user acceptance of information technology

USER ACCEPTANCE OF INFORMATION

TECHNOLOGY: TOWARD A UNIFIED

B004020003 張家瑄

B004020007 林漪寒

B004020013 羅珮綺

B004020019 周紹文

B004020036 游騰方

B004020047 簡志樺

OUTLINE

a. Abstract

b. Empirical Comparison of the Eight Models

c. Formulation of the Unified Theory of

Acceptance and Use of Technology

d. Empirical Validation of UTAUT

ABSTRACT

(1) Review user acceptance literature and

discuss eight prominent model1. the Theory of Reasoned Action (TRA)

2. the Technology Acceptance Model (TAM)

3. the Motivational Model (MM)

4. the Theory of Planned Behavior (TPB)

5. a model Combining the Technology Acceptance Model and the Theory of Planned Behavior (C-TAM-TPB)

6. the Model of PC Utilization (MPCU)

7. the Innovation Diffusion Theory (IDT)

8. the Social Cognitive Theory (SCT) 4

ABSTRACT

(2) Empirically compare the eight model and their extensions

1. 17 ~ 53% of the variance in user intention

2. Within-subjects, longitudinal validation and comparison

3. A baseline assessment of the relative explanatory

ABSTRACT

(3) Formulate a unified model that integrates elements across the eight models

four core determinants of intention and usage, and four moderators of key relationship

(4) Empirically validate the unified model

1. UTAUT outperforms each of the eight original

models

2. UTAUT is cross-validated using data from two new

organization

ABSTRACT

a. Since the 1980s, 50 percent investment in organizations used for IT.

b. Technologies to improve productivity, they must be accepted and used by employees in organizations.

c. Research in this area roots in IS, psychology, and sociology.

d. Researchers are confronted with a choice among a multitude of models.

INTRODUCTION

a. IS research has long studied how and

why individuals adopt new information

technologies.

b. There have been several streams of

research

One stream of research focuses on individual acceptance of technology about intention or usage.

Other stream have focused on implementation success at the organizational level and task-technology fit.

DESCRIPTION OF MODELS AND CONSTRUCT

Figure 1 presents the basic conceptual

explaining individual acceptance of

information technology that forms the basis of

this research.

Figure 1. Basic Concept Underlying User Acceptance Models

DESCRIPTION OF MODELS AND CONSTRUCT

Model Core

Constructs

Definitions

Theory of

Reasoned

Action (TRA)

Attitude

Toward

Behavior

individual’s positive or negative feelings

about performing the target behavior

Subjective

the person’s perception that most

people who are important to him think

he should or should not perform the

behavior in question

TABLE 1. THEORY OF REASONED ACTION (TRA)

Model Core

Constructs

Definitions

Technology

Acceptance

Model (TAM)

Perceived

Usefulness

the degree to which a person believes

that using a particular system would

enhance job performance

Perceived

Ease of Use

the degree to which a person believes

that using a particular system would be

free of effort

Subjective

Adapted from TRA/TPB. Included in

TAM2 only

TABLE 1. TECHNOLOGY ACCEPTANCE MODEL (TAM)

Social Influence Processes

Cognitive Instrumental Processes

TABLE 1. TECHNOLOGY ACCEPTANCE MODEL 2(TAM2)

Model Core

Constructs

Definitions

Motivational

Model (MM)

Extrinsic

Motivation

The perception that users want to

perform an activity “because it is

perceived to be instrumental in

achieving valued outcomes that are

distinct from the activity itself, such as

improved job performance, pay, or

promotions”

Intrinsic

Motivation

The perception that users want to

perform an activity “for no apparent

reinforcement other than the process of

performing the activity per se”

TABLE 1. MOTIVATIONAL MODEL (MM)

Model Core

Constructs

Definitions

Theory of

Planned

Behavior (TPB)

Attitude

Toward

Behavior

Adapted from TRA

Subjective

Adapted from TRA

Perceived

Behavioral

Control

• the perceived ease or difficulty of

performing the behavior

• In context of IS research, perceptions

of internal and external constraints on

behavior

TABLE 1. THEORY OF PLANNED BEHAVIOR (TPB)

Model Core

Constructs

Definitions

Combined

TAM and TPB

(C-TAM-TPB)

