evaluacion affordances
TRANSCRIPT
Corresponding author:
Shih-Wen [email protected].
edu.tw
rdance evaluation model for
An online affoproduct designShih-Wen Hsiao, Chiao-Fei Hsu and Yin-Ting Lee, Department of Industrial
Design, National Cheng Kung University, No.1, University Road,
Tainan 701, Taiwan
This paper aims to establish an online affordance evaluation model for
measuring affordance degree to evaluate the usability of a product. By using this
model, designers could easily identify the appearance features of a product
necessary to be revised and optimized. In addition, an online survey, which
replaces the realized operational survey, is also recommended. This model
includes three parts: first, identifying the affordance properties and its
correlative weights by using multidimensional scaling, K-means clustering and
the Analytic Hierarchy Process; second, analyzing the user’s tasks and
functional components of the product; third, constructing an evaluation model
which provides the affordance degree. Finally, a case study with the steam iron
GC2510 is performed to verify the effect of this model.
� 2011 Elsevier Ltd. All rights reserved.
Keywords: product design, affordance, online evaluation model,
user interface design, humanecomputer interaction
With the progress of science and technology, newly-developed prod-
ucts with multiple powerful functions have come into existence.
However, multiple functions are often accompanied by complex
and difficult operations, which often cause unpleasant use experiences and
mental frustrations to consumers (Moggridge, 2007). In the The Theory of Af-
fordances, James Gibson (1977) presented an effective method to connect users
and products. When a user perceives the affordance clues from the appearance
features of a product, the user can correctly and intuitively operate the product
to complete the operating tasks without any explanation or specification
Gibson (1977, 1979/1986).
The theory of affordance was coined to explore the co-dependent relationship
between environment and animal. Gibson’s (1979) description of affordance is
“The affordances of the environment are what it offers the animal, what it pro-
vides or furnishes.” For example, if an object which has a rigid, level, flat and
extended surface and it is about knee-high to human, then it affords sitting-on.
If a human can detect visual information of the five properties, the object can
offer the affordance of sit-ability to the human. After that, affordance was
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doi:10.1016/j.destud.2011.06.003 126� 2011 Elsevier Ltd. All rights reserved.
An online affordance eva
introduced and applied to the design field by Norman, 1988. In Norman’s
view, affordance is the properties of the thing that directs the user how the
thing is to be used if it is perceived. Simply put, the user knows what to do
just by looking (Norman, 1988). Norman also mentioned how affordance
was used in computer systems, and then this concept was extended to the
HCI (HumaneComputer Interaction) design by Gaver (1991).
In product design, the concept of affordance provides a simplified and exter-
nalized framework to explain how the appearance features of a product can
direct a specific user’s action; and it also helps designers to shift their focus
from the user’s mind to their action, which suggests new possibilities for prod-
uct design (You & Chen, 2007). Recently, the number of products claiming to
be affordance-based has been growing considerably, and many designers have
unanimously incorporated the affordance concept into their development pro-
cesses (Stone, Wood, & Crawford, 2000). However, the concept of affordance
is ambiguous and not easy to express in precise analytical terms. The well-
intentioned affordance has become superficial, and what’s worse, has been
reduced to a design gimmick (McGrenere & Ho, 2000; Norman, 1999).
Galvao and Sato (2005) proposed that while a product can be described by its
function and its features, affordances can help users to accomplish their goals
and familiarize themselves with appropriate manipulations. They try to estab-
lish a quantitative evaluating method (Function-Task DesignMatrix) for eval-
uation of the affordance index of a product. This matrix constructs the
relationship between technical functions and user tasks. These functions are
important for product operation and can be the source of indirect affordances
to complete the user’s tasks. By identifying the relationships between functions
and tasks, an individual affordance index for each task of a product and a total
affordance index for a product can be obtained. An effective evaluation
method of affordance helps designers identify earlier the appearance features
of a product necessary to be optimized, which also assists users to operate
the product easily even when using a complex product for the first time.
Besides, with the advent of the Web, the Internet has evolved into a user partic-
ipation medium capable of high speed, on demand information delivery (Lee &
Chang, 2010). That being the case, much design information, such as marketing
research, and consumers’ preferences andneeds, has been surveyedwith question-
naires via the Internet. Considering the traditional operational survey, we see that
subjects must operate the realized product model and answer the questions per-
taining to feeling or experience of operation and/or the shortcoming of the prod-
uct. Compared to the online survey, the process of the traditional operational
survey not onlywastes labor and resources, but also limits the number of subjects.
This paper is based on the affordance concept and Galvao and Sato’s research
to propose an online affordance evaluation model for product design. With the
luation model for product design 127
128
evaluation result, designers can easily identify earlier the appearance features
of a product necessary to be optimized, and then the revised product can be
evaluated again until the affordances are proven ideal; that is, the user knows
what to do just by looking (Norman, 1988). This model also proposes an
online evaluation model to replace the realized operational survey for
usability of product, which can effectively save labor and time in the product
developing processes. This study consists of three parts: first, identifying the
affordance properties and its correlative weights by using multidimensional
scaling (MDS) (Kruskal, 1964; Schiffman, Reynolds, & Young, 1981;
Green, Carmone, & Smith, 1989), K-means clustering and the Analytic Hier-
archy Process (AHP) (Saaty, 1980; Hsiao, 2002); second, analyzing the prod-
uct to obtain the user’s tasks and its functional components for affordance
evaluation; third, constructing an online product affordance evaluation model
which can specifically quantify the level of affordance. The evaluation results
of this model include the overall and individual affordance score for each
property, each operational step, and each component. By analyzing the eval-
uation results, it can explicitly indicate how the unsatisfactory components
should be improved. Furthermore, specific reference data are provided for
the designer so that he/she may redesign and reevaluate the product. Finally,
a practical case study is performed on Company P’s steam iron, the GC2510,
in order to compare the affordance evaluation results before modification with
those after modification. Also, a verified experiment for correlation of the eval-
uation result between online and realized evaluation mode was performed. The
experimental results proved that this cost-efficient online affordance evalua-
tion model is reliable enough to replace realized operational experiments.
1 Defining affordance
1.1 Gibson’s affordanceThe theory of affordance is meant to explore the co-dependent relationship
between environment and animal. In the past, no specific term was used to
describe this relationship untilGibson coined affordance by adding the noun suf-
fix “-ance” to the verb afford. Gibson’s (1979) first description of affordance is
deceptively simple: “The affordances of the environment are what it offers the an-
imal, what it provides or furnishes, either for good or ill. What they afford the ob-
server, after all, depends on their properties.”This seems to imply that affordance
is a resource that the environment offers the animal (observer) which has capa-
bilities to perceive and use it. In other words, the environment of a given animal
affords behaviors for that animal. If a gap in a wall has a certain size relative to
the size of a person, the gap affords passage; if a surface is rigid relative to the
weight of an animal, it affords stance and perhaps traversal.
In Gibson’s book (1979/1986), The Ecological Approach to Visual Perception,
Gibson further defined “.the affordance of anything is a specific combination
of the properties of its substance and its surfaces taken with reference to an
Design Studies Vol 33 No. 2 March 2012
An online affordance eva
animal.” For example, if an object has a rigid, level, flat and extended surface
and it is about knee-high to a human, then it affords sitting on. These five
properties, rigidity, levelness, flatness, extendedness, and knee-height, are
combined to yield for the human. If a human detects visual information of
the five properties, the affordance of sit-ability offered by object can be per-
ceived (You & Chen, 2007); but the object may not provide support or per-
ceived sit-ability for another human, perhaps because of a differential in
weight or size (McGrenere & Ho, 2000). According to his view, an affordance
has three features (Galvao & Sato, 2005; McGrenere & Ho, 2000):
1. Affordance is the mutual relationship between environment and animal.
This relationship only exists relative to a particular animal which can per-
ceive it and use it.
2. Affordance is independent of the animal’s ability to perceive it, even with-
out the animal’s interpretation or experience.
3. Affordance is a constant which does not change as the animal’s needs and
goals do.
