ICT Adoption and Usage in Africa: Towards an Efficiency Assessment

References

• Abbott, M. (2005). Determining levels of productivity and efficiency in the electricity industry. The Electricity Journal, 18(9), 62–72.
   Google Scholar
• Abdoulkarim, S., & Rugege, A. (2013). Africa's ICT development challenges and opportunities. Retrieved October 14, 2014, from http://au.int/en/sites/default/files/Final_ITU-ATU_2013ICTWEEK_Presentation_v12.pdf
   Google Scholar
• African Telecom Transmission Map. (2011). Africa's fiber roll-out: 138 route-kilometers of new fiber network enters service per day. Retrieved from http://www.africabandwidthmaps.com/?p=2572
   Google Scholar
• African Economic Outlook. (2013). Africa's growth is supported by domestic activity while exports remain subdued. Retrieved from http://www.africaneconomicoutlook.org/en/outlook/africa%E2%80%99s-growth-is-supported-by-domestic-activity-while-exports-remain-subdued/
   Google Scholar
• African Economic Outlook. (2014). Global value chains and Africa's industrialization. African Development Bank. Retrieved from http://www.africaneconomicoutlook.org/fileadmin/uploads/aeo/2014/PDF/Thematic_Edition/Edition_Thematique_EN_web.pdf
   Google Scholar
• African Development Bank. (2012). Economic brief. Open, smart and inclusive development: ICT for transforming North Africa. Retrieved from http://www.afdb.org/fileadmin/uploads/afdb/Documents/Publications/Brochure%20Open%20Smart%20Anglais.pdf
   Google Scholar
• African Development Bank. (2011, January). Angola 2011–2015. Country strategy paper and country portfolio performance review. Country and Regional Department –  South B (ORSB).
   Google Scholar
• Andoh-Baidoo, F. K., Osatuyi, B., & Kunene, K. N. (2014). ICT capacity as the investment and use of ICT: Exploring its antecedents in Africa. Information Technology for Development, 20(1), 44–59.
   Web of Science ®Google Scholar
• Avkiran, N. K., Tone, K., & Tsutsui, M. (2008). Bridging radial and non-radial measures of efficiency in DEA. Annals of Operations Research, 164(1), 127–138.
   Web of Science ®Google Scholar
• Bagchi, K., & Udo, G. (2007). Global digital divide: A longitudinal analysis. In P. Palvia, S. Palvia, & A. L. Harris (Eds.), Managing global information technology: Strategies and challenges (pp. 81–95). Marietta, GA: Ivy League Publishing.
   Google Scholar
• Baliamoune-Lutz, M. (2003). An analysis of the determinants and effects of ICT diffusion in developing countries. Information Technology for Development, 10(3), 151–169.
   Google Scholar
• Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092.
   Web of Science ®Google Scholar
• Bankole, F. O., Osei-Bryson, K. M., & Brown, I. (2011). ICT infrastructure utilization in Africa: Data envelopment analysis based exploration. Proceeding of special interest group on ICT and global development at Americas Conference on Information System (AMCIS) Workshop, Detroit, USA.
   Google Scholar
• Bankole, F. O., Osei-Bryson, K. M., & Brown, I. (2013). The impact of information and communications technology infrastructure and complementary factors on Intra-African trade. Information Technology for Development, 12–28.
   Web of Science ®Google Scholar
• Best, M. L., & Wade, K. W. (2009). The internet and democracy: Global catalyst or democratic dud? Bulletin of Science, Technology & Society, 29, 255–271.
   Google Scholar
• Bhagavath, V. (2006). Technical efficiency measurement by data envelopment analysis: An application in transportation. Alliance Journal of Business Research, 2(1), 60–72.
   Google Scholar
• Bollou, F., Ngwenyama, O. K., & Morawczynski, O. (2006). The impact of investments in ICT, health and education on development: A DEA analysis of five African countries from 1993–1999. European Conference on Information Systems- ECIS paper 35 (pp. 1043–1055). Retrieved from http://aisel.aisnet.org/ecis2006/35
   Google Scholar
• Bollou, F., Ngwenyama, O. K., & Morawczynski, O. (2008). Are ICT investments paying off in Africa? An analysis of total factor productivity in six West African countries from 1995 to 2002. Information Technology for Development, 14, 294–307.
   Google Scholar
• Bruno, G., Esposito, G., Iandoli, L., & Raffa, M. (2003). The ICT service industry in North America and the role of partnership in Morocco. Journal of Global Information Technology Management, 7(3), 5–26.
