We analyse architects and nonarchitects' emotional assessments of different districts in their own city (Valencia, Spain) by applying Kansei engineering techniques. A field study was carried out on a sample of 140 subjects (70 architects and 70 nonarchitects) who were asked to express their opinions on different areas in the city. The set of emotional impressions used by architects and non-architects to describe their sensations was obtained using differential semantics. The semantic space was described by 9 independent axis which explained 62% of the variability. Then, for each collective the set of impressions which influence the final residential or investment area decision was analysed. This relationship was obtained applying linear regression models. The results showed no significant differences between both groups so that the emotional attributes determining the choice of area were very similar for architects and non-architects. Greater discrepancies were found when the purpose of the choice was investment and not residential. Finally a neighbourhood was semantically profiled to represent and compare both collectives' perceptions.
There are many studies on the differences in architects and nonarchitects’ evaluations [
Other studies have focused on the different assessments of architectural styles. Gans [
Fewer works have attempted to identify what specific design elements cause the different assessments. In this regard, Gifford et al. [
Two basic causes were noted as determinants for the different assessments, different personality factors, and different knowledge structures. In relation to personality factors, it seems that enterprising, daring individuals who seek new sensations prefer the “high” style while individuals with a low level in this personality factor prefer the “popular” style [
Although there are many examples in the literature of both groups’ different assessments of buildings, no studies have been found which analyse these differences in terms of urban design and more specifically in the choice of a certain residential environment. Dieleman and Mulder [
Our question then is how are such preferences arrived at? The theory proposed by Brunswik in 1956 suggested that the relational process between the stimulus and the opinion or judgment emitted by the subject was an indirect one. Applied to the sphere of urban design, this approach assumes that subjects respond to the particular characteristics of the physical environment, integrate these reactions into emotional impressions, and transfer those emotional impressions to an aesthetic evaluation of the street or neighbourhood as a whole. This indirect assessment process has also been proposed by other evaluation models developed in very different areas. Thus, Kansei Engineering, developed in the area of user-oriented products design, attempts to identify and quantify users’ perceptions of a product in their own language and to find quantitative relationships between these subjective responses and design features [
Although scarce, the literature does offer some studies which determine the emotional reactions, subjective attributes, or semantic axes which are relevant in the evaluation of residential environments. Thus, Lynch [
Following this outline, this study aims to analyse the different perceptions in the collective of architects and non architects in the decision to choose an area. This was done by carrying out the first phase of Kansei methodology to analyse both collectives’ emotional responses to the neighbourhoods in a city. Specifically, the study aims to: (a) quantify the difference between the opinions in both groups on choice of an area. We felt it was relevant to analyse the differences in relation to the purpose of the choice, residential or investment purposes. This aspect has not been studied so far in the area of perception, and it seems interesting to analyse whether the decision to reside or invest in an area depends on different symbolic aspects or attributes for each collectives (b) select relevant words, with as few words as possible to describe the semantic space for neighbourhoods, (c) order the set of emotional attributes in relation to their influence on the choice of an area as a place to live or invest, and (d) describe for both collectives the perceived images of a neighbourhood in relation to the rest of the city.
The results of this study could be used in future studies to determine what specific features or services should be present in a neighbourhood in order to create a certain impression.
The study was carried out in the city of Valencia (Spain) (Figure
Map of Valencia with the neighbourhoods included in the sample.
The sample comprised 140 subjects, 70 architects, and 70 nonarchitects; all staff from the Universidad Politécnica in Valencia (professors, research staff, administration, and services staff). The architects were considered to be “experts” in urban design as in Spain they have the necessary academic qualifications to become town planners. The architects in the sample came from departments related to architecture or town planning. The sample size was chosen with the criterion of having 8 cases per adjective. This sample size is greater than the number of 300 indicated as sufficient in field [
The questionnaire contained 59 adjectives to describe citizens’ emotional response when evaluating areas of a city. Only words and expressions in Spanish were collected. This set of adjectives was obtained through a word search (142 adjectives) on neighbourhood evaluation. Most of the expressions were found on the Internet, in newspapers, journals, and professional magazines. This set of words was reduced using the affinity diagram which groups semantic descriptions according to their affinity [
The set of stimuli used to develop the field study consisted of a total of 74 images of the different neighbourhoods in the city of Valencia. Each stimulus had a graphically defined set of streets for evaluation. In addition to facilitating recognition of the area, it was given the name used by the City Council and its popular commercial name. Figure
Example of the stimuli used in the field study.
