IntroductionSub-Saharan Africa lags in adoption of mobile health (m-health) applications and in leveraging m-health for sustainable development goals. There is a need for a comprehensive investigation of determinants of hospitals’ adoption of m-health in Sub-Saharan Africa to inform policies, practices and investments.MethodsThis investigation used a logit regression model to analyze the determinants of m-health adoption in Kenyan hospitals applying the Technological, Organizational and Environmental (TOE) framework and the Diffusion of Innovation (DOI) theory. A representative sample of 211 executives of Level 4–6 hospitals in 24 counties provided primary data on Patient-Centered (PC) and Facility-Centered (FC) m-health applications.ResultsBoth PC and FC m-health adoption were predicted by competition for patients (PC p = 0.041, FC p = 0.021), IT human resource capacity (PC p = 0.048, FC p = 0.037), and hospital pursuit of market growth through technological leadership (PC p = 0.010, FC p = 0.020). Further determinants of PC m-health adoption included hospital access to slack financial resources (p = 0.006), acquisition strategy (p = 0.011), compatibility with the hospital systems (p = 0.015), trialability (p = 0.019), medical insurance company support (p = 0.025),patient pressure (p = 0.036), and perceived effect of global medical tourism (p = 0.039). FC m-health adoption was predicted by hospital size (p = 0.008), ICT infrastructure capacity (p = 0.041), and government support (p = 0.013).ConclusionA differentiated approach is required to scale up m-health adoption. PC m-health requires emphasis on establishing national and regional compatibility and interoperability, developing trialability processes and validation mechanisms, incentivizing patient competition and mobility, establishing innovative and cost-effective acquisition strategies, and ensuring integration of digital services within national insurance schemes and policies. These policies require support from patients and communities to drive demand and spur investment in adequate IT human resources to maintain reliability. Pilot PC m-health projects should prioritize hospitals with slack financial resources, while FC m-health should target large facility size. FC m-health applications are more complex and costly than PC, requiring government incentives to trigger hospital investments and national investment in ICT infrastructure. Investors and hospital managers should integrate m-health into market growth strategies for sustainable m-health scale-up in Kenya and beyond.

The research purpose was to examine the influence of available resources on organizational effectiveness. The research philosophy was positivism, with explanatory and descriptive research design espoused. The population was registered non-governmental organizations (NGOs), with the sample unit as the project managers. A questionnaire was used for data collection. Data analysis was executed using inferential and descriptive statistics. The descriptive analysis included standard deviation, mean and percentages, whereas inferential analysis included regression analysis and ANOVA. The study concluded that fundraising efforts and how funds are distributed to the various strategic activities and operations influence the level of efficiency in the organization process. Staff empowerment, negatively though, significantly influenced process efficiency. The recommendation is to develop an NGO organizational effectiveness ranking metric to allow the classification of NGOs into categories based on levels of effectiveness in achieving their respective missions and strategies. It was also the aim to carry out an in-depth study of why fundraising efforts in NGOs did not significantly influence stakeholder satisfaction.

Purpose: The purpose of this study was to establish how operational risk management strategies lead to growth of MFI sector in Kenya.Methodology: The study adopted a correlation survey research design. The population of this study was fifty seven (57) MFIs. The sampling frame was the list of MFIs provided in the AMFI website www.amfikenya.com. A sample of thirteen (17) MFIs was selected using the random sampling approach. A questionnaire and an interview schedule were the main data collection tools. Qualitative data was analyzed using content analysis whereas the quantitative data was analysed using Statistical Package for Social Sciences (SPSS) where descriptive and regression analysis were conducted to determine the relationship between enterprise risk management strategies and growth of MFIs.Findings: Findings revealed that the MFI had adequate policies and procedures to manage its operational risks and the MFI had an operations manual. The findings also indicated that the MFIs have adhered to written policies and procedures to manage operational risks in the financial operations area, procurement area, treasury area, and financial management area. Results further indicated that the MFI had effective internal control systems for detecting fraud or other significant operational risks. Finally the study findings indicated that MFI’s internal audit functions ensured effective use of resources, accurate financial reporting, and ample random spot checks of MFI branches, clients, and staff. The regression results indicated that there was a positive relationship between operational risk management strategies and MFI growth.Unique contribution to theory, practice and policy: The study recommends that the MFIs to continue practicing effective operational risk management practices such as internal control framework comprising of policies and procedures. MFIs need to uphold the existence and accessibility of operational manuals. It is suggested that adherence to written policies and procedures is positive strategy and it should be emphasized.  The internal audit functions for effective use of resources and accurate financial reporting needs to be emphasized as it had a positive effect on growth. The MFIs should also benchmark their technology with that of banks to reduce human error, to produce timely and relevant data. It is recommended that implementation of know your client (KYC) requirements should be enhanced as it has an effect on growth.

Purpose: The purpose of this paper was to investigate the price and non-price determinants of demand for air passenger transport among selected airlines.Methodology: The study target population was airlines across the World. The study used a sample of 10 airlines across the World. The airlines included; British Airways, Ethiopian Airways, Emirates , Qatar Airways, Turkish Airlines, South Africa Airlines, China Southern Airlines, Kenya Airways, Egypt air and Air France. Secondary data of the selected airlines was collected from the International Air Transport Association (IATA) for the period from 2005 to 2014. The data collected was analyzed using STATA software to generate descriptive, trends and inferential statistics which were used to derive conclusions and generalizations regarding the population. The panel data regression model was used to determine the relationship between study variables.Results: Based on the findings, the study concluded that both domestic and global interest rates have a negative and significant effect on demand for air passenger transport. Further, the study concluded that GDP growth (domestic), GDP growth (global) and GDP per capita have a positive and significant effect on demand for air passenger transport.Recommendations: Based on the findings, the study recommended that, at a macro level, airlines should consider adjusting their travel prices using the directional movements of the above mentioned variables as a guideline. Based on the findings, the study recommended that governments should use the study of demand drivers to forecast their capital investment plan for the improvement of the air transportation systems in their respective countries and design policies that require use of the demand drivers observed in this study for planning of aviation infrastructure expansion.