understanding expectations and values of students in higher
This paper investigates the nature of service quality in higher
education and in particular what qualities and behaviors
students expect from their lecturers. The paper begins by
reviewing the literature on service quality in higher education
and the role of the lecturer, and then describes a study that uses
the means–end approach and laddering technique to develop a
deeper understanding of the attributes of lecturers preferred by
students. The study uncovers constructs that underlie students'
desire expectations and the paper concludes with a summary of
findings and suggestions for further research.
2. Quality in higher education and the role of lecturers
Quality in higher education is a complex and multifaceted
concept and a single appropriate definition of quality is lacking
(Harvey and Green, 1993). As a consequence, consensus
concerning “the best way to define and measure service quality”
(Clewes, 2003, p. 71) does not as yet exist. Every stakeholder in
higher education (e.g., students, government, professional
bodies) has a particular view of quality dependent on their
specific needs. This paper is concerned with one particular
stakeholder in higher education, students, and as outlined above,
the introduction of tuition fees and the new degree structure, is
likely to increase the attention which German universities will
pay to this stakeholder's requirements. The services literature
focuses on perceived quality, which results from the comparison
of customer service expectations with their perceptions of actual
performance (Zeithaml et al., 1990). Thus, O'Neill and Palmer
(2004, p. 42) define service quality in higher education as “the
difference between what a student expects to receive and his/her
perceptions of actual delivery”. Guolla (1999) shows that
students' perceived service quality is an antecedent to student
satisfaction. Positive perceptions of service quality can lead to
student satisfaction and satisfied students may attract new
students through word-of-mouth communication and return
themselves to the university to take further courses (Marzo-
Navarro et al., 2005; Wiers-Jenssen et al., 2002; Mavondo et al.,
2004; Schertzer and Schertzer, 2004).
Zeithaml et al. (1993) distinguish between three types of
service expectations: desired service, adequate service, and
predicted service. Customers have a desired level of service
which they hope to receive comprising what customers believe
can be performed and what should be performed. Customers
also have a minimum level of acceptable service as they realize
that service will not always reach the desired levels; this is the
adequate service level. Between these two service levels is a
zone of tolerance that customers are willing to accept. Finally,
customers have a predicted level of service, which is the level of
service they believe the company will perform.
This paper examines how lecturers should behave and which
qualities they should possess (desire expectations) from a
student's point of view. The issue of customer expectations in
general and desire expectations in particular is still a neglected
area (Yim et al., 2003; Pieters et al., 1998). Customers can use
such desire expectations as reference standards for satisfaction
judgments (Singh and Widing, 1991). In addition, Zeithaml
et al. (1993) point out that desire expectations are more stable
and less dependent on the particular service situation than other
types of expectations. Thus, examining the nature of desire
expectations is an important contribution to the area of service
quality in higher education.
Pieters et al. (1998, p. 757) suggest that the “extent to which
customers attain their goals depends partly on the behavior of
service employees” and Oldfield and Baron (2000) characterize
higher education as a “pure” service and point to the importance
of the quality of personal contacts. Thus, the underlying
assumption of this paper is that for students, the qualities and
behaviors of lecturers have a significant impact on their
perceptions of service quality. Several research findings in the
services literature support this assumption; Hartline and Ferrell
(1996) for example believe that the behaviors and attitudes of
customer contact employees primarily determine the customers'
perceptions of service quality. Studies also indicate that the
human interaction element is essential to determine whether
customers consider service delivery satisfactory (Chebat and
Kollias, 2000). Bitner et al. (1994) recognize that in services,
the nature of the interpersonal interaction between the customer
and the contact employee often affects satisfaction.
In the context of higher education, Hansen et al. (2000)
develop a valid instrument to evaluate modules or units of study.
