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.
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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)
plaindirect- 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
hedgedcorrelational- 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
plaindirect- 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
plaindirect- 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
plaincorrelational- 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
plaincorrelational- 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
plaindirect- 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
hedgedconditional- 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
plaincorrelational- 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
hedgeddirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
hedgedconditional- 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
plaindirect- 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
plaindirect- 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.
plainconditional- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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.
plaincorrelational- 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
plainconditional- 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
hedgeddirect- 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
plaindirect- 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
hedgeddirect- 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
plaindirect- 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
hedgedconditional- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
plaindirect- 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
hedgedconditional- 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
plaindirect- 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
hedgedconditional- 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
hedgeddirect- 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
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Perceived usefulness, perceived ease of use, and user acceptance of information technology
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Multiple regression: testing and interpreting interactions
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A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
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Self-citationIntrinsic and Extrinsic Motivations: Classic Definitions and New Directions
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Structural equation models with unobservable variables and measurement error: Algebra and statistics
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Items 7,401–7,500 of 8,090
Resistance, Reflexivity, and the Dynamics of AI Adoption:Evidence from Software EngineersPreprint
Wei, J., & Peng, S. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6052269
Zebrowski, A., Fernandez, J., Pinkelton, C., Kitzmiller, R. R., Kiefer, A., Stanley, L., Mody, G. N., Moore, C., & Mazur, L. M. (2025) · doi:10.2196/preprints.90626
Khan, K., Shaikh, S. Z., Sherwani, F. K., Khan, M. U., & Singh, P. (2025) · International Conference on Digital Innovations for Sustainable Solutions (ICDISS) · doi:10.1109/icdiss68238.2025.11320664
Why Users Keep Watching: An Integration Model of Motivations and Acceptance in Sports-OTT Engagement
Dove, J., Kim, S., Lim, S., & Kim, H. (2026) · International Journal of Sport Communication · doi:10.1123/ijsc.2025-0195
Developing a Conceptual Model for Clinician Adoption of Mobile App in Palliative Care
Monis, E. M., Shetty, D. K., Prabhu, D. R., Shukla, V. K., & Sudhi, M. (2025) · International Conference on Computational Intelligence and Knowledge Economy (ICCIKE) · doi:10.1109/iccike67021.2025.11318181
“The results were interpreted in the context of the Unified Theory of Acceptance and Use of Technology, which comprises performance expectancy, effort expectancy, social influence and facilitating conditions [19].”
Determinants of AI-Driven Accelerated Learning for Junior Auditors
Koming, A. B., Vaizira, C. D. J., & Handoko, B. L. (2025) · IEEE International Conference on Computing, Engineering and Design (ICCED) · doi:10.1109/icced68324.2025.11324086
“This is particularly relevant for junior auditors, who often have varying levels of technical expertise and may come from diverse technical backgrounds [17].”
Integrating E-Commerce and Games for Mental Wellbeing
Chai, A. T.-E., & Lee, C. S. (2025) · IEEE International Conference on Computing (ICOCO) · doi:10.1109/icoco67189.2025.11334126
“Design includes [1, 2, 3]’s utilitarian (gamification) and hedonic factors to enhance user engagement and boost purchase intentions, [9]’s meaningful social connection games, [3, 11]’s gamified elements and Technology Acceptance Models 1, 2, 3 [14].”
Durneva, P., & LeRouge, C. (2026) · European Journal of Information Systems · doi:10.1080/0960085x.2025.2605343 · Cited by 1
“Concerning technology use, one could argue that personal usefulness has some association with perceived usefulness (Davis, 1989; Venkatesh & Bala, 2008; Venkatesh et al., 2003; Viswanath & Fred, 2000).”
WIP: Investigating Engineering Students' Adoption Intention of AI for Competency Development
Moyaki, D., Fakiyesi, V. O., Dunmoye, I. D., & Hunsu, N. J. (2025) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie63693.2025.11328492
“This study administered a 49-item instrument adapted from Venkatesh and Bala [27] to assess students' behavioral intention to adopt AI.”
