Unified Theory of Acceptance and Use of Technology (UTAUT)

Unified Theory of Acceptance and Use of Technology (UTAUT)

The Unified Theory of Acceptance and Use of Technology (UTAUT) was developed by Venkatesh, Morris, Davis, and Davis in 2003. It integrates elements from eight existing theories/models to explain technology adoption and user behavior. The primary theories it originated from are:

1. Theory of Reasoned Action (TRA) – Focuses on how attitudes and subjective norms influence behavior.
2. Technology Acceptance Model (TAM) – Emphasizes perceived usefulness and ease of use in predicting technology adoption.
3. Motivational Model (MM) – Examines how intrinsic and extrinsic motivation affect behavior.
4. Theory of Planned Behavior (TPB) – Builds on TRA by adding perceived behavioral control as a key determinant.
5. Combined TAM and TPB (C-TAM-TPB) – Combines aspects of both the TAM and TPB.
6. Model of PC Utilization (MPCU) – Focuses on the drivers of computer usage.
7. Innovation Diffusion Theory (IDT) – Examines how innovations spread over time in a social system.
8. Social Cognitive Theory (SCT) – Explores the role of self-efficacy, outcome expectations, and the social environment in technology use.

UTAUT unifies these theories into a comprehensive model to better predict user acceptance of new technologies.

“UTAUT is suitable for general technology acceptance, while UTAUT2, with added variables like trust and pleasure, is more appropriate for specific contexts like analyzing user behavior in new payment methods. ”

 

Bakri, A. A., Wandanaya, A. B., Violin, V., & Fauzan, T. R. (2023). The Application of UTAUT Modified Model to Analyze the Customers Use Behavior of Shopee Paylater. Jurnal Sistim Informasi dan Teknologi, 96-101.

The Unified Theory of Acceptance and Use of Technology (UTAUT) explains technology adoption by identifying four key factors that influence users’ intention to adopt and use a new technology. These factors aim to predict whether individuals will accept and continue using a technology. Here’s how UTAUT works:

Key Determinants in UTAUT:

1. Performance Expectancy (PE):
– This refers to the degree to which an individual believes that using the technology will help them achieve better outcomes or improve their performance. If users expect that the technology will make their tasks easier or more effective, they are more likely to adopt it.
– Similar to the “perceived usefulness” in the Technology Acceptance Model (TAM).

2. Effort Expectancy (EE):
– This represents the ease of use of the technology. If users find the technology easy to learn and operate, they are more inclined to adopt it. It’s similar to “perceived ease of use” from TAM.
– Simpler, user-friendly technologies have higher adoption rates.

3. Social Influence (SI):
– This is the extent to which individuals perceive that important others (friends, family, coworkers, or authority figures) believe they should use the technology. Social pressure or the perception that using the technology is a social norm plays a significant role in technology adoption.

4. Facilitating Conditions (FC):
– These are the resources and support available to help individuals use the technology, such as infrastructure, training, or technical support. If users feel they have the necessary resources to use the technology, they are more likely to adopt it.

 Mediating Role:
– Behavioral Intention (BI):
– UTAUT suggests that the above factors (PE, EE, SI) directly influence an individual’s behavioral intention to use the technology.
– The stronger the intention, the higher the likelihood of actual adoption and usage.

 Moderators:
– Gender, Age, Experience, and Voluntariness of Use:
– UTAUT also incorporates these variables as moderators, suggesting that the strength of the relationship between the key factors and behavioral intention may vary depending on demographic characteristics and the context of technology use (e.g., whether adoption is voluntary or mandatory).

Summary:
UTAUT explains technology adoption by examining how users’ expectations of performance, effort, social pressure, and the availability of resources shape their intention to adopt and use new technology. The model is widely used in research because it provides a comprehensive framework that accounts for various psychological and contextual factors influencing technology acceptance.

