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Anti-social behaviour: profiling
the lives behind road rage
Anti-social
behaviour
Arch Woodside
Department of Marketing, Carroll School of Management, Boston College,
Chestnut Hill, Massachusetts, USA
Abstract
Purpose – The purpose of this paper is to propose that “social demarketing” campaigns need to
recognize unique sub segments of individuals engaging in behaviours having substantial negative
societal impacts.
Design/methodology/approach – Volume segmentation and extremely frequent behaviour theory is
applied to examining several unique sub segments among survey data (n ¼ 6,393) of Americans not
engaging and engaging in anti-social behaviour (“giving-the-finger”) to other motorists while driving.
Findings – Less than 2 percent of Americans are estimated to enact 40 percent of the total incidences of
“giving-the-finger” to other motorists; three unique sub segments of the chronic anti-social actors participate
in different lifestyles (including media usage behaviours) and each has unique demographic profiles.
Research limitations/implications – The study is based on two years of a national survey taken
in one country and self-reports only. The implications support the propositions of a general theory of
extremely frequent consumption behaviour.
Practical implications – Government demarcating programs are likely to increase in effectiveness
through tailoring a few strategies, rather than one, to influence unique segments of chronic anti-social
actors.
Originality/value – The paper provides individual-level analysis of chronic anti-social actors
engaging in road-rage related behaviours and compares them to one another as well as non-equivalent
comparison groups of actors not engaging in such behaviour; the paper describes the merits of
experience frequency segmentation.
459
Received December 2007
Revised February 2008,
April 2008
Accepted May 2008
Keywords Drivers, Individual behaviour, Individual psychology, Individual conflict
Paper type Research paper
“Social demarketing” refers to strategies attempting to influence individuals and/or
organizations to decrease or stop doing behaviours that harm themselves, others, or the
environment. This definition is intentionally broader than the one Engel et al. (1990)
propose and Comm (1997, p. 95) adopts; “demarketing refers to a deliberate attempt to
induce consumers to buy less in product classes where environmental impacts are most
severe.” The proposal for “social demarketing” builds upon but is broader than Kotler
and Levy’s (1971, p. 75) proposal that demarketing is a strategy that a firm may pursue
in some contexts:
[. . .] we define demarketing as that aspect of marketing that deals with discouraging
customers in general or a certain class of customers in particular on either a temporary or
permanent basis.
The author acknowledges the helpful comments and suggestions by Carol M. Megehee, Nicholls
State University, USA, and the anonymous reviewers of Marketing Intelligence & Planning on
earlier drafts of this paper.
Marketing Intelligence & Planning
Vol. 26 No. 5, 2008
pp. 459-480
q Emerald Group Publishing Limited
0263-4503
DOI 10.1108/02634500810894316
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Wall (2007) describes how the term, “demarketing,” has passed from the earlier
association with marketers’ attempts to reduce consumer purchases/use of
conventional products to a particular prevalence in the context of public health and
consumption patterns that threaten to have a serious impact on future generations.
Intervention programs aiming to decrease road rage behaviour are at the start-up stage
in the USA. For example, “In 1998, nine states introduced 26 aggressive driving bills.
To date, only two of these have been enacted: Arizona’s aggressive driving bill and the
Virginia Driver’s Education Requirement” (Rathbone and Huckabee, 1999, p. 7).
The social marketing literature (Andreasen, 1995, 1997; Bloom and Novelli, 1981;
Hastings and Haywood, 1991, 1994; Hastings et al., 1998; Kotler and Zaltman, 1971;
Laczniak et al., 1979; Levy and Zaltman, 1975; Manoff, 1985; Murray and Douglas,
1988) informs theory, research, and practice of social demarketing strategies.
MacFadyen et al. (1999, p. 1) emphasize, “Many social and health problems have
behavioural causes: the spread of AIDS, traffic accidents and unwanted pregnancies
are all the result of everyday, voluntary human activity.” MacFadyen et al. (1999, p. 5)
review important differences between social and commercial marketing:
Specifically, in social marketing the products tend to be more complex; demand is more
varied; target groups are more challenging to reach; consumer involvement is more intense;
the competition is more subtle and varied.
The aims of the present paper are modest and ontological. The focus is on proposing
and testing a property-space (Lazarsfeld, 1965) method for identifying and describing
potential target groups of individuals chronically engaging in anti-social behaviour.
The proposal is that such a research approach is useful to take before crafting influence
strategies in social demarketing programs. The aims do not include advancing a
general theory of social marketing strategies or testing the efficacy of specific social
demarketing strategies.
Following this introduction, the second section offers propositions that inform
testing a property-space paradigm for increasing understanding of who commits and
who does not commit anti-social behaviour. The third section defines anti-social
behaviour and reviews the literature on road rage behaviour that is pertinent to this
report. The fourth section is an exposition on extremely-frequent behaviour (EFB)
theory; it also includes formal statements of EFB theoretical propositions for testing
using property space analysis. The fifth section describes the field survey and method
for data analyses to examine the efficacy of the propositions. The sixth section presents
the findings including specific profiles of subsegments of groups of individuals
engaging in road-rage related behaviour. The final section presents conclusions,
limitations, and suggestions for further research.
Property space propositions of anti-social behaviour
Because extremely low income often relates to behaviours of interest in social demarketing
programs (e.g. chronic alcohol drinking, drug addiction, and gambling ( Jarvis, 1994;
MacFadyenet al., 1999)), this paper proposes and tests an income and anti-social behaviour
property-space paradigm for informing understanding of groups of individuals
chronically engaging in anti-social behaviour. The present paper proposes that
recognizing uniquely different subsegments of adults engaging in the behaviour
targeted for social demarketing programs is also a useful step in crafting strategies.
The present paper proposes and tests the seemingly obvious but often overlooked
propositions that:
.
engaging in a specific anti-social behaviour is not widespread in a population – the
majority does not engage in the anti-social behaviour of interest;
.
