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Record W2236018726 · doi:10.2478/gfkmir-2014-0074

Preparing for the Adoption of the New Arrival

2009· article· en· W2236018726 on OpenAlexaff
Raquel Castaño, Mita Sujan, Manish Kacker, Harish Sujan

Bibliographic record

VenueGfK Marketing Intelligence Review · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement, Economics, and Public Policy
Canadian institutionsMcMaster University
Fundersnot available
KeywordsProduct (mathematics)MarketingBusinessWelfareEconomics

Abstract

fetched live from OpenAlex

Abstract The emotional state of many expecting parents shifts from unbridled joy to anxiety as the reality of learning to care for a newborn and forsaking their current lifestyle sinks in. Similarly, consumers have different concerns when they first hear about a new product compared to the time when they consider buying it. If the buying decision is in the distant future, consumers are primarily concerned with the benefits derived from using the product, such as how the product performs and symbolic benefits of owning the new product. As the buying decision draws closer, consumers shift attention to cost-related issues, such as how long will it take to learn how to use the product or how much will it cost to maintain and use it. Executing a two-phased communication strategy by management that is synchronized with this shift in mental processes by first emphasizing new product benefits and features and later focusing on the practical aspects of using the innovation can have a beneficial impact on both organizational performance and consumer welfare

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.041
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0410.012

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 head0.034
GPT teacher head0.278
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2009
Admission routes1
Has abstractyes

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