Communication Theory ISSN 1050-3293
ORIGINAL ARTICLE
A Re-Explication of Social Norms,
Ten Years Later
Rajiv N. Rimal1 & Maria K. Lapinski2
1 Department of Prevention and Community Health, The George Washington University, Washington, DC, USA
2 Department of Communication, Michigan State University, East Lansing, MI, USA
We revisit some ideas from our previous article on social norms by conceptualizing norms
as dynamic entities that both affect and are affected by human action; elaborating on the
distinction between collective and perceived norms; summarizing key findings from studies
that have adopted the theory of normative social behavior (TNSB) and thereby proposing
guidelines for further expanding the purview of the TNSB; discussing the attribute-centered
approach as a framework for focusing on behavioral characteristics; and highlighting areas
for further inquiry into social norms.
Keywords: Social Norms, Descriptive Norms, Injunctive Norms, Collective Norms, Theory
of Normative Social Behavior.
doi:10.1111/comt.12080
Social norms are not static phenomena, lurking in the background, ready to pounce
on individuals contemplating action; they both affect and are affected by human
action. A number of sociologists and anthropologists acknowledge the cultural
evolution of norms (Campbell, 1965; Ingold, 1985), thereby according norms a bit
more fluidity, but they, too, view norms as the seed of, not as being susceptible to,
influence. Another conceptualization, from game theorists, views norms as structures
that are “built up from the choices of rational, self-interested individuals” (Boyd &
Richerson, 1994, p. 73), and the implication here is that norms are adaptive to the
self-interested actions of individuals. The modality through which these actions take
place are inherently communicative in nature (Real & Rimal, 2007), which is why
this concept is of critical importance to communication scholars.
Ten years ago, we published an article (Lapinski & Rimal, 2005) in this journal that
described normative influences through a communication lens. Our central assumption was and continues to remain that, at their core, norms are communication phenomena. Indeed, a special issue of this journal was dedicated to this topic (Yanovitzky
& Rimal, 2006). In this article, to celebrate Communication Theory’s 25th volume, we
Corresponding author: Rajiv N. Rimal; e-mail: [email protected]
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revisit several key ideas under the social norms umbrella. Our goal is not to conduct
a review of the literature on social norms, as others (Axelrod, 1986; Biel & Thøgersen,
2007; Lewis & Neighbors, 2006) have already done so. Rather, we seek to clarify some
concepts, make theoretical contributions to this literature, and propose research that
will push the literature in a new and meaningful direction.
At this point, to minimize ambiguity in meaning, we reiterate the difference
between norms, on one hand, and laws and traditions, on the other. Different from
laws, norms are socially negotiated and contextually dependent modes of conduct;
laws are explicitly codified proscriptions that link violations with their corresponding
punitive measures. Laws are not socially negotiated (although their enforcement
might be), whereas norms and their transgressions, by definition, are negotiated
through social interaction. This is an important criterion because it explains why
the same mode of conduct (e.g., littering) is acceptable in one social context (littered
environment) but not in another (clean environment; Cialdini, Reno, & Kallgren,
1990). Laws and norms can certainly reinforce each other. For example, smokers
may choose to refrain from lighting up in a public place for a number of reasons,
including legal (fear of being penalized) or normative (fear of being accosted by
someone in the vicinity), both of which lead to the same outcome (not lighting up).
At other times, the two may act in opposition to each other, as when underage college
students follow alcohol-drinking norms despite this behavior being illegal.
Traditions, like norms, are also socially negotiated, but they are more stable.
Indeed, stability and predictability are defining characteristics of traditions (Handler
& Linnekin, 1984). Willey and Phillips (1958) note, for example, that traditions
are characterized by “long temporal continuity” (p. 37), and one can conceptualize
traditions as the crystallization of norms enacted over an extended period of time.
In this conceptualization, norms often emanate from traditions, both guided by the
desire to maintain homeostasis, but norms are dynamic, shaped, and understood
through communication processes.
Social upheavals, when abrupt disruptions in the environment call into question
(or render ineffective) the utility of traditional modes of conduct, often highlight
the functional nature of norms in daily life. For example, during the sudden emergence of Ebola in West Africa in late 2013, behaviors considered normal—hugging
each other as a form of greeting or using elaborate burial rituals as a sign of “coming home” to one’s place of belonging (Gugler, 2002; Smith, 2008)—were no longer
deemed appropriate. The gravity of the life-and-death situation brought about by the
disease, coupled with uncertainly emanating from lack of proper normative information, created an environment conducive to confusion (Altman, 2014). To the extent
that norms evolve through social interaction, this public health crisis could be construed as an evolution accelerator, an event that greatly speeds up the formulation of
new or modification of existing norms.
