How do corporate information managers assess the quality of information and select online sources: evidences from a fieldwork research with 53 Belgian executives
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Presentation of the paper I submitted ti IR9.0 conference at ITU of Copenhagen. It present the evidence of a perceived shift in the information quality assessment by corporate information specialists (competitive intelligence, environmental scanning, etc. )
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How do corporate information managers assess the quality of information and select online sources: evidences from a fieldwork research with 53 Belgian executives
- 1. Information Quality © Jeremy Depauw 2008 Assessment and Source Selection on the internet Fieldwork research with 50 competitive intelligence professionals in Belgium Jeremy Depauw jdepauw@ulb.ac.be
- 3. ??
- 4. What if... ‣ On a blog? © Jeremy Depauw 2008 ‣ On a wiki? ‣ Via a podcast? ‣ Via an item from a file sharing platform? ‣ Via an item from a social network site? Would you change your information quality assessment strategy?
- 5. Corporate Information Management Alert threats and opportunities © Jeremy Depauw 2008 Collect Treatment Mediation CIM support in Decision Making Distribution Influence actions
- 6. Research design • 50+ interviews with IM pros in Belgium • Relative importance of criteria (Cooke’s checklist - 2001) • Blogs, wikis, podcasts, file sharing, social networks © Jeremy Depauw 2008 • Objective, coverage, autorithy, accuracy, currency, accessibility, presentation, ease of use, comparison • +, -, = BLOG WIKI POD FS SN OBJ-1 Criterion_01 + + = = - Criterion_02 - - = = = Criterion_03 + - + = +
- 7. Data structure ‣ 360 observed variables © Jeremy Depauw 2008 • Ordinal • 3 modalities ‣ Frequencies of answers (ALL, FORMATS, CAT) ‣ Scores (ALL, FORMATS, CAT) ‣ Indices
- 8. Dealing with Frequencies Frequency < 17% Frequency > © Jeremy Depauw 2008 26% Frequency = 57%
- 9. Dealing with Frequencies ALL SN POD FREQ_< WIKI © Jeremy Depauw 2008 FS BLOG FREQ_> PRES CUR EASE FREQ_= COMP ACCESS AUT COV ACC OBJ
- 10. Dealing with indices Scope Min Max Mean Std. Dev Index Frequency < Frequency = Frequency > ALL_ 405 489 894 686,4 66,803 63,56 BLOG 83 91 174 135,55 15,382 62,75 © Jeremy Depauw 2008 WIKI 68 112 180 141,38 12,472 65,45 OBJ 11 46 43 POD 100 80 180 136,87 16,402 63,37 FS 98 82 180 135,53 17,271 62,75 COV 16 51 33 SN 70 110 180 137,08 14,285 63,46 AUT 15 54 31 OBJ 21 24 45 34,92 5,106 77,6 ACC 16 48 36 COV 60 60 120 86,79 11,011 72,33 AUT CUR 14 62 25 50 40 90 64,96 8,685 72,18 ACC 47 43 90 66 9,794 73,33 CUR 55 50 105 73,94 10,803 70,42 ACCESS 25 56 20 ACCESS 121 74 195 126,77 19,06 65,01 PRES PRES 15 65 20 70 55 125 92,11 13,725 68,23 EASE 60 55 115 89,25 12,476 66,11 EASE 21 61 19 COMP 52 41 93 69,75 10,425 42,27 COMP 12 59 29 Content related/form related criteria
- 11. Discussion & Follow up ‣ No generalization ambitions © Jeremy Depauw 2008 ‣ Weak explicative power ‣ Phase 2 - 14 semi-directed interviews • Investigates the reasons of the perceived shift in IQ assessment process. • Under analysis
- 12. Key take-aways ‣ IQ & Web 2.0: Perceived shift supported © Jeremy Depauw 2008 ‣ Formats: no impact on the perceived shift ‣ Criteria: impact on the perceived shift • Content-related criteria are seen as more challenging on Web 2.0 formats • Form-related criteria are seen as less challenging on Web 2.0 formats.