The recent work of Owen [SIAM/ASA J. Uncertainty Quantification, 2 (2014), pp. 245--251] has introduced the Shapley value as an importance measure for global sensitivity analysis (Shapley effect, henceforth). When inputs are dependent, using Shapley effects provides a strategy to overcome conceptual difficulties related to the interpretation of Sobol' sensitivity indices. However, Shapley effects have been formulated thus far only to quantify the importance of individual model inputs, without providing information about interactions. This article extends the above-mentioned work to propose a Shapley sensitivity measure for interaction effects. We make use of the generalized Shapley value introduced by Owen [Management Sci., 18 (1972), pp. 6...