Michalski R. (2024). The influence of product digital visual presentation on purchase willingness: effects of roundedness axes and degree, Multimedia Tools and Applications, 83 (1), 2173-2202.   Cited (JCR): 0, Other Cites: 0 IF:3.6 5yIF:3.1 Pt:
Abstract
The research examines the influence of digital visual product package presentations on perceived purchase willingness. Subjects pairwise compared the graphical stimuli displayed on a computer monitor. Gathered purchase willingness preference weights were calculated by means of the Analytic Hierarchy Process technique. Two studies focused on the package edge roundedness effect applied along different axes are reported. The first one included the following factors: Roundedness axis defined on three levels (X, Y, Z) and Roundedness degree also specified on three levels (Small, Medium, Large). The second involved Roundedness type (two levels: All edges rounded, Only sides rounded – along one axis) and Roundedness degree (Tiny, Small, Medium, Large). Both package Roundedness axis and Roundedness degree influenced perception and purchase willingness. This research extends existing knowledge by presenting empirical evidence on how a variety of product digital forms influences visual perception and purchase willingness. The results deliver useful and detailed information for practitioners and the outcomes may be applied as guidelines for computer graphics designers preparing visual appearance for articles in electronic shops, websites, banners, or advertisements displayed in networked screens.
Keywords:
Digital package perception; Electronic commerce; Marketing; Roundedness axis; Visual processing
1. Introduction
In today’s highly digitized world, the importance of illustrating
products in a way that supports the customer’s willingness to buy is
ever more critical. Aesthetically pleasing products, their packaging
design along with graphical presentation in either electronic shops or
online advertisements may positively influence potential buyers’
perception and, therefore, have an impact on purchase decisions.
Product visualization is the process of creating visual
representations of various goods and services. This can be done by
designing, demonstrating, or advertising through physical means such as
building real-size or scaled mockups and models. Nowadays, visual
representations of products are often constructed using information
technology methods and tools. To facilitate communication of product
design and its features to stakeholders, various systems, or computer
software can be utilized. These multimedia tools enable the creation,
editing, and sharing of content, such as images, videos or animations.
They play a crucial role in digital product presentations, which are
designed to showcase product’s features, benefits, usage, and provide
additional information about them.
Generally, the interest in an effective product presentation is not
new and has been subject to investigation for a long time. Usually, a
given article is presented in packaging which typically serves the
following functions [63]: containment, protection, convenience, and
communication. Currently, situations when a product is physically not
available, for instance, software, music, or various kinds of services,
are not rare. It sometimes occurs that not only products, but also their
packaging exists only in a digital form. In such cases, the role of a
package is actually limited to providing information to customers.
Because of this, static visual message conveyance is gaining in
importance for both scientists and practitioners. On the one hand side,
psychologists or neurophysiologists try to discover how people respond
to specific factors related to graphical stimuli and explain it by
proposing formal theories. On the other hand, marketing research is more
focused on how these general rules influence human behavior in a real
environment or in a specific context. The present paper is
a continuation of the latter trend and systematically examines, in two
studies, inspired by results from more general fields of science, the
impact of the packaging presentation form on the potential buyers’
subjective purchase willingness. The general importance of research on
packaging and a detailed discussion of the relevance of its various
aspects was presented, e.g., by Sample and colleagues [67].
Although there was research dealing with how various packaging
features, such as rounded vs. angular shapes, can influence consumers’
perceptions, this study provides a more specific and detailed approach.
The roundedness factor is investigated along different axes of the
package and involves a number of degrees. Moreover, current studies,
unlike almost all prior studies, involve a product that, according to
Vaughn [77, 78], belongs to the high involvement class of goods.
One should also notice that the online product presentation context
examined in the present study is associated with some unique features
that are qualitatively different from in-store displays and real
packaging. Packages presented online may not exist in reality or it may
even be impossible or too expensive to produce them. Some of the digital
package designs could cause practical problems if they were physically
manufactured, e.g., the package largely rounded along the Z axis
examined in the current study would probably not stand firmly on the
shelf. Other package shapes might be troublesome while storing or
transporting.
Another difference is concerned with the lack of haptic interaction
in online purchases, which was identified as an important factor
influencing purchase decisions [16]. The absence of tactile experience
can influence the perception of visual components. Various aspects of
packaging are becoming important for practitioners and researchers who
are looking increasingly closely at the details of the product
presentation. For example, Togawa et al. [74] focused on the
influence of visual packaging design on flavor perception and healthy
eating decisions, whereas Simmonds and Spence [69] examined how
presenting products on, or through packaging impacts consumer
perceptions and purchase behavior. Other sensory aspects of package
design are thoroughly discussed in the work of Krishna and colleagues
[41].
In the following sections, a brief literature review regarding visual
aspects of human processing together with research on digital and real
package demonstrations is provided. To provide an appropriate context
and reinforce the importance of product packaging digital presentation,
the paper outlines the strong relationships between this concept and
various multimedia tools and systems. It is supported by relevant
references. Based on this, specific hypotheses are formulated. Next,
there are detailed reports from the two studies including results,
statistical analyses, and discussion of findings. General discussion
along with limitations and future research end up the paper.
2. Related work
2.1. Multimedia Systems and Tools Regarding Product Visualization
There is a close relationship between multimedia tools and digital
product presentations. Various tools enable the creation of high-quality
product and its packaging images and videos that can be used to showcase
different aspects of a product and provide a better understanding of it.
Computer-aided design (CAD) software is one of the key systems involved
in detailed product visualization [11, 26, 39]. This software allows
designers and advertisement specialists to create two and
three-dimensional models of products, including their geometry,
materials, and textures [70, 79]. CAD software typically includes a
range of tools for modeling, rendering, and animation. Some studies have
used CAD software to generate product visualizations and employ them in
marketing research [29, 49, 50, 59]. The latest technological
developments can significantly facilitate content creation by
transforming free-hand paper sketches into realistic three-dimensional
digital objects [47]. Interestingly, even sketches hand-drawn in the air
can be used for generating digital object representations or searching
purposes [44].
In addition to displaying static rendered images, it is also possible
to create animations for product digital presentation. In this way, not
only the basic geometry of a product, including its shape and size, is
presented, but also motion and movement can be incorporated [27].
Animations can show product features from all angles (see, e.g., [53])
and demonstrate the kinematics of movable components [33]. Moreover,
they allow for simulations presenting how a product might behave in
different conditions and environments, or show how it can be assembled
or disassembled [38]. Although creating animations is usually more
demanding than elaborating still images, recent advancement can make it
simpler by providing appropriate methods and tools, such as automated
video creation (see, e.g., [32, 43]).
