Start Date

12-13-2015

Description

Collaboration technologies are heavily used in organizations enabling employees to communicate, cooperate, and collaborate with each other. There exist much research investigating why different people are using different kinds of collaboration technologies, but some of the research results on technology acceptance are contradictious. A reason for these inconsistent results may be unobserved heterogeneity. Aiming to understand the heterogeneity, the presented research-in-progress discusses the examination of collaboration technology user segments. By applying the finite mixture partial least squares (FIMIX-PLS) approach, we aim to provide a differentiated picture of factors affecting individuals in their acceptance of collaboration technologies. Our preliminary results indicate that the aggregated model basing on the four identified segments provides more explanations than the global research model. Our overall research contributes to existing research, since we characterize different users groups and thus, improve interpretability of collaboration technology acceptance.

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Dec 13th, 12:00 AM

Are you a Maverick? Towards a Segmentation of Collaboration Technology Users

Collaboration technologies are heavily used in organizations enabling employees to communicate, cooperate, and collaborate with each other. There exist much research investigating why different people are using different kinds of collaboration technologies, but some of the research results on technology acceptance are contradictious. A reason for these inconsistent results may be unobserved heterogeneity. Aiming to understand the heterogeneity, the presented research-in-progress discusses the examination of collaboration technology user segments. By applying the finite mixture partial least squares (FIMIX-PLS) approach, we aim to provide a differentiated picture of factors affecting individuals in their acceptance of collaboration technologies. Our preliminary results indicate that the aggregated model basing on the four identified segments provides more explanations than the global research model. Our overall research contributes to existing research, since we characterize different users groups and thus, improve interpretability of collaboration technology acceptance.