SCELC Colloquium 2011 Patron Driven Acquisition Promotes Collection Use
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SCELC Colloquium 2011 Patron Driven Acquisition Promotes Collection Use
- 1. The evidence is in: Patron Driven Acquisition Promotes Collection Use Jason Price & John McDonald Claremont University Consortium SCELC Colloquium - March 2, 2011 (with thanks for data & discussion from Kari Paulson & Alison Morin of EBL)
- 2. Bananas tipped the boat: a cautionary tale Early patron-driven deal with a major platform Assignment on economics of banana plantations UC Boulder ‘bought every book with banana in the title’ Used by librarians & vendors(!) as evidence that user-driven selection is a bad idea
- 3. Patron-driven model objections:cautionary conclusions? Books will be selected based on click-thrus that don’t indicate interest Users will select ebooks that no one (else) is interested in User selected collections will be unbalanced turkeys
- 4. Definitions Purchase type Patron selected = Demand Driven = User-selected Librarian selected ≈ Library selected ≈ Pre-selected Ebook usage was measured conservatively Data reflects post-purchase use Did not count uses that lead to user-selection ‘Casual’ use eliminated 1 use ≈ 1 ‘read online’ ≈ 1 ‘download’ read online = >10 min w/click thru OR copy OR print Transaction level data each use recorded separately with user anonymously identified
- 5. Questions we’ll address Are user-selected ebooks used less often than pre-selected ebooks? Do user-selected ebooks have a narrower audience? Are user-selected collections less balanced? Do we have anything to fear in patron-driven selection? (Can we use this to build better acquisition models?)
- 6. Scope of the overall dataset 1 Ebook Vendor – EBL (Ebook Library) 11 Libraries 28,327 ebooks bought from 2006 - 2009 212,887 uses during that period Purchase Models: User Selection, Pre-Selection, or Mixed
- 7. Total Books & Usage
- 8. Total Books & Usage
- 9. Total Books & Usage
- 10. Total Books & Usage
- 11. Scope of this analysis 5 Mixed-model libraries Design Test variables: Purchase type & Library Response variables: Uses per year Unique users per year Books owned more than 6 months Inferential stats: Negative binomial regression (not shown), ANOVA
- 12. Question 1 Are user-selected ebooks used less often than pre-selected ebooks? Do user-selected ebooks have a narrower audience? Are user-selected collections less balanced?
- 15. Question 2 Are user-selected ebooks used less often than pre-selected ebooks? Do user-selected ebooks have a narrower audience? Are user-selected collections less balanced?
- 18. User-selected collections have fewer unused titles
- 19. Question 3 Are user-selected ebooks used less often than pre-selected ebooks? Do user-selected ebooks have a narrower audience? Are user-selected collections less balanced?
- 20. User-selected collections have similar subject profiles Proportion of individual collection User Pre User Pre User Pre User Pre User Pre Library
- 21. User-selected collections have similar LC profiles Blue = User selected Green = Pre selected
- 22. User-selected collection have similar YBP Content Levels
- 23. Patron vs. Librarian: Content LevelShenet al. 2011 ER&L Conference Head first into the PDA Pool…
- 24. User-selected collections have similar YBP select ratings
- 25. Patron vs. Librarian: YBP SelectShenet al. 2011 ER&L Conference Head first into the PDA Pool…
- 26. Summary Are user-selected ebooks used less often than pre-selected ebooks? No. User-selected ebooks are used 2-5x more often Do user-selected ebooks have a narrower audience? No. User-selected ebooks are used by 2-3x more unique users Are user-selected collections less balanced? No. User selected collections are similarly balanced.
- 27. Questions & Discussion Given our results – what do we still have to fear from patron-driven purchasing (at least in the EBL model)?
- 28. Thanks! Jason Price jason.price@cuc.claremont.edu John McDonald john.mcdonald@cuc.claremont.edu For more detail see: http://ccdl.libraries.claremont.edu/u?/lea,175
Notas do Editor
- Conclusions from the cautionary tale: Phrase in terms of the banana story
- Read online - Can think of as in-library useDownload – can be thought of as a checkout
- We are interested in studying how usage varies by selection method for ebooks. Ultimately, we would like to better understand if user-selected, or patron-initiated, selection for a library collection is any better or worse than librarians doing selection, either title-by-title selection or approval plan profiling. A few obvious research questions emerge: Does usage vary by who selects a book for the collection? And if so, what are the effects? If we know those effects, can we build better acquisition models? And if not qualitatively better, at least through less effort or staff commitment.
- Analysis I’ll present to day is based on 5 libraries that each employed both Pre-selection and Patron-selection
- Length of book ownership had significant effect on response variables when treated as a test variableIt was incorporated in to the response variables for simplicity, and books owned less than 6 months were ignoredTo avoid high use per year ratio due to a few uses in a short period of time— when the analysis was repeated with Books owned at least 1 year – there was no affect on the patterns or strength of the effect
- We are interested in studying how usage varies by selection method for ebooks. Ultimately, we would like to better understand if user-selected, or patron-initiated, selection for a library collection is any better or worse than librarians doing selection, either title-by-title selection or approval plan profiling. A few obvious research questions emerge: Does usage vary by who selects a book for the collection? And if so, what are the effects? If we know those effects, can we build better acquisition models? And if not qualitatively better, at least through less effort or staff commitment.
- We are interested in studying how usage varies by selection method for ebooks. Ultimately, we would like to better understand if user-selected, or patron-initiated, selection for a library collection is any better or worse than librarians doing selection, either title-by-title selection or approval plan profiling. A few obvious research questions emerge: Does usage vary by who selects a book for the collection? And if so, what are the effects? If we know those effects, can we build better acquisition models? And if not qualitatively better, at least through less effort or staff commitment.
- We are interested in studying how usage varies by selection method for ebooks. Ultimately, we would like to better understand if user-selected, or patron-initiated, selection for a library collection is any better or worse than librarians doing selection, either title-by-title selection or approval plan profiling. A few obvious research questions emerge: Does usage vary by who selects a book for the collection? And if so, what are the effects? If we know those effects, can we build better acquisition models? And if not qualitatively better, at least through less effort or staff commitment.
- We are interested in studying how usage varies by selection method for ebooks. Ultimately, we would like to better understand if user-selected, or patron-initiated, selection for a library collection is any better or worse than librarians doing selection, either title-by-title selection or approval plan profiling. A few obvious research questions emerge: Does usage vary by who selects a book for the collection? And if so, what are the effects? If we know those effects, can we build better acquisition models? And if not qualitatively better, at least through less effort or staff commitment.