83 CHAPTER THREE RESULTS This chapter examines the statistical findings of analyses conducted on the data collected. The initial aim of the research report was to explore call centre agent?s perceptions of the work experienced in call centres, characterised specifically by their experiences of high demand and low control in the call centre environment. A second subsidiary aim was to ascertain whether or not organisational climate influences call centre agent?s perceptions of their job satisfaction, their life satisfaction and their self-esteem. Taking the exploratory nature of this study into consideration a number of findings emerged. These findings will follow. 3.1. Level of Employee Performance Monitoring The present study obtained a description of the different monitoring systems used within the four organisations from the managers of the call centres. The information was obtained to provide a description of the monitoring equipment used, what the findings are used for and how this information is conveyed to the call centre agents. Table two represents these findings. 84 TABLE 2: EMPLOYEE PERFORMANCE MONITORING ORGANISATION TYPE OF MONITORING SYSTEM FREQUENCY OF REPORTS INFORMATION USED FOR MANNER CONVEYED FREQUENCY OF COMMUNICATION 1 Siemens Hipath 300: Monitors who is actively on a call or unavailable, monitors agent?s call performance, statistics of calls Unison Stella Nova: Logs all incoming and outgoing call numbers, duration and cost. Spescom Data Voice: Voice recorder, records all calls Daily Agent performance Trends in buying E-mail Meetings Monthly 2 Mystery shopping (tape their calls) In-house training where the focus is on customer services, dealing with conflict and telephone skills Weekly Improving employee performance Team sessions: play back 4 calls in the sessions Group discussions of the calls Weekly 3 A standard template is used Avaya: monitor the calls sign on times, abandoned, dialed calls, and calculate the productivity from the codes used Daily To measure and address performance One-on-one discussions Monthly 4 Avaya: monitor the calls (sign on times, abandoned, dialed calls), and calculate the productivity from the codes used Daily Performance management Training One-on-one discussions on targets reached between manager and agent Managers: monthly Call centre agents: self-monitoring can be done daily 85 3.2. Descriptive Statistics The present study computed descriptive statistics to classify and describe the sample with means, frequencies, variance and correlations. Means are used to describe the average (Howell, 1999). Frequency data represents the number of observations in each category (Howell, 1999). The variance is the ?measure of the average deviations of each score from the mean? (Howell, 1999, p69). Table three below contains the means, maximum and minimum values, number of observations, number of missing observations and standard deviations, for all the subscales in the JCQ scale and the job satisfaction, life satisfaction and self-esteem scales. From the table, one can see that there is not a significant deviation from the mean, thus, one can conclude that the distributions are relatively normal. The researcher attempted to answer research question one by taking the mean rating of the variables that characterise the demand and control construct. For the purposes of the present research, the researcher used the scales ?decision latitude? to classify the construct of job control and ?psychological job demands? to classify the construct job demand. The researcher used the maximum value of decision latitude (34.00) as the benchmark for high control and the minimum value (9.00) as the benchmark for low control. Similarly, the maximum value (30.00) was used to classify high psychological job demand and the minimum value (14.00) was used to classify experiences of low psychological job demand. The mean value for decision latitude was found to be 23.34, while the mean rating for psychological job demands was 20.78. However, from these scores one can see 86 that the actual mean score for decision latitude should be 21.50 and 22 for psychological job demand. TABLE 3: DESCRIPTIVE SUMMARY STATISTICS Variable Max. Mean Min. N N Miss SD Skill Discretion 24 15.96 6 219 0 3.09 Decision Authority 12 7.38 3 219 0 1.66 Decision Latitude 34.00 23.34 9.00 219 0 4.29 Psychological Job Demands 30.00 20.78 14.00 218 1 3.00 Co-worker Support 24 18.10 7.2 218 1 2.69 Supervisor Support 20 15.11 1.25 217 2 2.69 Social Support 44.00 33.15 18.00 218 1 4.58 Organisational Climate with Technology subscale 135.00 111.70 83.87 214 5 9.33 Job Satisfaction 35.00 24.63 10.00 214 5 4.75 Life Satisfaction 35.00 22.34 5.00 215 4 6.61 Self-Esteem 30.00 22.37 9.00 216 3 4.43 87 3.3. Correlations Table four graphically represents the findings of the present research in the form of a correlation matrix. Additionally, a detailed description will follow. TABLE 4: CORRELATION MATRIX OC DL SD DA PsD SS SupS CS Tech JS LS SE OC DL 0.77193 <.0001 214 SD 0.75328 <.0001 214 0.94902 <.0001 219 DA 0.58799 <.0001 214 0.81145 <.0001 219 0.99991 <.0001 220 PsD 0.35823 <.0001 214 0.08887 0.1911 218 0.10664 0.1164 218 0.03058 0.6534 218 SS 0.72544 <.0001 214 0.39573 <.0001 218 0.39251 <.0001 218 0.28892 <.0001 218 -0.06108 0.3694 218 SupS 0.57707 <.0001 214 0.39767 <.0001 217 0.36547 <.0001 217 0.34449 <.0001 217 -0.16682 0.0139 217 