The goal of this study was the determination of how the trend of information technology investment has influenced the financial performance of deposit money banks in Nigeria. The study utilized the longitudinal research design. Statistical bulletin of the CBN and financial reviews and accounts of selected banks for the period (2010-2023) was employed as the source of secondary data, being the post financial crises era and banking reform of 2009. The population for this work consists of 24 deposit money banks in Nigeria that have been authorized to conduct banking operations. During the study period, ten deposit money institutions which were in existence and which also have the required and complete data for the study were selected as a sample. The appropriate technique made use of for the purpose of this study was a purposive sampling technique. In analysing the trend of investment in IT in deposit money banks in Nigeria, this work mainly utilized descriptive statistics. This analysis was done with the aid of graph and bar charts for the aggregated values of IT investment for each year across the study period. The results showed that the trend of investment in information technology and performance of deposit money banks in Nigeria over the years has been fluctuating constantly, with return on asset dropping to a negative of 0.0024 in 2011 from a positive of 0.0279 in 2010.

Financial Literacy (FL) is vital for Small and Medium Enterprises (SMEs) as it allows entrepreneurs to lead sustainable growth of their businesses. This research aims to conduct a bibliometric analysis of the literature on FL in SMEs. The analysis is based on 182 documents obtained from the Scopus database, covering the period of 2005-2023. The researchers executed a performance analysis targeting the recognition of influential entities such as countries, organizations, journals, authors, and publications that have played an important role in the development of research in this field. The study used several bibliometric tools including trend analysis, Bradford’s Law, Lotka’s Law, corresponding author analysis, country analysis, keyword analysis, and thematic maps using Biblioshiny software. It was found that there is a consistent upward trend in the annual publications with a peak in the year 2022. Lotka’s law highlights the significant contribution of a few authors to the total scholarly output. Worth mentioning among these findings is the USA's status as the highest academic contributor with 38 papers in the field and a substantial total citation count of 1864. These results indicate that the subject of FL of SMEs is gaining an increasing attraction among scholars with great potential for further scientific development.

Foreign Direct Investment (FDI) has emerged to be a pivotal for economic growth. In this regard, this study examined the nexus between FDI and monetary policy fluctuations in Tanzania. Methodologically, a time series study from 1960 to 2023 using the World Bank and Bank of Tanzania data, Interest Rate Parity theory, Autoregressive Distributed Lag (ARDL) and Vector Autoregressive (VAR) models with EViews 12software where the Augmented Dickey-Fuller (ADF), Phillips tests Lag selection criteria—Akaike Information Criterion (AIC), Schwarz Information Criterion (SIC), Hanna-Quinn Criterion (HQC), Final Prediction Error (FPE), Breusch-Godfrey Serial Correlation LM, Jarque-Bera, Granger Causality, Impulse response function, CUSUM and CUSUM of square tests were done. This study found long and short-terms relationships among variables where the key determinants of FDI include the positive impact of previous FDI, negative effects of the Consumer Price Index (CPI), mixed impacts of exports and external debt stock, and the influence of foreign aid, GDP, and GNP growth rates. Imports and money supply positively affect FDI, while the official exchange rate, tariff rates, and trade openness show mixed impacts. The discount rate positively impacts FDI, with non-significant negative effects from reserves and treasury bills yield. The Granger Causality Test indicates relationships between the discount rate and FDI, and between FDI and reserves. The VAR model indicates a positive impact of trade volume on FDI, with trade volume responding immediately to shocks and FDI showing a delayed response. This study recommends controlling inflation, encouraging exports, management of external debt and proper use of foreign aid.

Using artificial intelligence (AI) tools to identify emotions is beneficial for evaluating customer satisfaction after interacting with a product or service. This paper aims to conduct a comparative analysis between two facial expression detection solutions. The paper focuses on analyzing the DeepFace and Azure Custom Vision services for a set of processed image data from a public database. The aim of the research is to determine the extent to which these systems can be integrated into real-time customer satisfaction monitoring applications. This approach is superior to subjective assessments because it is unmediated by words or a masked formulation of the true emotion. The analysis was performed on a limited number of images per emotion category due to cost constraints. The number of tests was maintained the same for the two services to produce an equidistant analysis. The categories of emotions analyzed were anger, disgust, fear, happiness, sadness, surprise, and neutrality. The performance of each instrument was evaluated by the accuracy identified using confusion matrices. The results showed superior performance for the DeepFace service, which achieved an accuracy of 87.29%, compared to Azure Custom Vision, which only achieved 82.99%. These results were obtained for the experimental dataset used. The research shows the importance of the dataset used in training AI models. In this case, the 48x48 pixel image quality compromises the model's ability to correctly recognize users' emotional states. A second experimental test was made by increasing the number of images to 28,709 images for the DeepFace service with the objective of analyzing the accuracy improvement. A slow increase was observed from 87.29% to 89.84%. The findings highlight that DeepFace is superior to Azure Custom Vision, but in this version, it cannot be used for customer satisfaction monitoring due to its low performance. The research will continue using higher-quality datasets and will be reapplied to an extended class of instruments in future research.

