making the customer the coproducer -...
TRANSCRIPT
Making the customer the co-producer:
A critical incident study on customer satisfaction and self-
service-channel choice in commercial air travel
Att förvandla kunden till medarbetare:
En ”kritiska händelser” studie på kundnöjdhet och
självbetjäningskanal-val vid kommersiella flygresor
Henrik Huotari
Faculty: Faculty of Economy, Communication and IT
Subject: Industrial Engineering and Management
Points: 30 ECTS
Supervisor: Maria Åkesson
Examiner: Berndt Andersson
Date: Spring 2012
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Acknowledgements
I would like to thank my supervisor Maria Åkesson for her guidance and
advice throughout this semester. I would also like to express my sincere
gratitude to all of you who agreed to participate in this study and hope that
this thesis will bring you more pleasurable future flight experiences. And
finally, I also want to thank all of you who took time, listened, and helped me
in discussing the thesis material.
Henrik Huotari,
June 2012
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ABSTRACT
This thesis is based on a case study of an airline’s (Scandinavian Airlines
(SAS)) customers’ views on self-service technologies for check-in; mobile
check-in, internet check-in, and machine (kiosk) check-in. The first aim of the
paper was to find sources of satisfaction and dissatisfaction in the airline
industry. A number of critical incidents leading to satisfactory and
dissatisfactory experiences have been categorized by using the critical incident
technique method based on customers’ recalls of past events. Main sources of
satisfaction were the SSTs ability to provide a more efficient service by time
savings, avoiding queues and by providing increased customer control. Main
sources of dissatisfaction were related to technology failure such as
malfunctioning machines, technical design problems and service design
problems due to unclear role clarity among customers caused by lack of
information and trust in own abilities.
Second aim of the study was to identify a number of variables affecting SST
channel selection. Qualitative interviews revealed following main variables
affecting channel choice: accessibility, awareness, lack of trust, and perceived
channel efficiency. Findings have been discussed from the perspective of
models used in present research such as the consumer readiness model and
trusting intentions model so that future researchers can identify and use valid
models for understanding SST channel adoption and satisfaction drivers in the
flight industry. Hands on managerial implications are provided in the closing
part of the paper.
Originality: The thesis show industry specific satisfaction and dissatisfaction
causes that differ from previous research. Second contribution is the
development and classification of factors in groups that influence the SST
channel choice for check-in at airports. Finally the paper shows that none of
the current models for use intention can independently be used to fully explain
choice of channel.
Keywords: self-service technologies, customer satisfaction, SST, self-service
channels, SAS, service design, self-service, customer co-production, adoption,
self-service options.
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Table of Contents
1. INTRODUCTION .................................................................................................................. 6
2. THEORETICAL FRAMEWORK ...................................................................................... 10
2.1. CUSTOMER SATISFACTION ........................................................................................... 10
2.2. EFFICIENCT COMPLAINT MANAGEMENT ................................................................. 10
2.3. PREVIOUS FINDINGS ON CUSTOMER SATISFACTUON, DISSATISFACTION AND
ADOPTION ................................................................................................................................ 11
2.4. ADOPTION MODELS ........................................................................................................ 12
2.4.1. TECHNOLOGY READINESS ....................................................................................... 12
2.5.2. SITUATIONAL FACTORS ............................................................................................ 13
2.5.3. CONSUMER READINESS ........................................................................................... 14
2.5.4. TECHNOLOGY ACCEPTANCE MODEL .................................................................... 17
2.5.5. THEORY OF PLANNED BEHAVIOR .......................................................................... 17
2.5.6. TRUSTING INTENTION .............................................................................................. 18
3. METHODOLOGY .................................................................................................................... 24
3.1. RELATION TO THEORETICAL FRAMEWORK ............................................................ 24
3.2. CRITICAL INCIDENT TECHNIQUE ................................................................................ 27
3.3. COMPANY INTRODUCTION: THE SAS GROUP .......................................................... 29
3.4. SELF-SERVICE CHECK-IN OPTIONS AT SAS .............................................................. 30
3.5. SAMPLE CHARACTERISTICS ......................................................................................... 31
3.6. PROCEDURE ...................................................................................................................... 32
4. EMPIRICAL FINDINGS ......................................................................................................... 35
4.1. SATISFYING AND DISSATISFACTYING INCIDENTS ................................................ 35
4.1.1. SATISFYING INCIDENTS ............................................................................................ 35
4.1.2. DISSATISFYING INCIDENTS ..................................................................................... 38
4.2. CHECK-IN ALTERNATIVES ............................................................................................ 41
5. ANALYSIS ................................................................................................................................. 46
5.1. SOURCES OF SATISFACTION AND DISSATISFACTION ........................................... 46
5.2. SELF-SERVICE CHANNEL USE ...................................................................................... 51
6. STUDY LIMITATIONS, STRENGTHS AND DIRECTIONS FOR FURTHER
RESARCH ..................................................................................................................................... 57
7. MANGERIAL IMPLICATIONS ............................................................................................. 59
8. CONCLUSIONS ........................................................................................................................ 64
REFERENCES .............................................................................................................................. 65
APPENDIX .................................................................................................................................... 71
APPENDIX A: INTERVIEW GUIDE: SELF-SERVICES FOR CHECK-IN AT SAS (English
version) ....................................................................................................................................... 71
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APPENDIX B: INTERVJUGUIDE: SJÄLVBETJÄNINGSTJÄNSTER HOS SAS (svensk
version) ....................................................................................................................................... 74
Table of figures and tables
Figure 1: Consumer readiness model………………………………………………….....…16
Figure 2: Example on how antecedent variables can affect or are mediated by consumer
readiness dimensions and trial……………………………………………………16
Figure 3: Combining TR, TPB and TAM models………………….………………………18
Figure 4: Research logic…………………………………………………………………….27
Figure 5: Check-list for managers for successful SST to ensure customer satisfaction and
increase trial with SSTs………………..…………………………………..……..63
Table 1: Variables affecting SST users’ satisfaction and usage intentions………………..20
Table 2: Interview questions’ relation to theoretical framework…………………………..25
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1. INTRODUCTION
After months of arguing the Johnson family finally decided to spend their holiday in
Frankfurt, Germany. Mr. Johnson takes a seat in front of a computer and searches for “air
travel Frankfurt”. Soon he has found a webpage where he pays and reserves his desired
flight.
A couple of weeks later it is time to fly and the Johnson family just arrived at the airport. It
is late afternoon and the airport is swarming of people so they decide to use some machines
that are marked with “check-in”. The reservation number and the amount of baggage is
typed into the machine, the family also get to decide which seats to pick and naturally chooses
to put the whole family together. After typing all necessary information the tickets are printed
out of the machine together with some baggage tags. Next the family moves to the baggage
check-in desk which has quite a long queue, so they need to wait for about 10 minutes before
getting served. Here an argument erupts with the service personnel about the definition of a
bag. The issue was that one of the bags was not a suitcase and had an additional bag
wrapped around it (that is two bags), but their combined weight was just under the limit for
what was allowed for a single bag. A year ago when the Johnson family had traveled with
another airline in the same alliance, that airline had accepted the bag as one, thus the
Johnson’s believed this would happen again. In the end the Johnson family had to pay good
money for the extra bag and left the baggage check-in fairly upset.
The story above is fictional; however, it could reflect some of the issues and
opportunities currently present in a service environment that is semi-
automatized. Traditionally, the service environment was characterized by an
encounter between a service employee (seller) and a customer (buyer), but due
to the introduction of service-replacing technology there is no longer a need
to have the physical presence between the seller and buyer in a marketplace
interaction, thus modern transactions are said to take place in the
“marketspace” (Rayport & Sviokla 1995; Meuter et al. 2003). During the past
decade we have experienced an increasing trend away from face-to-face
contacts and towards self-service technologies; at the moment most noticeably
in the retail environment (Liljander et al. 2006). This development should not
come as a surprise; replacing human service personnel with machines has the
opportunity to drastically cut costs by avoiding labor costs, enhance
productivity and efficiency, provide customers with new and convenient
service-channels, increase customer satisfaction for instance through the
creation of the marketspace that removes service use from constraints put by
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time and space (Meuter et al. 2000; Meuter et al. 2003; Lin & Hsieh 2007;
Walker et al. 2002; Bitner et al. 2002; Lovelock & Young 1979).
In the academic world, the technologies that replace services and that transfer
a load of the work to the customer are known as self-service technologies or
SSTs. According to Meuter et al. (2000) SSTs are technological interfaces that
replace face-to-face contact between the customer and service personnel. SSTs
allow a customer to consume a service without human interaction or direct
personal contact. ATMs, automated hotel checkouts, online-banking,
telephone-banking, self-service gas pumps are all examples on various SSTs. In
the introductory story we encountered internet reservation of a flight and
check-in kiosks and these are just two of the various SSTs that are used in the
airline industry. Other SSTs used in the airline industry are e-ticket, internet
check-in, mobile phone check-in, and electronic gate services for frequent
flyers, which were introduced to the airline industry in order to cut costs and
increase service efficiency by reducing waiting lines at the airport and giving
customers increased control over the check-in process (SAS 2012; Liljander et
al. 2006). At the moment there are restrictions on how much self-service
technology is deployed, still customers need to check in luggage at the over-
the-counter check-in desk (Liljander et al. 2006). However; SAS has recently
introduced the “Self Service Baggage Drop” (SAS 2012), so the limits on the
“work” that can be transferred to the customer can always be extended.
According to Meuter et al. (2005) the key barrier in consumer adoption (long
term usage intention) of SSTs is trial. The adoption of the self-service kiosk
for automated check-in has been slow, in the period from the introduction in
1996 to 2002 an airline in a major airport only achieved a 14% adoption and
by 2006 the adoption rate had reached 37.6 % for a set of European airlines
(Liljander et al. 2006). The low adoption rate indicate that there are clearly
some hurdles associated with making the customer a co-producer of the
service, which implies a change in customers’ current behaviors (Bendapudi &
Leone 2003; Meuter & Bitner 1997; Meuter et al. 2005). In most cases
customers still have the choice of using an SST or to use the traditional over-
the-counter service (Meuter et al. 2003); however, the reluctance of some
customers to adopt SSTs may add up costs for companies trying to focus only
on SSTs (Walker et al. 2002).
In the airline industry there are several self-check-in SSTs that provide benefits
like time saving, but many customers do not try them either because they are
unaware of benefits or because they do not know how to use the system.
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Some airlines have decided to keep interpersonal service check-in, but some
like SAS (Scandinavian Airlines) have completely switched to self-service
options by removing the interpersonal check-in option at some airports (SAS
2012; Liljander et al. 2006). Such a maneuver could possibly hurt customer
satisfaction and call for new strategies to meet new expectations (Cunningham
et al. 2009) and result in new considerations as described by Meuter et al.
(2005):
“It is important to understand the long-term implications of shifting customers away from interpersonal
interactions, which are traditionally viewed as important elements for establishing trust and loyalty in service
contexts.” (Meuter et al. 2005, pp. 79)
Hence, this thesis aims to answer: What are sources of satisfaction and
dissatisfaction with currently used SSTs in commercial flight industry? The
research problem has been previously addressed by Meuter et al. (2000), but
the studies were conducted through online questionnaires and had not been
limited to any specific SSTs. The importance of context in these kinds of
studies on SSTs has continuously been cited as a potential or valid source of
error (Meuter et al. 2000; Gelderman, Ghijsen, and van Diemen 2011).
Previous studies have been focused on initial trial decision and attitudes
towards SSTs (Gelderman et al. 2011; Meuter et al. 2000), this thesis will focus
on those customers’ experiences that have already tried SSTs and are more
experienced users.
It is clear that some SST channels (e.g. mobile phone, internet, check-in kiosk)
are cheaper to maintain than others and customers are faced with the choice
of picking among a variety of different SST options (Liljander et al. 2006),
thus it is interesting to know what causes a customer to adopt one self-service
option in favor of another? Which variables are behind people’s choice of SST
channels and which current behavioral models used in explaining SST
adoption in the present research can explain SST-channel choice?
This thesis starts off with explaining the self-service check-in options
customers currently are faced with. Thereafter theoretical framework
introduces customer satisfaction concept and various models behind SST
adoption. Critical incident technique (CIT) interviews have been used in order
to determine drivers of satisfaction with self-service encounters and qualitative
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interviews have been used to study the drivers behind self-service channel
choice. Results from the interviews are discussed and compared to the
theoretical framework in the analysis part and managerial implications are
explained and further research directions are suggested.
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2. THEORETICAL FRAMEWORK
2.1. CUSTOMER SATISFACTION
It is necessary to make a distinction between attitude and customer
satisfaction. The difference between an attitude and satisfaction is that an
attitude has an enduring effect while satisfaction is transient and experience-
specific (Oliver 1980; Oliver 1981). Attitude has also a minor influence to
behavioral intention in comparison to customer satisfaction (Chen et al. 2009).
Customer satisfaction can be viewed as a confirmation-disconfirmation
paradigm, also called the expectation-confirmation model (ECM) (Oliver
1980, 1993). Emergence of customer satisfaction is viewed as a psychological
process where prior expectations of a service (or product) are compared to the
perceived performance of the service. If perceptions exceed the expectations
customers feel delighted, if perceptions equal expectations customers feel
satisfied, and if expectations exceeds the perceived service then customers feel
dissatisfied, hence customer satisfaction is the result of disconfirmation of
expectations. Customer satisfaction can lead to loyalty, but it will not per se
result in continuance intention. This model has previously been used to
predict and explain information systems’, such as SSTs, long-term usage
(Bhattacherjee 2001; Chen et al. 2009).
2.2. EFFICIENCT COMPLAINT MANAGEMENT
If a critical incident occurs, such as customer contact with unfriendly
personnel or technology failure, this reduces customer loyalty. If not dealt with
this reduction is permanent. However; if the critical incident is dealt with
effective complaint management research has shown that customer loyalty will
permanently increase to a higher level than the initial level. It is important to
address the complaint quickly in order to have effective complaint handling
and preventing service switching (Tax, Brown, and Chandrashekaran 1998).