Twedt’s (1964) “heavy-half” proposition is extendable to anti-social behaviour – half,
or substantially less than half, of the individuals who do engage in an anti-social
behaviour commit two-thirds or more of the total of anti-social acts; and
.
not all individuals chronically engaging in an anti-social behaviour fit the same
profile – the lifestyles, including media exposure, of extremely low, low-to-high,
and extremely high-income segments of individuals that chronically commit
anti-social acts differ dramatically from each other as well as from the majority
of the population not engaging in the anti-social behaviour.
This paper profiles the lives of Americans who report chronically “giving-the-finger” to
other motorists while driving and comparing these motorists to other drivers. This
report provides a nation-wide (USA) examination of persons engaging extremely
frequently versus infrequently versus never engaging in this anti-social behaviour –
such lifestyle activities, interests, opinions, and media-usage information about
persons doing such behaviour may be useful for designing effective programs to
reduce the occurrence of such behaviour.
The focus here is on taking a group-based view of survey data – rather than a
variable-based approach in examining antecedents to chronic anti-social behaviour
(Crimmins and Callahan, 2003). This paper describes the:
(1) Demographic.
(2) Consumption constellation (Solomon and Buchanan, 1991) of using products
and services.
(3) The attitudes-interests-opinions.
(4) Media use of three segments of drivers:
.
drivers chronically engaging in giving-the-finger to other motorists;
.
drivers occasionally engaging in this anti-social behaviour; and
.
drivers reporting never engaging in this behaviour.
The research this paper reports is part of a larger study by Woodside (2007) focusing
on developing a theory of EFB for experience products (e.g. travel and tourism, dining
out, and attending the theater and/or social events):
Antisocial behaviour is just what it sounds like. It is behaviour that is contrary to the
standards of the society we live in. This behaviour usually involves ignoring the rights of
other people and instead being totally selfish. There is a disorder known as antisocial
personality disorder. Fortunately, this is not a very common problem. People who
occasionally behave in an antisocial manner do not have it. Some of the signs of this disorder
are:
breaking laws
lying to or conning others for fun or for personal benefit
being impulsive and not considering the results of this behaviour
picking on other people or getting in fights
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ignoring the safety of self or others
being irresponsible, not holding down a job or paying back money and
lacking remorse, not worrying about hurting other people (Health Topics, 2006).
Anti-social behaviour and road rage
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Antisocial behaviours are disruptive acts characterized by covert and overt hostility and
intentional aggression toward others. Antisocial behaviour can be identified in children as
young as three or four years of age. If left unchecked these coercive behaviour patterns will
persist and escalate in severity over time, becoming a chronic behavioural disorder
(Hanrahan, 2007).
dePasquale et al. (2001), Dula (2003) and Dula and Ballard (2003) review the literature
on road rage as one type of anti-social behaviour. In metropolitan areas, aggressive
driving and road rage seem to be of particular concern. Over three months in 1998,
Sarkar et al. (2000) analyzed cellular phone calls to the California Highway Patrol from
drivers in San Diego. They put 1,987 calls into five categories. They found that
20 percent of the calls were about drivers who were said to be speeding excessively;
25 percent were related to drivers mixing speeding with at least one other unsafe
behaviour; 27 percent were related to drivers weaving in and out of traffic and cutting
off other vehicles, but who were not speeding (usually in congested traffic); 12 percent
referred to drivers who were tailgating; and 20 percent referred to drivers who were
said to be perpetrating various types of road rage (the percentages include multiple
responses for the categories).
Willis (1999, p. 2), President of the American Automobile Association Foundation
for Traffic Safety (AAAFTS), reports, “For every aggressive driving incident serious
enough to result in a police report or newspaper article, there are hundreds or
thousands more which never got reported to the authorities.” Typing in “aggressive
driving” as a unified term on a common internet search engine, revealed 21,100 hits in
February 2003 (Dula, 2003) and 416,000 in November 2007. Similarly, a search for
“road rage” as a unified term revealed a staggering 173,000 hits in February 2003
(Dula, 2003) and 1,790,000 in November 2007 and 4.4 million in February 2008.
Granted a considerable redundancy occurs between searches for the two concepts,
and the results included web sites dedicated to spin-off themes, nonetheless, a great
public concern exists regarding these topics. In contrast, using the same unified terms,
a current search on a psychology journal database reveals only 29 works dedicated to
aggressive driving and 18 pertaining to road rage. Joint (1995) reports the results of an
AAAFTS sponsored survey of 526 UK motorists. Almost 90 percent of the drivers
report having experienced road rage incidents in the last 12 months and 60 percent
admit to losing their tempers while driving. It appears the majority of events occurred
during the day on a main road, and involved drivers under the age of 35 (Joint, 1995).
A 1997 Gallup Poll revealed that three out of four people felt drivers were more
aggressive today than they were five years ago (Insurance Institute for Highway
Safety, Highway Loss Data Institute, 1998).
Goehring (2000) relates results of a nationwide telephone survey sponsored by
NHTSA involving 6,000 drivers of all ages. About 75 percent, thought it important to do
something about unsafe drivers; 62 percent believed another driver’s behaviour had
been personally threatening in the last year; 61 percent felt enforcement of tailgating was
lacking; and 33 percent reported that driving is more dangerous now than one year ago.
The problem of aggressive driving in the USA has prompted a flurry of legislative action
in an attempt to curtail what the public perceives as a great danger (Dula, 2003).
Rathbone and Huckabee (1999) report that nine states introduced 26 aggressive driving
bills in 1998. Rathbone and Huckabee (1999) conducted a survey of 504 randomly
selected law enforcement offices in the 50 largest metropolitan areas in the USA and
received 139 responses. Of these, 54 percent believed road rage was definitely a problem
in their area while only 14 percent did not think it was a problem at all (Rathbone and
Huckabee, 1999).