Attitude

Toward

Behavior

Adapted from TRA/TPB

Subjective

Perceived

Behavioral

Control

Perceived

Usefulness

Adapted from TAM

TABLE 1. C-TAM-TPB

Model Core

Constructs

Definitions

Model of PC

Utilization

(MPCU)

Job-fit

the extent to which an individual

believes that using [a technology] can

enhance the performance of his or her

Complexity

the degree to which an innovation is

perceived as relatively difficult to

understand and use

Long-term

Consequences

Outcomes that have a pay-off in the

future

TABLE 1.MODEL OF PC UTILIZATION (MPCU)

Model Core

Constructs

Definitions

Model of PC

Utilization

(MPCU)

Affect Towards

feelings of joy, elation, or pleasure, or

depression, disgust, displeasure, or

hate associated by an individual with a

particular act

Social Factors

the individual’s internalization of the

reference group’s subjective culture

specific interpersonal agreements that

the individual has made with others, in

specific social situations

Facilitating

Conditions

Objective factors in the environment that

observers agree make an act easy to

accomplish

TABLE 1.MODEL OF PC UTILIZATION (MPCU)

Model Core

Constructs

Definitions

Innovation

Diffusion

Theory (IDT)

Relative

Advantage

the degree to which an innovation is

perceived as being better than its

precursor

Ease of Use the degree to which an innovation is

perceived as being difficult to use

Image The degree to which use of an

innovation is perceived to enhance

one’s image or status in one’s social

system

TABLE 1. INNOVATION DIFFUSION THEORY (IDT)

Model Core

Constructs

Definitions

Innovation

Diffusion

Theory (IDT)

Visibility The degree to which one can see

others using the system in the

organization

Compatibility the degree to which an innovation is

perceived as being consistent with the

existing values, needs, and past

experiences of potential adopters

Results

Demonstrabilit

the tangibility of the results of using the

innovation, including their observability

and communicability

Voluntariness

of Use

the degree to which use of the

innovation is perceived as being

voluntary, or of free will

TABLE 1. INNOVATION DIFFUSION THEORY (IDT)

創新的

採納

創新的可試用性

創新的自願性

創新的相對優勢個人形象的提升

創新的可見度

與既有知識或工作

的相容性

創新本身的複雜性

創新結果的可呈

現性

INNOVATION DIFFUSION THEORY STRUCTURE

BEHAVIOR

ENVIRONMENTAL

PERSONAL

SOCIAL COGNITIVE THEORY STRUCTURE

TABLE 1. SOCIAL COGNITIVE THEORY (SCT)

Model Core

Constructs

Definitions

Social

Cognitive

Theory (SCT)

Outcome

Expectations—

Performance

The performance-related consequences

of the behavior. Specifically, job-related

outcomes

Outcome

Expectations—

Personal

The personal consequences of the

behavior. Specifically, individual esteem

and sense of accomplishment

Self-efficacy

Judgment of one’s ability to use a

technology to accomplish a particular

job or task.

AffectAn individual’s liking for a particular

behavior

AnxietyEvoking anxious or emotional reactions

when it comes to performing a behavior

KEY MODERATING VARIABLES

1. Experience

2. Voluntariness

3. Gender

4. Age

Model Experience Voluntariness Gender Age

TRAMore experience Attitude ↑

Subjective norm ↓

Less voluntary Subjective norm ↑

N/A N/A

More experience Ease of use ↓

Within TAM2:

