Initial structural model-RTN analysis

The initial structural model-RTN (Figure 5.10) analysis uses the Maximum Likelihood (ML) to estimate as recommended by other researchers as this method provides statistically robust results with complete data irrespective of the normal distribution of the data (Little & Rubin, 1987). ML method also provides estimates of all the parameters in the model simultaneously with model estimation (Kline 1998). According to Kline (1998) ML method estimates parameters taking into account the associations within the model that are unanalyzed between exogenous variables AMOS, the software used in this research, facilitates the use of ML method, enabled the researcher to generate estimated outputs of the model in two formats namely the unstandardized output and the standardized output. Reports generated by AMOS as standardised output, provide model parameter measurements in the same metric uniformly for the entire model while the unstandardized output provides parameter measurements in metrics that are particular to each variable. The main disadvantage of unstandardized output is that the reports generated by AMOS are not comparable across variables (Abramson et al. 2005). Additionally, standardized reports generated by AMOS provide regression coefficients with absolute values. According to Kline (1998) regression weights with absolute values 0.1, 0.3 and 0.5 are classified as small, moderate and large. These arguments support the easy understanding and interpretation of standardized reports generated by AMOS. A major point that needs to be considered at this point is that unstandardized report generated by AMOS addresses individual exogenous variable variance directly on the

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model whereas endogenous variable variance is reported by AMOS in terms of squared multiple correlation directly on the model as standardized output. In view of the fact two different types but relevant information is reported by AMOS under two different reports, both unstandardized and standardized outputs are normally reported by researchers. Thus Figures 5.11 and 5.12 outputs generated by AMOS pertain to unstandardized and standardized reports of the Initial structural model-RTN.

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Figure 5.12 Standardised initial structural model-RTN

The initial structural model-RTN was examined for validity by examining the sample correlation, standard residual covariance and the goodness fit of the model to the data. (Appendix 10) provides the sample correlation tabulation. Reference value of sample correlation set as acceptable was 0.8 based on the recommendation of other researchers 9 (Holmes-Smith et al. 2006). Appendix 10 shows that all correlation values are less than 0.8. (Appendix 11) tabulates the standardized residual covariance values. Acceptable value of standardized residual covariance recommended by researchers is less then ±2.0 (Eom, 2008). One item MP17 was a cause of concern with respect to the standardized residual covariance values and was deleted. The resulting standardized residual covariance generated by AMOS is given in (Appendix 11) which indicates that all values are less than or equal to ±2.0. Goodness fit was measured using RMR, IFI, TLI, CFI and

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RMSEA. As explained in Section 5.7.3 goodness fit measures were found to be satisfactory (see Appendix 12). Next the paths linking the different variables in the model were analysed. The regression weight report produced by AMOS is given in Table 5.10. Paths were analysed beginning with the examination of the p-value of significance for each one of the relationship between variables. According to researchers (e.g. DeCoster & Claypool, 2004) p-value determines whether a relationship is significant or not. According to Albright and Park (2009) p-values less than 0.05 provide the basis to reject the null hypothesis while values greater than 0.05 provide the basis for reject the alternate hypothesis and hence the corresponding relationship between the independent and dependent variables. From these arguments and an inspection of Table 5.9 it was possible to infer that the paths MP-2 → MOTIVAT, MP-3 → SATISFAC, MOTIVAT → SATISFAC, MOTIVAT → RTN and SATISFAC → RTN were found to be significant while the paths MP-1 → MOTIVAT, MP-3 → MOTIVAT, MP-1 → SATISFAC and MP-2 → SATISFAC where found to be insignificant.

Regression Weights: (Group number 1 - Default model)

Estimate S.E. C.R. P Label MOTIVAT <--- MP-2 .149 .076 1.956 .050 par_33 MOTIVAT <--- MP-1 .109 .092 1.191 .234 par_34 MOTIVAT <--- MP-3 -.056 .114 -.495 .621 par_36 SATISFAC <--- MP-1 -.069 .081 -.863 .388 par_30 SATISFAC <--- MP-3 .379 .104 3.643 *** par_31 SATISFAC <--- MP-2 .005 .067 .077 .938 par_32 SATISFAC <--- MOTIVAT .341 .056 6.093 *** par_35 RTN <--- SATISFAC .424 .079 5.341 *** par_29 RTN <--- MOTIVAT .575 .075 7.626 *** par_37

Table 5.9 Initial model-RTN

In order to understand how the results of this analysis stand with respect to findings of other researchers it was essential to define MP-1 and MP-2 and MP-3. Using the contents of Table 5.5 it was possible to describe the factors MP-1 and MP-2 and MP-3. From Section 4.9 where it has been described how the various items were extracted from already published research work, it can be seen that factor MP-1 comprises items that measure management practice pertaining to planning (MP1-MP4) and recruitment (MP5- MP9). Thus factor MP-1 was named as Management Practice (P&R) (i.e. Management

