Traditional and new funding mechanisms for cities

6.1 INTRODUCTION

This study was construed around the research aim and objectives, presented in Chapter 1, section 1.3.3.

Based on the research question, the study aimed to develop a structured approach for the strategic positioning of a private credit-providing enterprise, specialising in asset-backed short-term finance, which could assist in ensuring success in the credit provisioning market.

The objectives in support of the aim of this study were:

 to determine why some business people prefer private asset-backed short-term loans to credit from commercial banks;

 to identify the most relevant risks to providers of asset-backed short-term finance; and

 to develop a framework for asset-backed short-term finance as a structured approach that could assist the existing and potential market players to ensure a successful enterprise.

Chapters 2, 3, 4 and 5 dealt with the literature and subsequent deductions and conclusions regarding the concept of credit, internationally and locally, as well as asset-backed short-term finance as a credit industry. These conclusions, based on the literature, pointed towards areas where existing knowledge could be augmented by empirical research. The aim of this section is to link this chapter to the literature review by way of an empirical analysis and by outlining the systematic research process. The process consists of a summary of literature findings, which require further investigation in terms of the research aim, synthesising a hypothesis from the consulted literature, outlining the methodological foundations, and explaining the methodology employed in the empirical research. Results and analysis are reflected in Chapter 7.

6.2 RESEARCH DESIGN

The empirical research consisted of two surveys: one among customers and potential customers of asset-backed short-term finance to collect views on the reasons for using

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this financial industry; and the other among providers of asset-backed short-term finance to gain insight into the handling of risk. Both served to develop a structured approach to this industry. The complete investigation was conducted according to a quantitative survey research design. To explain this, philosophical position and methodology are discussed in this section.

6.2.1 Philosophical position

The philosophical position is considered from the perspective of two basic divisions of philosophy, ontology and epistemology. Ontology deals with the nature of being, and epistemology deals with the question what is (or should be) regarded as acceptable knowledge (Bell & Bryman, 2011, pp. 15–23).

 Ontological tension exists between:

o objectivism, which holds that even cultural phenomena, such as organisations, are entities in themselves, which can be studied from the outside; and

o constructionism, which holds that reality is not fixed, but continuously transformed by different actions, including those of the researcher.

 Epistemological tension exists between:

o Positivism, which applies the approach and methodologies of natural sciences to social sciences. This includes sensory observation as ultimate test for validity and the belief that science can and must be conducted value-free; and

o interpretivism, which regards social reality as fundamentally different from nature in the sense that an inevitable interaction between researcher and reality exists. The researcher should ‘bracket out’ own preferences, but will inevitably be influenced by it (Bell & Bryman, 2011, pp. 15–23).

If judged by its first appearance, this study was done in the positivist tradition as, according to Denzin and Lincoln (2005, p. 1), quantitative research is, by definition, positivist. This judgement is problematised by Hair, Celsi, Money, Samouel, and Page (2011, p. 277), who state:

Postpositivism is a modern revision of positivism. Postpositivists believe that there is an objective reality, but acknowledge that it is difficult to describe or analyse that reality

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without socio-cultural and psychological lenses filtering interpretation. However, postpositivists continue to try to interpret research findings in a bias-free fashion under the assumption that there is an objective reality to describe.

The reconciliation of objectivism with constructionism; and positivism with interpretivism, as articulated by post-positivism, was the philosophical foundation of this study, although it is difficult to conceive how a complex subject, such as the reasons for using a specific form of credit, can be investigated according to the exact premises and categories of the natural sciences. However, it was regarded possible to determine, in an unbiased way, the relative importance of certain factors, as envisaged by post-positivism. In the present study, the application of post-positivism, therefore, did not lie in the method of enquiry, but in the interpretation of results, as presented in Chapter 7.

6.2.2 Methodology

‘Methodology’ refers to a body of methods, rules and postulates employed by a discipline, a particular procedure or set of procedures, and the analysis of the principles or procedures of inquiry in a particular field (Merriam-Webster Dictionary, 2017). This is described in the next section.

6.2.2.1 Methodological options

Bell and Bryman (2011, p. 5) convincingly argue that “evidence” in business settings are not “there to be discovered” in a technical, value-free scientific pursuit, but is always informed by the preferences of the observer. For the present study, a fundamental choice between quantitative and qualitative methods or a combination thereof, was necessary, as indicated in section 6.4.

Hill and McGowan (1999) suggest that smaller firms (such as private providers of asset-backed finance) should be studied qualitatively for a comprehensive analysis.

However, the literature review revealed information on customers’ preferences which need to be verified, which could be accomplished with Best-Worst Scaling (section 6.2.5.1). Therefore this study is exclusively quantitative in nature.

Myers (2013, p. 8) identifies a survey research design as an accepted method to find the opinions of a specific target group on well-defined questions. Williams (2003) mentions that surveys are conducted by means of a questionnaire, which is a

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specialist research tool, and must be designed consciously to ensure valid and reliable results. Stone (1993) opines that a questionnaire should, from the respondent’s²⁰ perspective, be appropriate, intelligible, unambiguous, unbiased and capable of coping with all possible responses. From the researcher’s perspective, a questionnaire should be satisfactorily coded, piloted with a limited number of informed respondents, and ethical. Stone (1993) proceeds to identify the key steps in designing a questionnaire as:

 deciding which data is needed;

 selecting items for inclusion;

 designing individual questions;

 composing the wording;

 designing layout and presentation;

 thinking about coding;

 preparing and pretesting the first draft;

 submitting the questionnaire to a knowledgeable pilot group;

 evaluating the form.

