Adoption and diffusion of cloud computing in the public sector A case study of Zambia. Shuller Habeenzu ITMC/RIA Focal Point-Lusaka

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Adoption and diffusion of cloud computing in the public sector A case study of Zambia Shuller Habeenzu ITMC/RIA Focal Point-Lusaka

Zambia : A brief Overview Rapid and youthful population growth Poverty levels deepening in rural areas high Gini coefficient Increasing budgetary constraints to meet social needs Lack of fiscal discipline unknown external debt exposure Significant fiscal deficits Government introduces excise duty on data bundles sept 2017 ( same as airtime) Increasingly, government required to deliver more for less

Smart Zambia Initiative (launched Dec 2015)

Smart Zambia Initiative A Digital Transformation Agenda

Smart Zambia Institute to coordinate SZ Office of the President Ministry of Communications and Transport Industrial Development Corporation Smart Zambia Institute ICT Sector Policy ZICTA (Regulator) Telecommunications Industry Zambia ICT College Zambia National Data Centre (SVP)

Cloud Computing Platform Smart Zambia Initiative is predicated on cloud computing Zambia National Data Centre to host the government cloud No definitive budget figures (part of an estimated cost US$65m debt financed package) for Smart Zambia Phase 1 Smart Zambia Phase 2 extending national backbone and metros to all districts (lowest government administrative centres) Address digital-divide: Roll-out 1000+ LTE base stations by 2012 (through state-owned Zamtel) Government favours big-bang approach rather than gradual progression

Research Objectives Highly useful for policy makers to gain insights into the diffusion patterns of cloud computing in the public sector in Zambia. To provide the much needed research support for ongoing cloud computing implementations in Zambia and other developing countries (action research).

Research Questions What are the contextual factors that are influencing the adoption and usage of cloud computing (in the public sector public sector) in Zambia and in which way? (predictive) What policy or strategy interventions that need to be considered to induce adoption of cloud computing in Zambia? (action research)

Literature Review Most studies have explore the importance of the technological factors affecting cloud computing adoption. However, the influences of environmental and organisational factors on cloud computing adoption vary across different environments. Therefore, there is a need to analyse the determinants of cloud computing adoption in different sectors to acquire a better understanding of cloud computing adoption. Feasible to apply the Rogers DOI theory and technologyorganisation-environment (TOE) framework to explore the cloud computing adoption.

Rogers Theory of Innovation and TOE Model Management Concerns Relative Advantage Compatibility Legal Issues IT Alignment Complexity Rate of Cloud Adoption Trailability Risks Security Issues & Trust Observability Theoretical and empirical factors operating on the rate of adoption. [Adapted from (Kuiper et al. 2014)]

Approach Cloud Computing is a nascent industry in the public sector Complex adaptive system Lack of historical data or perspective - limited experience and data Technology Adoption/acceptance Theories Rogers Theory of Diffusion of Innovation (DOI) Technology, Organisation and Environment (TOE) & Exploratory and predictive approach Structural equation modelling - a multivariate statistical analysis technique used to analyse structural relationships between measured variables and latent constructs.

Proposed Research Model & Hypotheses Technological Factors H 1 (+): Relative Advantage H 2 (+): Compatibility H 3 (-):Complexity H 4 (+): Trialability Organisational Factors H 5 (+):Technology Readiness H 6 (+): Top Management Support H 8 (+): Cloud/IT skills H 54 (+): Security & Privacy Intention to Adopt Cloud Computing DEMOGRAPHIC FACTORS Age Gender Education Position/Role Experience 11 Constructs 45 Survey Items Environmental Factors H 10 (-):Policy and Legal Issues H 12 (-): Risks H 14 (+): Government Support

Data Collection and Analysis Face-to-face Interviews with Smart Zambia senior management Structured Questionnaire Sample population drawn from Smart Zambia technical staff Data collection (and validation) - an ongoing process Preliminary descriptive data analysis -

Selected preliminary findings Perceived Challenges by Smart Zambia Management: Sustainability Draft Policy Framework : Lack of policy framework (no public documentation on Smart Zambia ) Funding based on external funding unknown budget Procurement single sourcing and non-transparency Technical obsolesce /lock-in Human Resource Capacity constraints -(60% of key staff above 41 years or above) Lack of business case analysis ( top down command structure)

Policy and regulatory frameworks Strongly Disagree Strongly Agree

Lack of Policy and privacy laws Strongly Disagree Strongly Agree

Incentives to adopt Strongly Disagree Strongly Agree

Pressure to adopt cloud computing Strongly Disagree Strongly Agree

Job Opportunities Strongly Disagree Strongly Agree

Leadership Strongly Disagree Strongly Agree

Organisational IT readiness Strongly Disagree Strongly Agree

Organisational Readiness Strongly Disagree Strongly Agree

Capacity development Strongly Disagree Strongly Agree

Top Management Support Strongly Disagree Strongly Agree

Pressure to Implement Strongly Disagree Strongly Agree

Security Strongly Disagree Strongly Agree

Immediate Next Steps Revisit model with a view towards KISS (Keep it simple and sweet) Address data gaps Face-to face Interviews with IT Managers in Ministries (triangulation) Data collection (Survey Questionnaire) Data Validation Revisit sample population with a view to determine useful respondents Inferential Data Analysis Structural equation modelling (SEM-PLS) allows testing and estimating complex cause-effect (causal) relationships among multiple independent and dependent constructs simultaneously