Abstract
The heavy machinery industry is transitioning towards electric mobile working machines in response to increasing pressure to decarbonize. Despite recent technological advancements in electric vehicles, mainstream adoption remains challenging. The economic sustainability of these machines depends not only on technological development but also on the implementation of innovative business models. This study analyzed 684 documents from the LexisNexis Academic database, focusing on the mining industry, through thematic content analysis. The results revealed seven sustainable business model archetypes and 22 specific business models, including Deliver functionality, rather than ownership, Sustainable Intelligence, Skill sharing, Sustainable Energy Transition, Create value from ‘waste’, Carbon Stewardship, and Eco-Commercial Synergy. By bridging the gap between technological innovation and economic feasibility, these initiatives aim to facilitate the widespread adoption of electric machinery in the mining industry and beyond.
Original language | English |
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Title of host publication | Proceedings of the International Conferences on Digital Transformation and Innovation Management 2024, DTIM 2024; and ICT, Society and Human Beings 2024, ICT 2024 |
Editors | Pedro Isaias, Paula Miranda, Piet Kommers |
Publisher | IADIS |
Pages | 19-28 |
Number of pages | 10 |
ISBN (Electronic) | 978-989-8704-60-3 |
Publication status | Published - 2024 |
Publication type | A4 Article in conference proceedings |
Event | International Conference on Digital Transformation and Innovation Management - Budapest, Hungary Duration: 13 Jul 2024 → 15 Jul 2024 |
Conference
Conference | International Conference on Digital Transformation and Innovation Management |
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Country/Territory | Hungary |
City | Budapest |
Period | 13/07/24 → 15/07/24 |
Keywords
- Decarbonization
- Electrified Machinery
- Green Companies
- Sustainable Business Model
- Sustainable Value Creation
Publication forum classification
- Publication forum level 0
ASJC Scopus subject areas
- General Computer Science