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Record W4399431622 · doi:10.1057/s41270-024-00320-3

The second mover’s market research dilemma

2024· article· en· W4399431622 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Marketing Analytics · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCapital Investment and Risk Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFirst-mover advantageHerdingDilemmaMicroeconomicsBusinessEconomicsIntuitionIndustrial organizationCompetition (biology)Private information retrievalMarketingComputer science

Abstract

fetched live from OpenAlex

Abstract Several well-established research streams examine how incumbent firm behavior affects the entry decisions of later entrants, e.g., in terms of herding or differentiation. While it makes sense for a new entrant to take into account an incumbent’s behavior to inform its entry decisions, it would be risky to base such a decision solely on that information. In particular, the potential entrant may also want to conduct its own market research. Naturally, the market research should account for incumbent behavior. Yet, little is known about how a second mover decides where it should conduct market research. Is the information gained from observing the incumbent a substitute or a complement to market research? The information a second mover gathers through observation includes the incumbent’s choice of market. Even more important is the signal generated by an incumbent’s decision to exit or stay in a market. This decision signals to a second mover whether a market is viable, at least for one firm. A second mover that considers entry between an existing market (with an operating incumbent) and a new market (that has no incumbents) chooses between different types of uncertainty. Our paper addresses how this uncertainty affects the second mover’s market research decision. Should a second mover do market research in the competitor’s backyard or should it boldly go where no firm has gone before and research a new market? How is this decision affected by factors such as expected demand conditions and competition? Intuition suggests that information about a virgin market is always more valuable because the first mover already provides information about the existing market. Our research shows that this intuition is not always correct. It is correct when market research generates perfect information. However, market research is rarely perfect. When market research provides estimates subject to an error, a second mover may gain by conducting market research in a market with an existing competitor. Here, the complementarity of the competitor’s performance coupled with market research amplifies the value of the research.

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.

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)0.022
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.297
Teacher spread0.234 · 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