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Jonathon MoteThe George Washington University
Gretchen B Jordan360 Innovation LLC
Rosalie RueggTIA Consulting
Exploring the Use of Netchain Analysis in Evaluating Emerging Markets
Work prepared for the U.S. Department of Energy (DOE), under contract with Lawrence Berkeley National Laboratory (LBNL). Opinions expressed do not necessarily reflect those of the U.S. DOE or LBNL.1
Introduction
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Team brought together to develop evaluation framework for specific set of the DOE’s Office of Energy Efficiency and Renewable Energy initiatives:
Includes Thomas Choi (Arizona State) and Angela Becker-Dippmann (Pacific Northwest)
Establish an evaluation framework that will guide impact and process assessments of DOE/EERE R&D and related investments aimed at accelerating innovation, advancing manufacturing and creating a domestic supply base and early markets in the U.S.
Explored the use of network analysis to derive interim indicators of changes in supply chains/netchains2
Supply chains, value chains and networks Previous work on supply chain networks (Choi) and
netchains (Lazzarini) suggested the use of social network analysis to assess impact on value chains for specific alternative energy industries
Focus on near-term (early stage) changes and intermediate indicators
Focus on connectedness of firms within value chain, as well as other relevant actors (R&D, finance, etc)
Is the DOE-EERE fostering networks that lead to positive outcomes?3
Supply chains Sequence of processes across a value chain involved in the
production and distribution of a product. Flexible, Robust and Resilient – many stable suppliers can
accommodate significant threats
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Supply chain network Choi – supply chains
should be considered networks
Highlights interconnections – cross-linked and two-way exchanges
But few, if any, companies (OEMs) know the extent of their supply chain networks
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Netchains Netchain – set of networks comprised of
horizontal ties between firms in an industries, such that networks (or layers) are sequentially arranged based on vertical ties between firms in different layers (Larrarini et al, 2001)
Highlights that supply chains overlap and intersect
Conceptually offers a way to understand the interaction of supply chain networks across an industry, value chain or product
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The innovation ecosystem
R&DInstitutions Sources of
Capital, Other Resources
Other actors involved with product Component,
Sub systemSuppliers
Manufacturers/Assemblers
Distributors, Sellers Service Providers
Consumers
Raw Material Suppliers
Technical:Competing, complementary technologies…
Economic:Market characteristics, NGOs...
Government:Policies, procurement … (including EERE)
Information, Culture: Human resources, networks, beliefs…
Innovation Ecosystem
Product Value Chain
Product & Marketof Focus
Product Supply Chain firmsOther firms in the industryOther elements contributing to product, market
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Network indicators
Both one-mode and two-mode networks One-mode – network connections across the netchain (buyers/supplier as “firms”) Two-mode - network connection across the innovation ecosystem (“firms” and
“support organizations”) Goal is robust and resilient domestic supply chains for energy technologies
Suggests plentiful actors and plentiful connections among actors Suggests key actors playing positive roles (cooperative and collaborative) Suggests strong, stable actors
Three principal areas of indicators Connectivity Overall Network Health Intended Interim Outcomes/Impacts
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Network indicators - connectivity Connectivity
Does the structure enable efficient sharing of info, ideas and resources?
Is the network growing (new actors, but new links as well)?
Is the network more interconnected (more dense)? Does the network bridge clusters? How are actors connected? – suppliers, buyers,
communication, collaboration, alliances, joint ventures
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Network indicators – overall health Overall Network Health
Who are the primary leading actors (organizational leaders in horizontal networks)? What role are they playing—controllers or collaborators?
How diverse is the network? Small/large (horizontal networks), suppliers, manufacturers, distributors, R&D, universities, agencies, venture capital/private equity (netchains)
Is the network balanced and growing – able to grow more inclusive and sustain collaboration?
Is the structure appropriate for the work of the network (different horizontal networks may require different structures)? Assumed core/periphery is optimal, but may not be the case.