Surveys can be conducted by way of personal interviews, mailing of questionnaires and online surveys (Sue & Ritter, 2012, p. 11). According to these authors, the highest response rate can be expected from personal interviews, but these are time-consuming. Mailing of questionnaires demands few resources, but a low response rate can be expected. Online surveys can be conducted by email, where anonymity cannot be guaranteed, or by providing a link to a website, where anonymity can indeed be guaranteed (Survey Monkey, 2014). Setup costs of online surveys are high, but can be justified by the number of geographically dispersed respondents, or when a high number of respondents have to be reached (Sue & Ritter, 2012, pp 10–11).

Commercial services for online surveys are available, but may need customisation (Survey Monkey, 2014).

20 In quantitative research, people answering questionnaires are called respondents. In qualitative research, people engaged with are called participants, or in observation-based research designs, they are called informants (Saunders et al., 2012, p. 340).

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The questionnaire to be used for a survey needs to be compiled by the researcher, or selected, if an appropriate questionnaire already exists. Aldlaigan and Buttle (2005), for example, identified a large number of phrases relevant to their topic through qualitative research (focus groups and individual interviews). These were reduced to 17 statements, which were presented to respondents, to evaluate according to a 7-point Likert-type scale (Aldlaigan & Buttle, 2005, p. 351–355). Whichever option, or combination of options, is followed, the reliability and validity of the research instrument must be ensured.

The methodological choices for this study are presented in section 6.4.

6.2.2.2 Reliability and validity of a research instrument

Reliability of a research instrument is determined by consistency and validity by accuracy, as explained in the paragraphs below.

6.2.2.2.1 Reliability

Reliability is established if repeated application of a research instrument results in consistent scores (Hair et al., 2011, p. 233). Reliability is created by interaction among the instrument, the specific group of people taking the test, and the situation – therefore the results can be declared reliable, not the instrument (Streiner, Norman, &

Cairney, 2015, p. 163). As such, reliability indicates whether a the results of a test are consistent, not whether it is a true reflection of reality. For instance, a person may (for the sake of acceptability) present the same answers repeatedly, without it being his or her real opinion (Streiner et al., 2015, p. 164).

As reliability depends on consistent results, it can be measured by presenting the same test to a respondent at different times – the so-called test–retest method (Hair et al., 2011, p. 233), or the test for temporal stability (Pallant, 2013, p. 6). This is problematic, however, as the first test may prejudice respondents towards the following test, a prejudice which can be overcome by the second test, named alternative-form reliability, which means that the same construct is presented in an equivalent form. The third way to determine reliability is internal consistency reliability. With this method, different questions dealing with the same concepts are divided – if responses correlate, the instrument can be regarded as reliable. When the average coefficients of all possible combinations are calculated, the answer is the

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coefficient alpha or the Cronbach alpha (see (Hair, Celsi, Money, Samouel, & Page, 2011). This ranges from 0 to 1, where, 0.7 is regarded as the lowest acceptable value (Hair et al., 2011, pp. 233–235). When there are fewer than 10 items in the scale, Cronbach alpha values can be quite small, and then it is better to calculate the mean inter-item correlation for the items. Optimal inter-item correlation values range from 0.2 to 0.4 (Pallant, 2013, p. 6). Other tests which can be applied are the weighted Kappa (see Williams, 2003) or categorical data (see Williams, 2003) and Spearman’s rank correlation coefficient (see Williams, 2003, or its non-parametric equivalent, the Wilcoxon rank sum test (Williams, 2003, p. 249).

In order to be able to run the above-mentioned statistical tests, each concept has to be measured by at least three items. If these are not positively correlated, one could be reverse coded, for example, Likert-type scale level 4 in one statement is 2 in another. An item with a Cronbach alpha coefficient below 0.3 should be omitted completely (Hair et al., 2011, p. 237).

Validity, the topic of the next subsection, is related to reliability in the sense that reliability places an upper limit to validity – the more reliable a scale is, the more valid it can be (Streiner et al., 2015, p. 232).

6.2.2.2.2 Validity

‘Validity’ refers to the extent to which a construct measures what it is supposed to measure. If disposable income is investigated, then the research instrument should not measure total income (Hair et al., 2011, p. 238).

Hair et al. (2011, pp. 238–240), supported by Pallant (2013, p. 7) present the conventional description of validity, as assessed by measuring content validity, construct validity and criterion validity. Content validity is found where constructs in the research instrument are in cohesion with prevailing theory. This has to be augmented by either construct validity or criterion validity. Construct validity refers to comparison of the results of an instrument to that of another instrument measuring the same or opposite concept(s), called either convergent or discriminant validity.

Criterion validity presents the forms of concurrent and predictive validity.

Concurrent validity is found where two or more related concepts affirm each other, for instance when satisfied customers of a restaurant are also frequent customers.

Predictive validity is found where the expectation created by one concept is