Limitations and weakness of quantitative research methods

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 generalisations 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). 

Improper representation of the target population

As mentioned in the article, 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 purports to check the proportion 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 meagre form against the total population. Hence, the results of the study cannot be generalised in context to a larger population, but rather be suggested.

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 organisations, public service providers, educational institutions, etc.) may lack knowledge and especially the resources needed to conduct a thorough quantitative research (Science 2001).

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).

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 generalised 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

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.

Difficulty 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.

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Requirement of extra resources to analyse 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.

References

  • Barbour, R.S., 2000. The role of qualitative research in broadening the “evidence base” for clinical practice. Journal of Evaluation in Clinical Practice, 6(2), pp.155–163.
  • Baxter, P., 2008. Qualitative Case Study Methodology: Study Design and Implementation for Novice Researchers. The Qualitative Report, 13(4), pp.544–559.
  • Bowen, G.A., 2006. Document Analysis as a Qualitative Research Method. Qualitative Research Journal, 9(2), pp.27 – 40.
  • Elo, S. & Kyngäs, H., 2008. The qualitative content analysis process. Journal of Advanced Nursing, 62(1), pp.107–115.
  • Maxwell, J.A., 2005. Qualitative Research Design: An Interactive Approach, SAGE Publications. Available at: https://books.google.co.in/books/about/Qualitative_Research_Design.html?id=XqaJP-iehskC&pgis=1 [Accessed May 20, 2015].
  • Morgan, G., 1980. The Case for Qualitative Research. Academy of Management Journal, 5(4), pp.491–500.
  • Ong, S.-E., 2003. Mass spectrometric-based approaches in quantitative proteomics. Methods, 29(2), pp.124–130.
  • Saunders, M., Lewis, P. & Thornhill, A., 2009. Research Methods for Business Students 5th ed., Essex, England: Pearson Education Limited.
  • Science, J. of D., 2001. Invited Review: Integrating Quantitative Findings from Multiple Studies Using Mixed Model Methodology. Journal of Dairy Science, 84(4), pp.741–755.
  • Simon, M.K., 2011. Dissertation and scholarly research: Recipes for success, Seattle, W.A.: Dissertation Success LLC.
  • Younus, M.A.F., 2014. Research Methodology. In Vulnerability and Adaptation to Climate Change in Bangladesh: Processes, Assessment and Effects (Springer Theses). Springer, pp. 35–76. Available at: http://link.springer.com/10.1007/978-94-007-5494-2_2 [Accessed August 1, 2016].
Importance of ethical considerations in a research

Priya Chetty

Partner at Project Guru
Priya is a master in business administration with majors in marketing and finance. She is fluent with data modelling, time series analysis, various regression models, forecasting and interpretation of the data. She has assisted data scientists, corporates, scholars in the field of finance, banking, economics and marketing.
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