Other systems involved in product visualization can include virtual
and augmented reality platforms, which allow users to experience and
interact with products in a simulated three-dimensional environment
[76]. These systems can be particularly useful for product
demonstrations [27] and user testing, as they allow customers to
experience a product in a more immersive way. An example is the
application of so-called situated visualization. A brief description of
how this type of information support may be incorporated and facilitate
decision-making in everyday real-life shopping is provided, e.g., in
[48]. Taking advantage of mixed reality, product visualization can play
an important role during design and production. It can reduce costs of
developing new or changing existing products as well as speed up the
assembly process or training inexperienced workers (see, e.g., [14, 30,
75]; for a comprehensive review, refer to [25]). This area of research
and applications is becoming more popular as augmented reality is
increasingly common and appropriate software for visualization is not
necessarily expensive [52, 73].
Finally, multimedia tools related to the Internet facilitate the
sharing of digital product presentations. They can be easily distributed
on websites, social media platforms, and other digital channels,
allowing potential customers to access the information they need at any
time and from practically any place in the world.
2.2. Objects’ Shapes and Their Human Visual Perception
Object shape perception has been subject to investigation by many
researchers from various fields of science. One of the interesting
directions is the subjects’ response to curved versus angular objects.
More than 55 years ago, Berlyne [8, 9] suggested that people may link
angular figures with energy, toughness, and strength, while rounded
contours with approachableness, friendliness, and harmony. The latter
set of traits commonly seems to be more attractive, thus, curved shapes
should possibly be better liked than the edgy ones.
Particularly extensive investigations in this regard were reported by
Bar and Neta in their three papers [4–6]. In the first study, they
examined 117 pairs of real, every day three-dimensionally looking items
plus 23 English characters and 140 pairs of two-dimensional meaningless
patterns. All graphical objects’ pairs had the same meaning and were
differentiated only by the curvature of their contours. The study
clearly showed that people preferred more curved than edgy shapes. They
argued that sharp transitions in contours might be associated with a
sense of threat and therefore evoke negative attitudes. This hypothesis
was further pursued in the next work of Bar and Neta [6]. In this study,
they took advantage of functional magnetic resonance imaging (fMRI) of
the human brain to investigate this phenomenon in a series of three
experiments. The obtained data confirmed their previous results showing
reduced likings for sharp-angled objects, which was accompanied by an
increased amygdala activation for this condition versus curved objects.
Since such brain activation is typical for an increased sense of threat
and danger [1, 81], they confirmed their conjecture that objects may be
subconsciously perceived in this way based solely on their contours’
features. In the last study, Bar and Neta [5] discuss their previous
results and embed them in a more general theory describing how people
make fast predictive judgments based on characteristic objects’
features.
Stimuli examined in the papers described above either presented
two-dimensional shapes or included three-dimensional looking objects
that were not manipulated in the experimental design. Some of the other
investigations focused on persons’ attitudes towards two- or
three-dimensional objects being either displayed in various ways or
deformed according to specific rules. Silvia and Barona [68], for
instance, in their two experiments, examined people’s preferences
towards the angularity degree. They reported a strong influence of this
effect both for arrays of circles and hexagons as well as for random
polygons and their rounded versions. They controlled for symmetry,
prototypicality, and balance. One of the especially interesting works in
the neuroscience field was conducted on macaque monkeys by Kayaert
et al. [36]. They examined the responses of neurons located in
the inferior temporal cortex to various three-dimensionally looking
shapes. Unlike in some previous studies, they manipulated the objects’
shapes systematically in a fully controlled experiment. Later, Kim and
Biederman [37] examined similar differences in objects’ relations in
humans.
2.3. Package Designs and Consumers’ Behavior
The importance of a package function concerned with communication
with a customer has been acknowledged many years ago see, e.g., Dichter
[21], Cowley [19]. Thus, it is not surprising that there exists a
significant amount of research dealing both with classical packages and
with their digital versions. Azzi et al. [2] reviewed and
classified scientific papers in this area published between 1990 and
2011. Among the most important fields of research regarding package
design, they include marketing and communication.
Studies confirmed that various types of package designs have a
significant effect on peoples’ brand impressions [56] and evaluation
[46]. Packaging has also an impact on consumer price expectations [55]
and this, in turn, influences final purchase decisions [10]. Reimann
et al. [62] have shown that people prefer aesthetically
pleasing packages – even if their prices were higher – over products of
well-known brands in standardized packages. Based on fMRI data, they
also noticed that people’s affective product involvement was connected
with aesthetic product perception.
In recent years, some studies focused specifically on consumers’
responses towards packaging or its components. The package graphics
design has been subject to investigation, e.g., by Westerman et al.
[80]. They showed the importance of the shape, angularity, alignment,
and orientation effects in a more specific context of design labels of
water and vodka. An interesting investigation of Clement et al. [17]
based on two eye-tracking experiments showed a statistically meaningful
effect of packaging on human visual attention. The authors determined
that the contour and contrast dominate the early stage of the product
search. In a recent study, involving the analysis of yoghurt packages,
Suzianti et al. [72] confirmed some previous results showing
that rounded packages were better rated than the angular ones. By using
conjoint analysis, they demonstrated that the shape factor was the most
important in comparison with a font type and a color scheme. In light of
these outcomes, the packaging shape effect on human behavior seems to be
especially worth paying attention to. As far as the angular and curved
shapes are concerned, Zhang et al. [83] provided some evidence
that the liking of more angular or rounded shapes may be related to the
interdependent self-construal. Their claim was confirmed in a field
experiment where subjects’ subjective attitudes towards shapes in actual
corporate logos from culturally different countries were
investigated.
3. Research Hypotheses
A great body of literature concerned with the visual aspects of
packaging has been focused on low involvement products classified by
Vaughn [77, 78]. Among them, there were works examining packages
containing chocolate and salt [45], orange juice, chocolate bars, pasta
and biscuits [42], snacks [13], yoghurt [7, 72], jam [17], wine [57,
71], Champagne [22], vodka [80], shampoo [28], non-prescription drugs
[34, 35]. Among a few papers that investigate other types of products,
there is the work of Grobelny and Michalski [29]. They examined
smartphone package designs differentiated by background colors, brand’s
name position in relation to the product’s picture, and the typography
of the brand name. In the current study, the trend is continued by
analyzing smartwatch packages that draw noticeably more consideration
than low-involvement items.
As it was presented in the literature review, there are studies
concerning the perception of digitally presented three-dimensional
looking objects, however similar investigations concerning virtual
high-involvement product presentations are rare. Taking this into
account and in light of the studies regarding curved and edgy shapes,
the following hypothesis may be generated:
H1: Rounded packages have a more positive impact on customers’
purchase willingness than classical cuboid shaped ones.