Using a variable-based approach to analyzing four years (1997-2000) of national
(USA) survey data in the DDB Lifestyle Study, Crimmins and Callahan (2003) report
that giving-the-finger frequency relates negatively with age and education; males on
average report engaging in the behaviour more frequently than females. Crimmins and
Callahan find that household income and population density do not predict
giving-the-finger to other motorists. Using attitudes, interests, and opinions (AIO)
responses, they emphasize that lifestyle and values responses increase the ability to
accurately predict giving-the-finger frequency:
Controlling for age, gender, and education, the expected frequency of giving someone
“the finger” while driving is 32 percent higher among people who agree with any of
the following statements: “People should live together before marriage.” “I am in favor of the
legalization of abortion.” Road rage is not just the result of impetuous youthfulness, gender,
or lack of education [. . .] Road rage reflects our values (Crimmins and Callahan, 2003,
pp. 384-5).
Extremely frequent behaviour theory
EFB theory builds on prior theory of “property space” (Elman, 2005; Lazarsfeld, 1965)
and the “heavy half” proposition (Twedt, 1964; Cook and Mindak, 1984). Property
space analysis focuses on building and reducing multi-way contingency relationships
(tables) among antecedent and outcome variables. Property space analysis serves to
identify the possible existence of extreme cases, the possibilities of paradoxical
relationships, and explanations of such paradoxes. Variable-based data are often
treated as case-base data in property-space analysis; Bass et al. (1968) recommend
similar theory and research approaches for the field of consumer research.
Twedt (1964) illustrates the heavy half proposition by dividing 700 households from
the 1962 Chicago Tribune panel data reporting their weekly purchases. Twedt (1964,
p. 28) creates three groups (non-users, light, and heavy users) according to their
purchase rates for various grocery store products:
Arranging the purchasing households in order of purchase volume, and cutting the
households at the median purchase point (so that we have a “light using half” and a “heavy
using half”), it becomes apparent that one heavy half household is equal in purchase volume to
nine households in the light half [for lemon-lime beverages and colas for example; italics in the
original article]. Even the category with least purchase concentration – toilet tissue –
indicates that the heavy half of users purchase three times as much as the light half.
Cook and Mindak (1984) report very similar distributions using across 16 product
categories for data reported in the Simmons Market Research Bureau (1982) study. For
example, Cook and Mindak report that 15 percent of the households buy 81 percent of the
dog food; 15 percent buy 19 percent, and 70 percent buy no dog food. From Cook and
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Mindak’s report the heavy half index of buy-share/household-share for dog food is
81/15 ¼ 5.4 (similar to Twedt’s, 1964 finding of a heavy half index of 5.1 for dog food).
EFB theory includes:
.
building a property-space contingency table from one or a few antecedent variables
that are likely to influence the frequency of participating in a given behaviour; and
.
identifying extreme (X) household groups and groups of consumers not engaging in
the behaviour as well as light to moderate participants in the behaviour under study.
Figure 1 shows such a property space analysis.
Figure 1 shows seven groups of households by anti-social behaviour and income.
While analyses of more than seven groups are possible, the focus of the study is on
comparing the variances in antecedents for these seven groups. The study is an
application of Ragin’s (2000) view that not all variability is of theoretical interest and
that conjunctive statements are useful for describing antecedents and consequences of
behaviours of particular interest.
The study here adopts Penn and Zalense (2007, p. 171, italics in the original) view
that “1 percent folks can and do make a big difference in business or politics or the
social sector.” Profiles of such small big-impact segments increases understanding of
what drives their behaviour – unconsciously as well as consciously; such
understanding is often useful for planning effective intervention programs to
influence such behaviour – increase or reduce such behaviours or direct its influence to
affect other behaviours (e.g. “Soccer Moms” as one such unique group being influenced
to vote for President Clinton in the 1996 election through deep profiling of their AIOs
(Penn and Zalense 2007, p. xiii).
EFB behaviour theory includes a series of propositions:
P1.
X-behaviour households exist in a large population.
Behavior /
Income
0 times
Very low
Group 1
14.2 %
1 - 4 times
5 - 7 times
8 - 12 times
12 - 24 times
25+ times
Group 5
X-Givers
I0.4%
Low
Group 2
Moderate
High
49.1%
Group 4
Group 6
24.4 %
X-Givers II
(Non-equivalent
comparison
Group)
1.2 %
Group 3
10.5 %
Group 7
X-Givers III
0.2%
Very high
Figure 1.
Property space
configuration for “giving
the finger” to other
motorists while driving
Extreme
Notes: Percents in cells represent the distribution of US households based on DDB survey data, n = 6,392
This basic proposition extends from the heavy half proposition.Given that less than
20 percent of the households often account for more than 80 percent of the purchases of
many product categories, X-behaviour households are likely to exist – chronic
(i.e. ever-present, persistent, acute) behaviour happens for many different experience
categories. Less than 2 percent of the households accounting for 20, 30, or 40 percent
plus of total behaviour frequency is one metric reflecting X-behaviour.
An index of X-behaviour-share-to-household-share should compute to a size double or
higher than the heavy-half purchase-share-to-household share. Thus, while the dog food
heavy-half share indices are 5 þ , the X-behaviour-share index should be 10 þ in support of
the proposition that 2 percent of the households purchase 20 percent or more the dog food:
P2.
X-behaviour households include distinct sub-groups that differ among
themselves by demographics; consumption constellations; and lifestyle AIOs.
Not all X-behaviour households are alike. While other antecedents might be useful, this
study examines how income levels inform the creation of unique profiles of
X-behaviour sub-groups – X-behaviour Groups 1-3 in Figure 1. P2 serves to provide
contextual nuance as well as to replicate how additional antecedent and lifestyle
patterns relate to X-behaviour. Is X-finger-giving a young men’s activity among all
income levels or do older extremely high-income men and women also engage in such
X-behaviour? P2 is one example of addressing this issue and similar questions.
