Category: Theory and Model

What is the meaning of the theory and model?

First of all, A theory is a set of statements that is produced through a method of continued considerations. In addition, A theory is a generalized report directed at describing a phenomenon. Finally, A model is a deliberate representation of reality. As you can see, both share common elements in their definitions.

Components of the Technology Acceptance Model TAM

The components of the technology acceptance model refer to the dependent, independent, moderator, and mediator variables of TAM theories. Understanding the components of the technology acceptance model is crucial for students, researchers, and HR professionals. It helps professionals understand why people adopt and use the new systems. The researchers adopt the technology acceptance model questionnaire to conduct new research in different fields. The components of the technology acceptance model help top management understand user behavior towards new systems, AI, Gemini AI, and ChatGPT in organizations. They predict acceptance rates and set the implementation strategy, addressing perceived usefulness and ease of use elements of the TAM model.

This article explains the components of the technology acceptance model (TAM) from 1986 to 2008. Based on the literature review, many articles describe the elements of the technology acceptance model (TAM) published in 1989; however, this article presents the components of the TAM model as published in 1986, 1989, 1993, 1996, 2000, and 2008.

components of the TAM model as published in 1986, 1989, 1993, 1996, 2000, and 2008.

Components of TAM Model-1, 2, & 3 at a Glance

TAM Model Authors Establish Year Variables
Technology Acceptance Model (TAM) Fred D. Davis 1986 Perceived Usefulness, Perceived Ease of Use, and Attitude toward using the system. (Feature: X1, X2, and X3)
Technology Acceptance Model (TAM) Fred D. Davis 1989

Perceived Usefulness, Perceived Ease of Use, Attitude toward Use, Behavioral Intention. (External Variables)
Technology Acceptance Model (TAM) Fred D. Davis 1993

Perceived Usefulness, Perceived Ease of Use, Attitude Toward Using, Actual Usage Behavior. (System Design Features)
Technology Acceptance Model (TAM-1) Venkatesh and Davis 1996 Perceived Usefulness, Perceived Ease of Use, User Behavioral Intention (External Variables).
Extended Technology Acceptance Model (TAM 2) or ETAM Venkatesh and Davis 2000 Perceived Usefulness, Perceived Ease of Use, Intention to Use, Use Behavior, and (Subjective Norm, Voluntariness, Image, Job Relevance, Output Quality, Result Demonstrability, Experience, and Voluntariness)
The Technology Acceptance Model (TAM-3) Venkatesh & Bala 2008 Perceived Usefulness, Perceived Ease of Use, Behavioral Intention, Use behavior, and (Subjective Norm, Voluntariness, Image, Job relevance, Output Quality, Result Demonstrability, Experience, Voluntariness, Computer Self-Efficacy, Perception of External Control, Computer Anxiety, Computer Playfulness, Perceived Enjoyment, Objective Usability)

These components of the technology acceptance model have evolved in diverse fields of study over the years.

Components of the Technology Acceptance Model (TAM-1986)

Initially, in 1986, Fred D. Davis included three elements: perceived usefulness, perceived ease of use, and attitude toward use. According to the technology acceptance model (Davis, 1986), the components of the technology acceptance model are:

  1.  Perceived Usefulness
  2. Perceived Ease of Use
  3. Attitude toward using the system

However, Fred D. Davis introduces external variables Design Feature: X1, X2, and X3 in the technology acceptance model.

Perceived Usefulness

Perceived Usefulness refers to the extent to which a person believes that using a particular system will enhance their job performance (Davis, 1986). It is a measurement factor that assesses how it influences users’ decisions to accept or reject the new system in the workplace. It is an outcome of the anticipated effect on productivity using the new system. For example, using ChatGPT enhances creating images to promote products on social media platforms. It is the most significant element of the technology acceptance model, as it measures people’s beliefs.

Perceived Ease of Use

Perceived ease of use is the degree to which a person believes that utilizing a certain system would be free of mental and physical pressure (Davis, 1986). It is the most significant construct to demonstrate a person’s belief in using the new system. PEOU identifies the user’s perception that the new system will require no or less effort. The user adopts and utilizes the new system when the PEOU is higher. For example, Gemini AI reduces employee workloads, enhancing content creation for product marketing. Perceived ease of use is another crucial component of the technology acceptance model.

