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We collected over a thousand technology-mediated positive experiences with media and obtained measures describing aspects of the experience itself (affect, psychological need fulfillment) and of the product (i.e., content and technology) integral to the experience (pragmatic quality, hedonic quality). We found a strong relation between intensity of need fulfillment and positive affect. Furthermore, different activities had different need profiles. Watching was foremost a relatedness experience, listening a stimulation and meaning experience, and playing a competence experience. Need fulfillment and positive affect was related to perceptions of hedonic quality, however moderated through attribution, that is, the belief that the product played a role in creating the experience. Pragmatic quality was not linked to experiential measures. The present study (a) demonstrates the merits of distinguishing between an experience-oriented and a product-oriented evaluation, (b) suggests a set of possible measurement instruments for experience-oriented and a product-oriented evaluation, and (c) details the process of how positive experience is transformed into positive product perceptions and judgments of appeal.
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Experience-Oriented and Product-Oriented Evaluation:
Psychological Need Fulfillment, Positive Affect, and
Product Perception
Marc Hassenzahla, Annika Wiklund-Engblomb, Anette Bengsb, Susanne Hägglundb & Sarah
Diefenbachc
a Experience and Interaction, Faculty of Design, Folkwang University of Arts, Essen,
Germany
b MediaCity, Åbo Akademi University, Vaasa, Finland
c Economic Psychology, Ludwig-Maximilians-University Munich, Germany
Accepted author version posted online: 27 Jul 2015.
To cite this article: Marc Hassenzahl, Annika Wiklund-Engblom, Anette Bengs, Susanne Hägglund & Sarah Diefenbach
(2015) Experience-Oriented and Product-Oriented Evaluation: Psychological Need Fulfillment, Positive Affect, and Product
Perception, International Journal of Human-Computer Interaction, 31:8, 530-544, DOI: 10.1080/10447318.2015.1064664
To link to this article: http://dx.doi.org/10.1080/10447318.2015.1064664
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Intl. Journal of Human–Computer Interaction, 31: 530–544, 2015
Copyright © Taylor & Francis Group, LLC
ISSN: 1044-7318 print / 1532-7590 online
DOI: 10.1080/10447318.2015.1064664
Experience-Oriented and Product-Oriented Evaluation:
Psychological Need Fulfillment, Positive Affect, and Product
Perception
Marc Hassenzahl1, Annika Wiklund-Engblom2, Anette Bengs2, Susanne Hägglund2,
and Sarah Diefenbach3
1Experience and Interaction, Faculty of Design, Folkwang University of Arts, Essen, Germany
2MediaCity, Åbo Akademi University, Vaasa, Finland
3Economic Psychology, Ludwig-Maximilians-University Munich, Germany
We collected over a thousand technology-mediated positive
experiences with media and obtained measures describing aspects
of the experience itself (affect, psychological need fulfillment)
and of the product (i.e., content and technology) integral to
the experience (pragmatic quality, hedonic quality). We found a
strong relation between intensity of need fulfillment and positive
affect. Furthermore, different activities had different need pro-
files. Watching was foremost a relatedness experience, listening a
stimulation and meaning experience, and playing a competence
experience. Need fulfillment and positive affect was related to
perceptions of hedonic quality, however moderated through attri-
bution, that is, the belief that the product played a role in creating
the experience. Pragmatic quality was not linked to experiential
measures. The present study (a) demonstrates the merits of distin-
guishing between an experience-oriented and a product-oriented
evaluation, (b) suggests a set of possible measurement instruments
for experience-oriented and a product-oriented evaluation, and (c)
details the process of how positive experience is transformed into
positive product perceptions and judgments of appeal.
1. INTRODUCTION
A cozy evening at home, snuggled up on the sofa with your
spouse, a glass of red wine ready at hand. Tonight’s treat is one
of the old James Ivory movies, Howard’s End, starring a won-
derful Helena Bonham Carter. And while the drama unfolds,
you sip your wine, enjoying yourself immensely.
This episode is a—presumably positive—experience.
A memorable chunk of time one went through, “sights and
sounds, feelings and thoughts, motives and actions, all closely
knitted together and stored in memory” (Hassenzahl, 2010,
p. 1). Obviously, experiences are complex narratives. This
example features a home, a sofa, a spouse, red wine, a movie,
Address correspondence to Marc Hassenzahl, Experience and
Interaction, Faculty of Design, Folkwang University of Arts,
Universitätsstraße 12, 45141 Essen, Germany. E-mail: marc.
hassenzahl@folkwang-uni.de
a television set, and a DVD player, all combined to create
positive feelings, positive thoughts, meaning, and a lasting
memory.
Despite the complexities and intricacies of positive experi-
ences, providing them to consumers has become the prime goal
of all makers of consumer merchandise. The sofa is built to
be comfortable and sets the stage for the snuggling through its
design. The wine satisfies with its taste and its relaxing effect.
Finally, the technology provides the entertainment, thereby
supplying a central element of the experience. Ultimately, all
those products—and especially technology and its features—
become meaningful to people only by the experience they
convey. Accordingly, Hassenzahl (2010) argued to put “experi-
ence before the product” (p. 63), which requires rethinking what
technology actually is, why it matters, and what its intended
effects are (Forlizzi & Battarbee, 2004; Hassenzahl, 2010;
Hassenzahl & Tractinsky, 2006; McCarthy & Wright, 2004).
As opposed to a task-oriented approach, the experience-oriented
approach focuses on the personal, subjective side of interac-
tion with a product, understanding interaction as a dynamic
story, able to create emotions and meaning. Admittedly, we are
far from a common accepted definition of what user experi-
ence could or should be (Law, Roto, Hassenzahl, Vermeeren,
&Korte,2009) and experience research can be biased and sub-
optimal (Bargas-Avila & Hornbæk, 2011). But experience is at
the heart of the emerging postmaterialistic, experiential soci-
ety (Schulze, 1992) and economy (Pine & Gilmore, 1999).
Technology firms can hardly afford to ignore it (Hassenzahl,
2011).
In addition to changes in how to think about or even design
technology, a focus on experience suggests reconsidering the
models and assumptions underlying well-accepted approaches
to evaluation. So far, the “product” is often quite narrowly
understood as the tangible set of materials it is made of (e.g.,
screens, keys, buttons, knobs, windows, sliders) and evalua-
tion focuses on those material aspects. An experience-oriented
530
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EXPERIENCE-ORIENTED AND PRODUCT-ORIENTED EVALUATION 531
perspective, however, acknowledges that people foremost cre-
ate meaningful and memorable stories through interacting with
a product. These stories become in fact a part of the product and
in turn serve as a basis for a more explicit product evaluation.
In other words, if asked about aspects of a product, such as its
perceived usefulness or the quality of certain features, people
will likely probe their memory for experiences they have had
and then base judgments upon a particular or a collection of
remembered moments. This process is so pervasive that it even
works with imagined experiences (Rajagopal & Montgomery,
2011).
This calls for an extended perspective on evaluation, includ-
ing products and experiences, as well as a better understand-
ing of how people derive judgments from recollected expe-
riences. This study sheds further light on the relationship
between an experience-oriented and a product-oriented perspec-
tive. Specifically, we collected positive experiences with media
content (e.g., games, movies, music) mediated by technologies
(e.g., consoles, TVs, players) and measured experienced affect,
as well as psychological need fulfillment of those experiences.
The relationships of experiential constructs (affect, need ful-
fillment) to each other and product perceptions were further
explored. The present study foremost replicates but also extends
earlier studies, which found the fulfillment of psychological
needs and positive affect to be related and already explored
relationships between experience-oriented and product-oriented
aspects (e.g., Aranyi, 2012; Hassenzahl, 2008; Hassenzahl et al.,
2010; Partala & Kallinen, 2012; Partala & Kujala, 2015; Tuch
& Hornbæk, in press; Tuch, Trusell, & Hornbæk, 2013).
