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MODELLING THE MULTIGROUP MODERATOR-MEDIATOR ON MOTIVATION AMONG YOUTH IN HIGHER EDUCATION INSTITUTION TOWARDS

VOLUNTEERISM PROGRAM

NAME:WAN MOHAMAD ASYRAF BIN WAN

AFTHANORHANMATRIC NUMBER:

GSK1478MAIN SUPERVISOR:

ASSOCIATE PROFESOR DR. SABRI AHMAD

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Introduction Literature Review

Methodology Findings

Conclusion

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INTRODUCTION

Problem Statement

To what extent the role of goverment support as a source

variable creates barrier, benefits, and challenges to the

motivation

Ibrahim mamat, 2012 find out the level of involvement in

volunteerism program is low

Bollen, 1989 explore moderator-mediator can explain both effect at the

same time.

Carol Hardy-Fanter, 1993 found that males and

females took on different roles when volunteering.

To address the comparison between male and female in

volunteering activity

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OBJECTIVE RESEARCH

To compare the group effect for moderator variable.

To differentiate the type of moderating effect through the structural model.

To determine the gender as moderator variable on the path interest.

To identify the type of mediating effect through the structural model.

To develop the best structural (path) model through the model estimation, model fit, and model modification verification on motivation towards volunteerism program.

To validate the independent (exogenous) and dependent (endogenous) variables through measurement model.

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SIGNIFICANT OF STUDY

Significant of Study

The study on interrelation between goverment

support, benefits, barrier, challenges, and motivation in an integrated framework

by using Structural Equation Modeling (SEM)

is a good interest for researchers.

The undergraduates and postgraduates involvement towards

the volunteerism program is the focus in this study since it may

bring tremendous benefits to the universities in the future besides to provide optimum exposure to the

community.

This study claims itself to be among the first to explore the gender role

on the relationship between goverment support, barrier, benefits,

challenges and motivation.

The comparison between male and female can be conducted to investigate

which group is more pronounce in volunteerism

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LITERATURE REVIEW

Mediating Effect

•Mediation effect can be called as an intervening effects.• A mediator is a predictor link in the relationships between two other variables. •Normally, a mediator variable can become an exogenous and endogenous variable at same time. •According to Zainudin Awang (2010) the mediation have three types of mediator: 1. Full mediation, 2. Partial mediation 3. Non-mediation.

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Moderator-Mediator

•Moderation is quite different with mediation. •This method is employed to examine the strength influences of relationships between the endogenous and exogenous variables. •Moderation variable can be categorical and continuous variables.•In this case, the gender role become as moderator in this model to examine whether the gender influences of these relationship between exogenous and endogenous constructs.•According to Zainudin Awang (2012) the moderation have three types of moderator: 1. Full moderation 2. Partial moderation 3. Non-moderation

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Summary why benefits, barrier and challenges become mediator?

AUTHOR/ YEARS STATEMENTS VARIABLE

Dingle, 2001Goverments may contribute by supporting such infrastructure. Further, if goverments is better informed about the people who volunteeer, it is likely to become more aware of how policy legislation it introduces can affect, both directly and indirectly , people giving of their time

Benefits

Dingle, 2001Describe three factors that challenges volunteering which can be indirectly among people to involve the volunteerism program . These are : globalization, relations with the state, and the relation with the market

Challenges

Marlene wilson, 1976 and Eva Schindler- Rainman, 1987

Explores the barrier is the early mainstream( i.e not about supported volunteering specifically) volunteer program management literature contains encouraging messages about broadening the base of volunteering. In generals, this factor can be main research problem of people from getting involve in volunteerism program due to the scenario that they will faced. . Hence, the number whose involve in these activity will become decrease

Barrier

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THEREOTICAL FRAMEWORK

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METHODOLOGY

Respodent age’s must be between 15 to 40 years old.

