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© 2011 Macmillan Publishers Ltd. 1751-8040 Place Branding and Public Diplomacy Vol. 7, 1, 50–63www.palgrave-journals.com/pb/

Correspondence: C é line Brandt University of Liege, Boulevard du Rectorat 7 (B31), 4000 Li è ge, Belgium; Rue des Vennes 364, 4020 Li è ge, Belgium

INTRODUCTION Internal decline cycles, as well as external shocks, have caused certain regions and cities to go into decline. Forces such as rapid technological changes, global competition and intergovernmental power shifts often exacerbate the situation ( Kotler et al , 1993 ). In Western Europe, most of the coal and steel industries have disappeared. Affected regions must now focus on

revitalization. Owing to this decreasing attractiveness, interest in city marketing and city promotion is growing not only from practitioners, but from academics as well.

Several authors investigated the dimensions of attitudes toward a city for different segments ( Kotler et al , 1993 ; Walmsley and Young, 1998 ; Gallarza et al , 2001 ; Foley and Fahy, 2004 ; Hankinson, 2004a, 2005 ). Other authors

Students ’ Corner

City branding: A brand concept map analysis of a university town Received (in revised form): 7 th December 2010

C é line Brandt is Assistant Professor in the Marketing Department of HEC, Management School of the University of Liege. Her research focuses are in the areas of product and corporate brand reputation, branding, networks in marketing and consumer behavior. Her doctoral thesis deals with the measurement of individual Brand Image Perception and Brand Reputation using Associative Networks.

Charles Pahud de Mortanges is a Professor of marketing at the HEC School of Management of the University of Liege (Belgium). His current research interests include products and services branding, corporate branding, brand equity and brand valuation, international marketing, and return on marketing investments.

ABSTRACT The aims of this research are (1) to assess the relative saliency of image attributes associated with history, heritage and culture in shaping the perceptions of students choosing a university town and (2) to investigate whether brand concept mapping (BCM) is applicable to cities. The city brand image is captured through Zaltman ’ s Metaphor Elicitation Technique, BCM and importance-performance ratings. The authors identifi ed six categories of criteria used by students when selecting a university town. In applying the results to Liege, a Belgian university town, the authors showed that Liege is recognized for its nightlife, its young population and its historical heritage. This article proposes a useful framework for city councils to assess how to compare the perception of different segments regarding cities; how to improve the city brand image; how to compare different university towns; and how to attract students. Finally, the research validates earlier studies on BCM, confi rms the improvement of the methodology and widens its applications to city brands. Place Branding and Public Diplomacy (2011) 7, 50 – 63. doi: 10.1057/pb.2010.37

Keywords: brand concept map ; city branding ; brand perception ; brand attributes ; brand image ; brand identity

© 2011 Macmillan Publishers Ltd. 1751-8040 Place Branding and Public Diplomacy Vol. 7, 1, 50–63 51

A Brand Concept Map Analysis of a University Town

( Veloutsou et al , 2004 ; Briggs, 2006 ; Holdsworth and Nind, 2006 ), as well as non-scientifi c publications such as the Financial Times, Business Week, The Wall Street Journal and The Economist , investigated the expected attributes considered by prospective students when choosing the university itself. However, research on the dimensions of attitudes of students when selecting a university town is almost non-existent, despite the attractiveness of this young, heterogeneous and educated segment.

In the area of branding, a growing stream of research covers quantitative brand mapping techniques to study brand identity and how the information about the brand is stored in the consumers ’ long-term memory ( Henderson et al , 1999 ; Roedder John et al , 2005 ). Researchers are developing techniques that are easy to use for brand managers. However, brand mapping and its applications are still in their infancy. Brand Concept Maps (BCM) have, so far, not been applied to city branding, where the competitive context creates a real need to defi ne brand identities.

Therefore, our research questions are: (1) What are the decisive criteria for students choosing a university town? And (2) Is the classical BCM technique applicable to city marketing?

On the basis of the results, practitioners will be able to assess how to attract students, how to improve the city brand image, how to compare different university towns and how to compare the perception of different segments regarding cities. Finally, the research validates earlier studies on BCM and confi rms the methodology improvement. Furthermore, it enlarges the scope of BCM ’ s applications and demonstrates the reliability and validity of the method in this particular area of branding. As a case, the authors will study the city of Liege (Belgium) and identify how students from the University of Liege perceive the city as a university town differentiating between local and foreign students.

LITERATURE REVIEW After an extensive review of the literature on city marketing, the authors will focus on city identity

and the different expectations of different segments regarding the benefi ts a city offers. Finally, authors will examine previous research on the dimensions of beliefs considered by prospective students when choosing the university itself.

