Skip to main content
SpringerLink
Log in

A Startup Assessment Approach Based on Multi-Agent and Blockchain Technologies

  • Conference paper
  • First Online:
Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection (PAAMS 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1047))

  • 1075 Accesses

Abstract

The dynamic nature of startups is linked to both high risks in investments as well as potentially important financial benefits. A key aspect to manage interactions among investors, experts, and startups, is the establishment of trust guarantees. This paper presents the formalization and implementation of a system enforcing trust in the startup assessment domain. To do so, an existing architecture has been extended, incorporating a multi-agent community and related interactions via private blockchain technology. The developed system enables a trust-based community, immutably storing, tracking, and monitoring the agents’ interactions and reputations.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    “unicorns”: startups companies which have market value of 1 billion dollars (or more). This term is widely used in venture investment industry. Highly successful startups. It commonly refers to businesses having valuation higher than a certain amount (e.g., 1 BLN dollars).

  2. 2.

    The features implemented in the ledger are listed in Appendix A.

  3. 3.

    The features implemented in ledger are listed in Appendix B.

References

  1. Bellifemine, F.L., Caire, G., Greenwood, D.: Developing Multi-agent Systems with JADE, vol. 7. Wiley, Hoboken (2007)

    Book  Google Scholar 

  2. BV4: Certified expert evaluation (2018). https://www.bv4.ch/startup-rating. Accessed 24 Mar 2019

  3. Cachin, C.: Architecture of the hyperledger blockchain fabric (2016)

    Google Scholar 

  4. Calvaresi, D., Dubovitskaya, A., Calbimonte, J.P., Taveter, K., Schumacher, M.: Multi-agent systems and blockchain: results from a systematic literature review. In: Demazeau, Y., An, B., Bajo, J., Fernández-Caballero, A. (eds.) PAAMS 2018. LNCS (LNAI), vol. 10978, pp. 110–126. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-94580-4_9

    Chapter  Google Scholar 

  5. Calvaresi, D., Dubovitskaya, A., Retaggi, D., Dragoni, A.F., Schumacher, M.: Trusted registration, negotiation, and service evaluation in multi-agent systems throughout the blockchain technology. In: 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), pp. 56–63. IEEE (2018)

    Google Scholar 

  6. Calvaresi, D., Marinoni, M., Dragoni, A.F., Hilfiker, R., Schumacher, M.: Real-time multi-agent systems for telerehabilitation scenarios. Artif. Intell. Med. (2019)

    Google Scholar 

  7. Calvaresi, D., Mattioli, V., Dubovitskaya, A., Dragoni, A.F., Schumacher, M.: Reputation management in multi-agent systems using permissioned blockchain technology. In: 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), pp. 719–725. IEEE (2018)

    Google Scholar 

  8. Cbinsights: Understanding the health of tech startups (2018). https://www.cbinsights.com/company-mosaic. Accessed 24 Mar 2019

  9. Crunchbase: Crunchbase web startup ranking platform (2018). https://about.crunchbase.com/blog/influential-companies/. Accessed 24 Mar 2019

  10. Dubovitskaya, A., Urovi, V., Barba, I., Aberer, K., Schumacher, M.I.: A multiagent system for dynamic data aggregation in medical research. BioMed. Res. Int. (2016)

    Google Scholar 

  11. Hedin, Y., Moradian, E.: Security in multi-agent systems. Procedia Comput. Sci. 60, 1604–1612 (2015). https://doi.org/10.1016/j.procs.2015.08.270. http://www.sciencedirect.com/science/article/pii/S1877050915023972. Knowledge-Based and Intelligent Information and Engineering Systems 19th Annual Conference, KES-2015, Singapore, September 2015 Proceedings

    Article  Google Scholar 

  12. Hsieh, F.S.: Modeling and control of holonic manufacturing systems based on extended contract net protocol. In: Proceedings of the 2002 American Control Conference, vol. 6, pp. 5037–5042 (2002)

    Google Scholar 

  13. InnMind: 62 top listings to promote your startup (2018). https://innmind.com/articles/1816. Accessed 24 Mar 2019

  14. InnMind: Global sturtup community for supporting innovation (2018). https://innmind.com/. Accessed 24 Mar 2019

  15. Ramchurn, S.D., Huynh, D., Jennings, N.R.: Trust in multi-agent systems. Knowl. Eng. Rev. 19(1), 1–25 (2004). https://doi.org/10.1017/S0269888904000116

    Article  Google Scholar 

  16. Harvard Business School: The venture capital secret (2018). https://www.hbs.edu/news/Pages/item.aspx?num=487. Accessed 24 Mar 2019

