López-Mosquera e Sánchez 2011

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Tourism Management 32 (2011) 875e889

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Tourism Management

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The influence of personal values in the economic-use valuation of peri-urbangreen spaces: An application of the means-end chain theory

Natalia López-Mosquera, Mercedes Sánchez*

Universidad Pública de Navarra, Dpto. Gestión de Empresas. Edificio Madroños, 31006 Pamplona, Spain

a r t i c l e i n f o

Article history:Received 12 February 2010Accepted 3 August 2010

Keywords:Peri-urban green spaceContingent valuationMeans-end chain theoryPersonal valuesTerritorial managementAbstraction level

* Corresponding author. Tel.: þ34 948 169396; fax:E-mail address: [email protected] (M. Sánchez)

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a b s t r a c t

The implication of land-use managers and the local community in matters relating to peri-urban greenspaces has been modified by the growing importance of the values attached to such areas. This paperuses means-end chain techniques to examine whether green space users reflect their own personalvalues through the benefits and attributes they perceive in this type of good. The results show key factorsto be opportunities for sport and recreational activities, improvement of physical and mental well-beingand enjoyment of landscape beauty. Other values, both individual (personal enjoyment and quality oflife) and social (respect for others and a clearer conscience) also emerge. Further analysis to determinewhether values differ according to whether or not the visitor assigns a monetary value to the green spaceshowed higher environmental and social awareness to be associated with higher willingness to pay forperi-urban green space. Thus, the greater the perceived environmental values and the higher theirsubsequent monetary valuation, the more effective environmental protection and conservation policiesare likely to be. These results may be worth consideration by land-use managers engaged in environ-mental cost benefit analysis

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1. Introduction

Most of the existing research on green spaces takes the form ofvisitor perception studies focusing on the use and valuation of thistype of environmental goods (Asayu-Adjaye & Tapsuwan, 2008;Baral, Stern, & Bhattarai, 2008; Jim & Chen, 2006) or the physicaland mental welfare benefits they provide (Kaplan, 1995; Korpela,Ylén, Tyrväinen, & Silvennoinen, 2008; Tyrväinen, Mäikinen, &Schipperijn, 2007). There has also been a recent upsurge ofstudies attempting to explain the variation in how people use andperceive the attractiveness of green spaces (Krenichyn, 2006). Theliterature defines landscape perception as a complex processinvolving both the more technical aspects of vision and psycho-logical factors relating to cognition, affect and evaluation. All theseaspects, which are highly interrelated in visitors’ minds, determinetheir preferences for specific landscapes (Sevenant & Antrop, 2009).

Over the last decade, the consideration of cognitive and affectiveissues in user decision-making processes has led to a substantialchange in the conception and valuation of green spaces (Chiesura,2004; Manzo, 2003; Sanesi & Chiarello, 2006; Velarde, Fry, &Tveit, 2007). This change has come about largely as a result of the

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growing importance attached to the personal values expressedthrough green space use (Brown, 2005; Brown & Raymond, 2007)and to the phenomenon of place attachment or people’s emotionaland cognitive with their physical environment (Williams & Vaske,2003). Several studies have already shown that the evaluation ofa natural space usually reveals a person’s environmental valueorientation (Coogan, Karash, Adler, & Sallis, 2007; Kaltenborn &Bjerke, 2002; Stern, Dietz, Abel, Guagnano, & Kalof, 1999, amongothers). In exploring this last concept, researchers have focused onhuman attitudes and behaviour towards natural landscapes, basedon the theory that they derive from underlying personal values,regarded by some as the simple principles that guide evaluations orcognitive inferences (Rokeach, 1979; González & Amérigo, 2008).Given their role in determining people’s attitudes and responsestowards specific aspects of the environment (Kaltenborn & Bjerke,2002) personal values need to be integrated into the analysis ofdecision-making processes (Perugini & Bagozzi, 2001).

The above context of analysis, which examines the individualdecision-making process in terms of the relationship betweenmotivations and values and behaviour, provides the framework forthis study, which has two features that distinguish it from previousresearch. The first is that it applies means-end chain methodologyin a cognitive model, to determine whether the differentiatingattributes of a given environmental good provide users withbenefits and reasons for its use and enjoyment that later lead to the

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N. López-Mosquera, M. Sánchez / Tourism Management 32 (2011) 875e889876

fulfilment of personal end values. The environmental good inquestion is a peri-urban green space,1 the Monte San Pedro park(A Coruña, Spain), selected for its accessibility and possibilities forrecreational enjoyment. The second is that it aims to test forvariations in individual decision-making structures as revealed bybehavioural observation, with particular emphasis on contingentvaluation estimates of WTP.

The final understanding of the personal or intrinsic values thatdrive the green space decision-making processes may assistmanagers, primarily, to establish and justify their global aims andecosystem management strategies (Bengston, 1994; Brown &Raymond, 2007; Kyle, Mowen, & Terrant, 2004). It might alsocontribute to the anticipation, identification and fulfilment of theneeds and desires of visitors and to defining value orientations andpotential responses to landscapes. Thirdly, it could potentiallyimprove the prediction of public reactions to environmental prac-tices in the face of future changes in ecosystem management andprovide new criteria for dealing with management-related conflict.Finally, the analysis of landscapepreferences, in termsof greenspaceusers’ attitudes and environment-related economic behaviour, mayprovide a useful tool for the design of environmental educationprogrammes (Múgica & De Lucio, 1996; Pooley & O’Connor, 2000).Additionally, citizen participation in environmental education pro-grammes helps to stimulate certain perceptive patterns andpromote a positive evaluation of the landscape. All of the above-mentioned actions could potentially bring urban managementobjectives into line with users’ needs.

The remainder of the paper is organised in five parts. Part 2presents a review of the literature on personal values related to theenvironment. Part 3 describes the methodological details and theenvironmental good to be tested. Part 4 presents the main findings.Thediscussion and themain conclusions and limitationsof the studytogetherwith suggestions of lines for future researchmakeupPart5.

2. Personal values related to the environment

The growing importance assigned to urban and peri-urbangreen spaces has altered both how they are conceived and how theyare valued. Thus, attention has been drawn to the aesthetic, psycho-physical and social health-related benefits provided by these spaces(Chiesura, 2004), the importance of the social factor in theirvaluation has been examined (Sanesi & Chiarello, 2006), andemotional, health-benefit and landscape factors have been takeninto consideration (Velarde et al., 2007). This change of focus hascome about as the result of interest in identifying and quantifyingindividuals’ landscape values and environmental values in general,and in delimiting the nature of users’ personal attachment to them.One important line of investigation has examined the link betweenusers’ emotional responses and perceptions of environmentalgoods with a view to gaining a deeper understanding of thevaluation mechanism (Manzo, 2003; Williams, Davids, Burwitz, &Williams, 1992). Subsequent studies have identified people asactive participants in the landscape, established a distinctionbetween functional and symbolic values, demonstrated the role ofculture, and linked place attachment to landscape values (Brown,2005; Brown & Raymond, 2007). Thus, the research has extendedto the analysis of users’ reasons for using environmental goods andthe identification of the associated benefits. Another recentcontribution to the research is an interesting study of the benefits

1 Taking peri-urban green space to mean any area of outstanding landscapeinterest, natural or artificial, located within a metropolitan boundary, whereoverlapping natural, semi-natural, transition and artificial areas are adapted tomeet the recreational needs of the local community.

obtained from the use of green space as a means to fulfil personalvalues (Krenichyn, 2006).

Broadly speaking, contact with the outdoors provides two typesofbenefits; somedirectly relatedwith theenvironmental good itself,andothers relating to its effectonusers. The reportedenvironmentalbenefits include aesthetic appeal, cleaner air, observation of nature,landscape beauty and wilderness, while the benefits for users arepredominantly of a psychological nature (Gobster & Westphal,2004; Kalisch & Klaphake, 2007; Tyrväinen et al., 2007; Vesely,2007). Another perspective describes contact with nature ascontributing to improve the sensory capacities, reduce fatigue andstress, restore emotional balance, and sharpen cognitive skills(Kaplan, 1995; Velarde et al., 2007; Korpela et al., 2008). Theresulting health benefits and outdoor physical activity are alsoreported to have a positive effect onphysical andmentalwell-being,and a direct relationship has been established between exposure tothe natural environment and positive emotional responses(Hansmann, Hug, & Seeland, 2007; Maas & Verheij, 2007). Finally,focusing on the ways in which natural spaces stimulate social inte-gration and personal interaction, one strand of research includesa social component among the personal benefits (Barbosa et al.,2007; Burgess, Harrisson, & Limb, 1998; Coley, Kuo, & Sullivan,1997; Tyrväinen et al., 2007).