Attitude Toward Use

Attitude toward using is a crucial explicit mediator variable in the TAM model that directly affects actual system use. ATU is a person’s emotional response to whether they accept the new system. According to the TAM model, perceived usefulness and perceived ease of use affect attitude toward use and actual use behavior (Davis, 1986).

Design Feature (External Variable)

Design features are external variables in the TAM model that positively affect two core cognitive beliefs: perceived usefulness and ease of use; however, they do not impact attitude or behavioral intention. They are external stimuli such as attributes, interface components, and technical capabilities of the new system. The researchers indicate these features, such as X₁, X₂, and X₃.

model illustrating technology acceptance components

TAM Model (Davis, 1986)

Fred D. Davis is the pioneer of the technology acceptance model. He is a professor at the University of Michigan School of Business Administration. His research interests include user acceptance of technology, technology support for decision-making, and motivational factors in computer acceptance.

Research Title: A technology acceptance model for empirically testing new end-user information systems: Theory and results

Author and Published Year: Fred D. Davis (Fred Donald Davis)- 1986

Publisher: Massachusetts Institute of Technology (MIT), Sloan School of Management

Components of the Technology Acceptance Model (Davis, 1989)

The components of the Technology acceptance model (Davis, 1989) are: external variables, perceived usefulness, perceived ease of use, attitude towards use, behavioral intention, and actual system use.

The six core elements of the TAM model ( Davis, 1989) are:

1. External Variables (EV) (Belief): Factors that influence the adoption of a new system, such as implementation strategy, context, and training methods.

2. Perceived Usefulness (PU): The measurement of a person’s belief in using the new system to enhance productivity in the workplace. It is commonly believed that adopting new technology helps to improve performance.

3. Perceived Ease of Use (PEOU): It is the degree to which a person assumes that the new system helps to complete tasks smoothly without hassle.

4. Attitude Toward Use (ATU): It is an overall affective response of users that the new system is good for us. It is a core variable to determine the user’s emotional reaction to whether to accept or reject the new system. It affects people’s contemporary psychology and actions.

5. Behavioral Intention (BI): It is a crucial component of the technology acceptance model that indicates the user has decided to use the new system in the workplace. It prompts users to implement the new system in both personal and professional contexts.

6. Actual System Use (ASU): It is a dependable variable in the technology acceptance model that refers to the degree to which users accept the new system and apply it in real-life activities. It measures how the new system works when people use it to complete regular tasks.

Difference Between the TAM 1986 and TAM 1989

According to the technology acceptance model (Davis, 1989), Perceived Usefulness (PU) directly influences the user’s Behavioral Intention to accept and use the new system. PU bypasses the Attitude Toward Use entirely and positively affects BI.

components of the technology acceptance model davis 1989 with six elements

TAM Model (Davis, 1989)

Research Title: Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology

Author and Published Year: Fred D. Davis- 1989

Publisher: Management Information Systems Research Center (MISRC), University of Minnesota (via the journal MIS Quarterly)

Components of the Technology Acceptance Model (TAM) (Davis et al., 1989)

The components of the technology acceptance model (Davis et al., 1989) are:
  1. External Variables (EV) (Belief)
  2. Perceived Usefulness (PU)
  3. Perceived Ease of Use (PEOU)
  4. Attitude Toward Use (ATU)
  5. Behavioral Intention (BI)
  6. Actual System Use (ASU)

According to the technology acceptance model (Davis et al., 1989), its components explain why users accept new computer technology. It also helps explain user behavior towards the adoption of new computer technology.

The Technology Acceptance Model (TAM) explains users’ intention to adopt technology through three variables: perceived usefulness, perceived ease of use, and attitude toward use.

Technology Acceptance Model (TAM) (Davis et al., 1989)

In 1989, Fred D. Davis, Richard P. Bagozzi, and Paul R. Warshaw presented the technology acceptance model in the research paper “User Acceptance of Computer Technology: A Comparison of Two Theoretical Models,” published by the Institute for Operations Research and the Management Sciences (INFORMS) located in Maryland, USA. The TAM model was derived from the Theory of Reasoned Action (TRA), which describes the factors that stimulate people to change their behavior.

