The DOI matches its Crossref record; 135 of the 135 references it cites were found in a registry or an index; 2 of the 55 sources its claims cite were checked for support.
Technology Acceptance Model 3 and a Research Agenda on Interventions
Open accessAbstract
ABSTRACT Prior research has provided valuable insights into how and why employees make a decision about the adoption and use of information technologies (ITs) in the workplace. From an organizational point of view, however, the more important issue is how managers make informed decisions about interventions that can lead to greater acceptance and effective utilization of IT. There is limited research in the IT implementation literature that deals with the role of interventions to aid such managerial decision making. Particularly, there is a need to understand how various interventions can influence the known determinants of IT adoption and use. To address this gap in the literature, we draw from the vast body of research on the technology acceptance model (TAM), particularly the work on the determinants of perceived usefulness and perceived ease of use, and: (i) develop a comprehensive nomological network (integrated model) of the determinants of individual level (IT) adoption and use; (ii) empirically test the proposed integrated model; and (iii) present a research agenda focused on potential pre‐ and postimplementation interventions that can enhance employees' adoption and use of IT. Our findings and research agenda have important implications for managerial decision making on IT implementation in organizations.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
51 Own result · 35 Own interpretation · 21 No full text of the sources · 13 Sources not found · 7 Own method · 5 Not checked yet · 2 No basis given · 1 Supported · 1 Partly supported · accuracy not yet measured
Every source the paper cites for this claim was checked and supports it.
In the paper
“Venkatesh and Speier (1999) investigated the effect of mood during training on user acceptance and found that mood during training played an important role in forming individuals' perceptions of a new IT.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Training
What the sources say
- Supportedcites Venkatesh & Speier, 1999 source
The Short-Term Mood Effects section links mood during computer training to perceptions of enjoyment in using the technology. The Discussion reports that negative mood during training reduced intrinsic motivation and intentions to use it, supporting the citing sentence’s broad characterization of the finding. The copy provides no page numbers for these passages. (LLM, conf=0.91)
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The two-way interaction between subjective norm and voluntariness (SN × EXP) indicated that the effect of subjective norm on behavioral intention was stronger in a mandatory context.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Explaining and Predicting Behavioral Intention and Use
hedgedstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Participants who completed all measurement points are representative of the initial user populations at the four sites.
- Rests on an assumption: The four sites' data can be pooled for the PLS analysis despite differences in industry, organizational context, and technology.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we found that experience moderated the effect of computer anxiety on perceived ease of use such that the effect became weaker with increasing experience (CANX × EXP).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Explaining and Predicting Perceived Usefulness
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Participants who completed all measurement points are representative of the initial user populations at the four sites.
- Rests on an assumption: The four sites' data can be pooled for the PLS analysis despite differences in industry, organizational context, and technology.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“experience moderated the effect of perceived ease of use on perceived usefulness such that with increasing experience the effect became stronger.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Explaining and Predicting Perceived Usefulness
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Participants who completed all measurement points are representative of the initial user populations at the four sites.
- Rests on an assumption: The four sites' data can be pooled for the PLS analysis despite differences in industry, organizational context, and technology.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, TAM3 was able to explain between 52% and 67% of the variance in perceived usefulness across different time periods and models (see Table 5).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Explaining and Predicting Perceived Usefulness
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Participants who completed all measurement points are representative of the initial user populations at the four sites.
- Rests on an assumption: The four sites' data can be pooled for the PLS analysis despite differences in industry, organizational context, and technology.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we found that job relevance and output quality had an interactive effect on perceived usefulness such that with increasing output quality, the effect of job relevance on perceived usefulness was stronger.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Explaining and Predicting Perceived Usefulness
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Participants who completed all measurement points are representative of the initial user populations at the four sites.
- Rests on an assumption: The four sites' data can be pooled for the PLS analysis despite differences in industry, organizational context, and technology.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found that experience, in fact, moderated the effect of perceived ease of use (PEOU × EXP) on behavioral intention such that with increasing experience the effect became weaker.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Explaining and Predicting Behavioral Intention and Use
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Participants who completed all measurement points are representative of the initial user populations at the four sites.
- Rests on an assumption: The four sites' data can be pooled for the PLS analysis despite differences in industry, organizational context, and technology.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The square root of the average variance extracted (AVE) for each construct was higher than the correlations across constructs.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Measurement Models
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As Table 4 shows, internal consistency reliabilities (ICRs) were greater than .70 for all constructs at all points of measurement.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Measurement Models
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Table 3 shows that the item loadings were greater than or at least equal to .70 for all constructs at all time periods.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Measurement Models
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 25
- The quote only partly states this claim. 4
- Probably not a substantial claim. 26
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Further, incentive alignment, and an important extrinsic reward, may reduce anxiety and increase perceived enjoyment as extrinsic rewards are considered important drivers of intrinsic motivations (Vallerand, 1997;Deci, Koestner, & Ryan, 1999;Ryan & Deci, 2000).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Incentive alignment
What the sources say
- Not checked — no full text of the sourcecites Vallerand, 1997 source
- Partly supportedcites Deci, Koestner, & Ryan, 1999 sourceExperimental — accuracy not yet measured
The Results report that verbal rewards (positive feedback) enhanced self-reported interest, which offers limited support for the possibility that an extrinsic reward could increase enjoyment. But the paper does not assess incentive alignment or anxiety, and its Concluding Comments (pp. 658–659) say tangible rewards generally diminish rather than promote intrinsic motivation. The cited source therefore does not support the proposed effect of incentive alignment. (LLM, conf=0.83)
- Not checked — no full text of the sourcecites Ryan & Deci, 2000 source
hedgedstates a possible cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we found that perceived ease of use, subjective norm, image, and result demonstrability were significant predictors of perceived usefulness at all time periods (see Table 5).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Explaining and Predicting Perceived Usefulness
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Participants who completed all measurement points are representative of the initial user populations at the four sites.
- Rests on an assumption: The four sites' data can be pooled for the PLS analysis despite differences in industry, organizational context, and technology.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While perceived ease of use was significant at T1 and T2, it was not significant at T3, suggesting a moderating effect of experience in the relationship between perceived ease of use and behavioral intention.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Explaining and Predicting Behavioral Intention and Use
hedgedstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Participants who completed all measurement points are representative of the initial user populations at the four sites.
- Rests on an assumption: The four sites' data can be pooled for the PLS analysis despite differences in industry, organizational context, and technology.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the adjustments-that is, perceived enjoyment and objective usability-were not significant at T1, but they were significant at both T2 and T3.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Explaining and Predicting Perceived Usefulness
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Participants who completed all measurement points are representative of the initial user populations at the four sites.
