Elements of Research Design

THE RESEARCH DESIGN

In order to address your research questions, a research design is a blueprint or plan for the gathering, measuring, and analysis of data. As is evident, decisions about the research strategy (experiments, surveys, case studies, etc.), the degree of researcher interference, the location of the study (i.e., study setting), the level of analysis (unit of analysis) of the data, and temporal considerations (time horizon) are all crucial to research design.

There are multiple crucial decision points presented by every element of the research design. Needless to say, no single design is better under all conditions. You will need to make decisions instead, coming up with a design that works for the task at hand. Carefully selecting the best design options while keeping in mind the project's limitations (time, money, and/or data access, for example) and particular goals and research questions will determine the caliber of the research design. Apart from the aforementioned choices pertaining to the research design, considerations need to be made concerning the data collection technique, sample type (sampling design), measurement methodology, and analysis techniques to verify the hypotheses.

ELEMENTS OF RESEARCH DESIGN

RESEARCH STRATEGIES

An approach is a plan for accomplishing a specific objective. You can address the research questions of your study and achieve your research objective(s) with the aid of a research strategy. The selection of a specific research strategy will thus be contingent upon the research objective(s) and (kind of) research questions of your investigation, in addition to your opinion regarding the qualities of good research and pragmatic considerations like time constraints and data source accessibility.

EXPERIMENTS

A hypothetico-deductive approach to research is typically linked with experiments. Investigating causal relationships between variables is the goal of an experiment. Answers to exploratory and descriptive research questions are not as well-suited for experimental designs. The purpose of an experiment is to examine how changing the independent variable affects the dependent variable. To put it another way, the researcher purposefully modifies one or more variables, like the "reward system," in order to determine whether or not this change will affect productivity, the other variable under consideration. The most basic type of experiment design is a randomized, two-group, post-test-only study in which one group receives a treatment (let's say "piece wages"). In this case, the "hourly wages" are the comparison group. The other group? (the comparison group, in this example the “hourly wages” group) does not get the treatment.?

The researcher can ascertain whether there is a difference in the productivity of the two groups following the treatment by randomly assigning workers to the groups. We will talk more about the degree of researcher interference with the study. This will enable us to distinguish between lab and field experiments.

An experimental design is a very powerful design to use in the right situations. However, when conducting applied research to try to solve a management issue, experimental designs are not always practical. For obvious reasons, we do not want, for example, to place employees in extremely stressful situations to look into the impact of work-related stress on relationships with coworkers or customers in low-quality service settings to study the impact of service quality on customer retention.

In these situations, we might choose to use a different research approach to address the study's research questions.

SURVEY RESEARCH

A survey is a method for gathering data from or about individuals in order to characterize, contrast, or elucidate their behavior, attitudes, and knowledge (Fink, 2003). Because it enables the researcher to gather both quantitative and qualitative data on a wide range of research questions, the survey approach is highly common in business research. In fact, surveys are frequently used to gather information about subjects, occasions, or circumstances in descriptive and exploratory research.

In the business world, for example, surveys are frequently conducted regarding consumer decision making, customer satisfaction, job satisfaction, health service utilization, management information systems, and similar topics. A significant portion of these surveys are one-time inquiries. The researcher can track changes over time by continuing to conduct additional surveys.

Survey instruments usually consist of a set of questions that are organized into self-administered questionnaires that a respondent fills out on their own, either online or on paper. Structured observation and interviews are two more survey instruments.

ETHNOGRAPHY

Anthropology is the source of the research method known as ethnography. According to Markus and Fischer (1986, p. 18), the technique involves the researcher "closely observing, recording, and engaging in the daily life of another culture [...] and then writes accounts of this culture, emphasizing descriptive detail." Immersion in the specific culture of the social group under study—bankers in the City of London, for example—as well as behavior observation, conversation listening, and questioning are all part of ethnography.

Thus, its goal is to provide insight into a social group's culture and behavior by adopting a "insider's point of view."

Ethnography is closely associated with participant observation. That being said, opinions regarding the precise nature of the relationship between the two vary widely.

In some cases, participant observation and ethnography are used interchangeably in the literature. Some people view ethnography and participant observation as research approaches that entail spending a lot of time observing people and conversing with them about their thoughts, feelings, and behaviors in order to gain insight into the social group being studied (Delamont, 2004). Others feel that participant observation is more specific and tied to a particular technique of data collection, while ethnography is a more general term. According to this viewpoint, participant observation serves as the main source of ethnographic data.

Nonetheless, it is merely one technique among many that a researcher employs to develop an understanding of a culture or social group—and seldom the only one. Accordingly, one of the many techniques used in ethnographic research is observation, which involves tracking behavior over an extended period of time in the field where the study is conducted. In ethnographic research, data can also be gathered through other techniques like questionnaires and interviews.