As well as identifying the beneficial effects derived from the useof environmental goods, investigators have tried to determine towhat extent these effects are subject to personal and behaviouralfactors. Thus, the visitor’s decision-making process varies, not onlywith the good considered, but alsowith the user’s personal interestsand life experiences, and with the physical and social setting(Neuvomen, Sievänen, Tönnes, & Koskela, 2007). Life experiences, inparticular, are a major focus of research interest. Two of theperceptionsmostwidely expressed by visitors to green spaces are offreedom and silence (Klijn, Buij, Dijkstra, Luttik, & Veeneklaas,2000). Other authors mention tranquillity, comfort, emotionalstimulation, security, anxiety, and boredom (Galindo & Corraliza,2000). Fun, pleasure, tranquillity; the desire for new experiences;emotional stimulation; health improvement and solitude have alsobeen documented (Davenport, Borrie, Freimund, &Manning, 2002).The reported emotional benefits include experience of nature andescape from the stressful pace of daily life, and the evidencesuggests that experience of nature is a source of positive feelings,such as freedom, connectedness with nature and happiness(Chiesura, 2004). Contact with nature as a means to attainemotional and sensory experiences such as visual beauty andphysical and mental well-being has also been mentioned(Krenichyn, 2006). Recent studies further emphasise the impor-tance of these personal experiences, describing them as the root ofvarious perceptions, behavioural responses and practices amonggreen space users (Tyrväinen et al., 2007; Hanley et al., 2009). Thesepersonal experiences depend on the personal beliefs and values thatdetermine people’s aesthetic appreciation and social values. Someresearchers perceive values as the objectives or goals that motivateor drive people’s actions, with responses varying according to howindividuals draw on their personal experience (Ford, Williams,Bishop, & Webb, 2009).

The case for the importance of personal values draws supportfrom the fact that certain studies have found them to have moreexplanatory power than context for explaining people’s environ-mental valuation and behaviour (González, 2002). Elsewhere, theevidence suggests values as the main driver of environmentalbehaviour (Grob, 1995). A recent strand of research highlights therole of personal values of this type in human decision-makingrelated to the environment. Thus, the range of existing researchincludes the distinction between internal values and externalvalues (Chryssohoidis & Krystallis, 2005), the influence of these

N. López-Mosquera, M. Sánchez / Tourism Management 32 (2011) 875e889 877

values on behaviour (Stern et al., 1999; Coogan et al., 2007) and theimpact of personal values on willingness for environmentalconservation (Winter, Prozesky, & Esler, 2007).

The recent incorporation of these behavioural differences intovarious cognitive decision models has improved model perfor-mance (Ford et al., 2009). In other words, the inclusion of personalvalues enables more accurate prediction of public attitudes towardsthe environment (Bodur & Sarogöllü, 2005; González, 2002;Kotchen & Reiling, 2000; Kyle et al., 2004). From the economicperspective, however, the main interest of this study lies in the useof explanatory models incorporating monetary valuations of theenvironmental good in order to explain the interrelation betweenbehavioural traits, willingness to pay (WTP) and personal values ingreen space users. This kind of approach led to the development ofa model using values, perceptions and motivations for the use ornon-use of the environmental good as the explanatory variables forthe valuation process (Harris & Brown, 1992). Subsequent researchinvestigated the relationship between attitudinal and motivationalfactors and contingent valuation estimates of environmental non-use values (Kotchen & Reiling, 2000). The findings indicate anassociation between higher WTP and more positive attitudestoward the environment. Some research reports that WTP forenvironmental protection is value-oriented (Stern & Dietz, 1994). Inthe same vein, some authors have urged a renewal of interest in theindividualmotives underlyingWTP (Cooper, Poe, & Bateman, 2004).This has generated research examining the role of motives inexplainingWTP values for a set of nested environmental goodswithpotential use and non-use benefits, the findings revealing greatercomplexity in the motivational structure when the analysisconsiders both social and personal motivational factors. Analysis ofthe preferences for multiple use forest management and averagesocial and individualWTP revealed the relevance of personal factors(Mill, Van Rensburg, Hynes, & Dooley, 2007). Yet another strand ofwork, relating attitudes towards pollutionwithWTP forwastewatertreatment and recycling, reports positive correlation between thetwo (Tziakis et al., 2009). Investigation of citizens’ perceptions andWTP for a market-based instrument and analysis of the influence ofsocial factors on individuals’ views have revealed social capital,perceptions of the compliance of fellow citizens and the effective-ness of the proposed policy as significant determinants of WTP(Jones, Evangelinos, Halvadakis, Iosifides, & Sophoulis, 2010).

In the context of analysis presented above, this paper usesmeans-end methodology to reveal the personal values underlyingthe decision-making processes of visitors to the San Pedro peri-urban park based on its attributes and related benefits. It alsoassesses whether the cognitive structure varies according tocontingent valuation estimates of monetary values for the goodconsidered. The next section describes the research methodology.

3. Methodological issues

3.1. Means-end chain theory

Information concerning the relationship between the decision-making process and cognitive structure in green space users is ofpotential interest to environmental economists. Research on thistopic has largely focused on the most concrete level of visitors’ deci-sion-making, that is, the attributes that the green space has to offer.The intricacies of the cognitive structure, however, are such thatperceptions and valuations of the attributes of the goodoften result incomplexchoice structures.Means-end chain (MEC) analysis involvingpersonal values has revealed the multi-level nature of decision-makers’ cognitive choice structures (Pitts, Wong, & Whalen, 1991).

The means-end chain theory (Gutman, 1982; Howard, 1977;Young & Feigin, 1975) assumes that the decision-maker’s subjective

perception of a good is the result of associations between its attri-butes (the “means”) and more abstract cognitive schemata, whichinclude the personal values underlying certain behaviour (the“ends”). Such associations determine the appeal of the characteris-tics of the good in question (Reynolds & Gutman, 1988).

According to this theory, consumers’ product knowledge isorganised into hierarchical levels of abstraction, where the higherthe level of abstraction, the stronger andmore direct the connectionto the self. Six ascending levels of abstraction describe the cognitivestructure linking product knowledge (concrete attributes, abstractattributes and functional consequences) with self-knowledge(psychological consequences, instrumental values and end values)(Olson&Reynolds,1983). In the case inhand, the attributes are thoseproperties or characteristics of the environmental good, service orperformance that visitors may desire or pursue. The abstract attri-butes are thosewhose verification is impossible to verify prior to useexcept through internal or external information sources. Explora-tionof theknowledge structure in the environmental context clearlyestablished the distinction between concrete and abstract attributes(Purcell, 1992). Functional consequences are the benefits obtaineddirectly from the use of an environmental good. Psychosocialconsequences are of amore personal, social and less tangible nature.Instrumental values are intangible goals related with the beha-vioural means used to achieve the end aims and, finally, terminalvalues refer to desired end states (Miele & Parisi, 2000).

Existing studies using this methodological approach in a similarenvironmental context include an investigation of Dutch people’smotivation to recycle under a compulsory recycling scheme(Smeesters et al., 2003), which showed that they were driven byenvironmental and “civic duty”-related values. Prior researchattempting to identify recycling goals and their effect on the deci-sion to recycle had reached similar conclusions (Bagozzi &Dabholkar, 1994). Exploration of social structure and social rela-tions to determine the extent and quality of the environmentalimpacts deriving from economic activities revealed the deter-mining effect of human skills and human capital on time structuredynamics (Cogoy, 1999). This paper aims to apply means-end chainmethodology to the study of peri-urban green spaces in order toreveal the cognitive structure of the decision-making processunderlying the use and evaluation of the environmental good.

