European Social Enterprise Monitor (ESEM) was first launched in 2020 by Euclid Network (EN) to provide reliable and comparable data on the social entrepreneurship ecosystem. In the 2021-2022 period, the study is supported by the European Commision and the number of countries scaled from eight to 21 with the contribution of national partners within the Network.
The survey for the 2022 ESEM study was launched on 28 September 2021 by European Network for Social Enterprises (Euclid) – EN simultaneously in 21 European countries through an online platform. The survey was officially closed in February 2022.
To ensure methodological consistency and enable the benchmarking of results across 21 countries, the ESEM consortium has agreed on common criteria for the definition of SEs. When social impact is declared to be more important or equally important to financial interests when making strategic business decisions by respondents, it is accepted as an SE. This decision is based on the European Commission’s SE definition that reads as
A social enterprise is an operator in the social economy whose main objective is to have a social and environmental impact rather than make a profit for their owners or shareholders
Final Responses
Questions
Country
Time for one survey
The ESEM Survey has been coordinated by the Türkiye Social Entrepreneurship Network (TSEN) in Türkiye. Following members of TSEN (in alphabetical order) have worked in translation of survey questions, cleaning of survey data and reintegration of responses.
Koç University Social Impact Forum – KUSIF
Impact Hub Ankara
Vehbi Koç Foundation
Koç University Social Impact Forum – KUSIF
Yekpare – Social Enterprise Türkiye
TED University Center for Social Innovation – İstasyonTEDU
Koç University Social Impact Forum – KUSIF
Analysis of Türkiye survey data and reporting of the findings have been done by the following members of TSEN
Impact Hub Ankara
TED University Center for Social Innovation – İstasyonTEDU
Interactive data visualization and design has been conducted by DNDLAB