VERIFICACIÓN DE DOS MODELOS NO-ESTRUCTURALES DE CONDUCTA BANCARIA

The focus of this section is to contribute a descriptive summary and provisional assessment of the quantitative data in this study. In devising a framework for communicating the overall results of the study a number of conceptual, analytical themes were further identified according to the scope of the study. The themes are also identified for analysis and assessment of the results. This section focuses on providing preliminary results to address two research hypotheses. Firstly, hypothesis one aimed to determine whether current best practices in risk management, combined with performance management approaches, can effectively mitigate risks. Secondly, hypothesis two aimed to determine whether effective strategic control of PPP projects necessitates the systematic integration of strategic planning, risk management and internal control of such projects. This section presents preliminary results which are integrated with the qualitative results in Chapter Six, in order to draw conclusions regarding the research hypotheses.

In concluding the data-collection and analysis, the researcher extrapolated that the qualitative data-collection and analysis consisted mostly of high-level decision-makers in the private sector. The quantitative set consisted mostly of individuals from the implementation level. This presented a limitation to the study because the skills, experience and knowledge gap affects the usefulness of the quantitative data because the respondents for the quantitative data set have a lower understanding and grasp of the themes applied in the survey. This and other factors explained in this section, indicate research bias. Therefore the researcher isolated the quantitative results that were not rich in interpretation, and integrated only the results that supplied conclusions about the research questions, and that illustrated and identified meaningful trends.

The quantitative stage of data-collection analysis was deductive. Themes employed in the self-administered survey were derived from the various conceptual frameworks that were applied in this study, including market-based governance, good governance, risk management theory and strategic management concepts. See annexure B for a full outline of the survey.

The survey utilised a nominal scale using closed-ended questions. Variables assessed on the nominal scale included categorical variables or categorical data that had only two possible outcomes: "yes" or "no". The purpose of employing a nominal scale with categorical data was to simplify the survey and take into consideration the respondent, firstly in order to take limited time to complete the survey, and secondly, considering that the respondents in the second stage might be indirectly involved in PPPs, it was not their main occupation and they were not experts on risk management or PPPs. However, post data analysis revealed that the use of a nominal scale presented a limitation to the study; that because of the presence of research bias, the categorical variables limited measurement. Conversely, if the study applied for instance multiple choice, rank ordering, or a rating scale such as the Likert scale to measure the continuum of variables, the study would be able to measure relationships, correlation and variance by utilising regression or multiple regression analysis (such as Persons R), analysis of variance (anova) or analysis of covariance. This was not the onset purpose of the survey; because the study was interested in frequency values, a nominal scale and categorical data were

162 appropriate. However, due to missing data, contradicting values, duplication of responses, incomplete fields and the lack of expertise of respondents, the aforementioned measurements could have proven useful to analyse variance and relationships. Consequently, as mentioned earlier, in response to this limitation the researcher isolated the results. The results and limitations are outlined in this section. Bad practice contributes to potential risk factors on a strategic, business and operational level. A number of practices that are indicative of the effectiveness of governance are listed below. The practice factors indicated in the survey included beta (business) and alpha (non-business) risks. In addition, the indicators are representative of legal, financial, managerial, regulatory, human resource, institutional, business compliance and contractual practice.

Respondents were required to select the relevant box to indicate whether current practice is reflecting negatively on the governance of PPPs. A negative (no) response is indicative of bad practice and is a potential risk. A positive (yes) response is indicative of good practice and does not present a potential risk to the governance of PPPs. In addition, respondents were required to indicate whether his or her response was applicable to the public or the private partner.

