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Interventions to change everyday behaviors often attempt to change people’s beliefs and intentions. As the authors explain, these interventions are unlikely to be an effective means to change behaviors that people have repeated into habits. Successful habit change interventions involve disrupting the environmental factors that automatically cue habit performance. The authors propose two potential habit change interventions. “Downstream-plus” interventions provide informational input at points when habits are vulnerable to change, such as when people are undergoing naturally occurring changes in performance environments for many everyday actions (e.g., moving households, changing jobs). “Upstream” interventions occur before habit performance and disrupt old environmental cues and establish new ones. Policy interventions can be oriented not only to the change of established habits but also to the acquisition and maintenance of new behaviors through the formation of new habits.
Vol. 25 (1) Spring 2006, 90–103
© 2006, American Marketing Association
ISSN: 0743-9156 (print), 1547-7207 (electronic) 90
Interventions to Break and Create Consumer
Bas Verplanken and Wendy Wood
Interventions to change everyday behaviors often attempt to change people’s beliefs and intentions. As
the authors explain, these interventions are unlikely to be an effective means to change behaviors that
people have repeated into habits. Successful habit change interventions involve disrupting the
environmental factors that automatically cue habit performance. The authors propose two potential
habit change interventions. “Downstream-plus” interventions provide informational input at points
when habits are vulnerable to change, such as when people are undergoing naturally occurring
changes in performance environments for many everyday actions (e.g., moving households, changing
jobs). “Upstream” interventions occur before habit performance and disrupt old environmental cues
and establish new ones. Policy interventions can be oriented not only to the change of established
habits but also to the acquisition and maintenance of new behaviors through the formation of new
Bas Verplanken
is Professor of Social Psychology, Department of Psy-
chology, University of Tromsø (e-mail:
Wendy Wood
is James B. Duke Professor of Psychology, Professor of
Marketing, and Codirector of the Social Science Research Institute,
Department of Psychology, Duke University (e-mail: Wendy.Wood@ (After September 2006, Bas Verplanken will be at Depart-
ment of Psychology, University of Bath [e-mail: B.Verplanken@bath.].) Preparation of this article was supported by National Insti-
tute of Mental Health Award 1R01MH619000-01 to Wendy Wood.
The authors thank Joel Cohen, Alan Lind, John Lynch, Jeffrey Quinn,
and Daniel Rodriguez for their thoughtful comments on a previous
version of the article.
What a person eats for dinner has little impact on his
or her overall health, and whether a person drives to
work on a particular morning contributes only min-
imally to traffic congestion and air pollution. However,
these kinds of small actions and decisions that consumers
make in daily life have an impact beyond any single
As everyday behaviors are repeated, they exert signifi-
cant, cumulative impact on medical, social, and economic
outcomes experienced by both individual consumers and
society as a whole. For example, it has been estimated that
weight gain and obesity in the majority of the population
could be addressed if people ate a few less bites at each meal
or took approximately 2000 extra steps each day (Hill and
Wyatt 2003). In addition, highway traffic congestion can
emerge from a few drivers’ nonessential trips. Even a single
car that proceeds at varying speeds within a stream of traf-
fic can send waves of congestion propagating down the line
behind it (Nagatani 2000).
In this article, we explain the implications of consumers’
repeated behavior for policy interventions focused on
behavior change. In particular, we focus on two consumer
issues, health policies designed to reduce obesity and trans-
portation policies designed to ensure smart use of the auto-
mobile. Policy interventions to change behavior will be
most successful when they are designed with consumers’
habits in mind. As we explain, a variety of interventions are
likely to be effective at changing nonhabitual behaviors,
including informational campaigns and self-help strategies.
However, actions that have been repeated in stable contexts
are most likely to be changed through interventions that dis-
rupt the environmental cues that trigger habit performance
automatically. We ground these recommendations in a
review of the psychological literature on habits.
Behavior Change Interventions
Policy interventions to promote a healthful diet, increase
physical activity, and manage transportation often take the
form of information campaigns. Information is provided to
the public through public media campaigns, private sector
advertising, some types of individual counseling, and edu-
cational programs. For example, the U.S. government’s
guidelines for daily food intake have been reworked into
various pyramid shapes in recent years in an effort to con-
vey effectively the sizes and numbers of daily servings for
various foods. Information campaigns exhort people to eat
five fruits and vegetables daily and to drink milk. With
respect to transportation, daily ozone reports in major cities
advise people when to stay indoors and limit nonessential
driving. Local transportation authorities in towns and cities
advertise their bus routes and train schedules to encourage
public use.
Information campaigns that successfully convey informa-
tion do not necessarily change consumers’ behaviors. The
disconnection between changing minds and changing
behavior has been noted in several different literature
streams. Derzon and Lipsey (2002) conducted a meta-
analytic synthesis of 110 reports of the effectiveness of
Journal of Public Policy & Marketing 91
media interventions to curb substance abuse. For the dura-
tion of the campaigns, on average, viewers’ levels of abuse
actually increased, even though their attitudes toward abuse
became more negative. In addition, Albarracin and col-
leagues’ (2005) synthesis of various health interventions to
increase condom use found no significant increase in use
from persuasive messages alone. Similarly, Lodish and col-
leagues’ (1995) synthesis of more than 350 real-world
experiments on the effects of television advertising revealed
that increases in the amount of advertising did not yield any
simple increase in product sales. Even commercials that
were effective (as assessed by consumers’ successful recall
and reports of persuasion) did not strongly correspond to
consumer purchases as reflected in sales impact.
Informational campaigns and self-help programs repre-
sent only one possible approach to behavior change. The
various points at which interventions can be applied are
illustrated in an anecdote that John McKinlay (1975, p. 7)
shared more than 30 years ago at an American Heart Asso-
ciation conference. In this anecdote, a physician made the
following lament:
“You know,” he said, “sometimes it feels like this. There I am
standing by the shore of a swiftly flowing river, and I hear the
cry of a drowning man. So I jump into the river, put my arms
around him, pull him to shore and apply artificial respiration.
Just when he begins to breathe, there is another cry for help. So
I jump into the river, reach him, pull him to shore, apply artifi-
cial respiration, and then just as he begins to breathe, another cry
for help. So back in the river again, reaching, pulling, applying,
breathing and then another yell. Again and again, without end,
goes the sequence. You know, I am so busy jumping in, pulling
them to shore, applying artificial respiration, that I have no time
to see who the hell is upstream pushing them all in.”
Informational campaigns and self-help programs offer a
kind of “downstream,” individual-level intervention
designed to change the behavior of people who already suf-
fer from a given risk factor (e.g., sedentary lifestyle,
unhealthful diet). These interventions attempt to solve
health and traffic congestion problems through the decision
making of individual consumers.
In this article, we explain that consumers’ everyday
lifestyle habits limit the effectiveness of downstream inter-
ventions that do not address the performance contexts and
social structural factors that maintain habits. Habits are a
form of automaticity in responding that develops as people
repeat actions in stable circumstances (Pascoe and Wood, in
press; Verplanken 2006; Verplanken and Aarts 1999).
When initially performing an action, people typically decide
what to do and how to do it to achieve certain outcomes and
avoid others. As people repeat actions, their decision mak-
ing recedes, and the actions come to be cued by the envi-
ronment. Specifically, habit formation involves the creation
of associations in memory between actions and stable fea-
tures of the circumstances in which they are performed.
Recurring aspects of performance circumstances come to
trigger habitual responses directly without input from
people’s intentions or decisions to act (Ji Song and Wood
2006; Ouellette and Wood 1998; Verplanken et al. 1998).
Habits might be triggered by prior responses in a chain of
responses; by environmental cues, such as time of day or
location; by internal states, such as particular moods; and by
the presence of typical interaction partners (Ji Song and
Wood 2006; Ouellette and Wood 1998; Wood, Tam, and
Guerrero Witt 2005).
As we explain, because habits are linked to recurring per-
formance environments, they are not easily changed with
only downstream, informational interventions. However,
the dependence of habits on environmental cues represents
an important point of vulnerability. Disrupting the environ-
mental cues that trigger and maintain habit performance ren-
ders habits open to change (Wood, Tam, and Guerrero Witt
2005). Thus, for interventions targeted at changing con-
sumers’ habits, downstream approaches will be most suc-
cessful when they are paired with environmental changes
that disrupt existing habits. Specifically, informational cam-
paigns to change habits gain power when they are applied
during naturally occurring periods of change in consumers’
lives (e.g., moving to a new location, changing jobs). We
call these “downstream-plus-context-change” interventions
to indicate that not only do they provide new information,
but they do so when consumers are undergoing natural shifts
in the performance environment.
As an alternative to focusing downstream, McKinlay
(1975, 1993) proposes “upstream” policy and environmen-
tal interventions that do not treat problems after they occur
but rather are designed to prevent undesired outcomes and
maintain optimal lifestyles (see also Butterfield 1990; Jef-
fery 1989; Milio 1976; Orleans 2000; Smith, Orleans, and
Jenkins 2004). Upstream interventions target social norms
and contextual supports for desired actions and include pro-
grams such as establishing standard portion sizes for pack-
aged foods, improving the availability and efficiency of bus
networks, and providing opportunities for telecommuting
from home instead of driving to an office. To the extent that
interventions aimed upstream of a behavior alter critical fea-
tures of the performance environment, they are likely to be
successful at disrupting unwanted habits. Furthermore, new
performance environments can provide a stable context to
foster the creation of more desirable habits and the mainte-
nance of those habits over the long run. Thus, whereas
downstream interventions aim to alleviate existing negative
outcomes, upstream interventions aim to prevent such out-
comes in the first place.
