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)
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
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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
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Multiple regression: testing and interpreting interactions
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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
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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
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Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead
University of Arkansas, Venkatesh, V., Thong, J., Hong Kong University of Science and Technology, Xu, X., & The Hong Kong Polytechnic University (2016) · Journal of the Association for Information Systems · doi:10.17705/1jais.00428 · Cited by 2,513
“Note that we did not count studies that integrated TAM (Davis, 1989) and its updates (e.g., TAM3: Venkatesh & Bala, 2008) in this category but as general citations.”
BackgroundMethodInfluentialSelf-citationDwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019) · Information Systems Frontiers · doi:10.1007/s10796-017-9774-y · Cited by 2,137
Scherer, R., Siddiq, F., & Tondeur, J. (2019) · Computers & Education · doi:10.1016/j.compedu.2018.09.009 · Cited by 1,923
“Venkatesh and Bala (2008), therefore, classi fi ed the possible relevance of the TAM model into two categories: pre-implementation and post-implementation phases.”
BackgroundInfluentialEvaluating E-learning systems success: An empirical study
Al-Fraihat, D., Joy, M., Masa'deh, R., & Sinclair, J. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2019.08.004 · Cited by 1,350
Borghouts, J., Eikey, E., Mark, G., De Leon, C., Schueller, S. M., Schneider, M., Stadnick, N., Zheng, K., Mukamel, D., & Sorkin, D. H. (2021) · Journal of Medical Internet Research · doi:10.2196/24387 · Cited by 1,069
“…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].”
Backgroundde Queiroz, M. M., & Wamba, S. F. (2018) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2018.11.021 · Cited by 1,199
The literature review of technology adoption models and theories for the novelty technology
Lai, P. C. (2017) · Journal of Information Systems and Technology Management · doi:10.4301/s1807-17752017000100002 · Cited by 1,312
Ashfaq, M., Yun, J., Yu, S., & Loureiro, S. M. C. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2020.101473 · Cited by 1,200
Trust in AI and Its Role in the Acceptance of AI Technologies
Choung, H., David, P., & Ross, A. (2023) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2050543 · Cited by 963
“Later, more elaborate versions of the TAM (i.e., TAM 2, TAM 3) were developed, incorporating additional external factors, such as social norms and perceived enjoyment (Venkatesh & Bala, 2008; Venkatesh & Davis, 2000), and treating attitude as a predictor of behavior.”
BackgroundVenkatesh, V., Thong, J. Y. L., Chan, F. K. Y., Hu, P. J.-H., & Brown, S. A. (2011) · Information Systems Journal · doi:10.1111/j.1365-2575.2011.00373.x · Cited by 852
“This extension is in line with recent calls for incorporating constructs relevant to the changing nature of emerging technologies to aid the design of interventions (Venkatesh et al ., 2007; Venkatesh & Bala, 2008).”
ResultSelf-citationPatil, P. P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102144 · Cited by 783
Makransky, G., & Lilleholt, L. (2018) · Educational Technology Research and Development · doi:10.1007/s11423-018-9581-2 · Cited by 796
“According to the technology acceptance model (TAM), behavioral intention to use predicts actual use (Venkatesh and Bala 2008).”
BackgroundMethodInfluentialMcLean, G., & Osei-Frimpong, K. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.05.009 · Cited by 762
(2012) · DSpace (Open University in the Netherlands) · Cited by 754
Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model
Chatterjee, S., Rana, N. P., Dwivedi, Y. K., & Baabdullah, A. M. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120880 · Cited by 825
Abdullah, F., Ward, R., & Ahmed, E. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.05.014 · Cited by 693
“(Venkatesh & Bala, 2008, p.314; Venkatesh & Davis, 2000) BI2 Given that I had access to the e-portfolio, I predict that I would use it.”
