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Adaptive and Generative Learning: Implications from Complexity Theories
Author(s) -
Chiva Ricardo,
Grandío Antonio,
Alegre Joaquín
Publication year - 2010
Publication title -
international journal of management reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.475
H-Index - 107
eISSN - 1468-2370
pISSN - 1460-8545
DOI - 10.1111/j.1468-2370.2008.00255.x
Subject(s) - generative grammar , intuition , organizational learning , process (computing) , psychology , epistemology , experiential learning , cognitive science , order (exchange) , computer science , knowledge management , artificial intelligence , philosophy , mathematics education , finance , economics , operating system
One of the most important classical typologies within the organizational learning literature is the distinction between adaptive and generative learning. However, the processes of these types of learning, particularly the latter, have not been widely analyzed and incorporated into the organizational learning process. This paper puts forward a new understanding of adaptive and generative learning within organizations, grounded in some ideas from complexity theories: mainly self‐organization and implicate order. Adaptive learning involves any improvement or development of the explicate order through a process of self‐organization. Self‐organization is a self‐referential process characterized by logical deductive reasoning, concentration, discussion and improvement. Generative learning involves any approach to the implicate order through a process of self‐transcendence. Self‐transcendence is a holo‐organizational process characterized by intuition, attention, dialogue and inquiry. The main implications of the two types of learning for organizational learning are discussed.