Series of AI-INNOM Project Seminars. Day #2
After two years of working on a project titled Adding Data and Artificial Intelligence into Innovation Equation: Conceptualizing and Exploring AI-Based Innovation Management (AI-INNOM), we are approaching its closure. We are inviting you to discuss our results and outlook for the future research through the series of seminars. Detailed schedule is below.
DAY #2 – MONDAY, MAY 29
Seminar: Why Google Trends data are valuable for research (and practice)
Monday, May 29, starts at 10:15
Online, in English
Google Trends (GT) is the most frequently used big data tool that aggregates web search queries in academic studies. It entered academic research in 2009. First, Google scientists demonstrated how GT data could be applied to predicting automotive, retail, home sales, and tourism flows. Then, GT data was used to develop a model for predicting influenza epidemics and the paper based on it was published in Nature. These results opened a door for a wide usage of GT data across scientific fields resulting in more than 4.500 journal publications in the English language indexed in Scopus – which contain the phrase “google trends” in their title, abstract, or keywords – as of mid-2022. In this seminar, we will try to explain why they are so useful for academic research and how it can be used.
About the speaker: Zeljko Tekic is an Associate Professor at the Graduate School of Business, HSE University, Moscow. Zeljko earned his PhD in Engineering Management at the University of Novi Sad (Serbia). He was a postdoctoral scholar at the Fraunhofer Institute for Industrial Engineering in Stuttgart and at Freie Universität Berlin. More recently, he was a visiting researcher and a visiting professor at the Massachusetts Institute of Technology (MIT). Zeljko’s research interest evolves around topics at the interplay of digital transformation, open innovation, and startups formation. His latest research focuses on understanding 1) how startups grow using big data instruments; and 2) how artificial intelligence is revolutionizing innovation management. In these two directions, as a part of international research teams, he is investigating how Google Trends data can be used to analyze entrepreneurial phenomena, and how far AI could improve innovation management and what kind of innovation tasks could be assisted by machines.
Seminar: Using Entrepreneurs’ Digital Footprint for Analyzing a Country’s Entrepreneurial Activity
Monday, May 29, starts at 11:00
Online, in English
This work focuses on the challenges in understanding and measuring entrepreneurship, a key topic in numerous policy debates. Due to a lack of valid data on business registrations, there is disagreement about the impact of rules and regulations on entrepreneurial activity within a country. The research attempts to address this issue by using Internet search data.
About the speaker: Andrei Parfenov is Curriculum Developer at Practicum Tech, Belgrade, Serbia. He holds a Master's degree in Business Informatics from the Graduate School of Business at HSE University, Moscow. He gained professional experience as a software engineer and technical editor at Yandex and has worked on start-up educational products. His research interests include big data, AI, and innovation management.
Seminar: How do scholars employ Internet search query data? The review of recent econometrics publications
Monday, May 29, starts at 11:45
Online, in English
During the seminar, Dr. Maksim Malyy will present the selected recent publications on the use of Google Trends data for various econometrics tasks. In the presentation, five papers - four published and one pre-print - from high impact factor international journals will be reviewed. These papers employ GT data for various purposes: studying the volatility of Bitcoin, predicting consumer mobility during the pandemic, understanding digital platform evolution, re-questioning the value of online searches for the trading market, and proposing a new model for new ventures' growth trajectory. The papers' methods, results, and limitations will be proposed for the after-presentation discussion.
About the speaker: Dr Maksim Malyy is a researcher at Creative Educational Center, Novi Sad, Serbia He received his aerospace engineer's degree in 2012 from the Baltic State Technical University “VOENMEKH,” St. Petersburg, Russia, and his Ph.D. from Skolkovo Institute of Science and Technology, Moscow in 2022. He worked as an analyst in Start-up Accelerator and Venture Fund iDealMachine and contributed to several start-up acceleration programs as a mentor, advisor, and instructor. His research interest evolves around question of how startups grow and how to use the internet search queries to better understand startups.
Seminar: Analysis of the Impact of Short-Term Public Interest on Startup Growth: Big Data Approach
Monday, May 29, starts at 12:30
Online, in English
In the digital age, there are many cases of technology-based ventures that gain a lot of attention but end up either not solving real problems, or being fraudulent. This is often due to hype, where people get excited about a vision of the future that may not be realistic. This study wants to find out if short bursts of public interest have a lasting impact on the growth of startups.
About the speaker: Elizaveta ShlikhtI is a fourth-year bachelor student of the Business Informatics program at the Higher School of Economics who is unsure about future career path, so she have decided to explore research as an option while writing her thesis.
Seminar: Do accelerators help all startups they select or just those already successful?
Monday, May 29, starts at 13:00
Online, in English
Responding to rapidly growing number of accelerators and startups going through their programs, research on this topic started to emerge approximately a decade ago. Since then, the dominant question in the academic studies and government sponsored reports has been effectiveness of accelerators (do they help startups?). However, conclusions are mixed with the evidence showing a positive, but also a neutral or even negative impact of acceleration on startups. However, what is less known is how between startups differences influence the effect of acceleration. This is an important question, because if found that accelerators, despite tough selection, are helping only or dominantly to already growing startups, this would suggest that there are low benefits from participation for entrepreneurs and that startups should avoid participation in accelerators and policy makers supporting them. Aiming to help in closing this gap, in this seminar, we will present evidence based on Google trends data in the response to the following question: Do startup accelerators help growth of already successful (i.e., growing) startups only? Or do they help growth of startups with declining or stagnating growth trends as well?
About the speaker: Zeljko Tekic is an Associate Professor at the Graduate School of Business, HSE University, Moscow. Zeljko earned his PhD in Engineering Management at the University of Novi Sad (Serbia). He was a postdoctoral scholar at the Fraunhofer Institute for Industrial Engineering in Stuttgart and at Freie Universität Berlin. More recently, he was a visiting researcher and a visiting professor at the Massachusetts Institute of Technology (MIT). Zeljko’s research interest evolves around topics at the interplay of digital transformation, open innovation, and startups formation. His latest research focuses on understanding 1) how startups grow using big data instruments; and 2) how artificial intelligence is revolutionizing innovation management. In these two directions, as a part of international research teams, he is investigating how Google Trends data can be used to analyze entrepreneurial phenomena, and how far AI could improve innovation management and what kind of innovation tasks could be assisted by machines.