- Rests on an assumption: The four sites' data can be pooled for the PLS analysis despite differences in industry, organizational context, and technology.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“OU × EXP | | | | .20 * *”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Objective Usability (OU) | .04 | .19 * * | .23 * * * | .03”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“CANX × EXP | | | | .21 * * *”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Subjective Norm (SN) | .40 * * * | .32 * * * | .13 * | .04”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“SN × VOL | .29 * * * | .22 * * * | .17 * | .03”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Perceived Enjoyment (ENJ) | .02 | .22 * * * | .24 * * * | .04”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Result Demonstrability (RES) | .22 * * * | .26 * * * | .28 * * * | .26 * * *”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: fails — The authors may not put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The authors may not put it forward as true. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“CPLAY × EXP | | | | -.22 * * *”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Perceived Ease of Use (PEOU) | .22 * * * | .26 * * * | .33 * * * | .08”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“ENJ × EXP | | | | .18 * *”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Perceived Ease of Use (PEOU) | .24 * * * | .17 * | .05 | .04”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Although longitudinal studies were conducted, the specific moderating role by experience was not tested in Venkatesh (2000).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Determinants of Perceived Ease of Use
What the sources say
- Not matchedcites Venkatesh, 2000
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, in the context of enterprise systems, if an individual perceives that his or her use of the system does not benefit the members of his or her work units but rather benefits members from other work units, the user will perceive a lack of incentive alignment that may lead to low user acceptance and use of the system.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Incentive alignment
hedgedstates a possible cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“we conducted Harmon's single factor test and marker variable test (we used job satisfaction as a marker variable) and did not find any significant common method bias.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Measurement Models
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We used validated items from prior research to test TAM3.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Measurement
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Our research design allowed us to collect the use data separate from its determinants (e.g., behavioral intention, perceived usefulness, etc.).Particularly, there was at least a 1-month gap between the collection of survey data and the measurement of use.”
- Also stated in: § Measurement · plain
“Such a design approach helped us overcome the problems associated with common method biases.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Measurement
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Measurement · plain
In the paper
“Operationalization of the determinants of perceived ease of use (i.e., computer self-efficacy, perceptions of external control, computer playfulness, computer anxiety, objective usability, and perceived enjoyment) was consistent with Venkatesh (2000).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Measurement
What the sources say
- Not matchedcites Venkatesh (2000)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“It posits that individuals' behavioral intention to use an IT is determined by two beliefs: perceived usefulness, defined as the extent to which a person believes that using an IT will enhance his or her job performance and perceived ease of use, defined as the degree to which a person believes that using an IT will be free of effort.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > BACKGROUND
What the sources say
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“Ba et al. (2001) argued that while aspects of software engineering (e.g., system characteristics) and technology acceptance (e.g., perceived usefulness, perceived ease of use, user satisfaction) are important considerations for system development processes, organizations may fail to gain expected benefits from employees' effective utilization of a system unless employees find that the system fe”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Incentive alignment
What the sources say
- Not matchedcites Ba et al., 2001
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainstates a possible cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“All constructs at each time period exhibited strong psychometric properties and satisfied the criteria of reliability and convergent and discriminant validity.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Measurement Models
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“According to Ba et al. (2001), incentive alignment does not necessarily mean organizational rewards for using a system.It is a broad concept that entails an individual's perception that the IT fits with his or her job requirements and value system.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Incentive alignment
What the sources say
- Not matchedcites Ba et al., 2001
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
- Not matched
In the paper
“Chin, Marcolin, and Newsted (2003) noted that PLS has minimal restrictions in terms of distributional assumptions and sample size.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > We used Partial Least Squares (PLS), a component-based structural equation modeling technique, to analyze our data. PLS-Graph, version 3, build 1126 was used
What the sources say
- Not checked — no full text of the sourcecites Chin, Marcolin, and Newsted (2003) source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Mean-centering helps limit potential multicollinearity, evidenced by the low variation inflation factors (VIFs) for all constructs in our model.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > We used Partial Least Squares (PLS), a component-based structural equation modeling technique, to analyze our data. PLS-Graph, version 3, build 1126 was used
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Perceived usefulness is an instrumental belief that is conceptually similar to extrinsic motivation and is a cognition (as opposed to emotion) regarding the benefits of using a system.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Crossover Effects
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
In the paper
“It further theorizes that the effect of external variables (e.g., design characteristics) on behavioral intention will be mediated by perceived usefulness and perceived ease of use.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > BACKGROUND
What the sources say
- Not checked — no full text of the sourcecites Davis et al., 1989 source
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The research sites represented different industries, organizational contexts, and functional areas.Further, the types of ITs were different across the sites.Such variability in organizational settings and types of technologies adds to the potential generalization of our findings.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > METHOD
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“TAM constructs-that is, perceived usefulness (PU), perceived ease of use (PEOU), and behavioral intention (BI)-were operationalized using items adapted from Davis (1989) and Davis et al. (1989).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Measurement
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Incentive alignment has been suggested as the third dimension in systems design (Ba, Stallaert, & Whinston, 2001).The other two dimensions are software engineering and technology acceptance (Ba et al., 2001).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Incentive alignment
What the sources say
- Not matchedcites Ba et al., 2001
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Second, the modification and enhancement activities performed by peers will increase job relevance of a system, improve the output quality of a system, and reduce anxiety related to system use.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Peer support
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The implementation of interventions is, of course, not a silver bullet for greater IT adoption and effective utilization.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Implications for Decision Making
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“He also found that the effect of perceived ease of use on behavioral intention to use a system was stronger for individuals who received game-based training.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Training
What the sources say
- Not matchedcites Venkatesh, 1999
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainstates an association- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If we can develop a rich understanding of the determinants of IT adoption and use and interventions that can favorably influence these determinants, managers can proactively decide on implementing the right interventions to minimize resistance to new ITs and maximize effective utilization of ITs.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
plainstates a possible cause- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: ITs are becoming increasingly complex and implementation costs are very high.
- Rests on an assumption: Implementation failures of many of today's ITs cost millions of dollars for organizations.
