Research design explains how a research study addresses its research questions (Saunders et al., 2012). Research approach and strategy form an integral part of the research design. This section identifies the various research approaches and strategies considered by the researcher and provides justification for the selected approach. According to scholars (Saunders et al., 2009; Collins, 2010) the choice of approach and strategy is dependent on the clarity of the theories to be adopted for the proposed research. There are three major research approaches which are the deductive, inductive and abductive approaches. In addition, there are three major research strategy, namely: quantitative, qualitative and mixed research (Bryman and Bell, 2011; Bell et al., 2018). These are explained in the subsequent sub-sections and concluded in a sub-section on justification of the selected research design.
64 3.3.1 Deductive research approach
Deductive research finds its roots in natural sciences, where laws and theories provide the framework for knowledge creation (Collis and Hussey, 2003). It consists of 5 sequential stages: (1) developing a testable hypothesis (2) proposing how variables are to be measured (3) testing the developed hypothesis (4) reviewing the results to identify conformity or non-conformity with theory or if theory modification is necessary and (5) consequently modifying existing theory (Collins, 2012). A key advantage of deductive approach is its suitability when searching for causal relationships between phenomena. In this approach, it is necessary for the researcher to take an objective stance by ensuring that data collection, analysis and results obtained are always devoid of personal views (Saunders et al., 2009;
Collins, 2012).
This approach also utilizes quantitative techniques to test research hypotheses. Therefore, data collected must be adaptable to quantitative techniques and must be drawn from a relatively large sample in line with the scope of the proposed research (Saunders et al., 2009).
This further enhances the generalisability of the research, which is a very strong advantage for adopting the deductive stance (Sanders et al., 2016). Yet critics of this approach ask how a social scientist can arrive at a salient conclusion without incorporating the human perspective? In addition. it does not give room for alternative justifications to findings because of its dependence on rigid methodologies (Saunders et al., 2009). Irrespective, the generalisability of the results of deductive approach, its suitability to search for causal relationships and its suitability to scientifically test hypotheses using statistical analysis rebuff the criticisms of this approach.
3.3.2 Inductive research approach
The inductive approach is a theory generating method which originates from the social sciences domain as a consequence of criticisms levelled at the deductive approach explained above. This approach lays emphasis on understanding the subject matter taking into consideration time and context, as against investigating causal effect, using a flexible method which enables the researcher to find alternative justification for observed realities (Collins, 2012). Therefore, the inductive approach follows this sequence – the observation stage, discovering trends and patterns, drawing up conjectures or tentative hypothesis and then developing theory.
65 For this approach, the researcher utilizes their experiences, intuitions and knowledge to formulate research questions rather than depend on theoretical explanation (Remenyi et al., 1998). Using this approach, researchers do not concern themselves with developing hypothesis at the initial stages of the research, but rather develop paradigms from the data based on dominant themes (Thomas, 2006). What is more, the sample size suitable for this approach is usually small and therefore does not allow for generalisation. Hence, the small sample sizes and subjective nature of the approach affect the representativeness of the results (Saunders et al., 2009).
3.3.3 Abductive Research Approach
The abductive approach starts with a surprising (or a set of premises) and moves back and forth between the inductive and deductive research approaches. The approach allows the researcher to switch from induction to deduction and vice versa to generate new insights and conceptions of the observed reality. (Suddady, 2006), “that is, reasoning from an observation to its possible explanations” (Aliseda, 2007, p.261). It does not move from data to theory (induction) or from theory to data (deduction). Instead as it moves back and forth between the two and allows the researcher to combine both deduction and induction approaches (Saunders et al., 2015). The abduction approach begins with identifying a problem and then linking it to acceptable realities. As explained “as a foundation for inquiry, abduction begins with an unmet expectation and works backward to invent a plausible world or a theory that would make the surprise meaningful (Van Mannen et al., 2007, p. 1149). The abductive approach involves three major processes which are mnemonics (getting familiar with the data), de-familiarisation and revisiting observations (see Tavory and Timmermans, 2014, for details).
To adopt an abductive research approach, a major consideration is to ensure that available data is rich and robust enough to allow for development of important themes and conjectures regarding the subject matter to enhance development of plausible explanations; by so doing, researchers can link the explanations to appropriate theories (Van Mannen et al., 2007).
There are some criticisms levelled against abduction for instance, “if abduction is a two-stage process, how are the two two-stages different? Do they use the same argument form or different ones?” (Plutynski, 2011, p. 230). However, a major advantage of the abductive approach is that because it allows the researcher to move from induction to deduction, it allows for robust findings.
66 3.3.4 Quantitative research
The term “quantitative” is used to describe numerical measurement of an observation.
Therefore, quantitative research provides valid answers to raised research questions by adopting numerical measurements to attempt to understand the relationship between phenomena (Saunders et al., 2015). Bryman and Bell (2011); Bell et al., (2018) and explain that quantitative research adopts a deductive stance and is embedded in the positivist philosophy and an ontological assumption that there is only one truth. It involves the gathering of numerical data to understand the linkages between research and theory.
