Data Presentation and Analysis

To enhance analysis of data collected in the study, scores are allocated to the 38 indicators according to the degree of their incidence or presence in each of the study cases. This is similar to the approach adopted by Ilskog and Kjellström (2008) in which scores are awarded in accordance to the level reached by each study case in comparison with the other cases included in the study. However, unlike in Ilskog and Kjellström, the aim of this study goes beyond ranking of the study cases among themselves in order of their

110 performances, but seeks to reveal underlying reasons for their (under)performances. Therefore, scores are allocated mainly on the basis of existence or absence of an indicator in each study case without necessarily ranking them relative to the degree of their presence in each of the other study cases. Furthermore, to make the allocation of scores more pragmatic and less subjective, a 4-level scoring system to categorise the existence or degree of incidence of an indicator is employed as “Low” (Poor), ‘Medium” (Average) and “High” (Good) which are respectively allotted numerical scores of “1”, “2” and “3”, while “0” is allotted when an indicator is absent whereas it is relevant/necessary for it to be present. As shown in Table 4.5, a score of ‘1’ is allocated to an indicator which is present or exists at a degree that is considered minimum. Similarly, a score of ‘2’ is awarded when the occurrence or existence level of an indicator is adjudged to be average – in-between minimum and maximum possible levels, while ‘3’ is awarded to an indicator which degree of existence is considered to be above average. The interpretation of scores as presented in Table 4.5 can be considered generic as the terms ‘minimum’, ‘average’, and ‘maximum’ may assume different meanings under each of the indicators based on the indexes a specific indicator expresses in a study case. For example, while the indicator “availability of support infrastructures” accesses the nature, type and effectiveness of both human and technical support services available against a benchmark that is considered essential for it in each of the study cases, the nature and type of such support services may not be same across all study cases. Similarly, the indicator “Business development” evaluates the number of businesses that has developed by virtue of the existence of the solar PV installation in each community. In this wise, while the development of one business enterprise due may be regarded as “High” in a very small community, this same number may be regarded as “Low” in a relatively larger community where more opportunities for such business development exists. This is contrary to the approach adopted by in Ilskog and Kjellström (2008) where scores range of 1 to 7 are allotted to each of the seven cases being analysed. Such allocation of scores, which is more of ranking and awarding positions to each study case, could be highly subjective and become cumbersome if a larger number of study cases are being considered. It is also noted that some of the indicators as listed in Table 4.4 - especially those under ‘Institutional Development/ Government Policies - may be considered as general indicators which impact equally across all study cases. Therefore, while their level of impact may be

111 assessed, they may need not be allocated scores on case study-by-case study basis, but are discussed generally.

The cumulative scores and average scores obtained by each study cases under each of the five sustainability dimensions are obtained and explained in section 5.10, while further analysis and integration of the outcomes are integrated into the findings of the study in CHAPTER 6 .

Table 4.5: Interpretation of Scores Level of

Incidence Numerical Interpretation of Scores

Absent

Not Applicable

(N/A)

N/A is awarded against an indicator that does not occur because it is not related or relevant in the context of the study.

0

A score of ‘0’ is awarded against an indicator that does not occur or does not exist despite the possibility or necessity of such existence in the context of the study.

Low/Poor 1 The score is awarded to an indicator which is present or exists at a degree that is considered minimum. Medium/Average 2

An average occurrence of an indicator is awarded a score of ‘2’. Such score will be given for an indicator which is adjudged to exist at an average level

average.

High/Good 3

A high score of ‘3’ is awarded to an indicator whose degree of existence is considered to be above average level.

To further give credence to the outcomes of this study, additional analysis of data collected from the interviews and discussions held with the various stakeholders, and from the non-participant observation and evaluation of the RETs in the locations of study are carried out along with those from documented data as earlier reviewed. This is done by cross-referencing between data and evolving themes in the study cases in order to identify and correlate key themes that could contribute to the framework development. Specifically, the data were analysed to reveal the various process, factors and actors involved before, during and after the deployment of RET Installations to rural locations and how they may have contributed to the (under)performance of the installations in these places. While indicators that reflect some of these factors are already captured in Table 4.4, this approach may be regarded as using a checklist of requirements that are

112 fundamental to the effective deployment and performance of installations and is therefore used to further evaluate and assess the study cases on a current theme basis. This is done in section 6.2.