In the paper
“Training has been suggested as one of the most important postimplementation interventions that leads to greater user acceptance and system success (see Sharma & Yetton, 2007).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Training
What the sources say
- Not checked — no full text of the sourcecites Sharma & Yetton, 2007 source
hedgedstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Organizational support captures the role of both internal and external experts who can help users deal with the complexity associated with new systems as well as business processes.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Organizational support
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Implementation of interventions can increase system development costs substantially.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Implications for Decision Making
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“TAM3 emphasizes the unique role and processes related to perceived usefulness and perceived ease of use and theorizes that the determinants of perceived usefulness will not influence perceived ease of use and vice versa.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Theoretical Contributions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Prior research has suggested that employees' perceptions regarding organizational support-that is, facilitating conditions or perceptions of external control (Taylor & Todd, 1995;Venkatesh, 2000;Venkatesh et al., 2003)-will lead to greater user acceptance of new systems.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Organizational support
What the sources say
hedgedstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our key argument in this article is that unless organizations can develop effective interventions to enhance IT adoption and use, there is no practical utility of our rich understanding of IT adoption.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Theoretical Contributions
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Rests on an assumption: There is little or no scientific research aimed at identifying and linking interventions with specific determinants of IT adoption.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We suggest that interventions discussed in this article can help organizations generate favorable individuals' reactions toward business process changes and process standards implementation.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Implications for Decision Making
hedgedstates a possible cause- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
In the paper
“For example, while self-efficacy may have weak influence on perceived usefulness as shown in Agarwal and Karahanna (2000), we argue that this influence will become nonsignificant in the presence of other important social and cognitive constructs.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Theoretical Contributions
What the sources say
- Not checked — no full text of the sourcecites Agarwal and Karahanna (2000) source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“TAM3 posits that perceptions of external control are important and stable determinants of perceived ease of use.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Organizational support
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Organizational support is a key source of perceptions of external control.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Organizational support
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, experts can help employees modify certain aspects of a new system, thus increasing job relevance, output quality, and results demonstrability of a system.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Organizational support
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Due to the complexity of ITs, it is increasingly difficult for employees to make effective decisions about adoption, utilization, and coping with new ITs.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Implications for Decision Making
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: ITs are becoming increasingly complex and implementation costs are very high.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“Some employees may react favorably to these changes, while the others may perceive these changes as a threat to their well-being (Orlikowski, 2000;Boudreau & Robey, 2005).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Postimplementation Interventions
What the sources say
hedgedstates a possible cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“TAM3 posits that with increasing experience, while the effect of perceived ease of use on behavioral intention will diminish, the effect of perceived ease of use on perceived usefulness will increase.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Theoretical Contributions
plainstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We suggest that the role of training will be even more important in the context of complex systems (e.g., enterprise systems) that are more central to employees' work life.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Training
hedgedstates a possible cause- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: Much prior research on training in the context of IT adoption has been conducted for simple ITs, such as word processing and e-mail.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As these systems are more likely to invoke negative reactions from employees because of their disruptive nature, effective training interventions can mitigate these negative reactions and help employees form favorable perceptions toward these systems.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Training
hedgedstates a cause- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
The paper relies on this without support.
Participants who completed all measurement points are representative of the initial user populations at the four sites.
“Out of 50 potential users of the system who participated in the training, 39 provided usable responses at all points of measurement.”
“Out of 51 potential users of the new system who attended the training, 43 provided usable responses at all points of measurement.”
“Out of 51 potential users of the new system, 36 provided usable responses at all points of measurement.”
The paper relies on this without support.
The four sites' data can be pooled for the PLS analysis despite differences in industry, organizational context, and technology.
“Data were collected from four different organizations-sites A through D-implementing new ITs.”
“The research sites represented different industries, organizational contexts, and functional areas.”
The paper relies on this without support.
Management support in individual-level IT adoption literature has been conceptualized and operationalized as organizational mandate and compliance.
“While management support has been conceptualized and operationalized as organizational mandate and compliance, particularly in the individual-level IT adoption literature, we suggest that there is a need to develop a richer conceptualization of management support to enhance our understanding of its role in IT adoption contexts.”
The paper relies on this without support.
There is limited research on the role of incentive alignment in IT adoption contexts.
“There is limited research on the role of incentive alignment in IT adoption contexts.”
The paper relies on this without support.
Much prior research on training in the context of IT adoption has been conducted for simple ITs, such as word processing and e-mail.
“However, much of the prior research on training in the context of IT adoption has been conducted for simple ITs, such as word processing and e-mail.”
The paper relies on this without support.
There is little or no research on the role of peer support in the context of IT adoption.
“While peer support is potentially an important intervention that can lead to greater user acceptance, there is little or no research on the role of peer support in the context of IT adoption.”
The paper relies on this without support.
There is little or no scientific research aimed at identifying and linking interventions with specific determinants of IT adoption.
“However, there is little or no scientific research aimed at identifying and linking interventions with specific determinants of IT adoption.”
The paper relies on this without support.
There have been numerous cases of enterprise system failures because of user resistance.
“There have been numerous cases of enterprise system failures because of user resistance.”
The paper relies on this without support.
In many cases, users stopped using an enterprise system because they saw no benefits of using the new system.
“In many cases, the users stopped using an enterprise system, as they saw no benefits of using the new system.”
The paper relies on this without support.
Other types of reactions, such as avoidance, sabotage, workarounds, and shortcuts, are prevalent.
“Other types of reactions, such as avoidance, sabotage, workarounds, and shortcuts are also prevalent.”
The paper relies on this without support.
ITs are becoming increasingly complex and implementation costs are very high.
“ITs are becoming increasingly complex and implementation costs are very high.”
The paper relies on this without support.
Implementation failures of many of today's ITs cost millions of dollars for organizations.
“Implementation failures of many of today's ITs cost millions of dollars for organizations.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source doesn’t support the claim as written.
In the citing paper
“the extensive focus of TAM on technology to the neglect of social and psychological parameters (Agarwal & Prasad, 1998;Venkatesh & Bala, 2008) limits its explanatory and predictive utilities, and therefore demands its integration with other frameworks”
From Using T-O-E theoretical framework to study the adoption of ERP solution (2016) · cites this paper as Venkatesh & Bala, 2008
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“A technology that provides information quickly and easily will lead to improvements in job performance, which in turn will encourage greater use of a given technology (Venkatesh and Bala, 2008).”
From Examining the antecedents of the technology acceptance model within e-procurement (2018) · cites this paper as Venkatesh and Bala, 2008
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“The adoption of new technologies is shaped by user perceptions and usage patterns (Venkatesh & Bala, 2008) as well as student characteristics and experiences (Abdaljaleel et al., 2023; Tiwari et al., 2024).”
From “ChatGPT seems too good to be true”: College students’ use and perceptions of generative AI (2024) · cites this paper as Venkatesh & Bala, 2008
The cited source says what the claim attributes to it.
In the citing paper
“It is proposed that perceived enjoyment is positively related to perceived ease of use [12].”
From Gender and Acceptance of E-Learning: A Multi-Group Analysis Based on a Structural Equation Model among College Students in Chile and Spain (2015) · cites this paper as [12]
The cited source says what the claim attributes to it.
In the citing paper
“The scales applied have been verified in preceding studies [12, 28].”
From Gender and Acceptance of E-Learning: A Multi-Group Analysis Based on a Structural Equation Model among College Students in Chile and Spain (2015) · cites this paper as [12]
The cited source says what the claim attributes to it.
In the citing paper
“Moreover, it is proposed that perception of external control is an element that conditions perceived ease of use [12].”
From Gender and Acceptance of E-Learning: A Multi-Group Analysis Based on a Structural Equation Model among College Students in Chile and Spain (2015) · cites this paper as [12]
The cited source says what the claim attributes to it.
In the citing paper
“It is proposed that result demonstrability is an antecedent of perceived usefulness [12].”
From Gender and Acceptance of E-Learning: A Multi-Group Analysis Based on a Structural Equation Model among College Students in Chile and Spain (2015) · cites this paper as [12]
The cited source says what the claim attributes to it.
In the citing paper
“which explains that users’ decisions to accept and use a technology are influenced by perceived usefulness, ease of use, and social influence of others.”
From Barriers to and facilitators of user engagement with digital mental health interventions: Systematic review (2021) · cites this paper as [253]
The cited source says what the claim attributes to it.
In the citing paper
“Some of the themes identified in this review overlap with previous models conceptualizing engagement with digital health interventions, as well as general technology acceptance and health behavior, such as the Efficiency Model of Support [251], Technology Acceptance Model [253], and Health Belief Model [249].”
