Cooperation Among Pro Eminent Actors_Annals of Tourism Research_Beritelli_2011

8/2/2019 Cooperation Among Pro Eminent Actors_Annals of Tourism Research_Beritelli_2011

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COOPERATION AMONG PROMINENT

ACTORS IN A TOURIST DESTINATION

Pietro Beritelli

University of St. Gallen, Switzerland

Abstract: Cooperative behavior in tourism destination communities is a condition for sus-tainable planning and development. However, evidence is lacking on how actors choose tocooperate. Previous research in institutions, organizations, and communities show that for-mal, contract-based as well as informal, relation-based cooperation occur jointly or in substi-tution, depending on the context and the subject of research. However, neither theapproaches nor their underlying dimensions have been tested for the reality of tourist desti-nation communities. For a European Alpine tourism destination the results show that onlyrelation-based items, in combination with communication variables, strongly positively influ-ence cooperative behavior. The paper suggests a series of implications for tourism destinationplanning and concludes with indications for further research. Keywords: contract-basedcooperation, relation-based cooperation, social network analysis, tourism destina-tion. 2010 Elsevier Ltd. All rights reserved.

INTRODUCTION

Cooperation plays a central role for tourism destination communi-ties. Cooperation is a central requirement for sustainable planningand development of destinations (Bramwell & Lane, 2000), for theadvancement and realization of projects ( Vernon, Essex, Pinder, &Curry, 2005), and for the establishment and operation of destination

governance structures (Yuksel, Bramwell, & Yuksel, 2005). In this con-text, the communities comprise a variety of stakeholder groups thatinterweave across networks of actors of private and public institutions(Dredge, 2006), and must find at least partial consensus (Bramwell &Sharman, 1999). The literature on cooperative action among stake-holders in tourism communities describes conceptualizations (Selin,1993), then provides first empirical evidence (Selin & Chavez, 1995),and finally improves the notions from different perspectives andinstitutional angles, mainly with the help of case studies (Aas,Ladkin, & Fletcher, 2005; Getz, Anderson, & Sheehan, 1998; Presenza,

Sheehan, & Ritchie, 2005; Sheehan & Ritchie, 2005).

Pietro Beritelli is Assistant Professor at the University of St. Gallen and Deputy Director atthe Institute for Public Services and Tourism (Dufourstrasse 40a, 9000 St. Gallen, Switzerland.Email:< [email protected]>), where he studies Business Administration.

Annals of Tourism Research, Vol. 38, No. 2, pp. 607629, 20110160-7383/$ - see front matter 2010 Elsevier Ltd. All rights reserved.

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Thus far, most of the research on cooperation and cooperativebehavior, in tourism destinations as well as in other industries, analyzesthe institutional level and centers on the firms and stakeholder groupsas the object of research. This paper is novel in two respects. First, the

paper extends research on this topic to the level of the individual. Thestudy in this report analyzes a network of 42 prominent actors with re-spect to their formal connections, their relational preferences, theircommunicative and their cooperative behavior, revealing the underly-ing dimension of institutional cooperation. Second, the researchempirically applies social network analysis to the prominent actors net-work. With the help of network data the study tests the relevance of twocooperation approaches which are often used as either complementaryor substitutive, namely the formal, contract-based and the informal,relation-based approach. The paper investigates the importance of

interpersonal versus professional connections and identifies the roleof communication in the initiation and realization of cooperative ac-tion. The results show that cooperative behavior in tourism destinationtranspires via interpersonal preferences, which likely override institu-tional agreements. Embedding an actors behavior in the destinationcommunity context and therefore taking account of the multiple rela-tions that affect him and the various cooperation processes hes involved in, extends the current research on organizational andinstitutional cooperation to the individual level with respect to bothprofessional and personal conditions.

