study introduces a nonlinear dynamical systems approach, also known as a complexity science approach, to characterize the intraindividual variability of flow experiences in the workplace.With nonlinear dynamical systems theory at its basis, the aims of the current study are threefold. The first goal is to examine whether flow exhibits both linear and nonlinear patterns. The second objective is to study if nonlinear patterns (i.e., chaotic dynamics) are associated with higher well-being (i.e., high levels of flow). The third goal is to sift out some of the variables associated with different dynamical patterns of flow (i.e., chaotic, random or linear) while engaging in work-related activities. Flow and Well-Being at Work

Recent conceptual work draws meaningful distinctions between experiential and declarative well-being (Shmotkin, 2005), but little has been done to apply such distinctions in organisational psychology. We use this framework to integrate self-determination theory (Deci & Ryan, 1985) and flow theory , leading to hypotheses proposing that flow experiences at work (experiential well-being) lead to declarative well-being outcomes through their influence on the satisfaction of basic psychological needs for competence and autonomy. Findings from a two-week experience sampling study of full-time employees offer support for our hypotheses. This study also shows support for the moderating effect of individual differences in personality on the relationships among flow experiences, need fulfillment, and declarative well-being.

Work-related flow is defined as a sudden and enjoyable merging of action and awareness that represents a peak experience in the daily lives of workers. Employees' perceptions of challenge and skill and their subjective experiences in terms of enjoyment, interest, and absorption were measured using the experience sampling method, yielding a total of 6,981 observations from a sample of 60 employees. Linear and nonlinear approaches were applied in order to model both continuous and sudden changes. According to the R 2 , AICc, and BIC indexes, the nonlinear dynamical systems model (i.e., cusp catastrophe model) fit the data better than the linear and logistic regression models. Likewise, the cusp catastrophe model appears to be especially powerful for modeling those cases of high levels of flow. Overall, flow represents a nonequilibrium condition that combines continuous and abrupt changes across time. Research and intervention efforts concerned with this process should focus on the variable of challenge, which, according to our study, appears to play a key role in the abrupt changes observed in work-related flow.

The aims of this study are to consider the experience of flow from a nonlinear dynamics perspective. The dynamic history of motivation, coupled with the temporal nature of the flow experience, would suggest that flow experiences fluctuate over time in a dynamical fashion.Thus it can be argued that the potential for chaos is strong. The sample was composed of 20 employees (both full and part time) recruited from a number of different organizations and work backgrounds. The Experience Sampling Method (ESM) was used for data collection. Once obtained the temporal series, they were subjected to various analyses proper to the complexity theory (Visual Recurrence Analysis and Surrogate Data Analysis). Results showed that in 80% of the cases, flow presented a chaotic dynamic, in that, flow experiences delineated a complex dynamic whose patterns of change were not easy to predict. Limitations of the study and future research are discussed.