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Network indicators – interim impacts
Intended Outcomes/Impacts Evidence of greater coordination and collaboration –
alignment of priorities/R&D, working agreements, alliances, joint ventures, etc.
Identification of key actors (either within or outside the networks) for future network weaving.
More innovative products being developed for market and deployed – movement through the TRLs and MRLs.
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Opportunities and challenges Opportunities
Network analysis able to capture complexity of innovation ecosystem (one-mode, two-mode and multi-level)
Suggests interim indicators based on how firms are interacting (or not)
Possible to identify opportunities for network “weaving” Challenges
Network theory and methodology still nascent – suggestive, but not conclusive
Magnitude of data gathering
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Network “Weaving”
Identifying important actors and assessing emerging network patterns could allow for network “weaving”
Strategic interventions to make connections that strengthen the network
A hypothetical example – li-ion batteries for vehicles
Application of netchain analysis to real-world Hypothetical dataset based on parameters of li-ion
battery industry and the EERE li-ion batteries for vehicles initiative
Utilized existing industry analysis conducted by Marcy Lowe at Center on Globalization Governance & Competitiveness (Duke University)
Constructed a hypothetical value chain with linkages that attempted to mirror real-world linkages
Hypothetical Value ChainFirm Type by Category
Number of Firms
OEM 7Supplier – Battery Pack
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Supplier - Anode 9Supplier - Cathode 8Supplier - Lithium 4Supplier – Other 41
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Li-ion value chain, firms and recipients
15 Source: Center for Globalization, Governance & Competitiveness, Duke University
Note: Red indicates firms that received DOE investment
Li-ion value chain, firms and recipients – time 1
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Red = OEM
Green = Battery Pack Supplier
Blue = Lithium Supplier
Teal = Component Supplier
Li-ion value chain, firms and recipients – time 2
Network Measures Over TimeMeasures Time 1 Time 2Size 75 74Network Density .024 .025Network Centralization .323 .322Network Closeness .016 .083Degree Centrality (individual firms)
Top 5.338 Firm 43 (Supplier-Battery).189 Firm 17 (Supplier-Battery).135 Firm 33 (OEM).122 Firm 1 (OEM).068 Firm 9 (Supplier-Battery)
Top 5.338 Firm 43 (Supplier-Battery).196 Firm 17 (Supplier-Battery).135 Firm 33 (OEM).122 Firm 1 (OEM).074 Firm 9 (Supplier-Battery)
Closeness (individual firms)
Top 5.039 Firm 38 (Supplier-Lithium).039 Firm 33 (OEM).039 Firm 43 (Supplier-Battery).038 Firm 17 (Supplier-Lithium).038 Firm 34 (Supplier-Anode)
Top 5.111 Firm 73 (Supplier-Lithium).107 Firm 17 (Supplier-Battery).103 Firm 33 (OEM).102 Firm 19 (Supplier-Anode).101 Firm 38 (Supplier-Lithium)
Betweenness (individual firms)
Top 5.333 Firm 43 (Supplier-Battery).289 Firm 33 (OEM).232 Firm 17 (Supplier-Battery).231 Firm 38 (Supplier-Lithium).039 Firm 1 (OEM)
Top 5.409 Firm 43 (Supplier-Battery).391 Firm 17 (Supplier-Battery).326 Firm 33 (OEM).244 Firm 38 (Supplier-Lithium).193 Firm 1 (OEM)
Isolates 7 4
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Conclusion
Need for early-stage indicators requires exploration of new methodologies
Development of new products in emerging industries does not happen in isolation – supply chains and networks
Netchain analysis (network analysis across product value chains) offers one potential avenue HOWEVER, provides a limited set of metrics which can only
answer a limited set of questions
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Questions?
Gretchen Jordan – [email protected]
Rosalie Ruegg – [email protected]
Jonathon Mote – [email protected]
Thanks for your time!
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