LITERATURE REVIEW

For a purposeful approach, this section first explains the need forcooperation and highlights the peculiarities of cooperative behaviorin tourism destinations with the help of selected literature. While coop-eration research in tourism destinations offers numerous contribu-tions, theoretical foundations are meager. Therefore, in the secondsection the prevalent theories which explain cooperative behavior pro-

vide a differentiated picture of the phenomenon. In the third section,the constructs and items derived from the theories set the basis for theempirical research presented in the subsequent section. Figure 1 ex-plains the logic of the three parts of literature research by emphasizingthe main purposes and pointing out that cooperative behavior takesplace in three different contexts (regions and communities, organiza-tions/firms, institutions/administrative and governing bodies) and atthree different levels (individual, groups, organizations).

Cooperation in Tourism Destinations

In communities, three phenomena constrain cooperative behavioramong stakeholders and their institutions (Ostrom, 1991). The firstone is the tragedy of the commons, with no incentive for institutionsto avoid the overexploitation of common resources (e.g. natural

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landscape, cultural assets) (Hardin, 1968), and therefore the lack ofpricing of public goods due to missing property rights. The secondone is the prisoners dilemma, which induces the actors, under theconditions of limited information and non-repeated rounds, not tocooperate even though they would be better off if they cooperated(Axelrod & Hamilton, 1981). The third one is the challenge of collec-tive action, whereby collective failure and the individuals inability toacknowledge the importance of collective goods increases with the size

of the groups, their homogeneity, and the lack of institutionalstructures that promote collective action (Olson, 1965). Hence, coop-eration among stakeholders in tourism destination communities isnecessary but per se neither obviously occurs nor is formally estab-lished (e.g. through public authorities).

Cooperative behavior is multilayered and fluid when firms and insti-tutions act with public goods and within the public space. In fact,shared beliefs and preferences, stable membership, and continuedand direct relationships are typical characteristics for local and regio-nal communities (Singleton & Taylor, 1992). Nee describes this in

the following way:Formal rules are produced and enforced by organizations such as thestate and firms to solve problems of collective action through third-party sanctions, while informal norms arise out of networks and arereinforced by means of ongoing social relationships, to the extent thatmembers of networks have interests and preferences independent of

2.1. Cooperative behavior

in tourist destinations

2.2. Theories explaining

cooperation

2.3. Determinants and

constructs of

cooperative

behavior

identifying the need

and the peculiarities

of cooperation in

tourist destinations

distinguishing the

theories underlying

cooperation and

deriving the

constructs and items

for the empirical

research

objects of research

regions and communities

organizations/ firms

institutions/ administrative and governing bodies

level of research

individual

groups

organizational

Figure 1. Connection Between the Three Parts of Literature Research

P. Beritelli / Annals of Tourism Research 38 (2011) 607629 609


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what rulers and entrepreneurs want. The respective contents ofinformal norms and formal organizational rules are likely to reflectopposing aims and values (Nee, 1998, 8687).

Consequently, in light of community-based tourism planning, cooper-

ation is a process of joint decision making among autonomous, keystakeholders of an inter-organizational, community tourism domain(Jamal & Getz, 1995).

Empirical research on cooperation among stakeholders in tourismdestinations is rather recent and presents a wide range of issues andchallenges. A substantial body of literature deals with community plan-ning and the role of local institutions and local residents (Getz &Jamal, 1994; Gill & Williams, 1994; Ritchie, 1999; Robson & Robson,1996). Although community planning approaches are criticized(Taylor, 1995), they are an expression of what happens in everyday lifein tourist communities: people meet in their professional environmentor privately; talk about issues and about other people; form a viewon something; have disputes or form friendships; and make decisionsat a personal and institutional level. While earlier contributions in thisfield focused on the community as a social system consisting of localresidents, recent empirical research discusses community planning with a more strict classification of stakeholder groups, of which thelocal residents are at most one (Byrd, 2007; Huybers & Bennett,2003; Reed, 1997; Ryan, 2002; Timothy, 1998; Wang & Fesenmaier,

2007).While stakeholder theory addresses morals and values in managingan organization (Freeman & McVea, 1984), it does not help under-stand why individuals, stakeholder groups and organizations cooperateor not. In fact, gathering stakeholders at a round table is no guaranteefor initiating collective action, launching joint projects or sealing alli-ances. The mechanisms and conditions for cooperation are specifiedin a number of different theories.