1.1. Theoretical Background: Affect, Needs, and
Attribution
In the present article we define “an experience” (Forlizzi &
Battarbee, 2004) as a retrospectively constructed personal nar-
rative, based on feelings, thoughts, and actions remembered
from a collection of moments (e.g., Baumeister & Newman,
1994). Most approaches emphasize emotions and affect as inte-
gral aspects of an experience. Wright, Wallace, and McCarthy
(2008), for example, cited Dewey, who argued “that sensation
and emotion make the cement that holds experience together”
(p. 18:2). Indeed, pleasure and pain are integral parts of all
experience (Kahneman, 1999), and well-being as an ultimate
personal goal implies having at least some recollections of plea-
surable moments in life. Accordingly, the capacity of experi-
encing positive emotions becomes central to human flourishing
(Fredrickson, 2000). Russell (2003) defined affect as a com-
mon “psychological currency” that facilitates the comparison
of qualitatively different experiences. In short, affect—positive
and negative—is central to any experience. Consequently, we
find it quite natural to distinguish positive from negative experi-
ences. The present article, however, focuses on positive expe-
riences, as this is certainly still an underresearched topic in
human–computer interaction. Although the study of stress,
anxiety, and errors in interacting with technology is ubiquitous,
the study of technology and pleasure is less well covered (see
Diefenbach, Kolb, & Hassenzahl, 2014, for an overview).
Although affect is crucial to an experience, the question
remains, From where does the positive affectivity of a posi-
tive experience actually stem? Sheldon, Elliot, Kim, and Kasser
(2001; summarizing a wide array of need-based theories, such
as Maslow, 1954; Reiss, 2004; Ryan & Deci, 2000) identi-
fied the fulfillment of psychological needs, such as the need
for competence, for feeling related, or for being stimulated,
as an important correlate of—at least positive—affect in expe-
rienced life events. Hassenzahl et al. (2010) transferred this
general idea to experiences with technology (see also Aranyi,
2012; Hassenzahl, 2008; Partala & Kallinen, 2012; Partala &
Kujala, 2015; Tuch & Hornbæk, in press; Tuch et al., 2013).
As expected, they found a strong correlation between intensity
of need fulfillment and positive affect. In other words, the more
intense the need fulfillment in an experience, the more positive
the experience. Accordingly, in the present study, we employed
need fulfillment as the second experiential aspect besides affect,
further distinguishing qualitative differences between experi-
ences.
The experience-oriented perspective is complemented by
a product-oriented perspective. Hassenzahl and colleagues
(Hassenzahl, 2001,2003; Hassenzahl, Platz, Burmester, &
Lehner, 2000) distinguished between products’ instrumental,
pragmatic aspects and their noninstrumental, self-referential,
hedonic aspects (see also Batra & Ahtola, 1991; Voss,
Spangenberg, & Grohmann, 2003; see Diefenbach et al., 2014,
for an overview of research on hedonic quality in human–
computer interaction [HCI]). Pragmatic quality refers to a
judgment of a product’s potential to support particular, concrete
“do-goals” (e.g., to make a telephone call). Hedonic quality
is a judgment with regard to a product’s potential to support
pleasure in use and ownership, that is, the fulfillment of needs
(“be-goals,” such as to be admired, to be stimulated).
We assume a link between experience-oriented and product-
oriented aspects. Affect is an important basis for all types
of judgments. More than three decades ago, Abelson, Kinder,
Peters, and Fiske (1982) showed that affective reactions to
politicians better predicted political preference than perceived
personality traits (e.g., intelligent). This process is not differ-
ent for products. Typically, individuals probe their affective
state (“How do I feel about it?”) and then use the valence
of experienced affect as informational basis for further judg-
ments (Schwarz, 2001). In the same vein, Russell (2003) argued
that affect will be “attributed” to an object (i.e., thing, person,
event), that is, individuals identify an object as potential “cause”
of their current affective state or change in state and ascribe
affective quality to the object.
However, using affect in judgments is far from an automatic
process. In a classic study, Schwarz and Clore (1983) found that
the participants’ current mood influenced general judgments of
life satisfaction, because incidental, situationally induced affect
Downloaded by [Professor Marc Hassenzahl] at 09:03 03 September 2015
532 M. HASSENZAHL ET AL.
(i.e., mood) became misattributed to life satisfaction. However,
this effect disappeared when individuals’ attention was drawn to
potential situational determinants of their current mood, such as
the weather. In other words, individuals were able to discount
effects of incidental affect when made or becoming aware of
it. In addition, they can accentuate or discount their affective
state as basis for judgments, depending on whether they find
affect representative for the respective judgment. Pham (1998),
for example, showed that people rely more on affect when the
target is experiential and consummatory (e.g., watching a movie
for fun) compared to instrumental (e.g., watching a movie to be
admitted to a subsequent paid study; see also Yeung & Wyer,
2004). In a prior study, Hassenzahl and colleagues (2010) found
the relationship between experience and product judgments to
be moderated by attribution. The more people found the prod-
uct to be responsible for the positive experience, the stronger
the relationship between experience and product perception.
However, this held true only for hedonic, not for pragmatic, per-
ceptions. In other words, people rely on attributed positive affect
only for the hedonic and not for the pragmatic quality judg-
ment. All in all, we assume a relationship between what was
experienced in an episode and particular product perceptions.
Attribution, however, moderates this link.
1.2. Objectives of the Study
In general, we were interested in positive experience and
product perception. Specifically, we explored the following
issues, thereby replicating and at times extending our and oth-
ers’ work (e.g., Aranyi, 2012; Hassenzahl, 2008; Hassenzahl
et al., 2010; Partala & Kallinen, 2012; Partala & Kujala, 2015;
Tuch & Hornbæk, in press; Tuch et al., 2013).
Need fulfillment. In the previous studies, we collected peo-
ple’s experiences with technology in general. For the present
study, we narrowed this to experiences with media content
and technology, such as movies and DVD player, music and
mp3 player, or games and consoles. First, we were interested
to what extent our previous results would replicate in the face
of a more restricted and homogenous sample of experiences
and technologies. Second, so far, we were not able to demon-
strate that different activities actually differ in the way they
fulfill needs. An exception is a recent study (Hassenzahl &
Klapperich, 2014), which compared need fulfillment through
two ways of coffee making, a more manual (i.e., Italian stove-
top espresso maker, grinder) and a more automated (i.e., Senseo
pad coffeemaker). Results showed manual coffee making to
provide more competence and stimulation, resulting in a more
intense and positive experience. Although this is encouraging, it
remains unclear whether we would find similar activity-specific
need profiles in a sample of experiences, such as the present.
However, the measurement of needs as a strategy to charac-
terize qualitative and quantitative differences in experiences
hinges on the measure’s sensitivity to differences in activity.
Previous studies did not include this type of analysis, because
the gathered activities had been too diverse to be clustered
meaningfully (Hassenzahl et al., 2010; Sheldon et al., 2001;but
see Tuch et al., 2013, for an alternative approach to summarize
the content of reported experiences). Due to the more homoge-
neous sample of activities in the present study, we were able
to cluster activities into meaningful groups (i.e., watching, lis-
tening, playing) and to compare emerging differences among
activity-specific need profiles.
Need fulfillment and affect. The relationship between need
fulfillment and positive affect is crucial. The present study
provided a fresh sample to replicate previous findings and
to explore, which aspects of this relationship remain stable
(general relationship, single needs etc.).
Need fulfillment/positive affect and product perception. In
previous studies, we found a clear relationship between general
need fulfillment and hedonic quality as well as general need ful-
fillment and positive affect. Both were moderated by attribution.
This relationship was not apparent for pragmatic quality. This is
a very detailed prediction, in need of replication. In addition to
replication, we have extended previous findings through a more
detailed analysis of the relationship between single needs (e.g.,
relatedness, stimulation, competence) and hedonic quality.
