PhD Seminar: Research Methodology WS 2013 Prof. Dr. Roman Boutellier Prof. Dr. Oliver Gassmann Prof. Dr. Sabine Raeder Ass-Prof. Dr. Marco Zeschky How do qualitative and quantitative research differ? Submitted by: Onur Saglam ETH Zürich Chair of Entrepreneurship Department of Management, Technology, and Economics WEV H 301, Weinbergstrasse 56/58 CH-8092 Zurich, Switzerland osaglam@ethz.ch Veselina Milanova Universität St. Gallen Institut für Medien- und Kommunikationsmanagement Blumenbergplatz 9 CH-9000 St. Gallen, Switzerland veselina.milanova@unisg.ch
Table of Contents 1 Introduction... 3 2 Quantitative Research... 3 3 Qualitative Research... 3 4 Summary of Differences... 4 5 Mixed Method Approach... 5 6 Conclusion... 6 7 Annotated Bibliography... 7 Research Methodology 2
1 Introduction The motivation of quantitative and qualitative research in two different paradigms the positivism and constructionism or post-positivism, accounts to a great extent for their controversial discussion. Quantitative research can be described as a cause-effect relationship, searching for standardisation, reproducibility, and measurability. Qualitative research aims at understanding and interpreting behaviours, contexts, and interrelations. At first sight, these two approaches to the understanding of science seem to be competing and even incompatible; there are many publications contributing to the elaboration of their differences. However, lately there have been considerations that quantitative and qualitative methods are two sides of one coin and can complement each other in certain research situations. This summary gives a short overview of these two methodologies, their strengths and weaknesses in the explanation of social realities, and finally discusses a new approach to science, namely the combination of both. 2 Quantitative Research There are many explanations to quantitative research, yet Aliaga & Gunderson (2002) describe it as explaining a phenomenon by collecting quantitative (numerical) data that are analysed using mathematically based methods such as statistics. A common misconception is that quantitative data does not require data that is naturally available in quantitative form. Non-quantitative data (such as beliefs and/or attitudes) can be transformed into quantitative form by using measurement instruments such as Likert scales. Despite its limitations, quantitative methods have been more prominent in social sciences traditionally due to the fact that natural sciences and their standard methods were seen as a model in this field (Flick, 2006). Yet, perhaps it was the Chicago school that gave rise to widespread use of qualitative research in social sciences; however, this did not last too long as Columbia school disrupted this convention and laid the foundations of today, where the debate is still not fully resolved. Today, quantitative research is often placed in opposition to qualitative research, still a legacy of clashes of schools, dating back to early 1900s (Hamel, Dufour & Fortin, 1993). The incompatible worldviews underlying quantitative and qualitative methods gave birth to this paradigm war. It is often argued that the quantitative research is more realistic and objective as compared to the qualitative research and the researchers consensus is to use quantitative methods if there is a hypothesis to test, using deductive reasoning. The main strength of quantitative research is that it is neutral and easily generalizable; however, it is challenging to gauge the theoretical constructs (e.g. innovation) in social sciences and proxying them with several variables usually undermines establishing causality. 3 Qualitative Research The qualitative turn in social research took place during the 70`s as a countermovement to quantification, the landmark of natural sciences (Mayring 2002). This turn addressed the critique of quantitative methods and research strategies, often judged as too standardized in order to reflect the facets of social reality. Instead of testing, measuring, and experimenting, qualitative research aims at understanding the subject of study (Mayring 2002). Creswell defines qualitative research as the process of understanding a social or human phenomenon, based on methodological research traditions. Researchers aim at generating a complex, holistic view, at analysing and describing the Research Methodology 3
standpoint of the subjects within a natural context (Creswell 1998). Hoffmann-Riem even advocates to let the theoretical structure of the object of research emerge from the research subjects (1980, p.343). In the meanwhile qualitative social research has turned into an interdisciplinary point of reference for new qualitative approaches (Mayring 2002). Several lines of research can be seen as the roots of qualitative methods. Aristotle is regarded as their prime father; for him historic and evolutionary developments as well as inductive approaches belong to the understanding of science. Further precursor of qualitative thinking is Gianbattista Vico who sees the practical and the truth as non-universal, but dependant on time and space. Hermeneutics, as the effort to develop a foundation for scientific text interpretation, is as well seen as one of the originators of qualitative approaches (Mayring 2002). The main strength of qualitative research is its ability to create knowledge about new phenomenon and complex interrelations that have not yet been researched thoroughly or at all (Seipel & Rieker 2003). In such cases it is per definition a suitable approach for theory building, elaboration, and testing, where theory implies a reference to context. Adequate methods for data collection within a qualitatively-oriented research project are e.g. problem-centred or narrative interviews, group discussions, semi-structured interviews, archival or content analysis. Most of these are very timeconsuming due to two reasons: 1) the emphasis of qualitative research methods is on context and verbal access to data (Hoffmann-Riem 