Mandatory and

limited experience Subjective norm ↑

Men Perceived usefulness ↑

Women Perceived ease of use ↑

Women in the early

stages of experience Subjective norm ↑

MM N/A N/A N/A N/A

TABLE 2. ROLE OF MODERATORS IN EXISTING MODELS

Model ExperienceVoluntarines

s Gender Age

TPBMore experience Subjective norm ↓

voluntary Subjective

norm↑

MenAttitude ↑

Women in the early

stages of

experience Subjective norm ↑

Perceived behavioral

control ↑

Younger

workers Attitude ↑

Older workers Perceived

behavioral

control↑

Older womenSubjective norm ↑

Combine

More experiencePerceived

usefulness↑

Attitude toward

behavior ↑

Perceived

behavioral control ↑

Subjective norm ↓

N/A N/A N/A

Model Experience VoluntarinessGende

Less experienceComplexity ↑

Affect toward use ↑

Social factors ↑

Facilitating conditions ↑

More experienceLong-term consequences ↑

N/A N/A N/A

For adoption (no/low experience)Relative advantage, Ease of use,

Trialability, Results demonstrability

and Visibility

For usage (greater experience)Relative advantage and image

Voluntariness was not

tested as a moderator,

but was shown to have

a direct effect on

Intention

N/A N/A

SCT N/A N/A N/A N/A

TABLE 3. REVIEW OF PRIOR MODEL COMPARISONS

Compariso

Studies

Theories/

Models

Compare

Context of

(Incl.Technolog

Participant

Newness of

Technology

Studied

Number of

Points of

Measureme

Cross-

Sectional or

Longitudinal

Analysis

Findings

Davis et al.

(1989)

TRA, TAM • Within-subjects

• intention and

use of a word

processor

students

new to the

technology

214 weeks

Cross-

sectional

The variance

in intention

and use TRA：32% ,26%

TAM：47% ,

Mathieson

(1991)

TAM, TPB • Between-

subjects

• intention to use

a spreadsheet

and calculator

students

familiarity

with the

technology

1 Cross-

sectional

The variance

in intention

TAM：70%

TPB：62%

Taylor and

(1995b)

TPB/DTP

• Within-subjects

a computing

resource center

students

already

familiar with

the center

For a three-

period

Cross-

sectional

The variance

in intention

TAM：52%

TPB：57%

DTPB：60%

Plouffe et al.

(2001)

TAM, IDT • Within-subjects

in the context of

a market trial of

an electronic

payment system

using smart card

merchants

Survey

administere

after 10

months

of use

1 Cross-

sectional

The variance

in intention

TAM：33%

IDT：45%

TABLE 3. REVIEW OF PRIOR MODEL COMPARISONS

Compariso

Studies

Theories/

Models

Compare

Context of

(Incl.Technolog

Participant

Newness of

Technology

Studied

Number of

Points of

Measureme

Cross-

Sectional or

Longitudinal

Analysis

Findings

Davis et al.

(1989)

TRA, TAM • Within-subjects

• intention and

use of a word

processor

students

new to the

technology

214 weeks

Cross-

sectional

The variance

in intention

and use TRA：32% ,26%

TAM：47% ,

Mathieson

(1991)

TAM, TPB • Between-

subjects

a spreadsheet

and calculator

students

familiarity

with the

technology

1 Cross-

sectional

The variance

in intention

TAM：70%

TPB：62%

Taylor and

(1995b)

TPB/DTP

• Within-subjects

a computing

resource center

students

already

familiar with

the center

For a three-

period

Cross-

sectional

The variance

in intention

TAM：52%

TPB：57%

DTPB：60%

Plouffe et al.

(2001)

TAM, IDT • Within-subjects

in the context of

a market trial of

an electronic

payment system

using smart card

merchants

Survey

administere

after 10

months

of use

1 Cross-

sectional

The variance

in intention

TAM：33%

IDT：45%

Five limitations of these prior model tests and comparisons:

1. Technology studied- Prior : simple, individual-oriented IT

- UTAUT : complex, organizational IT, managerial concern

2. Participants- Prior : most are students

- UTAUT : employees in organizations

3. Timing of measurement- Prior : after the participants’ acceptance or rejection decision

- UTAUT : from the initial introduction to stages of greater experience

PRIOR MODEL TESTS AND MODEL COMPARISONS

4. Nature of measurement- Prior : cross-sectional and/or between-subjects

comparisons

- UTAUT : various stages of experience with a new technology and compares all models on all participants

5. Voluntary vs. mandatory contexts- Prior : voluntary usage contexts

- UTAUT : both voluntary and mandatory contexts

PRIOR MODEL TESTS AND MODEL COMPARISONS

EMPIRICAL COMPARISON OF

THE EIGHT MODELS

• Settings and

Participants

• Measurement

• Results

We sampled for heterogeneity across :

1. technologies

2. organizations

3. industries

4. business functions

And nature of use :

voluntary vs. mandatory

SETTINGS AND PARTICIPANTS

Measuring constructs from all eight models was administered at three different points in time:

- T1:post-training

- T2:one month after implementation

- T3:three month after implementation

SETTINGS AND PARTICIPANTS

A questionnaire was created with items

validated in prior research.

