%0 Journal Article %T A Meta-Analysis of Marketing Communication Carryover Effects %A Köhler, Christine %A Mantrala, Murali K. %A Albers, Sönke %A Kanuri, Vamsi K. %D 2017 %J Journal of Marketing Research %@ 0022-2437 %N 6 %V 54 %P 990–1008 %! Köhler, Mantrala et al. 2017 – A Meta-Analysis of Marketing Communication %R 10.1509/jmr.13.0580 %X To optimally set marketing communication (“marcom”) budgets, reliable estimates of short-term elasticities and carryover effects are required. Empirical generalizations from meta-analyses of prior field studies can help guide these decisions. However, the last such meta-analysis of marcom carryover effects was performed on Koyck model–based estimates collected before 1984 and was confined to mass media advertising. The authors update and extend extant empirical generalizations via two meta-analyses of carryover estimates compiled from studies encompassing personal selling, targeted advertising, and mass media advertising, using diverse model forms, until 2015. The first is focused on and utilizes 918 estimates of the carryover proportion of the total effect, termed long-term share of the total effect, and the second focuses on 863 derivable estimates of 90% implied duration intervals. The authors find the mean long-term shares of the total effect for personal selling (.687) and targeted advertising (.650) are distinctly larger than that for mass media advertising (.523) and the corresponding median 90% implied duration intervals are 12.6, 2, and 3.4 months, respectively. The authors conclude by discussing differences by model type and the implications for marcom budget-setting and analyses.