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Theory and effects in consu mer psychology
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Theor y and effects i n consumer psychology – 1

Theor y and effects in consumer psychology

Norbert Schwarz
University of Southern California
20 Oct 2020

Journal of Consumer Psychology, in press

Note. This is a commentary on a target article by Calder, Brendl, Tybout, and Sternthal as part of a JCP
Methods Dialog ue to appear in Jan 2021 . This version is the accepted manuscript prior to copy -editing
by the publisher.
Contact information: [anonimizat]

Theor y and effects i n consumer psychology – 2

Abstract . Drawing on Calder, Brendl, Tybout, and Sternthal’s (2021) discussion of constructs and variables,
I suggest that the verification approach’s focus on variables fosters a plethora of disconnected “effects”
and a dearth of integrative theorizing in consumer behavior research . I discuss how publication practices
and incentive structures are likely to contribute to these phenomena.

Science advances through conjectures and refutations (Popper , 1963 ). Scientists propose theories that
postulate relationships between concepts of interest . To test t hese conjectures , they derive testable
predictions and operationalize concepts into manipulable and measurable variables . Unfortunately ,
empirical tests have a limited vocabulary – they can say “No” to the theory when the data are
incompatible with the specific predictions derived from it and can say “Maybe” when the data are
compatible. They can never say “Yes” (that is, confirm the theory ) because future tests may reveal
incompatible observations, as Hume emphasized almost 300 years ago . Moreover, any finite set of
observations is compatible with an infinite set of different explanations, including ones that nobody has
yet thought of, as L eibniz had noted even earlier . This renders refutation the mo st informative outcome
and the best a theory can hope for is that it has not yet been refuted or replaced by a theory that can
account for a broader scope of observations . Because the odds of being wrong increase with scope, m ore
limited theories a re less vulnerable to refutation but enjoy th is security at the cost of increasing triviality
(Merton, 1949) .
In a nutshell, this was the philosophy of science presented in my first undergraduate social
psychology class , taught by Martin Irle (Irle, 1975) , in a social science department that made philosophy
of science, represented by Hans Albert ’s “critical rationalism ” (Albert, 1968) , a mandatory part of the
curriculum. The approach had t hree important corollaries. First, desirable explanations are general
explanations that cut across variables , contexts , and academic disciplines and generate a myriad of
predictions . Second, any theory worth thinking about is likely to be proven wrong – and that’s scientific
progress and something to welcome , whereas a desire to avoid refutation sends one on a path to triviality .
Third, data never speak for themselves. What they have to say depends on the question a theory poses ;
different questions will lead to different answers from the same data .
Lipton’s (2004) program of “inference to the best explanation” (IBE ) is compatible with the basic
tenets of this approach in terms of empirical testing and complements them with attempts to develop
criteria for selecting a “best” explanation from the set of candidates that have not yet been refuted. Lipton

Theor y and effects i n consumer psychology – 3

himself equates the latter piece of IBE with Peirce’s (1931) logic of abductive inference , writing that
inference to best explanation is “sometimes also known as ‘ab duction’” (Lipton, 200 7, p. 238) . This has
become the topic of some debate as Peirce (1931) saw the role of abductive inferences in the context of
discovery, describing it as “ the process of forming explanatory hypotheses” , whereas Lipton places it in
the context of justification (for diff erent perspectives, see Campos, 2011; McAuliffe, 2015; Nyrup, 2015 ;
for a comprehensive discussion of abductive inferences, see Magn ani, 2009 ). But as Calder, Brendl,
Tybout , and Sternthal (2021 ; henceforth CBTS ) point out in their target article , neither IBE nor critical
rationalism guide common research procedures and editorial policies in consumer research. Increasingly,
they also fail to do so in other areas of the cognitive and behavioral sciences. Instead, researchers are
more likely to encounter what CBTS describe as a “verification approach” (VA) , which most readers will
recognize as the tacit assumptions underlying many reviews (and perhaps their own practice ).
The core issues emphasized by the verification approach are relevant in any framework of
philosophy of science : Is the operationalization an adequate implementation of the theoretical concept?
Is it also compatible with known (!) alternative conceptualizations? Does the predicted pattern of effects
across multiple dependent variables ( including manipulation checks ) make known alternative
conceptualizations less plausible ? These are difficult issues because the number of possible alternative
explanations is only limited by the creativity of the explainer – and the more general the concept, the
easier it is to come up with some. To be on the “safe” side, the researcher can articulate a “theory ” that
is close to the operationalizations used . But t his constrains the theory’s scope and invites triviality . CBTS’s
description of Schwarz et al.’s (1991) findings as “the number -of-exemplars effect” highlights this tension
– it is an adequate description at the effect lev el but makes me wonder who would ever want to study
such a narrow thing? Alternatively, one can conceptualize in terms of the interplay of declarative and
experiential information in judgment, with the metacognitive experience of ease -of-recall being one of
many instantiations of experient ial information (including moods, emotions, bodily sensations , and the
fluency of mental operations). Feelings -as-information theory (for review s, see Schwarz, 2012 ; Schwarz &
Clore, 2007 ) does so, but its broader explanatory scope also makes it more fallible.
We chose Tversky and Kahneman’s (1973) availability heuristic as a starting point for the
exploration of metacognitive experiences because their robust findings had received broad attention
while suffering from a glaring ambiguity: Were the findings driven by how many exemplars people could
think of (a content -based judgment) or by how easily some examples came to mind (an experience -based
judgment) ? Tversky and Kahneman’s procedures were inconclusive for this question , whereas our

