The Empirical Research Process


Empirical research is critical in all academic and professional disciplines as it enables practitioners to analyze problems and phenomenon and discover new knowledge that advance their field. Students are often required to undertake empirical research activities in the form of research projects, capstone projects, theses, and dissertations. This paper explains the empirical research process.

Research Aim and Objective

The research process begins by define the aim and the objective of the research. Research aim refers to the reason that has informed the research. The aim may be to solve a problem, to understand a given phenomenon, or test relationships. Objectives are specific statement on what the research process seeks to achieve. Objectives are essential as they help to clarify the intent of the researcher and the scope of the study.

Literature Review

The review of the literature represents one of the most vital steps in the research process (Onwuegbuzie, Leech & Colling, 2012). This process enables the investigator to distinguish what has already been undertaken and what need further exploration in a given research issue. The process also enables the research to understand relationships between variables, as well as, links between theory and practice.

Research Methodology

The next step in conducting an empirical research is to develop a suitable methodology for collecting and analyzing empirical data. The process of developing the methodology has a several steps.

  1. Determining the Research Approach

Scientific studies must utilize systematic and disciplined approaches of discovering knowledge using the method that best suit the research question. There are three main approaches of research; quantitative, qualitative and mixed-methods approach (Creswell, 2013). The quantitative approach utilizes the positivist research paradigm, which proposes that truth is objective; hence, it can be studied independent of context in which it occurs. This approach of research uses deductive reasoning and focuses on generalizing findings. The quantitative research approach is associated with a number of advantages included a high level of objectivity and generalizability of findings. However, the approach has disadvantages such as the inability to explain reasons behind relationships.

The qualitative research approach uses a post-positivist research paradigm, which proposes that truth is relative; hence, it must be studied in the context in which it occurs. This approach of research uses inductive reasoning to conduct an in-depth analysis of a given phenomenon. The investigator is actively engaged in the process of finding knowledge. This approach also has its advantages included the ability to provide in-depth knowledge regarding a given phenomenon. However, qualitative research approach is marred by problems of subjectivity and lack of generalizability of data. The mixed-method research design combined both the quantitative and qualitative approaches of research (Creswell, 2013). This approach uses the constructivist research paradigm, which proposes that truth is social constructed but does not take a hard-line stance regarding the existence of universal truths.

          2. Research Design

Research design is the overall strategy that the researcher uses to integrate different components of the study, thereby, tackling the research problem (Creswell, 2013). It is a blueprint that guides the processes of collecting, measuring and processing data.  The selection of research design is determined by the research problem and research questions. Research design can be defined in terms of purpose, method of data collection, and time frame. In terms of purpose, research design may be explanatory, descriptive, phenomenology, grounded theory, or explanatory. In terms of method of data collection, a research may use a census,survey, case study, or multiple-case study design. In terms of the time frame, a study can either be longitudinal or cross-sectional. A single study can apply more than one research design. For instance, a study can utilize the case study approach and still be descriptive in nature, as well as, apply the cross-section method of collecting data. The design should be consistent with the objective of the research.

         3. Selection of Participants

There are many techniques of selecting participants. However, these techniques can be split into two categories; probability sampling and non-probability sampling methods (Schindler & Cooper, 2013). Probability sampling methods seek to select participants using random methods; hence, no participant is given special consideration. These methods give all members of the population an equal chance of being selected. Probability methods of selecting participants have a number of advantages including elimination of sampling bias (Bryman & Bell, 2011). However, a significant demerit of this method is that it does not assure the appointment of participants who have the required information. Consequently, these methods of selecting participants are highly suitable for quantitative studies, whose chief objective is to generalize findings rather than qualitative studies that focus on gaining an in-depth analysis of the problem.

Conversely, non-probability methods of selecting participants do not apply random technique in the process of selecting participants. This method means that the researcher pays greater attention to some members of the population than others (Schinder & Cooper, 2013). Participants may be selected based on their availability, ease of access and their capacity to provide the required information. In this study, the researcher proposes the use of non-probability method of sampling. Specifically, the researcher proposes the use of purposive sampling methods. In this technique, participants are chosen based on their capacity to provide the required information.

         4. Instrumentation

This step entails developing the instrument for collecting data. There are numerous data collection instruments. The most common include questionnaires, interview protocols, and observation checklists. In this step, the researcher needs to determine the instrument that is most suitable for his or her research objectives. Some study may apply more than one data collection instrument.

       5. Data Collection

This step involves the actual collection of data. The method used to collect data will be determined by the research approach, the research design, and the data collection instrument. For instance, if the study is a survey and entail the use of questionnaires as the main data collection instrument, the researcher may opt to mail the questionnaire or hand deliver them to potential respondents. Each method of collecting data has its advantages and disadvantages, which the researcher should consider when making decisions regarding the method to use in his or her study.

      6. Data Analysis

The data analysis steps focuses on processing the collected data in order to develop information that is relevant to the research issue. There are many methods of data analysis, but all can be grouped into two categories: quantitative and qualitative methods of analysis. Quantitative methods of data analysis use numerical or statistical techniques to process and make sense of available data. Quantitative data analysis technique can subdivided into descriptive and inferential techniques. Descriptive techniques focus on define characteristics of available data in order to identify patterns or trends. Descriptive analytical techniques include use of percentages, frequencies, mean, median, standard deviation, and box plots. On the hand, inferential statistics focuses on making conclusion that extend beyond the existing set of data. Inferential techniques include correlation analysis, regression analysis, and cross-tabulation

Qualitative methods of data analysis do not involve the use of statistics or numerical methods. They focus on interpreting meaning, views, and experiences of the participants. Unlike in quantitative methods of data analysis, the researcher plays a central role in qualitative data analysis as qualitative methods of data analysis are founded on the interpretative philosophy. Qualitative methods of data analysis use the inductive process where individual concepts and insights are synthesized with aim of constructing patterns. Examples of qualitative methods of data analysis include content analysis, narrative analysis, discourse analysis, framework analysis, and grounded theory.  A single study can combine both qualitative and quantitative methods of data analysis. Such studies are known as mixed-method research.

       7. Data Presentation and Discussion

The final step in the empirical research process entails presenting research findings and discussing their implications. Findings can be presented using various methods including narratives, tables, and graphs. Researchers should combine different methods of presentation in order to appeal to people with different styles of learning.


Creswell, J. (2013). Qualitative Inquiry and Research Design: Choosing Among Five Approaches. New York: Sage Publications.

Onwuegbuzie, A., & Leech, N. (2007). Sampling designs in qualitative research: Making the sampling process more public. The Qualitative Report, 12 (2), 238- 254

Cooper, D., & Schindler, P. (2013). Business Research Method. New York, NY: McGraw-Hill Education.