INFLUENCE OF EMERGING TECHNOLOGIES ON SERVICE DELIVERY IN GOVERNMENT INSTITUTIONS IN KENYA: A CASE OF NAIROBI COUNTY’S E-JIJI PAY
Abstract
The purpose of this study was to assess the influence of emerging technologies on service delivery in government institutions. The study utilized four specific objectives which included: assessing the influence of technological infrastructure, ascertaining the influence of training capacity, finding out the influence of policy framework and determining the influence of resource allocation on the delivery of Nairobi County’s e-jiji pay. The study was guided by two theories: Technology Acceptance Model (TAM) and Unified Theory of Acceptance. The study adopted a descriptive survey design to examine the relationship between the independent and dependent variables. The design helps the researcher to obtain information concerning the current status of the problem under study and describe it with respect to its variables. The target population was 1445 employees of Nairobi County and these comprised of administrators, accountants, revenue collectors, car park attendants as well as market and licensing officers. The study adopted stratified random sampling procedure to identify specific groups from which data was collected. Simple random sampling procedure was then used to select respondents for data collection from the various strata. A sample size of 212 respondents was utilized for this study in data collection. Data collected was analyzed quantitatively using statistical package for social sciences version 25. Quantitative data collected was analyzed using descriptive statistics. Correlation examination, regression analysis were applied to reveal the relationship between the independent and the dependent variable. The study recommended that institutions should invest more in emerging technologies to improve existing service delivery; there should continuous creation of training capacities and workshops for enhancement of skills. Policies of technology adoption should be improved to attract adoption of the everyday changing technology and Nairobi County in conjunction with the national government and other counties must ensure that there is increased funding on resource acquisition which enables acquisition and use of emerging technologies in Nairobi county.
Key Words: Technological Infrastructure, Training Capacity, Policy Framework, Resource Allocation, Service Delivery
CITATION: Riogi, N. N., & Ombui, K. (2020). Influence of emerging technologies on service delivery in government institutions in Kenya: A case of Nairobi County’s e-jiji Pay. The Strategic Journal of Business & Change Management, 7(4), 470 – 484.
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Abass, M., Munga, J. & Were, E. (2017). The Relationship between Strategies Implementation and Performance in County Governments of Kenya: A Case Study of Wajir County Government. International Academic Journal of Human Resource and Business Administration. 2 (3). 381 – 401
Abdelqader, M., Abu, Q., & Al Sakarneh, B. (2013). Impact of knowledge management and innovation on performance. Baghdad collage journal for economic sciences, 34(78), 45-78.
Abu-Dalbouh, H. (2016). An integrated expert user with end user in technology acceptance model for actual evaluation. Comput. Inform. Sci. Canadian Center Sci. Educ., 9: 47-53.
Andrews, R., Beyon, M., & Genc, E. (2017). Strategy Implementation Style and Public Service Effectiveness, Efficiency and Equity. Administrative Sciences. Adm.sci.2017, 7,4
Babbie, E. (2016). The Practice of Social Research. Qualitative data analysis. Quantitative data analysis, Reading and writing social research. New York: Oxford University Press.
Che, A,, Romle, A., Udin, M., Mohd, Y., Husin, N.. & Shahuri, N. (2016). The Implementation of ICT Towards Improving Service Quality in Public Sector. World Applied Sciences Journal, 34 (4); 499-505
Cooper, D., & Schindler, S. (2010). Business Research Methods. New York: McGraw-Hill Irwin.
Davis, F. (1989). ‘Perceived Usefulness, Perceived ease of use, and user acceptance of information technology’ mis quarterly, 13(3)pp 319-340.
Economic Survey Report (2019). Kenya ICT Board Monitoring and Evaluation Indicators Study.
Elliott L. (2018). Robots will take our jobs. We’d better plan now before it’s too late. The Guardian.. https://www.researchgate.net/publication/330693514_
European Commission. Eurostat. 2018. Available online: http://eceuropa.eu/eurostat(accessed on 10june2018).
Ewuim, N., Igbokwe-Ibeto, C. & Nkomah, B. (2016). Information and Communication Technology and Public Service Delivery in Amuwo-Odofin Local Government Council of Lagos State-Nigeria. Singaporean Journal of Business Economics and Management studies, 5(1), 13-25.
Frey, C. & Osborne, M. (2017). The future of employee: How susceptible are jobs to computerization? Technological forecasting and social change Elsevier, 114(1).
Githinji, A. (2014). Effects of training on employee performance: a case study of United Nations support office for the African Union Mission in Somalia (doctoral dissertation, United States international university. Africa).
Hackney, R., Tassabehji, R. (2017), The impact of ICT on public service development in Africa: an empirical analysis, available: at: http://bura.brunel.ac.uk/ handle/2438/14682, (accessed 22 September 2017).
Hussein, Z. (2015). Explicating Students’ Behaviours of E-Learning: A Viewpoint of the Extended Technology Acceptance, International Journal of Management and Applied Science, 1 (10), 2015
ICT Authority Strategic Plan (2013 – 2018). Retrieved from http://www.icta.go.ke.
Institute of Economic Affairs (2017). Annual Report.
Karimi, H (2017). Effects of Technology and Information systems on Revenue collection By the County government of Embu, Kenya. 2(1), 19-35.
KBSR (2019). Kenya Bureau of Statistics (KBSR) Report. Ministry of Planning; National Development and vision 2030.