Thus, it is necessary to consider the effects of complaint handling in order to
get a more accurate picture on service-quality and satisfaction.
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2.3. PREVIOUS FINDINGS ON CUSTOMER SATISFACTUON,
DISSATISFACTION AND ADOPTION
Previous studies on satisfaction and dissatisfaction regarding SSTs exists
(Meuter et al. 2000; Liljander et al. 2006). Meuter et al. (2000), findings offer
general insights on the benefits of SSTs which are: (1) solving an intensified
need, (2) better than the alternative, (3) completes the task. The second insight
can be subdivided into (2A) easy to use, (2B) avoid interpersonal contact with
service personnel, (2C) saves time, (2D) can be used at any time (when I want),
(2E) service can be performed (almost) anywhere (where I want), (2F) saves
money. The previously mentioned benefits lead to satisfying SST experiences.
Dissatisfying events occurred when technology or process failed, design
problems (poorly designed technology leading to confusion or when the
service offered by the machine didn’t match the need of the customer), and
during failures caused by the customer itself. Process failure is especially
troublesome since the customer might not be fully aware of the failure before
damage has been done.
Liljander et al. (2006) found, from the point of view of the customer,
following reasons for customers to adopt self-service kiosks at airports; (1)
saves time, (2) avoid queuing, (3) being in control (able to pick own seat and
flexibility to perform the service), (3) interested in new technologies, (4) habit,
and (5) part of modern lifestyle. The researchers also found the following
reasons for customers not to adopt self-service kiosks; (1) benefits are not
clear or known, (2) lack of motivation, (3) preference or confidence of
interpersonal service and dislike of self-service, (4) no negotiation possibilities
for SST, (5) low perceived ease of use, (6) lack of trust in machines or own
skills to use them or previous negative experiences with machines, (7) other
stated reasons are laziness, habit, and “not possible to do it”.
Dabholkar (1996) found enjoyment and being in control as sources of
satisfaction that related to usage intention. Langeard et al. (1981) referred to in
Dabholkar (1996) suggested that people prefer using (playing with) machines
that brings them enjoyment. Control dimension (found by Liljander et al.
(2006) as well) is related to the amount of control a customer has over the
service process and outcome. In airline check-in context it relates to pick a
seat and flexibility in performing the service. It is believed that increased
perceived control can lead to increased customer satisfaction and value of the
service (Bateson and Hui 1987).
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2.4. ADOPTION MODELS
Previous studies on SSTs have predominantly focused on various variables’
positive or negative impact on adoption and continued use of SSTs (e.g.
Meuter et al. 2000; Gelderman et al. 2011). Several variables have been
proposed and tested under various contexts, but for the scope and focus of
this thesis all variables will not be covered.
2.4.1. TECHNOLOGY READINESS
A number of studies (Parasuraman 2000; Liljander et al. 2006; Chen et al.
2009) have studied the effect on individual characteristics that encompass
technology readiness (TR) which determines the predisposition to use SSTs.
The researchers have been focused on four main personality traits:
innovativeness, optimism, discomfort, and insecurity. In this context optimism
is a positive view of technology. According to (Chen et al. 2009, pp. 1251) a
positive view of technology is defined as the “belief in increased control,
flexibility, and efficiency in life due to technology.” Innovativeness expresses a
person’s tendency to be first to adapt a new technology (Parasuraman 2000;
Chen et al. 2009; Tsikriktsis 2004). Discomfort is the distrusting and skeptical
belief towards technology and its ability to work properly (Parasuraman 2000;
Chen et al. 2009; Tsikriktsis 2004). Insecurity is defined as feeling
overwhelmed by and lack of control over technology (Parasuraman 2000;
Chen et al. 2009; Tsikriktsis 2004).
The relationship between TR and consumer behavior is currently unclear,
where different studies have yielded in mixed results (e.g. Lin and Hsieh 2007;
Liljander et al., 2006; Massey, Khatri, and Ramensh 2005; Chen et al. 2009).
The researchers have found that the TR variables influence the attitudes
towards SSTs in airports, but the relationship between trial behavior and TR
influenced attitude is only minor with optimism as the major predictor of trial
behavior (Liljander et al. 2006). Gelderman et al. (2011) argues that the studies
are conducted in different context, thus TR’s impact on SST usage is possibly
context specific. Chen et al. (2009) found that customer satisfaction is strongly
related to the individual personality traits related to technology readiness
which confirms studies by Parasuraman (2000) and Liljander et al. (2006).
Optimism and innovativeness was seen to be the traits that increased
satisfaction, while discomfort and insecurity the traits that reduced satisfaction
(Chen et al. 2009). Liljander et al. (2006) found that innovativeness has no
effect on service quality satisfaction for check-in kiosks at airports.
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Liljander et al. (2006) also found that people using one kind of SST (kiosks)
are more likely to use other kinds as well. The authors showed that TR is
positively correlated with self-service kiosk-use and the effect was seen to be
largest for internet check-in followed by mobile and kiosk services. Authors
argue that an adoption hurdle could be the lack perceived differences between
SST alternatives.
2.5.2. SITUATIONAL FACTORS
Gelderman et al. (2011) investigated the impact of the situational factors
(Oyedele and Simpson 2007): perceived crowdedness (Machleit et al., 2000)
and role clarity (Lee & Allaway 2002) on the initial trial decision where
customers could choose between using a check-in kiosk (SST) or check-in
counter (interpersonal). With increased crowdedness waiting times increase
and positive attitude towards SSTs increases indicating that the time saving
benefit becomes more attractive during this situational variable, consequently
crowdedness is an important variable when considering air travel (Dabholkar
1996; Liljander et al. 2006; Gelderman et al. 2011). Dabholkar (1996) clarify
that the crowds are situational since they might not be evident before the
passenger has arrived at the airport. The author also explain that people that
are unfamiliar with the technology would be less likely to use the option even
if crowds are large and people that are uncomfortable with social interactions
would be more likely to use SSTs even if crowds are small.
Role clarity is the customer’s understanding of what is expected (“what to do”)
from him in the service process and it has been shown that increasing role
clarity leads to increased SST acceptance (Lee & Allaway 2002; Gelderman et
al. 2011). Insufficient role clarity has been shown to reduce participation since
the consumer lacks awareness and understanding of his or her role in the
service process (Larsson & Bowen 1989; Meuter et al. 2005). A common way
for airlines to increase customer’s role clarity with SSTs is through occasional
demonstrations and real-time “hand-holding” by service personnel (Liljander
et al. 2006).
Gelderman et al. (2011) found that SST users (when considered as a group)
that are faced with the choice between an interpersonal service encounter and
a self-service kiosk have a lower need for human interaction, therefore “need
for interaction” should be viewed as an independent variable influencing the
situational factors. Studies have shown that customers do not chose SSTs to
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avoid personal service, but the opposite SSTs are avoided since some
customers enjoy the personal service and interaction (Meuter et al. 2000;
Meuter et al. 2005; Liljander et al. 2006).
2.5.3. CONSUMER READINESS
Role clarity is as well a part of the consumer readiness model. Consumer
readiness consists of role clarity, motivation and ability and the model is found
to be a significant contributor to the adoption and trial of SSTs and it is an
instrumental model that is used to understand customer’s willingness to co-
produce (Meuter et al. 2005). Motivation is the willingness to perform an
activity (use SSTs) because of some clear benefit and it is influenced by
intrinsic (e.g. felling of prestige, personal growth) and extrinsic rewards (price
discount, time savings) (Meuter et al. 2005). Ability is the feeling of self-
efficacy to perform the task and includes such things as knowledge and skills
(Ellen, Bearden, and Sharma 1991; Jayanti & Burns 1998; Jones 1986; Meuter
et al. 2005). Ability can also be described as more about “can do” than “want
to” or “knowing how to” (Meuter et al. 2005). Research has shown that self-
efficacy (ability) is more likely lower for more complex tasks, but relatively
simple tasks can produce these feelings as well (Ellen et al. 1991). The
consequence of low self-efficacy is that those who experience this feeling will
not engage in the behavior (e.g. using SST) even if they acknowledge it being
better than the alternative (Seltzer 1983).
Role clarity and extrinsic motivation from the consumer readiness model has
been shown to be the two strongest predictors of trial (Meuter et al. 2005).
From corporations point of view to successfully make the customer
coproduce companies need to conduct a “job analysis” (usually done for
employees) of the task. If customers are clear in their role for the task (know
what to do), are motivated to do the task and as well have the ability to
complete the task, then successful transfer of responsibilities is more likely
(Dellande, Gilly and Graham 2004; Schneider & Bowen 1995 referred to in
Meuter et al. 2005).
The consumer readiness model also includes a number of antecedent variables
that can be grouped in two categories: innovation characteristics and
individual differences. Innovation characteristics include antecedent variables
relative advantage, compatibility, complexity, trialability, observability,
perceived risk. Individual differences include: need for (human interaction),
15
inertia, previous experience, and demographics (Ellen et al. 1991; Gremler
1995 referred to in Meuter et al. 2005; Olshavsky & Spreng 1996; Meuter &
Bitner 1997; Raub 1981 referred to in Meuter et al 2005; Ray & Minch 1990
referred to in Meuter et al 2005; Dabholkar 1996; Mohr & Bitner 1991; Meuter
et al. 2005). These antecedent variables are more or less affecting the role
clarity, motivation and ability dimensions (Meuter et al. 2005). A figure on
how the antecedent variables relate to consumer readiness and two examples
on how the variables are mediated through consumer readiness dimensions are
illustrated in figure 1 and 2 on the next pages. Some of the variables are
explained in table 1 (starts at page 19).
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Figure 1: Consumer readiness model. Directly taken from Meuter et al. (2005), p. 63.
Figure 2: Example on how antecedent variables can affect or are mediated by consumer
readiness dimensions and trial, figure from Meuter et al. (2005) p. 77.
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2.5.4. TECHNOLOGY ACCEPTANCE MODEL
A number of studies have been focused on the technology acceptance model
(TAM) that considers “perceived ease of use” and “perceived usefulness”
(Davis 1989; Dimitriadis & Kyrezis 2011). Perceived ease of use is the
perception and salient beliefs that the SST will be user-friendly and effortless
to use (Davis 1989; Chen et al. 2009; Taylor & Todd 1995). According to
Dabholkar (1996) effort and complexity are underlying factors affecting
perceived ease of use. Perceived usefulness is defined as the salient belief that
an SST will enhance performance and productivity (Davis 1989; Chen et al.
2009; Taylor & Todd 1995). TAM has demonstrated capabilities to a lesser
degree predict customer satisfaction where perceived ease of use had the
greatest impact on satisfaction. The TAM variables are also interrelated since
usefulness of an SST will drop if it is difficult to use (Chen et al. 2009; Wang et
al. 2008).
2.5.5. THEORY OF PLANNED BEHAVIOR
Theory of planned behavior (TPB) is yet another model used to determine
continuance intention of customers (Chen et al. 2009). TPB consist of two
variables; perceived behavioral control and subjective norm. Perceived
behavioral control express to which degree a behavior of interest is perceived
easy or hard to perform (Ajzen & Fishbein 1980; Taylor & Todd 1995;
Bhattacherjee 2000; Chen et al. 2009). The perceived social pressure that
hinders one from taking action (performing behavior) is defined as subjective
norm (Ajzen & Fishbein 1980; Taylor & Todd 1995; Bhattacherjee 2000; Chen
et al. 2009) and can be exerted by friends, family and the society. Subjective
norm have a strong influence on perceived usefulness for instance through
word-of-mouth that occurs after consumption, thus indirectly influences
customer satisfaction (Liao, Chen and Yen 2007; Chen et al. 2009). Behavioral
control has been seen as the strongest predictor of long-term adoption and
usage of SSTs. Behavioral control variable was followed by customer
satisfaction (that is heavily influenced by optimism) and subjective norms
(Chen et al. 2009). A model that illustrates how TPB, TR and TAM can be
combined is illustrated in figure 3.
18
Figure 3: Combining TR, TPB and TAM models. Figure is directly taken from Chen et al.
(2009), p. 1252.
2.5.6. TRUSTING INTENTION
Dimitriadis and Kyrezis (2011) investigated the influence of trust on adoption
of SSTs in an e-commerce environment (e-banking). Authors show in a model
that intention to transact (use the SST-channel) is dependent on trusting
intentions for the channel, that is in turn dependent on trusting beliefs in the
channel, perceived ease of use, perceived usefulness and customer’s degree of
information about the channel (the last antecedent variable also directly
influences the intention to transact). Trusting intention is defined as “the
trustor’s willingness to engage in a risky behavior or to interact with a trustee”
(Dimitriadis & Kyrezis 2011, p. 1294).
Trusting intention was seen to be the most important variable in explaining
use intention for banking channels. Customers have indicated that check-in
kiosks at airports are perceived ease to use, but only worth using if the queue
for the check-in desk is long enough, therefore ease of use benefit should be
communicated with others (Liljander et al. 2006). Communicating the benefit
means exchanging information to the customer about the channel.
19
McKnight and Chervany (2002) conceptualization of trust is four dimensional,
consisting of competence, benevolence, integrity, and predictability.
Competence is defined as the belief that the other party is able to fulfill
promises. The belief that the trustee is motivated to act in the trustor’s
interests is the definition of benevolence. Belief that trustee will act ethically,
make good-faith agreements, tells the truth encompasses the integrity factor.
Foreseeability and consistency of actions encompasses the integrity factor of a
trustor. At some occasions the four dimensions can be grouped into two;
cognitive (competence and predictability) and affective (benevolence and
integrity). In online-banking context affective trust had the greatest impact on
continued use intention (Dimitriadis & Kyrezis (2011).
All the models and variables that are believed to have an influence on SST
satisfaction and to influence the choice and adoption of channels are listed in
table 1.