Although some studies dealt with package shape perception and its
importance in human’s purchase behavior, there is a significant shortage
of research that investigates this factor in a more systematic way in
diverse contexts. There is still a number of questions that need to be
addressed and clarified. For example, it is not known whether rounding
box package edges along a specific symmetry axis has an impact on human
perception or, to what extent the various degrees of objects’ curvature
may influence subjects’ purchase willingness. Thus, the following
hypotheses were formulated:
H2: Applying curvature to package edges along X, Y, and Z axes does
not influence customers’ purchase willingness.
H3: Bigger degree of roundedness applied to packages increase
purchase willingness.
These hypotheses are examined in Studies 1 and 2 presented in next
sections.
4. Study 1: Effects of Package Roundedness Axis and Degree
4.1. Stimuli
Subjects were asked to assess their purchase willingness of a
fabricated device which was displayed on the virtual package together
with a fictious brand name. The product image used in this study was
created by deleting any identification elements from the picture of a
real device. Images of digital packaging were designed in 3D Studio Max
environment version 6.0. All prepared 3D grey objects were based of
cuboids having the depth (equivalent to the X axis from Figure 1) of one
unit, the height (corresponding to the Y axis) of three units, and the
width (referring to the Z axis) of two units. These dimensions obey the
so-called golden proportion, which according to many studies [20, 54,
60] is the most preferred one. The following two independent variables
differentiated the digital product presentation: (1) Roundedness axis of
which specified rounded edges and (2) Roundedness degree. The former
effect was examined on three levels including X, Y, and Z axes of
symmetry. The latter one involved three levels of roundedness extent.
They were set at radii 0.1, 0.3, and 0.5 of a unit and named Small,
Medium, and Large. As one of the box dimensions measured one unit, the
roundedness degree could not be bigger than 0.5. The next levels were
determined by decreasing linearly the biggest radius value using the 0.2
step. Based on these two factors, nine different electronic versions of
the mockup packages were prepared. As a point of reference, a typical
box with all sharp edges was also included in this study. A front view,
grey scale picture of a smart watch without 3D perspective, was picked
to minimize the influence of other factors on the results. All ten
experimental conditions regarding package shapes together with axes’
denotations are illustrated in Figure 1.
Figure 1. Product presentation variants investigated
in Study 1.
4.2. Design and Procedure
A full factorial design was used for package shapes, so each
participant evaluated all ten experimental conditions, namely, three
Roundedness axes of symmetry {X, Y, Z} ×
three roundedness degrees {Small, Medium,
Large} plus one classic box without any edges rounded. These
conditions were examined within subjects. Information about the goal and
the general procedure of the experiment was presented to all
participants before they gave informed consent to take part in the
study. At the beginning, they answered some typical questions about
themselves such as gender and age. Then, the proper part of the
examination took place. The subjects pairwise compared the product
package pictures appearing on a computer monitor.
They were told to choose this version of the digital presentation,
which would better persuade them to buy the displayed product. The
degree of their preference was to be specified on the following scale:
No preference, Somewhat more, More, Much
more, and Decidedly more. Pairwise comparisons are
considered to provide more precise results than a direct ranking of
assessed variants [40]. However, this method requires significantly more
effort from subjects because the number of comparisons (c)
increases quickly with the number of objects being evaluated
(n), and follows this formula
c = (n2 - n) / 2.
Because this study involved ten package variants, the number of
necessary comparisons amounted to (100 - 10) / 2 = 45.
Figure 2. An exemplary single comparison displayed
by experimental software.
The digital product packages were displayed by an application written
in a Microsoft Visual Basic, (version 6.0, service pack 6.0)
environment. The software controlled the random presentation of
appropriate pairs of pictures. The left-right location of variants
within a single comparison was also set at random. The illustration of
the software with an exemplary comparison is demonstrated in Figure
2.
The same application collected and processed participants’ responses,
saved them in a relational Microsoft Office Access (version
2003) database, and later exported the data to a statistical package
(TIBCO Statistica, version 13.3).
The pairwise comparison results for a particular participant were
mathematically processed further by constructing a square symmetric
matrix, denoted as PRi, where
i represents the participant number. The matrix contained
dominance values of each assessed variant over every other variant. To
make the calculations possible, ones, equivalents of the “No
preference” response, were put on the diagonal. For all matrices of
pairwise responses, the final hierarchy of participants’ preferences was
computed according to the Analytic Hierarchy Process (AHP) method
proposed by Saaty [65, 66]. This computation formally involved finding
the eigenvector (Vi) and eigenvalue
(Λi) decomposition of matrix
PRi, by solving the matrix equation
PRi· Vi = Λi·
Vi. After applying the appropriate
algorithm, the eigenvector (vi
(max)) associated with the largest eigenvalue
(λi (max)) approximated the weights of
preferences for the investigated visual stimuli.
Finally, the vectors are standardized so that their values sum up to
one. A bigger weight denotes a bigger preference of a given stimulus.
Another useful feature of this technique is the possibility of verifying
individuals’ consistency of responses by calculating consistency ratios
(CRi). The CR values are computed for every
participant based on the maximal eigen value (λi
(max)), the random consistency index
(RIn), which compensate for the number of compared
items n, and has been experimentally determined for a given
item set [65, 66]. First, the consistency index
(CIi) is derived according to formula ${CI}_{i} = \frac{\lambda_{i\ \left( \max \right)} -
n}{n - 1}$ , then
${CR}_{i} = \frac{{CI}_{i}}{{RI}_{n}}$.
The smaller the CRi, the more coherent subject
responses are. Values of CRi close to one are
obtained for responses generated randomly. Both preferences’ vectors and
CRs are used in the current study as dependent measures and analyzed in
the next section.
The studies were conducted in university teaching laboratories using
identical desktop computers and comparable lighting conditions. The
workstations had the same computer mice and 17” LCD monitors with a 1024
by 768 pixels resolution. A classic Microsoft Windows XP color scheme
was used on all computers.
4.3. Participants
The subjects were recruited from among University of Science and
Technology students. The sample included 62 males and 53 females with
the youngest being 18 and the oldest 26 years old (Mean = 20.58, SME =
0.125). All subjects reported normal or corrected to normal visual
acuity.
4.4. Results
Subjects’ consistency ratios computed according to the AHP
methodology varied from 0.0018 up to 0.06 with the mean of 0.0136 and
the Standard Mean Error (SME): 0.00091.
