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This research was done at South Africa‟s largest open, distance-learning institution with a staff complement of approximately 4 500. This institution has over 300 000 00 active students in and outside the Republic of South Africa. Its main campus is in Pretoria, with decentralised regional offices for registration and student support.
This university has six main colleges, 68 academic departments and approximately 1400 academic staff. The majority of academic staff report to a formally appointed chair of department (CoD) which intern reports to directors of schools. The span of control of these departments differs across the spectrum and is mostly determined by the number of students each department is responsible for.
In order to obtain a representative sample of this institution two main sampling approaches for quantitative and qualitative data were used (see Table 4.3). The quantitative research (a) was done based on a quota sampling procedure, which is a form of non-probability sampling. According to Wellman and Kruger (2001:61), when using this form of sampling an effort should be made to have the same proportion of unit of analysis of demographic variables for important strata. The researcher distributed the online survey questionnaire to all the colleges and departments of the institution.
This institution has 1 413 academic members of staff. These staff members were targeted based on the consideration that the success of their leader‟s actions is based on their own willingness to be influenced by their leaders (see Chapter 2). Views and perceptions of academic staff who report to CoDs can, therefore, provide much clarity on how they perceive their leaders (CoDs) and the development support they receive. Secondly, for purposes of this study and the hypotheses that were formulated, it was important to determine followers‟ perceptions of the quality of the relationship with their leaders, which would influence how they perceived supervisory support for development and the organisation‟s perceived investment in their development (PIED). It was also important to learn more about the dynamic relationship between the academic leader and follower across the spectrum of one academic institution. In view of the aims stated, academic leaders, such as heads of department (CoDs), did not form part of the 1 413 academic staff population who were targeted for the quantitative analysis. Demographic aspects that were taken into account to achieve sufficient representation in this quantitative sample included the colleges and departments of the institution, gender, tenure and academic position. Colleges that formed part of the initial distribution were:
College of Education
College of Science, Engineering and Technology
College of Economic and Management Sciences
College of Law
College of Human Sciences
College of Agriculture and Environmental Sciences
After surveys had been distributed to and received back from the above-mentioned colleges, completed surveys were monitored to make sure that a cross-section of the population had been covered based on equal representation in respect of the set demographic criteria. This approach and procedure allowed for the control of all other variables associated with other academic institutions and the achievement of a representative sample that was as close as possible to a replica of the population (De Vos, Strydom, Fouche & Delport, 2007: 207).
A total of 301 questionnaires were received back, representing a final response rate of 21,5%. Ten questionnaires that formed part of the original sample from the College of Education were omitted because the CoDs of this newly established college had been appointed fairly recently and responses were perhaps not a true reflection of the relationship between CoDs and staff. The total sample after the omission of the 10 respondents resulted in an effective response rate of 20,8%.
The second part of the research included obtaining qualitative data (b) by conducting in-depth semi-structured interviews with a select sample of CoDs (see Table 4.3). This was required to better understand and clarify certain findings obtained from the quantitative analysis. The qualitative research component was based on a purposive sampling procedure. According to De Vos et al. (2007:328), qualitative studies apply non-probability sampling methods in the form of purposive sampling techniques.
Wellman and Kruger (2001:63) are of the opinion that purposive sampling is the most important kind of non-probability sampling that exists. The authors point out that this type of sampling relies mainly on the experience and ingenuity of the researcher in order to obtain representative units of analysis. However, Wellman and Kruger caution against this form of sampling due to different researchers opting for different approaches and methods to obtain a relevant sample, which could affect the representation of the study. De Vos et al. (2007:329) support this view by stating that it is important to have a clear identification and formulation of appropriate criteria for the selection of the respondents. Erlandson, Harris, Skipper and Allen (1993:33) expand on the issue of the selection of appropriate criteria by adding that the search for data should be guided by sound processes that can ensure rich detail of information taken from a particular context. Of particular importance to this study was to seek divergent data that could be thoroughly analysed.
