Empirical Analyses of eCommerce: The Findings – A Mixed Methodology Perspective

Introduction

The reconnoitring is done and over with. What is next? It is the time for sense making—the time for making sense out the seemingly nonsensical.

In this chapter, readers are driven through the revelations from the study. This study had a good response rate. The analysis included univariate, bivariate, and multivariate and content analysis. Sections and subtopics tackled in this chapter include:

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  The Motivation: In this section, readers are driven through the results attained from this investigation. The research questions and hypotheses were explained in Chapter 6, along with the research design methodology. In this chapter, the focus is on the results and the findings, utilising analyses based on a mixed model research approach which according to this study, must be viewed in this study as a Research-Divide-Research-Bridge (RDRB).

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  Subject Demographics: The sample size was calculated to be 715 consisting of 55 historically black colleges and universities, called clusters for the purposes of this research. Within each cluster or historically black colleges and universities, 13 senior administrators were surveyed to make a total of 715 administrators.

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  Descriptive Statistics-Painting the Picture: Values for variables were computed by summing the values for each electronic commerce solution indicated by each respondent.

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  Functional Relationships between Dependent and Independent Variables: The dependent and independent variables were identified in order to address the research questions and the hypotheses as described. The rationale for each hypothesis in relation for the research questions was succinctly explained in the previous chapter along with matrix mapping research questions to hypotheses.

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  Regression Model: In the preceding sections, the relationships between three dependent variables and several of the independent variables were described. Regression analysis is used to explain linear dependence between the dependent and independent variables.

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  Bivariate Regression Analysis: In the regression, the bivariate regression analysis is first considered, which uses least square approximation to determine a linear fit between pair of dependent and independent variables.

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  Analysis of the Hypothesis: Results presented in this chapter favoured this research; hypotheses were supported by the analyses and the research questions were addresses.

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  Multivariate Regression Models using Stepwise Approach: To determine multiple regression models it is first important to know the interdependency or multicollinearity of the independent variables. In the case when multicollinearity among independent variables occurs, it sufficient to regress the dependent variable with one of the collinear variables. This is one of the motivations for the hierarchical or stepwise regression model adopted in this research.

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  Content Analysis: Open-ended questions were included in the instrument to serve the qualitative purposes in this research. Responses to the questions were coded and re-coded to call attention to emerging themes.

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  Summary: The summary section encapsulates the chapter.

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  Key Terms and Definitions: Some of the key words together with their definitions are presented under this section.