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This paper in the journal "Gruppe. Interaktion. Organisation. (GIO)" presents a study that investigated user experience characteristics as determinants of technology acceptance. Organizations planning to implement new technologies are confronted with the challenge to ensure user acceptance. Barely accepted technologies are used less often, result in lower job satisfaction, and ultimately lead to performance losses. The technology acceptance model (Venkatesh and Bala 2008) incorporates determinants of information technology use. The model's predictors have a strong focus on interindividual user characteristics (such as computer self-efficacy) and the job context (e.g., voluntariness). Yet, what is lacking in the model, are characteristics of the technology itself that can be used as starting points to design better technologies. To bridge this gap, we introduce the User Experience Technology Acceptance Model, and provide a first test of this model. In our online survey (N = 281), we investigated how technological determinants, more specifically user experience characteristics, affected technology acceptance. Except for two paths of our proposed model, all path coefficients were significant with small to large effect sizes (f 2 = 0.02-0.66). User experience predictors resulted in 60.6% of explained variance in perceived ease of use, 38.2% of explained variance in perceived usefulness, and 25.8% of explained variance in behavioral intention. Our results provide mostly support for our extension of the technology acceptance model. The technology-inherent characteristics output quality, perspicuity, dependability, and novelty were significant predictors of technology acceptance. We discuss theoretical and practical implications with the focus on technology designers, change managers, and users.
This paper in the journal "Gruppe. Interaktion. Organisation. (GIO)" presents a study that investigated user experience characteristics as determinants of technology acceptance. Organizations planning to implement new technologies are confronted with the challenge to ensure user acceptance. Barely accepted technologies are used less often, result in lower job satisfaction, and ultimately lead to performance losses. The technology acceptance model (Venkatesh and Bala 2008) incorporates determinants of information technology use. The model's predictors have a strong focus on interindividual user characteristics (such as computer self-efficacy) and the job context (e.g., voluntariness). Yet, what is lacking in the model, are characteristics of the technology itself that can be used as starting points to design better technologies. To bridge this gap, we introduce the User Experience Technology Acceptance Model, and provide a first test of this model. In our online survey (N = 281), we investigated how technological determinants, more specifically user experience characteristics, affected technology acceptance. Except for two paths of our proposed model, all path coefficients were significant with small to large effect sizes (f 2 = 0.02-0.66). User experience predictors resulted in 60.6% of explained variance in perceived ease of use, 38.2% of explained variance in perceived usefulness, and 25.8% of explained variance in behavioral intention. Our results provide mostly support for our extension of the technology acceptance model. The technology-inherent characteristics output quality, perspicuity, dependability, and novelty were significant predictors of technology acceptance. We discuss theoretical and practical implications with the focus on technology designers, change managers, and users.
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