  17. Startupgenome: Global startup ecosystem report 2018: Succeeding in the new era of technology (2018). https://startupgenome.com/all-report-thank-you/?file=2018. Accessed 24 Mar 2019

  18. Startupgenome: PWC G4 2018 evaluation (2018). https://www.pwc.com/us/en/industries/technology/moneytree.html. Accessed 24 Mar 2019

  19. StartupRANKING: SR web startup ranking platform (2018). https://www.startupranking.com/how-it-works. Accessed 24 Mar 2019

  20. Stephan, D.: Crunchbase rank and trend score (2018). https://about.crunchbase.com/blog/crunchbase-rank-trend-score. Accessed 24 Mar 2019

  21. Swan, M.: Blockchain: Blueprint for a new economy (2015)

    Google Scholar 

  22. Tapscott, D., Tapscott, A.: Blockchain Revolution: How the Technology Behind Bitcoin is Changing Money, Business, and the World. Penguin, Westminster (2016)

    Google Scholar 

  23. TILab: cbinsights research (2018). https://www.cbinsights.com/research/startup-failure-reasons-top/. Accessed 24 Mar 2019

  24. Yu, B., Singh, M.P.: An evidential model of distributed reputation management. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems: Part 1, pp. 294–301. ACM (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Applied Sciences and Arts Western Switzerland, Sierre, Switzerland

    Davide Calvaresi, Jean-Paul Calbimonte, Valerio Mattioli & Michael Schumacher

  2. Innovare Digital s.a.r.l., Lausanne, Switzerland

    Ekaterina Voronova

Authors
  1. Davide Calvaresi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ekaterina Voronova
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jean-Paul Calbimonte
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Valerio Mattioli
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Michael Schumacher
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Davide Calvaresi .

Editor information

Editors and Affiliations

  1. University of Salamanca, Salamanca, Spain

    Fernando De La Prieta

  2. University of Salamanca, Salamanca, Spain

    Alfonso González-Briones

  3. Poznań University of Technology, Poznan, Poland

    Pawel Pawleski

  4. HES-SO Valais Wallis, Sierre, Switzerland

    Davide Calvaresi

  5. Polytechnic University of Valencia, Valencia, Spain

    Elena Del Val

  6. National Laboratory for Energy and Geology, Amadora, Portugal

    Fernando Lopes

  7. Polytechnic University of Valencia, Valencia, Spain

    Vicente Julian

  8. Tecnalia Research & Innovation, Derio, Spain

    Eneko Osaba

  9. University of Murcia, Murcia, Spain

    Ramón Sánchez-Iborra

Appendices

A Startup Self-evaluation Features

  • Product: technology/product, value proposition, scalability, and IP rights;

  • Customer: customer development, targeted market, and regional coverage;

  • Market competition: competition, current partnerships, need in the market, marketing, and PR Strategy

  • Finance: business model/tokenomics, current financial situation, pace of ROI, and exit Strategy.

  • Team and administrative: components, team experience, company registration, and legal aspects;

B Startup Assessment Features for Expert Evaluation

  • Team: experience, roles covered, traditional Media, and social media proof (in regards to the team and their connection to the project), blockchain knowledge and experience, and advisory board;

  • Product/Service development: stage of development, proof of stage of development, speed of development, roadmap, correlation between, plans and capacities, innovativeness of the product/service, sufficiency of resources/assets for creation of the product, specialised conferences participation, and comments;

  • Technology chosen: technology fits the goals of the product/service, technology helps to create the value added in the best way, the level of internal risk wrt. the use of the technology, coding activity, blockchain added value, and comments;

  • Added value and problem solved: product/market fit, relevance added value, solved problem, difficulty in creating value, and comments;

  • Market research: differentiation, Economies of scale, competition analysis and understanding, real competition, and comments

  • Customer development: target audience (analysis), market size, market fit, market share potential, and comments;

  • Marketing strategy: marketing documentation, channels of distribution, clear positioning, partners, media coverage, online marketing activities, offline marketing activities, power of buyer, and comments;

  • Business model and tokenomics: financial planning, business model validity, tokenomics margin, power of buyer and supplier, access to finance, and comment;

  • Risks: political, economic, social, technological, environmental, legal, and internal;

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Calvaresi, D., Voronova, E., Calbimonte, JP., Mattioli, V., Schumacher, M. (2019). A Startup Assessment Approach Based on Multi-Agent and Blockchain Technologies. In: De La Prieta, F., et al. Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection. PAAMS 2019. Communications in Computer and Information Science, vol 1047. Springer, Cham. https://doi.org/10.1007/978-3-030-24299-2_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-24299-2_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24298-5

  • Online ISBN: 978-3-030-24299-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation