Question 4 Read the following case extract and answer ALL questions that follow. The survival of businesses in the 21st century depends largely on organisational climate. The organisational competencies and capabilities that steered companies to success in the past will almost certainly not guarantee any success going forward. Today, managers are grappling with the multiple challenges of delivering higher economic returns, improving productivity and reducing cost. In this regard, a deeper understanding of the dynamics of performance management has the potential to help steer an organisation towards an environment that has a competitive advantage (Rowland & Hall, 2012). Employee performance is defined as the outcome or contribution of employees that enable them to attain goals (Herbert, John & Lee 2000). The literature presents evidence of an existence of obvious effects of training and development on employee performance. Some studies have proceeded by looking at performance in terms of employee performance in particular (Purcell, Kinnie & Hutchinson 2003; Harrison 2000) while others have extended to a general outlook of organisational performance (Guest 1997: Swart et al. 2005). In one way or another, the two are related in the sense that employee performance is a function of organisational performance since employee performance influences general organisational performance. In relation to the above, Wright & Geroy (2001) noted that employee competencies change through effective training programs. It therefore not only improves the overall performance of the employees to effectively perform their current jobs but also enhances the knowledge, skills an attitude of the workers necessary for the future job. thus contributing to superior organisational performance. Zambezia Limited is an Information Technology company operating in a Southern African country. As part of a broad set of plans to sharpen the company's competitive edge, the new Chief Technology Officer (CTO) of the company, Mr Trevor Ncube, has hypothesized that a continuous improvement programme (CIP) consisting of several specialised training sessions for employees would improve employee performance in the long run. A pilot study premised on three specialised training sessions for 200 employees who were randomly selected from the company's 500 workforce took place during the 2020 fiscal year, at the end of which the impact of the programme was evaluated to determine its efficacy. At the beginning of the exercise, the 200 employees were randomly selected out of 410 individuals who volunteered to take part in the study. The 200 employees were tested for their baseline competence on a scale of 1 to 10 (where 1 denotes the lowest possible score and 10 the highest possible score), using a standardised measurement instrument. The 200 employees were subsequently tested using the same instrument at the end of the first, second and third training sessions The scores obtained in each of the tests were recorded as shown below in Table 4.1. There was zero participant attrition throughout the continuous improvement programme. Table 4.1: An excerpt of the data collected as part of the CIP (Note the scores of only ten participants are shown here) Post-training 3 score Respondent # Pre-training score Post-training score Post-training 2 score 6 7 5 5 7 9 2 4 6 3 7 6 6 7 8 4 4 7 7 8 GO 5 5 8 6 6 7 5 6 ON 7 4 6 5 02 8 6 7 7 7 7 9 6 6 8 8 CO 200 5 8 8 The data was analysed using IBM SPSS Statistics version 25 and the output showed in Table 4.2 to Table 4.6 was produced Table 4.2: Test of Normality of Employees Competence Scores measured on 4 occasions Tests of Normality Kolmogorov-Smirova Shapiro-Wilk Statistic df Sig Statistic df Sig Pre_Training Score 090 200 084 985 200 323 Post_Training1_Score 136 200 .079 987 200 469 Post_Training2_Score 072 200 200 992 200 855 Post Training Score 082 200 097 964 200 407 This is a lower bound of the true significance a, Lilliefors Significance Correction Table 4.3: Dependent Variable measured on 4 occasions Within-Subjects Factors Measure: MEASURE_1 Time Dependent Variable 1 Pre_Training Score 2 Post_Training1_Score 3 Post_Training2_Score Post_Training3_Score 4 Table 4.4: Descriptive Statistics of the Dependent. Variable measured on 4 occasions Descriptive Statistics N N Mean Sid. Deviation 5.010 .81438 200 Pre-Training Score 95894 200 6.755 Post Training Score 200 Post Training Score 7.240 .86959 7.930 Post Training Score 200 79893 Table 4.5 Multivariate Tests Multivariate Tests Elect Value Hypothesis df F Error of Sig Partial Eta Squared Time Pillai's Trace 643 31.050 3.000 197.000 000 643 Wilks lambda 495 31.050 3.000 197.000 000 643 Hotoling's Trace 1.132 31.050 3.000 197.000 .000 643 Roy's Largest Root 1.132 31.050 3.000 197.000 000 543 a Design: Intercept Within Subjects Design: Time b. Exact statistic Table 4.6: Test of Sphericity Mauchly's Test of Sphericity Measure. MEASURE 1 Epson Approx Chi- Square Mauchly's W Within Subjects Elfect Greenhouse Geisser Huynh- Feldt Sig Lower-bound Time 878 26 252 3 104 681 .723 500 Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix a. Design: Intercept Within Subjects Design: Time b. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table Table 4.7: Testof Within-Subjects Effect Tests of Within-Subjects Effects Measure: MEASURE 1 Type III Sum of Squares Partial Eta Squared Source F Mean Square Sig Time Sphericity Assumed 423 021 3 141007 58.228 000 543 Greenhouse-Geisser 423.021 1.782 237386 58 228 000 543 Huynh-Feidt 423.021 1.845 229 280 58 228 000 543 Lower-bound 423.021 1.000 423.021 58.228 000 543 Error(Time) Spherioty Assumed 1445.934 597 2.422 Greenhouse-Geisser 1445.934 354 671 4077 Huynh-Foldt 1445.934 367 210 3.938 Lower-bound 1445.934 199.000 7.265 Table 4.8: Test of Within-Subjects.Etfect Pairwise Comparisons Measure MEASURE_1 95% Confidence interval for Difference Mean Differencell - J) Time Sid. Error Lower Bound J) Time Upper Bound Sig -1.504 1 2 -1.745 003 - 1986 123 3 598 -2 230 -3.402 -1.058 000 4 -2.920 1.158 000 -5.190 -0.650 2 2 1 1.745 123 003 1.504 1.986 3 -485 638 042 -1735 .765 4 -1.175 931 ,000 -3.000 650 1 2.230 598 .000 1.058 3.402 2 485 638 042 - 400 2.100 4 - 690 794 033 -2.246 866 4 1 2.920 1.158 000 650 5.190 2 1.175 931 000 -650 3.000 3 690 .794 033 - 866 2.246 Based on estimated marginal means The mean difference is significant at the 05 level b. Adjustment for multiple comparisons: Bonferroni. 4.1 (4 marks) 4.2 (3 marks) Specify and elaborate on the type of research conducted by Mr Ncube in the study and the research design employed Specify the independent and dependent variables implicit in Mr Ncube's study, Formulate the nul and alternative hypotheses for Mr Ncube's study On the basis of the output, discuss whether the impact evaluation was performed using a parametric test or a non-parametric test. Substantiate your answer 4.3 (2 marks) 4.4 (3 marks) 4.5 (2 marks) 4.6 With the aid of the statistical decision making tree, specify the main inferential statistical test which was performed as part of the data analysis to evaluate the impact of the continuous improvement programme on employees' performance and substantiate the appropriateness of this test Provide a comprehensive interpretation of the output, stating the primary findings from the study and specify whether the training programme (ie, the intervention) yielded a significant improvement in employee scores? On the basis of a preliminary literature review, state ANY TWO (2) actions that Mr Ncube could have taken to address the problem at Zambezia Limited without conducting the study. (4 marks) 4.7 (2 marks)