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A cross-country model of contextual factors impacting cloud computing adoption at universities in sub-Saharan Africa

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Abstract

Cloud computing is a new computing paradigm that is revolutionizing the way we access and use computer infrastructure and services. Universities in developing countries lag behind their Western counterparts due to lack of cutting edge technology required for teaching, collaboration, and research. The purpose of this study was to investigate the factors that impact diffusion, adoption, and usage of cloud computing at universities in sub-Saharan Africa (SSA). An adoption model was developed focusing on contextual factors and constructs from two technology adoption theories. Structural equation modelling was used for data analysis and model validation. Results from 355 valid responses to a survey of information and communication technology (ICT) experts and decision makers at universities in SSA indicated that socio-cultural factors, results demonstrability, usefulness, and data security significantly impact their propensity to recommend adoption of cloud computing in the universities. The implications of the findings and practical contributions are discussed.

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References

  • Aaron, L. S., & Roche, C. M. (2011). Teaching, learning, and collaborating in the cloud: applications of cloud computing for educators in post-secondary institutions. Journal of Educational Technology Systems, 40(2), 95–111.

    Google Scholar 

  • Abubakar, A. D., Bass, J. M., & Allison, I. (2014). Cloud computing: adoption issues for sub-Saharan African SMEs. EJISDC, 62(1), 1–17.

    Google Scholar 

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

    Google Scholar 

  • Aker, J. C., & Mbiti, I. M. (2010). Mobile phones and economic development in Africa. The Journal of Economic Perspectives, 24(3), 207–232.

    Google Scholar 

  • Al-Gahtani, S. S. (2003). Computer technology adoption in Saudi Arabia: correlates of perceived innovation attributes. Information Technology for Development, 10(1), 57–69.

    Google Scholar 

  • Al-Jabri, I. M., & Sohail, M. S. (2012). Mobile banking adoption: application of diffusion of innovation theory. Journal of Electronic Commerce Research, 13(4), 379–391.

    Google Scholar 

  • Alsaif, M. (2013). Factors affecting citizens' adoption of e-government moderated by socio-cultural values in Saudi Arabia. Proceedings Of The European Conference On E-Government, 578.

  • Alshamaila, Y., Papagiannidis, S., & Li, F. (2013). Cloud computing adoption by SMEs in the north east of England: a multi-perspective framework. Journal of Enterprise Information Management, 26(3), 250–275.

    Google Scholar 

  • Asongu, S. A., & Nwachukwu, J. C. (2016). The role of governance in mobile phones for inclusive human development in sub-Saharan Africa. Technovation. doi:10.1016/j.technovation.2016.04.002.

    Article  Google Scholar 

  • Avgerou, C. (2010). Discourses on ICT and development. Information Technologies & International Development, 6(3), 1–18.

    Google Scholar 

  • Awamleh, R., & Fernandes, C. (2005). Internet banking: an empirical investigation into the extent of adoption by banks and the determinants of customer satisfaction in the United Arab Emirates. Journal of Internet Banking and Commerce, 10(1), 1–12.

    Google Scholar 

  • Awamleh, R., & Fernandes, C. (2006). Diffusion of internet banking amongst educated consumers in a high income non-OECD country. Journal of Internet Banking and Commerce, 11(3), 1–17.

    Google Scholar 

  • Bagchi, K., Cerveny, R., Hart, P., & Peterson, M. (2003). The influence of national culture in information technology product adoption. AMCIS 2003 Proceedings, 956–965.

  • Battaglia, M. (2008). Nonprobability sampling. In P. Lavrakas (Ed.), Encyclopedia of survey research methods (pp. 524–527). Thousand Oaks: SAGE Publications.

    Google Scholar 

  • Bellamy, M. (2013). Adoption of cloud computing services by public sector organisations. In Services (SERVICES), 2013 I.E. Ninth World Congress on Services (pp. 201–208). IEEE.

  • Blue, E., & Tirotta, R. (2011). The benefits & drawbacks of integrating cloud computing and interactive whiteboards in teacher preparation. TechTrends, 55(3), 31–39.

