Adoption of New Service Development Tools in the Financial Service Industry

Dayu Jin, Kah-Hin Chai, Kay-Chuan TanDepartment of Industrial and Systems Engineering

National University of Singapore

Introduction - Background

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• New service development (NSD) is important; however NSD success rate is low.

Success rate is as low as 58% (Griffin, 1997).

NSD lacks structured processes and services just “happen” ((de Jong and Vermeulen, 2003).

• Various NSD tools have been proposed. Prototyping services (Shostack, 1984).

Identifying customer needs (Alam, 2002).

Trouble-shooting causes of potential problems (Dorsh et al., 1997).

Introduction – Motivations

• There is no systematic review of the NSD tools used in NSD projects (Menor et al., 2002).

• It is not clear about the role of key factors in influencing the adoption of NSD tools (Kettinger et al., 1997).

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1) What are the NSD tools that can facilitate NSD process?

2) What are the factors influencing the adoption of NSD tools in service firms?

Literature Review (1)

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• NPD tools studies

• NSD tools studies

Usage is low (Mahajan and Wind, 1992; Nijssen and Lieshout, 1995).

To improve success rate and to identify problem (Mahajan and Wind, 1992; Nijssen and Lieshout, 1995).

Overall satisfaction (Mahajan and Wind, 1992).

Correlate with NPD success (Nijssen and Lieshout, 1995; González and Palacios, 2002; Yeh et al., 2008).

General (e.g., Bitran and Pedrosa, 1998; Edvardsson et al., 2000; Alam, 2002; Antony, 2004).

Specific (e.g., Shostack, 1984; Wind et al., 1989; Ko and Lee, 2000; Ahn and Skudlark, 2002).

Lack of systematic studies on NSD tools.

Literature Review (2)

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Organizational adoption of innovation

Innovation characteristics – relative advantage, compatibility, and complexity (Tornatzky and Klein, 1982; Rogers, 1995).

Organizational factors – resources and specialization (Rosner, 1968; Kimberly and Evanisko, 1981; Greenhalgh et al., 2004).

Institutional environment – pressures from competitors, customers, and suppliers (DiMaggio and Powell, 1983; Wu et al., 2003).

Link determinants directly to the adoption while ignore the decision-making process.

Literature Review (3)Theory of Planned Behavior (TPB)

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Applying TPB at firm-level: use NSD mangers and team members as proxies.

Behavioral Beliefs

Normative Beliefs

Control Beliefs

Attitude

Subjective Norm

Perceived Behavior Control

Intention Behavior

Framework

Attitude

Subjective Norm

Perceived Behavior Control

Intention

Behavioral Beliefs

Normative Beliefs

Control Beliefs

H1, +

H2, +

H3, +

Hypothesis 1: Attitude towards adopting NSD tools has a positive and direct effect on the intention to adopt these tools.Hypothesis 2: Subjective norm towards adopting NSD tools has a positive and direct effect on the intention to adopt these tools.Hypothesis 3: Perceived behavior control towards adopting NSD tools has a positiveand direct effect on the intention to adopt these tools.

Perceived Usefulness

Perceived Ease of Use

Supplier Coercive Pressure

Competitive Pressure

Customer Coercive Pressure

Compatibility

Resource Commitment

H4, +

H5, +

H6, +

H7, +

H8, +

H9, +

H10, +

Hypothesis 4: Perceived usefulness has a positive and direct effect on organizational attitude towards NSD tools adoption.Hypothesis 5: Perceived ease of use has a positive and direct effect on organizational attitudes towards NSD tools adoption.

Hypothesis 6: Supplier coercive pressure has a positive and direct effect on organizational subjective norm towards NSD tools adoption.Hypothesis 7: Competitive pressure has a positive and direct effect on organizational subjective norm towards NSD tools adoption.Hypothesis 8: Customer coercive pressure has a positive and direct effect on organizational subjective norm towards NSD tools adoption.

Hypothesis 9: Compatibility has a positive and direct effect on organizational perceived behavior control towards NSD tools adoption.Hypothesis 10: Resource commitment will have a positive and direct effect on organizational perceived behavior control towards NSD tools adoption.

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Research methodologySample: 420 financial institutions in Singapore. Active innovators of a range of services (Menor and Roth, 2008).

Offerings are standardized which provides opportunities for tool use (Easingwood, 1986).

Unit of analysis: NSD projects conducted in 3 years. Chief executive officers as respondents.

Response: 99, response rate of 23.6%. 63 responses indicated no NSD, and 2 incomplete. Data analysis is based on 34 usable replies.

Method: Partial Least Squares (PLS) Use of both reflective and formative measures. Accurate results under small sample.

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Reliability and validity

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Competitive pressure1 2

Compatibility1 2 3

Resource commitment1 2

VIF 1.748 1.748 4.816 1.775 6.138 1.705 1.705

Formative measures Indicators are causes of latent variable rather than results.

Indicators are independent of each other, making validation process different.

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Rotated Component Matrixa

.848

.835

.829

.652

.557 .515

.876

.853

.831

.621

.859

.809

.766

.859

.789

.746

.556

.532

.908

.897

.857

.898

.804

.638

.611

.545

.940

.909

.871

.758

.738

.608

SN2

SN1

SN3

CMPT3

CMPT1

PU2

PU1

PU4

PU3

INT2

INT3

INT1

CMPT2

PEU1

PEU2

PEU3

COMPR1

COMPR3

CUSPR1

CUSPR2

CUSPR3

PBC2

RECS2

PBC3

PBC1

RESC1

SUPR2

SUPR1

SUPR3

A3

A4

A1

A2

1 2 3 4 5 6 7 8

Component

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 8 iterations.a.