The demographic and lifestyle profiles of road rage drivers are open questions:
While the AAA authors note there is a profile of the lethally inclined aggressive driver –
“relatively young, poorly educated males who have criminal records, histories of violence,
and drug or alcohol problems” – road-rage scholars (and regular drivers) believe other
groups are equally represented in the less violent forms of aggressive driving. To some, it’s
tempting to look at this as a psychologically mysterious Jekyll-and-Hyde phenomenon; for
others, it’s simply attributable to “jerk drivers.” In reality, there’s a confluence of emotional
and demographic factors that changes the average citizen from mere motorist to Mad Max
(Vest et al., 1997, p. 28).
P3.
X-finger-giving households differ substantially from Group 4 households
(sometimes engage in the activity) and the non-equivalent comparison group
(Group 2) in their demographic, consumption constellations, and lifestyle
AIOs.
P3 takes a step toward controlling an important demographic antecedent (income) in
predicting that the three sub-groups of X-behaviour households each differ:
.
demographically and by lifestyles in the same manner or uniquely from groups
of households in the same respective income levels not engaging in finger-giving
as well as; and
.
households across all income levels who occasionally engage in finger-giving
behaviour.
P4.
Participating in other activities that likely relate to X-finger-giving provide
high-nomological validity (Peter, 1981).
Nomological validity refers to the degree of finding relationships among a set of
behaviours fitting a priori expectations, for example, the expectation is that
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X-finger-giving households also often report engaging in other anti-social behaviour
(e.g. “Flashed my lights at another motorist when annoyed with his or her behaviour
(frequency last 12 months)”).
Participating in the following activities by one or more X-finger-giving groups
should differ substantially from all four other groups:
.
One or more X-finger-giving groups should report higher average frequencies in
going to bars and taverns than households in the other groups.
.
“Gambled in a casino (frequency during the last 12 months)” should be higher for
the X-finger-giving groups.
.
“Went to an auto race (NASCAR, Formula 1, etc.) (frequency during the last 12
months)” should be higher on average for one or more X-finger-giving groups.
.
“Rented an X-rated movie (frequency during the last 12 months)” should be
higher on average for one or more of the X-finger-giving groups.
.
“Told a lie (frequency during the last 12 months)” averages should be higher for
X-finger-giving groups if telling lies is viewable as an anti-social behaviour.
Average participation should be lower for pro-social behaviours among
X-finger-giving segments in comparison to the other groups. Pro-social behaviour
likely includes the following activities:
.
“Sent a greeting card on a holiday (Christmas, Mother’s Day, etc.) (frequency
during the last 12 months).”
.
“Attended church or other place of worship (frequency during the last 12
months).”
.
“Went to a club meeting (frequency during the last 12 months).”
.
“Contributed to an environmental or conservation organization (frequency
during the last 12 months).”
.
“Did volunteer work (frequency during the last 12 months).”
X-finger-giving informants should report lifestyle AIOs indicating higher stress and
lower overall happiness than other households. For example, one or more
X-finger-giving informant groups should have significantly higher average
agreements with the following lifestyle statements compared to Groups 1-4 (Figure 1):
.
“I feel like I’m so busy trying to make everybody else happy that I don’t have
control of my own life.”
.
“I get more headaches than most people.”
.
“I dread the future.”
.
“I feel I am under a great deal of pressure most of the time.”
.
“There should be a gun in every home.”
P5a. The media habits (e.g. watching TV, reading the local daily newspaper) differ
among the different chronic finger-giving groups.
P5b. The media habits differ between chronic finger-giving and non-finger-giving
adults.
Assuming anti-social behaviour and heavy TV watching relate positively as the movie,
Taxi Driver, depicts, the expectation is that chronic giving-the-finger drivers watch
more TV and read the newspaper less than adults reporting never giving-the-finger.
Method
Data from national (USA) surveys made available from DDB World of Chicago – the
“DDB Life Style Study” (year 1997 and 1998) – provides the bases for examining
chronic finger-giving behaviour. The surveys in 1997 and 1998 include the activity
question, “Gave ‘the finger’ to someone while driving my car (frequency last 12
months)” with seven response levels to pick from: 1 (0), 2 (1-4 times), 3 (5-8 times), 4
(9-11 times), 5 (12-24 times), 6 (25-51 times), and 7 (52 þ times). The surveys collect
detailed information on the demographics and lifestyles of adults and households
living in the USA.
The data used in this study were gathered in an annual mail survey conducted by
Market Facts and funded by the DDB Needham advertising agency. Market facts uses
a stratified quota sampling procedure, beginning with a large list of names and
addresses acquired from commercial list brokers. Each year the study draws a sample,
counterbalanced along demographic characteristics to account for expected differences
in response rates, from the pool of approximately 500,000 individuals. Then the final
sample of approximately 5,000 individuals is drawn so as to best approximate the
“actual distributions within the 9 Census divisions of income, population density, panel
member’s age, and household size” (Groeneman, 1994, p. 4). Although this panel
under-represents the very poor, the very rich, transient populations, and certain
minority groups, several studies show that the data are an effective barometer of
mainstream USA (Keum et al., 2004; Putnam, 2000; Shah et al., 2001). The annual
surveys comprise 3,000-4,400 adult respondents – the useable numbers varying
annually. The response rates against the mail-outs range from 58 to 72 percent.
Findings
Figure 1 shows seven groups after cross-tabulating six income response levels by six
frequency levels of giving the finger to other motorists while driving. (Both x 2 and
analysis of variance indicate that giving-the-finger relates to level of annual income –
and the shape of the relationship holds for both full-time and part-time workers.
