Abstract
Preference plays an important role in organisational and human decision making as it may be a manifestation of proven practices or of individual working styles. The significance of the notion of preference has been recognised in a number of different disciplines. Unfortunately its potential does not seem to have been fully unlocked in the field of Business Process Automation (BPA), even though resource and task allocations play a pivotal role in process performance and these allocations could be guided by explicit formulations of preferences. In this paper, we examine the state of the art with respect to preference in the field of BPA and use this as the basis for a conceptual model capturing recognised manifestations of preference in the literature. We investigate how preferences may exhibit themselves in process automation through the notion of well-established (workflow) resource patterns. We then show that manifestations of preference may occur in real-life process event logs and how these can be extracted through the application of machine learning techniques. The findings from this research contribute towards establishing a rich understanding of preferences in the context of business processes, ways of specifying and deriving these preferences, and their more explicit incorporation in work allocation mechanisms, which can lead to a step change for realising better process performance and more effective work collaboration in today’s organisations .
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Bidar, R., ter Hofstede, A., Sindhgatta, R., Ouyang, C. (2019). Preference-Based Resource and Task Allocation in Business Process Automation. In: Panetto, H., Debruyne, C., Hepp, M., Lewis, D., Ardagna, C., Meersman, R. (eds) On the Move to Meaningful Internet Systems: OTM 2019 Conferences. OTM 2019. Lecture Notes in Computer Science(), vol 11877. Springer, Cham. https://doi.org/10.1007/978-3-030-33246-4_26
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