Their findings indicate that the instructional quality of the
lecturer is the main influence on the perceived quality of
modules. Likewise, Hill et al. (2003) find that the quality of the
lecturer belongs to the most important factors in the provision of
high quality education. Pozo-Munoz et al. (2000, p. 253)
maintain that “teaching staff are key actors in a university's
work”. Therefore, the behaviors and attitudes of lecturers should
be the primary determinant of students' perceptions of service
quality in higher education. If lecturers know what their students
expect, they may be able to adapt their behavior to their students'
underlying expectations, which should have a positive impact on
their perceived service quality and their levels of satisfaction.
Given the current lack of knowledge concerning desire
expectations (Pieters et al., 1998) the research study will be
explorative in nature. The study aims to develop a deeper
understanding of the attributes (qualities and behaviors) of
effective lecturers that students desire and to uncover the
constructs that underlie these desire expectations and reveal the
underlying benefits students look for. To address these issues,
the research study uses a semi-standardized qualitative tech-
nique called laddering as O'Neill and Palmer (2004, p. 41)
suggest that qualitative methods “provide an interesting insight
into the mindset of individual students”. Laddering allows
researchers to reach deeper levels of reality and to reveal what
Gengler et al. (1999 p. 175) refer to as the “reasons behind the
reasons”. Apparently, no research study applies the means–end
chain framework and the laddering technique to the issue of
service quality in higher education. The paper details how the
means–end approach is appropriate and useful in this research
study. Another aim of this paper is to compare two laddering
techniques (laddering interviews and laddering questionnaires)
to see whether as Grunert et al. (2001, p. 72) suggest, “different
950 R. Voss et al. / Journal of Business Research 60 (2007) 949–959
techniques may lead to different sets of attributes, leading to the
measurement of different excerpts from cognitive structure”.
3. Means–end chain approach and laddering technique
The means–end chain approach (Gutman, 1982; Howard,
1977; Olson and Reynolds, 1983; Young and Feigin, 1975)
attempts to discover the salient meanings that consumers
associate with products, services and behaviors. The focus is
on associations in the consumer's mind between the attributes of
products, services or behaviors (the means), the consequences of
these attributes for the consumer, and the personal values or
beliefs (the ends), which are strengthened or satisfied by the
consequences. These linkages between attributes, consequences
and values are the means–end chains, the mental connections that
link the different levels of knowledge (Reynolds et al., 1995).
Grunert et al. (2001, p. 63) describe the means–end approach
as “one of the most promising developments in consumer research
since the 1980s”. Researchers are able to examine the consumer's
individuality in depth while still producing quantifiable results.
Early work in this area helps to resolve product — or brand
positioning problems and to link the consumer's product
knowledge to his/her self-knowledge (Gutman, 1982; Olson and
Reynolds, 1983). Researchers apply the means–end framework to
the domain of consumer behavior (e.g., Bagozzi and Dabholkar,
1994; Pieters et al., 1995, 1998), sales management (e.g.,
Botschen et al., 1999; Deeter-Schmelz et al., 2002; Reynolds
et al., 2001), and strategic marketing (e.g., Norton and Reynolds,
2001; Reynolds and Rochon, 2001). This research suggests that
the ability of students to attain their personal goals and values
(ends) depend to a certain degree on the qualities and behaviors of
lecturers (means) during the personal interaction in class.
The means–end approach assumes consumer knowledge to
be hierarchically organized, spanning different levels of
abstraction in the consumer's memory (Reynolds et al., 1995).
At higher levels of abstraction, the connections to the self are
more direct and stronger than at lower levels of abstraction.
Such an approach assumes that the extracts from the cognitive
structure are of linear type with cognitive concepts linked by
one-to-one associations. The interviewer deduces this linear
structure from a possibly larger cognitive network during the
laddering interview (Grunert and Grunert, 1995). Researchers
criticize the means–end approach for assuming a hierarchical
knowledge structure (Herrmann, 1996) while modern cognitive
psychology research indicates that cognitive structures are
complex networks. Van Rekom and Wierenga (2002) for
example present knowledge representations as association
patterns or semantic networks (Chang, 1986). In this alternative
model, consumers have patterns of interconnected concepts in
their minds, with each concept gaining meaning from links with
other concepts. Van Rekom and Wierenga (2002) also stress the
importance of the network over the hierarchies within the
network. Olson and Reynolds (2001) reinforce this issue by
maintaining that the critical elements of networks are the
connections between components, the attributes, consequences
and values, as they carry the weight of the meaning. Following
this development in thinking, the current study is primarily
interested in the relations between the concepts of meaning both
as hierarchies and within the broader framework of the network.