Participation in giving-the-finger is much less among respondents retired from working
(M ¼ 0.7, standard error (SE) ¼ 0.11, n ¼ 1,014) compared to full-time (M ¼ 2.6,
SE ¼ 0.24, n ¼ 3,728), part-time working respondents (M ¼ 1.8, SE ¼ 0.30, n ¼ 588),
and unemployed respondents (2.0, SE ¼ 0.23, n ¼ 1,062). The mid-value for each
possible response level was used in computing the means with a value of 60 assigned for
the 52 þ level – assigning a value of 52 or 58 provide the same direction and levels of
statistical significance as using a value of 60. Contrary to possible “that’s obvious”
expectations, giving-the-finger frequency does not have a linear positive or negative
relationship with level of annual income; the relationship is inverted “U” shaped for each
year that data are available.) However, the focus on extremely frequent (X) behaviour is
on identifying X behaviour groups and testing propositions of X behaviour theory and
not on the relationship between annual income and frequency of behaviour.
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The mean and proportion comparisons in this findings section are all significant
statistically at p , 0.001 levels. Analysis of variance and planned comparisons of
differences in proportions were used to test the propositions for statistical significance.
Support for P1: X-behaviour households exist
Extreme (X) behaviour for giving-the-finger 25 þ times annually includes less than
two percent of households. A total of 1.8 percent of households represents a 40.6
percent share of finger-giving frequency. The X-behaviour frequency share to share-of
households is above 20. Table I presents details of these findings.
The non-equivalent comparison group of households not engaging in finger-giving
behaviour with low-to-high incomes represent close to half of all households. From
Figure 1 and Table I note that just under three-fourths of all informants report not
engaging in this anti-social behaviour. The case can be made for focusing on
examining the 24 percent of the households who engage sometimes in finger-giving
behaviour (representing 59 percent of the frequency of the behaviour) – such
individuals may be more conscious and less programmed to automatically enact this
anti-social behaviour in comparison to chronic finger-givers. However, the focus in this
report is on EFB and the less than 2 percent of the total adult population chronically
enacting finger-giving to other motorists.
Support for P2: X-behaviour sub-groups are identifiable
X-finger-giving adults with extremely low incomes differ from moderate income and
extremely high income X-finger-givers in the consumption constellations and lifestyle
(AIO) responses. Profiling X-behaviour by these three income subgroups provides a
deeper understanding of finger-giving individuals than assuming that all finger-givers
are alike.
Segment
Table I.
Share of people and share
of giving finger
behaviour for
non-behaviour to extreme
behavior segments
Very low income no giving finger
Low to extremely high income no
giving finger
Extremely high income no giving
finger
All incomes and give finger
1-24 times
Low income extreme finger giver
Mid-income extreme finger giver
High income extreme finger giver
(A) Share of
people
(percent)
(B) Share of giving
finger behaviour
(percent)
B/A Index
14.2
0.0
0.0
49.1
0.0
0.0
10.5
0.0
0.0
59.4
8.4
28.2
4.0
100.0
2.4
21.0
23.5
20.0
24.4
0.4
1.2
0.2
100.0 (n ¼ 6,392 households)
Notes: Confirming the core extreme behaviour hypothesis, 1.8 percent of the population give
40.6 percent of the fingers to other drivers; a total of 74 percent of the population report never giving
the finger to other drivers
Figures 2-4 show conjunctive-stream demographic trees showing extremely low,
moderate, and extremely high-income individuals who all chronically give-the-finger to
other motorists. Note that a number of branches include no leaves at the end – a
depiction of empty sets of no one on these branches chronically engaging in the
anti-social behaviour.
Note that in analyzing the three trees that about equal numbers of males and
females are chronic finger-givers for the extremely low and extremely high-income
groups. Only for the low-to-high income groups are chronic finger-givers more often
males versus females. The greatest number of chronic finger-givers appears in two
branches in Figure 3 – full-time working male under 31 with college educations and
full-time working males 31-50 with high-school educations.
All three trees include very sparse-leaf branches for individuals 51 þ years. Might
chronic finger-giving decrease especially in the 2010s with the dramatic increases in
the large aging (. 60 years old) Baby Boomer population? While no definitive forecast
is possible from survey data across two years, the individual-level analysis is
suggestive that chronic finger-giving decreases as age increases.
Figure 5 shows consumption constellation information for behaviours expected to
differ among the seven groups. Figure 6 shows AIOs information that were expected to
differ for the seven groups as discussed in the statement of propositions.
Note that the averages for “Flashed my lights at other motorists when annoyed with
his or her behaviour” reflects prior expectations of being substantially higher for the
three chronic finger-giving groups in comparison to Groups 1-3 – the
non-finger-giving groups. Also the pattern of the averages for this item differs
within the three chronic finger-giving groups – highest for Group 7 and lowest for
Group 6. While the average for Group 4 (group sometimes giving-the-finger) is higher
Anti-social
behaviour
469
3
1
3
2
4
1
1
1
1
1
2
F PSN
H
Age
1
F P S N F PS N PSNF P S NF PSNF PSN F P SN F P SNFPSN F P SN FP SNF P SNFPSNFPSNFP SN
1
1
F
C
< 31
G
H
C
G
H
31-50
C
51+
Females
G
H
C
<31
G
H
C
31-50
G
H
F P SN F P SN
C
G
51+
Males
Key: H – high school degree or less; C – some college to college graduate; G – graduate school; R – retired; F – full-time employed; P – part-time;
S – self-employed; N – not employed, retired, homemaker
Note: Data for one individual is missing
Figure 2.
Demographic tree for
extremely low-income
extreme-finger-giver
individuals
MIP
26,5
3
1
1
3
1
5
7
1
1
2
2
3
7
9
8
2
1
1
1
1
470
1
1
1
1
2
1
1
F PSN
F P S N F PS N
P SN F P S N F P S N F PSN F PSN
1
F P SN F PSN F P S N F PSN F PSN FPSN F PSN F P SN
1
F P SN F P S N
1
1
F
Figure 3.