From Barriers to and facilitators of user engagement with digital mental health interventions: Systematic review (2021) · cites this paper as [253]
The cited source says what the claim attributes to it.
In the citing paper
“Our findings are in line with the Technology Acceptance Model”
From Barriers to and facilitators of user engagement with digital mental health interventions: Systematic review (2021) · cites this paper as [253]
The cited source says what the claim attributes to it.
In the citing paper
“Information-related characteristics of a system can impact its PU as they can improve productivity and performance (Venkatesh and Bala, 2008).”
From Examining the antecedents of the technology acceptance model within e-procurement (2018) · cites this paper as Venkatesh and Bala, 2008
The cited source says what the claim attributes to it.
In the citing paper
“Firstly, considering usability , a reliable, flexible and user-friendly system is more likely to create a positive user experience (Venkatesh and Bala 2008).”
From Examining the antecedents of the technology acceptance model within e-procurement (2018) · cites this paper as Venkatesh and Bala 2008
The cited source says what the claim attributes to it.
In the citing paper
“A typical criticism of the TAM is in relation to its lack of practical managerial guidance (Venkatesh and Bala, 2008).”
From Examining the antecedents of the technology acceptance model within e-procurement (2018) · cites this paper as Venkatesh and Bala, 2008
The cited source says what the claim attributes to it.
In the citing paper
“Venkatesh and Bala (2008) present four generic antecedents to the TAM: i ndividual differences , system characteristics , social influence , and facilitating conditions .”
From Examining the antecedents of the technology acceptance model within e-procurement (2018) · cites this paper as Venkatesh and Bala (2008)
The cited source says what the claim attributes to it.
In the citing paper
“The model explains approximately 40% of the variance in individuals’ intention to use a new technology and actual use [39].”
From An Assessment of How Clinicians and Staff Members Use a Diabetes Artificial Intelligence Prediction Tool: Mixed Methods Study (2023) · cites this paper as [39]
The cited source says what the claim attributes to it.
In the citing paper
“It theorizes that individuals’ intention to use new technology is determined by perceived usefulness, defined as “the extent to which a person believes that using [a new technology] will enhance his or her job performance,” and perceived ease of use, defined as “the degree to which a person believes that using [a new technology] will be free of effort” [39].”
From An Assessment of How Clinicians and Staff Members Use a Diabetes Artificial Intelligence Prediction Tool: Mixed Methods Study (2023) · cites this paper as [39]
The cited source says what the claim attributes to it.
In the citing paper
“TAM's assertion that perceived usefulness is a primary determinant of technology acceptance and subsequent usage behaviors (Venkatesh & Bala, 2008).”
From The impact of AI-assisted pair programming on student motivation, programming anxiety, collaborative learning, and programming performance: a comparative study with traditional pair programming and individual approaches (2025) · cites this paper as Venkatesh & Bala, 2008
In the citing paper
“Currently, many studies contributing to the adoption research of mHealth for youths are based on the technology acceptance model, an information systems theory that models user’s acceptance of technology mainly based on perceived usefulness and perceived ease of use [48-50].”
From Understanding Mobile Health and Youth Mental Health: Scoping Review (2023) · cites this paper as [50]
In the citing paper
“Currently, many studies contributing to the adoption research of mHealth for youths are based on the technology acceptance model, an information systems theory that models user’s acceptance of technology mainly based on perceived usefulness and perceived ease of use [48-50].”
From Understanding Mobile Health and Youth Mental Health: Scoping Review (2023) · cites this paper as [50]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Measurement
“Specifically the measurements of use and its determinants were separated by 1 month (T1-T2), 3 months (T2-T3) and 2 months (T3-T4).”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Procedure
“after initial training (T1), 1 month after implementation (T2), and 3 months after implementation (T3).We also measured self-reported usage at T2, T3, and 5 months after implementation (T4).”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Additional information
“a All items were measured on a 7-point Likert scale (where 1: strongly disagree; 2: moderately disagree, 3: somewhat disagree, 4: neutral (neither disagree nor agree), 5: somewhat agree, 6: moderately agree, and 7: strongly agree), except computer self-efficacy, which was measured using a 10-point Guttman scale.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Additional information
“Use (USE) USE1 On average, how much time do you spend on the system each day?”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > Explaining and Predicting Behavioral Intention and Use
“The two-way interaction between subjective norm and voluntariness (SN × EXP) indicated that the effect of subjective norm on behavioral intention was stronger in a mandatory context.”
§ Technology Acceptance Model 3 and a Research Agenda on Interventions > CONCLUSIONS
“| SN × VOL | .29 * * * | .22 * * * | .17 * | .03 |”
Citations
Cites
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Self-citation(1975) · PhilPapers (PhilPapers Foundation) · Cited by 36,737
Multiple regression: testing and interpreting interactions
(1992) · Choice Reviews Online · doi:10.5860/choice.29-3352 · Cited by 36,647
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
Multiple Regression: Testing and Interpreting Interactions
Aiken, L., West, S. G., & Reno, R. R. (1991) · Oxford University Press eBooks · doi:10.1037/10520-147 · Cited by 24,912
A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066
Self-citationIntrinsic and Extrinsic Motivations: Classic Definitions and New Directions
Ryan, R. M., & Deci, E. L. (2000) · Contemporary Educational Psychology · doi:10.1006/ceps.1999.1020 · Cited by 18,666
Structural equation models with unobservable variables and measurement error: Algebra and statistics
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800313 · Cited by 13,287
Research works printed but not linked: 8
- Beach L. R., 1996, Decision making in the workplace: A unified perspective, 1
- Cohen D. S., 2005, Why change is an affair of the heart, CIO Magazine
- Gross G., 2005, Standards a must for adoption for health‐care IT, CIO Magazine
- Koch C., 2004, Nike rebounds: How (and why) Nike recovered from its supply chain disaster, CIO Magazine
- Mennecke B. E., 1998, Discovering and overcoming the hidden profile bias in group decision making: The influence of group history and use of a group support system, Journal of MIS, 15, 173
- Overby S., 2002, How to win friends and influence users, CIO Magazine
- Saga V. L., 1994, Diffusion, transfer and implementation of information technology, 67
- Vallacher R. R., 1996, The psychology of action: Linking cognition and motivation to behavior, 260
Cited by
Sorted by citations
Items 4,601–4,700 of 8,090
User-Adaptive Personalized Chatbots for Conversational Information Seeking Tasks
Yazan, M. (2025) · Conference on Human Information Interaction and Retrieval · doi:10.1145/3698204.3716483 · Cited by 3
“The acceptance of a technology depends on many factors [23, 24], including performance expectancy [24] and perceived competence [2, 26].”
Balaji, K. C. (2025) · International Journal of Engineering Technologies and Management Research · doi:10.29121/ijetmr.v12.i(4se).2025.1585 · Cited by 3
Decoding FinTech Uptake: The Interplay of Digital Literacy, Brand Image, Data Security, and Trust
Ahmad, S. Y. T., & Hassan, R. (2025) · Cureus Journal of Business and Economics. · doi:10.7759/s44404-025-03865-3 · Cited by 5
“To address this, the interaction effects between the factors influencing perceived usefulness and ease of use were addressed by (Venkatesh and Bala, 2008), integrating them into a unified framework.”