   Google Scholar
• Business Insider. (2013). Our list of the world's largest social networks shows how video, messages, and China are taking over the social web. Retrieved from http://www.businessinsider.com/the-worlds-largest-social-networks-2013–12
   Google Scholar
• Charnes, A., Cooper, W. W., Lewin, A. Y., & Seiford, L. M. (1994). Data envelopment analysis: Theory, methodology, and applications. Dordrecht: Springer.
   Google Scholar
• Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.
   Web of Science ®Google Scholar
• Chen, S., & Xie, Z. (2014). Is China's e-governance sustainable? Testing Solow IT productivity paradox in China's context. Technological Forecasting and Social Change, 96, 51–61.
   Web of Science ®Google Scholar
• Chinn, M. D., & Fairlie, R. W. (2006). The determinant of the global digital divide: A cross-country analysis of computer and internet penetration. Oxford Economic Papers, 59(1), 16–44.
   Web of Science ®Google Scholar
• Chinn, M. D., & Fairlie, R. W. (2010). ICT use in the developing world: An analysis of differences in computer and internet penetration. Review of International Economics, 18(1), 153–167.
   Web of Science ®Google Scholar
• Chuhan-Pole, P., Angwafo, M., Mapi Buitano, A. D., Korman, V., & Fox, M. L. (2013). Africa's pulse. An analysis of issues shaping Africa's economic future (Vol. 8). Washington, DC: The World Bank.
   Google Scholar
• Ciborra, C. (2005). Interpreting e-Government and development efficiency, transparency or governance at a distance? Information Technology & People, 18(3), 260–279.
   Google Scholar
• Cook, W. D., Tone, K., & Zhu, J. (2014). Data envelopment analysis: Prior to choosing a model. Omega, 44, 1–4.
   Web of Science ®Google Scholar
• Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis a comprehensive text with models. Applications, references and DEA-Solver software second edition. New York: Springer.
   Google Scholar
• Cooper, W. W., Seiford, L. M., Zhu, J. (2004). Data envelopment analysis. Handbook on data envelopment analysis. International Series in Operations Research & Management Science, 71, 1–39.
   Google Scholar
• Corrales, J., & Westhoff, F. (2006). Information technology adoption and political regimes. International Studies Quarterly, 50(4), 911–933.
   Web of Science ®Google Scholar
• Dalberg Report. (2013, April). Impact of the Internet in Africa. Establishing conditions for success and catalyzing inclusive growth in Ghana, Kenya, Nigeria and Senegal. Retrieved from http://www.impactoftheinternet.com/pdf/Dalberg_Impact_of_Internet_Africa_Full_Report_April2013_vENG_Final.pdf
   Google Scholar
• Dasgupta, S., Lall, S., & Wheeler, D. (2001). Policy reform, economic growth and digital divide: An econometric analysis (Working Paper No. 2567). Washington, DC: World Bank.
   Google Scholar
• De, P., Dhar, A., & Bhattacharya, B. N. (2012). Efficiency of health care system in India: An inter-state analysis using DEA approach. Social Work in Public Health, 27(5), 482–506.
   PubMed Web of Science ®Google Scholar
• Drake, L., Hall, M. J., & Simper, R. (2006). The impact of macroeconomic and regulatory factors on bank efficiency: A non-parametric analysis of Hong Kong's banking system. Journal of Banking & Finance, 30(5), 1443–1466.
   Web of Science ®Google Scholar
• Dzidonu, C. (2010). An analysis of the role of ICTs to achieving the MDGs. Paper commissioned by the Division for Public administration and Development Management of the United Nations Department of Economic and Social affairs (UNDESA), Accra Institute of Technology, Accra.
   Google Scholar
• Erumban, A. A., & De Jong, S. B. (2006). Cross-country differences in ICT adoption: A consequence of culture? Journal of World Business, 41(4), 302–314.
   Web of Science ®Google Scholar
• Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. The American Economic Review, 84, 66–83.
   Web of Science ®Google Scholar
• Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 120, 253–290.
   Web of Science ®Google Scholar
• Groshek, J. (2009). The democratic effects of the Internet, 1994–2003: A cross-national inquiry of 152 countries. International Communications Gazette, 71, 115–136. Retrieved from http://www.internetworldstats.com/africa.htm
   Google Scholar
• Gupta, B., Dasgupta, S., & Gupta, A. (2008). Adoption of ICT in a government organization in a developing country: An empirical study. The Journal of Strategic Information Systems, 17(2), 140–154.
   Web of Science ®Google Scholar
• Holmner, M., & Britz, J. J. (2011). The road less travelled: A critical reflection on infrastructure development in Africa from a perspective of the new economics of information. Mousaion, 29(1), 1–16.