Two different approaches to city marketing exist within the literature ( Bradley et al , 2002 ). The fi rst approach links urban revitalization to political and economical decisions ( Gotham, 2001 ; Nelson et al , 2004 ; Larsen, 2005 ). The second approach focuses on marketing tools and strategies that have been adopted and their relative success. The latter movement covers the challenges of how to attract tourists ( Hankinson, 2004a, 2005 ; Pike, 2005 ); how to use sporting events to develop the brand image ( Taylor, 2005 ; Xing and Chalip, 2006 ); how to capitalize on culture ( Jones and Wilks-Heeg, 2004 ; Richards and Wilson, 2004 ); which are the best practices used in renowned city marketing campaigns ( Hall, 2002 ; Morgan et al , 2004 ; Prebensen, 2005 ); and how certain marketing tools can be employed for effectively marketing the places ( Olins, 2002 ; Caldwell and Freire, 2004 ; Tasci and Kozak, 2006 ).

IDENTITY AND IMAGE OF THE PLACE Kotler and Andreasen (1991, p. 102) defi ne the image of a place as: ‘ a sum of beliefs, ideas, impressions that a people have of a place, they represent a simplifi cation of a large number of associations connected with the place ’ . Burmann and Meffert (2005) differentiate between brand image and brand identity. Whereas identity-based city branding focuses on internal groups of a city (local residents, politicians or entrepreneurs), brand-image analysis explores how external groups perceive the city (tourists, potential investors or residents).

Stakeholders (residents, tourists, investors, students) associate a brand, including places, with particular features, logos, usage situations and so on. Typically, researchers capture the beliefs about a brand through the measurement of brand attributes on a Semantic Differential Scale, Likert scale or Guttman scale ( Kardes, 2002 ) or using multidimensional scaling. These

© 2011 Macmillan Publishers Ltd. 1751-8040 Place Branding and Public Diplomacy Vol. 7, 1, 50–6352

Brandt and Pahud de Mortanges

techniques are very helpful in understanding how consumers perceive brands and which dimensions underlie these perceptions. However, if such a technique shows how the brand performs on these attributes, it never shows which attributes are directly or indirectly linked to the brand, the intensity of the links and which associations are interdependent ( Roedder John et al , 2005 ). Furthermore, understanding brand equity implies the identifi cation of strong, favorable and unique associations in the minds of consumers. Our methodology, namely BCM, solves these problems.

A BCM is a graphical representation of a brand and its associations ( Roedder John et al , 2005 ). A BCM not only identifi es essential brand associations, but also conveys how these associations are connected to the brand and to each other ( Roedder John et al , 2005 ). The best-known method designed to capture brand image and identity is the Zaltman Metaphor Elicitation Technique (ZMET) ( Higie Coulter and Zaltman, 1994 ), combining visual and narrative aspects. The method consists of three steps, namely attributes elicitation, mapping and aggregation. During the elicitation stage, the researchers select 15 persons (as we reached theoretical saturation after the fi fteenth interview) and introduce the topic. Then, these participants collect 12 pictures about the topic to prepare 2-hour interviews each, which will take place 10 days later. During this interview, interviewers ask participants to tell ‘ stories ’ about the picture. As a result, the interviewers write down the constructs using the repertory grid method, which is used to evaluate the similarities and differences between constructs ( Hankinson, 2004b ), and laddering process, which allows researchers to gather and interpret information in a structured manner ( De Ruyter and Norbert, 2004 ). During the mapping stage, participants create a map illustrating the connections among important constructs. Finally, during the aggregation stage, the interviewers codify the data and choose the constructs according to how frequently they are mentioned. ZMET ’ s main strength is its ability to reveal personal feelings, irrationality,

illogical behavior and repressed attitudes, which are hard to obtain through conventional interviewing techniques ( Pellemans, 1999 ). However, the ZMET method is very labor-intensive: interviewers must be thoroughly trained in cognitive psychology, while participants must be willing and able to participate in two interviews and in the creation of the BCM.

Roedder John et al (2005) developed a quantitative method that is easier to administer, with less labor-intensive processes in the elicitation and aggregation stage, and procedures that do not require specialized expertise and training for interviewers. This approach enables researchers to capitalize on existing brand research (using brand attributes coming from past research instead of a classical elicitation stage) and allows data collection from larger sample sizes. The main weakness of those methods (compared with ZMET), however, is the emphasis on the conscious parts of brand evaluation. Therefore, the authors suggest combining the strengths of the quantitative methods with the elicitation stage of ZMET, which enables the researcher to elicit ‘ hidden ’ , unconscious information as well.

