136
Views
0
CrossRef citations to date
0
Altmetric
Articles

Knowledge economy classification in African countries: A model-based clustering approach

ORCID Icon, ORCID Icon & ORCID Icon

References

  • Abad-González, J., & Martínez, R. (2017). Endogenous categorization of the human development. Applied Economics Letters, 24(4), 243–246. https://doi.org/10.1080/13504851.2016.1181703
  • Acuña, E., & Rodríguez, C. (2004). The treatment of missing values and its effect on classifier accuracy. In D. Banks, F. R. McMorris, P. Arabie, & W. Gaul (Eds.), Classification, clustering, and data mining applications. studies in classification, data analysis, and knowledge organisation (pp. 639–647). Springer.
  • Agyapong, B. G., & Oseifuah, E. K. (2015). Knowledge and economic growth: A comparative analysis of three regional blocks in Sub-Saharan Africa. Environmental Economics, 6(4–1), 196–208. https://www.businessperspectives.org/index.php/component/zoo/knowledge-and-economic-growth-a-comparative-analysis-of-three-regional-blocks-in-sub-saharan-africa
  • Ahlquist, J., & Breunig, C. (2012). Model-based clustering and typologies in the social sciences. Political Analysis, 20(1), 92–112. https://doi.org/10.1093/pan/mpr039
  • Alfo, M., Trovato, G., & Waldmann, R. (2008). Testing for country heterogeneity in growth models using a finite mixture approach. Journal of Applied Econometrics, 23(4), 487–514. https://doi.org/10.1002/jae.1008.
  • Amavilah, V. (2006). Non-parametric diversity indices of technical capability of African countries. African Development Review, 18(18), 205–220. https://doi.org/10.1111/j.1467-8268.2006.00139.x
  • Amavilah, V., Asongu, A., & Andrés, A. R. (2017). Effects of globalization on peace and stability: Implications for governance and the knowledge economy of African countries. Technological Forecasting and Social Change, 122 (September), 91–103. https://doi.org/10.1016/j.techfore.2017.04.013
  • Andrés, A. R., Amavilah, V., & Asongu, A. (2017). Linkages between formal institutions, ICT adoption, and inclusive human development in Sub-Saharan Africa. In D. E. Lechman, D. A. Marszk, & D. H. Kaur (Eds.), Catalyzing development through ICT adoption: The developing World experience. Chapter 10 (pp. 175–203). Springer Verlag.
  • Andrés, A. R., Asongu, S. A., & Amavilah, V. H. (2015). The impact of formal institutions on the knowledge economy. Journal of the Knowledge Economy, 6(4), 1034–1062. https://doi.org/10.1007/s13132-013-0174-3
  • Anyanwu, J. (2012). Developing knowledge for economic advancement in Africa. International Journal of Academic Research in Economics and Management Sciences, 1(2), 73–111.
  • Archibugi, D., & Coco, A. (2004). A new indicator of technological capabilities for developed and developing countries (ArCo). World Development, 32(4), 629–654. https://doi.org/10.1016/j.worlddev.2003.10.008
  • Archibugi, D., Denni, M., & Filippetti, A. (2009). The technological capabilities of nations: The state of the art of synthetic indicators. Technological Forecasting and Social Change, 76(7), 917–931. https://doi.org/10.1016/j.techfore.2009.01.002
  • Arrow, K. (1962). Economic Welfare and the allocation of resources to invention. In The rate and direction of inventive activity: Economic and Social factors, edited by the Universities- National Bureau Committee for Economic Research and the Committee on Economic Growth of the Social Science Research Councils (pp. 609–626). Princeton University Press. http://www.nber.org/books/univ62-1
  • Asongu, S., Andrés, A. R., & Amavilah, V. (2019). Business dynamics, knowledge economy, and the socio-economic development of African countries. Information Development, 36(1), 128–152. https://doi.org/10.1177/0266666919832336
  • Asongu, S., Tchamyou, V., & AchaAnyi, P. (2018). Who is who in knowledge economy in Africa? Journal of the Knowledge Economy, 1–33. https://link.springer.com/article/10.1007/s13132-018-0547-8.