Kihara, P. Bwisa, H., & Kihoro, J. (2016). Relationships Among Structural Adaptations, Strategy Implementation and Performance of Small and Medium Manufacturing Firms inThika Sub-County, Kenya. Asian Journal of Applied Science and Technology. 17(1): 1- 16
Kinuthia, J., & Akinnusi, D. (2014). The magnitude of Barriers facing e-commerce business in Kenya. Journal of internet and information systems, 4(1), 12-27.
Kothari, C. (2014). Research Methodology: Methods and Techniques. New Delhi: New Age International
Lee, Y., Kozar, K., & Larsen, K. (2003). The technology acceptance model; past, present and future. Communication of AIS, 12 (50), 752-780.
Mieseigha G. & Ogbodo, U.(2013). An Empirical Analysis of the Benefit of Cashless Economy on Nigeria’s Economic Development. J Finance Account 4:11-16.
Mills, G. (2011). Action research: A guide for the teacher researcher (4th ed.). Boston: Pearson
Mimbi, L., & Bankole, F. (2016). ICT and public service value creation in Africa: efficiency assessment using DEA approach, 29th Australasian Conference on Information Systems (ACIS2018), UTS, Sydney, and 3rd-5th December 2018.
Moindi, J. (2014). Resource Allocation Strategies in Devolved System of Governance in Selected Counties in Kenya. MBA project. University of Nairobi.
.Mohamed, M. (2018). Resource allocation: Experiences and Challenges in County Governments. Thesis. Strathmore University. Retrieved from; http: su-plus. Strathmore.edu/handle/11071/6049. On 1st May 2019.
Mugambi, K. (2013). Effects of e-government strategy on service delivery in the government ministries in Kenya.
Mugenda, A., & Mugenda, O. (2008). Research Methods. Nairobi: Acts Press.
Nabukera, J., Ali, B. & Raja G (2014). Management and Administration of Education in Uganda. In Education for Development, Ed, S. Abide. Kampala: Foundation for African Development: Kampala.
Nairobi City County Finance Act, Various issues (2013, 2014 and 2015) via www. Nairobi.go.ke
Ndegwa, A., Kiriri, P., & Achoki, G. (2017), Factors affecting adoption of donor funded ICT projects in the public sector in Kenya, International Journal of Project Management, 1(1): 1–18.
Ndunda, J., Ngahu, S.., Wanyoike, D. (2015). Analysis of factors influencing optimal revenue collection by county government in Kenya. A case study of Nakuru County.
Nwaogwugwu, I., Evans, O. (2016). A sectoral analysis of fiscal and monetary actions in Nigeria. The Journal of Developing Areas, 50(4); 211-230.
Office of Controller of Budget (2013? 14-2016/17). Annual County Budget Implementation Review Reports various issues.
Omotayo, F. (2015). Knowledge management as an important tool in organ library philosophy and practice (e-journal. http://digitalcomjuly 2nd 2017
Onserio, K. (2008). Strategy Implementation and Organizational Performance among Institutions of Higher Learning in Kiambu County. A MBA Thesis. Kenyatta University.
Oyewole O., El-Maude J., Abbas M, Onuh M. (2013). Electronic payment system and economic growth: a review of transition to cashless economy in Nigeria. Int J Sci Eng Technology 2:913-918.
Palamountain, K., Baker, J., Cowan, E, Essajee, S., Mazzola, L., Metzler, M., Schito, M., Stevens, W., Young, G., & Domingo, G. (2012). Perspectives on introduction and implementation of new point-of-care diagnostic tests, Journal of Infectious Diseases, (1); 203.
.Republic of Kenya (2010). The Constitution of Kenya. The National Council of Law Reporting NCLR
Republic of Rwanda (2010). 5 Year Capacity Building Strategy for Local Governments (2011-2015). Ministry of Local Government, Kigali.
Riany, G., Were, S., & Kihara, A. (2018). Influence of e-Government Strategy Implementation on the Performance of Public Service Delivery in Kenya. International Journal of Strategic Management. 7(2); 32 – 49.
Shithole, A., Chirasha, V. & Tatire, M. (2013). Implementation of strategic plans by Zimbabwean Local Authorities: A Case of Nyanga Rural District council. Journal of Emerging Trends in Economic and Management Sciences. Vol, 4(1): 106 – 110.
Thompson, R., & Higgins, C. (2014). Personal Computing: Toward a Conceptual Model of Utilization. MIS quarterly, 54(1), 125.
World Bank (2012). Devolution without Disruption Pathways to Successful New Publication of Australian AID. Nairobi.
Venkatesh, V., Morris, M., Davis, F., & Davis, G.. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27, 425-478.
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46 (2), 186-204.
Yator, R., & Shale, N. (2014). Role of information communication technology on service delivery at the ministry of interior and coordination of national government: A case of immigration service. International Journal of Social Sciences and Entrepreneurship, 1 (12), 863- 876.
Yu, C. (2012), Factors affecting individuals to adopt mobile banking: empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13(2); 104-121.
Zhang J. & Guan J. (2016). Scientific relatedness and intellectual base: a citation analysis of 26 uncited and highly-cited papers in the solar energy field. Scientometrics, (1); 1-22
DOI: http://dx.doi.org/10.61426/sjbcm.v7i4.1799
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