MULTIPLE STAKEHOLDERS As ‘ Place ’ has a multiplicity of stakeholder groups ( Vishwas et al , 2007 ), several authors covered the components of destination brand image (and identity) from different perspectives: business tourists ( Hankinson, 2005 ), leisure tourists ( Gallarza et al , 2001 ; Kozak, 2003 ; Hankinson, 2004a ), local residents ( Kotler et al , 1993 ), companies and investors ( Kotler et al , 1993 ; Kotler and Gertner, 2002 ), and event organizers ( Kotler et al , 1993 ; Bonn et al , 2005 ; Hankinson, 2005 ). However, no research exists on the dimensions of beliefs of students choosing a university town.

OUR STUDIES First, to investigate the dimensions of beliefs when selecting a university town (study 1), the authors will use ZMET. Second, they will apply ZMET, BCM and conventional measures of



importance-performance to the city of Liege (Belgium) to show how Liege is perceived by a population of students, and to validate the BCM method in the area of city branding (study 2). Finally, they will show the differences in perceptions between local and foreign students.

Study 1: Dimensions of beliefs The fi rst step of this study is to show the dimensions of beliefs of students selecting a university town. Researchers ask 35 local and foreign undergraduate students to collect 12 pictures that express their notion of a perfect university town. As we reach theoretical saturation after the fi fteenth interview, this number should be suffi cient ( Zaltman and Coulter, 1995 ). Then, the participants explain the reasons why they selected them. From these justifi cations, the interviewer draws the list of brand attributes by assigning abstract associations to consumer quotes. The following example illustrates this process:

Respondent 10: ‘ I choose this picture of the City Parade because there are lots of parties in Li è ge ’ .

Attribute: caf é ’ s, nightlife and parties. Researchers thus obtain a defi nitive list of 25

attributes grouped in six dimensions as shown in Table 1 : the economy, the physical environment, activities and facilities, brand and reputation, people, and accessibility.

Hankinson (2005) identifi ed fi ve dimensions of beliefs for leisure tourists (same as for the students except for accessibility) and eight clusters for business tourists (same as for the students, plus size and social facilities).

Study 2: The case of Liege (Belgium) Authors chose that city brand because it is a well-known city in Belgium with a wide variety of associations. Liege is the third largest city located in the French-speaking part of Belgium. Cultural life in Liege is particularly rich with 10 theaters, the Royal Opera of Wallonia, a Symphony Orchestra, some 30 cinemas, dozens of art galleries and museums, as well as many public libraries and other cultural

establishments. The city center is well developed, with a multitude of shops, restaurants and caf é s for all tastes and budgets. Students often prefer the Carr é , a network of backstreets known for its vibrant nightlife.

Since the nineteenth century, the economy of the region has been based on coal mines, steelworks and metallurgy plants. Now most of these industries have disappeared. However, the region is currently experiencing a (although slow) recovery. Numerous enterprises have set up business in the region (for example, biotech), whereas remaining older enterprises are undergoing a transformation.

Since November 2003, the city council has embarked on a so-called ‘ City Project ’ . This project has been developed jointly by the local

Table 1 : Dimensions of beliefs

Economy Cheap public services, special prices for students Successful companies, partnership with the university Physical environment Cleanliness Parks, greenery Safety, police presence Activities and facilities Access to news, newsstands Research, laboratory, teaching hospital (CHU) Architecture, history, folklore Caf é ’s, nightlife, parties, meeting place Culture, arts, theater, concerts, museums, cinema Ease in fi nding apartments, single entity for housing Large choice of restaurant, healthy food, fast food Large panel of schools Sidewalks for pedestrians Sports facilities Supermarkets, shops Technologies, WIFI, cybercaf é , computers, printers,

scanners Brand and reputation Famous university, good brand image, recognized as a

business park of the city International city, knowledge of English, international

reputation People A lot of students, young population Accessibility Centralized campus Centralized library Infrastructure for bicycles, bicycle paths Parking Public transportation



authorities and the city ’ s residents. As part of this collective approach, Liege ’ s population was asked what they thought were important issues regarding their city and their suggestions. For example, residents expect improved cleanliness, increased police visibility and better public transportation.

The city council took important measures to offer more public services and protect the environment. It also developed a ‘ mobility plan ’ , to enhance public transportation, improve the accessibility of the city, and develop infrastructure for bicycles and pedestrians. Another project is to create a cultural center, increase tourism, reinforce the brand focusing on history, culture and a central position in Europe. These initiatives are aimed mostly at businesses and residents. However, Liege is also an important university town.

