Value co-creation domains in a Machine Learning-enabled context
| Domain | Definition |
|---|---|
| VCC driver | Expected benefits the customer can gain from using the digitally-enabled PSS, and the needs that can be predicted via ML before they become explicit |
| Resource used | Intangible resources, such as existing skills and knowledge embedded in goods, and brand-new knowledge that ML algorithms and related software are able to create within a virtuous cycle of resource generation and development |
| Role of goods | Bi-directional vehicles of resources exchanges, through which the manufacturers transfer their skills and knowledge to the customer and collect data to be turned into new knowledge |
| Role of value co-creators | All the actors that interact within the ecosystem by sharing data to be processed via ML become simultaneously value co-creators and beneficiaries of the co-created value |
| Purpose and measurement of co-created value | ML helps in translating the concepts of “adaptability, survivability and system well-being” in terms of more tangible dimensions that can be measured to express the degree to which such purposes have been achieved |
| Process of VCC | Set of concurrent activities to be analyzed dynamically according to at least two perspectives: that of the manufacturer and that of the customers |
| Contingent forces | Exogenous and endogenous forces that lead to the adoption of a specific configuration among the finite number of possible ones |
| VCC driver | Expected benefits the customer can gain from using the digitally-enabled PSS, and the needs that can be predicted via ML before they become explicit |
| Resource used | Intangible resources, such as existing skills and knowledge embedded in goods, and brand-new knowledge that ML algorithms and related software are able to create within a virtuous cycle of resource generation and development |
| Role of goods | Bi-directional vehicles of resources exchanges, through which the manufacturers transfer their skills and knowledge to the customer and collect data to be turned into new knowledge |
| Role of value co-creators | All the actors that interact within the ecosystem by sharing data to be processed via ML become simultaneously value co-creators and beneficiaries of the co-created value |
| Purpose and measurement of co-created value | ML helps in translating the concepts of “adaptability, survivability and system well-being” in terms of more tangible dimensions that can be measured to express the degree to which such purposes have been achieved |
| Process of VCC | Set of concurrent activities to be analyzed dynamically according to at least two perspectives: that of the manufacturer and that of the customers |
| Contingent forces | Exogenous and endogenous forces that lead to the adoption of a specific configuration among the finite number of possible ones |
Source(s): Author's own creation
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