{'fraction_non_alphanumeric': 0.021961932650073207, 'fraction_numerical': 0.0, 'mean_word_length': 5.417840375586854, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Contributing to knowledge-based decision support: a system dynamics model regarding the use of non-renewable resources

In dynamic business contexts where knowledge is continually evolving and thus critical for better organizational performance, not only knowledge re-use but also knowledge re-creation becomes more and more important. One of these contexts is the use of non-renewable resources in innovative hightech products. Since media recently spread – often contradictory – news about the increasing scarcity of non-renewable resources, decision makers face a high degree of uncertainty. They struggle to understand and handle the information available. Therefore, it is essential to provide a methodological approach to externalize and combine expert knowledge of a system’s inherent logic. Hence, in this paper we show that mental models of experts can be transformed into an explicit simulation model in order to support decision makers comprehending the shortand long-term dynamic interdependencies of the development of non-renewable resources on demand, supply, and price. For this purpose, we combine known cause-and-effect relationships into an integrated model using the system dynamics methodology. The application of the idea to capture knowledge in a simulation model is exemplarily instantiated with real-world information for the case of indium.