BackgroundA Systematic Review of the Technology Acceptance Model in Health Informatics
Rahimi, B., Nadri, H., Lotfnezhad Afshar, H., & Timpka, T. (2018) · Applied Clinical Informatics · doi:10.1055/s-0038-1668091 · Cited by 688
Adoption and use of AI tools: a research agenda grounded in UTAUT
Venkatesh, V. (2021) · Annals of Operations Research · doi:10.1007/s10479-020-03918-9 · Cited by 783
Self-citationMcLean, G., & Wilson, A. M. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.07.002 · Cited by 726
Salloum, S. A., Qasim Mohammad Alhamad, A., Al-Emran, M., Abdel Monem, A., & Shaalan, K. (2019) · IEEE Access · doi:10.1109/access.2019.2939467 · Cited by 651
“The term signifies the intrinsic motivation factor which is related to the use of a new system [64].”
BackgroundWhen predictors of outcomes are necessary: guidelines for the combined use of PLS-SEM and NCA
Richter, N., Schubring, S., Hauff, S., Ringle, C. M., & Sarstedt, M. (2020) · Industrial Management & Data Systems · doi:10.1108/imds-11-2019-0638 · Cited by 722
Fernandes, T., & Oliveira, E. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.08.058 · Cited by 671
Trenerry, B., Chng, S., Wang, Y., Suhaila, Z. S., Lim, S. S., Lu, H. Y., & Oh, P. H. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.620766 · Cited by 930
Zhong-qing, H., Ding, S., Li, S., Chen, L., & Yang, S. (2019) · Symmetry · doi:10.3390/sym11030340 · Cited by 746
“A large number of empirical studies on the adoption of information technology in the past decade have shown that perceived usefulness can have a positive impact on users’ intentions [22–25].”
BackgroundPredicting collaboration technology use: integrating technology adoption and collaboration research
Brown, S. A., Dennis, A. R., & Venkatesh, V. (2010) · Journal of Management Information Systems · doi:10.2753/mis0742-1222270201 · Cited by 592
“Effort expectancy can be particularly important in the context of personal technologies and non-workplace settings [70] and has been identified as an important predictor in the context of communication technologies [61].”
BackgroundInfluentialSelf-citationAlmost human? A comparative case study on the social media presence of virtual influencers
Arsenyan, J., & Mirowska, A. (2021) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2021.102694 · Cited by 566
Morosan, C. V., & Defranco, A. L. (2015) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2015.11.003 · Cited by 576
Aubert, B. A., Schroeder, A., & Grimaudo, J. (2012) · Decision Support Systems · doi:10.1016/j.dss.2012.07.002 · Cited by 637
“Finally, the perception of the usefulness of a technology is influenced by the extent to which a technology is seen as easy to use [18,70].”
BackgroundA hedonic motivation model in virtual reality tourism: Comparing visitors and non-visitors
Kim, M. J., & Hall, C. M. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2018.11.016 · Cited by 589
Hansen, J. M., Saridakis, G., & Benson, V. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.11.010 · Cited by 629
“Further research has been undertake to try to improve upon its accuracy and predictive ability (e.g., Szajna, 1996; Venkatesh & Bala, 2008; Venkatesh & Davis, 2000; Venkatesh, Morris, Davis, & Davis, 2003; Wixom & Todd, 2005).”
Backgroundde Luna, I. R., Liébana-Cabanillas, F. J., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2019) · Technological forecasting & social change · doi:10.1016/j.techfore.2018.09.018 · Cited by 468
The impact of trust and perceived risk on internet banking adoption in India
Kesharwani, A., & Bisht, S. S. (2012) · International Journal of Bank Marketing · doi:10.1108/02652321211236923 · Cited by 583
“Many researchers have empirically proven that perceived usefulness exert a significant and positive effect on attitude towards using IT or associated systems (Venkatesh and Bala, 2008; Davis, 1989; Venkatesh and Davis, 2000).”
BackgroundA theoretical model of mobile augmented reality acceptance in urban heritage tourism
Dieck, M. C. T., & Jung, T. H. (2015) · Current Issues in Tourism · doi:10.1080/13683500.2015.1070801 · Cited by 542
“Within previous TAM research, a number of researchers (Lucas & Spitler, 1999; Pai & Huang, 2011; Venkatesh & Bala, 2008) con-fi rmed the importance of information quality for perceived usefulness and perceived ease of use.”