Theories Explaining CooperationCooperation studies at different levels (i.e. between institutions/

administrations, between firms/organizations, and in communities)distinguish six major theories/approaches: (1) game theory, (2)rational choice theory, (3) institutional analysis, (4) resource depen-dence theory, (5) transaction cost economics, and (6) social exchangetheory. While they could all be used as a single research approach,today they complement one another and contribute jointly to theunderstanding of the complex phenomenon of cooperation.

Perhaps the first most specific theory laying the fundaments of coop-erative behavior is game theory, whereby a set of players carries out aset of moves and attains payoffs for each combination of moves (i.e.strategies). Cooperative games have been described early in the devel-opment of game theory (Von Neumann & Morgenstern, 1944). Notsurprisingly, game theory was the first approach to help forge a theoryof cooperation (Axelrod & Hamilton, 1981). Even until recently, some



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empirical research on cooperative behavior rests on pure gametheoretical assumptions, between institutions (Dinar & Wolf, 1994),between organizations (Heide & Miner, 1992; Hollander, 1990),and between individuals in communities (Bardhan, 1993; Carpenter,

Daniere, & Takahashi, 2004).Compared to the other approaches, game theory could be seen as

the stem out of which the younger branches have evolved. The firstmain branch, tightly linked to game theory, is rational choice theory.It assumes that the behavior of individuals maximizes personal advan-tage (Arrow & Hahn, 1971). Rational choice theory has become popu-lar to explain cooperative behavior in studies of interest groups,coalitions and bureaucracy (Dinar & Wolf, 1994; Dunleavy, 1991;Gately, 1974; Lang, 2002).

However, individuals act as members of organizations as well; and

organizations originate and affect cooperative behavior with givenrules and norms. Hence, institutional analysis helps understand thestructures and mechanisms of social order and cooperative behavior(North, 1971). Like rational choice, institutional analysis is predomi-nantly used for cooperation studies between administrative bodiesand international institutions ( Axelrod & Keohane, 1985; Martin &Simmons, 2005), as it offers direct access to questions regarding thedevelopment of strategies at an institutional level.

Additionally, in order to specify imbalances in cooperation, resourcedependence theory implies that organizations have different resources which are a basis of power. Hence, organizations are dependent oneach other because of different endowments due to their differingenvironments (Pfeffer & Salancik, 1978). Contributions on coopera-tion referring to resource dependence theory are found not only atthe institutional/national level (Christiansen, 2001; Remmer, 1998)but also at the organizational (Lee, Chen, & Kao, 2003; Lusch &Brown, 1996) and at the tourism community level ( Jamal & Getz,1995; Timothy, 1998).

Following the thread of rationality laid by game theory, we come to

transaction cost economics. In contrast to rational choice, which ex-plains the maximization of advantages or profit, transaction cost eco-nomics assumes that individuals and organizations minimize all thecosts incurred in economic exchanges (including cooperation pro-cesses). Transaction costs are determined by their frequency, specific-ity, and uncertainty as well as by the limited rationality and theopportunistic behavior of the involved actors and organizations(Williamson, 1979). In cooperation studies, transaction cost economicsis valuable particularly at the organizational level (Fritsch & Lukas,1999; Gulati, 1995; Lee & Cavusgil, 2006; Luo, 2002; Morgan & Hunt,

1994; Poppo & Zenger, 2002; Ring & Van de Ven, 1992; Ring & Van deVen, 1994; Zaheer, McEvily, & Perrone, 1998).However, all the above mentioned studies have combined transac-

tion cost economics with the sixth major theory: social exchangetheory. Related to rational choice theory, social exchange theoryemphasizes social traits of cooperative games like anticipatedreciprocity, expected gain in reputation and influence, altruism and



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perception of efficacy as well as direct reward (Blau & Alba, 1982; Ekeh,1974; Emerson, 1962; Homans, 1962). Empirical research on coopera-tive behavior based purely on social exchange theory could be found inthe field of inter-organizational cooperation (Mavondo & Rodrigo,

2001; Mohr & Spekman, 1994; Rodrguez & Wilson, 2002) and in tour-ism networks and communities (Aas et al., 2005; Pesamaa & Hair Jr.,2007, 2008).