4. Two laddering methods: soft and hard laddering
This section of the paper considers in more detail two
alternative methods, soft and hard laddering (Botschen and
Thelen, 1998; Grunert et al., 2001). Soft laddering involves in-
depth interviews with respondents following as far as possible
their natural flow of speech; the researcher aims to understand
the meaning of the given answers and to link them to the means–
end model (Grunert et al., 2001). Hard laddering uses data
collection techniques (interviews and questionnaires) where
respondents have to “produce ladders one by one and to give
answers in such a way that the sequence of the answers reflects
increasing levels of abstraction” (Grunert et al., 2001, p. 75).
In soft laddering the approach is to use semi-standardized
qualitative in-depth interviews during which interviewers follow
a process of digging deeper by asking probing questions to reveal
attribute–consequence–value chains by taking the subject up a
ladder of abstraction (Reynolds and Gutman, 1988). Prior to
laddering, an elicitation stage takes place to derive preference
based distinction criteria (Grunert and Grunert, 1995; Reynolds
and Gutman, 1988). Techniques such as triadic sorting, direct
elicitation or free sorting may be used, although research shows
that complex methods are time consuming and do not outperform
free sorting techniques such as direct questioning and ranking
(Bech-Larsen and Nielsen, 1999). The derived criteria from the
elicitation stage act as the opening for the laddering probes to
uncover the complete means–end structure which will reveal
cognitive relationships of personal relevance to the respondent
(Gengler and Reynolds, 1995). For this, the interviewer
repeatedly questions why an attribute/consequence/value is
important to the respondent. The answer to this question serves
as the starting point for further questioning.
Although the majority of published means–end chain studies
employ in-depth laddering interviews (Botschen and Thelen,
1998), some use questionnaires (hard laddering). In 1991,
Walker and Olson (1991) developed a paper-and-pencil version
of the laddering interview where respondents fill in a structured
questionnaire identifying up to four attributes that are of
relevance to them and then giving up to three reasons why each
attribute is of importance (Botschen and Hemetsberger, 1998).
The main advantage of the paper-and-pencil version is the lack
of interviewer bias (Botschen and Hemetsberger, 1998) and
with no social pressure involved, respondents themselves
decide when they want to end the laddering process. According
to Botschen et al. (1999), another advantage of the paper-and-
pencil version in comparison to the traditional in-depth
interviewing technique is the cost-efficient data collection.
Several examples of successful projects employ the paper-and-
pencil version (e.g., Botschen and Hemetsberger, 1998;
Botschen and Thelen, 1998; Pieters et al., 1995; Goldenberg
et al., 2000). Fig. 1 presents the laddering questionnaire used in
this research study.
Having outlined the means–end approach and the two
laddering techniques used in the study, the next section covers
951R. Voss et al. / Journal of Business Research 60 (2007) 949–959
the research carried out to explore the desired expectations of
teacher education students in general and to reveal the desired
attributes (qualities and behaviors) of lecturers in particular. As
stated, one aim of this paper was to compare these two laddering
techniques and investigate whether the techniques would lead to
5. The study
Laddering interviews and questionnaires took place amongst
students at a European University of during 2004 and 2005. The
researchers conducted personal laddering interviews with
twenty-nine students aged between 19 and 33 years (X=22.6)
and handed out laddering questionnaires to 53 students aged
between 19 and 32 years (X=22.9). Respondents enrolled in
two business management courses and took part on a voluntary
basis. Grunert and Grunert (1995) suggest that researchers
should collect ladders that are from a group of homogeneous
respondents, and teacher education students at this university all
have similar backgrounds, come from the surrounding area, and
have the common goal of wanting to become teachers. The
number of conducted interviews and distributed questionnaires
was theory-driven as qualitative researchers should always
theoretically reflect on gathered data to decide whether to
collect more. Researchers should sample respondents until they
believe that their categories achieve theoretical saturation.
