Information Professionals’ Attitudes Influence the Diffusion of Information and Communication Technologies
Notice bibliographique
Résumé
A Review of:
 Rabina, D. L., & Walczyk, D. J. (2007). Information professionals’ attitude toward the adoption of innovations in everyday life. Information Research, 12(4), 1-15. 
 
 Objective – This study examined the general characteristics and patterns of librarians in connection with their willingness to adopt information and communication technologies.
 
 Design – Online questionnaire. 
 
 Setting – General distribution to information professionals through online inquiry. More than 70% of responders worked in public or academic libraries.
 
 Subjects – Librarians and library staff at mostly public and academic libraries.
 
 Methods – The study was conducted during a two week period in April 2006 through an online questionnaire that was sent to library and librarian-related electronic mail lists. The questionnaire was divided into two parts and contained a total of 39 questions. Part one contained eight questions that asked for demographic data and the respondent’s daily attitude toward the adoption of information and communication technologies. Questions regarding age, number of years worked in a library, career, type of library environment worked in, and primary responsibilities within that environment were asked. For one question the respondents were asked to identify which of the categories they fall under when adopting a new technology. The results from part one were used to consider the innovativeness of librarians. The results from part two were used for a study of opinions on innovations and their relative advantage. 
 
 Main Results – A total of 1,417 responses were received. Of those, 1,128 were fully completed and considered valid and used for inquiry. The majority of respondents worked in public or academic libraries. Nine hundred and twenty-six respondents, or 88%, were from the U.S. and represented more than 300 distinct zip codes. Two hundred and two respondents, or 12%, were international respondents. 
 
 This study notes that the sociologist, Everett Rogers, identified and defined five adopter categories in 1958. Those categories are: innovators, early adapters, early majority, late majority, and laggards. The findings of this study indicate that regardless of the demographic variables considered, more than 60% of respondents, the majority of librarians surveyed, fall into two contrasting adapter categories: early adopters and early majority. The study suggests that the efficient and effective diffusion of new technologies in library settings may be difficult. Three problematic areas among librarians for the dissemination of innovation were identified: conflicting opinions among multiple opinion leaders, deceleration in the rate of adoption, and improper re-invention. The findings of the study also suggest that “contrary to common beliefs, librarians in academic or special libraries are no more innovative than public or school librarians” (Conclusion, ¶3). 
 
 Conclusion – The study concludes that librarians’ attitudes are unevenly distributed with most either accepting new innovations or being late adopters. The variables of age, role, tenure, and library type had little impact on the approach of the professional toward innovation. The identification of the three problem areas: opinion leadership, deceleration of adoption, and improper re-invention, represents where more time and effort may need to be spent to make the implementation of new technology a smoother process.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,556 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».