1.2 Further refinement of affordanceSome literatures extended Gibson’s affordance concept furthering the refine-
ment and formalization of affordance. Warren (1984) conducted an experi-
ment on stair climbing, and formalized the concept of affordance by using
ratios between the properties of environment and the properties of humans.
He defined p numbers to represent the affordance of stair climb-ability
between the height of stair (R) and the climber’s leg length (L); (p ¼ R/L).
He said, “This approach seeks a lawful explanation for the successful visual
control of action.” In Warren’s view, visual messages play an important role
in determining animal behavior. Humans can intuitively perceive the property
of an environment (stair-riser height), compare the perceived property with the
intrinsic property (leg length), and then establish the judgment of climbable
and unclimbable stairways. Consequently, different observers may have differ-
ent perceptions of the same environment. Turvey (1992) defined affordances as
being animal-relative properties of the environment that had significance for
the animal’s action. He also developed a formal definition of affordance: Let
Wpq (e.g., a person-climbing-stairs system) ¼ j (Xp, Zq) be composed of differ-
ent thing X (e.g., stairs) and Z (e.g., person). Let p be a property of X, and q be
a property of Z. Then p is said to be an affordance of X, and q is the person’s
ability of Z. Turvey believed that affordances are dispositional properties of
the environment and they must be complemented by properties of animals.
For example, nothing is soluble if there are no solvents; an object can be edible
only if there are animals that can eat and digest it. When properties of an an-
imal couple with the right properties of the environment, dispositions are guar-
anteed to become manifest. The soluble solid sugar always dissolves in water.
In addition, Turvey maintained that affordance is a capability which cannot be
selected by or imposed on an animal. By contrast, Chemero (2001, 2003)
luation model for product design 129
130
argued that affordance is the property of an environment, but it is the features
of an environmental object. He also argued that affordance relates to the prop-
erty of an animal in both Turvey’s and Warren’s researches, but it is related to
the ability of the animal. Assume there is an optimal ratio of height for stair
climbing, and all the information determines the tallest step an individual
could climb. For less flexible older adults, the steps are difficult to climb; for
flexible older adults, they have better stair-climbing abilities, so from them,
the stairs are easy to climb. Therefore, the ratio, which is the aspect of the en-
vironment perceived in determining climb-ability, is perceived in terms of
ability.
1.3 Affordance and designNorman (1988) introduced affordance concepts and applied them to the design
field through his book The Psychology of Everyday Things. He investigated the
affordances of everyday things, such as doors, telephones, and doors, and
indicated that the embodiment of these things provides strong clues as to how
to operate. According to Norman, “the term affordance refers to the perceived
and actual properties of the thing, primarily those fundamental properties that
determine just how the thing could possibly be used.” The definition of afford-
ance for Norman simply says that affordance is the properties of the thing,
which directs the user how the thing to be used if it is perceived. A new view-
point, “perceived affordances”, is recommended. Perceived affordances means
the properties of the object are perceived and interpreted as information by
the user’s mind which is based on his previous knowledge and experience. Com-
pared with Gibson’s affordances (“real affordance” in definition of Norman)
and Norman’s affordance (perceived affordance), real affordance is the action
possibility of objects with reference to physical characteristics of the object
that allow its operation; that is, perceived affordance is the perceived
information with reference to the mental and perceptual capabilities of the
user. For instance, the computer system with its keyboard, display screen, point-
ing device and selection buttons (e.g., mouse buttons) affords touching, looking,
pointing and clicking actions. Therefore, the computer system already has real
affordance. The graphs in screen-based interfaces can provide only perceived af-
fordance. While the user perceives that clicking on a graph (or object) is a mean-
ingful, useful action with a known outcome, perceived affordance can exist in
the graph/object and it is real used (Norman, 1999).
Gaver (1991) was the first pioneer to publish writings about applying afford-
ance concepts to the HCI (HumaneComputer Interaction) process. He pro-
posed, “when affordances are perceptible, they offer a direct link between
perception and action”, and “affordances per se are independent of percep-
tion.” The relation between affordances and perceptual information was
drawn in Figure 1. He explained that “Separating affordances from the infor-
mation available about them allows the distinction among correct rejections
and perceived, hidden and false affordances.”
Design Studies Vol 33 No. 2 March 2012
Figure 1 Separating affordan-
ces from the perceptual
information that specifies
affordances
Figure 2 Separating affordances
An online affordance eva
Successful affordances are perceptible affordances, in which there is perceptual
information available for an existing affordance. If there is no information for
an existing affordance, the affordance is hidden andmust be inferred fromother
clues. If information suggests a nonexistent affordance, a false affordance exists
and may cause people may mistakenly try to act. Finally, correct rejection
means that people do no action when there is no affordance or information.
He also addresses two additional concepts about affordances. One is that
“the physical attributes of the thing to be acted upon are compatible with those
of the actor.” In other words, an object has the physical attributes, which con-
veys information to a compatible actor as to how to use it. For example, thin
vertical door handles afford pulling, and flat horizontal plates afford pushing.
Another is that “Complex actions can be understood in terms of groups of af-
fordances that are sequential in time or nested in space.” The actor can proceed
through a series of actions naturally and continuously by perceiving sequential
affordances; for example, the door handle shown in Figure 2. The first afford-
ance leads the actor to grasp the door handle and the second affordance indi-
cates that it is to be turned.
luation model for product design 131
Figure 3 An example of an
FTIM
132
Galvao and Sato (2005) provided a quantitative evaluation method, Function-
Task Design Matrix (FTIM), to evaluate the degree of affordance for a given
product. They believed that “While a product can be described by its function
and its features, and affordances could provide additional understanding of
the relationships that take place between the product and the user during prod-
uct use.” Also, the applications of affordance confirmed that desirable product
attributes, such as shape, color andmaterial, can help users to accomplish their
goals and familiarize users with appropriate manipulations. In the matrix
(see Figure 3), the squares represent physical contact interactions and the cir-
cles represent cognitive interactions that utilize the output of technical func-
tions (e.g. noise or heat) as a cue for interaction. The overall sum presents
the relationships, as an affordance index, between the task and the function.
For example, on the third column of FTIM, there are three interactions be-
tween Task 3 and Technical Functions b, c, and d, which describe the interde-
pendence between each element. Function b offers one interaction to Task 3
based on the perceived signal from the energy or material flow. So, the afford-
ance index for Task 3 is 4.
Extending Gaver’s concepts of separating affordances from perceptual informa-
tion, McGrenere & Ho (2000) further proposed an evaluation method for the
degree of affordances, which can contribute a lot to the design of a graphical
user interface (GUI). They suggested a two-dimensional space where one
dimension describes the degree of affordance easily undertaken and the second
dimension describes the degree of clear perceptual information. These two
dimensions have a positive linear correlation. The goal of design is
Design Studies Vol 33 No. 2 March 2012
An online affordance eva
“improvements in design that maximize both dimensions.” For example, nov-
ices and experts have different necessary affordances. To respectively use a single
button to toolbar and an alias to command-line (e.g. turning “lpr-Pmyprinter”
into “lmp”) replaces the simultaneous pressing of multiple keys for a frequently
used command, which makes an affordance easier to undertake for novices and
experts.With an increasable degree of perceptual information, novices prefer vi-
sual information and mouse access, but the experts prefer using the command-
line interfaces because visual information is clutter and the mouse access is
a slow-down. You and Chen (2007) regarded “affordance was one of the se-
mantic dimensions describing operational meanings of objects.” They modified
Gaver’s theory and added the symbol concept derived from product semantics.
The affordance, perceptual information, and symbol are used to construct
a three-dimensional space that is applied to the design of product interfaces.
In You and Chen’s view, symbol makes users “note the affordances significant
to product functions and the overall purpose of the product.” For example,
a flat surface of button leads users to push it, and the standardized symbol
“ < ” above the button signifies to users the “play” function.
In recent years, utilizing the theory of affordances, the Japanese designer
Naoto Fukasawa has elaborated his design philosophy named “without
thought” (Naoto, Takeshi, & Masato, 2004). This phrase means returning
to Gibson’s original concepts of ecology and seeking design inspirations
from human intuitive interactions with the environment in daily life.
