Barriers and triggers to responsible business practices amongst SMEs.

Recently, there has been a growing call for businesses to become more connected to society and move

beyond simple corporate social responsibility reporting (CSR) and articulate values beyond profits

(Weaver et al. 2018). Given that small and medium sized enterprises (SMEs) account for over 90% of the

stock of businesses in the UK, if responsible business is to be embedded into the UK economy SMEs need

to play a prominent role and become a key enabling force (Fonseca et al. 2018). A wide range of support

from various organisations has developed over the last decade and this ecosystem helps to engage SME

owners and managers and provide encouragement for them to operate their firms in a more responsible

manner, whilst foresting partnership working to achieve socially desirable outcomes. The aim of this

project is to better understand the triggers and barriers that influence how SMEs engage with the

responsible business ecosystem, to develop a framework that will allow for better decision making and

ultimately, better outcomes. It is envisaged that that this project will be underpinned using a mixed

methods approach.

Academic qualifications

A first degree (at least a 2.1) ideally in Business and Management/ Entrepreneurship or a related

discipline with a good fundamental knowledge of Entrepreneurship/ SMEs.

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other,

equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential attributes:

 Experience of fundamental Independent academic research projects at undergraduate and / or

postgraduate level

 Competent in business and management research methods

 Knowledge of responsible business concepts

 Good written and oral communication skills

 Strong motivation, with evidence of independent research skills relevant to the project

 Good time management

Desirable attributes:

Knowledge of mixed methods research design and data analysis approaches