IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v140y2019icp315-327.html
   My bibliography  Save this article

Marketing innovations to old-age consumers: A dynamic Bass model for different life stages

Author

Listed:
  • Pannhorst, Matthias
  • Dost, Florian

Abstract

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.

Suggested Citation

  • Pannhorst, Matthias & Dost, Florian, 2019. "Marketing innovations to old-age consumers: A dynamic Bass model for different life stages," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 315-327.
  • Handle: RePEc:eee:tefoso:v:140:y:2019:i:c:p:315-327
    DOI: 10.1016/j.techfore.2018.12.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162517308922
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2018.12.022?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Patti Williams & Aimee Drolet, 2005. "Age-Related Differences in Responses to Emotional Advertisements," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(3), pages 343-354, December.
    2. Wagner, Janet & Hanna, Sherman, 1983. "The Effectiveness of Family Life Cycle Variables in Consumer Expenditure Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 10(3), pages 281-291, December.
    3. Dale Dannefer, 2003. "Cumulative Advantage/Disadvantage and the Life Course: Cross-Fertilizing Age and Social Science Theory," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 58(6), pages 327-337.
    4. Gilly, Mary C & Zeithaml, Valarie A, 1985. "The Elderly Consumer and Adoption of Technologies," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 12(3), pages 353-347, December.
    5. Vijay Mahajan & Eitan Muller & Frank M. Bass, 1995. "Diffusion of New Products: Empirical Generalizations and Managerial Uses," Marketing Science, INFORMS, vol. 14(3_supplem), pages 79-88.
    6. Tepper, Kelly, 1994. "The Role of Labeling Processes in Elderly Consumers' Responses to Age Segmentation Cues," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(4), pages 503-519, March.
    7. Schaninger, Charles M & Danko, William D, 1993. "A Conceptual and Empirical Comparison of Alternative Household Life Cycle Models," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 19(4), pages 580-594, March.
    8. Kristi Williams, 2004. "The Transition to Widowhood and the Social Regulation of Health: Consequences for Health and Health Risk Behavior," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 59(6), pages 343-349.
    9. Dana Kotter-Grühn & Thomas M. Hess, 2012. "The Impact of Age Stereotypes on Self-perceptions of Aging Across the Adult Lifespan," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 67(5), pages 563-571.
    10. Duane F. Alwin, 2012. "Integrating Varieties of Life Course Concepts," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 67(2), pages 206-220.
    11. Aimee Drolet & Patti Williams & Loraine Lau-Gesk, 2007. "Age-related differences in responses to affective vs. rational ads for hedonic vs. utilitarian products," Marketing Letters, Springer, vol. 18(4), pages 211-221, December.
    12. Vijay Mahajan & Robert A. Peterson, 1978. "Innovation Diffusion in a Dynamic Potential Adopter Population," Management Science, INFORMS, vol. 24(15), pages 1589-1597, November.
    13. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    14. Velickovic, Stevan & Radojicic, Valentina & Bakmaz, Bojan, 2016. "The effect of service rollout on demand forecasting: The application of modified Bass model to the step growing markets," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 130-140.
    15. John Mirowsky & John R. Reynolds, 2000. "Age, Depression, and Attrition in the National Survey of Families and Households," Sociological Methods & Research, , vol. 28(4), pages 476-504, May.
    16. Wilkes, Robert E, 1995. "Household Life-Cycle Stages, Transitions, and Product Expenditures," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 22(1), pages 27-42, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lang Liang, 2021. "Novel Optimization-Based Parameter Estimation Method for the Bass Diffusion Model," SAGE Open, , vol. 11(2), pages 21582440211, June.
    2. Zhang, Tianyu & Dong, Peiwu & Zeng, Yongchao & Ju, Yanbing, 2022. "Analyzing the diffusion of competitive smart wearable devices: An agent-based multi-dimensional relative agreement model," Journal of Business Research, Elsevier, vol. 139(C), pages 90-105.
