1 Introduction
2 Theoretical Reframing of Research on IS/IT Acceptance and Use
2.1 Alternative Theories on IS/IT Acceptance and Use
2.2 Unified Theory of Acceptance and Use of Technology (UTAUT, Venkatesh et al. 2003)
Model | Dependent variables (DV) | Role of attitude | Additional independent variables affecting DV | Study |
---|---|---|---|---|
Theory of Reasoned Action | Behavioural intention, Behaviour | Attitude → Behavioural intention | Subjective norm | Fishbein and Ajzen (1975) |
Technology Acceptance Model | Behaviour | NONE | Perceived usefulness Perceived ease of use | Davis (1989) |
IS Success Model | Use, User satisfaction | NONE | System quality Information quality | DeLone & McLean (1992) |
Theory of Planned Behaviour | Behavioural intention, Behaviour | Attitude → Behavioural intention | Subjective norm Perceived behavioural control | Ajzen (1991) |
Model of PC Utilization | Utilization | Affect → Utilization | Long term consequences Job fit Complexity Social factors Facilitating conditions | Thompson et al. (1991) |
Perceived Characteristics of Innovating | Behavioural intention, Behaviour | NONE | Relative advantage Compatibility Ease of use Result demonstrability Image Visibility Trialability Voluntariness | Moore and Benbasat (1991) |
Task-Technology Fit Model | Utilization | NONE | Task-technology fit | Goodhue & Thompson (1995) |
Social Cognitive Theory | Performance | NONE | Behaviour modelling Computer self-efficacy Performance outcome expectations Personal outcome expectations | Compeau and Higgins (1995) |
Innovation Diffusion Theory | Adoption | NONE | Relative advantage Compatibility Complexity Trialability Observability | Rogers (1995) |
TAM Extension (TAME) | Behavioural Intention | Attitude → Behavioural Intention | Situational involvement Intrinsic involvement Perceived usefulness | Jackson et al. (1997) |
Extended TAM (TAM2) | Intention to use, Usage Behaviour | NONE | Subjective norm Image Job relevance Result demonstrability Perceived usefulness Perceived ease of use | Venkatesh and Davis (2000) |
Unified Theory of Acceptance and Use of Technology | Behavioural intention, Behaviour | NONE | Performance expectancy Effort expectancy Social influence Facilitating conditions | Venkatesh et al. (2003) |
Extended IS Success Model | System use | Attitude → Satisfaction Attitude → System use | Top management support User experience User participation System quality User training | Sabherwal et al. (2006) |
TAM3 | Behavioural intention, Behaviour | NONE | Perceived usefulness Perceived ease of use Subjective norm Image Job relevance Output quality Result demonstrability Computer self-efficacy Perceptions of external control Computer anxiety Computer playfulness Perceived enjoyment Objective usability | Venkatesh & Bala (2008) |
Model of Acceptance with Peer Support (MAPS) | System use | NONE | Network density Network centrality | Sykes et al. (2009) |
UTAUT2 | Behavioural intention, Behaviour | NONE | Performance expectancy Effort expectancy Social influence Facilitating conditions Hedonic motivation Price value Habit | Venkatesh et al. (2012) |
2.3 Proposed Model of IS/IT Acceptance and Use
Construct | Definition |
---|---|
Performance Expectancy (PE) | Performance expectancy is defined as the degree to which an individual believes that using the system will help him or her to attain gains in job performance (Venkatesh et al. 2003). |
Effort Expectancy (EE) | Effort expectancy is defined as the degree of ease associated with the use of the system (Venkatesh et al. 2003). |
Social Influence (SI) | Social influence is defined as the degree to which an individual perceives that important others believe he or she should use the new system (Venkatesh et al. 2003). |
Facilitating Conditions (FC) | Facilitating conditions are defined as the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system (Venkatesh et al. 2003). |
Attitude (AT) | |
Behavioural Intention (BI) | Behavioural intention is defined as a measure of the strength of one’s intention to perform a specific behaviour (Fishbein and Ajzen 1975). |
3 Research methods
3.1 Meta-Analysis
3.1.1 Sample
3.1.2 Coding
PE | EE | FC | SI | AT | BI | UB | |
---|---|---|---|---|---|---|---|
PE | 39,048 (129) | 33,962 (98) | 38,661 (111) | 4706 (20) | 43,388 (134) | 22,282 (61) | |
EE | 0.543 | 32,239 (99) | 35,563 (107) | 4413 (20) | 41,450 (131) | 20,662 (60) | |
FC | 0.424 | 0.565 | 32,218 (92) | 4319 (19) | 36,223 (109) | 21,723 (58) | |
SI | 0.460 | 0.363 | 0.417 | 4752 (20) | 42,397 (126) | 22,378 (63) | |
AT | 0.685 | 0.566 | 0.499 | 0.455 | 16,012 (56) | 5098 (19) | |
BI | 0.542 | 0.506 | 0.453 | 0.415 | 0.626 | 24,963 (68) | |
UB | 0.389 | 0.314 | 0.359 | 0.248 | 0.475 | 0.437 |
3.1.3 Accumulation
3.2 Meta-Analytic Structural Equation Modelling (MASEM)
3.2.1 Preparation
Construct | Mean | SD | Reliability |
---|---|---|---|
UB | 4.275 | 2.678 | 0.864 |
BI | 4.487 | 1.938 | 0.886 |
PE | 4.499 | 1.890 | 0.859 |
EE | 4.399 | 1.905 | 0.869 |
FC | 4.750 | 1.531 | 0.793 |
SI | 4.274 | 1.612 | 0.824 |
AT | 4.415 | 1.934 | 0.879 |
3.2.2 Analysis
4 Results
4.1 MASEM Model for Basic UTAUT
Relationship | Path status | Basic UTAUT | Proposed model | Emergent model |
---|---|---|---|---|
UB ← BI | H | 0.35*** | 0.34*** | 0.12*** |
UB ← FC | H | 0.20*** | 0.20*** | 0.10*** |
UB ← AT | E (MI = 138.47) | 0.37*** | ||
BI ← PE | H | 0.32*** | 0.13*** | 0.11*** |
BI ← EE | H | 0.27*** | 0.14*** | 0.29*** |
BI ← SI | H | 0.17*** | 0.10*** | 0.13*** |
BI ← FC | H | 0.10*** | 0.14*** | |
BI ← AT | H | 0.37*** | 0.10*** | |
AT ← PE | H | 0.54*** | 0.47*** | |
AT ← EE | H | 0.28*** | 0.19*** | |
AT ← FC | E (MI = 122.63) | 0.20*** | ||
AT ← SI | E (MI = 59.17) | 0.15*** | ||
N | 4319 | 4319 | 4319 | |
Model χ2 (df) | 215.20*** (4) | 555.62*** (6) | 24.43*** (3) | |
GFI | 0.984 | 0.967 | 0.998 | |
CFI | 0.974 | 0.955 | 0.998 | |
NFI | 0.973 | 0.954 | 0.998 | |
RMSEA | 0.111 | 0.146 | 0.041 | |
R2 for UB | 0.21 | 0.22 | 0.27 | |
R2 for BI | 0.38 | 0.45 | 0.45 | |
R2 for AT | 0.52 | 0.55 |