   Google Scholar
• Holmner, M., & Britz, J. J. (2013). When the last mile becomes the longest mile: A critical reflection on Africa's ability to transform itself to become part of the global knowledge society. Innovation: Journal of Appropriate Librarianship and Information Work in Southern Africa: Information Ethics, 46, 117–134.
   Google Scholar
• Information Telecommunication Union. (2013, December). World telecommunication/ICT indicators database 2013 (17th Edition). List of the indicators included in the World Telecommunication Indicator/ICT indicators database.
   Google Scholar
• Information Telecommunication Union Statistics. Retrieved from http://www.itu.int/en/ITU-D/Statistics
   Google Scholar
• Internet World Stats. Internet usage statistics for Africa. Retrieved from http://www.internetworldstats.com/stats1.htm
   Google Scholar
• IT News Africa, Africa's Technology News Leader. (2013). Africa's most active ICT regions. Retrieved May17, 2013, from http://www.itnewsafrica.com/2013/05/africas-most-active-ict-regions/
   Google Scholar
• ITU & UNCTAD. (2007). World information society report 2007: Beyond WSIS. Retrieved from http://www.itu.int/osg/spu/publications/worldinformationsociety/2007/WISR07_full-free.pdf
   Google Scholar
• Jamasb, T., & Pollitt, M. (2000). Benchmarking and regulation: International electricity experience. Utilities Policy, 9(3), 107–130.
   Google Scholar
• Kamal, M., & Qureshi, S. (2009). How can information and communication technology bring about development? An information architecture for guiding interventions in developing regions. Association for Information Systems Electronic Library (AISeL). AMCIS 2009 Proceedings, 188. Retrieved from http://aisel.aisnet.org/amcis2009/188
   Google Scholar
• Kapurubandara, M., & Lawson, R. (2008). Availability of e-commerce support for SMEs in developing countries. International Journal on Advances in ICT for Emerging Regions (ICTer), 1(1), 3–11.
   Google Scholar
• Kelly, T. (2014). The state of Broadband in Africa: What's here and what's coming? In J. O'Neill, E. Noam, & D. Gerbarg (Eds.), Broadband as a video platform (pp. 41–49). Gewerbestrasse, Switzerland: Springer International Publishing.
   Google Scholar
• Kimura, K., Omole, D. W., & Williams, M. (2010). ICT in sub-Saharan Africa: Success stories. In P. Chuhan-Pole & M. Angwafo (Eds.), Yes Africa can: Success stories from a dynamic continent, (Part V) (pp. 339–352). Washington, DC: The World Bank.
   Google Scholar
• Kumar, M., & Vincent, C. (2011). Benchmarking Indian banks using DEA in post-reform period: A progressive time-weighted mean approach. The Service Industries Journal, 31(14), 2455–2485.
   Web of Science ®Google Scholar
• Malik, K. (2013, March 15). Human development report 2013. The rise of the South: Human progress in a diverse world. The Rise of the South: Human Progress in a Diverse World. UNDP-HDRO Human Development Reports. New York, NY: United Nations Development Program.
   Google Scholar
• Manyika, J., Cabral, A., Moodley, L., Moraje, S., Yeboah-Amankwah, S., Chui, M., & Anthonyrajah, J. (2013). Lions go digital: The Internet's transformative potential in Africa. New York: McKinsey & Company.
   Google Scholar
• Mark, D. J. W., Mayer, R., & Minges, M. (2011). Africa's ICT infrastructure. Building on the mobile revolution. Washington, DC: The International Bank for Reconstruction and Development (The World Bank).
   Google Scholar
• Matthee, K. W., Mweemba, G., Pais, A. V., Van Stam, G., & Rijken, M. (2007, December). Bringing internet connectivity to rural Zambia using a collaborative approach. Proceedings of the 2nd ACM international conference on information and communication technologies and development (ICTD), pp. 47–58, Bangalore. India.
   Google Scholar
• McGarty, C., Thomas, E. F., Lala, G., Smith, L. G., & Bliuc, A. M. (2013). New technologies, new identities, and the growth of mass opposition in the Arab spring. Political Psychology, 35, 725–740.
   Web of Science ®Google Scholar
• Milner, H. V. (2006). The digital divide the role of political institutions in technology diffusion. Comparative Political Studies, 39(2), 176–199.