2. METHOD
2.1. Participants
The study was carried out online. We used SurveyMonkey
(http://wwwsurveymonkey.com) to host the questionnaire and
collect the data. An invitation to participate was distributed
by e-mail to 16,225 Swedes registered in the Testpilot.fi panel
(http://www.testpilot.fi/en). There were 1,337 individuals who
responded (response rate =8.2%). Of those, 1,013 participants
(retention rate =75.8%) completed at least 95% of the ques-
tionnaire. This constituted our final sample (518 female, 51.1%;
490 male, 48.4%; five undetermined, 0.5%; Mage =34, SD =
10, Min =14, Max =75). Participants had a wide variety of
backgrounds. All participants in the final sample took part in a
raffle, handing out a number of 50C gift certificates.
2.2. Questionnaire
The questionnaire consisted of four parts. It started with
an introduction, explaining the general aim of the study. This
was followed by a set of open questions, which asked par-
ticipants to describe a positive experience they had involving
“media” and technology in the widest sense. They were asked
to provide information about content, technology, and context.
This particular experience was then the object of a number of
scales, aimed at eliciting experienced need fulfillment during
the experience, affect, and product perception, as well as attri-
bution. These scales and their properties are described in more
detail in the following. Finally, participants provided informa-
tion about their age, gender, and occupation. The study was
carried out in Swedish, and all questionnaires were translated
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EXPERIENCE-ORIENTED AND PRODUCT-ORIENTED EVALUATION 533
from English to Swedish (needs, affect) or German to Swedish
(product perception and appeal).
Need fulfillment. We modeled our questionnaire to mea-
sure experienced need fulfillment on Sheldon and colleagues’
(2001) work. Based on a review of psychological needs theories,
they originally suggested 10 psychological needs as poten-
tial sources for the positivity in life experiences. We adapted
this work to experiences with technology (Hassenzahl et al.,
2010) and found a subset of six needs to be the most relevant:
relatedness, competence, popularity, stimulation, security, and
meaning (see Table 1 for definitions).
To measure need fulfillment in the present study, we
devised a shortened 12-item questionnaire by using the two
best items in terms of factor loadings from Hassenzahl et al.
(2010;seeTable 1 for the items). Participants responded
on a 5-point scale ranging from 1 (not at all)to5
(extremely).
To establish convergent and discriminant validity of the
scales, we submitted the 12 items to a principal components
analysis with Varimax rotation (to establish independence of
components) and set the extraction criterion to six components
based on our a priori expectation. The principal components
analysis explained 80% of the available variance, which was
only 6% less than in Hassenzahl et al. (2010). Primary load-
ings of all the items were high (.71–.88), with only one
cross loading slightly above .30 (9% explained variance).
In general, the findings replicated Hassenzahl et al. (2010;see
Table 2).
We computed mean scale values for each need by averag-
ing the respective items for each participant. Table 3 shows the
internal consistencies per scale (Cronbach’s alpha) and scale
intercorrelations.
The internal consistency for relatedness and competence
was good and acceptable for meaning. Security, popularity,
and stimulation had internal consistencies below .70. However,
keeping in mind that none of the internal consistencies was out-
right inacceptable (<.50) and that each scale consisted only of
two items, we decided to include all needs for further analy-
ses. Although the computed need scale values were definitely
correlated (average r=.41), no correlation was high enough
to indicate redundancy (.80). Further analyses take potential
problems of collinearity into account.
TABLE 1
Needs and Respective Items
Need Description
Relatedness Feeling that you have regular intimate contact with people who care about you rather than feeling
lonely and uncared of.
“I felt a sense of contact with people who care for me, and whom I care for.”
“I felt close and connected with other people who are important to me.”
Meaning Feeling that you are developing your best potentials and making life meaningful rather than feeling
stagnant and that life does not have much meaning.
“I felt that I was ‘becoming who I really am’.”
“I felt a deeper understanding of myself and my place in the universe.”a
Stimulation Feeling that you get plenty of novelty and stimulation rather than feeling bored and understimulated
by life.
“I felt that I was experiencing new sensation and activities.”
“I felt that I had found new sources and types of stimulation for myself.”
Competence Feeling that you are capable and effective in your actions rather than feeling incompetent or
ineffective.
“I felt that I was successfully completing difficult tasks and projects.”
“I felt that I was taking on and mastering hard challenges.”
Security Feeling safe and in control of your life rather than feeling uncertain and threatened by your
circumstances.
“I felt that my life was structured and predictable.”a
“I felt glad that I have a comfortable set of routines and habits.”
Popularity Feeling that you are liked, respected, and have influence over others rather than feeling like a person
whose advice or opinion nobody is interested in.
“I felt that I was a person whose advice others seek out and follow.”
“I felt that I strongly influenced others’ beliefs and behavior.”a
Note. All items were originally in Swedish. Adapted from Hassenzahl et al. (2010) and Sheldon et al. (2001).
aThese items differ slightly from Hassenzahl et al. (2010).
Downloaded by [Professor Marc Hassenzahl] at 09:03 03 September 2015
534 M. HASSENZAHL ET AL.
TABLE 2
Principal Components Analysis Varimax Rotation of the Need Items
Component
Scale/Item
Ifelt... 123456
Relatedness [Cronbach’s α=.84]
...a sense of contact with people who
care for me, and whom I care for
.87 (.92)
...close and connected with other
people who are important to me
.88 (.93)
Meaning [Cronbach’s α=.72]
...that I was becoming who I really
am
.75 (.81)
...a deeper understanding of myself
and my place in the universea.85 (.81)
Stimulation [Cronbach’s α=.67]
...that I was experiencing new
sensation and activities
.81 (.88)
...that I had found new sources and
types of stimulation for myself
.83 (.87)
Competence [Cronbach’s α=.80]
...that I was successfully completing
difficult tasks and projects
.84 (.86)
.... that I was taking on and mastering
hard challenges
.82 (.84)
Security [Cronbach’s α=.64]
...That my life was structured and
predictablea.82 (.85)
...glad that I have a comfortable set of
routines and habits
(.31) .82 (.83)
Popularity [Cronbach’s α=.68]
...that I was a person whose advice
others seek out and follow
(.32) .31 .71 (.75)
...that I strongly influenced others’
beliefs and behaviora.84 (.81)
Eigenvalue 1.77 1.68 1.57 1.56 1.52 1.49
% variance explained 15 (20) 14 (17) 13 (13) 13 (13) 13 (12) 12 (11)
Note. All items were originally in Swedish. Component loadings <.30 are suppressed. Values obtained by Hassenzahl et al. (2010)arein
parentheses.
aThese items differ slightly from Hassenzahl et al. (2010).
In addition to the single scales, we computed a score denot-
ing general need fulfillment by averaging all items. This score
represents the extent to which need fulfillment took place,
regardless of the actual type of need.
We also included a question about presence of others in
the description of the experience (“Had you been alone or
did you share the experience with other people?”) to validate
our needs measurement. Experiences that include other people
should be more intense concerning socially oriented needs (i.e.,
relatedness, popularity).
Affect. We measured experienced affect with the Positive
Affect Negative Affect Schedule (PANAS; Watson, Clark, &
Tellegen, 1988; see Lewis & Mayes, 2014, for an overview
of emotion-measures in HCI and alternative instruments). The
PANAS consists of 20 verbal descriptors of different facets of
affective experience, namely, afraid, scared, nervous, jittery,
irritable, hostile, guilty, ashamed, upset, and distressed for
negative affect and active, alert, attentive, determined, enthusi-
astic, excited, inspired, proud, strong, and interested for positive
affect. Participants indicated the intensity of the experience of
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EXPERIENCE-ORIENTED AND PRODUCT-ORIENTED EVALUATION 535
TABLE 3
Internal Consistencies and Intercorrelations of Each Need
Need
Need REL MEAN COMP SEC POP STIM
Relatedness (REL) (.84)
Meaning (MEAN) .38∗∗ (.72)
Competence (COMP) .33∗∗ .50∗∗ (.80)
Security (SEC) .30∗∗ .36∗∗ .43∗∗ (.64)
Popularity (POP) .48∗∗ .51∗∗ .55∗∗ .42∗∗ (.68)
Stimulation (STIM) .24∗∗ .47∗∗ .42∗∗ .23∗∗ .41∗∗ (.67)
Note. N=1,013. Cronbach’s alpha is in parentheses.