Demographic tree
for low-to-high income
extreme-finger-giver
individuals
H
C
Age
<31
H
G
C
G
H
C
31-50
G
H
G
H
CG
H
31-50
<31
51+
Females
C
C
G
51+
Males
Key: H – high school degree or less; C – some college to college graduate; G – graduate school; R – retired; F – full-time employed; P – part-time;
S – self-employed; N – not employed, retired, homemaker
4
2
1
1
1
1
F P SN
F P S N F P S N F P SN F P S N F P S N F PSN F P SN F P SN F PSN
F P S N F P S N F P S NFPSN F PSN F P SN
F P SN F P S N
1
Figure 4.
Demographic tree for
extremely high-income
extreme-finger-giver
individuals
H
C
Age
<30
G
H
C G
31-50
Females
H
C G
51+
H
C
<30
G
H
C G
31-50
H
C
G
51+
Males
Key: H – high school degree or less; C – some college to college graduate; G – graduate school; R – retired; F – full-time employed;
P – part-time; S – self-employed; N – not employed, retired, homemaker
Note: Data for one individual is missing
than for Groups 1-3, the differences among these four means are not statistically
significant.
Note in Figure 5 that four pro-social behaviours – going to church or other places of
worship, doing volunteer work, attending club meetings, and sending greeting cards
30
Flashed my lights at
another motorist
when annoyed with
his or her behavior
Average Frequency of the Behavior
Attend church or other
place of worship
25
Sent a greeting card
on a holiday
20
Telling a lie
Anti-social
behaviour
471
15
Went to a bar or tavern
Did volunteer work
10
Casino gambling
5
Went to auto races (NASCAR)
Rented an X-rated movie
Went to club meeting
0
1
2
Extremely Low
Income and No
Finger-Giving
Low-to-High
Income and
No FingerGiving
3
4
5
6
7
Groups
Sometimes
Extremely Low Low-to-High Extremely High
ExtremelyIncome and
Income and
Income and
High Income Finger-Giving
Extreme Fingerby
All
Extreme
Extreme
and No FingerGiving
Income Levels Finger-Giving Finger-Giving
Giving
Figure 5.
Consumption
constellations for chronic
finger-givers and other
groups – one or more
comparisons of average
frequency across groups
significant statistically by
analysis of variance mean
comparisons for all ten
behaviours
Average agreementwith Attitude,Interest,or Opinion
Note: p < 0.001
+3
I am in favor of legalized
abortions
I feel that I am under a
great deal of pressure
most of the time
+2
+1
I feel like I’m so busy
trying to make everybody
else happy that I don’t
have control of my own
life
0
There should be a gun
in every home
−1
I get more headaches
than most other people
−2
−3
I dread the future
1
2
3
4
5
6
7
Groups
Extremely Low Low-to-High ExtremelySometimes Extremely Low Low-to-High Extremely High
Income and
Income and High Income Finger-Giving Income and
Income and
Income and
No FingerNo Finger- and No Finger- by All Income
Extreme
Extreme Extreme FingerGiving
Giving
Giving
Levels
Finger-Giving Finger-Giving
Giving
Note: p < 0.001
during holiday periods, all receive substantially higher levels of activity for the three
non-finger giving groups (Groups 1-3) in comparison to the three chronic finger-giving
groups (Groups 5-7). Attending auto races, renting X-rated movies, going to bars and
taverns, and telling lies are more frequent activities with one or more of the chronic
Figure 6.
The average agreement
with AIOs for the three
chronic finger-giving
groups and other groups –
one or more comparisons
of average agreement
across groups are
significant statistically by
analysis of variance
means for all six AIOs
MIP
26,5
472
finger-giving groups in comparisons with the non-finger-giving groups. (Details of
means, standard deviations, sample sizes, and confidence intervals are available from
the author by request ).
Supporting P3: chronic finger-giving groups differ substantially from occasional
finger-givers
While the averages between the sometimes give-the-finger Group 4 and the chronic
finger-giving Groups 5-7 often do not differ significantly statistically, the pattern of the
responses are clear. One to three of the chronic finger-giving groups have higher or
lower averages substantially for nearly all comparisons for consumption constellations
in Figure 5 and for the AIOs in Figure 6.
Supporting P4: high-nomological validity
Supporting activities that have the potential to harm others – such as advocating a
gun in every home – should find high agreement with one or more chronic
finger-giving groups in comparison to the other groups given the unpleasantness
implied by the finger display. Other potentially violent-oriented anti-social physical
actions – such as flashing vehicle lights at other drivers found to be annoying –
should occur more frequently with one or more chronic finger-giving groups in
comparison to the other groups given the both actions reflect the same anti-social
behaviour context. Both findings receive strong support in the findings. Figures 5 and
6 show details.
The relationships for each of the lifestyle behaviours in Figure 5 and the AIOs in
Figure 6 and the seven incomes-by-finger-giving segments are highly statistically
significant ( p , 0.000). Note that high frequencies of telling a lie and “went to bar or
tavern” are similar across all three extreme finger-giving segments in Figure 5. All
three extreme finger-giving segments have substantially higher average frequencies
for “flashed my lights at another motorist when annoyed with his or her behavior”
compared to the other four segments.
In Figure 6 two stress-related AIO items differentiate the three extreme
finger-giving segments from the other four segments. Attempts to create effective
intervention programs to control anti-social behaviour such as finger-giving
likely will need to explicit focus on managing stress among persons engaging in
extremely frequent finger-giving behaviour. Effective stress reduction strategies
may differ across the three income sub-segments of extreme finger-givers but
the general focus on managing stress appears to be relevant for all three
sub-segments.
Supporting P5: anti-social behaviour and media habits
Both parts of P5 receive substantial support for one specific group of chronic
finger-givers in regards to TV viewing versus newspaper reading – the extremely
low-income chronic finger-givers. This one group (Group 5) reports watching the most
number of weekend TV slots and 91 percent report that TV is the main source of daily
news; 19 percent of Group 5 report reading most or all of the business section of the
daily newspaper (the lowest share among the seven groups). Figure 7 shows further
details.
