Research
Discussion on Fintech Adoption Research
Financial industry including its services and deliveries have witnessed rapid transformation in the recent years due to advancement in technological tools. The reasons are not far-fetched, as there are needs for readily available services that are fast, convenient and more efficient. More also, the combination of the financial services and technology has deepened financial inclusion at ease. Aside alternative digital channels provided by traditional banks to deliver fintech-like services, the common Fintech brands are Stripe (U.S), Coinbase (US), Monzo (UK), Revolut (UK) Flutterwave (Nigeria), Paystack (Nigeria), Lendingkart (India), Instamojo (India),Lufax (China), WeLab (China), Yoco (South Africa) and Zoona (South Africa)..
Analysis and Visualization of Fuel Consumption Against Co2 Emission
CO2 emission has an adverse effect on the environment and cause greenhouse effect with significant negative climatic changes. This subsequently lead global warming which hurts both human and crops. It is important for us to perform visual analysis with available dataset using Canada as a case study.
Enhancing Demand Forecasting in Retail Supply Chains: A Machine Learning Regression Approach
This investigation discusses the importance of supply chain management and the role of demand forecasting in the business circle and presents a review of literature on demand forecasting techniques, emphasizing the shift from traditional methods to more sophisticated statistical and machine learning approaches. The study aims to contribute to existing knowledge on demand forecasting by utilizing machine learning regressors to predict orders in a Brazilian logistics company. It showed the use of the PyCaret Python library to develop robust regression models and validate key contributing features through feature importance plots. The performance of eighteen models, including Ridge, LASSO, XGBoost, Bayesian Ridge, Linear Regression, Gradient Boosting, KNN, Random Forest, among others, is evaluated using the Mean Absolute Error (MAE) metric.
Management Research: Discussion on Leadership Study Area
The study is to review leadership problems in management research. The discussion addresses the problems from theoretical backgrounds and reveal the possible leadership styles and behaviours seen in business world when such problems are experienced. Possible ways of managing the problems in order to minimize the negative effects on business outcomes was also discussed. This discussion will set pace for further specifics research in any organization settings having identified possible problems and how to formulate research questions.
