Pointers for Designing Context-Aware e-Government Strategy in Zambia: Context, Issues, and Opportunities

  • Bwalya Kelvin JosephEmail author
Part of the Public Administration and Information Technology book series (PAIT, volume 3)


Successful implementation of any e-government interventions or programs is hinged on having a carefully thought strategy which is informed by the local context. It cannot be overemphasized that every contextual setting has unique inherent contextual characteristics, which demand that any e-government interventions be designed bearing those characteristics in mind. In order to understand the contextual characteristics in Zambia, a quantitative research approach is utilized, where methodological triangulation is employed at all stages of the research cycle. The endpoint of this empirical research is that inherent factors that influence adoption of e-government mostly at individual (citizen’s and bussinesses’) levels are understood. The only major limitation of this research is that the sample (408 participants) may not be representative of the 14 million people in Zambia and therefore may not guarantee statistical generalizations. The chapter posits that there is chance that affluent e-Government development can be achieved in Zambia once a context-aware e-Government strategy/roadmap is put in place and followed.


e-Government Strategy Design Context-aware 


  1. Abanda, H., Ng’ombe, A., Tah, J. H. M., & Keivani, R. (2011). An ontology-driven decision support system for land delivery in Zambia. Expert Systems with Applications, 38, 10896–10905.CrossRefGoogle Scholar
  2. Ajzen, I. (1991). The theory of planned behaviour. Organisational Behaviour and Human Decision Processes, 50(2), 179–211.Google Scholar
  3. Bwalya, K. J., & Healy, M. (2010). Harnessing e-Government adoption in the SADC region: A conceptual underpinning. Electronic Journal of e-Government, 8(1), 23–32.Google Scholar
  4. Bwalya, K. J., Du Plessis, T., & Rensleigh, C. (2011). Setting the foundation for e-Democracy in Botswana: An exploratory study of interventions. In R. Cropf & W. S. Krummenacher (Eds.), Information communication technologies and the virtual public sphere: Impacts of network structures (pp. 229–241). New York: Information Science Reference.CrossRefGoogle Scholar
  5. Cho, Y. H., & Choi, B. (2004). e-Government to combat corruption: The case of Seoul metropolitan government. International Journal of Public Administration, 27(10), 719–735.CrossRefGoogle Scholar
  6. Coates, N., & Nikolaus, L. (2010). Zambia and e-Government: An Assessment and Recommendations. In E-Agriculture and E-Government for Global Policy Development: Implications and Future Directions. Maumbe, B. (Ed.). 137–161.Google Scholar
  7. Cooper, R. D., & Schindler, S. P. (2001). Business Research Methods (7th ed.). New York: McGraw-Hill.Google Scholar
  8. Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task technology fit constructs, Information & Management, 36, 9–21.Google Scholar
  9. Habeenzu, S. (2010). Zambia ICT Sector Performance Review 2009/2010: Towards Evidence-based ICT Policy and Regulation, 2, Policy Paper 17/2010. Retrieved November 3, 2011, from
  10. Heeks, R. (2004). e-Government for development basic definitions page. Retrieved May 25, 2009, from
  11. Horst, M., Kuttschreuter, M., & Gutteling, J. (2007). Perceived usefulness, personal experiences, risk perception and trust as determinants of adoption of e-Government services in The Netherlands. Computers in Human Behaviour, 23, 1838–1852.Google Scholar
  12. Iqbal, M. S., & Seo, J. W. (2008). e-Governance as an anti corruption tool: Korean cases. Journal of Korean Association for Regional Information Society, 11(2), 51–78.Google Scholar
  13. Kim, D. J., Ferrin, D. L., & Rao, H. R. (2007). A Trust-Based Consumer Decision-Making Model in Electronic Commerce: The Role of Trust, Perceived Risk, and their Antecedents. Decision Support System, 44, 544–564. Google Scholar
  14. Kim, S. C., Kim, H. J., & Lee, H. J. (2009). An institutional analysis of an e-government system for anti-corruption: The case of OPEN. Government Information Quarterly, 26, 42–50.CrossRefGoogle Scholar
  15. Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behaviour, Information Systems Research, 13(2), 205–223.Google Scholar
