Understanding digital platform evolution using compartmental models

Szalkowski, Gabriel Andy (author), Mikalef, Patrick (author)

Due to the growing impact of digital platforms, it is increasingly important to understand their evolution through mathematical models. As their value is dependent on their user base, we present an improved perspective on modeling the number of users. Modeling digital platforms is frequently constrained by the scarcity of available data. Thus, researchers resort to open access data like Google Trends. We provide a new interpretation of such data, using it as a proxy for the demand, in contrast with the previous method of considering it as the active user- base. This is implemented using compartmental methods, in which the expression of the demand is fitted to the number of Google Searches for a specific keyword. Two cases, the MMO World of Warcraft and Facebook are analyzed in this fashion, using two different compartmental models. The solutions given by both models replicate key features of the real evolution of the services at study, and the parameters of the fit are in accordance with the expected relative values.

• Language: English
• Keywords: market, digitalization, forecasting, models, digital economy, network effects, compartmental models, market dynamics, business forecasting
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: EF - School of Economics and Business
• Publication status: Published
• Publication version: Version of Record
• Year: 2023
• Number of pages: 10 str.
• Numbering: Vol. 193, article no.ǂ122600
• PID: 20.500.12556/RUL-148230
• UDC: 339.1
• ISSN on article: 0040-1625
• DOI: 10.1016/j.techfore.2023.122600
• COBISS.SI-ID: 151691267
• Publication date in RUL: 03.08.2023

Record is a part of a journal

• Title: Technological forecasting and social change
• Shortened title: Technol. forecast. soc. change
• Publisher: Elsevier
• ISSN: 0040-1625
• COBISS.SI-ID: 318745

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: trg, digitalizacija, predvidevanje, modeli

Projects

• Funder: ARRS - Slovenian Research Agency
• Project number: P5–0441
• Name: Regeneracija ekonomije in posla