Chemical Risk Assessment Traditional vs PublicHealth Perspe

Chemical Risk Assessment: Traditional vs Public
Health Perspectives
Preventing adverse health ef-
fects of environmental chemical
exposure is fundamental to pro-
tecting individual and public he-
alth. When done efficiently and
properly, chemical risk assess-
ment enables risk management
actions that minimize the in-
cidence and effects of environ-
mentally induced diseases related
to chemical exposure. However,
traditional chemical risk assess-
ment is faced with multiple chal-
lenges with respect to predicting
and preventing disease in human

populations, and epidemiological
studies increasingly report obser-
vations of adverse health effects
at exposure levels predicted
from animal studies to be safe
for humans. This discordance
reinforces concerns about the
adequacy of contemporary risk
assessment practices for pro-
tecting public health.
It is becoming clear that to
protect public health more effec-
tively, future risk assessments will
need to use the full range of
available data, draw on innovative
methods to integrate diverse data
streams, and consider health
endpoints that also reflect the

range of subtle effects and mor-
bidities observed in human pop-
ulations.
Considering these factors,
there is a need to reframe
chemical risk assessment to be
more clearly aligned with the
public health goal of minimizing
environmental exposures asso-
ciated with disease. (Am J Public
Health. 2017;107:1032–1039.
doi:10.2105/AJPH.2017.303771)
Maureen R. Gwinn, PhD, Daniel A. Axelrad, MPP, Tina
Bahadori, ScD, David Bussard, BA, Wayne E.
Cascio, MD, Kacee Deener, MPH, David Dix, PhD, Russell S.
Thomas, PhD, Robert J. Kavlock, PhD, and
Thomas A. Burke, PhD, MPH
See also Greenberg, p. 1020.
For the past several decades,human health risk assessment
has been a pillar of environmental
health protection. In general,

the products of risk assessment
have been numerical risk values
derived from animal toxicology
studies of observable effects at
high doses of individual chem-
icals. Although this approach has
contributed to our understanding
of overt health outcomes from
chemical exposures, it does not
always match our understanding
from epidemiology studies of the
consequences of real-world ex-
posures in human populations,
which are characterized by expo-
sure to multiple pollutants, often
chronically, at concentrations that
can fluctuate over wide ranges;
susceptible populations and life
stages; potential interactions be-
tween chemicals and nonchemical
stressors and background disease
states; and lifestyle factors that
modify exposures (e.g., airtight
houses).1 Theseandotherissuesare
particularly important when de-
termining risk of complex diseases,
such as cardiovascular disease.
Ten years ago, the National
Research Council offered a new
paradigm for evaluating the safety
of chemicals on the basis of
chemical characterization, testing
using a toxicity pathway ap-
proach, and modeling and ex-
trapolating the dose–response

relationship from in vitro testing,
all embedded in a risk context
and considering population-
based data and exposure.2 Efforts
such as the Tox21 Consortium3,4
and ToxCast program5 have
helped us better understand the
biological interactions of large
numbers of chemicals using
high-throughput assay systems,
and we are witnessing early
adoption of new technologies
and approaches for screening
chemicals for integrated testing.6
Several other factors are also
changing the way environmental
health professionals think about
chemical risks and how to most
effectively protect public health,
especiallyforcomplexdiseaseslike
cardiovascular disease. It is esti-
mated that intrinsic factors (e.g.,
those that result in mutations
stemming from random errors in
DNA replication) account for
only 10% to 30% of many com-
mon cancers.7 Similarly, only 30%
to 40% of birth defects can be
attributed to known causes such as
genetics, fetal alcohol syndrome,
maternal smoking, and folate in-
sufficiency.8 Other studies have
concluded that nongenetic envi-

ronmental factors and gene by
environment interactions are the
primary causes of chronic dis-
eases.9 The ability to evaluate and
quantifytheroleofenvironmental
factors on public health is a clear
opportunity, but it is limited by
thelack ofreadilyavailablemodels
for prominent clinical outcomes.
CURRENT
CHALLENGES
Understanding public health
risk from environmental chem-
ical exposures is complicated by
many factors, such as population
variability and susceptibility,
long latencies between critical
exposures and disease manifesta-
tions, and background environ-
mental exposures. Issues of
population variability and sus-
ceptibility are poorly understood
and difficult to characterize and
incorporate into risk assessments.
For example, a person’s unique
microbiome may modulate his or
her response to environmental
exposures.10,11 Although studies
are limited in this emerging area,
knowledge about the
ABOUT THE AUTHORS
At the time of the writing of this article, all of the authors were

with the US Environmental
Protection Agency, Washington, DC.
Correspondence should be sent to Maureen R. Gwinn, PhD
DABT ATS, Office of Research
and Development, US Environmental Protection Agency, 1300
Pennsylvania Ave NW, Ronald
Reagan Building, Room 41205, MC 8101R, Washington, DC
20460 (e-mail: gwinn.
[email protected]). Reprints can be ordered at
http://www.ajph.org by clicking the “Reprints”
link.
This article was accepted March 2, 2017.
doi: 10.2105/AJPH.2017.303771
1032 Analytic Essay Peer Reviewed Gwinn et al. AJPH July
2017, Vol 107, No. 7
AJPH RISK ASSESSMENT
mailto:[email protected]
http://www.ajph.org
microbiome may inform inter-
individual variability and un-
explained susceptibility observed
in populations. Scientists have
begun to appreciate the role of
the microbiome in the lack of
reproducibility and in-
terpretability of animal studies.12
Another example is the effects

of early life environmental
exposures on health outcomes
later in life. Advances in the field
of epigenetics have revealed that
developmental exposure to
endocrine disrupting chemicals
can alter epigenetic program-
ming of gene regulation and thus
may play a role in the risk of
obesity later in life.13 Similar to
microbiome research, studies in
this area are limited, and a better
understanding of the link
between chemical exposure,
epigenetic gene regulation, and
health outcomes through epide-
miological research can help us
better address factors that are
currently difficult to account for
in traditional risk assessment.
Finally, there are also methodo-
logical challenges in determining
attributable risks in populations
with background environmental
exposures, as these background
exposures may change the
populationhealthbaselinesoraffect
the response of the target chemical.
Other examples of important fac-
tors to incorporate in risk assess-
ments can be found in Table 1.
OPPORTUNITIES FOR
USING MULTIPLE
DATA TYPES

Concurrent with these chal-
lenges, science and technology
are advancing rapidly and in ways
that create opportunities for risk
assessment. Public health
disciplines help us understand
how baseline health status can
influence the effect of
population-level chemical ex-
posures. We also need to consider
how environmental pollutants
may contribute to overall disease
burden for endpoints not tradi-
tionally considered in chemical
risk assessment (e.g., metabolic
disorders, autism). New
methods in epidemiological re-
search help us evaluate complex
interactions among multifacto-
rial causes of disease ranging
from macro (societal, neigh-
borhood) to micro (molecular)
factors, relevance of exposures
during sensitive life stages, and
a better understanding of in-
terrelatedness of disease across
the life span.14
Advances in high-throughput
technologies and computational
modeling (e.g., ToxCast, Tox21,
and ExpoCast efforts) are
providing data on hazard and

exposure potential for a large
number of data-poor chemicals.
The increased generation of data
for both hazard and exposure
from these advances can be used
to better understand the bi-
ological pathways that lead to
adverse health effects in ways that
were not possible in the past. But
linking these observations to
specific disease endpoints is
challenging because the trans-
lation of effects across levels of
biological organization is not well
understood. One approach with
the potential to advance our
understanding of how chemical
exposures can affect health is the
use of adverse outcome path-
ways, which integrate various
types of biological information to
link molecular initiating events
to downstream key events and
ultimately unwanted health
outcomes.15,16
TABLE 1—Examples of Current Risk Assessment Challenges
and Opportunities
Risk Assessment Challenge Description Impact on Risk
Assessment Public Health Opportunity
Molecular initiating events and subsequent
key events in adverse outcome pathways

Earlybiologicalchangesor precursoreffects
in response to chemical exposures may be
identified by in vitro, animal, or
epidemiological studies
Useful for qualitative and quantitativ e
understanding of ultimate health effect of
early biological changes
Improved public health protection without
need for long-term toxicology or
epidemiology studies
Background exposures Population exposures to a myriad of
environmental chemicals at low
concentrations
Exposures to background chemicals may
affect response to target chemical
exposures and may change population
health baselines
Increased public health protection if

baseline exposures are taken into account
when determining prevention strategies
Nonchemical stressors Physical and psychosocial stressors,
including noise, temperature,
socioeconomic status, social stress, and
limited resources
Impact on baseline susceptibility and
potential effect modification
Potential role in cumulative assessment,
improved identification of vulnerable
populations, potential target for public
health interventions (e.g., stress
management)
Early life determinants of health Biological characteristics and
exposures
that can determine chronic and lifelong
health outcomes
Effect of exposures during early life may
play a role in later disease states (e.g.,

endocrine disruptors, epigenetic changes)
Potential for early life interventions for
prevention and management of later
disease
Baseline health status Individual health status, with a focus on
potential health susceptibilities
Baseline health status may affect response
to additional environmental chemical
exposures
Increased public health protection if
baseline health status is taken into
account
Microbiome Microorganisms that reside within and on
our bodies and interact with the
environment
Exposure modification, susceptibility and
resilience to environmental pollutants,
important as an early life determinant of

health
Potential targets for prevention and
intervention, management of allergic
responses, and precision risk management
July 2017, Vol 107, No. 7 AJPH Gwinn et al. Peer Reviewed
Analytic Essay 1033
To fully realize the potential
of adverse outcome pathway–
based approaches and to in-
tegrate biological findings across
disciplines, we must strengthen
our ability to detect precursor
events in human populations
and to identify biologically rel-
evant exposure metrics, ideally
measurable in individuals. An-
other advancement that has
a great potential to advance our
understanding of data-poor che-
micals is the use of nontesting
approaches (e.g., quantitative
structure–activity relationship)
that allow us to predict toxicity
when adequate testing data are
absent—especially when we

combine knowledge of chemical
structural features and in vitro
bioactivity determinations. Ad-
vances in the development
of chemical libraries,
cheminformatics, and
read-across predictions and in-
tegration with molecular data
and adverse outcome pathways
have significantly improved
their application and predictive
capacity, which will allow more
comprehensive assessment of the
health effects of exposures.17,18
Effectively predicting
population risk by integrati ng
a variety of data streams (e.g.,
epidemiology, toxicology,
high-throughput testing) and
considering multiple sources and
pathways of exposure can better
inform environmental public
health decisions. Advances in
technology and computational
capabilities have fostered new
opportunities for generating and
analyzing molecular, animal, and
human data on effects and ex-
posures, which can be integrated
TABLE 2—Data Streams and Opportunities and Challenges for
Informing Risk Assessment