Beside these six major theories/approaches, there are single contri-butions that highlight specific facets of cooperative behavior. Forexample, cooperation research may focus on contractual dimensionsand hence ground itself in contract theory and negotiation theory(Ness & Haugland, 2005) or may look at cultural differences by con-fronting individualism with collectivism (Chen, Chen, & Meindl,1998). Other research stems from organizational theories, such as

organizational learning (Doz, 1996), the resource-based view (Denicolai,Cioccarelli, & Zucchella, 2009), communicative rationality (Innes, 1996),or a purely structuralist perception (Williams, 2005).

To summarize, cooperative behavior is worthwhile if there is a payoffbased on a strategy (game theory) that maximizes advantages (rationalchoice theory). Actors must take into account that cooperative gamestake place in an institutional context with different norms and rules(institutional analysis) and different resource endowments, whichcause different distribution of power (resource dependence theory).Cooperative behavior is also convenient if costs incurred over thewhole process are minimized (transaction cost theory). Finally, cooper-ative behavior takes place in a social context in which the actors striveto gain reputation and rewards (social exchange theory). The next sec-tion derives a set of constructs and items from the discussed theorieswhich help develop the measurement construct and the variables forthe empirical study.

Determinants and Constructs of Cooperative Behavior

Literature on cooperation repeatedly combines and sometimes con-trasts (Lee & Cavusgil, 2006) two main types/approaches, namely theformal, contract-based and the informal relation-based one. Both ap-proaches could be seen as complementary or alternative perspectivesin the discussion of cooperation (Lee & Cavusgil, 2006). While formalcontract-based cooperation is often a subject of research for coopera-tive behavior between institutions and administrative and governingbodies (Christiansen, 2001; Dinar & Wolf, 1994; Martin & Simmons,2005; Remmer, 1998), informal relation-based cooperation isdistinctive for cooperation in regions and communities ( Aas et al.,

2005; Bardhan, 1993; Carpenter & Westphal, 2001; Denicolai et al.,2009; Timothy, 1998). The first one regards cooperation as a formalagreement which originates in institutional and organizationalresources and assets (Fritsch & Lukas, 1999; Lee et al., 2003; Lee &Cavusgil, 2006), economic dependencies (Poppo & Zenger, 2002;Remmer, 1998; Rodriguez, Langley, Beland, & Denis, 2007), and



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explicitly expected mutual gains (Gately, 1974; Lusch & Brown, 1996;Ness & Haugland, 2005). The formality of contracts relates not onlyto the results of the cooperative actions but also to the governanceof relationships established in the course of the cooperation process

(Ness & Haugland, 2005; Poppo & Zenger, 2002). Hence, it originatesin the professional and institutional context, in which individuals andorganizations operate.

In contrast, informal relation-based cooperation emphasizes mutualtrust (Bardhan, 1993; Denicolai et al., 2009; Pesamaa & Hair Jr., 2007;Ring & Van de Ven, 1992), personal commitment (Mavondo & Rodrigo,2001; Mohr & Spekman, 1994; Morgan & Hunt, 1994), and interrela-tionships (Chen et al., 1998; Innes, 1996; Rodriguez et al., 2007). Thesedimensions could drive cooperative behavior in an organizationalcontext, in which formal contracts govern as well. However, they are

so important that they could substitute the role of formal contracts(Gulati, 1995; Zaheer & Venkatraman, 1995). Both approaches takeinto account that cooperation is a multiple-round game at organiza-tional (Ring & Van de Ven, 1992; Ring & Van de Ven, 1994) as wellas individual levels (Carpenter et al., 2004; Doz, 1996; Luo, 2002;Rodrguez & Wilson, 2002), and that cooperative behavior is supportedby effective communication (Aas et al., 2005; Morgan & Hunt, 1994;Poppo & Zenger, 2002).