In this article, we first update an idea we brought up in 2005—the distinction
between collective norms and perceived norms—that has been the subject of a number of articles (Alexy & Leitner, 2011; Carcioppolo & Jensen, 2012; Chia, 2010; Jensen
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& Bute, 2010; Lippman & Campbell, 2014; Mabry & Mackert, 2014; Park, Jung, &
Lee, 2011; Reeves & Orpinas, 2011; Shulman & Levine, 2012; Storey & Kaggwa, 2009).
Conducting a brief review of the literature on the use of the theory of normative social
behavior (TNSB; Rimal & Real, 2005), we then categorize the growing list of moderators in the relationship between descriptive norms and behaviors. Subsequently,
adopting the attribute-centered approach (Rimal, Lapinski, Turner, & Smith, 2011),
we discuss why (and how) theorizing about norms needs to take into account the
properties of the focal behaviors, and finally we propose a roadmap for the next generation of research on social norms.
Theorizing about social norms and delineating pathways of and conditions
under which they operate—the essence of this article—form a substantive part of
scholarship dedicated to understanding behavioral determinants. Recent years have
seen an increased scholarly interest in adopting a holistic approach in this endeavor
(Glass & McAtee, 2006), which includes incorporating a socioecological perspective
(Sallis, Owen, & Fisher, 2008) that lends primacy to the role of social factors in shaping
human behavior (House, 2002). This perspective has also been adopted in communication scholarship, where researchers place social context (Street, 2003; Viswanath
& Emmons, 2006) at the nexus of inquiry into behavior. This increased emphasis
to push the intellectual envelope beyond the exploration of merely individual-level
determinants of behavior is challenging on a number of fronts. It requires not just
the adoption of a multilevel perspective, an observation many researchers have made
(Hanitzsch & Berganza, 2012; Pan & McLeod, 1991), but perhaps of more relevance
to communication scholarship, it requires tapping into concepts able to connect
individual-level behaviors with their societal-level determinants.
The study of norms constitutes one pathway that can link individual-level cognitions, beliefs, and behaviors, on one hand, with macrolevel social contexts and determinants, on the other. After all, individuals’ insights about others’ perceptions and
behaviors in their social environment, pressures they perceive to conform, and their
decisions to act in certain ways are determined not only by factors impinging on them
at the individual level but also by macrolevel phenomena of which they may or may
not be consciously aware (Bandura, 1986; Glass & McAtee, 2006). In the literature
on social norms, this idea is captured by the distinction we have made previously
(Lapinski & Rimal, 2005) between collective and perceived norms.
Collective norms and perceived norms
Collective and perceived norms differ according to the level at which they are conceptualized and thus measured (Lapinski & Rimal, 2005): Collective norms operate
at the societal level or at the level of the social network, whereas perceived norms
operate at the individual level. The distinction between these two norms is important
for at least two reasons. First, collective norms may not be isomorphic with perceived
norms. Individuals’ perceptions about the collective norms in their community may
be at odds with the actual collective norms. Indirect evidence for this comes from
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studies showing the persistent mismatch between individual and collective opinion
(O’Gorman & Garry, 1976; Ross, Greene, & House, 1977). These findings point not
just to the existence of the mismatch between perceptions and reality, but more importantly, they show that this mismatch, far from being haphazard, is, in fact, systematic
and predictive of behavior.
Second, measuring collective norms represents a key challenge in this line of
work. In our earlier article (Lapinski & Rimal, 2005), we had cautioned against
aggregating individual-level perceived norms as the operationalization of collective
norms—mostly because, as noted above, individuals’ perceptions often diverge significantly from collective norms. An aggregation of individuals’ behaviors, however,
can serve as a proxy for collective norms. The sum total of individual behaviors
in a community is a good indicator of the collective norm in that community,
an idea captured by the concept of social exposure (Mead, Rimal, Ferrence, &
Cohen, 2014). For example, if the majority of parents in a village immunize their
children—measurement of which could come from clinical records—it would be
appropriate to surmise that the community has a supportive collective norm on this
issue. Similarly, per capital alcohol sales in a community could serve as a reasonable
proxy for the collective norms surrounding alcohol consumption in the community.
