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Beguiled by Bananas :  A retrospective study of the usage & breadth of patron vs. librarian acquired ebook collections Jason Price & John McDonald Libraries, Claremont University Consortium November  5, 2009 (with data & discussion from  Kari Paulson & Alison Morin of EBL)
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
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
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 led 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 but permanently identified
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?)
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
Total Books & Usage
Total Books & Usage
Total Books & Usage
Total Books & Usage
Scope of this analysis 5 Mixed-model libraries only 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
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?
Librarian  Acquired
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?
User-selected collections have fewer unused titles
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?
User-selected collections have similar subject profiles  Proportion of individual collection User Pre	   User Pre	      User Pre	        User Pre             User Pre Library
User-selected collections have similar LC profiles Blue = User selected Green = Pre selected
User-selected collections have similar LC profiles
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 by subject? No.  User selected collections are similarly balanced.
Questions & Discussion Given our results – what do we (still) have to fear from patron-driven purchasing  	(at least in the EBL model)?
Thanks! Jason Price jason.price@cuc.claremont.edu John McDonald john.mcdonald@cuc.claremont.edu Kari Paulson kari.paulson@eblib.com

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Demand vs Pre-Selected Ebook Usage

  • 1. Beguiled by Bananas : A retrospective study of the usage & breadth of patron vs. librarian acquired ebook collections Jason Price & John McDonald Libraries, Claremont University Consortium November 5, 2009 (with 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 led 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 but permanently 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
  • 10. Total Books & Usage
  • 11. Scope of this analysis 5 Mixed-model libraries only 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?
  • 13.
  • 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?
  • 16.
  • 17.
  • 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 collections have similar LC profiles
  • 23. 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 by subject? No. User selected collections are similarly balanced.
  • 24. Questions & Discussion Given our results – what do we (still) have to fear from patron-driven purchasing (at least in the EBL model)?
  • 25. Thanks! Jason Price jason.price@cuc.claremont.edu John McDonald john.mcdonald@cuc.claremont.edu Kari Paulson kari.paulson@eblib.com

Editor's Notes

  1. Conclusions from the cautionary tale: Phrase in terms of the banana story
  2. *Read online - Can think of as in-library use*Download – can be thought of as a checkout*Combined these, but ignored all casual use – i.e. click in and click out never counted;Every use indicates true interest in the content: a click through saying I want to continue to view, or a copy command or a print command*The ability to eliminate casual usage (ie browsing) from EBL use data distinguishes it from all other e-resource use data that we’re aware of
  3. *Length of book ownership had significant effect on number of uses and users per book*For simplicity, it was incorporated in to the response variables (i.e. uses per year, and unique users per year) *Books owned less than 6 months were ignored to 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 pattern or strength of the effects
  4. *In all subsequent slides user books from user selected collections are in blue, and those from preselected collections are in green*Overall Average number of uses per year in general quite high ≈ 6 per year *Average number of post-purchase uses per year is significantly greater for user-selected ebooks (2x as high) *Even though the total number of books (n) in the user selected set is greater, this has no effect on the result—these are PER BOOK averages, so each book in the user selected collection is used an average of 8.6x per year, andeach book the preselected collection is used an average of 4.3x per year*This result rejects the hypothesis rejects the hypothesis that users will select ebooks will be used less than pre-selected ebooks
  5. *Pattern of greater use for user-selected books is consistent across all 5 libraries: 4 of 5 are significantly different based on non-overlapping 95% confidencec intervals*degree of difference varies from 1.75x to 4.5x
  6. *This figure shows for the number of unique users per ebook per year for the overall user selected and preselected collections*The average user-selected ebook was used by a significantly greater number of different users per year (about 2x as many)*These data allow us to result rejects the hypothesis that users select books that are only of interest to themselves
  7. *Here we see that pattern of wider use of user-selected ebooks is also consistent across the 5 libraries, with the same 4 libraries showingsignificantly wider useThe degree of this effect varies from 1.75x to 3.3 times more unique users per book per year in user-selected collections
  8. *Print book collections are often assessed by the percentage of their books with 0 checkouts*Here we report the percentage of books with zero use in discrete collections formed under both acquisition models*In every case more than 90% of the books had been used at least once, and in 4 out of 5 libraries, fewer books went unused in the user driven collections*On average there were about 6x as many unused books in the pre-selected collections
  9. *At a broad disciplinary level, 4 of 5 libraries had similar subject profiles for the collections built under the two acquisition models*For the one library (K) where the profiles appear to be different, the preselected collection seemed to over-emphasize Sci&Tech books vs their user selected collection
  10. At a slightly more granular level, subject profiles of the two types of collections also appear to be similar
  11. Same data in tabular form with a few additional classes included