Article 2: Predicting intraindividual changes in teacher burnout: The role of perceived school environment and motivational factors

h 60 (2007) 949–959
Journal of Business Researc
Service quality in higher education: The role of student expectations

Roediger Voss a, Thorsten Gruber b, Isabelle Szmigin c,⁎

a University of Education Ludwigsburg, Pädagogische Hochschule Ludwigsburg, Institut für Bildungsmanagement Postfach 220, 71602 Ludwigsburg, Germanyb The University of Manchester, Manchester Business School, MBS West, Booth Street West, Manchester M15 6PB, United Kingdom

c The University of Birmingham, Birmingham Business School, University House, Birmingham B15 2TT, United Kingdom

Received 1 June 2006; received in revised form 1 December 2006; accepted 1 January 2007

Abstract

The study aims to develop a deeper understanding of the teaching qualities of effective lecturers that students desire and to uncover theconstructs that underlie these desire expectations to reveal the underlying benefits that students look for. An empirical study using the means–endapproach and two laddering techniques (personal interviews and laddering questionnaires) gives a valuable first insight into the desired qualities oflecturers. While the personal laddering interviews produced more depth in understanding, the results of the two laddering methods are broadlysimilar. The study results indicate that students want lecturers to be knowledgeable, enthusiastic, approachable, and friendly. Studentspredominately want to encounter valuable teaching experiences to be able to pass tests and to be prepared for their profession. This study alsoshows that students' academic interests motivate them less than the vocational aspects of their studies.© 2007 Published by Elsevier Inc.

Keywords: Service quality; Higher education; Means–end; Laddering

1. Introduction

In January 2005, Germany's highest court overturned afederal law that had banned the introduction of fees, therebypaving the way for universities to charge student tuition fees forthe first time. By 2009/2010 German universities will alsoswitch to the two-cycle system of higher education (bachelor–master) to achieve the Bologna objectives; all German studentswill be able to complete a Bachelor degree at one university andfollow this with a master's degree at a different university. Oneconsequence of these changes is that German universities needto pursue a more customer friendly approach with the aim ofretaining students for postgraduate study as evidence shows thatthe recruitment of students is several times more expensive thantheir retention (Joseph et al., 2005). The new environment willalso force German universities to compete for the best studentsand to monitor the quality of the educational services they offermore closely in order to retain current students and attract newones. Students in Germany will probably also become more

⁎ Corresponding author.E-mail addresses: [email protected] (R. Voss),

[email protected] (T. Gruber), [email protected] (I. Szmigin).

0148-2963/$ - see front matter © 2007 Published by Elsevier Inc.doi:10.1016/j.jbusres.2007.01.020

selective and demanding, making the understanding of studentexpectations a priority for universities.

Student expectations are a valuable source of information(Sander et al., 2000; Hill, 1995). New undergraduate studentsmay have unrealistic expectations of the university experienceand if higher education organizations have a good understand-ing of such students' expectations, they should be in a betterposition to both manage and bring them to a realistic level.Universities could for example inform students of what isrealistic to expect from lecturers (Hill, 1995). The knowledge ofstudent expectations can also help lecturers in the design ofteaching programs (Sander et al., 2000). Hill (1995) finds thatstudent expectations in general and the expectations ofacademic aspects of higher education services such as teachingquality, teaching methods, and course content in particular, arequite stable over time. Telford and Masson (2005) point out thatthe perceived quality of the educational service depends onstudents' expectations and values. They cite several studies thatindicate the positive impact of expectations and values onvariables such as student participation (Claycomb et al., 2001),role clarity, and motivation to participate in the serviceencounter (Lengnick-Hall et al., 2000; Rodie and Kleine,2000). Such work clearly points to the importance of

mailto:[email protected]



http://dx.doi.org/10.1016/j.jbusres.2007.01.020

950 R. Voss et al. / Journal of Business Research 60 (2007) 949–959

understanding expectations and values of students in highereducation.

This paper investigates the nature of service quality in highereducation and in particular what qualities and behaviorsstudents expect from their lecturers. The paper begins byreviewing the literature on service quality in higher educationand the role of the lecturer, and then describes a study that usesthe means–end approach and laddering technique to develop adeeper understanding of the attributes of lecturers preferred bystudents. The study uncovers constructs that underlie students'desire expectations and the paper concludes with a summary offindings and suggestions for further research.

2. Quality in higher education and the role of lecturers

Quality in higher education is a complex and multifacetedconcept and a single appropriate definition of quality is lacking(Harvey and Green, 1993). As a consequence, consensusconcerning “the best way to define and measure service quality”(Clewes, 2003, p. 71) does not as yet exist. Every stakeholder inhigher education (e.g., students, government, professionalbodies) has a particular view of quality dependent on theirspecific needs. This paper is concerned with one particularstakeholder in higher education, students, and as outlined above,the introduction of tuition fees and the new degree structure, islikely to increase the attention which German universities willpay to this stakeholder's requirements. The services literaturefocuses on perceived quality, which results from the comparisonof customer service expectations with their perceptions of actualperformance (Zeithaml et al., 1990). Thus, O'Neill and Palmer(2004, p. 42) define service quality in higher education as “thedifference between what a student expects to receive and his/herperceptions of actual delivery”. Guolla (1999) shows thatstudents' perceived service quality is an antecedent to studentsatisfaction. Positive perceptions of service quality can lead tostudent satisfaction and satisfied students may attract newstudents through word-of-mouth communication and returnthemselves 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 ofservice expectations: desired service, adequate service, andpredicted service. Customers have a desired level of servicewhich they hope to receive comprising what customers believecan be performed and what should be performed. Customersalso have a minimum level of acceptable service as they realizethat service will not always reach the desired levels; this is theadequate service level. Between these two service levels is azone of tolerance that customers are willing to accept. Finally,customers have a predicted level of service, which is the level ofservice they believe the company will perform.

