Anssi Mattila,
InBCT 4.2
Relationship between seamless use experience, customer satisfaction and
recommendation[1]
Abstract
Relying on SERVQUAL service quality dimensions by Parasuraman et al. (1985, 1988), this study identifies the service quality dimensions pertaining seamless use experience and investigates the relationship between customer satisfaction and intention to recommend mobile Internet services. According to our analysis, which is based on data comprising of 778 survey responses among mobile and fixed-line users, the level of satisfaction after using mobile Internet services, intention to encourage the use of mobile Internet services and willingness to recommend the use of mobile services are strongly interrelated.
Keywords: customer, satisfaction, mobile services
1. Introduction
Internet has been said to increase the importance of customer satisfaction. To achieve good financial performance in e-services, the use experience must prove to be satisfactory (Cox et al. 2002). Although the Internet has traditionally been viewed and managed as technical innovation, the acid test of e-commerce lies in the incorporation of consumers’ needs and preferences into the Web site design and the business concept (Yang et al. 2003). This ethnographic approach places the user in the forefront of the Web site design process, taking into account the way business is conducted and the way people communicate in the target society when developing the interface design (Shneiderman 1996). Many scenarios, about to how many people a dissatisfied customer on the Internet can tell about her bad experiences, have been presented. According to Rotondaro (2002), a dissatisfied customer talks about an unpleasant event to 5000 people online. Mattila et al. (2003) have found the word-of-mouth effect to be especially powerful the more elderly the mobile service users are.
The service interface is interlinking service processes, which manage the activation points for different customer scripts. The service interface also has to maintain links to the backstage operations supporting both the service setting and the service encounters (Broderick et al. 2002). It is essential that the service providers acknowledge more self-determinism by clients and create more clarity and transparency in the service interface (Broderick et al. 2002). The information efficiency of an interface is defined as the minimum amount of information necessary to do a task, divided by the amount of information that has to be supplied by the user (Raskin 2000, 84). An information overload may lead to a customer frustration.
2. From satisfaction to service quality
Bowen and Chen (2001) found that the relationship between customer loyalty and satisfaction is non-linear. According to Coyne (1989) there are two critical thresholds affecting the link between satisfaction and customer loyalty. On the other side, when customer satisfaction reaches a certain level, the loyalty increases very strongly, and at the low end, when satisfaction decreases to a certain point, the loyalty drops very strongly (Oliva et al. 1992). Satisfaction with the user interface has not found to have direct effect on perceived value (van Riel et al. 2001). Van Riel et al. (2001) found that supplementary services are the value-adding component. Service quality is an important antecedent of consumer assessments of value (Imrie et al. 2002) and as e-CRM increases on Web site, the greater the customer satisfaction will be (Feinberg et al. 2002). Further, Ranaweera et al. (2003) postulate that there is a significant correlation between service quality and customer retention.
There is a debate stemming from the differences in service quality and customer satisfaction and the causal relationship between them (Lewis 1989; Babakus et al. 1992, Gilmore et al. 1992). Satisfaction studies have attempted to measure expectations at the same time as perceptions. Philip et al. (1997) argue that the perceptions automatically make an adjustment for the gap that exists between the expectations and the actual experience of a service. The literature is riddled with confusion and discontent as to whether customer satisfaction and service quality are two separate constructs. However, some agreement has been reached that “customer satisfaction is a transitory judgement made on the bases of a specific service encounter whereas service quality is a global assessment based on a long-term attitude” (Parasuraman et al. 1988; Bolton et al. 1991; Bitner 1990; Taylor et al. 1994; Brown et al. 1995). It has been suggested that customer satisfaction leads to a service quality indicating that the causal relationship would be from customer satisfaction to service quality. Some critics have argued that in fact the causal relationship would be from service quality to customer satisfaction (Johnston et al. 1990; Cronin et al. 1992; Cronin et al. 1994; Teas 1993; Parasuraman et al. 1994; Teas 1994).
