Final PhD Project


Final Project
Explore and explain three methods of collecting primary and secondary data and determine the advantages and disadvantages of each method. Explain ethics in conducting research and how ethics is applied when collecting date. You will use a minimum of eight references for this assignment, In addition to your textbook (Cooper, 2011). Word count will be between 1000-1500 words.
Your Final Project must be comprehensive, using terminology and concepts presented in the primary textbook as well as supplementary resources. Use the ESSAY FORMAT found in the Syllabus ADDITIONAL RESOURCES to complete your project. Write in complete sentences and use good grammar, double-spacing, 12 point font, with one-inch margins. Be sure to cite your resources and provide the references using APA format. Remember to reference all work cited or quoted by the text authors. You should be doing this often in your responses. Complete and submit the Final Project.
Assignment Outcomes
Evaluate information critically and effectively
Demonstrate your overall comprehension of the course relative to a broad-based evaluation of your understanding of the course concepts


Management of Business Research Methods


Review of Subject 2

Discussion. 2

Conclusion. 5

References. 6

Review of Subject

Data collection is at the crux of every research endeavor, and it forms a major component of business research methods. In the research process, research design strategy plays a vital role in determining the way in which the entire research will be conducted. Once the researcher has figured out the type, purpose, environment and the scope of the research, focus shifts towards the development of an ideal data collection design (Barrows & Andy, 2012). The design forms the basis for instrument development which then ultimately facilitates data collection and preparation. These different steps are vital in determining data usability in research. Based on the inferences, the researcher can easily back up his or her sources in a manner that increases data reliability. The data obtained may be in either primary or secondary form. The two forms call for distinct methods of data collection and this contributes to differences in terms of validity and reliability. Essentially, primary data collection methods, which include interviews and observations are the most preferred since they yield data that is of higher quality (Remenyi, Money & Bannister, 2007).



The three most common methods of collecting primary data include interviews, observations, and questionnaires. Firstly, interviews constitute a vital primary data collection technique because it enables interviewees to share information with the researcher based on their opinions, perspective or specific understanding of the subject. In business contexts, for example, interviews may be a useful tool that a scholar can use to gather information from the middle-level managers regarding a company’s operations (Spitzer, 2007). An interview is meant to focus on the important themes that are central to the subject of the research conducted. The main scope during interviews is understanding different perspectives and understanding the central issue from a primary source (Brace, 2008) and (Cooper & Schindler, 2014). However, identifying persons taking part in an interview and establish an index based on the reliability of their information is crucial because it assists in determining the credibility of the information (Isson & Harriott, 2013).

Nevertheless, the main disadvantage with interviews as a method of collecting primary data arises from the problem of the unreliable interviewee, who may be the result of an erroneous index used when identifying the participants, a choice which leads to erroneous information being gathered. On the other hand, a correct index guarantees correct and useable information while simultaneously enhancing the credibility of the information presented in the study. Eckerson (2011) suggests that interviews ought to be followed up by questionnaires because that is an additional failsafe approach that enhances the quality of the data gathered during the research process.

Secondly, observation is a common data collection method in research circles. It only requires the researcher to use all senses in examining a phenomenon by getting involved in a prolonged engagement adequate for making a deduction. In business research, observation is useful, especially when dealing with “how” and “what” type of research questions, the behavior of people within a setting and investigations into the meaning of a setting (Hope, Jeremy, & Steve, 2012; Kenett & Silvia, 2012). The main advantage of observation is that it offers raw information, most of which the researcher can verify rather easily. The verifiability of information raises the overall level of research credibility because it puts the researcher into the position of an active participant. Its main disadvantage, though, is that it is inapplicable when deducing information on different phenomena that form the basis of a complex research process particularly in business-related fields (Tonchia & Luca, 2010).