The interviewees were informed of the objectives of the study, and we asked them to fill in questionnaires expressing their opinions in a spontaneous way. It was therefore considered necessary for interviewees to know the neighbourhood being evaluated, and if they did not, they were asked about a different area. The order of questions was randomized for each individual questionnaire in order to avoid bias.
In a first phase, discriminant analysis was used to evaluate the differences in perception of the set of variables using the variable which represents the collectives of architects and nonarchitects as a grouping variable and the scores for the different adjectives as independent variables. It was thereby possible to verify the hypothesis that architects and nonarchitects have a sufficiently different perception structure to be able to classify a person by their responses. The indicators used to evaluate the efficiency of the discriminant function were: the eigenvalue of the discriminant function, the canonical correlation, and the Wilks’ Lambda value.
First of all the distribution of both variables was analysed. Then an ANOVA was applied to evaluate the differences in perception in the variables which reflect the choice of the area.
We use differential semantics developed by Osgood et al. [
Then, the ranking of axes or perceptions which influence the choice of a certain residential environment for each collective was determined by applying regression analysis to the choice of neighbourhood (residential or investment) as the predictive variable.
The semantic profile of a specific neighbourhood is a diagram that represents the scores obtained on each semantic axis and the overall evaluation (residential or investment choice). This graph allows us to visualise the relative position of a particular neighbourhood with respect to the mean of the other areas in the city. Thus we can represent the perception that architects and non architects have of a given neighbourhood and compare their impressions. This was done by analysing one particular neighbourhood based on a sample of 15 additional questionnaires not included in the above statistical analysis.
Statistical analyses were carried out using statistical package SPSS.16.0.
Discriminant analysis was used to determine the existence of significant differences between both collectives based on the set of adjectives analysed. This test determined a single discriminant function. The discriminating power of this function was moderate, with a canonical variation of 0.358 and an eigenvalue of 0.147. The separation given by the discriminant function was significant, with a Wilks’ Lambda value of 0.872 (see Table
Eigenvalue, canonical correlation, Wilks Lambda, and signification level of the discriminant function.
Eigenvalue | .147 |
Canonical correlation | .358 |
Wilks’ Lambda | .872 |
Signification level | .000 |
For the “residential choice” variable, descriptive analysis shows a tendency for both collectives to evaluate the same areas positively. 57% of architects and 53% of nonarchitects valued positively the same areas of the city for residential purposes (Figure
Evaluation of the variable “residential choice”: (a) nonarchitects (b) architects.
Furthermore, the ANOVA shows no significant differences between both collectives in residential choice decision (for a significance level of 0.05) (Table
Residential choice ANOVA.
Source | SS | df | MS | F | Sig |
---|---|---|---|---|---|
Residential choice | |||||
Intergroups | 2.579 | 1 | 2.579 | 1.305 | .255 |
Intragroups | 272.643 | 138 | 1.976 | ||
Total | 275.221 | 139 |
For the “investment choice” variable, again descriptive analysis shows a tendency for both groups to evaluate the same areas positively. 59% of architects and 51% of nonarchitects valued positively the same areas of the city for investment (Figure
Evaluation of the variable “investment choice”: (a) nonarchitects (b) architects.
In this case, the ANOVA (Table
Investment choice ANOVA.
Source | SS | df | MS | F | Sig |
---|---|---|---|---|---|
Investment choice | |||||
Intergroups | 6.007 | 1 | 6.007 | 3.558 | .061 |
Intragroups | 232.986 | 138 | 1.688 | ||
Total | 238.993 | 139 |
In short, although there are no significant differences it appears that there are more differences when the final choice is investment rather than residential. In any case, it seems appropriate to analyse what each evaluation depends on.
