Evidence-based case selection: an innovation knowledge management method to cluster public technical and vocational education and training colleges in South Africa

SOURCE: South African Journal of Information Management
OUTPUT TYPE: Journal Article
TITLE AUTHOR(S): M.Visser, J.A.van Biljon, M.Herselman
DEPARTMENT: Inclusive Economic Development (IED)
Print: HSRC Library: shelf number 10908
HANDLE: 20.500.11910/14076

If you would like to obtain a copy of this Research Output, please contact Hanlie Baudin at researchoutputs@hsrc.ac.za.


Case studies are core constructs used in information management research. A persistent challenge for business, information management and social science researchers is how to select a representative sample of cases among a population with diverse characteristics when convenient or purposive sampling is not considered rigorous enough. The context of the study is post-school education, and it involves an investigation of quantitative methods of clustering the population of public technical and vocational education and training (TVET) colleges in South Africa into groups with a similar level of maturity in terms of their information systems. The aim of the study was to propose an evidence-based quantitative method for the selection of cases for case study research and to demonstrate the use and usefulness thereof by clustering public TVET colleges. The clustering method was based on the use of a representative characteristic of the context, as a proxy. In this context of management information systems (MISs), website maturity was used as a proxy and website maturity model theory was used in the development of an evaluation questionnaire. The questionnaire was used for capturing data on website characteristics, which was used to determine website maturity. The websites of the 50 public TVET colleges were evaluated by nine evaluators. Multiple statistical techniques were applied to establish inter-rater reliability and to produce clusters of colleges. The analyses revealed three clusters of public TVET colleges based on their website maturity levels. The first cluster includes three colleges with no websites or websites at a low maturity level. The second cluster consists of 30 colleges with websites at an average maturity level. The third cluster contains 17 colleges with websites at a high maturity level. The main contribution to the knowledge domain is an innovative quantitative method employing a characteristic (in this case website maturity) as a proxy for MIS maturity. The method can be applied in quantitative, qualitative and mixed methods research, to group a population and thereby simplify the process of sample selection of cases for further in-depth investigation.