2 Outline of the constructed modelThis research includes the following steps:
1. Collecting and arranging the affordance properties to be evaluated.
2. Conducting similarity experiments on the affordance properties. Based on
the experimental results, the typical properties of affordance are identified
with the help of multidimensional scaling (MDS) and K-means clustering
analysis.
3. Conducting the online questionnaire survey to determine the weights of the
affordance properties. The results are analyzed through the analytic hierar-
chy process (AHP) to discover the correlative weights of these properties.
4. Establishing the affordance evaluation model.
5. Designing and implementing the interface of the online affordance evalu-
ation model.
6. Applying the quantitative online affordance evaluation model to Com-
pany P’s steam iron, the GC2510.
7. Redesigning part of the steam iron GC2510 in accordance with the eval-
uation results. The evaluation scores before modification are compared
with those after modification to verify the validity of this model.
8. Comparing the evaluation results of the online evaluation with those of
the realized evaluation performed on the steam iron GC2510.
luation model for product design 133
Figure 4 Two samples of
affordance properties, hint
and clear information, in the
similarity experiment
134
3 Implementation methods and procedures
3.1 Collecting and arranging the properties of affordanceto be evaluatedAs the concept of affordance is ambiguous and not an easy to express, we try to
identify the typical properties of affordance based on previous important research
by collecting and synthesizing the description of affordance. First, we collected the
important articles’ description of affordance and filtered out the influential key-
words as shown inAppendixA. Then these keywords are synthesized and digested
into ten affordanceproperties for evaluation (seeAppendixB). These include: hint,
clear information, perceptibility, symbol, appearance features, easy operation,
responsiveness, intuitiveness, proper action, andwithout thought.Also, the defini-
tion and example for each affordance property are presented in Appendix C.
3.2 Indentifying the typical affordance propertiesThe goal of this section is to sort out the typical affordance properties for evalu-
ationpurposes fromthe tenaffordancepropertiesmentioned in theprecedingpar-
agraph.A similarity experimentwas conducted, and then the experimental results
were analyzed with multidimensional scaling (MDS) and K-means clustering to
identify the typical affordance properties displaying the essence of affordances.
3.2.1 Samples of affordance properties in the similarityexperimentEachof the tenaffordancepropertieswas separately putona square card, its edge
being8 cm long, as is shown inFigure 4. Presentedoneach cardwas thedefinition
of the affordance property and a practical example. In this way, when asked to
judge the similarity between two affordance properties, the subjects were enabled
to grasp the characteristics of eachproperty.AppendixC shows thedefinitionsof
all affordance properties and their practical examples.
3.2.2 Similarity experiment on affordance propertiesA total of 30 subjects (14 males and 16 females) with design backgrounds, who
were between 21 and 27 years of age, participated in the similarity experiment
on the ten affordance properties. Two cards were grouped into a pair and the
similarity between the two properties was studied. The results of the
Design Studies Vol 33 No. 2 March 2012
An online affordance eva
comparison were arranged in the following order: extreme dissimilarity, dis-
similarity, medium, similarity, and extreme similarity. Then each of the five
ranks was given a score in sequence, with extreme dissimilarity getting the low-
est score (1 point) and extreme similarity the highest score (5 points).
3.2.3 Sorting out typical affordance propertiesMultidimensional scaling (MDS) is a non-attribute-based method that can con-
vert the subject’s judgments of similarity and preference into distances between
points in multidimensional space, or the perceptual map (Kruskal, 1964;
Schiffman et al., 1981; Green et al., 1989; Hsiao & Chen, 1997). Through
MDS, the data are transferred into coordinate points in multidimension space,
and then these points are clustered into several groups by theK-means clustering
methodbasedon their distribution characteristics.After the clusteringoperation,
the elements in the samegroupwill havehighhomogeneity and the elements in the
different group will have low homogeneity. This paper employsMDS to analyze
the distributional relationship in multidimensional space between the ten afford-
ance properties, and then K-means clustering is used to determine the cluster re-
lationshipbetween thoseproperties.Afterwards, theaffordanceproperty thathas
the shortest Euclidean distance to the center of the cluster is chosen as the repre-
sentative of the cluster, namely, the typical property.
The procedure for determining the typical affordance property is as follows:
first, based on the experimental results of each of the 30 subjects, the similarity
matrix of the affordance properties with 10 � 10 elements was constructed.
Next, the geometric mean method was used to derive the mean similarity ma-
trix. Since MDS takes the dissimilarity matrix as the entry, it is necessary to
convert the score of similarity into that of dissimilarity. That is to say, if an
affordance property scores 3.5 points in the similarity experiment, then its dis-
similarity score is 1.5 points, which is obtained by subtracting the similarity
score (3.5) from the maximum scale score (5). In this way, we transformed
the similarity matrix into the dissimilarity matrix, and then SPSS statistical
software was used to perform MDS analysis.
To make a judgment of MDS operational effectiveness, the stress coefficient is
calculated in the iterative process of MDS. If the Kruskal stress coefficient is
less than 0.05 (good, with 0.025e0.05 being excellent), the data distribution
in the n-dimensional perceptual space has a desirable judgmental value
(Kruskal, 1964; Hsiao & Chen, 1997). With this method, we computed the
stress coefficients of different dimensions, as is shown in Table 1. The stress co-
efficient in the fourth dimension, 0.03832, was the lowest.
After MDS analysis was finished, the data about the ten affordance properties
which had been changed into the coordinate points in the four-dimensional
space were worked out. At the same time, SPSS software was employed to per-
form K-means cluster analysis. The ten affordance properties were divided
luation model for product design 135
Table 1 The relationship between n-dimensional spaces and stress coefficients
Dimensional 2 3 4Stress coefficient 0.11052 0.04417 0.03832
Table 2 The analysis results o
Affordance propertyNo.
13592481067
136
into three clusters and then analyzed their clustering results are shown in
Table 2. Also, the Euclidean Distanced d ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiðXi � XÞ2 þ ðYi � YÞ2
qwas
used to figure out the distance between each property and the cluster center.
The affordance property nearest to the cluster center was chosen as the typical
sample of the cluster. In accordance with the analysis results in Table 2, the
three typical affordance properties were appearance features (AA), responsive-
ness (AR) and clear information (AC); in consequence, a set of typical afford-
ance properties to be evaluated was expressed by formula (1).
AE¼ fAA;AR;ACg ð1Þ
3.3 Correlative weights of affordance propertiesTo determine how much weight would be exerted by three affordance proper-
ties, the Analytic Hierarchy Process (AHP) (Saaty, 1980; Hsiao, 2002) was em-
ployed to discover their correlative weights, with the results obtained below:
WAA ¼ 0:27;WAR ¼ 0:36 andWAC ¼ 0:37
The consistency ratio (CR) was 0.0007, satisfying the requirement that CR
should be less than 0.1; afterwards, the correlative weight set of the three
properties was defined as formula (2) below:
WAE ¼ fWAA;WAR;WACg ¼ f0:27;0:36;0:37g ð2Þwhere WAA;WAR and WAC represent the correlative weight of the affordance
evaluation parameters, i.e., AA, AR, and AC, respectively.
4 Framework of affordance evaluation modelBased on the concept of affordance and the evaluation method of Galvao &
Sato (2005), the functional components for each operational task are analyzed,
f the ten affordance properties through K-means clustering
Affordance property Cluster The distance tothe cluster center
Hint 1 0.753Perceptibility 1 1.204Appearance features 1 0.507Proper action 1 1.224Clear information 3 1.255Symbol 3 2.127Intuitiveness 3 1.316Without thought 3 1.459Easy operation 2 1.061Responsiveness 2 1.016
Design Studies Vol 33 No. 2 March 2012
Figure 5 The process flow of
affordance evaluation model
An online affordance eva
and then the appearance feathers of each component are presented to a user
for evaluation the affordance degree, which means the usability of a product.
