The Green Multi Business Model Innovation Brain

Authors

DOI:

https://doi.org/10.13052/jmm1550-4646.17132

Keywords:

The Green Multi Business Model Innovation Brain, Advanced Green Business Modelling, AI, Deep Learning, Green Business Model Innovation, Sensors, Persuasive Technologies, Physical, Digital, Persuasive and virtual green business models

Abstract

Advanced Green technologies integrated in Business Models and Green Multi Business Model Innovation processes introduce a new leadership and management agenda of Green Business Models. Fast innovation of sensing, persuasive and virtual Business Modelling that can operate autonomously and dynamically primarily lead by machines. Green Multi Business Model Innovation Brains will soon be the state of the art in Business that want to become Green – but also for businesses that want to do circular and/or sustainable business modelling.

Businesses will build Green Multi Business Model Innovation competence and advanced Green Multi Business Models Innovation Brains capable to innovated and operate Green Business Models to all kinds of Business Model Ecosystems. This will open up to new Green Multi Business Model Innovation potential and create a new generation or archetypes of Business Models, new practice of Multi Business Model Innovation.

The paper is a second articles and extension of a conceptual paper on Multi Business Model Brains. First paper was presented at the BIT Sindri IEEE Conference 2020 conceptualizing on how a Multi Business Model Brain could be constructed and would operate supported by advance sensor technologies, artificial intelligence technologies, deep learning, persuasive technologies, Multi Business Model Innovation pattern analysis and libraries of BM archetypes. In combination they will all be important supporting tools to the Multi Business Model Innovation Brain – but now also to the Green Multi Business Model Innovation Brain. 8 case examples shows how Green Multi Business Model Innovation Brains can work in different contexts – in physical, digital, virtual and combined Business Model ecosystems.

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Author Biography

Peter Lindgren, CGC – Aarhus University, Business Development and Technology, Denmark

Peter Lindgren holds a full Professorship in Multi business model and Technology innovation at Aarhus University, Denmark – Business development and technology innovation and is Vice President of CTIF Global Capsule (CGC). He is Director of CTIF Global Capsule/MBIT Research Center at Aarhus University – Business Development and Technology and is member of Research Committee at Aarhus University – BSS.He has researched and worked with network based high speed innovation since 2000. He has been head of Studies for Master in Engineering – Business Development and Technology at Aarhus University from 2014–2016 and member of the management group at Aarhus University Btech 2014–2018. He has been researcher at Politechnico di Milano in Italy (2002/03), Stanford University, USA (2010/11), University Tor Vergata, Italy (2016/2017) and has in the time period 2007–2011. He has been the founder and Center Manager of International Center for Innovation www.ici.aau.dk at Aalborg University, founder of the MBIT research group and lab – http://btech.au.dk/forskning/mbit/ – and is cofounder of CTIF Global Capsule – www.ctifglobalcapsule.org. He has worked as researcher in many different multi business model and technology innovations projects and knowledge networks among others E100 – http://www.entovation.com/kleadmap/, Stanford University project Peace Innovation Lab http://captology.stanford.edu/projects/peace-innovation.html, The Nordic Women in business project – www.womeninbusiness.dk/, The Center for TeleInFrastruktur (CTIF), FP7 project about “multi business model innovation in the clouds” – www.Neffics.eu, EU Kask project – www.Biogas2020.se, Central Project, Motor5G, Recombine, Greenbizz. He is cofounder of five startup businesses amongst others – www.thebeebusiness.com, www.thedigibusiness.com, www.vdmbee.com. He is author to several articles and books about business model innovation in networks and Emerging Business Models. He has an entrepreneurial and interdisciplinary approach to research. His research interests are multi business model and technology innovation in interdisciplinary networks, multi business model typologies, sensing-, persuasive- and virtual- business models.

References

Valter, P., Lindgren, P., and Prasad, R. (2017) Artificial intelligence and deep learning in a world of humans and persuasive business models, GWS 2017 Proceedings IEEE Explorer, (in press).