Habits Resist Informational Interventions
To explain why downstream-plus-context-change and
upstream interventions effectively change habits, we first
consider why habits are resistant to downstream, informa-
tional interventions. In part, this resistance arises because
habit formation is associated with the development of
expectations about behavior and the performance environ-
ment. Repetition-based expectations reduce sensitivity to
minor variations in the performance setting, curtail informa-
tion search (especially search for information that chal-
lenges practiced ways of responding), and reduce thought
and deliberation about the action.
The expectations that develop with habit formation can
serve as a filter that renders people insensitive to minor
changes in performance contexts. With such expectations,
for example, consumers who are in the habit of eating a pint
of ice cream for dessert may fail to notice when the product
manufacturers add a label to the carton that indicates that a
92 Breaking and Creating Habits
pint is four servings. In a similar manner, consumers with
stronger driving habits use public transportation less often to
commute to work, even when the highway they use rou-
tinely for commuting is closed (Fujii, Gärling, and Kitamura
2001). In an experimental demonstration of the insensitivity
that arises with automatic responding, Fazio, Ledbetter, and
Towles-Schwen (2000) exposed participants repeatedly to
photographs of faces to create well-practiced reactions (i.e.,
accessible attitudes) toward them. Participants were subse-
quently shown some of the faces again but in a slightly
changed, “morphed” form. Participants who had seen the
faces repeatedly in the first part of the study had greater dif-
ficulty detecting the changes and apparently relied on their
expectations formed during the prior exposures. These find-
ings suggest that people with strong habits hold expectations
about the environment that reduce their capacity to detect
when it changes. In holding such expectations, consumers
may overlook new information that arises about the prac-
ticed action and its alternatives. They may fail to avail them-
selves of new and better alternatives simply because their
expectations reduce awareness of such information.
Expectations established with response repetition also
limit how much information consumers consider before they
act. To investigate information search, Verplanken, Aarts,
and Van Knippenberg (1997) asked a group of European car
owners to choose a travel mode for each of 27 hypothetical
travel situations. Each travel choice involved various fea-
tures (e.g., distance, weather conditions) that participants
could learn about by explicitly selecting information. Some
participants had strong habits to drive a car, and others had
weak habits. An important result was that car drivers with
stronger habits selected significantly less information. They
required less information about the travel situations to make
decisions to drive. Furthermore, the reduced information
search characterized not only automobile habits but also
habits for other transportation options. Thus, participants
with strong habits to ride a bike also were found to search
less for information about alternative travel options before
making travel choices.
Another feature of habit-based expectations is a confir-
matory information search strategy. As habits develop,
people form expectancies for certain outcomes and are espe-
cially receptive to these outcomes when they occur in the
future. As evidence of this confirmatory bias, Betsch and
colleagues (2001) report that when a decision context was
framed as being similar to previous ones, participants with
strong habits searched information that supported the habit-
ual choice and avoided information that might challenge it.
Similarly, Verplanken, Aarts, and Van Knippenberg (1997)
find that participants with strong habits acquired propor-
tionally the most information about the habitual travel mode
option itself compared with information about alternative
travel mode options, whereas this tendency was less evident
for those with weaker habits. Thus, in addition to limiting
the amount of information people seek out, strong habits are
associated with a search for information that is congenial
and supports continued habit performance.
Finally, the expectations established with strong habits
appear to decrease the complexity of consumers’ decision
making about action. Demonstrating this shallow process-
ing, Aarts, Verplanken, and Van Knippenberg (1997) pre-
sented participants with a large number of travel mode sit-
uations that varied on four dimensions (e.g., distance) and
asked them to indicate for each situation whether they
would ride a bike. Participants with a strong bike habit used
simpler (i.e., noncompensatory) decision rules than did
those with a weak bike habit. In addition, Betsch, Fiedler,
and Brinkmann (1998) find that time pressure increased the
likelihood of following established routines and using sim-
pler decision strategies. Thus, research also suggests that a
habitual mind-set is characterized by shallow, abbreviated
decision making about action.
In summary, consumers with strong habits develop
expectations for certain environmental and behavioral
events. These expectations lead to a kind of tunnel vision
that is evident in the following: People with strong habits
expect prior experiences to repeat, and as a result, they do
not easily detect minor changes in the performance environ-
ment. They also search less extensively for information
about behavioral alternatives and for information about the
performance context itself. In addition, their search tends to
be biased toward confirming the habitual option. Finally,
strong habits are associated with simple, shallow decision
rules. Essentially, people with strong habits possess motiva-
tional and informational biases that reduce the likelihood
that they will receive and evaluate favorably new, counter-
habitual information. These biases reduce the impact of
informational campaigns and help maintain existing behav-
ior patterns.
Environmental Control Perpetuates Habits
The expectations we have described are likely to dampen
the effects of new information, but they do not render people
impervious to it. As we noted in the beginning of this arti-
cle, media campaigns and product advertisements often are
effective in changing consumers’ attitudes and judgments.
This change is evident in the shifts in public opinion about
health and transportation over time as new information has
become available about diet, exercise, and transportation
options. For example, downstream interventions to exercise
and eat a healthful diet have convinced many people that
they would benefit from a healthier lifestyle. However,
these kinds of interventions have yielded disappointing
results with respect to long-term behavior change. In a
review of weight-loss interventions, Jeffery and colleagues
(2000, p. 8) note the “substantial weight regain that usually
follows successful weight loss with behavioral treatments.”
Why are people’s attempts to change unwanted health habits
not more effective?
One explanation for this failure to change behavior is that
many aspects of unwanted lifestyle habits are immediately
gratifying. That is, habits are maintained by incentives (e.g.,
the convenience of taking the car), biological factors (e.g.,
addiction to nicotine in cigarettes, metabolism in obesity),
or the psychological needs they serve (e.g., self-esteem
boost from shopping; Verplanken et al. 2005). Notwith-
standing these supports for unwanted habits, even minor
changes in health habits can yield significant, positive out-
comes that plausibly encourage performance of new, health-
ful behaviors. For example, in the case of weight control,
many obese people report gratifying physical and social
benefits of losing even a small amount of weight (e.g.,
improved sexual quality of life, Binks et al. 2005). Despite
such positive outcomes, healthful behavior is rarely main-
Journal of Public Policy & Marketing 93
tained at the end of self-help intervention programs (see Jef-
frey et al. 2000). To understand why habits persist despite
people’s best efforts to carry out intervention recommenda-
tions, it is useful to consider what is meant by environmen-
tal control.
Essentially, the environmental control of action reflects
people’s learning of associations between their actions and
their performance circumstances. These associations can
develop from deliberate reasoning, for example, when
people learn a new skill (see ball swing bat). Associa-
tions also can develop through implicit detection of covaria-
tion and, as such, reflect the contiguous activation of con-
structs in daily life (couch eating snack foods). With
repeated experience, responses and the contexts in which
they occur become bound together in memory into chunks
of information (Wood, Neal, and Quinn 2006). Whole
sequences of habitual responses can then be activated by the
environment and implemented as a unit.
Environmental control also may have a motivational sub-
strate. Through associative conditioning, environmental
cues can acquire the motivational power to initiate and
guide action. This is because organisms are oriented to pre-
dict and control rewards and punishments. Thus, with the
repeated receipt of rewards in a given context, the neural
responding that initially occurred to the reward is trans-
ferred to the contextual cues that predict the reward (Wood,
Neal, and Quinn 2006). In this way, contexts themselves can
motivate repeated responding. In short, habit learning is a
cognitive and motivational process in which the control of
action is outsourced to the environment so that sequences of
prior actions are triggered automatically by the appropriate
Habit automaticity is evident in minimal awareness, in
the sense that people do not need to attend closely to what
they are doing when they habitually repeat prior behavior.
Efficiency is evident in that habitually practiced actions are
performed quickly, easily, with little effort, and in parallel
with other behaviors. Lack of conscious intention is evident
when habits are triggered by circumstances seemingly with-
out people’s desire or wish to perform them. Finally, some
habits are characterized by lack of control, meaning that it is
difficult to avoid initiating the behavior or performing it in
the same way as in the past (e.g., Betsch et al. 2004; Heck-
hausen and Beckmann 1990; Verplanken 2006; Verplanken
and Orbell 2003). In short, the environment’s automatic
activation of well-practiced responses is a key to the persis-
tence of habits despite people’s best intentions.
Habits Versus Conscious Intentions
The automaticity of habit performance perpetuates habits
over alternative actions. There are several reasons for this
(see Wood, Neal, and Quinn 2006). First, given that habits
are cued relatively directly by the environment with mini-
mal decision making, the practiced response is likely to be
more immediately available than thoughtfully generated
alternatives. When multiple response options are available,
the speed of automatically activated responses gives them
precedence over responses generated through slower routes.