Created in 1817, the University of Liege is the only public university in the French-speaking part of Belgium, offering a comprehensive range of university programs at the bachelor, master and PhD levels. Of the 17 000 students, 18 per cent come from 70 different countries. The university is a center of excellence in aeronautics, astronomy, neurology, microbiology and biotechnology. Although the administrative services are located in the city center, the main university campus consists of a large (5000 acre) wooded area south of the city.

RESULTS FOR LIEGE AS A UNIVERSITY TOWN

Methodology Interviewers ask participants to create individual brand maps based on their perception of Liege as a university town. The target population is defi ned as persons studying in Liege. Taking into account the exploratory nature of the study, authors use a convenience sampling method. The sample consists of fi rst-year master ’ s students in business administration, with 60 men and 70 women in the age group of 19 – 33 years (100 Belgian students and 30 foreign students). Interviewers provide

participants with cards that contain brand attributes / brand associations and ask them to answer in the fi rst step the following question: ‘ Considering the brand and the associations listed on the cards, what comes to mind when you think about this brand? ’ They are allowed to select as many cards as they wish.

The associations are selected through several pre-tests: the elicitation stage of ZMET is used to elicit personal feelings, irrationality, illogical behavior and repressed attitudes. Thirty-fi ve local and foreign students participate in this phase of the study. The results are combined with other sources, namely the list of decisive attributes for a university town and statements on Liege from various sources, including university promotional material. Interviewers obtain a defi nitive list of 25 attributes in total for the city of Liege (same attributes as Table 1 ).

After the cards selection, the researchers show the 130 participants one BCM for another brand as an example to explain the construction process, and especially the different links that could appear. Considering that to our knowledge, no other study has applied BCM to cities, we used a BCM for the Volkswagen Beetle. The participants learn that some attributes are directly linked to the brand (like ‘ German car ’ , or ‘ easy to park ’ ), whereas others are linked to each other (like ‘ lime green or silver ’ , meaning that because of their lime green and silver colors Volkswagen Beetles have neat colors). Furthermore, BCMs contain different types of links between the brand and the attributes, as well as between attributes themselves (single, double or triple links), indicating the strength of the associations. After this ‘ learning process ’ , the participants create a personal concept map, using the pre-selected associations / cards, a blank poster containing the brand name in the center and simple, double and triple lines to connect the cards (all provided by the researchers). Participants stick the cards with the attributes on the poster and connect them with simple, double and triple links. Interviewers give participants all the time they needed, with the Volkswagen Beetle BCM next to them as an example.



The 130 students all report that they understand the procedure and have no problem following it. In the end, the interviewers ask the respondent to describe prior experiences with the brand (user or non-user), and to provide them with his / her demographics. The BCM construction and interviews last 15 – 30 min on average.

In a second step, the researchers have to aggregate the individual BCMs in order to show the general perception of the city brand. Figure 1 provides you with the aggregated Liege BCM as a university town.

As shown in Table 2 , two independent coders (inter-coder agreement: 98 per cent) code:

the presence or the absence of each of the 25 attributes; the types of links between associations and between the brand and the associations (single, double and triple); the level at which each attribute was placed on the map (1 means directly linked to the brand, 2 means linked to an attribute that is linked to the brand); and the associations linked above and below each brand association on the BCM.

First, researchers have to decide which attributes are ‘ core ’ in the aggregated BCM using the following measures: ‘ the frequency of

•

•

•

•

mention ’ and ‘ the number of interconnections ’ . The researchers calculate the fi rst measure by dividing the number of times an attribute is cited in the individual BCM by the total amount of individual BCM. The latter measure counts the number of times the attribute is linked to all the other associations. Following many content studies of brand attributes, beliefs and values ( Roedder John et al , 2005 ), interviewers use a 50 per cent cut-off criterion to decide whether or not one attribute should appear on the aggregated BCM. The borderline frequencies ( > 45 per cent) are included, resulting in a brand map containing seven core brand associations.

Second, the researchers have to decide which of the core associations should be directly linked to the brand. Two measures are used, namely the frequency and the ratio of fi rst-order mentioning. The fi rst measures the number of times an association is directly linked to the brand. The second is the frequency of fi rst-order mentions divided by the frequency of total mentioning. Finally, the type of position, superordinate or subordinate, indicates whether most linked associations appear below this association (superordinate position) on the map or above this association (subordinate position). First-order attributes are those whose frequency of fi rst-order mention is higher than 50 per cent, and whose number of

Liège as aUniversity

Town

History (Charlemagne), Folklore(Tchantche), Historic Buildings

Café’s (the “Carré”), Nightlife, Parties

Dirt, Graffiti, Waste

Arts and Culture: Theater,Concerts, Museums,Cinema, Aquarium

Supermarkets, Shops

Famous University,good Brand Image

DecentralizedCampus, far from

the Center

A lot ofStudents, Young

Population

Large number of schools

No safety

Figure 1 : Consensus brand map for Liege as a university town.



superordinate connections is higher than the number of subordinate connections.