    3. Matthias Pannhorst & Florian Dost, 2022. "A Life-Course View on Ageing Consumers: Old-Age Trajectories and Gender Differences," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 17(2), pages 1157-1180, April.
    4. Pandyaswargo, Andante Hadi & Siregar, Tifani Husna & Onoda, Hiroshi, 2023. "Exploring Japan’s older adults mobility challenges and the potential role of autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    5. Zhukov, Dmitry & Khvatova, Tatiana & Millar, Carla & Zaltcman, Anastasia, 2020. "Modelling the stochastic dynamics of transitions between states in social systems incorporating self-organization and memory," Technological Forecasting and Social Change, Elsevier, vol. 158(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matthias Pannhorst & Florian Dost, 2022. "A Life-Course View on Ageing Consumers: Old-Age Trajectories and Gender Differences," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 17(2), pages 1157-1180, April.
    2. Kuppelwieser, Volker G., 2016. "Towards the use of chronological age in research – A cautionary comment," Journal of Retailing and Consumer Services, Elsevier, vol. 33(C), pages 17-22.
    3. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    4. Martin Hewing, 2012. "A Theoretical and Empirical Comparison of Innovation Diffusion Models Applying Data from the Software Industry," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 3(2), pages 125-141, June.
    5. Robert Zniva & Wolfgang Weitzl, 2016. "It’s not how old you are but how you are old: A review on aging and consumer behavior," Management Review Quarterly, Springer, vol. 66(4), pages 267-297, December.
    6. John Hauser & Gerard J. Tellis & Abbie Griffin, 2006. "Research on Innovation: A Review and Agenda for," Marketing Science, INFORMS, vol. 25(6), pages 687-717, 11-12.
    7. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    8. Qin, Ruwen & Nembhard, David A., 2012. "Demand modeling of stochastic product diffusion over the life cycle," International Journal of Production Economics, Elsevier, vol. 137(2), pages 201-210.
    9. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    10. Kim, Namwoon & Srivastava, Rajendra K., 2007. "Modeling cross-price effects on inter-category dynamics: The case of three computing platforms," Omega, Elsevier, vol. 35(3), pages 290-301, June.
    11. Kivi, Antero & Smura, Timo & Töyli, Juuso, 2012. "Technology product evolution and the diffusion of new product features," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 107-126.
    12. Jing Jian Xiao & Rui Yao, 2011. "Consumer Debt Delinquency over Life Cycle Stages," NFI Working Papers 2011-WP-18, Indiana State University, Scott College of Business, Networks Financial Institute.
    13. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    14. Wagner A. Kamakura & Siva K. Balasubramanian, 1987. "Long‐term forecasting with innovation diffusion models: The impact of replacement purchases," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 6(1), pages 1-19.
    15. Guseo, Renato & Schuster, Reinhard, 2021. "Modelling dynamic market potential: Identifying hidden automata networks in the diffusion of pharmaceutical drugs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    16. Rixen, Martin & Weigand, Jürgen, 2014. "Agent-based simulation of policy induced diffusion of smart meters," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 153-167.
    17. Pablo Marshall, 2000. "Difusion De Internet En Chile," Abante, Escuela de Administracion. Pontificia Universidad Católica de Chile., vol. 3(2), pages 143-163.
    18. Carroll, Brídín & Walsh, Kieran & Scharf, Thomas & O'Donovan, Diarmuid & Keogh, Sinéad, 2023. "Positive health and ageing policies for older Irish travellers and older people who have experienced homelessness in Ireland: Life-course meanings and determinants," Social Science & Medicine, Elsevier, vol. 336(C).
    19. Francesco Bogliacino & Giorgio Rampa, 2012. "Quality risk aversion, conjectures, and new product diffusion," Journal of Evolutionary Economics, Springer, vol. 22(5), pages 1081-1115, November.
    20. Wei-yu Kevin Chiang, 2012. "Supply Chain Dynamics and Channel Efficiency in Durable Product Pricing and Distribution," Manufacturing & Service Operations Management, INFORMS, vol. 14(2), pages 327-343, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:140:y:2019:i:c:p:315-327. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.