InfluentialEngan, H. K., Landstad, I., Sand, K., Evenshaug, S., & Halsnes, E. H. (2025) · doi:10.2196/preprints.90442
Determinants of User Satisfaction in Digital Payment System Transactions: A Philippine Perspective
Mayuga, A. D., Berdin, K. C. A., Lagmay, M. F. F., et al. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-13203-1_9
Kaya, N. B., Yıldırım, H., & Raffaele, C. D. (2026) · Springer eBooks · doi:10.1007/978-981-95-4871-2_15
The Efficiency of Freemium Business Models
Leite, M. E., & Rua, O. L. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-3301-4.ch010
Technology Acceptance of Metaverse Tourism Services: Findings from Greece
Anthopoulos, L. G., Kontogianni, E., & Malama, A. (2025) · GATR Global Journal of Business Social Sciences Review · doi:10.35609/gjbssr.2025.13.4(5
Jiménez, I. A. C., Olivetti, E. C., Mangano, G., Rafele, C., Moos, S., Vezzetti, E., & Marcolin, F. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2611349
“…record-keeping systems in clinics (Holden & Karsh, 2010); also it has been employed to investigate the acceptance of enterprise resource planning (ERP) (Bueno & Salmeron, 2008) and customer relationship management (CRM) systems in organizations (Ngangi & Santoso, 2019; Venkatesh & Bala, 2008).”
Shaping Tomorrow’s Classrooms: Integrating AI in Technology Teacher Training and VET in Germany
Vernholz, M., Schäfers, J., Jonas-Ahrend, G., & Temmen, K. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-07316-7_10
Factors Affecting E-Wallet Usage: A Study in Türkiye
Altınkaya, Ş., & Nacar, R. (2026) · Manas sosyal araştırmalar dergisi · doi:10.33206/mjss.1592943
Laiti, J., Javadpour, S., Mullen, J. M., Conway, C., Byrne, E., & Dunne, P. J. (2026) · JMIR Human Factors · doi:10.2196/79381
“The primary outcomes are ease of use, perceived usefulness, and behavioral intention of Wellby, which are measured using the TAM framework both quantitatively and qualitatively [42].”
InfluentialDesigning Adoption: An Intervention-Augmented UTAUT for AI Use Across Generations
Chaisuwan, B.-N., Chantamas, M., Kuldilok, P., Sakuna, C., & Chanesirirattanakorn, T. (2025) · doi:10.1109/icitee66631.2025.11338429
Liu, Z., & Kim, S. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1738594
Digital maternity care in Germany: a cross-sectional web-based survey on midwives’ perceptions
Griewing, S., Teske, P., Wichmann, J., Oftring, Z. S., Knitza, J., Keil, C. N., Tauber, N., Däumichen, J., Potthast, M., Wallwiener, S., et al. (2026) · Archives of Gynecology and Obstetrics · doi:10.1007/s00404-025-08239-5
Technology-Enhanced Learning in Medical Education: Latest Developments
Sundaravally (2025) · International Journal of Education and Pedagogy (IJEP) · doi:10.63090/ijep/3108.1800.0021
Grandi, J. G., Costa, D. B., & Kopper, R. (2025) · Symposium on Virtual and Augmented Reality (SVR) · doi:10.1109/svr67689.2025.00019
“While the Technology Acceptance Model (TAM) provides a foundational framework for predicting adoption based on perceived usefulness and ease of use [34], its application in safety-critical fields requires significant extension.”
Educational ideals affect AI acceptance in learning environments
Richter, F., & Uhl, M. (2026) · AI and Ethics · doi:10.1007/s43681-025-00979-z
“Although the “Technology Acceptance Model” [36] has been extended to account for social influences [37, 38], it remains merely on a descriptive level.”