  • Research Title: User Acceptance of Computer Technology: A Comparison of Two Theoretical Models.
  • Author & Published Year: Fred D. Davis, Richard P. Bagozzi, and Paul R. Warshaw in 1989.
  • Publisher: INFORMS

Components of the Technology Acceptance Model (TAM) (Davis, 1993)

The five components of the technology acceptance model (Davis, 1993) are:

  1. System Design Features:
  2. Perceived Usefulness
  3. Perceived Ease of Use
  4. Attitude Toward Using
  5. Actual Usage Behavior
components of the technology acceptance model (tam) (davis, 1993)

TAM Model (Davis, 1993)

  • Research Title: User Acceptance of Information Technology: System Characteristics, User Perceptions, and Behavioral Impacts.
  • Author & Published Year: Fres D Davis- 1993
  • Publisher: University of Michigan, Business School, Ann Arbor, M1 48109, USA.

Components of the Technology Acceptance Model (TAM-1): Venkatesh and Davis, 1996

Variables: Perceived Usefulness, Ease of Use, User’s Behavioral Intention, and (External Variables)

External variables: Computer self-efficacy and Objective Usability

However, in 1996, Viswanath Venkatesh and Fred D. Davis included the variable “Attitude toward Using” in the previous model and outlined the final version of the Technology Acceptance Model.

components of the technology acceptance model (tam-1): venkatesh and davis, 1996

TAM Model (Venkatesh and Davis, 1996)

Research Title: A Model of the Antecedents of Perceived Ease of Use: Development and Test

Authors and Published Year: Viswanath Venkatesh and Fred D. Davis- 1996

Publisher: Wiley (on behalf of the Decision Sciences Institute via the journal Decision Sciences)

Technology Acceptance Model (TAM-2) Components

The components of the technology acceptance model (Venkatesh and Davis, 2000) are:

  •  Perceived Usefulness
  • Perceived Ease of Use
  • Intention to Use
  • Use Behavior
  • (Subjective Norm, Voluntariness, Image, Job relevance, Output Quality, Result Demonstrability, Experience, and Voluntariness)
components of the technology acceptance model tam 2 colorful diagram

TAM 2 Model Elements

Subjective Norm (SN): It is a crucial component of the technology acceptance model that directly affects perceived usefulness and indirectly affects it through another construct, Image. SN is the social influence of people close to them. This variable determines how your close people influence you, depending on their acceptance and use of the new system and technology.

Image (IMG): Image is a social pressure construct that influences people to adopt a new system to improve their status within an organization or society.

Job Relevance (JR): It is another key construct of PU that influences people to use the new system to complete a specific job in the organization. It is the degree to which people believe the technology is an ideal tool for completing their jobs.

Output Quality (OQ): It is a cognitive instrumental process that determines how well the new technology accomplishes the specific tasks required for the job.

Result Demonstrability (RD): It is a core cognitive instrument that identifies the tangible significance of the new system in performance.

Experience: It represents how experience affects the ability to accept and navigate new technology. Users rely on subjective norms when they have little experience, and, as their experience grows, they evaluate the new system based on skills rather than peer pressure.

Voluntariness of Use: It indicates whether use of the new system in the workplace is compulsory or discretionary. Social influence has a stronger positive impact on acceptance of the new system when it is mandatory.

TAM 2 Model Published Paper Details

TAM originated with Venkatesh and Davis in 2000, building on earlier work. Instead of just one idea, it added more reasons people find tech useful – like peer pressure or practical benefits. This version shows how factors such as coworkers’ perceptions, job fit, quality of results, and clear outcomes shape whether someone uses a system.

