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Record W7132870374

Essays in Industrial Organization and Inventory Management

2024· dissertation· W7132870374 on OpenAlexaboutno aff
Francis Guiton

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsnot available
Fundersnot available
KeywordsIncentiveOrder (exchange)DecentralizationProcess (computing)PortfolioStrategic business unitProduct (mathematics)Organizational unitInventory management
DOInot available

Abstract

fetched live from OpenAlex

This thesis investigates managerial decision-making within the framework of the inventory management of a multi-establishment firm. Through a combination of descriptive analysis, reduced-form evidence, and structural modelling, the research aims to understand how decisions made by managers at the business unit level can have an impact on the overall performance of a decentralized organization. Specifically, this thesis examines the intricate vertical relationship between local managers and the firm's headquarters in order (1) to understand the impact of manager ability in different organizational structures, and (2) to quantify the impact of a misalignment between the objectives of the firm and the objectives of its managers due to within-firm competition. The findings of the research offer valuable insights into the trade-offs associated with decentralization in large organizations, and provide evidence of the overall impact on the firm's profits from aligning the strategic incentives of managers with its own goals. The first chapter provides a detailed description of the empirical setting studied in this thesis: the Liquor Control Board of Ontario. An overview of the organization's history and its institutional details reveals how the company has become one the largest retailers of beverage alcohol in the world, and how it now operates as a large multi-divisonal organization with a decentralized inventory management structure. A descriptive analysis of the organization's product portfolio decisions -- the process of introducing new products and delisting existing products -- describes the crucial top layer of the inventory management process in the organization, and shows how the company interacts with producers in order to provide consumers with a continuously evolving selection of products. The second chapter, based on joint work with Victor Aguirregabiria, investigates the impact of decentralizing inventory decision-making in multi-establishment firms. The findings show significant heterogeneity among the inventory decisions made by the store managers in the retail chain. Specifically, a dynamic structural model reveals substantial differences in managers’ perceived costs, and a correlation between the variance of these perceptions and the education and professional experience of managers. Counterfactual experiments then show that centralizing inventory management reduces costs by eliminating the impact of managers’ skill heterogeneity. However, these benefits are largely offset by the negative effect of delayed demand information. The third chapter examines how the objectives of managers can be misaligned with the overall objectives of the firm. In particular, the chapter investigates how competitive interactions between store managers in a decentralized retail chain can lead to sub-optimal outcomes from the point of view of the organization. The structural estimation of a game of product assortment decisions shows that store managers do not fully internalize the impact of their inventory decision-making on the overall organization. Findings also reveal that the extent to which store managers behave in their own self-interest is correlated with the size of their store and the number of stores they compete with. Counterfactual experiments then show that this misalignment of objectives implies a substantial loss in profit for the firm, but a negligible effect on consumer welfare. However, enhancing the role of district managers, who are responsible for overseeing store operations within a defined geographic area, can mitigate within-firm competition and provide consumers with greater product variety.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0020.007
Scholarly communication0.0040.004
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.027
GPT teacher head0.269
Teacher spread0.242 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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