Standard one-way Anova showed that there was no statistically
significant difference in mean CR values for males and females
[F(1, 113) = 1.46, p = 0.23]. Since all CRs were below
the recommended by Saaty (1977, 1980) threshold of 0.1, further analyses
include the data of all examined subjects.
4.4.1 Descriptive Statistics
Averaged preference weights for all conditions from Study 1 are
demonstrated in Figure 3, while basic descriptive statistics are put
together in Table 1. The highest mean score was computed for the package
version with small rounded edges parallel to the X axis. The classic box
occurred to be the worst, however differences among the worst 8 variants
were very small and, according to Fisher’s LSD post hoc pairwise
comparisons, almost in all cases statistically irrelevant (Table 2). The
final preference hierarchy of the examined variants are given in Figure
4.
Analyzing the data from Table 1 and Figure 3, a fairly clear pattern
may be observed. Subjects’ willingness to buy decreased along with
increasing the edges’ roundedness degree. Secondly, it seems that
participants generally liked rounded edges along the X axis, the best
rounded edges parallel to the Y axis were in the second place, while
roundedness along the Z axis occurred to be the least preferred. These
observations are formally verified by applying Anovas in the next
subsection.
Table 1. The basic descriptive statistics for all
conditions in Study 1.
Package variant |
Basic descriptive statistics |
No |
Roundedness axis |
Roundedness degree |
Mean |
SME |
Median |
Min |
Max |
SD |
1. |
None |
None |
0.0956 |
0.0024 |
0.0880 |
0.0555 |
0.1646 |
0.0258 |
2. |
Edges parallel to X |
Small |
0.1071 |
0.0019 |
0.1099 |
0.0728 |
0.1606 |
0.0208 |
3. |
Edges parallel to X |
Medium |
0.1062 |
0.0017 |
0.1042 |
0.0728 |
0.1595 |
0.0178 |
4. |
Edges parallel to X |
Large |
0.0996 |
0.0018 |
0.0959 |
0.0625 |
0.1600 |
0.0196 |
5. |
Edges parallel to Y |
Small |
0.1013 |
0.0014 |
0.1016 |
0.0624 |
0.1370 |
0.0150 |
6. |
Edges parallel to Y |
Medium |
0.0994 |
0.0013 |
0.0996 |
0.0725 |
0.1362 |
0.0139 |
7. |
Edges parallel to Y |
Large |
0.0970 |
0.0016 |
0.0949 |
0.0671 |
0.1414 |
0.0174 |
8. |
Edges parallel to Z |
Small |
0.0990 |
0.0012 |
0.0979 |
0.0701 |
0.1490 |
0.0128 |
9. |
Edges parallel to Z |
Medium |
0.0978 |
0.0019 |
0.0971 |
0.0614 |
0.1528 |
0.0205 |
10. |
Edges parallel to Z |
Large |
0.0970 |
0.0022 |
0.0909 |
0.0554 |
0.1567 |
0.0233 |
Table 2. Fisher’s LSD post hoc pairwise comparisons
for all conditions in Study 1.
|
Not rounded |
X edges rounded |
Y edges rounded |
Z edges rounded |
Small |
Medium |
Large |
Small |
Medium |
Large |
Small |
Medium |
Large |
X edges rounded |
Small |
<0.0001*** |
× |
|
|
|
|
|
|
|
|
Medium |
<0.0001*** |
0.72 |
× |
|
|
|
|
|
|
|
Large |
0.12 |
0.0029** |
0.0088** |
× |
|
|
|
|
|
|
Y edges rounded |
Small |
0.026** |
0.021** |
0.052* |
0.50 |
× |
|
|
|
|
|
Medium |
0.13 |
0.0024** |
0.0075** |
0.96 |
0.46 |
× |
|
|
|
|
Large |
0.58 |
0.0001*** |
0.0003*** |
0.32 |
0.09* |
0.34 |
× |
|
|
|
Z edges rounded |
Small |
0.18 |
0.0014** |
0.0045** |
0.83 |
0.37 |
0.87 |
0.44 |
× |
|
|
Medium |
0.39 |
0.0002*** |
0.0009*** |
0.48 |
0.17 |
0.52 |
0.76 |
0.63 |
× |
|
Large |
0.58 |
0.0001*** |
0.0003*** |
0.32 |
0.09* |
0.35 |
0.998 |
0.44 |
0.77 |
× |
* α < .1; ** α < .05; ***
α < .001
Figure 3. Mean preference weights for all conditions
in Study 1.
Figure 4. Final preference hierarchy in Study 1.
4.4.2 Analysis of Variance
A formal examination of the gathered data, initially described in the
previous section, was carried out by means of the standard three-way
Anova. For this purpose, the experimental condition with a classic
cuboid package was excluded from the analysis. Taking into account the
possible association between angularity-masculinity and
femininity-roundedness [23, 24], gender was also included in the
analysis. The Anova results given in Table 3 revealed that Roundedness
axis [F(2, 1017) = 9.7, p = 0.0001,
η2 = 0.019] and Roundedness degree [F(2,
1017) = 5.8, p = 0.0030, η2 = 0.011]
considerably influenced mean participants’ weights. According to the
Cohen’s [18] rule of thumb (small ≈ 0.01, medium ≈ 0.06, and large ≈
0.14), the reported values of partial eta-squares
(η2) for both significant factors indicate that
their effect size was small. Although the Gender effect alone was
insignificant, its interaction with Roundedness axis was meaningful
[F(2, 1017) = 21, p < 0.0001,
η2 = 0.039].
The graphical representation of average preference weights along with
95% confidence intervals (whiskers) for statistically meaningful effects
are provided in Figures 5, 6, and 7. In all tables presenting Anova
results, the following abbreviations are used: SS –Sum of
Squares, MSS – Mean Sum of Squares, df – degrees of
freedom.
Table 3. Three-way Anova results for Study 1. The
influence of package roundedness axis, roundedness
degree, and gender on mean preference weights.
Effect |
SS |
df |
MSS |
F |
p |
η2 |
Roundedness axis (RA) |
0.0062 |
2 |
0.0031 |
90.7 |
0.0001* |
0.019 |
Roundedness degree (RD) |
0.0037 |
2 |
0.0019 |
50.8 |
0.0030** |
0.011 |
Gender |
0.000092 |
1 |
0.000092 |
0.29 |
0.59 |
|
RA × RD |
0.0014 |
4 |
0.00035 |
10.1 |
0.35 |
|
RA × Gender |
0.013 |
2 |
0.007 |
21 |
<0.0001* |
0.039 |
RD × Gender |
0.00026 |
2 |
0.00013 |
0.41 |
0.66 |
|
RA × RD × Gender |
0.00076 |
4 |
0.00019 |
0.59 |
0.67 |
|
Error |
0.33 |
1017 |
0.00032 |
|
|
|
* α < 0.0001; ** α < 0.05
Figure 5. Effect of Roundedness axis on
mean preference weights
[F(2, 1017) = 9.7, p = 0.0001,
η2 = 0.019].
