Paper Number
ECIS2026-2535
Paper Type
SP
Abstract
This research‑in‑progress examines why individuals with strong IT identity may reject discontinuous innovative information technologies (DIITs). Drawing on IT identity theory and structural symbolic interactionism, we theorise an esteem‑trap, where strong IT identity coupled with high self‑esteem heightens sensitivity to identity‑meaning misalignment, intensifying identity‑based filtering and increasing DIIT rejection. We propose a conditional process model in which IT identity affects DIIT rejection directly and indirectly through inhibitor‑focused evaluative pathways, with self‑esteem amplifying both effects. A scenario‑based survey will test the model. The study situates identity‑based filtering as a boundary condition for IT identity in DIIT contexts and seeks to uncover whether meaning misalignment drives rejection by highly capable users, informing the design of identity‑supportive cues for more effective DIIT diffusion.
Recommended Citation
Barbieri, Margaret; Carter, Michelle; and Evanschitzky, Heiner, "The Esteem Trap: It Identity-Driven Technology Rejection" (2026). ECIS 2026 Proceedings. 22.
https://aisel.aisnet.org/ecis2026/is_adopt/is_adopt/22
The Esteem Trap: It Identity-Driven Technology Rejection
This research‑in‑progress examines why individuals with strong IT identity may reject discontinuous innovative information technologies (DIITs). Drawing on IT identity theory and structural symbolic interactionism, we theorise an esteem‑trap, where strong IT identity coupled with high self‑esteem heightens sensitivity to identity‑meaning misalignment, intensifying identity‑based filtering and increasing DIIT rejection. We propose a conditional process model in which IT identity affects DIIT rejection directly and indirectly through inhibitor‑focused evaluative pathways, with self‑esteem amplifying both effects. A scenario‑based survey will test the model. The study situates identity‑based filtering as a boundary condition for IT identity in DIIT contexts and seeks to uncover whether meaning misalignment drives rejection by highly capable users, informing the design of identity‑supportive cues for more effective DIIT diffusion.
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