Abstract
The complexity of automation in heavy-duty mobile machines (HDMMs) is transforming traditional and transactional supply relationships into collaborative relationships, thereby leading to an emergence of ecosystems for autonomous HDMMs. However, our previous work highlights stakeholder identification and engagement in the HDMM industry as a predominantly ad hoc and heuristic exercise, wherein organizations lack clarity regarding appropriate business engagement strategies for autonomous HDMMs. Accordingly, we utilize the well-established theoretical stakeholder salience attributes of power, legitimacy, and urgency to propose a practical framework to classify and prioritize stakeholders in the HDMM industry. The proposed framework quantifies the stakeholder salience attributes into measurable parameters thereby enabling organizations to understand how different stakeholders are likely to affect the organization and to assign appropriate engagement strategies. The proposed framework can also be generalized and thereby contributes towards enabling collaborative innovation in other emergent ecosystems too.
| Original language | English |
|---|---|
| Title of host publication | ISPIM Connects Salzburg – The Sound of Innovation |
| Publisher | ISPIM publication |
| Number of pages | 18 |
| ISBN (Electronic) | 978-952-65069-4-4 |
| Publication status | Published - 13 Dec 2023 |
| Publication type | B3 Article in conference proceedings |
| Event | ISPIM Connects Salzburg – The Sound of Innovation - Salzburg Congress, Salzburg, Austria Duration: 11 Dec 2023 → 13 Dec 2023 https://www.ispim-connects.com/ |
Conference
| Conference | ISPIM Connects Salzburg – The Sound of Innovation |
|---|---|
| Abbreviated title | 2023 ISPIM Connects (Salzburg) |
| Country/Territory | Austria |
| City | Salzburg |
| Period | 11/12/23 → 13/12/23 |
| Internet address |
Keywords
- Heavy-duty mobile machinery
- automation
- autonomous solutions
- stakeholder salience
- emergent ecosystems
- Collaborations
- stakeholder engagement
- R&D
- Analytic hierarchy process
- Surveys