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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.

This paper aims to address which resources provided by an entrepreneurial ecosystem (EE) are necessary for deep technology entrepreneurship.

The authors used a novel approach known as necessary condition analysis (NCA) to data on EEs and deep-tech startups from 132 countries, collected in a global innovation index and Crunchbase data sets. The NCA makes it possible to identify whether an EEs resource is a necessary condition that enables entrepreneurship.

Necessary conditions are related to political and business environment; education, research and development; general infrastructure; credit; trade; diversification and market size; and knowledge absorption capacity.

The results show that business and political environments are the most necessary conditions to drive deep-tech entrepreneurship.

Policymakers could prioritize conditions that maximize entrepreneurial output levels rather than focusing on less necessary elements.

Some resources require less performance than others. So, policymakers should consider allocating policy efforts to strengthen resources that maximize output levels.

Studies on deep-tech entrepreneurship are scarce. This study provides a bottleneck analysis that can guide the formulation of policies to support deep-tech entrepreneurship, as it allows to identify priority areas for resource allocation.

This study aims to examine the potential determinants of entrepreneurial intentions (EIs) among business students. To that end, the study investigates the role of entrepreneurship education (EE) and entrepreneurial passion (EP) (inventing and founding), as well as the mediating role of attitude towards entrepreneurship (ATE) and the moderating role of university support.

A close-ended questionnaire measured on a seven-point Likert scale was used to collect data from business students at nine universities in Punjab, Pakistan. The sample size comprises 377 participants who were selected using a stratified random sampling technique. Partial least square structural equation modeling (PLS-SEM) was then applied to assess the study’s model and the postulated hypothesis.

The findings indicated that (a) every independent variable (IV) directly impacts EI [dependent variable (DV)] except EP for founding (EPF), (b) ATE significantly mediates the relationship between IV and DV (c) perceived university support positively moderates the relationship between ATE and EI.

As an implication to policy, the Government must ensure that students are exposed to business environments and find university support through different paths. Specifically, Pakistan’s Minister of Education and the Higher Education Commission (HEC) may consider designing university programs that lead to more influential EE. The empirical findings may help policymakers develop effective policies for promoting entrepreneurship.