A SYSTEM OF INDICATORS FOR SELECTING INNOVATION TRIGGERS TO DRIVE SUSTAINABLE DEVELOPMENT

Svitlana Tarasenko; Oleksandra Karintseva; Artem Bilovol; Wojciech Duranowski; Zbigniew Dabrowski

doi:10.32782/2308-1988/2024-51-5

Svitlana Tarasenko Sumy State University https://orcid.org/0000-0002-4829-0559
Oleksandra Karintseva Sumy State University https://orcid.org/0000-0001-9570-3646
Artem Bilovol Sumy State University https://orcid.org/0009-0000-5823-1379
Wojciech Duranowski Opole University https://orcid.org/0000-0002-3984-6332
Zbigniew Dabrowski Foundation of Z. Zamenhof

DOI: https://doi.org/10.32782/2308-1988/2024-51-5

Keywords: bass model, diffusion of innovation, forecast of innovation, hype cycle, technology, technological wave

Abstract

The foundation of sustainable development lies in innovation, technology, and entrepreneurship, which have significant positive impacts on socio-economic aspects of life. This study examines the indicators necessary for selecting innovation triggers that can lead country’s sustainable development. Innovation trigger system is mechanism that initiates and drives the development of new technologies and processes, essential for sustainable development by facilitating the transition to more sustainable practices. However, not all innovation triggers succeed or offer long-term benefits for sustainable development. This study aims to identify the indicators necessary to select effective innovation trigger for sustainable country development. It has been described hype cycle phases of main technologies in the 21-st century, and defines that there is no one duration of hype cycle phases for AI, IoT, AR and VR, blockchain technologies. It has been proposed the innovation trigger system indicators to select beneficial innovation trigger that divided into two groups, set of lagging indicators and set of leading indicators. Lagging indicators assess the effectiveness of past strategies and investments, while leading indicators provide insights into future performance and potential outcomes. By utilizing both types of indicators, a more balanced and comprehensive analysis can be achieved when selecting the most beneficial innovation trigger for a country’s development. The final choice of innovation trigger in each country will ultimately depend on its prioritized development goals. Additionally, it has been applied and modified the Bass Model to forecast the diffusion of AI among industrial enterprises in Ukraine. The basic Bass model has been extended to include a developer influence coefficient, which accounts for the role of AI developers in technology diffusion. Understanding the processes of diffusion and the effectiveness of innovation triggers, as well as the phases of the hype cycle, provides guidance for policymakers, business structures, and enterprises in technology implementation and the use of innovation for development, which determines the sustainability of national economic progress.

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