In these examples, individuals within the community may or may not harbor
accurate (or even be cognizant about) perceptions about the prevalence of the focal
behavior, but the social environment bounded by the collective behaviors often guides
their own behaviors. This operationalization of collective norms has been adopted in
at least two studies. In the first study, Rimal, Limaye, Roberts, Brown, and Mkandawire
(2013) measured collective norms around condom use in Malawi as the proportion
of individuals in a geographical area who reported using condoms. They found that
collective norms predicted individual condom use and that this influence was further
augmented by heightened interpersonal discussions around the topic. In the second
study, Lapinski, Kerr, Zhao, and Shupp (2015) operationalized collective norms as the
aggregated prevalence of actual behaviors of group members across trials in an experiment. They manipulated the presence of a financial incentive and sorted participants
based on initial cooperation levels, finding that both descriptive and collective norms
about donating to a financial pool predicted individuals’ own contributions.
Using the proportion of people in a community engaging in a certain behavior as
an indicator of collective norms requires researchers to define the area that constitutes
“the community.” Although this could be done on the basis of geographical, social, or
some other dimension, the decision should be theoretically based, similar to decisions
pertaining to the appropriate units of analysis in research. In some cases, the area may
be bounded geographically. It would make sense, for example, to use the geographical boundaries of a city to assess collective norms surrounding cigarette purchasing
behaviors, particularly when the city sets the sales tax, enforces laws against sales to
minors, or regulates the posting of no smoking signs in public places. For similar reasons, the area bounded by a college campus may serve as the appropriate geographical
unit for assessing collective norms surrounding student alcohol consumption.
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In summary, collective norms, operating at the societal level, signify the overall
social milieu within which behaviors occur. The extent to which behaviors are under
normative influence will be determined not only by the collective norms, but also
by people’s perceptions of these norms, also known as descriptive norms. Collective
norms likely constitute one of the drivers of descriptive norms, further enhanced
through communication processes, but this hypothesis has not yet been tested. The
relationship between descriptive norms and behaviors is at the crux of the TNSB
(Rimal & Real, 2005), a topic we turn to next.
The TNSB
The TNSB was formulated to highlight the idea that the influence of descriptive norms
on behaviors needs to be understood in the context of important moderators. The
inconsistent findings in the literature about the role of social norms in influencing
behavior (DeJong et al., 2006, 2009; Wechsler et al., 2003) provide important opportunities for conceptual development: They invite closer scrutiny about when and how
norms affect behaviors. The influence of norms on human behavior, after all, is contingent upon the copresence of a number of other factors, some of which have been
articulated in the TNSB (Rimal & Real, 2005).
Building on the work by Cialdini, Kallgren, and Reno (1991), who first provided
a clear distinction between injunctive and descriptive norms, the TNSB delineates
and tests specific hypotheses about the role of various moderators in the relationship
between descriptive norms and behavior. Subsequent theory building (e.g., Lapinski &
Rimal, 2005) and empirical work have identified other moderators, contextual factors,
and behavioral characteristics that can attenuate or enhance normative influences.
What follows is a brief discussion of some of the empirical findings pertaining to the
original moderators specified in the TNSB, consideration of moderators identified in
subsequent theorizing, and the categorization of the moderators for future research.
Descriptive norms’ influence on behavior is thought to occur because of people’s
motivations to do the right thing, which they surmise from their belief that most
others are engaging in the behavior (Cialdini & Trost, 1998). These norms promote
behaviors by providing information about what may be socially adaptive and are
believed to serve as a heuristic cue in guiding behaviors (Cialdini et al., 1990). They
have been shown to exert both a direct (e.g., Cialdini, 2007; Lapinski, Rimal, DeVries,
& Lee, 2007; Mollen, Rimal, Ruiter, & Kok, 2013) and indirect, through moderation
and mediation (Rimal, 2008), influence on behavior.
Injunctive norms, on the other hand, are thought to influence behavior because
of people’s motivations for affiliations with others (Cialdini & Goldstein, 2004). In
the TNSB, injunctive norms enhance the relationship between prevalence perceptions and behavioral response. Although empirical evidence supports this prediction
(Rimal, 2008; Smith & Louis, 2008), findings do not always conform to this pattern.