Second, habits require minimal regulatory control. Habit
performance places few demands on people’s limited capac-
ities for self-control (see Baumeister, Muraven, and Tice
2000), whereas greater capacity is required to suppress
1The behavior prediction findings we report in Figure 1 (i.e., intentions
do not predict performance for people with strong habits) are not simply a
measurement artifact, such as restriction of range. In additional analyses, Ji
Song and Wood (2006) and Verplanken and colleagues (1998) report that
no consistent association emerged between habit strength and variability of
measures. Thus, the failure for intentions to predict behavior for people
with strong habits cannot be attributed to uniformly favorable intentions or
uniformly high-frequency performance.
habits to carry out alternative behaviors that require con-
scious guidance and deliberation. For these various reasons,
habits assume precedence over more thoughtful actions. The
availability and efficiency of habits is a frustrating challenge
to New Year’s resolutions and other decisions to change
established behavior.
The greater potency of habits than dispositions that
require decision making has been illustrated in behavior pre-
diction research. A standard prediction study begins with the
assessment of participants’ intentions to perform some
action (e.g., eat five fruits and vegetables every day) and
might also assess the strength of any existing habits (e.g.,
number of servings eaten in the past). Then, sometime later,
participants are contacted again to determine whether they
performed the action. As Triandis (1977, p. 205) suggests,
“when a behavior is new, untried, and unlearned, the
behavioral-intention component will be solely responsible
for the behavior.” However, “as behavior repeatedly takes
place, habit increases and becomes a better predictor of
behavior than behavioral intentions” (p. 205). Thus, Trian-
dis suggests a trade-off between intention and habit in guid-
ing behavior. This pattern has been documented in research
on health habits and transportation use.
Illustrating the potency of health habits, Ji Song and
Wood (2006) assessed the determinants of college students’
purchase of fast food. Students reported on the strength of
their habits to purchase fast food and whether they intended
to purchase it in the next week. Each evening during the
next week, they indicated in a diary whether and how often
they had purchased fast food that day. Habit strength and the
favorability of intentions were used to predict the number of
times students purchased fast food during the week. As Fig-
ure 1 (Panel A) shows, when habits were weak or had not
been formed, students acted on their intentions, and those
who intended to purchase did so more often (simple slopes
were estimated in line with the work of Cohen et al. [2003]).
However, when habits were strong, intentions had little
effect on behavior. The relatively flat slope is consistent
with the idea that behavior continued to be cued by the per-
formance context regardless of intentions.1Illustrating the
potency of transportation habits, Verplanken and colleagues
(1998) assessed the travel mode choices of residents of a
small Dutch village. Participants kept a diary for one week
in which they recorded their choice of travel mode for all
trips outside the village. The village was connected to two
nearby towns by both a highway and efficient public trans-
port systems (i.e., bus and train). Frequency of car use,
which was calculated as the proportion of trips made by car
during the week, was predicted from the strength of partici-
pants’ car use habits and their reported intentions to use the
car. The pattern of findings followed that which we reported
for fast-food purchases (see Figure 1, Panel B); namely, for
residents with weak or moderate habits, more favorable
intentions generated greater use of the car, whereas for those
94 Breaking and Creating Habits
Figure 1. The Prediction of Behavior by Intentions Broken Down by Habit Strength
A: The Results of Poisson Regression Predicting College
Students’ Frequency of Purchasing Fast Food
B: The Results of Poisson Regression Predicting
Consumers’ Car Use During a Week
Notes: The results of Panel A are from Ji Song and Wood (2006). The figure is a simple slope decomposition of the interaction between favorability of inten-
tions to purchase and strength of prior purchasing habits (p< .01; N = 117). The results of Panel B are from Verplanken and colleagues (1998). Specifi-
cally, the figure is a simple slope decomposition of the interaction between favorability of intentions to use the car and strength of prior car use habits
(p< .01; N = 200).
with strong habits, intentions were essentially unrelated to
car use.
Although the behavior prediction findings suggest that
habitual actions are cued without consulting conscious
intentions, participants in these studies were likely aware of
their purchases or automobile use. They may even have
made decisions about aspects of their responses, such as
counting the change for their purchases or finding their car
keys. However, the performance context provided a suffi-
ciently strong cue so that they performed daily activities
(e.g., eating meals, going to the store) with specific, well-
practiced action sequences that were performed without
guidance from relevant intentions. Thus, regardless of their
intentions, students with fast-food habits and town residents
with driving habits repeated their prior actions.
The behavior prediction findings indicating that habits are
performed regardless of intentions have important implica-
tions for behavior change. Namely, downstream, informa-
tional interventions that successfully change intentions do
not necessarily influence behavior. Webb and Sheeran’s
(2006) recent meta-analytic review provides striking evi-
dence in support of this idea. They reviewed previous exper-
iments that had given people persuasive messages or other
information designed to change their intentions to perform
various behaviors. If the interventions addressed actions that
were not easily repeated into habits, interventions that
changed intentions also changed behavior. For example,
when people were given information that convinced them of
the benefits of getting a flu shot or that explained how to do
so (e.g., where to go), they changed their intentions and car-
ried them out by getting vaccinated. However, if the inter-
ventions addressed behaviors that could be repeated suffi-
ciently to form habits, interventions that changed intentions
did not necessarily change behavior. For example, interven-
tions that successfully persuaded people they should eat a
healthier diet, and therefore changed their eating intentions,
were not effective at changing their actual eating behavior.
Thus, habits were not easily altered through informational
interventions that altered people’s intentions.
Even when downstream interventions successfully alter
habits, the effects appear to be largely short lived. For exam-
ple, participants in Garvill, Marell, and Nordlund’s (2003)
field experiment kept travel diaries for three weeks. During
the second week, the diaries for some participants were
structured to make them especially aware of their travel
behavior. Although participants with strong existing car-use
habits reacted to the structured diaries by decreasing their
car use during the next week of the study, such effects
appear to be short lived. Verplanken, Aarts, and Van Knip-
penberg’s (1997, Study 3) research that used a conceptually
similar task to render participants aware of their travel
behavior found that it only temporarily influenced partici-
pants with strong car use habits. Participants quickly
reverted back to their original response patterns. We suspect
Journal of Public Policy & Marketing 95
that interventions designed to sensitize people to their habit-
ual response patterns, similar to other informational inter-
ventions, have only limited effectiveness in changing habits
to align them with people’s intentions about how they want
to act.
In summary, the expectations established through behav-
ior repetition and the automaticity of habit performance are
conservative forces that reduce openness to new information
and that perpetuate well-practiced behaviors despite
people’s intentions to do otherwise. These aspects of habit
performance significantly hinder the effectiveness of down-
stream, individually focused interventions, such as informa-
tional campaigns and self-help strategies. Interventions that
provide people with information about the right thing to do
or that increase their understanding about how to perform a
behavior are likely to be effective primarily with actions that
are not practiced habitually. When the target behavior is
habitual, people’s intentions, desires, and judgments do not
easily overcome the practiced response that is cued auto-
matically by the environment.
Although the dependence of habits on stable aspects of
the environment presents a barrier to information use, this
feature of habits also represents a unique source of vulnera-
bility; namely, habits can be changed through changes in
those circumstances. As we explain in the remainder of the
article, environmental control is a key to the success of
interventions that are designed to change everyday habits
and maintain new behavior.
Environmental Control of Habits
Because habits are triggered by the environment, successful
interventions must focus on changing the environmental
features that maintain those habits. A focus on environmen-
tal change is consistent with anecdotal reports that changing
well-practiced behavior (e.g., quitting smoking) is often eas-
iest while people are traveling or otherwise removed from
everyday circumstances. Evidence of this phenomenon
emerged in Heatherton and Nichols’s (1994) investigation
of people’s attempts to change some aspect of their lives.
Approximately 36% of people’s reports of their successful
change attempts involved moving to a new location,
whereas only 13% of reports of unsuccessful attempts
involved moving. In addition, 13% of successful change
reports involved alterations in the immediate performance
environment, whereas none of the unsuccessful reports
involved shifts in environmental cues. The change in con-
text presumably disrupted the automatic cuing of action,
freed it from environmental control, and thus facilitated
change efforts.
Empirical evidence for the power of environment change
comes from Wood, Tam, and Guerrero Witt’s (2005) study
of college students transferring to a new university. Transfer
students are of special interest because the move between
schools can disrupt the circumstances that support everyday
habits. One month before the transfer and one month after,
students reported their intentions to exercise (plus several
additional actions), their typical exercise frequency, and
their typical exercise locations. The focus of the study was
when exercising at the new university would be guided by
intentions and when it would follow students’ habits (if any)
at the old university. Some of the students had established
strong exercise-related habits at their old school, for exam-
ple, regularly jogging on a trail outside or working out in the
gym. For these students, old exercise habits maintained
across the transfer when the performance location was sta-
ble from the old to the new university. When locations
shifted and students could not, for example, work out in the
gym, their exercise habits were disrupted. Notably, when
locations shifted, students’ behaviors came under inten-
tional control and were predicted by the favorability of the
students’ intentions. Students who wanted to exercise at the
new university did so, whereas those who did not want to
exercise quit. Presumably, without the old contextual cues
to trigger automatically the well-practiced behavior, stu-
dents were spurred to make decisions about exercising.
