The straw that broke the camel’s back
: a quantitative study on social enterprises in the UK, and their subsequent risk of mission drift

  • Pontus Walter Peter Ekdahl (Student)

Student thesis: Master's Thesis


The goal of this study is to understand why some subsets of social enterprises outperform others in regards to social performance and impact, and what underlying factors contribute to this superior performance, resulting in lower risk of mission drift and mission failure. This paper will utilize secondary quantitative data, obtained from Social enterprises UK and their Social Enterprises Advisory Panel (SEAP), an initiative to collect data from social enterprises based in the UK, in a regular and light-hearted manner, with over 300 participants. SPSS will be utilized to run a multinomial logistics regression, observing the decreasing, and increasing odds ratios between the independent variables of annual turnover, number of social missions, impact of the pandemic (binary) and the 7 identified groups of social enterprises, for belonging in different outcome groups among the dependent variable’s “growth” and “cashflow”. This thesis concludes that as a social enterprise increases its number of social missions, the odds ratio of seeing positive organizational growth and a low cashflow position increases. Further, social enterprises which have been negatively affected by the pandemic faces increasing odds ratios of having a large cashflow position, and stagnant growth, possibly indicating a mission drift. This thesis contributes to the theoretical field of social enterprises through the extensions of the framework presented by Santos, Pache and Moroz (2015), as well as managerial contributions regarding the social and financial performance, and business models of the social enterprises.
Date of Award6 Jul 2021
Original languageEnglish
Awarding Institution
  • Universidade Católica Portuguesa
SupervisorMarta Bicho (Supervisor)


  • Social enterprise
  • Hybrid organization
  • Missions drift
  • Multinomial logistics regression


  • Mestrado em Gestão e Administração de Empresas

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