Papers

Venkatesh, V. “Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model,” Information Systems Research (11:4), 2000, 342-365. https://doi.org/10.1287/isre.11.4.342.11872 [2nd most cited of all papers ever published in Information Systems Research]

View Abstract
Much previous research has been established that perceived ease or use is an important factor influencing user acceptance and usage behavior of information technologies. However, very little research has been conducted to understand how that perception forms and changes over time. The current work presents and tests an anchoring and adjustment-based theoretical model of the determinants of the system-specific perceived ease of use. The model proposes control (internal and external-conceptualized as computer self-efficacy and facilitating conditions, respectively), intrinsic motivation (conceptualized as computer playfulness), and emotion (conceptualized as computer anxiety) as anchors that determine early perceptions about the ease of use of a new system. With increasing experience, it is expected that system-specific perceived ease of use, while still anchored to the general beliefs regarding computers and computer use, will adjust to reflect objective usability, perceptions of external control specific to the new system environment, and system-specific perceived enjoyment. The proposed model was tested in three different organizations among 246 employees using three measurements taken over a three-month period. The proposed model was strongly supported at all points of measurement, and explained up to 60% of the variance in system-specific perceived ease of use, which is twice as much as our current understanding. Important theoretical and practical implications of these findings are discussed.
Download Paper
Request Permission

    Name*

    Email*

    Permission for
    Model PictureInstrument

    Venkatesh, V. and Morris, M.G. “Why Don’t Men Ever Stop to Ask For Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior,” MIS Quarterly (24:1), 2000, 115-139. https://doi.org/10.2307/3250981

    View Abstract
    Using the Technology Acceptance Model (TAM), this research investigated gender differences in the overlooked context of individual adoption and sustained usage of technology in the workplace. User reactions and technology usage behavior were studied over a five-month period among 342 workers being introduced to a new software system. At all three points of measurement, compared to women, men’s technology usage decisions were more strongly influenced by their perceptions of usefulness. In contrast, women were more strongly influenced by perceptions of ease of use and subjective norm, although the effect of subjective norm diminished over time. These findings were robust even after statistically controlling for key confounding variables identified in prior organizational behavior research (i.e., income, occupation, and education levels), and another possible confound from technology research, prior experience with computers in general. Thus, in addition to identifying key boundary conditions in the role of the original TAM constructs (perceived usefulness and perceived ease of use), this research provides the basis for the integration of subjective norm into the model. In light of these findings, implications for theory and practice are discussed.
    Download Paper
    Request Permission

      Name*

      Email*

      Permission for
      Model PictureInstrument

      Venkatesh, V., Morris, M.G., and Ackerman, P.L. “A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes,” Organizational Behavior and Human Decision Processes (83:1), 2000, 33-60. https://doi.org/10.1006/obhd.2000.2896

      View Abstract
      This research investigated gender differences in the overlooked context of individual adoption and sustained usage of technology in the workplace using the theory of planned behavior (TPB). User reactions and technology usage behavior were studied over a 5-month period among 355 workers being introduced to a new software technology application. When compared to women’s decisions, the decisions of men were more strongly influenced by their attitude toward using the new technology. In contrast, women were more strongly influenced by subjective norm and perceived behavioral control. Sustained technology usage behavior was driven by early usage behavior, thus fortifying the lasting influence of gender-based early evaluations of the new technology. These findings were robust across income, organization position, and computer self-efficacy levels.
      Download Paper
      Request Permission

        Name*

        Email*

        Permission for
        Model PictureInstrument

        Venkatesh, V. and Speier, C. “Creating an Effective Training Environment for Enhancing Telework,” International Journal of Human-Computer Studies (52:6), 2000, 991-1005. https://doi.org/10.1006/ijhc.1999.0367

        View Abstract
        There is a growing need for research examining the effective implementation and management of teleworking as it is increasingly being used as an organizational work structure. The enhanced functionality of many information technologies facilitates the completion of work across geographically dispersed teleworkers while simultaneously providing a vehicle to overcome social isolation that has been viewed as an inhibitor of teleworker effectiveness. This research assesses two training methods that can be used to help teleworkers develop skill sets for using these technologies. The results suggest that using a game-based training method facilitates the training process by increasing users’ intrinsic motivation resulting in increased intention to use the technology. This can be particularly important in enhancing the effective completion of team and individual telework while at the same time providing a mechanism to minimize teleworkers social isolation.
        Download Paper
        Request Permission

          Name*

          Email*

          Permission for
          Model PictureInstrument

          Morris, M.G. and Venkatesh, V. “Age Differences in Technology Adoption Decisions: Implications for a Changing Work Force,” Personnel Psychology (53:2), 2000, 375-403. https://doi.org/10.1111/j.1744-6570.2000.tb00206.x

          View Abstract
          This research investigated age difference in individual adoption and sustained usage of technology in the workplace using the theory of planned behavior. User reactions and technology usage behavior were studied over a 5-month period among 118 workers being introduced to a new software system. At 2 points of measurement, compared to older workers, younger workers’ technology usage decisions were more strongly influenced by attitude toward using the technology. In contrast, older workers were more strongly influenced by subjective norm and perceived behavioral control, although the effect of subjective norm diminished over time. These findings were robust, even after controlling for key confounding variables identified in prior organizational behavior research (i.e., income, occupation, and education levels). Theoretical and practical implications for understanding the effects of aging on technology adoption and usage in the workplace are discussed.
          Download Paper
          Request Permission