Given the evidence that changes in performance contexts
can disrupt habits, it seems plausible that an effective inter-
vention to change habits is to teach consumers how to
change their typical performance contexts. This idea that
habits can be changed through individual control of trigger-
ing stimuli is a central component of some behavior modifi-
cation therapies (see Follett and Hayes 2001). However, the
use of these strategies can require substantial ability and
motivation. Consumers first need to identify the cues that
trigger unwanted habits, and then they must understand how
to avoid or control their exposure to the cues. Given that
cues to overeating and inactivity are pervasive in our soci-
ety, control of related actions will be challenging and will
require vigilant monitoring of the environment (Quinn and
Wood 2006). To the extent that control over these actions
places a continuing demand on ability and motivational
resources, stimulus control will be subject to the same prob-
lems of relapse and remission as other downstream inter-
vention programs that depend on people’s desire to change
(Baumeister, Muraven, and Tice 2000; Neal, Wood, and
Quinn, in press). For these reasons, relying on people’s
capacity to control the contexts of habit performance may
not be a promising intervention strategy for policy makers
who are interested in changing consumer habits.
Next, we outline what we believe are effective habit
change interventions. Essentially, these require shifts in the
performance environment that, unlike stimulus control
strategies, do not arise from individual control efforts.
Effective Habit Change Interventions
The first question to ask when designing behavior change
interventions is whether the target behavior is habitual. Has
the population of interest repeated the behavior regularly in
stable contexts (e.g., at particular times of day, in stable
locations)? If the answer is yes, the target behavior is likely
to be habitual. The diet and exercise behaviors that con-
tribute to obesity are classic examples of habitual responses.
In addition, automobile use, especially in the United States,
is the habitual form of transportation for many people.
The second design question involves distinguishing
between downstream and upstream behavior change inter-
ventions. As we noted at the beginning of this article, down-
stream interventions include education, counseling that
might involve stimulus control and other behavior modifi-
cation strategies, informational campaigns that identify
costs of existing behaviors and benefits of new responses,
and self-help programs that increase self-efficacy to perform
96 Breaking and Creating Habits
new behaviors. These interventions are typically targeted
directly to individual consumers to change problematic or
unwanted behaviors. In contrast, upstream interventions are
not aimed directly at individual behaviors but focus on the
larger structural conditions in which people’s behaviors are
embedded. Thus, upstream interventions may consist of
economic incentives, legislation, or structural changes in the
performance environment. These interventions aim to pro-
vide contexts and societal structures that promote and sus-
tain desired behavior.
In Table 1, we integrate the distinction between strong
and weak habits with that of upstream and downstream
interventions to yield four possible intervention approaches.
Each of these describes a particular type of intervention that
is likely to be effective for a particular type of behavior.
Downstream Interventions
The upper-left quadrant of Table 1 represents the applica-
tion of downstream intervention strategies with behaviors
that are not strong habits. In this quadrant, there are many
downstream strategies that have proved effective in chang-
ing nonhabitual behaviors (e.g., Perry et al. 1996, 2002;
Webb and Sheeran 2006) and in generating short-term
change in ongoing behaviors (e.g., Orleans 2000). A variety
of potential intervention strategies are available for these
kinds of behaviors and outcomes.
The strategies in the upper-left quadrant of Table 1 can be
applied effectively to behaviors that could evolve into habits
over time, such as unhealthful eating or overuse of automo-
biles. The interventions could be implemented among con-
sumers who have not, or have not yet, developed strong
habits. An illustration of this approach is the use of standard
weight-loss interventions that involve education and imple-
mentation of self-control strategies with young dieters.
These downstream approaches seem more effective in gen-
erating sustained weight loss with preadolescents than with
adults (e.g., Jeffery et al. 2000). Among the many possible
reasons for this effect is the possibility that obese children
have fewer strongly established eating and exercise habits
than obese adults.
Among the many available sources of downstream inter-
ventions, schools provide important health promotion infor-
mation to adolescents. For example, an exploratory study
among alternative-high-school teenagers suggested that
such small-scale environments were promising grounds to
deliver interventions to promote healthful food choices and
to increase efficacy through healthful cooking classes
(Kubrik, Lytle, and Fulkerson 2005).
Downstream interventions sometimes aim to provide
people with tools for self-regulation as part of being edu-
cated into new behavioral domains. For example, young dri-
vers must learn that speed control not only prevents getting
tickets but also holds the key for better driving, such as
being better prepared for handling unexpected situations,
freeing up mental capacity, and avoiding accidents. Young
dieters may learn how to monitor their weight properly, use
information provided on food labels, and manage bodily
sensations (e.g., by eating fruit to avoid feeling hungry).
Downstream-Plus-Context-Change Interventions
The lower-left quadrant of Table 1 involves effective down-
stream interventions that address unwanted behaviors with a
strong habitual component, including unhealthful eating,
alcohol use, or overreliance on the automobile. As we
explained, the information-processing mind-sets that
accompany strong habits and the automatic cuing of habits
by the environment hinder the effectiveness of typical
downstream interventions that involve solely informational
campaigns or self-regulation. However, greater success is
likely when such downstream strategies are paired with nat-
urally occurring lifestyle changes.
Downstream-plus-context-change interventions gain their
effectiveness because the changes in context render people
with strong habits vulnerable to new information. Specifi-
cally, environmental changes that disrupt habits also chal-
lenge habitual mind-sets and thus increase openness to new
information and experiences. Furthermore, because these
environmental changes impair the automatic cuing of well-
practiced responses, they enable performance of new
Changes in performance environments refer to aspects of
the physical environment (e.g., new houses and travel infra-
structures, introduction of healthful food items in restau-
rants) and the social environment (e.g., new friends who
have adopted a healthful lifestyle or who use public trans-
portation). Given shifts in these environmental features, var-
Table 1. Effective Policy Interventions to Change Weak Versus Strong Habits
Behavior to Be Changed Interventions Downstream of the Behavior Interventions Upstream of the Behavior
Weakly or not habitual Information/education to
•increase self-efficacy
•change beliefs/intentions
•motivate self-control
•form implementation intentions
Economic incentives
Legislation and regulation
Environmental design
Technology development
Normative approaches
Strongly habitual Downstream-plus-context-change Economic incentives
Legislation and regulation
Environmental design
Technology development
Normative approaches
Notes: Our distinction between interventions that are downstream and those that are upstream of the to-be-changed behavior is based on McKinlay (1975).
Journal of Public Policy & Marketing 97
ious related habits might be disrupted, including transporta-
tion habits (e.g., commuting), consumption habits (e.g.,
water use), social interaction habits (e.g., relating to neigh-
bors), and ecology-related habits (e.g., heating, electricity
use, waste disposal/recycling; see Rodriguez 2005). The dis-
ruption of existing habits provides opportunities for suc-
cessful downstream interventions that promote desired new
behaviors without competition from established behavior
Downstream-plus-context-change interventions can be
implemented at many of the significant life changes that
people experience naturally across their life course. Targets
for such interventions include residents who relocate to new
homes and employees who move jobs or experience
mergers in their work organizations. Such changes occur
with some regularity across the life span. On average,
Americans move every five years (Jasper 2000). At least
during some points of their life, they change jobs with even
greater frequency. According to a longitudinal survey of job
changes, people born from 1957 to 1964 held an average of
10.2 jobs from ages 18 to 38 (Bureau of Labor Statistics
2004). Aging across the developmental stages of the life
span also yields relevant lifestyle changes. Changes in per-
formance environments often coincide with people’s move-
ment into another life phase, such as adolescents leaving
their parents’ home, couples starting a family, and older
people entering retirement. Downstream-plus-context-
change interventions are especially efficient options when
environmental changes apply to groups of people, for exam-
ple, when new residential areas are built or organizations
The downstream-plus-context-change approach is exem-
plified in new resident marketing programs. Through “wel-
come wagons” and other such programs, new residents are
contacted soon after they move and are provided informa-
tion about local products, services, and vendors. Although
these programs currently are oriented toward addressing the
typical purchases of new homeowners, they could be
adapted to provide information about healthful lifestyle
options (e.g., parks and recreation facilities, public trans-
portation options) and incentives to adopt healthful behav-
iors. Incentives might include social benefits, such as meet-
ing others and receiving recognition for participating, and
tangible bonuses, such as free trial periods or use of
The downstream-plus-context-change approach is
already being used by several U.S. metropolitan bus sys-
tems, which provide new city residents with a free bus pass
(see, e.g., Centre Area Transportation Authority’s apartment
pass program;
Providing bus passes should be an especially effective strat-
egy to increase ridership when people are new to an area and
have yet to establish car-driving and other travel mode
habits that might conflict with taking the bus. Downstream-
plus-context-change interventions might successfully
increase people’s efficacy to perform the new behavior (e.g.,
learning bus routes or where to catch the bus) and the favor-
ability of their intentions to do so. Research is still at an
early stage in evaluating the success of such downstream-
plus-context-change interventions, though there is good rea-
son to believe that they will be more successful at altering
everyday lifestyle habits than downstream interventions
alone (e.g., simply providing a free bus pass; see Fujii and
Kitamura 2003).
In summary, although downstream interventions by
themselves are unlikely to change habitual behaviors,
such interventions can be used strategically at points
when naturally occurring changes in the performance
environment render people especially vulnerable to change.
