Contrasting and Comparing Qualitative and Quantitative Research Approaches: Objectives, Scope, and Philosophical Underpinnings

  • 14 Pages
  • Published On: 21-10-2023


Research is a systematic and methodological enquiry into a decided topic for study (Kothari, 2004; Collis & Hussey, 2009). Being systematic, research involves the adherence to a process that would take the researcher from the initial abstract ideas or perceptions to the ultimate specific findings and discoveries. Being methodological, research involves the structuring of the research process through the use of a specific research methodology and research design. Research must have a purpose and clear objective in order to be amenable to a structure and design (Saunders, et al., 2012).

The structuring of the research design is done as per the philosophical underpinnings of the researcher. These philosophical underpinnings include positivist, interpretivist, pragmatic or realist philosophies (Creswell, 2013). Depending upon the philosophy chosen, the researcher would then be able to decide upon the research design and choose the approach that is best suited to the research design. As such, research approaches may be qualitative or quantitative. These approaches are completely contrasted in their methodologies and processes (Creswell, 2013).


This essay contrasts and compares the two approaches, that is, qualitative and quantitative approaches, in their objectives, scope and philosophical underpinnings. The essay first discusses the different research philosophies and approaches that may be chosen by the researcher in order to understand the relation of these philosophies and approaches in the context of qualitative and quantitative approaches. Then the essay discusses in detail the two approaches as well as the commonly used methods of data collection and analysis within these approaches.

The value of research, research philosophy and approaches

Research is a systematic enquiry or investigation into a selected topic or it can also be said to be an art of scientific investigation (Kothari, 2004, p. 1). It can be defined as a process of enquiry and investigation, in a manner that is systematic and methodical and which leads to an increase in knowledge in the given area of research (Collis & Hussey, 2009, p. 3). As research methodology involves to process of conducting research from theoretical foundations to data collection (Kothari, 2004), analysis and disclosure of findings (Collis & Hussey, 2009).

Understanding research philosophy is essential for knowing how research is approached as the choice of research philosophy has a very strong impact on the research design, or in other words, the choice of research philosophy underpins the choice of research design (Wilson, 2014). Therefore, whether the researcher chooses qualitative or quantitative approach, will also depend greatly on the research philosophy that underpins the research. It can therefore be said that research philosophy comes at an initial stage of research where the choice of the philosophy leads on to the creation of the research design (Saunders, et al., 2012). Also, research philosophy is beneficial because it lends support to a researcher for identifying data, and the collection and analysis methods. It helps to fix on the appropriate research design and also leads to broadening of researcher’s knowledge of a new research design (Easterby-Smith, et al., 2002).

At this point, it is pertinent to understand the research philosophies and the outreach of these philosophies. In general, there are four principal research philosophies, which are, Realism, Interpretivism, Positivism, and Pragmatism (Creswell, 2013). These philosophies differ in their outreach and research scholars, who choose to be guided by a particular research philosophy would structure their research design according to the philosophy. This has implications for qualitative and quantitative approaches as well, because each would be guided by a specific philosophy which would not really fit with the other kind of research design. For example, Interpretivism generally has strong interconnections with qualitative research and pragmatic philosophy may be related to quantitative research methods (Collis & Hussey, 2009).

The research onion design is useful in understanding the research philosophies, approaches and methods (Saunders, et al., 2012). This design is discussed here.

The research onion design is useful

Table 1: The Research Onion helps by depicting the order and the sequence of research methodology components (Saunders, et al., 2012)

As is depicted in the research onion, research starts with the choosing of the research philosophy (Saunders, et al., 2012). Then, the researcher may choose the approach, that is inductive or deductive. Once the approach is chosen, the researcher may choose the method, that is qualitative or quantitative. Once the method is chosen, the researcher would be able to choose the method or methods of data collection. For instance, semi-structured interviews are a method for qualitative research. Then the data collection and analysis can be done as per the method chosen by the researcher.

There are five research philosophies that are identified in the onion. These are: Positivism, Critical Realism, Interpretivism, Post-modernism and Pragmatism. Here, some explanation of these philosophies is desirable for the purpose of relating these philosophies to the research design.