Figure 6. Effect of Roundedness degree on
mean preference weights
[F(2, 1017) = 5.8, p = 0.0030,
η2 = 0.011].
Figure 7. Effect of Roundedness axes ×
Gender on mean preferences weights
[F(2, 1017) = 21, p < 0.0001,
η2 = 0.039].
Performed Anovas formally confirm general observations based on basic
descriptive statistics. Participants liked the best situation when the
edges parallel to the X axis were rounded, the roundedness along the Z
axis was rated the worst, while packages with Y axis edges rounded were
in the middle. The post hoc Fisher’s pairwise comparisons showed that
the difference between Y and Z axes is statistically irrelevant
(α > 0.1), whereas all other differences were
significant.
Participants’ purchase willingness depended almost linearly on the
degree of roundedness, being the biggest for packages with small
roundedness and the smallest for the most rounded versions. Moreover,
for this factor, the Fisher’s pairwise post hoc tests showed
statistically meaningful differences (α = 0.005). Only the
discrepancy between Small and Medium levels of Roundedness degree was
not significant (α > 0.1).
The Gender × Roundedness axes interaction from Figure 7 suggests that
the significance of the main Roundedness axes effect was produced mainly
by males. Post-hoc pairwise tests confirmed that discrepancies between
Roundedness axes for women were not statistically meaningful (α
> 0.1).
4.5. Discussion
The findings of Study 1 do not fully support H1. A comparison of
purchase willingness rates for rounded variants with a plain box option
provided unexpected results confirming only to some extent the previous
psychophysiological results of better preferences for curved objects.
Although, in general, the sharp package version received the lowest
score, the mean preference weights for rounded objects were
significantly better than for the sharp edge box only when the edges
parallel to an X axis were curved slightly or medium and for the variant
with small rounded Y axis edges (conditions no. 2, 3, and 5). For all
remaining experimental conditions, the rounded packages did not differ
significantly from the plain cuboid.
The presented Anova findings show that subjects’ purchase willingness
was influenced both by the axis along which the package edges were
rounded as well as by the degree of applied curvature.
Data do not provide evidence supporting H2 which predicted no
influence of the first factor. One of the possible explanations of
favoring options with edges rounded along the X axis may be connected
with the product shape presented on the frontal plane of the package.
Particularly, with visible smartwatch curvatures corresponding to
packages with X axis edges rounded. Some previous studies in other areas
showed that people tend to rate better package attributes if they were
consistent with the product. For instance, Middlestandt [51] showed that
blue background color was more preferred than red for a pen, while for a
bottle of mineral water and a bottle of perfume there was no difference
between these colors. More evidence in this regard was reported, e.g.,
by Bar [3]. A similar effect could have influenced the participants’
purchase willingness in the current study. In a general psychology area,
one of the theories in this regard was put forward by Reber et
al. [61]. Based on a review of many investigations, they claim that
aesthetic preference judgments are mainly affected by processing
fluency. If we assume that the higher correspondence between the
packaging shape and the presented product results in better processing
fluency, the present findings to some degree support the theory.
Such an explanation, however, is in contrast to the contour of the
smartwatch strap visible in the picture. The smartwatch image, as a
whole, rather resembles packages rounded along the Z axis than others,
so subjects should favor them, which was not the case. The packages with
Z axis rounded edges were among the least preferred ones, and the
variant with the small rounded Y axis edges was the third best rated.
What is probably even more intriguing and difficult to explain, the
Roundedness axes factor was statistically meaningful only for male
subjects (Figure 7 and post hoc tests). For females, this effect was
irrelevant.
Regarding the second factor, it occurs that when the degree of
roundedness increases, the purchase willingness is becoming smaller and
smaller, which is in contrast with H3. The effect of decreasing values
of buying preferences for bigger curvatures may be partly attributed to
the fact that such packages are rarely to come across in real situations
or even in the virtual world of online product presentations.
Unfamiliarity with such shapes in this context may have markedly
diminished the positive impact of package roundedness. Such an
explanation is consistent with accidentally obtained results in Bar and
Neta [4], where real known objects were better rated on average than
meaningless, novel shapes. This effect was also earlier reported in
numerous general psychological studies. Zajonc [82] provides an
extensive discussion on possible explanations based on neuroanatomical
evidence of this mere-repeated-exposure phenomenon.
Another reason of the low rates for the most curved options may lie
in the fact that they seem to be less physically stable than the classic
box package. The solidity sensation has also been mentioned as one of
the factors that may affect human preferences [58]. Bigger degrees of
roundedness might have also looked as less realistic, which could have
affected the customers’ perception of the whole product presentation.
For instance, they may not be recognized as typical product packages.
The cognitive load increases as the customer comes across a nontypical
situation. This, in turn, requires longer processing which, according to
Reber et al. [61], may negatively affect peoples’ buying
preferences.
5. Study 2: Effects of Package Roundedness Type and Degree
5.1. Stimuli
Similarly to the first study, participants expressed their perceived
willingness to purchase a fictitious device demonstrated on a virtual,
box-shaped package. The digital packages had the same dimensions’
proportions as in Study 1. The second study was complementary to the
first one and dealt also with rounded edges, however, the main purpose
of this investigation was to compare boxes where only edges parallel to
one axis are rounded with the situation where all edges are curved. The
X axis was chosen as the most popular. Thus, the first independent
variable Roundedness mode was specified on two levels: (1) All edges
rounded, and (2) Only sides rounded (only edges parallel to the X axis
rounded).
While analyzing the results from Study 1, it occurred that packages
with rounded edges parallel to the X axis were significantly better
rated than other variants. Roundedness degree was investigated as the
second factor. The effect was examined on four levels. Three of them
were the same as in Study 1, namely, Small (radius 0.1), Medium (0.3),
and Large (0.5 of a unit).
The Study 1 statistical analysis revealed that the smaller the
roundedness degree, the bigger were the average weights. An additional
roundedness degree was included in this study to test whether this
tendency will be maintained for a considerably smaller roundedness
degree. Thus, the fourth radius was set at a value twice as small as the
smallest value from Study 1, that is, 0.05 of a unit, and was denoted as
Tiny. A combination of these two factors provided eight different
experimental conditions. All of them, along with the classical sharp
package which was also included in the design, are presented in Figure
8.