As is shown in Figure 5, the complete implementation process flow of the
affordance evaluation model has been established so that any category of
product may be evaluated through the model presented by this research.
When a product to be evaluated is selected, an affordance evaluation model
including five steps can be constructed. The five steps are presented below:
Step 1: The functional components and operational tasks of the product are
obtained by operational researching.
Step 2: if there is only one component in one user’s task, this component’s
correlative weights is 1. If there are more than two components in anyone
user’s task, these components should be given individual correlative weights
using the AHP method.
Step 3: based on the definition of three typical properties of affordance
(appearance features (AA), responsiveness (AR) and clear information
(AC), their definition are presented in Appendix C), the evaluation questions
for each functional component are designed by designers.
Step 4: with steps 1w3 above and the correlative weights of three affordance
properties (see Eq. (2)), the equations of affordance are established for calcu-
lating the affordance degree of the product.
Step 5: by using the evaluation equations of affordance and the web design
software, an online affordance evaluation model and its interface can be suc-
cessfully established.
Next, this model is applied by subjects in an online survey for the product.
Then, the evaluation equations of affordances are utilized to obtain four kinds
of evaluation results: the total affordance score (Vt), the individual score of
each affordance property (VAA;VAR and VAC), the individual affordance score
of each functional component (Vf), and the individual affordance score of each
operational step (Vxi ). If the affordance values of a product are higher, it
luation model for product design 137
138
represents the product has good usability. If the affordance values of the prod-
uct are lower, these data will serve as the references for modifications of a par-
ticular component for improving the usability of product.
4.1 Implementation process flow of affordanceevaluation model
4.1.1 Operational research of the productFirst, the product undergoing affordance evaluation is selected. If the product
is decomposed into n operational steps andm functional components, then the
i-th step involving the j-th component could be represented by xij. Now that all
the operational steps and functional components are combined, their relation-
ships can be expressed as a matrix, as is shown in formula (3) below:
X¼
266664x1
x2
x3
«xn
377775¼
266664x11 x12 / x1m
x21 x22 / x2m
x31 x32 / x3m
« «xn1 xn2 / xnm
377775 ð3Þ
4.1.2 Analyzing correlative weights of functionalcomponentsIn each of the operational steps, each of the functional components presents
a different degree of importance to the user. Therefore, the AHP is used to
determine the correlative weights of the functional components. If wxij repre-
sents the correlative weight of the functional component xij, then the correla-
tive weights of all the operational steps and the functional components can be
expressed as a matrix, as is shown in formula (4a) below:
Wx ¼
266664wx1
wx2
wx3
«wxi
377775¼
266664wx11 wx12 / wx1j
wx21 wx22 / wx2j
wx31 wx32 / wx3j
« «wxi1 wxi2 / wxij
377775 ð4aÞ
whereXmj¼1
wxij ¼ 1; i¼ 1;2;.n; j¼ 1;2;.m: ð4bÞ
4.1.3 Designing the evaluation questions of affordanceproperties for each functional componentTo avoid errors in the questionnaire results caused by the abstract affordance
properties, each of the properties based on its definition is converted into a con-
crete operational instruction and operational question/answer choice, as is
shown in Table 3. For each of the functional components, the operational
questions about three typical affordance properties have to be answered.
Then, the accuracy score of the operational question about each affordance
property is calculated separately.
Design Studies Vol 33 No. 2 March 2012
Table 3 Converting abstract a
Affordance propertya
Appearance featuresof the object (AA)
Kosiat
Responsiveness (AR) Uto
Clear information (AC) Pinth
An online affordance eva
In Table 3, the operational instruction of the affordance property AA is to se-
lect the operational step of the functional component. With the handle of the
steam iron GC2510 taken as an example, the subject faces the following ques-
tion: what is the correct operational step of the handle? And there are five pos-
sible answers to choose from: pushing, pulling, turning, pressing, and holding.
As for the affordance property AR, its operational instruction is to match the
operational step with the functional component. The subject is given the fol-
lowing prompt: indicate a designated functional component in the product;
meanwhile, the choice of answers is to indicate the functional component in
the product. Regarding the affordance property AC, it contains two opera-
tional instructions. When a single message symbol appears, either of the in-
structions can be chosen and responded to.
4.1.4 Calculating the results of affordance evaluationTo obtain the quantitative values of the affordance evaluation, a correct oper-
ation score is used in this study. If the total number of the subjects tested isNp,
then the mean correct operation score for the i-th operational step involving
the j-th component (xij) can be represented by eij, as is expressed in formulas
(5a) and (5b) below:
exij ¼XnNp¼1
�100� rxij
��Np ð5aÞ
rxij ¼ 2:5t2 þ 2:5t� 5t¼ t; for t� 6t¼ 6; for t> 6
�ð5bÞ
ffordance properties into concrete questions
Definition offfordance property
Operational instruction Operational question/Answer choice
nowing theperational stepmply by lookingthe object
Choosing the operationalstep of the functionalcomponent
Q: Can you choose the correctoperational step of the designatedfunctional component?A: The multiple operational choicesof the functional component.
ser’s responsethe object
Matching the operationalstep with the functionalcomponent
Q: Where is the designatedfunctional component?A: Indicate the functional componentin the product.
roviding suitableformation aboute operational step
Indicating the messagesymbol
Q1: Where is the designated messagesymbol?A1: Indicate the message symbolin the product.
Choosing the meaningrepresented by themessage symbol
Q2: What is the correct meaningof the message symbol?A2: The multiple meaning choicesof the message symbol.
luation model for product design 139
140
where rxij means the erroneous operation rate of the functional component xij.
rxij is the quadratic regression value, as is defined in formula (5b), obtained
after the evaluation experiment. In the above formula, t is the number of op-
erations performed to operate correctly. For instance, if the subject correctly
operates the functional component after three attempts, then t is equal to 3.
Therefore, after the subject finishes answering the operational questions about
all the functional components (X) connected with the three typical affordance
properties, namely, AA, AR, and AC, then three matrixes for the correct op-
eration rates EAAx ;EAR
x and EACx can be established, as is expressed in formulas
(6a), (6b), and (6c) respectively.
EAAx ¼
heAAxij
i¼
266664eAAx1eAAx2eAAx3«eAAxn
377775¼
266664eAAx11 eAAx12 / eAAx1meAAx21 eAAx22 / eAAx2meAAx31«
eAAx32 /eAAx3m«
eAAxn1 eAAxn2 / eAAxnm
377775 ð6aÞ
EARx ¼
heARxij
i¼
266664eARx1eARx2eARx3«eARxn
377775¼
266664eARx11 eARx12 / eARx1meARx21 eARx22 / eARx2meARx31«
eARx32 /eARx3m«
eARxn1 eARxn2 / eARxnm
377775 ð6bÞ
EACx ¼
heACxij
i¼
266664eACx1eACx2eACx3«eACxn
377775¼
266664eACx11 eACx12 / eACx1meACx21 eACx22 / eACx2meACx31«
eACx32 /eACx3m«
eACxn1 eACxn2 / eACxnm
377775 ð6cÞ
This affordance evaluation model is capable of performing four types of eval-
uation: the individual score of each affordance property, the individual afford-
ance score of each functional component, the individual affordance score of
each operational step, and the total score of the affordance properties. The cal-
culating equations as well as the variables used are shown in Table 4.
From the individual score of each affordance property, we can know the aver-
age performance of the whole product in relation to properties AA, AR, and
AC; in addition, the score points to the direction of modification. The individ-
ual affordance score of each functional component forms a matrix Vf with
n � m elements, describing its average correct operation rate. Likewise, the in-
dividual affordance score of each operational step forms a matrix Vxi with
n � 1 elements, describing its average score. Moreover, matrixes Vf and Vxi
can help to locate the functional components and the operational steps that
the subjects consider difficult, and then provide reference data about redesign.
