In quantitative research, quantitative methods accentuate measurements that are objective. Moreover, this method of research uses statistical, mathematical or numerical analysis of data collected through various means such as questionnaires, polls, surveys and the manipulation of pre-existing data that is statistical using computational techniques. As such, research that is quantitative places its focus on the gathering of numerical data and the generalization of it across various groups of people to bring about an explanation of a particular phenomenon of occurrence. The primary objective of conducting quantitative research is the study of determination in the relationship between an independent variable and the outcome or dependent variable within a population setting. As such, most quantitative research designs are descriptive, in that, the measurement of subjects usually occurs once, or are experimental, in that, the measurement of subjects occur before and after the treatment. In experimental studies, the establishment of causality takes place while in descriptive studies, the associations between variables are assessed. In business administration, the application of quantitative research is highly pertinent and usually aids in the understanding of subjects in relation to the various variables in question (Brandimarte, 2011). This paper discusses the use of quantitative research in the decision-making process within business administration. Further, it describes quantitative methods, evaluating their efficacy and finally provides opinions regarding the future of quantitative research in business administration.
Quantitative research has various data collection and analysis methods. To comprehend these methods, it is imperative to familiarize with the major characteristic nature of quantitative research as it relates to business and in particular, its administrative attribute. Fundamentally, quantitative research deals in logic, numbers and a stance that is objective. Through focusing on unchanging numerical data, quantitative research develops convergent reasoning rather than divergent understanding. Divergent reasoning, common in qualitative research provides a generation of a variety of ideas concerning research premises that are spontaneous and free flowing in nature. The major characteristics of quantitative research in administration include the fact that data gathering occurs using structured research instruments; the basis of results through using large sample sizes, demonstrative of the overall population; the definition of research questions through which objective answers evolve; and the use of pertinent tools for numerical data collection (Brandimarte, 2011). In satisfying these characteristics, quantitative research becomes applicable and highly relevant within the field of administrative business. More things to keep in mind include the description of assumptions; the explanation of collected data; the reporting of unexpected events; the choice of minimally sufficient statistical procedures among others.
Delegate your assignment to our experts and they will do the rest.
In business administration, quantitative research employs data collection and analysis methods that work on numerical data primarily. In research, data collection is highly imperative since it helps the research to come up with resolutions and answers to pertinent problems within a phenomenon of an objectified premise. Further, it also helps in the improvement of the decision-making process within a business setting; resulting in the making and effecting of quality decisions relevant to relatable business processes. As such, these processes of data collection include the use of quantitative surveys, which employ open-ended questions enquired through answer options and structured interviews that use one-to-one engagements on open-ended questions. Such interviews take on various forms including face-to-face data gathering; online or web-based interviews and telephones; and interviews that are computer-assisted. Such techniques of data collection are highly efficient, especially in business administration. For example, the use of online web-based questionnaires in a business setting saves time and accords the much-needed convenience to deliver work while at the same time to participate in a research study. In a quantitative research analysis, methods such as regression analysis, linear programming, factor analysis, and data mining are essential for the provision of accurate and objectified conclusions to proposed premises (Hall, 2017).
Various companies employ the use of quantitative research for multiple purposes including administrative studies. Good examples of quantitative reasoning in businesses include strategies and studies such as the feasibility studies, statistical analysis, cost-benefit analysis, and break-even analysis. Such quantitative analytical methods are imperative in creating a successful business flow that results in both productivities and innate understanding. Overall, quantitative research continues to have relevance in the future and is applicable in numerous fields not only in business administration but also in other business prospects as well. As the future beckons, quantitative research will become more objective and reliable using statistics to generalize pertinent findings. Moreover, the future will bring about quantitative research methods that restructure and reduce complex problems into a partial number of workable variables, easily interpreted and comprehended, thereby, resulting in the formulation of applicable hypotheses and conclusions. Within the business administration, and in quantitative research in general, the present move towards the age of social networking as a communication option and a mode of interaction brings about the implication that there will no longer be a limit on data collection to the conventional interview, survey, and ethnographic methodologies.
Ultimately, business requires quantitative research immensely. Although quantitative research is applicable in pertinent business settings such as finance, its applicability in an administrative capacity is somewhat limited since administration primarily observers phenomena and the behaviors of people. In addition, through facing the threat of self-report datasets, present studies are migrating from the traditional methods of data collection and analysis to more real-time data availability and instantaneous analytics ("The Future of Quantitative Data Collection," 2017). Such data interpretations are extremely relevant in the analysis of behavioral tendencies common within business administration spheres. Presently, this shift is gaining profound social and commercial implications.
References
Brandimarte, P. (2011). Quantitative Methods: An Introduction for Business Management . John Wiley & Sons.
Hall, S. (2017). Quantitative Methods for Business Decisions . Smallbusiness.chron.com . Retrieved 22 October 2017, from http://smallbusiness.chron.com/quantitative-methods-business-decisions-61671.html
The Future of Quantitative Data Collection . (2017). NBSPRN . Retrieved 22 October 2017, from http://www.policyresearchnetwork.ca/the-future-of-quantitative-data-collection/
