Creating Community Based Environmental Awareness with Social Media: A Kenyan perspective

One of the roles of community education is keeping citizens more informed on the need to conserve their environment. However, for this to be effective in the digital era, the use of modern communication tools is required to keep pace with current technological developments. One of these tools is social media, which is enormously popular and is used by both individuals and organisations for online communication. This paper analyses the role of social media in community-based organisations (CBOs) in creating environmental awareness through community education in Kenya. A non-probability sample comprising nine CBOs in Nakuru City was used to explore activities focused on environmental issues. Data were collected and analysed from a total of 98 respondents who participated in an online survey. It was concluded that the use of social media for environmental awareness in CBOs was minimal, but there is potential in its use as a social learning environment for creating environmental awareness. The study recommends capacity building and open online communication as a means of promoting the use of social media in creating environmental awareness through community education programmes. Keywords: environmental management, environmental awareness, community based organisation (CBO), community education, social medi

Modeling Insurance Returns with Extreme Value Theory (A Case Study for Kenya’s Fire Industrial Insurance Class of Business).

Most General insurance companies have faced huge losses arising from fire industrial class of business .It is for this reason this study uses extreme value theory approach to model these returns. Traditionally normal distribution was applied and could not capture rare events which caused enormous losses. Kenya’s Fire industrial insurance data for five insurance companies and average for entire industry was read into R program .The objective was to plot the time series data.  The time series plots aimed to capture the trend and the behavior of the returns over a seven year period. The returns were then standardized in order to transform the negative returns. Using fExtremes in R, the mean excess plot was obtained which helped in measuring the shape of the distribution in the tail. The returns were fitted in a GPD Model in which the excess distribution and the tail of the underlying distribution were obtained over a chosen threshold. These were significant in capturing the values that exceeded the threshold. They were found to be a smooth curve which implied the GPD fit was a good for the data. Scatter plot was obtained and a solid line was observed in the scatter plot which was the smooth of the scattered residuals. QQ plots were also obtained and followed linear form which implied that the parametric model fitted the data well. VaR estimate was finally obtained using extreme value method. The log log empirical distribution was also obtained and indicated how the data points were distributed. After the excesses over a high threshold were fitted to the GPD, parameters were estimated which were used to estimate VaR at different confidence intervals. Key words: Extreme Value Theory, Peak Over Threshold, Generalized Pareto Distribution, Value at Risk.

An exploratory study of online internal communication within an employee relationship management approach: A Kenyan case study

The aim of this study was to explore the adoption of online communication tools (OCTs) by employees and managers of a public sector organisation in Kenya in a bid to build relationships in the workplace. Online internal communication (OIC) is gaining more prominence in public sector organisations in Kenya owing to the recognition of its positive effects on sound employee relationships. Strong employee relationships are essential to enhance not only the competitive advantage, but also the productivity of organisations. It is for this reason that public sector organisations in Kenya have increasingly adopted various OCTs and channels to enhance employees’ interactions and engagement. Consequently, a qualitative research approach was adopted. Primary data was collected through focus group discussions and in-depth interviews and analysed in accordance with a well-known qualitative data analysis approach. The key findings in this study identified the lack of training, open communication, involvement, motivation and trust as some of the factors affecting employee relationship management (ERM) in an online setting. The findings provide deeper insight into the degree to which employees are using OCTs for relationship building in a public sector organisation, which could be used as a heuristic for similar organisations

Ordinal logistic regression versus multiple binary logistic regression model for predicting student loan allocation

This paper examines two different methodologies to a classification problem of higher education loan applicants. The paper looks into the allocations made by the Higher Education Loans Board (HELB) relative to the economic status of the applicant. In this article, we modeled Higher Education Loans Board (HELB) loan application data from three public universities to determine whether the loan was allocated based on the needs of the respective applicants. The data was classified into two natural categories of those not allocated the loan (0) and those allocated the loan (1). This paper classified further to consider the amounts awarded by theHELB. This was possible since we observed that HELB loans were awarded indistinct categories (Kshs 0, Kshs 35,000, Kshs 40,000, Kshs 45,000, Kshs 50,000), Kshs 55,000 Kshs 60,000). In this study, we used ordinal logistic regression and multiple binary logistic regressions in classifying the applicants into the identified categories. The models were generated that included all predictor variables that were useful in predicting the response variable. This study found that HELB allocate a loan amount to Kshs 40,000 but anything behold Kshs 40,000 is based on information provided by an applicant. The study revealed that the loans were not awarded based on the need of respective applicants. This has led to misclassification when allocating loan. The study found that wealth and amount of fees paid for siblings were other factors that could be considered to identify needy applicants. This results show that an ordinal regression model gives  accurate estimates that can enable HELB make a viable awarding decision. It is expected that proper determination of the most accurate model will go a long way in minimizing the number of mis-classifications when awarding HELB loan. The study raises questions on the criteria used by HELB in loan allocation but further studies may be commissioned to confirm or  disapprove our findings. Key words: regression, logistic, binary, ordinal; higher education, loa

Employees of Kenya power's perceptions of their adoption and implementation of online internal communication tools for relationship building

The purpose of this study was to explore and describe Kenya Power employees’ perceptions of their adoption and implementation of online internal communication tools as a means of creating and managing long lasting relationships among all employees in the organisation. The theoretical point of departure for this study was framed within online internal communication and relationship management while principles of e-government were also considered. A single case study design was adopted for the study which combined both quantitative and qualitative data collection techniques while data was triangulated using an online self-administered questionnaire, focus group moderator’s guide and an interview schedule. The results guided by the theoretical criteria indicate that the implementation of online internal communication tools was done at Kenya Power without considering the internal stakeholders’ needs and preferences. The consequence is that employees have developed negative perceptions about internal online communication resulting in low adoption for relationship management activities. The findings of this study could be useful for other public sector organisations in that it will help them to positively change employees’ perceptions as well as enhance the implementation and adoption of internal online communication tools for the purposes of relationship building which could result in better internal communication and public sector services.Communication ScienceM.A. (Communication