BackgroundWearable technologies: The role of usefulness and visibility in smartwatch adoption
Chuah, S. H., Rauschnabel, P. A., Krey, N., Nguyen, B., Ramayah, T., & Lade, S. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.07.047 · Cited by 595
“Visibility is distinct but related to the image construct and the norms construct in prior TAM research (Fisher & Price, 1992; Venkatesh & Bala, 2008; Venkatesh & Davis, 2000).”
BackgroundAntecedents of the adoption of the new mobile payment systems: The moderating effect of age
Liébana-Cabanillas, F. J., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.03.022 · Cited by 523
“…2000) with the inclusion of social influence processes and instrumental cognitive processes, UTAUT (Venkatesh, Morris, Davis, & Davis, 2003), TAM 3 (Venkatesh & Bala, 2008), which expand the primitive model with a set of predictive and moderating factors, and the MOPTAM (Renaud and Biljon’s Mobile…”
BackgroundMethodInfluentialAssessing Common Method Bias: Problems with the ULMC Technique1
Chin, W. W., Thatcher, J. B., & Wright, R. T. (2012) · MIS Quarterly · doi:10.2307/41703491 · Cited by 505
“…al. 2010; Sarker and Valacich 2010; Seddon et al. 2010; Setia et al. 2011; Sharma et al. 2009; Shi et al. 2008; Shim et al. 2009; Vance et al. 2008; Venkatesh and Bala 2008; Weerakkody et al. 2009; Wong et al. 2009; Xue et al. 2008; Xue et al. 2011; Yamouchia and Swanson 2010; Zhu et al. 2010 43…”
BackgroundExploring influencing variables for the acceptance of social robots
de Graaf, M. M. A., & Ben Allouch, S. (2013) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2013.07.007 · Cited by 499
“Behavioral control Bandura [56] 10 10 4.”
Determinants of intention to use the mobile banking apps: An extension of the classic TAM model
Muñoz‐Leiva, F., Climent-Climent, S., & Liébana-Cabanillas, F. J. (2017) · Spanish Journal of Marketing - ESIC · doi:10.1016/j.sjme.2016.12.001 · Cited by 556
Chang, C., Hajiyev, J., & Su, C.-R. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.04.010 · Cited by 533
Kim, J., & Park, H.-A. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.2143 · Cited by 475
“TAM has been continuously expanded to TAM2, the unified theory of acceptance and use of technology, and TAM3, and each of these expansions was motivated by the need to predict the usability of new information technology and to identify and stimulate the use of the technology [9-12].”
BackgroundEmpirical investigation of e-learning acceptance and assimilation: A structural equation model
Al‐Gahtani, S. S. (2014) · Applied Computing and Informatics · doi:10.1016/j.aci.2014.09.001 · Cited by 551
“According to Venkatesh and Bala [44], ‘‘individual difference variables include personality and/or demo-graphics (e.g., traits or states of individuals, gender, and age) that can influence individuals’ perceptions of PU and PEOU’’, while, ‘‘system characteristics are those salient features of a…”
BackgroundMethodInfluentialRese, A., Baier, D., Geyer-Schulz, A., & Schreiber, S. (2016) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.10.010 · Cited by 535
“Thus, the TAM model has been extended with various constructs, e.g. the TAM2 model (Venkatesh and Davis, 2000) adds antecedents to PU and the TAM3 model (Venkatesh and Bala, 2008) to PEOU.”
MethodAnalysis of users and non-users of smartphone applications
Verkasalo, H., López‐Nicolás, C., Molina‐Castillo, F., & Bouwman, H. (2009) · Telematics and Informatics · doi:10.1016/j.tele.2009.11.001 · Cited by 469
“Social norms, also referred to as subjective norms or social influence, represent a factor that is assumed to have a direct impact on perceived utility (López-Nicolás et al., 2008; Sun and Zhang, 2006; Venkatesh and Bala, 2008).”
