Experiences with a Sales Districting Model¶
Hess, S. W., & Samuels, S. A. (1971). Experiences with a Sales Districting Model: Criteria and Implementation. Management Science, 18(4).
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Receptive Field
- Sales-territory algorithms (k-means over customer locations weighted by revenue density) and key-range sharding algorithms are formally the same receptive-field tiling problem with the same load-balance constraint, so a distributed-systems engineer and a sales-operations analyst are solving one problem.
This sourceFormulates sales-territory design as a districting optimization over customer locations weighted by demand — structurally a coverage-tiling problem with a load-balance constraint.
Supported in partVerified against the publisher's abstract
The abstract documents sales districting as a coverage-and-workload-balance problem over weighted activity measures, but says nothing about k-means, key-range sharding, or any formal identity between the two.
“Better coverage, fairer work load and change in size of sales force, —criteria for measuring “good” districting: Single, multiple and weighted measures of salesman activity”
- Sales-territory algorithms (k-means over customer locations weighted by revenue density) and key-range sharding algorithms are formally the same receptive-field tiling problem with the same load-balance constraint, so a distributed-systems engineer and a sales-operations analyst are solving one problem.
Verification¶
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Registry ID ref:48ffe38db044 · see in the full table