Adoption of Technology Facilitated Services
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Transcript of Adoption of Technology Facilitated Services
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Pre se nt a t i on By I n d r a n i l R o y C h o w d h u r y ( P h . D )
ADOPTION OF TECHNOLOGY FACILITATED SERVICES
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INTRODUCTIONSERVICE ENCOUNTER & SELF SERVICE TECHNOLOGY
• SERVICE ENCOUNTER - Dyadic Interaction between a
Customer and the Employee of a firm during Service
Delivery
• SELF-SERVICE TECHNOLOGIES -
• “Technological interfaces that enable customers to
produce a service independent of direct service
employee involvement” (Meuter et.al, 2000)
• ATMs, online ticket booking, Phone banking, Mobile
Commerce etc.
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FORMS OF TECH INFUSION &LIMITATIONS
TFS: Technology – CSP – Customer coexist
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THE SERVICE CONTINUUM
Human Technology
Human - Technology
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TECHNOLOGY FACILITATED SERVICES FEW EXAMPLES
• Business Correspondent Banking• Bank partnerships with non-banks, typically retail commercial outlets such as
pharmacies, post offices, construction goods stores etc. to provide distribution outlets for financial services
• Tele-medical Treatment• Arrangement of providing clinical services by medical specialty centers to distant
patients with the help of technologically connected local health centers
• E-Governance Service Tele-centers• Public place where people can access digital technologies that enable them to
access governance services that include(a) procuring information (e.g., about health, education, agriculture, etc.), (b) transactions between citizens and government, and (c) procuring entitlements (including certificates, licenses, etc.)
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ATTITUDE INTENTION MODEL
Curram, Meuter and Surprenant (2003)
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FINAL CONCEPTUAL MODELSUMMARY
Perceived Ease of Use
Perceived Usefulness
Perceived Risk
Trust towards technology
Facilitating Conditions
Trust towards CSPAttitude towards CSP
Attitude towards Tech
Intention to use TFS
Network Externalities
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RESEARCH METHOD(Survey)
Sampling Technique – Non-Probabilistic Convenience - Population that is
exposed to BC banking
Sample Size Targeted - Ad-hoc rules of thumb - subjects to number of
variables ratio at 10:1 (Tanaka, 1987). Since, higher the sample size better the
model fit, an attempt was made to procure approximately 250 sample units
Sample Size Obtained – 222 – Success Rate – 75% acceptable responses
( 297 contacted ) – List of consumers obtained from a BC banking service
provider
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M- COMMERCE VALUE CHAIN
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BUSINESS CORRESPONDENT BANKING
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ANALYSIS & RESULTS
Respondent Profile - Summary
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ANALYSIS & RESULTS (contd)
Fit Index Values Recommended Range
χ2 (DOF) 564.519 (365) Normed χ2 1.547 (p < 0.001) ≤3
GFI 0.87 ≥0.90CFI 0.96 ≥0.90
RMSEA 0.050 0.50 -1.0Measurement Model Fit Indices
Fit Index Values Recommended Range
χ2 (DOF) 741.338 (413) Normed χ2 1.782 (p < 0.001) ≤3
GFI 0.84 ≥0.90CFI 0.93 ≥0.90
RMSEA 0.059 0.50 -1.0Structural Model Fit Indices
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ANALYSIS & RESULTS (contd)
√
X
√ √
√
√
√X√
√
√
0.351
0.370
0.241
0.323 0.197
0.162(p>0.1)
0.614
-0.731
0.404
0.507
0.165
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ANALYSIS AND RESULTSHYPOTHESES TESTING
Acsp
Att
0.406
0.241
0.225
0.539
Education > 10
Education < 10
0.437
0.336
0.280
0.380
Age < 25
Age>25
Attitude – Intention strength
0.027
0.3140.257
NENE – Intention
0.035
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CONTRIBUTIONS
• Attempts have been made to study a new type of
Technology based service unlike earlier studies on SST
• Studied the antecedents of Attitude towards CSP –
haven’t been studied earlier
• Importance of Network Externalities in a TFS – not many
earlier studies on technology have focused on this concept
• Impact of demographic variables – Age & Education - in a
TFS
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THANK YOU !!Q?