3. SERVQUAL at your service
Relying on SERVQUAL service quality dimensions (Parasuraman et al. 1985, 1988), this study identifies the
service quality dimensions pertaining seamless use experience and investigates
the relationship between customer satisfaction and intention to recommend
mobile Internet services. The SERVQUAL dimensions are (Parasuraman
et al. 1985, 1988):
- Tangibles: physical facilities, equipment and appearance of personnel
- Reliability: ability to perform the promised service dependably and accurately
- Responsiveness: willingness to help customers and to provide prompt service
- Assurance: knowledge and courtesy of employees and their ability to inspire trust and confidence
- Empathy:
caring, individualized attention, the service provider gives its
customers
van Dyke et al. (1999) has examined the suitability of SERVQUAL to assess the quality of information systems services. They found it to be good starting point and a diagnosis tool for cross-organizational benchmarking. However, they continue that service quality says nothing about the efficiency or effectiveness. Schacherer (2002) argues that SERVQUAL instrument should be used for overall quality assessment instead of comparing cross-functional quality of service.
Heinzl (2002) has defined the SERVQUAL instruments for information system services as follows:
- Tangibles: IS has up-to-date hardware and software
- Reliability: when users have a problem, IS shows a sincere interest in solving it
- Responsiveness: IS tell users exactly when services will be performed
- Assurance: Users will feel safe in their transactions with IS’s employees
- Empathy: IS give users individual attention.
Barnes et al. (2000) adapted SERVQUAL instrument to assess Web site service quality. The SERVQUAL characteristics are encompassed in WebQual developed by Barnes et al. (2000) but some dimensions are addressed to a smaller extent such as empathy. The WebQual subcategories include: navigation, ease of use, visual impact, individual impact, finding information, information content, external integration and communication. Also Cox et al. (2002) have developed their key quality factors particularly for creating successful Web sites. Their quality factors include clarity of purpose, design, accessibility and speed, content, customer service and customer relationship.
4. Methodology and data collection
The usability attributes by Nielsen (Nielsen 1993, 26-37)
were chosen as the starting point for our seamless use experience investigation
as they constitute a generic model and fit in the service context too. The
relation between usability and seamless use experience has been described in
detail in Mattila (2003a). Before the actual data
collection, focus group interviews among expert users were conducted. The
meaning of these interviews was to map the possible options for survey
questions. The questionnaire was pre-tested on a group of 60 students and
modified accordingly. A postal survey was conducted in May 2003. The sample was
drawn from TeliaSonera[2]
We call the customers, who did not own according to the database a
private fixed-line connection at home, the
FIGURE 1 The division of response rate among the different user segments of customers
After a second follow-up, 778 responses were accepted under
further analyses. The final response rate was 25.9%, which is acceptable
according to economic science standards. The distribution of the responses in
different user segments is presented in figure 1. A small minority of
respondents reported using mobile phone (GRPS or high-speed data connection) as
a modem in connection with a laptop as their primary electronic delivery
channel. Among the
The respondents were asked to fill out a structured
questionnaire on a 7-point Likert scale concerning
their preferences, experiences and beliefs towards usage of mobile and Internet
services. Literature (Cooper et al. 1995; Järvenpää
et al. 1997; Crisp et al. 1997) as well as prior conducted surveys guided us in
defining the scales to measure the customers’ perceived seamless use
experience. There were up to 27 questions in each tailored questionnaire. The
The survey questionnaire included questions concerning the respondent’s basic demographic variables, psychological determinants such as level of innovativeness and mobile Internet usage, which was further categorized under for main themes: usage context, service content, seamless interface dimensions and use experience. To get a more accurate and objective results, the mean value of the respondents’ subjective responses were calculated and used as the basis of our evaluation. Statistical methods such as ANOVA, crosstabulation, correlation coefficients, rotated factor analyses, Chi squares and finally structural modeling (AMOS) were applied to our data. Cronbach’s alpha was used to measure the reliability of the results. Only results relevant to this paper are presented in here.
5. Results
One third (33.9%) of the respondents were women and two
thirds (64.8%) were men (see table 1). The majority (59.8%) of the respondents
were 25-49 years old and their annual household income (28.1%) before taxes
fell within the range of 20 000 – 30 000 euros, which matches with the average
annual income of two adults family in Finland (Statistics Finland 2003). Only
every fifth (18.2%) of the respondents had two or more children living at home.
The majority of all the respondents were workers (40.6%). This result is
compatible with the result of the educational background of the respondents,
which was in most cases (29.0%) vocational school.
