1.0 Introduction
The purpose of this report is to critically analyze the various research methodologies for collecting data for determining the public reaction of a company dismissing its customer service employees on the adoption of ChatGPT in automating customer service. The report opens with a background to the evaluation which explains why research on this topic should be done. This is then followed by a critical appraisal of potential research approaches, primarily Qualitative surveys (Hall, 2020) and secondary analysis.
2.0 Background to the report
The situation involves an HR director of a multinational corporation who is considering whether to employ AI technology, such as ChatGPT so that they can simplify the process of customer service. During this adoption, it means that the UK Customer Services Centre in Portsmouth would lose 350 employees jobless. Therefore, to better understand and solve this situation, there is a need to research the UK public to understand the implications of ChatGPT.
First, the use of AI as a substitute for human workers has ethical implications that may lead to increased unemployment rates and socioeconomic inequalities. In addition, the potential shutdown of the Customer Services Centre leaves one wondering about corporate social responsibility and its impact on the Portsmouth community. Furthermore, the risks of public relations are very grave in mass layoffs since bad press can affect the reputation and brand name of a company.
In my personal view, this research would be conducted for the sake of knowledge acquisition concerning ethical and social complications related to automation while ensuring that the reputation of a company remains intact as well as preserving good relationships with stakeholders. In addition, with this study, the corporation can make informed decisions which balance cost reduction measures and ethical responsibilities. This entails considering alternatives, such as retraining employees for new jobs; integrating AI with human workers or supporting affected staff members.
3.0 Critical Evaluation
When exploring the potential impact of implementing ChatGPT for customer service purposes, two key research approaches can be utilized: qualitative and quantitative. Quantitative research is the systematic collection and analysis of numerical data to quantify attitudes, behaviours or opinions regarding a specific issue (Hall, 2020). For instance, surveys carried out among various individuals can provide information on how they are likely to react concerning the proposed automation. For this to be achieved, the UK’s Office for National Statistics (ONS) could be hired to provide surveys and gather quantitative data on public opinion (Office for National Statistics n.d.).
However, qualitative research is about attitudes, motivations and perceptions by collecting non-numerical data (Mohajan, 2020). This can be in the form of focus groups or interviews with both customers and employees to get a clear understanding of their concerns, opinions as well as insights regarding ChatGPT implementation. The Market Research Society in the UK is a reliable source of valuable input on ethical standards and accredited researchers for qualitative research (Market Research Society, n.d.).
The efficiency of every method in addressing the research objectives is largely determined by the depth and breadth of insights required (Powell, 2020). For instance, quantitative surveys provide a broad perspective of public sentiments by presenting statistical data on attitudes and preferences. They are ideal for fast and accurate measurement of overall trends and perceptions. On the contrary, qualitative approaches give a more comprehensive analysis of individuals’ attitudes and perceptions by going into deep details that may be lost in standard surveys.
In this case, if the ONS were to conduct quantitative surveys with ChatGPT use as a topic of interest, data on public opinion towards the application would be collected. Using this approach, a large number of people can be reached which would lead to statistically significant findings that could guide decisions (Ahmadin, 2022). In addition, using qualitative approaches such as focus groups with the aid of MRS will enable the HR director to understand more profoundly public perceptions and concerns. By combining the two approaches, a holistic view of society’s impact from automating customer service operations can be gained.
It is important to evaluate each approach in detail so that the reliability and validity of research findings can be determined (Stinchcombe, 2020). In particular, surveys that use numbers are susceptible to specific biases including the tendency among respondents to adjust their answers to conform to social norms rather than reveal true beliefs. While qualitative studies can be very informative, they are limited in terms of the number of participants and potential bias from the researcher.
4.0 Conclusion
For this situation, I would use qualitative research methods where I focus on the group’s views and perspectives through the Market Research Society. This method enables the comprehensive analysis of viewpoints and opinions towards job automation in customer service functions. This methodology engages participants actively, and it provides knowledge about hidden beliefs and fears that are essential for decision-making. Consequently, in this case, qualitative research using focus groups seems to be the best option for collecting detailed data and understanding how society would respond to ChatGPT usage.
References
Ahmadin, M. (2022). Social Research Methods: Qualitative and Quantitative Approaches. Jurnal Kajian Sosial Dan Budaya: Tebar Science, 6(1), 104-113.
DeepL. (n.d.). DeepL Write: AI-powered writing companion. https://www.deepl.com/write
Hall, R. P. (2020). Mixing methods in social research: qualitative, quantitative and combined methods. Mixing Methods in Social Research, 1-272.
Mohajan, H. K. (2020). Quantitative research: A successful investigation in natural and social sciences. Journal of Economic Development, Environment and People, 9(4), 50-79.
Powell, T. C. (2020). Can quantitative research solve social problems? Pragmatism and the ethics of social research. Journal of Business Ethics, 167, 41-48.
Stinchcombe, A. L. (2020). The logic of social research. University of Chicago Press.
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