Valter, P., Lindgren, P., and Prasad R. (2018) The consequences of artificial intelligence and deep learning in a world of persuasive business models. IEEE Aerospace and Electronic Systems Magazine, 33, 80–88.

Lindgren Peter (2020) The Multi Business Model Brain Proceedings BIT Sindry IEEE Conference February 2020 River Publishers.

Nalebuff Barry, Adam M. Brandenburger (1996) Coopetition Crown Business Publishers.

Lindgren P. (2018) Disruptive, Radical and Incremental Multi Business Model Innovation Conference Paper November 2018. DOI: 10.1109/GWS.2018.8686679 Conference: 2018 Global Wireless Summit (GWS).

Wirtz, B.W., Pistoia, A., Ullrich, S., Gottel, V., 2016. Business models: origin, development and future research perspectives. Long. Range Plan. 49, 36e54. https://doi.org/10.1016/j.lrp.2015.04.001.

Foss, N.J., Saebi, T., 2017. Fifteen years of research on business model innovation. Manag. 43, 200e227. https://doi.org/10.1177/0149206316675927.

Fine, Charles H. (1999) Clockspeed : Winning Industry Control in the Age of Temporary Advantage Perseus Books, Massachusetts.

Summer, Alex (2012) Managing Green Business Model Transformations Springer Verlag.

Taran, Y., Harry Boer, Peter Lindgren A business model innovation typology 2015, I : Decision Sciences. 46, 2, s. 301–331 31 s.

Gassmann Oliver, Karolin Frankenberger, Roman Sauer, A. Rechtschaffen and A. Kales, “Leading Business Model Research The Seven Schools of Thought”, chapter from Exploring the Field of Business Model Innovation: New Theoretical Perspectives, Springer 2016.

Pieroni, Marina P.P., Tim C. McAloone, Daniela C.A. Pigosso (2019) Business model innovation for circular economy and sustainability: A review of approaches Journal of Cleaner Production.

Poole, David; Mackworth, Alan; Goebel, Randy (1998). Computational Intelligence: A Logical Approach. New York: Oxford University Press. ISBN 978-0-19-510270-3.

Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, ISBN 0-13-790395-2.

Marblestone, Adam H.; Wayne, Greg; Kording, Konrad P. (2016). “Toward an Integration of Deep Learning and Neuroscience”. Frontiers in Computational Neuroscience. 10: 94. doi:10.3389/fncom.2016.00094. PMC 5021692. PMID 27683554.

Russell, Stuart J.; Norvig, Peter (2009). Artificial Intelligence: A Modern Approach (3rd ed.). Upper Saddle River, New Jersey: Prentice Hall. ISBN 978-0-13-604259-4.

McCorduck, Pamela (2004), Machines Who Think (2nd ed.), Natick, MA: A. K. Peters, Ltd., ISBN 1-56881-205-1.

Lindgren P. and Katharina Wuropulos (2017) Secure Persuasive Business Models and Business Model Innovation in a World of 5G Wireless Personal Communications October 2017, Volume 96, Issue 3, pp. 3569–3583.

Lindgren P, (2019) Advanced Business Model Innovation Supported by Artificial Intelligence, Deep Learning, Multi Business Model Patterns and a Multi Business Model Library Wireless Personal Communications DOI: 10.1007/s11277-019-06260-x.

Prasad Neili (2019) AI a job creator or job killer 4 in 1 conference Key note speech at CGC Denmark.

Schmidhuber, J. (2015). “Deep Learning in Neural Networks: An Overview”. Neural Networks. 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003. PMD 25462637.

Bengio, Yoshua; LeCun, Yann; Hinton, Geoffrey (2015). “Deep Learning”. Nature. 521 (7553): 436–444. doi:10.1038/nature14539. PMID 26017442.

Ciresan, Dan; Meier, U.; Schmidhuber, J. (June 2012). “Multi-column deep neural networks for image classification”. 2012 IEEE Conference on Computer Vision and Pattern Recognition: 3642–3649. arXiv:1202.2745. doi:10.1109/cvpr.2012.6248110. ISBN 978-1-4673-1228-8.