BackgroundMethodChopdar, P. K., Korfiatis, N., Sivakumar, V. J., & Lytras, M. D. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.04.017 · Cited by 468
Albayati, H., Kim, S. K., & Rho, J. J. (2020) · Technology in Society · doi:10.1016/j.techsoc.2020.101320 · Cited by 464
Predicting m-commerce adoption determinants: A neural network approach
Chong, A. Y. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.07.068 · Cited by 491
Miltgen, C. L., Popovič, A., & Oliveira, T. (2013) · Decision Support Systems · doi:10.1016/j.dss.2013.05.010 · Cited by 460
“Developing theory that is more focused and context specific – here, technology specific – is considered an important frontier for advances in IS research [68, 84].”
BackgroundInfluentialDiscovering Unobserved Heterogeneity in Structural Equation Models to Avert Validity Threats1
Becker, J.-M., Rai, A., Ringle, C. M., & Völckner, F. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37.3.01 · Cited by 478
“…existing theory expects contextual variables, such as voluntariness or task type (e.g., Venkatesh and Davis 2000), or psychographic variables, such as personal innovativeness and computer attitude, to cause heterogeneity in the relationships among the TAM constructs (e.g., Venkatesh and Bala 2008).”
BackgroundMeléndez, A. P., Obra, A. R. D. Á., & Garrido‐Moreno, A. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.12.014 · Cited by 484
Taking “Fun and Games” Seriously: Proposing the Hedonic-Motivation System Adoption Model (HMSAM)
Lowry, P. B., Gaskin, J. E., Twyman, N. W., Hammer, B. I., & Roberts, T. (2013) · Journal of the Association for Information Systems · doi:10.17705/1jais.00347 · Cited by 504
“It is by illuminating alternative theoretical perspectives and providing evidence for important theoretical boundaries that system acceptance studies continue to make meaningful contributions (Venkatesh & Bala, 2008; Venkatesh, Davis, & Morris, 2007).”
BackgroundTarhini, A., Hone, K., Liu, X., & Tarhini, T. (2017) · Interactive Learning Environments · doi:10.1080/10494820.2015.1122635 · Cited by 445
“Many studies have supported TAM ’ s explanatory power within the context of IS implementation in general (Venkatesh & Bala, 2008) and a number of studies have successfully extended its application to the context of e-learning (Alshare, Freeze, Lane, & Wen, 2011; Chang & Tung, 2008; Hu & Hui, 2012;…”
BackgroundA conceptual model for the process of IT innovation adoption in organizations
Hameed, M. A., Counsell, S., & Swift, S. (2012) · Journal of Engineering and Technology Management · doi:10.1016/j.jengtecman.2012.03.007 · Cited by 442
Al-Rahmi, W. M., Yahaya, N., Aldraiweesh, A. A., Alamri, M. M., Aljarboa, N. A., Alturki, U., & Aljeraiwi, A. A. (2019) · IEEE Access · doi:10.1109/access.2019.2899368 · Cited by 435
Xu, D. J., Benbasat, I., & Cenfetelli, R. T. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37.3.05 · Cited by 441
Faqih, K. M. S., & Jaradat, M.-I. R. M. (2014) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2014.09.006 · Cited by 421
“Meanwhile, this is an early adoption study, therefore we delete from the original TAM3 post implementation variables (perceived enjoyment and objective usability) which play a role in determining perceived ease of use after individuals gain experience with the new system (Venkatesh and Bala, 2008).”
BackgroundMethodInfluentialSukendro, S., Habibi, A., Khaeruddin, K., Indrayana, B., Syahruddin, S., Makadada, F. A., & Hakim, H. (2020) · Heliyon · doi:10.1016/j.heliyon.2020.e05410 · Cited by 482
“Studies reported some external factors to accompany the original TAM constructs (Venkatesh and Bala, 2008; Venkatesh and Davis, 2000).”