The third step involves an analysis of the associations ’ links in order to place the remaining core brand attributes. Therefore, the frequency of links between associations is examined (for example: ‘ A lot of students ’ was frequently connected above ‘ Famous university ’ ). Interviewers incorporate certain non-core brand associations that are frequently linked to core associations to show which non-core brand associations drive consumer perception of core associations. These non-core brand associations are linked to core associations, taking the average link used in the individual brand maps.

BCM represents how the information about the brand is stored in consumer memory. In the spread of activation theory ( Anderson,

1983 ), Lorch (1982) shows that the activation of a concept node is a function of the length of the associative pathway between the node and the source of activation (fi rst-order association, second-order association or third-order association), and Reder and Anderson (1980) show that the activation is a function of the strength of that pathway (single, double or triple link). The three fi rst-order core attributes that are the most strongly linked to Liege are: the young population, the history and folklore and the nightlife. As fi rst-order core attributes, the map also shows two positive attributes (shops, arts and culture) and one negative attribute (dirt). As second-order core attributes, the famous university is a positive characteristic, whereas the campus location (far from the city center) is negatively perceived. Finally, as non-core brand attributes, students perceive

Table 2 : Codifi cation of the individual brand maps

History Supermarkets Dirt

Presence / absence of the 32 attributes Individual maps … 1 1 1 0 2 1 0 0 3 0 1 1 4 1 0 1 5 0 0 0 … Type of links for each individual map Attributes … Li è ge 3 2 0 History — 1 0 Supermarkets — — 0 Dirt — — — … The level at which each attribute was placed on the map Individual maps … Map 1 1 1 0 Map 2 2 0 0 Map 3 0 1 1 Map 4 1 0 3 Map 5 0 0 0 … Subordinate or superordinate position Individual maps … 1 sup sup 0 2 sub 0 0 3 0 sup sup 4 1 0 sub 5 0 0 0 …



Liege as having a large number of schools, while the dirtiness of certain parts of the city causes a feeling of insecurity. Comparing the city brand perception with the dimensions of beliefs, the authors conclude that Liege has several strengths in terms of the activities and facilities (caf é s, history, markets, arts, large number of schools), brand and reputation (famous university) and people (a lot of students). In contrast, the accessibility of the city (decentralized campus) and the physical environment (cleanliness, safety) are criticized, while no economical aspect appears on the map.

In addition, to assess the convergent validity of our method with classical rating measures, interviewers ask the 130 students to complete a structured questionnaire by rating the expected level of all the attributes listed on a 7-point scale, the importance of the attributes and Liege ’ s performance on these attributes. Table 3 also shows the difference between the expected level and the performance, as well as a t -test, assessing whether the means of the two measurements are statistically different from each other.

For some attributes, the performance is not statistically different from the expected level. Indeed, students are satisfi ed with the nightlife and caf é s, the large number of schools, research, the young population, the variety of supermarkets and restaurants and the rich history of Liege. Five of these seven attributes are also present in the brand map, suggesting the convergence of the two techniques. With regard to the other attributes, the authorities should try to improve them in order to reach the expected level (affordable public services, centralized campus, cleanliness or infrastructure for bicycles).

Figure 2 shows the classifi cation of the attributes that are most important from a student point of view and the difference between performance and expected level.

On the basis of Figure 2 and Table 3 , the authors suggest that technology infrastructure should fi rst be improved (WIFI, cyber caf é s, computers, scanners, photocopy centers and so on). Next, public transportation and other

public services require attention, as well as the international image of the University. However, the infrastructure for bicycles, the lack of parking spaces and sidewalks for pedestrians were not perceived to be important problems from a students ’ perspective. Some negative attributes associated with the Liege brand also need to be improved. However, in the case of Liege as a brand, many of the brand attributes elicited, such as technology or the international image of the university, are beyond the control of the authorities.

