Objectives of Research

Exploration
Description
Explanation

The main reasons / objective why researchers research is finding something for a purpose. In some cases, the purpose is exploration: exploring subject, gaining knowledge on the various aspects of the subject , discovering some of its main dimensions, and possibly planning further, more structured research.

Some research has the purpose of description, as in the Census Bureau’s report on how many Indian House Hold has toilets and accessibility of drinking water, there are, a Exit poll predicting who will win an election.

Finally, research often has the aim of explanation. In addition to knowing which candidates voters favor, we may go the next step to ask why? What kinds of voters–men or women, young or old–prefer which candidates and why?

This may seem pretty straightforward, but you’ll discover there are some twists and turns in the road. In the case of description, for example, you’ll see that the answer you get often depends heavily on your definitions. What percentage of Indian are “adventurous,” for example? You cannot answer that question without defining what you mean by “adventurous,” and the definition you choose–from among the many possibilities–will move the percentage up or down among a group of people who haven’t changed.

Such variables needs to be defined before setting up the research. Hence a purpose of the research is important to find the variables.

Ironically, we will find that this is less of a problem in the case of explanation. We will see that we might be able to say with confidence what causes people to be adventurous even if we couldn’t agree on what the term meant.

Functions of Research :

correct and examples
Collect information on subject or undertaking of people lacks or have little knowledge
develops and evaluate concepts, practices and
evaluates methods that test concepts.
obtains knowledge for practical purpose like solving problems on population ¹

Research Design

As we know that any research program is a unit of analysis in the philosophy of science. It was proposed by Imre Lakatos as the focus of a demarcation criterion that depends on the distinction between progressive and degenerating research programs. The scientific evolution of any problem must follow a sequence of steps to increase the probability that it will produce relevant data.

There are many question one must answer before the research starts.

What is the scope of the Research?
Is any previous research conducted on the topic?
Is the topic too broad?
Is Sample Data representative of population?
Can the problem really be investigated?
Can the data be Validated and Analysed?
Is the problem significant?
Can the result of the study be generalised?
What costs and time are involved in the research?
Is the planned approach appropriate to the research?

The set of questions also to be asked for the relevance of the research program:

What type of research has been done in the area previously?
What has been found in previous research?
What suggestions do other researchers make for further study?
What has been investigated?
How can the proposed study add to our knowledge of the area?
What research methods and design were used in previous studies?

Problem solving through research / financial aspects of research Design:

Research is a process that links the consumer to the marketer through information. Information used to identify and define marketing opportunities and problems; generate, refine, and evaluate marketing actions; monitor marketing performance; and improve understanding of marketing as a process. Research specifies the information required to address these issues, designs the method for collecting information, manages and implements the data collection process, analyzes the results, and communicates the findings and their implications. Research is the systematic gathering, recording, and analysis of data about issues relating to human activities.

The goal of Research is to identify and assess how changing elements of the human activities impacts social behavior. The term is commonly interchanged with market research; however, expert practitioners may wish to draw a distinction, in that market research is concerned specifically with markets, while marketing research is concerned specifically about marketing processes.

Sources of Information:

Primary Date:

Direct Data collection
Interviews
Sample collection at site
Experimental data during research
Governmental Agencies

Secondary Data:

Journals and Magazines
Newspapers and
Research Summaries
Internet
Books on the subject
Direct Interviewing
Sampling of data
Questionnaire and personal

Nature of Study:

Exponential Research

Exploratory / Exponential research is a type of research conducted for a problem that has not been clearly defined. Exploratory research helps determine the best research design, data collection method and selection of subjects. It should draw definitive conclusions only with extreme caution. Given its fundamental nature, exploratory research often concludes that a perceived problem does not actually exist. Exploratory research often relies on secondary research such as reviewing available literature and/or data, or qualitative approaches such as informal discussions with consumers, employees, management or competitors, and more formal approaches through in-depth interviews, focus groups, projective methods, case studies or pilot studies. The Internet allows for research methods that are more interactive in nature. For example, RSS feeds efficiently supply researchers with up-to-date information; major search engine search results may be sent by email to researchers by services such as Google Alerts; comprehensive search results are tracked over lengthy periods of time by services such as Google Trends; and websites may be created to attract worldwide feedback on any subject.

Applied research

Applied research in administration is often exploratory because there is need for flexibility in approaching the problem. In addition there are often data limitations and a need to make a decision within a short time period. Qualitative research methods such as case study or field research are often used in exploratory research.

