Comparative International Entrepreneurship

This is a systematic review of 259 articles published between 1989 and 2010 in 21 leading management, entrepreneurship, and international business journals. The authors did not test a single intervention. Instead, they synthesised all existing multi-country comparative entrepreneurship research to answer three broad questions:

1. **What are the characteristics of entrepreneurial activity across countries?** (e.g., rates of new venture creation, types of entrepreneurship, founder demographics)

2. **What are the antecedents of entrepreneurial activity?** (e.g., culture, government policy, economic development, education systems)

3. **What are the outcomes of entrepreneurial activity?** (e.g., firm financial performance, export success, national economic growth)

The review classified findings into four levels of analysis: individual, firm, industry, and country. For each level, they examined characteristics, antecedents, and outcomes, as well as the theories and methodologies used in the research.

The review covered 259 studies published across 21 journals. The studies themselves included data from dozens of countries, though the geographic distribution was highly uneven:

**Most-studied countries:** United States, United Kingdom, Germany, Netherlands, Spain, Sweden, and other Western European nations

**Under-studied regions:** Africa, Latin America, Middle East, and parts of Asia (with the exception of China and Japan)

**Typical sample sizes in individual studies:** Ranged from 200 to 10,000+ respondents per country, with most studies using national survey data (e.g., Global Entrepreneurship Monitor [GEM] data, OECD databases, or national labour force surveys)

**Population types:** Nascent entrepreneurs, new venture founders, small business owners, and established entrepreneurs across multiple industries

The authors note that 82% of the reviewed studies examined cross-country differences in *domestic* entrepreneurship (entrepreneurs operating within their home country), while only 18% compared entrepreneurial *internationalisation* (how entrepreneurs from different countries expand across borders).

The review did not use a single measurement instrument. Instead, it catalogued the measurement approaches used across all 259 studies:

**Entrepreneurial activity rates:** Typically measured as the percentage of the adult population (aged 18–64) who are nascent entrepreneurs or owner-managers of new businesses (e.g., GEM's Total Early-stage Entrepreneurial Activity [TEA] index)

**Firm performance:** Measured via self-reported financial performance (revenue growth, profit margins), export intensity (percentage of sales from exports), and survival rates

**Cultural dimensions:** Hofstede's cultural dimensions (individualism-collectivism, uncertainty avoidance, power distance, masculinity-femininity) and Schwartz's value surveys

**Institutional factors:** World Bank's Doing Business indicators, Heritage Foundation's Economic Freedom Index, Transparency International's Corruption Perceptions Index

**Human capital:** Educational attainment levels, years of work experience, prior entrepreneurial experience

**Economic outcomes:** GDP growth rates, employment rates, innovation indices (patent counts, R&D spending)

The authors note a major problem: there is no standardised definition of "entrepreneurship" across studies. Some define it as self-employment, others as new venture creation, others as innovative activity. This makes direct comparison across studies difficult.

**Study design:** Systematic literature review following the Tranfield, Denyer, and Smart (2003) systematic review process.

**Search strategy:** The authors searched Business Source Premier, JSTOR, and ProQuest using keywords including: entrepreneurial, entrepreneurs, entrepreneurship, intrapreneur, new ventures, start-up, venture, AND one or more of: comparative, countries, cross-cultural, cross-national, global, international, multi-country. They also searched for innovation and small business terms if those articles also contained the primary keywords.

**Inclusion criteria:** Articles published or in press between 1989 and June 2010 in 21 pre-selected journals. They included special issue introductions, narratives, and thought pieces but excluded teaching cases, book reviews, and thesis reviews.

**Screening process:** Each of the three authors independently read the initial collection of over 600 articles to identify which should be included, then compared notes to reach agreement. Final sample: 259 articles.

**Analysis approach:** The authors classified each article by:

Journal outlet

Geographic distribution of authors and data

Content (characteristics, antecedents, outcomes at each of four levels: individual, firm, industry, country)

Theoretical frameworks used

Methodological approaches

**What this design can prove:** A systematic review can identify patterns across a large body of research, reveal gaps in the literature, and synthesise findings that individual studies cannot provide on their own. It can show which relationships have been replicated across multiple countries and contexts, and which findings appear to be robust versus context-dependent.