Acceptance of artificial intelligence among pre-service teachers: A multigroup analysis
Zhang, C., Schießl, J., Plößl, L., Hofmann, F., & Gläser-Zikuda, M. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00420-7 · Cited by 413
Consumer Resistance to Innovation in Services: Challenges and Barriers in the Internet of Things Era
Mani, Z., & Chouk, I. (2018) · Journal of Product Innovation Management · doi:10.1111/jpim.12463 · Cited by 444
Brown, B. C., Gude, W. T., Blakeman, T., van der Veer, S. N., Ivers, N. M., Francis, J., Lorencatto, F., Presseau, J., Peek, N. B., & Daker‐White, G. (2019) · Implementation Science · doi:10.1186/s13012-019-0883-5 · Cited by 409
“Technology Acceptance Model [66] Variables: Feedback attitude, Relevance, Usability Mechanisms: Relative advantage”
BackgroundCloud computing adoption and usage in community colleges
Behrend, T. S., Wiebe, E., London, J., & Johnson, E. C. (2010) · Behaviour and Information Technology · doi:10.1080/0144929x.2010.489118 · Cited by 383
“That is, more experience solidifies one’s perception of ease of use and increases its effect on perceived usefulness (Venkatesh and Bala 2008).”
BackgroundInfluentialOleson, A. K., & Hora, M. T. (2013) · Higher Education · doi:10.1007/s10734-013-9678-9 · Cited by 458
“September 2012”
BackgroundKowalczuk, P., Siepmann, C., & Adler, J. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.10.050 · Cited by 440
Mailizar, M., Burg, D., & Maulina, S. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10557-5 · Cited by 420
“Furthermore, for the other constructs, we adopted from (Al-Adwan et al., 2013; Davis, 1989; Venkatesh & Bala, 2008).”
MethodTechnology Acceptance in Healthcare: A Systematic Review
AlQudah, A. A., Al‐Emran, M., & Shaalan, K. F. (2021) · Applied Sciences · doi:10.3390/app112210537 · Cited by 461
“Those theories include but are not limited to the theory of reasoned action (TRA) [12], the technology acceptance model (TAM) [13–15], extensions of TAM [16,17], the unified theory of acceptance and use of technology (UTAUT) [18], social cognitive theory (SCT) [19,20], the theory of interpersonal behavior (TIB) [21],…”
BackgroundGansser, O. A., & Reich, C. S. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101535 · Cited by 435
Mobile-banking adoption: empirical evidence from the banking sector in Pakistan
Farah, M. F., Hasni, M. J. S., & Abbas, A. K. (2018) · International Journal of Bank Marketing · doi:10.1108/ijbm-10-2017-0215 · Cited by 361
Robotics for Customer Service: A Useful Complement or an Ultimate Substitute?
Xiao, L., & Kumar, V. (2019) · Journal of Service Research · doi:10.1177/1094670519878881 · Cited by 366
“Literature on TAM indicates that the characteristics of both customers and service robots will have an effect on customers’ behavior of adoption and interaction with service robots (e.g., Venkatesh and Bala 2008; Venkatesh et al. 2003).”
BackgroundInfluentialMcLean, G., Osei-Frimpong, K., & Barhorst, J. B. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.11.045 · Cited by 403
Nastjuk, I., Herrenkind, B., Marrone, M., Brendel, B., & Kolbe, L. M. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120319 · Cited by 380
Venkatesh, V., Thong, J. Y. L., Chan, F. K. Y., & Hu, P. J. (2016) · Information Systems Research · doi:10.1287/isre.2015.0612 · Cited by 378
“…and use of e-government services, some research has noted that findings concerning the general factors in these models (e.g., perceived usefulness, perceived ease of use) cannot provide specific guidance to direct design and practice (Hong et al. 2014, Venkatesh 2000, Venkatesh and Bala 2008).”
BackgroundSelf-citationThe role of task-technology fit as users’ motivation to continue information system use
Larsen, T. J., Sørebø, A. M., & Sørebø, Ø. (2009) · Computers in Human Behavior · doi:10.1016/j.chb.2009.02.006 · Cited by 382
“Over the last two decades, the amount of research within the TAM umbrella has been vigorous (Venkatesh, 2008).”
BackgroundFactors affecting the adoption and use of urban air mobility
Haddad, C. A., Chaniotakis, E. M., Straubinger, A., Plötner, K., & Antoniou, C. (2019) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2019.12.020 · Cited by 351
Predicting the intention to use mobile banking in India
Singh, S., & Srivastava, R. K. (2018) · International Journal of Bank Marketing · doi:10.1108/ijbm-12-2016-0186 · Cited by 377
“(Venkatesh & Bala, 2008), TPB (57”
de Queiroz, M. M., Wamba, S. F., de Bourmont, M., & Telles, R. (2020) · International Journal of Production Research · doi:10.1080/00207543.2020.1803511 · Cited by 390
“The literature concerning technology adoption models is rich (Davis 1989; Venkatesh and Davis 2000; Venkatesh et al. 2003; Venkatesh and Bala 2008; Venkatesh, Thong, and Xu 2012).”
