A presentation given on POMS conference

1. Are Tech S
Savvy Users More Likely to Use
Technology? A Study of Service Design
Planning in Online Financial Services
Pl i i O li Fi i lS i
Dr. Xin (David) Ding
Assistant Professor
Department of Information and Logistics Technology
University of Houston
Copyright @ 2009
Presented for the Production and Operations Management Society Conference
May 02, 2009

2. Outline
• Motivation
• Research Obj ti
R h Objectives
• Literature
• Research Findings
• Future Research Directions

3. Motivation

4. Research Objs and Questions
• Tactical level
– What components can deliver to the customers a
unique experience that is different from what
competitors deliver?
– How does the design of a service delivery system affect
the firm s relationship with its customer?
firm’s
• Strategic level
– How does the entry decision affect the firm’s
y
relationship with its customer?
• Individual level
– How does individual technology beliefs affect the
evaluation of and the intention to use the service?

5. Theoretical Background
• Service planning model (Chase and Acquilano
Acquilano,
1989; Goldstein et al. 2002)
Service
Input Delivery
D li Output
O t t Performance
System
•People •Service outcome
•Technology •Service experience
•Process
•Equipment
• Dual-layer experience model (Ding et al. 2008)
Dual layer
Flow
Experience Satisfaction
Experience
Clues
•System •Interactivity
•Product offerings •Focused attention
•Customer service •Control
•… •…

6. Research Model
Market Entry Structural/Infrastructural
Advantages Decisions
irm
Fi
Operations / Marketing Strategy
H4
Service Delivery
System (Clues)
System
Account
H1 Information
Individual
Product offerings H3a
Performance
Customer
I
H2 Behavioral
Technology Readiness intention
Output H3b
(Flow Experience)
Interactivity
Focused attention

7. Literature Review
• Technology readiness
gy
– People's propensity to use new technology
– Its typology helps access final usage, usability needs and
evaluations (Parasuraman & Colby 2001, Tsikriktsis 2004,
Massey et al 2007)
al.
• Service delivery system (clues)
y y ( )
– Consists of four major components including system, production,
information, and accounts (Krishnan et al. 1999; Wixom and
Todd 2005)
– The aggregate perception of the service system from interacting
with the clues lead customers into a cognitive flow experience
state, which stimulate further behavioral intention (Carbone and
Haeckel 1994, Ding et al. 2008).

8. Literature Review (Cont’d)
(Cont d)
• Flow experience
p
– Cognitive states during human-computer interaction (Krishnan et
al. 1999; Wixom and Todd 2005)
– Including the factors of focused attention, interactivity, sense of
control,
control level of challenges and skills (Ghani and Deshpande
challenges,
1994, Huffman et al. 1996, Novak et al. 2000).
– For the study context, it is best captured with focused attention
and interactivity (Brush and Artz 1999, Lovelock 2001).
• Market entry and operations strategy
– First mover advantage (Lieberman and Montgomery 1988 Kerin
First-mover 1988,
et al. 1992).).
– First-mover disadvantage (White 1983, Robinson et al. 1992).
– Marketing – operations dilemma (
g p (Bozarth and Berry 1997).
y )
• over-promise to lure customers and a push on operations to
move beyond an internal focus on reducing costs without a
clear vision of consumer needs

9. Research Hypotheses
H1 :: Major design elements within the service delivery
j g y
system, namely clues, affect customer experience;
H2 :: Customer experience affects customer firm
customer-firm
relationship in terms of behavioral intention;
H3 :: Market entry d i i affects the perceived
k decision ff h i d
performance of service delivery system and customer
experience;
H4 :: Individual technology beliefs affect the evaluation of
and the intention to use the service delivery system
y y

10. Research Methodology
• Sample
– Data from 666 individual investors from 14
major online brokers (RR > 10%)
– Unit of analysis: individual investor & broker
• Survey
– Likert-scale type, mostly validated scales
• St ti ti l analysis
Statistical l i
– ANOVA, LCA, PLS

11. TRI Clusters
Segment Variable Mean Scores (Standard Deviation)
Contributors Inhibitors
Segment Optimism Innovativeness Discomfort Insecurity TRI Score Segment
Size
1. Explorers 4.56 h 4.23 h 1.72 l 2.06 l 4.26 169
(.44) (.50) (.55) (.58) (.28)
2. Pioneers 4.28 h 3.94 h 3.65 h 3.82 h 3.19 65
(.47) (.58) (.76) (.61) (.28)
3. Skeptics 4.06 l 3.12 l 2.30 l 2.45 l 3.60 277
(.43) (.50) (.46) (.54) (.19)
4. Laggards 3.45 l 2.55 l 3.24 h 3.09 h 2.92 155
(.52) (.60) (.54) (.57) (.29)

12. TRI Clusters

13. Scale Reliability
Construct M SD SK Alpha CR AVE
Product 3.57 0.75 -0.48 0.71 0.76 0.51
Account 4.05 0.63 -0.59 0.70 0.83 0.56
Information 4.16 0.55 -0.15 0.82 0.89 0.67
System 4.13 0.53 -0.13 0.88 0.91 0.67
Focused Attention 3.71 0.74 -0.42 0.70 0.94 0.85
Interactivity 3.89 0.66 -0.64 0.91 0.85 0.85
Behavioral 3.98 0.72 -0.73 0.84 0.90 0.70
Intention

14. Convergent and Discriminant Validity
• Convergent validity
– Item-to-factors loadings > 0.7;
Item to factors
– AVE greater than 0.5 for each investigated construct;
• Discriminant validity
y
– The square roots of the AVE > corresponding
correlations;
– Items load substantially higher on intended construct
than on other constructs.