Theoretical saturation means that no new or relevant data
emerge concerning a category, that the category is well-
developed, and that the linkages between categories are well-
established (Strauss and Corbin, 1998). Qualitative researchers
face the problem of not knowing the optimum minimum sample
size at the start of a study (Bryman, 2004). The study originally
planned to hand out 78 laddering questionnaires in three
courses. Analysis of the questionnaires from the first two
courses, however, showed that respondents did not provide any
new categories. As the categories reached theoretical saturation,
no additional questionnaires were necessary from the third
course thus completing the laddering process after 53
questionnaires. Similarly, the categories based on the laddering
interviews reached theoretical saturation after 29 interviews.
Table 1 sums up the details of the two samples.
6. Data analysis and results
The analysis of the means–end data comprised of three
stages (Reynolds and Gutman, 1988). Firstly, the coding of
sequences of attributes, consequences and values (the ladders)
takes place in order to make comparisons across respondents
using the software program LADDERMAP (Gengler and
Reynolds, 1993). LADDERMAP allows entry of up to ten
chunks of meaning per ladder and to categorize each phrase as
an attribute, consequence or value. The second phase involved
the development of meaningful categories by grouping together
phrases with identical meanings. The identification of catego-
ries was through phrases and key words that respondents used
during the interviews and from concepts derived from the
literature review. For example, if respondents mentioned that
lecturers should have sufficient knowledge of the subject they
teach, this statement linked to the concept “expertise”. The
research followed an iterative process of recoding data,
splitting, combining categories and generating new or dropping
existing categories, followed by an aggregation of codes for
Fig. 1. Paper-and-pencil version of laddering. Source: Adapted from Pieters et al. (1998, p. 760) and Botschen and Hemetsberger (1998, p. 154).
Characteristics of samples
Female Male Min Max Average
29 17 (59%) 12 (41%) 19 33 22.6
53 34 (64%) 19 (36%) 19 32 22.9
952 R. Voss et al. / Journal of Business Research 60 (2007) 949–959
individual means–end chains across subjects. A matrix
presented the aggregations to express the number of associations
between the conceptual meanings (attributes/consequences/
values). This implications matrix details the associations between
the constructs and acts as a bridge between the qualitative and
quantitative elements of the technique by showing the number of
times one code leads to another (Deeter-Schmelz et al., 2002).
Finally, the research generates a Hierarchical Value Map
(HVM) that Gengler et al. (1995, p. 245) define as “a graphical
representation of a set of means–end chains which can be
thought of as an aggregate (e.g., market-level) cognitive
structure map”. The map consists of nodes, which stand for
the most important attributes/consequences/values (conceptual
meanings) and lines, which represent the linkages between the
concepts. The map graphically sums up the information
collected during the laddering interviews (Claeys et al., 1995).
To ensure readability and usefulness, the map only displays
associations up to a specific “cutoff” level, which meant that a
certain number of respondents had to mention linkages in order
for the map to include them. For example, a cutoff level of 1
means that the map includes every connection between
constructs mentioned by respondents. The resulting HVM is
“a mass of links and concepts that usually is unintelligible”
(Christensen and Olson, 2002, p. 484). The higher the chosen
cutoff level is, the more linkages and constructs of meaning
disappear and the more interpretable the map becomes.