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Practice-Planning and Recruitment). Similarly items MP9-MP17 measuring the factor MP-2, were found to represent training and support to the volunteers and were extracted from already published literature (Cuskelly et al. 2006). Hence factor MP-2 was named as Management Practice (T&S) (i.e. Management Practice-Training and Support). Finally the items measuring factor MP-3 were found to measure recognition of volunteers (MP18-MP22) and performance management of volunteers (MP23 & MP24). These items were also adopted from already published literature (Cuskelly et al. 2006). Therefore based on the contents and naming of the constructs by previous researchers factor MP-3 was named as Management Practice (RGN&PM) (i.e. Management Practice- Recognition& Performance Management). The resulting table with renamed factors is provided in Table 5.10.

No. Description Coding

MP-1 (Factor1): Management Practice (P&R) (Management Practice- Planning and Recruitment)

1. Management practices: In managing its volunteers to what extent do your organisations ...-1- Identify potential volunteers before events begin.

MP1

2. Management practices: In managing its volunteers to what extent do your organisations ...-2- Provide role or job description for individual volunteers.

MP2

3. Management practices: In managing its volunteers to what extent do your organisations ...-3- Actively encourage turnover of volunteers in key position.

MP3

4. Management practices: In managing its volunteers to what extent do your organisations ...-4- Maintain database of volunteers’ skills, qualifications, and experience.

MP4

5. Management practices: In managing its volunteers to what extent do your organisations ...-5-Match the skills, experience, and interests of volunteers to specific roles.

MP5

6. Management practices: In managing its volunteers to what extent do your

organisations ...-6- Develop positions to meet the needs of individual volunteers.

MP6

7. Management practices: In managing its volunteers to what extent do your organisations ...-7- Actively recruit volunteers from diverse backgrounds.

MP7

8. Management practices: In managing its volunteers to what extent do your organisations ...-8-Use advertising for volunteer recruitments (e.g. newsletters, internet, etc.).

MP8

MP-2 (Factor1): Management Practice (T&S) (Management Practice- Training and Support)

9. Management practices: In managing its volunteers to what extent do your organisations ...-9- Encourage volunteers to operate within a code of acceptable behavior.

MP9

10. Management practices: In managing its volunteers to what extent do your organisations ...-10- Introduce new volunteers to people with whom they will work during the organisation.

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11. Management practices: In managing its volunteers to what extent do your organisations ...-11- Provide support to volunteers in their roles (e.g. assist with the resolution of conflict).

MP11

12. Management practices: In managing its volunteers to what extent do your organisations ...-12-Manage the work loads of individual volunteers where they are excessive.

MP12

13. Management practices: In managing its volunteers to what extent do your organisations ...-13-Assist volunteers to access training outside the organisation (e.g. accreditation training course).

MP13

14. Management practices: In managing its volunteers to what extent do your organisations ...-14-Cover or reimburse the costs of volunteers attendance at training or accreditation course.

MP14

15. Management practices: In managing its volunteers to what extent do your

organisations ...-15-Conduct induction sessions for specific groups of volunteers (e.g. supervisor, team leader, etc.)

MP15

16. Management practices: In managing its volunteers to what extent do your organisations ...-16-Mentor volunteers, particularly when starting in a new role.

MP16

17. Management practices: In managing its volunteers to what extent do your

organisations ...-17-Provide sufficient support for volunteers to effectively carry out their task.

MP17

MP-3 (Factor1): Management Practice (RGN&PM) (Management Practice- Recognition & Performance Management)

18. Management practices: In managing its volunteers to what extent do your organisations ...-18-Recognize outstanding work or task performances of individual volunteers.

MP18

19. Management practices: In managing its volunteers to what extent do your organisations ...-19-Plan for the recognition of volunteers.

MP19

20. Management practices: In managing its volunteers to what extent do your organisations ...-20- Thank volunteers for their efforts (e.g., informal thank yous).

MP20

21. Management practices: In managing its volunteers to what extent do your organisations ...-21- Publicly recognize the efforts of volunteers (e.g. in newsletters, special events, etc.).

MP21

22. Management practices: In managing its volunteers to what extent do your

organisations ...-22- Provide special awards for long serving volunteers (e.g. life membership, etc.).

MP22

23. Management practices: In managing its volunteers to what extent do your organisations ...-23- Monitor the performance of individual volunteers

MP23

24. Management practices: In managing its volunteers to what extent do your organisations ...-24-Provide feedback to individual volunteers.