Factor analysis later reduced the 59 expressions on assessment of the areas to 14 uncorrelated factors which explained 71.4% of the variance. Table
Factor analysis.
Item | Factor | |||||||||||||
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | |
25.3 | 10.7 | 5.9 | 4.7 | 4.2 | 3.1 | 2.7 | 2.7 | 2.5 | 2.1 | 2.0 | 1.9 | 1.8 | 1.8 | |
.92 | .93 | .74 | .74 | .59 | .75 | .69 | .64 | .76 | .39 | — | — | .21 | .01 | |
With flavour, charm | .84 | |||||||||||||
Emblematic | .82 | |||||||||||||
Unique, special, unrepeatable | .81 | |||||||||||||
Tourist area | .78 | |||||||||||||
In surroundings of cultural interest | .78 | |||||||||||||
With personality and own character | .68 | |||||||||||||
In historical surroundings | .66 | |||||||||||||
With good views | .62 | |||||||||||||
Traditional, long-established | .60 | |||||||||||||
Well situated | .60 | |||||||||||||
Fashionable | .48 | |||||||||||||
Good investment with revaluation possibilities | .46 | |||||||||||||
Avant-garde | .44 | |||||||||||||
Luxury | .79 | |||||||||||||
Prestige | .46 | .75 | ||||||||||||
Noble | .71 | |||||||||||||
With expensive flats | .69 | |||||||||||||
Elegant | .55 | .59 | ||||||||||||
Marginal | −.41 | |||||||||||||
Wide, big open spaces | .75 | |||||||||||||
With parks and leisure areas | .69 | |||||||||||||
Decaying, deteriorated | −.57 | |||||||||||||
With wide avenues | .54 | |||||||||||||
Feeling of community | −.45 | |||||||||||||
Expanding, urban development | .79 | |||||||||||||
Established and consolidated | −.59 | |||||||||||||
In a natural, countryside environment | .59 | .43 | ||||||||||||
With promising future prospects | .56 | |||||||||||||
Easy to park | .53 | |||||||||||||
Contemporary, modern | .48 | |||||||||||||
Well located | .84 | |||||||||||||
Good public transport links | .72 | |||||||||||||
With wide, easy, fast access routes | .62 | |||||||||||||
Easy to reach the workplace | .61 | −.43 | ||||||||||||
Multicultural | −.74 | |||||||||||||
Contrasts | −.64 | |||||||||||||
Pleasant, agreeable | .40 | .50 | .47 | |||||||||||
With immigrant | −,42 | −.46 | ||||||||||||
Quality of life | .45 | |||||||||||||
Good urban planning | .44 | |||||||||||||
Commercial | .77 | |||||||||||||
With good shops | .72 | |||||||||||||
Business area | .61 | |||||||||||||
Noisy | −.75 | |||||||||||||
Friendly and welcoming | .66 | |||||||||||||
Peaceful | .56 | |||||||||||||
Youthful, vital, cheerful | .66 | |||||||||||||
With leisure and entertainment services | .44 | .54 | ||||||||||||
Plenty of nightlife and carefree | .42 | .52 | ||||||||||||
Lively, dynamic | .40 | .49 | ||||||||||||
Pedestrian areas | .41 | .47 | ||||||||||||
Good sports facilities | .45 | |||||||||||||
Urban character | .67 | |||||||||||||
With good facilities, infrastructures, and services | .56 | |||||||||||||
With no safety problems | .80 | |||||||||||||
Ongoing construction work | .77 | |||||||||||||
With a wide choice of schools | .75 | |||||||||||||
Heavy traffic | −.43 | .56 | ||||||||||||
Influenced by the sea | .46 | −.47 |
Axis 1 represents the with charm, emblematic, and unique axis with flavour, charm, emblematic, unique, tourist area, and in surroundings of cultural interest as main concepts. Axis 2 comprises the adjectives luxury, prestige, noble, expensive flats, and elegant. It is related to the concept of luxury and prestige. Axis 3 determines wide and landscaped with wide, big open spaces, and landscaped and leisure areas, with wide avenues and the negative decaying, deteriorated. Axis 4 refers to the character of the area being developed, not