence on patronage networks and group loyalty. However, the non-significant interaction effect (p = 0.221) suggests that the impact of corruption on Individualism is consistent across regions, contradicting Seleim & Bontis (2009), who proposed that corruption erodes Individualism more aggressively in certain cultural contexts than others. These results highlight that while regional influences shape Individualism, governance and institutional trust remain key factors in understanding its global variations.

Table 6: Tukey HSD Post Hoc Test for Individualism

Source: Researcher’s computation

Table 6 presents the Tukey HSD post hoc test results for Individualism across regions, highlighting significant differences between America andAfrica (p = 1.23E-07), Asia and Africa (p = 8.76E-07), Europe and America (p = 2.57E-06), and Europe and Asia (p = 2.09E-05), while other comparisons do not show statistical significance. The results confirm that African countries exhibit significantly lower Individualism than America and Asia, aligning with Hofstede (2011) and Dipierro & Rella (2024), who noted that collectivist cultures, often found in Africa, emphasizegroup cohesion over personal autonomy.

Additionally, European countries demonstrate significantly higher Individualism than both Asia and America, reinforcing Spry’s (2018) argument that Western societies encourage personal accountability, which discourages corruption and promotes institutional trust. However, the non-significant difference between Europe and Africa (p = 0.4577) suggests that African societies may not be entirely collectivist, challenging previous assumptions by Hofstede (2011) and supporting Hamilton & Hammer (2018), who argued that economic globalization is gradually shifting someAfrican cultures toward more individualistic tendencies. Furthermore, the insignificant difference between Asia and America (p = 0.7398) contrastswith Seleim & Bontis (2009), who proposed that American societies should be significantly more individualistic than their Asian counterparts. These findings indicate that while regional factors influence Individualism, additional economic and governance-related elements must beconsidered to fully understand its variations.

4.2.4.   Uncertainty Avoidance

Table 7: ANOVA Results for Uncertainty Avoidance

Source: Researcher’s computation

Table 7 presents the ANOVA results for Uncertainty Avoidance, showing that Region has a significant effect (p = 0.00385), while Corruption Level is only marginally significant (p = 0.05578), and the interaction effect between Region and Corruption is not significant (p = 0.08436). These results indicate that regional factors play a more prominent role than corruption in shaping Uncertainty Avoidance, aligning with Beugelsdijk & Welzel (2018), who found that cultural attitudes toward uncertainty are often rooted in historical and economic stability rather than governance alone. The marginal significance of Corruption Level suggests that while governance and institutional quality may influence Uncertainty Avoidance to someextent, it is not the primary determinant, challenging the assumptions of Achim (2016) and Seleim & Bontis (2009), who proposed that corruption fosters greater uncertainty aversion. The non-significant interaction effect (p = 0.08436) further reinforces the idea that corruption does notconsistently modify the regional differences in Uncertainty Avoidance, supporting Zhou & Kwon (2020), who emphasized that cultural responses to uncertainty are shaped by long-standing social structures rather than short-term governance fluctuations. These findings suggest that future studies should explore alternative institutional and economic factors that may better explain variations in Uncertainty Avoidance across differentsocieties.

4.2.4.1 Post Hoc Analysis for Uncertainty Avoidance

Table 8: Tukey HSD Post Hoc Test for Uncertainty Avoidance

Source: Researcher’s computation

Table 8 presents the Tukey HSD post hoc test results for Uncertainty Avoidance across regions, revealing significant differences between Africaand both America (p = 0.0206) and Europe (p = 0.0166), while other regional comparisons do not reach statistical significance. These findings indicate that African countries exhibit significantly lower Uncertainty Avoidance than both American and European nations, aligning with Beugelsdijk & Welzel (2018), who argued that African societies tend to be more adaptive and resilient to uncertainty due to historical andeconomic volatility. However, the lack of significant differences between Asia and Africa (p = 0.7589) and between Europe and Asia (p = 0.1052)suggests that cultural responses to uncertainty are not universally determined by region alone, supporting Zhou & Kwon (2020), who emphasized the importance of institutional and historical contexts. Additionally, the non-significant difference between Asia and America (p = 0.1131) challenges prior assumptions by Achim (2016) and Seleim & Bontis (2009) that higher corruption levels should be associated with greateruncertainty aversion in all societies. Instead, these results suggest that regional governance structures and economic stability play a more decisive role in shaping Uncertainty Avoidance than corruption alone.

Table 9: Tukey HSD Post Hoc Test for Uncertainty Avoidance (Corruption Level)

Source: Researcher’s computation

Table 9 presents the results of the Tukey HSD post hoc test for Uncertainty Avoidance across different levels of corruption, indicating that there are no statistically significant differences between corruption levels. The low -high corruption comparison shows a mean difference of -9.55 (p = 0.0924), while Medium - High corruption and Medium - -low corruption comparisons also fail to reach significance (p = 0.9989 and p = 0.1589, respectively). These findings suggest that corruption levels alone do not systematically influence Uncertainty Avoidance, challenging previous assumptions by Achim (2016) and Seleim & Bontis (2009), who argued that corruption fosters higher risk aversion. Instead, the results align more closely with Beugelsdijk & Welzel (2018), who proposed that regional and historical factors play a more decisive role in shaping how societies respond to uncertainty than corruption alone. The marginally The non-significant difference between Low and High corruption levels suggests that while corruption may contribute to uncertainty in governance and institutions, other socio-political and economic variables must be considered to fully understand cultural responses to uncertainty.

