This study examines how the concept of gender mainstreaming could influence the adoption of e-government services in Kenya, which like many other developing countries, the Kenyan e-government initiatives has faced a number of challenges since its inception. The study utilizes and expands on Technology Acceptance Model to explore the adoption of e-government services in the Siaya County of Kenya. A simple random sampling technique was used to select a sample size from the population and a questionnaire was used to collect data from the participants. Analysis of the demographic data was done to test the research hypothesis using descriptive statistics of frequency counts and percentage. The major findings of the study revealed that men are potential adopters of e-government services. This is exhibited by a positive correlation that was found after a regression done on gender in relation to E-government adoption. The findings of this study are meant to provide a better understanding of mainstreaming gender in order to engender the adoption of e-government services.

In the recent years, the demand for data processing has been on the rise prompting researchers to investigate new ways of managing data. Our research delves into the emerging trends of data management methods, one of which is the agent based techniques and the active disk technology and also the use of Map-reduce functions in unstructured data management. Motivated by this new trend, our architecture employs mobile agents technology to develop an open source framework called SPADE to implement a simulation platform called SABSA. The architecture in this research compares the performance of four network storage architectures: Store and forward processes(SAF), Object Storage Devices(OSD), Mobile agent with a Domain Controller (DMC) enhanced with map-reduce function and Mobile agent with a Domain Controller and child DMC enhanced with Map-reduce (ABMR): both handling sorted and unsorted metadata. In order to accurately establish the performance improvements in the new hybrid agent based models and map-reduce functions, an analytic simulation model on which experiments based on the identified storage architectures were performed was developed and then analytical data and graphs were generated. The results indicated that all the agents based storage architectures minimize latencies by up to 45 % and reduce access time by up to 21% compared to SAF and OSD.

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Improved ICT technologies have brought about massive online presence of users in the online space such as social media platforms as well as remote working tools. This has led to a massive mushrooming of online shops as they try to follow the changing behaviour of the customers. This has come about with an challenge of information overload since the customers have a myriad of alternatives at his disposal at the time of making a decision and indeed it is impractical for an average user to evaluate all the alternatives in a timely fashion, neither do some users know what to look at when evaluating an online vendor. This put the user at a risk of losing money due to potentially untrustworthy vendors masquerading as genuine shop owners online. In deed trust is a psychometric property which many at times is informed by past experience or social norms in a context aware fashion. In this study, we seek to identify the indicators of a trustworthy online vendor so the consumer can use these to estimate trustworthiness of an online vendor before committing to a purchase. We use focus group discussions and survey to uncover what majority of experienced shoppers consider before making a purchase online and share the indicators in order to help inexperienced shoppers get a footing without much exposure to risk, and also to help ecommerce platform developers and owners to align their services to the end user expectations.

Dynamic webservice composition is a promising ICT support service for virtual organizations. However, dynamic webservice composition remains a nondeterministic polynomial (NP) hard problem despite more than 10 years of extensive research, making the applicability of the technique to problems of industrial relevance limited. In [48], we proposed a layered method, SLUM, to combat the problem. Analytically, SLUM overcomes the relative weaknesses of two widely used approaches in the literature-the local planning (hereafter L-MIP) strategy and the Mixed Integer Programming (S-MIP) method. Despite the promising benefits of SLUM, it's unknown to what extent and under what circumstances SLUM is better or worse than L-MIP algorithms and S-MIP. The research objective of the study was to investigate the relative performance of SLUM w.r.t S-MIP and L-MIP using two performance criteria:-solution quality and CPU running time. Several randomly generated two task workflows of monotonically increasing hardness in the number of webservices per task were used to benchmark SLUM against the other two algorithms. A set of numerical and statistical techniques were used to experimentally compare the solution quality and the running time growth of SLUM against L-MIP and S-MIP. We determined that SLUM generates solutions with an average quality of 93% w.r.t the global optimum. Further, we show that SLUM yields solutions that are 5% more quality than L-MIP. On the other hand, we established that L-MIP outperforms both S-MIP and SLUM by multiple factors in terms of computational efficiency. However, we find that for problem instances with less than 22 webservices per task, S-MIP is about 1.3 times faster than SLUM. Beyond n=22, the running time of SLUM t eB , expressed in terms of the running time of S-MIP t eA , is given by t eB = t eA 0.78. We also establish that SLUM is asymptotically 3.6 times faster than S-MIP on average. We conclude that in order for a virtual enterprise broker to obtain maximum benefit from dynamic service composition, the broker should combine the three techniques in the following manner-(1) for service request without global constraints requirements, L-MIP is the most suitable method to use, (2) Where there is need for global constraints and the number of service providers per task is less than 22, S-MIP is most preferred and (3) in scenarios the number of service providers per task is more than 22 and there is a need to satisfy global constraints, SLUM is superior to both S-MIP and L-MIP.