Thirdly, questionnaires refer to a set of printed, written or digital questions related to the subject of interest, devised for purposes of a survey or statistical study (Brace, 2008).  Questionnaires are administered to respondents with the aim of gathering data related to the phenomenon under study. In business settings, they work best when administered to a large group of respondents especially after choosing a sample from the population (Wiley, 2010). Using questionnaires offers an advantage over other methods because it allows researchers access to a very large number of respondents regardless of their geographical location (Association for Talent Development, 2008). The disadvantage, though, is that they limit the respondents to only a set of questions and ultimately restrict the scope of the data that would ideally be brought forward if the respondents were to have the freedom to pore over the subject matter in general like in the case of interviews.

On the other hand, secondary data collection methods entail reliance on data that has been collected, compiled, and recorded by another party and is readily available from various sources. The very vital advantage that they offer over the primary methods is that they save the researcher time and effort required in data collection. The time-saving feature simplifies the researcher’s work especially if the study entails extensive use of quantitative data (Graen & Joni, 2009). The data-intensive nature of the quantitative approach makes it a daunting task for a researcher to generate a large and high-quality database while still working on the project. Moreover, secondary data collection methods provide descriptive information that supports research at a relatively low cost. These methods’ main disadvantage is that they bring into perspective variations in data and definition of concepts which often leads to inaccurate interpretations of study results (Cooper & Schindler, 2014). Additionally, they may bring forth outdated data that may not reflect the current reality of the phenomenon under study.


Data collection is the most important part of any research process because it ultimately determines the credibility of the findings generated. Therefore, the choice of data collection methods, particularly the decision on whether to rely on primary or secondary data, is the main driver of the decisions a researcher must make by opting for the specific choices throughout the research study. The choice of the method is highly dependent on the research model applied. For instance, the main sources of secondary include information by government authorities or departments, print, and digital journals, organizational records, books, newspapers, and all other forms of recorded information collected and compiled by other parties. Making inferences from such information is the essence of all research endeavors because of the utmost importance attributed to the very task of selecting what to include in one’s study and what not to. For instance, a researcher may consider a primary data collection method like interviewing to be less time-consuming and easier to implement in efforts to gather information from numerous interviewees. Such an argument would arise from the wide knowledge pool that the researcher stands to get, which he/she can later use for making correct inferences about the subject matter. The choice of interviews works best if the researcher is aiming to adopt the qualitative research model. The researcher not only gets data that reflects different perspectives on the subject but also gains access to quality first-hand information.


Association for Talent Development. (2008). Measurement and evaluation: Essentials for measuring training success, volume 4. London: ATD Press.

Barrows, E. & Andy Neely. (2012). Managing performance in turbulent times: analytics and insight. Denver, CO: John Wiley & Sons.

Brace, I. (2008). Questionnaire design: how to plan, structure and write survey material for effective market research, second edition. Washington, DC: Kogan Page.

Cooper, D. R. & Schindler, P. S. (2014). Business research methods (12th Edition). New York, NY: McGraw Hill.

Eckerson, W. (2011). Performance Dashboards: Measuring, Monitoring, and Managing Your Business, Second Edition. John Wiley & Sons.

Graen, G. B. & Joni, A. (Eds.). (2009). Predator’s game-changing designs: Research-based tools. Berkeley, CA: Information Age Publishing. 

Hope, Jeremy, & Steve Player. (2012). Beyond performance management why, when, and how to use 40 tools and best practices for superior performance. Boston, MA: Harvard Business Press.

Isson, J. &Harriott, J.  (2013). Win with advanced business analytics: creating business value from your data. London: Wiley & Sons

Kenett, R. S. & Silvia S. (2012). Modern Analysis of Customer Surveys: With Applications using R. John Wiley & Sons.

Remenyi, D., Money, A. & Bannister, F. (2007). The effective measurement and management of ICT costs and benefits, third edition. Los Angeles, CA: CIMA.

Spitzer, D. (2007). Transforming performance measurement: rethinking the way we measure and drive organizational success. Princeton, NJ: AMACOM.

Tonchia, S. & Luca, Q. (2010). Performance measurement: Linking the balanced scorecard to business intelligence. New York, NY: Springer.

Wiley, J. W. (2010). Strategic employee surveys: Evidence-based guidelines for driving organizational success. Amsterdam: Pfeiffer.

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