Research Article
Debt and the Excess Value of Diversified Firms: Evidence from Nigeria
Ibeawuchi Ibekwe*
,
Pedkuna Queenta Siliya
Issue:
Volume 12, Issue 5, October 2024
Pages:
235-249
Received:
26 July 2024
Accepted:
26 August 2024
Published:
6 September 2024
Abstract: The purpose of this study was to examine the relationship between debt and the value and excess value of diversified firms in Nigeria. This is against the background that there is no consensus on the factors that distinguish value-creating from value-destroying diversified firms. Data were collected from the annual reports of 62 diversified firms listed on the Nigerian Stock Exchange between 2008 and 2018. The multilevel generalized method of moments technique in the REndo package in the R Statistical Package was used to test the hypotheses. There is a significant positive relationship between debt and diversified firms’ value and excess value. The study and its findings are significant in several ways. First, no study has examined the relationship between debt and the value and excess value of diversified firms in the Nigerian context, and the few relevant studies have been in the context of developed countries. Second, it contributes to the literature on the valuation implications of firm diversification by providing some insight into the diversification discount often documented in the literature. These findings suggest that diversified firms’ failure to use the debt capacity that diversification creates is one reason some experience valuation discount. Third, the study employs the multilevel GMM analytical technique to control for endogeneity in the absence of valid instrumental variables. This technique has not been used in the diversification literature. The implication of the findings is that diversified firms should use the debt capacity that diversification provides to invest in positive net present value projects. The use of debt also adds a layer of corporate governance required in an environment of increased complexity and opacity associated with diversification. Increased investment in positive NPV projects and improved corporate governance through increased use of debt will enhance firm performance and value. The increased valuation of diversified firms due to debt increases the ability of diversified firms to play their developmental role in society. Investors would also benefit more from investing in diversified firms with higher debt ratios than those with lower debt ratios, all things being equal.
Abstract: The purpose of this study was to examine the relationship between debt and the value and excess value of diversified firms in Nigeria. This is against the background that there is no consensus on the factors that distinguish value-creating from value-destroying diversified firms. Data were collected from the annual reports of 62 diversified firms l...
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Research Article
Socio-Economic Perspectives of Household Water Treatment for Safe Drinking in Nigeria
Issue:
Volume 12, Issue 5, October 2024
Pages:
250-257
Received:
29 July 2024
Accepted:
22 August 2024
Published:
6 September 2024
Abstract: Access to safe drinking water remains a huge challenge to households in developing countries of which Nigeria is one. This is evident from the numerous cases of water related diseases ravaging the country. The United Nations Children Emergency Fund reports that over 150,000 Nigerians and about 117, 000 under five children, die of water borne diseases annually. Since safe water is gotten from water treatment, the challenges associated with ensuring that water is adequately treated for the households are enormous. Considering that the household is generally the primary source of drinking water for the populace, the socio-economic characteristics of a household plays a key role in determining their access to quality water for drinking. It is based on this that this study seeks to evaluate how household socio-economic characteristics influences a household’s decision to treat its drinking water. The study uses the Binary Logistic regression model to test for the correlates of household water treatment decisions. The data employed in this study is sourced from the Multiple Indicator Cluster survey conducted by UNICEF. A total of 26359 households were selected for the study. The study shows that about 23,495 of the selected households do not treat their water for safe drinking in Nigeria. The result also shows that source of drinking water is a key determining factor in the water treatment decisions of households, as different sources of water were found to have varying degrees of effects on water treatment decisions by households. Some ethnic groups were also observed to have a poor water treatment culture. Also, education of household head and high wealth status increases water treatment.
Abstract: Access to safe drinking water remains a huge challenge to households in developing countries of which Nigeria is one. This is evident from the numerous cases of water related diseases ravaging the country. The United Nations Children Emergency Fund reports that over 150,000 Nigerians and about 117, 000 under five children, die of water borne diseas...
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Research Article
A Soft Voting Ensemble Model for Hotel Revenue Prediction
Issue:
Volume 12, Issue 5, October 2024
Pages:
258-266
Received:
9 August 2024
Accepted:
9 September 2024
Published:
11 September 2024
Abstract: In recent years, the hotel industry has faced unprecedented opportunities and challenges due to the increasing demand for travel and business trips. This growth not only presents significant opportunities but also brings challenges to resource management and price setting. Accurate hotel revenue prediction is crucial for the hotel industry as it influences pricing strategies and resource allocation. However, traditional hotel revenue prediction models fail to capture the diversity and complexity of hotel revenue data, resulting in inefficient and inaccurate predictions. Then, with the development of the ensemble learning, its application to hotel revenue prediction has emerged as an influential research direction. This study proposes a soft voting ensemble model for hotel revenue prediction, which includes six base models: Convolutional Neural Network, K-nearest Neighbors, Linear Regression, Long Short-term Memory, Multi-layer Perceptron, and Recurrent Neural Network. Firstly, the hyper-parameters of the base models are optimized with Bayesian optimization. Subsequently, a soft voting ensemble method is used to aggregate the predictions of each base model. Finally, experimental results on the hotel revenue dataset demonstrate that the soft voting ensemble model outperforms base models across six key performance metrics, providing hotel managers with more accurate revenue prediction tools to aid in scientific management decisions and resource allocation strategies. This study confirms the effectiveness of the soft voting ensemble model in enhancing the accuracy of hotel revenue forecasts, demonstrating its significant potential for application in strategic planning within the modern hotel industry.
Abstract: In recent years, the hotel industry has faced unprecedented opportunities and challenges due to the increasing demand for travel and business trips. This growth not only presents significant opportunities but also brings challenges to resource management and price setting. Accurate hotel revenue prediction is crucial for the hotel industry as it in...
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