Statistics

Area of Research The research seeks to investigate the entrepreneurial success in electronic commerce. Previous research has identified several drivers and impediments to success and the study will mitigate those drivers and impediments to assist an entrepreneur in achieving success as a reseller of tangible goods. Types of Measurement In my research, the variables are categorized into two groups: success drivers and impediments to success. The one thing that is common in these items being measured is the fact that they either contribute to success or they inhibit success. As such, these variables are of a nominal category. Nominal categories could be further classified; for instance, among the success drivers are product selection, website characteristics, product pricing, and trust element. Accordingly, we can order these variables in terms of their impact for instance, we may observe from the body of research that the trust element has more weight than product selection in contributing to success thus, we can think of those variables as of an ordinal nature. Ordinal data however, cannot be measured therefore, if we are to construct a survey that would answer particular questions on a Likert scale of ten points, we would be able to measure and therefore treat the variables as interval variable so that we can statistically analyze our data. According to (Miles, 2010 pp. 8), asking for a subjective evaluation of a particular element may render the measurement as ordinal rather than interval, we would address this challenge by creating defined criteria’s where we can evaluate the answers given against guidelines and reject answers that would not fit. If we could assume that on our ten point scale, five will be considered the point at which the business is not capable of producing profit or incurring losses, we would have defined the zero point and as such we would be able to quantitatively measure the elements on a continuous scale and the variables