{"id":8190,"date":"2017-10-30T11:17:42","date_gmt":"2017-10-30T10:17:42","guid":{"rendered":"https:\/\/www.munich-business-school.de\/insights\/?p=8190"},"modified":"2023-07-04T09:27:12","modified_gmt":"2023-07-04T07:27:12","slug":"qualitative-vs-quantitative-research","status":"publish","type":"post","link":"https:\/\/www.munich-business-school.de\/insights\/en\/2017\/qualitative-vs-quantitative-research\/","title":{"rendered":"Qualitative Vs. Quantitative Research"},"content":{"rendered":"\n

When reading academic texts, it is helpful to understand the underlying paradigms and research philosophy the author uses in order to fully appreciate the contents. An understanding of academic worldviews is crucial when assessing or writing academic texts as they determine methodology and methods. Both quantitative and qualitative research methods also use distinct vocabulary, which academics instantly recognize and attribute to the respective philosophical framework and methodology.<\/strong><\/p>\n\n\n\n

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All scientific research<\/a> follows a set of procedures that must begin with a group of assumptions, a set of beliefs, a paradigm (Hiles, 1999). These underlying philosophical assumptions structure beliefs about methodology, knowledge and reality (Hathaway, 1995). Particularly in qualitative research it is necessary to understand the researchers\u2019 philosophical assumptions, as beliefs and theories inform their work (Creswell, 2012).<\/p>\n\n\n\n

Philosophy, methodology and methods – differences between qualitative and quantitative research<\/h2>\n\n\n\n

The nature of methodology therefore depends on the researcher\u2019s worldview (Capaldi & Proctor, 2005): Does they believe that there is one objective truth that can be uncovered? Is human behavior viewed as regular and predictable? If this is the case, the objective of research is to describe and explain reality and thus be able to predict. Consequently, objectivity is critical and the approach taken needs to be systematic so that the study can be replicated at any time (Lincoln & Guba, 1985). That approach is widely used in natural sciences and medicine, but also in economics and business, particularly in finance.<\/p>\n\n\n\n

However, human nature, which is researched in social sciences, education, anthropology and psychology, is too complex to be limited to a simple yes or no answer (Shuttleworth, 2008). Human behavior may be considered to be highly personal and situational and is subject to dynamic change over the course of time. Consequently, the researcher may believe that there is not necessarily one single, objective truth, but multiple realities depending on the individuals\u2019 subjective experience (Capaldi & Proctor, 2005).<\/p>\n\n\n\n

Qualitative research<\/strong> offers a systematic approach to studying a phenomenon within a particular context (Gast, 2010). It is exploratory and attempts to develop explanations (Lincoln & Guba, 1985). Phenomena are examined in breadth and depth, which is particularly useful when problems are in a preliminary stage (Babbie, 1989). The data collected usually consist of verbal reports of lived experience (Capaldi & Procter, 2005). Data is often generated by means of interviews, direct observation, to the analysis of artifacts, documents and cultural records, visual materials or personal experience (Denzin & Lincoln, 1994). The data is analyzed with the aim of formulating hypotheses.<\/p>\n\n\n\n

Quantitative studies<\/strong> on the other hand focus on proving or disproving hypotheses in a cause-effect manner by means of taking a close look at pre-defined variables (Shuttleworth, 2008). Quantitative data consists of numbers that are obtained by using structured and validated data-collection instruments and statistically analyzed. The findings should be generalizable and thus can be applied to other populations, being able to look at cause and effect as well as making predictions (Leung, 2015). Data is often generated by means of surveys, interviews with close-ended questions and experiments in a controlled environment in order to isolate causal effects (Kelley et al., 2003).<\/p>\n\n\n\n

Researchers and participants<\/h2>\n\n\n\n

On that basis, the role of the researcher differs significantly in qualitative and quantitative research (Sciarra, 1999).<\/p>\n\n\n\n