However, if the cutoff level is too high, too many constructs
will have disappeared and the resulting map will not be
interesting. Researchers, therefore, have to find a balance
between data reduction and retention (Gengler et al., 1995) and
between detail and interpretability (Christensen and Olson,
2002) to create a clear and expressive map with sufficient
information. The HVM based on the interviews only displays
associations beyond the cutoff level of 4, which means that the
map only graphically represents linkages that at least 4
respondents mentioned during the interviews. The chosen
cutoff level creates a map that keeps the balance between data
reduction and retention and between detail and interpretability.
Similarly, the study applies a cutoff level of 5 for the HVM
based on the questionnaires.
The two hierarchical value maps in Figs. 2 and 3 reveal that the
most critical attributes of lecturers are: teaching skills, teaching
methods, communication skills, approachability, enthusiasm,
expertise, humor, and friendliness. These findings are similar to
previous research that indicates the importance of these instructor
factors (e.g., Patrick and Smart, 1998; O'Toole et al., 2000;
Willcoxson, 1998; Westermann et al., 1998). In particular, Hill
et al. (2003) find that students want lecturers to be knowledgeable,
well-organized, encouraging, helpful, sympathetic, and caring to
students' individual needs. Sander et al. (2000) find that students
Fig. 2. Hierarchical value map of teacher education students (interviews).
953R. Voss et al. / Journal of Business Research 60 (2007) 949–959
at the beginning of their university life want lecturers to have good
teaching skills and to be approachable, knowledgeable, enthusi-
astic, and organized. According to Lammers and Murphy (2002),
students have a high regard for lecturers who are enthusiastic
about their subject, inspiring, knowledgeable, and helpful.
Similarly, Shevlin et al. (2000) mention “lecturer charisma” and
Andreson (2000) points out that students want lecturers to be
caring, enthusiastic, and interested in the students' progress.
Brown's (2004) research indicates that competent lecturers know
their subject, are willing to answer questions, are approachable,
and have a sense of humor. In addition, they should be flexible
enough to explain things in different ways, and to treat students as
As the size of the circles in the HVM stands for the frequency
respondents brought up a certain concept, expertise is the most
important attribute of lecturers. This supports findings by
authors such as Pozo-Munoz et al. (2000), Husbands (1998),
Patrick and Smart (1998), and Ramsden (1991) who also point
to the importance of lecturer expertise. For example, Pozo-
Munoz et al.'s (2000) study indicates that competency is by far
the most important characteristic of ideal teachers. Teachers
should have knowledge of their subject and be able to
communicate their expertise clearly to students.
According to Greimel-Fuhrmann and Geyer (2003), good
teachers should give explanations, answer questions, adapt their
teaching methods, and be interested in and show concern for their
students and their learning progress. Good teachers should also be
humorous, friendly, patient, and fair graders. Similarly, students in
this study want lecturers to answer their questions (problem
solution), to choose the most suitable teaching method (teaching
methods), and to be friendly (friendliness) and humorous (humor).
In addition to displaying the most important attributes of
lecturers, the hierarchical value map also shows why these
attributes are important to the respondents. In this way, the
HVM offers a deeper understanding of the attributes of lecturers
that teacher education students desire by uncovering the
constructs that underlie these desire expectations and graph-
ically illustrating the underlying benefits that students look for.
In this connection, respondents mentioned several conse-
quences. Students' desire to learn something (learning) appears
to be the most important consequence. As the width of the line
in the HVM reveals, learning is strongly associated with
performance and knowledge. Students believe that they need
valuable learning experiences at university and in particular that
they must acquire skills and methods (knowledge) which will
help them prepare for their profession (professional qualifica-
tion). The linkage between learning and knowledge supports
findings in psychological literature which indicate that the
learning process builds on existing knowledge leading to new
knowledge (e.g., Schönpflug and Schönpflug, 1995). Students
Fig. 3. Hierarchical value map of teacher education students (questionnaires).
954 R. Voss et al. / Journal of Business Research 60 (2007) 949–959
also want to have valuable teaching experiences to enable them
to pass examinations (performance) necessary to obtain their
degree and embark upon their careers. Students believe they
will be able to pass such tests if they are motivated (motivation)
and the lecturer's enthusiasm has a positive impact on their
motivation. In addition, the lecturers' expertise, enthusiasm, and
their teaching skills are associated with learning. The strong
focus on learning and performance supports findings by Rolfe
(2002) that suggest students may increasingly regard their
university education as ‘instrumental’ as they enter higher
education mainly for career reasons.
