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Enregistrement W2152400726 · doi:10.18438/b8x32x

Labour Costs for Inventory Control Less Expensive than Repurchasing

2010· article· en· W2152400726 sur OpenAlexaffvenue
Laura Newton Miller

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2010
Typearticle
Langueen
DomaineComputer Science
ThématiqueLibrary Collection Development and Digital Resources
Établissements canadiensCarleton University
Organismes subventionnairesnon disponible
Mots-clésLaptopComputer scienceEconomic order quantityOrder (exchange)Inventory controlBarcodeLibrary scienceOperations researchInterlibrary loanCollection developmentControl (management)World Wide WebDatabaseBusinessMathematicsMarketingOperating systemFinanceArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

A Review of: Sung, J. S., Whisler, J. A., & Sung, N. (2009). A cost-benefit analysis of a collections inventory project: A statistical analysis of inventory data from a medium-sized academic library. Journal of Academic Librarianship, 35(4), 314-323. Objective – To describe an inventory system that was created within the library and to show the cost-effectiveness of using the inventory system compared to the price of reacquiring mis-shelved books. Design – Bibliometric study and cost-benefit analysis. Setting – Medium-sized academic library in a rural community of the United States. Subjects – Approximately 300,000 books from LC classifications D through H, N, P and Q, representing two thirds of the library’s entire monograph collection. Methods – The library created its own electronic inventory and shelf-reading program, using a laptop computer equipped with a hand-held scanner, to scan barcodes in the stacks. Library staff used the Microsoft Access database to update two files containing a shelf-list and an active-status list while the books were scanned. The program alerted the worker if books found had an active status (i.e., Missing, Renewed, Overdue, Charged), were not in the correct order, or were not in the system. Each transaction created a log which contained a time stamp (to the second), the call number and the barcode number. It also took note of scanning errors, books that were out of order, and books that were not on a shelf-list. After a complete section was examined, a list was produced to reveal the distance of mis-shelved books from their correct location and the amount of time between each scan. The researchers used statistical analysis (using SPSS 15.0) to measure scan speed for each scan, mis-shelving rate and error distance of each mis-shelved book. In order to analyze the cost of labour to replace a book versus the cost of inventorying, the researchers estimated the salary costs of staff members involved in selection, acquisition and cataloguing. The library spent $440,000 USD in labour costs to purchase 15,000 monographs in one fiscal year (approximately $30.00 USD in labour costs per book). They multiplied this by 5300 books that were found to be “badly” mis-shelved (found beyond 25 books away from the proper position). Labour fees were used to determine costs of inventorying by calculating average scanning speed and cost per hour to pay someone to scan the entire half-million monograph collection. Main Results – It took approximately 707 hours to scan 305,000 monographs. The average (mode) calculation for scans was 5 seconds for 80% of the barcodes, with an average (mean) of 8.35 seconds between scans. The longest average (mean) time for scanning barcodes was in the N section, followed by G, H, P, Q, D, E and F. A total of 291 books were found on the shelves with an “active” status (i.e., Charged (4), Overdue (7), Renewed (4), In Transit (24), and Missing (228)). Twenty-four books with the status “Miscellaneous” (i.e., At Bindery, Call Slip, Cataloguing Review, Damaged, and Mending) were also found on the shelves. Of the 15 active books in the categories “Charged”, “Overdue” and “Renewed”, ten were found in the proper position on the shelf. Of the 228 “Missing” books, 30% were scanned in the correct location, 10% were found 26 to 100 books away, and half were located over 100 books from their proper location. In addition to the books already marked as “Missing” in the catalogue, there were 516 books (.17% of the entire scanned section) still not found on the shelf after three searches over a period of 6 months. Of the 291 active status books found on the shelves, 52% were reused as of July 2008. (The inventory was completed at the end of 2006). Over 36% of books mis-shelved further than 25 books from their correct location were reused. However, among all books scanned, only 17% were reused during the same time period. The researchers noted that inconsistencies between the call number as shown on the book label and how it appeared in the catalogue occurred 565 times. Of these discrepancies, 40% of the labels resulted in books being misplaced ten or fewer books away, 10% misplaced between 10 and 100 books away, and 35% misplaced more than 100 books away from the correct position. In general, 82% of mis-shelved books were found within 1 to 25 books away from their correct location. By calculating that 5300 books were mis-shelved beyond 25 books away from their proper position, labour costs were estimated to be at least $159,000 USD (5300 x $30.00 USD per book in labour costs). Costs for interlibrary loan were calculated at approximately $30.00 USD per transaction, and patron’s time wasted trying to locate misplaced books was estimated at 30 minutes per book. This was much more than the labour costs associated with scanning books, which at an average speed of 8 seconds per book and $10.00 US per hour for scanning worked out to be 2.2 cents per book, or $11,000 USD to scan the entire half-million monograph collection. Conclusion – The results appear to reveal that the labour costs for inventory control are less expensive than repurchasing or borrowing the same number of books.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,010
score de la tête « metaresearch » (Gemma)0,042
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,075
Score d'incertitude au seuil0,250

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0100,042
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0050,005
Études des sciences et des technologies0,0020,005
Communication savante0,0120,010
Science ouverte0,0030,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0750,013

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,239
Écart entre enseignants0,224 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2010
Routes d'admission2
Résumé présentoui

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