The Structure of Conceptual Performance Prediction Model

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This chapter is organised around the appropriateness of the research design, the population sampling and detailed description of the data collection instruments. The method used for data analysis is explained with a brief description of how validity and reliability were ensured. According to Webb and Auriacombe (2006), it is important in a research project to select those methods and techniques that are appropriate to the research goal. This research looked at proper methods of investigating and exploring a phenomenon and survey.


Flick (2006) defines a research design as a plan for collecting and analysing evidence that will make it possible for the investigator to answer questions posed to the target population. This study employed a mixed-method approach to explore the determinants of ECs business performance by applying both qualitative and quantitative research to provide a better understanding of the research problem than either form itself. According to Creswell, (2008) a mixed-method study presents the researcher with an opportunity to make a more convincing argument through triangulation, used to check if there was convergence, corroboration and correspondence of results. The first phase of the design was qualitative, with which in-depth interviews were conducted to define the various thematic areas that led to the development of the quantitative assessment part of the study (phase two) as shown in Figure 3.1 (below).
The researcher used a cross-sectional study design carried out in the Gauteng Province, which allowed for the determination of the prevalence of certain perceptions of SBEs, hence establishing the important determinants which helped set the strategy for performance improvement. Because there has been no similar study on the perceptions of SBEs on determinants of performance in the construction industry the design was considered appropriate, the nature of the information required making the adoption of the mixed-method approach most appealing. This was in line with Denzin and Lincoln (2008), who note that, epistemologically, a multi-methodological approach enables far richer insights to be gained on the phenomenon under consideration. Abowitz and Toole, (2009) also note possible improvements in validity and reliability of data as a result of the use of the approach.

Qualitative approach

The knowledge on SBEs’ perceptions was augmented by interviewing ECs’ chief executive officers, chief financial officers, contract directors and marketing directors as representatives. This means detailed descriptions of situations, events, interactions and observed behaviour from respondents about their experiences, attitudes, beliefs and thoughts, correspondences, records and case histories were collected and investigated, in line with Flanagan (1954). By using a qualitative technique, the findings had greater validity as the process revealed in-depth understanding and richness of the situation (Cooper and Schindler, 2011). However, the technique was undermined by the subjectivity and susceptible to human error and bias in data collection and interpretation. The results could not be generalised to a larger population, considered a fundamental weakness for the approach. Measuring perceptions which are subjective norms needed to be quantified, hence a quantitative component was added to explain the quantifiable perceptions as measured on a Likert scale.

Quantitative approach

A quantitative research approach is grounded on the positivist social sciences paradigm, which primarily reflects the scientific methods of the natural sciences. In line with Creswell (1994), a quantitative research approach was used in this study because it is an effective design for research questions related to measuring how much the perceptions were determinants of ECs’ performance. Quantitative method involves the use of numerical and statistical analyses of measurements to examine social phenomena (Cooper and Schindler, 2011). Numerical data was gathered on variables in establishing how dependent or independent variables were through the lens of statistical tools. The advantages that were considered for using this method included its great premium on objectivity and reliability of findings. The method was triggered by large amounts of data obtained from the survey, but whilst the researcher’s influence on the research was significantly reduced, thereby minimizing bias (Saunders, et al. 2003), quantitative research may not always be appropriate as it cannot accurately or reliably measure phenomenological issues such as perceptions, thus reducing the validity of the findings.

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Integration of the research designs

The results received from both qualitative and quantitative data were subject to integration, defined by Creswell, (2003) as a combination of both forms of research within a given stage of enquiry. It occurred within data analysis whereby transformation of qualitative themes into quantitative items was carried out and interpretation of both forms was assessed for convergence and divergence