Data Type Description Opportunity Challenge
Nontesting
data
Nontesting approaches, such as quantitative structure –
activity relationship models and read-across allow us
to predict toxicity when adequate testing data are
absent
Advances in the field have significantly improved
their application and predictive capacity
Developing principles for acceptance, for
characterizing and incorporating uncertainties into
predictions, and for developing objective metrics of
performance
Molecular Biochemical and cell-based bioactivity data and
“omics-
based” data on thousands of chemicals
Can help inform our understanding of the health
outcomes of environmental exposures, using data
that are potentially more human relevant

Lack of scientific consensus on inferring hazard from
bioactivity in vitro assay and omics-based data and
providing quantitative dose–response information
on exposure metrics
Animal Traditional animal testing provides a hazard based
point of departure for risk assessments
Targeted animal testing can be performed on the
basis of the results of bioactivity data to focus on
key health outcomes
Potential uncertainties with using traditional animal
testing to estimate human risk (e.g., extrapolating
from animal to human or high to low doses and
accounting for human population variability and
life stage susceptibility)
Human Epidemiological and other human data support holistic
assessment of the effects of chemical exposures on
public health
Newer exposure science and statistical techniques

advance the understanding of human variability
that can be obtained from epidemiology and
individual sequencing; understanding effect
modification by nonchemical stressors and baseline
health status
Often limited mechanistic and dose–response data,
and exposure misclassification can bias results to
the null; possibility of unmeasured confounders
often undermines confidence in observed
associations, and it may require multiple studies
and many years to rule out chance, bias, and
confounding as possible explanations for observed
associations
Exposure Exposure characterization that captured the variability
in time, space, and within and across populations;
better toxicokinetic data link external to internal
dosimetry and relevant environmental exposure
concentrations with biological significance

Targeted and nontargeted biomonitoring,
application of sensors, and other new technologies
are greatly advancing population exposure
characterization; high-throughput exposure
models allow exposure predictions on thousands of
chemicals with associated uncertainty
Estimating and incorporating the inter- and
intraindividual variability in exposures into current
designs of toxicity testing and risk assessments;
extrapolating relevant target tissue and organ dose
information from external exposures and in vitro
assays; accounting for multiple exposures; sample
collection, data management, and analysis; and
covering or extrapolating to a broader chemical
space
Digital data The ongoing revolution in social media use and
communication has provided a new source of data
used in exposure science and environmental

epidemiology for local and timely information about
disease and health dynamics
A significant source of untapped data The collection and
application of these data have
significant ethical implications that need to be
understood and managed, particularly taking
into account personal identifiable information;
methods to evaluate the quality of the data and
build confidence in the applications are needed
2017, Vol 107, No. 7
into chemical risk assessments.
At the same time, probabilistic
and high-throughput ap-
proaches for risk assessment have
been advancing. Table 2 high-
lights various data types available
and challenges in applying these
data types to inform risk
assessment.
A PUBLIC HEALTH

PERSPECTIVE
A public health perspective for
chemical risk assessment would
approach risk assessment from
a new lens. It would address
population health with a focus on
the health and societal burden of
disease; use and integrate all
available types of data—including
traditional toxicology, human
epidemiological findings, and
newer and emerging data
streams and information, such as
digital epidemiology,19 high-
throughput and high-content
data, and adverse outcome path-
ways; and draw on public health
approaches, such as attributable
risk or relative risk. This new
perspective may be especially
important for some historically
challenging aspects of risk assess-
ment, such as understanding
cumulative risks of exposures to
multiple chemical and non-
chemical stressors. Internationally,
scientists have raised concerns
about the large number of ubiq-
uitous chemicals people are
exposed to and called for re-
thinking approaches to evalu-
ating the health effects of
chemicals.16 Figure 1 presents
a conceptual model for a public

health perspective for risk
assessment.
Although approaching assess-
ments from the perspective of
health outcomes may be chal-
lenging, it provides the oppor-
tunity to evaluate exposures and
effects across the life span that are
relevant to population health.
Advances in science and tech-
nology, such as adverse outcome
pathway development, the
broader availability of chemical
and biological data, and the
applications of statistical and
bioinformatics tools, bring this
previously aspirational approach
well within reach.20
EXAMPLE:
CARDIOVASCULAR
DISEASE
A public health approach
may inform the challenge of
cardiovascular disease. Cardio-
vascular disease is the number 1
cause of mortality worldwide and
is a major US public health
burden.21,22 Annual costs of
cardiovascular disease in the
United States were estimated to
be $317 billion in 2011 and 2012,
considering direct medical costs

and lost productivity because of
premature mortality.22 This es-
timate is likely to substantially
underestimate the social cost
of cardiovascular disease
because of limitations in the es-
timation of indirect costs associ-
ated with morbidity and
premature mortality.23
Although much is known
about the biochemical and be-
havioral risk factors associated
with cardiovascular disease, par-
ticularly compared with other
diseases and health conditions,
the traditional risk factors fail to
account for 10% to 25% of its
prevalence.24 Environmental
factors, including air pollution25
and chemical exposures26 are
thought to contribute to the
unexplained fraction. Although
mortality stemming from car-
diovascular disease has decreased
over the past few decades in the
developed world as a result of
reductions in behavioral risk
factors, the rising prevalence of
obesity and diabetes might ac-
count for the deceleration in the
rate of improvement in annual
cardiovascular mortality in the
United States over the past
few years.27

There is an urgent need to
better understand the biological
pathways through which envi-
ronmental exposures to chemical
and nonchemical stressors act to
stimulate and accelerate athero-
sclerosis and promote adverse
cardiovascular health effects.
Applying the adverse outcome
pathway framework,28 the initial
molecular response to a chemical
exposure will often be receptor
Improved
public
health
Starting Point
• Adverse health outcome of
concern
Data Sources (along with those
used in traditional assessment)
• Clinical data on baseline
population health status
• Molecular epidemiology

• Exposure information in the
population
• Behavioral data
Synthesis
• Chemical/nonchemical
stressors contributing to the
adverse outcome
• Prevention strategies
Public Health Perspective
Starting Point
In context of a statutory authority
• Chemical or class of concern
• Route(s) of exposure
Data Sources
• Epidemiology studies
• Laboratory animal studies
• Mechanistic data
Synthesis

• Multiple health outcomes of
concern
• Toxicity values for specific
chemical/endpoint
• Output/risk metric: absolute
estimate of risk in population, or
safety assessment (e.g., hazard
index)
Traditional Risk Assessment
Note. This conceptual model illustrates how the starting point in
a public health–focused risk assessment would differ from
that of traditional risk assessment. In traditional risk
assessment, the starting point is focused on specific chemicals
or
classes of chemicals of concern, with multiple data streams
saying what the critical effects from that chemical are. A
public health perspective would focus on the adverse health
outcome of concern with multiple data streams, informing
our understanding of hazard and exposure in the context of
public health decisions related to that outcome and not
necessarily focused on just 1 chemical or class of chemicals.
FIGURE 1—Conceptual Model for a Public Health Perspective
for Chemical Risk Assessment

Analytic Essay 1035
activation and changes in meta-
bolism and, ultimately, changes
in tissue and organ function. Such
changes can be modified by
both intrinsic (e.g., gender, age,
genetic, and epigenetic back-
ground) and extrinsic factors
(e.g., coexposures to other
chemical and nonchemical
stressors; Figure 2). Over time,
these changes produce subclinical
effects, such as changes in elec-
trical and mechanical cardiac
function, vascular function, and
nonobstructive atherosclerotic
vascular changes. With the per-
sistence of metabolic changes
that stimulate the progression of
vascular disease, clinical cardio-
vascular events such as heart at-
tacks, strokes, heart failure, and
abnormal heart rhythms follow.
To date, the most compre-
hensive application of this ap-
proach has been in the study of
population-level health effects
of air pollution exposure.28
Epidemiological data at the

population level has provided
support that air pollutant
exposure (e.g., ambient particular
matter and NO2) accelerates the
development and progression
of coronary atherosclerosis.25
Xenobiotic metals such as arse-
nic, cadmium, lead, and mer-
cury are also associated with
atherosclerosis.29 Gene–
environment interaction alters
the risk of vascular disease30; for
example, the residential proximity
to highways (representing ex-
posure to a mixture of traffic-
related air pollutants) is associated
with peripheral vascular disease,
which is modified by the gene
encoding bone morphogenic
protein.7,31
Because of the complexity of
the drivers of atherosclerosis,
a medical model treating blood
pressure and high cholesterol and
advising dietary modification and
exercise will be inadequate to
fully address this disease. Like-
wise, identifying the chemicals
that increase risk on an individual
basis will be inadequate to pre-
vent vascular disease. Instead an
integrated systems approach is

Atherosclerosis
As TCDD
BaP Phthalate
PCB PM2.5
Cd
PCBs
TCDD
InflammationPlaque Growth
Chemical
Exposures
z
Oxidative Stress
Adipokine
Dysregulation
Dyslipidemia
Insulin
Resistance
Hyperglycemia

Myocardial Infarction Stroke
As
Cd
PCB
TCDD
BPA
BaP
Endothelial
Dysfunction
As
Cd
BPA
PM2.5
PCBs
TCDD
DEHP
PFOS
As

Cd
PM2.5
TCDD
Phthalates
PCBs As
TCDD Cd
PFOS BPA
PM2.5
Age
Gender
Family
History
Diet
Smoking
Physical
Inactivity
Emotional
State
High BP

High LDL
Low HDL
Diabetes
Obesity
R
is
k
F
a
c
to
rs
f
o
r
A
th
e
ro
sc
le
ro
si

s,
C
a
rd
io
v
a
sc
u
la
r
D
is
e
a
se
, a
n
d
C
a
rd
io
v

a
sc
u
la
r
E
v
e
n
ts
Clinical
Intrinsic
Behavioral
A
d
v
e
rs
e
O
u
tc
o

m
e
P
a
th
w
a
y
(
A
O
P
)
Clinical
Events (AO)
Biochemical
and Physiologic
Responses (IKE)
Cellular
Response (IKE)
Environmental
Exposure
Subclinical
and

