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Despite the constantly increasing number of publications in the field of business ecosystems, there are indications that a precise definition that appropriately captures the business ecosystem mindset is not yet available. Therefore, the purpose of this paper is to provide a consensus definition of business ecosystems.

Using structured content analysis, this paper examines a total of 43 definitions in terms of their core components.

The results indicate that the existing definitions focus only on single components, e.g. “network of actors,” thereby omitting other essential components, such as “cocreated value proposition” or “shared fate.” Consequently, it seems appropriate to develop a consensus definition that combines the perspectives of the academic and practitioner communities.

The proposed definition is more comprehensive than the prevailing definitions and represents a synthesis of previous considerations on business ecosystems. Such a definition will support researchers in developing a sound business ecosystem theory that will guide practitioners in the efficient design and management of business ecosystems in the long term.

This paper aims to show that current Industry 4.0 maturity models primarily focus on manufacturing processes. Until now, research has been lacking with regard to outbound logistics, that is, the delivery process. This paper develops such a model.

Methodologically, this paper is grounded in design science research (DSR) and rigorously follows the model development guidelines presented by De Bruin et al. (2005). This work builds on current maturity models and original empirical research to populate and test the model.

The model appears to be applicable to describing the status quo of the digitization efforts in outbound logistics, developing a corporate vision for delivery logistics excellence and providing guidance on the development path.

Thus far, the model has been applied only for a development stakeholder. For further validation, the authors are currently working on additional case studies to demonstrate the model’s applicability.

The developed model provides guidance for the digitization of an important value-adding activity in supply chain management: the delivery process.

To the authors’ knowledge, the proposed model is the first to explicitly consider the delivery process; therefore, it complements available approaches that focus on the manufacturing process. Moreover, the results show that the widely used Supply Chain Operations Reference model can serve as the basis for additional process maturity models.