  • Azam, J. P., Fosu, A., & Ndung’u, N. S. (2002). Explaining slow growth in Africa. African Development Review, 14(2), 177–220. https://doi.org/10.1111/1467-8268.00051
  • Balijepally, V., Mangalaraj, G., & Iyengar, K. (2011). Are we wielding this hammer correctly? A reflective review of the application of cluster analysis in information systems research. Journal of the Association for Information Systems, 12(5), 375–413. https://doi.org/10.17705/1jais.00266
  • Barro, R. (1991). Economic growth in a cross section of countries. The Quarterly Journal of Economics, 106(2), 407–443. https://doi.org/10.2307/2937943
  • Barro, R. J., & Lee, J. W. (1993). International comparisons of educational attainment. Journal of Monetary Economics, 32(3), 363–394. https://doi.org/10.1016/0304-3932(93)90023-9
  • Baudry, J. P., Raftery, A., Celeux, G., Lo, K., & Gottardo, R. (2010). Combining mixture components for clustering models. Journal of Computational and Graphical Statistics, 19(2), 332–353. https://doi.org/10.1198/jcgs.2010.08111
  • Bauer, D. F. (1972). Constructing confidence sets using rank statistics. Journal of the American Statistical Association, 67(339), 687–690. https://doi.org/10.1080/01621459.1972.10481279
  • Becker, M. (2005). Development: Josep A. Schumpeter. Journal of Economic Literature, 1(XLII), 108–111. 10.1257/0022051053737825
  • Beretta, L., & Santaniello, A. (2016). Nearest neighbor imputation algorithms: A critical evaluation. BMC Medical Informatics and Decision Making, 16(3. Suppl 74), 198–208. https://doi.org/10.1186/s12911-016-0318-z
  • Bezdek, J. C., & Pal, N. R. (1998). Some new indexes of cluster validity. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 28(3), 301–315. https://doi.org/10.1109/3477.678624
  • Biernacki, C., Celeux, G., & Govaert, G. (2000). Assessing a mixture model for clustering with the integrated completed likelihood. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(7), 719–725. https://doi.org/10.1109/34.865189
  • Blackburn, K., & Forgues-Puccio, G. F. (2010). Financial liberalization, bureaucratic corruption and economic development. Journal of International Money and Finance, 29(7), 1321–1339. https://doi.org/10.1016/j.jimonfin.2010.05.002
  • Borgmann, A. (2006). Technology as a cultural force: For alena and griffin. The Canadian Journal of Sociology, 31(3), 351–360. 10.1353/cjs.2006.0050
  • Burnside, C., & Dollar, D. (1997). Aid policies, and growth. World Bank Policy Research Working Paper (1777).
  • Buesa, M., Heijs, J., & Baumert, T. (2010). The determinants of regional innovation in Europe: A combined factorial and regression knowledge production function approach. Research Policy, 39(6), 722–735.
  • Carayannis, E. G., Clark, S. C., & Valvi, D. E. (2013). Smartphone affordance: Achieving better Business through innovation. Journal of the Knowledge Economy, 4(4), 444–472. https://doi.org/10.1007/s13132-012-0091-x
  • Carter, A. P. (1996). Measuring the performance of a knowledge-based economy. In D. Foray & B. A. Lundvall (Eds.), Employment and growth in the knowledge-based economy (pp. 61–68). Organisation for Economic Cooperation and Development.