Li, F., Zhu, L., Liu, Z., & Xu, Y. (2025) · Journal of Engineering Design · doi:10.1080/09544828.2025.2518655 · Cited by 3
“The Unified Theory of Acceptance and Use of Technology (UTAUT), developed by Venkatesh et al., enhanced the predictive power of TAM by incorporating additional variables such as performance expectations, effort expectations, social influence, and facilitating conditions (Venkatesh and Bala 2008).”
Cycling-Based Telerehabilitation: Acceptability and Feasibility Study
Arlati, S., Colombo, V. M., Mondellini, M., Nossa, R., Grasso, C., Rossini, M., Biffi, E., Fumagalli, A., Diella, E., Guanziroli, E., et al. (2025) · JMIR Human Factors · doi:10.2196/71099 · Cited by 4
“The questionnaires we used were the NASA Task Load Test (NASA-TLX) (considering raw scoring [42,43]), the System Usability Scale (SUS) [44], and the modified version of the Technology Acceptance Measure 3 (TAM3) [45] questionnaires, respectively.”
Liu, M., Wang, C., & Hu, J. (2025) · PLoS ONE · doi:10.1371/journal.pone.0325291 · Cited by 6
“For instance, TAM2 incorporated constructs related to social influence [48], while TAM3 further expanded its scope by integrating factors such as perceived enjoyment and user experience [49].”
Spilbergs, A. (2025) · Businesses · doi:10.3390/businesses5030034 · Cited by 3
Islam, M. F., & Rahim, A. (2025) · International Hospitality Review · doi:10.1108/ihr-10-2024-0047 · Cited by 3
Toward Artificial Intelligence Compliance: Impacts and Mechanisms of Performance Feedback
Wei, S., Zhang, Y., & Dong, J. Q. (2025) · Information Systems Research · doi:10.1287/isre.2023.0580 · Cited by 5
Valdez, J. P. M., Buenconsejo, J. U., Yang, W., Lin, X., & Saxena, A. (2025) · Journal of Research on Technology in Education · doi:10.1080/15391523.2025.2547183 · Cited by 3
Evaluation of Digital Public Health Interventions
Lange, O., Boskamp, P., Brannath, W., Santis, K. K. D., Muellmann, S., Rogowski, W. H., & Rothgang, H. (2025) · Springer series on epidemiology and public health · doi:10.1007/978-3-031-90154-6_8 · Cited by 3
Al-kfairy, M., Alfandi, O., & Alrabaee, S. (2025) · Cogent Education · doi:10.1080/2331186x.2025.2555530 · Cited by 3
“…the Technology Acceptance Model and related behavioral frameworks, financial stress can act as a contextual barrier that negatively influences behavioral intention by amplifying perceived cost, effort, and risk — thus making the adoption of new technologies less appealing (Venkatesh & Bala, 2008).”
Muth, M., Parsegyan, A. T., Litzinger, J., & Lingenfelder, M. (2025) · Journal of Marketing Analytics · doi:10.1057/s41270-025-00436-0 · Cited by 3
PosterMate: Audience-driven Collaborative Persona Agents for Poster Design
Shin, D.-H., Lee, D. W., Hsieh, G., & Chan, G. Y.-Y. (2025) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3746059.3747769 · Cited by 15
“The survey included (i) technology acceptance based on a subset of the Technology Acceptance Model [66], which assessed perceived ease of use, perceived usefulness, and intention to use, as well as output quality, to evaluate the potential future adoption of Poster-Mate.”
Abbas, N., Nazir, M. A., & Khan, M. R. (2025) · Journal of Science and Technology Policy Management · doi:10.1108/jstpm-04-2025-0163 · Cited by 5
Factors and patterns in mobile banking and payment services use in the United States
Sinha, G. R., Mehta, R. C., Kaittila, A., et al. (2025) · Journal of Financial Services Marketing · doi:10.1057/s41264-025-00319-6 · Cited by 3
Technostress and academicians performance: from the perspective of technology acceptance
Saeed, I., Xigen, W., Ahmad, A., Dukhaykh, S., & Khan, I. (2025) · Technology Analysis and Strategic Management · doi:10.1080/09537325.2025.2572046 · Cited by 4
Pérez-Portabella, A., Arias-Oliva, M., Castillo, G. P., & Sánchez, J. D. A. (2025) · Societies · doi:10.3390/soc15100285 · Cited by 5
Employee willingness to collaborate with autonomous delivery robots: a cross-cultural perspective
Shin, J., Wen, J., Liu, Z., Liu, X., Boone, C. A., Landers, V. M., Lee, G., & Huang, J. (2025) · International Journal of Physical Distribution & Logistics Management · doi:10.1108/ijpdlm-01-2025-0019 · Cited by 3
ChatGPT Acceptance Among Students: An Information System View
Berényi, L., Lázár, E., & Madaras, S. (2025) · Education Sciences · doi:10.3390/educsci15111464 · Cited by 7
Byrne, J., Walsh, L. E., Lillywhite, R., et al. (2025) · Crop Protection · doi:10.1016/j.cropro.2025.107478 · Cited by 3
From lecture hall to clinic: dental students’ AI readiness and anxiety across educational stages
Çakan, K. N., & İpek, İ. (2025) · BMC Medical Education · doi:10.1186/s12909-025-08181-9 · Cited by 3
Immersive technologies and academic performance in online learning: A sequential mediation analysis
Sam, T. H., Mu’min, H., Riyanto, M., Iskandar, A., Abid, S., & Melati (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.102192 · Cited by 3
Innovation resistance toward waste to energy technologies in China’s food industry
Yang, X., & Zailani, S. (2025) · Discover Sustainability · doi:10.1007/s43621-025-02066-z · Cited by 3
“The usage barrier refers to the perceived difficulty in learning, integrating, or using an innovation, especially when it disrupts established workflows [55, 66].”
Zhang, Y., Liang, C., Ren, A., & Li, K. (2025) · Electronic Markets · doi:10.1007/s12525-025-00855-y · Cited by 2
“Previous studies have also shown that users who have more occasions to take part in activities are more likely to form judgments about the system’s relevance, quality, and result in demonstrability (Venkatesh & Bala, 2008).”
Singh, V., Yadav, M. K., & Gupta, A. K. (2025) · Journal of Financial Services Marketing · doi:10.1057/s41264-025-00338-3 · Cited by 6
“Later, this framework was extended to ‘UTAUT 2’ and ‘UTAUT 3’ (Venkatesh and Bala 2008; Venkatesh et al. 2012; Venkatesh 2022 ), which give consideration to factors like innovativeness, perceived risk, attitude, and social influence.”
