https://hdl.handle.net/10419/238000 2026-10-29T09:19:37Z 2026-10-29T09:19:37Z Ivaldi, Marc Aimene, Louise Jeanjean, Francois Liang, Julienne https://hdl.handle.net/10419/238031 2023-11-10T02:29:07Z 2021-01-01T00:00:00Z

Title: The impact of RAN sharing Authors: Ivaldi, Marc; Aimene, Louise; Jeanjean, Francois; Liang, Julienne Abstract: In this paper, we formulate and estimate a structural model of demand to analyse the equilibrium effect of the RAN sharing by using cross-country panel data in 28 EU countries in years 2010-2020. Based on model estimates, our simulation analysis in Spain firstly provides a quantitative assessment of the impact of RAN sharing on mobile operators. We find that prices decrease for mobile operators involved in RAN sharing agreement due to cost reductions. In a competitive environment where operators compete, MNOs not involved in RAN sharing also lower their prices in a Nash equilibrium. We further evaluate the consumer welfare consequence of the presence of RAN sharing, and find that the RAN sharing enhanced the consumer surplus by generating lower prices for all mobile operators.

2021-01-01T00:00:00Z Fernández-Bonilla, Fernando Navío-Marco, Julio Gijón, Covadonga https://hdl.handle.net/10419/238021 2023-11-10T02:19:15Z 2021-01-01T00:00:00Z

Title: Business Innovation in the Spanish Companies (2003-2016): The Human Factors Definitively Count Authors: Fernández-Bonilla, Fernando; Navío-Marco, Julio; Gijón, Covadonga Abstract: This research analyses determining factors of business innovation in Spain during a long period of study. A panel is carried out with data from 2003 to 2016 obtained from the Spanish Technological Innovation Panel (PITEC) survey to determine their influence, and in particular variables related to human factors are included to observe their impact on innovation. Along with other general factors such as firm size, ownership of the company, turnover and financing of the company, it is found that training in R & D & I has a relevant influence on business innovation. The article put special emphasis on human factors and is an invitation to continue their study.

2021-01-01T00:00:00Z Berdibayev, Yergali Kwon, Youngsun https://hdl.handle.net/10419/238010 2023-11-10T02:19:25Z 2021-01-01T00:00:00Z

Title: Fear of COVID-19, Social Isolation and Digital Financial Services during the COVID-19 Pandemic: The Unified Theory of Acceptance and Use Technology (UTAUT) model Authors: Berdibayev, Yergali; Kwon, Youngsun Abstract: As of the end of May 2021, more than 170 million people worldwide were infected with COVID-19, with the total death toll exceeding 3.7 million. The COVID-19 pandemic and the demand for physical distancing and social isolation have highlighted digital financial services (DFS) as a typical solution for getting the basic services we need in our daily lives. Thus, to understand the behavior of people using digital financial services during a pandemic, in particular in developing countries, we used the UTAUT model, expanding it with two constructions: fear of COVID-19 as a moderator and social isolation as a direct determinant for behaviour intention. A survey method is used, in which primary data is collected through survey platforms and social networks from people from developing countries, more than 400 participants aged 18 and over. This study uses structural equation modeling (SEM) to test our constructs and hypotheses, analyze relationships, and determine the overall fit of the model. The study used factor analysis (EFA, CFA) and covariance-based SEM. As a result, we found that all UTAUT constructs and social isolation positively influence behavioral intent and actual use of DFS during a pandemic. Testing the moderating role of COVID fear for other constructs plays a positive role, with the exception of the relationship between expected performance and behavior intensity and the relationship between behavioral intent and actual use.

2021-01-01T00:00:00Z Lin, Trisha T. C. https://hdl.handle.net/10419/238037 2023-11-10T02:02:23Z 2021-01-01T00:00:00Z

Title: Socialbot representations on cross media platforms during 2020 Taiwanese Presidential Election Authors: Lin, Trisha T. C. Abstract: This big data research uses CORPRO, sentiment analysis and inter-media agenda setting approach to investigate cross-platform representation of socialbots and disinformation during 2020 Taiwanese presidential election. The results show key terms associated with socialbots emphasize Internet armies, election candidates, Facebook and China/Taiwan relations. Sentiment analysis of socialbot-related cross-platform contents tend to be negative, regardless of media types. Forums contents encompassed more diverse topics and negativity than news media and Facebook. Polarized sentiments and political slants were found in three media types. The time-series analysis of the salient socialbot event regarding Facebook's deleting illegal account showed inter-media agenda-setting from news to Facebook and forms. Even though news media set the initial agenda, journalists and social media users alter story angels and extend narratives to fit political inclinations and reflect polarized views.

2021-01-01T00:00:00Z