Browsing by Author "Goyal, Sandeep"

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    Expectation Confirmation in Information Systems Research: A Test of Six Competing Models
    Brown, Susan A.; Venkatesh, Viswanath; Goyal, Sandeep (Society for Information Management, 2014-09-01)
    Expectation confirmation research in general, and in information systems (IS) in particular, has produced conflicting results. In this paper, we discuss six different models of expectation confirmation: assimilation, contrast, generalized negativity, assimilation-contrast, experiences only, and expectations only. Relying on key constructs from the technology acceptance model (TAM), we test each of these six models that suggests different roles for expectations and experiences of the key predictor-here, perceived usefulness- and their impacts on key outcomes-here, behavioral intention, use, and satisfaction. Data were collected in a field study from 1,113 participants at two points in time. Using polynomial modeling and response surface analysis, we provide the analytical representations for each of the six models and empirically test them to demonstrate that the assimilation-contrast is the best existing model in terms of its ability to explain the relationships between expectations and experiences of perceived usefulness and important dependent variables-namely, behavioral intention, use, and satisfaction-in individual-level research on IS implementations.
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    Impact of an Enterprise System Implementation on Job Outcomes: Challenging the Linearity Assumption
    Venkatesh, Viswanath; Goyal, Sandeep (Routledge, 2022-01-02)
    Organizations usually have difficulty adjusting to technology-enabled changes. Recent research has examined the interaction between technology and the key job outcomes of employees. But this research stream has done so using a linear lens even though this interplay has been recognized to be dynamic and complex. We challenge here this linearity assumption. We theorized that enterprise system (ES) use influences post-implementation job scope, and the change from pre- to post-implementation job scope perceptions will have a complex effect on job outcomes that are best captured by a polynomial model. Drawing on the anchoring-and-adjustment perspective in decision-making research, our polynomial model highlights the dynamic nature of employee reactions to changes in job scope brought about by an ES implementation that cannot be captured by traditional linear models. We found support for our model using data collected in a longitudinal field study from 2,794 employees at a telecommunications firm over a period of 12 months. Our findings highlight the key role an ES implementation can have in changing the nature of jobs and how those changes can, in turn, drive job performance and job satisfaction. This research also extends classical job characteristics research by arguing for a more complex relationship between the scope and outcomes of technology-supported jobs.