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Record W1481767759

Influences on Administrative Costs in Convenience Store Chains: A Cross-Sectional Activity-Based Study

2013· article· en· W1481767759 on OpenAlexaboutno aff
Kirk Frederic Fischer

Bibliographic record

VenueAcademy of Accounting and Financial Studies journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessLotteryActivity-based costingPurchasingEconomies of scaleMarketingIndustrial organizationEconomicsMicroeconomics
DOInot available

Abstract

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ABSTRACTConvenience chains have administrative functions - largely accounting, human resource, and compliance activities - to support the business operations. Chains across the United States and Canada, while rich in operational industry benchmark data, have no data to help evaluate the appropriateness of their administrative costs.Using a mixed-methods approach built on the theoretical foundation of activity-based budgeting, data was gathered and analyzed attempting to link chain activities to administrative processes. The data gathered covered chains owning from five to seventy stores.The results show that economies of scale and automation of paperwork handling, particularly as it pertains to inside-the-store activity, yield per-store savings. Increases in chain size have more potential to increase administrative costs than increases in business complexity. Specific activities are linked to per-store administrative providing practitioners with inferential guidance as to where administrative savings can be found.INTRODUCTIONConvenience chains engage in many activities from selling lottery tickets to fresh food to gasoline. Which of these activities is likely to most increase, or decrease, administrative costs?The practical research goal is to establish a statistically sound links between chain activities and administrative costs. Academically, this comprises the first industry-specific cross-sectional activity based-budgeting study.The theoretical model for this research is activity-based budgeting (ABB), a budgeting methodology derived from activity-based costing (ABC). Unlike traditional budgeting methods, ABB focuses not on spending, but on activity; what the firm does as opposed to what it spends (McClenahen, 1995). With ABB the firm's activities form pools associated with drivers to estimate future costs. ABB's historical roots can be traced to ABC and budgeting (Abemethy & Vagnoni, 2004; Beatty, 2007; Hopwood, 1974).To accomplish its objectives this research pursues four specific outcomes: (a) A clear repeatable measurement of administrative costs; (b) the establishment of a data model materially free of intervening variables to establish valid correlations between activities and administrative costs; (c) a cross-sectional survey to collect industry data to establish an initial set of norms for subsequent comparison; and (d) results providing traceability between activities and administrative costs.RESEARCH QUESTIONWhich activity measures of a convenience chain drive administrative costs?GENERAL HYPOTHESISThe central number of interest, and dependent variable for this analysis, is per-store administrative Practical experience and anecdotal observation indicates that per-store administrative is measurably influenced by four attributes of a convenience chain - chain size, business complexity, organizational capabilities, and organization characteristics.The specific definition of administrative costs is detailed in the methodology section, but generally it could be described as headquarters cost as opposed to store cost. Per-store administrative is defined as total administrative costs divided by total company-owned, company-operated stores.Specific HypothesesFor each of the four major areas - chain size, business complexity, organizational capability, and organizational characteristics - proxies have been identified, beginning with chain size proxies.Chain SizeThere are three measures of chain size expected to influence per-store administrative costs:Smaller companies, on the whole, have been shown to bear a proportionally larger burden for administrative costs than larger companies (Nair & Rittenberg, 1983); therefore, economies of scale should emerge as the quantity of COCO stores increases.Dealer locations are those operated by independent businesses under a licensing agreement containing image restrictions and requirements to purchase fuel from the convenience chain. …

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)0.005
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.323
Teacher spread0.275 · 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 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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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