Theor y and effects i n consumer psychology – 4

procedures could pitch these possibilities against one another (Schwarz et al., 1991). But note that
conceptualizing the number -of-exemplars effect solely in terms of the availability heuristic would again
have limited the scope and the theoretical questions raised. T hinking is always accompanied by subjective
experiences . Hence, the relevance of understanding the interplay of declarative and experiential
information applies to all mental operations, not just the domain of frequency judgment: W hen do people
draw on thought content and when on their experience ? And how does one source of information qualify
what they infer from the other ? Framing the issue in these general terms invited the exploration of
numerous other phenomena driven by people’s use of their metacognitive experiences as a source of
information , from preference formation and judgments of truth to debiasing and the correction of
misinformation (for reviews, see Schwarz, 2015; Schwarz, Jalbert, Noah, & Zhang, 2021; Schwarz, Sanna,
Skurnik, & Yoon, 2007) ; it also highlighted the commonalities across diff erent sources of subjective
experience and their role in judgment and decision making (for reviews, see Schwarz, 2012; Schwarz &
Clore, 2007) .
Given the shortcomings of VA, which CBTS so clearly identify, one may wonder why it enjoys
enough popularity within consumer behavior research to be considered the dominant framework for the
relationship between theory and data ? I offer some conjectures.
Incentive structures and p ublication practices
The smaller the scope of one’s claim, the easier the claim can be defended and the less one needs
to deal with creative alternative accounts generated by one’s reviewers . This is pa rticularly tempting in a
field like consumer research, where the language of editorial letters suggests that editors and reviewers
tend to see themselves as (unnamed) co -authors , who “shape” the research by working with the authors
as a “team” that invests precious resources in a “joint” product . This approach to editing turns articles
into potpourris of different ex post perspectives on an “effect” , which puts the focus on the current
variable and possible ad hoc interpretations instead of the concept and its diverse implementations and
implications across many different variables . While this may contribute to an understanding of the
respective variable, it limits the contribution of the paper to a theory -driven program of research that
aims for more general insights. Alas, the only one reliably interested in the theoretical program is the
author, for whom a given set of studies is one building block in a larger argument. The potpourri produced
by the “team effort ” often thwarts this goa l and limits the intellectual impact of the paper.

