Retentivity beats prior knowledge as predictor for the acquisition and adaptation of new production processes
- In the time of digitalization the demand for organizational change is rising and demands ways to cope with fundamental changes on the organizational as well as individual level. As a basis, learning and forgetting mechanisms need to be understood in order to guide a change process efficiently and successfully. Our research aims to get a better understanding of individual differences and mechanisms in the change context by performing an experiment where individuals learn and later re-learn a complex production process using a simulation setting. The individual’s performance, as well as retentivity and prior knowledge is assessed. Our results show that higher retentivity goes along with better learning and forgetting performances. Prior knowledge did not reveal such relation to the learning and forgetting performances. The influence of age and gender is discussed in detail.
Author details: | Jennifer HaaseORCiDGND, Julia Matthiesen, Arnulf SchüfflerORCiDGND, Annette KlugeORCiDGND |
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DOI: | https://doi.org/10125/64331 |
Title of parent work (English): | Proceedings of the 53rd Hawaii International Conference on System Sciences |
Publication type: | Conference Proceeding |
Language: | English |
Year of first publication: | 2020 |
Publication year: | 2020 |
Release date: | 2022/09/28 |
Tag: | Innovation in Organizations: Learning; Intentional Forgetting; Unlearning; experiment; forgetting; learning; prior knowledge; production process; retentivity |
Volume: | 53 |
Number of pages: | 10 |
First page: | 4797 |
Last Page: | 4805 |
Funding institution: | Weizenbaum Insitute |
Funding number: | 16DII116 |
Organizational units: | Wirtschafts- und Sozialwissenschaftliche Fakultät |
DDC classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Publishing method: | Open Access / Gold Open-Access |
License (German): | CC-BY-NC-ND - Namensnennung, nicht kommerziell, keine Bearbeitungen 4.0 International |