Realism is concerned with the nature of scientific practice and to that point it can be empirical and critical (Bryman & Bell, 2015). Empirical realism postulates that with the use of appropriate methods, reality can be understood, whereas critical realism postulates the existence of the reality of the natural world and the need to identify relevant structures that guide events (Bryman & Bell, 2015, p. 29). Interpretivism is critical of the use of scientific realist method in social research and on the other hand, the focus is on the epistemological consideration of the researchers’ views (Saunders, et al., 2012). Positivism is based on objectivism and its approach is scientific and it uses scientific methods of enquiry, where the researcher is not overly concerned with the participants’ world for the purpose of formulating judgement and conclusion (Easterby-Smith, et al., 2002). Post modernism philosophy relates to post-colonial and capitalism (Dickens & Fontana, 2015) and it questions the existence of a dispassionate social scientist who is trying to uncover a pre-existing social reality, as for port-modernist philosophy, research itself is coloured by the existence of preconceived notions (Bryman & Bell, 2015, p. 715).

Here, these philosophies also underpin the research design that is finally chosen by the researcher (Saunders, et al., 2012). Interpretivism focuses on the correct meaning of the data in a contextual or theoretical sense (Myers, 2013). Qualitative research may or may not be interpretative, as the choice of philosophy would depend on the motivations of the researcher, who may or may not be guided by interpretivism (Myers, 2013, p. 37). Therefore, depending on the motivations of the researcher, qualitative research may be critical, positivist or interpretative (Myers, 2013, p. 37). Positivism postulates that by accepting a certain research methodology, the researcher accepts certain assumptions about the way he views the world, which then go on provide the researcher with the platform for research strategy (Collins, 2010). Positivism may be used to guide both qualitative as well as quantitative research design.

Once the research philosophy is decided upon by the researcher, he would then be required to choose the research approach that he would use to guide the research (Saunders, et al., 2012). Research approach may be defined as the approach that the researcher chooses to relate the research to theory (Bryman & Bell, 2015). Here, the researcher may formulate the plans and steps that would help him create detailed methods of enquiry and research from the earlier broad assumptions that he may have made at the initial stages of research (Creswell, 2013). These detailed methods relate to data collection, analysis and interpretation (Creswell, 2013).

There are two principle research approaches, which are, deductive and inductive approaches (Collis & Hussey, 2009). The deductive approach starts with a general theory which is applied to research specific case or context, therefore, deductive approach moves from theory to case or from general to specific (Perrin, 2015). The steps of deductive reasoning generally move through the process of: (a) starting with a theory; (b) developing a hypothesis; (c) collecting observations related to the hypothesis; and (d) confirming the theory (Perrin, 2015, p. 81).

In contrast, inductive approach observes some phenomena and collects data which may lead to a theory, therefore, the inductive approach moves from specific to general (Collis & Hussey, 2009). A further approach has also been outlined called abductive approach, which goes from observation to theory (Opoku, et al., 2016). It aims to find the most likely explanation of the subject under investigation and this approach includes a cyclical process in the sense that the researcher establishes a dialogue at every stage between theory, data and the social context (Opoku, et al., 2016).

This is the background for choosing the approach, either qualitative or quantitative, in a given research design. In the following section, the research approaches have been detailed along with the concepts discussed in this section, in order to contrast and compare the two approaches in their many aspects.

Qualitative and Quantitative approaches

Creswell defines research designs as “types of inquiry within qualitative, quantitative and mixed methods approaches that provide specific direction for procedures in a research design” (Creswell, 2013, p. 12). Researchers are not inhibited in the design that they finally choose, as long as the design and approach chosen coincides and complements the research philosophy and approach (Creswell, 2013). Many researchers create their research methods through their own philosophical assumptions. These methods are quantitative in the case of positivist research and qualitative in the case of interpretivist research (Bryman & Bell, 2015).

Sarantakos (1998) laid down some essential characteristics of qualitative and quantitative research, which are as follows.

The table above demonstrates

The table above demonstrates the key differences between quantitative and qualitative approaches. Clearly, qualitative approach is more subjective in nature, as well as being more focused on theory building as opposed the objective, theory testing approach of quantitative methods (Opoku, et al., 2016). This also leads to qualitative research being deductive oriented whereas the quantitative approach is inductive (Opoku, et al., 2016). However, qualitative and quantitative research may both involve inductive and deductive processes (Collis & Hussey, 2009).

Qualitative approach is generally associated with Interpretivism although it may also involve other philosophical approaches (Collis & Hussey, 2009, p. 46). It sees the researcher being close and not detached from the participants or respondents within a flexible framework (Collis & Hussey, 2009, p. 47). This makes qualitative research ideal for certain kinds of research studies, which are more interpretative in nature, or which involve multiple narratives, with a greater focus on gaining more insight into the topic under study (Creswell, 2013). Unlike quantitative research, qualitative research describes any data collection instrument and analysis procedure that use non-numerical data (Creswell, 2013, p. 44). Qualitative research generally seeks to derive relationships between research variables, at times by using an unstructured approach. Action research, case study research, ethnography, and grounded theory are typical of qualitative research strategies. It determines the meanings for participants, and emphasizes the social meanings of constructs as viewed by participants (Neuman, 2013). Social science research is generally complicated due to the issues that are involved in access of data, sampling issues and the ethics that may be involved in the research design and data collection (Ozerdem & Bowd, 2010).

