Suchergebnisse

AbstractThis paper examines (a) whether people are less accurate in judging choice time as choice tasks involve more choice options, more choice information, or a combination of both and (b) whether people with a higher tendency to look for the best option in choice making (maximizers) have less accurate duration judgments of choice time as compared to people who are more easily settling for a choice outcome that is satisfactory (satisficers). A multilevel analysis is used to explore the relationships of interest using data collected through a series of choice tasks. In general, the results suggest that people seem to misjudge time durations when making choices. Moreover, empirical evidence demonstrates that people with an outspoken tendency to maximize in choice making do not differ significantly in estimating choice time accurately as compared to people who experience almost no need to maximize.

The increasing availability of statistical data raises opportunities for 'big' data and learning analytics. Here, we review the academic literature and research relating to the use of big data analytics in the public sector, and its contribution to public organizations' performance and efficiency. We outline the advantages as well as the limitations of using big data in public sector organizations and identify research gaps in recent studies and interesting areas for future research.