Research Onion - Explanation of the Concept

Introduction

The research onion was developed by Saunders et al. (2007). It illustrates the stages that must be covered when developing a research strategy. When viewed from the outside, each layer of the onion describes a more detailed stage of the research process (Saunders et al., 2007).

"The research onion is an illustrative model, developed by Saunders et al, to describe the stages through which a researcher must progress to forumlate an effective methodology"

The research onion provides an effective progression through which a research methodology can be designed. Its usefulness lies in its adaptability for almost any type of research methodology and can be used in a variety of contexts (Bryman, 2012). This essay will examine and describe the different stages of the research onion, and explain the concepts at each stage.

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1.1: Understanding the Research Process

The research onion was developed by Saunders et al. (2007) in order to describe the stages through which the researcher must pass when formulating an effective methodology, a vital section to consider when writing a dissertation. First, the research philosophy requires definition. This creates the starting point for the appropriate research approach, which is adopted in the second step. In the third step, the research strategy is adopted, and the fourth layer identifies the time horizon. The fifth step represents the stage at which the data collection methodology is identified. The benefits of the research onion are thus that it creates a series of stages under which the different methods of data collection can be understood, and illustrates the steps by which a methodological study can be described.

Figure 1: The Research Onion

(Source: Institut Numerique, 2012, n.p.).

1.2: Research Philosophy

A research philosophy refers to the set of beliefs concerning the nature of the reality being investigated (Bryman, 2012). It is the underlying definition of the nature of knowledge. The assumptions created by a research philosophy provide the justification for how the research will be undertaken (Flick, 2011). Research philosophies can differ on the goals of research and on the best way that might be used to achieve these goals (Goddard & Melville, 2004). These are not necessarily at odds with each other, but the choice of research philosophy is defined by the type of knowledge being investigated in the research project (May, 2011). Therefore, understanding the research philosophy being used can help explain the assumptions inherent in the research process and how this fits the methodology being used.

Two main ontological frameworks can inform the research process: positivism and constructionism (Monette et al. 2005). These frameworks might be described differently (such as empiricism and interpretivism) but the underlying assumptions are broadly similar (Bryman, 2012). Positivism assumes that reality exists independently of the thing being studied. In practice this means that the meaning of phenomena is consistent between subjects (Newman, 1998). Conversely, constructionism suggests that the inherent meaning of social phenomena is created by each observer or group (Astlundet al. , 2011). In this philosophy, one can never presume that what is observed is interpreted in the same way between participants and the key approach is to examine differences and nuances in the respondents understanding.

Despite the inherent differences between these two practices, it is not necessarily the case that they form an inherent belief by the researcher that is then applied to all research contexts. One philosophy is not inherently better than the other, although researchers may favour one over the other (Podsakoffet al., 2012). The philosophy simply provides the justification for the research methodology. The methodology should be informed by the nature of the phenomena being observed.

1.3: Research Approaches

Two types of approaches are outlined here: the deductive and the inductive approach.

1.3.1: Deductive Approach

The deductive approach develops the hypothesis or hypotheses upon a pre-existing theory and then formulates the research approach to test it (Silverman, 2013). This approach is best suited to contexts where the research project is concerned with examining whether the observed phenomena fit with expectation based upon previous research (Wiles et al., 2011). The deductive approach thus might be considered particularly suited to the positivist approach, which permits the formulation of hypotheses and the statistical testing of expected results to an accepted level of probability (Snieder & Larner, 2009). However, a deductive approach may also be used with qualitative research techniques, though in such cases the expectations formed by pre-existing research would be formulated differently than through hypothesis testing (Saunders et al., 2007). The deductive approach is characterised as the development from general to particular: the general theory and knowledge base is first established and the specific knowledge gained from the research process is then tested against it (Kothari, 2004).

1.3.2: Inductive Approach

The inductive approach is characterised as a move from the specific to the general (Bryman & Bell, 2011). In this approach, the observations are the starting point for the researcher, and patterns are looked for in the data (Beiske, 2007). In this approach, there is no framework that initially informs the data collection and the research focus can thus be formed after the data has been collected (Flick, 2011). Although this may be seen as the point at which new theories are generated, it is also true that as the data is analysed that it may be found to fit into an existing theory(Bryman & Bell, 2011).