Clinical Responses
(IKE)
Molecular
Initiating Event
Public Health
Burden Mortality – Morbidity – Disability – Frailty
As PFOS
PCBs PM2.5
Individual Health
Burden
Source. Action of specific chemicals and metals adapted from
Kirkley and Sargis.26
Note. As = Arsenic; AO = adverse outcome; BaP =
benzo[a]pyrene; BPA = bisphenol A; Cd = Cadmium; DEHP =
di(2-ethylhexyl) phthlate; DES = diethylstilbestrol; HDL =
high-
density lipoprotein; IKE = intermediate key event; LDL = low -
density lipoprotein; PCB = polychlorinated biphenyl; PFOS =
perfluorooctane sulfonic acid; PM2.5 = particulate
matter £ 2.5 mm; TCDD = tetrachlorodibenzo-p-dioxin.This
figure illustrates the biological pathway leading from exposure
to adverse cardiovascular outcomes for a variety
of chemicals. On the left-hand side of the figure these pathways
are linked to the adverse outcome pathway, and on the right-
hand side of the figure we see the traditional
risk factors for adverse cardiovascular outcomes.
FIGURE 2—Adverse Outcome Pathway for Cardiovascular

Outcomes
2017, Vol 107, No. 7
needed to fully account for all
known risk factors and formulate
the problem to define the most
effective strategy to decrease in-
dividual risk and societal burden.
Accomplishing this will require
clinical data that fully reflect
a population under consideration
as well as exposures to traditional
risk factors, biomonitoring data
documenting exposures to mul-
tiple chemicals, and molecular
responses from in vitro and
in vivo studies indicative of
the activation of biochemical
pathways that accelerate
atherosclerosis.
Although this approach might
not be practical currently, it is not
unrealistic to think about future
states where it could become
standard practice. Our proposed
innovative approach to chemical
risk assessment is occurring
contemporaneously during the
formative stages of the National

Institutes of Health–sponsored
Precision Medicine Initiative,
which will drive integration of
genomics, data sciences, and
bioinformatics as the basis for
improved individual health care,
disease prevention, and public
health. The Affordable Care
Act has accelerated electronic
medical record adoption in
health care practices and hospital
systems, potentially offering
a valuable source of information
for population-level health
monitoring. Recent research has
used big data to study the early
stages of disease and better classify
and predict disease progression
and could be used to inform
personalized medicine to
optimize wellness in healthy
populations.32–34
Moreover, the anticipated
integration and development of
technologies and analytical tools
have the potential to improve
public health and increase the
spatial and temporal resolution of
environmental health
surveillance. The establishment
of a long-term representative
precision medicine cohort, if
integrated with the proposed
National Biomonitoring Net-

work,35 could have enormous
benefit in helping us understand
the relationship between chem-
ical exposures and disease and
in managing some of the most
challenging clinical problems
more effectively.
Applying this framework
would potentially expand our
understanding of the origins of
vascular disease and its progres-
sion, helping define strategies
for primary prevention to thwart
the initiation of the process we
ultimately call atherosclerosis.
Thus, such a framework would
provide new and ongoing
insights into the associations
between environmental expo-
sures that contribute the greatest
burden to public health. This
approach would facilitate ac-
counting for sensitive pop-
ulations and could inform
suggested individual health or
behavioral measures in which
there have been past exposures
or in which current exposure
cannot be reduced enough to
protect those most at risk.
CONCLUSIONS
The proposed conceptual
model is grounded in public

health principles and focused on
identifying the greatest oppor-
tunity to reduce environmental
exposures to improve health
outcomes. Along with traditional
risk assessment, this perspective
can better inform public health
decision-making. Although
there are clear benefits to
operating within a public health–
focused framework and moving
away from individual chemicals
and apical endpoints, there are
also challenges.
Informing Decision-
Making
Since the 1980s, the Envi-
ronmental Protection Agency’s
decision-making has been
grounded on traditional risk as-
sessments that are conducted
within the constraints of the
Environmental Protection
Agency’s statutes and programs.
Although program-targeted risk
assessments will remain an im-
portant component, the disease-
based approach draws on
information in a holistic fashion
that cuts across organizational and
legal boundaries, integrating
traditional inputs and newer data
streams. These assessments will
provide decision-makers with

critical information to inform
exposure-reduction efforts to
affect the selected health out-
comes and, ultimately, improve
public health. Because those
exposure-reduction efforts
would take place within the
existing statutory construct, an
important implementation step
would be to move from findings
of disease-based risk assessments
to assessments of specific risk
management actions under the
relevant statutory authorities.
Priorities for Screening
and Testing
A health outcome–focused
framework can inform priorities
for screening and testing the
toxicity of chemicals. Efforts to
develop and synthesize ap-
proaches for screening large
numbers of chemicals using
high-throughput toxicity testing
and exposure prediction should
continue to provide data for
data-poor chemicals. For
example, in the recently an-
nounced Cancer Moonshot,36
high-throughput approaches
could screen a large set of
chemicals for potential carcino-
genicity and identify a suite of

chemicals for additional animal
toxicity testing.
Examining noncancer end-
points will also be challenging,
which is why developing adverse
outcome pathways and networks
to contextualize and interpret
nonapical hazard data in relation
to population health is of in-
creasing value. Epidemiology
studies can be designed to inform
and validate high-throughput
testing approaches by identifying
both chemical stressors and
nonchemical stressors that mod-
ify responses to chemical expo-
sures; they can also be designed to
test relationships between disease
and early markers of exposure
and biological response (e.g.,
epigenetic changes).
The Impact of
Cumulative Exposures
Although cumulative risk
assessment has been of high in-
terest for the past few decades,
putting cumulative assessment
approaches into practice has been
challenging. This framework
provides a new construct for
considering cumulative risk. By
focusing on a health endpoint of

concern, one could consider the
multiple exposures that may
contribute to a health outcome.
Past National Research Council
recommendations have encour-
aged assessors to evaluate the
combined effects of exposures
to all chemicals that affect
a common adverse outcome,
for example, male reproductive
development.37 Challenges
include gaining adequate un-
derstanding of individual
chemical effects to group
chemicals by health outcome.
Increased research into the
biological pathways by which
chemicals affect health status
can help inform approaches
for estimating the joint
effect of chemicals without
Analytic Essay 1037
testing all permutations or
combinations.
One example of an alternative
approach is health impact assess-
ment, which uses a systems ap-
proach to array data sources and

analytic methods and considers
input from stakeholders to de-
termine potential effects of
a proposed action or decision
on the health of a population and
the distribution of those effects in
the population.38 Using health
impact assessment approaches for
chemical risk assessments made
through this framework can offer
a method to organize various data
streams that can influence our
understanding of a health effect,
inform potential multiple con-
tributors to adverse health
outcomes, and provide recom-
mendations to decision-makers
for monitoring and managing
these outcomes.
Consider Public Health
Concepts
This new approach takes
a systematic view of collective
factors that contribute to a health
outcome or disease state, in-
cluding those that are not reg-
ulated by a single federal entity.
Any single health outcome may
be influenced by multiple factors
beyond chemical exposures,
such as nutrition, genetics, and
social stressors. Because those
factors are not regulated, it is
important for environmental

regulatory agencies to un-
derstand what fraction of the
disease burden is influenced by
the regulated environmental
exposure.
Public health approaches,
such as attributable risk, can
help inform this understanding.
Challenges may include in-
corporating these approaches,
which are typically used in epi-
demiology, to animal and ad-
vanced toxicity testing data;
ensuring adequate training with
the approaches; and communi-
cating risk in a way that ac-
knowledges the influence of
nonregulated factors.
Public Health
Implications
Understanding the health
effects of chemicals has real im-
plications for public health. This
proposed approach for chemical
risk assessment starts at the health
endpoint and incorporates mul-
tiple data streams, including data
developed using newer tech-
nologies such as high-throughput
screening. In parallel with more
traditional risk assessment ap-
proaches, this will lead to a better

understanding of mechanisms of
single chemicals as well as cu-
mulative exposures that lead to
specific disease endpoints.
This new lens will need to be
applied to the complete risk as-
sessment process—problem for-
mulation, data considerations,
and data synthesis through mul-
tipathway methods, including
cumulative assessment and health
impact assessment—with an eye
to the prevention of adverse ef-
fects. This approach draws on the
best available science to improve
our understanding of the health
effects of environmental chem-
icals and informs decision-
making to prevent, reduce, or
mitigate exposure and ultimately
improve public health.
CONTRIBUTORS
M. R. Gwinn led the compilation of text
and revisions of the article. M. R. Gwinn
and K. Deener led creation of Figure 1.
M. R. Gwinn, K. Deener, and R. J.
Kavlock led the creation of Table 1. D. A.
Axelrad, T. Bahadori, D. Bussard, R. S.
Thomas, and R. J. Kavlock led the
drafting of text on challenges and op-
portunities. T. Bahadori, R. S. Thomas,
and R. J. Kavlock led the creation of
Table 2. W. E. Cascio led the creation of
Figure 2. W. E. Cascio and K. Deener

led the drafting of text on public health.
R. J. Kavlock and T. A. Burke led the
discussions and outlined the article. All
authors contributed to discussions of the
concepts behind this article and contrib-
uted text to the various sections.
ACKNOWLEDGMENTS
The authors would like to acknowledge
the assistance of Laura Romano in pre-
paring the article.
Note. The views expressed in this
article are those of the authors and do not
necessarily reflect the views or policies
of the US Environmental Protection
Agency.
REFERENCES
1. Birnbaum LS, Burke TA, Jones JJ.
Informing 21st-century risk assessments
with 21st-century science. Environ Health
Perspect. 2016;124(4):A60–A63.
2. National Research Council. Toxicity
Testing in the 21st Century: A Vision and
a Strategy. Washington, DC: National
Academies Press; 2007.
3. Kavlock RJ, Austin CP, Tice RR.
Toxicity testing in the 21st century: im-
plications for human health risk assess-
ment. Risk Anal. 2009;29(4):485–487;
discussion 492–497. [Comment on
Toxicity testing in the 21st century: im-

plications for human health risk assess-
ment. Risk Anal. 2009]
4. Tice RR, Austin CP, Kavlock RJ,
Bucher JR. Improving the human hazard
characterization of chemicals: a Tox21
update. Environ Health Perspect. 2013;
121(7):756–765.
5. Kavlock R, Chandler K, Houck K, et al.
Update on EPA’s ToxCast program:
providing high throughput decision sup-
port tools for chemical risk management.
Chem Res Toxicol. 2012;25(7):1287–1302.
6. Browne P, Judson RS, Casey WM,
Kleinstreuer NC, Thomas RS. Screening
chemicals for estrogen receptor bioactivity
using a computational model. Environ
Sci Technol. 2015;49(14):8804–8814.
7. Wu S, Powers S, Zhu W, Hannun YA.
Substantial contribution of extrinsic risk
factors to cancer development. Nature.
2016;529(7584):43–47.
8. Weinhold B. Environmental factors in
birth defects: what we need to know.
Environ Health Perspect. 2009;117(10):
A440–A447.
9. Rappaport SM, Barupal DK, Wishart
D, Vineis P, Scalbert A. The blood
exposome and its role in discovering
causes of disease. Environ Health Perspect.
2014;122(8):769–774.

