The Scientific Approach and Alternative Approaches to Investigation

THE HYPOTHETICO-DEDUCTIVE METHOD

To solve a problem, scientific research employs a methodical, systematic, logical, and rigorous approach known as the scientific method. The natural sciences were the setting for the development of the scientific method, which has served as the basis for numerous significant discoveries. This method is still the most widely used way to generate knowledge in the natural, social, and business sciences, despite the many criticisms of it and its application to social and business research (which we will address later in this chapter). Karl Popper, the Austrian philosopher, popularized the hypothetico-deductive method, which is a common variant of the scientific method. The hypothetico-deductive method offers a practical, methodical way to generate knowledge to address fundamental and managerial issues.

The hypothetico-deductive method's seven-step procedure

The following seven steps are involved in the hypothetico-deductive method.

1. Determine a wide range of issues.

2. Explain the problem description.

3. Formulate conjectures.

4. Choose your course of action.

5. Gathering data.

6. Analysis of data.

7. Data interpretation.

The manager may become interested in the research project if there is a decline in sales, frequent production disruptions, inaccurate accounting results, low-yielding investments, employee disinterest in their work, customer switching, and similar circumstances.

IDENTIFY THE PROBLEM STATUS

A specific goal or purpose informs the beginning of scientific research. A problem statement containing the general objective and research questions of the study should be created in order to find solutions for problems that have been identified. We can define the problem statement and reduce the scope of the problem by first collecting preliminary data about potential contributing factors. The process of obtaining preliminary information, entails looking closely at what is observed (e.g., the observation that our company is losing customers). To find out what is happening and why, this could be accomplished by conducting a literature review on the subject of customer switching, speaking with a number of coworkers, clients, or other pertinent sources. We are able to get a sense of what is going on in the situation by using any of these techniques. We are able to formulate a precise problem statement as a result.

DEVELOP HYPOTHESES

This step involves looking at variables to determine how they contribute to or influence the explanation of the problem's occurrence and potential solutions. Theoretically, the network of relationships between the variables is then woven, along with an explanation of how and why they could affect the issue. A theorized network of associations between the variables can be used to generate educated conjectures or hypotheses. At this point, for example, we may speculate that certain factors influence customer switching, such as overpricing, competition, inconvenience, and unresponsive staff.

A scientific hypothesis needs to fulfill two conditions. The hypothesis needs to be testable, which is the first requirement. The requirement that a hypothesis be falsifiable is the second criterion and a fundamental component of the hypothetico-deductive approach. In other words, the hypothesis needs to be able to be refuted.

This is crucial, in Karl Popper's opinion, because a hypothesis can never be proven to be true; there's always a chance that more research will reveal its falsity. Consequently, a hypothesis remains provisional until it is refuted; failing to falsify (!) a hypothesis does not prove it. Because of this, the falsifiability requirement highlights the tentative nature of research findings—we can only truly "prove" our hypotheses up until they are refuted.

CHOOSE YOUR MEASURES

We won't be able to test our theories unless the theoretical framework's variables are measured in some way. We must operationalize both customer switching and employee unresponsiveness in order to test the hypothesis that they have an impact on one another.

DATA COLLECTION

Data pertaining to each variable in the hypothesis must be gathered once we have decided how to measure our variables. Data analysis then starts with these data.

DATA INTERPRETATION

It is now up to us to interpret the data analysis results and determine whether or not our hypotheses are supported. For example, if the data analysis revealed that a higher level of employee responsiveness had a negative correlation (let's say, 0.3) with customer switching, we can conclude that training our staff to be more responsive is necessary to increase customer retention. This data analysis also suggests that 9% of the variance in customer switching can be explained (or accounts for) by the responsiveness of our staff (0.32). We can offer suggestions on how the "customer switching" issue might be resolved (at least partially) based on these deductions; we need to teach our staff to be more adaptable and communicative.

Observe that our research has been worthwhile even if the theory regarding the impact of unresponsiveness on customer switching is proven false. Unsupported hypotheses enable us to improve our theory by pondering the reason behind their lack of support. Next, in more research, we can put our improved theory to the test. In conclusion, there are seven procedures for locating and fixing a troublesome matter. In order to ensure a thorough understanding of the seven steps of the hypothetico-deductive method, let us quickly go over an example. In a corporate context and the actions performed in the seven steps.

REVIEW OF THE HYPOTHETICO-DEDUCTIVE METHOD

The seven steps of the hypothetico-deductive method are:

Defining the problem statement;

Selecting a broad problem area;

Formulating hypotheses;

Determining measures;

Collecting and analyzing data;

Interpreting the findings.

The scientific method tests a theory about an interesting topic by using deductive reasoning (keep in mind that a theory is an ordered collection of assumptions that yields testable predictions). We proceed from the more general to the more specific in deductive reasoning. We begin with a broad theory and work our way down to more specific testable hypotheses. When we get specific observations to test our theories, we get even more specific. In the end, analysis of these particular observations enables us to validate (or invalidate) our initial hypothesis.