The research population was limited to the ECs in Grade 2, registered with CIDB in Gauteng. The ECs that engage in General Building (GB) and Civil Engineering (CE) became the target population, however, it was noted that CIDB would not include every potential contractor of the same size in the province and such contractors were thus excluded. The registration database reflected 1,890 urban based ECs in Grade 2 registered with the provincial board. Grade 2 contractors are typically established and developing contractors that operate at a local level (Windapo Oladapo, 2012; CIDB, 2013). The details of the distribution of the total number of registrations in terms of class of work in Gauteng Province are shown in Table 3.1 (below).
Gauteng Province was selected based on the level of business confidence recorded during the financial year 2011 /2012 (CIDB Quarterly Review, 2013), when the province appeared the most prosperous in SA, also having a high concentration of construction works. On the bases of accessibility and time factors for the study, urban based ECs were considered. The participants were all executives of the respective ECs, which was in line with the research design.
The study focused on ECs in Grade 2 because using a single category in a sector enabled control of specific factors or an “industry recipe” (Masakure, et al. 2009) that everybody in the industry should recognise. The use of a single sector and particular grade made it possible to generalise the results beyond the studied provinces and particular CIDB grades. An EC was included in the target population if it met the following parameters:

  • The business operation was registered with CIDB Grade 2 in the construction industry and operated business in the geographic location of Gauteng.
  • The business had been in the construction sector for more than one year, because ECs that were very young might not have fully encountered construction business incidences that affected performance and this would skew the results.
  • The business that employed between four and ten full-time employees, because it was the focus of the South African Government.
  • The unit analysed comprised the SBEs (chief executive officer, chief financial officer,contract    director, marketing director and other executives) as representatives of ECs in the sample set. The unit of analysis is the entity being analysed, for example individual people, groups and/or organisations. It describes the level at which the research is performed and which objects are researched (Serumaga-Zake, 2011). By virtue of their seniority within the enterprise, SBEs were in an ideal position to give valuable information on the determinants of ECs’ performance. The reasons for selecting this unit of analysis were that SBEs have high degree of encounters which are significant for the performance of the business and play a more active role in decision-making, strategy formulation, implementation and reporting within an organisation. SBEs are also directly responsible for making strategies and encounter incidences that facilitate or impede such business decisions.
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Sampling for qualitative data

The qualitative research phase selected ECs who had been involved in the construction work within the Gauteng Province, and the sample size was determined according to Flanagan’s (1954) recommendations that adequate coverage has been achieved when the addition of 100 critical incidents to the sample adds only two or three critical behaviours. Based on this recommendation, six ECs were purposefully selected from the target population as all were available. There are no rules for sample size in qualitative inquiry, rather it depends on what the researcher wants to know, the purpose of the inquiry, what is at stake, what would be useful, what would have credibility and what could be done with available time and resources (Paton, 2002). Interviews were conducted with one SBE as representative of each EC.

Sampling for quantitative data

The sampling frame used for this study was constructed from a CIDB database, this being less costly than custom-made lists, and the register was current with new establishments. However, the researcher was aware that government organisations such as the CIDB are slow in dropping establishments that have gone out of business

1.1 Background to the Study
1.2 Theoretical foundation and Literature Review
1.3 The Problem Statement
1.4 Brief Research Design
1.5 The Scope of the Study
1.6 Perceived Contribution to Knowledge
1.7 Brief description of the Chapters in this Thesis
1.8 Summary
2.1 Chapter Introduction
2.2 Theoretical Foundation of the Study
2.3 Defining performance
2.4 Measuring performance
2.5 The Determinants of ECS’ performance
2.6 Clarification of Concepts
2.7 Summary and identification of the Gap
3.1 Chapter Introduction
3.2 The Research Design
3.3 Population of the Study
3.4 Phase one: Measuring qualitative data
3.5 Phase two: Measuring quantitative data
3.6 Pilot Study
3.7 Data collection procedure (Quantitative data)
3.8 Analytical techniques of quantitative data analysis
3.9 Control of bias
3.10 Ethical considerations of the study
4.1 Chapter Introduction
4.4 Chapter Conclusion
5.1 Chapter Introduction
5.2 Data Transformation
5.3 Case Analysis: Determinants of business performance
5.4 Typological Development
5.5 Chapter Conclusion
6.1 Chapter Introduction
6.2 The Structure of Conceptual Performance Prediction Model
6.3 Summary of The Conceptual Performance Prediction Model
6.4 Chapter Conclusion
7.1 Chapter Introduction
7.3 Conclusions
7.4 Recommendations
7.5 Implications of the Study
7.6 Limitation of the Study
7.7 Conclusion

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