Over half of the Mobile users (54.6%) thought that it is likely that they will recommend the use of mobile Internet services and majority of the Mobile users (58.8%) went even further by saying they it is likely that they will encourage their friends and relatives to start using mobile Internet services. Two thirds (61.6%) of the Mobile users reported of telling positive things about using mobile Internet services to their friends and 47.3 percent thought that it is likely that they will complain about problems in mobile Internet service usage to their friends. Every fifth (20.8%) said that they would change the service provider (operator) if they encounter problems in the mobile Internet usage.
TABLE 1 Profile
of respondents
|
Mobile
users |
Combined
users |
Fixed-line
users |
Total |
|||||
|
|
No |
% |
No |
% |
No |
% |
No |
% |
|
Total |
211 |
100.0 |
257 |
100.0 |
310 |
100.0 |
778 |
100.0 |
|
Gender |
|
|
|
|
||||
|
157 |
74.4 |
192 |
74.7 |
155 |
50.0 |
504 |
64.8 |
|
|
54 |
25.6 |
55 |
21.4 |
155 |
50.0 |
263 |
33.9 |
|
|
0 |
0 |
10 |
3.9 |
0 |
0 |
10 |
1.3 |
|
|
s.d. |
0.437 |
0.417 |
0.501 |
|
|
|||
|
|
|
|
|
|
|
|
|
|
|
Under
24 years of age |
64 |
30.3 |
33 |
12.9 |
43 |
13.9 |
140 |
18.0 |
|
25-34
years |
81 |
38.4 |
96 |
37.4 |
62 |
20.0 |
239 |
30.7 |
|
43 |
20.4 |
83 |
32.3 |
100 |
32.3 |
226 |
29.1 |
|
|
20 |
9.5 |
41 |
15.9 |
104 |
24.5 |
129 |
16.6 |
|
|
3 |
1.4 |
4 |
1.6 |
1 |
0.3 |
8 |
1.0 |
|
|
s.d. |
0.998 |
0.974 |
1.196 |
|
|
|||
|
|
|
|
|
|
|
|
|
|
|
Less
than 10 000 euros |
33 |
15.6 |
21 |
8.2 |
43 |
13.9 |
97 |
12.3 |
|
10 001
– 20 000 euros |
54 |
25.6 |
48 |
18.7 |
82 |
26.5 |
184 |
23.7 |
|
20 001
– 30 000 euros |
59 |
28.0 |
87 |
33.9 |
73 |
23.5 |
219 |
28.1 |
|
30 001
– 40 000 euros |
25 |
11.8 |
37 |
14.4 |
40 |
12.9 |
102 |
13.1 |
|
More
than 40 001 euros |
29 |
13.8 |
53 |
20.5 |
60 |
19.3 |
142 |
18.3 |
|
11 |
5.2 |
11 |
4.3 |
12 |
3.9 |
34 |
4.5 |
|
|
s.d. |
1.650 |
1.875 |
1.741 |
|
|
|||
|
|
|
|
|
|
|
|
|
|
|
27 |
12.8 |
101 |
39.3 |
128 |
41.3 |
256 |
33.0 |
|
|
60 |
28.4 |
69 |
26.8 |
58 |
18.7 |
187 |
24.0 |
|
|
Single (incl. widow, divorced) |
115 |
54.5 |
80 |
31.1 |
116 |
37.5 |
311 |
39.9 |
|
9 |
4.3 |
7 |
2.7 |
8 |
2.6 |
24 |
3.1 |
|
|
s.d. |
0.940 |
1.154 |
1.397 |
|
|
|||
|
Number of children living at home |
|
|
|
|
|
|
|
|
|
0 |
165 |
78.2 |
152 |
59.1 |
176 |
57.0 |
493 |
63.4 |
|
1 |
21 |
10.0 |
45 |
17.5 |
71 |
23.0 |
137 |
17.6 |
|
2 |
14 |
6.6 |
29 |
11.3 |
42 |
13.6 |
85 |
11.0 |
|
3
or more |
8 |
3.8 |
28 |
10.9 |
20 |
6.5 |
56 |
7.2 |
|
Missing |
3 |
1.4 |
3 |
1.2 |
1 |
0.3 |
7 |
0.8 |
|
s.d. |
0.791 |
1.074 |
1.019 |
|
|
|||
|
Education |
|
|
|
|
|
|
|
|
|
Elementary
school |
24 |
11.4 |
31 |
12.1 |
48 |
15.5 |
103 |
13.2 |
|
Secondary
education |
34 |
16.1 |
63 |
24.5 |
64 |
20.7 |
161 |
20.7 |
|
Vocational
school |
69 |
32.7 |
85 |
33.1 |
72 |
23.2 |
226 |
29.0 |
|
University
degree |
48 |
22.8 |
39 |
15.2 |
82 |
26.4 |
169 |
21.7 |
|
Other |
33 |
15.6 |
36 |
14.1 |
41 |
13.2 |
110 |
14.2 |
|
Missing |
3 |
1.4 |
3 |
1.2 |
3 |
1.0 |
9 |
1.2 |
|
s.d. |
1.952 |
1.916 |
2.063 |
|
|
|||
|
|
|
|
|
|
|
|
|
|
|
10 |
4.7 |
20 |
7.8 |
20 |
6.5 |
50 |
6.4 |
|
|
96 |
45.5 |
116 |
45.1 |