Downstream-plus-context-change interventions should be
most successful when the naturally occurring changes in the
environment alter the specific cues that triggered established
habits. As Wood, Tam, and Guerrero Witt (2005) observe,
habits are disrupted by changes in the specific environmen-
tal cues that trigger habit performance. Given that people
can report on changes in the performance environment for a
particular action, these reports can be used to indicate when
downstream interventions are likely to be effective. In short,
when a target sample reports that some lifestyle change has
disrupted critical aspects of a performance environment, the
change provides a promising context for instigating a
downstream-plus-context-change intervention.
Upstream Interventions
Upstream interventions that involve large-scale, macrolevel
policy changes are especially suited to address the societal
and environmental structures that promote and sustain
habits. We list the various upstream types of interventions in
the right column of Table 1. Examples that are especially
relevant to obesity and transportation include (1) taxes and
other economic incentives for healthful behaviors and the
smart use of automobiles, (2) policy-driven changes that
alter the physical environment or the behavioral alternatives
within that environment, and (3) education that promotes the
use of healthful and energy-efficient products (see McKin-
lay 1975; Orleans 2000). Policy makers who embark on
upstream intervention strategies may use these various
strategies depending on their particular goals.
Economic incentives are upstream policy interventions
that encourage desired behavior through the provision of tax
relief, cash incentives, or other subsidies for desired services
(e.g., medical, transportation). Economic measures also
might discourage undesired behaviors through the imposi-
tion of taxes (e.g., so-called sin taxes). With respect to trans-
portation, an example of a highly effective economic inter-
vention for traffic congestion is the practice of congestion
pricing, in which motorists are charged more to drive in a
certain area or use a tunnel or bridge during peak periods.
For example, in 2003, London implemented a policy in
which drivers of private automobiles are charged a fee to
drive in the central area during weekdays. According to Lit-
man (2006), this policy has significantly reduced traffic con-
gestion in the area, increased use of bus and taxi services,
and generated substantial government revenues. With
respect to health behaviors, economic incentives for preven-
tive measures appear to be effective in the short run, espe-
cially for vaccinations and other simple behaviors with dis-
tinct, well-defined goals (Kane et al. 2004). However,
economic incentives appear less effective when they pro-
vide rewards for specific outcomes of more complex behav-
iors, such as weight loss. Other scholars have argued that to
induce and sustain long-term lifestyle changes, economic
98 Breaking and Creating Habits
incentives are best coordinated with other system-level mea-
sures, such as educational experiences that support the
changes (Breslow 1996).
Another way upstream interventions change the environ-
ment is by modifying it directly. For example, city planning
and environmental design have the potential to yield spe-
cific transportation and health benefits. Smart city planning
that is coordinated with road design and efficient trans-
portation systems will be required to reduce consumers’
reliance on the automobile. In addition, city planning that
promotes human-powered transportation, such as biking and
walking, has the potential to reduce obesity. In support, resi-
dents from communities with higher density, greater con-
nectivity, and more mixed land use report higher rates of
walking and cycling for utilitarian purposes (Saelens, Sallis,
and Frank 2003). In addition, technological developments
may be important elements of upstream interventions. For
example, easily applicable monitoring devices (e.g., to mea-
sure heart rate, blood pressure, and blood sugar) may help
people sustain healthful lifestyles.
Policy regulations also directly change the performance
environment when they change available behavioral alterna-
tives. Sometimes this can be accomplished by increasing the
ease of performing certain behaviors. For example, recy-
cling can be significantly increased when the environment is
structured to promote such behavior through optimal collec-
tion periods and methods (Schultz, Oskamp, and Mainieri
1995). Other times, changes in behavioral alternatives can
be accomplished through limiting possible responses. For
example, school boards across the United States are adopt-
ing policies to ban or restrict access to junk food in school
cafeterias and vending machines located on school property.
Although currently there is little data indicating whether
such bans indeed increase the healthfulness of students’
diets and reduce obesity, the bans hold considerable promise
to do so (Fox et al. 2005). A better-known example of
upstream interventions that limit behavioral alternatives is
policies that prohibit smoking in workplaces and public
areas, such as restaurants and public buildings. The effec-
tiveness of such bans is attested by a 1992 internal docu-
ment from cigarette maker Phillip Morris, which summa-
rized the results of smoking bans in workplaces. “Total
prohibition of smoking in the workplace strongly affects
industry volume. Smokers facing these restrictions consume
11 per cent to 15 per cent less than average and quit at a rate
that is 84 per cent higher than average” (as reported in
Doward 2005). However, a recent analysis of the effects of
smoking bans undertaken in Australia indicates that not
everyone is influenced by them equally (Buddelmeyer and
Wilkins 2005). Among younger smokers, the introduction
of bans had the undesired effect of increasing the likelihood
that they continued to smoke. Such patterns suggest the use-
fulness of our proposed downstream-plus-context-change
interventions. Informational campaigns that addressed the
concerns of young smokers regarding the smoking ban
might have promoted quitting among this sample.
Finally, educating consumers is a form of upstream inter-
vention that does not involve immediate context change but
has the potential to change performance contexts over time.
Educational efforts can take many forms, including courses
or modules integrated into existing curricula at schools or
universities, self-education opportunities, or long-standing
public campaigns. The availability of the World Wide Web
makes this an increasingly important source of education.
Educational interventions that change consumers’ beliefs
and understanding of their behaviors are most likely to have
immediate impact on those who have not established habits
(e.g., educational programs about condom use aimed at
young teenagers). However, educational programs may
have long-term effects that bring about change in perfor-
mance environments, such as when education conveys new
norms and values that infuse the decisions of policy makers.
In recognition of these long-term effects, we include educa-
tion as an upstream intervention in the upper-right quadrant
of Table 1. However, because education typically has mini-
mal immediate impact on performance contexts, it has only
long-term promise as a habit change strategy.
In general, our review of research on effective habit
change strategies for complex behaviors, such as those that
yield obesity and overreliance on the automobile, suggests
that any single intervention strategy is unlikely to be suffi-
cient to yield change across a population. Instead, our
review suggests the effectiveness of broad-spectrum inter-
ventions that address multiple levels of analysis, such as our
downstream-plus-context-change strategy (see also Orleans
2000). Sometimes prescriptions that involve multiple strate-
gies have considered stages of behavior change, in which
interventions are tailored to individual phases of change
(e.g., the transtheoretical model; Prochaska, DiClemente,
and Norcross 1992). Although such models are not built on
an understanding of the psychological mechanisms that con-
trol repeated action in daily life, they propose a range of
possible interventions that might be useful for people as
they move from initially contemplating to undertaking
behavior change.
Swimming Upstream
The combined use of downstream and upstream initiatives
often begins with interventions focused at the downstream
level, when unwanted behaviors initially become a target for
intervention. As downstream attempts to change behaviors
develop, policy makers may expand these into broader,
long-term upstream interventions. An example of this pro-
gression from downstream to upstream intervention strate-
gies can be found in a remarkable project called Jamie’s
School Dinners by one of Britain’s popular chefs, Jamie
Oliver. Several schools were persuaded to abandon the
processed, ready-made junk food they were serving to stu-
dents and staff and to replace it with fresh, nutritious food
prepared from scratch every day (e.g., Oliver 2005).
Although students initially resisted the changes from their
fatty junk-food habits, they eventually were persuaded by
peer pressure, the school environment, and parental support.
During this process, it became apparent that the success of
this project was conditional on structural changes within the
schools themselves as well as at the level of community and
national politics (e.g., extra pay for cafeteria workers, addi-
tional training and equipment). Eventually, the British prime
minister addressed the issue of healthier school meals, and
an independent food trust was formed to expand the work
that Oliver began (Hinsliff and Hill 2005).
In summary, downstream-plus-context-change interven-
tions seize naturally occurring opportunities to disrupt exist-
ing habits and to provide new information and opportunities
Journal of Public Policy & Marketing 99
to create new habits. In addition, upstream interventions can
orchestrate the necessary environmental changes to reduce
competition from established responses and to encourage
the performance of new, more desirable responses. Essen-
tially, to alter old habits and establish new ones, the critical
ingredients for any interventions include (1) changes in the
old performance environment that disrupt existing habits
coupled with (2) opportunities or experiences that encour-
age performance of the desired response. In the next section,
we consider exactly how to construct interventions to
encourage performance of new responses and to ensure their
Creating Habits as an Intervention Goal
The effectiveness of interventions depends not only on the
change of existing habits and the initiation of a new behav-
ior but also on the maintenance of that behavior. One mech-
anism to ensure that new responses continue is through the
creation of new habits. Despite the large amount of research
and practice involving interventions to change behavior, the
idea that interventions can ensure maintenance by creating
habits has received little attention. This omission is partly
due to the history and definition of habit. Historically,
researchers often equated habit with frequency of behavior
and thus viewed strong habits simply as frequent perfor-
mance. When habits are defined as we do in this article—
that is, in terms of the automatic cuing of behavior by stable
performance circumstances—habit formation can be tar-
geted as an intervention goal, and changes in habit strength
can be monitored over time.
How should habits be created? As we explained previ-
ously, the basic mechanisms of habit formation involve
repetition and reinforcement of behavior (see Hull 1943). At
least initially, reinforcement is important to promote repeti-
tion. Adopting and repeating a new action depends largely
on people’s judgments that the outcome it affords is more
desirable than those offered by alternative actions (e.g.,
Rothman 2000). Imagine a successful intervention aimed at
convincing commuters to switch from car to train travel. It
is easy to predict what will happen if these new train pas-
sengers experience schedule delays or crowded trains. This
lesson is well learned among marketers, given that product
sales constitute a solid behavioral criterion that is monitored
over time.
