The future of marketing: old age or second adolescence?

1996 ◽  
Vol 2 (4) ◽  
pp. 7-10 ◽  
Author(s):  
John Brady
2005 ◽  
Vol 45 (4) ◽  
pp. 553-564
Author(s):  
Stephen Crystal
Keyword(s):  
Old Age ◽  

Author(s):  
Koen H. Pauwels ◽  
Peter S. H. Leeflang ◽  
Tammo H. A. Bijmolt ◽  
Jaap E. Wieringa

2004 ◽  
pp. 237-262
Author(s):  
Richard Brookes ◽  
Roger Palmer

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S976-S976
Author(s):  
Amber Xuqian Chen ◽  
Helene H Fung

Abstract We aimed to further investigate the linguistic-savings hypothesis (Chen, 2013) in the field of aging, which maintains that when languages grammatically divide the future and the present (e.g. English and Czech), speakers tend to behave less future-oriented than those speaking languages that do not mark future tense (e.g. German and Chinese). In the 2018 wave of Aging as Future Project, 2,042 participants from the United States, Germany, Czech Republic, Hong Kong and Taiwan (18-93 year, Mean age= 55.47, 55.61% female) completed online questionnaires. The results supported the hypothesis that people speaking future-less languages tended to perceive the timing of preparation for old age closer to the present in terms of finance, living arrangement, nursing care, and loneliness, they also took action earlier and performed more relevant activities. Furthermore, the association between language and preparation timing was more salient in older adults than younger counterparts. And path analysis revealed that time discounting was a significant predictor (P=0.049) for the future-oriented behavior. Hence, speakers of futureless languages will view the future as temporally closer to the present, causing them to discount the future less and prepare for old age actively. Using LIWC 2017, we then analyzed community-level of future orientation with 80 million Tweets across countries and replicated our principal result through that usage of future-oriented languages partly predicted prevalence of health behaviors. The findings indicate that language not only shape people's own future-oriented outcomes, through decreasing time discounting, but also influence population health as a whole.


2019 ◽  
Vol 48 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Thomas Davenport ◽  
Abhijit Guha ◽  
Dhruv Grewal ◽  
Timna Bressgott

Abstract In the future, artificial intelligence (AI) is likely to substantially change both marketing strategies and customer behaviors. Building from not only extant research but also extensive interactions with practice, the authors propose a multidimensional framework for understanding the impact of AI involving intelligence levels, task types, and whether AI is embedded in a robot. Prior research typically addresses a subset of these dimensions; this paper integrates all three into a single framework. Next, the authors propose a research agenda that addresses not only how marketing strategies and customer behaviors will change in the future, but also highlights important policy questions relating to privacy, bias and ethics. Finally, the authors suggest AI will be more effective if it augments (rather than replaces) human managers.


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