∗∗p<.01.
each of the particular affective facets on a 5-point scale ranging
from 1 (not at all)to5(extremely).
PANAS assumes a hierarchical structure (Watson &
Tellegen, 1985) with two broad independent factors represent-
ing positive and negative affect. Accordingly, we calculated
scale values for positive and negative affect by averaging the
respective 10 items. The internal consistency of positive and
negative affect was good (Positive affect: Cronbach’s α=.88;
negative affect: Cronbach’s α=.85). Scales were significantly
correlated, r(1011) =.18, p<.001, but not enough to indicate
redundancy. Due to the fact that we explicitly asked participants
to provide positive experiences only, the distribution of negative
affect was positively skewed (Skew =2.29, SE =.08), that is,
strongly asymmetric. As a rule of thumb, skew is considered
serious when it is greater than twice its standard error. In fact,
90% of all participants had a mean negative affect below 2,
resulting in an overall mean of 1.28 (on a scale ranging from 1 to
5) and restricted variance (SD =.45). In contrast, positive affect
was not skewed at all (Skew =–.03, SE =.08), with an overall
mean (M=2.92) and standard deviation (SD =.87) indicating
appropriate use of the scale. Accordingly, we restricted further
analyses to positive affect.
Product perception. Participants were told that “when
detailing your experience, you referred to particular media (e.g.,
a movie, a website, a record, a game) in combination with a
particular technology (e.g., a TV, a DVD player, a computer,
a games console). For the moment, think of this combina-
tion as “the product.” Product perceptions were then mea-
sured with the AttracDiff2 questionnaire (Hassenzahl, 2001,
2004). This questionnaire assumes two different, broad cat-
egories of perceptions: hedonic and pragmatic (Hassenzahl,
2003,2010). Pragmatic quality refers to a product’s perceived
potential to support particular “do-goals” (e.g., to make a
telephone call). In contrast, hedonic quality refers to a prod-
uct’s potential to support pleasure in use and ownership,
that is, the fulfillment of psychological needs (e.g., to be
stimulated).
AttracDiff2 is a widely used instrument. In a recent
paper, Diefenbach and colleagues (2014) reviewed more than
150 papers addressing the “hedonic” in HCI (excluding our own
work). Of the 74 papers using scales to measure hedonic per-
ceptions, 43 (58%) made use of the AttracDiff2 as used in the
present article or its abbreviated version (Hassenzahl & Monk,
2010). This is certainly a consequence of the fact that when
first presented (Hassenzahl et al., 2000), the notion of hedonic,
noninstrumental qualities complementing the pragmatic (i.e.,
ergonomics, usability) was not especially widespread in HCI.
It only later gained momentum. In the context of the technol-
ogy acceptance model (TAM), though, some researchers started
to focus quite early on “perceived fun” or “perceived enjoy-
ment” complementing “perceived ease-of-use” and “perceived
usefulness” (e.g., Igbaria, Schiffman, & Wieckowski, 1994).
However, as Diefenbach et al. (2014, p. 310) noted, there is
asubstantial difference between the way pleasure is measured
by the AttracDiff2 compared to TAM: Where the latter focuses
on users’ perceptions of their own emotional state (“I have
fun using the system”), the former presents a list of product
attributes to assess potential sources of pleasure. Thus, TAM
is already a rather experience-oriented measure, akin to affect
as just conceptualized. Moreover, Hassenzahl already based his
notion of different product attributes on an explicit model of
psychological needs to be fulfilled through interaction. In other
words, whereas TAM measures an experiential outcome, it
remains silent about the sources of that outcome. In contrast,
the AttracDiff2 explicitly defines a number of attributes, which
allegedly represent perceived sources of pleasure in use adding
to a favorable impression of the interactive product.
The questionnaire consists of 21 seven-point
semantic differential items. Seven items capture prag-
matic quality: human–technical, simple–complicated,
practical–impractical, straightforward–cumbersome,
predictable–unpredictable, clearly structured–confusing,
and manageable–unruly. Fourteen items capture hedonic
quality: connective–isolating, professional–unprofessional,
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536 M. HASSENZAHL ET AL.
stylish–tacky, premium–cheap, integrating–alienating,
brings me closer to people–separates me from peo-
ple, presentable–unpresentable, inventive–conventional,
creative–unimaginative, bold–cautious, innovative–
conservative, captivating–dull, challenging–undemanding,
and novel–ordinary.
We calculated pragmatic and hedonic quality scale values
by averaging the respective seven and 14 items. The inter-
nal consistency was good for hedonic quality (Cronbach’s
α=.85) but lower than the typical goal of .70 for prag-
matic quality (Cronbach’s α=.62). A closer look revealed the
item human–technical to have a problematic zero item-total-
correlation. By excluding this item from the scale, Cronbach’s
alpha improved to an acceptable .72. However, the results of all
analyses in the present article including pragmatic quality did
not substantially differ depending on whether human–technical
was excluded. For the sake of simplicity and the potential com-
parisons with other studies, we decided to use the original scale
even with a lower internal consistency. Pragmatic and hedonic
quality were significantly correlated, r(1011) =.20, p<.001.
The magnitude of the correlation, however, did not indicate
redundancy.
Attribution. Need fulfillment and affect is experienced in
a particular situation (e.g., “I felt ... that I had found new
sources and types of stimulation for myself”), whereas product
perception (and evaluation) is expressed through more general
product attributes (e.g., “captivating,” “creative”). An attribute
is the consequence of an attribution process that relates an expe-
rience to a particular object and establishes it as a perceived root
of this experience. To measure attribution in the present study,
we asked participants, “Think back to the feelings and emo-
tions you had during the experience. What do you think: How
much had they been caused by the product?” and to answer on
a 5-point scale ranging from 1 (not at all)to5(very much).
Note that this instruction slightly differs from the previously
used (Hassenzahl et al., 2010) by focusing people especially on
feelings and emotions.
3. RESULTS AND DISCUSSION
3.1. Need Fulfillment
Table 4 (Overall M(SD) and 95% CI columns) shows the
mean intensity of need fulfillment, its standard deviation, and
the 95% confidence interval. All mean values of intensity were
larger than 1.
Obviously, experiences mediated through media content and
technology fulfill psychological needs. Relatedness was the
most intense, followed by stimulation, competence, security,
meaning, and popularity. This replicated our previous findings
with the exception of the rank position of popularity, which
was fourth in Hassenzahl et al. (2010). People had experiences
mediated through media technology and content, marked by
feelings of closeness and communication with other people,
new stimulating insights, and opportunities for mastery.
We included a question about presence of others in the
description of the experience (“Had you been alone or did you
share the experience with other people?”) and categorized the
experience as social if at least one other person was present in
the experience. All in all, 927 (of 1,013; 92%) responded to
the question: the majority was alone (554; 60%). One would
expect that the fulfillment of the social needs of relatedness and
popularity is bound to having company. For the other needs,
being alone or in company may not be relevant at all, or even
counterproductive. Table 3 (Social column) shows the correla-
tion of whether the experience was social (0 =no, 1 =yes) and
the intensity of need fulfillment. As expected, the fulfillment of
relatedness was bound to company, and the same held true for
popularity, albeit not as strong. Both support the validity of the
needs measurement. Whereas the fulfillment of meaning was
TABLE 4
Intensity of Need Fulfillment Overall and Separately for Three Different Activities
95% CI
OverallaWatching Listening Playing
Need M (SD) Lower Upper SocialbM (SD) M (SD) M (SD) F(2, 805) ε2
Relatedness 3.02 (1.33) 2.93 3.10 .49∗∗∗ 3.14a(1.32) 2.81b(1.32) 3.00a,b (1.33) 4.70∗∗ .010
Stimulation 2.80 (1.13) 2.74 2.88 .02 2.62b(1.12) 3.00a(1.09) 3.12a(1.03) 15.51∗∗∗ .036
Competence 2.56 (1.24) 2.48 2.64 .04 2.29c(1.22) 2.60b(1.18) 3.16a(1.04) 27.39∗∗∗ .063
Security 2.42 (1.01) 2.36 2.48 .05 2.51a(0.99) 2.32a(1.00) 2.36a(0.98) 3.36.007
Meaning 2.24 (1.11) 2.17 2.31 .082.14b(1.05) 2.56a(1.17) 1.96b(0.92) 16.14∗∗∗ .037
Popularity 2.04 (1.03) 1.97 2.10 .13∗∗∗ 1.95a(0.99) 2.04a(1.00) 2.14a(1.02) 2.01 .004
General 2.51 (0.81) 2.46 2.56 2.44a(0.81) 2.55a(0.79) 2.62a(0.68) 3.36.007
Note. Number with the same subscripts in a row are not different from each other on a 5% level based on Scheffe-Tests (refer to text for more
information). CI =confidence interval.
aN=1,013. bN=927 (0 =no, 1 =yes).
p<.05. ∗∗p<.01. ∗∗∗p<.001.