CASE STUDIES

Information about a particular item, occasion, or activity—such as a certain business division or organization—is the main focus of case studies. In case studies, the case refers to the person, group, organization, occasion, or circumstance that the researcher is examining. A case study is based on the idea that in order to get a clear picture of an issue, one must look at the actual situation from a variety of viewpoints and angles while employing a variety of data collection techniques. According to Yin (2009), a case study is a type of research strategy that entails an empirical investigation of a specific contemporary phenomenon within its real-life context using a variety of data collection methods. It should be mentioned that case studies can offer qualitative as well as quantitative data for analysis and interpretation.

Case studies allow for the development of hypotheses just like in experimental research. All the same, no evidence can be established in favor of the alternative hypothesis if a given hypothesis has not been verified in even one additional case study.

GROUNDED THEORY

A methodical set of steps to create an inductively derived theory from the data is known as grounded theory (Strauss & Corbin, 1990). Theoretical sampling, coding, and ongoing comparison are crucial grounded theory instruments. According to Glaser and Strauss (1967, p. 45), theoretical sampling is "the process of data collection for generating theory whereby the analyst jointly collects, codes, and analyzes the data and decides what data to collect next and where to find them, in order to develop his theory as it emerges."

You compare data (like an interview) to other data (like another interview) in a never-ending comparison. Following this process, you develop a theory, which you then compare with fresh data.

It is necessary to modify your categories and theories until they better fit the data, particularly if there is a poor fit between your theory and the data (interviews). Discordant and disconfirming cases are crucial in the ongoing comparison process because they help to render categories and (grounded) theory.

ACTION RESEARCH

When consultants wish to start change processes within organizations, they occasionally engage in action research. Put differently, action research is a research methodology that aims to bring about predetermined changes. Here, the researcher starts working on an issue that is already identified, and gathers relevant data to?provide a tentative problem solution.

Then, this solution is put into practice, although it is understood that doing so could have unforeseen consequences. Following the evaluation, diagnosis, and definition of the effects, research is conducted continuously until the issue is completely resolved. The interplay between the problem, the solution, the effects or consequences, and the new solution makes action research an ongoing project.

Action research relies heavily on innovative data collection techniques as well as a rational and practical problem definition.

EXTENT OF RESEARCHER INTERFERENCE WITH THE STUDY

The degree of researcher intervention directly influences the causality or correlation of the study being conducted. A correlational study is carried out in an organic setting (like a grocery store or a manufacturing floor) with the least amount of researcher intervention with the regular course of events. To investigate the factors influencing training effectiveness, for instance, a researcher conducting a correlational study only needs to identify the pertinent variables, gather the necessary data, and conduct an analysis to draw conclusions. While conducting employee interviews and distributing questionnaires in the workplace causes some disruption to the system's regular workflow, the researcher's intervention in the regular operation of the system is minimal as compared to that caused during causal studies and experimental designs.

Researchers try to manipulate certain variables in order to examine the effects of such manipulation on the dependent variable of interest in studies aimed at establishing cause-and-effect relationships. Put another way, the researcher tampers with the events as they normally happen by purposefully altering a few variables in the environment. For instance, a researcher may alter the lighting in the workplace to different degrees in order to investigate the impact of lighting on worker performance. Significant researcher intervention with the typical and natural environment is present here. In other situations, the researcher may even wish to construct an entirely new artificial environment, similar to a laboratory, where causes and effects can be closely examined by adjusting some variables and strictly regulating others.

Therefore, in either an artificial lab setting or a natural setting, the researcher may interfere with the manipulation and control of variables in the research study to varied degrees.

STUDY SETTING: CONTRIVED AND NON-CONTRIVED

As we've just seen, business research can be conducted in two types of environments: ones that are artificial and contrived, or ones where events unfold naturally and without intervention. While most causal studies are carried out in lab settings with artificial conditions, exploratory and descriptive (correlational) studies are always carried out in no contrived environments.

Whereas the majority of causal studies are carried out in artificial lab environments, exploratory and descriptive (correlational) studies are always carried out in uncontrived environments. Field studies are research projects carried out in natural environments. Field experiments are investigations carried out in the same natural settings as the study subjects—employees, customers, managers, and the like—in order to determine cause-and-effect relationships. Here, as we've already seen, the researcher manipulates the independent variable, which impedes the events from occurring naturally.

For instance, a manager who is interested in learning how pay affects performance should increase the salary of workers in one unit, reduce the salary of workers in another unit, and do nothing to the salary of workers in a third unit. Even though the pay system is being manipulated in this instance to create a cause-and-effect link between performance and pay, the study is still carried out in a natural setting, which is why it is referred to as a field experiment.

An artificially created environment with strict controls over all extraneous factors is necessary for experiments aimed at proving a cause-and-effect relationship beyond a reasonable doubt. To see how they react to specific manipulated stimuli, similar subjects are carefully selected. These research projects? are referred to as lab experiments. To help you better understand the distinctions between a field study, which is an uncontrived setting with little researcher interference, a field experiment, which is an uncontrived setting with some researcher interference, and a lab experiment, which is a contrived setting with excessive researcher interference, allow us to provide some additional examples.

