Department of Business Development and Technology

Addressing Conceptual Randomness in IoT-Driven Business Ecosystem Research

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Addressing Conceptual Randomness in IoT-Driven Business Ecosystem Research. / Rezac, Fabien.

In: Sensors, Vol. 20, No. 20, 5842, 10.2020.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

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@article{37b68a329d0044dfaeb9ad72d73cfbd9,
title = "Addressing Conceptual Randomness in IoT-Driven Business Ecosystem Research",
abstract = "During the almost 27 years of its existence, the business ecosystem research has developed a substantial level of ambiguity and multifacetedness. Due to the technological advancements that promote interconnectedness and value co-creation, the field has consequently spun off into more domain-specific branches, such as the arena of digital business ecosystems driven by IoT. Nonetheless, despite the efforts to mend the theoretical foundations and to close the gap between academia and empirical practice, the absolute majority of IoT-driven digital business ecosystem literature follows the trend of conceptual randomness while expanding the volume of publications exponentially. Therefore, in order to address this unfavourable increase in random adoption of distinct concepts that ultimately refer to the same subject matter, the author encourages other scholars involved in the research field of IoT-driven digital business ecosystems to make extended efforts and support the external validity of their research (as well as the relevance of the research stream as a whole) by bounding the IoT-driven digital business ecosystems on a rigorous basis through deploying the extant theory in an careful and appropriate manner. Via a thorough examination of the theoretical fundaments that underpin the concept of IoT-driven digital business ecosystem, and based on a concise thematic review of corresponding literature published until September 2020, this article articulates logic for viewing the conceptual hierarchy within the business ecosystem research and proposes 6 literature-based recommendations for developing further IoT-driven DBE research in a rigorous way. ",
keywords = "ecosystem, business ecosystem, digital business ecosystem, IoT, Internet of Things, conceptual randomness",
author = "Fabien Rezac",
year = "2020",
month = oct,
doi = "10.3390/s20205842",
language = "English",
volume = "20",
journal = "Sensors",
issn = "1424-8220",
publisher = "M D P I AG",
number = "20",

}

RIS

TY - JOUR

T1 - Addressing Conceptual Randomness in IoT-Driven Business Ecosystem Research

AU - Rezac, Fabien

PY - 2020/10

Y1 - 2020/10

N2 - During the almost 27 years of its existence, the business ecosystem research has developed a substantial level of ambiguity and multifacetedness. Due to the technological advancements that promote interconnectedness and value co-creation, the field has consequently spun off into more domain-specific branches, such as the arena of digital business ecosystems driven by IoT. Nonetheless, despite the efforts to mend the theoretical foundations and to close the gap between academia and empirical practice, the absolute majority of IoT-driven digital business ecosystem literature follows the trend of conceptual randomness while expanding the volume of publications exponentially. Therefore, in order to address this unfavourable increase in random adoption of distinct concepts that ultimately refer to the same subject matter, the author encourages other scholars involved in the research field of IoT-driven digital business ecosystems to make extended efforts and support the external validity of their research (as well as the relevance of the research stream as a whole) by bounding the IoT-driven digital business ecosystems on a rigorous basis through deploying the extant theory in an careful and appropriate manner. Via a thorough examination of the theoretical fundaments that underpin the concept of IoT-driven digital business ecosystem, and based on a concise thematic review of corresponding literature published until September 2020, this article articulates logic for viewing the conceptual hierarchy within the business ecosystem research and proposes 6 literature-based recommendations for developing further IoT-driven DBE research in a rigorous way.

AB - During the almost 27 years of its existence, the business ecosystem research has developed a substantial level of ambiguity and multifacetedness. Due to the technological advancements that promote interconnectedness and value co-creation, the field has consequently spun off into more domain-specific branches, such as the arena of digital business ecosystems driven by IoT. Nonetheless, despite the efforts to mend the theoretical foundations and to close the gap between academia and empirical practice, the absolute majority of IoT-driven digital business ecosystem literature follows the trend of conceptual randomness while expanding the volume of publications exponentially. Therefore, in order to address this unfavourable increase in random adoption of distinct concepts that ultimately refer to the same subject matter, the author encourages other scholars involved in the research field of IoT-driven digital business ecosystems to make extended efforts and support the external validity of their research (as well as the relevance of the research stream as a whole) by bounding the IoT-driven digital business ecosystems on a rigorous basis through deploying the extant theory in an careful and appropriate manner. Via a thorough examination of the theoretical fundaments that underpin the concept of IoT-driven digital business ecosystem, and based on a concise thematic review of corresponding literature published until September 2020, this article articulates logic for viewing the conceptual hierarchy within the business ecosystem research and proposes 6 literature-based recommendations for developing further IoT-driven DBE research in a rigorous way.

KW - ecosystem

KW - business ecosystem

KW - digital business ecosystem

KW - IoT

KW - Internet of Things

KW - conceptual randomness

U2 - 10.3390/s20205842

DO - 10.3390/s20205842

M3 - Journal article

C2 - 33076487

VL - 20

JO - Sensors

JF - Sensors

SN - 1424-8220

IS - 20

M1 - 5842

ER -