The questions included in the survey that respondents were required to respond, included:

1. Implementation of BBBEE (black economic empowerment) 2. Intellectual Property Management (IPM)

3. Effectiveness of PPP legislation (legal) 4. Business Process Compliance (BPC) 4.1 Internal auditing (IA)

4.2 Monitoring and evaluation (M&E)

5. Document and Information Management (DIM) 5.1 Record keeping (RC)

5.2 Information sharing (Info)

6. Competitiveness of PPP process (CT) 7. Contract management (CM)

8. Project management capacity (PRM)

9. Consultation, stakeholder management, partnership cooperation and collaboration (SM)

10. Human resources (HR) 10.1 Capacity and skills (CS) 10.2 Training availability (TR) 11. Corporate governance (GV) 11.1 Professionalism (PR) 11.2 Efficiency (EF) 11.3 Quality (QL) 11.4 Leadership (LS) 11.5 Accountability (AC) 11.6 Innovation (IN) 11.7 Dispute resolution (DR) 11.8 Transparency (TR) 11.9 Corruption (CR) 12. Political commitment (PC) 13. Late payments (LP) 14. Risk management (RM) 14.1 Risk assessment (RM) 14.2 Risk mitigation (RI) 14.3 Risk controls (RC)

14.4 Risk controls verification (RCV) 14.5 Risk communication (RN)

The corresponding codes are utilsed to illustrate the primary theme of the question portrayed in the graphs presented below.

Originally Question 9 was split into two questions, firstly, consultation and stakeholder management, secondly, partnership cooperation and collaboration. However, when

164 composing the summary of amounts and graphs as presented below, the two questions were combined due to the overlapping nature of their themes, as the themes are all part of the stakeholder management function in a partnership.

The sample consisted of 168 surveys, thus n=168. However, when assessing the data the sample for each question was adjusted according to the number of responses for the particular question under assessment. This was performed in order to overcome the limitations presented by missing values or zero values, and duplication. In certain cases, the respondents did not complete each question. The incomplete questions were treated as missing data. The missing data can be explained in terms of the respondents’ understanding of the questions and the respondents’ experience related to the questions. The respondents either did not understand the question or had no experience related to the question. This did not affect the application of results, because respondents may only have had experience in dealing directly or indirectly with certain processes or sections related to the themes employed in this study. Thus, the respondents’ experience did not necessarily relate to the entire PPP process. In some cases, duplication of results occurred, where respondents responded ‘yes’ and ‘no’ for a question. This can be explained by a number of possible reasons. Either respondent’s made a mistake and accidently duplicated responses, or respondents intentionally responded ‘yes’ and ‘no’. This could either represent that the respondent meant that the response was a ‘maybe’ or it could signify that in some cases it was a ‘yes’ or a ‘no’. Thus, closed-ended responses and the use of a nominal scale presented a limitation. This limitation was not foreseen. A continuum scale would have been useful in order to prevent duplication, nonetheless, in order to overcome this limitation the duplicate results were omitted in the analysis, because the duplicate analysis skews the sample, the analysis and the results. Thus, the sample size was adjusted for each question and the sample size decreased in some cases due to missing values and duplicate (contradicting) values. However, this was acceptable, as the intention of the survey was to measure the frequency of ‘yes’ and ‘no’ responses.

As mentioned above, the use of a self-administered survey presented a limitation to the study. Reja et al. (2003) confirm this and explains that there is no interviewer to intervene

in the case of any misunderstanding. Also, selection bias may be present where respondents may not be motivated enough to complete the survey. Probing is also not possible (Reja et al. 2003:160-161).

In using closed-ended questions respondents have no choice other than to select one of the offered alternatives, and they do not have the opportunity to justify their responses (Reja et al. 2003:168). This can explain the presence of the missing data and duplicate data. Respondents either did not complete all fields because they could not choose from the two options provided as they could not justify their response, or it could be due to misunderstanding or lastly, lack of motivation for completing all fields. In effect, these values were treated as invalid responses and were excluded from the analysis.

Only descriptive data is presented because the nominal scale allows measurement for frequencies and Chi-square analysis. As mentioned earlier, this is acceptable for the purpose of this study, because this study is interested in comparing the frequencies firstly, of negative (no) responses that are indicative of bad practice and are a potential risk, and secondly, of positive (yes) responses that are indicative of good practice and do not present a potential risk to the governance of PPPs. The descriptive data for the binomial tests and further analysis is available in annexure C to this study. The descriptive quantitative data and results are available on request.

Marked data are presented in the following graphs. The data includes only the marked data, thus excluding any duplicate or missing responses. The table outlined in annexure C of this study represents the results for both public and private data, and arrives at a total for each question. The public data on the next page represents responses indicating whether there is currently good governance and best practice in the public sector involved in PPPs. Similarly, the private data indicates whether there is good governance and best practice in the private sector.