Sousa, M. M., Oliveira, B. F., Gonçalves, T. I., Alves, S., Carreira, C. A., & Barbosa, F. V. (2025) · International Journal on Interactive Design and Manufacturing (IJIDeM) · doi:10.1007/s12008-025-02464-7 · Cited by 3
Andayani, W., Adib, N., Arif, M. E., Indrayani, Wahyuni, S., Murdianingrum, S. L., & Widiastutik, R. N. (2025) · Cogent Business & Management · doi:10.1080/23311975.2025.2603023 · Cited by 17
Ghorbanzadeh, D., Alhitmi, H. K., Khan, S. A., Chandra, T., Sharairi, M. H., & Prasad, K. (2025) · International Journal of Pharmaceutical and Healthcare Marketing · doi:10.1108/ijphm-05-2025-0068 · Cited by 5
Generative AI adoption in universities: how TAM–TTF and neuroticism influence sustained usage
Bawa, R. K., Jain, K., & Goel, P. (2025) · Interactive Technology and Smart Education · doi:10.1108/itse-02-2025-0030 · Cited by 3
Evaluating Strategies for Teaching Micro Frontends: Do Anti-patterns Help?
Silva, N., Rodrigues, E., & Conte, T. (2025) · doi:10.5753/sbes.2025.11029 · Cited by 3
Stahmann, P., Rodda, A., Nebel, M., van der Staay, A., Janiesch, C., & Teuteberg, F. (2025) · Journal of Decision System · doi:10.1080/12460125.2025.2593245 · Cited by 3
“…and perspectives that are established in Information Systems research such as the task technology fit or the technology acceptance model may contribute further to understanding the implications of predictive and prescriptive information on users (Goodhue & Thompson, 1995; Venkatesh & Bala, 2008).”
Unlocking learning potentials: Understanding user intentions in AI-fueled metaverse education
Dhingra, S., Gupta, A., Chaudhry, K., Kumar, A., & Falwadiya, H. (2025) · Computers & Education X Reality · doi:10.1016/j.cexr.2025.100131 · Cited by 5
Kim, J. S., Feng, Y., Li, P., & Lee, T. J. (2025) · Journal of Hospitality and Tourism Technology · doi:10.1108/jhtt-06-2025-0513 · Cited by 3
Lowering Barriers to Augmented Reality in Chemistry─Easy Creation of Virtual 3D Molecular Models
Loch, F., Huwer, J., & Thoms, L. (2025) · Journal of Chemical Education · doi:10.1021/acs.jchemed.5c00278 · Cited by 4
“We adopted TAM, and not one of its extensions (e.g., TAM2, 78 TAM3 79 ), to focus on the individual perceptions of educators without incorporating social or organizational factors for adoption.”
The power of beliefs: How Generative Artificial Intelligence (GenAI) influences academic performance
Zhu, W., Li, T. C., & Li, Q. (2026) · Acta Psychologica · doi:10.1016/j.actpsy.2026.106218 · Cited by 6
Alanazi, A., Elias, N. F., Mohamed, H. B., & Ashaari, N. S. (2026) · Sustainability · doi:10.3390/su18031353 · Cited by 4
Tang, C. (2026) · PLoS ONE · doi:10.1371/journal.pone.0336166 · Cited by 5
Future work now: organizational culture in hybrid work modes
Pagnozzi, F., Pescatore, I., Cartone, A., & Antonelli, G. (2026) · Management Decision · doi:10.1108/md-01-2025-0164 · Cited by 4
Dzisi, E. K. J., Patterson, M., & Iddrisu, S. (2026) · Dialogues in Health · doi:10.1016/j.dialog.2026.100285 · Cited by 3
“While perceived usefulness (PU) denotes the extent to which a person believes that a technology enhances job performance, perceived ease of use (PEOU), on the other hand, refers to the degree to which the technology is as effortless to use or integrate into existing work systems [25, 26].”
Padi, A., Okyere, D. O., Musah, A., & Blay, M. W. (2026) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2026.100392 · Cited by 3
Polat, S., & Renner, G. (2026) · Contemporary Educational Technology · doi:10.30935/cedtech/17878 · Cited by 5
Abdullahi, H. O., Mahmud, M., & Rahim, E. E. A. (2026) · Cogent Food & Agriculture · doi:10.1080/23311932.2026.2631187 · Cited by 3
Persson, D. R., & Andersen, T. O. (2026) · Digital Health · doi:10.1177/20552076261425134 · Cited by 5
“…instance, when it comes to new technology such as AI in this case, acceptance is a topic of particular interest, and can be assessed through the technology acceptance model, 33 its various derivatives 34,35 or through the different versions of the Uni fi ed Theory of Technology Acceptance and Use.”
Team Member or Tool? The Role of Framing in Human-Autonomy Teaming
Hagemann, V., Rieth, M., Watermann, L., Appelganc, K., & Heinicke, C. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2634249 · Cited by 4
AI-Human synergy in single-session therapy: augmenting capacity for scalable mental health support
Joseph, J., Pai, M., Asai, K., & Turek, M. (2026) · Journal of Psychology and AI · doi:10.1080/29974100.2026.2636264 · Cited by 3
Mohamed, R. A. A. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2649549 · Cited by 3
“Subsequent extensions (e.g. TAM2/TAM3) and related models emphasize social influence, facilitating conditions, and enjoyment as additional determinants of uptake in institutional settings (Venkatesh & Bala, 2008; Venkatesh & Davis, 2000).”
Alharasis, E. E. (2026) · EDPACS · doi:10.1080/07366981.2026.2661841 · Cited by 4
From information evaluation to technology use: Generative AI adoption in Chinese business schools
Yu, T., Dai, J., Chen, X., & Wang, C. (2026) · The International Journal of Management Education · doi:10.1016/j.ijme.2026.101430 · Cited by 4
Cheng, Y., & Liu, H. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1822948 · Cited by 4
Alonso-Morales, N., Sáez-Martín, A., Hernández, A. M. L., et al. (2026) · Meditari Accountancy Research · doi:10.1108/medar-09-2025-3247 · Cited by 3
Ebrahimi, P., Hoffmann, S., & Schneider, J. (2026) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2026.103075 · Cited by 12
Artificial intelligence and service performance: empirical findings from the hospitality sector
Mukherjee, S., Panigrahi, R., Khan, S. A., & Cotha, K. (2026) · International Journal of Quality & Reliability Management · doi:10.1108/ijqrm-02-2025-0082 · Cited by 3
Kim, D. J., Al-Mubaid, H., Yue, K.-B., & Rizk, N. J. (2011) · Journal of the Association for Information Systems · Cited by 3
Cuello, K. C., Barraza, M. O., & Cataldo, A. (2018) · Ingeniare. Revista chilena de ingeniería · doi:10.4067/s0718-33052018000200296 · Cited by 3
Research on influential factors of E-commerce recommendation user behavior intention
Xiu-li, P., & Jiang, W. (2017) · International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) · doi:10.1109/fskd.2017.8393165 · Cited by 3
“Some scholars from the image[22], visibility[23], system features[24] and other areas to study the external influence factors.”
BackgroundSantokhee, A., Bekaroo, G., & Roopowa, D. (2019) · doi:10.1109/nextcomp.2019.8883629 · Cited by 3
“In total, forty young drivers were targeted so as to fulfill the requirement of the minimum number of users involved for application of this model [29, 28].”