91
TV is my main source
of daily news (phi = .15)
I subscribe to basic cable
TV service (phi = .08)
7
70
Mean
Number
Weekend
6 TV Viewing
slots (number
watched)
60
Percent agreeing
Anti-social
behaviour
91
50
5
40
4
473
Read most or all
of the business
section of the
newspaper
(phi = .18)
30
20
3
Radio is my
main source
of daily news
(phi = .15
2
4
10
1
2
Extremely Low
Income and
No FingerGiving
Low-to-High
Income and
No FingerGiving
3
4
5
6
7
1
Groups
Extremely Low Low-to-High Extremely High
Sometimes
ExtremelyIncome and
Income and
Income and
High Income Finger-Giving
Extreme FingerExtreme
Extreme
and No Finger- by All Income
Giving
Finger-Giving Finger-Giving
Levels
Giving
Note: p < 0.0001
About one-third of the largest extreme finger-giving segment (Group 6) reported that
“radio is my main source of daily news,” a share substantially higher than all other six
groups. Figure 7 shows that cable television reaches 91 percent of extremely
high-income finger-givers by less than half of the extremely low-income finger-givers.
These findings indicate greater effectiveness is likely from a nuanced media program
rather than using the same communication media to communicate to extreme
finger-givers.
The findings in Figure 7 serve to emphasize the distinctiveness of each of the three
chronic finger-giving groups from each other as well as the non-finger-giving groups.
For example, the share bias favoring weekend TV watching among the three chronic
finger-givers versus the three comparable non-finger-giving groups varies
considerable.
Figure 8 is a Venn diagram showing the conjunction of extremely frequent lifestyle
behaviours that relate negatively to extremely frequently giving-the-finger to other
motorists. This analysis represents a qualitative comparative analysis (QCA) using
Boolean algebra to show the union of two or more behaviours (using the symbol “· ”) and
the absence of a behaviour (using the symbol “ , ”). QCA is an individual (case-based)
analysis that permits the constructions of antecedent profiles leading to outcomes of
particular interest (Ragin, 2000). For example, the single largest group of extremely
frequently giving-the-finger motorists include low-to-high income informants not
engaging extremely frequently in any of the three lifestyle behaviours (n ¼ 31).
Figure 7.
Media habits of seven
groups
MIP
26,5
V = Extremely Frequently
Doing Volunteer Work
0+1+1=2
474
C = Extremely Frequently Attending
Church or Other Religious Service
0
0+5+0=5
0+3+0=3
0+4+0=4
0+5+0=5
Figure 8.
Conjunctive analysis
of individuals extremely
frequently doing three
lifestyle behaviors
(relating negatively
to giving the finger)
by income level and
giving-the-finger to other
motorists
11+ 31+ 4 = 46
12 + 26 + 7 = 45
G = Extremely Frequently Sending
Greeting Cards for Holidays
Notes: Numbers all reflect extremely frequent giving-the-finger behavior; the conjunction of V· C · ~G indicates sufficiency for notengaging
in extremely frequently giving-the-finger to other motorists; 46 of the informants engaging extremely frequently in giving-the-finger to other
motorists do not engage extremely frequently in any of the other three behaviors. The first of the three numbers added together represents
extremely low-income frequently giving-the-finger motorists, the second number represents the low-to-high income extreme finger givers,
the third number represents the extremely high income extreme finger giver
The conjunction of extremely frequently performing volunteer (V) work, attending
religious (R) services, and not extremely frequently sending greeting (G) cards (V · R ·
, G) represents an empty set of extremely frequently giving-the-finger to other
motorists. Thus, these results are suggestive that successfully nurturing community
organizational participation – reach out programs, programs inviting individuals to
become new members – may likely be effective antecedent actions in reducing
behaviour symptomatic of road rage.
The QCA conjunctive analysis in Figure 8 shows a case-based alternative to the
variable-based study of interaction effects (i.e. empirical positivistic approach) of the
influence of antecedents on an outcome. While considering a variable-based approach
of the main and interaction influences of frequency of volunteering, attending religious
services, and sending greeting cards has merit (e.g. explaining variance in a dependent
variable such as behaviour frequency), QCA conjunctive analysis is particularly useful
for indentifying and profiling people performing extreme behaviour – a main objective
of the present study.
Figure 9 is a QCA analysis that shows the conjunctions of informants
frequently performing three lifestyle behaviours relating positively with extremely
frequently giving-the-finger to other motorists. The majority of informants
extremely frequently giving-the-finger report telling lies frequently in association
with either or both going-to-bars-and-taverns and flashing lights at other motorists
found-to-be-annoying. Programs successfully promoting honest, free-from-lying,
communications are likely to relate to decreases in behaviour symptomatic to
road rage.
Discussion, limitations, and suggestions for further research
Descriptions and recommendations for using “backward segmentation” have a long
history in the marketing literature (Assael, 1976; Assael and Roscoe, 1976; Wells, 1968).
Anti-social
behaviour
F = Flashed my lights at other driver
when annoyed with his or her behavior
(frequency > 9)
L = Told a lie
(frequency > 9)
3 + 9 + 2 = 15
0+4+1=5
0+1+1=2
1 + 8 + 1 = 10
1+0+1=2
2+4+1=7
1+3+0=4
1 + 10 + 1 = 12
475
B = Went to bar or tavern
(frequency > 9)
Notes: Numbers all reflect extremely frequent giving-the-finger behavior; the conjunction of F· L captures more extremely frequently givingthe-finger informants than any other combination of frequently performing two lifestyle behaviors in the survey (37/57 = 65%). The first of
the three numbers added together represents extremely low-income frequently giving-the-finger motorists, the second number represents
the low-to-high income extreme finger givers, the third number represents the extremely high income extreme finger givers
However, volume segmentation (Twedt, 1964) is one backward segmentation approach
to group and case level analysis (Bass et al., 1968; Ragin, 2000) that continues to receive
less frequent use in comparison to forward segmentation variable-based approaches
(e.g. segmenting initially by demographic or psychographic characteristics). While
forward variable-based research offers important insights into understanding,
describing, and predicting the frequency of behaviour, in-depth research on specific
groups of individuals who exhibit unique behaviours of interest is equally valuable –
especially if the aim ultimately is to influence people to adopt new behaviours or to
help prevent non-participants from engaging in a given behaviour.