To test the reliability of our aggregation, all individual BCMs are randomly split into two groups, resulting in an aggregate map for each of the groups. The authors evaluate the degree of similarity between both consensus maps measuring the associations in terms of the attributes, the core attributes and the fi rst-link attributes of the two BCMs (see Figure 3 ). Nine attributes are present on both aggregated BCMs. Comparing both brand maps based on the presence of each of the possible 32 brand associations, the authors obtain a signifi cant chi-square (Chi-square = 21.09; P = 0.00 < 0.05; N = 25), indicating a strong association between the two brand maps (Phi = 0.92 > 0.7). The fi rst aggregate brand map has seven core attributes, while the second one has only nine. Comparing both brand maps based on the presence of each of the possible 32 brand associations as core associations, the researchers obtain a signifi cant chi-square (Chi-square = 7.284; P = 0.00 < 0.05; N = 25), indicating a strong association between the two brand maps (Phi = 0.83 > 0.7). Using a fi rst-link association criterion, they also obtain a signifi cant chi-square (Chi-square = 20.30; P = 0.00 < 0.05; N = 25) and thus a strong association between the two brand maps (Phi = 0.90 > 0.7). The high degree of similarity between both brand maps signifi es a high reliability of the method.

To test the nomological validity of the method, the authors split the individual brand maps into two categories that should differ in a predictable way (local students and foreign students). As the aggregated map for the ‘ local ’



group has a more complex structure with more brand associations (eight core brand attributes for the ‘ local ’ and seven for the ‘ foreign students), more interconnections between associations and more double links ( Roedder John et al , 2005 ) than the non-user-group map, we can conclude that there is a high level of nomological validity, as shown in Figure 3 and Table 4 .

Then, the researchers compare the features of the consensus brand map with the performance rating scale data to assess convergent validity. First, the authors examine the correlation between the frequency of mention of each

brand association and the performance rating. This results in a strong correlation of 0.69 ( P < 0.01; N = 25). Then, they develop a second frequency measure to assess how valid the placement of brand associations on the brand map was. Each brand association is weighted, depending on the level at which it is included in the map (direct link: weight 4, second-order link: weight 3 and so on). The authors obtain a signifi cant strong correlation of 0.69 ( P < 0.01; N = 25) with the performance rating. The authors assess the validity of the links by measuring the correlation (single, double or triple). They give a rating of 3 to an association

Table 3 : Ranking of the 25 criteria, expected level, performance and t -tests

Attributes

Ranking

Expected level

SD

Performance

SD

EL-P

t-value

sig

A lot of students, young population

1 6.4 1.2 5.5 1.3 0.9 − 2.35 0.2

Public transportation 2 6 1.1 4.8 1.5 1.2 − 7.64 0 Technologies, WIFI, cybercaf é ,

computers, printers, scanners 3 6 1.1 5 1.4 1 − 7.65 0

Cheap public services, special prices for students

4 5.9 1.1 3.7 1.5 2.2 − 14.20 0

Caf é ’s, nightlife, parties, meeting place

5 5.9 1.1 5.8 1.4 0 − 0.36 0.72

Famous university, good brand image

6 5.9 1.3 4.5 1.5 1.3 − 9.50 0

Centralized campus 7 5.6 4.6 3.4 1.7 2.2 − 4.89 0 Successful companies,

partnership with the university 8 5.6 1.3 4.7 1.3 0.9 − 6.99 0

International city, knowledge of English, international reputation

9 5.5 1.4 3.7 1.5 1.8 − 10.96 0

Sports, swimming pool, RCAE 10 5.4 1.3 4.9 1.4 0.5 − 3.44 0.00 Parks, greenery 11 5.3 1.3 4.3 1.4 1 − 6.1 0 Parking 12 5.2 1.6 3.8 1.7 1.5 − 7.04 0 Research, laboratory, teaching

hospital (CHU) 13 5.2 1.5 5.2 1.5 0 − 0.17 0.87

Ease in fi nding apartments, single entity for housing

14 5.2 1.4 3.8 1.5 1.4 − 8.36 0

Access to news, newsstands 15 5.2 1.4 4.3 1.1 0.9 − 6.46 0 Safety, police presence 16 5.1 1.4 3.8 1.4 1.3 − 7.13 0 Large number of schools 17 5.1 1.6 5.3 1.3 — 1.29 0.20 Supermarkets, shops 18 5.1 1.3 4.9 1.4 0.1 − 0.94 0.35 Culture, arts, theater, concerts,

museums, cinema 19 5.1 1.3 4.7 1.2 0.4 − 2.88 0.01

Cleanliness 20 5 1.5 2.7 1.4 2.3 − 1.25 0 Sidewalks for pedestrians 21 4.8 1.5 4 1.4 0.8 − 4.77 0 Centralized library 22 4.7 1.5 4.1 1.3 0.7 − 4.17 0 Large choice of restaurant,

healthy food, fast food 23 4.6 1.5 4.8 1.4 — 0.79 0.43

History, folklore, historic buildings

24 4.5 1.4 4.7 1.2 — 1.22 0.23

Infrastructure for bicycles, bicycle paths

25 4.1 1.6 2.6 1.4 1.6 − 7.75 0

In bold: No statistical signifi cance between expectancies and performance for � = 0.05.



linked with a triple link, a rating of 2 to an association linked with a double link and so on. Then, the authors compare this weighted frequency to the rating scale and obtained a signifi cant and moderate correlation of 0.49 ( P < 0.01; N = 25).

