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There is a growing understanding that gender-blind business support measures do not assist women’s enterprise development to the extent that they assist its male equivalent. Focusing efforts specifically on women’s enterprise development, and measuring the impact of those efforts, is paramount. This paper aims to assess the evolution of two indices that analyze high-impact female entrepreneurship development: the Gender-Global Entrepreneurship and Development Index (GEDI) and the 2015 Global Women Entrepreneur Leaders Scorecard. Both utilize data from reliable data sources, yet are limited by the quality and availability of sex-disaggregated data. However, they differ in terms of variable choice, methodology and results.

In this paper, the authors assess the evolution of two indices that analyze high-impact female entrepreneurship development. High-impact female entrepreneurship is defined as firms headed by women that are market-expanding, export-oriented and innovative. The assessment is focused on two new indices, the 2013 and 2014 Gender-GEDI and, the newly created measurement tool, the 2015 Global Women Entrepreneur Leaders Scorecard.

Both indices rely on existing data from reliable, internationally recognized data sets, yet are limited by the sex-disaggregated data that are currently available. However, they differ in terms of variable choice, methodology and results.

There is an increasing need by researchers and policy makers alike to consolidate existing data to better understand the existing barriers for women entrepreneurs and to be able to benchmark change. This paper assesses two indices that provide insights into the conditions for high-impact women entrepreneurs in a country comparative way.

This chapter shows how to construct and test case-based macro models. The chapter makes use of national data to examine influences on quality-of-life of national cultures as complex wholes and entrepreneurship activities in Brazil, Russia, India, China, Germany, and the United States (the six focal nations) plus Denmark (a small-size, economically developed, nation). The study tests McClelland’s (1961) and more recent scholars’ proposition that some cultural configurations nurture entrepreneur startups, while other cultures are biased toward thwarting startups. The study applies complexity theory to develop and empirically test a general theory of cultures’, entrepreneurship’s, and innovation’s impact on quality-of-life across nations. Because culture represents a complex whole of attitudes, beliefs, values, and behavior, the study applies a set-theoretic approach to theory development and testing of alternative cultural configurations. Each of 28 economical developed and developing nations is scored for the level of the national cultures for each of six focal countries. The study selected for the study enables multi-way comparisons of culture-entrepreneurship-innovation-QOL among large- and small-sized developing and developed nations. The findings graphically present the complex national cultural configuration (x-axis) with entrepreneur nurture/thwart (y-axis) of the 28 nations compared to the six focal nations. The findings also include recognizing national cultures (e.g., Switzerland, the United States) nurturing entrepreneurial behavior versus other national cultures (e.g., Brazil and India) thwarting entrepreneurial behavior. The study concludes with a call to recognize the implicit shift in culturally implicit thinking and behavior necessary for advancing national platforms designed to successfully nurture entrepreneurship. Entrepreneur strategy implications include the observation that actions nurturing firm start-ups by nations low in entrepreneurship will unlikely to be successful without reducing such nations’ high levels of corruption.

The purpose of the paper is to contribute to the understanding of regional entrepreneurial development by constructing an institutional environment index in India, where high heterogeneity is found in the economic development and entrepreneurial activities across its states. It tries to fill the gap of research which hampers the effectiveness of policy efforts to promote job growth through entrepreneurship development in India and contributes in understanding the phenomenon why the relative contribution of entrepreneurship varies across states.

The paper uses a composite index of institutional quality based on the Penalty for Bottleneck (PFB) methodology to capture the institutional environment differences across the states of India. The relationship between the institutional environment and the measures of entrepreneurship is established through various statistical and econometric techniques such as correlation and regression.

The paper finds the regional and contextual institutional environment differences in India starker and more varied than is generally viewed. The empirical evidence suggests that the differences in institutional quality scores can play a significant role in explaining the variations in the extent of entrepreneurial activities across the Indian states. The findings of this paper demonstrate a differential influence of the local institutional environment on the entrepreneurial activities at a regional level in a developing economy like India.

This study is limited by the data sources and index design; therefore, it cannot completely specify all institutional factors and their combined influences on entrepreneurial activities at the regional level. However, it makes a significant contribution to expanding the current body literature of institutional environment reform and entrepreneurship development in developing countries.

The policy implication of the paper highlights the need of policymakers to think outside the individual policy silos and consider the institutional environment as a whole. Priority attention of the policymakers should be on the institutional reform for any type of entrepreneurship development. A corollary implication of the O-ring theory of development and the PFB methodology is that the policy effort is allocated most effectively when it seeks to alleviate bottlenecks.

