When and how do innovation ecosystems outperform integrated organizations? On technological interdependencies and ecosystem performance
| DOI | https://doi.org/10.1108/IMDS-11-2021-0720 |
| Published date | 09 August 2022 |
| Date | 09 August 2022 |
| Pages | 2091-2120 |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
| Author | Huanren Zhang,Yimei Hu,Xianwei Shi,Yuchen Gao |
When and how do innovation
ecosystems outperform integrated
organizations? On technological
interdependencies and
ecosystem performance
Huanren Zhang
Department of Economics, University of Southern Denmark, Odense, Denmark
Yimei Hu
Aalborg University Business School, Aalborg University, Aalborg, Denmark
Xianwei Shi
Antai College of Economics and Management, Shanghai Jiao Tong University,
Shanghai, China, and
Yuchen Gao
School of Public Policy and Management, Tsinghua University, Beijing, China
Abstract
Purpose –Studies have documented the distinctive advantage of innovation ecosystems in integrating and
recombining heterogeneous knowledge resources across firms’boundaries. However, hierarchical governance
in the form of vertical integrationis still preferred in many industries for organizing innovation, and the current
literature touches little on the relative performance of different organizational structures (integrated firms vs
innovation ecosystem) and the factors that lead firmsto choose one over the other. The authors conjecture that
structure of technological interdependence is oneof such important factors. Using a computationalexperiment,
the authors compare the innovation performance of ecosystems with integrated firms under different
interdependency structures.
Design/methodology/approach –Using the NKC model, the authors incorporate non-generic
complementarities and modularity into the technological interdependence between different components.
The authors compare four different types of technological interdependence (modular, hierarchical, nearly
modular, and random).
Findings –The results show that integrated firms with centralized search demonstrate stable and consistent
performance that is robust to the structure of technological interdependencies, but an ecosystem significantly
outperforms integrated firms with centralized or decentralized when the products exhibit modular or nearly-
modular structures.
Originality/value –This study sheds light on why an ecosystem often exhibits modular structures while
vertical integration is prevalentin industries with complex technological interdependence. In addition, it shows
the evolutionary nature of ecosystems and indicates how the cooperation and competition between actors
shape the interdependence structure of ecosystems.
Keywords Interdependencies, Innovation, Ecosystem, NK model, Value creation, Value appropriation
Paper type Research paper
Innovation
performance of
ecosystems
2091
The first two authors contributed equally to this research.
Funding: The authors acknowledge the funding support by National Social Science Fund of China
(20&ZD075), National Natural Science Foundation of China (72102144 and 72104121), Humanities and
Social Sciences Project of the Ministry of Education of China (21YJC630114), Shanghai Pujiang Program
(2020PJC074) and Shanghai Chenguang Program (20CG17).
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 25 November 2021
Revised 29 April 2022
14 June 2022
Accepted 15 July 2022
Industrial Management & Data
Systems
Vol. 122 No. 9, 2022
pp. 2091-2120
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-11-2021-0720
1. Introduction
The conception of ecosystem refers to a set of multilateral actors that are aligned to realize a
core valueproposition (Adner,2006,2017;Adner and Kapoor,2010;Kapo or, 2018). Based on the
business ecosystem concept, the innovationecosystem is proposed to explain how innovation
can be achieved throughvalue-creating interactions between ecosystem actors (Adner, 2006).
Innovation activities arranged at the ecosystem level enjoythe advantages of the integration
and recombination of heterogeneous knowledge resourcesacross firms’boundaries.
An ecosystem is inherently a hybrid organization (Zenger and Hesterly, 1997) that infuses
coordination among loosely coupled firms or business units. While innovation ecosystems
mostly consist of firms that focus on theirown component development or niche role, we also
observe an “eco-systemization”trendinfirms’intra-organizationaldesign:an increasingnumber
of firms try to remove the hierarchy and allow business units and teams to work as self-
organizing and profit-seeking molecules that are loosely coupled by their task interdependencies
(Zenger and Hesterly, 1997). The Danish firm Oticon’s spaghettiorganization experiment (Fang
and Kim, 2018;Foss, 2003) and the Chinese home appliance leader Haier’s corporateinnovation
ecosystem (Jiang et al., 2019;Kanter and Dai, 2018) serve as good examples of stimulating
entrepreneurship and innovation through designing an ecosystem-like corporate structure that
challenges the conventional hierarchical governance mode.
With the emergence of “eco-systemization”at both the inter-firm and intra-firm levels,
hierarchical governance nevertheless remains salient. Vertical integration via internalizing
complementary tasks and components (Baldwin, 2019) within firms’boundaries becomes
common when strong interdependencies across firms’boundaries raise uncertainties and
coordination costs (Hu et al., 2021a,b). When involved in business relationships with multiple
interdependent actors, a firm often adopts a system strategy that tries to internalize
complementary tasks, components, and value-adding processes to increase control and value
capture possibilities (Hannah and Eisenhardt, 2018).
Despite the prevalence and coexistence of different organizational structures for
innovation (inter-firm ecosystem, intra-firm ecosystem, and vertically integrated firm),
current literature mostly focuses on the distinctive advantage of the inter-firm innovation
ecosystem, and we know little about the relative innovation performances of these
organizational structures quantitively. Research is needed to understand the factors that lead
firms to choose different organizational structures and the conditions under which
ecosystems outperform the other organizational structures. These are important questions
to answer, as they not only deepen our understanding of ecosystem governance but also
inform the firms as to what organizational structure is preferred if they have the chance to
choose. As the structure of technological interdependencies is shown to influence the
innovation performance of firms in ecosystems (Ganco et al., 2020), we conjecture that it could
also influence the performance of firms in different organizational structures. By comparing
the innovation performance under different organizational structures and investigating the
interaction between organizational structures and technological interdependency structure,
we answer the following questions: (1) Is ecosystem organization superior to vertically
integrated organizations in terms of innovation performances? (2) How do different structures
of technological interdependencies influence innovation performances?
To answer these questions, we turn to computational experiments that incorporate the
evolutionary nature of innovation search and the complexity of ecosystem structure (Ethiraj
et al., 2008;Fleming and Sorenson, 2003). First, because innovation is often considered as a
search for a high-performing combination of interdependent choices, we model the innovation
process based on the NK model and the NKC model that is widely used in the strategic
management and innovation ecosystem literature (Baumann et al., 2019;Ethiraj and
Levinthal, 2004;Fang and Kim, 2018;Fleming and Sorenson, 2001;Ganco, 2017;Ganco and
Agarwal, 2009;Levinthal, 1997). As an extension of the NK model, the NKC model captures
IMDS
122,9
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