Understanding Qualitative and Quantitative from Paradigm Views for Product Research
Research function is very crucial in decision making. From gather information, make measurable judgments, then weigh them up to conclusions. We as humans often do it consciously or unconsciously, when weighing the price and quality of the smartphone purchased, when choosing a place to go to school, even when deciding to get married. In companies on a small or large scale, research is also taken out to achieve business goals carried with the different form with academia did.
I fully believed when my HCI lecturer said that it is difficult to make digital products that are suitable for users without taking research from qualitative data. Our first mini project uses design thinking, where the early stage is empathizing, which taken from qualitative data. But I realized, depending on this approach is not enough to produce desirable products.
There is a condition when the product needs to scale up and meet general standards to understand various user demographics, and this can be obtained from quantitative data.
However, comparing qualitative and quantitative is incorrect because these two things are the designations of the forms of data generated by the research method (1). Comparison between positivism and interpretivism as a paradigm that uses the two data type separately is more relevant to use to and understand how these two major opposite paradigms each other works in the social situation.
Social Research
why should we understand society through science? Social science is the study of human behaviour both individually and in society and influencing the world around it (2) (3). By studying it, we will gain information and know-how society moves in it. This understanding will make people easier to adapt and innovate. For example, when we have an idea and want to monetize it and know the target market and its behaviour, it would be easy to sell the idea. Requires efforts to understand society. This is where the role of research is needed.
Ontology, Epistemology and Methodology
Before we begin paradigms views, firstly we need to know where the pillars of science are, namely ontology, epistemology and methodology. Ontology is the starting point of all research, it studies concepts that are directly related to existence, in particular fact, existence, reality, as well as the basic categories of being and their relationship (4). Epistemology is an attempt to understand the level of belief is rationally limited by the available evidence (5). Whereas methodology is a body of methods, rules, and postulates employed by a discipline (6). The term paradigm is used to describe a researcher’s ‘world view’. This worldview is a perspective, or thought, or school of thought, or a shared set of beliefs, that informs the meaning or interpretation of research data (7). The paradigm is how the scientist define their perspective in pillars of science
Research Paradigm
Kuhn, in his book The Structure of Scientific Revolutions, introduces the paradigm as a collection of concepts and practices that define a discipline in a certain period until it changes continuously and forms a cycle (paradigm shift). This paradigm is then characterized by normal science and revolutionary science. Normal science is a well-established theory of knowledge that is likely to be copied and imitated. In contrast, revolutionary science is a critical attempt to re-question established theories either before or when evidence is gathered. However, paradigm interpretations may vary among scientists. There are many paradigms introduced by scientists to study social science. In this post, I will describe two general paradigms.
Positivism and Interpretivism.
Positivism is a philosophical theory which states that knowledge comes exclusively from the experience of natural phenomena and their nature and relationships. Information obtained from sensory experience, as interpreted through reason and logic, forms the exclusive source of all particular knowledge (8). In short, positivism is an understanding that in achieving its truth comes from real things. In sociology, positivism tries to understand phenomena through comprehensive group analysis because society consists of social facts that exercise coercive control over the individual which makes them conclude their analysis from a large dataset.
Interpretivism or you may call anti-positivism is the opposite. According to researchers in this school, we cannot understand why or how someone feels or behaves through numerical analysis. This is because a person’s view of the world is closely related to their life experiences. Researchers need to see the world as something that is constructed, interpreted, and experienced by people in their interactions with other individuals and the broader system. According to Intepretivim, the basic nature of research is interpretation, while the aim is to understand certain phenomena. Not to generalize from the population. Research on this paradigm is natural or not tied to formulas because it is applied to real-world situations (9)(10)(11).
The following are the distinguish of these paradigms and also the data preferences and characteristics of each data
From the table above, we can see the differences in positivism, interpretivism characteristics, and the data types result. Positivism is attached to a rational and measured view. It looks at society as a whole in order to see general laws of human action based on cause and effect. Numerical data are more precise and quick to use. Because it can know, compare and predict social phenomena in large groups of people, enabling researchers to see how one thing affects another. The fundamental approach of this method is experimentation, which is an attempt to distinguish natural laws through manipulation and direct observation(12). Positivists also consider that being independent of the research process is absolute, so the research results remain objective. For these two reasons, quantitative data tends to be agreed upon as a result of the positivist paradigm.