This paper examines how lecturers should behave and whichqualities they should possess (desire expectations) from astudent's point of view. The issue of customer expectations ingeneral and desire expectations in particular is still a neglectedarea (Yim et al., 2003; Pieters et al., 1998). Customers can usesuch desire expectations as reference standards for satisfaction

judgments (Singh and Widing, 1991). In addition, Zeithamlet al. (1993) point out that desire expectations are more stableand less dependent on the particular service situation than othertypes of expectations. Thus, examining the nature of desireexpectations is an important contribution to the area of servicequality in higher education.

Pieters et al. (1998, p. 757) suggest that the “extent to whichcustomers attain their goals depends partly on the behavior ofservice employees” and Oldfield and Baron (2000) characterizehigher education as a “pure” service and point to the importanceof the quality of personal contacts. Thus, the underlyingassumption of this paper is that for students, the qualities andbehaviors of lecturers have a significant impact on theirperceptions of service quality. Several research findings in theservices literature support this assumption; Hartline and Ferrell(1996) for example believe that the behaviors and attitudes ofcustomer contact employees primarily determine the customers'perceptions of service quality. Studies also indicate that thehuman interaction element is essential to determine whethercustomers consider service delivery satisfactory (Chebat andKollias, 2000). Bitner et al. (1994) recognize that in services,the nature of the interpersonal interaction between the customerand 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 thelecturer is the main influence on the perceived quality ofmodules. Likewise, Hill et al. (2003) find that the quality of thelecturer belongs to the most important factors in the provision ofhigh quality education. Pozo-Munoz et al. (2000, p. 253)maintain that “teaching staff are key actors in a university'swork”. Therefore, the behaviors and attitudes of lecturers shouldbe the primary determinant of students' perceptions of servicequality in higher education. If lecturers know what their studentsexpect, they may be able to adapt their behavior to their students'underlying expectations, which should have a positive impact ontheir perceived service quality and their levels of satisfaction.

Given the current lack of knowledge concerning desireexpectations (Pieters et al., 1998) the research study will beexplorative in nature. The study aims to develop a deeperunderstanding of the attributes (qualities and behaviors) ofeffective lecturers that students desire and to uncover theconstructs that underlie these desire expectations and reveal theunderlying 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 insightinto the mindset of individual students”. Laddering allowsresearchers to reach deeper levels of reality and to reveal whatGengler et al. (1999 p. 175) refer to as the “reasons behind thereasons”. Apparently, no research study applies the means–endchain framework and the laddering technique to the issue ofservice quality in higher education. The paper details how themeans–end approach is appropriate and useful in this researchstudy. Another aim of this paper is to compare two ladderingtechniques (laddering interviews and laddering questionnaires)to see whether as Grunert et al. (2001, p. 72) suggest, “different

951R. Voss et al. / Journal of Business Research 60 (2007) 949–959

techniques may lead to different sets of attributes, leading to themeasurement 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 consumersassociate with products, services and behaviors. The focus ison associations in the consumer's mind between the attributes ofproducts, services or behaviors (the means), the consequences ofthese attributes for the consumer, and the personal values orbeliefs (the ends), which are strengthened or satisfied by theconsequences. These linkages between attributes, consequencesand values are the means–end chains, the mental connections thatlink the different levels of knowledge (Reynolds et al., 1995).

Grunert et al. (2001, p. 63) describe the means–end approachas “one of themost promising developments in consumer researchsince the 1980s”. Researchers are able to examine the consumer'sindividuality in depth while still producing quantifiable results.Early work in this area helps to resolve product — or brandpositioning problems and to link the consumer's productknowledge to his/her self-knowledge (Gutman, 1982; Olson andReynolds, 1983). Researchers apply themeans–end framework tothe 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; Reynoldset al., 2001), and strategic marketing (e.g., Norton and Reynolds,2001; Reynolds and Rochon, 2001). This research suggests thatthe ability of students to attain their personal goals and values(ends) depend to a certain degree on the qualities and behaviors oflecturers (means) during the personal interaction in class.

The means–end approach assumes consumer knowledge tobe hierarchically organized, spanning different levels ofabstraction in the consumer's memory (Reynolds et al., 1995).At higher levels of abstraction, the connections to the self aremore direct and stronger than at lower levels of abstraction.Such an approach assumes that the extracts from the cognitivestructure are of linear type with cognitive concepts linked byone-to-one associations. The interviewer deduces this linearstructure from a possibly larger cognitive network during theladdering interview (Grunert and Grunert, 1995). Researcherscriticize the means–end approach for assuming a hierarchicalknowledge structure (Herrmann, 1996) while modern cognitivepsychology research indicates that cognitive structures arecomplex networks. Van Rekom and Wierenga (2002) forexample present knowledge representations as associationpatterns or semantic networks (Chang, 1986). In this alternativemodel, consumers have patterns of interconnected concepts intheir minds, with each concept gaining meaning from links withother concepts. Van Rekom and Wierenga (2002) also stress theimportance of the network over the hierarchies within thenetwork. Olson and Reynolds (2001) reinforce this issue bymaintaining that the critical elements of networks are theconnections between components, the attributes, consequencesand values, as they carry the weight of the meaning. Followingthis development in thinking, the current study is primarily

interested in the relations between the concepts of meaning bothas 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 twoalternative methods, soft and hard laddering (Botschen andThelen, 1998; Grunert et al., 2001). Soft laddering involves in-depth interviews with respondents following as far as possibletheir natural flow of speech; the researcher aims to understandthe meaning of the given answers and to link them to the means–end model (Grunert et al., 2001). Hard laddering uses datacollection techniques (interviews and questionnaires) whererespondents have to “produce ladders one by one and to giveanswers in such a way that the sequence of the answers reflectsincreasing levels of abstraction” (Grunert et al., 2001, p. 75).

