HOW TO THINK LIKE A RESEARCHER Before we start discussing how to think like a researcher we need to first know what research is.
WHAT IS RESEARCH?
What is research? Depending on who you ask, you will likely get very different answers to this seemingly innocuous question. Some people will say that they routinely research Different online websites to find the best place to buy goods or services they want. Television news channels supposedly conduct research in the form of viewer polls on topics of public interest such as forthcoming elections or government-funded projects. Undergraduate students research the Internet to find the information they need to complete assigned projects or term papers. Graduate students working on research projects for a professor may see research as collecting or analyzing data related to their project. Businesses and consultants research different potential solutions to remedy organizational problems such as a supply chain bottleneck or to identify customer purchase patterns. However, none of the above can be considered “scientific research” unless:
(1) it contributes to a body of science, and (2) it follows the scientific method. This chapter will examine what these terms mean now how will one think like a researcher, in your quest to know to how one should think in terms of researching will lead you to many articles and write ups on how to think like a research ,so tune on and keep reading to find out how to think like a researcher Conducting good research requires first retraining your brain to think like a researcher. This requires visualizing the abstract from actual observations, mentally “connecting the dots” to identify hidden concepts and patterns, and synthesizing those patterns into generalizable Laws and theories that apply to other contexts beyond the domain of the initial observations. Research involves constantly moving back and forth from an empirical plane where observations are conducted to a theoretical plane where these observations are abstracted into Generalizable laws and theories. This is a skill that takes many years to develop, is not Something that is taught in graduate or doctoral programs or acquired in industry training, and is by far the biggest deficit amongst Ph.D. students. Some of the mental abstractions needed to think like a researcher include unit of analysis, constructs, hypotheses, operationalization, Theories, models, induction, deduction, and so forth, which we will examine in this work as we move on
Unit of Analysis One of the first decisions in any social science research is the unit of analysis of a scientific study. The unit of analysis refers to the person, collective, or object that is the target of the investigation. Typical unit of analysis include individuals, groups, organizations, countries, technologies, objects, and such. For instance, if we are interested in studying people’s shopping behavior, their learning outcomes, or their attitudes to new technologies, then the unit of analysis is the individual. If we want to study characteristics of street gangs or teamwork in organizations, then the unit of analysis is the group. If the goal of research is to understand how firms can improve profitability or make good executive decisions, then the unit of analysis is the firm. In this case, even though decisions are made by individuals in these firms, these individuals are presumed to represent their firm’s decision rather than their personal decisions. If research is directed at understanding differences in national cultures, then the unit of analysis becomes a country. Even inanimate objects can serve as units of analysis. For instance, if a researcher is interested in understanding how to make web pages more attractive to its users, then the unit of analysis is a web page (and not users). If we wish to study how knowledge transfer occurs between two firms, then our unit of analysis becomes the dyad (the combination of firms that is sending and receiving knowledge). Understanding the units of analysis can sometimes be fairly complex. For instance, if we wish to Understanding the units of analysis can sometimes be fairly complex. For instance, if we wish to study why certain neighborhoods have high crime rates, then our unit of analysis becomes the neighborhood, and not crimes or criminals committing such crimes. This is because the object of our inquiry is the neighborhood and not criminals. However, if we wish to compare different types of crimes in different neighborhoods, such as homicide, robbery, assault, and so forth, our unit of analysis becomes the crime. If we wish to study why criminals engage in illegal activities, then the unit of analysis becomes the individual (i.e., the criminal). Like, if we want to study why some innovations are more successful than others, then our unit of analysis is an innovation. However, if we wish to study how some organizations innovate more consistently than others, then the unit of analysis is the organization. Hence, two related research questions within the same research study may have two entirely different units of analysis. Understanding the unit of analysis is important because it shapes what type of data you should collect for your study and who you collect it from. If your unit of analysis is a web page, you should be collecting data about web pages from actual web pages, and not surveying people about how they use web pages. If your unit of analysis is the organization, then you should be measuring organizational-level variables such as organizational size, revenues, hierarchy, or absorptive capacity. This data may come from a variety of sources such as financial records or surveys of Chief Executive Officers (CEO), who are presumed to be representing their organization (rather than themselves). Some variables such as CEO pay may seem like individual level variables, but in fact, it can also be an organizational level variable because each organization has only one CEO pay at any time. Sometimes, it is possible to collect data from a lower level of analysis and aggregate that data to a higher level of analysis. For instance, in order to study teamwork in organizations, you can survey individual team members in different organizational teams, and average their individual scores to create a composite team-level score for team-level variables like cohesion and conflict. We will examine the notion of “variables” in greater depth in the next section C
oncepts, Constructs, and Variables We discussed in Chapter 1 that although research can be exploratory, descriptive, or Explanatory, most scientific research tend to be of the explanatory type in that they search for Potential explanations of observed natural or social phenomena. Explanations require Development of concepts or generalizable properties or characteristics associated with objects, Events or people. While objects such as a person, a firm, or a car are not concepts, their specific Characteristics or behavior such as a person’s attitude toward immigrants, a firm’s capacity for Innovation and a car’s weight can be viewed as concepts. Knowingly or unknowingly, we use different kinds of concepts in our everyday conversations. Some of these concepts have been developed over time through our shared language. Sometimes, we borrow concepts from other disciplines or languages to explain a phenomenon of interest. For instance, the idea of gravitation borrowed from physics can be used in business to describe why people tend to “gravitate” to their preferred shopping destinations. Likewise, the concept of distance can be used to explain the degree of social separation between two otherwise collocated individuals. Sometimes, we create our own concepts to describe a unique characteristic not described in prior research. For instance, technostress is a new concept referring to the mental stress one may face when asked to learn a new technology. Concepts may also have progressive levels of abstraction. Some concepts such as a person’s weight are precise and objective, while other concepts such as a person’s personality may be more abstract and difficult to visualize.
A construct is an abstract concept that is specifically chosen (or “created”) to explain a given phenomenon. A construct may be a simple concept, such as a person’s weight, or a combination of a set of related concepts such as a person’s communication skill, which may consist of several underlying concepts such as the person’s vocabulary, syntax, and spelling. The former instance (weight) is a undimensional construct, while the latter (communication skill) is a multi-dimensional construct (i.e., it consists of multiple underlying concepts). The distinction between constructs and concepts are clearer in multi-dimensional constructs, where the higher order abstraction is called a construct and the lower order abstractions are called concepts. However, this distinction tends to blur in the case of undimensional constructs. Constructs used for scientific research must have precise and clear definitions that others can use to understand exactly what it means and what it does not mean. For instance, a seemingly simple construct such as income may refer to monthly or annual income, before-tax or after-tax income, and personal or family income, and is therefore neither precise nor clear. There are two types of definitions: dictionary definitions and operational definitions. In the more familiar dictionary definition, a construct is often defined in terms of a synonym. For instance, attitude may be defined as a disposition, a feeling, or an affect, and affect in turn is defined as an attitude. Such definitions of a circular nature are not particularly useful in scientific research for elaborating the meaning and content of that construct. Scientific research requires operational definitions that define constructs in terms of how they will be empirically measured. For instance, the operational definition of a construct such as temperature must specify whether we plan to measure temperature in Celsius, Fahrenheit, or Kelvin scale. A construct such as income should be defined in terms of whether we are interested in monthly or annual income, before-tax or after-tax income, and personal or family income. One can imagine that constructs such as learning, personality, and intelligence can be quite hard to define operationally.