In an era of globalization, deregulation, increasing competition, new technologies and ecommerce, organizations are finding it harder to compete. Firm is said to be competitive when it develops and exploit their own unique resources and capabilities than to be excellent in how it imitates the resources and capabilities of other firms. The objective of the study was to examine the influence of technological innovation on competitiveness of universities in Nakuru, Kenya. More specifically, the study determined the influence of online teaching platforms and smart boards on competitiveness of universities in Nakuru, Kenya. The study was guided by Technology Acceptance Model. The study used descriptive research design. The target population of the study was 62 staff in six campuses in Nakuru town of diverse universities serving as chair of departments, registration staff, and director of online learning from universities in Nakuru town Kenya. Due to the low number of the target population a census method was used to select the sample members to be used in the study. In this context a sample size of 62 respondents was used for the study. Questionnaires structured in a 5-point Likert scale were used for data collection. Questionnaires were tested for reliability and validity. Cronbach alpha coefficient was used to indicate the reliability of the research instrument. The collected data was analyzed using Statistical Package for Social Sciences (SPSS) software. Data was analyzed using descriptive statistics which included frequency, chi square, correlational analysis and regression analysis.The study concluded that online teaching had a positive and significant relationship with the competitiveness of the universities. The study concluded that smart boards had a positive and significant relationship with the competitiveness of the universities. The study recommended that, management information systems, online teaching platforms should be considered as items for ensuring competitiveness of universities in Nakuru. In particular, the universities should focus on management information systems and online teaching platforms. The role of the diverse aspects of technological innovation should be examined in a holistic manner in diverse aspects of student life facets to examine on how they influence competitiveness of those universities.

This research was aimed at examining the pathogenic bacteria in both pasteurized and raw milk in Shendam L.G.A. Plateau State, Nigeria. A total number of thirty (30) samples 25ml each of both raw and pasteurized milk were obtained randomly and examined using white side test, dye reduction test and biochemical test such as oxidase, catalase, coagulase, indole and sugar fermentation test for confirmation. The results show that 24 (86.7%) were contaminated with Staphylococcus aureus when tested with the White Side Test. Based on the quality of the milk, Shimankar and Ndyak had the poorest handling practice. The bacteria load, showed highest count of 140 X 103 in Shimankar’s vendor and lowest count was recorded in raw milk in Kalong. The morphological and biochemical identification revealed that fivemicroorganisms namely; Staphylococcus aureus, Salmonellaspp,Klebsiellaspp.,Shigella dysentriaeand Streptococcusspp. Salmonellaspp. was the highest with 14(46.7%) while the least was Streptococcusspp. with 2(6.6%). This study showed that pathogenic bacteria were associated with both raw and pasteurized milk in the studied area. The prevalence of these pathogens in milk sampled could be associated with the occurrence of diseases such as mastitis, poor storage, poor hygiene of milkers and retailers. Goodhealth condition of cow,processing and hygiene practices are hereby recommended.  

This study examined the effect of oil price volatility on unemployment in Nigeria for the period of 1981 to 2016. The study employed Non-Linear Autoregressive Distributed Lags model (NARDL) to analyse the effect of oil price volatility on unemployment in Nigeria while Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH) was used to compute oil price volatility. The pass-through effect of oil price volatility on unemployment in Nigeria was however evaluated with the aid of a structural Vector autoregressive (SVAR) model. The study found that negative oil prices changes have a significant effect on unemployment rate in Nigeria in the short run. Also, the effect of oil price volatility is transmitted to GDP and subsequently to unemployment rate in Nigeria only in the long-run. The study concludes that oil price volatility has an indirect effect on unemployment in Nigeria. The study therefore, recommends that to minimize the problem of unemployment in Nigeria, it is necessary to cut dependence on oil and explore other alternatives to achieving economic growth and job creation in Nigeria.