In soft laddering the approach is to use semi-standardizedqualitative in-depth interviews during which interviewers followa process of digging deeper by asking probing questions to revealattribute–consequence–value chains by taking the subject up aladder of abstraction (Reynolds and Gutman, 1988). Prior toladdering, an elicitation stage takes place to derive preferencebased distinction criteria (Grunert and Grunert, 1995; Reynoldsand Gutman, 1988). Techniques such as triadic sorting, directelicitation or free sorting may be used, although research showsthat complex methods are time consuming and do not outperformfree sorting techniques such as direct questioning and ranking(Bech-Larsen and Nielsen, 1999). The derived criteria from theelicitation stage act as the opening for the laddering probes touncover the complete means–end structure which will revealcognitive relationships of personal relevance to the respondent(Gengler and Reynolds, 1995). For this, the interviewerrepeatedly questions why an attribute/consequence/value isimportant to the respondent. The answer to this question servesas the starting point for further questioning.

Although the majority of published means–end chain studiesemploy in-depth laddering interviews (Botschen and Thelen,1998), some use questionnaires (hard laddering). In 1991,Walker and Olson (1991) developed a paper-and-pencil versionof the laddering interview where respondents fill in a structuredquestionnaire identifying up to four attributes that are ofrelevance to them and then giving up to three reasons why eachattribute is of importance (Botschen and Hemetsberger, 1998).The main advantage of the paper-and-pencil version is the lackof interviewer bias (Botschen and Hemetsberger, 1998) andwith no social pressure involved, respondents themselvesdecide when they want to end the laddering process. Accordingto Botschen et al. (1999), another advantage of the paper-and-pencil version in comparison to the traditional in-depthinterviewing 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; Goldenberget al., 2000). Fig. 1 presents the laddering questionnaire used inthis research study.

Having outlined the means–end approach and the twoladdering techniques used in the study, the next section covers

Fig. 1. Paper-and-pencil version of laddering. Source: Adapted from Pieters et al. (1998, p. 760) and Botschen and Hemetsberger (1998, p. 154).

Table 1Characteristics of samples

Number ofrespondents

Gender Age

Female Male Min Max Average

Ladderinginterviews

29 17 (59%) 12 (41%) 19 33 22.6

Ladderingquestionnaires

53 34 (64%) 19 (36%) 19 32 22.9


the research carried out to explore the desired expectations ofteacher education students in general and to reveal the desiredattributes (qualities and behaviors) of lecturers in particular. Asstated, one aim of this paper was to compare these two ladderingtechniques and investigate whether the techniques would lead todifferent results.

5. The study

Laddering interviews and questionnaires took place amongststudents at a European University of during 2004 and 2005. Theresearchers conducted personal laddering interviews withtwenty-nine students aged between 19 and 33 years (X=22.6)and handed out laddering questionnaires to 53 students agedbetween 19 and 32 years (X=22.9). Respondents enrolled intwo business management courses and took part on a voluntarybasis. Grunert and Grunert (1995) suggest that researchersshould collect ladders that are from a group of homogeneousrespondents, and teacher education students at this university allhave similar backgrounds, come from the surrounding area, andhave the common goal of wanting to become teachers. Thenumber of conducted interviews and distributed questionnaireswas theory-driven as qualitative researchers should alwaystheoretically reflect on gathered data to decide whether tocollect more. Researchers should sample respondents until theybelieve that their categories achieve theoretical saturation.Theoretical saturation means that no new or relevant dataemerge concerning a category, that the category is well-developed, and that the linkages between categories are well-established (Strauss and Corbin, 1998). Qualitative researchersface the problem of not knowing the optimum minimum samplesize at the start of a study (Bryman, 2004). The study originallyplanned to hand out 78 laddering questionnaires in threecourses. Analysis of the questionnaires from the first twocourses, however, showed that respondents did not provide anynew categories. As the categories reached theoretical saturation,

no additional questionnaires were necessary from the thirdcourse thus completing the laddering process after 53questionnaires. Similarly, the categories based on the ladderinginterviews 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 threestages (Reynolds and Gutman, 1988). Firstly, the coding ofsequences of attributes, consequences and values (the ladders)takes place in order to make comparisons across respondentsusing the software program LADDERMAP (Gengler andReynolds, 1993). LADDERMAP allows entry of up to tenchunks of meaning per ladder and to categorize each phrase asan attribute, consequence or value. The second phase involvedthe development of meaningful categories by grouping togetherphrases with identical meanings. The identification of catego-ries was through phrases and key words that respondents usedduring the interviews and from concepts derived from theliterature review. For example, if respondents mentioned thatlecturers should have sufficient knowledge of the subject theyteach, this statement linked to the concept “expertise”. Theresearch followed an iterative process of recoding data,splitting, combining categories and generating new or droppingexisting categories, followed by an aggregation of codes for


individual means–end chains across subjects. A matrixpresented the aggregations to express the number of associationsbetween the conceptual meanings (attributes/consequences/values). This implications matrix details the associations betweenthe constructs and acts as a bridge between the qualitative andquantitative elements of the technique by showing the number oftimes 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 graphicalrepresentation of a set of means–end chains which can bethought of as an aggregate (e.g., market-level) cognitivestructure map”. The map consists of nodes, which stand forthe most important attributes/consequences/values (conceptualmeanings) and lines, which represent the linkages between theconcepts. The map graphically sums up the informationcollected during the laddering interviews (Claeys et al., 1995).To ensure readability and usefulness, the map only displaysassociations up to a specific “cutoff” level, which meant that acertain number of respondents had to mention linkages in orderfor the map to include them. For example, a cutoff level of 1means that the map includes every connection betweenconstructs 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 chosencutoff level is, the more linkages and constructs of meaning

Fig. 2. Hierarchical value map of teach

disappear and the more interpretable the map becomes.However, if the cutoff level is too high, too many constructswill have disappeared and the resulting map will not beinteresting. Researchers, therefore, have to find a balancebetween data reduction and retention (Gengler et al., 1995) andbetween detail and interpretability (Christensen and Olson,2002) to create a clear and expressive map with sufficientinformation. The HVM based on the interviews only displaysassociations beyond the cutoff level of 4, which means that themap only graphically represents linkages that at least 4respondents mentioned during the interviews. The chosencutoff level creates a map that keeps the balance between datareduction and retention and between detail and interpretability.Similarly, the study applies a cutoff level of 5 for the HVMbased on the questionnaires.

