Methodology is essential to any research project. This depends mainly on its role in depicting the process of conducting the research. This documentation provides a comprehensive analysis of how the research for the proposed study will be conducted. As well, the methodology that will be set forth in this chapter will make it possible to derive accurate and precise results in an organized, reliable, valid, and systematic manner. Furthermore, these results should not only be deemed viable, but also, they should be readily accepted in the field of study. Analyzing the definition of methodology corroborates the role outlined in research. Methodology may be defined as the systematic quest for undiscovered knowledge. Hence, it is believed that a good research should execute high level of systematic planning, organization with respect to achieving a set goal. This is a study that will be developed in order to identify the factors that most significantly affect women’s opportunities for attaining equality in corporate America.
Research Method and Design Appropriateness
During recent years, most corporations in the United States have more fully committed to the creation and development of diversity and inclusion programs. This means that there has been a clear tendency towards making sure that there is a greater level of equality between male and female employees (at all organizational levels). However, despite the apparent efforts being undertaken by corporations throughout the country, according to the 2011 Catalyst Census, Fortune 500 Women Board Directors, Executive Officers and Top Earners and prior catalyst censuses, women have made no significant gains in the last year and are no further along the corporate ladder than they were six years ago. This raises significant questions regarding the validity, reliability, appropriateness, and efficiency of such inclusion and diversity programs. Due to this, an attempt is being made to better understand how changing beliefs regarding ethnic and gender differences and leadership can influence corporate America’s diversity policies and initiatives and provide significant insight into problems with current practices, such as the diversity and inclusion barriers experienced by women.
All things considered, this is a study that attempts to achieve one major purpose: examining the relationship as to how different beliefs regarding ethnic and gender differences and leadership can influence corporate America’s diversity policies and initiatives. In order to achieve this primary purpose, a quantitative correlational design will be developed. On this point, it becomes necessary to discuss quantitative research methods in general. First of all, it is important to mention that quantitative research, like qualitative research, implies an inquiry on a specific problem; it is founded on theories that are generally composed of statistical elements like variables, numbers, and etc. and its ultimate objective is to deliver quantifiable results. Quantitative research is essentially descriptive, although it can also be inferential. It explores characteristics, as well as possibilities or probabilities of occurrences of events. It should be noted as well that quantitative research, when applied to social sciences, rarely concerns itself with cause and effect relationships as it does qualitative research; quantitative research limits itself to statistical analysis.
As far as quantitative research designs go, it is necessary to discuss four different design types: observational studies; developmental studies; correlational studies; survey studies. Observational studies tend to be focused on a very specific group; the idea is to observe, and study, some behavioral aspect. Developmental studies can either be cross-sectional or longitudinal. Cross-sectional studies are unique in the sense that the sample of subjects is comprised by cross section from different age groups. Longitudinal studies, on the other hand, involve a developmental, or progressive, study of a given group over a given period of time. It is also important to note that in discussing developmental studies, cross-sectional are generally less complicated, less time-consuming, and generally more economical and practical than longitudinal studies. This, however, will depend on the study’s actual design. Survey studies consist of collecting information as it pertains to specific questions; the answers given by the subjects are arranged and analyzed usually through statistical indexation. Correlational studies seek to establish the nature and strength of relationships between one variable and other variables. In essence, correlational studies seek to establish how a change in a given set of variables may bring about change in a given dependent variable.
Overview of the design appropriateness.
Correlational studies may be understood in a poly-functional manner. This owes to the fact that they permit themselves to be applied in some phase of different designs (with different levels of control and manipulation, especially as preparatory or exploratory studies) and are particularly suitable in descriptive studies and ex post facto that proceed from a given sample in which one or more variable can be related to another variable, or other variables, in order to attempt to analyze the relationship or association between them.
Also, they may be employed for predictive character studies. In such instances, the correlational study attempts to determine the direction of the relationship or association, in the measure of possible causality, if such has been effectively established and its magnitude previously confirmed. In other words, its magnitude will ultimately be the quantification of the relationship between one independent variable and a given set of dependent variables. From a merely technical point of view, the correlations are associated or are the basis for factor analysis, analysis of variance, and relationships that ultimately determine causal models. The magnitude or strength of the relationship obtained a value of between +1 and -1, with zero being the no relationship or association. A positive relationship will indicate a positive (+) sign; this will signify that a higher value for a given value will also imply higher values for the variables that correlate with it.
