Critique of a Qualitative Article

Critique of a Qualitative Article

Introduction

Artificial Intelligence (AI) refers to the making of computers that think and act rationally and like humans (Jackson, 2019). AI is believed to result in several advantages, which include a reduced error rate compared to humans, and the ability to work in and explore dangerous conditions (Jackson, 2019). Brougham and Haar (2018) explain that while AI implementations are advantageous and especially to the management of organizations, there are issues that are raised by employees on whether or not their jobs can be retained. The research conducted pertained to the implementations of AI in the workplace, and further exploration was done concerning talent acquisition, leaders, and employee retention to prevent business conflict and failure through AI. Previously, it was noted that other research conducted in this field merely focused on assessing the impact of Artificial Intelligence, as can get observed later in this article. This paper aims at critiquing research conducted by Brougham and Haar (2018) in proving that AI implementations in the corporate world have impacts on the employees, which further prompts the study conducted on exploring talent acquisition and employee retention to prevent business conflict and failure.

Problem Statement

As stated above, the selected article is that of Brougham and Haar (2018) titled Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees’ perceptions of our future workplace. As the title suggests, the article focuses on AI, as well as other related fields such as robotics, to analyze the perceptions of employees concerning the future workplace. The problem for the selected article, therefore, is that the implementations of smart technologies, artificial intelligence, robotics, and algorithms (STARA) raise concerns to employees concerning their replacement in the job market as a result of the developing technologies. The research looks into the fears that employees have using qualitative techniques and some quantitative data to capture the extent to which the said employees feel like they could get replaced by the upcoming technologies.

Purpose of the Study

Brougham and Haar (2018) explain that the primary purpose of their study was to develop a measure that captures an awareness for STARA, test the STARA awareness to determine whether it is viewed as a threat to careers by employees, and to determine the effects that STARA has on jobs and the well-being of the current employees. As can get observed from the purpose provided by Brougham and Haar (2018), the research touches on the aspects concerning the implementations and perceptions of AI on whether their applications will replace them from work. The study, however, does not touch on the issue of preventing business conflict and failure through exploring and leader and employee retention.

Research Questions

Some of the research questions for Brougham and Haar’s (2018) items included how satisfied the employees were with their success, how the job makes the employees feel to which there were three adjectives provided as a possible answer, including depressed, gloomy and miserable. Also asked, after the questions stated above were on how they felt concerning the implementations of Artificial Intelligence. The article also required integration with some quantitative methods, which prompted them to ask on whether or not the employees were worried that the future would get replaced by STARA and whether they were worried that their organizations would replace employees due to STARA.

Methodology / Design

The methodology used for the research conducted by Brougham and Haar’s (2018) consisted of qualitative methods, with the integration of some quantitative data. According to Creswell and Clark (2017), thoroughly mixing qualitative and quantitative data is known as fixed method research. Brougham and Haar (2018) explain that mixed kinds of studies are growing in popularity, and these techniques are very appropriate in ensuring that the best aspects of both qualitative and quantitative methods are visible. The most used techniques for the article, however, are qualitative methods.

Faulkner and Faulkner (2019) explain that various research methods can get used, such as experiments, surveys, case studies, and questionnaires, etcetera.  Cruz and Tantia (2017), in their article Reading and Understanding Qualitative Research, note that there are several reasons for using qualitative research, for instance, the complexity of the study. Sale and Thielke (2018) explain that qualitative research, which is research involving the collection of non-numeric data, is essential for scientific processes. Complex investigations concerning the collection of non-numeric data require an analysis that cannot get done through qualitative methods. Also, the nature of the research demands the use of qualitative methods since the data collected is not in numeric form. Walther et al. (2017) explain that qualitative research designs are essential for seeking out opinions and depth of researches rather than breadth. These methods are exploratory, as Walther et al. (2017) further assert, and are useful for informing new theories and concepts.

The method utilized for the research was done on one hundred and twenty employees, as Brougham and Haar (2018) explain. Brougham and Haar (2018) further explain that on average, the employees that participated were around thirty-two years old, and those that were married or n a relationship constituted 54.2 percent, 69.2 were female, and the job tenure of approximately five years.

Research Ethics

Tolich et al. (2017), in their article, teach about research ethics as active learning. Tolich et al. (2017) explain that some of the ethical concepts include doing no harm, as well as respecting persons and beneficence. On the other hand, Roth and von Unger (2018) explain that some of the ethical issues in qualitative research include ensuring anonymity, confidentiality, and informed consent. The possibility of intrusion for qualitative studies has to get minimized by all means, as Roth and von Unger (2018) further explain.