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EXPERIENCE-ORIENTED AND PRODUCT-ORIENTED EVALUATION 537
negatively correlated with the presence of others, the effect was
rather small.
We further hoped to obtain specific need profiles by a cate-
gorization of experiences into activities. Based on the notion of
aparticular, context-dependent prioritization of needs (Sheldon
et al., 2001), we hypothesized differences in the intensities of
needs as a function of activity. In other words, activities should
have activity specific need-profiles. A screening of the obtained
sample of experiences suggested three broad categories of activ-
ities: watching (a movie at the cinema or at home, TV), listening
(to music, to the radio, to audiobooks), and playing (com-
puter and video games). A first rater categorized all experiences
accordingly. This covered 808 (of 1,013; 80%) of all experi-
ences: the majority was watching (457 of 1,013; 45%), followed
by listening (226 of 1,013; 22%), and playing (125 of 1,013;
12%). A second rater independently categorized these experi-
ences according to the three activities. The initial inter-rater
agreement was very high (Cohen’s κ=.90). Disagreements
were resolved through subsequent discussion. Note that activ-
ities were not completely independent of the categorization as
social or not. Watching and playing was done alone or accom-
panied: watching alone (204 of 433; 47%), χ2(1) =1.44, p>
.05, adjusted Wald 95% confidence interval (CI) [43%, 52%];
playing alone (52 of 109; 48%), χ2(1) =0.23, p>.05, adjusted
Wald 95% CI [39%, 57%]; listening primarily alone (173 of
214; 81%), χ2(1) =81.42, p<.001, adjusted Wald 95% CI
[75%, 86%].
Table 4 (Watching, Listening, and Playing columns) shows
the mean intensities of need fulfillment for each activity.
To explore whether intensity differed from activity to activ-
ity, we performed a 6 ×3 analysis of variance with need
(relatedness, stimulation, competence, security, meaning, pop-
ularity) as a within-subjects variable, activity (watching, listen-
ing, playing) as a between-subjects variable, and intensity of
need as a dependent variable.1This revealed a large effect of
need, F(5, 4025) =117.72, p<.001, ε2=.122.2As already
discussed, intensity of need fulfillment differed for the differ-
ent needs, with relatedness, stimulation, and competence being
the most salient. Also a significant but small effect of activ-
ity emerged, F(2, 805) =3.35, p<.05, ε2=.007. Playing
provided the most need fulfillment, followed by listening and
watching. Even though the effect was significant, the practical
effect size was very small, which renders the general differences
1Note that here and in the following, the terms “variable,” “depen-
dent variable,” “predictor,” and “criterion” are used solely to specify
the input to analyses of variance and regression analyses. They do not
imply any causality. The present data are correlational in nature. Causal
inferences cannot be drawn solely on the basis of correlation.
2ε2is a variant of the n2measure of effect size, correcting n2’s
known overestimation of effect size, and is thus slightly smaller
(Olejnik & Algina, 2000). An n2of .01 is considered a small effect,
.06 medium, and .14 large.
between activities negligible. More interesting was the signifi-
cant interaction between need and activity, F(10, 4025) =20.24,
p<.001, ε2=.041, which pointed at particular differences in
the relative intensity of fulfillment of different needs, provoked
by the different activities.
To explore this further, we conducted one-way analyses of
variance with activity (watching, listening, playing) for each
need, followed by a post hoc comparison of the activities by
Scheffé tests. Table 3 (Fand ε2columns) shows the resulting
Fvalue, significance, and ε2for each need. Significant post
hoc differences emerged for relatedness, stimulation, compe-
tence, and meaning. The post hoc comparisons revealed that (a)
watching had more relatedness than listening; (b) listening and
playing had more stimulation than watching; (c) playing had
more competence than listening, and listening had more compe-
tence than watching; and (d) listening had more meaning than
watching and playing. There were no significant post hoc dif-
ferences among activities for security and popularity. Note that
although the analysis of variance registered a significant differ-
ence for security, the more conservative Scheffé test found this
difference to be negligible. See Figure 1 for the activity-specific
need profiles.
To summarize: Media experiences mediated through tech-
nologies fulfill psychological needs, with relatedness, stimu-
lation, and competence being the top three needs addressed.
An activity-specific analysis further revealed that the relative
fulfillment of different needs varies from activity to activity.
Watching and playing had the most relatedness, whereas listen-
ing and playing had the most stimulation. Playing had the most
competence and listening the most meaning. The fact that activi-
ties differed in the needs they fulfilled most lends support to the
notion that different activities offer different opportunities for
need fulfillment. The method of measuring need fulfillment ret-
rospectively was able to reveal these differences, which seems
crucial to the notion of an experience-oriented evaluation.
–0,8
–0,6
0,4
–0,2
0
0,2
0,4
0,6
0,8
Relatedness Stimulation Competence Meaning
Intensity
Needs
Watching
Listening
Playing
FIG. 1. Activity-specific need profiles (mean-centered).
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538 M. HASSENZAHL ET AL.
3.2. Need Fulfillment and Affect
Our approach to positive experience expects a relationship
between need fulfillment and positive affect. Table 5 (rcol-
umn) shows the bivariate correlations between intensity of need
fulfillment and positive affect with 95% CIs.
All correlations were significant (i.e., all CIs excluded 0).
The correlation between general intensity of need fulfillment
and positive affect was large, r(1011) =.58, and similar to the
r=.62 reported by Hassenzahl et al. (2010). In other words, the
more intense need fulfillment in general, the more positive the
experienced affect. In addition, all single needs were related to
positive affect (see Table 5,rcolumn), with competence being
the strongest and security the weakest. The CIs revealed two
groups of needs, which differed in their relationship to positive
affect: Competence, stimulation, meaning, and popularity were
more strongly related to positive affect than relatedness and
security. This differed from earlier findings (Hassenzahl et al.,
2010), where stimulation had the strongest relationship (r=
.44), followed by all other needs with correlations in the range
from .29 (competence) to .12 (security). An additional regres-
sion analysis with positive affect as the criterion and all needs
as predictors revealed a similar pattern (R=.64, R2adjusted =
.41), F(6, 1006) =117.83, p<.001. All needs contributed to
positive affect (see Table 4,βcolumn), again with competence
contributing the most and a negative value for security. None of
the predictor’s Variance Inflation Factors exceeded 1.88 (i.e., no
indication of serious multicollinearity).
All in all, general need fulfillment and positive affect were
positively related. In line with Hassenzahl et al. (2010), each
single need was related to positive affect as well, with security
showing the smallest relationship and even a negative weight
in the regression analysis. This further underscores the nature
of security as a deficiency need. Sheldon and colleagues (2001)
argued that security is important for negative affect through its
TABLE 5
Need Fulfillment and Positive Affect
(Bivariate Correlations and βWeights)
Positive Affect
95% CI
Need rLower Upper β
Competence .54∗∗∗ .50 .58 .34∗∗
Stimulation .50∗∗∗ .45 .55 .27∗∗
Meaning .46∗∗∗ .41 .51 .13∗∗
Popularity .43∗∗∗ .38 .48 .07
Relatedness .30∗∗∗ .24 .36 .07
Security .21∗∗∗ .15 .27 .10∗∗
General .58∗∗∗
Note. N =1,013.
p<.05. ∗∗p<.01. ∗∗∗p<.001.
absence but does not contribute to positive affect much com-
pared to the “enhancement”-oriented needs, such as competence
or stimulation.