The study applied the stratified sampling technique whereby in Terengganu only

Four higher education institution are selected randomly among the university available in Kuala Terengganu

All students in the selected university are taken as respondents in the study

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THE PROCEDURE FOR DATA ANALYSIS

STRUCTURAL EQUATION MODELLING (SEM)

•Commonly used for confirmatory factor analysis for unidimensionality procedure.

Measurement Model

•Assembled for the whole of measurement model with causal effect and correlation.

Structural Model

5 types of model required:

Model Identification

Model Specification

Model Evaluation

Model Modification

Model Estimation

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Construct Validity

Convergent Validity AVE AVE > 0.50

The validity is achieved when all items in a measurement model are

statiscally significant.

Construct Validity

GFI

CFI

RMSEA

Chisq/Df

GFI > 0.90

CFI > 0.90

RMSEA < 0.08

Chisq/Df < 5.0

This validity is achieved when the fitness indexes achieve the

following requirements

Discriminant Validity

Square Root of AVE and correlation of latent

constructs

All the correlation between these construct

should below 0.85

This validity is achieved when the measurement model is free from

redundant items.

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Fitness IndexesName of Category

Name of Index Index Full Name Level of Acceptance

Literature

Absolute Fit

GFIGoodness-of-fit Index

GFI > 0.90 Joreskog and Sorbom (1986)

AGFIAdjusted Goodness-of-fit test

AGFI > 0.90 Joreskog and Sorbom (1986)

SRMRStandardized root mean square residual

SRMR < 0.08 Bentler (1995)

RMSEARoot mean Square Error Approximation

RMSEA < 0.06 Steiger & Lind (1980)

Comment Higher values of GFI and AGFI as well as lower value of SRMR and RMSEA indicate better model data fit.

Incremental Fit

NFINormed Fit Index NFI > 0.90 Bentler & Bonett

(1980)

TLITucker Lewis Index TLI > 0.95 Tucker and Lewis

(1973)

RNIRelative noncentrality Index

Rni > 0.90 McDonald & Marsh (1990)

CFIComparative Fit Index

CFI > 0.95 Bentler (1989,1990)

IFIIncremental Fit Index

IFI > 0.90 Bollen (1989)

Comment Higher values of incremental fit indices indicate larger improvement over the baseline model in fit.

Parsiminous Fit Chisquare/Df

Chisquare/ degree of Freedom

Chisq/Df < 5.0 Marsh and Hancover (1985)

Comment Very sensitive to the sample size.

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Mediating Effect•Media

tion analysis or intervening effect permits examination process, allowing the researcher to examine by what means X exerts its effect on Y. Although systems of equations linking X to Y through multiple mediators are possibly to specify

MacKinnon,2000

Partially mediated model was proposed based on Baron and Kenny’s (1986) three required conditions is required for mediation effects:

• The independent variable must affect the mediating variable. In this instance, the goverment support predictor must affect the barrier, challenges, and benefits.

• The independent variable must affect the dependent variable. In this model, goverment support constructs must have effect on the outcome variable (i.e., motivation)

• The mediator must have effect on the dependent variable. In this case, the barrier, benefits, and challenges must affect motivation.

Moderator and Mediator

•Combination of moderator and mediator in simultaneously.

Moderated mediation

•Moderated mediation model attempt to explain both how and when a given effect occurs

Frone, 1999

•asserted that moderated mediation “happens if the mediating process that is responsible for producing the effect of the treatment on the outcome depends on the value of a moderator variable.

Muller et al. (2005)

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DATA ANALYSIS

To validate the independent (exogenous) and dependent

(endogenous) variables through measurement model.

To develop the best structural (path) model through the model

estimation, model fit, and model modification verification

on motivation towards volunteerism program.

To identify the type of mediating effect through the

structural model.

To determine the gender as moderator variable on the path

interest.

To differentiate the type of moderating effect through the

structural model.

To compare the group effect for moderator variable.

