Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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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 -