Page 103 - UKZN Proceedings of the Conference Report

table 3: distribution of sample size by functional category of Parastatals
functional category
No. of entities
Proportion
Sample size
financial
16
0.0678
10
Manufacturing
28
0.1186
17
regulatory
57
0.2415
35
Public universities
38
0.1610
24
training and research
9
0.0381
6
Service
74
0.3136
46
regional development authorities
5
0.0212
3
tertiary education
9
0.0381
6
total
236
1
147
Sample
The sample is made up of ICT Managers from all Parastatals.
Data collection methods
Quantitative data collection will be done using questionnaires with closed- and open-ended questions, while qualitative data will be collected using interviews. A one-hour appointment will be booked with the selected respondents by email at least three days before the interview.
Data quality control
To ensure data quality control, the participants in the qualitative study will be those who have worked for the organisation for a minimum period of one year. This is necessary to minimise errors of judgement, since the longer the working experience, the higher the credibility and trustworthiness of the individual responses.
Statement on data availability: Data for the research project is available and can be obtained from the respondents and participants subject to their informed consent and Ethical Clearance from the University of KwaZulu-Natal. Permission to collect data for the research project has been sought and obtained from the Kenya National Commission for Science, Technology and Innovation (NACOSTI).
funding: No funding yet
declaration of interest: None
authors’ contributions: This is an excerpt from ongoing doctoral research at the University of KwaZulu-Natal. Data collection for this research project is expected to commence by December 2024.
references
Abdul, D. and Wenqi, J. 2024. Identifying and prioritization barriers to renewable energy diffusion in developing countries: a novel spherical fuzzy AHP approach and application. Energy Efficiency, 17(5), pp.1-36.
Adam, A.M. 2020. Sample size determination in survey research. Journal of Scientific Research and Reports, 26, pp. 90-97.
Bebiano, N., Fernandes, R. and Furtado, S. 2020. Reciprocal Matrices: Properties and Approximation by a Transitive Matrix. Computational and Applied Mathematics, 39, p. 50.
Canco, I., Kruja, D. and Iancu, T. 2021. AHP, A Reliable Method For Quality Decision Making: A Case Study In Business. Sustainability, 13, p. 13932.
Daimi, S. and Rebai, S. 2023. Sustainability Performance Assessment of Tunisian Public Transport Companies: AHP and ANP Approaches. Socio-Economic Planning Sciences, 89, p. 101680.
Dano, U.L. 2020. Flash Flood Impact Assessment in Jeddah City: An Analytic Hierarchy Process Approach. Hydrology, 7, p. 10.
Doke, A.B., Zolekar, R.B., Patel, H. and Das, S. 2021. Geospatial mapping of groundwater potential zones using multi-criteria decision-making AHP approach in a hardrock basaltic terrain in India. Ecological Indicators, 127, p.107685.
Fischhoff, B. and Broomell, S.B. 2020. Judgment and decision making. Annual Review of Psychology, 71, pp. 331-355.
Creative Decisions Foundation. 2023. Superdecisions Ahp Software [Online]. Available: www.superdecisions.com
Franek, J. and Kresta, A. 2014. Judgment Scales and Consistency Measures in AHP. Procedia Economics and Finance, 12, pp. 164-173.
Godfrey, S., Wambugu, M., Parikh, P. and Tunhuma, F. 2022. Validation of the UNICEF Fiscal Diagnostic Tool for SDGs 6.1 and 6.2 in East and Southern Africa using the Analytical Hierarchy Process (AHP). Water, Sanitation and Hygiene for Development, 12, pp. 721-736.
Government of Kenya. 2023. Report on Performance Evaluation of Parastatals and Tertiary Institutions for the
Proceedings of the conference on Public innovation, develoPment and sustainability | 101