Research Title: A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies

Authors and Published Year: Viswanath Venkatesh and Fred D. Davis- 2000

Publisher: Institute for Operations Research and the Management Sciences (INFORMS), via the journal Management Science

Components of the Technology Acceptance Model (TAM-3)

The components of the technology acceptance model (Venkatesh and Bala, 2008) are:

  • Perceived Usefulness
  • Perceived Ease of Use
  • Behavioral Intention
  • Use behavior
  • (Subjective Norm, Voluntariness, Image, Job relevance, Output Quality, Result Demonstrability, Experience, Voluntariness, Computer Self- Efficacy, Perception of External Control, Computer Anxiety, Computer Playfulness, Perceived Enjoyment, Objective Usability)

TAM- 3 Model Elements

Computer Self‑Efficacy (CSE): CSE is the primary anchor construct of perceived ease of use (PEOU), representing the user’s ability and confidence in using the new system. It shows how confident people feel in using the new technology to complete a specific task in the workplace.

Perception of External Control (PEC): It is another crucial determinant of PEOU, representing the user’s belief that the organization will provide support, such as technical support and training to use the new system.

Computer Anxiety (CA): CA is an adverse feeling that hinders a user’s acceptance and use of a new system in the workplace. CA is an emotional barrier to adopting new technology.

Computer Playfulness (CP): It is an anchoring factor that enhances people’s primary willingness to accept and interact with the new system.

Perceived Enjoyment (PE): It is an adjustment construct in the technology acceptance model (TAM-3) that influences behavioral intention through perceived ease of use. Perceived enjoyment reflects users’ fun and experience when adopting and interacting with the new system in the workplace.

Objective Usability (OU): It is another adjustment construct that directly affects perceived ease of use to influence behavioral intention to use the new system. Objective Usability refers to data on how easily people can navigate the system to obtain precise results.

The author explains other variables (Subjective Norm, Voluntariness, Image, Job relevance, Output Quality, Result Demonstrability, Experience, and Voluntariness) in the component of the technology acceptance model TAM-2 section in this article.

components of the technology acceptance model (tam-3)

TAM 3 Model Publishing Paper Details

The Technology Acceptance Model (TAM3) was introduced by Venkatesh and Bala in 2008. TAM-3 provides valuable rational explanations of how and why individuals decide to adopt and use ITs, particularly the work on the determinants of perceived usefulness and perceived ease of use.

Research Title: Technology Acceptance Model 3 and a Research Agenda on Interventions

Authors and Published Year: Viswanath Venkatesh and Hillol Bala in 2008

Publisher: Decision Sciences Journal.

Edited by: Nagesh Murthy, University of Oregon; Liangfei Qiu, University of Florida

Conclusion: Components of TAM models

In conclusion, the key elements of the technology acceptance models are perceived usefulness and perceived ease of use, which influence attitudes towards using the new system. Understanding the core components of the technology acceptance model conveys significant insight into how organizations and policymakers adopt new systems. TAM is the most cited and accepted theory for understanding technological innovation and its application in organizations. Therefore, technology acceptance models make both theoretical and practical contributions across personal, social, and professional contexts.

FAQ (Frequently Asked Questions): Components of the Technology Acceptance Model

Q: What are the core components of the technology acceptance model?

A: The three key components of the technology acceptance model are Perceived Usefulness, Perceived Ease of Use, and Attitude toward using the new system.

Q: Who is the pioneer of the technology acceptance model (TAM)?

A: Fred D. Davis is the pioneer author of the TAM model.

Q: What is the original and final technology acceptance model?

Fred D. Davis introduced the final technology acceptance model in 1989, comprising six elements: external variables, perceived usefulness, perceived ease of use, attitude towards use, behavioral intention, and actual system use.

What is the most cited model in the field of information and communication technology?

TAM has been designated as the most-cited model in the field of information and communication technology (ICT).

What is the most significant theory to adopt for Artificial Intelligence AI adoption?

The technology acceptance model (TAM) is one of the most significant models of AI adoption.

References APA 7th Edition: Scholarly Sources

Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation, Massachusetts Institute of Technology, Sloan School of Management). Massachusetts Institute of Technology.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions, and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475–487. https://doi.org/10.1006/imms.1993.1022

Davis, F. D., & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the Technology Acceptance Model: Three experiments. International Journal of Human-Computer Studies, 45(1), 19–45. https://doi.org/10.1006/ijhc.1996.0040

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315.

