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Kostas Bimpikis

dblp:65/8821 · DBLP profile ↗
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4ranked-venue papers
4as first author
2since 2021 · last 2024
0000-0002-5289-0397ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4 · 4 first-author · 2 since 2021Theory of computation · 4 · 4 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
4 papers
Algorithmic game theory and mechanism design · 100%
Network and information security
1 paper
Privacy and data protection · 100%

Topics — the 8 heaviest of 10, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design
market design
1.322024
Market Fragmentation and Inefficiencies in Maritime Shipping · EC 2024
Data Tracking under Competition · EC 2021
Algorithmic game theory and mechanism design › mechanism design
contest design
0.212015
Designing Dynamic Contests · EC 2015
Algorithmic game theory and mechanism design › non-cooperative game › dynamic games
dynamic contest
0.212015
Designing Dynamic Contests · EC 2015
Algorithmic game theory and mechanism design
mechanism design
0.212015
Designing Dynamic Contests · EC 2015
Algorithmic game theory and mechanism design › non-cooperative game › duopoly competition
cournot competition
0.212014
Cournot competition in networked markets · EC 2014
Algorithmic game theory and mechanism design
equilibrium computation
0.212014
Cournot competition in networked markets · EC 2014
Algorithmic game theory and mechanism design › solution concepts in games › equilibrium concepts
equilibrium uniqueness
0.212014
Cournot competition in networked markets · EC 2014
Algorithmic game theory and mechanism design › market design
networked market
0.212014
Cournot competition in networked markets · EC 2014

Methods — techniques the papers use, named apart from their topics

game theory · 1.2equilibrium analysis · 1.0empirical analysis · 0.8stochastic modeling · 0.2bayesian learning · 0.2
YearPublicationVenuePosition
2024 Market Fragmentation and Inefficiencies in Maritime Shipping
abstract
Maritime transportation is critical for the global economy, with about 90% of goods traded by sea and volumes expected to triple by 2050. Despite rising demand, 40% to 50% of total miles are sailed empty (known as ballasting), causing significant economic and environmental costs. The oil transportation market is an ideal setting to study causes and remedies of ballasting, because: (i) oil tankers only carry a single cargo from origin to destination; and (ii) the market is highly fragmented.
Kostas Bimpikis, Giacomo Mantegazza, Salomón Wollenstein-Betech
EC1
2021 Data Tracking under Competition
abstract
We explore the welfare implications of data tracking technologies that enable firms to collect consumer data and potentially use it for price discrimination. The model we develop centers around two features: first, competition between firms and, second, consumers' level of sophistication. Our baseline environment features a firm that can collect information about the consumers it transacts with in a duopoly market, which it can then use in a second monopoly market. We characterize and compare the equilibrium outcomes in three settings of interest: (i) an economy with myopic consumers, who, when making purchase decisions, do not internalize the fact that firms have the ability to track their behavior and use this information in future transactions, (ii) an economy with forward-looking consumers, who take into account the implications of data tracking when determining their actions, and (iii) an economy where no data tracking technologies are used either due to technological or regulatory constraints.
Kostas Bimpikis, Ilan Morgenstern, Daniela Sabán
EC1
2015 Designing Dynamic Contests
abstract
Innovation contests have emerged as a viable alternative to the standard research and development process. They are particularly suited for settings that feature a high degree of uncertainty regarding the actual feasibility of the end goal. The objective of the contest designer is to maximize the probability of reaching the innovation goal while minimizing the time it takes to complete the project. Obviously here the important question is how to best design these contests. This paper departs from prior literature through three key modeling features. First, in our model, an agent's progress towards the goal is not a deterministic function of effort. As is typically the case in real-world settings, progress is positively correlated with effort but the mapping involves a stochastic component. Secondly and quite importantly, it is possible that the innovation in question is not attainable, either because the goal is actually infeasible or because it requires too much effort and resources that it makes little economic sense to pursue. We model such a scenario by having an underlying state of the world (whether the innovation is attainable or not) over which participants have some prior belief. Taken together, these two features imply that an agent's lack of progress may be attributed to either an undesirable underlying state (the innovation is not attainable) or simply to the fact that the agent was unlucky in how her effort was stochastically mapped to progress. Thirdly, we consider a dynamic framework that captures how competition between agents evolves over time and incorporates the fact that agents learn from each other's partial progress to discern the underlying reason for their own lack of progress. In particular, our modeling setup includes well-defined intermediate milestones that constitute partial progress towards the end goal.
Kostas Bimpikis, Shayan Ehsani, Mohamed Mostagir
EC1
2014 Cournot competition in networked markets
abstract
The paper considers a model of competition among firms that produce a homogeneous good in a networked environment. A bipartite graph determines which subset of markets a firm can supply to. Firms compete a la Cournot and decide how to allocate their production output to the markets they are directly connected to. We assume that markets have inverse linear demand and firms have quadratic production costs. First, we show that the resulting Cournot game has a unique equilibrium for any given network and provide a characterization of the production quantities at equilibrium. Our results identify a close connection between the equilibrium outcome and supply paths in the underlying network structure. In particular, we show that whether two firms see their output in different markets as strategic substitutes or complements depends critically on the paths between those markets in the line graph induced by the original bipartite network.
Kostas Bimpikis, Shayan Ehsani, Rahmi Ilkiliç
EC1