AbstractAcademia and business could benefit significantly from a framework allocating scarce resources to corporate social responsibility (CSR) programmes while considering the stakeholders’ importance. Methodologies that are capable of integrating CSR into business models in an operational way could be of great use.
This thesis makes a contribution to knowledge by the development of a decision support methodology to allocate resources to CSR programmes. The research introduces the concepts of CSR and decision analysis, while identifying a hybrid integrated framework combining several decision analysis techniques allowing elimination of the deficiencies of mono-methodologies and facilitating resources allocation to CSR projects.
Despite the high levels of awareness, the process of implementing CSR at the project level is difficult, as implementation of CSR at the design stage requires effective allocation of scarce resources in addition to considering diverging objectives of stakeholders, multiple criteria and uncertainty throughout the decision-making process.
A three phase research programme involving a pilot study, framework building, framework testing and validation is conducted to understand the principles of CSR practices and related implementation issues. The research explores and identifies methodologies of decision analysis that can be applied in an integrated manner to address problems in CSR.
The result is a sequential and iterative methodology that fills the gap identified through a literature review and practitioner survey. The documented framework, derived from the structured development and test programme, has shown to be feasible. It makes a significant contribution to knowledge, attained through the provisions of procedural fairness. The key stakeholders are fully engaged in the process of framework building as well as throughout the entire decision-making process.
The research provides a framework to allocate resources to CSR programmes in an efficient manner by considering the stakeholders’ diverging objectives, companies’ competitive advantage, interdependent criteria, and limited resources.
|Date of Award
|Ashraf Labib (Supervisor), Debbie Reed (Supervisor), Alessio Ishizaka (Supervisor) & Mike Page (Supervisor)