The two hierarchical valuemaps in Figs. 2 and 3 reveal that themost critical attributes of lecturers are: teaching skills, teachingmethods, communication skills, approachability, enthusiasm,expertise, humor, and friendliness. These findings are similar toprevious research that indicates the importance of these instructorfactors (e.g., Patrick and Smart, 1998; O'Toole et al., 2000;Willcoxson, 1998; Westermann et al., 1998). In particular, Hillet al. (2003) find that studentswant lecturers to be knowledgeable,well-organized, encouraging, helpful, sympathetic, and caring tostudents' individual needs. Sander et al. (2000) find that students

er education students (interviews).

Fig. 3. Hierarchical value map of teacher education students (questionnaires).


at the beginning of their university lifewant lecturers to have goodteaching 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 enthusiasticabout their subject, inspiring, knowledgeable, and helpful.Similarly, Shevlin et al. (2000) mention “lecturer charisma” andAndreson (2000) points out that students want lecturers to becaring, enthusiastic, and interested in the students' progress.Brown's (2004) research indicates that competent lecturers knowtheir subject, are willing to answer questions, are approachable,and have a sense of humor. In addition, they should be flexibleenough to explain things in different ways, and to treat students asindividuals.

As the size of the circles in the HVM stands for the frequencyrespondents brought up a certain concept, expertise is the mostimportant attribute of lecturers. This supports findings byauthors such as Pozo-Munoz et al. (2000), Husbands (1998),Patrick and Smart (1998), and Ramsden (1991) who also pointto the importance of lecturer expertise. For example, Pozo-Munoz et al.'s (2000) study indicates that competency is by farthe most important characteristic of ideal teachers. Teachersshould have knowledge of their subject and be able tocommunicate their expertise clearly to students.

According to Greimel-Fuhrmann and Geyer (2003), goodteachers should give explanations, answer questions, adapt their

teaching methods, and be interested in and show concern for theirstudents and their learning progress. Good teachers should also behumorous, friendly, patient, and fair graders. Similarly, students inthis study want lecturers to answer their questions (problemsolution), to choose the most suitable teaching method (teachingmethods), and to be friendly (friendliness) and humorous (humor).

In addition to displaying the most important attributes oflecturers, the hierarchical value map also shows why theseattributes are important to the respondents. In this way, theHVM offers a deeper understanding of the attributes of lecturersthat teacher education students desire by uncovering theconstructs 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) appearsto be the most important consequence. As the width of the linein the HVM reveals, learning is strongly associated withperformance and knowledge. Students believe that they needvaluable learning experiences at university and in particular thatthey must acquire skills and methods (knowledge) which willhelp them prepare for their profession (professional qualifica-tion). The linkage between learning and knowledge supportsfindings in psychological literature which indicate that thelearning process builds on existing knowledge leading to newknowledge (e.g., Schönpflug and Schönpflug, 1995). Students


also want to have valuable teaching experiences to enable themto pass examinations (performance) necessary to obtain theirdegree and embark upon their careers. Students believe theywill be able to pass such tests if they are motivated (motivation)and the lecturer's enthusiasm has a positive impact on theirmotivation. In addition, the lecturers' expertise, enthusiasm, andtheir teaching skills are associated with learning. The strongfocus on learning and performance supports findings by Rolfe(2002) that suggest students may increasingly regard theiruniversity education as ‘instrumental’ as they enter highereducation mainly for career reasons.

The ability of lecturers to choose the most suitable teachingmethod from a variety of teaching tools (teaching methods) isimportant to students as lecturers can then offer interestinglessons (interesting lessons), which results in students beingobservant 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 apositive impact on students' attentiveness. Students also believethey can save time (save time), through a quick learning process(learning). Lecturers need to take time for their students duringand after lessons (approachability). Approachable lecturersprovide direction and advice (counseling) and solve students'problems (problem solution).

According to the HVM, students particularly want to satisfythe following values: “well-being”, “security”, “satisfaction”,“universalism”, “self-esteem”, and “hedonism”. Students whobelieve that they are able to pass their tests, who feel prepared fortheir profession, and who receive advice, feel freed from doubt(security). Students feel good (well-being) if they can relax, savetime, and receive advice from friendly lecturers. Students whoacquire skills and methods are satisfied (satisfaction) and theyfeel they are in good hands (well-being) and better aboutthemselves (self-esteem). Students who can save time due to aquick learning process are also able to enjoy life and have fun(hedonism). The HVM also reveals that students who areprepared for their profession feel safe and certain (security) andthey want to positively influence society by educating youngpeople by imparting knowledge and values (universalism). Thisstrong association between the consequence “professionalqualification” and the value “universalism” that respondentsmention during the laddering interviews, however, could be asocial desirability effect as teacher education students may try togive the impression of being particularly concerned abouteducating their pupils. This link appears in the interviews, butonly from a few questionnaire respondents.

Table 2Comparison of attributes, consequences, and values

Attributes Consequences

Average number ofattributes perperson

Percentage of attributesof all concepts ofmeaning

Average numberconsequences peperson

Ladderinginterviews

4.3 21% 11.1

Ladderingquestionnaires

3.2 29% 6.8

A comparison of the two value maps reveals that the HVMbased on the interviews is more complex than the HVM basedon the questionnaires. Although the interview HVM comprisesthe same number of attributes and one consequence less than thequestionnaire HVM, the interview value map reveals far morevalues than the map based on the laddering questionnaires (6values in comparison to 2). Moreover, the interview HVMdisplays more associations between concepts than the HVMbased on the questionnaires (28 associations in comparison to23). During the laddering interviews, respondents mention threeconcepts that appear in the questionnaire HVM but not in theinterview HVM, namely “interesting lessons”, “humor”, and“atmosphere”. These concepts, however, do not appear in thecorresponding interview HVM owing to the chosen cutoff level.As stated, the HVM only displays associations that a certainnumber of respondents mentioned. Thus, only a few respon-dents mentioned these concepts during the interviews. Similar-ly, respondents wrote down the consequence “relaxation” thatappears in the interview HVM but not in the questionnaireHVM but this concept is not graphically represented owing tothe cutoff level.

