Tecnologias contábeis, decisões coletivas e gestão de risco nas relações de suprimento de gás liquefeito de petróleo
Bibliographic record
Abstract
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;LAW, 1986;STAR;GRIESEMER, 1989).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 (MOURITSEN; THRANE, 2006) which comes into existence when information is circulating between the parties.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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".