Qualitative research helps because of its flexibility in formulating the design and its emphasis on narratives, which makes it suited to complicated research studies. Qualitative research allows greater flexibility and can be molded to fit the demands of complex studies. This is because qualitative research is not based on pre fixed or pre-specified methods or hypotheses, that the researcher is bound to follow through the research (Willis & Jost, 2007, pp. 53-54). In particular, quantitative research may not be able to depict multi-layered information, as its methods are more suited to strictly streamlined methods of data collection and analysis, at times, social scientists may find that the more flexible approach offered by the qualitative methods is more suited to their research design (Walliman, 2015). There is now a growing body of researchers who conduct multi layered research in such areas of studies.

The methods of qualitative research include interviews, surveys, questionnaires, case studies, etc (Gill, et al., 2008). Interviews are a commonly used technique in social science research. These interviews can also be flexibly managed within the qualitative research design as qualitative research allows the use of in-depth interviewing techniques for the purpose of gathering data for analysis (Gill, et al., 2008). For instance, Broneus, says that in-depth interviews allow the researcher to guide the interviewee through an extended discussion on the topic, “leading the way with well-prepared, thought-through questions, and following the interviewee through active, reflective listening” (Broneus, 2008). Interviewees give a lot of insight to the interviewer, which helps the researcher understand the situation better through the perspectives of the interviewees (Yin, 2013, p. 23).

Another method of collecting data within the qualitative tradition involves the use of focus groups or group discussions on topics that would be selected by the researcher (Söderström, 2011, p. 148). Focus groups allow the researcher to collect the data through the process of questioning as well as interaction within the group (Söderström, 2011). The reason why focus groups fit so well into the structure of qualitative research is because there is no formality within the discussion. Participants in the focus groups are free to answer the moderator; talk to each other and express their opinions and reactions to the statements made by the other members of the group. Focus groups are freely structures and therefore the participants have the freedom to talk freely, and without interference from the researcher (Gill, et al., 2008). It is asserted that such freedom “also allows for the discovery or elaboration of information that is important to participants but may not have previously been thought of as pertinent by the research team” (Gill, et al., 2008, p. 292).

Another method that is used in qualitative research is the case study method (Myers, 2013). Case studies may be used in positivist research as a prelude to a more detailed research. A case study studies the characteristics of a single individual unit. This unit may be a person, an organization, even a method (Bryman & Bell, 2015). The purpose of a case study is to get in-depth information of what is happening, why it is happening and what are the effects of what is happening.

Qualitative research may suffer from some drawbacks, despite the many advantages that it offers to the researchers within the social sciences. Five such disadvantages are listed here (Perrin, 2015): first, difficult to establish reliability and validity due to subjectivity in data collection and analysis; second, a limited scope because of the data collection methods; third, researcher bias in data analysis and the findings due to subjectivity; fourth, difficult to achieve precise results; fifth, difficult to replicate qualitative research and generalize the findings and results. Another problem that is noted with respect to qualitative method is that these methods may seem unsystematic as compared to the more systematically constructed quantitative research design. Here, the use of semi-structured interviews and open ended questions may lead to the respondents giving responses that are idiosyncratic (Johnson, 2014). Another problem that may be noted is that because the researcher is close to the respondents in qualitative research, he may be carried away by some of the respondents who are more articulate than the others (Johnson, 2014). Therefore, there is a need for proper adoption of methods in data analysis, which allow the researcher to ensure that the findings of the research are verified and validated. Some of these methods that can be specifically used to improve the credibility of the research findings are discussed here.

Validation of findings is also important because it helps to create credibility for research; strengthen the findings of the researcher and make the research valuable to future research. Qualitative research can be validated by following the four steps of credibility, transferability, dependability and confirmability (Guba & Lincoln, 1989). It is the task of the researcher to ensure that the research findings are considered believable by the others. Transferability allows generalisation of the findings under different contexts or settings, making the findings credible through testing under different settings (Guba & Lincoln, 1989). The researcher must ensure that he clearly describes the context of the research. The central assumptions that are involved in the research must also be clearly described by the researcher. This sets the framework for the transeferability of the findings. When the data is observable time and again, it can be said that the findings are dependable. Finally, when the findings are corroborated or confirmed by other studies then the element of confirmability is also satisfied (Guba & Lincoln, 1989).