When presenting the data on a bar graph, the graph illustrated that the majority response is ‘yes’, which is indicative of a positive response which suggests good practice in the public sector. The label Q represents the question number, as outlined above. However,

166 questions 14.2 to 14.5 show more of an average response. This could be indicative of the respondents not having experience in risk management.

Figure 4.4: Public Marked Data 82 82 78 78 77 76 72 71 71 70 70 70 70 70 69 69 68 67 67 66 65 65 64 64 63 63 60 59 59 57 18 18 22 22 23 24 28 29 29 30 30 30 30 30 31 31 32 33 33 34 35 35 36 36 37 37 40 41 41 43 Capacity Learning and training Black Economic Empowerment Information sharing Record keeping Internal Auditing Political commitment Legislation Leadership Professionalism Stakeholder management, cooperation,…

Accountability Transparency Contract management Dispute resolution Project management capacity Information communication technology Risk management Monitoring and evaluation Innovation Quality Intellectual Property Management Competitiveness Efficiency Late payments Risk communication Risk mitigation Risk assessment Corruption Risk controls

Public Marked Data

Figure 4.5: Private Marked Data 92.42 90.91 88.16 88.06 88.00 87.27 86.44 86.15 85.94 83.87 82.86 80.52 79.71 78.95 77.55 77.19 76.92 76.81 75.44 75.00 74.63 73.91 73.24 72.60 72.41 60.00 57.81 55.56 49.21 47.46 7.58 9.09 11.84 11.94 12.00 12.73 13.56 13.85 14.06 16.13 17.14 19.48 20.29 21.05 22.45 22.81 23.08 23.19 24.56 25.00 25.37 26.09 26.76 27.40 27.59 40.00 42.19 44.44 50.79 52.54 Efficiency Professionalism Record keeping Project management capacity Quality Learning and training Leadership Accountability Capacity Information communication technology Internal Auditing Innovation Risk mitigation Contract management Legislation Stakeholder management, cooperation,…

Monitoring and evaluation Risk assessment Intellectual Property Management Dispute resolution Competitiveness Risk management Risk controls Risk communication Information sharing Black Economic Empowerment Late payments Transparency Corruption Political commitment

Private Marked Data

The software PSW 18.0 statistical package was utilised for the capturing and assessment of data. A Chi-square test was utilised as a “test of significance of the observed differences” (Bless & Kathuria 1993:187). The Chi-square test assesses the correspondence between facts and theory, but does not contribute information about the degree of relationship between the variables (Bless & Kathuria 1993:187). Because 2x2 tables were used in the Chi-square statistic, continuity correction was used. The assumption of validity for the continuity correction implies that 𝜋𝑔 = 𝜋𝑏 = 0,5. The theorem implies that πg indicates good governance and πb indicates bad governance; based on the binomial test of equality between responses, the difference between responses for good governance and bad governance was assessed. The H0: the

proportion of good governance is equal to the proportion of bad governance. H1: implies

that the proportions differ significantly. H0 is rejected when p < 0, 01. Thus, all the values

that are larger than 0, 01 assume that the proportion of good governance responses is not equal to the proportion of bad governance responses. In other words, if there is not a significant difference, then the results cannot be generalised.

The private marked data illustrated on the above chart also presents a majority of positive (yes) responses. However, a more averaged response is provided for questions 1, and 11.8 to 13. Conversely, 11.9 and 12 indicate a negative response. The questions include: 1. Implementation of BBBEE (black economic empowerment)

11.8 Transparency 11.9 Corruption

12. Political commitment 13. Late payments

Based on the negative response for questions 11.9 and 12, the data thus suggest that there is extant bad practice, through corruption and lack of political commitment. In sum, the above represented variables (questions 1, 11.8, 11.9, 12 and 13) present a significant difference, which leads the researcher to generalise these results.

The total amount of all frequencies presented above displays an overwhelming confidence of the respondents in the good practice and good governance of the public

sector. This could be suggestive of a bias towards the private sector. The study overcame this limitation by triangulating the quantitative results with the qualitative results.

