The role of incubator classification on performance of incubators in Kenya.
Miriti Jane Kinya ORCID ↗ · Kenneth Lawrance Wanjau · Nyagweth Ebenezer Odeyo ORCID ↗
International Journal of Research in Business and Social Science · 2021 · Vol. 10 / Issue 6 · 256-267
Publication metrics
External links open provider records or DOI searches. Provider counts are not combined. Mendeley readership measures saves, not citations.
Dimensions
Live provider badge. If unavailable, use the Dimensions link above.
Observed 21 Oct 2026, 07:22 UTC
Observed 22 Oct 2026 02:22 UTC
Observed 21 Oct 2026 23:01 UTC
OpenAlex and Mendeley observations refresh on article visits, at most once per 24 hours. Unavailable data is not zero. Google Scholar opens a DOI search.
Citations received by this article, grouped by the year of the citing work. Crossref and OpenAlex lifetime totals remain separate in Publication metrics.
2017–2026 Annual history last updated:
Citations received
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
View data & coverage
2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Years beyond a saved observation’s window remain unknown (—). Older citations are excluded, so this chart’s sum may differ from the OpenAlex lifetime total. The date above belongs to this annual history; an unsuccessful refresh keeps the previous observation.
Abstract
The study sought to assess the importance of classifying incubators based on the programs offered for optimum performance. Client selection criteria were assessed through three constructs namely: models that fit program goals, uniqueness of ideas, and standard selection tool. A mixed cross-sectional and causal design was adopted and a census was carried out targeting all the 51 incubators. Primary data was collected with an incubator program as a grouping/ cluster variable yielding a multilevel data structure with incubator centres nested in programs. Linear mixed effect models were fitted using Stata to assess the study objective taking into account the fixed effects for the incubator centre level (level-1) and random effects for the program level (level-2). The uniqueness of ideas was found to have a significant fixed effect on performance at level one while at level two, the study found significant random intercepts of incubator centre performance across the programs. Models that match program goals and standard selection tools were also found to have significant random slopes as level two random covariates in the model. Based on the findings of significant random slopes, the study concluded that incubator classification is key for client selection criteria and enhances incubator performance.
Keywords: {'name': 'Incubator Center, Classification, Client Selection Criteria; Multi-level'}
Authors & affiliations
Miriti Jane Kinya
Affiliation not supplied
Kenneth Lawrance Wanjau
Affiliation not supplied
Nyagweth Ebenezer Odeyo
Affiliation not supplied
Deposited references
Supplied references, not a list of publications citing this article.
DOI: 10.1007/s10961-018-9661-9
DOI: 10.1016/j.jbusres.2015.10.054
Babbie, Earl R. (1990). Survey research methods. Belmont, Calif. :Wadsworth Pub. Co.
Barrow, C. (2001). Incubators: a realist's guide to the world's new business accelerators. Wiley.
DOI: 10.1016/j.jbusvent.2003.12.005
Bugliarello, G. (1998). Knowledge parks and incubators. The Handbook of Technology Management, 1, 41-49.
Chimi, C. J., & Russell, D. L. (2009, November). The Likert scale: A proposal for improvement using quasi-continuous variables. In Information Systems Education Conference, Washington, DC (pp. 1-10).
Cooper, D.R., & Schindler, P.S., (2011).Business Research Methods.(11th ed.). New York: McGraw-Hill.
Dee, N., Gill, D., Lacher, R., Livesey, F., & Minshall, T. (2012). A review of research on the role and effectiveness of business incubation for high-growth start-ups. University of Cambridge Institute for Manufacturing, 42.
DOI: 10.1002/14651858.MR000008.pub2
DOI: 10.1108/17515630910956570
DOI: 10.1068/c0215
Hmelo, C. E., Williams, S. M., Vye, N. J., Goldman, S. R., & Bransford, J. D. Cognition and Technology Group at Vanderbilt (1993). A longitudinal study of the effects of anchored instruction on mathematical problem solving transfer.
Israel, G. D., (2012). Sampling: Determining Sample Size. (U. o. Extension, Ed.)
DOI: 10.7205/MILMED-D-10-00394
DOI: 10.20525/ijrbs.v7i1.857
Kuratko, D. F., & LaFollette, W. R. (1987). Small business incubators for local economic development. Economic Development Review, 5(2), 49.
DOI: 10.1207/s15327884mca0303_2
DOI: 10.1017/CBO9780511815355
DOI: 10.4337/9781786432797.00009
DOI: 10.1080/10618600.2017.1330207
DOI: 10.5367/000000006776928663
DOI: 10.1111/j.1751-9004.2007.00059.x
DOI: 10.1109/TEM.1987.6498875
DOI: 10.1108/JSBED-09-2014-0152
UKBI, (2009). The Business Incubation Development Framework, Business Incubation. Birmingham.
DOI: 10.6007/IJARBSS/v7-i1/2553