Using the attached rubric and proposal complete the following: Population and Sampling Data Collection—Instruments Data Collection Technique Data Analysis Study Validity Transition and Summary Rubric

doctoral study prospectus 12

Proposal

The Impact of Transformational Leadership on Organizational Performance and Employee Retention

by

John H. Smith

Doctor of Business Administration Prospectus- Leadership Specialization

Submitted in Partial Fulfillment of the Requirements for the Degree

of

Doctor of Business Administration

University

Prospectus: The Impact of Transformational Leadership on Organizational Performance and Employee Retention

The target population of this study will consist of employees who work at small to medium-sized enterprises in Colorado Springs, Colorado. The sample size will be determined based on a power analysis will be conducted through G*Power. Effective sizes across three categories, namely small, medium, and large for the purpose of hypotheses testing will be determined. Settings for G*Power will rely on hierarchal multiple regression test will be set to examine the relationship between transformational leadership components and organizational performance as well as employee retention.

Data will be collected using three sources. First, with regards transformational leadership components, a survey will be used in which all five components (idealized influence attributed, idealized influence behaviors, inspirational motivation, intellectual stimulation, and individualized consideration) are included. For this purpose, I will use Multifactor Leadership Questionnaire (MLQ) (Avolio and Bass, 1995), which consists of 20 questions across the five components with a five-point Likert-like scale for participants to provide their responses. Regarding the dependent variable of employee retention, I will use a five-item scale for employee retention measurement by Kyndt et al. (2009). Regarding the dependent variable of organizational performance, which will be measured through percentage of annual sales performance goal that is met by the employees, I will obtain financial performance documents from the organization for analysis.

Participants will be contacted through their organization’s HR executives. Participants selected in the study will be asked to fill a questionnaire survey consisting of the two instruments for measuring transformational leadership components and employee retention. It will be ensured beforehand that participants are educated regarding their rights to confidentiality and anonymity. Each questionnaire survey will take approximately 45 minutes, and participants will be given the opportunity to fill the survey either at home or at work. Organizational performance reports will be obtained from the HR executive for the latest financial year.

Regarding analysis, to ensure suitability of the data for statistical analysis, I will conduct tests of the following assumptions for multiple linear regression: standard residuals, multicollinearity, independence of errors, and variance and linearity. Measures will be examined through internal consistency coefficients, standard deviations, and means through the use of Cronbach’s, which will have an alpha of .01. Data will be imported to the statistical analysis tool SPSS. Next, I will conduct a Pearson’s product moment correlation in order to measure whether there is a relation between transformational leadership components and employee retention. Similarly, the relation between transformational leadership components and organizational performance will be assessed. I will use Pearson’s correlation r and hierarchical regression analysis to examine the relation between the variables.

The research will adopt a quantitative methodology. Quantitative research would be used to measure and analyze the numerical data that would be collected using questionnaires. The data collected would be used to make a generalization on the impact of transformational leadership on organizational performance and employee turnover intention. The study will establish statistically the percentage of employees that are willing to leave or stay in their current organization based on the character traits, behavior, motivations, influence, and the inspiration they draw from their leaders. The descriptive study would provide data that would be highly reliable since the process can be repeated to verify it.

Quantitative research method would be appropriate for this study because it helps determine to what extent the independent variable affects the dependent variable. It is applicable in the aspects of social behavior that can be represented numerically (Nardi, 2018; Togao et al., 2018). Various instruments such as questionnaires are used in the collection of data, and statistical methods are applied in the analysis of the collected data. The collected data is analyzed and presented in charts, tables, and columns to help the researcher make conclusions. The researcher is able to interpret the meaning of collected data and establish associations and frequencies.

The main advantages of quantitative research methods are that the results can be easily generalized to represent the characteristics of the whole population since a larger sample is used. Besides, the process of data analysis takes less time as compared to qualitative research because statistical software like SPSS is used. According to Powers and Powers (2015), large samples make the research findings more truth-worthy. Also, reliability is maintained by the use of two or more independent variables (Carroll & Bailey, 2016; Brannen, 2017; Kumar, 2019). Carroll and Bailey (2016) conducted research to assess language proficiency where several independent variables were used, including listening, reading, writing, and speaking, citing that the variables significantly influence language proficiency.

The major disadvantage of quantitative research is that it only relies on data collected at a specific point ant time which may be influenced by an individual’s mood at the time of the interview (Brannen, 2017; Kumar, 2019). However, the lack of direct connection with the participant means that the researcher is unable to dig deep to obtain more information and only takes a snapshot of the phenomenon. Therefore, it only gives an overall picture of the population without looking into the underlying explanations and meanings.

The study would employ a correlational research design. In this case, the researcher seeks to investigate the extent to which the character traits, behavior, motivations, influence, and inspiring leaders give their employees influence employee turnover intention and organization performance. As a correlational study, it would examine the type of relationship that exists between the variables (Brannen, 2017; Kumar, 2019). The study would show the relationship between leaders’ leadership styles and the employee turnover intention by use of techniques such as correlations, and cross-tabulation. The study would establish a regression equation that would be used to generalize the characteristics of the relationship between the variables and allow the researcher to make predictions on future trends.

Statistical analysis allows the researcher to measure the relationship between the variables and determine the direction and degree of the relationship. The degree of the relationship between shows how closely related the variables are, which defines whether there is a significant relationship between the variables (Curtis et al., 2016; Nardi, 2018). Correlation coefficients are used in correlational studies which range between -1 and +1. When there, the correlation is equal to zero, it means that there is no relationship between the variables. In this case, the null hypothesis is confirmed. If the correlation coefficient is either -1 or +1, there if perfect correlation. In this case, there is a significant relationship between the variables with -1 representing a negative relationship and +1 representing the positive relationship. Correlational research doesn’t imply causation like the experimental design. Therefore, there is a need for further research to determine whether the independent variables have a causal effect on the behavior of the dependent variable.

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