104 |
33.5 |
316 |
40.6 |
|
|
Public
servant |
28 |
13.3 |
31 |
12.1 |
40 |
12.9 |
99 |
12.7 |
|
Other |
71 |
33.6 |
85 |
33.0 |
144 |
46.3 |
300 |
38.5 |
|
Missing |
6 |
2.8 |
5 |
1.9 |
2 |
0.6 |
13 |
1.8 |
|
s.d. |
2.367 |
2.526 |
2.547 |
|
|
|||
Over half of the respondents (59.5%) were customers only to one operator. Every third of the respondents (33.8) had customer relationship with two operators and 5.2 percent of the respondents were customers to three operators. Minority of the respondents (1.4%) had four or more customer relationships with different operators. There was a significant correlation between the number of customer relationships with operators and frequency of particular electronic service delivery channel usage. The heavy users of Mobile Internet are more likely to be customers to several operators (r=.217, p<.01). Also, the more often one uses mobile phone as a modem in connection with PC to access Internet services (r=.354, p<0.1) and the more often on uses PDA to access mobile Internet services (r=.253, p<.01), the more customer relationships with different operators one will have.
No significant correlation was found between the willingness
to recommend the mobile Internet services, telling positive things about using
mobile Internet services, intention to encourage somebody’s use of mobile
Internet services, level of satisfaction and how many operators the user is
customer to. The customers seem to share the equal level of satisfaction after
using mobile Internet services regardless of how many operators they are
customers to (see figure 2). Proportionally the
FIGURE 2 Number of customer relationships with
different operators and feel of satisfaction after using mobile Internet
service
TABLE 2 Frequency of use in relation to level of satisfaction
|
|
|
Daily |
3-5 x a
week |
1-2 x a
week |
|
Mobile Internet users |
Mobile Internet usage
frequency |
11.4 % |
9.0 % |
16.9 % |
|
Feels satisfied after using
mobile Internet service |
10.6 % |
16.2 % |
10.2 % |
|
|
Mobile service quality
fulfills the expectations |
6.6 % |
14.6 % |
11.6 % |
|
|
Fixed-line Internet users |
Fixed-line Internet usage
frequency |
64.7 % |
10.3 % |
8.8 % |
|
Feels satisfied after using
fixed-line Internet service |
33.7 % |
21.1 % |
12.6 % |
|
|
Fixed-line service quality
fulfills the expectations |
30.7 % |
16.9 % |
18.3 % |
An exploratory factor analysis was used in order to identify underlying constructs and investigate relationships among key survey interval-scaled questions regarding customer satisfaction as part of seamless mobile service use experience (see table 3). Principal Axis Factoring was carried out, followed by Varimax Rotation with Kaiser Normalization. The Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy (0.92) were well above the 0.5 recommendation level, and Bartlett’s test of sphericity (p=0.0 and p=0.0) provided as well support for the validity of the factor analysis of the data set (Malhorta 1999). Varimax Rotation facilitated interpretability. In addition, Gronbach’s alphas were counted for each factor scoring above the level of acceptance set by Nunnally (1978). Hence, the data set can be defined as reliable.
