Browsing by Author "Ogot, Madara"

Now showing 1 - 7 of 7
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    AfricArXiv, Diamond Open Access, Sustainability & Funding
    (2023-10-26) Havemann, Jo; Ogot, Madara
    Presentation held at the II DIAMOND OPEN ACCESS CONFERENCE, October 25 - 26, 2023. Toluca, Mexico Plenary session: Sustainability and funding of diamond open access Capacity building and sustainable finances will be important for the future development of diamond open access. This session discusses how we can further strengthen, sustain, and fund a diamond open access scholarly communication model.
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    Emerging Digital Technologies Ecosystems in Kenya and South Africa: States of Maturity 2023
    (University of Nairobi and University of Johannesburg, 2023-09) Ogot, Madara; Hanlin, Rebecca; Muthee, Margaret; Mlilo, Wandile; Njunguna, Samuel
    Data generation is growing exponentially, driven by the rapid increase in devices such as mobile phones, computers, sensors, etc., connected to the Internet and thus to databases. The new data sources and technologies (e.g. machine learning algorithms) "can identify patterns in observed data, build explanatory models, and make predictions quicker and with more accuracy than humans". Emerging digital technologies (EDT) and X-Data-based applications, for example, have been used to develop mitigation measures against Malaria, Zika, and Dengue Fever in India, identify lower-priced generic drugs in South Africa (SA) and tackle flooding in Indonesia. However, these algorithms are mainly created in developed countries and often lack transparency arising from intellectual property rights, thus hindering the realisation of the enormous potential EDT/X- Data-based applications have in addressing socio-economic challenges faced by developing countries, where data literacy levels are also often insufficient to leverage on data-driven approaches fully. In addition, where applications do exist, they are often not broadly accessible, especially for vulnerable and marginalised groups and persons with disabilities in areas with slow internet connections. This study unpacks the generic term "big data" into four overlapping categories of data: big data, open data, user-generated data and real-time data, and collectively refers to them as "X-Data". Reaping the full benefits of X-Data requires the development of supportive systems, including more approaches to collect, aggregate, analyse, and visualise data, as well as building the capacity of communities involved in data generation, governance, and usage. Such systems are often limited or absent in developing countries, thus creating new digital divides between developing and developed countries. Whereas the access to technology gap is narrowing, gaps in social integration and the impact of technology are increasing. Further, barriers persist in the use and uptake of X-Data by decision-makers, including competing data sources, quality of data, limited awareness of data existence, and inadequate transformation of data into useful information or tailoring it to match decision-makers needs. EDTs are often used together and include artificial intelligence (AI), blockchain, Geographic Information Systems (GIS), Internet of Things (IoT), and big data analytics. AI includes systems, techniques and methods that incorporate human-level intelligence at much faster speeds, for example, data mining (including artificial neural networks, Bayesian networks and support vector machines), machine learning, natural language processing, computer vision, and expert systems. Collectively, they provide enhanced data analytics, better decision-making, and improved predictive analysis. Kenya and South Africa have for the past few years ranked high in Sub-Saharan Africa (Kenya: 4/41 in 2020 and 3/41 in 2021 and 2022; and South Africa: 2/41 in 2020, 2021 and 2022) and reasonably well globally (Kenya: 71/172 in 2020, 78/160 in 2021 and 90/181 2022; and South Africa: 58/172 in 2020, 68/160 in 2021 and 68/181 in 2022) on the Government AI Readiness Index. The index evaluates how ready a government is to implement AI in delivering public services. However, the Sub-Saharan African countries have the lowest average scores on households with internet access and the cost of the cheapest internet-enabled device relative to Gross Domestic Product (GDP) per capita. The definition of GIS is a computer system for capturing, storing, checking, and displaying data related to positions on Earth's surface. GIS can show different data types on one map, such as streets, buildings, and vegetation, enabling easier visualisation, analysis, and understanding of patterns and relationships. The hardware and software systems incorporate many data types, including cartographic, photographic and digital data. Big data combines structured, semi-structured and unstructured data collected by organisations. Big data analytics mines this data for information for machine learning projects, predictive modelling, and other advanced analytic applications to create value. Characteristics include great variety, high volume and the need for faster processing times. Blockchains are decentralised databases that permanently, without third parties, record user transactions. The transactions are cryptographically chained (thus cannot be altered) and shared with the linked users. A definition of IoT is a network of things embedded with sensors, software, and other technologies. They connect and exchange data with other devices and systems through the Internet. Using low-cost computing, the internet cloud, big data analytics and mobile technologies, physical objects (ranging from everyday household appliances to complex industrial applications) can share and collect data with minimal human intervention. This study took a deep dive into and assessed the maturity level of the EDT ecosystems in Kenya and South Africa, focussing on their applications in the context of X-Data. It builds upon the United Kingdom (UK), Foreign Commonwealth Development Organization (FCDO) – Funded project, Emerging technologies in Kenya and South Africa - A Landscape Analysis.