3.1.1. The laddering interviewWith respect to the choice of data collectionmethod for theMEC

application, the most widely known information-gathering tech-nique is one known as “laddering”, which was first developed byHinkle (1965). Based on the personal construct theory (Kelly, 1955),it is a face-to-face, one-on-one, in-depth, semi-structured inter-viewing technique designed to develop an understanding of howconsumers translate product attributes into meaningful associa-tions with respect to themselves (Bourne & Jenkins, 2005; Gutman,1982). In other words, its purpose is to reveal people’s motives forchoosing a particular good (Russell et al., 2004). The ladderinginterview is a three-stage process: the elicitation of key attributes,the in-depth interview, and the analysis of results. In the first stage,respondents are required to name the main attributes on whichthey focus when comparing and evaluating goods. The revealed keyattributes are the starting point for the second stage, which is an in-depth interview, where respondents are required to explain theirrelevance in terms of the perceived associated consequences andpersonal values. Interviewers repeatedly ask respondents “Why isthat important to you?” pushing them to increasing levels ofabstraction (from attributes to consequences and from there tovalues) until they can go no further. This results in sequences ofconcepts or “ladders”. The objective in the third stage is to plot theconcepts drawn out by the laddering technique on a so-called

Table 1Identification classification of the attributes, consequences and values used in this study.

Attributes Consequences Values

ConcreteAttributes

- Price (A1)- A place to practice sport andtake physical exercise (A3)

- Distance from home (A4)- Recreational facilitiesprovided (A7)

FunctionalConsequences

- I have good ecological habits (C1)- I help the environment (C5)- A way to escape fromroutine/a way to switch off (C6)

- Frequency of use /regularuser of green space (C7)

InstrumentalValues

- A source of fun, pleasureand enjoyment (V2)

- Enhances my quality of lifeand security (V4)

- Emotional stimulation (V6)- I’m more successful (V9)

AbstractAttributes

- Landscape beauty (A2)- Closeness to nature (A5)- Benefits to the health (A6)- Less noise (A8)

PsychologicalConsequences

- Stress relief /relaxation (C2)- Physical well-being /improvedfitness (C3)

- Rest (C4)- Better health /Mentalwell-being (C8)

EndValues

- A sense of social belonging (V1)- Better relationships with others (V3)- A sense of self-fulfilmentand accomplishment (V5)

- Being respected by others (V7)- Peace of mind dignity and self-respect (V8)


implication matrix (Chiu, 2005; Miele & Parisi, 2000; Ter Hofstede,Audenaert, Steenkamp, & Wedel, 1998). This matrix enables theconstruction of a hierarchical value map (HVM), which is a tree-diagram mapping the respondent’s thought process through thevarious levels of abstraction (Reynolds & Gutman, 1988).

A literature review and a pilot survey carried out on a group ofexperts guided the choice of attributes, consequences and valuesconsidered in the survey designed to reveal green space visitors’cognitive structures. It comprised eight attributes representing the(concrete and abstract) characteristics of a peri-urban green spaceand eight (functional and psychological) consequences relating toits use (Table 1). The concrete attributes were drawn from findingsin the literature indicating that users’ perception and overallvaluation of green spaces are influenced by the admission fee,distance from home, and the exercise and recreational facilities onoffer (Lee & Han, 2002; Tyrväinen & Väänänen, 1998; amongothers). Research showing the influential factors to be landscapebeauty, closeness with nature and green space benefits informedthe choice of abstract attributes (Gobster & Westphal, 2004;Krenichyn, 2006). The main functional benefits reportedlyperceived by green space visitors were the escape from routine,frequency of use and increased environmental awareness(Bernarth & Roschewitz, 2008; Chiesura, 2004; Togridou, Hovardad,& Pantis, 2006) and themost highly valued abstract benefits appearto be the physical and mental health improvements (Gidlöf-Gunnarsson & Öhrström, 2007; Kaplan, 1995). The values for theanalysis presented in this paper were adapted from the LOV (list ofvalues) proposed by Kalhe (1985), later modified by the RokeachValue Survey (RVS), which identifies nine key personal valuesthat influence people’s lives (Chryssohoidis & Krystallis, 2005; Lee,Soutar, & Louviere, 2007). The scale has been widely used to studythe impact of personal values.

The two possible approaches when conducting ladderinginterviews are soft laddering and hard laddering2 (Costa, Dekker, &Jongen, 2004; Grunert & Grunert, 1995). Hard laddering wasselected for the purposes of this study because it is quicker andcheaper than soft laddering, places less pressure on the respondent(Grunert & Grunert, 1995) and is more suitable whenworking withlarge samples (more than 50 subjects) (Russell et al., 2004). Thetechnique used in the case in hand is the Association PatternTechnique (APT) (Gutman, 1982; Ter Hofstede et al., 1998), whichuses two independent matrices: an AC matrix (attributes/conse-quences) and a CV matrix (consequences/values).

2 Hard laddering refers to all interview and data collection techniques in whichsubjects are compelled to generate or verify associations between elements withinindividual ladders, in sequences that reflect increasing levels of abstraction. In softladdering, a natural and unrestricted flow of speech is encouraged during inter-views, with associations between ACV being reconstructed subsequently during theanalysis (Costa et al., 2004).

Another methodological issue requiring consideration is howmany links to include on the HVM in order to obtain the mostmeaningful results, or “cut-off level”. This indicates the number oflinkages registered before a connection ceases on themap (Leppard,Russel, & Cox, 2004). It is not easy to determine what frequency oflinkages between two levels of abstraction is meaningful or signi-ficant enough to be included on theHVM. A high cut-off level (a highfrequency of linkages) will give a simpler map, involving fewerconnections, hence some loss of relevant information, but greaterease of interpretation. A low cut-off level (a lower frequency oflinkages) will result in a complex map that will contain a largeamount of information but will be more difficult to interpret. Priorresearch has shown various ways of determining the cut-off point(Pieters, Baumgartner, & Allen, 1995), but the consensus is thata good cut-off point is one that selects the solution combining themaximum amount of information with the greatest ease of inter-pretation (Audenaert & Steenkamp, 1997 in Leppard et al., 2004).The cut-off determination method used in this study, knownas “top-down ranking” (Russell et al., 2004; Leppard et al., 2004) isbased on the premise that a whole group of respondents will notnecessarily make the same number of linkages between two levelsof abstraction. It may therefore be inappropriate always to use thesame cut-off point when the number of linkages betweenthe different levels of abstraction varies (Barrena & Sánchez, 2009).Top-down ranking enables the HVM to include only the mostfrequent linkages between different levels of abstraction. In otherwords, it selects the linkages in order of importance (the mostimportant linkage being the one with the most cell entries). Thisprovides an ordered set of HVMs,where thefirstmap is the simplestand easiest to interpret while showing themost important linkages.The advantage of this method is that it allows observation of thelinkages between levels and permits between-group comparison(Russell et al., 2004; Leppard et al., 2004). The software packageused in the data analysis was MecAnalyst Plus 1.0.

3.2. Contingent valuation method

Using the methodology described above, this paper analyseswhether cognitive structure influences users’ monetary valuationof an environmental good. Contingent valuation (CV) provides theWTP estimates. The high flexibility of this method suits a broadrange of public goods and situations, hence its widespread use inthe valuation of environmental goods. It has the advantage ofproviding a hypothetical and direct method of estimating themonetary value of environmental resources based on the results ofpublic surveys (Mitchell & Carson, 1989). This method overcomesthe problem that environmental goods cannot be bought or sold inthe marketplace, by presenting consumers with hypotheticalmarkets, inwhich they are invited to declare their maximum (WTP)for the environmental good in question or their willing-to-accept


compensation (WTA) for a hypothetical loss (Venkatachalam,2004). Maximum WTP and minimum WTA estimates are possibleusing the economic concepts of compensating variation andequivalent variation (Venkatachalam, 2004). If the adopted policygenerates an increase in users’ well-being, the compensationvariation (WTP) is the amount of personal income that has to begiven up by the visitor to attain an increased level of utility(Venkatachalam, 2004), as in the case considered in this paper.Equivalent variation (WTA) represents the amount of compensa-tion offered to the user for a utility-level improvement in the eventthat the provision of the public good does not take place(Venkatachalam, 2004).