Studies of alcohol consumption have shown a direct effect of injunctive norms on
behavioral intent and no significant moderating effect of injunctive norms on the
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descriptive norm-behavior relationship (Rimal & Real, 2005; Woolf, Rimal, & Sripad,
2014). For handwashing, descriptive norms were found to be positively associated
with the behavior when strong injunctive norms were present, but descriptive norms
were negatively associated with the behavior in the presence of weak injunctive norms
(Lapinski, Anderson, Shugart, & Todd, 2013). The key here appears to be the fact that
others are not present to enforce the norms under threat of sanction.
Distinguishing injunctive and descriptive norms from other forms of normative
influence and testing for their unique effects is not uncontroversial. Revised formulations of the theory of reasoned action, for example, have failed to make distinctions
among these three types of norms (see Yzer, 2012 for a review). Yet, confirmatory
factor analysis evidence points to the fact that subjective, injunctive, and descriptive
norms can be operationalized separately and that each type of norm has an independent influence (Park & Smith, 2007).
Along with injunctive norms, outcome expectations and group identity constitute the other moderators originally specified in the TNSB (Rimal & Real, 2005). The
underlying idea in the theory is that people are likely to follow the group behavior if
they also believe that doing so will confer desirable benefits and that others they identify with engage in the behavior (Lapinski, Maloney, Braz, & Shulman, 2013; Rimal,
2008). In the TNSB, group identity has been considered a bidimensional construct,
comprising similarity and aspiration. Similarity is conceptualized as the extent to
which people perceive themselves to be alike, demographically and attitudinally, to
referent group members; aspiration is defined as the extent to which people desire to
emulate referent others (Rimal & Real, 2005).
Findings support the hypothesis that group identity moderates the relationship
between descriptive norms and behavioral intention (e.g., Glynn, 2012; Hogg & Reid,
2006; Lapinski, Anderson et al., 2013; Rimal & Real, 2005), with the effects of descriptive norms becoming stronger as group identity becomes more pronounced. But the
TNSB literature has also shown weak or inconsistent effects, depending on how group
identity is operationalized. In an experimental study that manipulated similarity of
referents by referring to others in the same (college students) or different (pregnant
women) category and examined intent to engage in physical activity, similarity was
found to moderate the effects of descriptive norms on self-efficacy but not on behavioral intentions (Rimal, Lapinski, Cook, & Real, 2005). Perceived similarity with referent groups, however, has been found to moderate the relationship between descriptive
norms and college students’ intentions to consume alcohol such that, when alcohol
consumption was prevalent (high descriptive norms), greater behavioral intentions
were exhibited by people who perceived higher levels of similarity with their referent
others (relative to those whose level of perceived similarity was low), but these effects
were weak, with less than 1% increment in explained variance (Rimal, 2008).
Expanding the purview of the TNSB
The TNSB was formulated as a framework that continuously invites further refinement through the addition of empirically tested mediators and moderators in the
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relationship between descriptive norms and behaviors. One study has shown, for
example, that injunctive norms and outcome expectations can both mediate and
moderate the descriptive norm-behavior relationship (Rimal, 2008).
Lapinski and Rimal (2005) expanded the theory by specifying an additional
moderator (ego-involvement) and describing the concept of behavioral attributes
(behavioral ambiguity and privacy). Subsequently, scholars have uncovered a number
of moderators in the descriptive norm-behavior relationship not specified in the
TNSB. This has presented us with a challenge as to how to categorize the growing
number of moderators in a theoretically compelling manner. In this article, we have
done so based on whether the moderators pertain to individual-level or group-level
phenomena.
Individual-level moderators
Involvement
Studies point to involvement as potentially a key variable in social normative influence. Göckeritz et al. (2010) found that high personal involvement attenuated the
relationship between descriptive norms and behavioral intention. Another study
(Lapinski, Zhuang, Koh, & Shi, 2014) delineated different forms of involvement
(value-relevant, impression-relevant, and outcome-relevant) across different behaviors (alcohol consumption, recycling, and fast food consumption) and found that
the nature of the relationship between value-relevant involvement and normative
influence varied according to the characteristics of the behavior under scrutiny, a
point we will return to later.