    Google Scholar 

  • Chin, W. W. (1998). The partial least squares approach for structural equation modelling. Modern methods for business research, 295(2), 295–336.

    Google Scholar 

  • Cho, V., & Chan, A. (2015). An integrative framework of comparing SaaS adoption for core and non-core business operations: an empirical study on Hong Kong industries. Information Systems Frontiers, 17(3), 629–644.

    Google Scholar 

  • Clark, L. A., & Watson, D. (1995). Constructing validity: basic issues in objective scale development. Psychological Assessment, 7(3), 309–319.

    Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New York: Academic Press.

    Google Scholar 

  • Commander, S., Harrison, R., & Menezes-Filho, N. (2011). ICT and productivity in developing countries: new firm-level evidence from Brazil and India. The Review of Economics and Statistics, 93(2), 528–541.

    Google Scholar 

  • Cresswell, K., & Sheikh, A. (2013). Organizational issues in the implementation and adoption of health information technology innovations: an interpretative review. International Journal of Medical Informatics, 82(5), e73–e86.

    Google Scholar 

  • Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks: Sage Publications, Inc..

    Google Scholar 

  • Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Thousand Oaks: Sage Publications, Inc..

    Google Scholar 

  • Daberkow, S. G., & McBride, W. D. (2003). Farm and operator characteristics affecting the awareness and adoption of precision agriculture technologies in the US. Precision Agriculture, 4(2), 163–177.

    Google Scholar 

  • Dahiru, A. A., Bass, J. M., & Allison, I. K. (2014). Cloud computing adoption in sub-Saharan Africa: an analysis using institutions and capabilities. In Information Society (i-Society), 2014 International Conference on (pp. 98–103). IEEE.

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

    Google Scholar 

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982–1003.

    Google Scholar 

  • Dawson, S., Heathcote, L., & Poole, G. (2010). Harnessing ICT potential: the adoption and analysis of ICT systems for enhancing the student learning experience. International Journal of Educational Management, 24(2), 116–128.

    Google Scholar 

  • Devarajan, S., & Fengler, W. (2013). Africa's economic boom: why the pessimists and the optimists are both right. Foreign Affairs, 92(3), 68–81.

    Google Scholar 

  • Dimelis, S. P., & Papaioannou, S. K. (2011). Technical efficiency and the role of ICT: a comparison of developed and developing countries. Emerging Markets Finance and Trade, 47(3), 40–53.

    Google Scholar 

  • Dubois, B. (1972). A cultural approach to the study of diffusion and adoption of innovations. In M. Venkatesan (Ed.), SV - proceedings of the third annual conference of the Association for Consumer Research (pp. 840–850). Chicago: Association for Consumer Research.

    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.

    Google Scholar 

  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behaviour: An introduction to theory and research. Reading: Addison-Wesley Pub. Co..

    Google Scholar 

  • Fong, M. W. L. (2009). Technology leapfrogging for developing countries (pp. 3707–3713). IGI Gobal: Encyclopedia of Information Science and Technology. Hershey.

    Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Google Scholar 

  • Frambach, R. T., & Schillewaert, N. (2002). Organizational innovation adoption: a multi-level framework of determinants and opportunities for future research. Journal of Business Research, 55(2), 163–176.

    Google Scholar 

  • Frank, K. A., Zhao, Y., & Borman, K. (2004). Social capital and the diffusion of innovations within organizations: the case of computer technology in schools. Sociology of Education, 77(2), 148–171.

    Google Scholar 

  • Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: an integrated model. MIS Quarterly, 27(1), 51–90. doi:10.2307/30036519.

    Article  Google Scholar 

  • Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101–107.

    Google Scholar 

  • Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: an organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185–214.

    Google Scholar 

  • Graham, L. S. (1956). Class and conservatism in the adoption of innovations. Human Relations, 9, 91–100.

    Google Scholar 

  • Guan, Y., & Liao, H. (2014). Socio-cultural influences on technology adoption and sustainable development. Proceedings of the 2014 Industrial and Systems Engineering Research Conference. Y. Guan and H. Liao, eds.