There are various reinforcements that can promote per-
formance of a new behavior. Some people may find that liv-
ing up to important health or environmental values is suffi-
ciently reinforcing to motivate repeated performance. For
others, these abstract values are not especially motivating,
and more potent reinforcements are the behavioral outcomes
of efficiency, profitability, and convenience (see Ver-
planken and Holland 2002). For example, tangible incen-
tives to change travel behaviors include providing free bus
tickets and passes, both of which have proved effective at
increasing frequency of bus ridership among college stu-
dents, a group likely to be still learning about transportation
options (Bamberg, Ajzen, and Schmidt 2003; Fujii and Kita-
mura 2003). In general, the various downstream interven-
tions listed in the middle column of Table 1 can be used to
emphasize the desirability of a target action over other pos-
sible responses.
As people repeat actions, habits may develop naturally as
environment–response associations are gradually laid down
in procedural memory (Wood, Neal, and Quinn 2006). In
addition, such associations may be formed deliberately
through “implementation intentions,” or plans of action that
specify exactly the behaviors that are to be performed in
response to specific cues (i.e., how, when, and where to act;
Gollwitzer and Schaal 1998). People might form implemen-
tation intentions and plan to go to the gym on their way
home from work every day this week or to take the bus on
Monday morning. When people form these plans to perform
an action in response to environmental cues, they are begin-
ning to establish a habit.
Implementation intentions are surprisingly effective
given the simple nature of such plans (Orbell 2004; Sheeran
2002). Although it is tempting to argue that the mechanism
by which implementation intentions works mimics the
mechanism of habits, the cue–response links associated with
implementation intentions have a different history than
those of habits. With implementation intentions, these links
are established by deliberate planning, whereas with habits,
they are established by a history of satisfactorily repeating
behavior. Furthermore, implementation intentions increase
performance only to the extent that people view the behav-
ior as relevant to achieving desired goals (Sheeran, Webb,
and Gollwitzer 2005). In contrast, habits continue to be per-
formed regardless of people’s intentions (see Figure 1, Pan-
els A and B). As such, implementation intentions represent
a promising starting point for establishing habits (Holland,
Aarts, and Langendam 2006; Verplanken 2005). With repe-
tition, the very same cue–response associations that are ini-
tially executed in a deliberate fashion as part of planning
may turn into habitual cue–response associations that func-
tion automatically.
To demonstrate that implementation intentions facilitate
habit formation, Orbell and Verplanken (2006) asked par-
ticipants to form a behavioral intention to floss their teeth
regularly. Some participants furnished this intention with
implementation intentions and outlined when and where
they would floss every day during the following four weeks.
When the study began, few participants had a flossing habit
(e.g., 66% reported never flossing before). Participants were
then given a floss packet. Four weeks later, the packets were
weighed, and participants reported on their behavior. As
expected, those who formed implementation intentions
flossed more frequently than those who did not, and on the
basis of their descriptions of performance, they were more
likely to form habits to floss automatically, given stable con-
texts. These results give some support to the contention that
forming implementation intentions facilitates the establish-
ment of future habits.
Despite their effectiveness in encouraging the repetition
of new actions, implementation intentions, as with most
downstream strategies, are less useful for countering exist-
ing habits. Illustrating the limits of implementation inten-
tions, Webb, Sheeran, and Luszczynska (2006) investigated
whether implementation intentions could help high school
smokers quit. Some smokers in the study were asked to for-
mulate specific plans of action in response to difficult situa-
tions for a smoker (e.g., “When someone offers me a ciga-
rette of my favorite brand, in order not to smoke I will.…”).
Habit strength was assessed according to the number of cig-
100 Breaking and Creating Habits
arettes smoked daily. One month later, participants were
asked how many cigarettes they smoked per day. The imple-
mentation intentions reduced the numbers of cigarettes
smoked per day only among participants with initially weak
smoking habits. Thus, implementation intentions were not
able to reduce strong smoking habits (see also Verplanken
and Faes’s [1999] study of eating habits). It seems that
implementation intentions are useful to link performance to
environmental cues and thus facilitate habit formation, but
they do not appear sufficiently powerful to override well-
practiced actions automatically cued by contexts. This
might be because overriding strong habits taxes self-control
resources, which appear to be limited in capacity and easily
depleted (Baumeister, Muraven, and Tice 2000).
Despite the promise of establishing new habits through
rewards for the new action and through links forged with
environmental features (e.g., from implementation inten-
tions), we are not aware of any health or transportation inter-
ventions to date that have adopted habit development as an
explicit goal. Such interventions would involve a multi-
pronged approach that promotes change of existing behav-
ior patterns through the adoption of a new behavior and the
formation of associations between actions and environmen-
tal cues to ensure the maintenance of the behavior over time
(see Rothman, Baldwin, and Hertel 2004).
Summary and Conclusions
Understanding habits is important to public policy in
domains concerned with everyday action, including health-
ful living, product purchase, media use, transportation, and
environmental quality. We argue that change interventions
are most likely to be successful when they are tailored to the
habit strength of the target behavior.
Everyday actions that are not habitual are open to change
through downstream interventions, such as informational
campaigns and self-help programs that are designed to edu-
cate people and motivate them to change. According to the
diary studies, in which college student and community sam-
ples reported on what they were doing, thinking, and feeling
once per hour for several days, approximately 45% of
respondents’ everyday actions were habits in the sense that
they were performed almost daily and usually in the same
location (Wood and Quinn 2005; Wood, Quinn, and Kashy
2002). Thus, a full 55% of reported actions were not habits.
Even regularly performed behaviors are not always per-
formed habitually. For example, driving is likely to be a
habit when going to work, but it is likely to involve decision
making when it represents a pleasure trip on the weekend or
when newly licensed drivers are still learning driving skills.
In this way, many everyday actions are amenable to change
through downstream interventions and to shift when people
learn new information or skills relevant to performance.
Habits perpetuate prior behaviors and limit the effective-
ness of downstream interventions. Consumers with habits
have strong expectations for the environment and action
alternatives that shield behavior from change through new
information. Even when consumers become convinced of
the advisability of habit change, they are likely to continue
to perform a behavior that is automatically cued by stable
features of the environment. However, the dependence of
habits on environmental cues renders them vulnerable to
intervention strategies that involve changes in those cues.
Sometimes environmental changes occur naturally, as when
people move to new homes, when organizations merge, or
when a town’s road and transportation infrastructure is
redesigned. When old cues to everyday activities change,
habits are disrupted, and people potentially are spurred to
think about their actions and perhaps to use their intentions
as a guide to new choices. Thus, an opportunity for success-
ful informational campaigns to change habitual behavior is
provided through pairing downstream interventions with
naturally occurring changes in living environments. We
termed these downstream-plus-context-change interven-
tions to emphasize their focus on immediate problem solv-
ing and kicking old habits by strategically taking advantage
of naturally occurring shifts in lifestyles. An example of a
downstream-plus-context-change intervention to address
transportation is the provision of bus passes to new residents
in some metropolitan areas in the United States.
Habits also are amenable to policy interventions that
occur considerably upstream of a target behavior and that
involve strategically designed changes in the performance
context itself. These types of interventions focus on preven-
tion of undesired behaviors. As we explained, examples of
upstream interventions that address obesity and transporta-
tion include taxes and other economic incentives for health-
ful behaviors and strategic use of automobiles; policies that
change the physical and social environment to reduce access
to food, encourage exercise, and encourage use of alterna-
tive forms of transportation; and education to yield long-
term changes in context and social structure.
Finally, we proposed that successful interventions need to
target not only change of old, unwanted behaviors but also
the maintenance of new, more desirable responses. When
habit formation is realized as an intervention goal, new
behaviors are maintained, and relapse is prevented. Inter-
ventions that specifically tie an action to a context by
employing implementation intention planning ensure repeti-
tion of an action and thus represent a useful component of
large-scale intervention programs.
In these various ways, the realization that behavior can
acquire habitual qualities has significant consequences for
the design of policy interventions. Effective interventions
are built most importantly on an analysis of the extent to
which consumers’ existing behaviors are habits. Is the
action targeted for change one that the target population
tends to repeat regularly in stable contexts? If the answer is
yes—and we guess that it is yes for many of the everyday
actions associated with health and consumers’ use of trans-
portation—this feature of action should guide the design of
change interventions. Successful interventions to change old
and establish new habits must (1) change the context cues
that trigger existing habits, (2) establish incentives and
intentions that encourage new actions, and (3) promote repe-
tition of new actions in stable circumstances so that associ-
ations form in memory between features of the environment
and the response. Through interventions designed with these
goals in mind, old habits can be disrupted, and new habits
can be established.
In the reality of everyday life, accidents, immediate prob-
lems, and mishaps usually attract the attention of the media
and policy makers, such as areas of serious traffic conges-
tion or alarming health statistics. The primary responses to
Journal of Public Policy & Marketing 101
these events are likely to be downstream interventions
aimed at solving these immediate problems. However, on
the basis of psychological research on habits, we offer a
rationale that addresses the structural factors that generate
such problems, including the lack of accessible and efficient
public transportation, the presence of an unhealthful diet
culture, and sedentary lifestyles. These underlying condi-
tions are more difficult to identify and change. However,
upstream interventions hold the promise of accomplishing
this. Such approaches often present significant challenges to
design and implement, given that they take time, often
require political support, and can be expensive. We believe
that such investments are necessary if society is to promote
ecologically responsible and healthful behaviors. Successful
change strategies address not only immediate problems
through downstream interventions but also the upstream
factors that encourage and maintain the repetition of every-
day behavior.
