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Record W2771293785 · doi:10.1111/1911-3838.12152

Bach Music Inc.: Impact of Price Pressure, Capacity Constraints, and a Special Order on Management Decision Making

2017· article· en· W2771293785 on OpenAlexaffvenue
Ling Chu, Theresa Libby, Robert Mathieu, Ping Zhang

Bibliographic record

VenueAccounting Perspectives · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting Education and Careers
Canadian institutionsUniversity of TorontoWilfrid Laurier University
Fundersnot available
KeywordsProfitability indexLeverage (statistics)IncentiveProfit (economics)Cash flowOrder (exchange)Discounted cash flowManagement accountingEconomicsBusinessComputer scienceOperations researchOperations managementAccountingMicroeconomicsFinanceEngineering

Abstract

fetched live from OpenAlex

Abstract This case has been developed for an introductory management accounting course at the undergraduate and MBA levels. Although the setting is relatively simple, it illustrates several management accounting issues that are relevant to firms of every size that produce a product or service under competitive pressures and capacity constraints. The case also integrates several topics that are often viewed as abstract by the students. Specifically, it deals with the concepts around cost‐volume profit analysis in a realistic environment, the tension between short‐term and long‐term decisions, discounted cash flow analysis, the impact of managerial incentives and compensation on decision making and the impact of operating leverage on profitability. The case was used successfully several times in an introductory course at the MBA level. Surveys of the students reveal that the case has contributed significantly to their learning and has clarified the concepts introduced in the case.

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), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
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
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.288
Teacher spread0.265 · 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.

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

Citations4
Published2017
Admission routes2
Has abstractyes

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