Lesson 1, Topic 1
In Progress

Research Strategies


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A strategy is a plan for achieving a certain goal. A research strategy will help you to meet your research objective(s) and to answer the research questions of your study. The choice for a particular research strategy will therefore depend on the research objective(s) and (the type of) research questions of your study, but also on your viewpoint on what makes good research and on practical aspects such as access to data sources and time constraints.

Experiments

Experiments are usually associated with a hypothetico‐deductive approach to research. The purpose of an experiment is to study causal relationships between variables. Experimental designs are less useful or appropriate for answering exploratory and descriptive research questions. In an experiment, the researcher manipulates the independent variable to study the effect of this manipulation on the dependent variable. In other words, the researcher deliberately changes a certain variable (or certain variables), for instance “reward system”, to establish whether (and to what extent) this change will produce a change in another variable, in this example “productivity”. The simplest experimental design is a two‐group, post‐test‐ only, randomized experiment, where one group gets a treatment, for instance “piece wages”.
The other group (the comparison group, in this example the “hourly wages” group) does not get the treatment. Subjects (workers) are randomly assigned to the groups and hence the researcher is able to determine whether the productivity of the two groups is different after the treatment. Later on in this chapter, we will have more to say about the extent of researcher interference with the study and the study setting. This will help us to make a distinction among field experiments and lab experiments. Under the right circumstances, an experimental design is a very strong design to use. However, experimental designs are not always feasible in an applied research context where the researcher tries to solve a management problem. For instance, we do not want (for obvious reasons) to assign customers to a low service quality treatment to study the effect of service quality on customer retention or assign workers to highly
stressful situations to investigate the effect of work‐related stress on personal and professional relations. In such cases, we may opt for an alternative research strategy to answer the research questions of their study.

Survey research

A survey is a system for collecting information from or about people to describe, compare, or explain their knowledge, attitudes, and behavior. The survey strategy is very popular in business research, because it allows the researcher to collect quantitative and qualitative data on many types of research questions. Indeed, surveys are commonly used in exploratory and descriptive research to collect data about people, events, or situations. For instance, in a business context, surveys are often taken on the subject of consumer decision making, customer satisfaction, job satisfaction, the use of health services, management information systems, and the like. A large number of such surveys are one‐time surveys. Other surveys are continuing, allowing the researcher to observe changes over time. The questions in survey instruments are typically arranged into self‐administered questionnaires that a respondent completes on his or
her own, either on paper or via the computer. Other survey instruments are interviews and structured observation.

Ethnography

Ethnography is a research strategy that has its roots in anthropology. It is a strategy in which the researcher “closely observes, records, and engages in the daily life of another culture [. . .] and then writes accounts of this culture, emphasizing descriptive detail” (Markus & Fischer, 1986, p. 18). Ethnography involves immersion in the particular culture of the social group that is being studied (such as, for instance, bankers in the City of London), observing behavior, listening to what is said in conversations, and asking questions. It thus aims to generate an understanding of the culture and behavior of a social group from an “insider’s point of view.” Participant observation is closely related to ethnography. However, different people have different ideas about the exact relationship between the two. Ethnography and participant observation are sometimes used interchangeably in the literature. For some, both ethnography and participant observation are research strategies that involve spending long periods watching people and talking to them about what they are doing, thinking, and saying, with the objective of generating an understanding of the social group under study (Delamont, 2004). For others, ethnography is a more inclusive term, whereas participant observation is more specific and related to a particular method of data collection. From this perspective, participant observation is a primary source of ethnographic data. However, it is just one of a number of methods, and rarely the only method, used by a researcher to generate an understanding of a culture or a social group. Along these lines, observation – observing behavior through a long‐term engagement in the field setting where ethnography takes place – is regarded as one of several methods for ethnographic research. Other methods, such as interviews and questionnaires, may also be used to collect data in ethnographic research.