consolidated. Concepts such as expanding, urban development, with promising future prospects, and the negative established and consolidated are very significant in this axis. Axis 5 represents the dimension well located with the adjectives well-located, good public transport links, with wide, easy, fast access routes, and easy to reach the workplace. Axis 6 contains pleasant, agreeable, with quality of life concepts and the negative multicultural, contrasts, and with immigrants. It is the nonmulticultural axis. Axis 7 can be understood as commercial and business area with the adjectives commercial, with good shops and business area. Axis 8 with the expressions friendly and welcoming, peaceful, pleasant, and agreeable, and the negative noisy represents the dimension of peaceful and friendly. Axis 9 represents the dimension youthful nature and leisure with the main adjectives being youthful, vital, cheerful, with leisure and entertainment services, plenty of nightlife and carefree and lively, dynamic. Axis 10 represents urban and with good facilities axis as it contains the adjectives urban character and with good facilities, infrastructures and services. Axis 11 contains the concept with no safety problems as the only expression. Axis 12 refers to ongoing construction work as it only contains this concept. Axis 13 is the with a wide choice of schools axis, as it only contains this descriptive. Finally, axis 14 is with traffic axis. It contains the expressions with heavy traffic and influenced by the sea.
Figure
Plot of principal component loadings.
Then, Cronbach’s Alpha values were calculated for all the dimensions. Following Streiner’s [
For the “residential choice” variable the model determined a total of 4 significant factors for both collectives (
Factor ordering according to influence on residential choice (regression analysis).
SE | Beta | Sig. | |||
(Constant) | .163 | .125 | 1.308 | .196 | |
Luxury and prestige | .485 | .135 | .352 | 3.598 | .001 |
Peaceful and friendly | .474 | .153 | .303 | 3.095 | .003 |
With charm, emblematic | .453 | .128 | .325 | 3.535 | .001 |
Not multicultural, no immigrants | .370 | .124 | .282 | 2.986 | .004 |
(Constant) | .334 | .126 | 2.657 | .010 | |
With charm, emblematic | .803 | .130 | .573 | 6.155 | .000 |
Luxury and prestige | .459 | .137 | .329 | 3.351 | .001 |
Peaceful and friendly | .387 | .117 | .308 | 3.292 | .002 |
Not multicultural, no immigrants | .362 | .146 | .243 | 2.481 | .016 |
The model for the architects has a correlation coefficient of 0.748. The factor with the greatest influence in the residential area decision is the one which reflects the perception of area with charm, emblematic, and unique a correlation of over 0.80. Then, with a correlation of over 0.4 is the variable which reflects perception of luxury and prestige. Finally, with correlations in the interval 0.35–0.40 are the impressions of a peaceful, friendly area and not multicultural area. Although the model for the collective of nonarchitects with a correlation coefficient of 0.721 includes the same factors, the order is different. Thus, perceptions of luxury, prestige, peaceful and friendly, and with charm and emblematic correlate positively in the interval 0.45–0.50. As in the case of the architects, the impression that the area is not multicultural also influences the residential decision, but less significantly (with a correlation of 0.37).
Models were obtained for the “investment choice” variable in a similar fashion (Table
Factor ordering according to influence on investment choice (regression analysis).