Space oddity: How context matters in waste-sorting behavior
Parguel, B., Monjon, S., Reniou, F., & Robert-Monnot, E. (2026) · Recherche et Applications en Marketing (English Edition) · doi:10.1177/20515707251406495 · Cited by 1
Arafat, Y., Kaihatu, T. S., & Kodrat, D. S. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6136612
A socio-technical perspective on product configuration systems: Insights from Grundfos
Jakobsen, A. M. S. Ø., & Vanhaverbeke, W. P. M. (2026) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2026.124564
Taib, F. F. M., Rahman, A. L. A., & Aziz, M. A. A. (2025) · Journal of Information System and Technology Management · doi:10.35631/jistm.1041009
Paavola, L. J., & Cuthbertson, R. W. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6142545
AI-Driven Marketing Communication and Customer Satisfaction in Jakarta’s Digital Banks
Husada, S., Yulianti, W., Yunus, U., & Nugraha, T. (2026) · Ilomata International Journal of Social Science · doi:10.61194/ijss.v7i1.1986
Responsible Behavior in Mega-Sports Events Under Facial Recognition Technology Surveillance
Choi, K., & Kim, E. (2026) · Event Management · doi:10.3727/152599526x17695712079039
Kanamugire, M., & Muhayimana, V. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6116146
Santos, M. R., Rosendo, N. J. C., Silva, Y. D., et al. (2025) · doi:10.1109/icalter69698.2025.11355054
“These concerns can be mitigated by building trust among students, focusing efforts on privacy policies, security certifications, effective guidance, and other actions that make users feel confident and safe when using digital wallets [27], [3].”
Raheem, I. A., Fakomogbon, M. A., Ogunlade, O. O., Yusuf, M. O., Falade, A. A., & Raheem-Folayinka, G. P. (2026) · Research in Science & Technological Education · doi:10.1080/02635143.2026.2620038
Automated specification search for composite-based structural equation modeling: A genetic approach
Trinchera, L., Pietropolli, G., Castelli, M., et al. (2026) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2026.108348
New tech, new consumers? A study of millennial technology adoption in Colombia
Rojas‐Méndez, J. I., Massi, M., Durán-García, O., et al. (2026) · Young Consumers Insight and Ideas for Responsible Marketers · doi:10.1108/yc-06-2025-2583
Livet, M., Watson, A., Pathak, S., et al. (2026) · BMC Health Services Research · doi:10.1186/s12913-025-13400-6
“…patient and pharmacist satisfaction [27], the fidelity assessment [28], the intent to sustain survey [29], and the perceived benefits survey [29]; descriptives and paired t-tests for the retrospective pre-post surveys, including the Implementation Outcomes (IOQ) measures assessing…”
Mensah, E. G., Amutenya, T., Nyamekye, E., Ampem, I. O., & Sarfo, F. O. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-025-00805-9 · Cited by 1
“Venkatesh and Bala [58] also found that higher technology self-efficacy not only predicts adoption but also means that new technology will be used less irresponsibly or unethically.”
Sharma, A. (2025) · Exploresearch. · doi:10.62823/exre/2025/02/04.142
“This aligns with research by Venkatesh and Bala (2008), who found that perceived ease of use and usefulness of digital tools are very important determinants of employee satisfaction which then in turn positively influences the overall job satisfaction among employees.”
Ortiz-López, A., Sánchez‐Prieto, J. C., & Migueláñéz, S. O. (2025) · Revista Electrónica Interuniversitaria de Formación del Profesorado · doi:10.6018/reifop.656221
“En las primeras etapas de adopción tecnológica, la facilidad de uso percibida puede actuar como una barrera que afecte tanto a la utilidad percibida como a la intención de uso (Venkatesh & Bala, 2008).”
Riaz, A., Rehman, S. U., Palmucci, D. N., Jabeen, F., & Santoro, G. (2026) · FIIB Business Review · doi:10.1177/23197145261416250
TAHAP KESEDIAAN MURID DALAM PEMBANGUNAN KANDUNGAN TVPSS BERASASKAN TAM3
Ramli, A. F., Rashid, S. M., & Khan, S. M. (2025) · International Journal of Law Government and Communication · doi:10.35631/ijlgc.1042017
IT Governance and Perceived Usefulness of CAATs: An Empirical Study
Pham, T. L., Nguyen, P. B. A., & Minh, T. H. (2026) · Studies in big data · doi:10.1007/978-3-032-06179-9_14
Usability Evaluation of Virtual Reality Laboratories in Biomedical Engineering Education
Moyaki, D., Hunsu, N. J., May, D., et al. (2026) · Biomedical Engineering Education · doi:10.1007/s43683-025-00210-9
“Venkatesh and Bala [33] posited that ease of use fosters positive attitudes and usage intentions in the users of technologies.”