10. Dietert RR, Silbergeld EK. Bio-
markers for the 21st century: listening to
the microbiome. Toxicol Sci. 2015;144(2):
208–216.
11. Patterson AD, Turnbaugh PJ. Mi-
crobial determinants of biochemical in-
dividuality and their impact on toxicology
and pharmacology. Cell Metab. 2014;
20(5):761–768.
12. Servick K. Of mice and microbes.
Science. 2016;353(6301):741–743.
13. Stel J, Legler J. The role of epigenetics
in the latent effects of early life exposure to
obesogenic endocrine disrupting chem-
icals. Endocrinology. 2015;156(10):
3466–3472.
14. Buck Louis GM, Bloom MS, Gatto
NM, Hogue CR, Westreich DJ, Zhang C.
Epidemiology’s continuing contribution
to public health: the power of “then and
now.” Am J Epidemiol. 2015;181(8):
e1–e8.
15. Ankley GT, Bennett RS, Erickson RJ,
et al. Adverse outcome pathways: a con-
ceptual framework to support ecotoxicol-
ogy research and risk assessment. Environ
Toxicol Chem. 2010;29(3):730–741.
16. Goodson WH III, Lowe L, Carpenter
DO, et al. Assessing the carcinogenic

potential of low-dose exposures to
chemical mixtures in the environment:
the challenge ahead. Carcinogenesis. 2015;
36(suppl 1):S254–S296.
17. Mansouri K, Abdelaziz A, Rybacka A,
et al. CERAPP: Collaborative Estrogen
Receptor Activity Prediction Project.
Environ Health Perspect. 2016;124(7):
1023–1033.
18. Judson R, Houck K, Martin M, et al.
Analysis of the effects of cell stress and
cytotoxicity on in vitro assay activity
across a diverse chemical and assay space.
Toxicol Sci. 2016;153(2):409. [Erratum in
Analysis of the effects of cell stress and
cytotoxicity on in vitro assay activity
across a diverse chemical and assay space.
Toxicol Sci. 2016]
19. Bakker KM, Martinez-Bakker ME,
Helm B, Stevenson TJ, et al. Digital ep-
idemiology reveals global childhood
disease seasonality and the effects of im-
munization. Proc Natl Acad Sci USA. 2016;
113(24):6689–6694.
20. National Academies of Sciences, En-
gineering, and Medicine. Using 21st
Century Science to Improve Risk-Based
Evaluations. Washington, DC: National
21. Moran AE, Forouzanfar MH, Roth
GA, et al. Temporal trends in ischemic

heart disease mortality in 21 world
regions, 1980 to 2010: the Global Burden
of Disease 2010 study. Circulation. 2014;
129(14):1483–1492.
22. Mozaffarian D, Benjamin EJ, Go AS,
et al. Heart disease and stroke statistics—
2016 update: a report from the American
Heart Association. Circulation. 2016;
133(4):e38–e360.
23. US Environmental Protection
Agency. Guidelines for Preparing Economic
Analyses. Washington, DC; 2010.
24. Kannel WB, Vasan RS. Adverse
consequences of the 50% misconception.
Am J Cardiol. 2009;103(3):426–427.
25. Kaufman JD, Adar SD, Barr RG, et al.
Association between air pollution and
2017, Vol 107, No. 7
coronary artery calcification within six
metropolitan areas in the USA (the
Multi-Ethnic Study of Atherosclerosis
and Air Pollution): a longitudinal
cohort study. Lancet. 2016;388(10045):
696–704.

26. Kirkley AG, Sargis RM. Environ-
mental endocrine disruption of energy
metabolism and cardiovascular risk. Curr
Diab Rep. 2014;14(6):494.
27. Sidney S, Quesenberry CP Jr, Jaffe
MG, et al. Recent trends in cardiovas-
cular mortality in the United States and
public health goals. JAMA Cardiol. 2016;
1(5):594–599.
28. Cosselman KE, Navas-Acien A,
Kaufman JD. Environmental factors in
cardiovascular disease. Nat Rev Cardiol.
2015;12(11):627–642.
29. Solenkova NV, Newman JD, Berger
JS, et al. Metal pollutants and cardiovas-
cular disease: mechanisms and conse-
quences of exposure. Am Heart J. 2014;
168(6):812–822.
30. Zanobetti A, Baccarelli A, Schwartz J.
Gene-air pollution interaction and car-
diovascular disease: a review. Prog
Cardiovasc Dis. 2011;53(5):344–352.
31. Ward-Caviness CK, Neas LM, Blach
C, et al. Genetic variants in the bone
morphogenic protein gene family modify
the association between residential ex-
posure to traffic and peripheral arterial
disease. PLoS One. 2016;11(4):e0152670.
32. Dinov ID, Heavner B, Tang M, et al.
Predictive big data analytics: a study of

Parkinson’s disease using large, complex,
heterogeneous, incongruent, multi-
source and incomplete observations.
PLoS One. 2016;11(8):e0157077.
33. Hood L, Lovejoy JC, Price ND. In-
tegrating big data and actionable health
coaching to optimize wellness. BMC Med.
2015;13:4.
34. Khoury MJ, Evans JP. A public health
perspective on a national precision med-
icine cohort: balancing long-term
knowledge generation with early health
benefit. JAMA. 2015;313(21):
2117–2118.
35. Association of Public Health Labora-
tories. National Biomonitoring Plan. Silver
Spring, MD; 2015.
36. Mitchell E. Moonshot toward a cure
for cancer. J Natl Med Assoc. 2016;108(2):
104–105.
37. National Research Council. Phthalates
and Cumulative Risk Assessment: The Tasks
Ahead. Washington, DC: National
38. National Research Council. Improving
Health in the United States: The Role of
Health Impact Assessment. Washington,
DC: National Academies Press; 2011.

Analytic Essay 1039
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514
ASBBS PROCEEDINGS OF THE 23RD ANNUAL
CONFERENCE
AN EXAMINATION OF THE INFLUENTIAL FACTORS OF
PACKAGING,
PRICE SENSITIVITYAND BRAND IMAGE ON FROZEN
FOOD CONSUMER
BUYING BEHAVIOR IN BANGKOK, THAILAND
Thiendej, Peeraput
Graduate School of Business, Assumption University of

Thailand
[email protected]
Chaipoopirutana, Sirion
Graduate School of Business, Assumption University of
Thailand
[email protected]
Abstract
Packaging has been gradually taking on an important role as a
way to serve consumers by
providing information and delivering functions. The role of
packaging is observed as a
strategic tool to influence consumer buying behavior. The main
purpose of this research
was to identify the influences of the visual elements of
packaging in terms of graphics and
size/shape and the informational elements of packaging in terms
of product information
and technology, brand image, price sensitivity on consumer
buying behavior of CP ready-
to-eat frozen food in Bangkok, Thailand. This study exclusively
made use of survey
methods to collect the data from 399 respondents. Descriptive
statistics were used in

describing parameters of the respondents and inferential
statistics was used to test the
hypotheses. The results of the Multiple Regression Model have
shown that the independent
variables, such as the visual elements of packaging in terms of
graphics and size/shape and
the informational elements of packaging in terms of product
information and technology
were significantly influenced on both brand image and
consumer buying behavior. In
addition, brand image was significantly influenced on consumer
buying behavior.
However, price sensitivity was not influenced on consumer
buying behavior. While the
result of Simple Regression Model showed that price sensitivity
had a significant influence
on brand image. Based on the results of the study, it is supposed
to be beneficial to the
ready-to-eat frozen food businesses in order to improve their
packaging design in terms of
graphics as well as their brand image. Packaging can make a
product stand out, and can be
a silent sale man on a shelf because it is growing in a
competitive market and has become

an important tool for communication with consumers.
Key words: - Consumer buying behavior, packaging, price
sensitivity and brand image.
Introduction
Food packaging is likely to grow in competitive market
conditions, as packages turn into a
tool for communication and branding, and there are many
factors affecting the consumer buying
behavior process through food packaging, therefore the
communication functions of the package,
such as the graphics of the packaging, the size and shape of the
packaging, the information on the
515
CONFERENCE
package, and innovative packaging must inform and assist
consumers in making their purchase
decision carefully (Ahmed et al, 2014).

Consumers are becoming more and more demanding and
packaging has been gradually taking
on an important role as a way to serve consumers by providing
information and delivering functions
to communicate with consumers. It is no wonder that the
important role of packaging is observed
as a strategic tool to influence consumer buying behavior.
Likewise, in Thailand, currently, the
lifestyle of people is being rushed. There are time constraints
and the need for speed in the activities
of everyday life and they are more likely to need more
convenience cookings (Silayoi and Speece,
2007). Convenience cookings could be considered as the ease of
use of consumption of the food
which indicates time reducing and less effort to prepare
(Luning, 2001). Consumers who need
convenience cookings, agree that ready-to-eat frozen foods are
convenient (Darian, 1995).
Moreover, packaging concepts of ready-to-eat frozen food are
designed more and more to fulfill
the consumers need for more convenience (Luning, 2001).
Packaging concepts, such as graphics,
size/shape, information, technology definitely could give

consumers more convenience (Ahmed et
al, 2014). For example, graphics on the packages, such as their
color and design, trend to have an
impact on consumer buying behavior because graphics are
necessary when consumers do not have
time for much consideration and decision making; therefore,
graphics could draw their attention to
the product (Ahmed et al, 2014).
Moreover, according to Jinkarn and Suwannaporn (2015),
the size and shape of packaging is
more likely to play an important role in consumer buying
behavior because the proper size and
shape of the package could offer convenience to the consumers
for storing and preparing or
grabbing and holding. In addition, information on the packaging
could also have an impact on
consumer buying behavior because it can connect consumers
with the product and it is very
important for the consumers to consider information on a
package in order to compare quality and
value (Deliya and Parmar, 2012). Similarly, some consumers
might pay more attention to the
information on the package, especially the consumers who are
concerned about health (Silayoi and