 5. Conclusion

The findings of this study conclude with the following:

Masculinity: The results indicate that Masculinity does not significantly vary across regions or corruption levels (𝑝 = 0.485), suggesting thatgender role differentiation and competitiveness remain relatively stable across different governance contexts. This finding aligns with previous studies (Hofstede, 2011; Beugelsdijk & Welzel, 2018), which argued that masculinity is more deeply rooted in societal values than in political oreconomic corruption. Achim (2016) also found that corruption had no significant relationship with masculinity, reinforcing our conclusion that corruption levels do not directly shape masculine traits within a culture. However, these results contrast with Seleim and Bontis (2009), who posited that masculinity might be linked to governance structures in certain societies.

Power Distance: Unlike Masculinity, Power Distance exhibited a significant interaction effect between Region and Corruption Level (𝑝 = 0.0024), indicating that hierarchical structures and authority perceptions are not uniform but rather shaped by both geography and governance. The post hoc analysis reveals that Africa, despite having high corruption levels, exhibited significantly lower Power Distance compared to highly corrupt countries in America, Asia, and Europe. This finding contradicts Hofstede (2011) and Achim (2016), who suggested that corruption fosters greater Power Distance by reinforcing hierarchical governance. Instead, our findings align with Beugelsdijk & Welzel (2018), who argued that Power Distance may not always increase with corruption but could be mitigated by regional sociocultural traditions emphasizing communal leadershipstructures. Moreover, Europe exhibited the greatest variation in Power Distance based on corruption levels, confirming Zhou & Kwon’s (2020) assertion that Western societies display fluidity in hierarchical perceptions depending on governance effectiveness. The results also align withChandler & Graham (2010), who found that Power Distance within a region fluctuates due to corruption, especially in Europe.

Individualism: The findings confirm that Individualism significantly differs across regions and corruption levels (𝑝 = 2.03𝑒 − 10 and 𝑝 = 0.002,respectively), with no significant interaction effect. This reinforces prior studies by Hofstede (2011) and Dipierro & Rella (2024), which highlighted that individualistic societies tend to have lower corruption perceptions due to greater personal accountability and institutional trust. The results also corroborate Spry (2018), who suggested that corruption weakens individualistic values by increasing reliance on collective patronage networks. The post hoc analysis reveals that Africa remains distinct from other continents, exhibiting significantly lower Individualism levels, while Europe stands apart as the most individualistic region. This aligns with Hamilton & Hammer (2018), who reported that Western societies foster individualistic behaviors through robust legal frameworks. Additionally, the significant difference in Individualism between high-and low-corruption countries supports Achim (2016), who found a negative correlation between Individualism and corruption. However, the lack of significant differences between medium- and high-corruption countries contradicts Seleim & Bontis (2009), who argued that Individualism erodes steadily as corruption intensifies.

Uncertainty Avoidance: The results show that Uncertainty Avoidance varies significantly by region (𝑝 = 0.00385) but does not show meaningful differences based on corruption levels. Africa exhibits significantly lower Uncertainty Avoidance than both America and Europe, while Asia, America, and Europe display similar tendencies. These findings confirm previous research by Beugelsdijk & Welzel (2018), who reported thatAfrican societies tend to adopt more flexible, adaptive approaches to uncertainty. However, the lack of significant differences in Uncertainty Avoidance across corruption levels challenges Achim (2016) and Seleim & Bontis (2009), who argued that corruption breeds greater uncertainty,making societies more risk-averse. The marginal significance of corruption (𝑝 = 0.05578) suggests that while governance instability may contribute to uncertainty management styles, it is not the sole determinant. This aligns with Zhou & Kwon (2020), who emphasized that historicaland economic contexts influence uncertainty perception more than corruption alone.

6. Recommendations

Based on the findings of this study, the following recommendations are proposed:

i.               Since Masculinity remains stable across regions and corruption levels, future governance policies should focus on socio-economic factors rather than cultural shifts when addressing gender-based issues.

ii.              Given that Power Distance is significantly influenced by both Region and Corruption Levels, policymakers should implement context-specific leadership and governance reforms to reduce hierarchical imbalances in highly corrupt regions.

iii.            Countries aiming to reduce corruption should promote institutional trust and individual accountability, as these are key drivers of Individualism in low-corruption societies.

iv.             Since Uncertainty Avoidance varies primarily by Region rather than Corruption Level, policies should focus on historical and economic stability rather than solely addressing governance issues.

Author Contributions: All authors contributed to this research.

Funding: Not applicable.

Conflict of Interest: The authors declare no conflict of interest.

Informed Consent Statement/Ethics Approval: Not applicable.