Conversely, inductive reasoning is a process by which we make generalizations based on the observation of particular phenomena.

As a result, inductive reasoning proceeds from the more particular to the more general. The claim that "all swans are white" may result from seeing a first, second, and third white swan—this is a well-known example. In this case, the generalization that all swans are white has resulted from the observation of a white swan on multiple occasions. Karl Popper argues that using induction to "prove" a hypothesis is impossible because there is no amount of evidence that can guarantee the absence of contrary evidence. Counting three, ten, hundred, or even ten thousand white swans does not justify the conclusion that “all swans are white” because there is always a possibility that the next swan we observe will be black. Instead, Popper proposed that (proper) science is accomplished by deduction.

Nevertheless, both deductive and inductive procedures are frequently employed in both fundamental and applied research, in spite of Popper's criticism of induction.

In fact, a number of scholars have maintained that the development of theories (induction) and their testing (deduction) are crucial steps in the research process. Deduction and induction are frequently applied in order. This process is known as "the double movement of reflective thought," according to John Dewey. When a researcher sees something and wonders, "Why does this happen?" induction occurs. The researcher may come up with a hypothesis as a tentative explanation for this query. This hypothesis is then put to the test via deduction. This procedure is demonstrated in the example below.

This illustration demonstrates how scientific research employs both deductive and inductive reasoning techniques. While deductive and inductive research methods can be applied to both quantitative and qualitative studies, deductive methods are more frequently employed in studies that are causal and quantitative, while inductive methods are more frequently employed in studies that are exploratory and qualitative.

In conclusion, theories based on induction and deduction aid in our comprehension, elucidation, and/or forecasting of business phenomena. The following procedures follow when a study is planned to test particular hypothesized outcomes (e.g., whether reducing unpleasant noise in the surroundings improves people's ability to solve mental puzzles). The researcher starts with the hypothesis that noise has a negative impact on the ability to solve mental puzzles.

The next hypothesis is that mental puzzles can be solved more accurately and quickly if noise levels are reduced. A study project is created to test the hypothesis in light of this. The study's findings assist the researcher in drawing the conclusion that reducing the unpleasant noise does, in fact, enable participants to perform better on mental puzzles. The process of generating hypotheses from the study's findings, starting with a theoretical framework, and drawing logical conclusions is known as the hypothetico-deductive method—you've probably heard of it before. This is an additional illustration of the hypothetico-deductive research methodology.

It is not always possible to conduct research that is 100% scientific in the management and behavioral fields because, in contrast to the physical sciences, the results obtained will not always be precise and error-free.

SOME OBSTACLES TO CONDUCTING SCIENTIFIC RESEARCH IN THE MANAGEMENT AREA

This is mainly due to the challenges that are likely to arise when measuring and gathering data in the subjective domains of feelings, emotions, attitudes, and perceptions. Every time we try to measure arbitrary or subjective constructs, these issues arise. Obtaining a representative sample may present challenges as well, limiting the findings' ability to be applied broadly. As a result, it is not always feasible to fully satisfy all of the requirements of science. It is frequently challenging to achieve comparability, consistency, and broad generalizability in research. Nevertheless, we would have attempted to conduct scientific research to the degree that the design of the study ensures purposiveness, rigor, and the maximum possible testability, replicability, generalizability, objectivity, parsimony, precision, and confidence.

ALTERNATIVE APPROACHES TO RESEARCH

Finding the truth about the research topic should be made easier for the researcher by using a scientific approach to the study. However, is the truth even a thing? Or is the truth merely something we have imagined and thus subjective? All research is predicated on assumptions about the world we live in (ontology is the philosophical study of what is deemed to exist) and what research may be able to uncover. Regarding these matters, various researchers hold varying opinions.

There is a long-standing debate that is not unique to business research concerning the nature of knowledge and how we arrive at it. This field of study is called epistemology. Inquiries like "What exists?" For over 2000 years, philosophers and researchers in a wide range of fields have been fascinated by the questions "What is knowledge?" and "How do we acquire knowledge?"

We are now going to take a quick look at the key viewpoints for modern business research. We will address positivism, constructionism, critical realism, and pragmatism in that order. Please take note that we occasionally exaggerate the descriptions of these research perspectives in order to make our point. Because of this, specialists in these fields may occasionally disagree with what we have to say.

POSITIVISM

A positivist perspective on the world holds that science and scientific investigation are the means to discover the truth—positing, in fact, the existence of an objective truth—and to gain a sufficient understanding of the world to enable us to forecast and manipulate it. A positivist believes that if we conduct research using a scientific method, we can determine the laws of cause and effect that govern the world.

