A political ideology lens on social entrepreneurship motivations

ABSTRACT

The traditional literature regarding social entrepreneurship does not question the political dimension. On the contrary, it tends to de-politicize societal issues. A growing number of researchers underline how this perspective cannot address the complexity and the dialogical nature of social entrepreneurship. However, while there may be a case for incorporating a political perspective, there is currently no conceptual framework to systematically inform an empirical exploration of the role played by the political vision of entrepreneurs. In this paper, we use the concept of political ideology to offer a solid framework to show how politics can shape social entrepreneurs’ motivations. More precisely we identify three political profiles – anti-statist, reformist and neoliberal – which shape the motives to engage in social entrepreneurship. We take an embedded case study approach of 17 social entrepreneurs involved in a social innovation boot camp and reveal the existence of both, left and right-wing approaches in social entrepreneurship.     

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企业、企业家等微观主体对货币政策的反应，在较大程度上影响货币政策的效果。货币政策可通过对企业家信心的影响，进而对公司投资效率产生作用。基于中国2007—2016年40个季度A股上市公司样本的实证研究表明：企业家信心在货币政策传导过程中有不可忽视的作用。企业家信心增强或者货币政策宽松时会加剧过度投资，减轻投资不足；企业家信心减弱或者货币政策紧缩时可以有效抑制过度投资，但会加剧投资不足。其中，国有企业对企业家信心和货币政策松紧的敏感性更强。进一步，货币政策对企业投资效率的影响，也会通过货币政策和企业家信心的交互作用而发挥作用。这种作用在国有企业和非国有企业之间无显著差异。     

What is happening in Paris? Airbnb,hotels, and the Parisian market: A case study

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Gender differences within early stage and established small enterprises: An exploratory study

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企业家创新的内在性和外在性

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我国经济适用房政策趋向分析

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Price and RevPAR determinants of Airbnb listings: Convergent and divergent evidence

This paper explores the performance determinants of Airbnb listings, analyzing three research questions. First, the study investigates the different effects generated by the antecedents on price and revenue; second, it ranks different groups of variables; third, it distinguishes between private rooms and entire homes or apartments. These research questions are addressed by analyzing Airbnb listings in Milan, a business city where the sharing economy is growing fast. In particular, the study will use the monthly data of all Airbnb listings in Milan recorded by AirDNA during the period from November 2014 to June 2019, which consists of 323,184 total observations. Some hedonic price models are calculated, adding the Shapley value approach. Empirical findings show some important differences between price and revenue determinants. Furthermore, listing type and size, along with location and seasonality, are by far the most important factors that explain performance differentials among Airbnb properties.     

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