  • Gupta, P., Seetharaman, A., & Raj, J. R. (2013). The usage and adoption of cloud computing by small and medium businesses. International Journal of Information Management, 33(5), 861–874.

    Google Scholar 

  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Englewood Cliffs: Prentice Hall.

    Google Scholar 

  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.

    Google Scholar 

  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.

    Google Scholar 

  • Herbig, P., & Dunphy, S. (1998). Culture and innovation. Cross Cultural Management: An International Journal, 5(4), 13–21.

    Google Scholar 

  • Hinde, C., & Van Belle, J. P. (2012). Cloud computing in south African SMMEs: risks and rewards for playing at altitude. International Journal of Computer Science and Electrical Engineering, 1(1), 1–10.

    Google Scholar 

  • Hofsted, G. (1991). Cultures and organizations: Software of the mind. London: McGrawHill.

    Google Scholar 

  • Hofstede, G. (1983). National Cultures in four dimension:a research based theory of cultural difference among nations. International Studies of Management and Organizations, 13(12), 46–74.

    Google Scholar 

  • Hofstede, G. (1995). In Nakata, C. and Sivakumar, K. (1996), “National Culture and new product development : an integrative review”. Journal of Marketing, 60, 61–72.

    Google Scholar 

  • Hoftstede, G. (2001). Culture’s Consequences (Second ed.). Thousand Oaks: Sage Publications.

    Google Scholar 

  • Hu, N. Z., Lee, C. Y., Hou, M. C., & Chen, Y. L. (2013). A cloud system for mobile medical services of traditional Chinese medicine. Journal of Medical Systems, 37(6), 1–13.

    Google Scholar 

  • Kapoor, K. K., Dwivedi, Y. K., & Williams, M. D. (2015). Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service. Information Systems Frontiers, 17(5), 1039–1056.

    Google Scholar 

  • Kaufman, L. M. (2009). Data security in the world of cloud computing. IEEE Security and Privacy, 7(4), 61–64.

    Google Scholar 

  • Kedia, B. L., & Bhagat, R. S. (1988). Cultural constraints on transfer of technology across nations: Implications for research in international and comparative management. Academy of Management Review, 13(4), 559–571.

    Google Scholar 

  • Khajeh-Hosseini, A., Greenwood, D., Smith, J. W., & Sommerville, I. (2012). The cloud adoption toolkit: supporting cloud adoption decisions in the enterprise. Software: Practice and Experience, 42(4), 447–465.

    Google Scholar 

  • Kline, R. B. (2011). Principles and practice of structural equation modeling. New York: Guilford Press.

    Google Scholar 

  • Kondo, D., Javadi, B., Malecot, P., Cappello, F., & Anderson, D. P. (2009). Cost-benefit analysis of cloud computing versus desktop grids. In Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on (pp. 1–12). IEEE.

  • Kshetri, N. (2011). Cloud computing in the global south: drivers, effects and policy measures. Third World Quarterly, 32(6), 997–1014.

    Google Scholar 

  • Kundra, V. (2011). Federal cloud computing strategy. The White House: Washington D.C.

    Google Scholar 

  • Leidner, D. E., & Kayworth, T. (2006). A review of culture in information systems research: toward a theory of information technology culture conflict. MIS Quarterly, 30(2), 357–399.

    Google Scholar 

  • Li, S., Da Xu, L., & Zhao, S. (2015). The internet of things: a survey. Information Systems Frontiers, 17(2), 243–259.

    Google Scholar 

  • Lian, J. W., Yen, D. C., & Wang, Y. T. (2014). An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital. International Journal of Information Management, 34(1), 28–36.

    Google Scholar 

  • Lundvall, B. A. (2009). Innovation as an interactive process: user-producer interaction to the national system of innovation: research paper. African Journal of Science, Technology, Innovation and Development, 1(2), 10–34.

    Google Scholar 

  • Malhotra, N. K., Ulgado, F. M., Agarwal, J., Shainesh, G., & Wu, L. (2005). Dimensions of service quality in developed and developing economies: multi-country cross-cultural comparisons. International Marketing Review, 22(3), 256–278.