To summarize; all suggested models; TR, TAM, consumer readiness,
situational factors, trusting intentions, and TPB have in previous studies
shown various degrees of predictive qualities on SST adoption and customer
satisfaction. Thus, it is interesting to consider all of them and their respective
variables especially since their impact are heavily context specific, e.g. trusting
intentions in online banking. As seen some variables are reoccurring in a
couple of models, e.g. role clarity is found in both consumer readiness model
and as a situational factor. Other variables such as; ability, complexity,
perceived behavioral control and perceived ease of use, perceived usefulness
and relative advantage; are very similar, almost analogous, which indicates
similarities between some of the suggested models. As mentioned attempts
have been made to combine the different models e.g. Chen et al. (2009),
however, no single study has yet considered the complete set of variables
associated to satisfaction and adoption of self-service technologies. And no
study has considered a larger set of several variables in the commercial flights
industry. Due to similarities an own framework of combining the presented
models are presented in table 2, page 25, more on this in the methodology
section.
20
Table 1: Variables affecting SST users’ satisfaction and usage intentions.
Model Used for: Variable Explanation Literature
Technology
Readiness (TR)
Customer
satisfaction and
trial
Optimism In this context optimism is a positive view of technology.
According to (Chen et al. 2009, pp. 1251) a positive view of
technology is defined as the “belief in increased control,
flexibility, and efficiency in life due to technology”.
Parasuraman 2000; Liljander et al. 2006;
Chen et al. 2009; Tsikriktsis 2004
Innovativeness Innovativeness expresses a person’s tendency to be first to
adapt a new technology.
Parasuraman 2000; Liljander et al. 2006;
Chen et al. 2009; Tsikriktsis 2004
Discomfort The distrusting and skeptical belief towards technology and its
ability to work properly.
Parasuraman 2000; Liljander et al. 2006
Chen et al. 2009; Tsikriktsis 2004
Insecurities Feeling overwhelmed by and lack of control over technology. Parasuraman 2000; Liljander et al. 2006;
Chen et al. 2009; Tsikriktsis 2004
Technology
Acceptance Model
(TAM)
Satisfaction,
trial and
adoption
Perceived ease of
use
The perception and salient beliefs that the SST will be user-
friendly and effortless to use. Effort needed to use the SST and
complexity are two underlying factors affecting perceived ease
of use.
Davis 1989; Chen et al. 2009; Taylor &
Todd 1995; Dabholkar 1996
Perceived usefulness The salient belief that an SST will enhance performance. Davis 1989; Chen et al. 2009; Taylor &
Todd 1995
Consumer
Readiness
Trial Motivation Willingness to perform an activity (use SSTs) because of some
clear benefit and it is influenced by intrinsic (e.g. felling of
prestige) and extrinsic rewards (time savings).
Meuter et al. 2005
Ability The feeling of self-efficacy to perform the task. Ellen et al. 1991; Jayanti & Burns 1998;
Jones 1986; Meuter et al. 2005
21
Role clarity The customers’ understanding of what is expected (“what to
do”) from him in the service process.
Meuter et al. 2005;
Lee & Allaway 2002; Gelderman et al.
2011
Antecedent
variables to
consumer
readiness
Various Need for (human)
interaction
Need to socialize and interact with other humans. Some people
feel that technology dehumanizes the service interaction.
Gelderman et al. 2011; Liljander et al.
2006; Dabholkar 1996; Langeard et al.
1981 referred to in Meuter et al. 2005
Perceived risk The perception of risk associated with a certain behavior with a
chance of negative consequences, a loss. Risks can be time or
convenience loss as well as financial, psychosocial , status,
security, physical, psychological, etc.
Ellen et al. 1991; Dowling 1986
Complexity Relates to perceived ease of use, that is it considers the
perceived difficulty to use and understand an SST.
Rogers 1995; Eastlick 1996 referred to
in Meuter et al. 2005; Gatignon &
Robertson 1991 referred in Meuter et al.
2005
Compatibility Consistency with the adopter’s lifestyle choices, previous
experiences, needs and values.
Rogers 1995; Eastlick 1996 referred to
in Meuter et al. 2005; Gatignon &
Robertson 1991 referred in Meuter et al.
2005
Trialability Opportunity to try and experiment with the SST. Generally
innovations that are tried on a more regular basis have higher
degrees of adoption.
Rogers 1995; Eastlick 1996 referred to
in Meuter et al. 2005; Gatignon &
Robertson 1991 referred in Meuter et al.
2005
Relative advantage Perception that an innovation is better than another or the
predecessor in performing a defined task.
Rogers 1995; Eastlick 1996 referred to
in Meuter et al. 2005; Gatignon &
Robertson 1991 referred to in Meuter et
al. 2005
22
Inertia Resistance to change and to perform new behaviors. Lack of
motivation to learn because of needed investments in time and
energy.
Gremler 1995 referred to in Meuter et
al. (2005); Olshavsky and Spreng 1996
Previous experience With increased experience with related technologies adoption
rate of a new technology increases.
Mohr & Bitner 1991; Meuter et al. 2005;
Dabholkar 1996
Observability Degree to which SST and its use and results, potential benefits,
are observed by others. Generally an innovation that is more
observable will have higher degree of adoption than the
opposite.
Rogers 1995; Eastlick 1996 referred to
in Meuter et al. 2005; Gatignon &
Robertson 1991 referred to in Meuter et
al. 2005
Situational factors Usage intention Role clarity The customers’ understanding of what is expected (“what to
do”) from him in the service process.
Meuter et al. 2005;
Lee & Allaway 2002; Gelderman et al.
2011
Perceived
crowdedness
Amount of people in the area where self-service technology is
to be performed.
Dabholkar 1996; Machleit et al. 2000;
Gelderman et al. 2011
Trusting
Intentions
Adoption Degree of
information about
the channel
What customers know about the channel. E.g. the extent to
which benefits (relative advantage) of the channel are clearly
communicated.
Dimitriadis & Kyrezis 2011; Liljander et
al. 2006
Trusting beliefs in
the channel
(affective)
“The trustor’s willingness to engage in a risky behaviour or to
interact with a trustee”.
Dimitriadis & Kyrezis 2011, p. 1294.
Theory of Planned
Behavior
Trial, adoption Subjective norm The perceived social pressure that hinders one from taking
action (performing behavior) is defined as subjective norm.
Ajzen & Fishbein 1980; Taylor & Todd
1995; Bhattacherjee 2000; Chen et al.
2009
Perceived behavioral
control
Perceived behavioral control express to which degree a
behavior of interest is perceived easy or hard to perform.
Dimension is similar to “Perceived ease of use”.
Ajzen & Fishbein 1980; Taylor & Todd
1995; Bhattacherjee 2000; Chen et al.
2009
Other Various
Efficient complaint
handling
Efficient complaint handling permanently increases customer
satisfaction.
Tax, Brown, and Chandrashekaran 1998
23
Customer
satisfaction
Primarily predicted by optimism. Satisfaction of use leads to
adoption and loyalty.
Chen et al. 2009
Perceived control Related to the amount of control a customer has over the
service process and outcome.
Bateson & Hui 1987; Dabholkar 1996;
Liljander et al. 2006
Enjoyment People prefer using (playing) machines that gives them
enjoyment.
Langeard et al. (1981) referred to in
Dabholkar (1996)
24
3. METHODOLOGY
The thesis took an inductive approach by using two qualitative interview
techniques. An inductive approach is used for the generation of new theories
(Bryman & Bell 2007). A critical incident technique (CIT) method was used
for answering the first research question: What are sources of satisfaction and
dissatisfaction with currently used SSTs in commercial flight industry? The
intention with using CIT is to deepen the knowledgebase in the field and
possibly find new sources of SST satisfaction and find reasons behind them
(antecedent variables). To answer research related questions a case company
has been used, Scandinavian Airlines, and its check-in options are considered;
mobile-check in, internet check-in and machine or kiosk check-in and over-the
counter check-in, other SSTs will be ignored. The check-in for this particular
airline defines the context of this thesis. The airline, SAS, and the check-in
alternatives are explained in the following sections.
3.1. RELATION TO THEORETICAL FRAMEWORK
Previous studies on SSTs have been predominantly focused at one model at
the time e.g. TR by Liljander et al. (2006), however, some attempts have been
made to combine some of the models, e.g. Chen et al. (2009) that combined
TR, TPB and TAM (see page 18). Nonetheless, no attempts have been made
to check the validity of all major theoretical models on SST adoption and
satisfaction in a single study and industry setting. Thus, this thesis will study
customer satisfaction and adoption of check-in SSTs in commercial airline
setting based on the models presented in theory section; TR, TAM, TPB,
consumer readiness, situational factors, and trusting intentions.
As seen several of the models had overlapping or analogous terms for
variables (e.g. perceived ease of use and perceived behavioral control), which
means that the term “perceived ease of use” will also include perceived
behavioral control, complexity and the term relative advantage will also
include perceived usefulness. Due to time limit issues some variables have
been left out, however, the left out variables have been used in the analysis
part.
From the four proposed variables in the TR model only “optimism” was
included. “Optimism” was left since it had shown greatest impact on customer
25
satisfaction and adoption in previous research (e.g. Parasuraman 2000,
Liljander et al. 2006, Chen et al. 2009) and other variables in TR were left out
due to inconclusive previous research on their respective influence on
adoption and satisfaction. The three main variables from the consumer
readiness model has been included, however, antecedent variables affecting
these have been left out since some of the variables are covered by other
models and due to study limits. However; these antecedent variables are used
to analyze empirical findings. Customer satisfaction is a strong predictor of
SST adoption; however, it has not been included in this thesis since it can be
predicted by other antecedent variables. Perceived control and enjoyment have
not been included as particular questions, but if they have an influence it can
be determined through analysis of the open-ended questions Q4 and Q20.
The thesis’ empirical findings have been based on the CIT method and semi-
structured interviews which are explained in the next section. The complete
set of questions used in interviews are listed in Appendix A and B. Some of
the questions as mentioned are open-ended, e.g. Q20; “What made you chose
that particular channel?”, others are leading questions such as Q17; “How did
you experience the crowds and queues at the airport? Did they affect your use
of self-services?” that are focused on validating the effect of a predefined
variable by directing the interviewees’ attention on a particular issue, in the
case of Q17 the effect of the situational factor perceived crowdedness. A
complete list on these leading questions and their connections to the
theoretical models are listed in table 2. As it can be seen; efficient complaint
handling has been included in the list and the reason is that non-efficient
complaint handling can have such a devastating effect on adoption that it
should not be ignored, thus it will function as a control variable.
Table 2: Interview questions’ relation to theoretical framework.
Theoretical model Variables Variable used? Question
Technology readiness
(TR)
Optimism Yes Q36, Q38
Innovativeness No -
Discomfort No -
Insecurities No -
Technology Acceptance
Model (TAM)
Perceived ease of use Yes Q18
Perceived usefulness Yes Q20, Q22, Q23
Consumer Readiness Motivation Yes Q32
Ability Yes Q15, Q16, Q25
Role clarity Yes Q14, Q25
Antecedent variables to
consumer readiness
Need for (human) interaction No -
Perceived risk No -
Complexity Yes Q18
26
Compatability No -
Trialability No -
Relative advantage Yes Q20, Q22, Q23
Inertia No -
Previous experience No -
Observability No -
Situational Factors Role clarity Yes Q14, Q25
Perceived crowdedness Yes Q17
Trusting Intentions Degree of information about
the channel
Yes Q21, Q29
Trusting beliefs in the channel Yes Q27
Theory of Planned
Behavior
Subjective norm Yes Q26
Perceived behavioral control Yes Q18
Other Efficient complaint handling Yes Q12, Q13
Customer satisfaction No -
Perceived control No -
Enjoyment No -
The open-ended questions will help in producing new information. The
leading questions will help customers to remember certain issues. The issues
are in form of adoption hurdles which will help in understanding “what causes
a customer to adopt one self-service option in favor of another?” and all
variables behind people’s choice of SST channels which in turn helps in
validating which SST adoption models or variables are useful. Optimism and
other variables from the models will also be relevant in explaining satisfying
and dissatisfying incidents in the commercial airline industry. The results will
be presented in form of a list of critical satisfying and dissatisfying incidents
and a set of factors describing the SST channel choice. These factors, or
causes, relation to SST adoption models will be explained in detail in the
analysis section. The logic behind the analysis is presented below in figure 4.
27
Figure 4: Research logic
3.2. CRITICAL INCIDENT TECHNIQUE
Critical incident technique (CIT) is an accepted and a common method used
in service research and has often been used when assessing sources of
satisfaction and dissatisfaction in service encounters (Gremler 2004). The
method is a qualitative interview procedure where respondents are asked to
recall critical incidents and the outcomes of such incidents as perceived effects
TR TPB CR TI SF TAM
Efficient complaint handling
Questionnaire
Empirical findings; factors and
”causes”:
1. Satisfaction/dissatisfaction
2. SST channel choice
Analysis
2
1
3
Validation and
conclusions
4
SS
T A
dopti
on m
odel
s C
ontr
ol
var
iable
Leading
Open
1
2
3
4
Construction of the questionnaire. Mix of open-ended questions to find new variables and
leading questions, derived from previous SSTs adoption models of SSTs as described by
table 2, in order to find the influence of theoretical variables,. Efficient complaint handling is
chosen as control variable. If complaints are handled efficiently then the impact off other
variables is more evident.
Establishment of factors and causes in groups; derived from empirical research to determine
1) Sources of satisfaction and dissatisfaction related to SSTs in the check-in process. 2)
Factors affecting SST channel choice.
Analysis of empirical findings and groupings in accordance to previous research, variables
and models.
Validation of which SST adoption models and variables are relevant in describing channel
choice and sources of satisfaction and dissatisfaction. Conclusions of which factors
determine channel choice and sources of satisfaction and dissatisfaction with check-in STs.