MP24

Table 5.10 Renamed constructs pertaining to Management Practice

The validity of the paths MP-2 → MOTIVAT and MP-3 → SATISFAC is similar to other findings of researchers (e.g. Cuskelly et al. 2006) who explained through their study of the literature that human resource management practices of volunteers is related to motivation and satisfaction. This led the researcher to the inference that the results strengthen existing findings in the literature with regard to the two relationships MP-2 →

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MOTIVAT and MP-3 → SATISFAC. Similarly the validity of the paths MOTIVAT → RTN and SATISFAC → RTN finds support from the findings of other researchers for instance Dolnicar and Randle (2007) who contend that motivation and satisfaction are important factors that help in retaining volunteers. Finally the validity of the relationship MOTIVAT → SATISFAC finds widespread support from volunteer literature for instance Ferreira et al. (2012) who argue that motivations influence volunteer satisfaction. An important caveat that must be added here is that while the findings of this research find support from the literature regarding the significance of the relationships MP-2 → MOTIVAT, MP-3 → SATISFAC, MOTIVAT → RTN and SATISFAC → RTN it is seen that empirical studies linking management practice to retention available in the literature is very limited. For instance some researchers (e.g. Cuskelly et al. 2006) have argued that much of the focus in the volunteer literature is on predicting volunteer motivation and satisfaction not retention. Cuskelly et al. (2006) argue that their work on relating management practice directly to volunteer retention in the context of volunteering in sports is one of the initial efforts. In this situation the findings of this research although indirectly linking management practice to volunteer retention with regard to volunteering in general regardless of contexts provides one of the first contributions to empirical research. Another point that signifies the findings is that the major management practice aspects that have been found to influence volunteer retention are training, support, recognition and performance management. This is an important finding that contributes to the current body of knowledge to volunteer management practice.

It must also be noted here that lack of significance of paths relating certain management practices to motivation and satisfaction namely MP-1 → MOTIVAT, MP-3 → MOTIVAT, MP-1 → SATISFAC and MP-2 → SATISFAC is contradictory to the explanations given in the extant literature. For instance MP-1 which represents the planning and recruitment part of management practice and MP-3 which represents recognition and performance management have been found to be related to volunteer motivation by researchers (see Fisher & Cole, 1993) who advocate that best practices of managing volunteers should involve responding to volunteer motivations. Best practices

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could involve a number of aspects which could include support and manage, recruitment and public relations efforts to attract volunteers, orientation and training to prepare volunteers for their responsibilities, recognition events to reward and reinforce volunteers’ motivation and sense of purpose (Brudney, 1990). The reason for this contradiction could be that training and support could be a greater motivator than planning, recruitment, recognition and performance management in general. In fact Brudney (1990) argues that training volunteers to prepare them for their responsibilities reinforces volunteer motivation. Thus while the results of this research which indicates that the paths MP-1 → MOTIVAT and MP-3 → MOTIVAT are not significant could be due to the greater importance given by volunteers to training and support.

Similar arguments are found with regard to the management practice-volunteer satisfaction relationship. For instance with regard to MP-1 and MP-2 (represents training and support management) Owens (1991) quotes other researchers as arguing that training and other performance management factors such as volunteer responsibility and promotion are associated with volunteer satisfaction. The reasons for finding this contradictory result could be that volunteers could have felt that recognition and performance management could be greater satisfying factors than the planning, recruitment, training and support. For instance (Ferreira et al. 2012) argue that a major influencing factor that leads to extrinsic satisfaction in volunteers is volunteer recognition. In similar vein (Tziner et al. 2001) argue that employee performance appraisal is related to employee satisfaction implying that performance management of employees could lead to employee satisfaction. Similar sentiments are echoed by other researchers, for instance Tidwell (2005) (also see Mathews & Kling, 1988). Mathews and Kling (1988) argue that volunteer management including performance management is an important factor that influences the association between volunteer satisfaction and performance.

While the paths MP-1 → MOTIVAT, MP-3 → MOTIVAT, MP-1 → SATISFAC and MP-2 → SATISFAC are found to be statistically not valid, it must be noted that the relationship MP-2 → MOTIVAT → SATISFAC is statistically significant implying that

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training and support contributes to volunteer motivation as well as satisfaction. This leads to the inference that training, support, recognition and performance management are related to volunteer satisfaction while training and support are related to volunteer motivation.

Although the findings that the statistical validity of the paths MP-1 → MOTIVAT, MP-3 → MOTIVAT, MP-1 → SATISFAC and MP-2 → SATISFAC appear to be contradictory to some research outcomes found in the literature, there are also supporting arguments for the findings of this research. This indicates that the findings of this research using the support of the arguments of those researchers provide the basis to argue that in comparison to the insignificant relationships, the significant relationships are more important in the views of the volunteers. This argument can further be extended that the linkage of management practice to volunteer retention through the mediating effects of motivation and satisfaction offers a new ways to interpret the relationships between management practice and volunteer retention mediated by volunteer motivation and satisfaction.