SE | Beta | Sig. | |||
(Constant) | .155 | .120 | 1.291 | .202 | |
With charm, emblematic | .533 | .123 | .400 | 4.326 | .000 |
Luxury and prestige | .358 | .130 | .271 | 2.765 | .008 |
Not multicultural, no immigrants | .355 | .119 | .283 | 2.976 | .004 |
Peaceful and friendly | .334 | .147 | .223 | 2.270 | .027 |
Wide and landscaped | .255 | .127 | .196 | 2.003 | .050 |
(Constant) | .395 | .112 | 3.537 | .001 | |
With charm, emblematic | .679 | .116 | .537 | 5.850 | .000 |
Luxury and prestige | .652 | .122 | .519 | 5.353 | .000 |
Well located | .373 | .123 | .268 | 3.032 | .004 |
Peaceful and friendly | .271 | .105 | .239 | 2.587 | .012 |
Youthful nature and leisure | .267 | .117 | .214 | 2.290 | .026 |
Wide and landscaped | .261 | .119 | .203 | 2.181 | .033 |
For the collective of architects the model includes 6 significant factors. The correlation coefficient is 0.756. The most significant axes in this variable reflect the perceptions of the area with charm, emblematic, luxury, and prestige with positive correlations in the interval 0.65–0.70. This is followed by well-located area with a correlation of 0.37. Finally, with correlations in the interval 0.25–0.30 perceptions of peaceful, youthful, wide, and landscaped For nonarchitects the model reflects 5 relevant factors. The correlation coefficient is 0.718. Outstanding, with a correlation of over 0.50, is the factor which reflects the perception of the area as being with charm and emblematic. Then correlations between 0.30–0.40 are the perceptions of the area as luxury, not multicultural and peaceful. This is followed by the factor of wide and landscaped area with a correlation of 0.25.
Finally and in order to represent the differences in perception between both collectives one of the areas in the city was chosen for semantic profiling. Figure
Stimuli of the particular neighbourhood evaluated.
To give the reader a better idea, we have included photographs of the area (Figure
Real images of the particular neighbourhood evaluated.
Figure
Comparison of semantic profiles of the neighbourhood evaluated (nonarchitects–architects).
It can be seen that the overall evaluations of both collectives are quite different. Whereas architects would choose this area for residence and investment, the other group would not. What is the reason for these differences? Account must be taken of the fact that for architects the most significant variable in the residential choice decision is an emblematic appearance, with charm and unique and this factor is very highly valued. It seems that this very positive evaluation compensates for the fact that it is not perceived as luxury, prestige, peaceful, or friendly (significant variables in the model). Nonarchitects also perceive the area as with charm and emblematic but this factor does not manage to compensate (it is not so significant in the model) for the negative evaluations in the perceptions of peaceful, friendly and not multicultural area.
With regard to investment choice, the architects’ decision is very positive. It appears that the sensation that it is an area with charm, emblematic, well-located, good public transport links, youthful, and with leisure and entertainment services compensates for the fact that it is not considered to be luxury, peaceful, wide or landscaped. For nonarchitects however, as the residential and investment models are practically similar the final decision is also negative. For this collective, the area does not give a sensation of luxury, it is multicultural and not very wide or landscaped. These evaluations do not seem to compensate for the fact that it is perceived as having charm or being emblematic. Thus, the final evaluation for this collective is again negative.
In this paper we have analysed the differences between architects and nonarchitects in their emotional assessments of different districts in their own city for the purposes of choosing a given residential or investment area.
This study provides significant implications on three levels: it contributes to the theory, methodology, and application.
At the theoretical level, it can be concluded that both collectives’ (architects and nonarchitects) evaluation scheme shows no significant differences in the decision to choose an area in the city. Thus, while there appear to be important differences in the initial set of adjectives, this does not hold for the choice of area variables (residential or investment). That is, the emotional attributes which determine the choice of area are very similar for architects and nonarchitects. Greater discrepancies, however, were found when the purpose of the choice was investment and not residential. Although there are no similar studies with which to compare these results, it is worth emphasising the difference in this conclusion with the studies to date which report significant differences between architects and nonarchitects when evaluating buildings [
From the methodological point of view the most outstanding contribution is the application of Kansei methodology to evaluate urban areas of a city to detect different evaluations made by the group of architects and nonarchitects. In particular, the first phase of this methodology has been developed using differential semantics as a verbal measurement instrument by measuring the subjective component of the emotional state which both collectives are able to recognise. Differential semantics has been previously applied in the field of residential environments with the aim of determining general perceptual qualities that people use to characterize architecture and the built environment [
With respect to the contribution to application, the findings of this study provide three important outcomes.