Backward segmentation relies on individual-level analysis that avoids the
“ecological fallacy” (Clancy et al., 2004; Robinson, 1950). The ecology fallacy is the
drawing of inferences about individuals based on aggregate level data. Given that the
very few (, 2 percent) perform 40 percent of the giving-the-finger acts, an individual
case-based approach to examining the lifestyles including media behaviour of the very
few receives support. Individual-level analysis provides a more nuanced view than
reporting that chronic road rage behaviour associates negatively with annual income
and annual income associates positively with subscribing with basic cable television.
Nearly, all very-income chronic finger-givers report television as their main source of
daily news (not so for low-to-high income chronic finger-givers). Such depth of analysis
provides credence to the strategy of designing of a few (e.g. 3) behaviour and
communication change strategies that is rarely viewable from an aggregate level
analysis.
Giving the finger to other motorist is one symptom of road rage and such behaviour
is not likely to always occur in conjunction with more aggressive behaviour such as
ramming other vehicles while driving or throwing debris at other drivers. Additional
study of who commits different and multiple acts of behaviour symptomatic of road
rage is necessary before reaching definitive conclusions.
Figure 9.
Conjunctive analysis of
individuals extremely
frequently doing three
lifestyle behaviours
(relating positively to
giving-the-finger) by
income level and
giving-the-finger to other
motorists
MIP
26,5
476
Identifying subgroups chronically giving-the-finger to other motorists as well as
specific subgroups not participating in such behaviour can suggest plans for crafting a
reverse “blue ocean strategy” (Kim and Mauborgne, 2005) – a blue ocean strategy
frequently involves creating a business model to attract non-users of a product-service
category into new uses by offering exceptional value to a unique target segment.
Creating pro-social behaviours that match the behaviours of specific subgroups of
chronic anti-social behaviour groups and non-anti-social behaviour groups would be a
step toward launching a reverse blue ocean strategy. Thus, marketing and social
reform strategies to stimulate Group 5 to adopt behaviours of Group 1, Group 6 the
behaviours of Group 2, and Group 7 the behaviours of Group 3 reverses and extends
Kim and Mauborgne’s suggestions of attempting to convert non-users into users to the
social marketing strategy of converting anti-social actors into non-actors.
The media habits of distinct subgroups of chronic anti-social adults are likely to
differ in substantial ways. One media plan to reach chronic finger-givers in general is
very likely to be less effective in comparison to using unique media plans for each
subgroup. Given that the findings indicate that the demographic and lifestyles differ
substantially among the chronic finger-giving subgroups, creating unique messages
and intervention programs for each subgroup are likely to be a more effective influence
strategy than implementing a single marketing strategy.
Market segmentation is a strategic decision. While each chronic anti-social adult is
distinct in several ways, most fit into a limited number of distinct subgroups. Just as
one profile does not fit all and the strategists should identify subgroups, crafting a
property space with limited number of chronic subgroups, occasional users, and a few
non-user subgroups is a very useful backwards segmentation strategy. The
substantial prevalence of chronic finger giving among the conjunction condition that
includes males with a high-school education who are working full-time is indicative
that stress management programs need to recognize that this segment is likely to be a
highly relevant client base. Previous research focusing on the aggressive driving
supports such conclusions. For example:
Age was found to have a negative relationship with driver stress and aggression in several
studies. Matthews et al. (1991) found that age was negatively correlated with several
dimensions of driver stress. Older drivers generally reported lower overall levels of stress.
Younger drivers reported a higher rate of aggression and more negative reactions about
being overtaken and overtaking other cars. These findings replicated previous research
conducted by the same investigators reporting that younger individuals report more daily
stress in driving during commuting [from and to work]. As a result of more stress, younger
drivers were seen to use more inefficient coping strategies (especially aggressive driving
behaviours) as compared to their older driving counterparts (Galovski et al., 2004).
Limitations in this report include the shortcomings of using one sample design in one
country and focusing exclusively on a single anti-social behaviour. The use of
self-report measures is another important limitation. The combination of direct
observation or independent confirmation of anti-social behaviour (e.g. via police
reports) combined with interviewing is worth consideration in future studies.
Replication studies using very recent data if available (e.g. 2007) are necessary to
confirm the findings in this report and the findings in Crimmins and Callahan (2003)
report. The present report examines the latest data made available as of 2007 in the
annual DDB Lifestyle Study.
Future research should include examining the efficacy of implementing alternative
demarketing “social reform experiments” (Campbell, 1969) – testing their relative
degree of effectiveness on well-defined subgroups of chronic anti-social adults. Rather
than advocating one social marketing program as best, the crafting and testing of
“competing hypotheses” (Armstrong et al., 2001) of what well work well to change the
behaviour of each subgroup is likely to increase knowledge and effectiveness about
pro-social intervention programs.
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Anti-social
behaviour
479
MIP
26,5
480
Further reading
Cook, T.D. and Campbell, D.T. (1979), Quasi-experimentation: Design and Analysis Issues for
Field Settings, Houghton-Mifflin, Boston, MA.
About the author
Arch Woodside is a Professor of Marketing, Boston College. He is a Fellow of the Royal Society of
Canada, the American Psychological Association (APA), the American Psychological Society,
the Society for Marketing Advances, and the Institute for the Study of Tourism Research. He is a
Past-President of Division 23, Consumer Psychology, of the APA. He has authored and
co-authored 175 articles in 35 academic journals in the fields of psychology, sociology,
marketing, travel and tourism, advertising, decision sciences, and retailing. Arch Woodside can
be contacted at: woodsiar@bc.edu
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