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Item Context Effects in IS Survey Research

This paper discusses correlational and directional item context effects as two method biases  that can threaten the validity of survey data. Two empirical studies are used to establish their  presence in IS research. In addition, item separation with partial randomization is shown to be a  viable way for researchers to control for correlational item context effects associated with inflated Cronbach’s alphas.