The ability of lecturers to choose the most suitable teaching
method from a variety of teaching tools (teaching methods) is
important to students as lecturers can then offer interesting
lessons (interesting lessons), which results in students being
observant and paying attention to what their lecturers are saying
(attentiveness). This, in return, helps students to learn
(learning). The lecturer's communication skills also have a
positive impact on students' attentiveness. Students also believe
they can save time (save time), through a quick learning process
(learning). Lecturers need to take time for their students during
and after lessons (approachability). Approachable lecturers
provide direction and advice (counseling) and solve students'
problems (problem solution).
According to the HVM, students particularly want to satisfy
the following values: “well-being”, “security”, “satisfaction”,
“universalism”, “self-esteem”, and “hedonism”. Students who
believe that they are able to pass their tests, who feel prepared for
their profession, and who receive advice, feel freed from doubt
(security). Students feel good (well-being) if they can relax, save
time, and receive advice from friendly lecturers. Students who
acquire skills and methods are satisfied (satisfaction) and they
feel they are in good hands (well-being) and better about
themselves (self-esteem). Students who can save time due to a
quick learning process are also able to enjoy life and have fun
(hedonism). The HVM also reveals that students who are
prepared for their profession feel safe and certain (security) and
they want to positively influence society by educating young
people by imparting knowledge and values (universalism). This
strong association between the consequence “professional
qualification” and the value “universalism” that respondents
mention during the laddering interviews, however, could be a
social desirability effect as teacher education students may try to
give the impression of being particularly concerned about
educating their pupils. This link appears in the interviews, but
only from a few questionnaire respondents.
A comparison of the two value maps reveals that the HVM
based on the interviews is more complex than the HVM based
on the questionnaires. Although the interview HVM comprises
the same number of attributes and one consequence less than the
questionnaire HVM, the interview value map reveals far more
values than the map based on the laddering questionnaires (6
values in comparison to 2). Moreover, the interview HVM
displays more associations between concepts than the HVM
based on the questionnaires (28 associations in comparison to
23). During the laddering interviews, respondents mention three
concepts that appear in the questionnaire HVM but not in the
interview HVM, namely “interesting lessons”, “humor”, and
“atmosphere”. These concepts, however, do not appear in the
corresponding interview HVM owing to the chosen cutoff level.
As stated, the HVM only displays associations that a certain
number of respondents mentioned. Thus, only a few respon-
dents mentioned these concepts during the interviews. Similar-
ly, respondents wrote down the consequence “relaxation” that
appears in the interview HVM but not in the questionnaire
HVM but this concept is not graphically represented owing to
the cutoff level.
Table 2 shows that respondents elicit on average more
attributes, consequences, and values during laddering inter-
views than in the laddering questionnaires. In particular,
respondents mention on average more than five times more
values during the interviews than in the laddering question-
naires. This also explains why the questionnaire HVM (2
values) only displays a small number of values in comparison to
the number of values shown in the interview HVM (6 values).
Respondents seem to have difficulties with climbing the ladder
of abstraction and with eliciting associations on the highest
value of abstraction without the presence of interviewers. In
face-to-face interviews, interviewers can employ several
laddering techniques (e.g., Reynolds and Gutman, 1988) to
help respondents reach the value level which researchers cannot
employ in the paper-and-pencil version of laddering. Respon-
dents also mention more attributes during the personal
interviews than in the questionnaires. This is explainable by
the fact that the questionnaire design only allows respondents to
write down four attributes while they are not limited during
personal interviews. The design of the paper-and-pencil version
of laddering also explains why respondents mention so many
consequences (respondents mention on average 6.8 conse-
quences per person in comparison to only 3.2 attributes with
consequences accounting for 62% of all concepts of meaning).