28
(Chell 1998). A critical incident is a human activity that is observable enough
that predictions and interferences can be made, but it needs as well to make a
significant negative or positive contribution to an activity. (Gremler 2004;
Bitner, Booms, and Tetreault 1990; Grove & Fisk 1997). Here an incident that
is not critical in the context of SST check-in is if the incident has not resulted
in any major changes in satisfaction, behaviors towards the use intention of
SSTs or the customer-firm relationship. The critical incident is determined as
the unit of analysis (Gremler 2004).
Strength of using CIT method is that the collected data is from customer’s
perspective and the stories are told in their own words (Edvardsson 1992),
thus this gives access to the most relevant information from the respondents
view (Gremler 2004). Respondents are neither likely to fall in the framework
of what the researchers finds important, but are able to determine the context
from their own perspective (Stauss 1993; Chell 1998). The CIT method also
provides researchers with very concrete information since respondents can
convey detailed information in their story (Stauss & Weinlich 1997),
something that often will be missed in a rigid questionnaire. A CIT study will
neither be restricted to a set of variables or activities (Walker & Truly 1992).
With the case of SSTs in commercial airlines context, frequently low adoption
rates of SSTs have demonstrated that there is a lack of knowledge in the
subject, which calls for research that is able to formulate new theories, which
the CIT method is fully capable of and intended to be used for (Bitner, et al.
1990). The low adoption rates also indicate that there is a further need to get a
thorough understanding of the subject and the currently non-existing research
on self-service channels choice calls for a CIT study that can lay the
groundwork for new theory (Bitner et al. 1990).
The CIT method is also excellent when the topic has been sparingly
documented (Grove & Fisk 1997). Presently only a couple studies have
studied SSTs in airports (Meuter et al. 2000; Liljandet et al. 2006; Gelderman
et al. 2011) and the overall number of literature on the subject of SSTs is still
rather limited and many of the studies have been conducted through
quantitative questionnaires that have been limited to validating a small number
of variables (e.g. Liljander et al. 2006; Gelderman et al. 2011; Chen et al. 2009;
Dimitriadis and Kyrezis 2011). Koelemeijer (1995) states also that CIT method
is effective to study phenomena where all variables are hard to specify prior to
the research. The CIT method also provides with in-depth and accurate record
of events (Grove & Fisk 1997) and the information is also very concrete for
29
managers since it can point out areas of improvement (Stauss 1993). The
method was successfully used previously by Meuter et al. (2000) on a study on
SSTs which indicates that it is appropriate to use for a study on SSTs and
customer satisfaction.
Limitation of a CIT study comes to questions about reliability and validity
(Chell 1998) since there is a risk of misunderstanding or misinterpreting the
respondents’ stories (Edvardsson 1992; Gabbott & Hogg 1996). Other sources
of criticism towards the method are category labeling ambiguity (Weber 1985),
recall bias (Michel 2001), and respondents that are not taking the time to tell
the complete story (critical incident) (Edvardsson & Roos 2001).
The second part of the thesis has been conducted through semi-structured
qualitative interviews (with the same respondents as for CIT) with the
intention to answer the second research question: What causes a customer to
adopt one self-service option in favor of another? Which variables are behind
people’s choice of SST channels and which current behavioral models used in
explaining SST adoption in the present research can explain SST-channel
choice?
The interview process was similar to CIT, but no critical incidents were
collected, but respondents’ answers were subject to analysis. Respondents
were allowed to state several reasons for not using one channel, they were not
asked to rank them only to speak about them, hence the total units of analysis
is larger than number of respondents. However; as with the CIT each
customers answer could only be marked once in respective category.
Categories were developed by using a similar categorization process as with
the CIT part, which is explained under procedure section.
3.3. COMPANY INTRODUCTION: THE SAS GROUP
SAS or Scandinavian Airlines is a commercial airline company in Scandinavia
where the Swedish, Danish and Norwegian government mutually own about
50 % of the shares. SAS flew 27 million passengers in 2010 at approximately
1,008 departures with 230 planes to 127 destinations and more than 30
countries. SAS holds a 30-50 % market share in home markets. The value
proposition is to “through cooperating airlines, the SAS Group offers flexible
and value-for-money air travel with a focus on products and services that meet
30
the needs of business travelers in the Nordic region.” In 2010 the group’s
revenue was 40,7 MSEK (SAS Group 2012).
3.4. SELF-SERVICE CHECK-IN OPTIONS AT SAS
Check-in at SAS is possible through four options, check-in through internet,
mobile check-in, self-service kiosk at the airport, and over the counter. Check-
in through internet can be done 22 hours until 1 hour before departure.
Checking in this way the customer can choose where to sit in the plane, seats
are distributed on a first come first serve basis. EuroBonus points can be
registered when checking in through internet and it is possible to print the
boarding card. However; if the passenger is carrying baggage they must use the
self-service kiosk at the airport to get tags for the baggage.
Mobile check-in is possible if the passenger has added a mobile-number and
an e-mail account during the reservation of the flight. SAS will send an e-mail
or a message to your phone 22 hours before departure and the passenger only
needs to answer “Yes” either via the phone or e-mail to be checked-in. A new
service offered by SAS is that passengers can get the boarding card to their
phone. If the passenger is carrying any baggage, then the passenger needs to
use the self-service kiosk to get tags for the baggage. The new service will
make it possible to simply scan the boarding-card in the phone to get the tags.
Officially stated benefits are: it is simple since the passenger only needs to
answer “Yes”, it is possible to check-in with or without baggage, it is possible
to pick the seat, and it is possible to download a boarding-card.
Kiosk check-in is done through a number of kiosks that are located around
the airport. From these the customer can get stickers to their baggage and
check-in. Check-in is done through placing your credit card in the machine or
by typing the reservation number and following instructions. A newly
introduced service for SAS is that passengers can use “Self Service Baggage
Drop” if they carry maximum 2 pieces of baggage and 20 kg each. Officially
stated benefits of kiosk check-in are that passengers can check-in with or
without baggage, pick the seat, change destination, register EuroBonus-poins,
and print boarding-card (SAS 2012).
31
3.5. SAMPLE CHARACTERISTICS
Data was collected so that recall bias (Michel 2001) was reduced by choosing
respondents that have used at least one of SAS’s self-service check-in options
within the past six months. Two samples were used in this study. The first
sample was made up of students that had studied abroad in Europe recently or
up to a half a year before the study. These people were chosen since they were
more likely to have flown during the past six months and also more likely to
fall in to the targeted company’s customer base since the company mainly
operates in Europe. The respondent selection from this group was based on a
convenience sample meaning that the interviewer already knew the
respondents. The interviews were conducted and recorded through Skype that
is a voice-over internet protocol service. First sample was made up of 5
respondents with a response rate of 55.6 %. Average and median age of
sample 1 was 24 year and a range of 23-25 years, 80 % of sample 1 were male
and 20 % female. The average interview length of sample 1 was 20 minutes.
The interviews for both samples were conducted between 7 and 14 of May
2012.
To reduce the number of respondents that don’t tell the complete story
(Edvardsson & Roos 2001), the second sample was based on random
sampling among respondents waiting at train- or bus-stations at the Stockholm
Central Station since they were more likely to stay an give the questions
adequate time so that detailed answers can be given (provided that the
interview started well-before departure). Choosing the respondents from these
locations also reduced any geographic biases since respondents were expected
to come from different cities and countries. However; the downside is that the
setting is full of distractions, meaning constant interruptions. Another
downside is that the venues are filled with people which could lead to some
respondents not answering with complete honesty in order to avoid looking
bad in front of peers. The respondents in both samples were asked if they
have at least 10 minutes to spare to questions in order to have adequate time
to answer questions, this and all respondents needed to be over 18 years old
were the basis for sample selection.
Sample two consisted originally of 21 respondents with an response rate of
11.67%, but four of the respondents were excluded because of vague, non-
descriptive answers mainly caused by short interview time and because of not
having used any check-in SST. The exclusion left 17 respondents (58.8 %
female and 41.2 % male) in sample two and an average age of 44.3 years (range
32
between 20 and 72 years). Median age for sample two was 38 years and the
average length of the interview was 10.5 minutes. There is a possible research
bias in the selection process of the sample. The data collector (interviewer)
might unconsciously have selected a certain sample characteristics over others,
so the randomness is questionable. Random sampling is more likely to ensure
that “unknown influences” are evenly distributed within the sample (Preece
1994) and it ensures that the sample is representing a larger base of the
customers (respondents) so that assurance is increased (Bouma & Atkinson
1995).
In data analysis samples were merged into one sample (total sample) of
respondents. The total sample consisted of 22 respondents with an average
age of 36.5 years (range between 20 and 72) and consisted of 50 % male and
50 % female respondents. The sample size (number of respondents) in CIT
studies have ranged between 9 and 3,852 with an average number of incidents
having 443 respondents (Gremler 2004), making the sample size of 22
relatively small, but acceptable since a small sample size is expected for this
kind of study since respondents are required to describe critical incidents in
sufficient detail (Johnston 1995).
The interviews lasted in average for about12.6 minutes and they were recorded
with an audio-recorder. The average number of flights during the 6 month
period is 4.23 per respondent (this number is heavily skewed upwards since
one passenger had flown 35 times). Removing the highest and lowest answers
results in the new average number of flights with SAS being 2.85.
3.6. PROCEDURE
The interviewer held no prior industry experience in the airline industry so the
researcher holds few industry specific biases. Nevertheless, the researcher
could hold biases caused by exposure to previous research in self-service
technologies. This is also reflected consciously in the formation of questions in
order to validate the variables (see table 2 and Appendix A), the issue
addresses conformability.
All respondents were told to tell a story (critical incident) about two positive
and two negative experiences with SSTs at airports. Negative incidents are
particularly dissatisfying experiences and positive incidents are particularly
satisfying experiences in line with the previously stated definition of critical
33
incidents. In another question (Q9) respondents were asked to describe how
these experiences affected them and their relationship with the service
providers. This is to take into consideration how the customer-firm
relationship has been affected by the critical incident, which has often been
neglected (Edvardsson & Strandvik 2000). As mentioned, the whole set of
questions are found in the interview guide in Appendix A and B.
All respondents were told that they are completely anonymous in the study.
They were also told that the interview will be recorded and their permission
was asked for prior to the interview. Respondents were also informed that the
recording will only be heard by the interviewer and the interviewer’s
supervisor. All participants were given the opportunity to refuse participation.
Participants were as well encouraged to be frank and never told that there is “a
right answer to the question” according to best practices for qualitative studies
described by Shenton (2004). The independence of the interviewer of the
study was emphasized as well by ensuring that the data is used for a master
thesis at Karlstad University and no direct data from single participants would
be available to the investigated case company, SAS. Participants were also
presented the opportunity to withdraw from the study at any point, which also
occurred at some interviews when travelers needed to catch a bus or a train.
The participant withdrawal also meant that all respondents did not answer all
questions. The number of respondents was adjusted properly to the number
of actual respondents answering to the affected research question. The data is,
however, used to suggest further research and come up with new theory and
not to be used quantitatively; this is up to further research.
Iterative questioning was used, some participants were asked the same
question again in a new form to ensure reliability of data and discover
falsehoods. It was also used if a participant gave vague answers, which
occurred more often in the beginning of the interview when the participant
was not “warmed up”. By using this interview technique participants where
given the opportunity to extend previous answers in case of something new
coming to mind during the interview.
All interviews were recorded and written down. When interviews where
transcribed words such as “hmm” and pauses where not included. All
repetitions of statements were also excluded. It is the interviewer’s or the
researcher’s right to summarize the interviews to the core essentials and leave
out information that is not related to the purpose of the study (Trost 2005;
Kvale 1997).
34
After data collection the stories (critical incidents) were subject to content
analysis (content analytical method) performed by one educated judge. The
content was categorized with respect to stated research questions and previous
classification schemes (Meuter et al. 2000; Liljandet et al. 2006). Due to the
small sample size no data set was used to confirm the initial classification
schemes (holdout sample). Systemization was ensured by following the
definition of critical incident (specificity) and aim of the research (purpose) in
order to exclude some responses.
The interviews were first categorized under existing research categories and
thereafter the interviews where re-read several times in order to find
statements that cannot be categorized in the previously mentioned categories.
New categories were developed. The new categories where thereafter
narrowed down from a larger number of categories and their fit as
subcategories to existing categories were tested. If a respondent could not
describe his or her feeling with using an example from a check-in SST, he or
she was allowed to describe a similar situation with another SST as long as the
implications and cause of satisfaction was similar.
Second part of the study (research question two) was conducted through semi-
structured qualitative interviews. These interviews were made parallel with the
CIT study. The aim was to understand customers’ choice of SST channel by
analyzing their answers. The data collecting procedure was the same as for
CIT as was the sample. The difference lay in how the data was interpreted and
the unit of analysis. Here the unit of analysis was more abstract, “a reason for
using a particular SST or a reason for not using it”.
35
4. EMPIRICAL FINDINGS
4.1. SATISFYING AND DISSATISFACTYING INCIDENTS
A total of 61 usable critical incidents describing satisfying and dissatisfying
critical incidents were collected from the sample, from these 42 described
positive critical incidents and 19 negative critical incidents. The second
research questions were based on stories told by respondents. From the stories
48 patterns or causes were identified that were divided in mutually exclusive
groups.
Critical incidents were grouped in mutually exclusive subcategories which were
grouped in main categories originally developed by Meuter et al. (2000) and
Liljander et al. (2006). The main categories were divided in two: those
incidents that lead to customer satisfaction into one and those incidents that
were dissatisfying into the other.
From the sample containing 22 interviews were used for the research question
concerning satisfying and dissatisfying incidents and 21 interviews were used
for research question relating to SST channel-choice.