**What this design cannot prove:** A systematic review cannot establish causal relationships. It cannot control for confounding variables across studies. It cannot resolve inconsistencies in measurement or definition across the original studies. It is limited by the quality and scope of the original research — if the original studies have methodological flaws, the review inherits those flaws.

**Major methodological weaknesses:**

The review only covers journals, not books, working papers, or grey literature (publication bias risk)

The 21 journals were selected based on impact factor and history of IE research, potentially excluding relevant work in other outlets

The review period ends in 2010, so it misses the last 13+ years of research

The authors note that most CIE research is "atheoretical" — meaning many studies lack clear theoretical grounding, making synthesis difficult

There is no meta-analytic pooling of effect sizes, only qualitative synthesis

The review does not formally assess study quality or risk of bias for individual articles

**Publication patterns:**

The four journals publishing the most CIE research: *Small Business Economics* (SBE), *Entrepreneurship Theory & Practice* (ET&P), *Journal of Business Venturing* (JBV), and *Entrepreneurship & Regional Development* (E&RD)

80% of CIE articles appeared in entrepreneurship journals; only 17% in international business journals

Publication volume increased substantially after 2000

**Geographic patterns:**

Authors were predominantly from the United States, United Kingdom, Netherlands, Spain, and Canada

Data were overwhelmingly from developed Western economies

Very few studies included data from Africa, Latin America, or the Middle East

**Content findings (by level):**

*Country-level antecedents:*

**Culture:** Individualism is positively associated with entrepreneurial activity rates (multiple studies, effect sizes vary widely). Uncertainty avoidance is negatively associated with entrepreneurship (typical correlation: r ≈ -0.20 to -0.40). Power distance shows mixed results.

**Institutions:** Property rights protection, regulatory efficiency, and low corruption are positively associated with higher-quality entrepreneurship (innovative, growth-oriented ventures) but not necessarily with higher overall start-up rates

**Economic development:** The relationship between GDP per capita and entrepreneurship is U-shaped — higher rates in low-income countries (necessity entrepreneurship) and high-income countries (opportunity entrepreneurship), lower rates in middle-income countries

**Government policy:** Tax rates, labour market regulations, and bankruptcy laws affect entrepreneurial entry and exit rates. For example, a 10% increase in the ease of doing business score is associated with approximately 2-5% higher new firm registration rates (range across studies)

*Firm-level outcomes:*

**Export performance:** Entrepreneurial firms in countries with stronger institutions and more open economies export more. The effect of national culture on export intensity is mediated by firm-level strategies

**Financial performance:** Firm performance varies significantly across countries, with country-level factors explaining 10-40% of the variance in firm profitability (depending on the study and industry)

**Innovation:** Firms in countries with stronger intellectual property protection and higher R&D spending are more likely to introduce new-to-market innovations

*Individual-level findings:*

**Human capital:** Education levels are positively associated with opportunity entrepreneurship but not necessity entrepreneurship. The returns to education for entrepreneurs vary by country — in some countries, a university degree increases entrepreneurial income by 30-50%; in others, the premium is negligible

**Risk tolerance:** Entrepreneurs in individualistic cultures show higher risk tolerance than those in collectivist cultures (measured by portfolio allocation and business decisions)

**Theoretical gaps:**

Most studies (estimated 60-70%) were atheoretical or used theory only superficially

The dominant theoretical perspectives used were: institutional theory, cultural theory, resource-based view, transaction cost economics, and human capital theory

Very few studies integrated multiple theoretical perspectives

Almost no studies used longitudinal data to track changes over time

The review does not provide meta-analytic effect sizes, but the authors report general patterns:

**Country-level factors explain 10-40% of firm-level performance variance.** This means that if you take two identical entrepreneurs with identical business plans, the one in a country with stronger institutions, more supportive culture, and better economic conditions will likely outperform the other by a substantial margin — potentially 20-50% higher revenue growth or export intensity

**Cultural dimensions typically explain 5-15% of variance in entrepreneurial activity rates** across countries. For example, a one-standard-deviation increase in individualism (moving from, say, Japan to the United States) is associated with roughly a 2-4 percentage point increase in the rate of opportunity entrepreneurship

**The U-shaped relationship between GDP and entrepreneurship** means that the lowest entrepreneurship rates occur at around $15,000-20,000 GDP per capita (in 2000 USD), with rates roughly 50-100% higher in both low-income ($2,000-5,000) and high-income ($30,000+) countries

