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Pp ts triple-layer smart grid business model- a comparison between sub-saharan africa and denmark
Transcript of Pp ts triple-layer smart grid business model- a comparison between sub-saharan africa and denmark
Triple-‐layer smart grid business model A comparison between Sub-‐Saharan Africa and Denmark
Presenter: Zheng Ma Associate professor [email protected]
Authors: Zheng Ma, Morten Lundgaard, Bo Nørregaard Jørgensen SDU-‐Center for Energy Informa3cs, University of Southern Denmark
Agenda
• Background • Methodology • Findings • Conclusions
Background • An esKmated of 585 million people
in Sub-‐Saharan Africa are without electricity in 2009 (Brandon et al., 2011)
• 46% of electricity generated in some naKons in Africa is lost in transmission (data.worldbank.org)
• Companies are introduced to these markets without understanding the inherent business ecosystem
Sub-‐Saharan Africa geospaKal grid (energy4humandevelopment)
Research Background – The needs for high-‐end mobile applica8ons and overly advanced smart metering etc. is not present in a low tech Sub-‐Saharan African market since focus remains on the basic components of electric power systems: GeneraKon, Transmission and DistribuKon (Deichmann et al., 2010).
– “Energy developments in Africa is a great market. They are willing to invest, and the public has the required finances” – GreenTech
– Companies from developed countries have been known to use undeveloped countries to introduce new energy development models as a plaZorm for technology ventures (Ladislaw, 2011)
Research QuesKon
• What is the ecosystem based business model for a Smart grid infrastructure?
• And is this transferable across countries?
Applied Theories
Smart Grid
Business model Open innovaKon Network theories
Research Boundary
Business ecosystem theory
Business Ecosystem theory adoptaKon
Research Framework
Methodology • Single case study design (Remergy)
– Gain significant in-‐depth insights in a parKcular business to analyze their business ecosystem
• Interviews with stakeholders in smart grid related organizaKons in Denmark and sub-‐Saharan Africa
Empirical data
Name Role/Responsibilities Date collected Mogens Michael Møller
Business Manager at Udvikling fyn
5th March 2015
Karsten Ingemann CEO Remergy 13th March 2015
Bo Nørregaard Centre manager at McKinney Møller InsKtute
14th April 2015
Tommy Lykkegaard Business manager at TreFor 21st April 2015
Jeanece Kristensen Business Development Manager 22st April 2015
Yusuf Khamis Partner at Greentech ConnecKons
29th April 2015
Methodology
Case study: Remergy • Danish situated • Operates in sub-‐Saharan Africa • Current business:
– Remergy develops microgrids in rural sub-‐Saharan Africa. They implement low technology smart grid concepts (i.e. demand management and peak capacity management) to ensure a high effeciency and reliability of the microgrid.
Remergy microgrid
Four Steps of Data analysis
Step 1-‐ OrganizaKonal factor DeterminaKon
Determining organiza8onal factors for focal company
Step 2-‐ Environmental factors of Denmark and Africa
Determine and compare Danish and African environmental factors to establish any potenKal commonaliKes and variability
Step 3-‐ Global factors of Denmark and Africa
Determine and compare Danish and African global factors to establish any potenKal commonaliKes and variability
Step 4-‐ Business ecosystem mapping
Construct a business ecosystem map for the focal company with the consideraKons derived from the data plot in the triangle model.
Research Findings Da
nish PerspecKve
Sub-‐Saharan Africa PerspecKve
Local Business Ecosystem Level
Keystone Business Ecosystem Level
Glocal Buesiness Ecosystem Level
Summary Triple-‐layer smart grid business model: • Integrated business ecosystem approach
• Applicable in scenarios of great market difference
• Understand/analyze a specific smart grid market
• EvaluaKon of the business potenKal and performance in a selected market
• Design company business model • explore the strategies of exporKng smart grid soluKons in a specific
markets
Future Research
• Business model interacKon • Network theory implementaKon • AdoptaKon of model to other case scenarios and other companies
• Transferability of knowledge
Thank you for your acenKon