Figure 8. All product presentation variants
investigated in Study 2.
5.2. Design and Procedure
A full factorial design was applied to the shape effects. Thus,
subjects assessed all nine digital package variants, that is, two
Roundedness types {All edges rounded, Only side edges rounded} × four
Roundedness degrees {Tiny, Small, Medium, Large} together with a classic
box with all sharp edges. These conditions were investigated within
subjects.
The procedures applied here were identical to the one from the first
study, and the same software was taken advantage of to present the
stimuli and do the calculations. As there were nine different package
versions, the number of necessary comparisons equal to (81 - 9) / 2
= 36. The studies were carried out in the same university teaching
laboratories as in the first study with identical hardware and
software.
5.3. Participants
The same group of 115 subjects as in the first study investigated the
stimuli in Study 2.
5.4. Results
In the second study, the smallest consistency indicator amounted to
0.00222, while the highest observed value was as big as 0.0588. The
average CR value equaled 0.0134 ± 0.000885 SME. One-way Anova discovered
no meaningful differences in average CRs for women and men
[F(1, 113) = 0.067, p = 0.80]. As all CRs were below
recommended by Saaty [65, 66] threshold of 0.1, further analyses include
weights computed for all examined subjects.
5.4.1. Descriptive Statistics
Basic descriptive characteristics of participants’ purchase
willingness expressed towards all versions of the package design in the
second study are provided in Table 4 and graphically presented in Figure
9.
The most favorite option on average occurred to be the one with Only
sides rounded (along axis X) to a Medium degree. On the other hand,
subjects disliked the sharp edge version the most. The markedly biggest
mean standard error was observed for the ninth condition. Relatively big
values of SME and mean confidence intervals demonstrated in Figure 9 may
denote that the subjects’ preferences were either not very distinct or
were influenced by other factors. The full preference hierarchy obtained
by ordering weights is demonstrated in Figure 10.
Table 4. The basic descriptive statistics for all
experimental conditions in Study 2.
Package variant |
Basic descriptive statistics |
No |
Roundedness type |
Roundedness degree |
Mean |
SME |
Median |
Min |
Max |
SD |
1. |
None |
None |
0.0973 |
0.0020 |
0.0926 |
0.0619 |
0.1758 |
0.0216 |
2. |
Only sides rounded |
Tiny |
0.1037 |
0.0016 |
0.0988 |
0.0694 |
0.1545 |
0.0176 |
3. |
Only sides rounded |
Small |
0.1121 |
0.0015 |
0.1091 |
0.0801 |
0.1525 |
0.0163 |
4. |
Only sides rounded |
Medium |
0.1170 |
0.0016 |
0.1129 |
0.0881 |
0.1761 |
0.0166 |
5. |
Only sides rounded |
Large |
0.1152 |
0.0021 |
0.1110 |
0.0770 |
0.1771 |
0.0221 |
6. |
All edges rounded |
Tiny |
0.1113 |
0.0017 |
0.1093 |
0.0710 |
0.1631 |
0.0179 |
7. |
All edges rounded |
Small |
0.1159 |
0.0015 |
0.1173 |
0.0783 |
0.1535 |
0.0158 |
8. |
All edges rounded |
Medium |
0.1148 |
0.0022 |
0.1128 |
0.0703 |
0.1589 |
0.0235 |
9. |
All edges rounded |
Large |
0.1128 |
0.0029 |
0.1080 |
0.0618 |
0.1779 |
0.0306 |
Figure 9. Mean preference weights for all conditions
in Study 2.
Figure 10. Final preference hierarchy in Study
2.
Given the data from Figures 9 and 10, one may notice that packages
with all edges rounded seem to be generally better assessed than those
with only side edges rounded. It is hard to tell whether there is any
clear pattern concerned with the applied roundedness degree, as there
are considerable variations between individual conditions. However, the
data suggest that there may exist a type of optimal amount of
roundedness as the medium rounded variant was the best in the group
where only sides were rounded, while for All edges rounded condition,
the smaller roundedness degree was preferred (compare Figure 9).
Fisher’s LSD post hoc pairwise comparisons were used to formally verify
differences between conditions’ mean weights. The results are put
together in Table 5.
According to them, both the classic box package and its tiny rounded
along one side version were markedly worse (at least at a level of 0.05)
than all other versions. The data also show that there is a quite clear
tendency of increasing purchase intentions for bigger roundedness degree
when options with only sides rounded are concerned. In this case, Tiny
roundedness is significantly better than no roundedness, Small
is better than Tiny, and Medium receives higher rates
than Small roundedness. There is, however, no meaningful difference
between Medium and Large. Among variants where all
sides were rounded, the only statistically significant
(α = 0.1) difference was observed between Tiny and
Small roundedness levels.
Analyzing the data in Table 5 along with the final preference
hierarchy given in Figure 10, it could be seen that among the first
best-rated variants the differences are insignificant. Moreover, the
variants either with sharp or Tiny rounded edges are decidedly worse
than other options. Further formal statistical analyses are provided in
the next subsection.
Table 5. Fisher’s LSD post hoc pairwise comparisons
for all conditions in Study 2.
|
Not rounded |
Only sides rounded |
All edges rounded |
Tiny |
Small |
Medium |
Large |
Tiny |
Small |
Medium |
Large |
Only
sides rounded |
Tiny |
0.019** |
× |
|
|
|
|
|
|
|
Small |
<0.0001*** |
0.0024** |
× |
|
|
|
|
|
|
Medium |
<0.0001*** |
<0.0001*** |
0.073* |
× |
|
|
|
|
|
Large |
<0.0001*** |
<0.0001*** |
0.25 |
0.53 |
× |
|
|
|
|
All
edges rounded |
Tiny |
<0.0001*** |
0.0057 |
0.79 |
0.039** |
0.15 |
× |
|
|
|
Small |
<0.0001*** |
<0.0001*** |
0.17 |
0.69 |
0.82 |
0.097* |
× |
|
|
Medium |
<0.0001*** |
<0.0001*** |
0.32 |
0.43 |
0.87 |
0.20 |
0.70 |
× |
|
Large |
<0.0001*** |
0.001** |
0.79 |
0.13 |
0.37 |
0.59 |
0.26 |
0.46 |
× |
* α < 0.1; ** α < 0.05; ***
α < 0.001
5.4.2. Analysis of Variance (Anova)
A standard three-way analysis of variance was employed to formally
verify the differences between the analyzed effects. A classic cuboid
package was not included in this analysis. The first factor grouped
presentations with either only side edges rounded (symmetry along X
axis) or boxes having all edges rounded. The second factor
differentiated presentations by the degree of roundedness
(Tiny, Small, Medium, and Large).