Modeling inflation in Kenya: Comparison of SARIMA and Generalized Least Squares models

One desire by the policy makers in a country is to have access to reliable forecast of inflation rate. This is only achievable if the right model with high predictive accuracy is used. In this paper, seasonal auto regressive integrated moving average (SARIMA) and Generalized Least Squares regression models are developed to predict Kenya's inflation using quarterly data for the period 1981 to 2013. SARIMA (0,1,0)(0,0,1)4 was chosen as the model with the least Akaike Information Criterion and Bayesian Information Criterion. The parameters were then estimated. The residuals were checked to find out if they follow a white noise process by using residual Q-Q and normality test plots. The Test for normality of residual was also done. Given the high p-values (0.0639237) associated with the statistics as compared to 0.05, we fail to reject the null hypothesis that an error is normally distributed in this residual series. Thus, we conclude that the model provides an adequate fit for the data. In an effort to improve this, inflation was also modeled using Generalized Least Squares regression model.. The data was first checked for heteroscedasticity using the Breusch-Pagan test. Based on the p-value=0.000, which is less than alpha (of 5%), we conclude that there is substantial amount heteroscedasticity in the data. A regression model that forecasts inflation using its lags was constructed. The residuals were checked for normality using q-q plot. Additionally, the Shapiro-Wilk normality test was carried out. Its p-value was 0.08178 and since its greater than 0.05, its concluded that the residuals does not deviate from normality A comparison was made on the predictive ability of both models. SARIMA (0,1,0)(0,0,1)4 model had the least values of MAPE, MAE and RMSE with the corresponding values given by MAPE=14.155, RMSE=0.2871and MAE=0.23692 Keywords: SARIMA, Generalized Least Squares, Akaike Information Criterion ,Bayesian Information Criterion, Shapiro-Wilk normality test and Breusch-Pagan tes

Addressing Sanitation Challenge in Poor Urban Areas through Sustainable Technologies, Gender Integration and Supportive Policy Framework

This successful project developed delivery mechanisms for gender responsive water and sanitation services, and influenced regulatory and policy frameworks in East Africa (Kenya and Uganda). Given that women are traditionally responsible for provision of water and sanitation at the household level, but have no input into infrastructure design and policy, they are particularly affected by lack of services. Partnerships with WSUP, NETWAS and UN HABITAT contributed a great deal of success to the project. Water and sanitation development must be accompanied by adequate training and capacity building that ensures proper management and sustainability of any interventions

Role of Top Management Support in Health Workforce Performance: A Cross-Sectional Survey in ISO 9001:2008 Certified Kenyan Public Health Hospitals

This study sought to establish the role of Top Management Support in health workforce performance in the Kenyan public health sector among the ISO 9001:2008 certified hospitals. Poor performance of health workers poses a major challenge for improving service delivery in developing countries like Kenya and leads to inaccessibility of care and inappropriate care, which thus contributes to reduction in health outcomes as people are not using services or are mistreated due to harmful practices. Few studies have investigated the effect of Top Management Support in ISO 9001:2008 certified hospitals on outcomes such as health workforce performance especially in Kenya. The research design adopted for this study was cross-sectional survey. Survey questionnaires were used to collect quantitative data. Data obtained was analyzed qualitatively through factor analysis, descriptive analysis, correlation analysis and regression analysis. The study found that top management support was a significant predictor of health workforce performance. The general conclusion that was drawn from the study findings is that Top Management Support in ISO 9000:2008 certified hospitals plays a significant role in health workforce performance. The study recommends that the Kenyan Government should consider facilitating other public hospitals to be ISO 9001:2008 certified because the study showed that Top Management Support in ISO 9001:2008 certified hospitals has led to better health workforce performance. Keywords: Top Management Support, ISO 9001:2008 Quality Management System, Health Workforce performanc

Antidiabetic Properties of <i>Bidens pilosa</i> and Its Polyacetylenic Compounds for Management of Diabetes:Systematic Review

Bidens pilosa is a member of the Asteraceae family that is widely distributed across the tropics. It has been utilized by different communities both as food and medicinal herb. This plant and its polyacetylenic compounds hold potential as a natural antidiabetic intervention that can be used to combat this global public health problem. Bioactive compounds found in this plant constitute promising interventions for combating obesity which is a major risk factor for the development of type 2 diabetes. These phytocompounds can work independently or synergistically to modulate appetite, lipase activity, adipogenesis and adipocyte apoptosis. However, the efficacy, mode of action and scope of management of diabetes by these compounds remains elusive. The current review aims to summarize data on efficacy in the management of diabetes, an antidiabetic candidate polyacetylenic compound and possible biological activities as an antidiabetic agent from the available literature. Much emphasis has been directed to cytopiloyne as a representative of polyacetylenic compounds extracted from Bidens pilosa and its activity on diabetic animal models. The majority of the studies conducted on animal models described antidiabetic mechanisms that range from hypoglycemic to secretagogue activity of cytopiloyne in a dose-dependent manner. A clinical trial pilot indicated improved glycemic control of Bidens pilosa formulation among diabetic patients in the study. Bidens pilosa and its compounds are highly potent antidiabetic agent(s) that should be graduated to an intervention for management of diabetes through pre-clinical and clinical trials to elucidate its efficacy and safety