Defining hypotheses, variables and data
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This study is guided by two key hypotheses that the researcher aims to test at the end of the inquiry. They include:
H1: integrating internal corporate governance mechanisms in a publicly-funded university will positively impact productivity.
H2: integrating external corporate governance mechanisms in a publicly-funded university will positively impact productivity.
Variables
The study hypotheses will play an important role in testing both the independent as well as the dependent variables. The various variables that will be tested through these hypotheses include:
IV1: internal corporate governance mechanisms, such as Council structure, process as well as composition. The mechanisms will be measured in terms of council size, independence on government regulation, committee meetings as well as transparency in reporting. The type of data that will be collected under this variable is nominal.
DV1: increased productivity, measured in terms of improved performance in teaching, research as well as financial prospects.
-performance in teaching will be measured on basis of overall satisfaction, progression in teaching, student staff ratio as well as permanent employment rates.
-performance in research will be measured in terms of research income, research degree completion, as well as research and publications made per academic.
Financial performance will be measured in terms of equity, assets turnover as well as the current ratio. The type of data that the researcher will aim to collect through this variable is ordinal.
IV2: external corporate governance mechanisms, which will be measured on basis of Regulatory authority; based on conformity with the 2003 Corporate Governance Protocols for higher education institutions, and stakeholder influences; based on dependence on state funds. The type of data that the researcher will aim to respond to through this variable is nominal.
DV2: increased productivity, measured in terms of improved performance in teaching, research as well as financial prospects. The type of data that will be collected through this variable is ordinal.
Data collected
The type of data that will be collected under IV1 is nominal. This is because mutual exclusion of factors such as council size, independence on government regulation, committee meetings as well as transparency in reporting, which characterize the internal corporate governance, is more important than establishing any ordered category.
The data that will be collected under DV1 and DV2 is ordinal. This is because establishing order in factors such as financial, teaching as well as research performance is important.
The data that will be collected in IV2 is nominal. This is because mutual exclusion of factors such as regulatory authority and stakeholder influences, which are linked to internal corporate governance, is important.
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