Speece, 2004). In addition, consumer buying behavior is also
likely to be influenced by the
technology of packaging, such as its recyclability,
microwavable, easy-to-open, easy-to-store, easy-
to-carry, and preventing breakages (Silayoi and Speece, 2007).
However, in this case, the consumer
buying behavior is influenced not only by the convenience of
the ready-to-eat frozen food
packaging. Price and brand of the ready-to-eat frozen food
could have an impact on consumer
buying behavior as well. For example, price could refer to the
perceived value of goods and service,
and the different perception of the goods or service leads to a
difference in identifying the price,
especially the importance of food price often has its effect on
consumer’s income (Walters and
Bergiel, 1989). On the other hand, brand names could create
important information and key benefits
of the product, and help consumers remember it (Parry, 2001).
Literature Review
Consumer buying behavior: Consumer buying behavior involves
the selection, purchase and
consumption of goods and services in order to satisfy their

needs and wants. Basically, there are
516
CONFERENCE
different processes involved in consumer buying behavior.
Firstly, the consumers would try to find
what product and service they would like to consume, then they
choose only those products or
services that give them greater benefits, and after selecting the
product and service, the consumer
tends to make an estimate of the available money which they
can spend. Lastly, the consumers tend
to identify the price of the product and make a decision (Kotler
and Keller, 2011). Moreover, there
are other factors influencing buying behavior of the consumer
such as social class, culture, personal
aspect and psychological factors. For example, firstly, culture is
critical when it comes to
understanding the needs, wants and behaviors of an individual.
Basically, culture is part of society

and the influence of culture on buying behavior varies from
country to country. Therefore,
analyzing the culture of different groups is very important in
terms of consumer buying behavior
(Schiffman and Kanuk, 2007). Visual elements of packaging in
terms of graphics: Nancarrow et
al (1998) stated that graphics is the methodology of visual
communication and a combination of
visual arts and typography. Mostly, the graphics is developed by
marketers.
Basically, graphics contain image, layout, color and the total
presentation of image communicated
to consumers. However, different consumers may observe
different packaging in different ways
because when consumers learn graphics associations, it could
lead the consumers to prefer a certain
graphic for certain product categories. In addition, according to
Herrington & Capella (1995), when
consumers examine packages in the supermarket, the
differential perception and the positioning of
the graphics can be the difference between identifying and
missing the product because eye-
catching graphics could make the product stand out on the shelf
and attract the consumers.

Therefore, graphics can affect through the colors and printed
lines on the package on which
different signs and symbols are located. Moreover, in many
situations graphics could create a
positive mood and also an important role of packaging graphics
is that they could gain the attention
of consumers to the product (Silayoi & Speece, 2004).Visual
elements of packaging in terms of
size/shape: Raghubir and Krishna (1999) conceptualized that
size and shape combined with a
dimension and consumers trends to use it to make judgments
about volume. Basically, consumers
could respond to different sizes and shapes in different ways
because the effect of packaging size
and shape is stronger when product quality is hard to be
clarified. Silayoi and Speece (2007) also
stated that different packaging sizes attract consumers from
different involvement. For example,
some consumers find products in larger packaging as a good
offer with great value for money and
this indicates that when the quality of the product is difficult to
judge, the impact of packaging size
is greater because bigger packages of food products are more
likely to be chosen. For example, if

consumers are not familiar with the brand of the product, the
larger packaging size and shape could
be also noticed easily.Informational elements of packaging in
terms of product information:
Coulson (2000) mentioned that one of the functions of
packaging is to communicate product
information to consumers, which can help them in their
purchase decisions carefully because
communication of information is one of the important functions
of packaging. For example, it could
help consumers to make the right decision in the purchasing
process and also provide the consumer
the opportunity to consider alternative products and make a
choice by reading the information on
the package or product. Moreover, Ahmed and Salman (2005)
conceptualized that in the food
industry, packaging is considered as a communication tool
providing information on the product
517

CONFERENCE
about ingredients, contents, price, cooking directions and the
expiry date. Basically, the objective
of the information functions of packaging is to inform
consumers about the product’s contents and
help the consumers in making their decisions carefully.
Informational elements of packaging in terms of technology:
Mcllveen (1994) stated that the
informational elements of packaging in terms of technology is a
combination between research
development and innovation that are more effectively packaged
for the product. Basically, the
development of packaging technologies is concerned with food
safety, and these technologies
could be related to improving the quality, expiration date,
safety, and components of the package.
Silayoi and Speece (2004) also mentioned that the technology
developed for packaging comes
from consumer behaviors. For example, working people often
purchase microwavable food
packaging which is convenient and suits their lifestyle;
therefore, consumers are more likely to
pay attention to packaging materials which have an impact on

convenience as well as the product
itself because it could help them with their food preparation.
For example, microwavable
packaging could be a good solution for consumers when they do
not have enough time to prepare
their meal.
Price sensitivity: Kim et al. (1999) mentioned that price is the
value of purchasing goods or
services and might be involved in consumer buying behavior
and price could be an important
factor for some consumers because they are more likely to feel
price sensitivity when purchasing
the product at a lower or higher price. Monroe (1971) also
stated that price sensitivity is an
individual difference variable describing how individual
consumers show their reactions to
changes in price levels. In addition, Kanghyun and Thanh
(2011) conceptualized that price
sensitivity occurs when each consumer shows their reactions to
changes in price levels. Basically,
it is the awareness of the consumers to what they observe about
the cost when purchasing a
particular product or service. Normally, each customer will
have a certain price acceptability

range in their mind. When customers are satisfied with the
products or services, they are more
likely to buy the product again.
Brand image: Keller (2008) stated that a brand may include a
symbol, name, design, or
experience that help consumers identify products and services,
in addition branding could also
help consumers to reduce risk by ensuring a certain level of
product quality and brand image
could create values for the product in many ways, such as by
helping consumers to process
information, differentiate brands, generate reasons to buy, give
positive feelings, and increase the
reliability of the product. Keller and Lehman (2006) also
mentioned that a good brand image
provides important benefits to the product and company. For
example, a good brand image could
help the company to reduce the costs of advertising and help the
company to be ahead of the
competitors in terms of recognition. Lassar et al. (1995) also
mentioned that consumer confidence
could occur with a good brand image because loyalty and trust
of the consumers are more likely

to be developed through a good brand image and these lead to
confidence in the consumers and
the greater the confidence they have in the brand, the more
likely they are willing to pay a high
price for it. Therefore, a good brand image may give buyers
confidence that it performs better
than a brand which is unknown and the feeling of confidence
communicated by the brand can be
an important additional benefit to the buyer.
518
CONFERENCE
Visual elements of packaging in terms of graphics, size/shape
and consumer buying
behavior.
Ahmed et al. (2014) conceptualized that graphics on the
package, such as color and design

play an important role in consumer buying behavior because
graphics are necessary when
consumers do not have time for much consideration and the
decision making process for a product.
Abdullah et al. (2013) concluded that there is a significant
positive relationship between the
graphics on packaging and consumer buying behavior.
Moreover, Adam and Ali (2014) stated that
consumer consumption trends increased when packages are
available in larger sizes. For example,
a larger package is considered by consumers of larger families,
and a smaller package for them
could be considered as a waste. Jinkarn and Suwannaporn
(2015) also revealed there is a positive
relationship between the size and shape of packaging and
consumer buying behavior.
Visual elements of packaging in terms of graphics, size/shape
and brand image
Underwood et al. (2001) stated graphics could help
consumers find the brand of their choice
and if they do not have any strong preference for a brand then
graphics at least gain their attention
to consider a particular product for evaluation. Edward (2013)
summarized that graphics used in

packaging have a significant relationship with brand image.
According to Agariya et al.
(2013), a proper size and shape packaging can help brands in a
good position in the market place
and set a brand apart from its competitors in order to get
consumers’ attention easier and also can
represent an image of the brand. Orth and Malkewitz (2006)
also concluded that there is a
significant positive relationship between size and shape of
packaging, and brand image.
Informational elements of packaging in terms of product
information, technology and brand
image.
Sial et al. (2011) stated that packaging information,
such as labeling which is written on the
package or a product could contain the brand name of the
product as well as the ingredients.
Moreover, a company uses packaging and labeling as a tool to
attract consumers because the
consumers tend to pay more for the product which has a good
brand name, compared to those
products which do not have a good brand image. Machado et al.
(2012) concluded that there is

statistically significant relationship between product
information and brand image. In addition,
Danaei et al. (2014) conceptualized that companies tend to
create a strong brand image by
improving the quality of products as well as establishing strong
brands through the packaging
technology of the product, such as ease of use, ease of handling
and safety. Mahajan et al. (2013)
also mentioned that there is a significant relationship between
packaging technology and brand
image.
Informational elements of packaging in terms of product
information, technology and
519
CONFERENCE
According to Deliya and Parmar (2012), the

information elements on packaging include
the label indicating the brand name of the product, and
information could connect consumers with
the product because the consumers feel that it is very important
to consider information on a
package in order to compare quality and value. Mutsikiwa et al.
(2013) concluded that there is a
significant relationship between the information on the package
and consumer buying behavior.
Mahajan et al. (2013) conceptualized that packaging
technology, such as innovative packaging
could add value to the product in the eyes of consumers, such as
portion control, recyclability,
child-proofing, easy-open, easy-store, easy-to-carry, and non-
breakability. Silayoi and Speece
(2007) also stated that there is a positive relationship between
the technology of packaging and
Price sensitivity and brand image.
Soba and Aydin (2012) stated that when consumers have
a high income level, it means that
price sensitivity of the consumers is low because consumers
with a higher income prefer to buy

products at higher prices and they also think that a higher price
means higher quality. Moreover,
price sensitivity of the consumers also has an impact on brand
image. For example, the consumer
with a high income is more likely to purchase any product
which has a good brand image. Dhurup
et al. (2013) studied about price sensitivity and brand image and
found that there is an impact of
price sensitivity on brand image.
Price sensitivity, brand image and consumer buying behavior.
Diaz (2003) conceptualized that consumers’ knowledge
of prices was found to be dependent
on how much importance they placed on price. For example, if
the consumer comes from lower-
income households, they tend to spend less because their
sensitivity to price is influenced by their
income level. Kanghyun and Thanh (2011) also mentioned that
when consumers do an evaluation
on the price of the product, price sensitivity will occur. Brucks
et al. (2000) summarized that there
is a relationship between price and consumer buying behavior.
Sial et al. (2011) mentioned that a
good brand image enhances the value of the brand in the

consumer’s mind because a good image
could increase the likeability and desirability of the product.
Fianto et al. (2014) also concluded
that that brand image has a positive and significant influence on
Research Framework
Based on three previous studies conducted by Sial et al.
(2011), Karampour and
Ahnmadinejad (2014) and Silayoi and Speece (2004), the
researcher developed a conceptual
framework consisting of six independent variables which are the
visual elements of CP ready-to-
eat frozen food packaging in terms of graphics, the visual
elements of CP ready-to-eat frozen
food packaging in terms of size/shape, the informational
elements of CP ready-to-eat frozen food
packaging in terms of product information, the informational
elements of CP ready-to-eat frozen
food packaging in terms of technology, price sensitivity of CP
ready-to-eat frozen food, brand
image of CP ready-to-eat frozen food and consumer buying
behavior as dependent variable. The
conceptual framework is shown in Figure.1.

