Importance Of Quantitative Research Across The Fields

Importance of Quantitative Research across the fields “All progress is born of inquiry. Doubt is often better than overconfidence, for it leads to inquiry, and inquiry leads to invention” is a famous Hudson Maxim in context of which the significance of research can well be understood. Increased amounts of research make progress possible. Research inculcates scientific and inductive thinking and it promotes the development of logical habits of thinking and organization. The role of research in several fields of applied economics, whether related to business or to the economy as a whole, has greatly increased in modern times. The increasingly complex nature of business and government has focused attention on the use of research in solving operational problems. Research, as an aid to economic policy, has gained added importance, both for government and business. Research provides the basis for nearly all government policies in our economic system. For instance, government’s budgets rest in part on an analysis of the needs and desires of the people and on the availability of revenues to meet these needs. The cost of needs has to be equated to probable revenues and this is a field where research is most needed. Through research we can devise alternative policies and can as well examine the consequences of each of these alternatives. Decision-making may not be a part of research, but research certainly facilitates the decisions of the policy maker. Government has also to chalk out programmes for dealing with all facets of the country’s existence and most of these will be related directly or indirectly to economic conditions. The plight of cultivators, the problems of big and small business and industry, working conditions, trade union activities, the problems of distribution, even the size and nature of defence services are matters requiring research. Thus, research is considered necessary with regard to the allocation of nation’s resources. Another area in government, where research is necessary, is collecting information on the economic and social structure of the nation. Such information indicates what is happening in the economy and what changes are taking place. Collecting such statistical information is by no means a routine task, but it involves a variety of research problems. These days nearly all governments maintain large staff of research technicians or experts to carry on this work. Thus, in the context of government, research as a tool to economic policy has three distinct phases of operation, viz., (i) investigation of economic structure through continual compilation of facts; (ii) diagnosis of events that are taking place and the analysis of the forces underlying them; and (iii) the prognosis, i.e., the prediction of future developments. Research has its special significance in solving various operational and planning problems of business and industry. Operations research and market research, along with motivational research, are considered crucial

and their results assist, in more than one way, in taking business decisions. Market research is the investigation of the structure and development of a market for the purpose of formulating efficient policies for purchasing, production and sales. Operations research refers to the application of mathematical, logical and analytical techniques to the solution of business problems of cost minimization or of profit maximization or what can be termed as optimization problems. Motivational research of determining why people behave as they do is mainly concerned with market characteristics. In other words, it is concerned with the determination of motivations underlying the consumer (market) behavior. All these are of great help to people in business and industry who are responsible for Taking business decisions. Research with regard to demand and market factors has great utility in business. Given knowledge of future demand, it is generally not difficult for a firm, or for an industry to adjust its supply schedule within the limits of its projected capacity. Market analysis has become an integral tool of business policy these days. Business budgeting, which ultimately results in a projected profit and loss account, is based mainly on sales estimates which in turn depend on business research. Once sales forecasting is done, efficient production and investment programmes can be set up around which are grouped the purchasing and financing plans. Research, thus, replaces intuitive business decisions by more logical and scientific decisions. Research is equally important for social scientists in studying social relationships and in seeking answers to various social problems. It provides the intellectual satisfaction of knowing a few things just for the sake of knowledge and also has practical utility for the social scientist to know for the sake of being able to do something better or in a more efficient manner. Research in social sciences is concerned both with knowledge for its own sake and with knowledge for what it can contribute to practical concerns. “This double emphasis is perhaps especially appropriate in the case of social science. On the one hand, its responsibility as a science is to develop a body of principles that make possible the understanding and prediction of the whole range of human interactions. On the other hand, because of its social orientation, it is increasingly being looked to for practical guidance in solving immediate problems of human relations.” In addition to what has been stated above, the significance of research can also be understood keeping in view the following points: a) To those students who are to write a master’s or Ph.D. thesis, research may mean a careerism or a way to attain a high position in the social structure; b) To professionals in research methodology, research may mean a source of livelihood; c) To philosophers and thinkers, research may mean the outlet for new

ideas and insights; d) To literary men and women, research may mean the development of new styles and creative work; e) To analysts and intellectuals, research may mean the generalizations of new theories. Thus, research is the fountain of knowledge for the sake of knowledge and an important source of providing guidelines for solving different business, governmental and social problems. It is a sort of formal training which enables one to understand the new developments in one’s field in a better way.