Theor y and effects i n consumer psychology – 5

The narrow scope and low impact fostered by such publication procedures would usually be
detrimental to researchers ’ careers , which rest on the answer to a straightforward question: What do we
think about differently because this scholar worked on it? Variable X is rarely a good answer to this
question. In some fields, the difficult to evaluate criterion of an intellectual cont ribution has been replaced
with how often an author can place a paper in a defined list of “A” ( top) journals, often described as
“scor ing an A” . The smaller the field’s number of “A” journals, the higher the incentive s to avoid the risks
of broad scope and the more pressing the need to play along with whatever it takes to “score ”. Consumer
research is one of these fields , characterized by a remar kably small number of journals that “count ”, in
particular for junior faculty .
When “counting A’s” becomes central to career advancement, it can disincentivize the
development of a coherent conceptual framework . Theories of desirable scope can turn studies that are
new and exciting at the variable level into mere conceptual replications of one another at the conceptual
level , given that all test predictions derived from the same theoretical principle . Scoring an A is easier
when each variable can be presented as the next new thing. Honoring this insight, some well-intentioned
colleagues in consumer behavior repeatedly suggested that my students and I should not conceptualize
the effect of a new variable in terms of an overarching theory – they worried that it just wouldn’t seem
“new enough ” if we “admitted” that the same theoretical principles apply. A “new effect” with a new
catchy label would be more successful.
One consequence of chasing the next new thing , and hyping its unique ness, is a proliferation of
unconnected phenomena and a dearth of integrative theorizing that organizes them. The resulting
scarcity of cumulative knowledge further adds to the “anything goes” flavor of the colorful potpourris of
mini -explanations, unconstrained by whether a n ad hoc proposal is compatible with anything beyond the
current experiment , let alone with what else we know about the human mind. This makes conferences
stimulating (So many cute phenomena! ) but limits the impact of the work to the specific variables studied
and curtails its reception in neighboring fields . It also contributes to consumer psychology ’s standing as a
user rather than a producer of theories that inform thinking about human behavior across disciplinary
boundaries .
Focus on applied issues
In the famous dictum of Kurt Lewin ( 1943 ), there is nothing as practical as a good theory. Despite
this admonition, practice can proceed without theoretical understanding. Pharmaceutical companies, for

Theor y and effects i n consumer psychology – 6

example, have identified many compounds that effectively ameliorate medical conditions despite limited
understanding of the underlying mechanism ( Ban, 2006 ). The discoveries are serendipitous, the
mechanism shrouded in uncertainty, but the benefits real. The effectiveness of such comp ounds can be
tested without opening the black box. S uppose , for example, that you conduct a clinical trial to determine
whether a daily dose of atorvastatin reduce s the level of blood lipids. To do so, you need to administer
the intervention (a specified daily dose of atorvastatin) and measure the outcome ( blood lipids ). The
underlying process is of li mited interest for the trial, whereas the effect size loom s large . You also want to
know whether the intervention’s benefi ts can be obtained under the noise of naturalistic conditions and
you want to safeguard against severe side -effects. A lthough such investigations would benefit from a
theory of the underlying process , they can be completed by merely focusing on the treatment and
outcome variables. The same applies to the evaluation of many business interventions.
Notwithstanding lofty editorials and the theoretical ambitions of its founders , consumer behavior
research is at its heart an applied field, practice d in professional schools whose core mission (and revenue
source) is the education of competent business practitioners . As CBTS review, this is reflected in a
preference for the “right ” variables , preferably in the form of operationalizations that mirror shopping
environments or – better yet – a test in a field setting. T he main goal of a field study is t o ascertain whether
an effect can be observed under the noisy conditions of the intended domain of applicat ion. This is not
an exercise of theory testing – any effect is more likely to be observed in the absence of no ise than in the
presence of noise. Unless one has a theoretical rationale for how specific aspects of the application setting
would interact with the treatment, the observations are silent on conceptual issues . Indeed, t he routine
editorial request for showing robustness in a field setting is rarely accompanied by a specifi ed theoretical
rationale – but neither is th e request justified by saying, “ Show me how it helps the shop keeper”. Instead,
the distinct rationales of theory testing, application development, and implementation evaluation are
mingled in yet another potp ourri that mudd les the consumer research agenda . By failing to distinguish
between theory development and testing, the derivation and development of potential applications, and
the evaluation of their implementation, VA hurts theory, application, and practice.
It is also worth noting th e role of VA in the current discussion about the reproducibility of scientific
findings, from psychology to medicine and chemistry (Baker, 2016 ). The conceptual and methodological
tools of this discussion have been developed in the domain of clinical trials, where salient conflicts of
interest and selective reporting carr y the potential of hurting public health in the interest of corporate
success. While the variable focus is co mpatible with the primary goals of c linical trials , it also found its

Theor y and effects i n consumer psychology – 7

way into the discussion of the reproducibility of theory tests , where VA’s failure to distinguish between
concepts and their operationalization is a reasoning error that invites a plethora of misleading inferences
(for discussions, see Schwarz & Clore, 2016 ; Schwarz & Strack, 2014 ; Stroebe & Strack, 2014 ).
Change ahead?
CBTS seem (somewhat ) optimistic that the dominance of VA can be corrected. I hope they are
right . Their review of VA and its shortcomings has the potential to stimulate a fruitful discussion of the
issues; whether this is sufficient to initiate change despite the incentive structures noted above is another
question. But at least, exasperated authors can now refer to CBTS when the next reviews come in.
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