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Start Date

16-8-2018 12:00 AM

Description

The study examines how quality and trust, critical factors of IS success, combine and interact with each other to explain e-government adoption. Quality is decomposed in information quality, system quality, and service quality, and trust into trust of service and trust of the government. E-government success and adoption is measured as citizens perceived net benefits. Drawing from complexity and configuration theories a conceptual model is developed that depicts the possible combinations between quality and trust. Fuzzy-set qualitative comparative analysis (fsQCA) is employed to identify these combinations (or configurations) on 502 users of e-government services. Findings identify 5 alternative solutions that increase net benefits and 5 solutions that hinder it. None of the factors is a necessary or sufficient condition for increased net benefits, but it is their combinations that can lead to high net benefits. We stress the need to have either high perceptions on quality or trust for high net benefits, as there is no solution on which any of the quality and trust factors are both at low levels. The study contributes to theory and practice (1) by offering new insights into the interrelationships among predictors of e-government adoption, and (2) by advancing the theoretical and methodological foundation of how quality and trust combine to lead to high and low/medium net benefits when using e-government services.

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Aug 16th, 12:00 AM

Combining system success factors with trust to explain e-government adoption using fsQCA

The study examines how quality and trust, critical factors of IS success, combine and interact with each other to explain e-government adoption. Quality is decomposed in information quality, system quality, and service quality, and trust into trust of service and trust of the government. E-government success and adoption is measured as citizens perceived net benefits. Drawing from complexity and configuration theories a conceptual model is developed that depicts the possible combinations between quality and trust. Fuzzy-set qualitative comparative analysis (fsQCA) is employed to identify these combinations (or configurations) on 502 users of e-government services. Findings identify 5 alternative solutions that increase net benefits and 5 solutions that hinder it. None of the factors is a necessary or sufficient condition for increased net benefits, but it is their combinations that can lead to high net benefits. We stress the need to have either high perceptions on quality or trust for high net benefits, as there is no solution on which any of the quality and trust factors are both at low levels. The study contributes to theory and practice (1) by offering new insights into the interrelationships among predictors of e-government adoption, and (2) by advancing the theoretical and methodological foundation of how quality and trust combine to lead to high and low/medium net benefits when using e-government services.