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... to or seeking to influence beliefs and values through messaging (as discussed above) is typically insufficient (Verplanken & Wood, 2006). What is needed is disruption to environmental factors that cue habit performance. ...
... What is needed is disruption to environmental factors that cue habit performance. This might include providing information when people's behaviors are most likely to be influenced to change such as when their circumstances change (downstream interventions) or changing the environment to disrupt habits (upstream interventions; Verplanken & Wood, 2006). For the former that might include providing information to encourage responsible leashing behaviors when dog owners acquire a new dog, or when dog owners move into a new local government area, for example, by governments partnering with real estate agents to provide information when new residents purchase or rent in the area. ...
... Yet they differ in their appreciation of habit change. Psychological theories often describe habits as stable and rarely modified (Verplanken and Orbell 2003;Verplanken and Wood 2006;Neal, Wood and Quinn 2006). For several mobility scholars, however, this view is reductive. ...
... These researchers identify the source of change as being linked to changes in the natural and/or built environment. If the habit is still being learned, the source of change resides in the individual's intentions (Verplanken and Orbell 2003;Verplanken and Wood 2006;Neal, Wood and Quinn 2006). ...
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How do habits change? Some mobility scholars describe habits as regularly evolving. Several psychologists, on the other hand, observe radical changes originating from disruptions in our environment. I show that these two perspectives can be integrated using Berger and Luckmann's model of individual change. In the first phase, a shock from the environment disrupt a habit or habits, which are later replaced by new habits progressively learned as part of a group. I applied this model to two French bike workshops active in cycling subculture. I used interviews and participant observation in the two workshops to examine how communities potentially lead their members to change their body habits (their way of moving, seeing, touching), their perception of the car and social mobility, and to adopt a radical definition of the "good life". I found that the depth and breadth of habit change depended on the individual's involvement in the bike workshop and of the type of shock he/she experienced. As a result, I show how an instance of the cycling subculture transforms habits, both progressively and radically, by strengthening the relationship between individuals and their bikes. The article opens the path to applications of Berger and Luckmann's theory to mobility.
... It reflects an ingrained behavior, which implies that it is difficult to divert an individual's attention when faced with a change in situation. However, several studies find that a habit can be modified because of an event that changes the course of a lifetime-this is what the theory of habit discontinuity assumes [14][15][16][17]. The use of an awareness campaign to identify the public seems more promising to increase public awareness than the use of "classic" campaigns whose message seems "impersonal" or too "general" to arouse the interest of the greatest number [18]. ...
... It is this level of reflection that allows them to distinguish the extraordinary from the ordinary [54]. If the extraordinary is based on the intensity of an experience greater than what the ordinary provides, we can define this type of experience as an upsetting event that disrupts a person's daily life [14][15][16]. In an advertising approach, the development of a surprising narrative (or "storytelling") makes it possible to capture attention, mark the spirits and give a "transformative" feature to an experienced situation [55,56]. ...
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Climate change appears to be the ecological issue which benefits from the most attention in the literature, compared to equally alarming situations such as plastic pollution. In fact, waste management issues took a new step with the recent discovery of microplastics in human blood for the first time, as it used to be a hypothesis. Instead of separating those questions, some researchers tend to consider that a link exists between the effects of global warming and plastic degradation in the ocean. Research focusing on the construal-level theory and the psychological distance explain the lack of public interest in the environmental crisis. However, recent studies highlight the empirical support of the psychological distance instead of the CLT, especially regarding climate change, but a few studies explore the psychological distance related to plastic pollution. With that in mind, any means to reduce the perceived psychological distance regarding environmental issues such as plastic pollution might increase their sensitivity and motivation to act. Moreover, the change of habit could be induced by a new event that would disrupt someone’s daily life according to the habit discontinuity hypothesis, and the use of immersive media such as video games might be the solution. Given numerous possibilities of creation with the scenarios, gameplay, public of interest and gaming contexts, video games also influence motivation, engagement and learning ability. We can also find specific components and mechanisms from game design in media that do not focus on entertainment first but on pedagogical purpose: serious games. Thus, this study investigates how immersive media might reduce specific psychological distance dimensions and trigger emotions using an educational video game on plastic pollution, which might play a major role in changing ones’ daily habits. The research uses a qualitative method centered on semi-structured individual interviews and the experimentation of a video game named Plasticity. Results support all the propositions and show that different types of immersion might reduce each dimension of the psychological distance, which is a first, reinforcing environmental awareness and new intentions of pro-environmental behavior. Other areas of discussion are furthered explored.
... It has been proven that outcome expectations cause habits to some degree. Verplanken and Wood found that habit formation was steered by the cognitive process of comparing performance expectations about behavior with the actual outcome of the behavior [77]. Similarly, Hu et al. identified that expectation-confirmation of social media use was positively associated with habit [67]. ...
... However, different from two independent impacting paths of information sharing in previous studies, the results of this study verified the mediating role of habit in the model, which supplement the association of two approaches. Consistent with relevant findings, habit is formed by outcome expectations and has an impact on information sharing intention [69,77]. There is also an indirect relationship between outcome expectations and information sharing intention that is mediated by habit. ...
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Information sharing is critical in risk communication and management during the COVID-19 epidemic, and information sharing has been a part of individual prevention and particular lifestyles under the “New Normal” of COVID-19. Thus, the purpose of this study was to explore influencing factors and mechanisms in public and private information sharing intention among people under the regular risk situation. This study investigated an information sharing mechanism based on a cross-sectional design. We collected 780 valid responses through a sample database of an online questionnaire platform and utilized partial least squares structural equation modeling (PLS-SEM) to further analyze the data. To explore the difference caused by news frames, we divided respondents into two groups according to the news frame (action frame vs. reassurance frame) and proceeded with the multi-group analysis. The results showed that four types of outcome expectations (information seeking, emotion regulation, altruism and public engagement) and habit had impacts on public and private information sharing intention. Two paths influencing information sharing proposed in this study were supported. The results showed that outcome expectations were positively related to habit, which implies that the cognitive mechanism was positively relevant to the formation of habit. The results proved that habit played a mediating role between outcome expectations and information sharing. This research found that emotion regulation and public engagement outcome expectations only affected two types of information sharing intention mediated by habit. Regarding the role of the news frame, this study found no significant difference between the group exposed to action-framed news and the group exposed to reassurance-framed news. By exploring influencing factors and the mechanism of information sharing under the “New Normal”, these findings contribute to understanding of information sharing and have implications on risk management. The proposed mechanism classifying public and private information sharing complements risk information flowing by considering online risk incubation.
... Similarly, in terms of health our study showed how rather than from changing attitudes by being educated on health only, reflexivity on health can also come from diverse elements or cues in the socio-material environment (Polhuis, 2019). In our study, being diagnosed with a major health issue also appeared not to be sufficient motivation for changing lifestyles, in spite of the opportunities for change it might contain according to the literature (Verplanken & Wood, 2006). We concur with Burningham and Venn (2020)'s view on change as a drawn-out and ongoing process, rather than as singular pathway of transition. ...
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As cities are growing in size and changing in demographic composition, new responsibilities in the field of food and inclusiveness emerge. While their populations get more diverse, urban governments are struggling with their newly emerging governance task around food system transformation towards health and sustainability. With this increasing urban diversity, residents from lower socio-economic positions and from ethnic minority groups appear to lag in healthy as well as sustainable diets, and are underrepresented in food policy development. These apparent inequalities pose challenges to the food system transformation needed at the urban level, and have led to the call for more inclusiveness in urban food systems. However, precisely what it means to be more inclusive appears not to be very well defined. This thesis therefore explores dynamics of in- and exclusion that occur within and through social practices around food, i.e. food consumption and governance practices. The primary empirical context for studying these questions is the Dutch city of Almere. Theoretically, the thesis primarily builds on social practice theories and additionally uses Manuel Castells’ network theory of power. Methodologically, the thesis relies on a mix of primarily qualitative methods. The thesis concludes that inclusiveness is elusive: what constitutes in- and exclusion is nuanced and dynamic as it is negotiated in a variety of everyday food practices. To realize more effective urban food governance, it is essential to observe more closely what is happening in the diverse urban food consumption practices across all citizen groups, to ultimately indicate multiple pathways of transition to a healthier and more sustainable food system. It is necessary to look for alternatives to the formalized food governance practices that better align with the variety of current and future food consumption practices.
... Such product categories have higher sales turnover, however, consumer decisions in these situations are largely habitual in comparison with durable items (e.g. electronics) (Verplanken and Wood, 2006). Hence, these products can be considered low-involvement goods that arouse lesser degree of consumer interest than that of high-involvement goods (Estelami and De Maeyer, 2004;Kuenzel and Musters, 2007;Mittal and Lee, 1989). ...