But as the aforementioned examples demonstrate, it is crucial to determine the various design details prior to starting the research study because one choice criterion may affect another. For instance, there will be very little need for the researcher to tamper with the usual course of events if one wishes to conduct an exploratory or descriptive study. However, in order to establish causal relationships, experimental designs must be set up in a lab experiment, which is artificially created, or in a field experiment, which takes place in the actual location of the events.

So far, we have distinguished between three types of research: (1) field studies, in which different factors are investigated in an authentic environment where everyday activities continue as usual with little intervention from the researcher; (2) field experiments, in which cause-and-effect relationships are studied with some interference from the researcher but still in an authentic environment where events continue as usual; and (3) lab experiments, in which the researcher investigates cause-and-effect relationships while exerting a high degree of control as well as in an artificial and purposefully created setting.

UNIT OF ANALYSIS: INDIVIDUALS, DYADS, GROUPS, ORGANIZATIONS, CULTURES

The degree of data aggregation obtained during the ensuing data analysis stage is referred to as the unit of analysis. We are interested in specific employees within the company and need to determine how to increase their motivation if, for example, the problem statement concentrates on how to increase employee motivation generally. In this case, the person is the analytical unit. We will examine the information received from each individual and consider each employee's response to be a separate source of information. The unit of analysis will be multiple two-person groups, or dyads, if the researcher is interested in studying interactions between two people.

Dyads as the unit of analysis are well-represented by analyses of husband-wife interactions in families and supervisor-subordinate relationships in the workplace. In the event that the problem statement pertains to group effectiveness, the group level will be the unit of analysis. Put another way, even if we collect pertinent data from each individual that makes up, let's say, six groups, we combine the individual data into a group set in order to observe the differences between the six groups.

When comparing various departments within an organization, data analysis is conducted at the departmental level, which means that each individual within the department is viewed as a single unit. Departments are used as the unit of analysis for comparison purposes. The proper analysis unit is determined by our research question. To investigate group decision-making patterns, for instance, we would likely look at factors like cohesiveness, group size, group structure, and the like to try and explain why decisions made by groups vary. Here, group decision-making rather than individual decision-making is our primary focus, and we will investigate the dynamics that exist in a variety of groups as well as the variables that affect group decision-making.? In such a case, the unit of analysis will be groups.

Our research question moves the unit of analysis from individuals to dyads, groups, organizations, and even nations, addressing issues that go beyond the individual to dyads, groups, organizations, and even nations. These "levels of analysis" are characterized by the lower levels being absorbed into the higher levels. Therefore, gathering and analyzing data from, let's say, sixty people is necessary if we want to study buying behavior. To investigate group dynamics, we might have to look at, say, six or more groups, collect data, and then examine the patterns in each group to analyze the information. To examine the cultural variations across nations, we must gather information from various sources and study the underlying patterns of culture in each country.

Both individuals and groups do not share the same traits (e.g., IQ, stamina), nor do they share the same qualities (e.g., structure, cohesiveness). People from different cultures have different perspectives, attitudes, and behaviors. Therefore, choices regarding the type of analysis unit are heavily influenced by the type of information obtained and the degree to which data are combined for analysis. Even as we formulate the research question, we must choose the unit of analysis because, depending on the level at which data are aggregated for analysis, the variables included in the framework, sample size, and even data collection techniques may be influenced.

TIME HORIZON: CROSS-SECTIONAL VERSUS LONGITUDINAL STUDIES

CROSS-SECTIONAL STUDIES

To address a research question, a study may be conducted in which data are collected only once, possibly over the course of a few days, weeks, or months. They are referred to as cross-sectional or one-shot studies.

PERIODICAL RESEARCH

To address the research question, however, the investigator may occasionally wish to examine subjects or phenomena over multiple time periods. To find out what effects a change in top management had, the researcher might, for example, want to compare the behavior of employees before and after the change. This study is longitudinal over time rather than cross-sectional or one-shot in nature because data are collected at two distinct times. These kinds of studies are referred to as longitudinal studies since they address research questions by collecting data on the dependent variable at two or more points in time.

Studies using experimental designs are always longitudinal in nature because data are gathered before and after a manipulation. Longitudinal field studies are also possible. A longitudinal field study would be conducted, for instance, to compare the attitudes managers in a company have toward working women now and ten years later. Nonetheless, due to the time, expense, and effort required to gather data over multiple time periods, the majority of field studies that are carried out are cross-sectional in nature. If a manager wishes to monitor specific factors (such as sales, the efficacy of advertising, etc.) over time in order to evaluate improvements or identify potential causal relationships (such as the frequency of drug testing or the relationship between sales promotions and actual sales data), longitudinal studies will undoubtedly be required. Longitudinal studies are more costly, but they provide valuable insights into the fact that employers are more willing to assist graduates in managing their careers. This shows that there might be a chance for employers to establish a "virtuous circle" of career management wherein organizational and individual efforts support one another.

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