Brougham and Haar’s (2018) research ensures that anonymity and confidentiality are upheld throughout their research through seeing to it that there are no names mentioned, and the study also minimizes the possibility of intrusions. Brougham and Haar’s (2018) article cannot be said to cause any harm, and people are excellently respected. The process that is not described in Brougham and Haar’s (2018) article is the considerations of obtaining consent, which is essential in qualitative research ethics.

Analysis

     Brougham and Haar (2018) explain that their research utilized open-ended questions that are appropriate for qualitative research. These open questions, as Brougham and Haar (2018) further explain, proved useful in capturing the comments of the participants concerning the awareness of STARA and how it affects the current jobs of those participants, as well as how they expect it to impact their career. Brougham and Haar (2018) explain that sixty-seven of the one hundred and twenty selected participants took the open-ended questions while fifty-three chose not to answer. A thematic analysis got conducted, which had three broad categories, including no threat, potential threat, and real threat. Also applied for the research was hierarchical multiple regression analysis that assisted Brougham and Haar (2018) in testing the influence of STARA awareness on the well-being and job outcomes of the employees. The results of the study were that greater STARA awareness presented negative relations to the commitment that employees have in organizations as well as to career satisfaction. The awareness of STARA was also found to relate positively to cynicism, turnover intentions, and depression.

Other Procedures

Since thematic analysis got used for this research, coding would also be appropriate for the same. Castleberry and Nolen (2018) explain that thematic analysis and coding in qualitative research data refers to a type of analysis for qualitative data that entails the identification of texts or only data that are linked by common ideas and themes. According to Belotto (2018), the identified themes that are common can then allow one to index the text into categories and create thematic idea frameworks. The next step for the data, therefore, is identifying common themes when reading through each transcript. Richards and Hemphill (2018) assert that during coding and thematic development, it is also essential to detect bias in the data, or among interviewees and methodologies or even in the objectives. The data shall then get conceptualized and segmented where the use of software applications like spreadsheet will come in.

Conclusion

Conclusively, this paper aims at critiquing research conducted by Brougham and Haar (2018) in proving that AI implementations in the corporate world have impacts on the employees, which further prompts the study conducted on exploring talent acquisition and employee retention to prevent business conflict and failure. The overall quality of the article is impeccable, and the research conducted was excellent. There was the utilization of a sample through selected participants. Also, the methodology used was appropriate, with thematic analysis getting used, which is recommendable.

References

Belotto, M. J. (2018). Data Analysis Methods for Qualitative Research: Managing the Challenges of Coding, Interrater Reliability, and Thematic Analysis. Revista Brasileira de Enfermagem, 71, 2622–2633.

Brougham, D., & Haar, J. (2018). Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees’ perceptions of our future workplace. Journal of Management & Organization, 24(2), 239-257.

Castleberry, A. & Nolen, A. (2018). Thematic analysis of qualitative research data: Is it as easy as it sounds? Currents in Pharmacy Teaching and Learning, 10(6), 807-815. doi:10.1016/j.cptl.2018.03.019

Creswell, J. W., & Clark, V. L. P. (2017). Designing and conducting mixed methods research. Sage publications.

Cruz, R.F., & Tantia, J.F. (2017). Reading and Understanding Qualitative Research. American Journal of Dance Therapy, 39(1), 79-92. doi:10.1007/s10465-016-9219-z

Faulkner, S. S., & Faulkner, C. A. (2019). Research Methods for Social Workers : A Practice-Based Approach (3rd.ed.). New York, NY: Oxford University Press.

Jackson, P. C. (2019). Introduction to artificial intelligence. Courier Dover Publications.

Richards, K. A. R., & Hemphill, M. A. (2018). A Practical Guide to Collaborative Qualitative Data Analysis. Journal of Teaching in Physical Education, 37(2), 225–231.

Roth, W., & von Unger, H. (2018). Current perspectives on research ethics in qualitative research. Forum: Qualitative Social Research, 19(3), 3-3. doi:10.17169/fqs-19.3.3155

Sale, J. E. M., & Thielke, S. (2018). Commentary: Qualitative research is a fundamental scientific process. Journal of Clinical Epidemiology, 102, 129-133. doi:10.1016/j.jclinepi.2018.04.024

Tolich, M., Chloe, L., Doesburg, A., Foster, A., Shaw, R., & Wither, D. (2017). Teaching research ethics as active learning: reading Venkatesh and Goffman as curriculum resources. International Journal of Social Research Methodology, 20(3), 243-253. doi:10.1080/13645579.2017.1287870

Walther, J., Sochacka, N. W., Benson, L.C., Bumbaco, A. E., Kellam, N., Pawley, A. L., & Phillips, C. M. L. (2017). Qualitative Research Quality: A Collaborative Inquiry Across Multiple Methodological Perspectives, Journal of Engineering Education, 106(3), 398-430. doi:10.1002/jee.20170