Kinds of Quantitative Research Design Quantitative Research is a type of empirical investigation. It means that the research focuses on verifiable observation. Most often this type of research is expressed in numbers. A researcher will represent and manipulated certain observation that they are studying. There are four basic types of quantitative research, these are: 1. Descriptive Research Design - According to Ochave (1992), the principal aim of descriptive research is to describe the nature and the time of study and to explore the causes of particular phenomenon. It is also purposive process of gathering, analyzing , classifying and tabulating data about prevailing conditions, practices, belief, processes, trends cause – effect relationship and then make adequate and accurate interpretation about such data with or without the aid of statistical methods. It is concerned with the most appropriate methods to use to come up with adequate interpretation of the data and is purposive for accurate utilization of the significant variables that needs to emphasize the true meaning of the gathered data. Classification of Descriptive Research a) Descriptive - Correlational Research - test for the relationship between two variables. Performing correctional research is done to establish what the effect of one on the other might be and how that affects the relationship. The purpose is to use two or more variables to better understand the condition of events that we encounter, to predict future conditions and events and correlation does not always mean causation (Almeida, Gaerlan & Manly, 2016). b) Descriptive - Survey Research - this research methods are employed to measure the existing phenomenon without inquiring into why it exists. In such studies, you do not take into account the relationship between the

variables. Your main intention is to use your data for problem solving rather than for hypothesis testing. Survey researches have two scopes: census and sample. Census is a survey that covers the entire population of interest. Sample survey, on the other hand, is more which deals only with a portion of the population (Sevilla, et al., 1992). c) Descriptive - Status Research - this approach to problem - solving seeks to answer question to real facts relating to existing conditions. This is a technique of quantitative description which determines the prevailing conditions in a group of cases chosen for study. Several descriptive status research stress current conditions with the assumption that things will change. They cover many traits or characteristics of the group (Calmorin & Calmorin, 2007). d) Descriptive - Analysis Research - this method of research determines or describes the nature of an object by separating it into parts. Its purpose is to discover the nature of things. The researcher should determine the composition, structure. He also determines the individual parts and units integrated into an internal system. He should consider the forces that hold them together, and the strains that tend to destroy the system apart. He analyzes what makes the system work and regulates it (Zulueta & Costales, 2003). e) Descriptive - Classification Research - this method is employed in natural sciences subjects, namely: Biology, Botany, Zoology, Phycology, Ichthyology, concology, and like. The specimens collected, indentified and classified from taxonomic order (Calmorin & Calmorin, 2007). f) Descriptive - Evaluation Research - this kind of research aims to assess the effects, impacts or outcomes of practices, policies or program (Faltado, et al. 2016). 2. Ex - Post Facto (Causal - Comparative) Research Design - it looks to uncover a cause and effect relationship. This research is not conducted between the two groups on each other. They look solely for a statistically relationship between the two variable it tries to identify, specially, how the different groups are affected by the same circumstance. Causal comparative research involves comparison. The study of two or more groups is done without focusing on their relations. The use of statistical is engaged to synthesize the data. 3. Action Research Design - this research follows a cyclical process. First, the researcher identifies a problem and determines a plan of action to address it. Then, the action plan is implemented and data is gathered to determine the effects of the action implemented. The information gathered during the implementation phase is analyzed and evaluated in order to gain a better understanding of the problem and determine the effectiveness of solution implemented. Action research is pragmatic and solution - driven, and any information gathered is used to identify and

implement a solution to the problem. This design is appropriate for community - based situations. It requires the researcher to directly relate with his or her subjects and the community. 4. Experimental Research Design - This type of research seeks to determine the effect of one or more manipulative factors upon a dependent variable under controlled condition on a carefully controlled sample. The design compares the result obtained from an experimental sample with the control sample, which is practically identical to the experimental sample except for the one aspect whose effect is being tested. According to Ochave (1992) it also blueprint of the procedure that enables the researcher to test his hypothesis by reaching valid conclusions about relationships between independent and dependent variables and its conceptual framework within which the experiment is conducted.