Behavioral intention to use the system was

measured using a three-item scale.

Seven point scales were used for all of the

aforementioned constructs’ measurement.

Actual usage behavior was measured as

duration of use via system logs.

MEASUREMENT

RESULTS - USING PARTIAL LEAST SQUARES (PLS)

Key findings :

1. Variance in intention explained ranging from 17 percent to 42 percent.

2. Constructs related to social influence were more significant in the Mandatory settings .

3. Some determinants going from significant to nonsignificant with increasing experience.

The data were pooled across studies and time periods.1. Voluntariness

2. Gender

3. Age

4. Experience

Pooling the data across the three points of measurement

Time1+Time2+Time3 = 215x3= 645(N)

There is an increase in the variance explained in the case of TAM2

1. With the exception of MM and SCT, the predictive validity of the models increased after including the moderating variables.

2. The extensions to the various models mostly enhance the predictive validity of the various models beyond the original specifications.

1. There was at least one construct that was significant in all time periods.

2. Several other constructs were initially significant, but then became nonsignificantover time.

3. The voluntary vs. mandatory context did have an influence on the significance of constructs related to social influence

4. Unified theory of acceptance and use of technology(UTAUT)

FORMULATION OF THE UNIFIED

THEORY OF ACCEPTANCE AND

USE OF TECHNOLOGY

• UTAUT

Direct Determinants

• Performance expectancy

• Effort expectancy

Indirect Determinants

• Self-efficacy

• Anxiety

• Attitude toward using

Key moderators

• Gender

• Age

• Voluntariness

• experience47

THE UTAUT RESEARCH MODEL

UTAUT RESEARCH MODEL

PERFORMANCE EXPECTANCY

• Definition

The degree to which an individual believes that using the

system will help him or her to attain gains in job

performance.

Construct Source Model

Perceived UsefulnessTAM/TAM2/C-TAM-

Extrinsic Motivation MM

Job-fit MPCU

Relative Advantage IDT

Outcome Expectations SCT

TABLE 9. FIVE CONSTRUCTS OF PERFORMANCE EXPECTANCY

It has two moderating variables with

gender and age.

• Gender:

It has a more significant effect on men.

• Age:

Stronger for Younger workers.

The influence of performance expectancy on behavioral intention

will be

Moderated by 1. Gender

2. Age

Such that the effect will be stronger for

1. men

2. particularly younger men

EFFORT EXPECTANCY

• DefinitionThe degree of ease of associated with the use ofsystem

Perceived ease of use TAM/TAM2

Complexity MPCU

Ease of use IDT

TABLE 10. THREE OF EFFORT EXPECTANCY

EFFORT EXPECTANCY

It has three moderating variables withgender, age and experience.

• Gender:

It has a more significant effect on women.

• Age:

It is significant by older worker.

• Experience:

Person has few experience with system.

EFFORT EXPECTANCY

The influence of effort expectancy on behavioral intention will

2. Age

3. Experience

1. women

2. particularly older workers

3. particularly at the early stages of experience

SOCIAL INFLUENCE

• Definition : The degree to which an individual perceives that important others believe he or she should use the new system.

Subjective NormTRA, TAM2, TPB/DTPB

and C-TAM-TPB

Social Factors MPCU

Image IDT

SOCIAL INFLUENCE

T1 T2 T3

In Voluntary

SettingsNonsignificant Nonsignificant Nonsignificant

In Mandatory

SettingsSignificant Significant Nonsignificant

Experience and Voluntariness of use are moderating

variables.

SOCIAL INFLUENCE

• Gender : Women tend to be more salient when forming an intension to use technology, with the effect declining with experience.

• Age :Older workers are more likely to place increased salience

on social influences, with the effect declining with

experience.

Gender and Age are moderating

variables 61

SOCIAL INFLUENCE

The influence of social influence on behavioral intention will

2. Age

3. Voluntariness

4. Experience

1. women

2. particularly older women

3. particularly in mandatory settings in the early stages of experience

FACILITATING CONDITIONS

• Definition : The degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system.

