WHAT IS RESEARCH DESIGN

The research design constitutes the blueprint for the collection, measurement, and analysis of data. It aids the scientist in the allocation of his limited resources by posing crucial choices. The blueprint of a research design includes experiments, interviews, observation, the analysis of records, simulation or some combination. The method of data collection and the research situation to be high structured. The analysis in research design should be primarily quantitative and qualitative.

Research design in the plan and structure of investigation so conceived as to obtain answers to research questions. The plan is the overall scheme or program or the research. It includes an outline of what the investigator will do from writing hypotheses and their operational implications to the final analysis of data. Structure is the framework, organization, or configuration of the relations among variables of a study. A research design expresses both the structure of the research problem and the plan of investigation used to obtain empirical evidence on relations of the problem.

The above definition differs in detail, but together they give the essentials of research design. First the design is a plan for selecting the sources and types of information used to answer the research question.. Second it is a framework for specifying the relationships among the study’s variables. Third, it is a blueprint that outline each procedure from the hypotheses to the analysis of data the design provides answers for such questions as What techniques will be used to gather data? What kind of sampling will be used? How will time and cost constraints be dealt with?

CLASSIFICATION OF DESIGN

Early in any research study one faces the task of selecting the specific design to use. A number of different design approaches exist, but unfortunately, no simple classification system defines all the variations that must be considered. We can classify research design using at least eight different perspectives.

1. The degree to which the research problem has been crystallized (the study may be either exploratory or formal).
2. The method of data collection (studies may be observational or survey)
3. The power of the researcher to produce effects in the variables under stud (the two major types of research are the experimental and the ex-post facto).
4. The purpose of the study (research studies may be descriptive or causal)
5. The time dimension (research maybe cross-sectional or longitudinal)
6. The topical scope-breadth and depth of the study (a case or statistical study).
7. The research environment (must business research is conducted in field setting, although labor try research is not unusual; simulation is an other category).
8. The subject perception of the research (do they perceive deviation from their everyday routines).

DEGREE OF PROBLEM CRYSTALLIZATION

A study may be viewed as exploratory or formal. The essential distinction between these two is the degree of structure and immediate objective or discovering future research task. The immediate purpose of exploration is usually to develop hypotheses or question for further research. The formal study begins where the exploration leaves off- it begins with the hypotheses or question and involves precise procedures and data source specifications. The goal of formal research design is to test the hypotheses or answer the research question posed.

The exploratory-formalized dichotomy is less precise than some other classification. All studies have elements of exploration in them and few studies are completely uncharted. Recall that the general project sequence, suggests that more formalized studies contain at least an element of exploration before the final choice of design.

Method of Data Collection

This classification distinguishes between monitoring and interrogation (survey) processes. The former includes observational studies, in which the researcher inspects the activities of a subject or the nature of some material without attempting to elicit response s from anyone. A traffic count at an intersection, search of the library collection, an observation of the actions of a group of decision makers all are examples of monitoring. In each case the researcher notes and records the information available from observations.

In the survey mode, the researcher questions the subject and collects their responses by personal or impersonal means. The data may result from

• Interview or telephone conversations,
• Self-report instruments sent through the mail, left in convenient locations, or transmitted electronically or through another means, or
• Instruments presented before and or after a treatment or stimulus condition in an experiment.

Researcher Control of Variables

In terms of researcher’s ability to manipulate variables, we differentiate between experimental and ex-post facto designs. In an experiment, the researcher attempts to control and or manipulate the variables in the study, It is enough that we can cause variables to be changed or held constant in keeping with our research objectives. Experimental design is appropriate when one whish to discover whether certain variables produce effects in other variables. Experimentation provides the most powerful support possible for a hypothesis of causation.

With an ex-post facto design, investigators have no control over the variables in the sense of being able to manipulate them. They can only report what has happened or what is happening. It is important that researchers using this design not influence the variables; to do so introduces basis. The researcher is limited to holding factors constant by judicious selection of subject according to strict sampling procedures and by statistical manipulation of findings.

The purpose of the study

The essential difference between descriptive and casual studies lies in their objective. If the researcher is concerned with finding out who, what, where, when, or how much, then the study is descriptive. If it is concerned with learning  why, that is, how one variable produces change in another, it is causal. Research on crime is descriptive when it measures the types of crime committed, how often, when, where, and by whom. In a causal study, we try to explain relationship among variables—for instance, why the crime rate is higher in city A than in city B.

