Addressing Conceptual Randomness in IoT-Driven Business Ecosystem Research

Area of Science:

• Business Administration
• Information Systems
• Technology Management

Background:

• Business ecosystem research is nearly 27 years old, marked by ambiguity and complexity.
• Technological advancements, particularly the Internet of Things (IoT), have spurred the growth of digital business ecosystems (DBEs).
• Existing literature on IoT-driven DBEs suffers from conceptual randomness despite efforts to bridge theory and practice.

Purpose of the Study:

• To address the conceptual ambiguity in IoT-driven digital business ecosystem research.
• To establish a rigorous theoretical foundation for IoT-driven DBEs.
• To propose recommendations for future research in this domain.

Main Methods:

• A thorough examination of the theoretical underpinnings of IoT-driven digital business ecosystems.
• A concise thematic review of relevant literature published up to September 2020.
• Articulation of a conceptual hierarchy for business ecosystem research.

Main Results:

• Identified significant conceptual randomness in the burgeoning field of IoT-driven DBEs.
• Established a logical framework for understanding the conceptual hierarchy within business ecosystem research.
• Developed six literature-based recommendations for enhancing the rigor of future IoT-driven DBE research.

Conclusions:

• The field of IoT-driven digital business ecosystems requires a more rigorous theoretical grounding.
• Scholars should focus on deploying existing theories carefully to enhance the external validity and relevance of their research.
• The proposed conceptual hierarchy and recommendations offer a pathway for more structured and impactful future research in IoT-driven DBEs.