Self-monitoring
Low self-monitors tend to be influenced by their personal values and attitudes,
whereas high self-monitors tend to be influenced by the behavior of those around
them (Snyder & Gangestad, 2000). Although logic and theory appear to predict that
high self-monitors should be more susceptible to normative influence, the data to date
are not consistent with this prediction. Jang (2011) found, for example, that the association between descriptive norms and intention to drink was strengthened among low
self-monitors. In explaining this finding, Jang (2011) argued that high self-monitors
are likely to deviate from social norms when they believe the opposite norms (e.g.,
not drinking alcohol) could result in a more positive image and create more favorable
impressions, akin to findings reported by Blanton, Stuart, and Van den Eijnden (2001).
Self-efficacy
College students with high alcohol refusal self-efficacy not only moderate their
drinking, but they are also less affected by descriptive norms (Jang, Rimal, & Cho,
2013), while those who show low refusal self-efficacy tend to be more susceptible to
drinking on the basis of their perceptions about how many others are drinking (Jang
et al., 2013). This finding can also be explained from the perspective that having
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low self-efficacy is an undesirable state, one that most people feel uncomfortable
basing important decisions upon. Thus, when a behavioral decision is characterized
by feelings of low self-efficacy in the context of high descriptive norms, people are
more likely to be guided by the normative cue. In contrast, when self-efficacy is high,
people are likely more comfortable using the efficacy cue in decision-making, in
which case others’ behaviors may be less instrumental. This is the finding reported
by Jang et al. (2013), although the underlying mechanism being proposed here is
worthy of future empirical testing.
Other individual-level variables
Research is beginning to show that a number of other individual-level factors also
affect the norms-behavior relationship. Some of these include external monitoring,
people’s perceptions about how others facilitate or hinder their behaviors (Jang,
Rimal, and Cho (2011); social comparison tendency, people’s predisposition to compare themselves to others (Litt, Lewis, Stahlbrandt, Firth, & Neighbors, 2012); and
age, particularly being an adolescent (Donohew et al., 1999; Elek, Miller-Day, &
Hecht, 2006). Before we are able to make this latter case more definitively, however,
we need more studies that investigate the source of normative information that
adolescents use in making behavioral decisions. For certain behaviors, particularly
those that define membership into a peer group, normative information emanating
from their peers, but not from adults, may be more important for adolescents. In
other domains (e.g., making long-term career choices), normative information from
peers may be less instrumental.
Interpersonal- and societal-level moderators
Characteristics of social networks play a key role in initiating and reinforcing both
positive and negative (Donohew et al., 1999; Dorsey, Sherer, & Real, 1999) behaviors,
some of which are described below.
Group proximity
Neighbors et al. (2010) varied the social distance of reference groups and found that
when participants’ reference groups were proximal, normative influence on drinking behaviors was stronger. Woolf et al. (2014), who investigated high school athletes’
use of steroids as a function of their perceptions about use of steroids by others who
varied on social proximity (friends, teammates, college athletes, and professional athletes), reported similar findings: Norms emanating from those perceived to be most
proximal were strongest in influencing intention to use steroids.
Interdependence
Normative pressures have been considered a defining characteristic of collectivism (Triandis, 1994); personal behaviors are contingent on the will of the group
and conformity to normative pressure is a mechanism for maintaining harmony
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(Triandis, 1989). Normative influence should thus be stronger for those who are
more interdependent. Among group-oriented people, in comparison to those who
are more individualistically oriented, perceptions of high prevalence of a behavior
within their social group is associated with more positive attitudes toward the
behavior and stronger behavioral intentions (Lapinski et al., 2007). It may be that
individualistically oriented people identify with the minority (or perhaps disidentify
with the majority) and thus express attitudes and behavioral intentions that are
consistent with the minority (Lapinski et al., 2007).
Fear of social sanctions—particularly the fear of isolation—and the effect it
can have on behaviors constitutes another possible explanation for this finding.
When a society is built on interdependent social ties, bonds of reciprocity are
strongly entrenched (Miller & Bersoff, 1994). In such societies, because people are
dependent on others to meet their various needs, they themselves strive to meet
others’ needs—to “do their part”—so that, when they themselves are in need, they
can, correctly, expect to receive others’ assistance. Put another way, when people
are dependent on others, motivations to comply with others’ behaviors should be
stronger, in comparison to societies characterized by independent ties in which
people are less dependent on each other for their daily functioning.