The Time Dimension

Cross-sectional studies are carried out once and represent a “snapshot” of one point in time. Longitudinal studies are repeated over an extended period. The advantage of a longitudinal study is that it can track changes over time

In longitudinal studies of the panel variety the researcher may study the same people over time. In marketing panels are set up to report consumption data on a variety of products. These data collected from national samples, provide a major data bank on relative market share. Consumer response to new products and new promotional methods. Other longitudinal studies such as cohort groups, use different subjects for each sequenced measurement. The service industry might have looked at the needs of aging baby boomer by sampling 40 to 45 year olds in population of 1945 to 1950 cohort survivors would remain the same.

Some types of information once collected cannot be collected a second time from the same person without the risks of bias. The study of public awareness of an advertising  campaign over a six-month period would require different samples for each measurement.

The Topical Scope

The statistical study differs from the case study in several ways. Statistical studies are designed for breath rather than depth. They attempt to capture a population characteristics by making inferences from a samples characteristics. Hypotheses are tested quantitatively. Generalizations about findings are presented based on the representative ness of the sample and the validity of the design.

Case study place more emphasis on a full contextual analysis of fewer events or conditions and their interrelations. Although hypotheses are often used, the reliance on qualitative data makes support or rejection more difficult. An emphasis on detail provides valuable insight for problem solving evaluation and strategy. This detail is secured from multiple sources of information. It allows evidence to be verified and avoids missing data.

The Research Environment.

Design also differ as to whether they occur under actual environmental conditions or under other conditions. These are called field and laboratory conditions. Respectively.

To simulate is to replicate the essence of a system or process. Simulations are being used more in research especially in operations research. The major characteristics of various conditions and relationships in actual situations are often represented in mathematical models. Role playing and other behavioral activities may also be viewed as simulations.

Subject Perception

The usefulness of a design may be reduced when people in the study perceive that research is being conducted. Subject’s perceptions influence the outcomes of the research in subtle ways or more dramatically.

EXPLORATORY STUDIES

Exploratory is particularly useful when researchers lack a clear idea of the problems they will meet during the study. Through exploration the researchers develop the concepts more clearly establish priorities and improve the final research design. Exploration may also save time and money if it is decided the problem is not as important as first thought.

Despite its obvious value researchers and managers alike give exploration less attention than it deserves. There are strong pressures for quick answers and exploration is sometimes linked to old biases about qualitative research subjective ness, non representative and nonsystematic design. A wiser view is that exploration saves time and money and should not be slighted.

Mean of Exploration

The objective of exploration may be accomplished with several data collection techniques. Both qualitative and quantitative techniques are applicable although exploration relies more heavily on qualitative techniques. When we consider the scope of qualitative research several approaches are adaptable for exploratory investigations of management questions.

Secondary Data Analysis

The first step in an exploratory study is a search of the secondary literature. Studies made by others for their own purposes represent secondary data. It is inefficient to discover anew through primary data collection or original research what has already been done. There are tens of thousands of periodicals and hundreds of thousands of books on all aspects of business.

A search of secondary sources provides an excellent background and will supply many good leads if one is creative. If we confine the investigation to obvious subjects in bibliographic sources, we will often miss much of the best information.

Experience Survey

While published data are a valuable resource, seldom is more than a fraction of the existing knowledge in a field put into writing. Thus we well profit by seeking information from persons experienced in the area of study.

When we interview persons in an experience survey, we should seek their ideas about important issues or aspects of the subject and discover what is important across the subject’s range. The investigative format we use should be flexible enough so that we can explore various avenues that emerge during the interview.

Focus Groups

A focus Groups is a panel of 8 to 12 respondents led by a trained moderator. The moderator uses group dynamics principles to focus or guide the group in an exchange of ideas feelings and experiences on a clearly understood topic. The topical objective is often a new product or product concept. The output of the session is a list of ideas and behavioral observations with recommendations of the moderator.

Two-Stage Design

Research study is a two stage design  first stage with limited objective. Clearly defining the research problem and developing the research design. Thus exploration can be a preliminary study of limited scope and budget. For a two stage approach, we recognize that  much about the problem is not known but should be before effort and resources are committed. In these circumstances, one is operating in unknown areas, where it is difficult to predict the problems and cost of the study. A limited exploration for a specific, modest cost carries little risk for both parties and often uncovers information that reduces the total research cost. 