Table 2 shows that respondents elicit on average moreattributes, consequences, and values during laddering inter-views than in the laddering questionnaires. In particular,respondents mention on average more than five times morevalues during the interviews than in the laddering question-naires. This also explains why the questionnaire HVM (2values) only displays a small number of values in comparison tothe number of values shown in the interview HVM (6 values).Respondents seem to have difficulties with climbing the ladderof abstraction and with eliciting associations on the highestvalue of abstraction without the presence of interviewers. Inface-to-face interviews, interviewers can employ severalladdering techniques (e.g., Reynolds and Gutman, 1988) tohelp respondents reach the value level which researchers cannotemploy in the paper-and-pencil version of laddering. Respon-dents also mention more attributes during the personalinterviews than in the questionnaires. This is explainable bythe fact that the questionnaire design only allows respondents towrite down four attributes while they are not limited duringpersonal interviews. The design of the paper-and-pencil versionof laddering also explains why respondents mention so manyconsequences (respondents mention on average 6.8 conse-quences per person in comparison to only 3.2 attributes withconsequences accounting for 62% of all concepts of meaning).Respondents can give up to three reasons why a certain attribute

Values

ofr

Percentage ofconsequences of allconcepts of meaning

Average numberof values perperson

Percentage of values ofall concepts of meaning

54% 5.1 25%

62% .96 9%

Table 3Comparison of number and length of ladders

Numberofladders

Number of ladders perrespondent

Number of concepts of meaning (A/C/V) Number of concepts ofmeaning per ladder(=length ofladder)

Min Max Average Min Max Average

Laddering interviews 125 2 7 4.3 597 2 8 4.8Laddering questionnaires 170 1 4 3.2 582 2 6 3.4


is important to them and the lack of elicited values may havebeen compensated for by the large number of consequences asrespondents were not always able to completely climb theladder of abstraction to the value level.

Table 3 shows the total of 125 ladders collected from theladdering interviews with the 29 respondents providing between2 and 7 ladders each, with an average of 4.3 ladders perrespondent. The longest ladder consists of eight concepts ofmeaning (attributes, consequences, and values) and the shortesttwo, with an average of 4.8 concepts of meaning per ladder. Bycomparison, the laddering questionnaires give a total of 170ladders and the 53 respondents provide between 1 and 4 ladderseach, with an average of 3.2 ladders per respondent. The longestladder consists of six concepts of meaning (attributes,consequences, and values) and the shortest two, with anaverage of 3.4 concepts of meaning per ladder. The 29 ladderinginterviews reveal more concepts of meaning than the 53questionnaires. These results demonstrate that researchers cancollect more ladders with more concepts of meaning duringpersonal laddering interviews than with the paper-and-pencilversion of laddering. The ladders collected from the interviewswere also on average longer than the ladders from thequestionnaires.

7. Limitations and directions for further research

The research study has several limitations. The study isexplorative in nature as this was the first to compare twoversions of the laddering technique in the context of servicequality in higher education. The aim of the study is to give a firstvaluable in-depth insight into what matters for teachereducation students by revealing several important constructs.Further research studies, however, should improve knowledgeof this topic.

Due to the explorative nature of the study in general and thescope and size of the sample in particular, the results aretentative in nature. As the study involves two groups ofuniversity students from one university, one may not generalizethe results to the student population as a whole. Qualitativeresearchers, however, can enhance generalizability by carryingout further studies using similar data collection and analysismethods at other research sites with a view to achieving“moderatum generalization”(Bryman, 2004, p. 285) anddemonstrating that the findings are valid beyond and outsideparticular research contexts. Thus, fellow researchers shouldcarry out further studies using similar data collection andanalysis methods at other research sites. Researchers could thencompare results from these studies and reveal differences.

The measurement of service quality in higher educationrequires researchers to take the perspectives of other stake-holders (e.g., the government, employers, students' families)into consideration as well (Rowley, 1997). Thus, fellowresearchers could examine the desire expectations of otherstakeholder groups. Further research, for example, couldinvestigate whether student desire expectations differ greatlyfrom what lecturers believe students want. Mattila and Enz(2002) found a large gap between customer and employeeperceptions regarding service quality expectations. Thus, fellowresearchers could hand out questionnaires to both lecturers andtheir students. The researchers could then compare the resultinghierarchical value maps to highlight different views. Insightsgained should help make lecturers aware of differing percep-tions and identify areas for appropriate training. In the contextof service quality in higher education, first research resultsalready indicate that a service expectation gap exists. Shanket 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 contextinformation. As a consequence, the development of meaningfulcategories during content analysis is occasionally difficult toperform (Grunert and Grunert, 1995). In addition, Botschenet al. (1999 p. 55) admit that “little is known about the validityand reliability of the procedure and the comparability of resultsobtained from traditional laddering interview (soft laddering)and paper-and-pencil laddering”. Due to the lack of personalinterviewing techniques (e.g., postulating the absence of anobject 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 fewrespondents reach the highest level of abstraction. However, incomparable paper-and-pencil laddering studies by authors suchas Pieters et al. (1998), Botschen et al. (1999) and Botschen andHemetsberger (1998), respondents only express a few valueslike “feeling good”, “harmonywith yourself”, and “satisfaction”.Banister et al. (1994) point out that many people may havedifficulties with verbalizing their experiences and with reflectingon their behaviors and attitudes. This may explain why only fewrespondents who filled in the laddering questionnaires men-tioned values. Without the guidance of interviewers, mostrespondents are not able climb the ladder of abstraction.

8. Conclusion

This paper describes the application of the means–end chainapproach and the laddering technique to investigate service


quality in higher education. Given the current lack ofknowledge of student desire expectations, this is an explorativeresearch study using the laddering technique to investigate howlecturers should behave and what qualities students look for.The laddering method revealed the constructs which drive theimportance of the desired attributes of lecturers and preferredbenefits.

