Raphael Mutisya Kieti and Walter Ogolla
This paper applies the hedonic pricing model (HPM) approach to identify critical determinants of apartment value and employs the technique to develop a valuation model that can…
Abstract
Purpose
This paper applies the hedonic pricing model (HPM) approach to identify critical determinants of apartment value and employs the technique to develop a valuation model that can accurately estimate the value of apartments.
Design/methodology/approach
The research employed a case study design that was limited to transaction sales and attribute data of apartments in Nyali estate, Mombasa County in Kenya. A sample of 120 sales of apartments obtained from registered real estate firms was analyzed using quantitative methods.
Findings
According to the study results, the hedonic valuation model developed comprises four critical determinants of apartment value, namely, number of parking lots, presence of swimming pool, age of apartment and provision of balcony. The hedonic model was tested and found to be accurate and reliable in estimating apartment value.
Research limitations/implications
The model will improve accuracy, reliability and efficiency in valuation. The application of the model in the valuation of apartments is, however, limited to the case study area where the data are obtained. The scope of application of the model may be improved by increasing the sample size to include apartment sales data from other estates in Mombasa County.
Originality/value
Previous studies that have used the HPM technique in analysis of apartment values have focused on the “explanatory” and “contributory” power of attributes on apartment values, rather than the development and use of the model to measure value. The present study is the first to develop a HPM equation for property value estimation in the apartment real estate sector in Kenya.
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Sintayehu Alemayehu, Daniel Olago, Opere Alfred, Tadesse Terefe Zeleke and Sintayehu W. Dejene
The purpose of this study is to analyze the seasonal spatiotemporal climate variability in the Borena zone of Ethiopia and its effects on agriculture and livestock production. By…
Abstract
Purpose
The purpose of this study is to analyze the seasonal spatiotemporal climate variability in the Borena zone of Ethiopia and its effects on agriculture and livestock production. By examining these climate variables in relation to global sea surface temperatures (SST) and atmospheric pressure systems, the study seeks to understand the underlying mechanisms driving local climate variability. Furthermore, it assesses how these climate variations impact crop yields, particularly wheat and livestock production, providing valuable insights for developing effective adaptation strategies and policies to enhance food security and economic stability in the region.
Design/methodology/approach
The design and methodology of this study involve a multifaceted approach to analyzing seasonal spatiotemporal climate variability in the Borena zone of Ethiopia. The research uses advanced statistical techniques, including rotated empirical orthogonal function (EOF) and rotated principal component analysis (RPCA), to identify and quantify significant patterns in seasonal rainfall, temperature and drought indices over the period from 1981 to 2022. These methods are used to reveal the spatiotemporal variations and trends in climate variables. To understand the causal mechanisms behind these variations, the study correlates seasonal rainfall data with global SST and examines atmospheric pressure systems and wind vectors. In addition, the impact of climate variability on agricultural and livestock production is assessed by linking observed climate patterns with changes in crop yields, particularly wheat and livestock productivity. This comprehensive approach integrates statistical analysis with environmental and agricultural data to provide a detailed understanding of climate dynamics and their practical implications.
Findings
The findings of this study reveal significant seasonal spatiotemporal climate variability in the Borena zone of Ethiopia, characterized by notable patterns and trends in rainfall, temperature and drought indices from 1981 to 2022. The analysis identified that over 84% of the annual rainfall occurs during the March to May (MAM) and September to November (SON) seasons, with MAM contributing approximately 53% and SON over 31%, highlighting these as the primary rainfall periods. Significant spatiotemporal variations were observed, with northwestern (35.4%), southern (34.9%) and northeastern (19.3%) are dominant variability parts of the zone during MAM season, similarly southeastern (48.7%), and northcentral (37.8%) are dominant variability parts of the zone during SON season. Trends indicating that certain subregions experience more pronounced changes in climate variables in both seasons. Correlation with global SST and an examination of atmospheric pressure systems elucidated the mechanisms driving these variations, with significant correlation with the southern and central part of Indian Ocean. This study also found that fluctuations in climate variables significantly impact crop production, particularly wheat and livestock productivity in the region, underscoring the need for adaptive strategies to mitigate adverse effects on agriculture and food security.
Research limitations/implications
The implications of this study highlight the need for robust adaptation strategies to mitigate the effects of climate variability. Detailed research on seasonal climate patterns and the specific behaviors of livestock and crops is essential. Gaining a thorough understanding of these dynamics is critical for developing resilient adaptation strategies tailored to the unique ecological and economic context of the Borana zone. Future research should focus on seasonal climate variations and their implications to guide sustainable development and livelihood adjustments in the region.
Originality/value
This study offers significant originality and value by providing a detailed analysis of seasonal spatiotemporal climate variability in the Borena zone of Ethiopia, using advanced statistical techniques such as rotated EOF and RPCA. By integrating these methods with global SST data and atmospheric pressure systems, the research delivers a nuanced understanding of how global climatic factors influence local weather patterns. The study’s novel approach not only identifies key trends and patterns in climate variables over an extensive historical period but also links these findings to practical outcomes in crop and livestock production. This connection is crucial for developing targeted adaptation strategies and policies, thereby offering actionable insights for enhancing agricultural practices and food security in the region. The originality of this work lies in its comprehensive analysis and practical relevance, making it a valuable contribution to both climate science and regional agricultural planning.
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Lucy Kibe, Tom Kwanya and Hesbon Nyagowa
The fourth industrial revolution (4IR) has changed the way people operate. All sectors of the economy have been affected by this technological advancement. However, little is…
Abstract
Purpose
The fourth industrial revolution (4IR) has changed the way people operate. All sectors of the economy have been affected by this technological advancement. However, little is known of how 4IR technologies are used in Africa. This paper aimed to investigate how 4IR technologies can be harnessed to support sustainable development in Africa. The objectives of the study were to: examine the infometric patterns of research production on 4IR technologies for sustainable development in Africa; explore the perception of 4IR technologies and their potential for sustainable development in Africa; investigate the extent to which 4IR technologies have been harnessed to support sustainable development in Africa; determine the factors influencing the use of 4IR technologies for sustainable development in Africa; and identify the strategies which can be used to harness 4IR technologies for sustainable development in Africa.
Design/methodology/approach
The study applied a mixed methods research approach. Quantitative data was collected through bibliometrics analysis while qualitative data was collected by use of systematic literature review. Data was collected from Google Scholar using Harzing's “Publish or Perish” software and analysed using Microsoft Excel, Notepad, VOSviewer and Atlas.ti and presented using tables, graphs and figures.
Findings
The study retrieved 914 research publications on 4IR and sustainable development in Africa. It emerged that production of research on the subject has increased gradually over the years. The findings reveal that Africa is aware of the potential of 4IR for sustainable development. In fact, it emerged that 4IR technologies are being used to support education, health services, tourism, e-commerce, records integrity and project management. Some of the factors that inhibit the use of 4IR for sustainable development Africa include lack of relevant policies, low skill levels in 4IR technologies, inadequate infrastructure and lack of stakeholder involvement. This study recommends the development of policies in 4IR, capacity building and upgrading of infrastructures. The findings can be used by governments in Africa to harness 4IR technologies for sustainable development.
Originality/value
The research is original in scope and coverage.