The actual pattern of the relationships between positive affect
and single needs differed from Hassenzahl et al.’s (2010)pre-
vious study. However, it seems only natural that this pattern
varies with the actual sample of experiences. The present study
showed that general need fulfillment and positive affect were
related and that all needs were potentially related to positive
affect except security. All in all, need fulfillment and positive
affect were tightly coupled. Although causality cannot be deter-
mined from the present data, conceptually we understand need
fulfillment as the source of positive affect. Positive affect is—so
to say—felt need fulfillment. Although positive affect is quite
accessible to people, assessing need fulfillment is a more reflec-
tive process. Nevertheless, need fulfillment and positive affect
were highly correlated, and activities plausibly differ in the
salience of specific needs (e.g., social situations primarily fulfill
social needs). This lends support to the assumption that people
are able to describe their experiences through need fulfillment
and affect, and both are two sides of the same coin.
3.3. Need Fulfillment/Affect and Product Perception
In our view, perceived hedonic quality is the consequence of
need fulfillment attributed to the product. Overall, the correla-
tion between general need fulfillment (i.e., mean of all single
need intensities) and hedonic quality was significant, r(1011) =
.27, p<.001. To assess the influence of attribution, we com-
pared participants who stated that their feelings and emotions
had not at all been caused by the product (scale value 1, N=
95) with those who stated that the product very much caused
their feelings and emotions (scale value 5, N=195). Overall,
the high-attribution participants experienced more need fulfill-
ment (low: M=2.25 vs. high: M=2.62), t(288) =3.27, p<
.01, and perceived the product as more hedonic (low: M=
4.23 vs. high: M=5.47), t(288) =11.85, p<.001, compared
to the low-attribution participants. More important, in the low-
attribution group, need fulfillment and hedonic quality remained
uncorrelated, r(93) =–.06, p>.05, whereas in the high-
attribution group the correlation was substantial, r(193) =.31,
p<.001. In other words, only if participants felt that the prod-
uct was responsible for their experience did experienced need
fulfillment result in positive judgments about hedonic product
quality.
Concerning pragmatic quality, the correlation with general
need fulfillment remained insignificant, r(1011) =.04, p>.05.
Neither in the low-attribution group nor in the high-attribution
group was need fulfillment and pragmatic quality correlated:
low, r(93) =–.01, p>.05; high, r(193) =–.06, p>.05.
In addition, there was no difference in perceived pragmatic
quality for the low- compared to the high-attribution group (low,
M=4.78 vs. high, M=4.98). This underlines the specific
role of need fulfillment for hedonic quality perceptions but not
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EXPERIENCE-ORIENTED AND PRODUCT-ORIENTED EVALUATION 539
pragmatic quality perceptions. Even if people feel that the prod-
uct plays an important role for their experience, perceptions
of psychological need fulfillment and pragmatic quality remain
distinct aspects.
We were further interested in exploring how the fulfill-
ment of particular needs may be related to particular hedonic
attributes. We thus studied hedonic quality perceptions on a sin-
gle item level. We first performed regression analyses for each
of the six needs, with all 14 hedonic items as predictors and the
intensity of the respective need fulfillment as criterion. We then
used a stepwise regression to determine the most predictive item
for each need. The stepwise regression initially searches for the
predictor explaining the most of the variance in the criterion.
In a step-by-step search, it then determines a next potential pre-
dictor, if there is one, which explains a substantial amount of
additional variance.
Table 6 shows the multiple correlations between all hedonic
items and each need, as well as the respective most “predic-
tive” item, that is, the item first included by the second stepwise
regression. All needs were related to the 14 hedonic items,
with relatedness and stimulation revealing the strongest mul-
tiple correlations. This is not astonishing, given that hedonic
quality was originally conceptualized as consisting of attributes
related to Identification and Stimulation (Hassenzahl, 2003).
The most predictive item for relatedness was brings me closer
to peopleseparates me from people, an item that is part
of the Identification subscale of hedonic quality and in line
with the definition of relatedness. The same holds for novel–
ordinary, an item that is part of the Stimulation subscale of
hedonic quality and in line with the definition of stimulation.
For popularity connecting–isolating was the most predictive.
This is also an item of the Identification subscale, that is, it
is in the social domain as expected for popularity. Of inter-
est, competence was covered by challenging–undemanding,an
item that belongs to the Stimulation subscale. In retrospect,
however, challenge much better expresses a competence expe-
rience (to accomplish a goal but to be challenged on the way)
than a stimulation experience (to be stimulated by something
novel).
Meaning and security were not covered well by the hedonic
items. Although the multiple correlations were significant, the
most predictive items did not clearly denote the respective
needs. The most obvious reason is that meaning as well as
security—in the sense of pleasurable routines and habits—was
not covered by the earlier concept of hedonic quality. Another
reason is the special role of security as a deficiency need,
already discussed.
To get a better idea of the role of attribution in the context
of specific needs, we repeated the previous analysis for the low-
and high-attribution groups separately.
Table 7 shows that none of the multiple correlations between
needs and the hedonic items remained significant for the
low-attribution group, mirroring the analysis of general need
fulfillment just presented. In the high-attribution group, how-
ever, all multiple correlations except those for security were
significant.
Our expectations concerning the relationship between affect
and product perception were similar to those regarding need
fulfillment and product perception. Positive affect should be
related to hedonic quality; however, attribution should take a
moderating role. Overall, the correlation between positive affect
and hedonic quality was significant, r(1011) =.37, p<.001,
and the high-attribution participants experienced more positive
affect compared to the low-attribution participants (low: M=
2.51 vs. high: M=3.31), t(288) =7.25, p<.001. More impor-
tant, in the low-attribution group positive affect and hedonic
quality remained uncorrelated, r(93) =.06, p>.05, whereas
in the high-attribution group the correlation was substantial,
r(193) =.41, p<.001.
In general, the relationship between pragmatic quality per-
ceptions and positive affect remained weak and only reached
statistical significance in the total group of participants,
r(1011) =.12, p<.001, but not in the attribution subgroups:
low, r(93) =.17, p>.05; high, r(193) =.03, p>.05.
TABLE 6
Multiple Correlations Between Each Need and All Items of the Hedonic Quality Scale
Need R
R2
Adjusted F(14, 924) Most Predictive Item
Relatedness .37∗∗∗ .12 10.50 brings me closer to people–separates me
from people
Stimulation .36∗∗∗ .12 10.07 novel–ordinary
Popularity .32∗∗∗ .07 7.33 connecting–isolating
Competence .28∗∗∗ .07 5.80 challenging–undemanding
Meaning .24∗∗∗ .05 4.14 integrating–alienating
Security .16.01 1.75 professional–unprofessional
Note. N =938.
p<.05. ∗∗∗p<.001.
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540 M. HASSENZAHL ET AL.
TABLE 7
Multiple Correlations Between Each Need and All Items of the Hedonic Quality Scale for the Low- and the
High-Attribution Groups
Attribution
Low (1)aHigh (5)b
Need R Adj. R2F(14, 69) R Adj. R2F(14, 171)
Relatedness .47 .06 1.37 .49∗∗∗ .18 3.85
Stimulation .39 .00 0.88 .43∗∗∗ .12 2.74
Popularity .35 .06 0.69 .53∗∗∗ .22 4.80
Competence .36 .04 0.75 .41∗∗ .10 2.44
Meaning .38 .03 0.85 .45∗∗∗ .13 3.03
Security .46 .05 1.30 .29 .01 1.13
Note. Adj. =adjusted.
aN=83. bN=185.
p<.05. ∗∗p<.01. ∗∗∗p<.001.