As for the total affordance score, it takes into consideration both the correla-
tive weights of the functional components and the affordance properties,
Design Studies Vol 33 No. 2 March 2012
Table 4 The calculating equations of the affordance evaluation
Type of Affordance Evaluation Abbreviation and Calculating formula Nomenclature
1. Individual score of eachaffordance property
AA VAA ¼Pni¼1
Pmj¼1e
AAxijwxij=Ns eAAxij ; e
ARxij; eACxij mean
the average correctoperation score of thefunctional componentX in relation to theaffordance properties AA,AR and, AC
AR VAR ¼Pni¼1
Pmj¼1e
ARxijwxij=Ns wxijmeans the correlative weight
matrix of the functionalcomponent xij.
AC VAC ¼Pni¼1
Pmj¼1e
ACxijwxij=Ns Ns means the number of the
operational steps involvingthe product.
2. Individual affordance scoreof each functional component
Vf ¼ ðeAAxij þ eARxij þ eACxij Þ=3
3. Individual affordance scoreof each operational step
Vxi ¼�Pm
j¼1eAAxijwxij
�þ�Pm
j¼1eARxijwxij
�þ�Pm
j¼1eACxijwxij
�3
4. Total affordance scoreVt ¼
Pni¼1
Pmj¼1e
AAxijwxij
3
!$WAA þ
Pni¼1
Pmj¼1e
ARxijwxij
3
!$WAR þ
Pni¼1
Pmj¼1e
ACxijwxij
3
!$WAC
or Vt ¼ ðVAA$WAAÞ þ ðVAR$WARÞ þ ðVAC$WACÞ
Anonlin
eaffordance
evaluatio
nmodel
forproduct
desig
n141
142
describing the overall performance of the product based on a maximum score
of 100.
4.1.5 Designing the affordance evaluation interface andconducting the surveyIn the product development stage, the online evaluation model enables the de-
signer to immediately grasp the cognitive level of the user concerning the func-
tionality of the product. It will eliminate the defects found in the realized
operational survey, which are time-consuming and wasteful. Furthermore,
by the mean of the online model, a large number of comments are offered
by the web-subjects; as a result, the product is analyzed more objectively as
far as the affordance properties are concerned. In this way, not only are re-
sources conserved but the functionality of the product is enhanced.
The evaluation model in question mainly consists of designing the evaluation
interface and conducting surveys. The designer is expected to put data about
the product under evaluation into the system, finish creating a webpage involv-
ing the evaluation system, and then publish the data on the Internet so that the
subjects may participate in the affordance evaluation. The system receives the
respondent’s answers as the input and generates the four types of evaluation
results as the output.
The interface of the evaluation model is divided into six sections, as is shown in
Figure 6. The first to sixth section therein represent one of the following cate-
gories respectively: the name of the product, the operational steps, product pic-
ture identification, operational questions, multiple answers, and the next
question or the end of response. The operational procedure is illustrated as
follows:
(1) Name and Model number of the Product under Evaluation
The designer should first select the product to be evaluated under the online
model, enter its name and model number in section 1 of Figure 6, or the upper
left corner, and mark it specifically so that the subjects can understand it well.
(2) Operational Steps
After selecting the product to be evaluated, the designer analyzes its opera-
tional steps and enters all the steps successively in section 2 of Figure 6. As
a certain step is evaluated by the subject, it will be displayed in red letters so
that the subject can recognize the progress of evaluation.
(3) The Display Mode of Product Picture and Zooming In/Out
The product picture section, or section 3 of Figure 6, is divided into upper and
lower areas. In the upper area, there are three types of thumbnail pictures avail-
able: the left-view picture, the front-view picture, and the right-view picture.
When a certain angle of view is chosen by clicking on it, the full-view picture
Design Studies Vol 33 No. 2 March 2012
Figure 6 The operational
interface of the online evalua-
tion system
Figure 7 Clicking on the
picture of the designated
component
An online affordance eva
will be displayed in the lower area. Additionally, in the lower right corner of the
product picture are the symbols þ and �, which can be clicked to zoom in and
out of the picture so that the subject can clearly see each functional component in
the picture, as is shown in Figure 7. Also, a close-up of a given functional com-
ponent can be displayed, as is shown in Figure 8, so that the subject can clearly
ascertain the correct answer to the question or instruction.
(4) Working out Questions and Offering Answers
In accordance with Table 3, which converts the affordance property into the
operational question or answer choice, a relevant question is worked out
luation model for product design 143
Figure 8 Displaying the picture
of the designated component
144
concerning each operational step involving functional component X. When
questions appear one at a time in the operational question section, the subject
has to answer them in sequence. For example, if the question is: what is the
handle in the product? The subject has to click on the handle directly in the
product picture section (section 3 of Figure 6); in this way, the question is suc-
cessfully answered. For another example, if the question is: which is the correct
operational step for the handle? The multiple answer section (section 5 of
Figure 6) will present five possible answers: pushing, pulling, turning, pressing,
and holding. If the subject chooses holding, the question is successfully solved.
When a question is correctly answered, the subject has to press the key indicat-
ing the next question or the end to go on answering or to conclude that part of
evaluation.
After the subject has finished answering the questions, the system immediately
starts to calculate the following four types of evaluation results and display
them in the proper places: the total affordance score (Figure 9a), the individual
score of each affordance property (Figure 9d), the individual score of each func-
tional component (Figure 9c), and the individual score of each operational step
(Figure 9b). Additionally, the single-person icon indicates the evaluation re-
sults of the current subject, while the three-person icon indicates the average
evaluation results of all the accumulated subjects Np.
5 Practical case studyTo verify the feasibility of the quantitative online affordance evaluation model
proposed by this paper, we used Company P’s steam, iron GC2510, to illus-
trate the evaluation process in detail.
Design Studies Vol 33 No. 2 March 2012
Figure 9 The displayed sample
results of online affordance
evaluation
An online affordance eva
5.1 Constructing an online affordance evaluation modelfor steam iron GC2510
Step 1: Operational Research of Steam Iron GC2510
The operational steps of the steam iron GC2510 can be divided into five major
operational steps: setting the steam control to switch it off, filling the water
tank, setting the temperature, plugging in and waiting for the desired temper-
ature, and doing the ironing. The relationship between the operational steps
and the functional components can be expressed in formula (7) below, in
which 0 means that such a function is unavailable.
X¼
266664
setting the steam control to switch it offfilling the water tanksetting the temperature
plugging in and waiting for the desired temperaturedoing the ironing
377775
¼
266664
steam control 0 0water� filling opening 0 0
temperature dial 0 0temperature light 0 0
handle steam button spray button
377775
ð7Þ
Step 2: Correlative Weights of Functional Components
The fifth operational step mentioned above “doing the ironing” includes
three functional components: the handle, the steam button, and the spray
luation model for product design 145
Table 5 Analyzing the correla
Functional componentsIn step 5
Handle (X51)Steam button (X52)Spray button (X53)Total
146
button. Therefore, it is necessary for these components to be analyzed their
correlative weight through the Analytic Hierarchy Process (AHP). After
ten subjects were surveyed concerning the importance of the handle, the
steam button, and the spray button, the survey results and the correlative
weights of the functional components were determined and are shown in
Table 5. Moreover, the geometric mean method was employed to obtain
the correlative weights of the three components, with that of the handle being
0.43, that of the steam button being 0.29, and that of the spray button being
0.28. The consistency measurement discovered that the consistency ratio
(CR) was 0.0006 (less than 0.1), verifying that the correlative weights were
valid data.
After the results obtained in the above paragraph were put into formula (4a),
the correlative weights of the functional components in all five steps could be
expressed as formula (8) below:
Wx ¼
266664wx1
wx2
wx3
wx4
wx5
377775 ¼
266664
1 0 01 0 01 0 01 0 0
0:43 0:29 0:28
377775 ð8Þ
As steps 1 through 4 involved only one component, the correlative weight was
1. By contrast, step 5 involved three components, and the correlative weight
of the first component, the handle, was 0.43 (wx51), that of the second compo-
nent, the steam button, was 0.29 (wx52), and that of the third component, the
spray button, was 0.28 (wx53). In addition, the total correlative weight satis-
fied the requirement of formula (4b):Pm
j¼1 wxij ¼ 1.
