TY - JOUR

T1 - Marketing innovations to old-age consumers

T2 - A dynamic Bass model for different life stages

AU - Pannhorst, M.

AU - Dost, Florian

PY - 2019/3/1

Y1 - 2019/3/1

N2 - To identify context-dependent opportunities to market innovations to the elderly, this study empirically analyzes the most prevalent pathways through advanced age, demonstrating which circumstances in the old-age life course provide the strongest potential for specific targeting strategies. First, using a latent Markov model and longitudinal survey data spanning 15 years, we produce a dynamic life course model with transitions over time. Second, we link a modified Bass diffusion model using both static and dynamic parameters to our model, augmenting it with a second cross-sectional consumer behavior data set. The results show comparatively strong consumption spending, high media interaction, but diminishing social inclusion in old age, though all factors exhibit heterogeneity among old-age clusters. Employing dynamic diffusion models, we find that a static view of the elderly market that ignores life course transitions generally overestimates their spending power. Forecasts of cluster-specific adoption dynamics draw a differentiated picture of individual clusters' attractiveness. Our analysis underscores the influence of life events on individual behavior and shows that a dynamic view of elderly markets yields a more nuanced and accurate assessment of their potential and attractiveness. It also confirms that social status and income strongly affect consumer behavior and spending, though we identify several exceptions.

AB - To identify context-dependent opportunities to market innovations to the elderly, this study empirically analyzes the most prevalent pathways through advanced age, demonstrating which circumstances in the old-age life course provide the strongest potential for specific targeting strategies. First, using a latent Markov model and longitudinal survey data spanning 15 years, we produce a dynamic life course model with transitions over time. Second, we link a modified Bass diffusion model using both static and dynamic parameters to our model, augmenting it with a second cross-sectional consumer behavior data set. The results show comparatively strong consumption spending, high media interaction, but diminishing social inclusion in old age, though all factors exhibit heterogeneity among old-age clusters. Employing dynamic diffusion models, we find that a static view of the elderly market that ignores life course transitions generally overestimates their spending power. Forecasts of cluster-specific adoption dynamics draw a differentiated picture of individual clusters' attractiveness. Our analysis underscores the influence of life events on individual behavior and shows that a dynamic view of elderly markets yields a more nuanced and accurate assessment of their potential and attractiveness. It also confirms that social status and income strongly affect consumer behavior and spending, though we identify several exceptions.

KW - Aging

KW - Consumer lifetime value

KW - Diffusion model

KW - Innovation

KW - Longitudinal model

KW - Targeting

KW - Aging of materials

KW - Commerce

KW - Diffusion

KW - Markov processes

KW - Bass Diffusion Model

KW - Individual behavior

KW - Lifetime values

KW - Longitudinal models

KW - Longitudinal surveys

KW - Marketing innovations

KW - Consumer behavior

U2 - 10.1016/j.techfore.2018.12.022

DO - 10.1016/j.techfore.2018.12.022

M3 - Journal article

VL - 140

SP - 315

EP - 327

JO - Technological Forecasting and Social Change

JF - Technological Forecasting and Social Change

SN - 0040-1625

ER -