What are the differences of UTAUT1 vs. UTAUT2

The Unified Theory of Acceptance and Use of Technology (UTAUT) and its extended versions, such as UTAUT2, build on the original Technology Acceptance Model (TAM), making them more comprehensive and nuanced models for explaining technology adoption. Below is a comparison between UTAUT (sometimes called UTAUT1), UTAUT2, and their effectiveness compared to the earlier TAM models:

UTAUT (UTAUT1) vs. Earlier Models (TAM1 & TAM2)

1. Scope and Variables:
– TAM (TAM1) primarily focused on two factors: Perceived Usefulness (similar to Performance Expectancy in UTAUT) and Perceived Ease of Use (similar to Effort Expectancy).
– TAM2 extended TAM1 by adding Subjective Norms, which is related to Social Influence in UTAUT. TAM2 also considers Cognitive Instrumental Processes, enhancing the explanation of technology adoption, but it was limited in scope.

UTAUT1 expands these models by adding more comprehensive variables like:
– Performance Expectancy(similar to Perceived Usefulness),
– Effort Expectancy (similar to Perceived Ease of Use),
– Social Influence (similar to Subjective Norms),
– Facilitating Conditions (not explicitly in TAM, focuses on external factors like infrastructure and support).

This expansion makes UTAUT1 more robust and applicable to a wider variety of contexts compared to TAM1 and TAM2.

2. Moderators:
– TAM1 and TAM2 didn’t use demographic variables like gender or age to explain differences in technology adoption.
– UTAUT1 introduced four moderators: Age, Gender, Experience, and Voluntariness of Use, which made it more powerful for studying how different user segments behave regarding technology adoption.

3. Prediction Power:
– TAM models explained 30-40% of the variance in users’ intention to adopt technology.
– UTAUT1, with its broader scope and added moderators, significantly improved predictive power, explaining up to 70% of the variance in behavioral intention and technology use.

UTAUT2 (Extension of UTAUT1)
In 2012, Venkatesh et al. introduced UTAUT2, which was aimed at consumer technology use, expanding the original UTAUT model. Here’s how it differs from UTAUT1 and improves upon it:

1. Additional Constructs:
– UTAUT2 added three new constructs:
– Hedonic Motivation: The enjoyment or pleasure derived from using the technology.
– Price Value: The trade-off between the perceived benefits of the technology and the cost of acquiring or using it.
– Habit: The extent to which people use technology habitually, which influences both behavioral intention and actual use.

These additions made UTAUT2 more suitable for consumer settings, where personal preferences, enjoyment, and cost factors are more significant than in organizational contexts.

2. Applicability to Consumer Context:
– UTAUT1 was more suited for organizational contexts where technology adoption was often mandatory or tied to job performance.
– UTAUT2 expanded to include factors relevant to consumer behavior and voluntary adoption of personal technologies (e.g., smartphones, apps).

3. Predictive Power:
– UTAUT2 further improved the predictive power over UTAUT1, explaining up to 74% of the variance in behavioral intention and technology use in consumer settings.

Effectiveness of UTAUT1 vs. UTAUT2

1. UTAUT1 is better suited for organizational settings, where factors like social influence and facilitating conditions (e.g., technical support and infrastructure) play a more critical role in technology adoption.
2. UTAUT2 is more effective in consumer markets, where factors like habit, enjoyment (hedonic motivation), and price considerations are more relevant. It captures additional layers of human behavior that are important when technology adoption is voluntary.

Summary of Strengths:

• UTAUT1 is excellent for understanding workplace adoption of technology, considering its utility and the social/infrastructural context of its use.
• UTAUT2 extends these insights into the consumer domain, adding constructs that explain personal preferences and voluntary use.
• Both models significantly outperform TAM1 and TAM2 in predictive power due to incorporating additional variables and moderators.

In conclusion, UTAUT1 and UTAUT2 are more comprehensive, predictive, and versatile than TAM models and are tailored to specific settings (organizational vs. consumer).