Abstract:This study uses the model of Patzelt and Shepherd (2011) to examine the factors influencing the identification of sustainable opportunities among SMEs in a developing country, Zambia. The factors under investigation include knowledge of the natural/social environment, perception of threats to the natural/social environment, altruism towards others and entrepreneurial knowledge. We interviewed 220 owner-managers in the trading and service sector who supply goods and services to the mining industry in Zambia. We found that altruism towards others was partially supported by our empirical results while the positive effects of knowledge of the natural/social environment and perception of threats to the natural/social environment on the identification of sustainable opportunities were not supported. Contrary to our expectations, entrepreneurial knowledge does not positively moderate the relationship between explanatory variables and the identification of sustainable opportunities. In sum, we found only limited empirical support for the model of Patzelt and Shepherd (2011) concerning the identification of sustainable opportunities. Our findings contribute to literature on entrepreneurship and sustainable opportunity identification by showing what factors influence the identification of sustainable opportunities. This can help us to create awareness among entrepreneurs regarding the effects of entrepreneurial activities on the environment and society; consequently, stimulating entrepreneurs to identify sustainable opportunities.

Purpose – The purpose of this study is to investigate the relationship between entrepreneurial motivation and small business growth in one of the poorest emerging countries: the African least developed country (LDC), Rwanda. Design/methodology/approach – On the basis of theoretical resources and a pre-study of interviews with local experts in Rwanda, the authors developed a survey for this study. Based on primary data from 133 Rwandan small business owners, the authors conducted an exploratory factorial analysis to uncover the underlying factors. Subsequently, the authors conducted regression analyses to test the hypotheses. Findings – The analyses show that the predictors for the growth of small businesses can be divided into three factors: one factor with a mix of motivations related to family background, necessity and opportunity motivations; one factor with items predominantly related to opportunity motivation; and one factor with items related to necessity motivation. The first factor has the strongest positive effect on small business growth followed by the second factor. The factor concerning necessity motivation was irrelevant for further inclusion in the regression model, due to insufficient reliability. Research limitations/implications – The study contributes to the debate in the literature about which entrepreneurial motivations affect the growth of small businesses in LDCs. Practical implications – The results reported in this study also have implications for how small business growth in LDCs can be supported and stimulated by policy-making practice. Originality/value – This study shows that entrepreneurial motivation is not a clear distinction between necessity and opportunity, but that a mix of motivations is important to assess the growth of small businesses in an LDC, which is an understudied context.

The financial services sector has internationalized over the last few decades. Important differences and similarities in financial behavior can be anticipated between both consumers within a particular country and those living in different countries. For companies in this market, the appropriate choice between strategic options and the resulting international performance may critically depend on the cross-national demand structure for the various financial products. Insight into country segments and international consumer segments based on domain-specific behavioral variables will therefore be of key strategic importance. We present a multi-level latent class framework for obtaining simultaneously such country and consumer segments. In an empirical study we apply this methodology to data on ownership of eight financial products. Information is available for fifteen European countries, with a sample size of about 1000 consumers per country. We find that both country segments and consumer segments are highly interpretable. Furthermore, consumer segmentation is related to demographic variables such as age and income. Our conclusions feature implications, both academic and managerial, and directions for future research. JEL codes: C2, D1, F00, G1, M31

The financial services sector has internationalized over the last few decades. Important differences and similarities in financial behavior can be anticipated between both consumers within a particular country and those living in different countries. For companies in this market, the appropriate choice between strategic options and the resulting international performance may critically depend on the cross-national market structure of the various financial products. Insight into country segments and international consumer segments based on domain-specific behavioral variables will therefore be of key strategic importance. We present a multi-level latent class framework for obtaining simultaneously such country and consumer segments. In an empirical study, we apply this methodology and several alternative modeling approaches to data on ownership of eight financial products. Information is available for 15 European countries, with a sample size of about 1000 consumers per country. We find that both country segments and consumer segments are highly interpretable. Also, consumer segmentation is related to demographic variables such as age and income. Our conclusions feature implications, both academic and managerial, and directions for future research. D

Summary.  The paper demonstrates application of the latent Markov model for assessing developments by individuals through stages of a process. This approach is applied by using a database on ownership of 12 financial products and various demographic variables. The latent Markov model derives latent classes, representing household product portfolios, and shows the relationship between class membership and household demographics. The analysis provides insight into switching between the latent classes, reflecting developments of individual household product portfolios, and the effects of demographics on such switches. Based on this, we formulate equations to predict future acquisitions of financial products. The model accurately predicts which product a specific household unit acquires next, for most of the products.