4.1.1. SATISFYING INCIDENTS
42 mutually exhaustive critical incidents were found that were related to a
satisfying experience. Following four groups (main categories) were identified
four critical incidents that were satisfying:
1. More efficient service: Improvements that SSTs brought in relation to the
alternative (interpersonal over-the-counter check-in) related to efficiency have
been included in this group. The group made up of 64.29 % (N=27) of total
satisfying incidents, thus being the leading cause for satisfying critical
incidents. The group is compared to how optimistic towards the development
of self-services the respondents found themselves to be. Respondents were
asked “In general, how do you experience the development of self-services in
the society?” People indicating a positive attitude towards the development are
considered optimistic by the definition of the term. 17 of the 22 respondents
were optimistic, three were indifferent and gave answers like “I accept the
technology and think it is user-friendly, but I question if it is the path we
should follow”, and two had a negative view on the development and
36
providing answers like “I think it is impersonal and boring”. The “more
efficient service” group can be divided into four subcategories:
1A. Saved time: 35.71 % (N=15) of all satisfying critical incidents were
attributed to SSTs ability to save time primarily by reducing queues and
waiting time and achieving the desired outcome fast. This subcategory was the
primary and largest cause of satisfying events. Statements included:
“You don’t need to turn up at the airport five hours before departure.”
“You queue less and it is quicker!”
“I feel that the self-service technologies saves me time, I don’t need leave bed early and I avoid the queues so I
don’t need to think ‘damn I must stand in line for three hours tomorrow… [ ] … it saves my time and
energy…. [ ] … I have never waited to use a machine, I don’t even know if you have to wait!’”
1B. Easy to use: 23.81 % (N=10) of all satisfying critical incidents indicated that
the SSTs were easy to use or easier than use than when checking in manually,
thus feeling satisfied. When the SSTs use is straight, the process is clear and
instructions are understandable then respondents found the check-in
satisfactory and simple. When asked individually only two of the 22
respondents felt the design to be difficult or hard to use, implying good and
user-friendly design. Statements included:
“I inserted my card and I got my ticket. It was very smooth. I read all the information and followed it. It was
really smooth and the design was very good.”
“The greatest advantage, when you don’t have any baggage when you are going to check-in, then you only need
to click three times on the internet and then you only need to run to the safety control.”
1C. Avoid paperwork: One respondent was delighted of not having to deal with
paperwork, thus making up 2.38 % (N=1) of the sample.
“It was better than any airline I have flown with. Usually I get loads of paperwork. I was very happy with
it.”
37
1D. Saved money: One respondent (N=1, 2.38 %) was delighted by the fact that
she could get bonus points by using SSTs that could be used for future private
travel, therefore saving her money. This category included incident(s) that
saves the customer money.
“I receive bonus on my travels so I can travel privately”
2. Being in control: 28.57 % (N=12) of the satisfactory critical incidents could be
linked to this group created by Liljander et al. (2006). The group is related to
optimism dimension in the TR model (Liljander et al. 2006) and relates to the
customer’s sense of being in control of the provided service. The control
dimension here has been divided into three subcategories:
2A. Able to pick my seat: 16.67 % (N=7) of the sample was pleased to have the
opportunity to select their own seat.
“… it is wonderful to be able to pick your seat and do it all by yourself. It is important for me to pick a seat
since I always want to sit next to the aisle and stretch my legs.”
“You can pick your seat, I want room for my legs so it is important to be early, you don’t have the big
selection if you stand at the airport two hours before take-off.”
2B. Do it by myself: 4.76 % (N=2) of the sample were pleased to be able to
complete and use the SST to check-in by themselves.
“The positive thing with SSTs is that there are no queues, it is fast and you can do it all by yourself…”
2C. When I want: 7.14 % (N=3) of the sample were glad that they had the
opportunity to perform the check-in at any time during the day.
“You can use it any time you want. Once I travelled during the night and I could get the ticket by myself from
the machine”
38
3. Enjoyment: Two (N=2) respondents (4.76 %) indicated it was fun to use or
play with the check-in SSTs.
“It is fun using the machine, it [IT] is my job as well.”
4. Did its job: One respondent (N=1, 2.38 %) was pleased by the fact that the
machine did what is supposed to do when needed.
“It was nice; you just use the machine and get a ticket.”
4.1.2. DISSATISFYING INCIDENTS
An important notification is that the customers that reported dissatisfying
events were not per se dissatisfied with the service, service provider or flight
experience. The events only represented isolated occurrences in time that
affected them at that moment negatively, in fact when the passengers were
asked “Does SAS’ SSTs give you a better total experience with the flight?”
only one of the 22 respondents felt that the introduction of SSTs was negative
as one respondents said “To be honest, I would not chose a machine. I prefer
and think it is always better to interact with a human”. 18 respondents agreed
on it being positive leaving comments such as “I think it is really good that I
don’t need to talk to anybody” and “the self-services at SAS improves my
travel experience since if it starts simple the rest of the journey will feel simple
as well”. Three respondents felt indifferent, saying “I don’t care about it so
much; sometimes it is better to speak to a person”. This same observation
holds naturally also true for the previously mentioned satisfying incidents.
19 mutually exhaustive dissatisfying critical incidents were grouped in four
categories:
5. Technology failure: Incidents caused by failing self-service technology (or not
working as intended) was included in this category consisting of 31.58 %
(N=6) of the total number of dissatisfying incidents. Failures included people
who because of a malfunctioning machine did not receive any tag for the
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baggage and boarding card. Incidents where machines were simply not
working properly were included in this category as well. The following quote is
by a woman who strongly dislikes the SSTs:
“It malfunctions a lot; you don’t get your check-in number and stuff, small details that don’t work. The
sticker [for the baggage] does not appear. There is a person present who helps others and I often have to go to
him and ask for help.”
6. Process failure: Two respondents (N=2; 10.53 %) experienced a process
failure. Process failures are those incidents when technology functioned as
intended but some kind of failure occurred after the customer-technology-
interface session (Meuter et al. 2000). Failures included an instance were the
respondent had to re-do the booking since his phone stopped working and
one case where the respondent was unaware that he had the boarding card in
his phone and was notified that he already had “printed” the boarding card.
“Yesterday I checked in with my mobile. This thing with the boarding card was confusing, since the boarding
card was send to my phone and it was not clear to me that this had happened. When I arrived to the airport
and I tried to print out the sticker for my baggage I got the message that I already had printed my boarding
card, but I hadn’t, it was on my phone.”
7. Poor design: The largest portion of dissatisfying events, 52.63 % (N=10), were
caused by poor design. Poor design implies that technology is functioning as
intended, but it is performing in an unsatisfactory manner causing confusion
and problems (Meuter et al. 2000). These types of problems were not faced by
all customers even though they had been exposed to and used the same
machine. Design related problems have been split in two subcategories:
7A. Technology design problem: When respondents felt that the machines were
hard and complicated to use or in any other manner causing an unsatisfactory
customer experience without actual failure, but functioning as intended, then
there was a problem related to the design of the self-service technology. 26.32
% (N=5) of the incidents were attributed to this category. Customers who
needed to ask for help and situations where no personnel were available to
instruct customers when needed were included in this subcategory as well.
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These numbers should once again be compared to what customers actually felt
about the machine’s design; when asked individually only two of the 22
respondents felt the design to be difficult or hard to use, implying that 3 of the
critical incidents were caused by underestimations of one’s ability.
“… when we arrived during the morning. First time we were going to check-in at Arlanda we felt clueless and
thought ‘what is this? There is not a single person in here [to ask for help]?!’”
7B. Service design problem: In this category unsatisfactory incidents that were
caused of other reasons than the technology-customer interface, 26.32%
(N=5). It differs from the process design since there is no actual failure, but
the technology has worked as intended but some other service aspect to the
design of the overall check-in service has made the execution of the service
more complicated than necessary or wanted. Here two incidents came from
customers who checked in with the mobile, but later found themselves
disappointed that they could not check-in via the mobile if they had more than
light baggage and were forced to repeat the process with the machines
(kiosks). Other found service design problems are described in the quotes
below.
“There is confusion with the luggage; am I going to print the ticket out by myself and put it on myself or am I
going to the luggage drop and they do it for me? Then it feels it makes the check-in a bit meaningless so I
can’t understand why I am queuing for this and not going to the luggage drop directly. I always think if I can
do this myself, why don’t they do this for me?”
“Last time I arrived really late, 13 minutes prior to departure. Then I read [in the machine] ‘too late to print
please contact personnel’ and now I was even more in a hurry thinking ‘stop wasting my time!’ I feel you
should always be able to print. This time I ended up further more in an emergency because I had to find
service personnel.”
8: Customer driven failure: Only one incident (N=1, 5.26 %) could be placed in
this category which includes those incidents where the customer takes
responsibility for the failure that occurred when using SST for check-in.
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“One time I had more baggage than I was allowed to have when I checked-in, then I had to go and check-in
via the counter and tell them that I had more baggage.”
4.2. CHECK-IN ALTERNATIVES
Respondents were asked to tell stories of situations where they decided to use
a particular SST-channel. The questions were answered by 21 of 26
respondents of which five where discarded because of vague, non-descriptive
answers and by the fact they did not use SSTs. The respondents’ answers
(N=48) to why they choose to use or not use a particular SST channel could
be categorized in 13 groups that were inspired by categorization schemes by
Meuter et al. (2000) and Liljander et al. (2006). The groups were the following:
1. Low perceived difference between self-service channels: When users are unable to
differentiate or perceive any differences in their use or benefits of two
alternatives. 6.25 % (N=3) of the sample was made up of this group.
“Checking in through internet, it is for me the same as checking in through a machine at the airport. I don’t
perceive any big difference, I think some people use the internet to be sure, but me, I know the system.”
2. Perceived channel efficiency: The more efficiently an SST channel could complete
the task of checking in the more likely it was to be used. This group made up
18.75 % (N=9) and is split in two subgroups which are both affected by the
antecedent variable relative advantage:
2A. Perceived simplicity: Category includes instances where one self-service
channel is perceived to be easier to use than any alternative for completing the
desired task. Subgroup made up 6.25 % (N=3) from the total sample of
answers.
“I choose the channel that is simplest to use.”
“I assume you could do it [check-in] online. That was the only opportunity I thought I had, but the phone
made it easier … [ ] … I was going to do that [machine check-in] originally, but I had the text message and
went straight to the baggage and didn’t have to queue either.”
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2B. Perceived quickness and chance of avoiding queues: Group includes incidences
where the choice of channel is based on one self-service channel being
perceived to be able to achieve the desired performance faster than
alternatives. This group consisted also of answers related to the channels
ability to avoid queues. Respondents that faced a queue were more likely to
switch from one self-service to another so that queues could be avoided. If
queues would not exist the task would have been perceived to be faster than
using the alternative SST. The subgroup made up 12.50 % (N=6) of the total
sample. Demonstrative quotes related to this category are found below.
“The advantage of mobile [check-in] is that it is really quick, you get the ticket and everything.”
“If I had traveled seven or eight a Monday morning, then I probably would have checked in the night before
[through the internet] to avoid the queues.”
“I use my cellphone when it is crowded.”
3. Awareness and channel knowledge: This group consisted of answers such as “…
I didn’t know you could check-in through a text message”, that is customers
who lacked information about the channel, thus also awareness, were not
using the channel simply because they did not know about its existence and
other answers related to not knowing enough to be able (or confident) to use
the channel. The group stood for 12.50 % (N=6) of total units of analysis.
Demonstrative quotes are found below.
“I would have checked in through internet on other airports than Arlanda. The reason is I don’t know the
other airports. I don’t know where the SAS machines are located and maybe I can’t get internet on my phone.
So it is safer to use internet check-in before you go there.”
“I would have used it if I had known about it … [ ] … I didn’t know that the machines existed, I only
thought trains and buses had those”
4. Lack of trust: This group, used as well by Liljander et al. (2006), includes
8.33% (N=4) of incidents were the respondent felt unsure that the transfer
would be completed successfully. The members of this group felt a risk with
43
using one particular because of the danger of travel documents getting
destroyed, lost or stolen.
“I didn’t [check in through the internet], but my friend did it. I would use it if I had somebody next to me
that knew what they were doing… [ ] … There is an uncertainty, ‘am I doing the right thing?’ especially
when you are spending a lot of money, you want to know that you are doing the right thing, you don’t want to
make an error.”
“I can use the cellphone, but the reason I don’t use it is that I believe in the “the ticket”, paper. Maybe
somebody steals my mobile or something else happens, but I still have it on paper.”
“[Downsides with mobile] is not having enough batteries since you have all your information in it, I like
carrying paper in my hand”
5. Social pressure: This group consisted of answers (2.08 %, N=1) that relate the
use of one channel as an outcome of social pressure, peers influencing a
respondent’s choice to use any particular channel.
“I wanted to check-in through the counter, but the people with me wanted to check-in through a machine.”
6. Service design: This fairly large group 10.42 % (N=5) consisted of enlightened
passengers that knew that they could not use a particular channel because the
service design would not be optimal or allowed it. Service design relates to the
process flow of the service. Passengers with much baggage would for instance
not use the mobile to check-in since they knew that they would still need to
get to the machines (kiosks) to get a tag for the baggage. Illustrative quotes are
presented below.
“I had luggage so I didn’t do online check-in, I checked in at Arlanda with a machine.”
“… if I would have used the phone I would still needed to go the machine to get my sticker, then it is as good
to skip the mobile since I in any case have to go to the machine”.
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7. Technical design: Passengers that preferred one SST channel in favor another
because of some design features such as screen size are included in this group.
One instance was found (N=1) making 2.08 % of the total sample.
“I prefer to do it on internet, to have a big screen, pick a seat and finish in just a couple of seconds”.
8. Accessibility: If passengers were unable to easily access the self-service
channel they were more likely not to use it. This was the case for 16.67 %
(N=8) of instances. The reasons for not choosing one particular channel were
for instance no access to internet through the computer or mobile so online-
check in could not be performed, not owning a computer or a printer so the
ticket could not be printed, making online check-in a less attractive option.
Other passengers would not have any mobile operator abroad or needed to
pay expensive charges to use the mobile. Illustrative quotes are listed below.
“When I can’t reach my network with my mail I use the mobile [to check-in]”.
“I don’t have any internet flat-rate on my cellphone so I haven’t checked in there…”
“While I am over here I use the internet to do it [check-in], I cannot use my phone much because of data
charges… [ ] … I don’t have a printer so it makes my life difficult.”
