Skip to main content

Managing sustainable projects: Analyzing qualitative interview data using the recursive abstraction method.

Polkinghorne, M., Bobeva, M. and Shahid, S., 2023. Managing sustainable projects: Analyzing qualitative interview data using the recursive abstraction method. Sage Research Methods: Business.

Full text available as:

[img]
Preview
PDF
Pre-Print Version.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.

349kB

DOI: 10.4135/9781529626520

Abstract

This research methods case study is based upon an investigation into the delivery of educational projects in Pakistan. The research considers the sustainability of these projects using the outcome targets of the United Nations (UN) Sustainable Development Goal (SDG) 4 as a measure of quality education. In the project, data were collected via interviews undertaken with a wide range of stakeholders, including government officials who support projects, non-governmental organizations (NGOs) that deliver projects, donors and sponsors who fund projects, and communities that benefit from projects. This case study considers the analysis of an example interview undertaken with one of these stakeholders. Starting with the background context for the project and the research design used, the analysis process undertaken using the recursive abstraction method is detailed, and from this, the underlying patterns and trends identified within the data are revealed. Each step of the research process is carefully explained to provide a clear path from the original source data to the final recommendations proposed. Lessons learned from analyzing this example interview are then expanded upon to illustrate broader points that researchers should be aware of when using recursive abstraction.

Item Type:Article
Uncontrolled Keywords:Success; Project Management; Non-Governmental Organisations; United Nations Sustainable Development Goals; Quality Education
Group:Bournemouth University Business School
ID Code:38403
Deposited By: Symplectic RT2
Deposited On:23 May 2023 15:59
Last Modified:23 May 2023 15:59

Downloads

Downloads per month over past year

More statistics for this item...
Repository Staff Only -