1980) and 2) the research process is circular and interactive. An inevitable consequence is the rather small sampling when compared to quantitative methods. The exploratory and explanatory character of qualitative research becomes apparent through the flexibility of the approach, the personal involvement, and the openness of the researcher to the research subjects and the research process. However, according to Mayring (1990, p. 17) this does not imply that the research process is not controlled and does not follow well-grounded rules. Very important to the process are the illustration of the context, the intersubjective traceability of the interpretation, and the relevance of the results. Qualitative research explicitly turns itself against reliability and validity, the quality criteria that apply for quantitative research. It has been often critiqued to be lacking scholarly rigor (Gioia, Corley & Hamilton 2012), which makes it necessary to clearly state what quality criteria apply for this kind of research. However, up to now there is no unambiguous agreement in the scientific community about a criteria catalogue for qualitative research. 4 Summary of Differences A comparison of quantitative and qualitative research can be carried out on various levels, e.g. application domain, prerequisites, research process, etc. The main differences between the two approaches come from their underlying science models. These models differ in their understanding of how phenomena should be studied. The aim for objective and precise prediction characterizes the natural science model (quantitative), whereas thick descriptions of incidents that advance the understanding of human behaviour distinguish the human science model (qualitative). This fundamental difference implies the remaining ones. Due to its precise and seeking for objectivity nature, quantitative research focuses on the quantification of concepts and their relationships via measurement. In contrast, qualitative research tries to understand qualities of entities via text production and interpretation. Quantitative researchers study phenomena with a distant and objective science stance from the outside; whereas qualitative researchers are engaged in face-to- Research Methodology 4
face interactions and role taking from the inside. The deductive nature of quantitative research implies a rather selective approach, where a small number of key variables across many data points are researched. Qualitative research aims at a holistic view of phenomena and more often deploys an inductive, exploratory approach. The last two differences refer to the research process and its impact on the segment of social reality that is studies. Due to a pre-structured and linear research process, quantitative methods allow for a static image of that segment. Qualitative methods follow a more flexible, open-ended and circular process, so they enable a dynamic view of the segment. Despite these fundamental differences, both methodologies can be successfully combined into one research design. 5 Mixed Method Approach When comparing quantitative and qualitative research, Wilson (1982) argues for a balanced use of both, considering the object or phenomenon of research and not relying upon philosophical doctrines. The increasing popularity of mixed methods could be due to many factors, one of them being the intention of utilizing the strengths of both qualitative and quantitative research. Also, the interdisciplinary nature of mixed methods can address the increasing complexity of social reality. Moreover, the insights gained from the combination of both qualitative and quantitative research provide a better and expanded understanding of the research subbject. Finally, it could also be argued that mixed methods help to better understand, explain, or build on the results from quantitative and qualitative approaches. Before discussing the different types of mixed methods designs, it is helpful to discuss the several aspects that influence the design of procedures for mixed methods study. These are timing, weighting, and mixing strategies (Cresswell, 2002). Timing refers to the order of data collection. Data could be collected sequentially or concurrently. Weighting refers to where the priority is given in collection of data, either quantitative or qualitative. The strategy of deciding the weighting also depends on the extent of treatment of one type of data and the use of primarily an inductive or deductive approach. Mixing refers to either that the qualitative and quantitative data are actually merged. It is possible to merge data at several stages such as during the collection or while doing the analysis or finally during the interpretation stage. The primary aim here is to collect one form of data and have the other form of data provide supportive information. Theorizing is up to what extend a theoretical perspective is guiding the entire design. Theories, frameworks and hunches to inquiries may be made explicit or implicit. If they are explicit, theories are found typically in the beginning section as an orienting lens that shapes the types of questions asked. In general, there are many types of mixed methods but here only six of them, based on the work of Creswell (2002), are to be briefly explained in the following table. Sequential Explanatory Design Characteristic is that qualitative data and its analysis assist in the interpretation of quantitative findings. The first phase consists of collection and analysis of quantitative data and the second phase is the collection and analysis of qualitative data. The purpose of this strategy is to explain and interpret quantitative results by collecting and analyzing follow-up qualitative data. Research Methodology 5
