Performance in Safety Management Systems (SMS)

Study Design

The study will employ a cross-sectional research design in examining regulations and technologies employed in the aviation industry to provide a high level of performance in safety management systems (SMS). This research design is appropriate because it is easy to implement, promotes data collection from a representative sample, allows examination of multiple variables, and permits hypothesis testing (Creswell & Creswell, 2019). The research question is: What are the common patterns of applied aviation SMS regulations and technologies that provide high-quality SMS performance? Based on this research question, the study hypothesizes that the most effective SMS regulations those with international and collective patterns. Another hypothesis is that the most productive SMS technologies are those that belong to the software sphere. The study will collect data on improvement patterns of SMS regulations and technologies as two qualitative independent variables and risk factors and accident rates as two quantitative dependent variables using a structured questionnaire to test these hypotheses. In the analysis of data, the study will use descriptive statistics to establish patterns of regulations and technologies and analysis of variance to test their effectiveness in SMS performance.

Population Sample

The target population of the study will be employees who work in the aviation industry. To enhance the findings’ external validity, the study will target employees working in both international and domestic airlines. The sample size will use a sample size of 390 employees estimated using Cochran’s formula by considering the significance level of 0.05, the proportion of 0.5, and the margin of error of 0.05 (Anderson et al., 2017). In the selection of respondents, the study will utilize the convenience sampling strategy. The study will ensure that respondents work for both domestic and international airlines, have experience of more than five years, and understand SMS regulations and technologies advocated by the International Civil Aviation Organization (ICAO) and the European Aviation Safety Agency (EASA).

Variables and Measures

The study will examine four variables, which are regulations, technologies, risk factors, and accident rates, relating to the performance of SMS in the aviation industry. Regulations and technologies of SMS are two independent variables. In contrast, risk factors and accident rates comprise two dependent variables. Regulations and technologies will be measured on a categorical scale of “Yes” and “No”, while risk factors and accident rates will be assessed on a seven-point ordinal scale. As an essential relationship of these variables, the adoption and implementation of SMS regulations and technologies would effectively reduce risk factors and accident rates in the aviation industry.

Data Collection Methods

The study will utilize a questionnaire as a research instrument in the data collection. Qualitative data of regulations and technology and quantitative data of risk factors and accident rates will be collected from selected respondents. After seeking informed consent from the aviation industry’s target respondents, the study will administer the structured questionnaire and collected data. Appendices A and B have the cover letter and the questionnaire, respectively, for the study.

Data Analysis Method

The study will employ both descriptive and inferential statistics as techniques in data analysis. Descriptive statistics, which are means, standard deviations, and frequencies, are appropriate because they will depict patterns and trends of risk factors and accident rates in response to SMS regulations and technologies’ adoption and use. Analysis of variance is a suitable inferential technique because it evaluates SMS regulations and technologies’ significance in reducing risk factors and accident rates in the aviation industry.

References

Anderson, D. R., Sweeney, D. J., Williams, T. A., & Camm, J. D. (2017). Essentials of statistics for business and economics. Langara College.

Creswell, J. W., & Creswell, J. D. (2019). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.

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StudyCorgi. "Performance in Safety Management Systems (SMS)." February 9, 2022. https://studycorgi.com/performance-in-safety-management-systems-sms/.

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StudyCorgi. 2022. "Performance in Safety Management Systems (SMS)." February 9, 2022. https://studycorgi.com/performance-in-safety-management-systems-sms/.

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