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Record W2045237363 · doi:10.1509/jm.11.0225

You get what you Pay for: The Effect of Top Executives’ Compensation on Advertising and R&D Spending Decisions and Stock Market Return

2012· article· en· W2045237363 on OpenAlexaff
Imran S. Currim, Jooseop Lim, Joung W. Kim

Bibliographic record

VenueJournal of Marketing · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsConcordia University
Fundersnot available
KeywordsIncentiveEquity (law)Stock (firearms)EconomicsBusinessCouponStock marketAdvertisingMonetary economicsMicroeconomicsFinance

Abstract

fetched live from OpenAlex

Although there is literature on how top executives’ compensation influences general management decisions, relatively little is known about whether and how compensation influences advertising and research-and-development (R&D) spending decisions. This study addresses two questions. First, is there an incentive effect of long- versus short-term compensation on advertising and R&D spending? Second, is there a mediation effect of advertising and R&D spending on the relationship between long- versus short-term compensation and stock market return? The authors address these questions using a combination of ExecuComp, Compustat, and Center for Research in Security Prices data on 842 firms during the 1993–2005 period. They find that an increase in the equity to bonus compensation ratio is positively associated with an increase in advertising and R&D spending as a share of sales. Advertising and R&D spending as a share of sales also mediates the effect of equity to bonus ratio on stock market return. The authors discuss implications for top management seeking to mitigate myopic management of resources by employing compensation to incentivize a longer-term orientation for advertising and R&D spending to improve stock return.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.258
Teacher spread0.236 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations107
Published2012
Admission routes1
Has abstractyes

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