Sequential Exploratory Design Sequential Transformative Design Concurrent Triangulation Design Concurrent Embedded Design Concurrent Transformative Design It is very similar to sequential explanatory design except the phases are reversed. The first phase is the collection and analysis of the qualitative data whereas the second phase is the collection and analysis of the quantitative data. The main purpose is to use quantitative data and results to assist in the interpretation of qualitative findings. The main characteristic of this strategy is a two-phase project with a theoretical lens overlaying the sequential procedures. The theoretical lens shapes a directional research question aimed at exploring a problem, creates sensitivity to collecting data from marginalized or underrepresented groups, and ends with a call for action. The first phase could be either qualitative or quantitative. The characteristics of this strategy are the concurrent data collection and the comparison of the two databases to determine if there is convergence, differences, or some corroboration. Mixing occurs by merging the data in an interpretation or discussion section or integrating or comparing the results in a discussion section. Here, the data is collected concurrently and has a primary method that guides the project and a secondary database that provides a supporting role in the procedure. The secondary method (quantitative or qualitative) is embedded within the predominant method. Here embedding refers to a secondary method addressing a different question than the primary method. Concurrent transformative design s main characteristics are the use of specific theoretical perspective, concurrent collection of both data, and a perspective that can be based on ideologies such as critical theory, advocacy, participatory research, conceptual or theoretical framework. 6 Conclusion Finally, both quantitative and qualitative methods have their own strengths and weaknesses. Although there is no final recipe for which methods to employ in social sciences, the research question remains the single most navigator to reach the optimum design. That is also the reason why mixed method approach is gaining popularity as it provides both the breadth (causality) of quantitative methods and the depth (meaning) of qualitative methods. However, when one looks closer at researchers actual beliefs, it appears that the so-called subjectivist (qualitative) versus realist (quantitative) divide is not that clear-cut and the debate on methods is likely to further go on. Research Methodology 6
7 Annotated Bibliography Aliaga, M. & Gunderson, B. (2002). Interactive statistics. New Jersey: Prentice Hall. Provides introduction of basic statistical methods with its strong emphasis on data analysis, also describes how to understand and interpret a variety of statistical results. Creswell, J. W. (1998). Qualitative Inquiry and Research Design: Choosing Among Five Traditions. Thousand Oaks, CA: Sage. The book aims at revealing the design process for qualitative studies. Creswell presents and compares in his book five qualitative approaches to inquiry narrative, phenomenological, grounded theory, ethnographic, and case study research. Creswell, J.W. (2002), Research design. Qualitative, quantitative and mixed method approaches. Chapter 11: Mixed methods procedures, pp. 208-227 Method handbook. In this chapter the author explains six different mixed method strategies and data collection, analysis, and validation procedures. Flick, U. (2006), An introduction to qualitative research (3 ed.). Chapter 3: Qualitative and quantitative research, pp 32-43, London: Sage. Well-known source for qualitative research and target both novice and experienced researchers. Explains every step of qualitative research from planiing, data collection to anlaysis. Gioia, D. A., Corley, K.G., Hamilton, A.L. (2012), Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology. Organizational Research Methods, vol. 16 (1), p.15-31. The authors point that inductive qualitative research is felt to not meet the high standards needed for scientific advancement. In this paper they propose an approach to systematically present inductive research, designed to bring scientific rigor to it. Hamel, J., Dufour, S. & Fortin, D. (1993), Case Study Methods. Sage Publication, Newbury Park, California. Explains several differing traditions of case study research including the Chicago School of Sociology, the anthropological case studies of Malinowski, and the French La Play school tradition. Hoffmann-Riem, C. (1980), Die Sozialforschung in einer interpretativen Soziologie - Der Datengewinn. Kölner Zeitschrift für Soziologie und Sozialpsychologie, vol. 32, p.339-372. Hoffmann-Riem discusses critically in this article the normative social sciences that follow the research postulates of natural sciences in contrast to its opposing methodological paradigm, the interpretative one. The differences between the two research lines are motivated as originating from the Galilean and respectively the Aristotelian tradition. Research Methodology 7
Mayring, Ph. (2002), Einführung in die Qualitative Sozialforschung. Eine Anleitung zum qualitativen Denken (5. ed.), p. 9-18, München: Psychologie-Verlags-Union. The book is well-suited for prospective researchers and introduces the background, developments, and methods of qualitative social research. Seipel, Ch. & Rieker, P. (2003), Integrative Sozialforschung. Konzepte und Methoden der qualitativen und quantitativen empirischen Forschung. Weinheim/München: Juventa. This methods handbook presents quantitative and qualitative approaches and aims at closing the gap between them. It discusses the problems and moreover the possibilities of combining them and thus encourages methodological openness among researchers. Wilson, T. P. (1982). Qualitative oder quantitative Methoden in der Sozialforschung. Kölner Zeitschrift für Soziologie und Sozialpsychologie, vol. 34, p. 487-508. In this article the author presents qualitative and quantitative research with their characteristic attributes and weaknesses. Wilson argues that each of the research methodologies focuses on certain aspects of situational acting and thus disregards others. Research Methodology 8