   Web of Science ®Google Scholar
• Minges, M., Briceno-Garmendia, C., Williams, M., Ampah, M., Camos, D., & Shkratan, M. (2008). Information and communications technology in Sub-Saharan Africa: A sector review. Background Paper, 10. Retrieved from http://www.eu-africa-infrastructure-tf.net/attachments/library/aicd-background-paper-10-ict-sect-summary-en.pdf
   Google Scholar
• Mo Ibrahim Foundation. (2012, October). Ibrahim index of African governance: Summary. Swindon, UK: Author.
   Google Scholar
• Mwesige, P. G. (2003). Cyber elites: A survey of internet cafe users in Uganda. Telematics and Informatics 2003, 21, 83–101.
   Google Scholar
• Ngwenyama, O., & Morawczynski, O. (2009). Factors affecting ICT expansion in emerging economies: An analysis of ICT infrastructure expansion in five Latin American countries. Information Technology for Development, 15(4), 237–258.
   Web of Science ®Google Scholar
• Outlook, A. E. (2011). Africa and its emerging partners. Paris: African Development Bank, OECD Publishing.
   Google Scholar
• Outlook, A. E. (2013). Structural transformation and natural resources in Africa. Paris: African Development Bank, OECD Publishing.
   Google Scholar
• Pohjola, M. (2003). The adoption and diffusion of ICT across countries: Patterns and determinants. In D. C. Jones (Ed.), The New economy handbook (pp. 77–100). Amsterdam: Elsevier Science Academic Press.
   Google Scholar
• Puri, S. K. (2006). Technological frames of stakeholders shaping the SDI implementation: A case study from India. Information Technology for Development, 12(4), 311–331.
   Google Scholar
• Quibria, M. G., Ahmed, S. N., Tschang, T., & Reyes-Macasaquit, M. L. (2003). Digital divide: Determinants and policies with special reference to Asia. Journal of Asian Economics, 13(6), 811–825.
   Google Scholar
• Rahemtulla, H., Kaplan, J., Gigler, B.-S., Cluster, S., Kiess, J., & Brigham, C. (2011). Open data Kenya: Case study of the underlying drivers, principle objectives and evolution of one of the first open data initiatives in Africa. Open Development Technology Alliance, 45 pp. The World Bank. Retrieved from http://www.scribd.com/doc/75642393/Open-Data-Kenya-Long-Version.
   Google Scholar
• Rao, M. (2011). Mobile Africa report 2011: Regional hubs of excellence and innovation. Mobile Monday.
   Google Scholar
• Reda, A., Cutrell, E., & Noble, B. (2011, June). Towards improved web acceleration: Leveraging the personal web. Proceedings of the 5th ACM workshop on Networked Systems for Developing Regions (NSDR) (pp. 57–62). Bethesda, MD.
   Google Scholar
• Samoilenko, S., & Osei-Bryson, K. M. (2008). Increasing the discriminatory power of DEA in the presence of the sample heterogeneity with cluster analysis and decision trees. Expert Systems with Applications, 34(2), 1568–1581.
   Web of Science ®Google Scholar
• Samoilenko, S., & Osei-Bryson, K. M. (2010). Determining sources of relative inefficiency in heterogeneous samples: Methodology using cluster analysis, DEA and neural networks. European Journal of Operational Research, 206(2), 479–487.
   Web of Science ®Google Scholar
• Samuel, J., Shah, N., & Hadingham, W. (2007, March). Mobile communications in South Africa, Tanzania, and Egypt: Results from community and business surveys, in Africa: The impact of mobile phones. The Vodafone Policy Paper Series, No 3 (pp. 44–52).
   Google Scholar
• Sanou, B. (2013). The world in 2013: ICT facts and figures. Geneva: International Telecommunications Union.
   Google Scholar
• Sein, M. K., & Furuholt, B. (2012). Intermediaries: Bridges across the digital divide. Information Technology for Development, 18(4), 332–344.
   Web of Science ®Google Scholar
• Shirazi, F., Ngwenyama, O., & Morawczynski, O. (2010). ICT expansion and the digital divide in democratic freedoms: An analysis of the impact of ICT expansion, education and ICT filtering on democracy. Telematics and Informatics, 27(1), 21–31.
   Google Scholar
• Singh, S. (2010). The South African ‘information society’, 1994–2008: Problems with policy, legislation, rhetoric and implementation. Journal of Southern African Studies, 36(1), 209–227.