UTAUT Model 4 Key Variables and Questionnaire Explanation

This article discusses the UTAUT Model, also known as the Unified Theory of Acceptance and Use of Technology, along with its variables, questionnaires, examples, advantages, and drawbacks. Additionally, it showcases the Venkatesh Questionnaire related to the UTAUT Model. The UTAUT Model identifies four key constructs that influence user acceptance: performance expectancy, effort expectancy, social influence, and facilitating conditions. Each of these variables plays a critical role in determining how individuals perceive and utilize new technologies.

What is the UTAUT Model?

The UTAUT model (Unified Theory of Acceptance and Use of Technology) was developed by Venkatesh, Morris, Davis, and Davis in 2003. UTAUT is the short form of the Unified Theory of Acceptance and Use of Technology.

The unified theory of acceptance and use of technology (UTAUT) is one of the most up-to-date and widely accepted models of technology adoption.

This study used a longitudinal qualitative design and found that around 70% of Behavioral Intention to Use (BI) and about 50% of actual use.

Viswanath Venkatesh and other authors proposed this theory based on a review of eight models that examine factors affecting information systems usage behavior. It is an extension of the eight-technology adoption models.  The authors mentioned the eight theories in the paper’s abstract. The UTAUT model was adopted from eight earlier models.

The eight models adopted for the UTAUT model development are as follows:
  1. Theory of Reasoned Action (TRA)
  2. Technology Acceptance Model (TAM)
  3. Motivational Model (MM)
  4. Theory of Planned Behavior
  5. Combined Theory of Planned Behavior/Technology Acceptance Model
  6. Model of Personal Computer Use
  7. Diffusion of Innovations Theory (DIT)
  8. Social Cognitive Theory (SCT)

The authors collected and used data from four organizations over six months to observe and record changes in variables.

The data were analyzed using three measurement points.

Based on the user acceptance literature, the UTAUT model is widely used to identify factors influencing users’ adoption of new technologies and information systems.

Venkatesh et al. (2003) identified four constructs that directly and indirectly determine users’ motivation to use systems (Venkatesh, Morris, Davis & Davis, 2003).

The three constructs are: 1. Performance Expectancy, 2. Effort Expectancy, and 3. Social Influence. These determine the intention to use the technology through behavioral intention (Venkatesh, Morris, Davis & Davis, 2003).

The fourth characteristic, Facilitating Conditions, directly determines the intention to use the technology.

The UTAUT model also presents four moderator variables: Age, Gender, Experience, and Voluntariness of Use.

utaut model
UTAUT Model Framework

UTAUT Model Basic Info

Authors: Viswanath Venkatesh, Michael G. Morris, Gordon B. Davis, and Fred D. Davis
Title: “User acceptance of information technology: Toward a unified view”
Publishers: Management Information Systems Research Center, University of Minnesota
DOI URL: https://www.jstor.org/stable/30036540
Research Strategy: Survey
Methodological Choice: Mono-method Qualitative
Time Horizon: Longitudinal

What is the UTAUT Model Full Form?
The full form of UTAUT is: Unified Theory of Acceptance and Use of Technology

The Management Information Systems Research Center at the University of Minnesota published the UTAUT model in 2003, titled “User Acceptance of Information Technology: Toward a Unified View.”(Venkatesh, Morris, Davis & Davis, 2003).

unified theory of acceptance and use of technology  (utaut) model

Unified Theory of Acceptance and Use of Technology  (UTAUT) Model

Previous research has validated the unified theory of technology acceptance and use as a comprehensive theoretical model for predicting the intention to adopt new technologies and systems across diverse contexts. Consequently, the UTAUT model provides an in-depth understanding of the factors that predict individuals’ acceptance and use of new systems or tools. The UTAUT model describes why and how users adopt new systems and technology. This theory posits that performance expectancy, effort expectancy, facilitating conditions, and social influence influence people’s use of new systems in social and organizational contexts.

Many researchers have extended this theory to examine factors influencing the acceptance of new systems across different contexts. For example, in 2012, Venkatesh, L. Thong, and Xin Xu extended the UTAUT model to examine consumer acceptance and use of technology.

