The study of consumer payment choice at the point of sale involves a classification of payment methods such as cash, credit cards, debit cards, prepaid cards, paper checks, and electronic payments withdrawn from consumers' bank accounts. I describe alternative methods for studying consumer...

The mobile money transfer industry has been the most successful information and communications technology-enabled service in Kenya, having recorded an exponential growth relative to its neighbours within the East Africa region. This could be attributed to Kenya's status as a leading commercial...

The main focus of the present paper is to analyze the impacts of financial policy on inflation rates. The analysis depended on time series data and was divided into theoretical and applied analytical framework. An econometric model was utilized to reflect the relations between financial policy...

The study of consumer payment choice at the point of sale involves a classification of payment methods such as cash, credit cards, debit cards, prepaid cards, paper checks, and electronic payments withdrawn from consumers' bank account. I describe alternative methods for studying consumer...

The mobile money transfer industry has been the most successful information and communications technology-enabled service in Kenya, having recorded an exponential growth relative to its neighbours within the East Africa region. This could be attributed to Kenya's status as a leading commercial...

Using machine learning techniques applied to consumer diary survey data, the author of this working paper examines methods for studying consumer payment choice. These techniques, especially when paired with regression analyses, provide useful information for understanding and predicting the...

This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: univariate, linear, discriminate and logit regression; recursive partitioning, rough sets, artificial neural networks, and DEA. Our goals are: clarify the complexity-effectiveness balance of each...

We study the interplay between scientific progress and culture through text analysis on a corpus of about eight million books, with the use of techniques and algorithms from machine learning. We focus on a specific scientific breakthrough, the theory of evolution through natural selection by...

In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...

The complexity of machine learning models presents a substantial barrier to their adoption for many investors. The algorithms that generate machine learning predictions are sometimes regarded as “black box”, demanding interpretation and additional explanation. In this paper, we present a...