DESCRIPTIVE STUDIES

The objective of a descriptive study is to learn the who, what when, where and how of a topic. The study may be simple or complex; it ma be done in many settings. Whatever the form a descriptive study can be just as demanding of research skills as the causal study and we should insist upon the same high standards for design and execution.

The descriptive study concern a univariate question or hypothesis in which we ask about or state something about the size form distribution

CAUSAL STUDIES

Causal inferences are going to be made. Although they are not permanent nor universal they allow us to build knowledge of presumed causes over time. Such empirical conclusions provide us with successive approximations to the truth .

Causal analysis is concern with how one variable affects or is responsible for changes in another variable. Experiment found that some external factor produces a change in the dependent variable. The reciprocal relationship exists when two variables mutually influence or reinforce each other. This could occur if the reading of an advertisement leads to the use of a brand of product. The usage in turn sensitizes the person to notice and read more of the advertising of the particular brand.

Asymmetrical Relationship

The major relationships of interest to the research analyst are asymmetrical. With these relationships we postulate that changes in one variable are responsible for changes in another variable. The indentification of the independent variable(IV) and dependent variabl(DV) is often obvious, but sometimes the choice is not clear. In these latter cases we evaluate them on the basis of (1) the degree to which they may be altered and (2) the time order between them. Since age, social class, climate, world events and present manufacturing technology are relatively unalterable we normally choose them as independent variables. In business research the tuypes of asymmetrical relationships of most interest are:

1.                  Stimulus-response relationship. This represents an event or force that results in a response from some object. A price rise results in fewer unit sales a change in work rules leads to a higher level of worker output or a change in government economic policy restricts corporate financial decisions. Experiments usually involve stimulus response relationship.

2.                  Property disposition relationship. A property is an enduring characteristic of a subject that does not depend upon circumstances for its activation, Age, gender family status, religious affiliation, ethnic group, and physical condition are personal properties. A disposition is a tendency to respond in a certain way under certain circumstances. Dispositions include attitudes, opinion, habits, values and drives. Examples of property disposition relationships are the effect of age on attitudes about saving gender and its effect on attitudes towed social issues, or social class and opinions about taxation. Properties and dispositions are major concepts used in business and social science research.

3.                  Disposition behavior relationship. Behavior responses include consumption practices, work performance, interpersonal acts, and other kinds of performance. Examples of relationships between dispositions and behavior include opinions about a brand and its purchase job satisfaction and work output and moral values and tax cheating. Much of ex post facto causal research involves relationships between properties, dispositions, and behaviors.

4.                  Property behavior relationship. Examples include such relationships as the stage of the family life cycle and purchases of furniture, social class and family savings patterns, and age and sports participation. When thinking about possible causal relationships or proposing causal hypotheses, one must state the positional relationship, cause and effect.

Causation and Experimental Design

Successful inference making from experimental design must meet two other requirements. The first is referred to aas control. All factors with the exception of the independent variable must be held constant and not confounded with another variable that is not part of the study. Second each person in the study must have an equal chance for exposure to each level of the independent variable. This is random assignment of subject to groups. Here is a demonstration of how these factors are used to  detect causation. Assume you which to conduct a surve of a university’s alumni to enlist their support for a new program. There are two different appeals, one largely emotional in nature and the other much more logical in its approach. Before mailing out appeal letters to 50000 alumni.

We emphasize that random assignment of subject to experimental and control groups is the basic technique by which the two groups can be made equivalent. Matching and other control forms are supplemental ways of improving the quality of measurement. In a sense, matching and controls reduce the extraneous noise in the measurements system and in this way improve the sensitivity of measurement of the hypothesized relationship.

Causation and Ex Post Facto Design.

Most research studies cannot be carried out experimentally by manipulating variables. Yet we still are interested in the question of causation. Instead of manipulating and controlling exposure to an experimental, we study subjects who have been exposed to the independent factor and those who have not.

Ex post facto design is widely used in business research and often is the only approach feasible. In particular, one seeks causal explanations between variables that are impossible to manipulate. Not only can the variables not be manipulated, but the subjects usually cannot be assigned to treatment and control groups in advance. We often fund that there are multiple causes rather than one be careful using the ex post facto design with causal reasoning. Through testing, validating of multiple hypotheses, and controlling for confounding variables are essential.