Entries by Pedro Ferreira

The Effects of Timeshift TV Published at Management Science

My paper with Filipa Reis, Rodrigo Belo and Miguel Matos on the impact of Timeshift TV (TSTV) on TV consumption and ad avoidance has been accepted for publication at Management Science. In this paper, we partner with a major telecommunications provider to study the effect of Time-Shift TV (TSTV) on TV consumption. We find that, on […]

Two Best Paper Awards at ICIS

Our paper on the Impact of TSTV on TV viewership and ad consumption won the best paper award at the 2017 International Conference on Information Systems in the Data Science, Decision Analytics and Visualization track. In this paper, we show that the introduction of TSTV does not reduce the consumption of live TV nor the […]

Paper on Vehicular Mesh Networks Published in IEEE Access

My paper with Alexandre Ligo, Jon Peha and Joao Barros on the Throughput and Economics of DSRC-Based Internet of Vehicles has been accepted for publication in IEEE Access. In this paper, we characterize conditions under which Dedicated Short Range Communications (DSRC) can be more cost-effective than expanding the capacity of cellular networks to provide Internet access. For […]

Three Papers Accepted at ICIS

Pedro Ferreira and co-authors have three papers accepted at the International Conference on Information Systems, which will take place in Seoul, South Korea, in December 2017. One paper focuses on the effect of binge watching on the subscription of video-on-demand. Another paper focuses on the impact of time-shift TV on the consumption of TV and […]

Qiwei Han Successfully Defends PhD Thesis

Qiwei Han successfully defended his PhD thesis on the impact of search costs in offline environments. In his thesis, Qiwei shows that consumers behave alike in offline and online settings when thinking about what to purchase. In particular, consumers first search for products and only later consider purchasing a product from the consideration set they […]

Xiaochen Successfully Defends PhD Thesis

Xiaochen Zhang successfully defended her PhD thesis on the welfare properties of recommender systems. In her thesis, Xiaochen looks at how recommender systems affect consumer surplus and firm profits. She shows that personalization can be used as a tool to extract excessive surplus from consumers just like price discrimination. Xiaochen is joining the Uber Data […]