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The information gap between businesses and consumers concerning the sustainability impacts of products and services is considered a key obstacle impeding sustainable consumption. To that end, mobile technologies such as QR codes have been identified as a useful tool that may bridge this information gap by providing consumers with sustainability-related product information at the point of purchase. However, the literature offers scarce insight into the factors that influence consumers' intention to use QR codes for sustainability-related product information in daily consumption decisions. The present paper investigates this relationship in two studies of consumer acceptance of QR codes. Study 1 utilises the Technology Acceptance Model to study the factors that may affect consumers' intention to scan QR codes with sustainability information. The results showed that the perceived ease of use and perceived usefulness of the QR codes were significant predictors of consumers’ attitudes toward and intentions to scan the QR codes. Further analysis showed that QR code visuals and written appeals may also affect scan intention. The extant literature lacks evidence from investigations of real-life behaviour. Study 2 contributes to this gap in the literature by investigating the usage of QR codes in a field experiment. The results showed an overall scan rate of 4.22% for the QR codes, with consumers scoring high on perceived usefulness of QR codes, perceived sustainability quality of the product and preference for using QR codes in the future. Importantly, QR codes with a suggestive appeal were scanned at higher rates than that of QR codes without such appeal. The paper thus responds to calls for research on how companies can leverage marketing innovations using technology to communicate sustainability-related product information to consumers and stimulate sustainable consumption.
Objectives A key challenge for behaviour change is by-passing the influence of habits. Habits are easily triggered by contextual cues; hence context changes have been suggested to facilitate behaviour change (i.e., habit discontinuity). We examined the impact of a COVID-19 lockdown in England on habitual consumption of sugar-sweetened beverages (SSBs). The lockdown created a naturalistic context change because it removed typical SSB consumption situations (e.g., going out). We hypothesised that SSB consumption would be reduced during lockdown compared to before and after lockdown, especially in typical SSB drinking situations. Design In two surveys among the same participants (N = 211, N = 160; consuming SSBs at least once/week) we assessed the frequency of SSBs and water consumption occasions before (Time 1), during (Time 2) and after lockdown (Time 3), across typical SSB and water drinking situations. We also assessed daily amount consumed in each period, and perceived habitualness of drinking SSBs and water. Results As predicted, participants reported fewer occasions of drinking SSBs during lockdown compared to before and after, especially in typical SSB drinking situations. However, the daily amount of SSBs consumed increased during lockdown, compared to before and after. Exploratory analyses suggest that during lockdown, participants increased their SSB consump¬-tion at home, especially if they had stronger perceived habitualness of SSB consumption. Conclusion These findings suggest that SSB consumption is easily transferred to other situations when the consumption context changes, especially for individuals with strong consumption habits. Habitual consumption may be hard to disrupt if the behaviour is rewarding.
Purpose.This research contributed to the customer decision-making style (CDMS) theory in the online framework (eCDMS) to unravel new orientations and segmentation to generate marketing innovation strategies for the new normal firms.Methodology. It is based on a literature review designing a model and questionnaire applied to 400 Mexican online customers (May-Aug, 2021). The dataset is analyzed under Covariance-Based Structural Equation Modelling (CB-SEM), Cluster Analysis, and one-way-ANOVA multivariate methods. Findings and Originality.The obtention of an empirical model with 9 factors,24 indicators as new online customer decision-making styles orientations (eCDMS orientation), being quality, brand, and customer experience the most relevant. Besides, we obtained four new online customer groups (eCDMS Segmentation) that we called: marketing followers, price searchers, convenience shoppers, ethics& reputation keepers.The originality is based on a framework proposal about the discussion of new online consumers after the COVID-19 pandemic as the first insights to conform to an online customer decision-making style (eCDMS) theory.
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To illustrate the differing thoughts and emotion's involved in guiding habitual and nonhabitual behavior, 2,. diary studies were conducted in which participants provided hourly reports of their ongoing experiences. When participants were engaged in habitual behavior, defined as behavior that had been performed almost daily in stable contexts, they were likely to think about issues unrelated to their behavior, presumably because they did not have to consciously guide their actions. When engaged in nonhabitual behavior,or actions performed less often or :in shifting contexts; participants' thoughts tended to correspond to their behavior, suggesting that thought was necessary to guide action. Furthermore, the self-regulatory, benefits of habits were apparent in the lesser feelings of stress associated with habitual,. than nonhabitual behavior.
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The present research examined whether individuals with more accessible attitudes have more difficulty detecting that the attitude object has changed. While being repeatedly exposed to photographs of undergraduates, participants either rehearsed their attitudes toward each photo or performed a control task. They then saw these original photos and computer-generated morphs representing varying degrees of change in an original. Participants in the attitude rehearsal condition required more time to correctly identify morphs that were similar to the original as "different" (Experiment 1) and made more errors in response to such morphs (Experiment 2). Experiment 3 revealed that participants with accessible attitudes perceived relatively less change; they were less likely to view a morph as a photo of a novel person and more likely to view it as a different photo of a person seen before. The costs and benefits of accessible attitudes are discussed.
Research in transportation, urban design, and planning has examined associations between physical environment variables and individuals' walking and cycling for transport. Constructs, methods, and findings from these fields can be applied by physical activity and health researchers to improve understanding of environmental influences on physical activity. In this review, neighborhood environment characteristics proposed to be relevant to walking/cycling for transport are defined, including population density, connectivity, and land use mix. Neighborhood comparison and correlational studies with nonmotorized transport outcomes are considered, with evidence suggesting that residents from communities with higher density, greater connectivity, and more land use mix report higher rates of walking/cycling for utilitarian purposes than low-density, poorly connected, and single land use neighborhoods. Environmental variables appear to add to variance accounted for beyond sociodemographic predictors of walking/cycling for transport. Implications of the transportation literature for physical activity and related research are outlined. Future research directions are detailed for physical activity research to further examine the impact of neighborhood and other physical environment factors on physical activity and the potential interactive effects of psychosocial and environmental variables. The transportation, urban design, and planning literatures provide a valuable starting point for multidisciplinary research on environmental contributions to physical activity levels in the population.
The authors analyze results of 389 BehaviorScan® matched household, consumer panel, split cable, real world T.V. advertising weight, and copy tests. Additionally, study sponsors—packaged goods advertisers, T.V. networks, and advertising agencies—filled out questionnaires on 140 of the tests, which could test common beliefs about how T.V. advertising works, to evaluate strategic, media, and copy variables unavailable from the BehaviorScan® results. Although some of the variables did indeed identify T.V. advertising that positively affected sales, many of the variables did not differentiate among the sales effects of different advertising treatments. For example, increasing advertising budgets in relation to competitors does not increase sales in general. However, changing brand, copy, and media strategy in categories with many purchase occasions in which in-store merchandising is low increases the likelihood of T.V. advertising positively affecting sales. The authors’ data do not show a strong relationship between standard recall and persuasion copy test measures and sales effectiveness. The data also suggest different variable formulations for choice and market response models that include advertising.
INTRODUCTION, Many of the motivational challenges in daily life recur at routine intervals. For example, most appetitive drives (e.g., hunger, sleep) are cyclic, and people act to address them at certain times of the day in certain circumstances. Many other goals, such as getting to work or achieving physical fitness, also involve periodic activities that occur in specific, recurring times and places. This regularity in motivated behavior organizes everyday experience into repeated patterns of goal-directed activities in particular circumstances. With repetition of behavior in stable contexts, actions become automatic in the sense that deliberation about behavior becomes unnecessary. These well-practiced behaviors represent habits, and in this chapter we consider the role of habitual behavior in motivational processes. A role for habits in motivated behavior was outlined early in classic learning theories, which specified how habits emerge from previous motivated responding and how they structure subsequent motivated responding. For example, Hull (1943, 1950) believed that habits are stimulus— response (S—R) linkages that develop when a given response is reinforcing because it successfully reduces a drive state such as hunger or thirst. This reinforcement increases the association between the stimulus and the response and thereby increases habit strength. Thus, habits orient people to repeat activities that have in the past successfully met motivational needs.
Making choices, responding actively instead of passively, restraining impulses, and other acts of self-control and volition all draw on a common resource that is limited and renewable, akin to strength or energy. After an act of choice or self-control, the self's resources have been expended, producing the condition of ego depletion. In this state, the self is less able to function effectively, such as by regulating itself or exerting volition. Effects of ego depletion appear to reflect an effort to conserve remain ing resources rather than full exhaustion, although in principle full exhaustion is possible. This versatile but limited resource is crucial to the self's optimal functioning, and the pervasive need to conserve it may result in the commonly heavy reliance on habit, routine, and automatic processes.
The authors analyze results of 389 BehaviorScan® matched household, consumer panel, split cable, real world T.V. advertising weight, and copy tests. Additionally, study sponsors-packaged goods advertisers, T.V. networks, and advertising agencies-filled out questionnaires on 140 of the tests, which could test common beliefs about how T.V. advertising works, to evaluate strategic, media, and copy variables unavailable from the BehaviorScan® results. Although some of the variables did indeed identify T.V. advertising that positively affected sales, many of the variables did not differentiate among the sales effects of different advertising treatments. For example, increasing advertising budgets in relation to competitors does not increase sales in general. However, changing brand, copy, and media strategy in categories with many purchase occasions in which in-store merchandising is low increases the likelihood of T.V. advertising positively affecting sales. The authors' data do not show a strong relationship between standard recall and persuasion copy test measures and sales effectiveness. The data also suggest different variable formulations for choice and market response models that include advertising.