Marblestone, Adam H.; Wayne, Greg; Kording, Konrad P. (2016). “Toward an Integration of Deep Learning and Neuroscience”. Frontiers in Computational Neuroscience. 10: 94. doi:10.3389/fncom.2016.00094. PMC 5021692. PMID 27683554.

Bengio, Yoshua; Lee, Dong-Hyun; Bornschein, Jorg; Mesnard, Thomas; Lin, Zhouhan (2015-02-13). “Towards Biologically Plausible Deep Learning”. arXiv:1502.04156 [cs.LG].

Andersen, G.K., Susan Durst, Per Valter and Peter Lindgren (2019) Collaborative knowledge sharing and knowledge generation in Multi Business Model Innovation processes – A three-dimensional Knowledge Ecosystem Proceedings IFKAD Conference 2019.

Martins, L. L., Rindova, V. P., & Greenbaum, B. E. (2015). Unlocking the hidden value of concepts: A cognitive approach to BMI. Strategic Entrepreneurship Journal, 9, 99–117.

Andersen, G, Peter Lindgren, Jane Flarup (2019) Business Model Innovation Process Management in a Business Model Innovation Continuum Wireless Personal Communications WIRE-D-19-00379 ISSN 0929-6212.

Gartner 2019 https://www.gartner.com/en/sales/insights/b2b-buying-journey

H2020 ID: LC-GD-5-1-2020 Green airports and ports as multimodal hubs for sustainable and smart mobility – https://buff.ly/3mDvV8U.

World Street Journal (2019) https://www.wsj.com/articles/loreal-expands-virtual-try-on-service-11576776586?mod=hp_minor_pos4 20-12-2019.

Center for Energy https://ens.dk/sites/ens.dk/files/CO2/standardfaktorer_for_2019.pdf.

Lindgren, P & Ole Horn Rasmussen (2016) The Business Model Ecosystem Journal of Multi BMI, River Publisher I. S.

Delmas, M. A., Burbano, V. C. (2011). The drivers of greenwashing. California Management Review, 54, 64–87.

CADS – https://arsutoriamagazine.com/what-is-cads/.

https://arsutoriamagazine.com/biodegradable-shoes/.

https://www.google.com/search?tbm=isch&sa=1&ei=MYZKXa-wL8WqrgSRy6fgAg&q=brain+and+senses&oq=brain+and+sens&gs_l=img.3.0.0j0i8i30j0i24l4.92604.95391..99089...0.0..0.108.830.6j3......0....1..gws-wiz-img.......0i67.ma2eqJNwLQE#imgrc=BaheBWXQofSeiM:&spf=1565165222814.

https://blog.retail.org.au/newsandinsights/sensing-a-successful-store-design

Englemann David https://www.youtube.com/watch?v=8tN3J_V-J5w.

https://www.redbubble.com/people/dang3r/works/32417758-analytical-and-creative-brain?p=poster.

Saghaug, K. F. 2015. Revelation and Innovation of Value- Interactions between Revelatory Theology, Artistic Creativity and Small Business Owners in a Business Model Innovation Context. PhD Dissertation. Aalborg: Aalborg University Press.

Ligthart, Leo P. and Ramjee Prasad Towards Future Technologies for Business Ecosystem Innovation CONASENSE, The Netherlands River Publishers ISBN: 9788793609778 eBook ISBN: 9788799923700.

Prahalad, C.K. and Hamel, G. (1990) “The core competence of the corporation Archived 2014-07-14 at the Wayback Machine”, Harvard Business Review (v. 68, no. 3) pp. 79–91.

Prasad, R. (2016) Knowledge home. 2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS), IEEE Explorer.

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Published

2021-02-02

How to Cite

Lindgren, P. (2021). The Green Multi Business Model Innovation Brain. Journal of Mobile Multimedia, 17(1-3), 27–64. https://doi.org/10.13052/jmm1550-4646.17132

Issue

2021: Vol 17 Iss 1-3

Section

CONASENSE