The main implication of this paper for the policymaking is that it is necessary to focus more on the weak institutional factors (bottlenecks) and on the general environment improvement for any entrepreneurship development.

The study contributes to study the problem of entrepreneurship discrepancy in India through the lens of institutions and institutional environment. This study is an improvement over the previous studies by testing the statistical significance of the institutional environment on the entrepreneurship.

Using various macro-level measures of economic and political performance Shleifer and Treisman (2005) and Treisman (2014) call Russia a “normal country” implying that Russia’s economic and political development is not deviating from the other middle-income or transition countries significantly. The purpose of this paper is to challenge this proposition and investigate whether Russia is a normal country in terms of entrepreneurship by comparing Russia with other post-socialist and similarly developed countries.

Many studies have examined Russia’s institutional setup to explain its deficiencies in entrepreneurial activity. However, there is a lack of comprehensive research taking into account both the individual and institutional dimensions of the entrepreneurial ecosystem. The authors use the Global Entrepreneurship Index (GEI) methodology to analyze Russia’s quality-related individual as well as institutional features from a system perspective in a single model.

Russia’s performance has been poor relative to the post-socialist countries and to most of the former republics of the Soviet Union. Russia’s entrepreneurial profile is different from other transition and similarly developed non-transition countries, as well. Russia’s scores are less than the scores of other post-socialist countries in six out of the nine pillars of entrepreneurial attitudes and abilities. In sum, conditions supporting entrepreneurship in Russia lag seriously behind other post-socialist countries. Moreover, Russia’s individual scores are even lower than the institutional ones. Hence, improving the hostile environment alone would not be sufficient for entrepreneurship development.

Although, there have been numerous studies analyzing Russia’s macroeconomic conditions, institutional development, and entrepreneurship, there is lack of comprehensive studies. Besides common macro-level measures, the authors use a unique, GEI data set that combines institutional factors relating to entrepreneurship or new business creation with measures of individual capabilities, motivations, and attitudes about entrepreneurship. The single-model framework reveals that individual factors are even greater obstacles to entrepreneurship development in Russia than the institutional factors that most studies focus on.

This paper aims to investigate and examines Sweden's overall entrepreneurship performance (ecosystem) by applying the Global Entrepreneurship Index (GEI) while benchmarking the entrepreneurial ecosystem of Sweden with that of Finland and Norway.

In terms of subindices, pillars and component factors, this research analyzes the entrepreneurial ecosystem of Sweden using the GEI supplemented by the Penalty for Bottleneck (PFB) approach utile for identification of bottlenecks. In addition, the Swedish ecosystem is benchmarked against its Finnish and Norwegian counterparts drawing on data collected between 2015 and 2018.

Using data drawn from the GEI, Sweden manifests a strong entrepreneurial ecosystem with a GEI score of 72.7 out of 100. However, fledgling start-up skills, insufficient human capital, and slow and erratic growth undercut otherwise solid entrepreneurial aspirations drawing on well-developed institutional variables. On a macrolevel, Sweden evinces greater capacity for entrepreneurship and innovation than either Norway or Finland but, on a microlevel, several discontinuities manifest in terms of subindices, pillars and component factors to the advantage of Norway and/or Finland and, conversely, to the detriment of Sweden.

Policymakers should fund a mix of programs and institute regulatory reforms designed to promote entrepreneurial systemic development in Sweden by remediating entrepreneurial gaps depressing GEI scores. Crucial policy interventions are required to accrete start-up skills and human capital and engender high growth. Incremental funding of 47% over current levels budgeted to buoy entrepreneurial activity are mandated for Sweden to approach its GEI potential.

Insights are derived from extracting data drawn from a new methodology for gauging entrepreneurial activity incorporating individual and institutional variables into a single model that combines PFB and GEI analysis with a view to identifying, through the PFB approach and weak aspects of Sweden's entrepreneurial performance.

By drawing upon institutional theory, the purpose of this paper is to investigate the role of four critical resources (credit, electricity, contract enforcement and political governance) in explaining the quality of entrepreneurship and the depth of the supporting entrepreneurship ecosystem in Africa.

A quantitative approach based on ordinary least squares regression analysis was used. Three data sources were employed. First, the Global Entrepreneurship Index (GEI) of 35 African countries was used to measure the quality of entrepreneurship and the depth of the entrepreneurial ecosystem in Africa which represents the dependent variable. Second, the World Bank’s data on access to credit, electricity and contract enforcement in Africa were also employed as explanatory variables. Third, the Ibrahim Index of African Governance was used as an explanatory variable. Finally, country-specific data on four control variables (GDP, foreign direct investment, population and education) were gathered and analysed.

