1. Financial Motivation as a multi- dimensional construct: A positive psychology approach Dan Stone, 2008 Synopsis: Colin Onita

2. Justification Theories of external motivation do not properly explain human behavior Biological and anthropological theories – interpersonal relationship motivation Positive Psychology – intrinsic motivators – self development, self mastery Hedonic utility

3. Ecological view Motivation as a ecological, holistic view –Financial motivations –Accounting and organizational controls –Intrinsic motivation –Social motivators –Relational motivators

4. Main theories Self-determination Theory- goals influence well being based on their contribution to psychological needs –Autonomy –Competence –Relatedness Hedonic Utility

5. Main constructs Materialism – is a motivation for obtaining money and wealth as a means of attaining position and status Financial self efficacy – the belief that one is capable of successfully managing the financial events of ones life Financial Autonomy – the belief that ones financial decisions are volitional choices that reflect one's interests, beliefs and values.

6. Main constructs Financial community – the belief that financial resources are creating and sustaining community and interpersonal relationships Gratitude – not defined

7. Hypotheses H1: Materialism will negatively predict happiness H2: Positive financial attitudes will positively predict happiness H3: One or more PFAs will moderate the negative effect of materialism on happiness. Specifically higher levels of PFAs will increase happiness more among high than low materialism individuals

8. Hypotheses H4: Gratitude will fully mediate the effect of materialism on happiness H5: Gratitude will partially mediate the effect of PFAs on happiness

9. Methodology Survey using various scales (MES FA, possession defined success, Emmons & McCullogh scales) 688 participants – undergraduate and graduate accounting students General linear modeling Structural equation modeling

10. Results All hypotheses supported by both GLM and SEM Statistical results: –Reliabilities of scales – all about 7.5 –Not much discussion of divergent and convergent validities –Excellent fit coefficients for SEM