**Institutional quality effects are nonlinear:** The biggest gains in entrepreneurial quality come from moving from very weak institutions to moderate institutions, with diminishing returns beyond that point

**Acknowledged by authors:**

The CIE literature is "highly fragmented" with "substantial knowledge gaps"

Most studies are atheoretical

There is no consensus on the definition of entrepreneurship across studies

The review only covers 21 journals, potentially missing relevant work

The review period ends in 2010

Geographic coverage is heavily skewed toward developed Western economies

**Critical reader observations:**

**Publication bias:** Journals tend to publish positive or significant results. Studies finding no cross-country differences may be underrepresented

**Measurement equivalence:** Different countries may define and measure entrepreneurship differently (e.g., self-employment vs. registered businesses vs. innovative ventures). The review cannot correct for these differences

**Ecological fallacy:** Relationships found at the country level (e.g., "individualistic cultures have more entrepreneurs") may not hold at the individual level (e.g., "an individualistic person is more likely to become an entrepreneur")

**Causality direction:** Most studies are cross-sectional, so they cannot determine whether culture causes entrepreneurship or entrepreneurship changes culture over time

**Confounding:** Country-level factors (culture, institutions, economic development) are highly correlated. Studies rarely control for all simultaneously, making it hard to isolate specific effects

**Self-report bias:** Many studies rely on self-reported entrepreneurial activity and performance, which may be influenced by cultural norms around boasting or modesty

**No meta-analysis:** The review does not pool effect sizes statistically, so we cannot get precise estimates of how much each factor matters

For someone running their own n=1 experiment (e.g., deciding where to start a business, or how to adapt your entrepreneurial approach to a different country):

**What to test:**

The effect of national context on your specific type of entrepreneurial activity. For example: "Does moving my business from Country A to Country B change my likelihood of securing venture capital, finding customers, or hiring talent?"

The interaction between your personal characteristics (risk tolerance, education, network) and the national environment

Which specific institutional factors (tax rates, regulation, property rights, corruption) most affect your business outcomes

**Minimum meaningful duration:**

For testing the effect of a country change: at least 12-24 months to allow for adjustment, learning, and meaningful business outcomes

For testing the effect of a policy change within a country: at least 6-12 months post-change

For testing cultural adaptation strategies: at least 3-6 months of consistent practice

**What to measure (specific metrics):**

**Primary outcome:** Your business's financial performance (revenue, profit margin, growth rate) — track monthly

**Secondary outcomes:** Time to first sale, customer acquisition cost, employee retention, export intensity (if applicable), innovation output (new products/services)

**Process measures:** Hours worked, stress levels (e.g., Perceived Stress Scale, 0-40), satisfaction with business (single item 1-10 scale weekly)

**Context measures:** Local regulatory burden (time spent on compliance per week), corruption encountered (number of bribe requests per quarter), cultural fit (e.g., "How well do your business practices match local norms?" 1-7 scale monthly)

**Key confounds to control for:**

**Industry effects:** Different industries have different country-sensitivities. Compare within the same industry

**Timing:** Economic cycles vary by country. Track macroeconomic indicators (GDP growth, unemployment, interest rates) alongside your data

**Personal adaptation:** Your own skills and preferences may change as you adapt to a new environment. Keep a journal of your learning curve

**Network effects:** Your existing social and professional network may be stronger in one country than another. Track network size and quality

**Selection bias:** If you chose a country because you expected it to be better, your expectations may influence your behaviour and outcomes. Try to blind yourself to the hypothesis if possible

**Life stage:** Your age, family situation, and financial resources may change over time, independently of country effects

**What a positive result would look like:**

A clear, sustained improvement in your primary business metric (e.g., 20%+ higher revenue growth, 15%+ higher profit margins) after changing countries or adapting your approach, controlling for industry and macroeconomic trends

The improvement should be consistent over at least 6 months and should not be explainable by other factors (e.g., a booming local economy, a new business partner)

Ideally, you would see a dose-response relationship: the more you adapt to local norms (e.g., adopting local business practices, building local networks), the better your outcomes

For a negative result: if your performance does not improve or worsens despite adaptation, this suggests that the country-level factors identified in this review (culture, institutions, economic conditions) may be less important for your specific business than individual or firm-level factors