    Google Scholar 

  • Mbarika, V. W. A. (2002). Rethinking information and communications technology policy focus on internet versus teledensity diffusion for Africa's least developed countries. The Electronic Journal of Information Systems in Developing Countries, 9(1), 1–13.

    Google Scholar 

  • Mbarika, V. W., Musa, P. F., Byrd, T. A., & McMullen, P. (2002). Teledensity growth constraints and strategies for Africa's LDCs: "Viagra" prescriptions or sustainable development strategy? Journal of Global Information Technology Management, 5(1), 25–42.

    Google Scholar 

  • Mell, P., & Grance, T. (2011). The NIST definition of cloud computing (draft). NIST Special Publication, 800-145, 7.

    Google Scholar 

  • Meso, P., Musa, P., & Mbarika, V. (2005). Towards a model of consumer use of mobile information and communication technology in LDCs: the case of sub-Saharan Africa. Information Systems Journal, 15(2), 119–146.

    Google Scholar 

  • Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a world-wide-web context. Information & Management, 38(4), 217–230.

    Google Scholar 

  • Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.

    Google Scholar 

  • Musa, P. F. (2006). Making a case for modifying the technology acceptance model to account for limited accessibility in developing countries. Information Technology for Development, 12(3), 213–224.

    Google Scholar 

  • Nambisan, S., Agarwal, R., & Tanniru, M. (1999). Organizational mechanisms for enhancing user innovation in information technology. MIS Quarterly, 23(3), 365–395.

    Google Scholar 

  • Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.

    Google Scholar 

  • Oliveira, T., Thomas, M., & Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: an analysis of the manufacturing and services sectors. Information & Management, 51(5), 497–510.

    Google Scholar 

  • Olla, P., & Choudrie, J. (2014). Mobile technology utilization for social development in developing countries: an ethnographic futures research study. Information Systems Frontiers, 16(3), 369–382.

    Google Scholar 

  • Ozdemir, S., & Trott, P. (2009). Exploring the adoption of a service innovation: a study of internet banking adopters and non-adopters. Journal of Financial Services Marketing, 13(4), 284–299.

    Google Scholar 

  • Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students' behavioral intention to use e-learning. Journal of Educational Technology & Society, 12(3), 150–162.

    Google Scholar 

  • Pedersen, H. A. (1951). Cultural differences in the acceptance of recommended practices. Rural Sociology, 16, 37–49.

    Google Scholar 

  • Purkayastha, S., & Braa, J. (2013). Big data analytics for developing countries – using the cloud for operational BI in health. Electronic Journal of Information Systems in Developing Countries, 59(6), 1–17.

    Google Scholar 

  • Ringle, C. M., Wende, S., & Becker, J. (2015). SmartPLS 3. Hamburg: SmartPLS http://www.smartpls.com. Accessed 6 Sept 2015.

    Google Scholar 

  • Rogers, E. M. (1962). Diffusion of innovations. New York: The Free Press.

    Google Scholar 

  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: The Free Press.

    Google Scholar 

  • Rogers, E. M., & Shoemaker, F. F. (1971). Communication of innovations. New York: The Free Press.

    Google Scholar 

  • Sabi, H. M., Uzoka, F. E., Langmia, K., & Njeh, F. N. (2016). Conceptualizing a model for adoption of cloud computing in education. International Journal of Information Management, 36(2), 183–191.

    Google Scholar 

  • Sathyanarayana, T. V., & Sheela, L. (2013). Data security in cloud computing. In Green Computing, Communication and Conservation of Energy (ICGCE), 2013 International Conference (pp. 822–827). IEEE.

  • Seethamraju, R. (2015). Adoption of software as a service (SaaS) enterprise resource planning (ERP) systems in small and medium sized enterprises (SMEs). Information Systems Frontiers, 17(3), 475–492.

    Google Scholar 

  • Shane, S., Venkataraman, S., & MacMillan, I. (1995). Cultural differences in innovation championing strategies. Journal of Management, 21(5), 931–952.

    Google Scholar 

  • Somekh, B. (2008). Factors affecting teachers’ pedagogical adoption of ICT. In International handbook of information technology in primary and secondary education (pp. 449–460). Springer US.