Gender was included as the additional third factor. Anova
outcomes provided in Table 6 show no statistical significance of the
Roundedness type effect. The second factor was statistically
significant [F(3, 896) = 7.7, p < 0.0001,
η2 = 0.025]. Applying the Cohen’s [18] rule of
thumb, the size effect of this factor can be classified as small.
Table 6. Three-way Anova results for Study 2. The
influence of package Roundedness type, Roundedness
degree, and Gender on mean preference weights.
Effect |
SS |
df |
MSS |
F |
p |
η2 |
Roundedness type (RT) |
0.0010 |
1 |
0.0010 |
20.4 |
0.12 |
|
Roundedness degree (RD) |
0.0097 |
3 |
0.0032 |
70.7 |
<0.0001** |
0.025 |
Gender |
0.000011 |
1 |
0.000011 |
0.027 |
0.87 |
|
RT × RD |
0.0037 |
3 |
0.0012 |
30.0 |
0.031* |
0.0098 |
RT × Gender |
0.0052 |
1 |
0.0052 |
12 |
0.0004** |
0.014 |
RD × Gender |
0.0012 |
3 |
0.00040 |
0.94 |
0.42 |
|
RT × RD× Gender |
0.0012 |
3 |
0.00038 |
0.92 |
0.43 |
|
Error |
0.38 |
896 |
0.00042 |
|
|
|
* α < 0.05; ** α < 0.005
The Roundedness degree effect is illustrated in Figure 11.
Figure 11. Effect of Roundedness degree on
mean preference weights in Study 2.
[F(3, 896) = 70.7, p < 0.0001,
η2 = 0.025].
Additional Fisher’s LSD post hoc pairwise comparisons were performed
to see whether there were any differences between levels. These results,
put together in Table 7, revealed that the Tiny roundedness degree was
decidedly worse than all other factor levels.
Table 7. Fisher’s LSD post hoc pairwise comparisons
for the Roundedness degree effect in Study 2.
|
Tiny |
Small |
Medium |
Large |
Small |
0.0008* |
× |
|
|
Medium |
<0.0001* |
0.32 |
× |
|
Large |
0.0007* |
0.98 |
0.33 |
× |
*α < 0.001
The Anova also presents the existence of two significant
interactions: Roundedness type × Roundedness degree
[F(3, 896) = 3.0, p = 0.031, η2 =
0.0098] and Roundedness type × Gender [F(1,
896) = 12, p = 0.0004, η2 = 0.014]. The
first one, demonstrated in Figure 12, suggests that subjects preferred
packages with all rounded edges when the Roundedness degree was
Small.
Figure 12. Effect of Roundedness type ×
Roundedness degree interaction on mean preference weights in
Study 2. [F(3, 896) = 30.0, p = 0.031,
η2 = 0.0098].
For boxes with only sides rounded (symmetry along X axis),
Medium or even Large roundedness degrees were better
perceived. The second interaction (Figure 13) showed that men liked more
conditions with only sides rounded whereas females quite the opposite –
markedly favored options with all edges rounded.
Figure 13. Effect of Roundedness type ×
Gender interaction on mean preference weights in Study 2.
[F(1, 896) = 12, p = 0.0004, η2 =
0.014].
5.5. Discussion
In this follow-up study, the roundedness effect was further explored
to see whether curving all edges of the package box would result in
higher purchase willingness than in the case where edges only along the
axis X are rounded (the best from the first study).
Generally, all rounded shapes were perceived better than the sharp
version. This is consistent with the results from the first study where
Small and Medium conditions rounded along the X axis were
meaningfully better than the classical cuboid. In this respect, the
findings confirm H1.
The data analysis indicates that there are differences in perceiving
variants with all edges rounded and those curved only along the
X axis. This is again in contrast to H2 where no impact of
rounding specific axes was expected. Based on the literature review, one
could conclude that more roundedness transforms to bigger buying
preferences. However, if one takes into account the Roundedness
degree results and the Roundedness type × Roundedness
degree interaction, the picture seems not to be so clear.
The decreasing trends concerned with the Roundedness degree effect
for Small, Medium, and Large options (Figure
9) obtained for boxes with all edges rounded visually follow the
patterns from Study 1 (Figures 3 and 6), however the differences are
statistically irrelevant. Only the Tiny version in this case was
significantly less rated than the mean scores for the Small option. This
suggests that although Tiny roundedness is much better than the
sharp edge box yet worse than the Small version. Similar
relation may be noticed for boxes rounded along one axis, however in
this event, Medium is better than Small
(α < 0.1) and seems to constitute a kind of optimum. These
outcomes and the visual analysis of Figures 9, 11, and 12 rather do not
provide evidence for supporting H3, which assumed a positive and linear
relationship between bigger degrees of roundedness and purchase
willingness.
The different results obtained in the first and second studies are
probably caused by changing the context of comparisons. It is widely
acknowledged in the psychological literature that preferences may be
strongly influenced by conditions accompanying the examination. As
compared to the previous examination, another Tiny roundedness degree
level was included and a qualitatively different factor was added. It
occurred that the one axis (single axis symmetry) versus all edges
rounded factor probably had an impact on subjects’ perception. A similar
disturbing influence might be attributed to the additional level of
Roundedness degree.
The visual inspection of data regarding the Roundedness degree
(Figure 9) suggests that there probably exists an optimal value of this
feature since the Tiny rounded edges were on average worse than
their Small rounded counterparts. The statistically significant
interaction of Roundedness type × Roundedness degree
additionally supports the conjecture of optimal amount of roundedness.
The Roundedness type × Gender interaction revealed
that females markedly more preferred package variants with all edges
rounded. The effect of liking more rounded shapes by women is consisted
with studies showing associations between femininity and curved contours
[23, 24].
6. General Discussion
6.1. Theoretical Contributions
A number of past studies have tested curved versus angular shape
effects in various contexts, however it is unclear if the findings apply
also to customers’ purchase willingness for packages presented
digitally. The current study fills this gap by partly confirming the
better perception of some of the examined curved shapes as compared to
a standard edgy cuboid. These data also reveal that the roundedness
effect may be irrelevant to purchase willingness depending on other
investigated factors.
Apart from verifying the knowledge in a very specific context, the
research contributes to the existing literature by providing additional
insight about the influence of packaging features related to symmetry
that were earlier not examined in such detail. Data from Study 1 show
that purchase willingness of rounded packages decreases while increasing
the degree of roundedness, whereas findings from Study 2 suggest that
there probably exists optimum “amount” of the roundedness that
positively influences consumers’ perception and purchasing
willingness.