Respondents can give up to three reasons why a certain attribute
Comparison of attributes, consequences, and values
Attributes Consequences Values
Average number of
Percentage of attributes
of all concepts of
Average number of
consequences of all
concepts of meaning
of values per
Percentage of values of
all concepts of meaning
4.3 21% 11.1 54% 5.1 25%
3.2 29% 6.8 62% .96 9%
955R. Voss et al. / Journal of Business Research 60 (2007) 949–959
is important to them and the lack of elicited values may have
been compensated for by the large number of consequences as
respondents were not always able to completely climb the
ladder of abstraction to the value level.
Table 3 shows the total of 125 ladders collected from the
laddering interviews with the 29 respondents providing between
2 and 7 ladders each, with an average of 4.3 ladders per
respondent. The longest ladder consists of eight concepts of
meaning (attributes, consequences, and values) and the shortest
two, with an average of 4.8 concepts of meaning per ladder. By
comparison, the laddering questionnaires give a total of 170
ladders and the 53 respondents provide between 1 and 4 ladders
each, with an average of 3.2 ladders per respondent. The longest
ladder consists of six concepts of meaning (attributes,
consequences, and values) and the shortest two, with an
average of 3.4 concepts of meaning per ladder. The 29 laddering
interviews reveal more concepts of meaning than the 53
questionnaires. These results demonstrate that researchers can
collect more ladders with more concepts of meaning during
personal laddering interviews than with the paper-and-pencil
version of laddering. The ladders collected from the interviews
were also on average longer than the ladders from the
7. Limitations and directions for further research
The research study has several limitations. The study is
explorative in nature as this was the first to compare two
versions of the laddering technique in the context of service
quality in higher education. The aim of the study is to give a first
valuable in-depth insight into what matters for teacher
education students by revealing several important constructs.
Further research studies, however, should improve knowledge
of this topic.
Due to the explorative nature of the study in general and the
scope and size of the sample in particular, the results are
tentative in nature. As the study involves two groups of
university students from one university, one may not generalize
the results to the student population as a whole. Qualitative
researchers, however, can enhance generalizability by carrying
out further studies using similar data collection and analysis
methods at other research sites with a view to achieving
“moderatum generalization”(Bryman, 2004, p. 285) and
demonstrating that the findings are valid beyond and outside
particular research contexts. Thus, fellow researchers should
carry out further studies using similar data collection and
analysis methods at other research sites. Researchers could then
compare results from these studies and reveal differences.
The measurement of service quality in higher education
requires researchers to take the perspectives of other stake-
holders (e.g., the government, employers, students' families)
into consideration as well (Rowley, 1997). Thus, fellow
researchers could examine the desire expectations of other
stakeholder groups. Further research, for example, could
investigate whether student desire expectations differ greatly
from what lecturers believe students want. Mattila and Enz
(2002) found a large gap between customer and employee
perceptions regarding service quality expectations. Thus, fellow
researchers could hand out questionnaires to both lecturers and
their students. The researchers could then compare the resulting
hierarchical value maps to highlight different views. Insights
gained should help make lecturers aware of differing percep-
tions and identify areas for appropriate training. In the context
of service quality in higher education, first research results
already indicate that a service expectation gap exists. Shank
et al. (1995), for example, find that service delivery expecta-
tions are lower among professors than among their students.
Botschen et al. (1999) point to the fact that the paper-and-
pencil version of laddering provides hardly any context
information. As a consequence, the development of meaningful
categories during content analysis is occasionally difficult to
perform (Grunert and Grunert, 1995). In addition, Botschen
et al. (1999 p. 55) admit that “little is known about the validity
and reliability of the procedure and the comparability of results
obtained from traditional laddering interview (soft laddering)
and paper-and-pencil laddering”. Due to the lack of personal
interviewing techniques (e.g., postulating the absence of an
object or a state of being or evoking the situational context),
paper-and-pencil laddering loses richness of data.