Cai, M., Gao, K., Luo, X., & Wu, M. (2026) · Data Science and Informetrics · doi:10.1016/j.dsim.2026.01.003
Reluctant to Ask a Human-ish Chatbot? When Anthropomorphic Cues Help and When They Backfire
Jeon, Y. A., Rau, D., Pickard, M. D., & Palese, B. (2026) · Marketing Education Review · doi:10.1080/10528008.2026.2623036
Söğütlüler, T. (2025) · DergiPark (Istanbul University)
TECHNOLOGY READINESS AND TECHNOLOGY ACCEPTANCE OF ACADEMIC STAFFS
Bakırtaş, H., & Akkaş, C. (2019) · DergiPark (Istanbul University)
Miron, J., & Domsy, C. (2026) · Journal of innovation in polytechnic education. · doi:10.69520/jipe.v8i1.291
Drivers of Blockchain Adoption Intention in the Fisheries Sector
Douzi, S., Abid, H. S., & Kehmakhem, R. (2026) · Journal of African Business · doi:10.1080/15228916.2026.2622171
A Systematic literature review on financial innovation adoption and financial inclusion: an analysis
Singh, H., & Kaur, P. (2026) · Global Knowledge, Memory and Communication · doi:10.1108/gkmc-08-2024-0507
Nativel-Fontaine, G., Balssa, F., Lespinet‐Najib, V., Chevrié, M., Aioun, F., & Ojeda, L. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2623214
“These models describe the direct effects of habits and facilitating conditions, as well as the moderating effects of age, gender, and experience on the intention to use a technology (Venkatesh & Bala, 2008).”
Abdullahi, U., Mudey, M. H., Manaf, H. B. A., & JiFang, C. (2026) · Multidisciplinary Reviews · doi:10.31893/multirev.2026403
“Despite its widespread use, TAM has been criticised for oversimplifying the complexity of public sector adoption.”
InfluentialAugmented Reality in InsurTech: UTAUT Insights for Green and Digital Transformation
Sakici, Ş., Yaprak, B., & Magueta, D. (2026) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-80592-551-420261001
NDREGJONI, Z., Sula, L., & Elmazi, L. (2026) · Multidisciplinary Reviews · doi:10.31893/multirev.2026434
Selvaratnam, V., Snelgrove, R., & Naraine, M. L. (2026) · Sport Marketing Quarterly · doi:10.1177/10616934261418757 · Cited by 2
“Compared to extended versions of TAM such as TAM2 (Venkatesh & Davis, 2000), TAM3 (Venkatesh & Bala, 2008), and the uni fi ed theory of acceptance and use of technology (Venkatesh et al., 2003), the original TAM provides a theoretically grounded yet fl exible framework that is well-suited for…”
(In)human decisions: algorithms, employee emotions, attitudes and behavior
Hudson, S. A., & González‐Gómez, H. V. (2026) · European Journal of Work and Organizational Psychology · doi:10.1080/1359432x.2026.2628002
“In line with the procedure proposed by Bernerth and Aguinis (2016), we selected the controls based on the technology acceptance literature (Venkatesh & Bala, 2008), which suggests that previous technology usage and familiarity/experience are key to the adjustment of users to new technology.”