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    Generic Competitive Business Strategies and Performance of Micro and Small Enterprises in Nairobi: An Empirical Validation of the MSE Typology
    (University of Nairobi, 2014-11) Ogot, Madara
    Competitive business strategy typologies classify business strategies based on common elements and provide a framework for gaining competitive advantage in the market. In Sub-Saharan Africa, it is estimated that the informal sector, mainly consisting of micro and small enterprises (MSEs) accounts for approximately 90% of all new jobs and up to 85% of total employment. In Kenya, the significance is evident in that the sector employs approximately 8.8 million people or 81.1% of those employed. In Nairobi, informal manufacturing MSEs have sprung up in clusters in areas that have combinations of high vehicular and human traffic, high populations densities, as well as transport arteries. Despite the significant role informal sector MSEs play in Sub-Saharan Africa national economies, few transition to formal medium or large size enterprises due to a wide array of challenges that include lack of access to markets; information on and access to finance; low ability to acquire necessary technical and managerial skills, and limited access to technology. The MSE competitive business strategies typology posits that combining Porter’s theory of competency and strategic alliance theory is better suited to MSEs than the use of competency theory alone, as has traditionally been the case. Using manufacturing and agro-food processing MSEs in Nairobi as the study population, the research objective of this study was to empirically determine if the use of competitive business strategies based on a combination of competency and strategic alliance theories by informal sector MSEs leads to better business performance, as compared to those who employ competency-based theories only. The results from the study established the following. First, from the study population, the adoption of Broad Hybrid, Hybrid Differentiation, Hybrid Mentor and Peer differentiation strategies corresponded to better performance, providing support to the proposition that collaboration may provide MSEs with access to additional resources that they may have lacked due to their small size, allowing them to better address threats and take advantage of opportunities available to them. Adoption of Mentor Differentiation, Peer Low Cost, Mentor Low Cost, Hybrid Peer and Hybrid Low-cost strategies, however, did not correspond to better performance. Businesses adopting these strategies were statistically neither better nor worse than those businesses that adopted none. Lack of support for Hybrid Peer, Hybrid Low Cost and Peer Low Cost may have been due to the low numbers of businesses that were within these categories, which may have affected the validity of the statistics tests. Third, the study compared the business performance of those adopting Porter’s strategies (competency-based) with those adopting strategies in the MSE typology. From the results, MSEs adopting strategies defined within the Peer Differentiation, Hybrid Differentiation, Hybrid Mentor or Broad Hybrid ideal types performed better than those adopting low cost, differentiation or mixed strategies under the Porter typology. These results suggest that strategies that incorporate collaboration both with peers and mentors, should lead to superior business performance of MSEs.
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    Let's make African research discoverable, together
    (2023-11-13) Havemann, Johanna; Ogot, Madara; Nyirongo, Revelation
    Presentation held at the Science Granting Councils Initiative (SGCI) 2023 Annual Forum and Global Research Council (GRC) Sub-Saharan Africa Regional Meeting, which took place from November 13th to 17th in Mombasa, Kenya.
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    Oxygen Access and Affordability in Health Facilities in Kenya
    (University of Nairobi, 2021-01) Ogot, Madara; Ayah, Richard; Muriuki, Rita; Nyangaya, James
    Medical Oxygen can represent a significant cost to hospitals in low- and middle-income countries (LMICs). Contributors to the high cost include logistical challenges in transporting oxygen that also lead to intermittent availability. The high oxygen cost to the patient can limit use or lead to early discharge. Even where oxygen is in government health facilities and hospitals, its high cost often leads to periods of unavailability. Oxygen concentrators are portable devices that remove nitrogen from the air and are able to produce oxygen at concentrations of 85%-95%. Although the use of concentrators could solve the supply chain problems of oxygen cylinders, concentrators come with their own host of challenges. These include the need for a continuous, reliable supply of electricity (often not available in LMICs), a robust system for monitoring, maintenance and repair, and a clinical staff trained in their use.
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    Strengthening the Emerging Digital Technologies Ecosystem in Kenya
    (2023-09) Ogot, Madara; Muthee, Margaret; Muriuki, Rita; Njunguna, Samuel
    The rapid increase in devices (mobile phones, computers, sensors, etc.) connected to the Internet (and thus to databases) has resulted in exponential growth in data generation and associated EDTs that can “identify patterns in observed data, build explanatory models, and make predictions quicker and with more accuracy than humans” (Pawelke et al., 2017) EDT/x-data-based applications and algorithms are mainly created in the developed countries and often lack transparency arising from intellectual property rights, thus hindering realization of the enormous potential EDT/x-data- based applications have in addressing socio-economic challenges faced by developing countries, including Kenya. Where applications exist, they are often not broadly accessible, especially for persons with disabilities, areas with slow internet connections or members of underrepresented groups. In this policy brief, the generic term “big data” is unpacked into four overlapping categories of data: big data, open data, user-generated data and real-time data, and are collectively referred to as “x-data”. EDTs are taken to include artificial intelligence (AI), blockchain, geographic information systems (GIS), the Internet of Things (IoT), and big data analytics. These methodologies are often used collectively. Gaps in support systems to develop EDT/x-data-based applications have created new digital divides between developing and developed countries. Further, barriers persist in the use and take-up of x-data by decision-makers, competing data sources, quality of data, limited aware- ness of data existence, and inadequate transformation of data into useful information or tailoring to match the decision-makers needs