  • Castellacci, F. (2011). Closing the technology gap. Review of Development Economics, 15(1), 180–197. https://doi.org/10.1111/j.1467-9361.2010.00601.x
  • Castellacci, F., & Archibugi, D. (2008). The technology clubs: The distribution of knowledge across nations. Research Policy, 37(10), 1659–1673. https://doi.org/10.1016/j.respol.2008.08.006
  • Chavula, H. K. (2013). Telecommunications development and economic growth in Africa. Information Technology for Development, 19(1), 5–23. https://doi.org/10.1080/02681102.2012.694794
  • Chen, J., & Chen, Z. (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95(3), 759–771. https://doi.org/10.1093/biomet/asn034
  • Chen, H., & Dahlman, C. (2006). The Knowledge Economy, the KAM Methodology, and World Bank Operations. World Bank Institute Working Paper 37256. The World Bank
  • Clement, J. (2020). Social protection clusters in sub-Saharan Africa. International Journal of Social Welfare, 29(1), 20–28. https://doi.org/10.1111/ijsw.12378
  • Collier, P. (2007). Africa’s economic growth: Opportunities and constraints. African Development Review, 19(1), 6–25. https://doi.org/10.1111/j.1467-8268.2007.00153.x
  • Collier, P., & Gunning, J. W. (1996). Policy towards commodity shocks in developing countries. IMF Working Paper 84.
  • Collier, P., & Gunning, J. W. (1999a). Explaining African performance. Journal of Economic Literature, 37(1), 64–111. https://doi.org/10.1257/jel.37.1.64
  • Collier, P., & Gunning, J. W. (1999b). Why has Africa grown slowly? Journal of Economic Perspectives, 13(3), 3–22. https://doi.org/10.1257/jep.13.3.3
  • Conway, P., & Greene, J. (1993). Is Africa different? World Development, 21(12), 2017–2028. https://doi.org/10.1016/0305-750X(93)90073-I
  • Csereklyei, Z., Thurner, P., Langer, J., & Kuchenhoff, H. (2017). Energy paths in the European Union: A model-based clustering approach. Energy Economics, 65(1), 442–457. https://doi.org/10.1016/j.eneco.2017.05.014
  • Datta, A., & Agarwal, S. (2004). Telecommunications and economic growth: A panel data approach. Applied Economics, 36(15), 1649–1654. https://doi.org/10.1080/0003684042000218552
  • Devarajan, S. (2013). Africa’s statistical tragedy. Review of Income and Wealth, 59(1), S9–S15. https://doi.org/10.1111/roiw.12013
  • Dodgson, M., & Gann, D. (2018). Innovation: A very short introduction. (2nd ed). Oxford University Press.
  • Dolowitz, D. P., & Marsh, D. (2000). Learning from abroad: The role of policy transfer in contemporary policy making. Governance, 13(1), 5–23. https://doi.org/10.1111/0952-1895.00121
  • Driouchi, A., Azelmad, E. M., & Anders, G. C. (2006). An econometric analysis of the role of knowledge in economic performance. The Journal of Technology Transfer, 31(2), 241–255. https://doi.org/10.1007/s10961-005-6109-9
  • Drucker, P. (1969). The age of discontinuity. Harper Business.
  • Easterly, W. (2001). Can institutions resolve ethnic conflict? Economic Development and Cultural Change, 49(4), 687–706. https://doi.org/10.1086/452521
  • Easterly, W., & Levine, R. (1997). Africa’s growth tragedy: Policies and ethnic divisions. The Quarterly Journal of Economics, 112(4), 1203–1250. https://doi.org/10.1162/003355300555466
  • Englebert, P. (2000). Solving the mystery of the African dummy. World Development, 28(10), 1821–1835. https://doi.org/10.1016/S0305-750X(00)00052-8
  • European Commission. (2020). Develop an Upgraded Single Market Scoreboard as a Governance Tool for the Single Market. https://ec.europa.eu/internal_market/scoreboard/
  • Fop, M., & Murphy, T. (2018). Variable selection methods for model-based clustering. Statistics Surveys, 12 (2018), 1– 48. https://doi.org/10.1214/18-SS119
  • Fraley, C., & Raftery, A. (1998). How many clusters? Which clustering method? Answer via model-based cluster analysis. The Computer Journal, 41(41), 578–588. https://doi.org/10.1093/comjnl/41.8.578
  • Fraley, C., & Raftery, A. (2002). Model-based clustering, discriminant analysis and density estimation. Journal of the American Statistical Association, 97(458), 611–631. https://doi.org/10.1198/016214502760047131
  • Fraley, C., Raftery, A. E., Murphy, T. B., & Scrucca, L. (2012). MCLUST version 4 for R: Normal mixture modeling for model-based clustering, classification, and density estimation. Technical Report 597, Department of Statistics, University of Washington, 290–296.