This explorative study gives a valuable first insight into thedesired teaching qualities of lecturers and reveals the linkagesbetween attributes, consequences and values. The resultsindicate that these teacher education students want lecturers tobe knowledgeable, enthusiastic, approachable, and friendly.They should possess sufficient communication and teachingskills and be able to choose the most suitable teaching methodfrom a variety of teaching tools. Respondents also mentionseveral values that they regard as relevant and desirable:security, well-being, satisfaction, self-esteem, hedonism, anduniversalism. A comparison of two different ladderingtechniques reveals that although the results of the two methodsare broadly similar, the personal laddering interviews producemore depth in understanding and significantly more respon-dents were able to reach the value level.

The analysis also reveals why lecturers should possess thedesired attributes: students predominately want to encountervaluable teaching experiences to be able to pass tests and to beprepared for their profession. Vocational aspects of their studiesmotivate students more than academic interest. Such knowledgeof student expectations should help lecturers design theirteaching programs. German lecturers in particular should paymore attention to vocational aspects in their teaching as theyregularly receive criticism for offering courses that are tootheory-laden (Voss, 2006). Thus, lecturers should include topicsin the curriculum that help students prepare for their profession.Lecturers could also provide assignments that are directlyrelevant to work, and use interesting and thought-provokingexamples and case studies from the “real world”. Lecturerscould also stress links between theory and practice more andinvite guest speakers who are willing to share valuableexperiences with students.

The introduction of tuition fees in Germany will probablystrengthen this “consumerist” approach and German universi-ties will have to offer value for money while lecturers will haveto emphasize the vocational relevance of their courses.Approaches for attracting new students such as a “studentsatisfaction guarantee” (Gremler and McCollough, 2002;McCollough and Gremler, 1999a,b) might be considered.Such a guarantee could make education appear more tangibleand signal the quality of the educational experience to currentand new students. McCollough and Gremler (1999a) find thatsatisfaction guarantees have a positive impact on studentconfidence in lecturers and they help set clear expectationsthat both students and lecturers will work hard. As apedagogical device, satisfaction guarantees set performancestandards and help increase the accountability of both studentsand lecturers. They also influence student evaluations oflecturers and courses positively without losing rigor in theclassroom (Gremler and McCollough, 2002). In this connec-

tion, the laddering technique helps lecturers identify how theyshould behave and which qualities they should possess from astudent's point of view; the satisfaction guarantee could coverthe desired teaching qualities. This study shows that theladdering technique is a useful tool in examining the issue ofservice quality in higher education and future research shouldbe able to develop further studies to test the application of theladdering technique in their investigations of service quality inhigher education.

References

Andreson Lee W. Teaching development in higher education as scholarlypractice: a reply to Rowland et al. turning academics into teachers. TeachHigh Educ 2000;5(1):23–31.

Bagozzi Richard P, Dabholkar Pratibha A. Consumer recycling goals and theireffect on decisions to recycle: a means–end chain analysis. Psychol Mark1994;11:313–40.

Banister Peter, Burman Erica, Parker Ian, TaylorMaye, Tindall Carol. Qualitativemethods in psychology — a research guide. Maidenhead: Open UniversityPress; 1994.

Bech-Larsen Tino, Nielsen Niels Asger. A comparison of five elicitationtechniques for elicitation of attributes of low involvement products. J EconPsychol 1999;20:315–41.

Bitner Mary J, Booms Bernard, Mohr Lois A. Critical service encounters: theemployee's viewpoint. J Mark 1994;58:95–106 [October].

Botschen Günther, Hemetsberger Andrea. Diagnosing means–end structures todetermine the degree of potential marketing program standardization. J BusRes 1998;42(2):151–9.

Botschen Günther, Thelen Eva M. Hard versus soft laddering: implications forappropriate use. In: Balderjahn Ingo, Mennicken Claudia, Vernette Eric,editors. New developments and approaches in consumer behaviour research.Stuttgart: Schäffer-Poeschel Verlag; 1998. p. 321–39.

Botschen Günther, Thelen Eva M, Pieters Rik. Using means–end structures forbenefit segmentation. Eur J Mark 1999;33(1/2):38–58.

Brown Nigel. What makes a good educator? The relevance of meta programmes.Assess Eval High Educ 2004;29(5):515–33.

Bryman Alan. Social research methods. 2nd ed. Oxford: Oxford UniversityPress; 2004.

Chang Tien M. Semantic memory: facts and models. Psychol Bull 1986;99:199–220.

Chebat Jean-Charles, Kollias Paul. The impact of empowerment on customercontact employees' roles in service organizations. J Serv Res 2000;3(1):66–81.

Christensen Glenn L, Olson Jerry C. Mapping consumers' mental models withZMET. Psychol Mark 2002;19(6):477–502.

Claeys Christel, Swinnen A, Abeele Piet Vanden. Consumers' means–endchains for “think” and “feel” products. Int J Res Mark 1995;12:193–208.

Claycomb Vincentia, Lengnick-Hall Cynthia A, Inks Lawrence W. Thecustomer as a productive resource: a pilot study and strategic implications.J Bus Strategies 2001;18(1):193–218.

Clewes Debbie. A student-centred conceptual model of service quality in highereducation. Qual High Educ 2003;9(1):69–85.

Deeter-Schmelz Dawn R, Kennedy Karen Norman, Goebel Daniel J.Understanding sales manager effectiveness — linking attributes to salesforce values. Ind Mark Manage 2002;31(7):617–26.

Gengler Charles E, Reynolds Thomas J. LADDERMAP: a software tool foranalyzing laddering data, version 5.4. 1993 [Computer software].

Gengler Charles E, Reynolds Thomas J. Consumer understanding andadvertising strategy: analysis and strategic translation of laddering data.J Advert Res 1995;35:19–33 [July/August].

