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Record W2080638532 · doi:10.1108/18325910610675961

The impact of institutions on management accounting changes at the Hudson's Bay Company, 1670 to 2005

2006· article· en· W2080638532 on OpenAlexaff
Gary Spraakman

Bibliographic record

VenueJournal of Accounting & Organizational Change · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsYork University
Fundersnot available
KeywordsManagement accountingAccountingOriginalityBusinessShareholder valueCost accountingProject accountingAccounting information systemEconomicsPositive accountingFinancial accountingShareholderFinanceSociologyCorporate governance

Abstract

fetched live from OpenAlex

Purpose Aims to examine the four different management accounting systems or sets that existed at the Hudson's Bay Company (HBC) during the 1670‐2005 period with Burns and Scapens' institution‐based framework of management accounting change. Design/methodology/approach A case study was used with comprehensive archival evidence coming mainly from the Hudson's Bay Company Archives (HBCA) and the HBC's private archive for 1670‐1970 and from interviews with retired and existing senior managers at the HBC for 1970‐2005. Findings The findings indicated that Burns and Scapens' framework was helpful. Institutions did prevent management accounting changes, even when seriously needed. Under certain conditions, institutions do not resist management accounting changes. Six suggestions are provided for extending and refining Burns and Scapens framework. Research limitations/implications Although the 325 years of evidence was uniquely rich, it was still a case study of a single firm. Practical implications Management accounting is slow to change because of institutions. Originality/value Management accounting change is very much path‐dependent. Changes occur in management accounting because of major external changes such as competition and modernization. Also, management accounting changes come from the introduction of taken‐for‐granted external techniques such as budgeting, capital budgeting, and planning.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.023
GPT teacher head0.255
Teacher spread0.232 · 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

Citations33
Published2006
Admission routes1
Has abstractyes

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