In various scientific fields, there can be different methods of research, including quantitative and qualitative studies. The quantitative design implies the use of logic and statistics for proving a hypothesis and making conclusions. In contrast, a qualitative study is an exploratory process, focusing on understanding and interpreting rather than calculating. The first method is usually associated with exact sciences, while the second is primarily used in the social sphere and humanities. However, both types of research can be used in a combination and may be applied in a variety of scientific fields. Further, the quantitative and qualitative research methods are described in detail using specific examples.
The quantitative method is research where attention is paid to facts and numerical data. This type of study is objective and oriented toward a result; moreover, it deals with measurable data. An example of a quantitative study is research by Sun (2016), which aimed to define the influencing factors of reverse logistics carbon footprint. According to the author, the use of quantitative methods, such as the Johansen co-integration test and an augmented Dickey-Fuller test, allowed us to measure the role of these factors in a more precise way. Another research by Zhou and Chen (2017) investigated the inventory control problem of the reverse logistics supply chain.
In their study, a quantitative examination was performed to establish an inventory control model. Moreover, the numerical simulation and sensitivity analysis showed the connection between the inventory cost of reverse logistics and influencing factors. Finally, quantitative methods in the study by Dutta et al. (2021) allowed for measuring the effect of barriers to reverse logistics and their interconnections. These examples demonstrate that qualitative research is generally connected to facts and aims to identify correlations and connections between various aspects.
The qualitative research design is a subjective scientific approach based on observation and interpretation and aims to analyze patterns and behaviors. An example of such research is the study by Knemeyer et al. (2002), who investigated how reverse logistics systems can be used in recycling end-of-life computers. The particular method was an interview of the potential participants of the proposed system. Sundin and Dunbäck (2013), who studied reverse logistics strategies in the remanufacturing industry, used a similar technique. Through interviews, they identified challenges that small and medium-sized enterprises face in performing remanufacturing.
Finally, a common research design is the convergence of quantitative and qualitative methods. For example, the study by Janse et al. (2010) focused on the consumer electronics industry and its environmental and economic situation. In order to measure the diagnostic tool for accessing reverse logistics practices in the mentioned sphere, the researchers used a quantitative multifactor survey and qualitative methods, which included interviews and company visits. It is possible to notice that interview is one of the most common methods in qualitative research design since it allows for receiving subjective opinions. These examples prove that the qualitative research method is primarily used for the evaluation of existing theories and the investigation of current problems.
As was demonstrated in this paper, both types of research can be applied within the same discipline, depending on the aim of the study. Quantitative research can be defined as the use of statistical and logical tools in order to objectively test a hypothesis. This research design mostly deals with causes, effects, and relationships between variables. Qualitative research, on the other hand, is a subjective approach, where special attention is paid to words and visual data. It is possible to conclude that the discussed methods include various techniques and tools and can be used in a combination.
References
Duttaa, P., Talaulikar, S., Xavier, V., & Kapoor, S. (2021). Fostering reverse logistics in India by prominent barrier identification and strategy implementation to promote circular economy. Journal of Cleaner Production, 294, 1-16. Web.
Janse, B., Schuur, P., & de Brito, M. P. (2009). A reverse logistics diagnostic tool: the case of the consumer electronics industry. The International Journal of Advanced Manufacturing Technology, 47(5-8), 495–513. Web.
Knemeyer, A. M., Ponzurick, T. G., & Logar, C. M. (2002). A qualitative examination of factors affecting reverse logistics systems for end‐of‐life computers. International Journal of Physical Distribution & Logistics Management, 32(6), 455–479. Web.
Sun, Q. (2016). Research on the influencing factors of reverse logistics carbon footprint under sustainable development. Environmental Science and Pollution Research, 24(29), 22790–22798. Web.
Sundin, E., & Dunbäck, O. (2013). Reverse logistics challenges in remanufacturing of automotive mechatronic devices. Journal of Remanufacturing, 3(1), 1-8. Web.
Zhou, W., & Chen, L. (2017). Research on the inventory control of the remanufacturing reverse logistics based on the quantitative examination. Scientia Iranica, 24(2), 741-750. Web.