15. Market Entrants
Explorer Pioneer Skeptics Laggards Company a Total
first entrant 37% 10% 28% 26% e*Trade (1992) 90
Ameriprise (1994),
explorers 28% 14% 39% 19% 128
Ameritrade (1994)
Charles Schwab (1996),
Scottrade (1996),
followers 22% 9% 45% 24% ShareBuilder (1996), 406
TD. WaterHouse (1996)
Fidelity (1997)
Interactive (1998),
Vanguard (1998),
g ( ),
Merrill Lynch (1998),
late entrants 29% 0% 50% 21% 42
Wells Fargo (1998),
Buy & hold (1999),
Optionsxpress (2000)
p p ( )
Average 25% 10% 42% 23% 1996 167

16. Analysis Results
R2 = 0.28
R2 = 0.15 R2 = 0.46
H1 H2
Copyright @ 2009

17. Analysis Results
Mean (standard deviation) F Mean (standard deviation) F
1. 2. 3. 4. 1. 2. 3. 4.
Explorers Pioneers Skeptics Laggards first entrant explorers followers late entrants
3.67 3.99 3.55 3.34 3.61 3.64 3.57 3.35
Product ***
offerings -0.9 -0.56 -0.66 -0.7 13.72 -0.79 -0.78 -0.71 -0.93 1.59
4.24 4.25 4.04 3.78 4.03 3.98 4.09 3.95
Account -0.64 -0.49 -0.61 -0.59 18.50
***
-0.59 -0.57 -0.61 -0.69 1.49
4.31 4.31 4.18 3.92 4.18 4.21 4.15 4.12
Information -0.55 -0.49 -0.52 -0.53 17.24
***
-0.55 -0.53 -0.54 -0.68 0.52
4.3 4.2 4.16 3.85 4.05 4.14 4.14 4.11
System -0.51 -0.51 -0.51 -0.52 23.03
***
-0.54 -0.56 -0.51 -0.61 0.73
3.81 4.11 3.65 3.55 3.59 3.72 3.72 3.88
Focused ***
attention -0.81 -0.68 -0.71 -0.67 10. 92 -0.84 -0.75 -0.72 -0.59 1.52
4.04 3.88 3.96 3.62 3.76 3.93 3.9 4.02
Interactivity -0.52 -0.43 -0.63 -0.66 12.90
**
-0.67 -0.7 -0.65 -0.65 1.91
4.07 4.24 3.98 3.75 3.76 4.03 4.01 3.92
Behavioral *** **
intention -0.77
0 -0.56
0 6 -0.71
0 1 -0.68
0 68 9.11
9 11 -0.75
0 -0.69
0 69 -0.72
0 2 -0.7
0 3.36
3 36
H3 H4

18. Research Findings
• Perceived service delivery system and behavioral
y y
intention differ across TR segments
• Perceived service delivery system does not differ across
TR segments, yet
t t
– Behavioral intention differs across TR segments
• Service delivery system affects service outcome and
following behavioral intention
• Service outcome mediates the relationship between
service d li
i delivery system and b h i l i t ti
t d behavioral intention
Copyright @ 2009

19. Research Contribution
• Four major contributions:
– Examines the connection between customer tech
needs and experience/evaluation from service design
perspective;
– Examines how the critical decision in service
operations strategy - market positioning relative to
competitors, can affect the type of relationship the
firm wishes to pursue with its customers;
– Examines how the design of a service delivery
system affect the firm’s relationship with its customer;
– Empirically tests the dual-layer experience model
model.

20. Managerial Contribution
• Customer needs affect his/her experience and
valuation of a service f
l i f i from service d i perspective
i design i
– target the right customer segment to obtain the maximum
value from addressing each of the service delivery system
elements
• Market positioning affect the type of relationship the
firm wishes to pursue with its customers
– be the second to market (explorers) tend to draw more
loyal customers
• The design of a service delivery system affect the
firm’s relationship with its customer
– S t
System is most important, following by account,
i ti t t f ll i b t
information, and then product offerings
Copyright @ 2009

21. Future direction
• Applying
– Explore the service design planning model
and dual-layer experience model among other
service settings
• Extending
– Include additional factors measuring service
input and service delivery system
–CCross-cultural comparison
lt l i
• Validating
– C t ll d experiments
Controlled i t
Copyright @ 2009

22. end
d
Copyright @ 2009

23. Not So Good Examples
Copyright @ 2009