16janellerose

60 %
40 %
Information about 16janellerose
Education

Published on January 17, 2008

Author: Susett

Source: authorstream.com

Predicting Mature Consumers’ Attitude and Behaviour Towards Using Self-Service Banking Technologies:  Predicting Mature Consumers’ Attitude and Behaviour Towards Using Self-Service Banking Technologies Janelle Rose James Cook University Gerard Fogarty University of Southern Queensland Purpose of study :  Purpose of study How do key determinants influence mature consumers’ attitude towards using, intention to use and actual usage behaviour of SSTs? context mature consumers – 50 years and older use of self-service banking technologies (SSBTs) EFTPOS, ATMs, telephone banking & Internet banking justification growing population financially powerful group strong need for financial service lowest adoption rate of SSBTs limited mature consumer research Theoretical background to study:  Theoretical background to study development of research employee acceptance of information technologies (start in 70’s; Davis, Bagozzi & Warshaw 1989; Moore & Benbasat 1995; Agarwal & Prasad 1997; Venkatesh 2000; Venkatesh & Davis 2000; Venkatesh et al. 2003) individual acceptance and use of technologies (Plouffe, Vandenbosch & Hulland 2001; Taylor & Todd 1995) self-service technologies (SSTs), technology customer interaction (Meuter et al. 2005, Currran & Meuter 2005, Curran, Meuter & Surprenant 2003; Dabholkar & Bagozzi 2002; Walker et al. 2002; Wang et al. 2003) Core research model:  Core research model Technology acceptance model (TAM) (Davis, Bogazzi & Warshaw 1989) extended TAM (ETAM):  extended TAM (ETAM) Subjective Norm Actual usage Behaviour SSTs + + Research design and method:  Research design and method in-depth interviews (10 non-users & 6 users) focus groups (2 groups each of non-users & users) literature and qualitative stages to develop the measurement scales (Netemeyer, Bearden & Sharma 2003) self-administered questionnaire measurement scales: multi-item Likert scales sampling frame: consumers over 50 years of age & registered QLD COTA National Seniors database proportional stratified random sample, 600 respondents selected by 8 age categories effective response rate of 35% (208 responses) Respondent profile:  Respondent profile age ranged from 50 to over 85 years of age (25% 70+) 36% male; 64% female 67% married and 62% living in a 2-person household household income < $9 000 to >$60 000 education : junior or lower 47%; senior, skill, diploma 38%; degree or higher 15% 48% retired; 16% employed full time 52% managerial or professional occupations; 25% service, clerical, sales (current or previous) respondents from rural, regional & capital city location Use of SSBTs & face-to-face banking:  Use of SSBTs & face-to-face banking 19% (40) non-users; 19% (40) low users (<55% use of SSBTs); 62% (128) medium-to-high users (≥55% use of SSBTs) EFTPOS 56% ATMs 67% Telephone 41% Internet 15% Face-to-face 94% Summary of measurement scales:  Summary of measurement scales Scale analysis:  Scale analysis measurement scales tested for unidimensionality index - perceived ease of use; perceived risk; self-efficacy composite measures reliability >.80 path model tested - AMOS 6.0; maximum likelihood estimation method Extended Technology Acceptance Model:  Extended Technology Acceptance Model Fit Indices χ2 = 24.5 df = 14 (p = 0.04) CMIN/df 1.74 Adjusted GFI 0.92 RMSEA 0.06 CFI 0.99 TLI 0.98 Implications for Senior Consumers:  Implications for Senior Consumers non-users perceive SSBTs as not ease to use or useful non-users lack the confidence and perceived ability to use SSBTs How do we improve seniors’ confidence & ability? communicate benefits for seniors in a user friendly manner hands on training in a senior friendly environment physiological, perceptual and cognitive changes systems approach – needs assessment and task & person analysis select less complex SSBTs – EFTPOS goal - productive ageing Limitations & directions for future research:  Limitations & directions for future research limitations cross sectional generalisability of results further scale development moderation effects – age, gender, education, innovativeness consider other factors in the model test model in other industries/technologies Thank you :  Thank you Questions & Discussion

Add a comment

Related presentations