Kenya Methodist University crestKENYA METHODIST UNIVERSITYDigital Repository
 

Master of Science in Computer Information Systems

Permanent URI for this collectionhttp://41.89.31.6:4000/handle/123456789/74

Welcome to Master of Science in Computer Information Systems collection

Browse

Filters

2021 - 20222

Settings

Subject: search.filters.subject.Small and medium enterprises

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Predictive Analytics Model for Small and Medium Enterprises in Kenya, Forecasting on Supply and Demand
    (KeMU, 2022-10) Mureithi, Mburu John
    Predicting business operations is a critical task for small and medium enterprises (SMEs). With increased unpredictability in the business environment, small enterprises find themselves in the receiving end simply because they do not have the tools in decision-making like their counterparts who have established business decision-making tools. With increased use of ICT, SMEs can now tap into the power of data to support decision-making. Transactional data like sales, purchases, payments, service requests, invoices, purchase orders, delivery notes, repairs, and maintenance notes are collected by SMEs and are readily available. Currently, SMEs in Kenya have limited on non-existent quantitative forecasting systems in place, predictive analytics is a preserve of well-funded, large, well-established or international companies. SME owners can now benefit from the power of predictive analytics in areas like sales, purchases, business lead generation, recommendations systems, and risk prediction. With predictive analytics, SME owners can have added confidence in decision-making to help propel their business to successful ventures. Predictive analytics algorithms like clustering algorithms, linear regression, and classification algorithms can be used to aid SME owners and managers gain insights into their business by identifying relationships and associations between the various variables in their business or identification of trends. SMEs in Kenya, have in the past run out of business due to wrong decisions associated with lack of information regarding their customers, their business, or the business sector as a general. SMEs' contribution to Kenya’s GDP growth is vital and the use of technology and ICT could mitigate the challenge of access to information that SMEs have. The use of technology to predict business operations and performance is the next frontier in ensuring business sustainability, job security, and a good business environment. This research aimed to solve this information gap by designing a demand and supply forecasting model that equips SME owners and managers with insightful information about the demand and supply of the products they are selling, helping them make informed decisions based on their sales and purchase data. The study was carried out on five (5) SMEs in Nairobi and Muranga who had access to ICT infrastructure and had some knowledge of digital book-keeping methods but had no forecasting or prediction systems in place. A fully functional web passed demand and supply forecasting model accessible via a browser was designed. A beta test was conducted by the five respondents with positive feedback. The majority of the respondents, as the study found out, derived great value from forecasting their demand and supply and were able to stock right and meet their clients’ needs better, the forecasting model was developed using the agile prototyping method of software development with cascading style sheets (CSS), hyper-text markup language (HTML), react graphical user interface and an R based forecasting engine. The designed system allowed the users to interact with a user-friendly graphical user interface on either a mobile device or a computer allowing more freedom and flexibility in accessing the platform. It allowed SMEs to upload their sales and purchase data in a predefined format that the forecasting model consumes and provide accurate demand and supply forecasts and provided forecasting accuracies in the 95% quartiles for all the SMEs sampled. The model was evaluated by the same SMEs with 100% of them indicating that they would be relying on the forecasting model for all future forecasts. The designed model allows SMEs to benefit from the demand and supply forecasts irrespective of its sector and the type of enterprise engages in.
  • Thumbnail Image
    Item
    Framework for Adoption of Cloud Computing by Small and Medium-Sized Enterprises in Meru County.
    (KeMU, 2021-03) Odero, Eunice Achieng
    Cloud Computing is a technology that has emerged in the market and it is widely used across the world for data processing of information and storage capability. It is a growing trend and is seen as a game-changer to SMEs business growth and development as far as technology deployment and usage is concerned. Organizations everywhere are trying to leverage Cloud Computing to achieve business missions and goals. Many believe it's just a marketing strategy while others see it as a benefit on how information technology is delivered. In the case of Kenya, many SMEs are still struggling to survive in an on-going global business cycle for growth and development. Cloud Computing on the other hand offers many opportunities that can help such SMEs improve their business and use technology more efficiently and effectively to reduce the cost of equipment and services. The main objective of the study was to develop a framework for the adoption of Cloud Computing by SMEs, covering: identification of usage, challenges and decision making support in the process of Cloud Computing adoption. The usage of Cloud Computing is still low among SMEs in Meru County mainly because of lack of expertise to give them training. Moreover, Cloud Computing adoption is impeded by the competing interest to deal with challenges such as poor network connectivity, need to ensure ease of use, ensure manageable cost implications and competition. The study developed a framework for adoption of Cloud Computing to be used by SMEs in Meru County. The theoretical underpinning of the framework is based on the theories of reasoned action, technology acceptance model and interplay of technology, organization and environment among others. A descriptive research design was adopted in conducting this study and stratified sampling was done covering the various players in the adoption process who included ICT managers, business owners and consultants. The data analysis was both qualitative and quantitative, the data analysis tools used included a laptop and SPSS software. A survey was carried on SMEs within Meru County. Primary data was analyzed to show the relationship between independent and dependent variables. This study ensured that all ethical considerations such as confidentiality, privacy and integrity were observed. The results in this study shows that decision making, application used and the type of model used are the major factors to be considered for adoption. A framework was proposed that SMEs can adopt and reap the benefits of a systematic adoption of Cloud Computing. This framework is from the results of this study and it has been demonstrated that SMEs and other stakeholders will achieve cost cutting, reduced timeframes in embracing technology and enhanced fit in the technology ecosystem that the SMEs operate in. The study focused on storage of data.