Task absorption analysis in the job demands-resources theory : An episodic perspective
Autor corporativo
dc.contributor
Universidad de Chile, Facultad de Economía y Negocios, Escuela de Postgrado
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Professor Advisor
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Torres Cepeda, Juan Pablo
Author
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Juyumaya, Jesus
Admission date
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2023-08-10T20:49:18Z
Available date
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2023-08-10T20:49:18Z
Publication date
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2022
Identifier
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https://repositorio.uchile.cl/handle/2250/195124
Abstract
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This dissertation offers an episodic view of job demands and resources (JD-R) theory,
showing that task characteristics are related to episodic task absorption, namely that episodic
task absorption fluctuates synchronously as a function of concurrent appraisals of demands
and resources. Furthermore, I delivered empirical evidence for the episodic process model
(EPM) proposition that attention facilitates performance during an episode, namely that
episodic task absorption positively relates to task performance, using evidence from
physiological, behavioral, and self-reported data. In this study, demand and resource levels
change during repeated decision-making episodes. The levels of demands and resources
generate different levels of task absorption that consequently cause different levels of task
performance. Therefore, task absorption would vary within the task. The results of this study
can be used for time management and job recovery programs, and highlight the importance
of physiological measures that can complement self-reported measures and provide a more
objective indicator of task absorption. All in all, I offer an episodic view of JD-R theory,
showing that demands and resources can be related to episodic task absorption. This
dissertation is the first approximation of episodic task absorption. It makes an incremental
contribution that can supplement the JD-R theory and delivers empirical evidence to the
EPM. Finally, it verifies the importance of experimental studies and lays the groundwork for
future research.
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Lenguage
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en
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Publisher
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Universidad de Chile
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Type of license
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Attribution-NonCommercial-NoDerivs 3.0 United States