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Figure: 1 Conceptual framework
hhhhh

Research Hypotheses
H1: Visual elements of CP ready-to-eat frozen food packaging
in terms of graphics and size/shape
are significantly influenced on consumer buying behavior.
H2: Visual elements of CP ready-to-eat frozen food packaging
in terms of graphic and size/shape
are significantly influenced on brand image.
H3: Informational elements of CP ready-to-eat frozen food
packaging in terms of product
information and technology are significantly influenced on
brand image.
Packaging Elements of CP
Ready-to-eat Frozen food
Visual Elements
Graphics
Size/Shape

Informational Elements
Product Information
Technology
Brand Image of CP
ready-to-eat frozen
food
Consumer
Buying
Behavior
H1
H2
H3
Price sensitivity of CP ready-
to-eat frozen food
H5
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H4: Informational elements of CP ready-to-eat frozen food
packaging in terms of product
information and technology are significantly influenced on
H5: Price sensitivity of CP ready-to-eat frozen food is
significantly influenced on brand image.
H6: Price sensitivity of CP ready-to-eat frozen food and Brand
image are significantly influenced
on consumer buying behavior.
Research methodology
The researcher applied descriptive research by using
survey techniques, and also the
researcher distributed the questionnaire using a self-
administered techniques to collect the data
from 399 respondents in Bangkok, Thailand. The target of this
study is males or females who have
experience purchasing CP ready-to-eat frozen food. The
researcher collected data from CP Fresh
mart stores from three main target areas which are Fortune
town, Silom and Phayathai. These three

areas are crowded because they are close to the BTS sky train
and MRT subway train where many
people use as transportation during rush hours
(www.google.co.th/maps/place/CP+Freshmart,
accessed the data on 22/06/2015). The questionnaire for this
study was separated into two parts –
Sections A and B. Section A of the questionnaire contains
questions on the demographic profile,
such as the respondents’ age, gender, education level, marital
status and monthly income. Section
B of the questionnaire was based on the researcher’s conceptual
framework, and the five point
Likert scale was applied for the questionnaires, and the meaning
of each scale is 1 indicates
“strongly disagree”, 2 indicating “disagree”, 3 indicating
“moderate”, 4 indicating “agree”, and 5
indicating “strongly agree”.
The result of this study will represent specific areas in
Bangkok only. The researchers will
not be able to collect data from all the population who have
purchased CP ready-to-eat frozen foods
from every CP fresh mart branches in Thailand, due to
limitations of money, time and personnel;
also, the researcher used purposive sampling, quota sampling

and convenience sampling to gather
the data, therefore it may not cover all answer of CP ready-to
eat frozen food consumers in
Thailand. The data collection for this study took place in the
month of September 2015; therefore,
the result of this study is limited to this particular time frame.
In this research, the Cronbach’s Alpha
test was also done to see the reliability and consistency of
variables of this research. The collected
data were treated using Descriptive and Inferential statistics.
Moreover, descriptive statistics were
used in describing the parameters of the respondents and
inferential statistics were used to test the
hypotheses. Multiple Regression Model and Simple Regression
Model were used find out the
influences of the independent variables on the dependent
variable.
Research Findings
According to the descriptive analysis of the
demographic factors among 399 respondents,
it showed that a majority of respondents were mostly female,
which is equal to 62.2% (248). The
highest percentage of respondents’ age mostly is between 21 to

30 years old which is equal to
48.1% (192). Most of respondents are single which is equal to
65.9%. The highest education level
http://www.google.co.th/maps/place/CP+Freshmart
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of the respondents is a Bachelor’s Degree which is equal to
84.2% (336), and the highest percentage
of respondents’ monthly income is the range of 20,000-40,000
Baht which represents 82.0% (327).
Moreover, the result of descriptive analysis of the variables
revealed that the price sensitivity of CP
ready-to-eat frozen food has the lowest mean which is equal to
2.87. It means that the price
sensitivity of CP ready-to-eat frozen food does not have much
influence on the buying decision of
the consumers, and it means that the consumers are not
concerned with the price of CP ready-to-
eat frozen food. On the other hand, the highest mean belongs to
the informational elements of CP

ready-to-eat frozen food packaging in terms of product
information which is equal to 3.42, and it
means that most of the consumers mainly focus on the
packaging information when making a
buying decision. For this study, the researcher made use of
Multiple Linear Regression (MLR) and
Simple Linear Regression (SLR) to test the influences of the
hypotheses. The research results of
Multiple Linear Regression (MLR) and Simple Linear
Regression (SLR) showed that all the null
hypotheses were rejected as the following table 1 shows the
results of the hypotheses testing.
Table 1: Summary results of hypotheses testing
Variables (H1) Beta Significance Result
Visual elements of CP
ready-to-eat frozen food
packaging in terms of
Graphics and Size/shape
0.456
0.296
.000

.000
Rejected
Visual elements of CP
Graphics and Size/shape
0.147
0.423
.014
.000
Rejected
Informational elements of
CP ready-to-eat frozen
food packaging in terms of
product information and
technology

0.239
0.418
.000
.000
Rejected
Informational elements of
CP ready-to-eat frozen
food packaging in terms of
product information and
technology
0.397
0.145
.000
.000
Rejected
Variable (H5) Beta Significance Result
Price sensitivity of CP

0.382 .000 Rejected
Price sensitivity of CP
and brand image
-0.051
0.422
.142
.000
Rejected
As stated in Table 1, the visual elements of CP ready-to-eat
frozen food packaging in terms
of graphics had the strongest influence on consumer buying
behavior at 0.456 of beta, followed by
the brand image of CP-ready-to-eat frozen food which is
influenced on consumer buying behavior
with at 0.422 of beta. In addition, the visual elements of CP
ready-to-eat frozen food packaging in

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terms of size/shape had the strongest influence on brand image
at 0.423 of beta, followed by the
informational elements of CP ready-to-eat frozen food
packaging in terms of technology which is
influenced on brand image at 0.418 of beta. However, the price
sensitivity of CP ready-to-eat frozen
food is not influenced on consumer buying behavior at -0.051 of
beta respectively. Therefore, it
implies the visual elements of CP ready-to-eat frozen food
packaging in terms of graphics had a
stronger influence on consumer buying behavior than the other
variables.
Conclusions
The purpose of this study is to identify the factors of CP ready-
to-eat frozen food packaging
on consumer buying behavior towards CP fresh mart stores,
Bangkok, Thailand. There are six

independent variables which are the visual elements of
packaging in terms of graphics, the visual
elements of packaging in terms of size/shape, the informational
elements of packaging in terms of
product information, the informational elements in terms of
technology, price sensitivity and brand
image, and one dependent variable to study is consumer buying
behavior.
The data was collected from 399 questionnaires that were
distributed to the respondents
when they purchased CP ready-to-eat frozen food at three
selected areas of CP fresh mart stores
starting from 25 September 2015 to 7 October 2015. Basically, a
majority of the respondents were
females aged between 21 to 30 years, with a bachelor’s degree,
having a monthly salary in the range
of 20,000 – 40,000 THB, and they were single. For hypothesis
testing, all of the six hypotheses
were analyzed by SPSS, and all of null hypotheses were
rejected. As stated in table 1, the visual
elements of CP ready-to-eat frozen food packaging in terms of
graphics had the strongest influence
on consumer buying behavior at 0.456 of beta coefficients,
followed by the brand image of CP-

ready-to-eat frozen food which is influenced on consumer
buying behavior with at 0.422 of beta
coefficients, the informational elements of CP ready-to-eat
frozen food packaging in terms of
product information which is influenced on consumer buying
behavior at 0.397 of beta coefficients,
the visual elements of CP ready-to-eat frozen food packaging in
terms of size/shape which is
influenced on consumer buying behavior at 0.296 of beta
coefficients, the informational elements
of CP ready-to-eat frozen food packaging in terms of
technology which is influenced on consumer
buying behavior at 0.145 of beta coefficients. However, the
price sensitivity of CP ready-to-eat
frozen food is not influenced on consumer buying behavior at -
0.051 of beta coefficients
respectively.
In addition, the visual elements of CP ready-to-eat frozen food
size/shape had the strongest influence on brand image at 0.423
of beta coefficients, followed by the
informational elements of CP ready-to-eat frozen food
packaging in terms of technology which is

influenced on brand image at 0.418 of beta coefficients, the
price sensitivity of CP ready-to-eat
frozen food is influenced on brand image at 0.382 of beta
coefficients, the informational elements
of CP ready-to-eat frozen food packaging in terms of product
information which is influenced on
brand image at 0.239 of beta coefficients and the visual
elements of CP ready-to-eat frozen food
packaging in terms of graphics which is influenced on brand
image at 0.147 of beta coefficients.
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Recommendations
Based on the results of hypotheses testing. The
researcher found that the visual elements of
CP ready-to-eat frozen food packaging in terms of graphics had
the strongest influence on
consumer buying behavior at 0.456 of beta coefficients which
means this part of the ready-to-eat

frozen food packaging caught consumers’ attention effectively.
Therefore, the researcher would
like to suggest the marketing teams of a ready-to eat frozen
food companies to focus on the graphics
of the package, such as color and design. The marketing teams
may compare what some of the
competitors have done with their packaging in terms of
graphics. The researcher observed that the
brand image of CP-ready-to-eat frozen food had the high impact
on consumer buying behavior as
well at 0.422 of beta coefficients which means that brand image
plays an important role on buying
behavior of the consumers. A good brand image will help the
consumers understand what the
companies’ product or service is all about, and what they can
expect from the product or service.
The good brand image could get the business perceived as
reliable, and this will engage the
consumers with the product. Therefore, the ready-to-eat frozen
food companies need to make sure
that their products have the good brand image. The
informational elements of CP ready-to-eat
frozen food packaging in terms of product information which is
also influenced on consumer

buying behavior at 0.397 of beta coefficients which means
consumers are more likely to consider
an information on a package in order to compare quality and the
value of the products. Therefore,
the companies are supposed to come up with a clear
information, and not giving too much
information on the package because it is necessary for
consumers to consider nice and clear
information on the package
The researcher also found that the visual elements of CP
ready-to-eat frozen food packaging
in terms of size/shape is influenced on consumer buying
behavior at 0.296 of beta coefficients
which means that the consumers are concerned with the size and
shape of the package. The
researcher would like to suggest that the ready-to-eat frozen
food companies also need to create a
proper size and shape packaging for consumers when grabbing
or holding because they are more
likely to take this function to the evaluation of the brand of the
product. Therefore, a proper size
and shape of the package can help brands in a good position in
the market and set a brand apart
from its competitors. Lastly, the technology of packaging is

influenced on consumer buying
behavior at 0.145 of beta coefficients which means the
technology of packaging such as innovative
packaging can never be ignored. The researcher would like to
suggest that the companies also need
to focus on research and development of packaging because
innovative packaging with
recyclability, un-breakability, microwavable and so on could
add value to ready-to-eat frozen foods
and result in companies brand to have a good image.
References
Aaker, A., Kumar, VD. and George, S. (2000), Marketing
research, John Wiley and Sons,
Inc, New York.
Aaker, D.A., Kumar, V. and Day, G.S. (1998), Marketing
Research, ( 6th ed):John Wiley &
Sons,Inc
525