Three different survey modes are available: the face-to-faceinterview, the telephone and e-mail (Del Saz, García, & Palau,1999),the choice depends on the characteristics of the particularCVM study, and the advantages and drawbacks of each method(Mitchell & Carson, 1989). Another issue for consideration is thechoice of elicitation format. There are five different formats foreliciting subjects’WTP for a given public good. The most commonlyused are the dichotomous choice (DC), the open-ended and themixed formats (the last being a combination of the first two). Theother two are the payment card format and the bidding game.3

Note also that, despite the advantages provided by the CVM,4 ithas often been criticised for its potential biases (Carson, Flores, &Meade, 2001; Sudgen, 2005), which can arise for a variety ofreasons. (1) The hypothetical nature of the simulated market cantrigger strategic behaviour (free riding) by respondents. (2)The “embedding” effect, whenWTP for goods and services does notvary according to the context; (3) The “sequence” effect, whereWTPvaries according to position of the good in the valuation sequence;(4) The “information” effect, whereWTP is influenced by the type ofinformation supplied across different valuation scenarios; (5) Theelicitation effect, whereWTP is influenced by the elicitation format;(6) The hypothetical bias, where the hypothetical market presenteddiffers considerably from the real market; and, finally, (7) Protestzeros, which are motivated by protest behaviour triggered by somecomponent of the survey design, such as the payment vehicle, orethical objections to personal payment for a public good(Venkatachalam, 2004). Utmost care is necessary to avoid estima-tion problems resulting from biases in order to maintain the relia-bility of the results and the usefulness of this method for themonetary valuation of environmental resources (Arrow et al.,1993).

A large number of CVM studies in the context of green spacemanagement and planning consider both the recreational use valueof various environmental goods (Bernarth & Roschewitz, 2008; DelSaz & García, 2007; Jim & Chen, 2006; Sayadi, González-Roa, &Calatrava-Requena, 2009) and the non-use value of the conserva-tion of an area for future use (Baral et al., 2008; Chen & Jim, 2008;Pedroso, Freitas, & Domingos, 2007; Zoppi, 2007).

3.2.1. Logit regression and WTP econometric modelThis paper uses logit regression to model the relationship of the

binary dependent variable (WTP) to the independent variablesbased on econometric models presented by Lee & Han (2002),Asafu-Adjaye and Tapsuwan (2008), and Baral et al. (2008). Most ofthe variables tested have shown significant predictability in other

3 For a more detailed description of interview modes and elicitation formats, seeMitchell and Carson (1989), Del Saz et al. (1999) and Carson (2000).

4 The main advantages are: (1) It is the only method available when it isimpossible to establish a link between the quality of the environmental good andthe consumption of a private good; (2) Its flexibility makes it suitable for addressingall kinds of public goods and situations; (3) Ex-ante valuation; (4) the Hicksianconsumer surplus measure can be obtained directly; (5) It allows for the estimationof non-use values (Carson, 2000; Del Saz & Suárez, 1998).

contingent valuation studies of natural resources (Asafu-Adjayeand Tapsuwan, 2008; Chen & Jim, 2008; Del Saz & García, 2007).The equation takes the following form:

ProbabilityðWTPÞ ¼aþ b1bid amountþ b2ageþ b3genderþ b4educationþ b5incomeþ b6frequencyþ error ð1Þ

where a is the constant and bi are the coefficients of the explana-tory variables.

The dichotomous choice format was used to elicit WTP byasking respondents whether they would be willing to pay a givenbid amount A. Visitors were assumed to be utility maximizingwhen expressing their WTP the specified bid amount in exchangefor the recreational use of the peri-urban green space. FollowingHanemann (1984), this paper adopts the assumption that theprobability of a respondent being willing to pay a given bid amountfollows a standard logistic variate, if:

vð1; Y � A; sÞ þ 31 � vð0; Y ; sÞ þ 30 (2)

and rejects it otherwise. Here, v is the indirect utility which isassumed to equal the utility u; Y is income, A is the admission fee, sis other socio-economic characteristics affecting individual prefe-rence, and 30 and 31 are the identically, independently distributedrandom variables with zero means.

The utility difference (Dv) between the “yes” and “no” answerstakes the form:

Dv ¼ vð1;Y � A; sÞ � vð0; Y ; sÞ þ ð31 þ 30Þ (3)

The DC format of CVM has a binary choice dependent variable,which requires a qualitative choice model. This paper uses a logitmodel. The probability (P1) that the individual will accept an offer(A) takes the form of the following logit model (Hanemann, 1989):

Pi ¼ FnðDvÞ 11þexpð�DvÞ ¼

11þexpf�ða�bAþgYþqSÞg (4)

where Fh(/) is the cumulative distribution function of a standardlogistic variate and some of the socio-economic variables includedin this study. b, g, and q are coefficients to be estimatedwhere b� 0; g> 0; and 0< q or q> 0 are expected.

WTP values are the truncated means. The logit model in Eq. (4)is estimated by the maximum likelihood (ML) estimation method,after which, the expected WTP value of can be calculated bynumerical integration, ranging from zero to Maximum Bid (A) asfollows:

EðWTPÞ ¼ZMax:A

0

FpðDvÞ dA ¼ZMax:A

0

�a* þ bA

�dA; (5)

where E(WTP) is the expected value of WTP, and a* is the adjustedintercept added by the socio-economic term to the original inter-cept term of a. The area beneath the curve in Eq. (5) provides thetruncated mean WTP values. Finally, the chi-square test of inde-pendence provides an assessment of the associations betweencategorical variables.

3.3. Questionnaire design

The application of CV and MEC theory requires the use ofa structured survey questionnaire. This study uses a four-partquestionnaire.

Part 1 collects data on visitors’ real and potential use of thegreen space and the level of satisfaction experienced during the


visit. Part 2 elicits WTP for the recreational use of a peri-urbangreen space. The scenario5 presented to respondents prior to the CVquestions was formulated to be as realistic as possible and remindthem of the main assets of the area (Buckley, van Rensburg, &Hynes, 2009; Kotchen & Reiling, 2000; Pedroso et al., 2007). Thepurpose of this choice of scenario was to improve the credibility ofthe proposal and minimise the risk of misinterpretation that isinherent in this valuation method. The standard DC format incombination with open-ended questions was used to elicit WTP(Bateman, Langford, & Rasbash,1999; Riera, 1994; Zoppi, 2007); theinclusion of a control question helped to identify the reasons forpossible unwillingness to pay (Jorgensen, Wilson, & Heberlein,2001; León, 1996; Tyrväinen & Väänänen, 1998). The three bidprices selected were 1.5V, 2.5V or 3.5V6, and, to ensure indepen-dence, they were uniformly and randomly distributed acrossvisitors (Scarpa, Hutchinson, Chilton, & Buongiorno, 2000). The useof three bid prices raised the need for three versions of the ques-tionnaire, one for each bid price.

Part 3 of the questionnaire was designed to capture those socio-economic and demographic characteristics of respondents (age,gender, level of education and income) that have been shown inprevious studies to play a role in user valuation of similar spaces(Álvarez & Larkin, 2008; Creel & Farell, 2008; Jim & Chen, 2006;Maat & De Vries, 2006; Mmopelwa, Kgathi, & Molefhe, 2007;Tyrväinen & Väänänen, 1998).

Part 4 was designed as a laddering interview to reveal themeans-end chains formed by respondents and thus determine thebenefits they expect to obtain and personal end values they hope tofulfil by using the park. In other words, this procedure tests for linksbetween certain personal values of the individual, the benefitsderived from green space use, and the associated attributes. Thisinformation, as stated earlier, may serve to guide environmentalmanagement.

A pre-test carried out prior to the survey on a sample of 30subjects helped to improve the validity and user-friendliness of thequestionnaire. The design and administration of the pilot study tookplace in a series of meetings and interviews with experts and focusgroups, who suggestedminor adjustments. All thosewho answeredthe questionnaire remarked on its clarity, readability and ease ofunderstanding. As a result, no rewording of the items was required.

The chosen methodology was face-to-face interviews adminis-tered to respondents during their visit to the park. On average,respondents took 15e20 min to fill out the questionnaires. Theywere also encouraged to make further suggestions to the inter-viewer. Interviews with samples of visitors to the two parks tookplaceover theperiod JanuaryandFebruary2008. This resulted in180usable questionnaires from the 200 visitors recruited from thevarious zones of the “Monte San Pedro Park” (A Coruña, Spain); butonly 110 valid replies to the laddering interview section, due to itslength and complexity. This is a larger sample than reported in otherstudies applying MEC theory, where, due to the numerous linkagesgenerated by this type of methodology, the average is 60 (Leppardet al., 2004). Using distributions published in local census data7 itwas possible to stratify the overall sample by age and gender. This

5 The proposed assessment scenario and the contingent valuation questions areexplained in Annex 1.

6 The three bid prices were set based Silverman and Klock (1989) and Del Saz andSuárez (1998) and the recommendations of the focus groups and panels of expertsconsulted in the pre-test.

