Perceptual Map

The second part of the framework is the development of the perceptual map (PerMap) to be used in the assessment of IQ of AM programs in FM.

According to Gower et al., (2014) perceptual maps are used to visually study relationships between two or more attributes whereby the attributes, which are grouped together on the perceptual map, are said to be associated (Remenyi, 1992). According to Remenyi, (1992), the association of such attributes may be thought of as a type of correlation which indicates the existence of a relationship14 _{between the variables. The}

perceptual maps are visual representation of peoples’ perceptions and preferences, which provides a quantitative illustration of how people perceive different products or

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services in a number of dimensions (Kotler & Keller, 2012). Remenyi, (1992) noted that perceptual map represents the relative positions or grouping of the various concepts listed in a matrix or frequency table. According to Mojtahed et al., (2014) perceptual mapping provides technical intelligence to help organisations understand the vision customers have for their products that compete with similar products by producing graphical representations in a two-dimensional space. This approach adopts an objectivist view in collecting and analysing data on consumers opinion by developing and using attribute-based methods such as factor analysis, similarity based methods such as multi-dimensional scaling (MDS), correspondence analysis, and principal component analysis (Gower et al., 2014; Mojtahed et al., 2014). However, A. J. T. Lee, Yang, Chen, Wang, & Sun, (2016) argues that the ability to display attributes in a two- dimensional space constitutes a weakness in the use of perceptual map. Another shortcoming of the perceptual map, as presented by Adaval, Coupey, & Narayanan, (2015) is the use of subjective determination of the dimensions in the perceptual map. Nonetheless, its simplicity of use, adaptability, and constitution within empirical methods outweighs these shortcomings.

According to Mojtahed et al., (2014) a typical perceptual map feature the following characteristics:

1. Pair-wise distances between product alternatives that indicate how closely related products are according to customer’s understanding

2. A vector on the map that geometrically denote attributes of the perceptual map

3. Axes that suggest the underlying dimensions that best characterise how customers differentiate between alternatives

Adaval et al., (2015) separates perceptual maps into two categories: (1) attribute-based, (2) non-attribute based. The first of these uses techniques such as factor analysis to uncover underlying factors while the second uses multidimensional scaling to elicit consumer judgement of products (Adaval et al., 2015). Adaval et al., (2015) further states that important elements which characterised perceptual maps are: (1) the

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number of dimensions, (2) names of the dimensions, and (3) location of the attributes on the dimensions.

3.8 Chapter Summary

This section presents the summary of the methodology chapter. The principles that have been discussed above shall be revisited with a key focus on the challenges this brings to the research. This study adopts a qualitative research paradigm for the investigation of IQ in AM. As indicated above, the ontological and epistemological position taken are constructivism and interpretivism respectively. These positions present an axiological conundrum for researchers in trying to ensure that a level of objectivity is established. Axiology studies judgements about the role of values and permits the understanding of what values go into knowing what we know (Bloomberg & Volpe, 2012; Saunders et al., 2012). According to Saunders et al., (2012), the axiology adopted by a qualitative researcher is value-laden i.e. the researcher is part of what is being researched, cannot be separated from it, and so will be subjective.

It has been argued that, unlike quantitative research, qualitative research has the tendency to be subjective in its outputs (Bryman, 2008; Carter & Little, 2007). This is an effect caused by the inherent values possessed by the research practitioner or the very nature of what is being studied i.e. information quality and presents a major challenge in such research activities. Values are the preconceptions a researcher possesses that reflects either a personal belief or feeling (Bryman, 2008). This has the tendency to create bias and blur the objectivity in the results of the research. Thus it is important to establish a level of trustworthiness. It has been reported that for qualitative research to be trustworthy, it needs to be value-free (Bloomberg & Volpe, 2012; Bryman, 2008; Carter & Little, 2007). However, this goes against the basic fabric of such research endeavour whereby the researcher tends to immerse himself or herself in the context of the research thus influencing it to an extent (Saunders et al., 2012). Therefore qualitative research is described a value-laden (Healy & Perry, 2000).

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The paradigm of qualitative research, as highlighted, tends to introduce bias. In order to minimise this effect, it is important that a criteria for ensuring trustworthiness of the research is adopted. These criteria have been elucidated by Bloomberg and Volpe, (2012), Golafshani, (2003), and (Bryman, 2008) as follows:

1. Credibility: refers to whether the participants’ perceptions match up with the researcher’s portrayal of them i.e. has the researcher accurately represented what the participants think feel and do?

2. Dependability: refers to whether one can trace the processes and procedures used to collect and interpret data

3. Transferability: refers to the fit or match between the researcher context and other contexts as judged by the reader i.e. how well the outcomes of the research will fit similar contexts as judged by the reader

In order to meet the criteria for evaluating trustworthiness outlined by Bloomberg and Volpe, (2012), data triangulation will be adopted. Triangulation is a procedure that draws on multiple perceptions or data sources to clarify meaning (Bloomberg & Volpe, 2012; Bryman, 2008). It has been described as a test for improving the validity and reliability of research or evaluation of findings (Golafshani, 2003). The goal is to limit the chances of bias in the methods or sources employed (Grix, 2001). Amaratunga et al., (2002) indicated that triangulation is the combination of methodologies in the study of the same phenomenon. According to Bryman, (2008) triangulation can operate within and across strategies to develop measures resulting in greater confidence in findings. The assumption made in triangulation is that effectiveness of research findings rests on the premise that the weaknesses in each single method used is compensated by the strengths of the other method used (Amaratunga, Baldry, et al., 2002). Therefore, this implies that triangulation is affiliated to mixed-methods research (Amaratunga, Baldry, et al., 2002) which has been adopted in this study.

Barbour, (2001) argues that though triangulation is used to confirm or refute the internal validity of research by corroborating or refining finding, the adoption does not in itself confer rigour if adopted without thorough, and clear justification. Therefore, a robust

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theoretical and methodological approach that incorporates multiple sources of information, models and methods in a study to adequately inform knowledge is required (Korte, 2009). This involves the combination of the use of theory, literature, and respondent validation (Amaratunga, Baldry, et al., 2002; Bryman, 2008). This approach is forthwith applied in the context of this research. The succeeding chapter presents the analysis of data using the identified techniques.

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Chapter 4 Qualitative Data Analysis