Firstly, a 9-dimension model for perception of the analysed urban area with a 61.8% capacity is to reproduce perception variability in the sample. The semantic axes represent concepts related to the neighbourhood’s appearance (1st axis, with charm, emblematic; 2nd axis, luxury and prestige and 6th axis, not multicultural), good urban planning (3rd axis, wide and landscaped), character or area in expansion or not consolidated (4th axis), good services (5th axis, well-located, with easy access and 7th axis, commercial and business) and pace of life (9th and 8th axes, youthful character, leisure, and peaceful, resp.). These axes provide a tool for objective measurement of the perceptions that different areas in the city of Valencia arouse in users (architects and nonarchitects). A similar study was done in 2004 [
Secondly, the significance of each semantic concept in the final evaluation of areas in the city has been analysed to provide descriptive maps of the emotional evaluation associated to the stimulus for both collectives. In the residential choice decision, it can be stated that for architects and nonarchitects perception of an urban area as emblematic, unique, luxury and prestige, peaceful and welcoming, and not multicultural will maximise the success. However, these perceptions are ordered differently in the two groups. For architects areas with charm and emblematics are very important. For nonarchitects however, the appearance of luxury and prestige and the sensation of a peaceful, friendly area are more important. The differences are more significant when the area is being chosen for investment purposes. For both collectives it is important that the area gives the impression of being emblematic, unique, and luxury. As in the above case the factor of being an area without noise, friendly, welcoming, and peaceful is also important. However, for investment purposes, architects focus on aspects related to services in the area; thus it is with easy access and is perceived of as youthful and for leisure while nonarchitects also take into account the fact that it is not perceived of as multicultural. In both cases the last significant factor in the decision to invest is that the area is perceived of as wide and landscaped. It should be noted with regard to the multicultural factor that the immigrant population has tended to concentrate in the most disadvantaged areas of the city with lack of green spaces, excessive noise levels, lack of cleanliness, and high levels of delinquency and vandalism. Perhaps that is why the individuals in the sample gave a negative evaluation to multiculturality in the residential decision (Figure
Radial representation of absolute values for beta coefficient of the linear regression between the semantic axes and the choice of neighbourhood: (a) residence (b) investment.
It is interesting to see the differences in the same collective in relation to the duality in the residential or investment choice (Figure
Radial representation of absolute values for beta coefficient of the linear regression between the semantic axes and the choice of neighbourhood: (a) nonarchitects (b) architects.
Thirdly, the semantic profiles of both collectives have been obtained with regard to a specific area of the city. These semantic profiles may be very useful to town planners when planning a city as they provide insights to analyse the perception of specific neighbourhoods.
The results of this study are not comparable with previous studies as most have focused on analysing what aspects of the urban environment manage to improve or worsen the overall appearance. Thus, spacious well-structured setting [
In terms of future lines of work, after obtaining architects and nonarchitects’ affective dimensions which influence the choice of area, it could be interesting to identify what design elements in the urban environment cause them. For example, it has been seen that both groups coincide in the importance of an area being perceived as having charm and being emblematic, but what does each collective focus on specifically to arrive at this evaluation? what design elements in the urban environment cause it? This relation between design elements and semantic attributes constitutes the second phase in Kansei methodology and can be determined by applying statistical treatments such as linear regression [
Finally, the limitations to be taken into account are firstly that the results obtained cannot be extrapolated for cities other than Valencia. When evaluating a specific city, the obtained axes are specific to this city in particular, with its singular characteristics as perceived by the inhabitants. Secondly, the sample used is representative of a given market segment. This limitation is given by the need to use homogeneous population groups. Account should be taken of the fact that the inclusion of different groups can cause high intergroup variability which can alter the structure of the semantic axis.