  • Fruhwirth-Schnatter, S. (2011). Panel data analysis: A survey on model-based clustering of time series. Advances in Data Analysis and Classification. Theory, Methods, and Applications in Data Science, 5(4), 251–280. https://doi.org/10.1007/s11634-011-0100-0
  • Fruhwirth-Schnatter, S., & Kaufmann, S. (2008). Model based-clustering of multiple time series. Journal of Business & Economic Statistics, 26(1), 78–89. https://doi.org/10.1198/073500107000000106
  • Grant, D., & Yeo, B. (2018). A global perspective on tech investment, financing, and ICT on manufacturing and service industry performance. International Journal of Information Management, 43 (December), 130–145. https://doi.org/10.1016/j.ijinfomgt.2018.06.007
  • Grossman, G., & Helpman, E. (1991). Innovation and growth in the global economy. MIT Press.
  • Gyimah-Brempong, K., & Wilson, M. (2004). Health human capital and economic growth in Sub-Saharan African and OECD countries. The Quarterly Review of Economics and Finance, 2(44), 296–320. https://doi.org/10.1016/j.qref.2003.07.002
  • Hair, J. F., Jr., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th Edition). Pearson Prentice Hall. Chapter 8.
  • Hamdy, A. (2007). Survey of ICT and Education in Africa: Algeria Country Report. InfoDev ICT and Education Series. World Bank. https://openknowledge.worldbank.org/handle/10986/10683 License: CC BY 3.0 IGO
  • Havens, T. C., Bezdek, J. C., Keller, J. M., & Popescu, M. (2008). Dunn’s cluster validity index as a contrast measure of VAT images. In 2008 19th International Conference on Pattern Recognition (pp. 1–4). IEEE. 8-11 December 2008.
  • Isaacs, S. (2007). Survey of ICT and Education in Africa: Botswana Country Report. InfoDev ICT and Education Series. World Bank. https://openknowledge.worldbank.org/handle/10986/10713 License: CC BY 3.0 IGO
  • Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern Recognition Letters, 31(8), 651–666. https://doi.org/10.1016/j.patrec.2009.09.011
  • Jerven, M. (2011). The quest for the African dummy: Explaining African post-colonial economic performance revisited. Journal of International Development, 23(2), 288–307. https://doi.org/10.1002/jid.1603
  • Jerven, M. (2013). Poor numbers: How we are misled by African development statistics and what to do about it. Cornell University Press.
  • Jung, Y. G., Kang, M. S., & Heo, J. (2014). Clustering performance comparison using K-means and expectation maximization algorithms. Biotechnology & Biotechnological Equipment, 28(suppl 1), S44–S48. https://doi.org/10.1080/13102818.2014.949045
  • Kaplinsky, R. (2005). Globalization, inequality, and poverty: Between a rock and a hard place. Polity.
  • Kaufmann, D., Kraay, A., & Mastruzzi, M. (2010). The worldwide governance indicators: Methodology and analytical Issues. World Bank Policy Research Working Paper no. 5430.
  • Knedlink, T., & Reinowski, E. (2008). The African growth gap, development policy, and realization of MDGs. Proceedings of the German Development Economics Conference, Zurich 2008 23, Verein für Socialpolitik, Research Committee Development Economics.