There are three types of objectives in a marketing research project.

Exploratory research or formulate research
Descriptive research
Causal research

Exploratory research or formulate research: The objective of exploratory research is to gather preliminary information that will help define problems and suggest hypotheses.

Descriptive Research: The objective of descriptive research is to describe things, such as the market potential for a product or the demographics and attitudes of consumers who buy the product.

Causal research: The objective of causal research is to test hypotheses about cause-and-effect relationships.

Ethnography : Interacting closely with the decision makers

Grounded Theory : Putting forth data, integrating them at various levels to develop a theory.

Phenomenology : Seeking data and documenting the same so as to be in a position to explain the causes of various events or thought processes.

Action Research : Moving back and forth between preliminary conclusions to the respondents and studying the responses by decision- makers to the macro level changes.

Definition of terms:

For better understanding to the reader of the report, terms used in the research report or thesis must be defined. Given below are some of the examples :

Attitude: A feeling or emotion toward a fact. Learn more about employee attitude surveys.

Autonomy: The degree of unsupervised freedom granted individuals to do their work.

Benefits: Company paid or sponsored programs that benefit employees in addition to compensation.

Career Development: Company sponsored programs that prepare employees for advancement within the organization.

Climate: The general mood of the work place.

Communications: The exchange of information relating to one’s work.

Community Involvement: The degree to which the company participates in charitable events.

Company Behavior: The actions or reactions of a company in response to external or internal stimuli.

Company Image: The public perception of the organization.

Compensation: Money received for one’s work.

Competition: Those organizations who provide products or services which, if purchased by the public, reduces the revenue of the company.

Competitive Position: The company’s ability to thwart the efforts of competition.

Control Systems: The means by which the company ensures compliance with policies and procedures.

Techniques of Study

Concept and Constructs: A concept is a term that expresses an abstract idea formed by generalizing from particulars and summarizing related

A construct is a concept that has three distinct characteristics. First, it is an abstract idea that is usually broken down into dimensions represented by lower-level concepts. In other words, a construct is a combination of concepts. Second, because of its abstraction, a construct usually cannot be observed directly. Third, a construct is usually designed for some particular research purpose so that its exact meaning relates only to the context in which it is found.

Independent and Dependent Variables

For any research, we have to identify relative variables. The variables depend on the nature of environment and interaction and co-relationship with each other.

Variables are classified in terms of their relationship with one another. Independent Variables are systematically varied by the researcher and Dependent Variables are observed and their values presumed to depend on the effects of the independent variables.

Qualitative and Quantitative Research:

Qualitative Research involves several methods of data collection, such as focus group, field observation, in-depth interviews, and case studies.

Quantitative Research also involves several methods of data collection, such as telephone surveys, mail surveys and internet surveys. In these methods, the questioning is static or standardizes.

The Nature of Measurement:

A researcher assigns numerals to objects, events or properties according to certain rules. Quantifying human behaviour is difficult hence event based and probability and analogies are constructed for desired comparison between present and past data.

Validation Technique

Data validation process is most important technique researcher’s adopt while analyzing the data and information. Systematic and tagging for validation of information into various stages and levels of data collections process are defined and validated.

Collection, analysis and presentation of data

Data collection is a term used to describe a process of preparing and collecting data – for example as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record, to make decisions about important issues, to pass information on to others. Primarily, data is collected to provide information regarding a specific topic. Data collection usually takes place early on in an improvement project, and is often formalised through a data collection plan which often contains the following activity.

Pre collection activity – Agree goals, target data, definitions, methods
Collection – data collection
Present Findings – usually involves some form of sorting analysis and/or

Prior to any data collection, pre-collection activity is one of the most crucial steps in the process. It is often discovered too late that the value of their interview information is discounted as a consequence of poor sampling of both questions and informants and poor elicitation techniques. After pre- collection activity is fully completed, data collection in the field, whether by interviewing or other methods, can be carried out in a structured, systematic and scientific way.

A formal data collection process is necessary as it ensures that data gathered is both defined and accurate and that subsequent decisions based on arguments embodied in the findings are valid. The process provides both a baseline from which to measure from and in certain cases a target on what to improve.