Rotated Component Matrixa

.867

.850

.825

.659

.895

.873

.868

.911

.911

.868

.860

.807

.803

.919

.844

.784

.962

.912

.870

.914

.707

.668

.741

.741

.673

.554

PU2

PU1

PU4

PU3

SN2

SN1

SN3

CUSPR1

CUSPR2

CUSPR3

INT2

INT3

INT1

PEU1

PEU2

PEU3

SUPR2

SUPR1

SUPR3

PBC2

PBC3

PBC1

A1

A4

A3

A2

1 2 3 4 5 6 7 8

Component

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 7 iterations.a.

Reliability and validity

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  AVE CR α 1 2 3 4 5 6 7 8

1.Attitude 0.65 0.88 0.83 0.65

2.Customer Coercive Pressure 0.92 0.97 0.96 0.32 0.92

3.Adoption Intention 0.94 0.98 0.97 0.47 0.31 0.94

4.Perceived Behavior Control 0.75 0.90 0.84 0.34 0.22 0.46 0.75

5.Perceived Ease of Use 0.91 0.97 0.95 0.49 0.33 0.59 0.50 0.91

6.Perceived Usefulness 0.71 0.91 0.86 0.48 0.10 0.50 0.11 0.30 0.71

7.Subjective Norm 0.94 0.98 0.97 0.48 0.47 0.40 0.53 0.50 0.07 0.94

8.Supplier Coercive Pressure 0.85 0.94 0.93 -0.09 0.29 0.22 0.07 0.11 0.01 0.09 0.85

Reflective measures Reliability: Cronbach’s alpha > 0.7, composite reliability (CR) > 0.7 Convergent validity: average variance extracted (AVE) > 0.5 Discriminant validity: correlation is smaller than square root of AVE

Results

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Brainsto

rming

Bench

marking

Scenari

o Planning

Concept T

esting

Structu

red Analy

sis an

d Design

Focu

s Gro

up

Servi

ce Bluep

rint

Lead User

s

Quality

Functi

on Deploym

ent

Conjoint Analy

sis

Affinity Diag

ram

Failu

re Modes

and Eff

ects A

nalysis

Root Cau

se Analy

sis0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0.91

0.74

0.560.50 0.50 0.47 0.44

0.38 0.35 0.32

0.24 0.21 0.21

% o

f firm

usin

g to

ols

Percentage of financial institutions using NSD tools

Results

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Percentage of financial institutions using NSD toolsBank Fund mgmt Insurance Real estate Other

Benchmarking 75% 82% 62.5% 100% 60%Scenario planning 50% 55% 62.5% 50% 100%Affinity diagram 0% 36% 37.5% 0% 20%Brainstorming 87.5% 91% 100% 100% 80%Conjoint analysis 25% 45% 37.5% 0% 20%Focus group 62.5% 36% 25% 100% 60%Lead users 37.5% 27% 25% 100% 60%Concept testing 50% 36% 75% 0% 60%Quality function deployment 37.5% 36% 50% 0% 20%Service blueprint 50% 36% 50% 0% 60%Structured analysis and design 62.5% 36% 50% 100% 40%Failure modes and effects analysis 25% 27% 0% 0% 40%Root cause analysis 25% 27% 12.5% 0% 20%

■ Significantly higher than usage in other industries (p<5) ■ Significantly lower than usage in other industries (p<.05)

Results

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Percentage of financial institutions using NSD toolsIdea generation and

screenBusiness and

market analysisService design Service testing Service

launching

Benchmarking (25) 44% 76% 60% 28% 24%Scenario planning (19) 42% 74% 53% 32% 16%Affinity diagram (8) 13% 50% 38% 13% 0%Brainstorming (31) 77% 58% 74% 13% 35%Conjoint analysis (11) 27% 36% 73% 36% 9%Focus group (16) 50% 56% 63% 50% 50%Lead users (13) 23% 38% 77% 69% 38%Concept testing (17) 47% 24% 41% 47% 29%Quality function deployment (12) 17% 25% 83% 25% 8%Service blueprint (15) 20% 27% 80% 60% 33%Structured analysis and design (17) 29% 47% 82% 41% 24%Failure modes and effects analysis (7) 29% 43% 71% 57% 14%Root cause analysis (7) 43% 57% 29% 43% 57%

■ Significantly higher than usage in other NSD stages (p<.05)

■ Significantly lower than usage in other NSD stages (p<.05)

ResultsFactors affecting the adoption of NSD tools

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Dependent Variable Predictor β t-Value Conclusion

Behavior intention(R2 = 0.47, F2 = 0.41)

Attitude 0.315 1.653 supported

Subjective norm 0.093 0.394 not supported

Perceived behavior control 0.325 1.775 supported

Attitude(R2 = 0.54, F2 = 0.40)

Perceived usefulness 0.387 2.550 supported

Perceived ease of use 0.384 2.669 supported

Subjective norm(R2 = 0.30, F2 = 0.27)

Supplier coercive pressure -0.137 -1.025 not supported

Competitive pressure 0.689 4.325 supported

Customer coercive pressure 0.055 0.168 not supported

Perceived behavior control(R2 = 0.50, F2 = 0.39)

Compatibility 0.405 2.840 supported

Resource commitment 0.528 3.968 supported

Implications/ConclusionsProvided a systematic review on the use of NSD tools. When to use which NSD tool in NSD project.

Conceptualized a framework explaining the adoption of NSD tools in service firms. Provide implications for future development of new NSD tools by

both scholars and practitioners. Suitable to understand the adoption of innovation in service firms.

Extended the application of TPB to firm-level other than confined it to individual-level. In accordance with the survey method.

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Thank you!