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Tecnologias contábeis, decisões coletivas e gestão de risco nas relações de suprimento de gás liquefeito de petróleo

2012· dissertation· pt· W1828528361 on OpenAlexaff
Beatriz Fátima Morgan

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsBoundary objectBusinessSupply chainSpace (punctuation)Operations managementAccountingEngineeringComputer sciencePolitical scienceMarketingLaw

Abstract

fetched live from OpenAlex

This research discusses how accounting technologies contribute to construct collective decisions for operational risk management across the supply relationships. Decision construction is seen as a process and the collective is formed by humans and nonhumans. The accounting technologies are approached as inscriptions and boundary objects. The inscriptions mediate the action at a distance and simplify complex objects making them separate entities that act as boundary objects (LATOUR, 1987; The concept of risk in the literature presents ambiguities. The way to manage it is problematized in the accounting literature on inter-organizational relationships. The field study was conducted in liquefied petroleum gas supply relations which involve the oil company, the transport suppliers and the distribution company. The information was obtained from the perspective of the latter, through ethnography which included interviews, observations and shadowing of objects and people, and narrative analysis permeated by deconstructive analysis was employed. Initially we identified the threats that can cause shortage of the product in production unit in the distribution company. Not all threats found are possible to transform into an object to risk management. To do this they must be inscribed and accumulated in the management of suppliers that acts as a center of calculation. However, many are intertwined with other factors and have unexpected effects on the dimensions of space and time. The accounting standard technologies, such as long-term planning and budgeting, when used alone they do not have enough force to mobilize interventions to reduce risk. On the other hand, the conflicts generated when both are combined to propel the search for other information that results in a more precise figure. In the relations studied, the risks increase in short term in contrast to long term as seen in the literature. Thus, the technologies built in practice, exert force to mobilize immediate decisions. Although contractually the partnership for gas supply to be signed by two companies, which on one side is the supplier and the distributor on the other, in day-to-day activities multiple relations are built among production units, refineries and supply area. In this way, inscriptions such as purchase orders are able to redefine the boundaries. They translate to act as instruments of operational risk management. Trust manifests itself as a quasi-object Thus, the risk of shortage of the product presents itself as a "ghost" that can be materialized depending on information flows. This study contributes empirically by showing the risks involved in the supply relations of petroleum liquefied gas throughout the Brazilian territory, and how accounting helps to manage them. Furthermore, it extends the knowledge on how the information flows occur in an inter-organizational setting, as well as the adoption of hybrid practices to achieve collective actions to manage supply risks and build relations. Theoretically, the study contributes to the discussion of the risk concept and how the accounting is associated with this concept.

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)0.007
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.070
GPT teacher head0.384
Teacher spread0.314 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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