Step 3: Designing Evaluation Questions
Based on the operational research, the steam iron GC2510 was found to
contain five operational steps and seven functional components. Then, in ac-
cordance with the conversion table of affordance properties (Table 3), the
concrete evaluation questions and their multiple choice answers were
created.
tive weights of the functional components
Handle(X51)
Steam button(X52)
Spray button(X53)
Meancorrelativeweight
Unifiedcorrelativeweight
1.00 1.49 1.47 1.32 0.430.67 1.00 1.07 0.91 0.290.68 0.93 1.00 0.87 0.28
3.10 1.00
Design Studies Vol 33 No. 2 March 2012
An online affordance eva
Step 4 and 5: Establish Affordance Evaluation Equation and Design Evaluation
Interface
Based on the formulas (5a) and (5b), formulas (6a), (6b) and (6c), and four types
of affordance evaluation formulas (see Table 4), the evaluation equation for eval-
uating the affordance degree were established. Several examples for explaining
the calculative procedures to obtain the affordance degree will be described in de-
tail in next section (5.2 Section). After that, the evaluation question/answer data
and the product picture were combined to create the online evaluation interface
(Figures 6e8).
5.2 Online affordance evaluation surveys and thesurvey resultsFive male and five female subjects between 21 and 27 years of age, who had
never used the steam iron, were engaged in the online affordance evaluation.
As soon as they finished answering the questions, the correct operation rates
were calculated through formulas (5a) and (5b), and the results were put
into formulas (6a), (6b), and (6c). In consequence, in addition to the current
subject’s evaluation matrix, the mean evaluation matrixes of all ten subjects
were obtained. Owing to the length limit of this paper, only the mean evalua-
tion matrixes of all ten subjects, or EAAx , EAR
x and EACx were expressed in
formula (9a), (9b), and (9c) below:
EAAx ¼
heAAxij
i¼
266664
94:00 0 088:00 0 0100:00 0 088:00 0 0100:00 100:00 100:00
377775 ð9aÞ
EARx ¼
heARxij
i¼
266664
90:00 0 082:00 0 089:00 0 098:00 0 0100:00 69:50 87:50
377775 ð9bÞ
EACx ¼
heACxij
i¼
266664
91:00 0 069:00 0 096:00 0 081:00 0 0100:00 100:00 87:00
377775 ð9cÞ
The correct operation matrix of each of the ten subjects was successively en-
tered into the affordance evaluation equations (Table 4) to obtain the four
types of evaluation results regarding the steam iron GC2510. The calculation
luation model for product design 147
Table 6 The evaluation result
Operationalstep
Rele
1 Steam c2 Water-fi3 Temper4 Temper5 Handle
Steam bSpray b
Mean affordance score ðVA
148
process and result of each affordance property evaluated are explained in de-
tail as follows:
Type 1: The Individual Score of Each Affordance Property
With the help of the calculating equations in type 1 of Table 4, the individual
score of each affordance property was obtained below:
VAA ¼Xn
i¼1
Xm
j¼1eAAxij wxij=Ns ¼ 470
5¼ 94
VAR ¼Xn
i¼1
Xm
j¼1eARxij wxij=Ns ¼ 446:66
5¼ 89:33 ð10Þ
VAC ¼Xn
i¼1
Xm
j¼1eACxij wxij=Ns ¼ 433:36
5¼ 86:67
The results obtained in the preceding paragraph and the correct operation rate
of each functional component were grouped together and listed in Table 6. As
is shown in the table, the steam iron GC2510 did best in the respect of appear-
ance features (AA). On the other hand, it left something to be desired in the
respect its responsiveness (AR) and clear information (AC), with the average
score being 89.33 and 86.67, respectively. As for the responsiveness (AR) of the
steam iron, the steam button got the lowest score, i.e., 69.50, indicating that it
needed to be greatly improved. In the “clear information” category (AC) of the
iron, the water-filling opening got the lowest score, 69.00.
Type 2: Affordance Evaluation of Functional Components
Through the affordance evaluation of the functional components, the overall per-
formance of the seven components of the steam ironwas discovered. Bymeans of
s of typical affordance properties
vant functionalcomponent
Correct operationscore (AA)
Correct operationscore (AR)
Correct operationscore (AC)
Currentscore
Averagescore
Currentscore
Averagescore
Currentsubject
Averagescore
ontrol 100.00 94.00 100.00 90.00 90.00 91.00lling opening 100.00 88.00 90.00 82.00 100.00 69.00ature dial 100.00 100.00 100.00 89.00 100.00 96.00ature light 100.00 88.00 100.00 98.00 100.00 81.00
100.00 100.00 100.00 100.00 100.00 100.00utton 100.00 100.00 100.00 69.50 100.00 100.00utton 100.00 100.00 100.00 87.50 100.00 87.00
A;VAR and VACÞ 100.00 94.00 98.00 89.33 98.00 86.67
Design Studies Vol 33 No. 2 March 2012
Table 7 The results of affordance evaluation concerning the functional components
Operational step No. Correspondingfunctional component
Affordance evaluation score offunctional components (Vfi)
Current score Average score
1 Steam Control 96.67 91.672 Water-filling opening 96.67 79.673 Temperature dial 100.00 95.004 Temperature light 100.00 89.005 Handle 100.00 100.00
Steam button 100.00 89.83Spray button 100.00 91.50
An online affordance eva
the equation in type 2 of Table 4 (see also formula (11)), the affordance scores of
the functional components (Vf) were calculated and the results were listed in
Table 7
Vf ¼�eAAxij þ eARxij þ eACxij
�.3¼
266664
91:67 0 079:67 0 095:00 0 089:00 0 0100:00 89:83 91:50
377775 ð11Þ
As is shown by the results of affordance evaluation concerning the functional
components in Table 7, the ten subjects found it very hard to operate the
water-filling opening, giving it the lowest score, i.e., 79.67. Without a doubt,
the water-filling opening was the component that most notably needed to be
improved. It was followed by two other unsatisfactory components, the tem-
perature light and the steam button, which got 89.00 and 89.83 points
respectively.
Type 3: Affordance Evaluation of Operational Steps
The correct operation rates in formulas (9a), (9b), and (9c) as well as the cor-
relative weights of the functional components in formula (8) were put into the
equation in type 3 of Table 7 to calculate the affordance results of the five op-
erational steps (Vxi ): namely, setting the steam control to switch it off, filling
the water tank, setting the temperature, plugging in and waiting for the desired
temperature, and doing the ironing. For example, for the fifth operational step
(x5), i.e. doing the ironing, its affordance evaluation was expressed by formula
(12). The affordance results of the other four operational steps, 1 through 5,
were calculated with the same equation, with the results, shown in Table 8.
From the table, it is clear that the subjects gave the lowest score, 79.67, to
the water-filling step.
