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Record W3121407675

Patent Breadth As An Entry Deterrent: The Case Of Vertically Differentiated Product Innovations

2002· article· en· W3121407675 on OpenAlexaff
Amalia Yiannaka, Murray Fulton

Bibliographic record

Venue2002 Annual meeting, July 28-31, Long Beach, CA · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInnovatorMonopolyIntellectual propertyIncentiveCompetitor analysisEconomic rentProduct (mathematics)Patent trollBusinessIndustrial organizationCompetition (biology)EconomicsExclusive rightLaw and economicsPatent lawMarketingLawMicroeconomicsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Patents provide very important incentives for innovative activity by enabling innovators to appropriate innovation rents through the granting of exclusive rights on their innovations. The limit of these exclusive rights is defined by two elements - patent length and patent breadth. Patent length is the time period during which the innovator has exclusive rights on the innovation and is predetermined by law. Patent breadth defines the technological territory claimed and protected by the patent - the area in the technological space within which competitors cannot offer rival innovations without infringing the patent - and is explicitly chosen by the innovator. A standard assumption in the economics literature is that an innovator should always choose to claim the maximum patent breadth, thereby deterring the entry of other firms and thus enabling the innovator to earn monopoly rents (see Gilbert and Shapiro and Gallini for examples of this view). Such a strategy, however, fails to recognize that patents are often challenged legally in the Patent Office or in the courts (Cornish). The nature of this challenge is such that the broader is the patent protection, the higher is the probability that the patent will be challenged legally by competitors, that it will overlap another patent and/or that the courts will invalidate it or narrow its scope (Lerner). Given that patent breadth is routinely challenged, the question arises as to whether the innovator is able to choose a patent breadth that deters entry, or whether the innovator is forced to share the market with a new entrant. The purpose of this paper is to examine the optimal patent breadth strategy that an innovator should employ when faced with the possibility that the patent breadth claimed will be challenged. In this paper, the optimal patent strategy is determined in a sequential game of complete information. The agents in the game are an innovator who seeks patent protection and decides on the patent breadth claimed and a potential entrant who decides on whether to enter the patentee's market and, if entry occurs, where to locate in the vertically differentiated product space. The solution to this game is obtained by backward induction - the problem of the entrant is examined first, followed by the problem of the innovator. The paper shows that that it is possible under some conditions for an innovator to use patent breadth to deter entry - when this is possible, the optimal patent strategy is to always deter entry. These conditions occur under certain combinations of the entrant's R&D effectiveness and trial cost values (i.e., low R&D effectiveness - which results in high R&D costs - and high trial costs). When these specific conditions do not hold, the optimal strategy for the innovator is to allow a new competitor to enter the market. When allowing entry, the innovator chooses patent breadth so that the benefits of increased product differentiation that result from greater patent breadth are traded off with the increased likelihood of patent challenge that comes with greater patent breadth. One of the conclusions of the paper is that the innovator will only choose the maximum patent breadth when patent infringement is never an optimal strategy for the entrant. This occurs under a very specific set of conditions (i.e., a combination of very high R&D effectiveness and high trial costs values).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.079
GPT teacher head0.233
Teacher spread0.154 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

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