This method is more commonly used in qualitative research, where the absence of a theory informing the research process may be of benefit by reducing the potential for researcher bias in the data collection stage (Bryman & Bell, 2011). Interviews are carried out concerning specific phenomena and then the data may be examined for patterns between respondents (Flick, 2011). However, this approach may also be used effectively within positivist methodologies, where the data is analysed first and significant patterns are used to inform the generation of results.

1.3.3: The Quantitative Approach

As the name suggests, this approach is concerned with quantitative data (Flick, 2011). It holds a number of accepted statistical standards for the validity of the approach, such as the number of respondents that are required to establish a statistically significant result (Goddard & Melville, 2004).

Although this research approach is informed by a positivist philosophy, it can be used to investigate a wide range of social phenomena, including feelings and subjective viewpoints. The quantitative approach can be most effectively used for situations where there are a large number of respondents available, where the data can be effectively measured using quantitative techniques, and where statistical methods of analysis can be used (May, 2011).

1.3.4: The Qualitative Approach

The qualitative approach is drawn from the constructivist paradigm (Bryman & Allen, 2011). This approach requires the researcher to avoid imposing their own perception of the meaning of social phenomena upon the respondent (Banister et al., 2011). The aim is to investigate how the respondent interprets their own reality (Bryman & Allen, 2011). This presents the challenge of creating a methodology that is framed by the respondent rather than by the researcher. An effective means by which to do this is through interviews, or texts, where the response to a question can be open (Feilzer, 2010).

Furthermore, the researcher can develop the questions throughout the process in order to ensure that the respondent further expands upon the information provided. Qualitative research is usually used for examining the meaning of social phenomena, rather than seeking a causative relationship between established variables (Feilzer, 2010).

1.4: Research Strategy

The research strategy is how the researcher intends to carry out the work (Saunders et al., 2007). The strategy can include a number of different approaches, such as experimental research, action research, case study research, interviews, surveys, or a systematic literature review.

Experimental research refers to the strategy of creating a research process that examines the results of an experiment against the expected results (Saunders et al., 2007). It can be used in all areas of research, and usually involves the consideration of a relatively limited number of factors (Saunders et al., 2007). The relationship between the factors are examined, and judged against the expectation of the research outcomes.

Action research is characterised as a practical approach to a specific research problem within a community of practice (Bryman, 2012). It involves examining practice to establish that it corresponds to the best approach. It tends to involve reflective practice, which is a systematic process by which the professional practice and experience of the practitioners can be assessed. This form of research is common in professions such as teaching or nursing, where the practitioner can assess ways in which they can improve their professional approach and understanding (Wiles et al., 2011).

Case study research is the assessment of a single unit in order to establish its key features and draw generalisations (Bryman, 2012). It can offer an insight into the specific nature of any example, and can establish the importance of culture and context in differences between cases (Silverman, 2013).

This form of research is effective in financial research, such as comparing the experiences of two companies, or comparing the effect of investment in difference contexts.

Grounded theory is a qualitative methodology that draws on an inductive approach whereby patterns are derived from the data as a precondition for the study (May, 2011). For example, interview data may be transcribed, coded and then grouped accordingly to the common factors exhibited between respondents. This means that the results of the research are derived fundamentally from the research that has been completed, rather than where the data is examined to establish whether it fits with pre-existing frameworks (Flick, 2011). Its use is common in the social sciences (Bryman, 2012).

Surveys tend to be used in quantitative research projects, and involve sampling a representative proportion of the population (Bryman & Bell, 2011).

The surveys produce quantitative data that can be analysed empirically. Surveys are most commonly used to examine causative variables between different types of data.

Ethnography involves the close observation of people, examining their cultural interaction and their meaning (Bryman, 2012). In this research process, the observer conducts the research from the perspective of the people being observed, and aims to understand the differences of meaning and importance or behaviours from their perspective.

An archival research strategy is one where the research is conducted from existing materials (Flick, 2011). The form of research may involve a systematic literature review, where patterns of existing research are examined and summed up in order to establish the sum of knowledge on a particular study, or to examine the application of existing research to specific problems. Archival research may also refer to historical research, where a body of source material is mined in order to establish results.