Different from the interpretivism. Research through this paradigm is more in-depth, specific and too difficult to compare. According to interpretivism, the theories used positivism are too general and are not suitable to reflect the nuances and variability of human interaction. Researchers need to be involved and not using assumptions in the first place to understand the details of events. Research conducted by Intepretivits is mostly involving direct contact with the model of the study also. The data generated is quite complex and specific because it does not always have categorical characteristics to distinguish. Based on these reasons, qualitative data tends to be reflected in the interpretivism paradigm (13).
However, I emphasize that the two data types cannot absolutely differentiate the paradigm because the two data can also be used in reverse
In general, research objectives can still be met using data in reverse, but the results may not be as effective for achieving the goals, and the progress may not be as efficient as expected. All must be returned to its context.
Case Example
A marketer wants to increase the sales of his detergent product. Because the desired information that marketing wants to get is an outcome with a clear and tangible reciprocal relationship (selling and buying). The positivism approach is more appropriate to maximize its sales potential. With statistical tools, the marketer can provide the types of offers based on the customer patterns obtained. The assumption of customer buying behaviour can be taken from the analysis of sales and purchasing variables from the previous year’s data, target market demographics, etc.
An example of a case that can be used with an interpretivism perspective is when a detergent product is unable to compete with similar products in the same area. Even those product have the same price. Assuming could be a wrong step because we do not know for sure the cause and effect of the decline in sales. Therefore, marketers need to go to the field and observe the sales process to draw sales pain points and provide solutions so that detergents can be well sold (14).
Why We Need to Understand This
Although most of my work using positivism views unconsciously. I personally do not take sides between positivism or interpretive.
I am more believe that the two paradigms that produce both types of data must be understood by professionals in various professions especially who don’t have researcher background, to help them in noticing the problem context, what type data they should use and challenges with using paradigms views
Thus professionals can make the right decisions in their respective fields. Then, after learning the two paradigms, I recommend a mixed data of the two paradigms to get an overall picture for accurate and actionable insight (15).
The use of these two data type will strengthen the sense and cover the deficiency of both paradigms.
I reiterate that there is no standard data type of understanding society. However, I provide an example with a recommended data type from each characteristic of the paradigm as I see the context of the problem. However, organizational and personal abilities also need to be considered.
The two paradigms also do not have a hierarchy where paradigm one is the starting point for starting research. Both paradigms can be either the first or be secondary place.
Lean vs Design Thinking
Meanwhile, I focus on data types and paradigms. I also saw the intrinsic relationship between the characteristics of innovation by the two paradigms. Design thinking is a non-linear, iterative process of understanding users, challenging assumptions, redefining problems, and creating innovative solutions to prototype and test them(16). Whereas Lean is defined as a set of practices to increase efficiency and effectiveness by eliminating waste(17). The two characteristics emphasized in how the two innovations perceive the situation. Lean focus on known problems with solutions that are easy to get because of their general nature. Meanwhile, design thinking focuses more on uncertain problems with uncertain solutions due to in-depth research that does not reflect the population(18).
In the video AJ & smart, Why Do Design Thinking Projects Fail ?. I learn that sticking to one innovation can be a mistake. It needs to follow the context of the problem to be solved. An example case is Weekly Shonen Jump, which is a line of popular manga magazine from Japan. Manga is comic originating from Japan. The magazine applies design thinking when Mangaka (manga artist) conducts research to make their Ne-mu (rough sketched) before submitting it to the editor to create Reisin (manga serialization). This process conducted through repeated editing(19). After the manga published, the evaluation was continued using competitor analysis and surveys to drive the manga always occupies top rank. This process is identical to lean.
This case validating that Innovation application strategies need to be carried out based on the context of the problem. It also proves that the two innovation theory which using paradigm that I purposing, complement one another to build a successful product.
Even though the Weekly Shonen Jump not labelling design thinking and lean on their editorial process, the inherent character of innovation indicates that Innovation application strategies need to be carried out based on the context of the problem. It also proves that the two innovation theory which using paradigm that I purposing, complement one another to build a successful product.
* I add another example of using positivism views in UX in here*
Another Reference
The Positivist Paradigm and The Interpretative Paradigm
Interpretivism (interpretivist) Research Philosophy
Differences between Positivism and Interpretivism Paradigms
Positivism and Interpretivism in Social Research
Understanding Quantitative vs. Qualitative Research
Outcomes and Processes in Economics and Anthropology
Convergent vs. Divergent Thinking
i also need to say that my knowledge of the entire editorial Shonen Jump process was taking from Bakuman: the road of becoming a manga artist, a comic that reflected from the real-life editorial process of mangaka