The attribute-centered approach
In the behavior change literature, individual factors—as drivers of behaviors—have
garnered a great deal of scholarly attention; less attention has been directed toward
group and societal-level factors. Further, the nature of the behaviors itself has not
been thematically studied.
Another way of saying this is that, although we know a great deal about the characteristics of people, situations, and contexts in which behaviors are enacted, we know
far less about particular characteristics of behaviors themselves that make them more
or less susceptible to various types of influences, including influences of norms. For
example, behaviors characterized by high levels of uncertainty (Cialdini, 2001) are
typically susceptible to normative influence, whereas those enacted in private settings tend to be less so (Lapinski & Rimal, 2005). Indeed, even if one were to hold
constant all the known behavioral predictors, including the sociocultural context,
individual preferences and characteristics, and normative influences, as articulated
by the integrated behavioral model (Kasprzyk, Montaño, & Fishbein, 1998), behaviors
with different underlying properties would likely exhibit dissimilar patterns of change.
These underlying properties of behaviors are known as the behavioral attributes, and
the attribute-centered approach (Rimal et al., 2011) promotes the idea that, in order
to model the drivers of behavior with greater precision, one needs to take into account
the role of behavioral attributes that constitute the behavior.
Take, for example, behavioral privacy. Behaviors can be aligned on a continuum
defined by privacy at one end and openness at the other, corresponding, for example,
to condom use and participating in a protest march, respectively. In this example,
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behavioral privacy constitutes an important attribute that would score high for
condom use and low for the protest march. Similarly, behaviors can also be aligned
according to their monetary cost for enactment. Some behaviors, like exercising,
have little monetary costs associated with them, whereas others, like mammography
screening, are more expensive. Hence, monetary costs would constitute another
important attribute. The frequency with which the behavior needs to be enacted constitutes yet another attribute; immunization, for example, is often a low-frequency
behavior (it has to be enacted but just a handful of times in one’s life), whereas
regular glucose monitoring for diabetics is a high-frequency behavior. Similarly,
some behaviors are addictive and habit-forming, whereas others are not. Many other
attributes could be similarly described for various behaviors.
In the attribute-centered approach (Rimal et al., 2011), each behavior is
conceptualized to comprise a unique configuration of underlying properties
weighted according to their importance for the specific behavior. Applying this
attribute-centered approach to the study of norms entails identifying specific behavioral properties amenable to a norms-based change. For example, one hypothesis that
might emerge from this focus is that the influence of descriptive norms on behaviors
is stronger when the behavior is characterized by attributes that are social in nature.
Thus, holding other factors constant, one would expect behaviors performed in
the presence of other people (e.g., giving to charity in an open forum) to be under
greater normative influence, in comparison to the same behavior conducted in the
absence of others (privately giving to charity). Empirical evidence suggests that for
some behaviors (fast food consumption) public enactment of the behavior enhances
normative influence (Bagozzi, Wong, Abe, & Bergami, 2000), but the presence of
others did not enhance the effects of normative messages about handwashing in a
field-experiment (Lapinski, Maloney et al., 2013). The key difference between these
two studies appears to be the type of norm under scrutiny (subjective norms in the
first and descriptive norms in the second) as well as the visibility of the enactment of
the behavior to important others (present in the first and absent in the second).
The primary benefit of this attribute-centered approach lies in its ability to
facilitate theory selection. Once behaviors are categorized according to their primary
attributes, one can select the appropriate theory for bringing about change. Some
behavior change theories, including social cognitive theory (Bandura, 1986), for
example, are characterized by their assumptions about the primacy of human agency.
Normative considerations in these theories are only indirect. Other theories, including the theory of planned behavior (Ajzen, 1991), place rational decision-making at
the forefront, but they also make explicit allowance for normative influences. In the
mass communication literature, cultivation theory (Gerbner & Gross, 1976) posits
that people’s perceptions about the world are shaped by a combination of what they
see on television and what they experience in their daily lives—their mediated and
social lives, respectively. To the extent that their social lives are key, a norms-based
approach would likely be relevant for investigating how communication and other
agents shape people’s perceptions.