CONFERENCE
Abdullah, A. M., Rahman, K.M. and Robel1, S. (2014), A
Critical Review of Consumers’
Sensitivity to Price: Managerial and Theoretical Issues, Journal
of International Business
and Economics, 2 (2), 1-9.
Abdullah, M., Kalam, A. and Akterujjaman., S. M. (2013),
Packaging Factors Determining
Consumer Buying Decision, International Journal of
Humanities and Management
Sciences (IJHMS), 1 (5), 285 -289.
Adam, A. M. and Ali, K. (2014). Impact of Visual Packaging
Elements of Packaged Milk on
Consumers Buying Behavior, Interdisciplinary Journal
of Contemporary Research in
Business,5 (11).
Agariya, K. A., Johari, A., Sharma, K. H., Chandraul, U. and
Singh, D. (2012), The Role of
Packaging in Brand Communication, International Journal of
Scientific & Engineering
Research, 3 (2), 1-9.

Ahmed, A., Ahmed, N. and Salman, A. (2005). Critical issues in
packaged food business,
British Food Journal, 107 (10), 760-80.
Ahmed, R. R., Ahmad, N., Parmar, V. and Imamuddin, K.
(2014). Role of Packaging and
Labeling on Pakistani Consumers Purchase Decision,
European Scientific Journal, 10
(16)
Ahmed, R. R. and Nawaz, A. (2014), Role of packaging and
labeling on Pakistani consumer,
European Scientific Journal, 10 (16), 464-473.
Ahmed, R. R., Parmar, V. and Amin, A. M. (2014), Impact of
Product Packaging on
Consumer’s Buying Behavior, European Journal of Scientific
Research, 120 (2), 145-157.
Almus, M, and E. A. Nerlinger, 1999, Growth of New
Technology Based Firms: Which
Factors Matter?, Small Business Economics, Vol13, 41-154
Ares, G. and Deliza, R. (2010), Studying the influence of
package shape and color on
consumer expectations of milk desserts using word association
and conjoint analysis, Food
Quality and Preference, 21 (8), 930-7.

Battaglia, P. M. (2011), Nonprobability Sampling,
Encyclopedia of Survey Research.
Blackwell, R. D., Miniard, P. W. and Engel, J. F. (2006).,
Consumer behavior. Mason:
Thomson.
Brown, K.M. (2005). Reconciling moral and legal collective
entitlement: Implications for
community-based land reform.
Brucks, M., Zeithaml, M. and Gillian, N. (2000), Price and
brand name as indicators of
quality dimensions for consumer durables, Academy of
Marketing Science Journal, 28 (3),
360-374
Churchill, G. A. (1991). Marketing Research: Methodological
Foundations,(5th ed.), Dryden
Press.
Comfrey, A. L. and Lee, H. B. (1992). A First Course in Factor
Analysis. Hillsdale, NJ:
Lawrence Eribaum Associates.
Corston, R. and Colman, A. (2000), A Crash Course in SPSS for
Windows, Blackwell,
Oxford.

Cooper, D. and Schindler, P. (2001), Business Research
Methods, (7th ed), New York:
McGraw-Hill/Irwin.
Coulson, N.S. (2000), An application of the stage of change
model to consumer use of food
labels, British Food Journal, 102 (9), 661-8.
Danaei, H., Haghtalab, H. and Ali, B. (2014), The effect of
product performance on brand
image: case study Razavi Yeast product, Indian Journal of
Fundamental and Applied Life
Sciences, 4 (1), 635-640.
526
CONFERENCE
Deliya, M. M. and Parmar, J. B. (2012), Role of Packaging on
Consumer Buying Behavior–
Patan District, Global Journal of Management and Business
Research, 12 (10), 49-67.

Dhurup, M., Mafini, C. and Dumasi, T. (2014), The impact of
packaging, price and brand
awareness on brand loyalty: Evidence from the paint retailing
industry, 14(1), 1-9.
Díaz, R. and Maria, I. (2004), Price knowledge: effects of
consumers' attitudes towards
prices, demographics, and sociocultural characteristics, Journal
of Product & Brand
Management, 13 (6), 406 – 428
Darian J.C. (1995) Segmenting by consumer time shortage,
Journal of Consumer Marketing,
12(1), 32-44.
Edward , W. (2013), The influence of visual packaging desi gn
on perceived food product
quality, value, and brand preference, International Journal of
Retail & Distribution
Management, 41(10), 805 – 816
Everett, J. and Armstrong, B. (1990), Research Note:
Book/Software Review: SPSS for
teaching statistics in marketing. Asia Pacific Journal of
Marketing and Logistics, 2(1).
Fisher, R. A. (1925). Statistical methods for research workers.

Edinburgh, Scotland: Oliver
and Boyd.
Gay, L.R. (1987), Competencies for Analysis and Application,
(3rd ed),Ohio:
Education Research.
Guadagnoli, E. and Velicer, W.F, (1988), Relation of sample
size to the stability of
component. Psychological bulletin, 103, 265-275.
Hair, J., Anderson, R. and Tatham, W. B. (1998). Multivariate
Data Analysis, (5th ed),
Prentice Hall International, London.
Henry, L. (1968), Historical demography. Daedalus, 97, 385–96
Herrington, J.D. and Capella, L.M. (1995), Shopping reactions
to perceived time pressure,
International Journal of Retail & Distribution
Management, 23 (12), 13-20.
Hill, H. and Tilley, J. (2002), Packaging of children’s breakfast
cereal, British Food Journal,
104 (9), 766-77.
Holbrook, M. B. and Hirschman, E. C. (1982). The Experiential
Aspects of Consumption:
Consumer Fantasies, Feeling, and Fun, Journal of

Consumer Research, 132-140.
Jinkarn, T. and Suwannaporn, P. (2015), Trade-off analysis of
packaging attributes for foods
and drinks, British Food Journal, 117 (1), 139-156.
Kanghyun, Y. and Thanh, V. (2011), Revisiting the relationship
between consumer loyalty
and price sensitivity: the moderating role of deal-proneness,
journal of Marketing Theory
and Practice, 19, (3), 293–306.
Karampour, A. and Ahmadinejad, B. (2014), The research model
of Purchase intention for a
private label brand: direct impact of factors including price
sensitivity, understanding
brand, image of private brands and metal image of store. Kuwait
Chapter of Arabian
Journal of business and management review, 3(7), 417-424.
Keller, K. L. (1993). Conceptualizing, measuring, and managing
customer-based brand
equity. Journal of Marketing, 57(1), 1–22.
Keller, K. L. (2008). Strategic brand management: Building,
measuring, and managing brand
equity. (3rd ed.). Upper Saddle River, NJ: Prentice Hall.

Keller, K. L. and Lehmann, D. R. (2006). Brands and branding:
Research findings and future
priorities. Marketing Science, 25(6), 740-759.
Kim, B., Srinivasan, K. and Wilcox, R. T. (1999). Identifying
price sensitive consumers: the
Kolodinski relative merits of demographic vs.
purchase pattern information. Journal of
Retailing, 75(2), 173-193.
527
CONFERENCE
Kotler, P. and Keller, K. (2011). Marketing Management, (14th
ed), London: Pearson
Education.
Kupiec, B. and B. Revell. (2011). Measuring consumer quality
judgments. Br. Food J, 103,
7-22.
Lassar, W., Mittal, B. and Sharma, A. (1995). Measuring
customer-based brand equity.

Journal of Consumer Marketing, 12 (4), 11-19.
Lind, D., Marchal, W. and Wathen, S. (2010). Statistical
Techniques in Business &
Economics, (14th ed), New York: McGraw-Hill Irwin.
Luning, A .P. (2001), Safety in the Agri-food chain,
Wageningen Academic Publishers.
Machado, C. J., Carvalho, V. L., Costa, P. and Lencastle, P.
(2012), Brand mergers:
examining consumers' responses to name and logo design,
Journal of Product & Brand
Management, 21(6), 418 – 427.
Mahajan, S., Vaishya, O.R., Gupta, A. and Dholle, V. (2013).
Role of Packaging for
Enhancing the Sales Appeal, 2 (7), 111-114.
Malhotra, N. K. (2000). Marketing Research, (3rd Ed.). New
Jersey: Prentice Hall.
Malhotra, N. K. (2004), Marketing Research: An applied
orientation (4th ed), Upper Saddle
River: Prentice Hall.
Malik, E. M., Ghafoor, M. M., Iqbal K. H., Ali, Q., Hunbal, H.,
Noman, M. and Ahmad, B.
(2013).Impact of Brand Image and Advertisement on Consumer
Buying Behavior, World

Applied Sciences Journal, 23 (1), 117-122.
Matthew, B. (2008). Multiple Hypothesis Testing: The F-test,
Resources:
http://www.mattblackwell.org/files/teaching/ftests.pdf.
McDaniel, C. and Gate, R. (1999), Contemporary Marketing
Research, South Western
College Publishing: Cincinnati, OH.
Mcllveen, H. (1994), Product development and the consumer:
the reality of the managing
creativity, Nutrition and Food Science, 6, 26-30.
Monroe, K. B. (1971). Measuring Price Thresholds by
Psychophysics and Latitudes of
Acceptance, Journal of Marketing Research, 8, 460–
64.
Mousavi, A. S. and Jahromi, M. M. (2014), Examining the
Relationship between Packaging
and Consumer buying behavior (Case study: Comparison of
Pasteurized 1.5L Milk of
Brands Roozaneh and Mihan), Indian Journal of Fundamental
and Applied Life Sciences,
4 (1), 1038-1044.
Mutsikiwa, M., Marumbwa, J. and Mudondo, C. D. (2013), The
Impact of Informational