7 Data from statistical sources in the area concerned (Instituto Gallego de Esta-dística (IGE)) show the samples to be representative of local age, gender andincome strata, allowing us to conclude that San Pedro park is used by a represen-tative cross-section of the local population.

helped to reducepotential samplingerrorand increase the likelihoodof generating a representative sample of the A Coruña population.

This methodology section concludes with a brief description ofthe survey area.

3.4. The peri-urban green space selected for the study: Monte deSan Pedro Natural Park (Coruña e Spain)

The Monte de San Pedro Natural Park, opened on June 6, 1999, islocated in the north-west of the Iberian peninsular (Spain). It isa large, topographically varied area measuring 7.84 ha, offeringvistas of the city of A Coruña (Galicia) and a wide strip of coastlinestretching from Cape San Adrián and the Sisargas Islands, which lieto the west, to Cape Prior and Cape Prioriño to the east. Theseashore is of particular interest due to its characteristic rockformations, and the flora and fauna8 dispersed throughout the parkadd a touch of colour and vitality to the scenery.

Abandoned army bases have left underground shelters,barracks, lookout posts and shore batteries. The panoramic view asone descends from the park includes all the major landmarks of thecity below. In addition to what nature itself has provided, there areplenty of tracks and pathways, landscaped areas, public amenities,ponds and information panels, etc. Since admission is free to allwho wish to enjoy the views, and generally relax, this park makesa major contribution to the leisure and recreational opportunities,and hence the quality of life, of locals and visitors alike.

4. Results

4.1. Characterisation of the groups based on theirvaluation of the green space

The primary goal of this study is to reveal the cognitive structureof visitors to a peri-urban green space. An additional aim is todetermine whether the complexity of the cognitive structure of thevisitors and the linkages they establish differ according to theirmonetary valuation of the green space considered. To achieve theseobjectives, two hierarchical value maps were created, one for thegroup in which the contingent valuation estimate of WTP for greenspace benefits was higher than zero and another for the groupdeclaring unwillingness to pay.

The two WTP groups were first characterised by usagefrequency, user satisfaction levels, socio-demographic characte-ristics and differences with respect to the overall sample. Asalready noted, of the 180 respondents who completed the ques-tionnaire, only 110 correctly completed the in-depth ladderinginterview. To assess whether the visitor profile remained invariantover the whole sample (n¼ 180) and the subsample (n¼ 110),their respective socio-demographic profiles were estimated. Table1A in Annex 2 and Table 2 give the profiles of the overall sampleand subsample, respectively. Comparison of the two tables revealsa similar visitor profile in both groups, despite the difference insample size. Groups 1 and 2 contain similar proportions ofrespondents (�50% in each group). In both the overall sample(n¼ 180) and the subsample (n¼ 110), group 2 respondents (thosedeclaring willingness to pay for the use and enjoyment of the parkfacilities) show a lower rate of usage (42% versus 50%) anda higher level of user satisfaction (7.17 versus 7.18) than the overallsample. In socio-demographic terms, the proportion of positive

8 The flora are dominated by yellow gorse and pink heather interspersed withother typical coastal plants, some of them unique to the area. A great variety ofsmall birds including warblers, goldfinches and linnets add life and colour to thescenery.

Table 2Characterisation of respondents based on willingness or unwillingness to pay for use of the green space (n¼ 110).

Group 1 Group 2 c2a/Fb Sig.

Respondents who are unwilling to payfor use of the peri-urban green space, 49%

Respondents who are willing to pay for useof the peri-urban green space, 51%

Frequency of visitsSporadic 64.8% 50.0% 2.46a 0.12Weekly/monthly 35.2% 50.0%

General level of satisfaction 6.78 7.18 2.59b 0.11

AgeUnder 20 0.0% 8.9% 6.15a 0.1921e30 25.9% 32.1%31e50 61.1% 48.2%51e65 11.1% 8.9%Over 65 1.9% 1.8%

GenderMale 53.7% 53.6% 0.00a 0.99Female 46.3% 46.4%

IncomeLow 42.6% 23.2% 5.38a 0.07Average 46.3% 55.4%High 11.1% 21.4%

Level of educationLess than high 25.9% 14.3% 3.20a 0.20School/vocational school 29.6% 42.9%University Degree 44.4% 42.9%

*All the parameters have a non-significant value, p> 0.05.a Levels of statistical significance determined by Pearson’s chi-square tests.b Levels of statistical significance determined by the Anova F.

9 As indicated in the methodology section, the questionnaire included a controlitem in order to distinguish protest zeros from real zeros. The scale items designedto identify reasons for unwillingness to pay are given in Appendix 1.


willingness to pay is higher in the 31e50 age category (53.4% forthe overall sample and 48.2% for the subsample), and in themiddle-high class income group (60.2% for the overall and 55.4%for the subsample).

The only noteworthy socio-demographic difference betweenthe two groups in both samples is disposable income (for theoverall sample: c2¼10.90 (sig. 0.00); for the subsample: c2¼ 5.38(sig. 0.07)), which is not surprising given that WTP for use of thepark is the classification criterion. Income usually tends to playa role in WTP for environmental goods. Thus, low income is posi-tively associated with unwillingness to pay.

Following the proposed objectives, the next step is to determinethe cognitive structure displayed by each group. The ultimateinterest is to test for variation in cognitive structure in relation toWTP, taking into account both the range of issues considered in thedecision-making process and the level of abstraction. The maindistinguishing feature between this study and others relatingpersonal values to WTP (Cooper et al., 2004; Harris & Brown, 1992;Kotchen & Reiling, 2000; Mill et al., 2007) lies in the fact that theselected methodology enables detection of interrelations betweenpersonal values, desired benefits and the differentiating attributesof the good in question.

4.2. Contingent valuation results

As already stated, WTP was estimated by the contingent valua-tion method. Table 3 presents the results of the estimation of thelogit models for the overall sample (n¼ 180) and the subsample ofladdering interviews (n¼ 110), to enable comparison of the results.

The table shows that mean WTP is 1.33 Euros for the overallsample and 1.014 Euros for the smaller subsample. The significanceof the bid price variable in both models (overall sample: t¼�4.62(p< 0.01); subsample: t¼�2.75 (p< 0.01)) suggests the presenceof starting-point bias.

The data shown in Table 3 also reveal the influence of socio-demographic variables on WTP in both samples. The bid price

retains its significance (overall sample: t¼�4.48 (p< 0.01);subsample: t¼�2.82 (p< 0.01)), and higher WTP can still beobserved among the younger members of the subsample(t¼�1.63 (p< 0.10)) and among the women in the overall sample(t¼ 2.03 (p< 0.05)).

In order to complete the contingent valuation results andanalyse real WTP9, all protest responses were removed from thesample (Cho, Yen, Bowker, & Newman, 2008; Verbic & Slabe-Erker,2008). This reduced the number of observations to 97 in the overallsample and 66 in the subsample. The response options: “I alreadypay enough in taxes” and “I’m not sure the money would be put togood use” were interpreted as protest responses.

After screening for protest responses, a repeat logit analysisresulted in considerably higherWTP values than those presented inTable 3 (a mean WTP of 2.38 Euros for the overall sample and 2.74Euros for the subsample). The statistical significance of the bid pricevariable in both models is slightly higher (overall sample: t¼�4.65(p< 0.01); subsample: t¼�3.01 (p< 0.01)), again suggesting thepresence of starting-point bias.

Table 4 reveals the influence of the socio-demographic variableson real WTP in both samples. The bid price retains its significance(overall sample: t¼�4.46 (p< 0.01); subsample: t¼�2.68(p< 0.01)), and therewas no significant variation in the effect of theremaining socio-economic variables.

4.3. Hierarchical value maps

The WTP profiles resulting from the CV application describedabove enabled the construction of two 6-level hierarchical valuemaps, one for each WTP group. The cut-off points for the differentlevels of abstraction appear in Table 5. These maps show all the

Table 3Logit models estimated to calculate mean WTP and assess the influence of socio-economic variables.