The study examined the socio-economic determinants influencing tourists' destination choices in Tanzania's Coastal circuit, thus analysing the influence of social, economic, and tourism-related factors on tourists' choices. The research involved 365 tourists, both domestic and foreign, and utilized questionnaires and interviews, employing descriptive and logit regression analysis for interpretation. The findings indicated significant social determinants such as age, marital status, and family size; older age and being married increased the likelihood of choosing the coastal region, while larger family size decreased it. Education had a minor impact, with those possessing a diploma or higher showing a lower probability of choosing the circuit. Economic factors like income, employment, exchange rate, and travel cost played a significant role; higher income and lower employment boosted the preference for the coastal circuit. Tourism-related aspects such as accessibility and promotions were crucial, with increased promotions and perceived accessibility raising the probability of selecting the coastal area. Recommendations include tailoring services to match predominant demographics and offering family-friendly packages, improving accommodation satisfaction, and implementing policies to enhance employment in the tourism sector, stabilize the exchange rate, and reduce travel costs for domestic tourists. Additionally, it suggests comprehensive promotional strategies, leveraging digital platforms, and collaborating with influencers to boost the circuit's appeal, while emphasizing high standards, safety measures, and responsiveness to tourist concerns.

This study empirically examined the impact of voluntary information disclosure on share price performance of publicly traded non-financial companies in Nigeria. Voluntary disclosure was captured by using environmental, social and governance (ESG) reporting; share price performance was proxy by annual stock returns. The study employed ex-post facto research design so as to determine the cause-effect relationship between the explanatory variable and the response variable. Using purposive sampling technique to draw on a sample of 76 listed non-financial firms over a ten-year period from 2013 to 2022, the data sourced from audited annual reports, accounts and other publicly available sources were analyzed using descriptive and inferential statistics. The findings disclosed that voluntary disclosure when measured in terms of environmental reporting [coef. =52.916 (0.018)] significantly and positively impact share price performance. Also, voluntary disclosure when measured in terms of governance reporting [coef. = -128.388 (0.000)] significantly and adversely affect share price performance. The study established that voluntary information disclosure has a notable effect on the share price performance of non-financial companies listed in Nigeria. The study recommends that the management of corporate organizations should be deliberate about reporting detailed and comprehensive information, specifically, on environmental practices as this will help investors in making economic and informed decision. Furthermore, users of financial report appreciate when companies disclose all-inclusive information in their audited annual report, when companies voluntarily disclose additional information, it builds investors’ trust and confidence.

This study aims to analyze the effect of petroleum price fluctuations on economic growth (Gross Domestic Product) in Tanzania from 1990 to 2023. The research utilized data on petroleum prices and GDP, drawn from the World Bank and the Statistical Review of World Energy. The study used Autoregressive Distributed Lag (ARDL) model to analyze both short-term and long-term relationships between petroleum prices and GDP. According to the findings, petroleum prices have a significant but contrasting impact on GDP. In the short term, rising petroleum prices lead to an immediate decline in GDP growth, reflecting the economy's vulnerability to energy price shocks. However, in the long- run, rising in petroleum prices are positively correlated with GDP growth, fueled by increased demand for transportation and industrial operations. The study found no evidence of a long-run co-integration between GDP and petroleum prices, indicating that short-term fluctuations play a more immediate role in influencing economic performance. These results highlight the importance of balancing short-term energy price stabilization measures with long-term strategies focused on energy diversification and efficiency to ensure sustainable economic growth. The study emphasizes the crucial role of internal forces in driving changes in the economy, suggesting that both endogenous factors and external price shocks should be considered in policy-making.

The scientific literature suggests that the network enterprise is a dominant strategy for many organisations that outsource to meet customer requirements for complex products to be produced or delivered. However, without adequate preparation, many network enterprises fail. This is why it seems justified to open up a line of research into the process of preparing a network company. How can a third party develop and experiment with a change process to encourage the involvement of companies in the network organisation? This study was carried out as part of a research-intervention applied to the case of the SEP Congo oil distribution company. It involved several weeks’ work with subcontractors of land transport of petroleum products (TTPP) based in Kinshasa. The scarcity of companies managing human resources capable of meeting the required quality criteria is an essential element in petroleum distribution in Kinshasa. In short, in a dynamic context where uncertainty is high, companies face new management challenges: innovation in all aspects of the value chain, and the development of innovative skills through collective learning. So, for several companies to be effective in subcontracting relationships, it is necessary to synchronize their activities and share their knowledge in order to facilitate the search for common solutions to common problems, which requires a change in strategy. This approach to preparing a network company has been tried out with the aim of improving risk management skills in oil companies and developing their capacity for collaborative learning. This process is part of an evolutionary approach that involves the creation and implementation of activities from uprooting to rooting, through the process of understanding, from objection to exploration and commitment, taking into account the reactions of participating companies throughout the change implementation process.

This study investigates the impact of informal sector finance on the development of microenterprises in Ijebu North Local Government Area of Ogun State, Nigeria. Utilizing a structured questionnaire survey administered to four hundred and eight (408) microenterprises, the study employs simple regression analysis to draw insights from the data. The findings reveal that microenterprises heavily rely on informal financial sources, such as rotating savings and credit associations (ROSCAs) and credit and thrift societies, to meet their financial needs. However, these informal financing mechanisms have not significantly enhanced micro-enterprise development within the local government. The study identifies several challenges, including high interest rates, limited loan sizes, and inadequate financial literacy, which hinder access to formal financial services. Furthermore, it highlights the importance of factors such as social networks, trust, and reputation in facilitating access to informal finance. In light of these findings, the study recommends that policymakers promote financial literacy programs to equip micro entrepreneurs with essential financial management skills. In addition, the study suggests improving the outreach of microfinance institutions to ensure better access to financial resources and encourages the development of tailored financial products that cater to the specific needs of microenterprises. By focusing on these critical areas, it is possible to enhance the overall financial inclusion of microenterprises, thereby fostering their growth and contributing to local economic development in Ijebu North Local Government Area, Ogun State, Nigeria.