The results of the research study indicate that only a few
respondents reach the highest level of abstraction. However, in
comparable paper-and-pencil laddering studies by authors such
as Pieters et al. (1998), Botschen et al. (1999) and Botschen and
Hemetsberger (1998), respondents only express a few values
like “feeling good”, “harmony with yourself”, and “satisfaction”.
Banister et al. (1994) point out that many people may have
difficulties with verbalizing their experiences and with reflecting
on their behaviors and attitudes. This may explain why only few
respondents who filled in the laddering questionnaires men-
tioned values. Without the guidance of interviewers, most
respondents are not able climb the ladder of abstraction.
This paper describes the application of the means–end chain
approach and the laddering technique to investigate service
Comparison of number and length of ladders
Number of ladders per
Number of concepts of meaning (A/C/V) Number of concepts of
meaning per ladder(=length of
Min Max Average Min Max Average
Laddering interviews 125 2 7 4.3 597 2 8 4.8
Laddering questionnaires 170 1 4 3.2 582 2 6 3.4
956 R. Voss et al. / Journal of Business Research 60 (2007) 949–959
quality in higher education. Given the current lack of
knowledge of student desire expectations, this is an explorative
research study using the laddering technique to investigate how
lecturers should behave and what qualities students look for.
The laddering method revealed the constructs which drive the
importance of the desired attributes of lecturers and preferred
This explorative study gives a valuable first insight into the
desired teaching qualities of lecturers and reveals the linkages
between attributes, consequences and values. The results
indicate that these teacher education students want lecturers to
be knowledgeable, enthusiastic, approachable, and friendly.
They should possess sufficient communication and teaching
skills and be able to choose the most suitable teaching method
from a variety of teaching tools. Respondents also mention
several values that they regard as relevant and desirable:
security, well-being, satisfaction, self-esteem, hedonism, and
universalism. A comparison of two different laddering
techniques reveals that although the results of the two methods
are broadly similar, the personal laddering interviews produce
more depth in understanding and significantly more respon-
dents were able to reach the value level.
The analysis also reveals why lecturers should possess the
desired attributes: students predominately want to encounter
valuable teaching experiences to be able to pass tests and to be
prepared for their profession. Vocational aspects of their studies
motivate students more than academic interest. Such knowledge
of student expectations should help lecturers design their
teaching programs. German lecturers in particular should pay
more attention to vocational aspects in their teaching as they
regularly receive criticism for offering courses that are too
theory-laden (Voss, 2006). Thus, lecturers should include topics
in the curriculum that help students prepare for their profession.
Lecturers could also provide assignments that are directly
relevant to work, and use interesting and thought-provoking
examples and case studies from the “real world”. Lecturers
could also stress links between theory and practice more and
invite guest speakers who are willing to share valuable
experiences with students.
The introduction of tuition fees in Germany will probably
strengthen this “consumerist” approach and German universi-
ties will have to offer value for money while lecturers will have
to emphasize the vocational relevance of their courses.
Approaches for attracting new students such as a “student
satisfaction guarantee” (Gremler and McCollough, 2002;
McCollough and Gremler, 1999a,b) might be considered.
Such a guarantee could make education appear more tangible
and signal the quality of the educational experience to current
and new students. McCollough and Gremler (1999a) find that
satisfaction guarantees have a positive impact on student
confidence in lecturers and they help set clear expectations
that both students and lecturers will work hard. As a
pedagogical device, satisfaction guarantees set performance
standards and help increase the accountability of both students
and lecturers. They also influence student evaluations of
lecturers and courses positively without losing rigor in the
classroom (Gremler and McCollough, 2002). In this connec-
tion, the laddering technique helps lecturers identify how they
should behave and which qualities they should possess from a
student's point of view; the satisfaction guarantee could cover
the desired teaching qualities. This study shows that the
laddering technique is a useful tool in examining the issue of
service quality in higher education and future research should
be able to develop further studies to test the application of the
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