To support entrepreneurship development, Africa needs broad financial inclusion and state institutions that are more effective at enforcing contracts. Access to credit was non-significant and therefore did not contribute to the dependent variable (entrepreneurship quality and depth of entrepreneurial support in Africa). Access to electricity and political governance were statistically significant and correlated positively with the dependent variables. Finally, contract enforcement was partially significant and contributed to the dependent variable.

A lack of GEI data for all 54 African countries limited this study to only 35 African countries: 31 in sub-Saharan Africa and 4 in North Africa. Therefore, the generalisability of this study’s findings to the whole of Africa might be limited. Second, this study depended on indexes for this study. Therefore, any inconsistencies in the index aggregation if any could not be authenticated. This study has practical implications for the development of entrepreneurship in Africa. Public and private institutions for credit delivery, contract enforcement and the provision of utility services such as electricity are crucial for entrepreneurship development.

The institutional void is a challenge for Africa. This study highlights the weak, corrupt nature of African institutions that supposedly support MSME growth. Effective entrepreneurship development in Africa depends on the presence of a supportive institutional infrastructure. This study engages institutional theory to explain the role of institutional factors such as state institutions, financial institutions, utility providers and markets in entrepreneurship development in Africa.

While the trade sector has long been the backbone of growth followed by real estate development in Dubai, the impact of reduced oil revenues in the Gulf Cooperation Council (GCC) has affected Dubai. GCC countries have identified innovation and transitioning to a knowledge-based economy as critical components of sustainable growth in the post-oil world. The purpose of this chapter is twofold: (1) to examine UAE’s competitiveness relative to four economies for which we can draw meaningful conclusions (Qatar, Singapore, Norway, and Switzerland) and (2) to integrate macro- and micro-level findings in an actionable framework. Using the composite Knowledge Economy Index (KEI) developed by the World Bank (2008, 2012), we conclude that UAE should prioritize three key areas to ­transition to a knowledge-based economy: the regulatory regime, innovation, and human capital. These findings are consistent with a recent study by the UAE Department of Economic Development/INSEAD, which highlights two areas that need addressing: “Creation” (knowledge creation) and “Anchoring” (institutional environment for innovation). We integrate these macro-level findings with research at the innovation ecosystem level (and particularly survey-based research completed by Wamda Research Lab) to propose a comprehensive action framework across all ecosystem stakeholders (i.e., government, entrepreneurs, academia, support ecosystem, and corporates). The action matrix allows individual stakeholders to drive corresponding actions and prioritize across short- and long-term initiatives.

Based on an efficiency analysis of the Global Entrepreneurship Index (GEI), the purpose was to demonstrate that the Key Performance Indicators’ analysis leads to a misinterpretation of the dynamics of National Systems of Entrepreneurship (NSEs). This might hamper the formulation of sound initiatives in other economies, with relevant implications for developing countries.

This study categorized GEI indicators into output and input indicators. Following this procedure, each dimension was analyzed separately and then compared to each other, considering countries’ productivity rates. The main focus is given to the case of the US, the usual benchmark for NSEs and leader in the GEI Index. Lastly, a taxonomy of NSEs according to their efficiency levels was developed.

The findings of the analysis demonstrates that innovation-driven economies with lower positions in GEI ranking often have higher productivity rates when compared to economies with higher positions in GEI ranking. Specifically, the US appears not to be a good benchmark in terms of NSE efficiency.

The study’s approach is limited in scope by data availability on NSEs and the use of GEI, a representation of aggregate patterns of country-level entrepreneurial dynamics. More refined data are needed in order to clarify some insights from this research.

The perception of systemic efficiency should be considered more thoroughly when designing dedicated entrepreneurship-oriented policies in other countries that aim at establishing a more vibrant entrepreneurial system while facing resource constraints.

Simplistic views of systemic aspects may hamper the formulation of sound entrepreneurship-oriented initiatives with particularly relevant implications for public policy in laggard economies.

The value of this article relies on applied a simple metric – efficiency ratio – order than, e.g. data envelopment analysis to portray a key issue related to the interpretation of supranational rankings related to the entrepreneurship ecosystem make mainly by policymakers and scholars that is: pick the 1st one, follow the leader.