BackgroundHolmes, T. C., Singh, R., Axt, M., Brenner, S., & Barteit, S. (2022) · npj Digital Medicine · doi:10.1038/s41746-022-00700-y · Cited by 413
“In general, technology acceptance is a complex process 48 .”
BackgroundIntegrated technology-organization-environment (T-O-E) taxonomies for technology adoption
Awa, H. O., Ojiabo, O. U., & Orokor, L. E. (2017) · Journal of Enterprise Information Management · doi:10.1108/jeim-03-2016-0079 · Cited by 415
Pynoo, B., Devolder, P., Tondeur, J., van Braak, J., Duyck, W., & Duyck, P. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.10.005 · Cited by 341
Zhang, P. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37.1.11 · Cited by 331
“…Tam 2006; Hwang and Kim 2007; Igbaria et al. 1996; Lin et al. 2005; Parboteeah et al. 2009; Thong et al. 2006; van der Heijden 2004; Venkatesh 2000; Venkatesh and Bala 2008; Yi and Hwang 2003 The extent to which the activity of using the computer is perceived to be enjoyable in its own right,…”
BackgroundBehavioural intention to adopt mobile wallet: a developing country perspective
Madan, K., & Yadav, R. (2016) · Journal of Indian Business Research · doi:10.1108/jibr-10-2015-0112 · Cited by 281
Wang, J., & Fan, W. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04787-y · Cited by 322
“The technology acceptance model posits that perceived usefulness and perceived ease of use in fl uence an individual ’ s intention or attitude toward using new technology (Venkatesh and Bala, 2008).”
RetractedLim, S. H., Kim, D. J., Hur, Y., & Park, K. (2018) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2018.1507132 · Cited by 354
“…behaviors in information technology, the usefulness of emerging technologies (e.g. IoT), the factors that affect the acceptance behavior, etc. (Davis et al., 1989; Venkatesh, 2000; Venkatesh & Bala, 2008; Venkatesh & Davis, 2000; Venkatesh et al., 2003; Yang, Lu, Gupta, Cao, & Zhang, 2012).”
BackgroundMe, My Self, and I(T): Conceptualizing Information Technology Identity and ITS Implications1
Carter, M., & Grover, V. (2015) · MIS Quarterly · doi:10.25300/misq/2015/39.4.9 · Cited by 324
Technology Adoption by Older Adults: Findings From the PRISM Trial
Mitzner, T. L., Savla, J., Boot, W. R., Sharit, J., Charness, N., Czaja, S. J., & Rogers, W. A. (2019) · The Gerontologist · doi:10.1093/geront/gny113 · Cited by 311
Predictors of customer acceptance of and resistance to smart technologies in the retail sector
Roy, S. K., Balaji, M. S., Quazi, A. M., & Quaddus, M. (2018) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2018.02.005 · Cited by 370
“…system characteristics, individual differences, facilitating conditions, consumer traits and organisation characteristics as exogenous variables of the TAM model (Venkatesh and Bala, 2008; Kwee-Meier et al., 2016; Gelderman et al., 2011; Rosenbaum and Wong, 2015; Purohit and Srivastava, 2001).”