Determinants and mechanisms of green travel behavior in Mobility-as-a-ServicePreprint
Li, J., Chi, X., Tian, J., Zhang, C., Xiao, G., & Wu, R. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6210624
Anthropomorphism and Familiarity in AI Adoption
Sboui, M., Sfar, N., & Baati, O. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-2747-1.ch015
Ortova, M., Lund, G. K., & Syversen, A. G. (2026) · Procedia CIRP · doi:10.1016/j.procir.2026.01.169
Wadhar, S. B., Shahani, R., Guang, Y., et al. (2026) · SAGE Open · doi:10.1177/21582440261419863
“…be highlighted: (1) Theoretically, the Technology Acceptance Model (TAM; Bagozzi, 2007), Unified Theory of Acceptance and Use of Technology (UTAUT; Venkatesh & Bala, 2008), the theory of gratification (Apuke & Omar, 2021), and the theory of media richness (Cao et al., 2022) are the prominent…”
Exploring the Adoption of AI Tools Among PhD Students at Ibn Tofail University
Bentatou, N., & Lemqeddem, H. A. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-3436-3.ch010
Omata, M., & NAKANO, A. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-16454-4_4
Li, J., Chi, X., Tian, J., Zhang, C., Xiao, G., & Wu, R. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6228900
The Impact of AI-Driven User Experience in Digital Payment Systems
Thapa, B., & Beikverdi, L. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-4526-0.ch009
Balancing automation and control: user perceptions of tool invocations in conversational agents
Hennekeuser, D., Vaziri, D. D., Golchinfar, D., Schreiber, D., & Stevens, G. (2026) · i-com · doi:10.1515/icom-2025-0053
“33”
Inconsistance spatiale : L’influence du lieu sur le tri des déchets ménagers
Parguel, B., Monjon, S., Reniou, F., & Robert-Monnot, E. (2026) · Recherche et Applications en Marketing (French Edition) · doi:10.1177/07673701251408247
Lin, L., Zhang, R., & Zhai, M. (2026) · International Journal of Construction Management · doi:10.1080/15623599.2026.2631161
She, M., Zeren, D., Zhang, Z., & Wang, Y. (2026) · BMC Psychology · doi:10.1186/s40359-026-04162-9 · Cited by 1
Why should I use social chatbots? On potential users’ acceptance and the role of anthropomorphism
Rüth, M., Eifler, J., & Schneider, A. C. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1656749
Agritech Ventures in India: Impact of Entrepreneurial Ecosystem on Smart Digital Solutions
Adapa, S., & Yarram, S. R. (2026) · Springer eBooks · doi:10.1007/978-981-95-4909-2_13
Exploring Teachers’ Acceptance of Video Games as an Educational Tool
Guichard, É., Potocki, A., Lambert, E. G., & Gimenes, M. (2026) · Technology Knowledge and Learning · doi:10.1007/s10758-026-09957-8
“The second factor, perceived ease of use, corresponds to the belief that using the technology would require little effort (Davis, 1989; Venkatesh & Bala, 2008).”
Insurance chatbot adoption and continued usage in emerging markets: impact of human-agent access
Pandey, S., Chawla, D., & Puri, S. (2026) · International Journal of Bank Marketing · doi:10.1108/ijbm-03-2025-0225
Huang, Y., Fair, N., Godfrey, K. M., Millard, D., Boniface, M., & Bagust, L. (2025) · International Conference on Education Technology and Computer · doi:10.1109/icetc66579.2025.11387630
“In addition, selected elements from TAM2 [20], and TAM3 [21], including job relevance, perceptions of external control, and perceived enjoyment, were included to better capture educators’ perspectives in real-world classroom contexts.”
Ayyıldız, E., Kesici, B., & Erdoğan, M. (2026) · International Journal of Quality & Reliability Management · doi:10.1108/ijqrm-02-2025-0058
Magna, N. L., Bettelli, A., Nenna, F., Orso, V., Pierobon, L., Mingardi, M., & Gamberini, L. (2026) · Virtual Reality · doi:10.1007/s10055-025-01289-9
Burak, M. F. (2026) · Revista de Gestão e Projetos · doi:10.5585/2026.29466
Generational dynamics and the bandwagon effect in consumer electronics e-commerce
Jajić, I., & Herceg, T. (2026) · Strategic Management · doi:10.5937/straman2600003j
Long, X., Tu, M., Cheng, Z., & Shi, M. (2026) · Literature Language and Cultural Studies · doi:10.63313/llcs.9132
“Extensions like TAM2 and TAM3 add variables such as subjective norms and job relevance (Venkatesh & Bala, 2008[24]).”
InfluentialInfrastructure or culture? Identifying determinants of consumer payments digitalization
Bosek-Rak, D., Kaszyński, D., & Chutnik, A. (2026) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2026.100979 · Cited by 1
Technologies as facilitators of dynamic capabilities in external audits during turbulent times
Fotoh, L. E., Lorentzon, J., & Mugwira, T. (2026) · Accounting Research Journal · doi:10.1108/arj-01-2025-0011
Roba, A. A., Shah, G. H., Mase, W. A., & Apenteng, B. A. (2026) · Research Square · doi:10.21203/rs.3.rs-8942270/v1
Riaz, S., & Shahzad, F. (2025) · Media and Communication Review · doi:10.32350/mcr.52.10
“Their involvement intensified the trust of the community towards the system and improved on the aspect of technological trialability and compatibility dimension, a fact that appealed to the constructs of TAM3, regarding perceived usefulness and facilitating conditions (Venkatesh & Bala, 2008).”
