Exploring causal recipes of startup acceptance into business incubators: a cross-country study

Purpose: This study aims to outline the influence of various combinations of antecedent conditions for startups being accepted into business incubators in Italy and Romania. The degree to which these conditions affect acceptance is referred to here as the Business Ideas Acceptance Degree (BIAD). The antecedent conditions considered are business idea potential, business plan quality, entrepreneurial team features, business project progress stage, available financial resources, debts of potential incubated companies, commitment to apply for national/EU funds, business area related to incubator mission, proposed technological content level, technological transfer from university/research centres and spin-off of a partner-entity of the incubator. Design/methodology/approach: The methodological toolkit used was mixed: correlation-based analysis (CBA), machine learning (ML) techniques and fsQCA. Principal component analysis enabled the selection of the most representative antecedent conditions from both business incubator samples in Italy and Romania, further used in fsQCA analyses. XGBoost algorithm has been also used. K-Means clustering, an unsupervised learning algorithm that groups unlabeled dataset into different clusters, led to the configuration of two clusters associated to each of the countries involved in this study (Romania and Italy). Findings: The findings reveal the differences between the different antecedent conditions that can contribute to startups being accepted into business incubators in Italy and Romania. The validation of the fsQCA equifinality principle in both samples shows that the selected antecedent conditions, mixed in combinations of “causal recipes”, lead to a high BIAD by business incubators from both countries. Originality/value: This study reveals the differences between different antecedent conditions, capable to contribute to the start-up acceptance within business incubators from Italy and Romania. Furthermore, the validation of fsQCA equifinality principle in both samples highlight that the selected antecedent conditions, mixed in combinations of causal recipes, lead to a high degree of business ideas' acceptance in business incubators. This study aims to outline the influence of various combinations of antecedent conditions for startups being accepted into business incubators in Italy and Romania. The degree to which these conditions affect acceptance is referred to here as the Business Ideas Acceptance Degree (BIAD). The antecedent conditions considered are business idea potential, business plan quality, entrepreneurial team features, business project progress stage, available financial resources, debts of potential incubated companies, commitment to apply for national/EU funds, business area related to incubator mission, proposed technological content level, technological transfer from university/research centres and spin-off of a partner-entity of the incubator. Design/methodology/approach The methodological toolkit used was mixed: correlation-based analysis (CBA), machine learning (ML) techniques and fsQCA. Principal component analysis enabled the selection of the most representative antecedent conditions from both business incubator samples in Italy and Romania, further used in fsQCA analyses. XGBoost algorithm has been also used. K-Means clustering, an unsupervised learning algorithm that groups unlabeled dataset into different clusters, led to the configuration of two clusters associated to each of the countries involved in this study (Romania and Italy). Findings The findings reveal the differences between the different antecedent conditions that can contribute to startups being accepted into business incubators in Italy and Romania. The validation of the fsQCA equifinality principle in both samples shows that the selected antecedent conditions, mixed in combinations of “causal recipes”, lead to a high BIAD by business incubators from both countries. Originality/value This study reveals the differences between different antecedent conditions, capable to contribute to the start-up acceptance within business incubators from Italy and Romania. Furthermore, the validation of fsQCA equifinality principle in both samples highlight that the selected antecedent conditions, mixed in combinations of causal recipes, lead to a high degree of business ideas' acceptance in business incubators.