Quantitative Data Analysis using PLS-SEM (SmartPLS): Issues and Challenges in Ethical Consideration

In research, ethical issues are crucial, including the preservation of participants' rights, privacy, and well-being to secure informed consent and minimize potential harm. Throughout the study, researchers must maintain transparency, honesty, and integrity, promoting trust and credibility in the pursuit of knowledge. In the realm of quantitative research, the process of data analysis plays a fundamental role, serving as a critical element in the generation of reliable and precise findings. The purpose of this concept paper is to provide the growing recognition of the ethical importance of quantitative data analysis in research. This paper delves into the ethical aspects of quantitative data analysis, underscoring the necessity for researchers to approach matters related to data collection, storage, and analysis with meticulous attention when using SmartPLS. This study highlights that preserving privacy and confidentiality requires the secure handling of various data types, especially those containing personally identifiable or health information. Additionally, it is crucial to subject biases and discrimination in data analysis to rigorous examination to ensure fair representation and mitigate potential negative consequences. The current prevalence of privacy breaches and the accompanying ethical concerns underscore the critical importance of prioritizing ethical considerations. This paper also explores the ethical complexities unique to Partial Least Squares Structural Equation Modelling (PLS-SEM), a widely used statistical technique across multiple disciplines by using SmartPLS software. SmartPLS enables researchers to analyse intricate relationships, facilitating the derivation of significant conclusions. Nevertheless, researchers employing SmartPLS must remain attentive to distinct ethical dilemmas, particularly those related to the interpretation, management, and disclosure of data. The exercise of ethical vigilance becomes essential when the conclusions drawn from SmartPLS have an impact on various stakeholders, such as employees, consumers, and shareholders. Researchers can ensure the integrity, accountability, and ethicality of their research endeavours by adhering to ethical guidelines, conducting comprehensive analyses, and exercising caution when making generalizations while utilizing SmartPLS.