Only respondents reporting actually using mobile Internet services were included in the analyses. Initial runs based on a screen plot and eigenvalues showed support for five factors. Only factors with eigenvalues above 1 were expected. In our analyses the eigenvalues varied between 8.5221 and 1.7652. The criterion for assignment of reasons to a certain factor was a minimum factor loading of 0.5. The factors were labeled as tangibles, reliability, responsiveness, assurance and empathy respectively. All the five factors account for more than 10 percent of the total variance and they are defined by two variables each. It is common for all the factors that they seem to be very much operator related. Apparently, customers tend to relate their feel of satisfaction primarily to the service provider instead of device used to operate the service or service content or context. It is an acknowledged phenomenon in marketing, that customers are rarely straightforward in how their satisfaction constitutes.
TABLE 3 Satisfaction attributes for the
seamless use of mobile Internet services
|
Mobile
Internet service users’ perceptions about satisfaction attributes |
Factors
|
||||
|
|
1 15.3% α=.69 |
2 18.7% α=.72 |
3 13.6% α=.71 |
4 12.2% α=.63 |
5 10.5% α=.62 |
|
Factor 1: Tangibles Operator provides updated software needed to use
mobile Internet services on their Web site Operator’s Web
site satisfies my needs Factor 2: Reliability Speed of data
transfer equals what operator promised Operator installs
the new Internet connection as agreed Factor 3: responsiveness Operator solves my
problems in a timely manner Operator is never
too busy to answer my questions Factor 4: assurance Operator treats my
problems with discretion and onfidentiality Operator provides
secure data transfers Factor 5: empathy Operator offers
after-sales services suitable for my needs Operator remembers
me with personal gifts |
.633 .543 |
.701 .642 |
.675 .512 |
.673 .523 |
.685 .598 |
Extraction Method: Principal Axis Factoring.
Rotation Method: Varimax
with Kaiser Normalization.
The customers’ level of innovativeness was mapped with a set of ethnographically oriented arguments. The division of innovator categories was modified from Thorton (2001) to the framework of our study (see table 4). The significant correlations are presented in table 4. Surprisingly, there was no significant correlation between customer’s innovativeness and satisfaction related in reliability. Empathy seems to be the most important satisfaction factor to all the innovator categories. Assurance correlated with change driven and personal service driven types of innovativeness. Responsiveness was the most controversial with significant correlations with computer positive and personal service driven types of innovators.
TABLE 4 Correlation
matrix on innovator categories and satisfaction attributes
|
CORRELATION MATRIX Type and level of innovativeness
Þ Satisfaction variables ß |
Change driven |
Personal service
driven |
Technology positive |
Knowledgeable |
Computer positive |
|
Operator is never too busy to answer my questions (RES) |
|
|
|
|
.176* |
|
Operator offers after-sales services suitable for my needs (EMP) |
.148* |
.144* |
.305** |
.191** |
.147* |
|
Operator provides secure data transfers (ASS) |
|
.175* |
|
|
|
|
Operator offers unique customized offers and benefits only for me (EMP) |
.141* |
.253** |
|
|
.177* |
|
Operator solves my problems in a timely manner (RES) |
.191** |
.183** |
|
|
|
|
Operator provides updated software needed to use mobile Internet services
on their Web site (TAN) |
.170* |
.163* |
.160* |
|
.157* |
|
Operator’s Web site satisfies my needs (TAN) |
.164* |
.216** |
|
.152* |
|
|
Operator treats and solves my problems with discretion and
confidentiality (ASS) |
.164* |
.233** |
|
|
|
** Correlation
is significant at the 0.01 level.
*
Correlation is significant at the 0.05 level.
RES=Responsiveness EMP=Empathy ASS=Assurance
TAN=Tangibles
We found two different types of efficiency of use. Efficiency is related
in the utilization factor – how well the customer achieves the aims, which she
has set on the use of service. Effectiveness is related in the capacity ratio –
how fast is the data transfer and does the customer get her money worth.
Previously, we have defined two types of errors and their relation in purpose
of use (content) and use context (see Mattila 2003b).