Strength of Quantitative Research The Advantages of quantitative research include: 1. It is objective. Since it provides numerical data, it can’t be easily misinterpreted. 2. The use of statistical techniques facilitates sophisticated analyses and allows you to comprehend a huge amount of vital characteristics of data. 3. The numerical data can be analyzed in a quick and easy way. By employing statistically valid random models, findings can be generalized to the population about which information is necessary. 4. Quantitative studies are replicable. Standardized approaches allow the study to be replicated in different areas or over time with the formulation of comparable findings. Weaknesses and Limitation of Quantitative Research According to Saunders et al. (2009), research methodology serves as the backbone of a research study. Quantitative research’s main purpose is the quantification of the data. It allows generalizations of the results by measuring the views and responses of the sample population. Every research methodology consists two broad phases namely planning and execution (Younus 2014). Therefore, it is evident that within these two phases, there likely to have limitations which are beyond our control (Simon 2011). 1. Improper representation of the target population - improper representation of the target population might hinder the researcher for achieving its desired aims and objectives. Despite of applying appropriate sampling plan representation of the subjects is dependent on the probability distribution of observed data. This may led to miscalculation of probability distribution and lead to falsity in proposition. For example, a study purpose to check the proportions of female aged between 20-30 years are applying make-up ranges of international brands. The target population in this case is the women belonging to the said age group, with both professional and non-professional backgrounds, residing in Delhi. The sampled population based on the probability distribution has to be calculated against the total females residing in the city (e.g. 400 sampled out 7,800,615 female populations). However, there is a scope of getting partial information about the range of makeup products from the sampled, owing to its meager form against the total population. Hence, the results of the study cannot be generalized in context to a larger population, but rather be suggested. 2. Lack of resources for data collection- Quantitative research methodology usually requires a large sample size. However due to the lack of resources this large-scale research

becomes impossible. In many developing countries, interested parties (e.g., government or non-government organizations, public service providers, educational institutions, etc.) may lack knowledge and especially the resources needed to conduct a thorough quantitative research (Science 2001). 3. Inability to control the environment - Sometimes researchers face problems to control the environment where the respondents provide answers to the questions in the survey (Baxter 2008). Responses often depend on particular time which again is dependent on the conditions occurring during that particular time frame. For example, if data for a study is collected on residents’ perception of development works conducted by the municipality, the results presented for a specific year (say, 2009), will be held redundant or of limited value in 2015. Reasons being, either the officials have changed or the development scenario have changed (from too effective to minimal effective or vice versa). 4. Limited outcomes in a quantitative research - Quantitative research method involves structured questionnaire with close ended questions. It leads to limited outcomes outlined in the research proposal. So the results cannot always represent the actual occurring, in a generalized form. Also, the respondents have limited options of responses, based on the selection made by the researcher. For example, answer to a question– “Does your manager motivates you to take up challenges”; can be yes/no/can’t say or strongly agree to strongly disagree. But to know what are the strategies applied by the manager to motivate the employee or on what parameters the employee does not feel motivated (if responded no), the researcher has to ask broader questions which somewhat has limited scope in close-ended questionnaires 5. Expensive and time consuming - Quantitative research is difficult, expensive and requires a lot of time to be perform the analysis. This type of research is planned carefully in order to ensure complete randomization and correct designation of control groups (Morgan 1980). A large proportion of respondents is appropriate for the representation of the target population. So, as to achieve in-depth responses on an issue, data collection in quantitative research methodology is often too expensive as against qualitative approach. For example, to understand the influence of advertising on the propensity of purchase decision of baby foods parents of 5-year old and below of Bangalore, the researcher needs collect data from 200 respondents. This is time consuming and expensive, given the approach needed to each of these parents to explain the study purpose. 6. Difficultly in data analysis - Quantitative study requires extensive statistical analysis, which can be difficult to perform for researchers from non- statistical backgrounds. Statistical analysis is based on scientific discipline and hence difficult for non-mathematicians to perform. Quantitative research is a lot more complex for social sciences, education, anthropology and psychology. Effective response should depend on the research problem rather than just a simple yes or no response. For example, to understand the level of motivation perceived by Grade 5 students from the teaching approach taken by their class teachers, mere yes and no might lead to ambiguity in data collection and hence improper results. Instead a detailed interview or focus group technique might develop in-depth views and perspectives of both the teachers and children. 7. Requirement of extra resources to analyze the results - The requirements for the successful statistical confirmation of result is very tough in a quantitative research. Hypothesis is proven with few experiments due to which there is ambiguity in the results. Results are retested and refined several times for an unambiguous conclusion (Ong, 2003). So it requires extra time, investment and resources to refine the results.