Package Elements on Consumer Purchase Behavior of Breakfast
Cereal Products: The
Case of University Students in Masvingo, Zimbabwe, European
Journal of Business and
Management, 5 (8), 55-63.
Nancarrow, C., Wright, T.L. and Brace, I. (1998).Gaining
competitive advantage from
packaging and labeling in marketing communications, British
Food Journal,100 (2),110-
18.
Ogba, I.E., and Johnson, R. (2010). How packaging affects the
product preferences of
children and the buyer behavior of their parents in the
food industry. Young Consumers:
Insight and Ideas for Responsible Marketers, 11(1),
77-89.
Orth, R. and Malkewitz, K. (2006), Packaging design as
resource for the construction of
brand identity, International Wine Business Research
Conference (3rd ed), Montpellier.
Parry, M.E. (2001), Strategic Marketing Management, McGraw -
Hill Professional.
Polit, D. and Beck, C. (2008), Nursing research: generating and

assessing evidence for
http://www.emeraldinsight.com/action/doSearch?ContribStored
=C%C3%A9sar+Machado%2C+J
=C%C3%A9sar+Machado%2C+J
=Costa%2C+P
http://www.mattblackwell.org/files/teaching/ftests.pdf
528
CONFERENCE
Nursing practice, (8th ed), New York.
Prendergast, P.G. and Pitt, L. (1996), Packaging, marketing,
logistics and the environment:
are there trade-offs?, International Journal of Physical
Distribution & Logistics
Management,
26 (6), 60-72.
Proctor, D. N. and Joyner, M. J. (1997). Skeletal muscle mass
and the reduction of VOµmax
in trained older subjects. Journal of Applied
Physiology, 82, 1411—1415.

Raghubir, P. and Krishna, A. (1999), Vital dimensions in
volume perception: Can the eye
fool the stomach?, Journal of Marketing Research, 36 (3), 313-
26.
Rensis, L. (1932). A Technique for the Measurement of
Attitudes, Archives of Psychology,
140, 1-55.
Rettie, R. and Brewer, C. (2000), “The verbal and visual
components of package design”,
Journal of Product & Brand Management, 9 (1), 56-70.
Robbins, M.C. and Pollnac, R.B. (1969), Drinking patterns and
acculturation in rural
Buganda, American Anthropologist, 71, 276-285.
Schaeffer, N. C. (1991). Conversation with a Purpose--Or
Conversation? Interaction in the
Standardized Survey in Measurement Errors in
Surveys.
Schiffman, L. and Kanuk, L. (2007), Consumer behavior, (8th
ed), Prentice Hall.
Sekaran, U. (2003). Research methods for business: A skill -
building approach. (2nd Ed.). New
York: John Wiley and Sons Inc.

Sial, M., Gulzar, A., Ain Riaz., and Nawaz, B., (2011). Impact
of labeling and Packaging on
buying behavior of young consumers with mediating role of
Brand Image.
Interdisciplinary Journal of Contemporary Research in
Business, 3 (8). 1022-1028
Silayoi, P. and Speece, M. (2004), Packaging and purchase
decisions an exploratory study on
the impact of involvement level and time pressure, British Food
Journal, 106 (8), 607-628.
Silayoi, P. and Speece, M. (2007), The importance of packaging
attribute: a conjoint analysis
approach, Europen Journal of Marketing, 41 (12), 1495-1517.
Soba, M. and Aydin, E. (2012), The Role of Income Level on
Sensitivity Levels for Similar
Product: A Purchasing Behavior Study, International Journal of
Humanities and Social
Science, 2 (18), 177-181.
Stewart, B. (2004), Packaging Design Strategies. Second
Edition. The UK: Pira International
Ltd.
Stewart, D.W. (1984), Secondary Research: Information Sources
and Methods, Beverly Hills:

Sage.
Underwood, L.R., Klein, M.R. and Burke, R.R. (2001),
Packaging communication:
attentional effects of product imagery, Journal of Product &
Brand Management, 10 (7),
403 – 422
Underwood, R.L. (2003), The communicative power of product
packaging: creating brand
identity via lived and mediated experience, Journal of
Marketing Theory and Practice ,11
(1), 62-76.
Walters, G. and Bergiel. B.J. (1989), Consumer Behavior: A
Decision-Making Approach,
Cincinnati, Ohio: South-Western Publishing Co.
Williams, R. (2015). Review of Multiple Regression, University
of Notre Dame, Resources:
http://www3.nd.edu/~rwilliam/.
Www.euromonitor.com/ready-meals-in-thailand/report.
Zikmund, W. G. (2003). Business research methods, (7th Ed.).
USA: Thomson South-Western.

http://www3.nd.edu/~rwilliam/
http://www.euromonitor.com/ready-meals-in-thailand/report
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MAR 3211, Consumer Behavior 1
Course Learning Outcomes for Unit I
Upon completion of this unit, students should be able to:
1. Discuss how the field of marketing is influenced by the
actions of consumers.
1.1 Analyze how the actions of consumers impact an
organization.
3. Explain how consumers interpret information about products
and people.
3.1 Describe factors that will impact how consumers view and

ultimately purchase products and
services.
7. Explain the steps of the consumer decision-making process.
7.1 Explain the steps in the consumer decision-making process
and how they relate to consumer
behavior.
Course/Unit
Learning Outcomes
Learning Activity
1.1
Unit Lesson
PowerPoint Presentation
Foxall and Sigurdsson (2013) article
Article Review
3.1
Unit Lesson
Shateri, Nayebzadeh, and Roknabadi (2016) article
Article Review
7.1
Unit Lesson
Article Review

Reading Assignment
In order to access the following resources, click the links
below.
Click here to access the Unit I PowerPoint presentation. (Click
here to access a PDF version of the
presentation.)
Foxall, G. R., & Sigurdsson, V. (2013). Consumer behavior
analysis: Behavioral economics meets the
marketplace. The Psychological Record, 63(2), 231–238.
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Shateri, F., Nayebzadeh, S., & Roknabadi, A. D. (2016).
Evaluating advertisement: The role of customer's
decision-making style, innovativeness, and ideology.
International Journal of Information, Business
and Management, 8(4), 159–177.
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UNIT I STUDY GUIDE
Introduction to Consumer
Behavior and Decision-Making

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UNIT x STUDY GUIDE
Title
Unit Lesson
When you think of consumer behavior, what thoughts come to
your mind? Why do you think that there is a
consumer behavior course included in most marketing degree
programs? There are many definitions of
consumer behavior, but the main concepts involve studying how
people choose goods and services to fulfill
any wants or needs they may experience. Consumer behavior is
truly an ongoing process in which marketers

attempt to understand behaviors in order to fulfill the needs of
the consumer. Another focus of consumer
behavior is the spending habits of consumers. There is a need
for organizations to understand this behavior
as it relates to consumer buying. Identifying the stages of the
consumption process provides a good
perspective on how organizations accomplish this, beginning
with the pre-purchase stage where marketers
need to understand how a consumer begins the buying process.
Providing valuable information on the
worthiness of the product or service might be effective during
this stage. Subsequently, during the purchase
stage, the marketer should look to make the experience a
pleasant one. Finally, during the post-purchase
stage, the consumer decides if the product or service has truly
fulfilled his or her need. Think about a product
that you purchased recently. Was it a pleasant experience? Did
the product fulfill your needs? Would you
recommend it to friends? These are all questions that the
marketer is asking.
As marketers look to examine the
needs of consumers, it is
important to understand that the
most economical and effective
method for an organization to
meet consumer needs is to
identify a target market. The target
market is the group of people on
which marketers will focus their
marketing efforts. You are
probably wondering why
marketers would not prefer to
target everyone, which seemingly
would reach a larger market and

provide greater exposure. The
simple answer is that marketing
departments do not have
unlimited marketing budgets. It is
not financially feasible to attempt
to reach everyone. A better
method is to focus on a certain
group of individuals who would
most likely be interested in a
company’s product or service.
Understanding the needs and
wants of this group is paramount. The process of identifying the
target market begins with segmentation. This
involves dividing a broad population into subsets of consumers
based on several criteria. The first criterion we
will discuss is demographics, which involves looking at
characteristics such as age, gender, family structure,
social class/income, and race/ethnicity. Another criterion could
be geographic, which speaks to the region of
the country or world, region in a country, neighborhood, or even
the size of the city in which the consumer
lives. The psychographic criterion relates to personal values
that will drive perception and motivations. Finally,
the behavioral criterion utilizes the specific interests, rate of
use, and brand familiarity of the consumer. Once
a marketer has completed this segmentation process, he or she
can better identify a detailed description of
the target market.
Consumer at coffee shop
(Pexels, 2016)

UNIT x STUDY GUIDE
Title
Criteria Characteristics Example
Demographic Age, gender, family structure,
social class/income, family
life cycle, race/ethnicity
Identifies who the
consumer is and where
he or she is in life
Geographic Region of the country or
world, region in a country,
neighborhood, size of city the
consumer resides
Location in world or
country in which the
consumer lives
Psychographic Personality, perceptions,
values, beliefs
Reflect for weeks on a
purchase or buy quickly
Behavioral Special interests, rate of use,
brand familiarity

Soccer player, traveler,
healthy living
Table 1.1: Segmentation criteria
Involvement refers to the relevance in the consumer decision-
making process. What this suggests is that the
consumer’s perceived familiarity with the product, message, or
situation will have an impact. Product
involvement is simply the consumer’s level of interest in a
particular product; in contrast, message
involvement refers to the influence that media vehicles have on
the consumer. Finally, situational involvement
refers to whether the consumer is in a store, on a website, or at
a location where the product or service
is consumed.
Think about the theme stores and restaurants that we frequent
and how that theme encourages us to stay
longer and enjoy the environment or situation. Through all of
this, perceived risk is important—the greater the
risk, the less likely the consumer will be to make the purchase.
Perceived risk refers to any negative
consequence associated with the decision. This can involve
monetary risk, functional risk, physical risk, social
risk, or psychological risk. As expected, the monetary risk
involves a poor choice associated with the
exchange of too much money. Functional risk relates to a
situation when the product does not function as
expected, and physical risk is one that may physically harm the
consumer. Social risk involves a results that
may affect the consumer’s self-esteem, confidence, or image.
Finally, psychological risk reflects on the loss of
self-respect with a poor buying decision. The goal of the
marketer is to reduce these perceived risks as much
as possible in order to encourage and influence the consumer.

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