luation model for product design 149
Table 8 The affordance score of the operational steps
Operational task Affordance evaluation score ofoperational steps (Vxi)
Operational step Operational description Current score Average score
1 Setting the steamcontrol to switch it off
96.67 91.67
2 Filling the water tank 96.67 79.673 Setting the temperature 100.00 95.004 Plugging in and waiting
for the desired temperature100.00 89.00
5 Doing the ironing. 100.00 94.67
150
Vx5 ¼�Xm
j¼1eAAx5j wx5j
�þ�Xm
j¼1eARx5j wx5j
�þ�Xm
j¼1eACx5j wx5j
�.3
¼ ð100� 0:43þ 100� 0:29þ 100� 0:28Þþ ð100� 0:43þ 69:5� 0:29þ 87:5� 02:8Þþ ð100� 0:43þ 100� 0:29þ 87� 0:28Þ=3¼ ð100þ 87:66þ 96:36Þ=3 ¼ 94:67 ð12Þ
Type 4: Total Score of Affordance Evaluation
Finally, the correlative weights of affordance properties (WAA, WAR and WAC)
in formula (2), the correlative weights of functional components
ðwx1 ;wx2/wx5Þ in formula (8), and the correct operation rates of functional
components ðEAAx ;EAR
x and EACx Þ in formulas (9a), (9b), and (9c) were put
into the equation in type 4 of Table 4 to obtain the total affordance evaluation
result (Vt) of the ten subjects. Alternatively, the individual scores of affordance
properties ðVAA;VAR and VACÞ obtained previously in formula (10) could be
used to calculate the average affordance evaluation result. The calculation pro-
cess was expressed in formula (13) and the result in Table 9 below:
Vt ¼ Pn
i¼1
Pmj¼1e
AAxij
wxij
3
!$WAA þ
Pni¼1
Pmj¼1e
ARxij
wxij
3
!$WAR
þ Pn
i¼1
Pmj¼1e
ACxij
wxij
3
!$WAC
¼ ðVAA$WAAÞ þ ðVAR$WARÞ þ ðVAC$WACÞ
¼ ð94:00� 0:27Þ þ ð89:33� 0:36Þ þ ð86:67� 0:37Þ ¼ 89:61 ð13Þ
From the total affordance evaluation result (Vt) calculated above, the designer
knew the level of the user’s satisfaction with the product. The affordance
Design Studies Vol 33 No. 2 March 2012
Table 9 The total affordance evaluation result
Model number of the product Total affordance evaluation score (Vt)
Current score Average score
Steam iron GC2510 98.54 89.61
An online affordance eva
evaluation of operational steps (Vxi ) and the affordance evaluation of func-
tional components (Vf) clearly indicated the wrong operational step and the
component to be modified. In addition, based on the individual scores of af-
fordance properties ðVAA;VAR and VACÞ; the system informed the designer
how perceived affordance should be improved.
5.3 Redesigning the product after affordance evaluation andverifying the results of the new evaluationAccording to the ten subjects’ evaluation, the steam iron GC2510 scored
89.61 points (full score being 100 points) in the respect of total affordance
evaluation (see Table 9); in other words, their satisfaction level was close
to 90 percent, which indicates this product is a well designed operational
product with high affordance clues. If a designer would like to improve the
affordance level of this product, he/she can reference the other three types
of affordance evaluation data. With the affordance evaluation result of the
functional components and the operational steps, a designer can determine
precisely which component or step needs to be modified and improved.
Then the affordance evaluation result of affordance properties (Table 6)
and the definition of affordance properties (Table 3) should be consulted
to direct the revision. Afterwards, the revised product will need to be evalu-
ated again by using the online affordance model to prove that its operational
usability is better than before the revision. By repeating the above process,
the product will have the adequate affordance cues and its operational usabil-
ity will be optimized.
For example, among all the operational steps, step 2, water-filling, got a rel-
atively low score with 79.67, which means that the subjects had much trouble
in filling up the water tank. Referring to the evaluation result of functional
components in Table 7, we discovered that the difficulty involving water-
filling was related to the component of the water-filling opening. As is shown
by the score of the relevant affordance property (Table 6), the item “clear in-
formation” (AC) connected with the water-filling opening left much to be de-
sired. In reference to the definition of affordance properties in Table 3, we see
that the component of water-filling opening has insufficient information for
indicating the message symbol or grasping the meaning of the message sym-
bol. Therefore, the symbol of this component must be modified to make it
easily recognizable; the revised component is shown in the upper section of
Figure 10.
luation model for product design 151
Figure 10 The modified prod-
uct compared with its original
version
152
Moreover, the steam button got a very poor score when it was evaluated in the
aspect of its functional component (see Table 7). Observing Table 6, the func-
tional component of steam button got a low average affordance score (see
Table 6) with 69.5 in affordance properties ofResponsiveness (AR). Then, in ref-
erence to the definition of affordance properties in Table 3, the component of
steam button is determined to have insufficient responsiveness for responding
to the object to match the operational step. This situation also implies that the
users can’t easily figure out the component of steam button, so the component
must be modified to strengthen the connection between the component of steam
button and the operational task of doing the ironing. Wemodified the representa-
tional pattern of steam and enlarged the size of the pattern to strengthen its iden-
tifiably to strongly connect the component and the operational task. The revised
component of steam button is presented in the bottom section of Figure 10.
Afterwards, the ten subjects were asked to make a second affordance evalua-
tion of the revised steam iron. The two results are compared in Table 10. From
this table, we can see that the evaluation scores for the revised product are
much higher than those for the first version as the total affordance score
rose from 89.61 to 92.20. The average evaluation results of typical affordance
properties with components of water-filling opening and steam button in the af-
fordance properties of AC and AR are improved to reach 100% and 84%, re-
spectively. In consequence, the online affordance evaluation model proposed
renders valuable assistance to the designers in improving, redesigning, and en-
hancing the product, with focus set on some of the functional components and
the affordance properties.
Design Studies Vol 33 No. 2 March 2012
Table 10 The total affordance evaluation scores before and after modification, with focus on clear information, the steam
button, and the spray button
Evaluated item Evaluation score beforemodification
Evaluation score aftermodification
Water-filling opening (clear information, AC) 69.00 100.00Steam button (responsiveness, AR) 69.50 84.00Total score 89.61 92.2
Table 11 Analyzing the correl
survey
Correlation coefficient (R)
Scores ðVAAÞ of affordanceobtained from the online suScores ðVARÞ of affordancefrom the online survey andScores ðVACÞ of affordanceobtained from the online suAverage
An online affordance eva
6 Verifying the effect of online evaluation modelapplied to product designThe online evaluation model is not only labor-saving and resource-saving,
but also highly efficient. Therefore, this paper proposes replacing the real-
ized affordance evaluation with online affordance evaluation. To verify
that the online model really leads to the same result as the operational ex-
periment conducted traditionally on realized objects, ten subjects were in-
vited to participate in two kinds of evaluation. The subjects consisted of
five males and five females between 21 and 27 years of age, none of whom
had ever used the steam iron GC251. They carried out the designated eval-
uation as planned.
Then, we used Pearson correlation coefficient to compare the similarity be-
tween the data obtained from the online model and the realized model, discov-
ering the degree of linear dependence between the two groups of data.
Generally, the value of Pearson correlation coefficient is between �1 and 1.
If the coefficient is positive, it shows that the two variables are in the same di-
rection, that is, positively correlated. On the contrary, if the correlation coef-
ficient is negative, it means that the two variables are in opposite directions and
are negatively correlated. As the absolute value of the coefficient is closer to 1,
the linear dependence between the two variables is stronger. Instead, if the ab-
solute value of the coefficient is closer to 0, the linear dependence between the
ation coefficient between the results of the online evaluation survey and the physical evaluation
property, appearance features,rvey and the realized object survey
0.99
property, responsiveness, obtainedthe realized object survey
0.89
property, clear information,rvey and the realized object survey
0.80
0.86
luation model for product design 153
Figure 11 The results of the
online survey compared with
those of the physical survey
154
two variables is weaker. The equation of Pearson correlation coefficient is ex-
pressed in formula (14) below:
R ¼P
i
PjðAi � AÞ�Bj � B
�ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiP
iðAi � AÞ2q ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiP
j
�Bj � B
�2q ð14Þ
where R represents the correlation coefficient between the results obtained
from the online model and the realized model, Ai represents the i-th on-
line evaluation data, and Bj represents the j-th realized evaluation data.
Seven functional components underwent online evaluation and realized
evaluation and their scores on the three affordance properties were repre-
sented by VAA;VAR and VAC respectively. The correlation coefficients of
the above scores were analyzed, as is shown in Table 11 and Figure 11
below:
It was discovered that, based on the two groups of scores obtained from
the online and realized models, the average correlation coefficient was
0.86, or approaching 1. Since the correlation coefficient regarding afford-
ance property, appearance features (AA), was as much as 0.99, the results
of the two models proved to be very much alike. Therefore, we have proved
that it is feasible to replace the realized evaluation model with the online
model.