Positive affect seems to bear a stronger relation to hedonic
quality (r=.37) than need fulfillment to hedonic quality (r=
.27). Previously, we argued that positive affect has a mediating
role between need fulfillment and hedonic quality (Hassenzahl
et al., 2010). Although we conceptualize fulfillment of psy-
chological needs as the source of positive affect, the actual
affect is much more accessible to an individual than need ful-
fillment. One may say that need fulfillment has to be felt and
that positive affect is actually experienced need fulfillment.
Consequently, positive affect becomes an important resource for
assessing hedonic quality. In line with this, a mediation analysis
with a regression of general need fulfillment and positive affect
on hedonic quality (all variables centered) revealed a media-
tion. The substantial correlation of general need fulfillment and
hedonic quality (r=.27) became much smaller but remained
significant (β=.08, b=.08, SE =.04, t=7.25, p<.001). The
indirect effect via positive affect was strong (indirect effect =
.21, Sobel’s Z=10.98, p<.001; positive affect: β=.32,
b=.30, SE =.03, t=8.93, p<.001). This analysis con-
firms positive affect’s mediating role and is in line with a notion
of affect-as-information in judgment processes (Schwarz,
2001).
In sum, these findings lend further support to the hypothe-
sized relationship between need fulfillment and positive affect
(as experiential concepts) and product perception. Experienced
need fulfillment and positive affect were related to hedonic
quality perceptions but not to pragmatic. The relationship
between the experiential measures and hedonic quality was,
however, especially strong, and hedonic quality especially
salient, when the feelings and emotions experienced were
seen as caused by the product (i.e., had been attributed to
the product). A mediation analysis confirmed the central role
of positive affect for hedonic product quality perceptions.
Compared to reflections on the intensity of fulfillment of
different needs, positive affect seems to be more readily
accessible. Only if need fulfillment is accompanied by affect,
that is, “experienced,” it will be reflected in hedonic quality
perceptions.
Others (e.g., Tuch & Hornbæk, in press) have argued for
a conceptual relation between pragmatic quality and positive
affect, since “convenience” can also be experienced as pos-
itive (see also Meuter, Ostrom, Roundtree, & Bitner, 2000).
In the present study, however, pragmatic quality perceptions
were not driven by need fulfillment or positive affect, whereas
hedonic quality perceptions were strongly related. This in line
with Hassenzahl et al. (2010), who found a medium correlation
between positive affect and pragmatic quality (r=.28) but a
larger correlation between positive affect and hedonic quality (r
=.46). Note that this does not render pragmatic quality percep-
tions unimportant. In the present sample of positive experiences
with media technology, pragmatic quality is already experi-
enced as above average (M=4.84, SD =0.82; 4 is the theoret-
ical midpoint of the scale), 95% CI [4.79, 4.89], and almost as
strong as hedonic quality (M=4.93, SD =0.81), 95% CI [4.88,
4.98]. In this respect, pragmatic quality may be an important
precondition for positive experiences but not a driver of positiv-
ity in itself. Because the present study addressed only positive
experiences, its potential for clarifying these inconsistencies is
limited.
Finally, the collection of AttracDiff2’s 14 hedonic items
substantially represented need fulfillment. Although we may
replace the original crude notion of stimulation and identifi-
cation with the more refined set of six needs studied here, the
average of all hedonic items still remains a substantial product-
oriented indicator of need fulfillment attributed to the product.
However, one must be aware of the fact that meaning as well as
security was not well covered by the hedonic quality construct
as operationalized by the AttracDiff2.
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EXPERIENCE-ORIENTED AND PRODUCT-ORIENTED EVALUATION 541
3.4. Summary and Conclusion
We collected more than 1,000 positive experiences with
media, mediated and created by the combination of content
and technology. In line with previous research on life experi-
ences (Sheldon et al., 2001) and experiences with technology
(e.g., Aranyi, 2012; Hassenzahl, 2008; Hassenzahl et al., 2010;
Partala & Kallinen, 2012; Partala & Kujala, 2015; Tuch &
Hornbæk, in press; Tuch et al., 2013), positive affectivity
was related to the fulfillment of psychological needs, such as
relatedness, stimulation, competence, popularity, meaning, and
security. As long as needs denote more specific aspects of an
experience (e.g., “I felt close to a significant other”) than posi-
tive affect (e.g., “I felt good”), one may assume positivity to be
a consequence of fulfilled needs—at least in the retrospective
process of meaning making. Note, however, that the current data
are correlational in nature and do not prove such causal hypothe-
ses. Whether the experience of positivity is first and then further
qualified by the fact that it covaries with feelings of closeness
or whether the feeling of closeness is first and valued (or even
both) remains an open question for future studies.
Although the experiential aspects affect and need fulfillment
were directly related, their relationship to hedonic product per-
ceptions was moderated by attribution. Even if a person felt
like “experiencing new sensations and activities” (i.e., stimula-
tion) in the course of an experience accompanied by positive
affect, it had an impact only on hedonic quality perceptions
(as “novel”) given the person believed the product to play a
crucial role for the experienced emotions and feelings. There
are at least two interesting implications of this finding. First,
it reveals the necessity for both: an experience-oriented and a
product-oriented evaluation. However, typical studies on user
experience evaluation often rely on a product-oriented perspec-
tive only, sometimes complemented with a questionnaire to
measure affect. The present research implies that people can
have positive experiences with a product, which may not be
reflected in hedonic quality perceptions. This is then, however,
not a problem of what the product actually creates but rather
a matter of whether people acknowledge the product’s role in
mediating and creating the experience. This leads to the second
implication. If attribution is crucial, we need to figure out ways
to ascertain that at least some of the positive affect a product cre-
ates is attributed to the product itself. This is not trivial. Take the
example at the beginning: How can we assure that the protago-
nist experiences the evening on the sofa as whole but at the same
time recognizes that this experience would only be half as good
without a spouse, the wine, the sofa, the movie, and the televi-
sion set. Of course, from an Experience Design perspective the
focus should be on the experience to be created and the product
is understood merely as mediator (e.g., Hassenzahl et al., 2013).
As long as the product is able to shape activities in a way that
they become need fulfilling, its design was successful. It is not
necessary that a user recognizes the role, the product actually
played. From this perspective, it becomes even more important
to evaluate experientially, as product-oriented measures may be
misleading.
We investigated three different activities—watching, listen-
ing, and playing—each with differing need profiles. Watching
and playing offered the most relatedness, whereas listening and
playing offered the most stimulation. Playing offered the most
competence and listening the most meaning. In other words,
some activities in their current form, involving current available
technologies, are better suited to fulfill certain needs than others.
If we further assume people to have context-dependent hierar-
chies of needs, we may begin to see how people match needs
and activities to fulfill those. A couple separated from each
other over the course of a day, may, for example, prefer sharing
the evening watching TV to listening to music. A reason might
be that the structure of the former allows for more relatedness.
However, given that the couple was already together for the best
part of the day, that is, they already had good opportunity to
fulfill relatedness needs, stimulation needs may be more pro-
nounced. Then, preferences may change in favor of playing.
The found sensitivity of need fulfillment to variations in activ-
ities is important for at least two reasons. First, it demonstrates
the sensitivity of the measurement. Second, and more impor-
tant, specific need profiles may inform design. Remember that
need fulfillment is an experiential measure and that the experi-
ence results from the interplay of different elements, with the
product itself being only one element out of many. Discovering,
for example, that watching is primarily a relatedness experi-
ence can have different implications for designing technology.
On one hand, this insight could be a starting point to create
even more opportunities for relatedness experiences, for exam-
ple, by devising TV sets that support watching TV together
over a distance or new devices for “guerrilla” (i.e., sponta-
neous) public viewing (Hassenzahl et al., 2013). On the other
hand, one may look for ways to create experiences that satisfy
a number of needs at once. Playing, for example, was fore-
most a competence experience, but it also fulfilled relatedness
and stimulation needs. In that sense, playing is a more holisti-
cally fulfilling activity than, for example, watching. The point
here is to understand need profiles as potential starting points
to deliberately enhance or alter an experience through one of
its designable elements—the product (see also Hassenzahl &
Klapperich, 2014, for an example).
