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Record W7071447567

Three Essays on The Interface of Sales and Operations Management

2021· article· en· W7071447567 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMachine Learning in Bioinformatics
Canadian institutionsnot available
Fundersnot available
KeywordsSupply chainExploitProfit (economics)Supply chain managementChannel (broadcasting)Flow networkMaximizationProfit maximizationAttractivenessService qualityProcess (computing)
DOInot available

Abstract

fetched live from OpenAlex

This dissertation investigates three profit maximization models for coordinating Sales and Operations (S\\&OP) management.\nThe first problem considers implementing a customer education strategy for the digital channel users of a multi-channel service provider. Using a customer network flow model, I investigate the effect of customer education in the digital channel on the number of users of digital and in-person channels. Further, I define a customer value metric that characterizes the optimal level of education effort. Finally, I determine conditions under which the effect of positive word-of-mouth regarding the quality of education dominates the lifetime value of customers.\nThe second problem studies a supply chain in which a distributor procures perishable products, transports them along the supply chain through distribution centers, and sells them at retail stores. The objective is to jointly optimize quality-based transportation decisions and pricing policies. I propose two frameworks to study this problem under sequential and integrated systems. Pricing and transportation decisions are made separately and then coordinated through an iterative process in the sequential model but jointly optimized in the integrated system.\nI exploit the special structure of the integrated model formulation and develop a decomposition-based solution method. I tested the model and solution methodology on a lettuce product distribution network in Eastern Canada.\nFinally, the third problem investigates the category space allocation at the macro-level and explores how considering location-based and product-based attractiveness can improve a retailer's overall space profitability. I consider both location-based and product-based attractiveness factors in a mixed-integer quadratic problem. As large-scale instances of this problem are computationally challenging to solve, I further provide a decomposition-based heuristic solution method for solving large instances of the problem.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.007
Scholarly communication0.0070.008
Open science0.0010.002
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0110.003

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 head0.010
GPT teacher head0.237
Teacher spread0.227 · 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 designSimulation or modeling
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

Citations1
Published2021
Admission routes1
Has abstractyes

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