  • Knedlik, T., & Reinowski, E. (2008). The African growth gap, development policy, and the realization of the MDGs. New In book: African Development Perspectives Yearbook, No. 13 Edition: Publisher: LIT Verlag Editors: Wohlmuth et al.
  • Kochetkov, D. M., & Vlasov, M. V. (2016). Teoretiko-metodologicheskie podkhody k analizu ekonomiki znanii na regional'nom urovne [Theoretical and methodological approaches to the analysis of the knowledge economy at the regional level]. Zhurnal Ekonomicheskoi Teorii [Russian Journal of Economic Theory], 4, 242–247.
  • Krugman, P. (2013). The New Growth Fizzle. New York Times.
  • Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one criterion variance analysis. Journal of the American Statistical Association, 47(260), 583–621. https://doi.org/10.1080/01621459.1952.10483441
  • Kuhn, M. (2008). Building predictive models in R using the caret package. Journal of Statistical Software. Articles, 28(5), 1–26. https://doi.org/10.18637/jss.v028.i05
  • Kumar, N. (2019). A model-based clustering approach for analyzing energy related financial literacy and its determinants. CER-ETH Economics working paper series 19/312, CER-ETH - Center of Economic Research (CERETH) at ETH Zurich.
  • Landes, D. (1998). ) The wealth and Poverty of nations: Why some Are So rich and some So poor. W.W. Norton.
  • Levine, E., & Domany, E. (2001). Resampling method for unsupervised estimation of cluster validity. Neural Computation, 13(11), 2573–2593. https://doi.org/10.1162/089976601753196030
  • Little, R. J. A., & Rubin, D. B. (2002). Statistical analysis with missing data (2nd ed). John Wiley & Sons.
  • Lucas, R. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22(1), 3–42. https://doi.org/10.1016/0304-3932(88)90168-7
  • Lucas, R. (1993). Making a miracle. Econometrica, 61(2), 251–272. https://doi.org/10.2307/2951551
  • Lundvall, BÅ, Joseph, K., Chaminade, C., & Vang, J. (2009). Handbook on innovation systems and developing countries: Building domestic capabilities in a global setting. Edward Elgar.
  • Machlup, F. (1962). The production and distribution of knowledge in the United States. Princeton University Press.
  • Mardia, K., Kent, J., & Bibby, J. (1979). Multivariate analysis. Academic Press London.
  • Marfo, K., Pence, A., LeVine, R. A., & LeVine, S. (2011). Strengthening Africa’s contributions to Child Development research: Introduction. Child Development Perspectives, 5(2), 104–111. https://doi.org/10.1111/j.1750-8606.2011.00164.x
  • Marrocu, E., Paci, R., Usai, S. (2013). Proximity, networking and knowledge production in Europe: What lessons for innovation policy? Technological Forecasting and Social Change, 80(8), 1484–1498.
  • Márquez, D. G., Félix, P., García, C. A., Tejedor, J., Fred, A. L., & Otero, A. (2019). Positive and negative evidence accumulation clustering for sensor fusion: An application to heartbeat clustering. Sensors, 19(21), 4635. https://doi.org/10.3390/s19214635
  • Mauro, P. (1995). Corruption and economic growth. The Quarterly Journal of Economics, 110(3), 681–712. https://doi.org/10.2307/2946696
  • Mitchell, R., Rose, P., & Asare, S. (2020). Education research in Sub-Saharan Africa: Quality, visibility, and agendas. Comparative Education Review, 64(3), 363–383. https://doi.org/10.1086/709428
  • Neath, A. A., & Cavanaugh, J. E. (2012). The Bayesian information criterion: Background, derivation, and applications. WIRES Computational Statistics, 4(2), 199–203. https://doi.org/10.1002/wics.199
  • North, D. C. (1990). Institutions, institutional change and economic performance. Cambridge University Press.
  • OECD. (1996). The Knowledge Based Economy.
  • OECD. (2005). Micro-policies for growth and productivity: Synthesis and benchmarking user guide.
