Abstract:

Objective: The aim of the research was to study the impact of broadband diffusion in assessing innovation in institutions of higher learning in Kenya.

Background: The Government of Kenya realized the importance of broadband provision to stimulate economic development through innovation and established the Kenya Education Network Trust (KENET) - a national research and education network that promotes the use of broadband in teaching, learning and research in institutions of higher learning in Kenya. The aim of KENET was to interconnect all the universities in Kenya by setting up a cost effective and sustainable private network with high speed access to the global internet.

Methodology: This study applied descriptive survey research design and a logistic regression model was used as an inferential analysis tool in the quantitative analysis. Inferential statistics used to analyse the model were; overall model evaluation, goodness-of-fit statistics, and statistical tests of individual predictors and validations of predicted probabilities.

Results: Reliability measures were above the recommended level of 0.70 as an indicator for adequate internal consistency. Inferential statistics used to analyse the model showed that the model performed well and was appropriate for the study.

Conclusion: Broadband diffusion in institutions of higher learning in Kenya is inhibited by poor infrastructural development attributed to high costs of connections and bandwidth acquisition and a high demand for broadband among the students and staff. Policies in broadband regulation from the national government and institutional governance are prudent in controlling and enabling access to this important resource for innovative purpose.

Keywords: Broadband diffusion, Innovation, Education, Internet, Bandwidth, Regression Model.

References:

[1]. Anderson, J.C., Gerbing, D.W., 1988. Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin 103, 423–441.

[2]. Cava-Ferreruela, I., Alabau- Muňoz, A., 2006. Broadband policy assessment: A cross-national empirical analysis. Telecommunications Policy 30, 445-463.

[3]. Chin, W., 1998. Issues and opinion on structural equation modeling. MIS Quarterly 22 (1), 7–16.

[4]. Chwelos, P., Benbasat, I., Dexter, A.S., 2001. Research report: empirical test of an EDI adoption model. Information System Research 12 (3), 304–321.

[5]. Denni, M., Gruber, H., 2005. The diffusion of broadband telecommunications: The role             of competition. Paper presented at International Telecommunication Conference, Pontevedra.

[6]. Distaso, W., Lupi, P., Maneti, F.M., 2006. Platform competition and broadband uptake: Theory and empirical evidence from the European Union. Information Economics and Policy 18, 87- 106.

[7]. Fronell, C.R., 1982. A Second Generation of Multivariate Analysis Methods. Praeger, New York.

[8]. Gandal, N., 2002. Compatibility, Standardization, and network effects: Some policy implications. Oxford Review of Economic Policy 18, 80-91.

[9]. Garcia-Murillo, M., 2005. International broadband deployment: The impact of            unbundling. Communications and Strategies 57, 83-108.

[10].            Grosso, M., 2006. Determinants of broadband penetration in OECD nations. Paper presented to the Australian Communications Policy and Research Forum.

[11].            Gruber, H., Verboven F., 2001. The evolution of markets under entry and standards regulation: The case of global mobile telecommunications. International Journal of Industrial Organization 19, 1189-1212.

[12].            Hair, J.F., Anderson, R.E., Tatham, R.L., Black, W.C., 1995. Multivariate Data Analysis   with Readings. Prentice-Hall International, Englewood Cliffs.

[13].            ITU, 2003. Promoting broadband: Background paper for workshop on promoting broadband. Electronic document at http://www.itu.int.

[14].            ITU, 2006. Digital.life. ITU, Geneva.

[15].            ITU, 2010. ICT Statistics. ITU, Geneva.

[16].            Kim, J. H., Bauer, J.M., Wildman, S.S., 2003. Broadband uptake in OECD countries: Policy lessons from comparative statistical analysis. Paper presented at the 31st             Research Conference on Communication, Information and Internet policy. Arlington, Virginia.

[17].            Koutroumpis, P., 2009. The economic impact of broadband on growth: A simultaneous approach. Telecommunications Policy 33, 471-485.

[18].            Lehr, W., Gillett, S., Osorio, C., Sirbu, M., 2006. Measuring broadband’s economic impact. Broadband Properties, 12-24.

[19].            Lohmoller, J.B., 1989. Latent Variable Path Modeling with Partial Least Square Analysis. Physica-Verlag, Heidelberg.

[20].            OECD, 2010. OECD broadband statistics. OECD, Paris.

[21].            Peng, C.-Y. J., Lee, K. L., & Ingersoll, G. M. (2002). An introduction to logistic regression analysis and reporting. The Journal of Educational Research, 96(1), 3– 14.doi:10.1080/00220670209598786

[22].            Rouvinen, P., 2006. Diffusion of digital mobile telephony: Are developing countries different? Telecommunications Policy 30, 46-63.