There is an overwhelming amount of positive responses which indicates that current best practices in risk management combined with performance management approaches can effectively mitigate risks, and based on the significantly different results effective strategic control of PPP projects necessitates systematic integration of strategic planning, risk management and internal control of such projects.

4.10 Conclusion

This chapter supplies an overview of the research process of the study. This includes the planning of the study, the methodological conduct and the execution of the study. The chapter provides an overview of the data, the analysis and the presentation of the results of this study.

This chapter provides an assessment of preliminary results. The conclusions drawn from the preliminary results indicate a degree of bias in respondents. In order to overcome this limitation, the research will further explore the research questions through the qualitative data and results. The subsequent chapter encompasses the background to the case studies under review in this study.

CHAPTER 5

EMPIRICAL CASE STUDIES’ BACKGROUND

5.1 Introduction

An objective of this study is to determine the successes and failures of PPPs through reflections on local experience. This is achieved through a comparative analysis and assessment of four case studies, to establish whether PPPs are successful in serving the public through effective service delivery and also to establish the shortcomings of the prevailing model. This chapter provides background to each case study according to an integrated systems management approach. Case studies are used in this study as illustrations of theoretical assumptions to test the results of the study. Stake (1995:xi) defines a case study as “the study of a particularity and complexity of a single case,

coming to understand its activity within important circumstances”. As mentioned in

Chapter Four, case study research can be applied in quantitative and qualitative method. This study adopts an integrated systems approach to assess the selected cases as background for the interpretation of interview results. The purpose of this chapter is to supply a descriptive outline of the background to each case study under investigation.

5.2 Background

As discussed in Chapter Four, system analysis is concerned with examining complexities by assessing various systems and their linkages. Considering the complex arrangements involved in the organisation of PPPs, it is necessary to systematically assess the components of organisation. In order to assess each case this study adapts the systems thinking of the McKinsey 7S model. The McKinsey 7S model was developed in the early 1980s by Tom Peters and Robert Waterman, working at the McKinsey & Company consulting firm. The McKinsey 7S model involves interdependent factors in an organisation which can be categorised as either hard or soft elements. The hard elements include strategy, structure and systems. The soft elements are less tangible and more

influenced by culture, including values and work ethic, leadership and management style, staff and their capabilities, and the skills and competencies of the employees. The elements are interdependent and a change in one element can affect the other elements (Mindtools n.d.). Strategy would reinforce the structure and systems in the organisation, and the culture in the organisation is strongly dependant on the functionality of the strategy, structure and systems.

The original contributors to the McKinsey 7S Model, Waterman, Peters and Phillips, (1980:17) explain that: "our assertion is that productive organisational change is not simply a matter of structure, although structure is important. It is not as simple as the interaction between strategy and structure, although strategy is critical too. Our claim is that effective organisational change is really the relationship between structure, strategy, systems, style, skills, staff, and something we call super ordinate goals”.

The strategy element in an organisation includes the organisation strategy, objectives, means of achieving organisational objectives, methods of dealing with competitive pressure, methods of dealing with changes in customer demands, and how the strategy is adjusted for external and environmental issues (Mindtools n.d.). Strategy would thus include the vision, mission, purpose, strengths, weaknesses, opportunities, threats and role of the organisation. Considering the definition of risk as a potential adverse effect to the optimal functioning of an organisation, risk would be treated as a threat or an opportunity; furthermore, the strengths and weaknesses of an organisation would reinforce the capability to effectively manage risk, thus, risk is classified as a strategy component for the purpose of this study.

The structure element in an organisation includes the following:

 the division of the organisation into teams;

 the hierarchy in the organisation;

 coordination of activities between the various departments;

 the organisation and alignment of team members;

 the centralisation or decentralisation of decision-making; and

 lines of communication, and whether communication lines are implicit or explicit (Mindtools n.d.).

The structure is also inclusive of the organisations’ organogram, location, reporting lines and delegation of authority.

The systems element considers the main systems and resources, through which the organisation operates, for example the financial, human resources procurement, supply chain, information, and knowledge, as well communications and document storage