1.5: Choices

The choices outlined in the research onion include the mono method, the mixed method, and the multi-method (Saunders et al., 2007). As the names of these approaches suggest, the mono-method involves using one research approach for the study. The mixed-methods required the use of two or more methods of research, and usually refer to the use of both a qualitative and a quantitative methodology. In the multi-method, a wider selection of methods is used (Bryman, 2012). The main difference between the mixed and the multi-method is that the mixed-method involves a combined methodology that creates a single dataset (Flick, 2011). The multi-method approach is where the research is divided into separate segments, with each producing a specific dataset; each is then analysed using techniques derived from quantitative or qualitative methodologies (Feilzer, 2010).

1.6: Time Horizons

The Time Horizon is the time framework within which the project is intended for completion (Saunders et al., 2007). Two types of time horizons are specified within the research onion: the cross sectional and the longitudinal (Bryman, 2012). The cross sectional time horizon is one already established, whereby the data must be collected. This is dubbed the 'snapshot' time collection, where the data is collected at a certain point (Flick, 2011). This is used when the investigation is concerned with the study of a particular phenomenon at a specific time. A longitudinal time horizon for data collection refers to the collection of data repeatedly over an extended period, and is used where an important factor for the research is examining change over time (Goddard & Melville, 2004). This has the benefit of being used to study change and development. Furthermore, it allows the establishment of some control over the variables being studied. The time horizon selected is not dependent on a specific research approach or methodology (Saunders et al., 2007).

1.7: Data Collection and Analysis

Data collection and analysis is dependent on the methodological approach used (Bryman, 2012). The process used at this stage of the research contributes significantly to the study's overall reliability and validity (Saunders et al., 2007). Regardless of the approach used in the project, the type of data collected can be separated into two types: primary and secondary.

1.7.1: The Primary Data

Primary data is that which is derived from first-hand sources. This can be historical first-hand sources, or the data derived from the respondents in survey or interview data (Bryman, 2012). However, it is not necessarily data that has been produced by the research being undertaken. For example, data derived from statistical collections such as the census can constitute primary data. Likewise, data that is derived from other researchers may also be used as primary data, or it may be represented by a text being analysed (Flick, 2011). The primary data is therefore best understood as the data that is being analysed as itself, rather than through the prism of another's analysis.

1.7.2: Secondary Data

Secondary data is that which is derived from the work or opinions of other researchers (Newman, 1998). For example, the conclusions of a research article can constitute secondary data because it is information that has already been processed by another. Likewise, analyses conducted on statistical surveys can constitute secondary data (Kothari, 2004). However, there is an extent to which the data is defined by its use, rather than its inherent nature (Flick, 2011). Newspapers may prove both a primary and secondary source for data, depending on whether the reporter was actually present. For a study of social attitudes in the Eighteenth Century, or for a study of the causes of fear of crime in present day UK, newspapers may constitute primary data. Therefore, the most effective distinction of the two types of data is perhaps established by the use to which it is put in a study, rather than to an inherent characteristic of the data itself.

1.8: Research Design

The research design is the description of how the research process will be completed. It is a framework which includes the considerations that led to the appropriate methodology being adopted, the way in which the respondents were selected, and how the data will be analysed (Flick, 2011). There are a number of different characteristic research designs, namely the descriptive, explanatory, and the exploratory.

The descriptive research design relates to reflecting the experiences of respondents. It is thus related closely to ethnographic studies, but a quantitative framework is also an appropriate framework; for example, the demographic characteristics of a population subgroup can be reported (Bryman, 2012). An explanatory research design is focused on how to effectively explain the characteristics of a population or a social phenomenon (Saunders et al., 2007). This may be seen as effective where using a quantitative framework, where the influence of one variable on another can be established (Kothari, 2004). The exploratory study is an exploration of an issue that takes place before enough is known to conduct a formulaic research project. It is usually used in order to inform further research in the subject area (Neuman, 2003).

1.9: Samples

A sample is a representative segment of a larger population (Bryman, 2012). In quantitative research, the sample size and how it is selected can be used to establish the reliability of the results of the study. In qualitative research, the sample characteristics are also important, but much smaller samples tend to be used.

1.9.1 Sample Size

The sample size represents the number of respondents selected from the overall population that are used in the research (Newman, 1998). In quantitative research, the size of the sample is essential in determining the reliability of the results of a study. Sample sizes of much less than 30 will tend to produce results where individual respondents may skew the results. In such cases, the larger the sample size the more reliable will be the results (Flick, 2011). In qualitative research, the size of the sample is less important, and the concept of representativeness is not as strong a guideline for the validity of the research.

