Development of a model for evaluating the effectiveness of innovative startups based on information cycles and using neural networks

Viktor Volodymyrovich Morozov, Anna Kolomiiets, Olga Mezentseva

Abstract


An integrated approach to the creation and development of innovative startup projects in the field of information technology is considered. To conduct research, the authors proposed a model of information cycles of startup projects based on the creation of an information model of such projects. At the same time there are dynamic processes of changes in the parameters of the model, which are turbulent in nature and require the use of tools and methods of artificial intelligence for research. The key areas of knowledge of such influence are defined. The mathematical model of processes of management of development of IT startups on the basis of creation and development of a difficult IT product, taking into account influences of environments of the project is constructed, the basic characteristics are allocated and parameters are defined. To do this, the construction of predictive models is proposed to be carried out by modified Demarc trends, the method of self-organization and the neural network. The modeling of the main objective functions of the mathematical model of these processes is performed. The analysis of the received results is carried out and the conclusions are made.

Keywords


Startup projects; Efficiency; Project management; Information cycles; Risks; Information impacts; Neural networks

References


"A Guide to the Project Management Body of Knowledge", 6th ed. USA: Project Management Institute Four Campus Boulevard, 2017, pp. 586.

A. E. Lytvyn. Trends in the world market of information technologies. Theoretical and Practical Aspects of Economics and Intellectual Property. Vol. 2, pp. 132-137, 2011. [Online]. Available at: http://eir.pstu.edu/ handle/123456789/4299.

A. Kolomiiets, V. Morozov, "Investigation of optimization models in decisions making on integration of innovative projects," Advances in Intelligent Systems and Computing, AISC, vol. 1246, pp. 51–64, 2020 https://doi.org/10.1007/978-3-030-54215-3

R. Cooper. "Winning at new products: creative value through innovation". Basic Books: Publisher, 2017.

M. Ramanujam, G. Tacke. "Monetizing Innovation: How Smart Companies Design the Product Around the Price". Wiley: Publisher, 2016.

O. Maimon, L. Rokach. The Data Mining and Knowledge Discovery Handbook, 2005. [Online]. Available at: http://www.bookmetrix. com/detail/book/ae1ad394-f821-4df2-9cc4-cbf8b93edf40.

V. Morozov, O. Mezentseva, M. , "Trainable neural networks modelling for a forecasting of start-up product development," IEEE 3rd International Conference on Data Stream Mining and Processing, DSMP, pp. 55–60,2020.

M. Mansfiels. Startup statistics – the numbers you need to know. Startup, 2020. [Online]. Available at: https://smallbiztrends.com/2019/03/startup-statistics-small-business.html

The top 20 reasons startups fail, CB Insights. 2019. [Online]. Available at: https://www.cbinsights.com/ research/startup-failure-reasons-top/

S. Blank, B. Dorf. "The Startup Owner's Manual: The Step-By-Step Guide for Building a Great Company (DIATEINO) ", 2012, p. 608.

Kunal Swani, Brian P. Brown, Susan M. Mudambi, "The untapped potential of B2B advertising: A literature review and future agenda," Industrial Marketing Management, Vol. 89, pp. 581-593, 2019. https://doi.org/10.1016/j.indmarman.2019.05.010

V. V. Morozov, O. V. Kalnichenko, O. O. Mezentseva, "The method of interaction modeling on basis of deep learning the neural networks in complex IT-projects," International Journal of Computing, Vol. 19(1), pp. 88–96, 2020.

V. Burkov, S. Bushuev, A. Vozny, "Resource management of distributed projects and programs," Resource management of distributed projects and programs, p.338, 2015.

N. Yehorchenkova, I. Teslia, O. Yehorchenkov, "Method of project and operational processes integration in the activities of project-oriented enterprises based on functional 4Р-environment," CEUR Workshop Proceedings, 2565, pp. 142–151?, 2020.

I. Teslia, N. Yehorchenkova, O. Yehorchenkov, L. Kubiavka, I. Khlevna, "Management of Online Learning Through Modeling of Non-force Interaction of Information Agents," Mathematical Modeling and Simulation of Systems. Advances in Intelligent Systems and Computing, Springer. vol 1019, 2019.

N. Dotsenko, D. Chumachenko, I. Chumachenko, "Modeling of the process of critical competencies management in the multi-project environment," IEEE 2019 14th International Scientific and Technical Conference on Computer Sciences and Information Technologies, CSIT 2019 - Proceedings, 3, pp. 89–93, 2019.

O. Sherstyuk, T. Olekh, and K. Kolesnikova, "The research on role differentiation as a method of forming the project team," Eastern-European Journal of Enterprise Technologies, Vol. 2/3 (80), pp. 63 – 68, 2016.

E. Ries. "The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses". Currency: Publisher, 2011, p. 336.

K. Coussement, D. Vanden Poel, "Improving customer attrition prediction by integrating emotions from client/company interaction emails and evaluating multiple classifiers," Expert Systems with Applications, Vol. 36, pp. 6127–6134, 2009. https://doi.org/10.1016/j.eswa.2008.07.021

S. Neslin, "Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models," Journal of Marketing Research American Marketing Association, Vol. 43, pp. 204–211, 2006.

C. Wei, T. Chiu, "Turning telecommunications call details to churn prediction: A data mining approach," Expert Systems with Applications, Vol. 23, pp. 103–112, 2002. https://doi.org/10.1016/S0957-4174(02)00030-1

G. Greco, A. Guzzo, L. Pontieri and D. Sacca, "Mining Expressive Process Models by Clustering Workow Traces," Lecture Notes in Computer Science, Vol. 3056, pp. 52 – 62, 2004.

J. Brownlee. Why One-Hot Encode Data in Machine Learning?, 2020. [Online]. Available at: https://machinelearningmastery.com/why-one-hot-encode-data-in-machine-learning/.

Proactive Project Management. [Online]. Available at: http://www. itexpert.ru/rus/ITEMS/200810062247/.

S. Larry. "At a Moment’s Notice: Final Mile Introduces Knowledge Management to a Project Already Underway", Knowledge Management, 2001.

"Practice Standard for Project Configuration Management". Newtown Square, Project Management Institute: Publisher, 2007, p. 61.

M. Gracheva, E. Tumanova. "Mathematical and instrumental methods in modern economic research. Faculty of Economics", Moscow State University Lomonosov: Publisher, 2018, p. 232.

T. Demark. "Technical analysis-new science". Moscow: Diagramma, 1999.

A. G. Ivakhnenko, Y. A. Muller. "Self-organization of predictive models". Kiev: Technika, 1985.

K. A. Newspin, J. L. Weiss. "Modification of the neural network technique of self-organization. Automation and Modern Technologies", Moscow: Mashinostroenie, 2007, p.8.




DOI: http://doi.org/10.11591/ijeecs.v22.i3.pp%25p

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

shopify stats IJEECS visitor statistics