  • Ouedraogo, R., Sourouema, W. S., & Sawadogo, H. (2021). Aid, growth. And institutions in Sub-Saharan Africa: New insights using a multiple growth regime approach. The World Economy, 44(1), 107–142. https://doi.org/10.1111/twec.12968
  • Parcero, O. J., & Ryan, J. C. (2017). Becoming a knowledge economy: The case of Qatar, UAE, and 17 benchmark countries. Journal of the Knowledge Economy, 8(4), 1146–1173. https://doi.org/10.1007/s13132-016-0355-y
  • Paz-Marín, M., Gutiérrez, P. A., & Martínez, C. H. (2018). Classification of countries’ progress toward a knowledge economy based on machine learning classification. Expert Systems with Applications, 42(1), 562–572. https://doi.org/10.1016/j.eswa.2014.08.008
  • Powell, W. W., & Snellman, K. (2004). The knowledge economy. Annual Review of Sociology, 30(1), 199–220. https://doi.org/10.1146/annurev.soc.29.010202.100037
  • Qureshi, S. (2013). What is the role of mobile phones in bringing about growth? Information Technology for Development, 19(1), 1–4. https://doi.org/10.1080/02681102.2013.764597
  • Rao, L., & McNaughton, M. (2019). A knowledge broker for collaboration and sharing for SIDS: The case of comprehensive disaster management in the Caribbean. Information Technology for Development, 25(1), 26–48. https://doi.org/10.1080/02681102.2018.1510363
  • Ryan, G., & Shinnick, E. (2011). Economic incentives and the knowledge economy (Second Edition), In Encyclopedia of knowledge management. Chapter 23. IGI Global.
  • R Core Team. (2019). R: A language and Environment for statistical computing. R Foundation for Statistical Computing.
  • Rebelo, S. T. (1990). Long run policy analysis and long run growth (No. w3325). National Bureau of Economic Research.
  • Rizk, N., El Said, A., Weheba, N., & De Beer, J. (2017). Towards an Alternative Assessment for Innovation in Africa. Working Paper, Open AIR.
  • Romer, P. (1986). Increasing returns and long run growth. Journal of Political Economy, 94(2), 1002–1037. https://doi.org/10.1086/261420
  • Romer, P. M. (1990). Endogenous technological change. Journal of Political Economy, 98(5), S71–S102. https://doi.org/10.1086/261725
  • 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. https://doi.org/10.1016/j.eswa.2007.01.039
  • Schumpeter, J. A. (2005). Development. Journal of Economic Literature, 43(1), 108–120. https://doi.org/10.1257/0022051053737825
  • Scrucca, L., Fop, M., Murphy, T., & Raftery, A. (2016). Mclust 5: Clustering, classification and density estimation using Gaussian finite mixture models. The R Journal, 8(8), 289–317. https://doi.org/10.32614/RJ-2016-021
  • Seo, H., & Thorson, S. (2016). A mixture model of global internet capacity distributions. Journal of the Association for Information Science and Technology, 67(8), 2032–2044. https://doi.org/10.1002/asi.23523
  • Shapira, P., Youtie, J., Yogeesvaran, K., & Jaafar, Z. (2006). Knowledge economy measurement: Methods, results, and insights from the Malaysian knowledge content study. Research Policy, 35(10), 1522–1537. https://doi.org/10.1016/j.respol.2006.09.015
  • Širá, E., Vavrek, R., Kravčáková, V., & Kotulič, R. (2020). Knowledge economy indicators and their impact on the sustainable competitiveness of the EU countries. Sustainability, 12(10), 4172. https://doi.org/10.3390/su12104172.