Reliability Normality

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Reliability Statistics

Cronbach's Alpha N of Items

.919 53

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Motivation

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Construct Validity

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Summary for convergent validity

Cronbach Alpha CR AVEBenefits 0.923 0.898 0.503

Motivation 0.941 0.941 0.519Challenges 0.849 0.844 0.477

Barrier 0.761 0.758 0.452Goverment_Support 0.835 0.838 0.467

Discriminant validity

Benefits Motivation Challenges Barrier Goverment_Support

0.709

0.690 0.721

0.219 0.229 0.691

0.287 0.297 0.390 0.672

0.451 0.449 0.277 0.261 0.683

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Multigroup Mediating Effect

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Findings For Mediating Effect

Estimate P Hypothesis

Barrier <--- Goverment_Support .353 *** Supported

Challenges <--- Goverment_Support .413 *** Supported

Benefits <--- Goverment_Support .536 *** Supported

Motivation <--- Goverment_Support .127 .027 Supported

Motivation <--- Barrier .090 .029 Supported

Motivation <--- Challenges .016 .645 Not Supported

Motivation <--- Benefits .812 *** Supported

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Type Mediator

Mediating Variable P-value Mediating Variable P-Value Type

Barrier <---Goverment_

Support*** Motivation <--- Barrier .029 Partial

Challenges <---Goverment_

Support*** Motivation <--- Challenge .645 Full

Benefits <---Goverment_

Support*** Motivation <--- Benefits *** Partial

Constant Motivation <---Goverment_

Support.027

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Multigroup Moderator-Mediator

Result

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Findings for Moderator-mediator

      Male Female  

      Estimate P Estimate P z-score

Barrier <--- Goverment_Support 0.29 0.011 0.343 0.000 -0.174

Challenges <--- Goverment_Support 0.462 0.000 0.36 0.004 -1.192

Benefits <--- Goverment_Support 0.665 0.000 0.264 0.000 -2.933***

Motivation <--- Goverment_Support 0.177 0.057 0.132 0.058 -0.2

Motivation <--- Barrier 0.095 0.099 0.03 0.56 -0.59

Motivation <--- Challenges 0.021 0.696 0.008 0.822 -0.543

Motivation <--- Benefits 0.695 0.000 0.892 0.000 0.715

Notes: *** p-value < 0.01; ** p-value < 0.05; * p-value < 0.10    

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Type Moderator

Constructs Male Female Type Moderation

Barrier <- Goverment_Support

0.011 0.000 Partially

Challenges <- Goverment_Support

0.000 0.004 Partially

Benefits <- Goverment_Support

0.000 0.000 Partially

Motivation <- Goverment_Support

0.057 0.058 Non

Motivation <- Barrier 0.099 0.56 Non

Motivation <- Challenges 0.696 0.822 Non

Motivation <- Benefits 0.000 0.000 Partially

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Standardized Estimates

Result

Comparing Group

Constructs Male P-value Female P-value

Barrier <--- Goverment_Support .265 0.011 .282 0.000

Challenges <--- Goverment_Support .347 0.000 .215 0.004

Benefits <--- Goverment_Support .573 0.000 .289 0.000

Motivation <--- Goverment_Support .108 0.057 .111 0.058

Motivation <--- Barrier .073 0.099 .031 0.56

Motivation <--- Challenges .050 0.696 .011 0.822

Motivation <--- Benefits .726 0.000 .687 0.000

Four significant path which is goverment support on barrier, challenges, and benefits while the benefits on motivation, one can conclude that the gender moderates the relationship between these variables

The effect of male group for government support on benefits and challenge, and benefits on motivation is more pronounced compare to female group.

The effect of female group for government support on barrier is more pronounced compare to male group only.

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Discussion and Conclusion

Conclusion

The study indicate the goverment support is statistical significant

different influences on benefits, challenges, barrier

and motivation.

Benefits is the most contribute on motivation

compare to other variables.

The male group is more contribute to involve in volunteerism program

than female group.

The theory to apply moderator-mediator in this study is supported.

Goverment support has evidence to support the

moderating effect of gender on the relationship

between benefits of volunteering.