There is also the method of triangulation, which may be used by the researcher to help improve the validity of findings (Bamberger, 2000). Triangulation involves the use of different data sources to arrive at the same findings because the findings are observed time and again, the triangulation is achieved (Bamberger, 2000). An example of the method of triangulation in practice can be seen in the practice of the researcher in asking the same kind of questions to the subjects in the sample population, but at different times (Bush, 2012, p. 85). Triangulation was always considered to be specific to qualitative research due to the greater need of the qualitative researcher to show the validity and reliability of his findings, as qualitative research is more loosely structured and is subjective in nature (Bush, 2012). However, the method of triangulation is being used in quantitative research as well (Bamberger, 2000, p. 14). In quantitative research triangulation can be used for the purpose of comparing different survey findings with each other, or comparing survey findings with the census data (Bamberger, 2000, p. 14).

Sometimes, the data collected through qualitative research can be so diverse and scattered that before it can be effectively analysed, the researcher may have to spend a considerable time in organizing it. Here, a particular method of organisation of data that can be used is the thematic network tool (Atrride-Sterling, 2001). This tool allows the researcher to organize a thematic analysis of qualitative data. Qualitative data may indeed involve many themes. The various themes can be identified by the researcher. After recognizing these themes, the researcher can use thematic networks to help in structuring and depiction of these themes as categorized into basic themes, organizing themes and global themes (Atrride-Sterling, 2001). A thematic network can be best described as a web like network is resulted from the whole process of application of thematic tool to the available data, where the basic themes, organising themes and global themes can be depicted in a web like map (Atrride-Sterling, 2001). Basic themes when read with other basic themes, allow the creation of a clear structure into the organizing theme and nn organizing theme can be described as a cluster of basic themes that relate to the same or similar issues (Atrride-Sterling, 2001). These organizing themes would then lead to groups of global themes, which are the macro themes that are super-ordinate in nature (Atrride-Sterling, 2001). Thematic network analysis is done in three broad stages: first, reduction or breakdown of the text (data); second, exploration of the text; and third, the integration of the exploration into basic, organizing and global themes (Atrride-Sterling, 2001). This leads to the researcher being able to organize the data collected better.

There are eight steps that can help analyse textual data as discussed here (Tesch, 1990). The researcher can get the sense of the entire data by reading through all the transcriptions carefully. Researcher may note some ideas as they come to mind.The researcher may pick one transcription of one interview or the focus group and seek to understand what the transcription is telling him. The researcher may then make a list of all topics. Similar topics can now be clustered together. Then columns can be arrayed as major topics, unique topics, and leftovers.The researcher may then re-read the data with the organized clusters. Abbreviation of the topics as codes helps to further organize the data. Then the researcher may use the most descriptive wording for topics and turn them into categories. The researcher must always look for reducing the total list of categories by grouping topics that relate to each other. This can also be done by drawing lines between categories to show interrelationships between various categories. Then the researcher may make a final decision on the abbreviation for each category and alphabetise these codes. Finally, the researcher may assemble the data material belonging to each category in one place and perform a preliminary analysis of the entire data (Tesch, 1990).

There are some tactics that can help to interpret qualitative data (Miles & Huberman, 1994). These tactics include noting patterns and themes, clustering (the process of sorting events, sites, actors and processes that have similar characteristics or patterns, and grouping them together),

making metaphors, counting, despite most qualitative data having nothing to do with numbers,

making contrasts/comparisons and building a logical chain of evidence.

After discussing the qualitative methods, it is now pertinent to discuss the quantitative method of research. Quantitative method relates to the use of numerical data, thus the term ‘quantitative’. Basically, the term quantitative is used to describe a data collection instrument (such as a questionnaire) or any analysis technique (such as regression) that uses numerical data (Bryman & Bell, 2015). Therefore, quantitative research involves use of numerical data for both data collection as well as analysis. Due to this focus on numerical data, quantitative research has always been associated with figures, numbers and statistics (Bryman & Bell, 2015). The principal research philosophy that guides quantitative research is positivist and the approach is usually deductive. The main quantitative research focus is concentrated on examining the causal relationships between research variables in a highly structured manner (Brown, 2013) such as experimental research and survey (Saunders, et al., 2012). Quantitative research is objective, deductive, logical, integrating of a natural science model and relevant to the precise measurements (Bryman & Bell, 2015). It involves great control by the researcher over the variables, which is one of the strengths of quantitative research (Houser, 2014, p. 52).