9. Habit: Some passengers simply used a channel that they were used to using,
thus using it by habit. Four passengers, 8.33 % (N=4), stated this being the
reason to their choice of self-service channel.
“There is actually no reason [I check in through the internet], I have always had access to a computer.”
10. Being in control: This group previously used by Liljander et al. (2006) and
Dabholkar (1996), includes the passengers that stated they chose one SST
channel in favor of another because it allows for more control, therefore
affected by perceived relative advantage between channels. Internet for
instance allows passengers to pick a seat earlier by doing it at home. The group
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includes matters affecting flexibility of when to perform the service and where
to perform the service and made up 8.33 % (N=4) of the total sample.
“It is simple, you have the phone with you and you can check-in no matter what you do….”
“It is important to be early; you don’t have the big selection if you stand at the airport two hours before take-
off.”
“I always pick a seat as soon as I get the opportunity.”
11. Lifestyle: Passengers (2.08 %, N=1) that were pleased that it worked and
experienced no need for getting a better service were placed in this group. The
group differs from habit group since this group has an “I don’t care” (more
negative) attitude towards SSTs. Illustrative quotes are given below.
“I have not tried internet check-in since it has worked fine so far and I have no need for enhanced efficiency…
[ ] … I’m very critical to that we reach new levels of availability and speed, etc. only because technology has
made a breakthrough… [ ]… I’m questioning if this is the right path to follow.”
12. Inconvenience: This group has previously been used by Liljander et al. (2006)
to explain why some respondents chose not to use SST. The group consists of
4.17 % (N=2) of answers relating to the time it takes to learn to use an SST
channel and the perceived complexity (antecedent consumer readiness
variable) of the task. Answers relating to needing to ask for help to use an SST
were included in this group as well.
“It feels like another step to learn to use the internet [check-in] and then yet another with the mobile [check-
in]”.
“I would like to have someone standing next to me when trying such things.”
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5. ANALYSIS
5.1. SOURCES OF SATISFACTION AND DISSATISFACTION
The findings from the CIT study related to causes for satisfaction and
dissatisfaction closely resembles the results and groups developed by Meuter et
al. (2000) in their study of general causes of satisfaction and dissatisfaction for
any at that moment available SST. In contrast to Meuter et al. (2000) initial
findings this study was able to identify four, instead of three, groups of factors
leading to satisfactory experiences. Out of the four groups two were new to
Meuter et al.’s (2000) study; “Enjoyment” and “Being in control”, although
being in control is a group used by Liljander et al. (2006) and Dabholkar
(1996), but was there used as a factor used to explain why passenger’s want to
use SSTs, which is closely linked to satisfaction since loyalty (continued use) is
related to satisfaction.
As mentioned “Enjoyment” (N=2) category was not included in the previous
study. There could be many reasons behind it and one potential reason is that
the SSTs back in the days, when the first study was done, might have been dull
and hard to use. The machines have in 12 years evolved and become more
user-friendly and including more colors etc., thus resulting in a more enjoyable
experience for some customers. From the sample only two of the 22
respondents felt that the machines were hard to understand and use implying a
sound and user-friendly design which gives the argument; that a well-designed
machine can result in satisfaction, some foundation. The discovery of this
group validates findings by Langeard et al. (1981) referred to in Dabholkar
(1996); that people simply can enjoy using the machines.
“Being in control” was partially mentioned in the previous study as “when I
want” and “where I want” in “better than alternative” category, but it was
never acknowledged as an individual main category. The group also contains
subcategories “do it by myself” and “able to pick my seat”. Here no incidents
were found under the subcategory “where I want” and the reason would be
that “where” gives no satisfaction to the use (if not being able to avoid queues
if checking in at home, but such an explanation were not given). “Where I
want” could also be missing because of the small size of the sample (N=22),
interviewing more passengers could possibly have produced some incidents
describing “where” as an important contributor to their satisfaction.
47
“Do it by myself” was a subcategory not included in the previous study and
consisted of people enjoying to independently perform the task by themselves.
The reason behind it was not clear, but speculatively it could have been in a
worst case scenario be caused by previous communication failures where a
passenger is asking for a seat close to the window, but the service personnel
don’t hear this request and assigns a seat closest to the aisle. In other words it
could have been caused by lack of trust in the service personnel, which could
be a serious matter. Meuter et al. (2000) had a subgroup in the satisfying
incidents category called “avoid service personnel” under main group “better
than the alternative”, this subgroup could partially be reflected in the “do it by
myself category”; however, no evidence for such a causality was made in this
study. For “avoid service personnel” group no incidents were recorded, which
for SAS is positive since customer facing employees seem to do (or have done)
their job in a satisfying (or at least non-dissatisfying) manner. If the study
would have been done on the customers from several companies in the flight-
industry, there would (most likely) be a higher number of incidents that would
have contained customers wanting to avoid the personnel.
Surprisingly, no critical incidents linked to Meuter et al.’s (2000) group “solved
an intensified need”, could be found even if the group was the largest in that
particular study. An intensified need is defined as “situations in which external
environmental factors add a sense of urgency to the transaction” (Meuter et al.
2000, p. 55). The lack of critical incident in this group can be attributed to the
use of SST and what kind of situations could cause an intensified need. One
clear example was found among the dissatisfying events in the “service design
problem” section that has the characteristics of an intensified need. The
problem is quoted below:
“Last time I arrived really late, 13 minutes prior to departure. Then I read [in the machine] ‘too late to print
please contact personnel’ and now I was even more in a hurry thinking ‘stop wasting my time!’ I feel you
should always be able to print. This time I ended up further more in an emergency because I had to find
service personnel.”
The external environmental condition is that the person involved arrived late
and the need is to quickly be able to check-in (transaction) and run to the
safety check without having to stand in line in order to avoid missing the
flight. Having access to SST would have solved the intensified need, but in this
48
case the service was designed somewhat foolishly (at least according to the
passenger) so the need could not be solved through the SST. The need had to
be solved through interpersonal contact at one of the counters. Had the SST
been able to solve the problem then it could have caused a very satisfying
event. With this in mind the reason for not finding critical incidents in this
category is that the service design has been deliberately (or unconsciously)
designed not to solve these problems, and probably also because of low
number of respondents.
The second group was “more efficient service” which was the largest cause of
satisfaction. In the previous study this group was named “better than the
alternative”, but some minor changes have been done such as excluding
“where I want” and “when I want” subcategories that were placed in the new
group “being in control”.
“More efficient service” had three subcategories; saved time, easy to use, and
avoid paperwork. Saving time by avoiding queues and being able to check-in
quickly was the major cause of all satisfactory events followed by it being easy
to check-in through a self-service technology. Flight-travelling customers
simply value being able to go through the check-in process without any
problems and quickly. “Avoid paperwork” was a new category that could have
been included in “ease to use” since not having to deal with paper can be
experienced as a simplification and a relief by some, but a horror for others
since they fear having the ticket electronically (more about this in the
discussion part of the second research question).
Only one incident were found related to “saved money”, the satisfaction was
attributed to the fact that the passengers’ use of SSTs entitles the customer to
air-miles that can be used for future travel. That particular customer traveled
several times per month with SAS through business trips and therefore was
able to collect enough points to travel for free privately. Explanation to the
low number of incidents is that the average customer did not feel any
monetary saving benefits from the bonus program since he or she traveled so
seldom. Another explanation to the low number of incidents in this category
that could be used is based on research by Cunningham (2009). The author
divided self-service technologies into different typologies and one of the
findings were that consumer distinguishes between the service-experience
related to reserving the ticket from the actual flight. Most customers have
already bought the ticket maybe days or even months prior to the SST
encounter so they might not feel that the SST saves them any money, and also
49
the money they might have saved by using an SST instead of checking in at the
counter is relatively small in comparison with the flight ticket.
“Did its job” was a large category (21%) in the initial study, here only one
incident was recorded that could be placed in this category. The “did its job”
included those respondents that were happy or somewhat surprised it worked.
In this study the respondent was a visitor from Turkey that had few
experiences with these machines. This kind of sensations are as discussed by
Meuter et al. (2000) occurrences that are felt when coming contact to new
technology. Local residents in Sweden (where the study was conducted, and
the vast majority of respondents included in this study) has grown to expect
that it works, because they have been in contact with similar technology at
train stations and bus stations which are far more often used than check-in
machines at the airport. According to the model on satisfaction, explained
earlier in the theoretical framework section (Oliver 1980, Oliver 1981),
satisfaction is a confirmation and disconfirmation paradigm where prior
expectations are determining satisfaction. Those local passengers used to using
similar machines have grown to expect that they work, consequently setting
the bar higher for satisfaction and therefore unlikely to feel delight by that fact.
The expectation-disconfirmation paradigm should also have an impact on this
particular study since more delightful experiences are prone to occur when the
technology that is introduced is new and customers have not created any big
expectations yet, thus producing more critical incidents close to product
introduction. In this case self-service technologies in the flight industry have
been available for over a decade; however, they have had low adoption rates
until recently. Thus, this study was more likely to get more detailed accounts
from new users from other countries or recent adopters.
For the dissatisfactory evens no new sources of dissatisfaction were found,
although all groups will be discussed as well. The largest portion of
dissatisfying events were found under “poor design” equally distributed under
subgroup “service design problems” (N=5) and “technology design problem”
(N=5). The main cause for dissatisfaction in the former group was caused by
unawareness of how things worked, thus having a weak role clarity. New,
inexperienced customers thought they could easily check-in with their mobile
phone, only to soon discover they still need to queue (if any) at the self-service
machines to get their tag for the baggage. The weak role clarity is caused by
lack of information about the channels.
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A relatively high number of “technology design problem” (N=5) incidents
were found. All incidents that were related to the machines being complicated
to use and expressed a need for at the site guidance were included in this
group. When including the fact that only two out of the 22 respondents
actually felt the machines to be hard to use. Since the incidents are collected
from the same period (past 6 months) and for SAS’ machines, they are likely
to be the same machines used so differences is not due to the customers
having used different machines. There are possibly two causes for this; the
first is that the customers perceived the machine hard to use at the beginning,
but after trial and guidance from any nearby person they learned to use it and
no longer felt it to be complicated. The other explanation is that the
passengers started to doubt their ability to use the machine at the sight of it if
they never encountered or used such a machine before. As Ellen et al. (1991)
mentions; the feeling of low self-efficacy occurs even for the relatively
simplest of tasks.
Only one instance when a customer felt dissatisfied with the SST encounter
where the customer took full responsibility. This particular customer had
reported too few bags in the machine. Even if the customer took
responsibility for it in this case it should not always be the case. Recently SAS
has also introduced the option for baggage self-check in. This option is very
close to the machine’s and certainly will reduce the baggage drop queues. The
development implies that SAS might be planning to skip the baggage drop
section of the service. A personal experience I (writer) had was when a friend
with me checked-in the baggage. The friend only marked one large bag in the
machine, but actually had two. The definition of what comprises one bag is
subjective. It is easy to determine if the suitcase is of standardized size, but if
the passenger uses a “hockey-bag” and a similar bag and ties them together it
is much harder to define if it is one or two bags especially if the person in
question has not put them on a scale and weighted them. The machines
cannot (presently) make these distinctions so it is up to the consumer to insert
the right number of bags. This can be used as an argument for why personnel
that can make these distinctions should be kept. However; the situation could
also be avoided by providing clearer instructions and definitions of baggage
sizes on the machines and the possibility to weight them just next to the
machines.
51
5.2. SELF-SERVICE CHANNEL USE
12 categories behind the choice of channel selection were identified.
The first group (6.25 %) was made up of answers related to the fact that
customers did not perceive any differences between the channels. This group
should not come as a surprise since if considering the example of internet
check-in compared to automatic check-in. One of the respondents did not
“feel like” using internet check-in since he was flying at an hour when the
presence of queues is unlikely. If he also lacked a need to have any particular
seat (being control) he would not likely to perceive any differences between
the options. This group is characterized by people who can’t find any extrinsic
motivation (Meuter et al. 2005) in other options and if there are any they are
relatively small, thus the antecedent variable “relative advantage” (Ellen et al.
1991) from the consumer readiness model between channels plays a major
influence when choosing SST channels.
The second group was related to efficiency of channels and consisted of
subgroups “perceived simplicity” and “perceived quickness and chance of
avoiding queues”. Both of the subgroups were found to be a major drivers for
satisfaction and both should also be influenced by the antecedent variable
“relative advantage” since both are providing the user with a benefit which
magnitude varies depending on the passenger’s needs. Since “saving time” and
“making the process simpler” both are external benefits then the choice is also
influenced by extrinsic motivation (Meuter et al. 2005) which is related to
perceived usefulness in TAM model.
“Perceived simplicity” is influenced by perceived ease of use, variable found in
the TAM model (Davis 1989; Chen et al. 2009; Taylor and Todd 1995) and its
equivalents perceived behavioral control in the TPB model (Ajzen & Fishbein
1980; Taylor & Todd 1995; Bhattacherjee 2000; Chen et al. 2009) and ability in
the consumer readiness model (Meuter et al. 2005). If one alternative is
perceived easier to use then the passenger is more likely to use it, as illustrated
in the demonstrative quote below.
“I assume you could do it [check-in] online. That was the only opportunity I thought I had, but the phone
made it easier … [ ] … I was going to do that [machine check-in] originally, but I had the text message and
went straight to the baggage and didn’t have to queue either.”
52
The fact that checking in through the phone was easier than using the machine
and having to queue influenced this passenger’s choice to use mobile check-in
channel. Perceived ease of use has also as mentioned in theory section a
positive relationship with perceived usefulness, the easier something is to use
the more useful its use is (Chen et al. 2009; Wang et al. 2008).
The second subgroup was “perceived quickness and chance of avoiding
queues”. Few customers would agree that standing in a queue at an airport is a
pleasant experience, thus most people want to avoid them. Some channels are
built to avoid queues better than others. For instance with internet the
passenger don’t have to queue at all, the same goes for mobile provided that
the people are not travelling with heavy baggage. This is as mentioned a
relative advantage of the channel. The perceived crowdedness (Machleit et al.