The present study further emphasizes the qualitative differ-
ence between hedonic and pragmatic quality perceptions. All in
all, pragmatic quality was not related to the experiential vari-
ables studied. This needs to be interpreted with care. Sheldon
and colleagues (2001), for example, showed that although the
presence of security played only a minor role in positive life
experiences, its absence became a major aspect of negative
life experiences—hence they called it a deficiency need as
opposed to enhancement needs. In analogy to this, we may
find that positive experience is related to need fulfillment and
the presence of hedonic quality perceptions, whereas negative
Downloaded by [Professor Marc Hassenzahl] at 09:03 03 September 2015
542 M. HASSENZAHL ET AL.
experience is more related to the presence of problems with
the technology itself and thus the absence of pragmatic qual-
ity perceptions (see Partala & Kallinen, 2012). This conceptual
independence of pragmatic and hedonic aspects is crucial: For
example, it can explain why, even in the face of usability prob-
lems, people may still appreciate a product for its potential need
fulfillment without experiencing this as a conflict or contradic-
tion. Note, however, that the present study addressed only posi-
tive experiences. Consequently, the nature of the relationships
between product perceptions and experiential aspects in the
case of negative experiences should be explored in future stud-
ies. Furthermore, the present findings are not consistent with
a recent study (Tuch & Hornbæk, in press), which found prag-
matic aspects contributing to positive experiences. When asking
people about positive experience with their mobile phone, they
found “reasons” for positive affect on a need level (e.g., pro-
vides relatedness), as well as on a more practical, instrumental
level (e.g., is convenient). In our theoretical framework, a pos-
itive experience is made positive by need fulfillment, but of
course pragmatic quality (as a lower level indicator of instru-
mentality) is at least to some extent a necessary precondition
for fulfillment of needs. In other words, although the stimula-
tion provided by playing a game on a console is what makes
the experience positive, a serious problem with operating the
console can of course ruin the entire experience. Nevertheless,
even the smoothest interaction with a console cannot save a bor-
ing game. All in all, this issue seems far from settled and worth
studying further.
Although the present study focused on retrospectively
reported individual narratives of product use, the very same
approach and related questionnaires can be applied to “product”
evaluation. Hassenzahl and Klapperich (2014), for example,
asked people to prepare coffee with different coffeemakers and
measured need fulfillment and affect directly after each task.
This resulted in clear (and statistically significant) differences
in the fulfillment of particular needs and positive affect.
For practitioners concerned with evaluating interactive prod-
ucts, the present article thus provides at least two valuable
insights. First, it suggests that product evaluation should con-
sider taking hedonic aspects into account. Although a certain
level of usability is a necessary precondition for a positive expe-
rience, the positivity itself stems from a different source. The
AttracDiff2 offers a simple and, by now, well-accepted way of
measuring these aspects beyond usability (see Diefenbach et al.,
2014). Second, the conceptual difference between experience
level and product level is helpful in distinguishing differ-
ent ways of evaluating. For instance, likelihood-to-recommend
measures, such as the Net Promoter Score (Reichheld, 2003),
obviously do not measure product perceptions or evaluations
but more remote consequences of positive experiences with
a product. There are limits in attributing a good or bad
score to the product alone; many other aspects may play a
role. Similarly, Lewis and Mayes’s (2014) Emotional Metric
Outcomes questionnaire explicitly attempts to measure “the
emotional outcome of interactions” (p. 685) but not attributes of
products. Both are rather experiential measures, concerned with
the meaning and positivity a certain product or service is able to
create in a given situation or across situations through use. This
is different from the still more common attempt in HCI to char-
acterize and describe the product itself through measurement.
We believe that the experience level and the product level are
important and that practitioners should be especially attentive to
both. Ultimately, practitioners need to estimate the meaning and
positivity a product is able to create in people’s lifeworld (i.e.,
their experience) while being capable of tracing experience cre-
ated back to the element under their control—the product itself.
In sum, focusing on the experience alone can be misleading as,
by its very nature, experience confounds many different aspects.
The contribution of the product remains unclear. Focusing on
the product alone can be misleading, too, because one never
knows whether the details of the product (i.e., content, func-
tionality, presentation, interaction), so carefully crafted, really
impact people’s experience as hoped for. The combination of
both will have many advantages. The present article provides
a potential approach to do so, grounded in well-researched
psychological theory and knowledge.
Of course, the present study has its limitations. Future stud-
ies, for example, may take a closer look at the differences
between negative and positive experiences to further clarify the
relation between pragmatic quality and experiential variables.
So far, we focused on positive experience, as we believe HCI as
a community to be much more in need of extending knowledge
on how technology can create or mediate positive experience
than on how to avoid problems. The latter is already well cov-
ered for more than 50 years. We still need to remind ourselves
that the absence of stress, usability problems, or complexity
does not equal enjoyment.
Surveying needs and affect is a step toward quantifying cer-
tain central aspects of experience. At the same time, needs
provide a framework to understand where the pleasure in expe-
riences may stem from, which seems crucial when designing for
positive, meaningful, worthwhile experiences. Taking needs as a
basis for design is not meant to constrain designers or to relieve
them from being creative. Enhancing relatedness through a TV
set while watching is nothing more than an objective. But tech-
nology designers can start to figure out with “what” (i.e., with
which functionality) and “how” (i.e., through which form and
interaction) they could possibly enhance or even create a partic-
ular experience. They can start to answer the question of how to
mediate a particular experience through an object, that is, how
to tell “material tales” (Dunne, 2006).
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544 M. HASSENZAHL ET AL.
ABOUT THE AUTHORS
Marc Hassenzahl is a professor of Experience and Interaction
Design at the Folkwang University of the Arts in Essen,
Germany. His work focuses on the theory and practice of
designing pleasurable, meaningful and transforming experi-
ences with interactive technologies.
Annika Wiklund-Engblom is a research coordinator at
MediaCity, Åbo Akademi University, Finland. She is a devel-
opmental psychologist and IT-pedagogue. Her research focuses
on human emotions and needs for learning, especially in
human-media interaction, e-learning, self-regulated learning,
and corporate e-learning.
Anette Bengs is a researcher at MediaCity, Åbo Akademi
University, Finland. She is a doctoral student in developmental
psychology. Her research focuses on user experience in general,
children’s perception of media and particularly on methods to
capture and measure user experience.
Susanne Hägglund is a manager at Content Testing Lab
of MediaCity, Åbo Akademi University, Finland. Her work
focuses on the understanding of, and the designing for, mean-
ingful meetings between human beings and technology, in
industry as well as in academia.
Sarah Diefenbach is a professor of Economic Psychology
at the Ludwig-Maximilians-University Munich, Germany. Her
research focuses on understanding, designing and evaluating the
consumer experience of interactive technologies, especially on
methods to capture hedonic aspects as well as the aesthetics of
interaction.
Downloaded by [Professor Marc Hassenzahl] at 09:03 03 September 2015
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Even in moments considered private, others often witness how we interact with technology. A typical example is smartphone use at home, in the presence of family members. This of course becomes even more likely in public - on streets, in libraries, or in the supermarket, places full of other people. The social context brings challenges and opportunities. When designing interaction, we often primarily focus on what users experience, like, and accept. Less do we explicitly consider what present others may think or feel about this interaction, and how it relates to their own current activities. This requires a deeper understanding of social context and frugal but sufficiently rich context descriptions. In turn, considering present others allows us to learn about what types of interaction are acceptable or even aesthetic in what types of context. In this workshop, we collaboratively explored the largely untouched questions of positive interaction from the perspective of others, and worked out ways in which these could improve the design process.
... p=.000: the more intense the need fulfillment, the more positive the moment. This corresponds to earlier findings with larger samples [18,19]. ...
... Current studies have highlighted the importance of acquiring relevant knowledge on user needs to develop technologies that can handle the real life situations of the older people [22,23]. When developing technological products, it is essential to consider social dynamics and contextual factors [24,25] in order to increase the usability and interaction with technological devices. ...
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