Perceived behavioral

controlTPB/DTPB, C-TAM-TPB

Facilitating conditions MPCU

Compatibility IDT

T1 T2 T3

In Voluntary

SettingsSignificant

Nonsignifica

Mandatory

Settings

SignificantNonsignifica

Nonsignifica

Perceived behavioral control

When both performance expectancy constructs and effort expectancy constructs are present facilitating conditions becomes non-significant in predicting intention.

H4a:Facilitating conditions will not have a significant influence on

behavioral intention.

• Experience : The effect will be stronger with increasing experience.

• Age :Older workers attach more importance to receiving help and assistance on the job.

Experience and Age are moderating

variables

H4b :The influence of facilitating conditions on usage will be

Moderated by 1. Age

2. Experience

Such that the effect will be stronger for 1. Older workers

2. particularly with increasing experience

CONSTRUCTS THEORIZED NOT TO BE DIRECT DETERMINANTS OF INTENTION1. Self-efficacy

2. Anxiety

3. Attitude toward using technology

SELF-EFFICACY AND ANXIETY

1. Self-efficacy and anxiety have been modeled as

indirect determinants of intention fully mediated

by perceived ease of use

2. We expect self-efficacy and anxiety to behave

similarly, that is , to be distinct from effort

expectancy and to have no direct effect on

intention above and beyond effort expectancy

SELF-EFFICACY AND ANXIETY

H5a:Computer self-efficacy will not have a significant influence on

H5b:Computer anxiety will not have a significant influence on

ATTITUDE TOWARD USING TECHNOLOGY

• Definition : An individual’s overall affective reaction to using a system.

Attitude toward behaviorTRA,TPB/DTPB, C-

TAM-TPB

Intrinsic motivation MM

Affect toward use MPCU

Affect SCT

T1 T2 T3

TPB/DTPB,

Significant Significant Significant

TAM-TPB,

MPCU, SCT

Nonsignifica

We expect strong relationships in UTAUT between performance expectancy and intention, and between effort expectancy and intention

We believe that attitude toward using technology will not have a direct or interactive influence on intention.

H5c:Attitude toward using technology will not have a significant influence on behavioral intention.

BEHAVIORAL INTENTION

Consistent with the underlying theory for all of the intention models discussed in this paper, we expect that behavioral intention will have a significant positive influence on technology usage.

H6:Behavioral intention will have a significant influence on usage.

EMPIRICAL VALIDATION OF

• Preliminary Test of

• Cross-Validation of

EMPIRICAL VALIDATION OF UTAUT

1. UTAUT was then tested using the original data

and found to outperform the eight individual

models (adjusted R2 of 69%).

2. UTAUT was then confirmed with data from two

new organizations with similar results (adjusted

R2 of 70%)

PERFORMANCE EXPECTANCY - FIVE CONSTRUCTS

PRELIMINARY TEST OF UTAUT

Performance expectancy The effect was moderated by gender and age such that it was more salient to younger worker, particularly men

SUPPORTING H1

H1 Effect stronger for men and younger worker

Effort expectancy The effect was moderated by gender and age, and effect decreasing with experience

SUPPORTING H2

Effect stronger for women, older

worker,and those with limited experience

Social influence Its role being more important in the context of mandatory use, and more so among older women, more significant in the early stages of individual experience with the technology

SUPPORTING H3

Effect stronger for women, older worker,

under conditions of mandatory use, and

with limited experience

Facilitating condition In predicting usage behavior, facilitating conditions were significant, with the latter’s effect being moderated by age (more important to order worker), and with increasing experience

SUPPORTING H4B

Effect stronger for older worker with increasing

experience

Behavioral intention In predicting usage behavior, the effect of behavior intention were significant

SUPPORTING H6

Direct effect

CROSS-VALIDATION OF UTAUT

CONTRIBUTION

1. UTAUT was able to account for 70 percent of variance

2. Integrate the main 32 effects and 4 moderator into 4 main effects and 4 moderators

CONCLUSION

1. UTAUT provides a refined view of how the determinants of intention and behavior evolve over time

2. Social influence construct has been controversial

3. Focus on integrating UTAUT with research that has identified causal antecedents of the constructs used within the model

4. Identify and test additional boundary conditions of the model

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