Tracking precursors of entrepreneurial intention: the case of researchers involved in eco-label industry

This article is based on the adaptation of Ajzen’s theory of planned behavior (TPB) to build an entrepreneurial intention framework tailored to the specific context of researchers involved in eco-label industry, who can be perceived as nascent entrepreneurs. The entrepreneurial intention model is tested on a convenience sample of researchers involved in eco-label industry from a wide range of countries. The configurational effect of research experience, personal attitude, funding instruments and entrepreneurial education level is tested for causal condition related to entrepreneurial intention of 25 eco-label researchers. The qualitative approach of data reveals that research experience and personal attitude relate positively to entrepreneurial career intentions and that these relationships are mediated by entrepreneurial education level. A multi-sided online platform connecting innovators and potential investors is considered a suitable solution for funding respondents’ results of research and innovation activities. Stimulating entrepreneurial motivations and intentions may help researchers to better adapt to alternative career perspectives. Results of this study suggest several ways to stimulate entrepreneurial career choices among researchers involved in eco-label industry.

     

International student mobility: A systematic review and research agenda

This study aimed to synthesize fragmented knowledge about international student mobility (ISM) in higher education to provide an understanding of existing studies and directions for future research. To this end, the authors conducted a systematic literature review using a hybrid approach that integrated bibliometric analysis with the theory, context, and method (TCM) framework (Paul et al., Journal of World Business, 2017;52(3):327–342). Applying bibliometric analysis, this study found publication trends, prolific journals, influential articles, and major themes in the field, whereas the TCM framework helped identify widely used theories (motivation theory, immigration theory, acculturation theory, learning theory, and capital theory), research contexts (destination country or region, population, and others), and methods in research and provided future study directions. The identified gaps in the existing literature suggest that future research should develop theoretical foundations and research designs to analyse new processes, patterns, and issues in ISM in higher education within the context of today's changing international environment. In addition to identifying the key research themes and research foundations of ISM in higher education, this review can help add value to the ISM literature from a marketing perspective. This is the first comprehensive literature review of this topic using a hybrid approach.     

Improving risk classification and ratemaking using mixture-of-experts models with random effects

In the underwriting and pricing of nonlife insurance products, it is essential for the insurer to utilize both policyholder information and claim history to ensure profitability and proper risk management. In this paper, we apply a flexible regression model with random effects, called the Mixed Logit-weighted Reduced Mixture-of-Experts, which leverages both policyholder information and their claim history, to categorize policyholders into groups with similar risk profiles, and to determine a premium that accurately captures the unobserved risks. Estimates of model parameters and the posterior distribution of random effects can be obtained by a stochastic variational algorithm, which is numerically efficient and scalable to large insurance portfolios. Our proposed framework is shown to outperform the classical benchmark models (Logistic and Lognormal GL(M)M) in terms of goodness-of-fit to data, while offering intuitive and interpretable characterization of policyholders' risk profiles to adequately reflect their claim history.