Further to an understanding of the path analysis on the various relationships between the exogenous and endogenous variables, the next step was to find the extent to which variance in the endogenous variables is accounted for by the exogenous variables using squared multiple correlations (Table 5.11). From Table 5.11 it can be seen that the exogenous variables MP-1, MP-2 and MP-3 account for 10.7% of the variance in MOTIVAT, 35% of the variance in SATISFAC and 40.4% of variance in RTN. While the percentage of variance in the endogenous variables is ranging from small to moderate, what is significant is that the results highlight the influence of management practice on volunteer retention through the mediation of volunteer motivation and satisfaction.

Squared Multiple Correlations: (Group number 1 - Default model) Estimate

MOTIVAT .107

SATISFAC .350

RTN .404

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After examining the variance in endogenous variables caused by the exogenous variables the next step involved analyzing the regression weights of the valid paths (Table 5.12) which enabled the researcher to understand the relative affect of each independent variable on the dependent variable directly (Hair et al. 2006).

Standardized Regression Weights: (Initial model-RTN) Estimate MOTIVAT <--- MP-2 .238 MOTIVAT <--- MP-1 .163 MOTIVAT <--- MP-3 -.067 SATISFAC <--- MP-1 -.109 SATISFAC <--- MP-3 .473 SATISFAC <--- MP-2 .009 SATISFAC <--- MOTIVAT .359 RTN <--- SATISFAC .306 RTN <--- MOTIVAT .436

Table 5.12 Regression Weights, Initial model-RTN

From Table 5.12, it can be seen that the paths MP-1 → MOTIVAT, MP-3 → MOTIVAT, MP-1 → SATISFAC and MP-2 → SATISFAC are not significant. That is to say those hypotheses H1, H2, H3 and H6 are rejected and H4, H5, H7, H8 and H9 are accepted. That is to say the pathsMP-2 → MOTIVAT, MP-3 → SATISFAC, MOTIVAT → SATISFAC, MOTIVAT → RTN and SATISFAC → RTN which are valid indicate that training and support influence volunteer motivation, recognition and performance management influence volunteer satisfaction, volunteer motivation influences volunteer satisfaction and volunteer retention and volunteer satisfaction influences volunteer retention.

From Table 5.12 the relative affect between MP-2 and volunteer motivation (0.238), MP- 3 and volunteer satisfaction (0.473), volunteer motivation and satisfaction (0.359), volunteer motivation and volunteer retention (0.436) and volunteer satisfaction and volunteer retention (0.306) show strong paths that are statistically significant. This means that higher is the level of management practice (training and support) higher is the level of volunteer motivation; higher is the level of management practice (recognition and performance management) higher is the level of volunteer satisfaction; higher is the level

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of volunteer motivation higher is the level of volunteer satisfaction; higher the level of volunteer motivation, higher is the level of volunteer retention; and higher is the level of volunteer satisfaction higher is the level of volunteer retention.

The regression weights analysis indicate how the cause and effect relationship between the exogenous and endogenous variables can be explained. In the same way the covariance between the exogenous variables MP-1, MP-2 and MP-3 were assessed to understand the association between the variables (Table 5.13). All the three covariance paths show statistically significant association between each pair of the exogenous variables with a large correlation between them. For instance from Table 5.13 it can be seen that MP-1 is highly associated with MP-2 (0.693) and MP-3 (0.534) indicating that higher the level of planning and recruitment higher will be the level of volunteer motivation and satisfaction and vice-versa. Similarly, MP-2 and MP-3 are highly correlated (0.55) which can be interpreted in a way that higher is the level of training and support provided to the volunteer, higher will be level of recognition and performance management of the volunteers. These arguments also lead to the inference that while MP- 1 and MP-3 are not statistically related to MOTIVAT, it can be said that they may be acting as moderators of MP-2. That is to say that training and support activities which are part of the management practice stands to be strengthened and moderated by the two management practice elements planning and recruitment and recognition and performance management leading to higher motivation of volunteers. Similarly in the case of the statistically insignificant paths between MP-1 and MP-2 on the one hand and SATISFAC on the other, it can be argued that MP-1 and MP-2 may be acting as moderators of MP-3. That is to say that recognition and performance management of volunteers is strengthened and moderated by the two management practice elements planning and recruitment and training and support. The foregoing arguments conclude the Initial model-RTN analysis. The next step was to evaluate the Initial model-RTN.

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Covariances: (Initial model-RTN)

Estimate S.E. C.R. P Label MP-2 <--> MP-1 .693 .073 9.545 *** par_26