Hypothesis development: structural equation model
M)Based
Because structural equation modeling focuses on testing of models of hypothesized theoretical relationships, we synthesized the results of our literature review to select theory-based latent constructs with the findings related to the qualitative configurational model (see Fig. Context-mechanism-outcome model for physician delivery of digital innovationWe chose the construct of organizational readiness for change as an organizational variable at the meso level [At the meso level, we hypothesized that organizational readiness for change is an important prerequisite to enable physicians to evaluate the effectiveness of innovation (mechanism [reasoning]; meso- and micro-level relations; a-path). This assumption was based on what our previous qualitative analyses demonstrated. For example, the process of patient registration and the groundwork for transferring additional patient data into digital innovation depend on the readiness of the primary care employees. They have to adapt to these changes brought about by the implementation of innovation. Both these tasks are related to organizational readiness and are important prerequisites for activating the part of the mechanism that corresponds to physician reasoning. The primary role of the physician is to make appropriate clinical decisions regarding the prescription of medications for patients with polypharmacy. Contextualized beliefs regarding the effectiveness of innovation consist of several components. These components are important from the pragmatic perspective of physicians in the management of polypharmacy patients in ambiguous clinical decision situations (context → mechanism [reasoning]). We hypothesized that physicians would only perceive the innovation as being effective if it addressed components relevant to the care of polypharmacy patients on a practical level.Moreover, physicians’ strong contextual beliefs increase a positive effect on the intention to use the innovation (b-path). Finally, we assessed whether the hypothesized direct relationship between the organization’s readiness to implement innovation and the physician’s intention to adopt (c-path) is mediated by the physicians’ belief in the effectiveness of innovation.Our empirical research questions for the mediation analysis are as follows: Do physicians’ contextualized beliefs regarding the effectiveness of innovation (micro level) mediate the relationship between primary care organizations’ readiness for change (meso level) and physicians’ adoption behavior (micro level) during the change process of implementing digital innovation for polypharmacy management? How strong are the direct and indirect effects?
Mediation modelNote: X = independent variable, M = mediator, and Y = outcome. The indirect effect is estimated as the product of the a- and b-paths (i.e., a*b). The c-path represents the direct effect of X on Y (i.e., the effect of X on Y that is not transmitted through the mediator, M)Based on the previous discussion, the following hypotheses are proposed:H1: Organizational readiness for change has a positive direct effect on behavioral intention to use digital innovation (c-path).H2: Organizational readiness for change has a positive direct effect on physicians’ contextualized innovation effectiveness beliefs (a-path).H3: Physicians’ contextualized innovation effectiveness beliefs have a positive direct effect on behavioral intention to use digital innovation (b-path).H4: Physicians’ contextualized innovation effectiveness beliefs mediate the relations between organizational readiness for change and behavioral intention to use digital innovation.H5: Physician and structural characteristics have direct and indirect effects on contextualized innovation beliefs and intention to use digital innovation.