  • Srinivasa, K. G., & Venkatesh, N. (2012). MeghaOS: a framework for scalable, interoperable cloud based operating system. International Journal of Cloud Applications and Computing (IJCAC), 2(1), 53–70.

    Google Scholar 

  • Steinmueller, W. E. (2001). ICTs and the possibilities for leapfrogging by developing countries. International Labour Review, 140(2), 193–210.

    Google Scholar 

  • Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, Series B (Methodological), 36(2), 111–147.

    Google Scholar 

  • Straub, D. W., Loch, K. D., & Hill, C. E. (2003). Transfer of information technology to the Arab world: a test of cultural influence modeling. In Advanced topics in global information management (vol. 2), (pp. 141–172).

  • Subashini, S., & Kavitha, V. (2011). A survey on security issues in service delivery models of cloud computing. Journal of Network and Computer Applications, 34(1), 1–11.

    Google Scholar 

  • Sultan, N. (2010). Cloud computing for education: a new dawn? International Journal of Information Management, 30(2), 109–116.

    Google Scholar 

  • Sumter, L. Q. (2010). Cloud computing: Security risk. In Proceedings of the 48th Annual Southeast Regional Conference (p. 112). ACM.

  • Teo, T. S. H., Srivastava, S. C., & Jiang, L. (2008). Trust and electronic government success: an empirical study. Journal of Management Information Systems, 25(3), 99–131.

    Google Scholar 

  • Thatcher, J. B., Srite, M., Stepina, L. P., & Liu, Y. (2003). Culture, Overload and Personal Innovativeness with Information Technology: Extending the Nomological Net. Journal of Computer Information Systems, 44(1), 74–81.

    Google Scholar 

  • Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington: Lexington Books.

    Google Scholar 

  • Uzoka, F. M. E., Akinnuwesi, B. A., Olabiyisi, S. O., & Demilade, A. (2012). An empirical study of potentials of adoption of grid computing as a vehicle for tertiary institutions collaboration. International Journal of Business Information Systems, 10(3), 245–263.

    Google Scholar 

  • Van der Schyff, K., & Krauss, K. E. M. (2014). Higher education cloud computing in South Africa: towards understanding trust and adoption issues. South African Computer Journal, 55, 40–55.

    Google Scholar 

  • Van Slyke, C., Belanger, F., & Sridar, V. (2005). A comparison of American and Indian consumers perceptions of electronic commerce. Information Resources Management Journal, 18, 24–40.

    Google Scholar 

  • Van Slyke, C., Lou, H., Belanger, F., & Sridhar, V. (2010). The influence of culture on consumer-oriented electronic commerce adoption. Journal of Electronic Commerce Research, 11(1), 30–40.

    Google Scholar 

  • Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: development and test. Decision Sciences, 27(3), 451–481.

    Google Scholar 

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425–478.

    Google Scholar 

  • Weerakkody, V., Irani, Z., Lee, H., Osman, I., & Hindi, N. (2015). E-government implementation: a bird’s eye view of issues relating to costs, opportunities, benefits and risks. Information Systems Frontiers, 17(4), 889–915.

    Google Scholar 

  • Xiong, H., Zhang, D., Zhang, D., Gauthier, V., Yang, K., & Becker, M. (2014). MPaaS: mobility prediction as a service in telecom cloud. Information Systems Frontiers, 16(1), 59–75.

    Google Scholar 

  • Yeboah-Boateng, E. O., & Essandoh, K. A. (2013). Cloud computing: the level of awareness amongst small & medium-sized enterprises (SMEs) in developing economies. Journal of Emerging Trends in Computing and Information Sciences, 4(11), 832–839.

    Google Scholar 

  • Zissis, D., & Lekkas, D. (2011). Securing e-government and e-voting with an open cloud computing architecture. Government Information Quarterly, 28(2), 239–251.

    Google Scholar 

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Sabi, H.M., Uzoka, FM.E., Langmia, K. et al. A cross-country model of contextual factors impacting cloud computing adoption at universities in sub-Saharan Africa. Inf Syst Front 20, 1381–1404 (2018). https://doi.org/10.1007/s10796-017-9739-1

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