Other main types of collection include census, sample survey, and administrative by-product and each with their respective advantages and disadvantages. A census refers to data collection about everyone or everything in a group or population and has advantages, such as accuracy and detail and disadvantages, such as cost and time. A sample survey is a data collection method that includes only part of the total population and has advantages, such as cost and time and disadvantages, such as accuracy and detail. Administrative by-product data is collected as a byproduct of an organization’s day-to-day operations and has advantages, such as accuracy, time simplicity and disadvantages, such as no flexibility and lack of control.²

A common goal for a statistical research project is to investigate causality, and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response. There are two major types of causal statistical studies: experimental studies and observational studies. In both types of studies, the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies in how the study is actually conducted. Each can be very effective. An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements. In contrast, an observational study does not involve experimental manipulation. Instead, data are gathered and correlations between predictors and response are investigated.

There are four main levels of measurement used in statistics: nominal, ordinal, interval, and ratio. Each of these have different degrees of usefulness in statistical research. Ratio measurements have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data. Interval measurements have meaningful distances between measurements defined, but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit). Ordinal measurements have imprecise differences between consecutive values, but have a meaningful order to those values. Nominal measurements have no meaningful rank order among values.

Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically, sometimes they are grouped together as categorical variables, whereas ratio and interval measurements are grouped together as quantitative variables, which can be either discrete or continuous, due to their numerical nature.

Testing hypothesis Null hypothesis

Interpretation of statistical information can often involve the development of

a null hypothesis in that the assumption is that whatever is proposed as a cause has no effect on the variable being measured.

The best illustration for a novice is the predicament encountered by a jury trial. The null hypothesis, H0, asserts that the defendant is innocent, whereas the alternative hypothesis, H1, asserts that the defendant is guilty. The indictment comes because of suspicion of the guilt. The H0 (status quo) stands in opposition to H1 and is maintained unless H1 is supported by evidence”beyond a reasonable doubt”. However,”failure to reject H0″ in this case does not imply innocence, but merely that the evidence was insufficient to convict. So the jury does not necessarily accept H0 but fails to reject H0. While one can not “prove” a null hypothesis one can test how close it is to being true with a power test, which tests for type II errors.

Stating Result:

The results section is not for interpreting the results in any way; that belongs strictly in the discussion section. You should aim to narrate your findings without trying to interpret or evaluate them, other than to provide a link to the discussion section.

For example, you may have noticed an unusual correlation between two variables during the analysis of your results. It is correct to point this out in the results section.

Speculating why this correlation is happening, and postulating about what may be happening, belongs in the discussion section.

It is very easy to put too much information into the results section and obscure your findings underneath reams of irrelevance.

If you make a table of your findings, you do not need to insert a graph highlighting the same data. If you have a table of results, refer to it in the text, but do not repeat the figures – duplicate information will be penalized.

One common way of getting around this is to be less specific in the text. For example, if the result in table one shows 23.9%, you could write….

“Table One shows that almost a quarter of…..”

Perhaps the best way to use the results section is to show the most relevant information in the graphs, figures and tables.

The text, conversely, is used to direct the reader to those, also clarifying any unclear points. The text should also act as a link to the discussion section, highlighting any correlations and findings and leaving plenty of open questions.

For most research paper formats, there are two ways of presenting and organizing the results. The first method is to present the results and add a short discussion explaining them at the end, before leading into the discussion proper.

This is very common where the research paper is straightforward, and provides continuity. The other way is to present a section and then discuss it, before presenting the next section with a short discussion. This is common in longer papers, and your discussion part of the paper will generally follow the same structure.

Be sure to include negative results – writing a results section without them not only invalidate the paper, but it is extremely bad science. The negative results, and how you handle them, often gives you the makings of a great discussion section, so do not be afraid to highlight them.

USING AN APPENDIX TO STREAMLINE WRITING THE RESULTS SECTION

If you condense your raw data down, there is no need to include the initial findings in the results, because this will simply confuse the reader.

If you are in doubt about how much to include, you can always insert your raw data into the appendix section, allowing others to follow your calculations from the start. This is especially useful if you have used many statistical manipulations, so that people can check your calculations and ensure that you have not made any mistakes.

In the age of spreadsheets, where the computer program prepares all of the calculations for you, this is becoming less common, although you should specify the program that you used and the version. On that note, it is unnecessary show your working – assume that the reader understands what a Chi Squared test, or a Students t-test is, and can perform it themselves.

Once you have a streamlined and informative results section, you can move onto the discussion section, where you begin to elaborate your findings.

References: