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Capturing and Analysing Emotions to Support Organisational Learning : The Affect Based Learning Matrix

<p>This thesis deals with the importance of managing employees’ thoughts and feelings in relation to organisational learning. To visualise and to identify affections within organisations is of major importance since most of our actions and the decisions we make are steered by our emotions rather than rational thinking.</p><p>In this work we show that employees’ thoughts and feelings can be managed by implementing the cognitive therapeutic process into the organisational setting. In comparison to the more traditional way of managing problems within organisations, i.e. the two activities of problem identification and problem solving, the cognitive therapeutic process also addresses the importance of identifying associated feelings and underlying automatic thoughts in relation to an occurrence or a situation.</p><p>Consequently, the overall purpose of this thesis has been to develop an approach for improving the quality of organisational learning processes which should stimulate employees’ contribution and facilitate the identification of their thoughts and feelings in relation to their work. As a result, ‘The Affect Based Learning Matrix’ (TABLe MATRIX) was developed. TABLe MATRIX can be used either in a paper-based or in a Web-based format and identifies and analyses individuals’ affections in relation to an organisational occurrence or change, a subject or a problem. Our empirical investigations show that TABLe MATRIX contributes to improving the output of organisational learning processes since unspoken negative emotions make people passive in finding new solutions. TABLe MATRIX has been evaluated by interviewing thirteen operational development representatives within eight different branches and also by testing the paper-based version at two large organisations within retail fast moving consumer goods and within education.</p>

Identiferoai:union.ndltd.org:UPSALLA/oai:DiVA.org:su-1230
Date January 2006
CreatorsOlsson Neve, Theresia
PublisherStockholm University, Department of Computer and Systems Sciences (together with KTH), Kista : Institutionen för data- och systemvetenskap (tills m KTH)
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeDoctoral thesis, monograph, text
RelationReport Series / Department of Computer & Systems Sciences, 1101-8526 ; 06-013

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