The comparison between these two techniques confi rms validity for the elicitation, mapping stage (level and type of links) and the aggregation procedure. Despite the different goals of the two techniques, they lead to the same results. However, the authors demonstrated that even if some attributes perform well, this does not automatically lead to the inclusion of the attribute in the BCM (such as parks, sports and successful companies). This suggests that common

rating approaches should be complemented by BCM approaches.

DISCUSSION, CONCLUSIONS AND IMPLICATIONS FOR BRAND MANAGEMENT University towns are currently under pressure to attract local and international students, and to improve their retention rate. From a managerial point of view, the fi rst study identifi es the dimensions of beliefs when students select a place to study and compares them with other decisive criteria for other segments. The authors grouped the 25 most important attributes in six clusters, based on content analysis. These six clusters are shown in Table 1 .

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

Infrastructure for bicycles, Bicycle paths 3.71

Research, laboratory, teaching hospital (CHU) 3.91

large number of schools 4.12

Parking 4.28

Sidewalks for pedestrians 4.33

History, folklore, historic buildings 4.40

Access to news, newsstands 4.54

Safety, Police presence 4.64

Successful companies, partnership with the university 4.65

Large choice of restaurant, healthy food, fast food 4.72

Centralized library 4.73

Culture, arts, theatre, concerts, museums, cinema 4.73

Cleanliness 4.79

A lot of students, young population 4.92

Supermarkets, shops 5.01

Sports, swimming pool, RCAE 5.12

Parks, greenery 5.14

Ease in finding apartments, single entity for housing 5.35

International city, knowledge of English, international reputation 5.40

Centralized campus 5.54

Famous university, good brand image 5.59

Cheap public services, special prices for students 5.63

Café's, night life, parties, meeting place 5.81

Public transportation 5.87

Technologies, WIFI, cybercafé, computers, printers, scanners 5.97

Att

rib

utes

im

po

rtan

ce o

n a

7-p

oin

t sc

ale

Performance on a 7-point scale Expected level on a 7-point scale

Figure 2 : Importance-expectation-performance graph.



From a theoretical point of view, this article validates earlier studies on BCMs and demonstrates the utility and benefi ts of the method, including the structure in the elicitation procedure, the standardized responses and the ease of use for participants in the study and the aggregation procedure. Furthermore, this research widens BCM applications to cities in addition to services ( Roedder John et al , 2005 ) and consumer goods. Methodologically, this article confi rms the improvement of the methodology when using ZMET in the elicitation stage of BCM. Finally, the importance of research and auditing having been highlighted in most of the city marketing literature, this article broadens the range of BCM applications to a diagnostic tool to compare different investments.

Then, we studied a case to assess how to use our methodology to improve the city brand image. In our case study, the main features included in the BCM are identifi ed, and researchers can compare them with the desired

features described in Liege ’ s City Projects. The three fi rst-order core attributes that are the most strongly linked to Liege are: the ‘ young population ’ , the ‘ history and folklore ’ and the ‘ nightlife ’ . As fi rst-order core attributes, the map also shows two positive attributes ( ‘ shops ’ , ‘ arts and culture ’ ) and one negative attribute ( ‘ dirt ’ ). As second-order core attributes, the ‘ famous university ’ is a positive characteristic, while the campus location far from the city center is negatively perceived. Finally, as non-core brand attributes, students perceive Liege as having a large number of schools and faculties, while the dirtiness of certain parts of the city causes a feeling of insecurity.

From a managerial point of view, the authors suggest investing in high-technology infrastructures fi rst (for example WIFI). Next, public transportation and other public services require attention, as well as the international image of the University. However, students did not perceive the infrastructure for bicycles, the lack of parking spaces and sidewalks for