Figure 2 illustrates the connection between the six theories and theformal contract-based versus the informal relation-based cooperation

informal relation-

based cooperation

formal contract-

based cooperation

institutional,

organizational resources

economic

interdependencies

explicit mutual gains

mutual trust

personal commitment

interrelationships

effective communication

multiple rounds

transaction

cost

economics

rational

choice

theory

institutional

analysis

social

exchange

theory

game theory

resource

dependence

theory

institutions/

administrative and

governing bodies

organizations/ firms

communities of

individuals

cooperation at various levels and with different

intensities in tourist destinations

Figure 2. Linking Theories, Cooperation Approaches, and the Application toDestinations



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approach. While institutional analysis, rational choice theory, andtransaction cost economics clearly point to the importance of formalcontract-based cooperation, social exchange theory relates to the infor-mal relation-based approach. Research based on the resource depen-

dence theory as well as the game theory applies for formal as well asfor informal cooperation. Reading Figure 2 from top to bottom, thetheory level indicates the specific mechanisms that are relevant incooperation. The formal and the informal approach relate both tothe dimensions which account for the theoretical mechanisms. Analyz-ing these dimensions helps operationalize the variety of possible coop-eration mechanisms which occur in tourist destination communities,because as we see in the bottom circle, cooperation involves institu-tions, organizations, and individuals and cooperative behavior pro-duces various forms and intensities of cooperation.

As indicated above, for tourism destination communities there maybe both formal contract-based as well as informal relation-based typesof cooperation approaches, depending on the specificity of the agree-ment and the conditions and circumstances under which the actorsconvene. As the actors represent institutions and organizations, theyare not only rational in their decision to cooperate but they also showa propensity to cooperate in a professional environment. Hence, wecan assume that on one hand cooperative behavior is supported by pro-fessional acquaintance and institutional/organizational connections.On the other, we must assume that actors are likely to cooperate if theytrust and understand each other, sometimes independently from theirinstitutional/organizational affiliation. But which of the two assump-tions is valid? Or are both equally relevant? These issues underlie thefundaments of the empirical research.

While the theories presented in the previous section help explainthe broader context of cooperative behavior and serve as cornerstonesfor the final discussion section, the differentiation between formal con-tract-based and informal relation-based cooperation defines the itemselection for the empirical study.

METHOD

Research Questions and Measurement Construct

In the empirical part, the research hypothesizes and tests four con-structs for cooperative behavior derived from the literature research:formal contracts; relational preferences; communication behavior asmodulating construct between the first two; and cooperative behavioras the dependent construct. Eleven variables represent the constructs:

The first three relate to formal contracts. They are (1) institutionalconnection (actors cooperate because their institutions are formallyconnected to each other) (Gulati, 1995; Lusch & Brown, 1996;Mavondo & Rodrigo, 2001), (2) professional contact (actors cooperatebecause of professional reasons, even if they would not want to; work-ing together is explicitly not formulated as cooperation) (Innes, 1996;



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Lee & Cavusgil, 2006; Rodriguez et al., 2007; Timothy, 1998), and (3)political contact (actors cooperate because they share common politi-cal interests or are obliged to work together at the political level, e.g.municipal authorities, commissions) (Benson, 1975; Yeung, 1997).

The next three reflect communication behavior, namely (4) commu-nication intensity (actors communicate with some people more inten-sely than with others) (Axelrod & Keohane, 1985; Mohr & Spekman,1994; Morgan & Hunt, 1994; Rodrguez & Wilson, 2002), (5) contactease (actors have easier access to some people than to others, e.g. ifthey want to discuss something with them or if they want to initiate acollective action) (Christiansen, 2001; Rodrguez & Wilson, 2002),and (6) information exchange (actors share information about thedestination and about other people, including gossip) (Heide &Miner, 1992; Poppo & Zenger, 2002).