BackgroundAnalysis of ERP Implementation in Perum BULOG with Extended TAM 3 Approach
Fahmi, M. A., Ciptomulyono, U., & Rahardjo, J. (2021) · IPTEK Journal of Proceedings Series · doi:10.12962/j23546026.y2020i7.9530 · Cited by 3
“Then, Venkatesh in 2008 [7] try to combine the TAM 2 model and the determinant model of perceived ease of use to develop an integrated model known as TAM 3.”
MethodMeuter, M. L. (2021) · Journal of Services Marketing · doi:10.1108/jsm-05-2021-0183 · Cited by 3
Fintech et seniors Sud-Coréens : une étude des facteurs d’acceptation
Um, S., Shin, H., Kim, Y., Branellec, G., & Lee, J. (2022) · Innovations · doi:10.3917/inno.067.0195 · Cited by 2
Vertrauen in digitale Technik. Der Einfluss mobiler Apps auf die Bereitschaft zur Verhaltensänderung
Weyer, J., & Kohaupt-Cepera, K. (2021) · Zeitschrift für Soziologie · doi:10.1515/zfsoz-2021-0028 · Cited by 4
Understanding Online Reverse Auction Determinants of Use: A Multi-Stakeholder Case Study
Boukef, N., Vlaar, P. W. L., Charki, M. H., & Bhattacherjee, A. (2016) · Systèmes d information & management · doi:10.3917/sim.161.0007 · Cited by 3
Dutra, E., Cerdeiral, C., Lima, P., et al. (2022) · doi:10.1145/3535511.3535534 · Cited by 3
“To continue the assessment of the performance of TACT, we invited team leaders to evaluate TACT considering TAM dimensions of Intention to Use, Perceived Usefulness, and Output Quality [29].”
MethodService Robots in Nursing Homes (SeRoNu): a holistic model of influencing factors
Obst, L., Bielefeldt, F., von der Weth, R., & Dick, M. (2022) · Gruppe Interaktion Organisation Zeitschrift für Angewandte Organisationspsychologie (GIO) · doi:10.1007/s11612-022-00639-4 · Cited by 3
“Scientifically proven models such as the Technology Acceptance Model (TAM) and its further developments (e.g. Davis 1989; Venkatesh and Davis 2000; Venkatesh and Bala 2008) examine one specific construct and do not provide a widespread view on this complex topic.”
BackgroundSPMM: A Model Taxonomy for Designing and Managing Quality System
Mannan, M. A., & Ansari, A. (2022) · IEEE Access · doi:10.1109/access.2022.3190081 · Cited by 4
Acceptance and Use of Cryptocurrency in Saudi Arabia: A Case Study of Bitcoins
Elshity, E. (2022) · Compunet ( The Egyptian Information Journal ) · doi:10.21608/jstc.2022.274486 · Cited by 3
Perceptions of Assistive Robots at Work: An Experimental Approach to Social Influence
Latikka, R., Savela, N., & Oksanen, A. (2023) · International Journal of Social Robotics · doi:10.1007/s12369-023-01046-5 · Cited by 4
Cippelletti, E., Adelé, S., Dionisio, C., et al. (2023) · Psychologie du Travail et des Organisations · doi:10.1016/j.pto.2023.09.001 · Cited by 3
Vietnamese EFL Learners’ Perspectives on Learning English Online and Employability
Huynh, N. T., Truong, V., & Nghia, T. L. H. (2023) · Global Vietnam · doi:10.1007/978-981-99-4338-8_15 · Cited by 3
Asokkumar, J., sekar, K., Mathew, A. S., & Thomas, R. (2023) · Technology Knowledge and Learning · doi:10.1007/s10758-023-09683-5 · Cited by 3
“Therefore, following (Mohan et al., 2020 ; Venkatesh & Bala, 2008), the authors suggest the need for organizational support – formal and informal to foster MOOC adoption.”
Cheng, M., Lai, X., Tao, D., Lai, J., & Yang, J. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-12325-z · Cited by 3
Factors Influencing the Adoption of RPA in Vocational College Accounting Courses
Liu, X., & Ishak, N. N. B. M. (2024) · Frontiers in Business Economics and Management · doi:10.54097/dzhm3n49 · Cited by 3
“(4) TAM3 TAM3 [7] integrates drivers of perceived usefulness and perceived ease of use, introducing elements such as computer self-efficacy and computer playfulness.”
BackgroundExternal Factors and Socioeconomic Influence on Users Acceptance of Online Payments
Uyaguari, F., Cordero, J. F., Lopez, A., & Sacoto-Cabrera, E. J. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-51982-6_19 · Cited by 3
Skill Development in Current and Future Workers to Thrive in the Digital Aquaculture Industry
McDonald, N., Lovric, K., & Cosby, A. (2024) · Aquaculture Journal · doi:10.3390/aquacj4010002 · Cited by 3
“Feeling confident in their ability to perform tasks using digital technology is vital for the current workforce’s acceptance and effective use of technology [41].”
InfluentialDigitale Kulturen der Lehre entwickeln
Mrohs, L. C., Franz, J., Herrmann, D., Lindner, K., & Staake, T. (2023) · Perspektiven der Hochschuldidaktik · doi:10.1007/978-3-658-43379-6 · Cited by 5
COVID-19 et le futur du télétravail : La perception et l’acceptabilité des employés
Baudier, P., Kondrateva, G., & Ammi, C. (2024) · Management & Prospective · doi:10.3917/g2000.403.0190 · Cited by 3
Unlocking the potential: UTAUT2 framework for embracing self-driving tractors in modern agriculture
Piroska, V. D., & Dávid, L. D. (2024) · Journal of Infrastructure Policy and Development · doi:10.24294/jipd.v8i6.3442 · Cited by 4
“TAM 3, for example, due to the increasing simplification of the user interfaces of technological devices, emphasizes the factors affecting the perceived ease of use compared to the previous versions (Venkatesh and Bala, 2008).”
BackgroundUnveiling the Puzzle of Social Media Adoption Among Small Grocery Retailers
Choubey, V. M., Chakraborty, D., Pahari, S., Kumar, K. S. K., Jain, R. K., & Rana, N. P. (2024) · Journal of Global Information Management · doi:10.4018/jgim.353395 · Cited by 7
The augmenting role of digital banking in reconstructing women's economic empowerment
Rohatgi, S., & Gera, N. (2024) · International Journal of Bank Marketing · doi:10.1108/ijbm-01-2024-0010 · Cited by 8
Christoforakos, L., Kolb, A., & Diefenbach, S. (2024) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3679318.3685339 · Cited by 4
The Role of Digital Marketing in International Marketing
Lubis, E. S., & Widodo, S. (2024) · Sinergi International Journal of Economics · doi:10.61194/economics.v2i1.209 · Cited by 3
“First, the Technology Acceptance Model (TAM), which explores how users come to accept and use technology, is crucial in understanding how digital platforms are adopted in international markets (Davis, 1989; Venkatesh & Bala, 2016).”