BackgroundAgudo-Peregrina, Á. F., Hernández-García, Á., & Pascual-Miguel, F. J. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.10.035 · Cited by 325
Pookulangara, S., & Koesler, K. (2011) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2011.03.003 · Cited by 354
Information and Communication Technologies in Tourism 2014
Xiang, Z., & Tussyadiah, I. P. (2013) · Springer eBooks · doi:10.1007/978-3-319-03973-2 · Cited by 359
Factors influencing students’ adoption of e-learning: a structural equation modeling approach
Tarhini, A., Masa’deh, R. M. T., Al‐Busaidi, K. A., Mohammed, A. B., & Maqableh, M. (2017) · Journal of International Education in Business · doi:10.1108/jieb-09-2016-0032 · Cited by 318
Sands, S., Ferraro, C., Demsar, V., & Chandler, G. (2022) · Business Horizons · doi:10.1016/j.bushor.2022.08.002 · Cited by 288
Factors Affecting Mobile Payment Adoption Intention: An Indian Perspective
Shankar, A., & Datta, B. (2018) · Global Business Review · doi:10.1177/0972150918757870 · Cited by 325
“The TAM is widely adopted and robust model in information technology adoption-related studies (Arvidsson, 2014; Chen, 2008; Duane et al., 2014; Keramati et al., 2012; Kim et al., 2010; Venkatesh & Bala, 2008; Venkatesh & Davis, 2000; Yan, Md-Nor, Abu-Shanab & Sutanonpaiboon, 2009).”
MethodCan teachers’ digital competence influence technology acceptance in vocational education?
Antonietti, C., Cattáneo, A., & Amenduni, F. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107266 · Cited by 551
Vahdat, A., Alizadeh, A., Quach, S., & Hamelin, N. (2020) · Australasian Marketing Journal (AMJ) · doi:10.1016/j.ausmj.2020.01.002 · Cited by 393
“The second group concentrates on factors as intermediaries (such as satisfaction and stickiness between TAM factors and the dependant variable), while the third group encompasses studies like TAM2 (Venkatesh and Davis, 2000) and TAM3 (Venkatesh and Bala, 2008), which propose factors anticipating perceived usefulness a…”
BackgroundMobile payments adoption by US consumers: an extended TAM
Bailey, A. A., Pentina, I., Mishra, A. S., & Mimoun, M. S. B. (2017) · International Journal of Retail & Distribution Management · doi:10.1108/ijrdm-08-2016-0144 · Cited by 309
Hertzum (2017) · doi:10.1145/3127358 · Cited by 307
“Consequently, several later TAM studies recommend the incorporation of subjective norm (e.g., Taylor & Todd, 1995; Venkatesh & Bala, 2008; Venkatesh & Davis, 2000).”
BackgroundMeasuring engagement in video game-based environments: Investigation of the User Engagement Scale
Wiebe, E., Lamb, A., Frankosky, M. H., & Sharek, D. J. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2013.12.001 · Cited by 336
“…and usability have a long, established history in research in human–computer interaction (cf., Shneiderman, 1998) and form the backbone of well-established frameworks such as the Technology Acceptance Model (Bourgonjon, Valcke, Soetaert, & Schellens, 2010; Venkatesh & Bala, 2008).”
MethodWells, J. D., Campbell, D. E., Valacich, J. S., & Featherman, M. S. (2010) · Decision Sciences · doi:10.1111/j.1540-5915.2010.00292.x · Cited by 324
“From a reward perspective, factors such as ease of use, trust, and usefulness have been shown to positively influence adoption intentions (Gefen, Karahanna, & Straub, 2003; Venkatesh et al., 2003; Venkatesh & Bala, 2008).”
BackgroundInfluentialAugmented reality smart glasses: an investigation of technology acceptance drivers
Rauschnabel, P. A., & Ro, Y. K. (2016) · International Journal of Technology Marketing · doi:10.1504/ijtmkt.2016.075690 · Cited by 306
“For example, TAM2, TAM3, and UTAUT all incorporate ‘image’ as a factor.”
BackgroundInfluentialCross-cultural differences in adopting mobile augmented reality at cultural heritage tourism sites
Jung, T. H., Lee, H., Chung, N., & Dieck, M. C. T. (2018) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-02-2017-0084 · Cited by 333
“In fact, perceived enjoyment was found to be a strong determinant of ease of use within a variety of studies and contexts (e.g., Venkatesh, 2000; Venkatesh & Bala, 2008).”
Unpacking teachers’ intentions to integrate technology: A meta-analysis
Scherer, R., & Teo, T. P. (2019) · Educational Research Review · doi:10.1016/j.edurev.2019.03.001 · Cited by 399
Choi, J. R., & Kim, S. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.06.007 · Cited by 325
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
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