Variables of the UTAUT Model

What are the determinants of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model?

The UTAUT model comprises four independent or predictor variables (1. Performance Expectancy, 2. Effort Expectancy, 3. Social Influences, 4. Facilitating Conditions), four moderators (1. Age, 2. Gender, 3. Experience, 4. Voluntariness of Use), and a dependent variable (Behavioral Intention).

The Elements of the UTAUT Model are:

  1. Performance Expectancy
  2. Effort Expectancy
  3. Social Influences
  4. Facilitating Conditions
  5. Behavioral Intention and Use Behavioral
  6. Moderating Variables (Age, Gender, Experience, and Voluntariness of Use)

The Additional Variables of the UTAUT Model are:

The four additional moderator variables are:
  1. Gender
  2. Age
  3. Experience
  4. Voluntariness of use
1. Performance Expectancy (PE)

Performance expectancy is a predictor variable that considers how the new system will help users improve performance in completing the task (Venkatesh et al., 2003). It validates why the new system is advantageous for individual performance and improves efficacy. It also simulates the decision-making process behind their use of the system.

In social contexts, people adopt new technologies when they perceive benefits. Performance expectancy refers to the perceived importance of new systems and technologies, influencing individuals to adopt them. Based on the UTAUT model, the researcher can hypothesize that when people perceive new systems and technologies as helpful tools, they will use them in personal, social, and professional contexts. In sum, Performance expectancy will positively influence users’ acceptance and use of the new system to complete a particular task.

 2. Effort Expectancy (EE)

Effort expectancy is another crucial independent variable that assesses how easy and effortless it will be to complete tasks using the new technology (Venkatesh et al., 2003). Researchers employ this construct to examine ease of use. It represents the extent to which users find modern technology easy to learn and operate. Effort expectancy refers to the perceived ease of using the new technology. People will adopt new technology if the tools are easy to use, which affects their decision to adopt it.

However, users may not adopt the new system if it is difficult to operate or takes much longer than the previous technique.

Effort expectancy is a crucial factor in making adoption decisions at the beginning stage.

 3. Social Influence (SI)

Social influence is the extent to which users prioritize others’ beliefs and, as a result, adopt the new system (Venkatesh et al., 2003). It directly affects others’ behavioral intentions to adopt the technology. People change their technology use behaviors when they consider that others benefit from the new technology (Peng & Miller, 2021; Mortenson & Vidgen, 2016). Social influence can come from friends, colleagues, family members, relatives, and managers. It occurs at the initial stage, when individuals are expected to meet their own and others’ expectations.

For example, people adopt WeChat for social media news consumption because their peers recommend it. Based on the UTAUT model, researchers can hypothesize that people adopt new systems to complete specific tasks when they observe others using them for the same purpose.  Therefore, Social influence will influence users to accept and use new tools positively.

4. Facilitating Conditions (FC)

According to the UTAUT model, the facilitating condition is the degree to which an individual believes the organization provides infrastructural, resource, and technical support for the new system. It ensures the organization’s capability to adopt the latest tools to complete tasks. For example, IT companies can readily adopt artificial intelligence because they have skilled human resources and the technological infrastructure to use it effectively. In this scenario, experienced employees and modern technology facilitate the adoption of the new system.

Based on the UTAUT model, researchers can hypothesize that people adopt new systems to complete complex tasks when they perceive that they have the technical and infrastructural resources to operate them.

Therefore, the Facilitating Condition will influence users to accept and use new tools positively.

Behavioral Intention (BI) is the dependent variable and central element of the Unified Theory of Acceptance and Use of Technology (UTAUT) model.

It is defined as the individual’s intention to use a new technology or information system.

Behavioral Intention (BI) is the dependent variable and central element of the Unified Theory of Acceptance and Use of Technology (UTAUT) model. It is defined as the individual’s intention to use a new technology or information system. It is considered that a person will actually use the technology. Essentially, BI measures an individual’s readiness to adopt and use a new system.

Use Behavior (UB) is the ultimate dependent variable in the UTAUT model. The predicted outcome is also known as Actual Use Behavior.

