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«Decision making and brand choice by older consumers Catherine Cole & Gilles Laurent & Aimee Drolet & Jane Ebert & Angela Gutchess & Raphaëlle ...»

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Market Lett (2008) 19:355–365

DOI 10.1007/s11002-008-9058-x

Decision making and brand choice by older consumers

Catherine Cole & Gilles Laurent & Aimee Drolet &

Jane Ebert & Angela Gutchess &

Raphaëlle Lambert-Pandraud & Etienne Mullet &

Michael I. Norton & Ellen Peters

Published online: 13 September 2008

# Springer Science + Business Media, LLC 2008


Older adults constitute a rapidly growing demographic segment, but

stereotypes persist about their consumer behavior. The goal of this review was to develop a more considered understanding of age-associated changes in consumer decision making. Our theoretical model suggests that age-associated changes in cognition, affect, and goals interact to make older consumers’ decision-making processes, brand choices, and habits different from those of younger adults. We first review literature on stereotypes about the elderly and then turn to an analysis of age C. Cole (*) Department of Marketing (Henry B. Tippie College of Business), University of Iowa, Iowa City, IA, USA e-mail: cathy-cole@uiowa.edu G. Laurent Department of Marketing, HEC Paris, Paris, France A. Drolet Department of Marketing, University of California, Los Angeles (UCLA), Los Angeles, CA, USA J. Ebert Department of Marketing, University of Minnesota, Minneapolis, MN, USA A. Gutchess Department of Psychology, Brandeis University, Waltham, MA, USA R. Lambert-Pandraud Department of Marketing, ESCP-EAP Paris, Paris, France E. Mullet Ecole Pratique des Hautes Etudes, Paris, France M. I. Norton Department of Marketing, Harvard Business School, Boston, MA, USA E. Peters Decision Research, University of Oregon, Eugene, OR, USA 356 Market Lett (2008) 19:355–365 differences in the inputs (cognition, affect, and goals) and the outcomes (decisions, brand choices, and habits) of decision processes.

Keywords Older consumers. Decision making. Choice Older consumers represent an increasingly large and financially powerful part of the population worldwide. We propose that age-associated changes in cognition, affect, and goals intermingle to influence older consumers’ decision-making processes, making these processes different from those of younger adults. Thus, the goal of this review was to come to a more considered understanding of age differences in the inputs (cognition, affect, and goals) and the outcomes (decisions, brand choices, and habits) of these processes. For example, the extant literature on consumer decision making focuses largely on the ways in which one input (e.g., memory) affects one outcome (e.g., brand choice). We broaden this literature by highlighting the impact of age-related changes in cognition, affect, and goals on decisions, brand choices, and habits.

1 Stereotypes Across cultures, people tend to possess stereotypical views of the elderly, with conventional wisdom holding that they are kindly, warm, and friendly, yet at the same time incompetent, ineffective, and helpless (Cuddy et al. 2005). While there is substantial overlap in abilities, preferences, and goals between older and younger consumers, there are also substantial differences. For example, the elderly are consistently more brand-loyal than younger consumers (Lambert-Pandraud et al.

2005). However, rather than view this trend as confirming a general stereotype of a decline in older consumers’ ability to process information about new brands, marketers might think more carefully about other underlying reasons for such changes in behavior, such as self-directed changes in motivations (Carstensen et al.

2003). Unfortunately, research tends to show that it is difficult to change these stereotypical views of the elderly (Cuddy et al. 2005). Thus, this article integrates recent literature from both marketing and psychology to understand which age differences in decision making are based in reality—such as increased brand loyalty—and which are the products of often erroneous conventional wisdom about the decreased abilities of older consumers.

2 Inputs: goals, affect, and cognition

2.1 Goals and affect Important motivational changes occur with aging. Carstensen et al. (2003) have proposed the socio-emotional selectivity theory, which argues that when people perceive remaining time as limited, they prioritize social goals that are emotionally meaningful over those that are more knowledge-related. The theory has also been Market Lett (2008) 19:355–365 357 applied to explain motivational changes of aging inside and outside of the social realm. Specifically, researchers have found that older consumers are more persuaded by messages that help adults to realize emotionally meaningful goals as opposed to those that serve knowledge-related goals (Fung and Carstensen 2003). They are also more persuaded by messages that are based on emotional appeals than by those based on rational appeals (Williams and Drolet 2005).

Theories about successful aging, including the selective optimization with compensation theory, Heckhausen and Schulz’s lifespan theory of control, and Brandtstädter and Renner’s coping strategies of accommodation and assimilation,

make additional predictions about goal change with age due to loss of resources:

predicting increased goal selectivity when people move away from developmental goals of growth (e.g., “I want to improve my health”) towards goals of maintenance (e.g., “I want to stay healthy”) and regulation of loss (e.g., “I do not want my health to deteriorate”; Ebner et al. 2006). Consistent with this, research has found that compared with younger and middle-aged adults, older adults’ goals more often reflect loss avoidance and a maintenance orientation (e.g., Heckhausen 1997). These theories and findings suggest a clear but as yet unexplored connection with regulatory focus theory (Avnet and Higgins 2006), a theory that has been wellexplored and widely applied in consumer behavior.