Gengler Charles E, Klenosky David B, Mulvey Michael S. Improving the graphicrepresentation of means–end results. Int J Res Mark 1995;12:245–56.

Gengler Charles E, Mulvey Michael S, Oglethorpe Janet E. A means–endanalysis of mothers' infant feeding choices. J Public PolicyMark 1999;18(2):172–88.


Goldenberg Marni A, Klenosky David B, O'Leary Joseph T, Templin Thomas J.A means–end investigation of ropes course experiences. J Leis Res 2000;32(2):208–24.

Greimel-Fuhrmann Bettina, Geyer Alois. Students' evaluation of teachers andinstructional quality — analysis of relevant factors based on empiricalevaluation research. Assess Eval High Educ 2003;28(3):229–38.

Gremler Dwayne D, McColloughMichael A. Student satisfaction guarantees: anempirical examination of attitudes, antecedents, and consequences. J MarkEduc 2002;24:150–60 [August].

Grunert Klaus G, Grunert Suzanne C. Measuring subjective meaning structuresby the laddering method: theoretical considerations and methodologicalproblems. Int J Res Mark 1995;12:209–25.

Grunert Klaus G, Beckmann Suzanne C, Sørensen Elin. Means–end chains andladdering: an inventory of problems and an agenda for research. In:Reynolds Thomas J, Olson Jerry C, editors. Understanding consumerdecision making — the means–end approach to marketing and advertisingstrategy. Mahwah, NJ: Lawrence Erlbaum Associates; 2001. p. 63–90.

Guolla Michael. Assessing the teaching quality to student satisfactionrelationship: applied customer satisfaction research in the classroom.J Mark Theory Pract 1999;7(3):87–97.

Gutman Jonathan. A means–end chain model based on consumer categorizationprocesses. J Mark 1982;46:60–72 [Spring].

Hansen Ursula, Hennig-Thurau Thorsten, Wochnowski Holger. TEACH-Q: Einvalides und handhabbares Instrument zur Bewertung von Vorlesungen. In:Stauss Bernd, Balderjahn Ingo, Wimmer Frank, editors. Dienstleistungsor-ientierung in der universitären Ausbildung. Stuttgart: Schäffer-PoeschelVerlag; 2000. p. 311–45.

Hartline Michael D, Ferrell Orville C. The management of customer-contactservice employees: an empirical investigation. J Mark 1996;60:52–70[October].

Harvey Lee, Green Diana. Defining quality. Assess Eval High Educ 1993;18(1):9–34.

Herrmann Andreas. Nachfrageorientierte Produktgestaltung – Ein Ansatz aufBasis der “Means End” – Theorie. Wiesbaden: Gabler Verlag; 1996.

Hill Frances M. Managing service quality in higher education: the role of thestudent as primary consumer. Qual Assur Educ 1995;3(3):10–21.

Hill Yvonne, Lomas Laurie, MacGregor Janet. Students' perceptions of qualityin higher education. Qual Assur Educ 2003;11(1):15–20.

Howard John A. Consumer behavior: application and theory. New York, NY:McGraw-Hill; 1977.

Husbands Christopher T. Implications for the assessment of the teachingcompetence of staff in higher education of some correlates of students'evaluations of different teaching styles. Assess Eval High Educ 1998;23(2):117–39.

Joseph Mathew, Yakhou Mehenna, Stone George. An educational institution'squest for service quality: customers' perspective. Qual Assur Educ 2005;13(1):66–82.

LammersWilliam J, Murphy John J. A profile of teaching techniques used in theuniversity classroom. Act Lear High Educ 2002;3:54–67.

Lengnick-Hall Cynthia A, Claycomb Vincentia, Inks Lawrence W. Fromrecipient to contributor: examining customer roles and experiencedoutcomes. Eur J Mark 2000;34(3/4):359–83.

Marzo-Navarro Mercedes, Pedraja-Iglesias Marta, Rivera-Torres M Pillar.Measuring customer satisfaction in summer courses. Qual Assur Educ2005;13(1):53–65.

Mattila Anna S, Enz Cathy A. The role of emotions in service encounters. J ServRes 2002;4(4):268–77.

Mavondo Felix T, Tsarenko Yelena, Gabbott Mark. International and localstudent satisfaction: resources and capabilities perspective. J Mark HighEduc 2004;14(1):41–60.

McCollough Michael A, Gremler Dwayne D. Guaranteeing student satisfaction:an exercise in treating students as customers. J Mark Educ 1999a;21:118–30[August].

McColloughMichael A, Gremler Dwayne D. Student satisfaction guarantees: anempirical investigation of student and faculty attitudes. Mark Educ Rev1999b;9(2):53–64.

Norton John A, Reynolds Thomas J. The application of means–end theory inindustrial marketing. In: Reynolds Thomas J, Olson Jerry C, editors.

Understanding consumer decision making — the means–end approach tomarketing and advertising strategy. Mahwah, NJ: Lawrence ErlbaumAssociates; 2001. p. 319–34.

Oldfield Brenda M, Baron Steve. Student perceptions of service quality in a UKuniversity business and management faculty. Qual Assur Educ 2000;8(2):85–95.

Olson Jerry C, Reynolds Thomas J. Understanding consumers' cognitivestructures: implications for marketing strategy. In: Percy Larry, WoodsideArch G, editors. Advertising and consumer psychology. Lexington, MA:Lexington Books; 1983. p. 77–90.

Olson Jerry C, Reynolds Thomas J. The means–end approach to understandingconsumer decision making. In: Reynolds Thomas J, Olson Jerry C, editors.Understanding consumer decision making — the means–end approach tomarketing and advertising strategy. Mahwah, NJ: Lawrence ErlbaumAssociates; 2001. p. 3–23.

O'Neill Martin A, Palmer Adrian. Importance–performance analysis: a usefultool for directing continuous quality improvement in higher education. QualAssur Educ 2004;12(1):39–52.

O'Toole Dennis M, Spinelli Michael A, Wetzel James N. The important learningdimensions in the school of business: a survey of students and faculty.J Educ Bus 2000;75:338–42.