0.82925 <.0001 217 CS 0.63517 <.0001 214 0.28683 <.0001 218 0.99922 <.0001 219 0.99914 <.0001 219 0.08127 0.2321 218 0.80967 <.0001 218 0.37718 <.0001 217 Tech 0.56004 <.0001 214 0.24261 0.0003 216 0.24304 0.0003 216 0.17303 0.0109 216 0.04676 0.4942 216 0.12997 0.0565 216 0.09014 0.1879 215 0.20621 0.0023 216 JS 0.46001 <.0001 212 0.52983 <.0001 214 0.49881 <.0001 214 0.44151 <.0001 214 -0.13200 0.0538 214 0.40467 <.0001 214 0.39992 <.0001 214 0.27209 <.0001 214 0.13949 0.0420 213 LS 0.27375 <.0001 213 0.23775 0.0004 215 0.19525 0.0041 215 0.24910 0.0002 215 -0.02974 0.6646 215 0.20042 0.0032 215 0.21237 0.0018 214 0.17064 0.0122 215 0.21159 0.0019 214 0.43673 <.0001 213 SE 0.08617 0.2104 213 0.04268 0.5327 216 0.01279 0.8517 216 0.08597 0.2082 216 -0.00885 0.8972 216 0.12187 0.0739 216 0.11908 0.0815 215 0.12825 0.0599 216 0.03799 0.5796 215 0.07125 0.2995 214 0.26830 <.0001 215 KEY INPUT VARIABLES OUTCOME VARIABLES OC Overall Organisational Climate JS Job Satisfaction DL Decision Latitude LS Life Satisfaction SD Skill Discretion SE Self-Esteem DA Decision Authority PsD Psychological Job Demand SS Social Support SupS Supervisor Support CS Co-Worker Support Tech Technology 88 a) Overall Organisational Climate Organisational climate was strongly correlated with technology (r = 0.56, p<0.0001) and job satisfaction (r = 0.5, p<0.0001), while it moderately correlated with psychological job demands (r = 0.4, p<0.0001). There was a weak correlation between organisational climate and life satisfaction (r = 0.27, p<0.0001). No other correlations were found to be significantly correlated with organisational climate. b) Skill Discretion The relationships between skill discretion and decision authority (r = 0.99, p<0.0001), co- worker support (r = 0.99, p<0.0001) and overall organisational climate (r = 0.75, p<0.0001) were very strong, and the relationship between skills discretion and job satisfaction (r = 0.5, p<0.0001) was strong. A moderate correlation was shown between skill discretion and social support (r = 0.4, p<0.0001) and supervisor support (r = 0.4, p<0.0001). Weak correlations are present between skill discretion and technology (r = 0.24, p = 0.0003) and life satisfaction (r = 0.19, p<0.0001). c) Decision Authority The relationships between decision authority and each of the other variables were either very weak or non-existent. A weak correlation was shown between decision authority and supervisor support (r = 0.34, p<0.0001) and overall social support (r = 0.28, p<0.0001). No other relationships were shown to be significantly correlated with decision authority. d) Decision Latitude A very strong relationship was shown between decision latitude and overall 89 organisational climate (r = 0.77, p<0.0001), and a strong relationship was shown to exist between decision latitude and job satisfaction (r = 0.53, p<0.0001). A moderate correlation was shown between decision latitude and supervisor support (r = 0.4, p<0.0001) and overall social support (r = 0.4, p<0.0001). Weak relationships were shown to exist between decision latitude and co-worker support (r = 0.28, p<0.0001), technology (r = 0.24, p = 0.0003) and life satisfaction (r = 0.23, p = 0.0004). e) Psychological Job Demands The relationships between psychological job demands and each of the eleven variables correlated showed either very weak negative relationship or no relationship whatsoever. Psychological job demands correlated with supervisor support (r = -0.16, p = 0.01) and job satisfaction (r = -0.13, p = 0.05) showed a negative weak relationship. f) Co-worker Support There is a strong relationship between co-worker support and overall organisational climate (r = 0.63, p<0.0001), and a moderate relationship between co-worker support and supervisor support (r = 0.4, p<0.0001). The correlations between co-worker support and the rest of the variables showed weak relationships or no relationship whatsoever. The weak correlations were shown to exist between co-worker support and technology (r = 0.20, p = 0.002), job satisfaction (r = 0.27, p<0.0001), life satisfaction (r = 0.17, p = 0.01) and self-esteem (r = 0.12, p = 0.05). g) Supervisor Support The highest correlation for supervisor support is with overall organisational climate (r = 90 0.6, p<0.0001). There is a moderate relationship between supervisor support and job satisfaction (r = 0.4, p<0.0001), and weak relationship was shown for life satisfaction (r = 0.21, p = 0.001). No other correlations were significant with supervisor support. h) Social Support A strong correlation was shown between social support and overall organisational climate (r = 0.72, p<0.0001), and a moderate correlation between social support and job satisfaction (r = 0.40, p<0.0001). Weak relationships between social support and technology (r = 0.13, p = 0.05), and life satisfaction (r = 0.2, p = 0.003) were shown to exist, while the remainder of the variables were not correlated at all with social support. i) Job Satisfaction The highest correlation for job satisfaction was between job satisfaction and life satisfaction, with only a moderate relationship found (r = 0.44, p<0.0001). j) Life Satisfaction Life satisfaction showed a weak relationship to self-esteem (r = 0.26, p<0.0001). The next chapter will present an interpretation and discussion of the findings, as well as highlighting some of the limitations of the present study.