This research investigates a potentially important and, it seems that
yet not reported, impact of the axis along which the packaging edges are
rounded on buying willingness. It was identified that purchase
willingness was considerably higher when edges parallel to the
X-axis were rounded as compared with rounding along other axes.
This phenomenon was observed only for male participants.
6.2. Practical Implications and Applications in Technological Solutions
Besides the contributions presented above, the results of this study
provide valuable information for practitioners on how digital product
presentations influence perception and purchase willingness. From this
point of view, effective product digital demonstrations are crucial in
today’s world, where they are ubiquitous, and people often make
purchasing decisions based solely on them.
The outcomes revealed here can serve as direct guidelines for
computer graphics designers, who are preparing the visual appearance of
products or their packaging. These recommendations can be applied to
anything from two-dimensional projects to three dimensional models,
animations, and virtual reality experiences or interactive product
demonstrations. For example, designers can use these guidelines to
visualize and display goods or services in electronic shops, banners for
websites or advertisements demonstrated in outdoor digital billboards,
video walls or smaller screens placed in elevators, corridors,
supermarkets, and other settings. The possible applications are also
important for designing and creating marketing content in various
multimedia systems and platforms, such as video on-demand, interactive
TV, network kiosk systems or personalized electronic journals. It is
worth noting that even simple and relatively inexpensive changes to
product displays can result in increased sales.
In addition to the above-mentioned applications in classic
two-dimensional environments, these findings can also be applied to
technology solutions or multimedia tools for three-dimensional modeling
and rendering. For example, by creating three-dimensional product
packaging, designers can showcase the curved shapes and axes of
curvature in a more realistic and visually appealing manner. Another
possibility is to use augmented or virtual reality technologies, which
can provide customers with a more immersive experience, allowing them to
interact with the product packaging and visualize the rounded edges in
real-time. Furthermore, incorporating haptic feedback can enhance a
customer’s perception of the designed packaging enabling them to feel
the difference in roundedness between parts of the packaging design.
Moreover, incorporating interactive elements in different multimedia
technology solutions can facilitate manipulating and exploring the
product packaging design, providing a more engaging experience. This, in
turn, allows customers to better understand and appreciate the curved
shapes. For example, a potential user could drag their finger along the
surface of the packaging design, causing it to rotate and reveal
different angles and curves.
On the other hand, digital product presentation requires the use of
technology to communicate and demonstrate product features. The study
results presented provide valuable insights into user or customer
behaviors, needs, preferences, and expectations. Thanks to this,
technology solution providers can create multimedia software and
hardware tools that are intuitive, engaging, and effective themselves.
These findings can also be used to develop analytics tools and
applications that offer content creators and marketers detailed
information about how users interact with their content. By closely
monitoring customer preferences, companies can ensure that their
technology solutions remain relevant and effective in meeting the needs
of their target audience.
6.3. Limitations and Future Research
As usually, in experimental investigations, a number of various
limitations need to be taken into account while drawing conclusions. One
should be aware that the examined subjects are coming from a specific
and very homogenous population: there were almost only young white
students living within a single cultural society. Naturally, they may
not be representative of the general population as they possibly differ
in education, habits, values, attitudes towards technological
innovations, or electronic novelties. In spite of this obvious
limitation, the examined group seems to be a big potential target.
Nevertheless, to generalize the obtained outcomes to a broader group of
target consumers, this paper studies should be replicated on subjects
from other populations.
Although experimental forced choice-based methodologies can be highly
correlated with actual purchase decisions [12], it is not clear to what
extent the declared purchase willingness will translate to real buying
situations, all the more that the current findings are based on a fully
controlled study conducted in an artificial laboratory environment. The
presented research results would undoubtedly gain much of their
theoretical and practical importance and validity if the subsequent
research confirms the study results in more ecological situations.
One should also be cautious in generalizing the presented outcomes to
markedly different products, especially those belonging to different
than the higher involvement class. As it has been shown in some papers
cited in the literature review, the observed effects may change if a
desired attribute of the presented product will be directly related with
potency or strength (e.g., energy drinks, or vacuum cleaners) since
these features are usually associated with sharp edges. The research
direction including different classes of products naturally deserves
further exploration. There is also an interesting question whether
subjects are making different inferences about the product depending on
its packaging form.
The obtained results could have also been moderated by
individual-specific differences. Although the gender effect was included
in the analyses, one should bear in mind that women from a
technology-oriented university might not be representative of the whole
female population. Thus, in future studies, apart from fully controlling
the gender factor and choosing a more representative sample, one may
incorporate the effect of subjects’ degree of femininity and masculinity
measured, for instance, by the Franck and Rosen [23] test. Moreover, in
light of the results showing that people with a high sensitivity to
design like more rounded contours [7], next experiments might also
verify if this factor applies in the current study context.
Another important consideration is concerned with the applied method
of eliciting relative preferences by means of pairwise comparisons.
Although, such a technique provides more accurate results than other
approaches [40], it, unfortunately, highly restricts the possible number
of examined factors and their levels in a particular experiment. In
addition, the scope of a single study was also limited by a decision to
apply a full factorial design meant for exploring the effects’
interactions. As the interactions were not always identified in the
present research, future designs may be based on a fractional factorial
approach which would facilitate analyses of more effects in a single
study.
This paper focuses on still image digital presentations. However, a
number of studies have shown that dynamic visualization of product
information in the form of videos or animations can significantly
influence and shape customer purchasing behavior and preferences
(compare, e.g., [15, 31, 64]). Thus, future research should also examine
the influence of roundedness features of product packaging in dynamic
visualizations. Moreover, it would be very interesting to incorporate
the graphical features examined in the present study into investigations
involving virtual and augmented reality, which have experienced rapid
development recently.
7. Conclusions
Generally, the current research presents some empirical evidence on
how a variety of digital forms of product presentation involving various
features influences the purchase willingness of potential buyers. The
present investigation tries to add some more insights into this problem
by experimentally analyzing such aspects of product packaging as various
roundedness degrees and roundedness axes.
Multimedia tools play a critical role in the creation, editing, and
sharing of digital product presentations. By leveraging multimedia
techniques and systems effectively and taking advantage of relevant
study results on digital information visualization, marketers and
designers can create informative, and compelling product presentations
that showcase the value and benefits of their products.
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Acknowledgements
This research was partially financially supported by Polish National Science Centre
under Grant No. 2017/27/B/HS4/01876. The author thanks the anonymous reviewers for their constructive
comments and suggestions on the previous versions of the paper.
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