Case studies

Case studies focus on collecting information about a specific object, event or activity, such as a particular business unit or organization. In case studies, the case is the individual, the group, the organization, the event, or the situation the researcher is interested in. The idea behind a case study is that in order to obtain a clear picture of a problem one must examine the real‐life situation from various angles and perspectives using multiple methods of data collection. Along
these lines, one may define a case study as a research strategy that involves an empirical investigation of a particular contemporary phenomenon within its real‐life context using multiple methods of data collection (Yin, 2009). It should be noted that case studies may provide both qualitative and quantitative data for analysis and interpretation. As in
experimental research, hypotheses can be developed in case studies as well. However, if a particular hypothesis has not been substantiated in even a single other case study, no support can be established for the alternate hypothesis developed.

Grounded theory

Grounded theory is a systematic set of procedures to develop an inductively derived theory from the data (Strauss &Corbin, 1990). Important tools of grounded theory are theoretical sampling, coding, and constant comparison. 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” (Glaser & Strauss, 1967, p. 45). In constant comparison you compare data (for instance, an interview) to other data (for instance, another interview). After a theory has emerged from this process you compare new data with your theory. If there is a bad fit between data (interviews), or between the data and your theory, then the categories and theories have to be modified until your categories and your theory fit the data. In constant comparison,
discrepant and disconfirming cases play an important role in rendering categories and (grounded) theory.

Action research

Action research is sometimes undertaken by consultants who want to initiate change processes in organizations. In other words, action research is a research strategy aimed at effecting planned changes. Here, the researcher begins with a problem that is already identified, and gathers relevant data to provide a tentative problem solution. This solution is then implemented, with the knowledge that there may be unintended consequences following such implementation. The effects are then evaluated, defined, and diagnosed, and the research continues on an ongoing basis until the problem is fully resolved. Thus, action research is a constantly evolving project with interplay among problem, solution, effects or consequences, and new solution. A sensible and realistic problem definition and creative ways of collecting data are critical to action research.

Cross-sectional studies

A study can be undertaken in which data are gathered just once, perhaps over a period of days or weeks or months, in order to answer a research question. Such studies are called one‐shot or cross‐sectional studies (see the following example). The purpose of the studies in the two following examples was to collect data that would be pertinent to finding the answer to a research question. Data collection at one point in time was sufficient. Both were cross-sectional
designs.

Longitudinal studies

In some cases, however, the researcher might want to study people or phenomena at more than one point in time in order to answer the research question. For instance, the researcher might want to study employees’ behavior before and after a change in the top management, so as to know what effects the change accomplished. Here, because data are gathered at two different points in time, the study is not cross‐sectional or of the one‐shot kind, but is carried
longitudinally across a period of time. Such studies, as when data on the dependent variable are gathered at two or more points in time to answer the research question, are called longitudinal studies. Longitudinal studies take more time and effort and cost more than cross‐ sectional studies. However, well‐planned longitudinal studies can, among other things, help to identify cause‐and‐effect relationships. For example, one could study the sales volume of a product before and after an advertisement, and provided other environmental changes have not impacted on the results, one could attribute the increase in the sales volume, if any, to the advertisement. If there is no increase in sales, one could conclude that either the advertisement is ineffective or it will take a longer time to take effect.
Experimental designs invariably are longitudinal studies, since data are collected both before and after a manipulation. Field studies may also be longitudinal. For example, a study of the comparison data pertaining to the reactions of managers in a company toward working women now and ten years later will be a longitudinal field study. Most field studies conducted, however, are cross‐sectional in nature often because of the time, effort, and costs involved in
collecting data over several time periods. Longitudinal studies will certainly be necessary if a manager wants to keep track of certain factors (e.g., sales, advertising effectiveness, etc.) over a period of time to assess improvements, or to detect possible causal connections (sales promotions and actual sales data; frequency of drug testing and reduction in drug usage, etc.). Though more expensive, longitudinal studies offer some good insights.