Based on the assumption that quantitative research<\/strong> is value-free and must not be influenced by the values of the researcher, they does not need to be known to participants. In order to avoid bias, double blind studies may be designed to exclude effects of expectation like demand characteristics (the researcher unwittingly gives clues on the expected answer or behavior) and the placebo effect (people experience a benefit from fake medical treatment, if they expect it to work) (Land, 2001).<\/p>\n\n\n\n

In qualitative studies<\/strong> however, there is much more focus on the researcher and participants as individual persons. Depending on the philosophical framework, participants may even be viewed as co-researchers (Waters, 2017). Therefore, it is well possible that participants know about the researcher\u2019s bias and the researcher knows about participant characteristics.<\/p>\n\n\n\n

Naturally, participants of qualitative and quantitative studies are selected using different criteria. As quantitative studies aim at statistically relevant results, they need to collect data from large numbers of participants.<\/p>\n\n\n\n

Sampling in qualitative and quantitative research<\/h2>\n\n\n\n

In quantitative research<\/strong>, samples are ideally selected in a way that allows generalizing the study\u2019s results to the population as a whole, thus achieving external validity (Bryman & Bell, 2007). As the composition of a quantitative study\u2019s participants is crucial for the quality of the results, there are a number of clearly structured varieties of sampling. Quantitative research prefers a probability sampling approach, with its sub-forms of random sampling, stratified sampling, systematic sampling, and cluster random sampling or a combination of these (Center for Innovation in Research and Teaching, 2017).<\/p>\n\n\n\n

Such clear sampling criteria usually do not work for qualitative research<\/strong> as the number of participants is much smaller and statistically relevant results are not sought. These relatively small samples should be selected purposefully (Patton, 2002). Thus, the aim is to select information-rich cases for in-depth study, from which issues of central importance to the purpose of the research can be learnt (Patton, 2002).<\/p>\n\n\n\n

The final report detailing the results of the study obviously is structured differently according to the respective research type. The analysis of a qualitative study consists of a narrative report with contextual description. This is underpinned by means of direct quotations from participants taken from interview transcripts (Lichtman, 2006).<\/p>\n\n\n\n

Mixed Methods Approach<\/h2>\n\n\n\n

Both qualitative and quantitative research can contribute to the academic body of knowledge and can complement each other (Wilson, 1986). So, a mixed methods approach can be used to combine the advantages of both methodologies and mitigate their weaknesses. Amongst researchers, that approach is quite disputed as it is difficult to justify the importance of either method.<\/p>\n\n\n\n

For example, quantitative experiments are useful for testing the results gained by qualitative experiments as they lead to a final answer and narrow the number of possible directions for follow up research (Shuttleworth, 2008).
In spite of the fact that there is a large variety of mixed methods designs, there are only four typical designs (adapted from Creswell & Plano Clark, 2007):<\/p>\n\n\n\n

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  1. Triangulation <\/strong>combines qualitative and quantitative data from every participant, e.g. questionnaire and interview.<\/li>\n\n\n\n
  2. In embedded design<\/strong>, either quantitative or qualitative research prevails while the respective other method is embedded, e.g. questionnaire plus additional interviews clarifying context.<\/li>\n\n\n\n
  3. Explanative design<\/strong> implies a study with two consecutive phases: starting off with a quantitative and subsequently conducting a qualitative study, e.g. experiment or questionnaire and subsequent qualitative interview. Thus, quantitative results can be illuminated and statistical relevance can be attributed to qualitative results.<\/li>\n\n\n\n
  4. Exploratory design<\/strong> works the other way round: starting with a qualitative part with a subsequent quantitative study, e.g. questionnaire is developed on the basis of qualitative interviews. This way, qualitative results can be generalized whilst quantitative elements get closer to reality.<\/li>\n<\/ol>\n\n\n\n

    This shows that the researcher\u2019s worldview determines the types of questions asked and the means of gathering and analyzing data to answer it. Both qualitative and quantitative approaches have their specific strengths and weaknesses. Knowledge about underlying philosophy, methodology, and terminology makes understanding easier and enables readers to fully appreciate academic research.<\/p>\n\n\n\n

    Literature<\/strong>: <\/p>\n\n\n\n