An ontology for defining and characterizing demonstration environments

Abstract

Demonstration Environments (DEs) are essential tools for testing and demonstrating new technologies, products, and services, and reducing uncertainties and risks in the innovation process. However, the terminology used to describe these environments is inconsistent, leading to heterogeneity in defining and characterizing them. This makes it difficult to establish a universal understanding of DEs and to differentiate between the different types of DEs, including testbeds, pilot-plants, and living labs. Moreover, existing literature lacks a holistic view of DEs, with studies focusing on specific types of DEs and not offering an integrated perspective on their characteristics and applicability in different contexts. This study proposes an ontology for knowledge representation related to DEs to address this gap. Using an ontology learning approach analyzing 3621 peer-reviewed journal articles, we develop a standardized framework for defining and characterizing DEs, providing a holistic view of these environments. The resulting ontology allows innovation managers and practitioners to select appropriate DEs for achieving their innovation goals, based on the characteristics and capabilities of the specific type of DE. The contributions of this study are significant in advancing the understanding and application of DEs in innovation processes. The proposed ontology provides a standardized approach for defining and characterizing DEs, reducing inconsistencies in terminology and establishing a common understanding of these environments. This enables innovation managers and practitioners to select appropriate DEs for their specific innovation goals, facilitating more efficient and effective innovation processes. Overall, this study provides a valuable resource for researchers, practitioners, and policymakers interested in the effective use of DEs in innovation.

An Approach for Developing an Ontology: Learned from Business Model Ontology Design and Development

“…3) Defining which attributes and properties (slots) classes can have and constraints on their values: In this step, the attributes and properties that each class can have are defined, along with any constraints on their values. However, Nie et al [27] pointed out a limitation of OD101. While it provides a basic guide for creating initial ontologies, it may not offer a comprehensive overview of diverse domains, which is essential for comparing and benchmarking different environments.…”

Places and spaces of collaborative R&D and innovation: navigating the role of physical and virtual contexts

“…Collaborators must navigate multiple agendas and engage in continuous relationship negotiation (Phillips et al., 2000). The diverse landscape of innovation contexts also poses challenges in terms of generalizing findings across different spaces and places (Nie et al., 2023). Together, the increasing diversity of actors and contexts has led to the emergence of popular concepts such as innovation communities (Fichter, 2009), knowledge networks (Phelps et al., 2012; Ritala et al., 2023), innovation networks (Jarvenpaa and Wernick, 2011; Aarikka‐Stenroos et al., 2017), innovation ecosystems (Ritala et al., 2013; Autio and Thomas, 2014), platforms (Gawer and Cusumano, 2014; Helfat and Raubitschek, 2018), and intermediaries (Howells, 2006; De Silva et al., 2018).…”