Use Behavior (UB) is the ultimate dependent variable in the UTAUT model. The predicted outcome is also known as Actual Use Behavior. The UB is the outcome variable in the Unified Theory of Acceptance and Use of Technology (UTAUT). In the context of the UTAUT model, Use Behavior is the observable, measurable act of using a technology or information system in real-world settings.

6. Moderating Variables (Age, Gender, Experience, and Voluntariness of Use)

The UTAUT model also includes four moderating variables: age, gender, experience, and voluntariness of use.

These variables affect the strength of the relationships between the independent variable (Behavioral Intention) and the dependent variables (Performance Expectancy, Effort Expectancy, Social Influences, Facilitating Conditions).

UTAUT Model: Moderating Factors
  • Gender: Moderates only three variables (PE, EE, and SI).
  • Age: Moderates all four variables (PE, EE, SI, and FC).
  • Experience: Moderates only three determinants (EE, SI, and FC).
  • Voluntariness of use: Moderates only the relationship between Social Influence (SI) and Behavioral Intention (BI). 

UTAUT Model Venkatesh Questionnaire

Venkatesh and other authors used the following items to estimate the UTAUT model, also known as the Unified Theory of Acceptance and Use of Technology (UTAUT). However, the authors removed the three determinants—self-efficacy, anxiety, and attitude—from the model.  Finally, they retained four predictive determinants. The researchers have adopted these research questionnaires to conduct diverse research in different contexts.

For example, Abdullah M. Baabdullah adopted UTAUT model questionnaires to validate his research questionnaire, estimating “The precursors of AI adoption in business.”

utaut model item to estimate hypotheses
UTAUT Model Questionnaire

UTAUT Model Questionnaire

Item Used To Estimate UTAUT Model Hypotheses

Performance Expectancy: 4 Questionnaire Items

U6: I would find the system useful in my job.
RA1: Using the system enables me to accomplish tasks more quickly.
RA5: Using the system increases my productivity.
OE7: If I use the system, I will increase my chances of getting a raise.

Effort Expectancy: 4 Questionnaire Items

EOU3: My interaction with the system would be clear and understandable.
EOU5: It would be easy for me to become skillful at using the system.
EOU6: I would find the system easy to use.
EU4: Learning to operate the system is easy for me.

Attitude Toward Using Technology: 4 Questionnaire Items

A1: Using the system is a bad/good idea.
AF1: The system makes work more interesting.
AF2: Working with the system is fun.
Affect1: I like working with the system.

Social Influence: 4 UTAUT Model Questionnaire Items

SN1: People who influence my behavior think that I should use the system.
SN2: People who are important to me think that I should use the system.
SF2: The senior management of this business has been helpful in the use of the system.
SF4: In general, the organization has supported the use of the system.

Facilitating Conditions: UTAUT Model 4 Questionnaire Items

PBC2: I have the resources necessary to use the system.
PBC3: I have the knowledge necessary to use the system.
PBC5: The system is not compatible with other systems I use.
FC3: A specific person (or group) is available for assistance with system difficulties.

Self-Efficacy (Dropped) From UTAUT Model Questionnaire

I could complete a job or task using the system…
SE1: If there was no one around to tell me what to do as I go.
SE4: If I could call someone for help if I got stuck.
SE6: If I had a lot of time to complete the job for which the software was provided.
SE7: If I had just the built-in help facility for assistance.

Anxiety (Dropped) From UTAUT Model Questionnaire

ANX1: I feel apprehensive about using the system.
ANX2: It scares me to think that I could lose a lot of information using the system by hitting the wrong key.
ANX3: I hesitate to use the system for fear of making mistakes I cannot correct.
ANX4: The system is somewhat intimidating to me.

Behavioral Intention to Use the System: 3 Questionnaire Items

BI1: I intend to use the system in the next months.
B12: I predict I would use the system in the next months.
B13: I plan to use the system in the next months.

UTAUT Model Limitations

The author has identified the following limitations and shortcomings of the UTAUT model in several leading papers.

Firstly, the authors analyzed secondary rather than primary data, which is a limitation of this model.