InfluentialFernández‐López, C., Arbeloa, M. C., Pacheco-Ramos, P., Valencia-Soto, C. M., Garrido-Sanchez, L., & Martínez, S. F. (2026) · Farmacia Hospitalaria · doi:10.1016/j.farma.2026.01.005
Roba, A. A., Shah, G. H., Apenteng, B. A., & Mase, W. A. (2026) · Research Square · doi:10.21203/rs.3.rs-8941200/v1
Algorithmic Advantage: Reimagining Business Administration in the Age of Intelligent Systems
Adedoyin, O.-I. G. (2023) · International Journal of Scientific Research and Modern Technology. · doi:10.38124/ijsrmt.v2i10.1258
From Curiosity to Practice: Exploring Generative AI Adoption in Non-STEM Higher Education
Patricia, A., Limios, B., Tanadi, J., & Limantara, N. (2025) · International Conference on Emerging Trends in Information Systems and Informatics (ICETISI) · doi:10.1109/icetisi67983.2025.11406061
“…higher education attest to this possible post-digital transformation: during the last several years, a majority of undergraduates non-STEM students included, were capable of online learning and were of a digital age, more versatile with technology, and diversifying across fields of study [16].”
Chedrawi, C., Haddad, G., Haddad, G., & ElAli, R. (2026) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2026.100986 · Cited by 3
Yang, H.-L., Hung, C., Huang, Y.-T., et al. (2026) · Therapeutic Advances in Respiratory Disease · doi:10.1177/17534666261427319
Delina, G., & Kumar, R. M. (2026) · Management and Labour Studies · doi:10.1177/0258042x261419180 · Cited by 2
“Prior study by Venkatesh and Bala (2008) indicates that even though the users perceive technology as highly useful, greater challenges decrease the willingness to adopt the AI tools.”
Phạm, T. (2026) · Accounting and Auditing Journal · doi:10.59006/vnfa-jaa.02202620
Jin, S.-H., Hoffman, D. L., Paek, S., & Kim, T.-H. (2026) · Educational Technology Research and Development · doi:10.1007/s11423-026-10603-4
“Traditional TAM research has focused primarily on system characteristics—specifically perceived usefulness and perceived ease of use—as the primary determinants of behavioral intention and technology adoption (Davis et al., 1989; Venkatesh & Bala, 2008).”
Sarma, P. K. (2026) · Journal of the Knowledge Economy · doi:10.1007/s13132-026-03178-1
Achabou, M. A. (2026) · Management & Sciences Sociales · doi:10.3917/mss.044.0118
How Cancer Online Support Groups Work, for Whom, and in What Circumstances: Realist Review
Bender, J. L., Scruton, S., Wong, G., Squires, L. R., Babinski, S., Englesakis, M. F., Cyr, A. B., POTTS, H. W. W., Tricco, A. C., Wassersug, R. J., et al. (2026) · Journal of Medical Internet Research · doi:10.2196/77445 · Cited by 1
“The TAM-3 [213] posits that perceived usefulness is determined by social influence (eg, subjective norm and image) and job performance characteristics (eg, job relevance, output quality, and tangible results), while perceived ease of use is determined by control beliefs (eg, computer self-efficacy,…”
Widiarti, N. S. A., Bernardus, D., & Herdinata, C. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6349669
Towards AI Literacy in L1 Education: Examining L1 Teachers’ Beliefs About Generative AI
Stevens, E., van Rijt, J., Bluijs, S., & Bax, S. (2026) · Digital studies in language and literature · doi:10.1515/dsll-2025-0003 · Cited by 2
“To examine the degree of acceptance, we selected a subset of the statements from TAM3 (Venkatesh and Bala 2008), listed in Appendix 1.”
Liu, R., Becerik-Gerber, B., & Lucas, G. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2635682
Ruffin, M. A., Davenport, M. K., & Beier, M. E. (2026) · Behaviour and Information Technology · doi:10.1080/0144929x.2026.2638916
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 ›
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