Hanemann’s model E(WTP)

n¼ 180 n¼ 110

Coefficient T-Ratio Coefficient T-Ratio

Constant 1.672 2.779*** 0.918 1.25Bid price �1.260 �4.62*** �0.905 �2.75***

Log-likelihood �83.10 �56.96Chi-squared 26.95 8.67Sig. 0.000 0.003

E(WTP) 1.33 Euros 1.014 Euros

Logit model estimated to assess the influenceof socio-economic variables

n¼ 180 n¼ 110


Constant 1.370 0.87 0.297 0.163Bid price �1.250 �4.48*** �0.965 �2.82***Age �0.289 �1.14 �0.515 �1.63*Gender 0.817 2.03** 0.777 1.57Education level �0.087 �0.34 0.234 0.71Income 0.263 0.806 �0.029 �0.08Frequency �0.273 �0.667 0.20 0.40


*p< 0.10, **p< 0.05, ***p< 0.01.

Table 5Cut-off points for the 5 levels of abstraction and percentage of total cases.

Group 1 Group 2

Respondents who areunwilling to pay for useof the peri-urbangreen space

Respondents who arewilling to pay for useof the peri-urbangreen space

Cut-off point % Cut-off point %

Level 1 ACa 32 29.0 34 30.9CVb 26 23.6 25 22.7

Level 2 AC 29 26.3 28 25.4CV 23 20.9 22 20.0

Level 3 AC 26 23.6 25 22.7CV 21 19.0 21 19.0

Level 4 AC 25 22.7 23 20.9CV 20 18.1 19 17.2

Level 5 AC 24 21.8 20 18.1CV 19 17.2 18 16.3

Level 6 AC 22 20.0 19 17.2CV 15 13.6 17 15.4

a Attribute-consequence.b Consequence-value.


attribute-consequence linkages and all the consequence-valuelinkages at or above the frequency of the sixth level of importance.Following Leppard et al. (2004) the cut-off point is different forevery level of abstraction and group of subjects, enabling use of themaps for between-group comparison. Thus, the cut-off point for theattribute-consequence linkages is 22 on the map of the “unwilling-to-pay” group and 19 on that of the “willing-to-pay” group. The cut-

Table 4Logit models estimated to calculate mean WTP and assess the influence of socio-economic variables without protest responses.

Hanemann’s model E(WTP)

n¼ 97 (total sample) n¼ 66 (subsample)


Constant 3.58 4.38*** 3.54 3.12***Bid price �1.502 �4.65*** �1.29 �3.01***


E(WTP) 2.38 2.74

Logit model estimated to assess the influenceof socio-economic variables

n¼ 97 n¼ 66


Constant 2.60 1.22 3.80 1.36Bid price �1.57 �4.46*** �1.31 �2.68***Age 0.06 0.17 �0.205 �0.39Gender 0.39 0.69 0.252 0.31Education level 0.34 0.90 0.568 1.16Income 0.13 0.31 �0.315 �0.53Frequency �0.65 �1.20 �0.817 �1.03


*p< 0.10, **p< 0.05, ***p< 0.01.

off points for the consequence-value linkages are 15 and 17,respectively.

Figs. 1 and 2 show the HVM (hierarchical value maps) for thetwo groups, with cut-off levels of 6 in both cases. The percentagevalue that appears next to each element in the chain (attributes,consequences and values) indicates the proportion of respondentsmaking that particular linkage. Both groups show a high frequencyof linkages between the different levels on the ladders, giving aninitial indication of the relevance of the items selected for the MECanalysis. That is, respondents establish a considerable number oflinkages between the attributes of the park, the consequences orbenefits they obtain from it, and their own personal values. Thissupports the notion that personal values play a part in users’perception of the attributes or differentiating features of the envi-ronmental good, with variations according to the desired conse-quences or benefits.

Analysis of the information provided by these linkages reveals,first, the existence of interesting between-group similarities. Thus,in terms of attributes, both groups value concrete features suchas “a place to practice sport and take physical exercise”and “distance from home”. One of the concrete attributes consi-dered only by the positive WTP group is “price”, indicating itsinfluence on WTP for green space facilities. The MEC method alsoshows which abstract attributes are important. The results indicatethat the two groups have similar views on issues relating to the useand enjoyment of the park, since both value “landscape beauty”,“benefits to the health” and “less noise”.

In this kind of discussion, it is usual to make a distinctionbetween functional and psychological consequences. As far asfunctional consequences are concerned, both groups appear tovalue the frequency of visits (“frequency of use”), the opportunityto take a break from the daily routine (“a way to escape fromroutine”) and environmental awareness (“I help the environment”).The finding that the positive WTP group was the only one to focuson the issue of “ecological habits” is a clear signal to managers ofthis type of environmental goods that ecological awareness isassociated with higher WTP for green space use.

The two groups also share a similar profile with respect topsychological consequences, both showing an appreciation for thepsycho-physical benefits derived from green space use (“physicalwell-being” and “mental well-being”) and the resulting healthbenefits (“stress relief” and “rest”). In short, visitors appreciate boththe functional and psychological benefits of green space use,

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AttributesConsecuencesValues

A place to takephysical exercise

Physicalwell-being

29.0%

A source of

fun, pleasure

and enjoyment

Benefits tothe health

Less noise

Stress relief

Landscapebeauty

Mental well-being

Rest

Distance fromhome

A way toescape

fromroutine

Enhaces my

quality of life

and security

Better

relationships

with others

A sense of self-

fulfilment and

accomplishment

I help theenvironment

Complete ladder Incomplete ladder

Frequencyof use

23.6%

20.9%

20.0% 26.3%21.8% 20.0% 22.7%

13.6%

17.2%

18.1%

19.0%19.0%

17.2%

23.9%17.2%

Fig. 1. Hierarchical value map for Group 1 “Respondents unwilling to pay for use of the peri-urban green space” (for a cut-off point of 6).

30.9%

Peace of

mind dignity

and

selfrespect

Complete ladder Incomplete ladder

Price

17.2%

15.4%

17.2% 18.1%

20.9%

25.4%

22.7%

18.1%

20.9%

18.1%

22.7%20.0%17.2%

17.2%

16.3% 19.0%

19.0%17.2%

A place to takephysical exercise

Distance fromhome

Benefits tothe health

Less noise Landscapebeauty

Physical well-being

A source of

fun, pleasure

and enjoyment

Stress reliefMental well-

beingRest

A way toescape

fromroutine

Enhaces my

quality of life

and security

Better

relationships

with others

A sense of self-

fulfilment and

accomplishment

I have goodecological

habitsFrequency

of useI help the

environment

AttributesConsecuencesValues

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Fig. 2. Hierarchical value map for Group 2 “Respondents willing to pay for use of the peri-urban green space” (for a cut-off point of 6).


Table 6Average numbers of complete and incomplete ladders.

F deSnedecor

Group 1 Group 2

Respondents who areunwilling to pay for use ofthe peri-urban green space

Respondents who arewilling to pay for use of theperi-urban green space

Completeladders

0.331 13.57 14.70

Incompleteladders

5.204** 4.11 2.84

**p< 0.05.


although the ecological component has greater weight amongthose whose monetary valuation of the good is higher.

A final key aspect of the between-group comparison concernsthe personal end values included in the hierarchical structure,which fall into two categories: instrumental and terminal. Bothgroups mention the instrumental values “A source of fun, pleasureand enjoyment” and “enhances my quality of life and security” andthe terminal values “better relationships with others” and “a senseof self-fulfilment and accomplishment”. Another terminal value“Peace of mind, dignity and self-respect” appears only in thepositiveWTP group. The greater use of values, particularly terminalvalues, by this group appears to suggest an association betweenWTP and a higher level of abstraction. Overall, the results confirmthe relevance of personal values in the valuation of green spaces.These initial results, nevertheless, call for deeper analysis andfurther examination of the ladders generated by the MEC applica-tion to enable clearer conclusions regarding the difference inabstraction levels between the two groups.