   Web of Science ®Google Scholar
• Standard Digital. (2013). Kenya mobile money transfer: The first of its kind in the world. Retrieved from http://www.standardmedia.co.ke/kenyaat50/article/2000096984/kenya-s-first-mobile-money-transfer-launched
   Google Scholar
• Statistic Brain. (2014). Africa continent statistics. Retrieved from http://www.statisticbrain.com/africa-continent-statistics/
   Google Scholar
• Sueyoshi, T., & Sekitani, K. (2009). An occurrence of multiple projections in DEA-based measurement of technical efficiency: Theoretical comparison among DEA models from desirable properties. European Journal of Operational Research, 196(2), 764–794.
   Web of Science ®Google Scholar
• Thanassoulis, E., Kortelainen, M., Johnes, G., & Johnes, J. (2011). Costs and efficiency of higher education institutions in England: A DEA analysis. Journal of the Operational Research Society, 62(7), 1282–1297.
   Web of Science ®Google Scholar
• The Africa Report. (2012). Six African states among top 2011 MDGs performers. Retrieved from http://www.theafricareport.com/North-Africa/six-african-states-among-top-2011-mdgs-performers.html
   Google Scholar
• The Economist Intelligence Unit. (2011). Democracy index 2011. Democracy under stress. A report from the Economist Intelligence Unit Limited 2011. London: Author.
   Google Scholar
• The Internet World Stats. Usage and population statistics. Retrieved from http://www.internetworldstats.com/africa.htm
   Google Scholar
• The World Bank data. Indicators and statistics. Retrieved from http://data.worldbank.org/indicator
   Google Scholar
• Thlabela, K., Roodt, J., Paterson, A., & Weir-Smith, G. (2006). Mapping ICT access in South Africa. Cape Town: HSRC Press.
   Google Scholar
• Tone, K. (1999). A slacks based measure of efficiency in data development analysis. European Journal of Operational Research, 130(2001), 498–509.
   Google Scholar
• Tone, K. (2002). A slacks-based measure of super-efficiency in data envelopment analysis. European Journal of Operational Research, 143, 32–41.
   Web of Science ®Google Scholar
• Touré, H. I. (2013). The role of ICTS in Africa's development. Retrieved from http://www.africanexecutive.com/modules/magazine/articles.php?article=7535
   Google Scholar
• Toussea-Oulai, A., & Ura, S. (1991). Information technology transfer: Problems facing African developing nations. International Journal of Human-Computer Interaction, 3(1), 79–93.
   Google Scholar
• Udo, G., Bagchi, K. K., & Kirs, P. J. (2008). Diffusion of ICT in developing countries: A qualitative differential analysis of four nations. Journal of Global Information Technology Management, 11(1), 6–27.
   Google Scholar
• UNCTAD. (2008). Information economy report 2007–2008. Science and technology for development: The new paradigm of ICT. Geneva: Author.
   Google Scholar
• United Nations. (2012). The millennium development goals report. New York: UN Statistics Division.
   Google Scholar
• Vicente Cuervo, M. R., & López Menéndez, A. J. (2006). A multivariate framework for the analysis of the digital divide: Evidence for the European Union-15. Information & Management, 43(6), 756–766.
   Web of Science ®Google Scholar
• Vincová, K. (2005). Using DEA models to measure efficiency. Biatec, 13(8), 24–28.
   Google Scholar
• Wallsten, S. (2001). An econometric analysis of telecom competition, privatization, and regulation in Africa and Latin America. Journal of Industrial Economics, 49(1), 1–19.
   Web of Science ®Google Scholar
• Wallsten, S. (2005). Regulation and internet use in developing countries. Economic Development and Cultural Change, 53(2), 501–523.
   Web of Science ®Google Scholar
• Worku, G. (2010). Electronic-banking in Ethiopia-practices, opportunities and challenges. Journal of Internet Banking and Commerce, 15(2), 1–8.
   Google Scholar
• World Bank. (2015). World development indicators database. Gross domestic product 2013. Washington, DC: World Bank.
   Google Scholar
• World Economic Forum. (2013). Insight report. The Africa competitiveness report 2013. Geneva: Author.
   Google Scholar
• Yonazi, E., Kelly, T. H. N., & Blackman, C. (Eds.). (2012). The transformational use of information and communication technologies in Africa: e-Transform Africa. Tunis: African Development Bank.
   Google Scholar
• Zhao, H., Kim, S., Suh, T., & Du, J. (2008). Social institutional explanations of global internet diffusion: A cross-country analysis. Selected Readings on Global Information Technology, 15, 347–372.
   Web of Science ®Google Scholar
• Zhou, Y., Xing, X., Fang, K., Liang, D., & Xu, C. (2013). Environmental efficiency analysis of power industry in China based on an entropy SBM model. Energy Policy, 57, 68–75.
   Web of Science ®Google Scholar