As social problems become more extensive and diverse, one of the most critical capabilities of social entrepreneurs is connecting and aligning various stakeholders. Social entrepreneurs can solve problems better through collaboration with stakeholders, and this leads to sustainable innovation of society. Accordingly, social entrepreneurship education (SEE) programs should be designed and operated to cultivate social entrepreneurs’ abilities to enhance connectivity with all relevant entities of the social enterprise ecosystem. Consequently, SEE can form ever-growing communities of social entrepreneurs while functioning as innovation hubs for entrepreneurial ecosystems (EEs) evolving on their own. To this end, this study proposes a design and assessment framework for SEE. The framework emphasizes strengthening internal connectivity among SEE program members and external connectivity with outside entities, including universities, firms, government agencies, civil societies, and natural environments. This framework clarifies how and to whom social entrepreneurs should connect throughout the SEE process. This paper analyzes the case of an MBA degree SEE program in Korea using this framework and identifies directions for further improvement of SEE, contributing to the social entrepreneurship and entrepreneurship education literatures by integrating SEE’s key features with social theories of learning and the quintuple helix model for sustainable innovation ecosystems. Practically, our findings provide a useful benchmark to find isolated internal and external entities that need more active interactions to achieve SEE’s purposes.

A variety of social enterprises (SEs) have recently emerged in many different countries in an effort to resolve diverse social problems. However, the value creation mechanism of SEs has not yet been disclosed. The purpose of this study is to reveal the value creation mechanism of SEs in manufacturing industry. To do so, we verify the role of social entrepreneurship and examine the effects of product innovation attributes and social capital on social value creation and financial performance by using structural equation modelling. Then, we conduct interviews with six experts in SE fields. According to the results of empirical study, the social entrepreneurship works as an antecedent of product innovation and social capital in SEs and the degrees of products' simplicity, usability and standardization positively affect the social value creation of SEs. In addition, the social value creation works as a complete mediator between the product innovation of SEs and their financial performance. The interviews suggest policy implications for successful social value creation and sustainability of SEs. This research contributes towards further studies on innovation of SEs and provides social entrepreneurs with guidelines in planning their innovation strategy or developing their products.

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PurposeThrough the resource-based view (RBV) and contingency theory, this study empirically investigates the impacts of smart manufacturing systems' maturity levels on the performance of small and medium-sized enterprises (SMEs). Moreover, it aims to examine how industry types (i.e. high- and low-tech industries) and human-resource factors (i.e. the proportion of production workers to total workers) as contingency factors influence the effects of smart manufacturing systems.Design/methodology/approachThe study conducted an empirical investigation of a sample of 163 Korean manufacturing SMEs. This study used an ordinary least squares regression to examine the impacts of the maturity levels of smart manufacturing systems on financial performance. Moreover, the impacts on operational efficiency were analysed using data envelopment analysis based on bootstrap methods and Tobit regression.FindingsThe RBV results indicate that the higher the maturity levels of smart manufacturing systems, the higher the financial performance and operational efficiency. Moreover, based on contingency theory, this study reveals that the effect of the maturity levels of smart manufacturing systems on financial performance and operational efficiency depends on firms' industry types and the proportion of production workers.Research limitations/implicationsThis study shows that the introduction of smart manufacturing systems can help SMEs achieve better financial performance and operational efficiency. However, their effectiveness is contingent on firms' industry types and the characteristics of their human resources.Practical implicationsSince the effects of the maturity levels of smart manufacturing systems on SME performance differ depending on their industries and the characteristics of human resources, managers need to consider them when introducing or investing in smart manufacturing systems.Originality/valueBased on the RBV and contingency theory, this is the first empirical study to examine the moderating effects of industry types and the proportion of production workers on the impacts of the maturity levels of smart manufacturing systems on the financial performance and operational efficiency of SMEs.