4.4. Analysis of the HVM ladders

The initial results described above are eligible for further ana-lysis aimed at advancing in the understanding of the means-endchain formation process through which users link green spaceattributes to consequences and thence to values. The laddersobserved in this study show four linkages common to all respon-dents, irrespective of WTP levels. The most important chain is theone linking the concrete attribute “a place to practice sport and takephysical exercise”, the psychological consequence “physical well-being” (formed by 29.0% of the zero WTP group and 30.9% of thepositive WTP group) and the instrumental value “a source of fun,pleasure and enjoyment” (19.0% versus 22.7%). This appears tosuggest, as might be expected, that one of the main values pursuedby green space users is the pleasure of exercise and keeping fit.A second important chain links the concrete attribute “distancefrom home” to the functional consequence “frequency of use”(23.6% of the zeroWTP group, 17.2% of the positiveWTP group) andthe value “a source of fun, pleasure and enjoyment” (17.2% versus17.2%). This is also unsurprising, given that, where green space useis concerned, frequency depends on proximity, and enjoymentincreases with frequency. The third key feature concerns the lin-kages between the abstract attribute “benefits to the health” andthe psychological consequences “stress relief” (26.3% for the zeroWTP group, 20.9% for the positive WTP group) and “mental well-being” (21.8% versus 25.4%). The latter, in turn, appear linked to theinstrumental value “a source of fun, pleasure and enjoyment”(19.0% versus 17.2%) and the terminal value “better relationshipswith others” (13.6% versus 19.0%).

The last key linkage, common to both groups, is between theabstract attribute “less noise” and the psychological consequences“stress relief” (20.0% for the zero WTP group, 20.9% for thepositive WTP group) and “rest” (22.7% for both groups) and theinstrumental values “a source of fun, pleasure and enjoyment”(19.0% versus 17.2%) and “enhances my quality of life and secu-rity” (23.9% versus 19.0%), respectively. This is a further reflectionof the association between green space use and health benefits.Thus, this methodology provides further confirmation of theinteresting linkages that environmental goods users establishbetween aesthetic, health-related, psycho-physical and socialbenefits.

Across the sample as a whole, therefore, the ladders thatappear on the HVMs indicate more basic, less complex, associa-tions between instrumental values, such as fun, pleasure andenjoyment, and the park’s concrete attributes, such as opportu-nities for practising sport and keeping fit or the possibility of

frequent visits. The linkages between park attributes and healthbenefits reveal more abstract or complex associations involvingterminal values, such as the enhancement of relationships withothers and quality of life.

Nevertheless, the HVMs also reveal a series of between-groupdifferences in some of the ladders. An important factor for thepositive WTP group is “price”, that is, the admission fee, an attri-bute associated by this group with the functional consequence“frequency of use” (a link formed by 18.1% of the respondents) andthe instrumental value “a source of fun, pleasure and enjoyment”(17.2%). Similarly, this group linked the abstract attribute “lessnoise” with the psychological consequence “mental well-being”(18.1%) and the terminal value “better relationships with others”(19.0%). Lastly, a linkage appears between the abstract attribute“landscape beauty” and the psychological consequence “rest”(18.1%) and the instrumental value “enhances my quality of life andsecurity” (19.0%). Particularly striking is an incomplete ladder thatis exclusive to this group, linking the functional consequence“I have good ecological habits” and the terminal value “peace ofmind, dignity and self-respect” (17.2%).

These results may lend support to the assertion thatcognitive structures involving health-related factors (noise avoi-dance, rest inducement, improvement of mental well-being) aremore complex, since they include a greater number of linksbetween abstract attributes and instrumental and terminal values(quality of life at the individual level and better relationships andpeace of mind at a more social, collective level). A further finding isthat respondents link concrete attributes, such as use of the park forrecreation, sports practice, and appreciation of the landscape topersonal enjoyment. Lastly, it is worth noting that linkages relatingto ecological issues are more numerous among those declaringpositive WTP. The following section proceeds with the analysis inorder to determine whether the initial differences, in terms of thecomplexity of the cognitive process as revealed by the HVMs forthe zero WTP and positive WTP groups, find further reflection indifferent degrees of abstraction.

4.5. Comparison of abstraction levels

Having identified the desired attributes, consequences andpersonal values of each WTP group, and established the chains oflinkages, the next step was to assess the degree of abstraction ofeach group’s cognitive structure. This was done by calculating theaverage number of ladders and average number of elements of eachlevel (attributes, consequences and values), formed by each groupin order to check for possible between-group variation.

The sum of ladders for the overall sample was 1,917. The sortingof these by WTP group revealed statistically significant differencesin terms of the average number of incomplete ladders, as shown inTable 6. Thus, respondents belonging to the positive WTP groupformed an average of 14.70 complete ladders and 2.84 incomplete

Table 7Average numbers of attributes, consequences and values done by each group

F Snedecor Group 1 Group 2

Respondents who are unwilling topay for use of the peri-urban green space

Respondents who are willing to pay foruse of the peri-urban green space

Concrete attributes 0.972 3.64 4.00Abstract attributes 0.833 7.36 6.74Functional consequences 2.651* 4.35 5.03Psychological consequences 1.114 6.75 7.36Instrumental values 0.505 4.62 4.91Terminal values 8.573*** 3.32 4.77

*p< 0.10 and ***p< 0.01.


ladders (F¼ 5.204, sig< 0.05), versus 13.57 complete and 4.11incomplete in the zero/negative WTP group (F¼ 0.331, sig> 0.10).These initial findings already point to greater complexity in thepositiveWTP group, because its members form a greater number ofattribute-consequence-value chains. Nevertheless, fuller analysiswill be required in order to support these findings.

The above results reveal a certain degree of abstraction in greenspace valuation, varying with WTP. Table 7 presents a summary ofthe average numbers of attributes, consequences and values eli-cited from each group. The statistically significant differences thatcan be observed relate to the number of terminal values (F¼ 8.573,sig< 0.01), which is greater in the positive WTP group, indicatingslightly more complexity or abstraction in their valuation process,which suggests higher personal involvement (Walker & Olson,1991). The presentation of the findings concludes with thefollowing table showing the complexity indices.

4.6. Complexity indices

The final part of the analysis was to compare the complexity ofthe attribute-consequence-value chains appearing on the HVMs ofthe two WTP groups, using the so-called complexity index, firstdeveloped by Bagozzi and Dabholkar (1994). Two complexityindices were estimated. The first, labelled C1, measures complexityin terms of the concepts used in the HVMs. It is the result ofdividing the number of complete chains on each HVM by the totalnumber of attributes, consequences and values represented. Thesecond, labelled C2, measures complexity in terms of the linkagesforming the ladders on the HVMs. It is the result of dividing thelength of each chain of concepts (that is, the sum of its linkages) bythe overall sum of linkages on the HVM.

As can be seen from Table 8, the positive WTP group scoredhigher than the zero WTP group on C1 (96.74 versus 94.75), but noton C2 (1.42 versus 1.50). These results reveal an associationbetween WTP and greater complexity of the hierarchical valuestructure in terms of the number of attributes, consequences andvalues it includes. In contrast, there is no apparent associationbetween WTP and greater complexity in terms of the number oflinkages established between the attributes, consequences andvalues. Thus, as previous analyses have already shown, there is no

Table 8Complexity indices.

Number ofcognitions(a)

Numberof links(b)

Numberof paths(c)

Totallength ofpaths (d)

C1

(b/a)C2(d/c)

Respondents whoare unwilling to pay

16 1516 16 24 94.75 1.50

Respondents whoare willing to pay

19 1838 19 27 96.74 1.42

clear evidence of more complex cognitive structures in respondentsdeclaring higher WTP. A fuller explanation of the complexity of thegreen space user’s decision-making process will therefore requiremore detailed analysis.

5. Discussion and conclusions

The conception and valuation of natural spaces in general, andperi-urban green spaces in particular, have evolved in line withincreasing awareness of the multiple benefits they provide interms of the physical and mental health of users. This evolutionhas given rise to a new approach to the valuation of naturalresources that takes into account, as well as user socio-demo-graphics, monetary valuation and the psycho-physiological bene-fits offered by such areas, the personal values and emotionalattachments that visitors associate with them. Emotional benefitsplay such an important role in people’s daily lives, particularly indecisions relating to the use and monetary valuation of greenspaces, that they can be said to play a key role in generatingsubjective responses in visitors and influencing the way they useand perceive green space facilities.