BackgroundFinancial Innovation and Crowdfunding: Influencing Investment Decisions in Tech Startups
Panitkulpong, K., Saengnoree, A., & Teerawatananond, T. (2024) · International Journal of Financial Studies · doi:10.3390/ijfs12040103 · Cited by 3
The use of ChatGPT for online health information seeking in Hungary
Rojkovich, Á. K., Kemény, I., & Simon, J. (2024) · International Conference on Control, Decision and Information Technologies (CoDIT) · doi:10.1109/codit62066.2024.10708295 · Cited by 4
“In response to these needs over past decades continuously evolving and incorporating new factors technology acceptance measuring models appeared one after another: TAM [3], TAM1 [4], TAM2 [11], TAM3 [10], UTAUT [12] and UTAUT2 [13].”
BackgroundImmersive Teleoperation of Collaborative Robot for Remote Vital Monitoring in Healthcare
Vishwakarma, H., Sampath, A., Sharma, V., et al. (2024) · IEEE RO-MAN · doi:10.1109/ro-man60168.2024.10731386 · Cited by 4
“Pre-test questionnaire established the baseline of technology acceptance before using the cobot [17].”
BackgroundMethodInfluentialFrom challenges to opportunities: navigating the human response to automated agents in the workplace
Ðula, I., Berberena, T., Keplinger, K., & Wirzberger, M. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03962-x · Cited by 4
“…Actions (TRA; Fishbein and Ajzen, 1975), the Technology Acceptance Model (TAM; Davis, 1989) and subsequent extensions (Venkatesh and Davis, 2000; Venkatesh and Bala, 2008), the Motivation Model (MM; Davis et al., 1992), the Theory of Planned Behaviour (TPB; Ajzen, 1991), the Combined TAM and…”
Chen, I.-C., Wu, C., Hu, Y.-L., & Huang, Y. (2024) · Clinical Interventions in Aging · doi:10.2147/cia.s471547 · Cited by 3
Digital Technology and the Empowerment of Indian Women Micro-Entrepreneurs
Pal, R., & Bhowmick, B. (2024) · IEEE Global Humanitarian Technology Conference (GHTC) · doi:10.1109/ghtc62424.2024.10771561 · Cited by 6
“Moreover, the cultural context plays a pivotal role in shaping attitudes towards technology use among women [6].”
Hinrichs, M., Bui, T. B. D., & Schneegaß, S. (2024) · International Conference on Mobile and Ubiquitous Multimedia (MUM) · doi:10.1145/3701571.3701585 · Cited by 4
“However, the effect of algorithmic aversion on trust in specific systems may decrease over time of use [58].”
InfluentialSae-tae, K., Ling, J., & Wang, Q. (2024) · Frontiers in Communication · doi:10.3389/fcomm.2024.1410975 · Cited by 11
An Instrument for Assessing Power Distance in Agile Organizations - Preliminary Results
Mattos, C. S., Dutra, E., & Santos, G. (2024) · doi:10.1145/3701625.3701653 · Cited by 3
“Furthermore, a questionnaire based on the Technology Acceptance Model (TAM) [43, 44] was used to consider the measures of intention to use, perceived usefulness, and quality of the result.”
hUGO, a Humanoid Robot for Training Memory: A Pilot Study on Healthy Younger and Older Adults
Gigliotta, O., Padulo, C., Chinzer, E., & Fairfield, B. (2024) · IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) · doi:10.1109/metroxraine62247.2024.10796359 · Cited by 3
“Finally, before beginning the training session with hUGO, and after completing the working memory task, participants completed the TAM3 [19], the Technophobia Scale [20] and the System Usability Scale (SUS) [21].”
InfluentialDeterminants of consumers’ emotions and willingness to use artificial intelligence in Indonesia
Laksmidewi, D., Efendi, & Hoo, W. C. (2024) · Innovative Marketing · doi:10.21511/im.20(4).2024.22 · Cited by 3
Zhang, H. J., Chan, W. W. H., Peralta, R. L., et al. (2025) · Journal of Quality Assurance in Hospitality & Tourism · doi:10.1080/1528008x.2024.2447876 · Cited by 4
Adopting a technological innovation to improve patient care cooperation
Garidi, S., & Karâa, M. (2025) · Supply Chain Forum an International Journal · doi:10.1080/16258312.2024.2446011 · Cited by 3
“In sum, our results corroborate the work of Rogers (2003) and Venkatesh and Bala (2008), but general factors were not identified in our study: subjective norms, image, voluntariness, anxiety, perceived joy, and formalisation.”
InfluentialProof of concept of a cobotic system in a constrained work environment
Fournier, É., Landry, A., Piras, B., Pellier, D., Fiorino, H., Daney, D., & Jeoffrion, C. (2025) · Applied Ergonomics · doi:10.1016/j.apergo.2025.104472 · Cited by 3
Technological acceptance in the retail sector: an empirical generalisation by a meta-analytic study
Santini, F. D. O., Maçada, A. C. G., Freitas, J. C. D. S., Ladeira, W. J., & Oliveira, T. (2025) · Journal of Systems and Information Technology · doi:10.1108/jsit-08-2021-0179 · Cited by 5
Learner Experience Evaluation: a Feasibility Study and a Benchmark
dos Santos, G. C., Silva, D. E. D. S., & Valentim, N. (2025) · Journal of the Brazilian Computer Society · doi:10.5753/jbcs.2025.4306 · Cited by 3
Kong, S. C., Lai, M., Li, Y., Chan, T.-Y. D., & Zhang, Y. T. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105281 · Cited by 5
Wang, Y., & Ping, H. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2476717 · Cited by 3
“The model suggests that an individual ’ s acceptance of technology depends primarily on perceived usefulness and perceived ease of use (Venkatesh & Bala, 2008).”
Stumbo, S. P., Hooker, S. A., Rossom, R. C., Miley, K. M., Ahmedani, B. K., Lockhart, E. A., Yeh, H.-H., & Yarborough, B. J. H. (2025) · BMC Psychiatry · doi:10.1186/s12888-025-06760-0 · Cited by 4
“The Technology Acceptance Model [52] posits that perceived usefulness of a technology positively influences use intention, which then drives adoption [53].”
Metadata
- Authors
- Venkatesh, V., & Bala, H.
- Affiliations
- University of Arkansas at Fayetteville (US)
- Indiana University Bloomington (US)
- Corresponding author
- Venkatesh, Viswanath
- Bala, Hillol
- Venue
- Decision Sciences
- Publisher
- Wiley
- Published
- 2008-05
- Volume
- 39
- Issue
- 2
- Pages
- 273-315
- ISSN
- 0011-7315 (ISSN-L)
- 1540-5915
- OpenAlex
- W2112042732
- Cited by
- 8,159
- References
- 135
- Citations by year
- 2026: 909 · 2025: 912 · 2024: 780 · 2023: 746 · 2022: 717 · 2021: 645 · 2020: 556 · 2019: 499 · 2018: 396 · 2017: 379 · 2016: 320 · 2015: 324 · 2014: 287 · 2013: 266 · 2012: 186
- FWCI
- 175.14
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Decision Sciences (publishedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Social Sciences › Business, Management and Accounting › Management Information Systems › ERP Systems Implementation and Impact
- Keywords
- technology acceptance model, information technology adoption, information technology use, perceived usefulness, perceived ease of use, management interventions, IT implementation, organizational decision-making, nomological network
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-09-30, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-09-30 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
