Abstract:
There is considerable interest in factors that influence individuals' decision-making behavior, in risky contexts. These differences in behaviour have important implications for economic outcomes including occupational choice, investment and consumption choices and insurance coverage. A number of studies have documented the effect of demographic variables such as gender, age, height, education level, income level, marital status and family background on risk behaviour. However, many of these studies have been conducted on human risk behavior, based on the European or Western context while the studies in the Asian context is limited. Therefore, this study attempts to evaluate the risk behaviour of young adults in Sri Lanka and to establish the relationship if any, between individual characteristics, external stimuli and risk behaviour. The research question addressed is, ―What factors determine risk behaviour of young adults in Sri Lanka?‖. A modified version of the Sitkin and Pablo model (1992) was used as a conceptual model to assess risk behavior which was adapted to focus on individual risk characteristics. A cross sectional study was carried out among young adults in five state universities in Sri Lanka using snow-ball sampling method to assess their risk behavior. This sample represents approximately 52.63% amount of the total number of students enrolling Sri Lankan state universities annually. Risk behavior was assessed by their likelihood of engaging in risk related activities associated with their daily life through a scenario based questionnaire. The findings suggest that among the demographic factors, only gender, education stream and the number of dependents were found to be significant. Furthermore, according to the normality test, the distribution of the risk behaviour tends to be right– skewed, suggesting that the overall risk behaviour of an average young adult in Sri Lanka is comparably low. Results also revealed a significant difference in risk behaviour between males and females. Males tended to exhibit high-risk behaviour compared to females. This result was robust even when the education background of the sample was evaluated, with the male dominated stream of engineering, showing the highest risk-taking behavior when compared to the arts, management and sciences. As expected, we found evidence to indicate an inverse relationship between number of dependents and risk behavior. The results could be used in functional areas such as marketing, finance and human resource management in the corporate sector, across multi industries to design and develop new products, understand customer behaviour and financial investment patterns.
