Summary
Large amounts of data generated by electronic commerce are becoming an increasingly important source of knowledge to support organisational decision making. An empirical study was conducted in a simulated electronic commerce environment to examine people’s ability to discover varying associative patterns in transactions data, and utilise that knowledge to support product sales forecasting. The results of the study indicate that people were able to reasonably well discover valid associations among data items and consequently improved performance over naive forecasts. The results also indicate that people were more successful in recognising and using stronger rather than weaker associative patterns. However, they failed to reach optimal performance.
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Handzic, M., Aurum, A. (2001). Knowledge Discovery: Some Empirical Evidence and Directions for Future Research. In: Buhl, H.U., Huther, A., Reitwiesner, B. (eds) Information Age Economy. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57547-1_86
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DOI: https://doi.org/10.1007/978-3-642-57547-1_86
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-642-63300-3
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