Primary data are convenient for assessing mediators and moderators. An additional shortcoming of the UTAUT model is the variability in findings across longitudinal research designs, as long-term studies may yield unexpected results.

UTAUT Model Significance

The academic significance of the Unified Theory of Acceptance and Use of Technology model includes Theory Consolidation, Strong Predictive Power, Identification of Key Variables, Inclusion of Moderating Variables, and Foundation for Future Research.

The practical significance of the UTAUT model includes an Evidence-Based Tool, Problem Identification, Multidimensional Evaluation, and Targeted Interventions.

In summary, the UTAUT Model remains a key framework in understanding technology adoption and user behavior. The UTAUT Model provides a comprehensive framework for understanding technology adoption and user behavior.

Difference Between TAM and UTAUT Model

CriteriaTechnology Acceptance Model (TAM)Unified Theory of Acceptance and Use of Technology (UTAUT)
Origin & DevelopersDeveloped by Fred Davis (1986, 1989) as an extension of the Theory of Reasoned Action (TRA).Developed by Venkatesh et al. (2003) by integrating eight previous technology adoption models, including TAM, TRA, MM, TPB, DIT, SCT, TPB, and CTPB.
PurposeTo explain users’ acceptance of technology through two central beliefs: usefulness and ease of use (Davis, 1989).To create a unified, more comprehensive model that improves the prediction of technology acceptance and usage behavior.
Key Constructs1. Perceived Usefulness (PU): belief that technology improves performance.
2. Perceived Ease of Use (PEOU): belief that technology is free of effort. These lea
2. Lead to Attitude, Behavioral Intention, and Actual Use.		1. Performance Expectancy (PE): similar to PU.
2. Effort Expectancy (EE): similar to PEOU.
3. Social Influence (SI): influence from people who matter.
4. Facilitating Conditions (FC): resources/support available. Leads directly to Behavioral Intention and Use Behavior.
Model ComplexitySimple and easy to apply; widely used in academic studies.More complex with additional constructs and moderators, but provides better predictive accuracy.
Moderating VariablesUses fewer moderators, such as experience or demographic factors (not originally included).Includes Age, Gender, Experience, and Voluntariness of Use as key moderators, strengthening predictive power.
Predictive Power
Moderate predictive ability (~40% variance explained in intention).High predictive ability (up to 70% variance explained in intention).
Attitude Toward UseExplicitly includes Attitude as a mediator between beliefs and intention.Attitude is removed; UTAUT assumes that core constructs already capture user motivation.
Focus of MeasurementMeasures individual cognitive beliefs (usefulness and ease).Measures cognitive, social, and organizational influences on usage.
Strengths1. Simple and widely validated.
2. Easy to adapt and modify.
3. Useful for early-stage technology studies.		1. High explanatory power.
2. Considers social and institutional factors.
3. Effective for organizational and workplace technologies.
Limitations1. Ignores social and facilitating factors.
2. Oversimplified for complex organizational environments.
3. Limited predictive accuracy (Davis & Venkatesh, 1996).		1. More difficult to apply due to complexity.
2. Requires detailed data for moderators.
3. May be less suitable for small-scale studies.
Best Use CasesSuitable for studies on basic consumer technologies, apps, websites, or early user acceptance.Suitable for workplace, enterprise systems, e-learning platforms, and contexts with strong social/organizational influence.
Overall Difference SummaryTAM is simpler, focuses on two beliefs (PU & PEOU), and is primarily cognitive (Davis, 1989).UTAUT is more comprehensive, integrating cognitive, social, and organizational factors to enhance predictive power.
FAQ (Frequently Asked Questions): UTAUT Model

Q: What is the latest model to adopt a questionnaire for AI Adoption?

A: The UTAUT is the most appropriate model to adopt questionnaire items for a technology acceptance study.

Q: What is the UTAUT model’s original reference for citation?

A: Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425-478.

References APA 7th Edition: Scholarly Sources

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425-478.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Davis, F. D., & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the Technology Acceptance Model: Three experiments. International Journal of Human-Computer Studies, 45(1), 19–45. https://doi.org/10.1006/ijhc.1996.0040

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