7 ConclusionThe progress of science and technology has constantly brought an increasing
number of functions to products while more and more operations and applica-
tions have been added. As the performance of products has been enhanced,
the intuitive operation has become an important factor on which the user
Design Studies Vol 33 No. 2 March 2012
An online affordance eva
depends when deciding the quality of the product. The concept of affordance
provides a good solution to link user and product.When a product has sufficient
affordances, the user can correctly and intuitively interact with the product to
perform appropriate manipulations. The ideal affordance, simply put, is one in
which “the user knows what to do just by looking” (Norman, 1988). However,
because the concept of affordance is ambiguous and not easy to express in precise
analytical terms, we identify the typical affordance properties by collecting and
synthesizing the previous descriptions of affordance found in the literature. Con-
sulting the affordance evaluation method purposed by Galvao and Sato, the
productwas analyzed toobtain its technical functions and its user’s tasks. If these
functional components have affordance clues, it can direct users to operate the
components and complete the user’s tasks. Based on the above, an online afford-
ance evaluationmodel for the productwas established that can rapidly and easily
evaluate the usability of the product via web survey. By this method, designers
can identify the appearance features of a product necessary to be revised and op-
timized based on the specific reference data provided by this model.
Additionally, this study provided an online method of operational survey to
replace the realized operational survey. To verify that the online survey leads
to the same result as a realized operational survey, a realized operational ex-
periment was completed with ten subjects. Comparing the results of the on-
line survey and the realized operational survey, it is observed that the data of
these two methods are very much alike and the average correlation coefficient
reaches 0.86. The correlation coefficient regarding affordance property, ap-
pearance features (AA), is as much as 0.99. Therefore, it is proved that it
is feasible to replace the realized operation survey with the online survey.
With this method on the Internet, the affordance evaluation of products
can be researched much more easily and widely for varied subjects. The on-
line evaluation method eliminates the waste of labor and resources resulting
from the traditional evaluation method, rendering the task of evaluation
more efficient.
This study presents a specific evaluation method through quantifying abstract
affordance concepts. The evaluation results enable the designers to detect ear-
lier the operational deficiency of product components and to strive to revise
the product to upgrade its usability. In addition, by following the steps of
this study, this online affordance evaluation model can be adopted and applied
across product categories enabling product development and design with op-
timal usability.
AcknowledgmentThe authors are grateful to the National Science Council of the Republic of
China (gs1) for supporting this research under grant NSC95-2221-E-006-127.
luation model for product design 155
Appendix AImportant articles
Article
Gibson “The affordananimal, whatWhat they affproperties.”“.the affordathe propertiesreference to anAffordance iswithout anima
Warren “This approacvisual control
Humans can icompare the pand then estab
Turvey Affordances athat had signiAffordances aand they must
Chemero Affordance isrelates the abi
Norman “the term afforproperties of thproperties thatAffordance isthe user how tPerceived afforeference to thcapabilities of
Gaver “when affordabetween perce“Affordances“Separating affabout them aland perceived,“the physicalcompatible wi
156
’ description of affordance
Description of affordance Keywords
ces of the environment are what it offers theis provides or furnishes, either for good or ill.ord the observer, after all, depends on their
U the properties of itssubstance and its surfacesU afford (provide orfurnish) observerU without interpretationU animal’s abilityU perceive
nce of anything is a specific combination ofof its substance and its surfaces taken withanimal.”
independent of the animal’s ability to perceivel’s interpretation or experience.
h seeks a lawful explanation for the successfulof action.”
U visualU actionU intuitively perceiveU property of environmentU animal propertyU judgment of action
ntuitively perceive the property of environment,erceived property with the intrinsic property,lish the judgment of action.
re animal-relative properties of the environmentficance to animal’s action.
U animal-relative propertiesU significance to animal’sactionU dispositional propertiesof the environment
re dispositional properties of the environmentbe complemented by properties of animals.
the features of an environmental object andlity of animal.
U features of anenvironmental objectU ability of animal
dance refers to the perceived and actuale thing, primarily those fundamentaldetermine just how the thing could possibly be used.”
U properties of the thingU how the thing couldpossibly be usedU perceived affordanceU perceived information
the properties of the thing, which directshe thing to be used if it is perceived.rdance is the perceived information withe mental and perceptualthe user.
nces are perceptible, they offer a direct linkption and action”
U perceptibleU link between perceptionand actionU direct actionU perceivedU perceptual informationU physical attributes
per se are independent of perception.”ordances from the information availablelows the distinction among correct rejectionshidden and false affordances.”
attributes of the thing to be acted upon areth those of the actor.”
Design Studies Vol 33 No. 2 March 2012
Appendix BExtraction afforda
(continued )
Article Description of affordance Keywords
Galvao &Sato
“While a product can be described by its function and itsfeatures, and affordances could provide additionalunderstanding of the relationships that take place betweenthe product and the user during product use.”
U functionsU featuresU product attributesU appropriatemanipulationsThe applications of affordance and confirmed that desirable
product attributes, such as shape, color and material,can help users to accomplish their goals and familiarizeusers with appropriate manipulations.
McGrenere& Ho
They suggested a two-dimensional space where one dimensiondescribes the degree of affordance easily undertaken and thesecond dimension describes the degree of clear perceptualinformation.
U clear perceptual informationU affordances easy undertakenU maximize both dimensions(clear perceptual informationand affordances easyundertaken)
The goal of design is “improvements in design that maximizeboth dimensions.”
You andChen
“Affordance was one of the semantic dimensions describingoperational meanings of objects.”
U semanticU operational meanings ofobjectsU symbolU product functionsU the overall purposeof the product
Symbol also makes users “note the affordances significantto product functions and the overall purpose of the product.”
NaotoFukasawa
The theory of affordances is utilized into the philosophy,named “without thought”.
U without thinkingU intuitive interactions
The design inspirations are sought from human intuitiveinteractions with the environment in daily life.
Keyword
U operational meanings ofU the overall purpose of thU product functionsU functionsU perceptual informationU perceived informationU clear perceptual informaU perceiveU perceived affordanceU perceptibleU link between perceptionU perceivedU semanticU symbol
An online affordance eva
nce property form the keywords
Property of affordance
objectse product
Hint
tion
Clear information
and action
Perceptibility
Symbol
(continued on next page)
luation model for product design 157
Appendix CDescription and ex
(continued)
Keyword Property of affordance
U the properties of its substance and its surfacesU VisualU property of environmentU dispositional properties of the environmentU features of an environmental objectproperties of the thingphysical attributesU featuresU product attributes
Appearance features
U affordances easy undertakenU maximize both dimensions (clear perceptualinformation and affordances easy undertaken)
Easy operation
U animal’s abilityU animal propertyU animal-relative propertiesability of animal
Responsiveness
U intuitively perceiveintuitive interactions
Intuitiveness
U actionU afford (provide or furnish) observerU judgment of actionU significance to animal’s actionU how the thing could possibly be usedU direct actionU appropriate manipulations
Proper action
U without interpretationU without thinking
Without thought
No. Affordance Proper
1 Hint
2 Clear information
3 Perceptibility
4 Symbol
5 Appearance featur
6 Easy operation
7 Responsiveness
8 Intuitiveness
158
ample of affordance property
ty Description Example
The functional component itselfgives clues to its operational steps.
The spiral ridge means “rotate”.
Enough messages are provided,indicating the operational steps.
ON means “turn on” while OFFmeans “turn off”.
The operational steps of thecomponent are perceptible.
With its surface made of slide-proofmaterial, the component is the handleto be held with the hand.
A symbol is used to representthe function of the component.
The symbol stands for thepower supply.
es The appearance features of thecomponent give clues to itsoperational steps.
The round component has theslide-proof ridges which indicateit is to be turned, not to be pressed.
The product is easy to operate,with nothing complicated.
The operational steps are veryeasy to learn.
The user has ability to reactto the object.
The user can find out the componentimmediately intended for thepresent task.
The user operates the productintuitively.
Without reading the manual, theuser understands the correctoperational steps.
Design Studies Vol 33 No. 2 March 2012
(continued )
No. Affordance Property Description Example
9 Proper action The user performs proper actionon the functional component.
Instead of being turned, thebutton is pressed.
10 Without thought Without extra learning ormemorizing, the user knowshow to operate the product.
On seeing the handle, the user knowsit is to be held with the hand.
An online affordance eva
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