Construct · 3 names · 4 citations

Where does result demonstrability collide?

Different names. Different fields. One construct. One map.

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Every construct on the map is compared with every other by the meaning of its definitions, and the closest one is surfaced here. The nearest construct to result demonstrability is observability.

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ITEMS RETAINED IN TAM2resultdemonstrability3 NAMESPCI / IDTMOORE & BENBASAT · PCITAM2VENKATESH & DAVIS · TAM2TAM3VENKATESH & BALA · TAM3

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2026

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Perceived characteristics of innovating

the degree to which a person can readily observe and describe the benefits of adopting an innovation.

The tangibility and communicability of the results of using an innovation, that is, the degree to which a person can readily observe and describe the benefits of adopting it. When Moore and Benbasat built the Perceived Characteristics of Innovating instrument in 1991, Rogers's single observability attribute would not hold together as one factor, so they split it in two: result demonstrability, about whether the consequences of use can be seen and explained, and visibility, about whether the artefact itself is seen around the organisation. Result demonstrability kept the four items that ask whether the user could tell others what the system does and whether its results are apparent. The referent is the innovation as perceived, and the criterion is rate of adoption.[1][2]

Unit
A user's perception of how demonstrable an innovation's results are
Recovery means
Not applicable
Measured by
Four-item PCI result-demonstrability subscale, seven-point agreement; adoption as the criterion
Scales indexed for this construct
  • PCI result demonstrability (RD)Moore, G. C., & Benbasat, I., 1991 · ability to see and explain the consequences of using the innovation4 items

TAM2

an antecedent of perceived usefulness in the extended technology acceptance model: systems with easily observed benefits are judged more useful.

The same construct placed inside the technology acceptance model, where Venkatesh and Davis made it one of the cognitive-instrumental determinants of perceived usefulness. In their 2000 A theoretical extension of the technology acceptance model, tested across four longitudinal field studies, result demonstrability joined job relevance, output quality, and subjective norm as antecedents of the usefulness belief: a system whose benefits are easy to observe and describe is judged more useful. The move takes Moore and Benbasat's diffusion subscale, keeps its items unchanged, and reassigns it a causal role in front of a belief about job performance rather than a direct link to adoption.[3]

Unit
A user's perception of how observable and communicable a system's benefits are
Recovery means
Not applicable
Measured by
The four PCI items reused verbatim, modelled as an antecedent of perceived usefulness

TAM3

a cognitive-instrumental determinant of perceived usefulness carried unchanged into TAM3, with the same four items as TAM2.

Result demonstrability carried forward unchanged into TAM3, Venkatesh and Bala's 2008 integration of the usefulness and ease-of-use determinants into one network with a research agenda on interventions. It remains a cognitive-instrumental determinant of perceived usefulness, with the same four items and the same role that TAM2 assigned it, and TAM3 adds no new theory to the construct, only a fixed place in the combined model beside the ease-of-use antecedents. The name, the scale, and the position are inherited; what is new is the surrounding nomological net and the emphasis on what managers can do to move the belief.[4]

Unit
A user's perception of how demonstrable a system's results are
Recovery means
Not applicable
Measured by
The same four items, positioned in TAM3 as a determinant of perceived usefulness

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Nearby collisions

job relevance3 names · 3 citationsjangle · does it fit my job, one antecedentoutput quality3 names · 4 citationsjangle · how well it does the job, one antecedentobservability6 names · 7 citationsjangle · four names, one construct

References

  1. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
  2. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192
  3. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
  4. Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x

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