  16. Kumar, R., & Best, M. L. (2006). Impact and sustainability of e-Government services in developing countries: Lessons learned from tamil nadu, india. The Information Society, 22, 1–12.CrossRefGoogle Scholar
  17. Kwon, H. (2000). A test of the technology acceptance model: the case of cellular telephone adoption, In: Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, Big Island, HI, USA.Google Scholar
  18. Lederer, A. L., Maupin, D. J., Sena, M. P. & Zhuang, Y. (2000). The technology acceptance model and the World Wide Web, Decision Support Systems, 29, 269–282.Google Scholar
  19. Legris, P., Ingham, J., Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40 (3), 191–204.Google Scholar
  20. Liang, H., Xue, Y., & Byrd, T. A. (2003). PDA usage in healthcare professionals: testing an extended technology acceptance model. International Journal of Mobile Communications, 1(4), 372–389.Google Scholar
  21. Lin, F., Fofanah, S. S., & Liang, D. (2011). Assessing citizen adoption of e-Government initiatives in Gambia: A validation of the technology acceptance model in information systems success. Government Information Quarterly, 28, 271–279.CrossRefGoogle Scholar
  22. Luna-Reyes, L. F., & Gil-Garcia, J. R. (2011). Using institutional theory and dynamic simulation to understand complex e-Government phenomena. Government Information Quarterly, 28, 329–345.CrossRefGoogle Scholar
  23. Maumbe, B.M., Owei, V., & Alexander, H. (2008). Questioning the pace and pathway of egovernment development in Africa: A case study of South Africa’s Cape Gateway project, Government Information Quarterly, 25, 757–777. Google Scholar
  24. Navarra, D. D., & Cornford, T. (2007). The state, democracy and the limits of new public management: Exploring alternative models of e-Government. Presented at the e-Government Workshop’06 (Egov06) September 11 2006, Brunel University, London, UB8 3PH. pp. 1–14. Retrieved August 14, 2011 from
  25. Papadopoulou, P., Nikolaidou, M., & Martakos, D. (2010). What is Trust in e-Government? A Proposed Typology. In: Proceedings of the 43rd Hawaii International Conference on System Sciences (HICSS-43- 2010), Koloa, Kauai, Hawaii.Google Scholar
  26. Pavlou, P. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model, International Journal of Electronic Commerce, 7(3), 101–134.Google Scholar
  27. Saadé, R. G., & Kira, D. (2007). Mediating the impact of technology usage on perceived ease of use by anxiety. Computers & Education, 49(4), 1189.Google Scholar
  28. Shareef, A. M., Kumar, V., Kumar, U., & Dwivedi, Y. K. (2011). e-Government Adoption Model (GAM): Differing service maturity levels. Government Information Quarterly, 28, 17–35.CrossRefGoogle Scholar
  29. Shen, C. C., & Chiou, J-S. (2010). The impact of perceived ease of use on Internet service adoption: The moderating effects of temporal distance and perceived risk, Computers in Human Behavior, 26(1), 42–50.Google Scholar
  30. Syamsuddin, I., & Hwang, J-S. (2010). A New Fuzzy MCDM Framework to Evaluate E-Government Security Strategy. IEEE 4th International Conference on Application of Information and Communication Technologies AICT2010. Retrieved April 1, 2010, from
  31. UN e-Government Report (2008). UN e-Government survey 2008: From e-Government to connected governance, ISBN 978 -92-1-123174-8, UN White paper.Google Scholar
  32. UN e-Government Survey. (2010). Leveraging e-Government at a time of financial and economic crisis. Retrieved October 4, 2010, from
  33. Venkatesh, V., Moris, M.G., & Davis, G.B. (2003). User acceptance of information technology: Toward a unified view, MIS Quarterly, 27(3), 425–478. Google Scholar
  34. Weerakkody, V., Dwivedi, Y. K., Brooks, L., Williams, M. D., & Mwange, A. (2007). e-Government implementation in Zambia: Contributing Factors. Electronic Government, An international Journal, 4(4), 484–505.CrossRefGoogle Scholar
  35. Wong, W., & Welch, E. (2004). Does e-Government promote accountability? A comparative analysis of web site openness and government accountability, Governance: An International Journal of Policy, Administration, and Institutions, 17(2), 275–297.Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Library and Information StudiesUniversity of BotswanaGaboroneBotswana
  2. 2.Senior Research AssociateUniversity of JohannesburgPretoriaSouth Africa

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