According to regulatory focus theory, having a promotion focus involves pursuing gains and ideals, whereas having a prevention focus involves avoiding losses and aiming to fulfill obligations. The dominant focus for individuals can vary, either chronically (people may have a higher promotion or prevention focus in general, or they may be high or low on both promotion and prevention focuses) or situationally (a context can temporarily encourage a particular focus). Researchers have demonstrated a wide range of effects of regulatory focus on product preference and communications (e.g., Avnet and Higgins 2006).

Given changes in goal selectivity with aging, we would expect that older consumers would be more prevention-focused and less promotion-focused compared to younger consumers, especially in domains in which older consumers expect or experience losses, such as some cognitive abilities, health, or fitness.

Furthermore, other variables that change with age may reinforce a relative increase in prevention focus with age. In particular, recent findings suggest that a limited time perspective may increase the relative importance of prevention over promotion goals (Pennington and Roese 2003) and that the cognitive processes associated with a promotion focus versus those associated with a prevention focus are likely to require more cognitive resources. Older consumers tend to have both a more limited time perspective and more limited cognitive resources than younger consumers, potentially reinforcing any tendency they might have to show increased prevention focus relative to younger consumers.

2.2 Cognition: The case of functional learning

Rather than review all existing literature about changes in cognition (see Yoon and Cole 2008), we emphasize several new findings pertaining to age-associated changes in functional learning, that is, learning of continuous functional mappings that relate stimulus and response continua. Through functional learning, an organism acquires a 358 Market Lett (2008) 19:355–365 judgment rule for correctly assigning each stimulus value encountered in a certain domain to one, and only one, response value. For example, “The better the product, the higher its price,” is a functional decision rule. The ability to detect and learn such continuous relations has strong adaptive value throughout a person’s life.

A few studies in aging literature report that when presented with one stimulus value (e.g., quality) and given feedback about the value to be predicted from it (e.g., price), elderly and younger adults are equally able to learn (and apply) the most common functional relations encountered in their daily lives, whether direct, inverse, U-shaped, or inverse U-shaped (Musielak et al. 2006). Without any feedback, older adults use direct relations as the default option. Other functional learning results indicate that when data contain a considerable amount of uncertainty, the elderly are able to learn, interpolate, and extrapolate as well as younger persons (Musielak et al.


However, when they are presented with more than one stimulus value and given feedback about the value to be predicted (e.g., health status), such that one relation is positive (e.g., dosage) and the other is inverse (e.g., side effects), older adults have difficulty learning the inverse relationship. They can detect which relation is a direct one and apply it, but they encounter difficulties learning how to combine the two stimuli into an overall prediction. Many older adults tend not to use the inverse relation stimulus. Yet when both relations are inverse, some elderly persons appear able to detect and learn the two inverse relationships and combine the stimulus values correctly. Finally, when presented with two direct relationship stimuli embedded within a set of invalid non-diagnostic stimuli, older adults have more trouble than younger adults detecting which stimuli are valid (Chasseigne and Mullet 2007).

Combining two stimuli with opposite meanings also creates a very challenging task for older adults in non-learning situations. For example, when judging the volume of an object from information about its weight and its density, many elderly people cannot use density information inversely. Instead, they judge volume as a direct function of weight and density (Léoni et al. 2002). Nevertheless, in settings in which the inverse information can be reframed easily as direct information, the elderly are able to use the inverse information as well as young adults.

Because a cognitive theory of functional relationships in everyday life is not yet available, it is difficult to know the extent to which differences in functional learning are consequential. If we assume that in everyday life direct relations between events are the rule and inverse or nonlinear relations are the exception, then the concrete consequences of the trouble experienced by older adults when they face combinations of inverse and direct relations should be limited, and even more so if many inverse relations can be reframed as direct relations.

2.3 Corroborating evidence from neuroimaging data

Neuroimaging data reveal that brain activity does not always mirror observed ageassociated changes in cognition, affect, and goals (Park and Gutchess 2004). For some tasks, young adults activate regions of the brain more robustly than older adults; for other tasks, older adults recruit regions of the brain that are not engaged by young adults. For example, on some memory tasks, elderly adults increase the activity in prefrontal regions in both hemispheres, but young adults activate only one Market Lett (2008) 19:355–365 359 hemisphere (as reviewed by Cabeza 2002). On other occasions, older adults fail to activate medial temporal regions to the same extent as the young do (Gutchess et al.

2005). These changing patterns of neural activation with age may serve compensatory functions (e.g., Cabeza 2002); at the very least, the patterns suggest flexibility in the engagement of cognitive and neural resources with age that is not apparent in behavioral data.

Recent behavioral work has begun to identify circumstances in which older adults’ cognitive performance reflects preservation and malleability. These findings converge with the neural evidence to suggest that cognitive limitations with age are not absolutes. Both socio-emotional information relevant to one’s well-being and meaningful financial information can motivate older adults to deploy cognitive resources flexibly and perform equivalently to younger adults (Castel 2005). This research is important because it suggests that memory and resource limitations with age can be improved depending on the goals and motivations of the individual.

One interesting question regarding older consumers concerns the extent to which brands—and, more generally, classes of objects—represent unique domains. In young adults, objects and persons represent distinct domains, with the medial prefrontal cortex engaged by person information and the left inferior frontal cortex engaged by object information. As far as brands, functional magnetic resonance imaging (fMRI) research on young adults shows that brands and people do not engage the same neural regions and that the activations for brands occur in the same region that has been identified for objects (Yoon et al. 2006). In addition, data show that person judgments evoke a stronger response in reward regions than do brands.

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