Quantitative research does suffer from some weaknesses despite its many advantages in conducting a systematic numerical research (Houser, 2014). Such research requires larger sample sizes, as compared to qualitative research, which means that the researcher will investigate broader issues related theoretically to the population (Houser, 2014, p. 52). It does not provide an in-depth insight of the topic under investigation. In general, there are three distinct disadvantages of quantitative research. These are: (a) if a finding of non-significance appears as a result of limited statistical power, there can be a misinterpretation that there is not relationship among variables; (b) quantifying study findings may reduce the substance of the study; and (c) possibility of an error in mathematical calculation or in misinterpretation, which affects the findings and the study conclusion and leads to misinformation (Haberfeld, et al., 2009, p. 27).

As mathematical errors are possible in quantitative research and due to the high numerical nature of the research design, it is advisable to start thinking of coding from the very beginning, of research, ideally at the time of devising of the questionnaire (Bryman & Bell, 2015). This can be done by assigning numbers to different categories and responses, i.e. numerical coding. This can be done either as pre-coding or post-coding (Bryman & Bell, 2015).

The method of triangulation, which is commonly used in qualitative research design to ensure the achievement of the validity and credibility of data, is also used at times in quantitative research to achieve the same objective of credibility of finding (Haberfeld, et al., 2009, p. 27).

As compared to qualitative research, quantitative research is objective and inductive in methodology. It is generally derived from the positivist philosophy of research. Irrespective of the contrasting and different nature of these two research methodologies, social scientists, in order to be credible as researchers, should be able to conduct both these types of researches (Haberfeld, et al., 2009, p. 28).

Based on the discussion above, qualitative research allows the researcher to focus more on the details and descriptions through interviews, discussions and observations. On the other hand, quantitative research is more focussed on the statistical data concerned. As such, both the techniques have decided advantages.

As compared to qualitative data, quantitative data is easier to interpret as the researcher here is mainly comparing and contrasting the numbers that are given to him in the data, as compared to the narrative themes which have to first be organised before it can be interpreted.

In certain kinds of research, it may be seen that the researcher may want to use both the methods of research. This has led to the development of the mixed methods research. One of the major contributors to the literature on mixed methods, has tried to solve the problem of competing approaches by suggesting three models of combined designs that he actually found in the research literature (Creswell, 1994). Research design is the blue print according to which research is planned and structured. The three models are (Creswell, 1994): Two-phase design approach, where the researcher proposes to conduct a qualitative and also a separate quantitative phase of the study; Dominant-less dominant design, where the researcher presents the study within a single approach, with one small component being from the other approach (QUAL-quan or QUAN-qual); and Mixed-methodology design, where the researcher mixes aspects of the qualitative and quantitative approaches at all or many methodological steps of the design (Creswell, 1994).

There is no rigid rule of using theory and this can be done through qualitative or quantitative research methods, or even by combining the two in a mixed methods research (Creswell, 2013). In a mixed methods research, theory can be placed as a framework for guiding the questions and the hypothesis of the study. It can be presented as literature review, as a theoretical framework, or as a theory that guides the researcher to explain the subject under investigation (Creswell, 2013). There are many researchers that are favouring thte mixed method research design composed of both quantitative and qualitative data collection techniques and analytical procedures (Atkinson, 2012). The good part about mixed method research design is that it is compatible with pragmatism (Tashakkori & Teddlie, 2010). Pragmatists value both qualitative and quantitative research design and they consider the extent to which they are appropriate depends on the research nature. In terms of theory development, there is also a tendency by pragmatists to combine deductive, inductive and abductive approaches therefore giving the flexibility to researcher within the mixed methods research. Creswell (2013) says that mixed methods enriches research as it allows one database to help explain the other database; one method could explain different types of questions than the other method.

In mixed methods research, it is seen that quantitative approach assists the qualitative study during the design stage by defining the representative sample, whilst the quantitative develops the qualitative approach during the data collection by providing the background data. Therefore, there are many benefits of the mixed methods research as well.

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Qualitative and quantitative research methods flow from different and contrasting research philosophies and objectives. The researcher has to choose the method of research depending upon his goals and the desired philosophy, which will underpin his research. As such, where the research flows from a positivist philosophy and the researcher wants to conduct an objective research with a distance from the respondents, the quantitative method is the proper method. Where the researcher wants to do a more in depth research into the topic at hand and wants to adopt an approach which is deductive and subjective in nature, he would choose the qualitative method of research.

Both quantitative and qualitative methods have their advantages. Quantitative method is useful when the researcher wants to draw out the statistical data and qualitative method is useful when the researcher wants to conduct a research into more complex narratives.


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