SDSU Management Employer Brand on Employee Motivation Discussion – Description
Select an article from your research, and evaluate the data analysis methodology used.
Was it quantitative or qualitative in nature?
Was this the appropriate analysis method? Why or why not?
Was bias clearly identified in the research?
Were there any weaknesses in the study?
RESPOND TO STUDENT #1 LINDSAY
Sanchez, M., Anglin, L., Rana, R., Butterfield, R., Everett, C. M., Morgan, P. (2020). Emerging practices in onboarding programs for PAs: Program content. Journal of the American Association of Physician Assistants, 33(9), 38-42. https://doi.org/10.1097/01.JAA.0000694968.61482.e Links to an external site..
The method in Sanchez, et al., (2020) was qualitative in nature due to the approach of interviewing and then analyzing the answers by grouping into themes in order to answer their research question of seeking information on what are the ideal topics and content for onboarding programs. This is qualitative because they are asking “how” to build better or more relevant onboarding programs specifically for nurse practitioners and physician assistants. The researchers classified the data collected into themes, which is a formal method of analyzing qualitative data (Byrne, 2017). This was an appropriate analysis method because the authors utilized interviewing to gather their data and then analyzed the data by looking for themes, ultimately determining eight content areas that should be considered for improved onboarding programs for these specific employees. Has this study been comparing something such as retention rates prior to and after deployment of an effective onboarding program, then quantitative analysis could have been an appropriate choice.
I did not note any declaration of bias in the study. To be honest, I’m not sure what to look for, in other words, when bias is being identified, is it a statement or less obvious than that? Could it be when the author describes limitations of the study in that they only interviewed 13 institutions and admitted it would have been more powerful had they done interviews with a larger group? This also answers the weakness question, in that the power of the study was small.
RESPOND TO STUDENT #2- 150 WORDS, KELLY
During the research process, it is important to focus on gathering quality data and resources, not just quantity. Valuing the quality of the research gathered can help ensure the project is ethical, unbiased, and valuable (Byrne, 2022b). Through a mindful lens of critical thinking, researchers can apply key questions to evaluate the use of research content in their project. To practice this skill, I will perform an analysis as guided by the questions in this week’s assignment prompt.
Resource article: Thiam, M. E. B., Liu, J., & Aston, J. (2019). Ignoring personal moral compass: Factors shaping bankers’ decisions. Journal of Financial Regulation and Compliance, 27(3), 357-379. https://doi.org/10.1108/JFRC-12-2017-011Links to an external site.
CSU Global Library permalink: https://csuglobal.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=137513564&site=eds-livLinks to an external site.
Was the study quantitative or qualitative in nature?
Thiam et al. (2019), conducted a study within the banking industry of the importance of ethical transparency on the decisions made by financial professionals. The material is presented as a quantitative study.
Was this the appropriate analysis method? Why or why not?
Yes, I do agree that a quantitative analysis approach was correct for this study. Thiam et al. (2019), utilized a very significant population for their data set, quoting close to 25,000 bank members. Given the amount of time that would have been needed to interview these financial professionals for a qualitative study, a quantitative approach via numerical survey was appropriate. Also, Thiam et al. (2019), were searching for high-level trends and variable characteristics. According to Byrne (2022a), quantitative analysis successfully explores classifications and categories. The resulting quantitative analysis successfully fulfilled this requirement.
Was bias clearly identified in the research?
Yes, I do believe that any bias was clearly identified in the research. For example, Thiam et al. (2019), explained in detail that although their original study population numbered almost 50,000 bank members, they ultimately focused on those financial professionals who “performed core operational banking activities” (p. 365) and not other generalized support positions (think legal, consultants, administrative, etc.). The authors go into great detail as to why this selection was highlighted, and it is appropriate based on the goal of the study. Likewise, the population was built specifically of financial professional members from banks which are chartered institutions. Without going into too much detail about the banking industry, given my professional experience, chartered banks are essentially entities that are regulated and operating on the up-and-up. This too, was an appropriate bias to set on the research.
Were there any weaknesses in the study?
This study was a very valuable find for my research project, but there is one weakness of note. Although the article itself was published in 2019, it was actually first submitted to the journal in 2017 and underwent many revisions. Although Thiam et al. (2019), call out this weakness, I was surprised during my reading that some of the data surveys were conducted in 2014. Granted, the authors include more current data and evolution notations in the literature which embrace a lot of the bank and economic changes and crises experienced between 2014 to 2019. This timeline actually gives a lot of great reasoning and extends the already established decision-making trends discussed. However, I wonder if someone glancing through this article, and not actually reading it, could misconstrue or misuse certain quantitative data charts. Again, not a significant enough weakness to impact my use or understanding of the literature, but a potential warning for others.
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