Inspired by the suggestion that emotional responses to greenspace use may play a key role, this study set out to explore thecognitive structures of a sample of green space visitors and estimatetheir WTP for such resources. The underlying cognitive structurewas revealed by means of means-end chain (MEC) methodology.From an overall sample of green space visitors, two subsamplesbased on contingent valuation estimates of WTP emerged. Theresulting visitor profile showed that respondents declaring wil-lingness to pay for the use and enjoyment of park facilities reportlower usage frequency rates and higher user satisfaction levels andtend to fall into the 31e50 year old, middle class/middle incomegroup. Thesefindings are consistentwithprevious researchongreenspace visitor typologies (Jim & Chen, 2006; Vesely, 2007; Yilmaz,Zengin, & Yildiz, 2007, among others). The only noteworthy socio-demographic difference between the two groups in both samples isdisposable income. This initial finding is consistent with priorresearch, where higher WTP is always associated with higherincome groups (Feinerman, Fleischer, & Simhon, 2004; Mmopelwaet al., 2007; Togridou et al., 2006; Gürlük, 2006). This supports theconclusion that the variation subsequently found in the analysis ofthe decision-making structure is due not to differences in visitorprofiles but to different perceptions of the attributes, consequencesand values under scrutiny.

The contingent valuation estimates of WTP were low at 1.33Euros for the overall sample and 1.014 Euros for the smallersubsample, revealing the possible presence of starting-point bias.Furthermore, only 51% of the subsample and 49% of the overallsample declared their willingness to pay for the facilities.These percentages of positive WTP responses lie withinthe range of sample percentages obtained in similar studies: 79%

Reason for unwillingness to pay Score

I already pay enough in taxesThis environmental resource is not worth

an entrance feeI’m not sure the money would be put to

good useI think entrance should be free of chargeI couldn’t afford to pay an entrance feeDon’t know/no answer


(Meyerhoff & Liebe, 2006); 35% (Adams et al., 2008; DelSaz, Barreiro, & García-Menéndez, 2003); and 46.8% (Jones,Sophoulis, & Malesios, 2008). These high refusal-to-pay ratessuggest considerable resistance to the elicitation format used andthe unfamiliarity of Spanish respondents with this kind of decision-making process (Del Saz-Salazar & Rausell-Köster, 2008).

The high refusal-to-pay rates obtained in this study led toa repeat analysis excluding protest zeros, which resulted ina substantial improvement of the mean WTP values, that is, 2.38Euros for the overall sample and 2.74 Euros for the smallersubsample, although the possibility of the presence of starting-point bias still remained. This shows the influence of protest beliefson WTP, in the sense that, the higher the number of protestresponses, the lower the WTP for the environmental good inquestion (Meyerhoff & Liebe, 2006). The high rate of protest bidsobtained in this analysis might be explained by poor economicstatus (low income or unemployment) and hence inability to pay,and difficulty in expressing the somewhat abstract idea of valua-tion in monetary terms (Jim & Chen 2006; Tyrväinen & Väänänen,1998).

The MEC analysis, performed with the in-depth ladderinginterview technique, confirmed that a large number of values areassociated with the enjoyment of environmental goods. Observa-tion of the HVM (hierarchical valuemaps) reveals the importance ofcertain concrete and abstract attributes (sporting activities, distancefrom home, landscape beauty, health benefits). These results fall inline with findings obtained with different methodology, indicatingthat green space valuation depends on the admission fee, theproximity, and the facilities provided (Baral et al., 2008; Togridouet al., 2006; Tyrväinen & Väänänen, 1998). An association betweenthe positive valuation of the environmental good and the search forbeautiful scenery and quieter surroundings has also been reported(Lee & Han, 2002; Prada, González, Polomé, Gómez, & Vázquez,2001). Some findings also point to the influence of awareness ofthe functional and psychological benefits provided by green spaceuse (Chiesura, 2004; Davenport et al., 2002; Gidlöf-Gunnarsson &Öhrström, 2007). Previous studies using alternative methodologyhad already reached conclusions regarding the influence of valuefulfilment, both individual (relating to fun or quality of life) andsocial (relationships with others), on the valuation of green spaces(Ford et al., 2009; González, 2002; Harris & Brown, 1992; Hanleyet al., 2009; Mill et al., 2007; Tyrväinen et al., 2007). Involvementin ecological issues and social awareness also feature stronglyamong the values revealed by the positive WTP group.

All of the above supports the conclusion that there is anemotional component in what peri-urban green spaces offer theirusers. In addition, respondents expressing willingness to pay showgreater personal involvement through the terminal values theyassociate with the environment and claim to get more than merefun and enjoyment out of their visits. Psychological consequencesor benefits, such as rest or stress relief, feature more prominentlyin association with positive WTP. The awareness of health benefitsresulting from the enjoyment of environmental goods leads tomore complex cognitive structures, that is, greater involvement ofthe subject’s personal values, where social values play a strongerrole than individual values. This confirms the already-acceptedassociation between health benefits and the use of this type ofgoods (Hansmann et al., 2007; Kaplan, 1995; Korpela et al., 2008;Maas & Verheij, 2007; Schultz, 2001; Velarde et al., 2007) whilealso revealing the previously reported link with collective or socialactivities (Chiesura, 2004; Sanesi & Chiarello, 2006). Thus, theemotional attachment of people to nature is manifest not only intheir use of green spaces in general or their preference for one inparticular, but also in their perception of green spaces as a meansto satisfy personal values.

Based on the above findings, one interesting conclusion mightbe that the greater the perceived benefits from environmentalgoods, the greater the user’s personal involvement with them. Itwould therefore be useful to convey to the public the range ofphysical and psychological benefits the environment has to offer,in order to increase their involvement in environmental conser-vation and protection and respect for nature. One of the obviouspotential impacts of the perceived mental and physical healthbenefits, and therefore worth factoring into the valuation, is thereduction of the social cost of health care. Furthermore, theproximity of peri-urban green spaces makes them highly acce-ssible to urban dwellers, increasing their health benefit potentialfor this segment of the population. These conditioning factors areworth consideration by land-use managers, who might use themto promote the social value of natural resources and to strengthentheir arguments in decision-making settings involving environ-mental cost/benefit issues. It might also be useful to promotecooperation between representatives of the local population andland-use managers in green space designs.

The application of alternative methodological and attitudinalapproaches or social psychology theories could enrich the analysisof this type of cognitive response and enable the prediction ofenvironmental goods users’ decisions. Further understanding of thecognitive structures of non-visitors would also be desirable, inorder to establish differences between users and non-users. Effortsto match visitor profiles to desired green space attributes andbenefits and to reveal the personal values involved in each casewould also enable extrapolation of the findings to other types ofenvironmental goods.

Annex 1

Questions used in the contingent valuation:

“A periurban park such as .. can be enjoyed for differentrecreational uses. In the questions that follow, therefore, wewish to ask you to estimate a monetary value for the satisfactionor feeling of well-being you obtain from such uses, that is, howyou value the good. Bear in mind that we are asking you to thinkin terms of real payment and to assume that the amount spentcould not be used for any other purpose”

- Taking into account all the possible benefits provided by thearea as a whole, would you be willing to pay an entrance fee ofX V?� Yes� No

- Bearing in mind that you would be willing to pay X V, howmuch more would you be willing to pay?..V

- Bearing in mind that you would not be willing to pay XV, whatis the maximum price you would be willing to pay?..V

- If you are NOT willing to pay, please indicate your reasons byplacing an X in the appropriate box


Annex 2

Table 1ACharacterisation of respondents based on willingness or unwillingness to pay for use of the green space (N¼ 180).

Group 1 Group 2 c2a/Fb Sig.

Respondents who are unwilling to payfor use of the peri-urban green space, 51%

Respondents who are willing to payfor use of the peri-urban green space, 49%

Frequency of visitsSporadic 55.4% 58.0% 0.12 0.73Weekly/monthly 44.6% 42.0%

General level of satisfaction 6.99 7.17 0.83 0.36

AgeUnder 20 0.0% 6.8% 7.65 0.1121e30 27.2% 27.3%31e50 56.5% 53.4%51e65 13.0% 8.0%Over 65 3.3% 4.5%

GenderMale 53.3% 47.7%Female 46.7% 52.3% 0.55 0.46

IncomeLow 44.6% 21.6% 10.90 0.00Average 44.6% 60.2%High 10.9% 18.2%

Level of education 26.1% 17.0% 2.31 0.31Less than high school/

vocational school39.1% 46.6%

University degree 34.8% 36.4%

*Only income shows a significant value, p< 0.05.a Levels of statistical significance determined by Pearson’s chi-square tests.b Levels of statistical significance determined by the Anova F.

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López-Mosquera e Sánchez 2011