Authors:
Thiago Oliveira
;
Mark Song
and
Luis Zárate
Affiliation:
Applied Computational Intelligence Laboratory – LICAP, Computer Science Department, Pontifical Catholic University of Minas Gerais, Brazil
Keyword(s):
Activity Based Working Environments, Data Mining, Longitudinal Data Mining, Triadic Concept Analysis, Triadic Rules.
Abstract:
A longitudinal database records data and its variations over a period of time. The objective of this article is to use this resource, together with the Triadic Concept Analysis theory, to analyze and characterize how employees adapted and felt before, during and after the implementation of an activity-based work environment which is defined as a flexible work setting where employees have the autonomy to choose where they perform their tasks, seeking locations that offer optimal solutions in terms of social interaction, communication, and collaboration. The results seek to support the implementation of this concept, verifying how, and under what conditions, key points of employee experiences vary over time.