Predicting faculty members’ adoption of online databases by diffusion theory approach

G D M N Samaradiwakara

ICASS - Malaysia

04-11-2014

A case study at the University of Sri Jayewardenepura in Sri

Lanka

Introduction

• Scholarly databases have been playing a crucialrole in the creation and diffusion of knowledge byserving as the key media of scholarlycommunication

• The rapid development of novel technologies hasinfluenced the expansion of new forms ofscholarly communication giving a plenty ofbenefits

• Their impact on libraries and scholars isnoteworthy and unprecedented together.

Online databases at Jayewardenepura University

The Library of the University of SriJayewardenepura (USJP) startedprovision access to online databasesin 2002 under the InternationalNetwork for the Availability ofScientific Publications (INASP) whichis a foreign collaborator formed tosupport libraries since many years.

• Library used to continue electronic access toscholarly databases under individual purchasing inpackaged deals, UGC consortia purchasing andthrough funding agents leading to anticipate theextinction of print journals.

• Currently 11 scholarly online databases includingEmerald, JSTOR and Sage Publications areavailable.

• By observation, the adoption rate of these onlinedatabases is seen to be lower for last year

• Librarians are having efforts to maintaincontinuous access to afford a convenient meetingof information needs of their users with yearlyincreasing budget demands of publishers under apressure with unexpected low rate diffusion.

• At the users’ end, they have brought into attentiononline databases’ potential pleasure and tendencytowards content and context together withacquiring essential skills and abilities needed to usethem.

Problem

• Rogers’ theoretical underpinnings provide astrong base to explain the effect of well setfactors on the diffusion of an innovation.

• Hence, this study aims to predict the universityfaculty members' adoption of online databaseservices based on the Rogers’ attributes;relative advantage, compatibility, complexity,triability and observability.

Study aims

• to identify the awareness of online databases

• the purpose behind using them and

• to investigate the effect of predictors on facultymembers' perceptions and adoption rate of onlinedatabases.

Objectives of the study

Theoretical underpinning

• The primary intention of DoI theory is to providean account of the manner in which anytechnological innovation moves from the stage ofinvention to widespread use (or not).

• It initiated in communication to elucidate how,over time, an idea or product gains momentumand diffuses (or spreads) through a specificpopulation or social system. The outcome of thisdiffusion is that people, as part of a social system,adopt a new idea, behavior, or product.

• In the process which person adopts an innovationand whereby diffusion is accomplished, he/shepasses five steps; (1) knowledge or awareness ofan innovation, (2) forming an attitude toward theinnovation, (3) decision to adopt or reject, (4)implementing the innovation by initial use, and(5) confirmation of this decision by continued use

Rogers constructed five main attributes that impactsthe adoption of an innovation;• Relative Advantage - The degree to which an innovation is seen as

better than the idea, program, or product it replaces.

• Compatibility - How consistent the innovation is with the values,experiences, and needs of the potential adopters.

• Complexity - How difficult the innovation is to understand and/oruse.

• Triability - The extent to which the innovation can be tested orexperimented with before a commitment to adopt is made.

• Observability - The extent to which the innovation providestangible results.

Conceptual framework of the study

Knowledge Personal characteristicsSocial characteristicsPerceived need

Perceived characteristics of innovation

Relative advantageCompatibilityComplexityTriabilityObservability

Adoption rate

Conceptual framework indicates the factors affect inpredicting the adoption of online databases as knowledge ofthe receiver and the characteristics of the databases whichshould be suited at users’ end.

Research design and methodology

• Target population is the total number of lecturesin four faculties in the USJP.

• The total number of lecturers in the university is474 and the sample size was 212 subjects.

• The research is designed to adopt the surveyresearch strategy and therefore structuredquestionnaire is used as the data collectingmethod.

Results and interpretation

• Response rate was 35.38% and the reliability toperform statistical tests achieved

• The highest percentage of the respondents (36%) were from the Science faculty

• 52% males and 48% females

• Majority of the respondents were in the seniorlecturer category (57.3%)

• Most of the academic staff members (48%) werebetween the age of 41-50 years.

Personal characteristics

• Majority of the academic staff members (56%) inthe USJP were in the high computer competencylevel.

• Majority of faculty members (91.9%) preferred touse electronic format.

• Most of the respondents (39.4%) have 5-10 yearsexperience using online databases

• Majority of the respondents (45.1%) were in a'Good' experience level with using onlinedatabases.

Social characteristics and the perceived need

• Most of respondents (85.3%) were aware aboutonline databases.

• Further, 92% of respondents agreed with theavailability of computer and Internet facilities inthe university and a majority of the staff members(62.7%) were satisfied with the facilities

• The perceived need for the adoption of theinnovation mostly confined on scholarly needs.

Perceived characteristics of the onlinedatabases

• Twenty one (21) attributes could be extracted into five main factors: relative advantage,compatibility, complexity, triability andobservability introduced by Rogers (2003).

• Approximately, 72% (71.918%) of the diffusionvariance of online databases explained by thosefactors

• The benefits of the online database innovation comparedto the offline practices, motivate the diffusion of usingthem.

Factor Variable with the highest mean rankMean rank

Chi-square value

Significance (p-value)

Relativeadvantage

Online databases make academic workmore interesting

3.80 15.206 0.010

Compatibility Information retrieved via onlinedatabases has authenticity like printmaterials

3.33 13.762 0.008

Complexity It is very difficult to obtain the advanceservices of online databases

1.69 11.364 0.001

Triability Trying to use online databases is a goodidea

2.64 69.667 0.000

Observability Online databases can be accessedsimultaneously by many people

3.37 20.543 0.000

Adoption rate

Database Usage percentage

American society of agricultural & Biological Engineers 7.2%

Emerald 42.0%

JSTOR 53.6%

Mary Ann Liebert, Inc. Publications 2.9%

Oxford Journals 33.3%

Research for life HINARI, AGORA, ARDI, OARE 30.4%

Sage Research Methods 43.5%

Symposium journals 20.3%

Taylor and Francis 30.4%

World Bank Policy Research Working Papers 13.0%

Other 39.1%

Very frequently

34%

Frequently35%

Occasionally28%

Rarely3%

Usage frequency of online databases

The adoption rate of the

online databases were

measured through the

frequency of using them

and majority of the

respondents (35%) were

used them 'frequently'

followed by 34% used

'very frequently'.

Predicting adoption rate using Rogers' factors

• All five predictors were affected negatively orpositively for the diffusion of online databaseadoption among the faculty members in the USJP

• While compatibility and the complexity havenegative correlations with individuals’ adoptionrates, relative advantage, observability andtriabilly have positive correlations

• Then the stepwise linear regression analysis was employed to findout the stronger predictors of online database adoption rate of theuniversity faculty members.

Predictors in the

model

Unstandardized

Coefficients

Standardized

Coefficients t Sig.

B Std. Error Beta

(Constant) 4.052 .093 43.726 .000

Relative Advantage .396 .092 .488 4.314 .000

Observability .356 .097 .417 3.682 .001Dependent Variable: Access frequency

Concluding Remarks

• Faculty members in the USJP were mostly knowledgeableabout the online database innovation

• While compatibility and the complexity have negativecorrelations with individuals’ adoption rates, triabilly hasa positive correlation.

• To take full reward of electronic resources it isrecommended to make possible programs to facilitatefaculty members' adoption and the understanding ofonline databases.

• Relative advantage and observability are the keyfactors for diffusion of this innovation with higherpositive correlations.

• More and more benefits and the tangiblesophistication may lead adoption of innovation.

Thank you!