Post-hoc model
Finally, a second, alternative post-hoc model was introduced. Due to the mediocre fit of the original theoretical model, an adjustment was made to the original model. During the process of fitting the original a priori model, it became apparent that a key linkage had been overlooked in the theorising phase. This linkage was between the positive relationship between training opportunities initiated by the CoD (19b) and the training opportunities received from the institution (19a). An adjustment to the model was made by treating both these variables as two dependent mechanisms, subsuming covariance rather than treating them as separate entities. However, this did not change the fundamental theorising underlying the model. Although I did not initially theorise that the amount of training and development opportunities received from the institution (19a) could also be shaped by the amount of training and development opportunities initiated by the CoD (19b), the modification indices indicated a significant improvement in fit if this path was freely estimated. Therefore, it made theoretical sense to include this path in the model. One reason for this inclusion was that both these measurements had been constructed to reflect on training and development opportunities received. Although it was initially intended to distinguish between these two measurements it was likely that they would impact on one another. Furthermore, the number of training and development opportunities members received from their CoD could also impact on the total amount of training and development opportunies the member perceived the institution to provide. This could be ascribed to the CoD‟s involvement in the whole process of training and development.
The modification indices between 19a and 19b and the parameter change of an additional path between these variables are indicated in Table 5.11. No outliers in the first analysis were removed and the sample size was the same for both the original and post-hoc models. In addition, no variables and factors were added or omitted in this second constructed post-hoc model (Quintana & Maxwell, 1999).
CHAPTER 1: PREVIEW AND BACKGROUND OF THE STUDY
1.1 INTRODUCTION
1.2 PROBLEM STATEMENT
1.3 PURPOSE STATEMENT
1.4 RESEARCH QUESTIONS
1.5 RESEARCH OBJECTIVES
1.6 RESEARCH DESIGN AND METHODOLOGY
1.7 SIGNIFICANCE OF THE STUDY
1.8 DELIMITATIONS AND ASSUMPTIONS
1.9 DEFINITION OF KEY TERMS
1.10 CHAPTER OUTLINE
1.11 CHAPTER SUMMARY
CHAPTER 2: LITERATURE REVIEW
2.1 INTRODUCTION
2.2 MAPPING THE TALENT MANAGEMENT LANDSCAPE
2.3 LEADERSHIP PARADIGMS, THEORIES AND EMPLOYEE DEVELOPMENT
2.4 LEADER-MEMBER EXCHANGE THEORY
2.5 SUMMARY
CHAPTER 3: THEORETICAL FRAMEWORK AND HYPOTHESES
3.1 INTRODUCTION
3.2 THEORETICAL FRAMEWORK OF THE STUDY
3.3 THEORETICAL TESTING
3.4 SUMMARY
CHAPTER 4: RESEARCH DESIGN AND METHODS
4.1 INTRODUCTION
4.2 DESCRIPTION OF INQUIRY STRATEGY AND BROAD RESEARCH DESIGN
4.3 MEASURES
4.4 SAMPLE
4.5 DATA COLLECTION APPROACH AND METHOD
4.6 SUMMARY
CHAPTER 5: DATA ANALYSIS
5.1 INTRODUCTION
5.2 QUANTITATIVE RESULTS
5.3 QUALITATIVE ANALYSIS
5.4 SUMMARY
CHAPTER 6: DISCUSSION OF THE RESULTS
6.1 INTRODUCTION
6.2 OVERVIEW AND CONSOLIDATION OF KEY RESEARCH RESULTS
6.3 FINDINGS IN RELATION TO LITERATURE
6.4 SUMMARY
CHAPTER 7: CONCLUSION AND RECOMMENDATIONS
7.1 INTRODUCTION
7.2 KEY FINDINGS
7.3 RECOMMENDATIONS
7.4 THEORETICAL IMPLICATIONS AND CONTRIBUTIONS
7.5 LIMITATIONS AND FUTURE RESEARCH
7.6 PRACTICAL IMPLICATIONS
REFERENCES