1.9.2: Sampling Techniques

Sampling techniques are the ways in which an appropriate sample size is selected for the wider study (Bryman, 2012). There are a number of accepted techniques that can be used. A random sample represents individuals within a larger population who are chosen at random. However, this can result in random distribution, which can mean significant skewing resulting from the random nature of sample selection (Neuman, 2003). For example, a random sample may result in more males than females being represented in a sample, or an unequal distribution across ages. A stratified sample may then be used to ensure that the representatives of the population in the sample reflect the significant characteristics of the wider population, such as making sure that the demographic characteristics of age and gender are reflected in the sample (Newman, 1998). A convenience sample is where the sample is taken from an existing framework, such as an educational institution, given that the ways in which respondents may be recruited is relatively straightforward. This may be appropriate if a study is concerned with students' views, and it proved convenient to sample just one educational institution; it may be considered unlikely that significant variation in students' characteristics will occur between institutions or that those characteristics will have a significant effect on the results of a study.

Conclusions

In this study, the different stages of the research onion were described. Given the research onion comprises different stages of many research projects and can be effectively adapted to different models, this report has necessarily been summative and restricted in depth. However, the stages defined by Saunders et al. (2007) have been expounded upon, and the usefulness of the staged development of the onion demonstrated. The most effective model of its effectiveness, however, lies in its use.

References

Banister, P., Bunn, G., Burman, E., & Daniels, J. (2011). Qualitative Methods In Psychology: A Research Guide. London: McGraw-Hill International.

Beiske, B. (2007). Research Methods: Uses and limitations of questionnaires, interviews and case studies, Munich: GRIN Verlag.

Bryman, A. (2012). Social research methods (5^th ed.). Oxford: Oxford University Press.

Bryman, A., & Allen, T. (2011). Education Research Methods. Oxford: Oxford University Press.

Bryman, A., & Bell, E. (2011). Business Research Methods (3^rd ed.) Oxford: Oxford University Press.

Feilzer, M. Y. (2010). Doing mixed methods research pragmatically: Implications for the rediscovery of pragmatism as a research paradigm. Journal of Mixed Methods Research, 4(1), pp.6-16.

Flick, U. (2011). Introducing research methodology: A beginner’s guide to doing a research project. London: Sage.

Goddard, W. & Melville, S. (2004). Research Methodology: An Introduction, (2^nd ed.) Oxford: Blackwell Publishing.

Gulati, P. M. (2009). Research Management: Fundamental and Applied Research, New Delhi: Global India Productions.

Institut Numerique, (2012). Research Methodology, http://www.institut-numerique.org/chapter-3-research-methodology-4ffbd6e5e3391 [retrieved 3rd October, 2014].

Kothari, C. R. (2004). Research methodology: methods and techniques. New Delhi: New Age International.

May, T. (2011). Social research: Issues, methods and research. London: McGraw-Hill International.

Monette, D.R., Sullivan, T. J., & DeJong, C. R. (2005). Applied Social Research: A Tool for the Human Services, (6^th ed.), London:

Brooks Publishing.

Neuman, W. L. (2003). Social Research Methods: Qualitative and Quantitative Approaches, London: Allyn & Bacon.

Newman, I. (1998). Qualitative-quantitative research methodology: Exploring the interactive continuum. Carbondale: Southern Illinois University Press.

Astlund, U., Kidd, L., Wengstram, Y., & Rowa-Dewar, N. (2011). Combining qualitative and quantitative research within mixed method research designs: a methodological review. International Journal of Nursing Studies, 48(3), pp. 369-383.

Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, pp.539-569.

Rowley, J. (2012). Conducting research interviews. Management Research Review, 35(3), pp.260-271.

Saunders, M., Lewis, P., & Thornhill, A. (2007). Research Methods for Business Students, (6^th ed.) London: Pearson.

Silverman, D. (2013). Doing Qualitative Research: A practical handbook. London: Sage.

Snieder R. & Larner, K. (2009). The Art of Being a Scientist: A Guide for Graduate Students and their Mentors, Cambridge: Cambridge University Press.

Wiles, R., Crow, G., & Pain, H. (2011). Innovation in qualitative research methods: a narrative review. Qualitative Research, 11(5), pp.587-604.