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The purpose of this paper is to explore how drivers differentially speed up the change process adoption in the perspective of a technological change. More specifically, the paper aims to answer the following question: “Which factors impact the technological change adoption speed of an information system?” Based on an empirical study, our results identify three factors that have a direct influence on the speed of technological change adoption.

Using the Unified Theory of Acceptance and Use of Technology model as a point of departure, the paper analyzes the impact of eight variables grouped in four categories: the perceived attributes of change (performance expectancy and effort expectancy), social influence (peer influence and supervisor influence), facilitating conditions (initial training and helpdesk) and individual characteristics (receptivity to change and self-efficacy). To evaluate which factors accelerate or inhibit change adoption, the paper uses a statistical model of survival analysis.

Based on a 15-month longitudinal study of a workflow system implementation in a telecommunications firm, the results highlight that performance expectancy, supervisor influence and self-efficacy have a direct influence on the speed of technological change adoption.

As a case study, the research findings may only be valid in the particular organization in which it is developed. Indeed, the organizational culture, the company's internal rules, and the history of the organization are factors which significantly influence the speed of change.

The results may help project leaders to be aware of the elements that must be dealt with effectively if a change process is to succeed within the allotted time.

The statistical model of survival analysis allows analyzing change adoption from a dynamic perspective. This statistical approach is quite new and complementary with most of the studies which are qualitative in the field.

Whereas past research has been valuable in explaining how “perceived usefulness” (PU) and “perceived ease of use” (PEU) constructs lead to technology acceptance and refusal behaviors in organizations, it has not explored the antecedents of these two factors. The purpose of this paper is to propose an interpretive approach to the study of front-line employees’ sense making of technological change as well as the understanding of behavioral and psychological origins of PU and PEU.

This study analyses a major transition in work mode induced by an IT innovation implemented within a leading French hospitality company. A qualitative method was employed to answer the research questions. The data were collected using 22 in-depth semi-structured interviews from front-line employees and their line managers in five 4-star hotels in Paris. The participants were asked how they made sense of the technological change and what they consider when they judge the usefulness and the ease of use during the implementation of change.

The analysis revealed that employees’ acceptance of technological change is paradoxical and shaped by a continuous process of sense making when using the IT innovation. The findings also suggest that PU can be explained by factors like job relevance, PEU and output quality. Anxiety, playfulness, perceived enjoyment, objective usability and facilitating conditions were identified as antecedents of PEU.

The paper reports the effect of perceptions of social influence, system characteristics, individual differences and facilitating conditions on PU and PEU constructs in IT adoption process. It is among the first to examine the antecedents of such beliefs in the hospitality industry through the use of a qualitative method. It also shows that that three variables – result demonstrability, computer self-efficacy and social influence process described by subjective norm and image – did not play a significant role in influencing the intensions of using the system through PU and PEU.

Understanding the antecedents of the two key predictors in technology acceptance models allows managers to implement efficient adjustments and interventions in order to positively influence employees’ IT innovation acceptance and use.

This qualitative study contributes to open the black boxes concerning the conceptualizations of PU and PEU. It advances the understanding of the employees’ acceptance of IT innovation.