Patrick Jeff, Smart Roslyn. An empirical evaluation of teacher effectiveness: theemergence of three critical factors. Assess Eval High Educ 1998;23(2):165–78.

Pieters Rik, Baumgartner Hans, Allen Doug. A means–end chain approach toconsumer goal structures. Int J Res Mark 1995;12:227–44.

Pieters Rik, Botschen Günther, Thelen Eva. Customer desire expectations aboutservice employees: an analysis of hierarchical relations. Psychol Mark1998;15(8):755–73.

Pozo-Munoz Carmen, Rebolloso-Pacheco Enrique, Fernandez-Ramirez Balta-sar. The “ideal teacher”. Implications for student evaluation of teachereffectiveness. Assess Eval High Educ 2000;25(3):253–63.

Ramsden Paul. A performance indicator of teaching quality in higher education:the course experience questionnaire. Stud High Educ 1991;16(2):129–50.

Reynolds Thomas J, Gutman Jonathan. Laddering theory, method, analysis, andinterpretation. J Advert Res 1988;28:11–31 [February/March].

Reynolds Thomas J, Rochon John P. Consumer segmentation based oncognitive orientations: the Chemlawn case. In: Reynolds Thomas J, OlsonJerry C, editors. Understanding consumer decision making — the means–end approach to marketing and advertising strategy. Mahwah, NJ: LawrenceErlbaum Associates; 2001. p. 283–98.

Reynolds Thomas J, Gengler Charles E, Howard Daniel J. A means–endanalysis of brand persuasion through advertising. Int J Res Mark 1995;12:257–66.

Reynolds Thomas J, Rochon John P, Westberg Steven I. A means–end chainapproach to motivating the sales force: the Mary Kay strategy. In: ReynoldsThomas J,Olson JerryC, editors. Understanding consumer decisionmaking—the means–end approach to marketing and advertising strategy. Mahwah, NJ:Lawrence Erlbaum Associates; 2001. p. 269–82.

Rodie Amy Risch, Kleine Susan Schultz S. Customer participation in serviceproduction and delivery. In: Schwartz Teresa A, Iacobucci Dawn, editors.Handbook of services marketing and management. Thousand Oaks, CA:Sage Publications; 2000. p. 205–13.

Rolfe Heather. Students demands and expectations in an age of reduced financialsupport: the perspectives of lecturers in four English universities. J HighEduc Policy Manag 2002;24(2):171–82.

Rowley Jennifer. Beyond service quality dimensions in higher education andtowards a service contract. Qual Assur Educ 1997;5(1):7–14.

Sander Paul, Stevenson Keith, King Malcolm, Coates David. Universitystudents' expectations of teaching. Stud High Educ 2000;25(3):309–23.

Schertzer Clinton B, Schertzer Susan MB. Student satisfaction and retention: aconceptual model. J Mark High Educ 2004;14(1):79–91.

Schönpflug Wolfgang, Schönpflug Ute. Psychologie: Allgemeine Psychologieund ihre Verzweigungen in die Entwicklungs-, Persönlichkeits- undSozialpsychologie. München: Psychologische Verlags Union; 1995.

Shank Matthew D, Walker Mary, Hayes Thomas. Understanding professionalservice expectations: do we know what our students expect in a qualityeducation? J Prof Serv Mark 1995;13(1):71–83.


Shevlin Mark, Banyard Philip, Davies Mark, Griffiths Mark. The validity ofstudent evaluation of teaching in higher education: love me, love mylectures? Assess Eval High Educ 2000;25(4):397–405.

Singh Jagdip, Widing II Robert E. What occurs once consumers complain?— atheoretical model for understanding satisfaction/dissatisfaction outcomes forcomplaint responses. Eur J Mark 1991;25(5):30–46.

Strauss Anselm, Corbin Juliet M. Basics of qualitative research: techniques andprocedures for developing grounded theory. Thousand Oaks, CA: Sage;1998.

Telford Ronnie, Masson Ron. The congruence of quality values in highereducation. Qual Assur Educ 2005;13(2):107–19.

Van Rekom Johan, Wierenga Berend. Means–end relations: hierarchies ornetworks? An inquiry into the (a)symmetry of means–end relationsERIMreport series research in management. Rotterdam: Erasmus ResearchInstitute of Management; 2002.

Voss Rödiger. Der Einsatz des internen Hochschulmarketing zur Verbesserungder Lehrqualität an Hochschulen. In: Voss Rödiger, Gruber Thorsten,editors. Hochschulmarketing. Lohmar: Eul Verlag; 2006. p. 205–24.

Walker Beth A, Olson Jerry C. Means–end chains: connecting products withself. J Bus Res 1991;22(2):111–8.

Westermann Rainer, Spies Kordelia, Heise Elke, Wollburg-Claar Stefan.Bewertung von Lehrveranstaltungen und Studienbedingungen durchStudierende: Theorieorientierte Entwicklung von Fragebögen. EmpirPädagog 1998;12:133–66.

Wiers-Jenssen Jeannecke, Stensaker Bjørn, Grogaard Jens B. Student satisfac-tion: towards an empirical deconstruction of the concept. Qual High Educ2002;8(2):183–95.

Willcoxson L. The impact of academics' learning and teaching preferences ontheir teaching practice: a pilot study. Stud High Educ 1998;23(1):59–70.

Yim Chi K, Gu Flora F, Chan Kimmy W, Tse David K. Justice-based servicerecovery expectations: measurement and antecedents. J Consum SatisfDissatisf Complain Behav 2003;16:36–52.

Young Shirley, Feigin Barbara. Using the benefit chain for improved strategyformulation. J Mark 1975;39:72–4 [July].

Zeithaml Valarie A, Parasuraman A, Berry Leonard L. Delivering qualityservice: balancing customer perceptions and expectations. New York, NY:The Free Press; 1990.

Zeithaml Valarie A, Berry Leonard L, Parasuraman A. The nature anddeterminants of customer expectations of services. J Acad Mark Sci 1993;21(1):1–12.