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Areas for further inquiry
Much of the literature on norms is based on the idea that behaviors are driven by and
not the drivers of norms. Researchers have not seriously considered the implications
of reversing the cause-effect linkage. Excessive drinking on the part of students, for
example, can drive their perceptions about the prevalence of this behavior among
their peers. Thus, students who drink excessively may develop exaggerated beliefs
about others’ consumption in order to rationalize their own drinking. This plausible
hypothesis has not been systematically tested in the literature. Indeed, the preponderance of cross-sectional studies in this area makes it difficult to draw definitive
conclusions. Although Cialdini et al. (1990, 1991) and others (Lapinski, Anderson
et al., 2013, Lapinski, Maloney et al., 2013; Rimal et al., 2005) have shown, through
experimental designs, that norms can be manipulated to induce behavioral outcomes,
their sustainability in community settings has yet to be determined.
As we have suggested in this article, researchers also need to conceptualize
norms in a more dynamic manner, making allowance for the possibility that events
in the environment shape norms and that individuals are discerning in adopting
some norms, ignoring others, and modifying still others. Periods of social upheaval,
when people have to formulate new norms out of necessity, provide important
opportunities to study how norms evolve.
Important theoretical issues also need further testing and elaboration. In the
TNSB, descriptive norms are conceptualized as the drivers of behaviors, with other
factors—pertaining to individuals, groups, situational contexts, and behavioral
attributes—identified as moderators in the relationship between descriptive norms
and behaviors. Although the role of collective norms has not been articulated in the
theory, we are suggesting in this article that descriptive norms themselves may be
driven, in part, by collective norms. This is a hypothesis worthy of testing.
Conditions under which the factors we have labeled as moderators, in fact, act as
moderators and conditions under which they take on the role of mediators (or both)
have also not received adequate attention. One could imagine, for example, that when
many in one’s social group engage in a behavior, people will perceive that others also
expect them to follow suit and that they will incur social sanctions if they do not.
This might be especially true if the particular behavior is part of the group’s identity.
For example, if most members in a fraternity characterized by heavy drinking view
drinking alcohol as a key feature of the group, then members will likely perceive strong
pressures to conform, which can in turn will increase individual level of consumption.
In this example, injunctive norms, being driven by both collective norms and descriptive norms, may function as a mediator in the relationship between descriptive norms
and behaviors. As noted previously, only one study (Rimal, 2008) has investigated this
hypothesis, but it needs further exploration.
From a practical perspective, more can be done in adopting a norms-based
approach in bringing about social change. A number of field experiments and
large-scale interventions have sought to change descriptive norms in order to affect
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behavior, with some success (Cialdini et al., 1990, 1991; DeJong et al., 2006, 2009;
Wechsler et al., 2003), but this field has been marked by studies that either do
not show anticipated behavioral outcomes or, when they do, fail to report results
from manipulation checks. Fewer studies have attempted to manipulate injunctive
norms—although the salience of the norm has been manipulated—and when they
have, the manipulations check is not reported (Lapinski et al., 2007; Smith & Louis,
2008). The importance for assessing the manipulated norms, as understood by participants, is not just methodological (so we know the strength of the manipulation);
practically, intervention designers would like to know which kinds of norms can be
successfully changed and which ones are more recalcitrant, so that they can adopt
suitable strategies. From the alcohol consumption literature, we know, for example,
that descriptive norms are amenable to change (Perkins & Berkowitz, 1986) and that
this change can result in behavioral modification (DeJong et al., 2006), but we have
not found evidence that interventions can successfully change injunctive or collective
norms in the same manner. It may well be that, because injunctive norms speak
to underlying values that others hold, they are less amendable to change, but that,
should they change, their effects on behaviors are more sustainable. This is another
hypothesis worthy of testing in future research.
Conclusion
Social anthropologists see social relations as the primary currency through which
social structures are created and sustained (Radcliffe-Brown, 1940). Within this
framework, norms are the socially negotiated and enforced rules of conduct that,
through prescriptions, proscriptions, and social sanctions, maintain the collective order. But norms are also dynamic phenomena and individuals, acting on
either self-interest or altruistic motives, continuously alter the normative contours.
Communication is central in this process because it is through communication
that members of a social group understand, negotiate, and accept (or reject) these
prescriptions, proscriptions, and social sanctions. This underlying idea, however, has
not received adequate attention in the communication literature. The extent to and
conditions under which different forms of communication affect the relationship
between norms and behaviors in an iterative manner are topics ripe for further
inquiry. We hope this article serves to stimulate additional inquiry into the issues we
have raised.
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