Running head: RESEARCH OBJECTIVES 1
RESEARCH OBJECTIVES 2
Columbia Southern University
Sun Coast has identified several areas for concern that they believe could be solved using business research methods. The previous director was tasked with conducting research to help provide information to make decisions about these issues. Although data were collected, the project was never completed. Senior leadership is interested in seeing the project through to fruition. The organization seek to achieve the objectives highlighted below in its endeavor to promote effective leadership and efficiency of service provision.
RO2: To evaluate if training has been successful in reducing lost-time hours and, if so, how to predict lost-time hours from training expenditures.
RO3: To employ the historical data from 1,530 contracts to predict the decibels (DB) levels of work environments before placing employees on-site for future contracts.
RO4: To evaluate whether the revised program is more effective than the prior training program based on the two groups of employees, A and B who participated in the prior training program and in the revised training programs respectively.
RO5: To determine if blood lead levels have increased based on 49 employees who recently concluded a 2-year lead remediation project.
RO6: To evaluate where the difference between return on investment exist considering four lines of service that Sun Coast offers to their customers including air monitoring, soil remediation, water reclamation, and health and safety training.
Research Questions and Hypotheses
Sun Coast faces different business problems which need to be addressed as one means of promoting its endeavor to achieve both short and long term goals. The research questions will help the researchers is designing an appropriate research process that will lead to a credible conclusion to the problem (Creswell, & Creswell, 2018). On the hand, both null and alternative hypotheses will enable the researchers to determine the possible outcome based on the research problem.
RQ1: Is there a relationship between Particulate Matter (PM) size and employee health?
H01: PM that is less than 2.5 microns is potentially more harmful than PM that is between 10 and 2.5
HA1: There is no statistical relationship between the PM size and the worker’s health
RQ2: Has health and safety training successful in reduced lost-time hours and, if so, how to can lost-time be predicted?
H02: Health and safety training has successfully limited lost-time hours and the lost time can be predicted based on current performance.
HA2: There is no statistical relationship between health and safety training and lost time. Hence, it is difficult to predict.
RQ3: Can (DB) levels of work environments be predicted before placing employees on-site for future contracts?
H03: The standard ear-plugs are adequate to protect employee hearing if the decibel levels are less than 120 decibels (dB).
HA3: It is difficult to predict the DB levels since there is no statistical link to it.
RQ4: Which program is more effective between two groups of employees, A and B prior training and during the revised training respectively?
H04: The program is more efficient with the revised programs than the prior training one.
HA4: The program is more efficient with the one prior training than revised one.
RQ5: Has the blood lead levels have increased based on 49 employees who recently concluded a 2-year lead remediation project.
H05: The blood lead levels have increased considering the sampled employees.
HA5: The blood sugar of the employees was maintained upon completion of a 2-year old lead remediation project.
RQ6: Is there a difference between return on investment exist considering four lines of service that Sun Coast offers to their customers?
H06: There is a difference between the return on investment
HA6: there is no statistical provision justifying the relationship between the four lines of service that Sun Coast offers to their customers
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Thousand Oaks, CA: Sage.