2000) can be seen to have situational influence on the channel choice as well
as seen by Gelderman et al. (2011). When stacks of people form in front of the
machines (even if most people said that longer queues did not occur at these
machines), as in the quote above, the context of the use changes. Before the
passenger might have intended to use the machine since it is he perceived it
easiest to use, but due to the formation of queues the relative advantage shifts
in favor of mobile check-in that allow the passenger the opportunity to avoid
the queues.
The third and third largest group was the “awareness and channel knowledge”
group. Awareness is a part of the well-known six step adoption model (Rogers
1995 referred to in Meuter et al. 2005), and it is essential to have awareness
before trial can occur. Awareness influenced by the “degree of information
about the channel” antecedent variable used in the trusting intentions theory
(Dimitriadis & Kyrezis 2011), the more the customers know about the channel
the more likely they will be to use it. Some customers had heard about mobile
check-in, but actually had no knowledge on how it worked so they chose not
to use it. Others on the other hand had zero knowledge so the chance that
they pick up a phone and send a text message to check-in is close to zero. The
awareness group is also affected by observability (Rogers 1995; Eastlick 1996
referred to in Meuter et al. 2005; Gatignon & Robertson 1991 referred to in
Meuter et al. 2005), being able to observe the machine increases its usage.
Some alternatives such as internet-check-in and internet check-in is harder to
observe than the machine (kiosk) check-in, thus should have been expected to
have lower degree of “information about the channel”.
53
The fourth group issues with trusting one particular channel. Perceived risk
(Ellen et al. 1991) as used as an antecedent variable in the consumer readiness
model has a large impact on this group. The risk as mentioned earlier is related
to the insecurity of the medium, people prefer to have the boarding card on
paper (as illustrated in the quote below) since they feel that the mobile phone
can run out of batteries or get stolen since it is quite valuable in comparison to
paper.
“I can use the cellphone, but the reason I don’t use it is that I believe in the “the ticket”, paper. Maybe
somebody steals my mobile or something else happens, but I still have it on paper.”
This group’s explanations are closely related to trusting beliefs in the channel
that is as well connected to perceived risk used by Dimitriadis and Kyrezis
(2011) that investigated online banking channels. If customers are not willing
to engage in the risky behavior as using the mobile as boarding card they will
simply use another channel. Some customers stated that they are willing to
engage in this behavior when travelling by bus or train, but not when flying.
Somehow they perceive the risk of engaging in this behavior to be higher than
for the other modes of transportation. The cause for the increasing risk lies in
the fact that losing your flight ticket and not be allowed to board the plane,
which is a great economical loss since a normal flight ticket costs much more
than a bus or train ticket, and this risk is something some passengers refuse to
face.
The fifth group, “social pressure”, was small (N=1), but nevertheless
important. It states that peer pressure have an impact on the choice of
channel, thus validating subjective norm (Ajzen & Fishbein 1980; Taylor &
Todd 1995; Bhattacherjee 2000; Chen et al. 2009) from TPB as a candidate to
explaining channel adoption. This factor has been ignored in consumer
readiness model and TAM, but here it is demonstrated to have minor
influence on the choice of channel decision. The factor is also situational and
might not affect long-term adoption, since if the closest peers (friends) are not
present when the channel choice is made then the passenger is likely to
convert to his or her own choice.
The sixth group (10.42 %) was the service design. Service design was an
important source for dissatisfying events. The consequence of it bringing
54
dissatisfying events is that people chose to avoid the channels where the
service design does not fit their use as quoted below.
“… if I would have used the phone I would still needed to go the machine to get my sticker, then it is as good
to skip the mobile since I in any case have to go to the machine”.
This variable is heavily influenced by role clarity (Meuter et al. 2005) from
consumer readiness model. It is clear for some customers that the service is
designed in a certain way that makes it unnecessary to choose the particular
channel. In a way this category is also influenced by degree of channel
information (Dimitriadis & Kyrezis 2011; Liljander et al. 2006) and relative
advantage (Eastlick 1996; Gatignon & Robertson 1991 both referred to in
Meuter et al. 2005) that decreases with some particular service designs that
don’t meet the customer’s purpose. Relative advantage is closely related to
perceived usefulness (Davis 1989; Chen et al. 2009; Taylor & Todd 1995) since
logically the usefulness should decrease with decreased relative advantage.
Seventh group was the one of technical design (2.08 %). Only one customer
based the choice on design. The reason could be that all channel options in
this case were perceived easy to use (Davis 1989; Chen et al. 2009; Taylor &
Todd 1995) meaning that the relative advantage between the channels should
be close in this aspect. That the design was user friendly for all channels were
confirmed by the fact that only two of the 22 respondents complained on the
machines being difficult to use and understand. The screen size is something
that cannot be transferred to a mobile where the screen is generally has very
small screens, which was the reason for this respondent using one option.
Group eight was accessibility. Accessibility is closely related to perceived ease
of use or behavioral control since ease of use should vastly increase if the
passenger lacks direct access to a printer if he wants to check-in online. The
passenger could solve the problem by using the printer at work, but this might
not be as convenient or easy as doing it at home.
Group nine (N=4) consisted of the habitual passengers. These passengers
based the choice of channel on habit. These people could not explain why
they chose one channel over another other than they just did because they
were used to it. They got used to using one channel and stick to it. The
reasons behind it can be many such as no perceived differences between
55
channels (because of small relative advantages) and no need for further
efficiency, but one should be careful in making such conclusions.
Group ten consisted of the people basing their choice of channel on increased
possibilities to be more in control (“being in control”). This group is directly
related to optimism in TR model by definition; “belief in increased control,
flexibility, and efficiency in life due to technology” (Chen et al. 2009, p. 1251).
The group has also previously been used by Liljander et al. (2006) when they
investigated how TR variables affect the choice of using an SST between
interpersonal check-in. This group as “perceived channel efficiency” is
offering an extrinsic rewards (seat selection) thus being affected by extrinsic
motivation (Meuter et al. 2005) and relative advantage (relative channel
performance) (Eastlick 1996; Gatignon & Robertson 1991 both referred to in
Meuter et al. 2005).
11th group (N=1), “lifestyle”, had only one respondent. The respondent
explained:
“I have not tried internet check-in since it has worked fine so far and I have no need for enhanced efficiency…
[ ] … I’m very critical to that we reach new levels of availability and speed, etc. only because technology has
made a breakthrough… [ ]… I’m questioning if this is the right path to follow.”
The respondent rejects the lifestyle of having to strive towards increased
efficiency, thus compatability (Eastlick 1996; Gatignon & Robertson 1991
both referred to in Meuter et al. 2005) is an explanatory variable behind the
choice of channel for some. Compatability is mediated through extrinsic
motivation in the consumer readiness model (see figure 1), therefore
motivation can be counted as an explanatory variable.
The final group 12 consisted of answers related to inconvenience (N=2). This
category is the negative (mirror image) of perceived simplicity and is mediated
by ability, answers related to the feeling low self-efficacy or self-esteem to
perform the task is the reason behind not using or trying to use the channel
are included in this category. The underestimated ability (Meuter et al. 2005)
led to these respondents needing guidance in order to try a new self-service
channel, thus ability from consumer readiness model (Meuter et al. 2005) is a
predictor of channel choice. Perceived ease of use is also a good predictor as
56
well as need for (human) interaction (Meuter et al. 2005) since these people
wanted someone to guide them on how to use the machine.
57
6. STUDY LIMITATIONS, STRENGTHS AND
DIRECTIONS FOR FURTHER RESARCH
The strengts of this study have been the clear focus on a single industry, thus
the study has a high inner validity. When considering outer validity on how the
groups in the “channel choices groups” would affect other SSTs in other
industries such as ATMs and internet banking it is harder to draw any
conclusions. Although accessibility would clearly be a relevant factor
explaining channel-choice for the person lacking internet connection or having
a lifestyle without internet (even if these people are presently few in the
western world). If considering the transportation industry that includes bus
and train-travel then the findings should prove to be highly relevant even if
their relative importance should shift.
This study by going into depths through qualitative interviews was able to
show that all of the behavioral models used, TAM, TPB, consumer readiness
in the SST literature are valid, but none of them could singularly explain all
categories that were found under the groups affecting channel-choice. Such a
discovery would most likely have been more complicated and resource
exhausting if done through a quantitative study, since question categories
would have been needed to be developed for each criteria. Qualitative studies
are good for getting in-depth information, but they are worse in quantifying
relationships. Relationships and category sizes proposed in the study should all
be treated cautiously, although being informative they were only based on a
sample of 22 respondents. Thus, all findings presented in this paper should be
used as starting material to start on in further research. It is impossible to say
from this research which factors influences the channel choice the most;
however, what is safe to say is that the groups that are mentioned in both
research question one and two have an influence.
There is also the matter of culture. This study was conducted in a highly
developed country; the people are more exposed to technologies and have
higher expectations as well. If the study had been conducted in another
country result might vastly differ. Differences could be related to levels of
optimism (belief that technology makes things easier) and need for human
interaction. Many of the respondents have lived with computers their whole
life, but somewhere else we would find that the sample consisted mostly of
individuals that just recently have been exposed to computers in their lives and
therefore not exhibiting the same levels of confidence in them (trusting
intentions). The study was, however, not completely culturally independent
58
about a fifth of the sample were not originated from the country of origin and
were visitors or had recently moved her.
Further research could make the results quantifiable and show how much each
of the variables explaining channel adoption behavior influences the choice
and continuance intention of a particular SST channel. This is important so
that managers can lay their priorities on the right factors. Further research
could also compare the results from this study with another industry setting. It
might be that the variables affecting channel adoption and satisfaction interact
in other ways depending on the context. Finally, as proposed by Meuter et al.
(2005) there is a lack of knowledge on how profitability is influenced by SST
usage, there is a need to track cost savings that can be made with using
multiple self-service technology channels. It might even turnout that it is
possible that keeping inter personal check-in would be more profitable than
implementing a set of different SST channels.
59
7. MANGERIAL IMPLICATIONS
A problem facing managers is that customers may lack motivation to seek out
the information that is uploaded on company webpage on the self-services
since they are only in their mind a mundane part of the trip. If the customers
don’t seek out the information their role clarity will remain weak and they will
be prone to be subject for dissatisfying service design effects or needing
excessive help with the machine consuming company resources. The problem
gets even more difficult when passengers come across the information and
read it, but soon forget it since it is as said mundane or because they reserved
the flight several months in advance which is a very common scenario. In
these situations it is up to managers to find ways refresh the passengers’
memory of how to perform the check-in or make sure they read it so that the
passengers have a clear understanding, one example will be mentioned soon.
If customers do not want to read or don’t understand their role managers
might want to change the service design which would be the second course of
action. Recently, with the help of new technology SAS has introduced the
possibility to get the boarding card to the mobile (SAS 2012). Now customers
don’t need to go to the machines anymore unless they have baggage.
However; it is much more difficult to mark your baggage with your phone. It
safe to say that most phones don’t have scanners today (to electronically mark
the bag), and they definitely can’t print paper, so managers today have decided
that only the passengers with light baggage that can be brought to the plane
can use the mobile check-in. As long as there is no technical feasible way to
check-in large baggage with the mobile phone (or internet) people need to get
a sticker and use the machines. One way is to transfer back the responsibility
of the job “put tag on the bag” to the service provider’s personnel for those
who use mobile check-in, which is recommended if dissatisfying incidents
continue to occur.
To avoid “technology design problems” managers can provide in-site
education to all new customers through traditional “hand holding” by placing
personnel close to the self-service machines. Many unaccustomed travelers
feel a low self-efficacy when encountering the machines, they perceive them
hard to use and want somebody next to them to show how things are done. It
is important to know that this feeling of low self-efficacy can’t be avoided by
making the machines ridiculously easy to use since the feeling even for the
relatively simplest of tasks (Ellen et al. 1991). It is clear when these people
have tried and used the machine, provided that they are optimistic towards
60
technology, they often are more likely to use it again especially if the
experience had been satisfying. The “hand holding” could also be used to the
mobile check-in. Passengers with mobiles can easily go to an available
informant that can show how to perform the mobile check-in and ask if the
passenger has any baggage and in that scenario tell him to use the self-service
machines and show how that is done. The downside of having people showing
what to do is that it is expensive and that studies have shown that after periods
of guiding in the airports the adoption rate only raised temporarily (Liljander
et al. 2006; Gelderman et al. 2011). Temporary increases can have been caused
by the fact that new passengers emerge soon after the trial periods. These are
passengers that have not been instructed or that instructed passengers travel
so seldom that they have forgotten (or think they have) how to do it and
convert to old habits by checking in at the counter. However; this study did
not measure adoption rate since it would not have been quantifiable.
Those managers that are unclear what the customer’s job is should conduct a
job analysis for the customer. Making a job analysis is essential in making the
customer a co-producer since it is actually what the term means; transferring a
portion of work traditionally that have been done by employees to the
customer. And the result of using such a practice is likely to lead to increased
role clarity, motivation and ability (Meuter et al. 2005).
Obviously managers should make sure that the self-service technology works.
This study found six instances where some kind of technology failure
occurred. The most common reason was that passengers did not get their tag
for the baggage or boarding card. To avoid such problems managers can
implement routine checks of the machines or some central control station
where malfunctioning machines can be spotted. Giving the customers an easy
procedure to report a malfunctioning machine could be done easily by creating
a “machine not working, press here”- button.
“When I want” also had few incidents and these were connected to the ability
to pick a seat early to avoid the misfortune to have a non-optimal seat.
“When” is particularly important to those passengers that are tall (long legs),
old or simply enjoy having that extra space for feet. Even if this subcategory
was mainly positive it had some drawbacks as reported in one of the incidents:
“… when we arrived during the morning. First time we were going to check-in at Arlanda we felt clueless and
thought ‘what is this? There is not a single person in here [to ask for help]?!’”