Conversely, if instead of higher values, there are lesser values given to the variables that correlate with a given variable, the nature of the relationship will be negative (and will be characterized by a negative sign). Once the correlation index (different than zero) has been obtained, it may be possible to consider the possibility of making generalizations regarding the population to which the test sample belongs. In order to do this, it will be necessary to calculate the statistical significance for a determined confidence level. A significant correlation is a necessary, but not sufficient, condition to establish causality. Therefore, it is necessary to go deeper into the study and develop more sophisticated methods such as causal analyses (as they allow for establishing the plausibility of a given causal model based on the correlation analyses between its different constituting variables).
The quantitative correlational study is appropriate to generate data that provides significant insight into problems with current practices, such as the diversity and inclusion barriers experienced by women. The research method and design of the study is appropriate in order to explore how different beliefs regarding gender differences and leadership can influence company diversity policies and initiatives. The goal is to analyze the impediments and barriers that materialize into conscious and sub-conscious discriminatory practices in corporate America.
This study attempts to answer three specific questions. All of these questions tackle the subject of diversity and inclusion (as they pertain to gender) in corporate America. This is the general topic that the study focuses on. This being said, an attempt will be made to develop three questions that conform to four major considerations, each of which will be generally explained:
Relevance: Questions need to have some level of relationship with the general topic that has been chosen, which in this case is diversity and inclusion in Corporate America. As well, it is important that the questions remain inside of the limits that were set beforehand (so that the study’s breadth can provide sufficient answers for all of them).
Interest: It is important that all questions spark the researcher’s interest. If the research questions are interesting, they will be stimulating, and this will allow for a more rapid and efficient research.
Focus and Specificity: Like it was previously mentioned, the questions that are proposed must be bound by the limits previously established for the research. Research questions may never be too broad, nor may they be too vague. In either such instance, the research will prove insufficient for developing complete answers for them, and the research study will ultimately fail. Based on this, it is advisable that research questions focus on a particular aspect of the general topic.
Researchable: All questions must offer the possibility of carrying out any and every research that is necessary for complete answers to be derived. This being said, it will be necessary to have guaranteed access to the primary and secondary data that will be required. On this point, it will be helpful to fall back on a preliminary search of information in order to determine if the questions that will be proposed are answerable (with the research that is available).
Having made sure that the proposed research questions conform to all four of the conditions delineated above, the three that have been derived for this research study (and that will be answered) are the following:
RQ1: Is there a correlation between gender differences and progress into the corporate suite?
RQ2: Are women, who do not model their leadership behavior after traditional white male styles of management, not successful or not recognized for their efficiency at workplace?
RQ3: Do stereotypes based on surface level diversity help or prevent women from trying to reach leadership positions?
RQ4: When women finally reach leadership positions, are they meaningful members of the leadership team or just tokens used to give the impression of diversity? Population
The statistical population, also known as universe or collective, comprises a set of reference elements about which a series of observations are made. The population is the set that the researcher is interested in finding conclusions, or making inferences, about. Also, a population is a set of subjects or individuals with a determined set of demographic characteristics. This population is analyzed and a sample is taken and analyzed; the results obtained are subsequently extrapolated to the full statistical population. Generally, a statistical population is too large to be covered by any kind of research. The number of elements, or subjects, that comprise a statistical population, is greater than or equal to the number of elements that can be obtained from it within a sample (n).
This being said, the statistical population of interest for the proposed study comprises all men and women currently holding corporate jobs in the United States of America. Granted, the statistical population will be too large for the proposed research study to cover it; this is consistent with the theoretical underpinnings of the statistical population. Furthermore, it becomes clear that the statistical population will be smaller than the statistical population previously described. The sampling frame for the proposed research study (which will provide the statistical sample for the proposed correlational study) is explained in the following section.