Reliability of observations, generalizability of findings, and research rigor and repeatability are all important to positivists. They propose hypotheses using deductive reasoning and test them with a fixed, predefined research design and objective metrics. The experiment is the main tool used by positivist researchers to examine cause-and-effect relationships through observation and manipulation. According to some positivists, the purpose of research should only be to describe phenomena that are measurable and directly observable. Anything beyond that, including feelings, thoughts, and emotions, is unknowable to them.

CONSTRUCTIONISM

Constructionism is an entirely different perspective on research and the best way to conduct it. Positivism's conviction that there is an objective truth is criticized by constructionism. On the other hand, constructionists maintain that the world—as we understand it—is essentially mental or man-made. Constructionists do not pursue the objective truth as a result. Rather, they study what goes on in people's minds in order to comprehend the rules that people use to make sense of the world.

Therefore, constructionism focuses on how individuals create knowledge; it investigates the explanations people provide for problems and subjects as well as how they arrived at these explanations. Constructionists are especially curious about how social interactions and the environment in which people live shape how people perceive the world.

Constructionist researchers frequently use qualitative research methodologies. They are able to gather rich data that is focused on the contextual uniqueness of the world under study through focus groups and unstructured interviews. In fact, comprehension of a particular case is frequently more important to constructionists than generalizing their conclusions. From the perspective of the constructionist, this makes sense because there is no objective reality to generalize about.

ESSENTIAL REALISM

There are a lot of middle ground perspectives between these two diametrically opposed ideas about research and how it ought to be conducted. Among these is the critical realism point of view. The concept of critical realism combines the belief in an external reality (an objective truth) with the rejection of the idea that this external reality can be measured objectively. This is because observations, particularly those concerning concepts like motivation, satisfaction, and culture, which are difficult to observe and quantify directly, are inherently interpretable. Thus, the critical realist challenges our capacity for certain understanding of the world. Whereas a positivist sees the purpose of research as discovering the truth, a critical realist sees the purpose of research as moving closer to this objective, even though it is impossible to reach it. The critical realist perspective holds that data collection is in general faulty and imperfect, and that measures of phenomena like emotions, feelings, and attitudes are frequently subjective in nature. Additionally, the critical realist holds that bias is ingrained in research. In order to gain a better understanding of what is going on around us, they contend that we must employ triangulation—that is, combining data from several faulty and inaccurate methods, observations, and researchers.

Pragmatists

Pragmatists are unbiased when it comes to what constitutes quality research. Depending on the study's research questions, they believe that studies on both subjective meanings and objective, observable phenomena can yield insightful information. Pragmatism focuses on applied, practical research where contrasting perspectives on the topic and the research are useful in resolving a (business) issue. According to pragmatism, research is a process in which ideas and interpretations (theory) are extrapolations of our prior experiences, behaviors, and interactions with the outside world. Thus, pragmatics emphasize how socially constructed research is and how different researchers may have different theories and interpretations of what they find.

The pragmatist supports eclecticism and pluralism because they believe that these various viewpoints, concepts, and theories aid in our understanding of the world. The idea that the present truth is provisional and subject to change over time is another crucial aspect of pragmatism. Stated differently, research findings should always be treated as tentative truths. The connection between theory and practice is emphasized by pragmatics. A pragmatist views intelligent practice as the result of applying theory to practice after it has been derived from it—as we just discussed. In this vein, pragmatists regard theories and concepts as crucial instruments for navigating the environment we live in. A pragmatist believes that research is valuable when it is applicable to real-world situations, and that theory should inform practice.

CONCLUSION

It's possible that you've asked yourself "Why do I need to know this" a lot. One response is that we think it's critical that you understand that there are multiple perspectives on what constitutes high-quality research. Understanding epistemology may make it easier for you to relate to and comprehend other people's research as well as the decisions that were made during this research. Regarding the nature of knowledge or how we learn, different researchers have different opinions. In fact, there is only one, albeit significant, perspective on what constitutes "good" research, and that is the scientific method. These disparate viewpoints influence the various approaches, designs, and methods of research that are employed in an investigation.

An additional response to the query, "Why do I need to know this?" is that you have most likely observed that you have a preference for one research perspective over another. It is possible to ascertain what types of research questions are important to you and what approaches to data collection and analysis will provide you with the best answer to these questions by having a clear understanding of your personal beliefs about research and how it should be conducted. Additionally, it will assist you in making well-informed decisions throughout the research process, comprehending the implications of your study's findings (both positive and negative), and determining the kinds of conclusions your research strategy permits you to reach. In this way, it aids in placing your research and its conclusions into context.

In conclusion, the research questions you pose, the research design you choose, and the research techniques you employ will all be greatly influenced by your beliefs about the nature of knowledge and how humans acquire it. Much less attention is paid to the philosophical issues raised above in favor of developing research questions, research designs, and research methods throughout the remainder of the book. But it's crucial that you periodically reflect on the philosophical foundations of your research questions, research design, and research methodology. This is crucial because the significance of your research findings is contingent upon how well they align with the techniques you employed, the design you have chosen, the questions you have asked, and the research perspective you have taken.

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