            Name*

            Email*

            Permission for
            Model PictureInstrument

            Venkatesh, V. “Creation of Favorable User Perceptions: Exploring the Role of Intrinsic Motivation,” MIS Quarterly (23:2), 1999, 239-260. https://doi.org/10.2307/249753

            View Abstract
            A key issue facing information systems researchers and practitioners has been the difficulty in creating favorable user reactions to new technologies. Insufficient or ineffective training has been identified as one of the key factors underlying this disappointing reality. Among the various enhancements to training being examined in research, the role of intrinsic motivation as a lever to create favorable user perceptions has not been sufficiently exploited. In this research, two studies were conducted to compare a traditional training method with a training method that included a component aimed at enhancing intrinsic motivation. The results strongly favored the use of an intrinsic motivator during training. Key implications for theory and practice are discussed.
            Download Paper
            Request Permission

              Name*

              Email*

              Permission for
              Model PictureInstrument

              Venkatesh, V. and Speier, C. “Computer Technology Training in the Workplace: A Longitudinal Investigation of the Effect of Mood,” Organizational Behavior and Human Decision Processes (79:1), 1999, 1-28. https://doi.org/10.1006/obhd.1999.2837

              View Abstract
              How does a person’s mood during technology training influence motivation, intentions, and, ultimately, usage of the new technology? Do these mood effects dissipate or are they sustainable over time? A repeated-measures field study (n = 316) investigated the effect of mood on employee motivation and intentions toward using a specific computer technology at two points in time: immediately after training and 6 weeks after training. Actual usage behavior was assessed for 12 weeks after training. Each individual was assigned to one of three mood treatments: positive, negative, or control. Results indicated that there were only short-term boosts in intrinsic motivation and intention to use the technology among individuals in the positive mood intervention. However, a long-term lowering of intrinsic motivation and intention was observed among those in the negative mood condition.
              Download Paper
              Request Permission

                Name*

                Email*

                Permission for
                Model PictureInstrument

                Venkatesh, V. and Davis, F.D. “A Model of the Antecedents of Perceived Ease of Use: Development and Test,” Decision Sciences (27:3), 1996, 451-481. https://doi.org/10.1111/j.1540-5915.1996.tb00860.x [in 2020, this paper was recognized as the 2nd most cited paper ever published in Decision Sciences’ 50-year history]

                View Abstract
                The Technology Acceptance Model (TAM) has been widely used to predict user acceptance and use based on perceived ease of use and usefulness. However, in order to design effective training interventions to improve user acceptance constructs. In this research, we focus on understanding the determinants of perceived ease of use. Data from three experiments spanning 108 subjects and six different systems supported our hypothesis that an individual’s perception of a particular system’s ease of use is anchored to her or his general computer self-efficacy at all times, and objective usability has an impact on ease of use perceptions about a specific system only after direct experience with the system. In addition to being an important research issue in user acceptance research, understanding antecedents of perceived ease of use is also important from a practical standpoint since several systems in which millions of dollars are invested are rejected because of poor user interfaces. Moreover, the actual underlying problem might be low computer self-efficacy of the target user group. In such cases, training interventions aimed at improving computer self-efficacy of users may be more effective than improved interface design for increasing user acceptance.
                Download Paper
                Request Permission

                  Name*

                  Email*

                  Permission for
                  Model PictureInstrument

                  Davis, F.D. and Venkatesh, V. “A Critical Assessment of Potential Measurement Biases in the Technology Acceptance Model: Three Experiments,” International Journal of Human-Computer Studies (45:1), 1996, 19-45. https://doi.org/10.1006/ijhc.1996.0040

                  View Abstract
                  The Technology Acceptance Model (TAM) is widely used by researchers and practitioners to predict and explain user acceptance of information technologies. TAM models system usage intentions and behavior as a function of perceived usefulness and perceived ease of use. The original scales for measuring the TAM constructs have been confirmed to be reliable and valid in several replications and applications spanning a range of technologies and user populations. However, a measurement bias may be present because the TAM instrument physically groups together the multiple items measuring each individual construct. Many scholars of instrument design would object to such item grouping, instead advocating that items from different constructs be intermixed in order to reduce “carryover” effects among the responses to multiple items targeting a specific construct, which might artificially inflate the observed reliability and validity. Three experiments involving two systems and a total of 708 subjects are reported which address whether such carryover biases are present in the TAM measures. All three studies found that item grouping vs. item intermixing had no significant effect (positive or negative) either on the high levels of reliability and validity of the TAM scales, or on the path coefficients linking them together. Ironically, open-ended verbal evaluations indicated that subjects were more confused and annoyed when items were intermixed, suggesting a tendency toward “output interference” effects, which themselves could have a biasing effect. Our findings suggest that those who employ the TAM measures should continue using the original (grouped) format in order to best predict and explain user acceptance of information technology.
                  Download Paper
                  Request Permission

                    Name*

                    Email*

                    Permission for
                    Model PictureInstrument


                    Pages: 1 2 3 4 5 6 7 8 9 10 11 12 13