  • Stigler, G. (1961). The economics of information. Journal of Political Economy, 69(3), 213–225. https://doi.org/10.1086/258464
  • Stiglitz, J. (2015). Leaders and followers: Perspectives on the Nordic model and the economics of innovation. Journal of Public Economics, 127(2015), 3–16. https://doi.org/10.1016/j.jpubeco.2014.09.005
  • Sulkowski, A., & White, D. (2016). A happiness Kuznets curve? Using model-based cluster analysis to group countries based on happiness, development, income, and carbon emissions. Environment, Development and Sustainability, 18(4), 1095–1111. https://doi.org/10.1007/s10668-015-9689-z
  • Tchamyou, V. S. (2016). The role of knowledge economy in African business. Journal of Knowledge Economy, 8(4), 1189–1228. https://doi.org/10.1007/s13132-016-0417-1
  • Therneau, T., & Atkinson, B. (2019). rpart: Recursive Partitioning and Regression Trees. R package version 4.1–15. https://CRAN.R-project.org/package=rpart
  • Thompson, M., & Walsham, G. (2010). ICT research in Africa: Need for a Strategic developmental focus. Information Technology for Development, 16(2), 112–127. https://doi.org/10.1080/02681101003737390
  • Torero, M., & von Braun, J. (2006). Information and communication technologies for development and poverty reduction: The potential of telecommunications. IFPRI books, International Food Policy Research Institute (IFPRI), number 0-8018-8041-6, December.
  • Tripathi, M., & Inani, S. K. (2020). Does information and communications technology affect economic growth? Empirical evidence from SAARC countries. Information Technology for Development, 26(4), 773–787. https://doi.org/10.1080/02681102.2020.1785827
  • UNESCO Institute of Statistics (Online). Algeria: Science, Technology, and Innovation. Accessed 3/6/2021.
  • UNESCO Institute of Statistics (Various Online). Algeria: Education and literacy. http://uis.unesco.org/country/DZ/. Accessed 3/6/2021
  • UNESCO Institute of Statistics (Various Online). Botswana: Science, Technology, and Innovation. http://uis.unesco.org/en/country/bw?theme=science-technology-and-innovation. Accessed 3/6/2021
  • UNESCO Institute of Statistics (Various Online). Botswana: Education and literacy. http://uis.unesco.org/en/country/bw. Accessed 3/6/2021
  • van Biljon, J., & Osei-Bryson, K. W. (2020). The communicative power of knowledge visualizations in mobilizing Information and communication technology research. Information Technology for Development, 26(4), 637–652. https://doi.org/10.1080/02681102.2020.1821954
  • Verbeek, J., Vlassis, N., & Kröse, B. (2003). Efficient greedy learning of Gaussian mixture models. Neural Computation, 15(2), 469–485. https://doi.org/10.1162/089976603762553004
  • Watson, G. H. (1993). Strategic benchmarking: How to rate your company’s performance against the World’s best. Wiley.
  • World Bank. (2007). Building knowledge economies: Advanced strategies for development. Washington, DC: World Bank. World Bank. https://openknowledge.worldbank.org/handle/10986/6853.
  • World Bank. (2008). Measuring World Knowledge in the World’s economies. Knowledge Assessment Methodology and Knowledge Economy Index. Knowledge for Development Program. World Bank Institute.
  • World Bank. (2012). Knowledge for Development (k4d), Knowledge Assessment Methodology 2012. Technical report.
  • World Bank. (2016). World Development report: Digital dividends.
  • World Bank. (2019). World Bank country and lending groups. World Bank. https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups.
  • Xiao, J., Lu, J., & Li, X. (2017). Davies Bouldin index based hierarchical initialization K-means. Intelligent Data Analysis, 21(6), 1327–1338. https://doi.org/10.3233/IDA-163129
  • Xiong, J., Qureshi, S., & Najjar, L. (2014). A Cluster Analysis of research in Information Technology for global development: Where to from here? AIS Electronic Library.
  • Zhou, H. B., & Gao, J. T. (2014). Automatic method for determining cluster number based on silhouette coefficient. In Zhang Jin & Zhao (Eds.), Advanced materials research (Vol. 951, pp. 227–230). Trans Tech Publications Ltd.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.