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This study aims to estimate the impact of refugee inflows on host countries’ entrepreneurial rates. The refugee crisis led to an increased scientific and public policy interest in the impact of refugee inflows on host countries. One important perspective of such an impact, which is still underexplored, is the impact of refugee inflows on host countries entrepreneurial rates. Given the high number of refugees that flow to some countries, it would be valuable to assess the extent to which such countries are likely to reap the benefits from increasing refugee inflows in terms of (native and non-native) entrepreneurial talent enhancement.

Resorting to dynamic (two-step system generalized method of moments) panel data estimations, based on 186 countries over the period between 2000 and 2019, this study estimates the impact of refugee inflows on host countries’ entrepreneurial rates, measured by the total early-stage entrepreneurial activity (TEA) rate and the self-employment rate.

In general, higher refugee inflows are associated with lower host countries’ TEA rates. However, refugee inflows significantly foster self-employment rates of “medium-high” and “high” income host countries and host countries located in Africa. These results suggest that refugee inflows tend to enhance “necessity” related new ventures and/ or new ventures (from native and non-native population) operating in low value-added, low profit sectors.

This study constitutes a novel empirical contribution by providing a macroeconomic, quantitative assessment of the impact of refugee from distinct nationalities on a diverse set of host countries' entrepreneurship rates in the past two decades resorting to dynamic panel data models, which enable to address the heterogeneity of the countries and deal with the endogeneity of the variables of the model.

Entrepreneurs are generally considered to be committed in order to strive for highly desirable goals, such as growth or commercial success. However, commitment is a multidimensional concept and may have asymmetric relationships with positive or negative entrepreneurial outcomes. This paper aims to provide a nuanced perspective to show under what conditions commitment may be detrimental for entrepreneurs and lead to overinvestment.

Using a sample of entrepreneurs from incubators in France (N = 437), this study employs a configurational perspective, fuzzy-set qualitative comparative analysis (fsQCA), to identify which commitment profiles lead entrepreneurs to overinvest different resources in their entrepreneurial projects.

The paper exposes combinations of conditions that lead to overinvestment and identifies five different commitment profiles: an “Affective profile”, a “Project committed profile”, a “Profession committed profile”, an “Instrumental profile”, and an “Affective project profile”.

The results show that affective commitment is a necessary condition for entrepreneurs to conduct overinvesting behaviors. This complements previous linear research on the interdependence between affect and commitment in fostering detrimental outcomes for nascent entrepreneurs.

This study aims to address the question of why managers make different decisions in employee downsizing when their firms face external threats. Our research intends to shed light on whether and how CEOs' cognition (motivational attributes associated with regulatory focus) influences their decision-making and firms’ strategic actions on downsizing under high resource scarcity in the industry environment.

We used a longitudinal panel of 5,544 firm-year observations of US firms from 2003 to 2015 to test our conceptual model. The data was obtained from various sources, including corporate earnings call transcripts and archival databases. We used panel logistic regressions with both fixed and random effects in our research design.

Our results suggest that CEOs' motivational attributes could influence their employee downsizing decisions in response to external threats. We find that CEOs who are more promotion-focused (a stronger drive towards achieving ideals) are less likely to lay off employees during high resource scarcity. Conversely, CEOs with a higher prevention focus (a greater concern for security) do not have a meaningful impact on employee downsizing during periods of external resource scarcity.

Previous research has argued that a significant external threat would diminish individuals' impact on firm strategies and outcomes. Our findings challenge this idea, indicating that CEOs with a stronger drive towards achieving ideals are less inclined to lay off employees when resources are scarce in the environment. This study contributes to behavioral strategy research by providing new insights into how upper echelons’ cognition can influence their decision-making and firms’ employee downsizing.

Rigorous applications of analytical tools in information systems (IS) research are important for developing new knowledge and innovations in the field. Emerging tools provide building blocks for future inquiry, practice and innovation. This article summarizes the findings of an analysis of the adoption and reporting of partial least squares structural equation modeling (PLS-SEM) analytical tools by Industrial Management & Data Systems authors in the most recent five-year period.

Selected emerging advanced PLS-SEM analytical tools that have experienced limited adoption are highlighted to broaden awareness of their value to IS researchers.

PLS-SEM analytical tools that facilitate understanding increasingly complex theoretical models and deliver improved prediction assessment are now available. IS researchers should explore the opportunities to apply these new tools to more fully describe the contributions of their research.

Findings demonstrate the increasing acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is a preferred structural equation modeling (SEM) method in many research settings and will become even more widely applied when IS researchers are aware of and apply the new analytical tools.

Emerging PLS-SEM methodological developments will help IS researchers examine new theoretical concepts and relationships and publish their work. Researchers are encouraged to engage in more complete analyses by applying the applicable emerging tools.

Applications of PLS-SEM for prediction, theory testing and confirmation have increased in recent years. Information system scholars should continue to exercise sound practice by applying these new analytical tools where applicable. Recommended guidelines following Hair et al. (2019; 2022) are included.