61
Those people arriving early need to check-in at hours when there is no
ordinary personnel except security guards present can come into trouble.
Companies save money on not needing to have full human resources at site
during night and early hours when few people are travelling. Those people
who do travel during these hours can run into trouble or at least risk becoming
dissatisfied if they can’t figure out how to use the machine and it is difficult for
them to find readily available help. Managers should provide instructions for
these people on what to do during these hours and always have at least
someone that can easily be found at the airport. A problem with this is that
some airports are very large and machines are spread all over the airport, it is
not economical having a person waiting around each corner. A solution is to
provide signs and clear directions on where to go to check-in if problems
occur.
As seen most satisfying incidents were found under “more efficient service”.
Managers who want to increase the use of SSTs should clearly communicate
the value proposition (benefits) of them since customer satisfaction is closely
linked to loyalty and use intention (Homburg, Kuester and Krohmer 2009). In
SAS case all customers were aware of the SSTs ability to cut queuing time
(even if all respondents did not agree that was the case). A delicate solution is
to send a text message at the time when most customers are expected to arrive
at the airport. The text message could say something like: “Experiencing long
queues? If you have no large baggage you can check-in through mobile check-
in. All you need to do is reply “yes” and the boarding card will be send to your
phone and you can go directly to the security control”. By sending such as
message the customers are not only being clearly communicated the value
proposition, they are also becoming aware of the SST channel’s existence and
as well become educated on site on how to perform the service. It is also
necessary to be clear with the fact that only customers with light baggage, that
can be brought with them to the plane, should use this option. The
clarification could be done by increasing the font size, changing the color,
sentence formulation or by underlining the particular words. If some
customers would still not understand that they could not use this option with
heavy baggage, then there should be clear directions at the airport on where to
go if problems occur.
Managers should also make sure that business partners they cooperate with are
as keen as supplying customers with information. One respondent stated that
“The reason I didn’t know about it I think was because I reserved the ticket
62
through Apollo (a charter company).” This calls for closer cooperation, but if
reservation can be done by phone this information is missed as it was with this
case. Companies might want to limit some opportunities to reserve the tickets
in order to provide customers adequate information.
When considering issues concerning channels managers can affect some
things, but not others. They cannot affect if the consumer has a printer or not
(accessibility). Ryan Air only allows for internet check-in, assuming that the
customers need to get a printer by themselves. Customers can do this, but they
will not feel it is comfortable and presently enjoys the flexibility that SAS
offers. This decision is a matter of positioning and decision “where to
compete”; the company will save most money by only allowing internet check-
in; however, by providing flexibility customer satisfaction can be increased.
There is always the issue of offering too many channels. Not only can it affect
profitability (cost of having several machines and people ensuring they are
working), but they can also be totally useless if customers are not using them.
There is no need to offer 12 different options for customer’s to check-in if the
customers are not able to tell them apart, meaning they having situational
relative advantages. This does not mean that currently there are too many SST
channels for customers in the airline industry, but it is something managers
should keep in mind. Managers should clearly communicate the relative
advantage of the SSTs that they have and offer a number of SSTs that make
sense from customer’s perspective.
One issue was trust. People did not trust in the SST- channel because of fear;
they perceived a risk of losing their travel documents because a mobile runs
out of batteries or it gets stolen, thus preferring to have documents in paper
format. Managers can reduce this fear by increasing customers’ role clarity by
providing them clear info on where to go if such a failure would occur and
have practices in place to retrieve lost information quickly. It is important to
ensure the customer that he is not left there only because of their choice of
SST-channel. By doing this more customers can be persuaded to use mobile-
check in.
A checklist on how managers should handle self-service technologies for
managers is presented in figure 5.
63
Figure 5: Check-list for managers for successful SST to ensure customer satisfaction and
increase trial with SSTs.
Make sure the customers have a clear understanding of their role by:
1. Conduc ting a job ana lysis for the c ustomer’ s part of the work.
2. Making sure tha t the servic e is designed in suc h a manner tha t
c onfusion c an be avoided and tha t SST use is user-friend ly.
3. Provid ing c ustomers with read ily ac c essib le information about
c hannel use.
4. Refreshing the c ustomer’ s memory on how to c hec k-in for instanc e
by send ing them instruc tive text messages or e -ma ils hours before
departure.
5. Making sure tha t there a re read ily ava ilab le in-site personnel tha t
c an instruc t need ing c ustomers.
Make sure that SST s are properly designed and functions by:
1. Making the tec hnology user-friend ly and fun to use. One c ustomer
suggested tha t it c ould be p leasant to hear a voic e saying “ thank
you” when transac tion was c ompleted .
2. Provid ing c ustomers an easy way to report ma lfunc tioning
mac hines, for instanc e by the p ress of a button on the mac hine.
3. Provid ing d irec tions to help -c enters in c ase of tec hnology fa ilure or
when c ustomers don’ t understand how to use the mac hine. This is
espec ia lly important during night hours when pa ssengers might not
have anyone to ask for help .
64
8. CONCLUSIONS
This thesis successfully identified four groups of incidents leading to
satisfaction, thus being sources of satisfaction; more efficient service, being in
control, enjoyment, and did its job. Four groups resulting in dissatisfying
customer experiences were identified as well; technology failure, process
failure, poor design and customer driven failure.
The largest group of satisfying experiences in the commercial flight industry
came from SSTs’ making the check-in process more efficient mainly by saving
time the passenger’s time by avoiding queues, but also by making the check-in
process simpler. The second largest group was attributed to the ability to have
greater control over the flight experience primarily by being able to pick the
seat, but also by giving the customer flexibility on when to perform the service
and for some by allowing the customer do it by themself.
The leading cause for dissatisfying events was caused by poor design. The
cause top service design failure was due to customers being unclear in their
role in the service process. The second largest group of dissatisfying incidents
was caused by technology failure because of malfunctioning machines.
This thesis found 12 categories affecting the choice; low perceived difference
between self-service channels, perceiver channel efficiency, awareness and
channel knowledge, lack of trust, social pressure, service design, technical
design, accessibility, habit, being in control, lifestyle, and inconvenience.
Most commonly mentioned reason for adapting one SST-channel in favor of
another was attributed to the fact that it could get the job done in a better way,
thus being more efficient. Efficiency in airline industry check-in process was
related to being able to check-in quicker and avoid queues as well as the
check-in process being simple. Second largest cause was accessibility. If a
customer cannot easily access one particular channel then perceived ease of
use as well as usefulness will drop and the customer choses to use another
SST-channel. Third largest cause was awareness and channel knowledge. If
customers lack enough information about the SST-channel in question they
are less likely to adapt it.
Finally, it can be concluded that TAM, TPB, trusting intentions, consumer
readiness models all are relevant and useful in explaining choice of SST-
channels and none of them could independently explain SST-channel choice.
65
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APPENDIX
APPENDIX A: INTERVIEW GUIDE: SELF-SERVICES FOR
CHECK-IN AT SAS (English version)
Presentation
Hello, I come from Karlstad University and I am currently writing my master
thesis on customer experiences with self-services. Would you agree to
participate in a recorded interview that would take about 10-20 minutes? All
provided information will be dealt with anonymously.
A. Sample characteristics and selection
1. Year of birth?
2. Have you flown with SAS, Scandinavian Airlines, during the past six
months?
3. How many times have you flown with them during the past six
months?
B. Critical incidents
4. Could you be kind and describe in detail two positive and two negative
experiences related to you checking in via any of SAS self-services?
5. Could you describe the events in even more detail?
6. What caused your positive/negative reaction?
7. Have the events occurred more than once?
8. What was the consequence?
9. How did these events affect your relation towards SAS?
10. Do you experience any problems with SAS self-services?
11. What do you think was the reason behind the problem occurring?
12. Did you receive any help when the problem occurred? Did you know
where to go?
13. Was the problem solved in a satisfying manner?
C. Variables
14. How do you, as a customer, experience your role in using SAS’s self-
services? Are you clear during the process on how to use the self-
service technology?
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15. How confident do you regard yourself to be in using the self-service
technology?
16. Have you been educated on how to use the self-services? (By personnel
or other helpful people?)
17. How did you experience the crowds and queues at the airport? Did
they affect your use of self-services?
18. How did you feel about the design of the self-service machines? Was it
easy to understand and use them?
D. Check-in self-service channels
19. Which self-service channel(s) for checking in do you use when
travelling?
20. What made you chose that particular channel?
21. Which check-in channels are you aware of?
22. What differences do you perceive between the check-in alternatives?
23. What advantages and disadvantages do experience with the different
channels (mobile, internet, and machine)?
24. How do you feel the different channels affect your check-in
experience?
25. Did you feel that you had enough knowledge about the different
channels when checking in?
26. Did you experience any social pressure that could have affected your
choice of channel? If yes, how?
27. Do you trust that all channels will function as intended? Is there any
channel you would not use? Why?
28. Do experience the different channels as easy to use and learn to use?
29. Do you have any desires to use other check-in channels now when you
know about their existence? Why? Why not?
30. What could make you switch from the check-in channel you are
currently using to another?
E. Interpersonal check-in vs. SST check-in.
31. Before you, the customer, could check-in over the counter, do you miss
the opportunity to check-in at the counter? Why or Why not?
32. Why is it important for you to check-in at the counter?
33. Would you base your choice of airline on the possibility to check-in
over the counter?
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34. If you had the choice to check-in over the counter or through one of
the self-services which option would you pick?
F. Optimism towards self-service technology
35. How do SAS’s self-services affect your travel experience? How do they
make your trip easier (or harder) and why do you think that is the case?
36. Do you agree; SAS’s self-services enhances your total travel experience?
If no; why not?
37. What, related to SSTs, would have made your experience better? (E.g.
would you have needed more guidance at the site on how to use the
machine? A more user-friendly design?)
38. When talking about self-services in general, what are your feelings
towards the development of self-services?
APPENDIX B: INTERVJUGUIDE:
SJÄLVBETJÄNINGSTJÄNSTER HOS SAS (svensk
version)
Presentation
Hej, jag kommer från Karlstads Universitet och skriver ett examensarbete om
kundupplevelser med självbetjäningstjänster. Skulle du kunna tänka dig att
ställa upp på en 10-20 minuter lång intervju? Självklart kommer alla uppgifter
behandlas anonymt.
A. Urval och bakgrund
1. Vilket år är du född?
2. Har du rest med SAS under de senaste 6 månaderna?
3. Hur många gånger har du flugit under de senaste 6 månaderna?
B. Kritiska händelser
4. Kan du beskriva två positiva och två negativa upplevelser du haft med
SAS självbetjäningstjänster?
5. Kan du beskriva händelseförloppen i mer detalj?
6. Vad orsaka din positiva/negativa reaktion?
7. Har händelserna inträffat flera gånger?
8. Vad ledde det till?
9. Hur påverka upplevelserna med självbetjäningstjänsterna ditt
förhållande/inställning gentemot SAS som företag? Har inställningen
förändrats efter händelsen?
10. Upplever du några problem med SAS självbetjäningstjänster?
11. Vad tror du var orsaken till att problemet uppstod?
12. Fick du hjälp när problemet uppstod? Visste du var du skulle vända
dig?
13. Hur upplevde du att problem löstes?
C. Enskilda faktorer
14. Hur upplever du din roll som kund att använda SAS:s
självbetjäningstjänster? Hade du klart för dig under processen hur du
skulle använda självbetjäningstjänsten(rna)?
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15. Hur självsäker känner du dig med att använda
självbetjäningstjänsten(rna)?
16. Har du blivit tränad att använda självbetjäningstjänsten(rna)? (Av
personal? Andra hjälpsamma individer?)
17. Hur upplevde du att trängseln/köer på flygplatsen påverka din
användning av självbetjäningstjänsten(rna)?
18. Hur upplevde du att maskinerna var designade? Var de lätta att
använda och förstå?
D. Check-in alternativ
19. Vilket check-in alternativ använde du under din resa?
20. Vad var anledningen till att du valde just det alternativet?
21. Vilka check-in möjligheter känner du till?
22. Vilka skillnader upplever du emellan check-in alternativen? Hur anser
du att de förenklar för dig som kund?
23. Vad ser du för nackdelar eller fördelar med de olika check-in
alternativen som erbjuds (mobil, internet, kiosk)?
24. Hur upplevde du att de olika check-in alternativen påverka din check-in
upplevelse?
25. Kände du att du hade tillräckligt mycket med information (kunskap)
om de olika alternativen när du checka-in?
26. Kände du av någon social press med att använda ett alternativ över ett
annat? Vad var orsaken till att du kände så?
27. Litar du på att check-in ”fungerar som det ska” för de olika
alternativen? Eller finns det något alternativ du inte skulle våga
använda?
28. Upplever självbetjäningsalternativen som lätta att använda? Att lära sig
använda?
29. Har du någon avsikt att använda andra check-in alternativ nu när du vet
att de existerar? Varför? Varför inte?
30. Vad skulle få dig att använda andra självbetjäningsalternativ?
E. Behovet av personal vid check-in
31. Förr hade kunden möjlighet att checka in genom bemannad disk,
saknar du möjligheten att checka-in genom bemannad check-in? Varför
(inte)?
32. Varför är det viktigt för dig att checka-in genom en bemannad check-
in?
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33. Skulle du välja ett annat flygbolag baserat på att de tillåter bemannad
check-in?
34. Mellan valet av självbetjänings check-in och manuell check-in över disk,
vilken väljer du?
F. Optimistisk attitud mot självbetjäningsteknologi
35. På vilket sätt påverkar självbetjäningstjänster hos SAS din
reseupplevelse? Hur förenklar (eller försvårar) de resan för dig och
varför?
36. Anser du att SAS:s självbetjäningstjänster ger dig en bättre total
upplevese av SAS?
37. Vad skulle gjort din upplevelse bättre? (Ex. Hade du behövt mer
vägledning av personal på plats? En mer användvänlig design? Ett
tydligare besked på att check-in fungerat?)
38. Hur upplever du utvecklingen av självbetjäningstjänster i samhället mer
generellt?