The results of a crosstabulation between willingness
to recommend mobile Internet services and experienced level of seamless use
experience are presented in figure 3. Logically, it appears that customers, who
have not had a seamless use experience, will not recommend the use of mobile
Internet services. Surprisingly, almost 20 percent of the customers with a
seamless use experience are also reluctant to recommend the use of mobile
Internet services. For example, every fifth (20.7%) of the customers, who
report high satisfaction figures are not going to recommend the use of mobile
Internet services. This finding is in line with previous studies conducted in
FIGURE 3 Crosstabulation:
Recommendation * Dimensions of seamless mobile service use
experience
To investigate further the relationship between demographic
variables and willingness to recommend the use of mobile Internet services, we
used Chi square to test the variables (see table 5). The respondents were
divided in two segments of regular users of mobile Internet services and
occasional users of mobile Internet services to perform this test. It can been
seen from table 5 that the only significant demographic variable in the segment
of regular users is gender. Although traditionally women are often perceived as
the more talkative sex, in this case men proved to be the ones more actively
recommending the use of mobile Internet services. This can be explained at
least partially with the high percentage of male users in the segment of
regular users. In the segment of occasional mobile service users the
significant demographic variables in relation to willingness to recommend the
use of mobile Internet services are gender, age and marital status. The most
likely occasional mobile service user to make a recommendation is a 25-34 years
old male, who is married.
TABLE 5 Chi square on demographics and
willingness to recommend use of mobile Internet
services
Chi-square df Sig. (2-sided)
value p
value
Regular users
Gender
9.701 3 .034
Age 11.253 9 .489
Marital status 3.674 4 .285
Education 17.497 15 .503
Income 11.953 12 .341
Profession 6.157 9 .614
Line of business 30.243 21 .129
Occasional
users
Gender 22.223 3 .000
Age 24.377 9 .013
Marital status 9.149 4 .018
Education 21.255 15 .312
Income
7.210 12 .923
Profession 13.140 9 .069
Line of business 26.057 21 .320
The construct of seamless use experience is described in detail in Mattila (2003a). Based on the research findings were are able to present a cognitive model of seamless use experience dimensions affecting the overall satisfaction, willingness to recommend and intention to encourage the use of mobile Internet services in figure 4.
FIGURE 4 A
cognitive model of seamless use experience dimensions affecting the overall
satisfaction,
willingness to recommend and intention to encourage the use of mobile Internet
services
Level of satisfaction, willingness to recommend the use of
mobile Internet services and intention to encourage the use of mobile Internet
services among friends and relatives are all highly interrelated with
correlation coefficients of .812, .867 and .927. The level of satisfaction
affects positively both the willingness to recommend and intention to encourage
the use of mobile Internet services. Moreover, willingness to recommend has a
positive effect on intention to encourage. Level of satisfaction and intention
to encourage are both characterized by two dimensions of seamless use
experience: learnability and efficiency of use, which
consists of efficiency and effectiveness. Memorability
is a common factor to all main determinants. Errors and frequency of use affect
the willingness to recommend. Thus, less experienced errors (minor or
catastrophic) are likely to lead into a recommendation. Willingness to
recommend and intention to encourage are both dependant on the level of satisfaction
and to be more precise, the experience empathy from the service provider
side.
6. Conclusions
In this study, our aim is to identify the service quality dimensions pertaining seamless use experience and investigate the relationship between customer satisfaction and intention to recommend mobile Internet services. According to our analysis the level of satisfaction after using mobile Internet services, intention to encourage the use of mobile Internet services and willingness to recommend the use of mobile services are strongly interrelated.
Over half of the
Customers felt that even though their expectations were not fully fulfilled, they still were satisfied with the service. Apparently, customers tend to relate their feel of satisfaction primarily to the service provider instead of device used to operate the service or service content or context. It is an acknowledged phenomenon in marketing, that customers are rarely straightforward in how their satisfaction constitutes.
From the results of a crosstabulation between
willingness to recommend mobile Internet services and experienced level of seamless
use experience can be drawn that customers, who have not had a seamless use
experience, will not recommend the use of mobile Internet services.
Surprisingly, almost 20 percent of the customers with a seamless use experience
are also reluctant to recommend the use of mobile Internet services. For
example, every fifth (20.7%) of the customers, who report high satisfaction
figures are not going to recommend the use of mobile Internet services. This
finding is in line with previous studies conducted in
One service provider might think about the following: If
customers feel that the services are functioning well, and they still will not
encourage people to use them or even recommend the use of the services, why
should we enhance the usability of services. It is very probable, that there
are other dimensions for satisfaction than service provider related variables.
Future research should consider this to reveal more of the secrets of customer
satisfaction.
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