Quantitative research not only concerns itself with describing how things are, but also moves further to understand the underlying reasons for the observed reality. Four concerns are attributed to quantitative research, namely: measurement, causality, generalisation and replication (see Bell et al., 2018 for details).
Many advocates of the interpretivist philosophical and qualitative research stance have levelled numerous criticisms against quantitative research. A strong criticism is that probabilistic analysis of relationships between phenomena implies a static relationship independent of people’s realities (Bell et al., 2018). Put simply, “they argue that conceptualizing the social world in terms of variables and the relationships among them abstracts away the character of social life…” (Hammersley, 1989). Advocates of quantitative research rebuff this criticism by opining that because of the random and large sample sizes usually employed for quantitative analysis, results are generalizable across different contexts (Carr, 1994; Muijs, 2010)
3.3.5 Qualitative research
Qualitative research on the other hand is based on idealism philosophies (interpretivism and constructionism; Guba and Lincoln, 1994; Seeker et al., 1995) Qualitative paradigm takes the standpoint that interaction between individuals creates social properties and people actively create their own social worlds (Bell et al., 2018). Methods associated with this research paradigm are ethnography, focus groups, interviews, conversation analysis and thematic analysis. In addition, samples sizes are usually relatively small, which allows for purposeful articulation of the respondents’ viewpoints. According to Duffy (1986), a major strength of qualitative research is that it puts the researcher and the respondents in close proximity thereby allowing the researcher to obtain valuable data through direct contact.
67 This proximity also facilitates genuine understanding of participants’ reality, directly observed from their lens (Bryman and Bell, 2011). A major criticism against qualitative research is its subjective nature because of reliance on the researcher’s viewpoint (Bell et al., 2018). Other criticisms levelled against qualitative research are lack of transparency, generalisation problems and it being very difficult to replicate due to its unstructured nature (Bell et al, 2015).
3.3.6 Mixed research
The various criticisms levelled at qualitative and quantitative research brought about this research strategy. This strategy combines the qualitative and quantitative strategies within a research (Bell et al., 2018). According to Johnson et al. (2007), mixed research attempts to consider the qualitative and quantitative viewpoints to develop knowledge. This strategy triangulates the results obtained from the quantitative perspective to those gained from the qualitative standpoint to validate knowledge. As summarised by Denscombe (2008), mixed research is used to aid sampling, further develop and improve findings, reduce the level of bias associated with the qualitative and quantitative perspectives, provide a comprehensive perspective using different data and validate the accuracy of results.
There are two major arguments against the use of mixed research. Critics opine that qualitative and quantitative methods are underlined by different epistemological underpinnings and also from two different paradigms (Bell et al., 2018). Qualitative and quantitative strategy are underpinned by interpretivist and positivist epistemologies respectively and combining these creates irreconcilable interpretations of social reality.
However, a major advantage of mixed methods is that it allows the researcher to adopt both exploratory and confirmatory type analysis tin the same study (Teddlie and Tashakkori, 2009).
3.3.7 Justification for research approach and strategy
For this research, an abductive approach is adopted to achieve the aim and objectives.
Selection of this approach was influenced by several factors. Firstly, this research is driven by a very practical problem which is to understand if AASRs disproportionately target vulnerable consumers. In addition, from the research questions, this study is exploratory in nature. Therefore, data used for the research were drawn from a large population and can be
68 subjected to rigorous statistical and geographical information systems techniques to obtain a result that is representative of the underlying spatial process. The data are also very robust and allow for development of important themes and conjectures regarding the subject matter (Van Mannen et al., 2007) to enhance understanding and explanation of the drivers of the location patterns of the concerned retail groups. Furthermore, to explore spatial processes responsible for the observed location patterns, it is important to recognise the role of perception of the real world as most spatial decisions (location decisions) are based on the perception of reality as against reality itself (Fotheringham, 2006). Hence, the need for abduction (which incorporates both inductive and deductive reasoning).
The research begins with the appraisal of various retail location theories as well as incorporating other themes on deprivation, SECs and retail location based on a critical review of literature. What is more, the researcher is skilled in analysis of spatial patterns using statistical and GIS technologies. Therefore, these factors must be considered before the selection of a research design (Creswell, 2009). More importantly, this research is not only interested in the patterns of retail distribution statistically, which is a key characteristic of quantitative study (Saunders et al., 2009), it goes further to provide plausible explanations for the observed patterns of AASRs and FGR distributions, an abductive approach.
Furthermore, the study did not test hypotheses, because the outliers are also as important as the model fitting, hence the approach is abductive and explanatory.
A major justification for not adopting a qualitative strategy was based on the aim and objectives of this research. This research is concerned with understanding whether there is an ethical issue regarding the location strategies of AASRs. Therefore, interviewing retailers might not have been the most suitable approach to achieve this because there could have been a high possibility that the responses that would be provided would be socially acceptable responses, and as such unreliable. Hence, the need for a quantitative strategy.