DecentralizedCampus, far fromthe Center

Local students

Dirt, Graffiti,Waste

Large number of schools


Town

A lot ofStudents,YoungPopulation

No Safety

Café’s (the“Carré”),Night-life,Parties

Arts and Culture: Theater,Concerts, Museums,Cinema, Aquarium Supermarkets

and shopsFamous University

Research


DecentralizedCampus, farfrom the Center

Half1

Dirt, graffiti,Waste


Town

A lot ofStudents,

YoungPopulation

No Safety

Café’s (the“Carré”), Nightlife, Parties

Arts and Culture:Theater, Concerts,Museums, Cinema,

Aquarium

Supermarketsand shops

Large numberof schools

Half 2


Decentralized Campus,far from the Center

Dirt, graffiti, Waste

FamousUniversity, goodBrand Image

A lot ofStudents,

YoungPopulation

Liège as a University

TownNo safety

Café’s (the “Carré”), Nightlife, Parties

Arts and Culture: Theater,Concerts, Museums,Cinema, Aquarium

Supermarkets, ShopsLarge number of schools

FamousUniversity, good

Brand Image

Foreign students

International city

Dirt, Graffiti, WasteA lot of

Students,Young

Population


Town

History (Charlemagne), Folklore (Tchantche),

Historic Buildings

Café’s (the “Carré”),Night life, Parties

Arts and Culture: Theater, Concerts,

Museums, Cinema, Aquarium

Public transportation

Figure 3 : Split-half reliability test and nomological validity test.



pedestrians as being important problems. Authorities also need to improve some negative attributes associated with the Liege brand (dirtiness, lack of safety). Addressing some of these problems is already part of the city project or in the plan to attract businesses, except for the ‘ nightlife ’ , the ‘ young population ’ , the ‘ shops ’ , the ‘ famous university ’ and the ‘ decentralized campus ’ . Therefore, the reconciliation of the preferences of the students with the preferences of other specifi c social and business groups within the city will be straightforward. Another observation is that some attributes are within the jurisdiction of the authorities, such as safety, culture or cleanliness, whereas other attributes are outside the realm of control of the authorities, such as the decentralized campus, or the town ’ s history.

Another objective was to determine whether brand perceptions are different when the participants ’ country of origin is different, as the authors created a brand map for local students and a second one for foreign students. For both groups, Liege is a city with a young population, a lot of caf é s and vibrant nightlife, supermarkets, arts and culture. The historical meaning of Liege has greater signifi cance for local students. Local and foreign students acknowledge the large number of schools. Contrary to local students, foreign students

perceive Liege as being a foreign city with a famous university and good public transportation. Local students perceive the dirtiness and insecure aspect of the city as being more directly linked to the city than foreign students.

From a methodological point of view, the BCM approach is a helpful analytical tool to understand how people perceive the city as a brand. Contrary to other mapping techniques ( Higie Coulter and Zaltman, 1994 ; Henderson et al , 1998 ; Joiner, 1998 ), BCM has proved to be valid, reliable and relatively easy to apply. Owing to its link with brand equity, BCM is an indispensable tool for brand managers to identify associations and linkages that make up the brand perception. Taking into account the differences in preferences allows managers to distinguish different brand perceptions for different subgroups of consumers, or different segments. After appropriate benchmarking, or making comparisons with the BCM of other university towns, a decision can be made to maintain or modify the city brand ’ s core identity. This change could be made by improving the basic city services, utilizing greater media coverage, managing the negative image, better integrating marketing communication, or leveraging secondary associations to build brand equity ( Keller, 2003 ).

LIMITATIONS AND FUTURE RESEARCH DIRECTIONS Future research on the branding of university towns may examine the attribute requirements and the university town perception of specifi c groups of students, such as men versus women, different age groups or specifi c countries of origin (instead of foreign and local students). Adding some control variables such as a limited budget or the proximity of the university town, which could affect the perception, could be useful. The authors would also suggest comparing students ’ perception of their university town with the opinions of other students having chosen a different university town. Contrary to these realized perceptions, students from high schools still have to make a

Table 4 : Nomological validity

Foreign Local

Total number of beliefs 8.5 8.4 (4.14) (2.88) Total number of fi rst-level 5.73 6.29 associations (1.70) (2.17) Total number of second- and 3.5 2.15 third-level associations (4.14) (2.26) Total number of links 9.17 8.68 (4.9) (3.12) Total number of fi rst-order 5.83 6.25 links (1.72) (2.17) Total number of second- and 3.33 2.43 third-order links (4.57) (2.38) Total number of triple lines 6.4 5.27 (4.39) (2.57) Total number of double lines 1.8 2.02 (1.52) (1.68) Total number of single lines 0.9 1.30 (0.88) (1.15)



choice and may have different brand maps too. Comparing BCMs from other university towns would show the strengths and weaknesses of different university towns, as well as their points of parity and differentiation.

Theoretically, researchers use BCM to assess how the city is perceived by a certain segment. However, this method does not explain the expected level of the different attributes and the importance of the attributes. The technique should therefore be accompanied by traditional importance and expectation measures (regression on satisfaction).

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