What is he best known for?
The fields of study he is best known for:
- Microeconomics
- The Internet
- Marketing
Martin Peitz spends much of his time researching Microeconomics, Industrial organization, Advertising, The Internet and Competition.
His work on Monopoly and Monopolization as part of general Microeconomics study is frequently linked to Rationing and Blockade, bridging the gap between disciplines.
His Industrial organization study incorporates themes from Market power, Telecommunications and Marketing.
His studies in Advertising integrate themes in fields like Welfare, Revenue and Product differentiation.
His study looks at the relationship between The Internet and topics such as Peer-to-peer, which overlap with Quality and Information good.
His work in Quality addresses issues such as Information asymmetry, which are connected to fields such as Investment.
His most cited work include:
- Industrial Organization: Markets and Strategies (329 citations)
- Piracy of digital products: A critical review of the theoretical literature (206 citations)
- The economics of crowdfunding platforms (182 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Industrial organization, Competition, Microeconomics, Quality and Advertising.
His work investigates the relationship between Industrial organization and topics such as Oligopoly that intersect with problems in Economic surplus.
Martin Peitz focuses mostly in the field of Competition, narrowing it down to matters related to Telecommunications and, in some cases, Voice over IP and Unbundling.
His research on Microeconomics frequently connects to adjacent areas such as Product.
His research investigates the connection between Quality and topics such as Information asymmetry that intersect with problems in Adverse selection, Investment and The Internet.
His work in Advertising covers topics such as Revenue which are related to areas like Welfare.
He most often published in these fields:
- Industrial organization (36.54%)
- Competition (29.57%)
- Microeconomics (25.58%)
What were the highlights of his more recent work (between 2018-2021)?
- Competition (29.57%)
- Industrial organization (36.54%)
- Incentive (12.96%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Competition, Industrial organization, Incentive, Merger control and Monopoly.
His study in the field of Market power also crosses realms of Single market.
In his articles, Martin Peitz combines various disciplines, including Industrial organization and Conventional wisdom.
His work in Incentive addresses subjects such as Liability, which are connected to disciplines such as Service provider, The Internet, Information asymmetry and Scope.
His studies deal with areas such as Allocative efficiency and Transparency as well as Monopoly.
His work on Horizontal differentiation and Duopoly as part of general Microeconomics research is frequently linked to Bottleneck, bridging the gap between disciplines.
Between 2018 and 2021, his most popular works were:
- Platform competition: Who benefits from multihoming? (24 citations)
- Platform competition: Who benefits from multihoming? (24 citations)
- Managing competition on a two‐sided platform (16 citations)
In his most recent research, the most cited papers focused on:
- Microeconomics
- The Internet
- Marketing
Competition, Industrial organization, Monopoly, Competitor analysis and Merger control are his primary areas of study.
His work deals with themes such as Variety, Intermediation and Imperfect competition, which intersect with Competition.
In general Industrial organization study, his work on Network effect often relates to the realm of Single market, thereby connecting several areas of interest.
His Monopoly research incorporates themes from Incentive and Allocative efficiency.
His research on Incentive concerns the broader Microeconomics.
He has researched Competitor analysis in several fields, including Market concentration and Segmentation.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