Three other variables refer to relational preferences, which are (7)sympathy (actors like some people more than others) (Bardhan,1993; Pesamaa, Ortqvist, & Hair, 2007), (8) trust (actors trust somepeople more than others) (Gulati, 1995; Mohr & Spekman, 1994;Morgan & Hunt, 1994; Zaheer et al., 1998), and (9) understanding(actors get along with some people better than with others) (Gulati,1995; Lee & Cavusgil, 2006). Finally, (10) starting initiatives (actorslaunch initiatives and projects more easily with some people than withothers) (Carpenter et al., 2004; Ness & Haugland, 2005; Ring & Van deVen, 1994; Zaheer et al., 1998), and (11) success of initiatives (imple-mented initiatives are more or less successful) (Doz, 1996; Lee et al.,2003; Ness & Haugland, 2005), describe cooperative behavior.

The context of cooperative behavior among actors and organizationsin tourist destination communities comprises various areas of cooper-ation (e.g. the formal creation of a marketing pool, the developmentof a jointly owned sport facility, the establishment of a sales deal withthe help of travel packages) and various intensities of cooperation(e.g. the formulation and the development of a common price strategyin the committee of a transport association, the shuttle service between

a hotel and a ski school). Additionally, cooperative behavior takes placebetween and among public institutions and private organizations aswell as between single individuals and therefore in a setting in whichthe term cooperation assumes different meanings depending onthe role of the respondents and the organizational context in whichthey operate. The research of this paper is not to investigate which typeof cooperation is originated and founded on which dimensions. It doesneither categorize nor evaluate any type of outcome from cooperativebehavior. As a matter of fact, it focuses on the drivers of human behav-ior that lead to establish every kind of cooperation. Independently

from the abovementioned differentiations of cooperation, the hereinpresented study assumes that cooperative behavior leads through for-mal or informal conditions to more or less successful results. Hence,the variables starting initiatives and success of initiatives reflect the whole universe of cooperative processes as understood by variousrespondents in various settings. By asking them about the success ofinitiatives, the study takes into account that every respondent could



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consider more than one initiative and therefore more than one coop-erative process. Thus the answers comprise the individuals perceptionof possible multiple rounds, a dimension which is only explicitly oper-ationalized in longitudinal studies.

Based on the abovementioned considerations, two null hypothesesguide the empirical research of this paper:

1. The approaches of formal contract-based and informal relation-basedcooperation are not valid for the case of a tourist destinationcommunity.

2. Cooperative behavior is not depending on variables referring to formalor to informal cooperation.

Figure 3 presents the constructs relating to the hypotheses. Institu-tional connections, professional contact, and political contact are as-sumed to refer to formal ties (named here formal contracts) whilesympathy, trust, and understanding represent relation-based variables(named relational preferences). The construct communication behav-ior could relate both to formal contracts and/or relational preferences,because communication intensity, ease of getting in contact, and infor-mation exchange are observable in either environment. Hence, thisconstruct acts as a modulating dimension between the otherconstructs. Finally, starting initiatives and success of initiatives reflect

institutional connection

(My institution and X's

institution are connected.

valued -2, -1, 1, 2)

professional contact

(I have professional contact

with X.

valued -2, -1, 1, 2)

political contact

(I have political contact with X.

valued -2, -1, 1, 2)

communication intensity

(I often have contact with X.

valued 1, 2, 3, 4)

contact ease

(It's easy for me to get in

contact with X.

valued -2, -1, 1, 2)

information exchange

(I exchange information with X.

valued -2, -1, 1, 2)

sympathy

(I find X likeable.

valued -2, -1, 1, 2)

trust

(I trust X.

valued -2, -1, 1, 2)

understanding

(I get along well with X.

valued -2, -1, 1, 2)

starting initiatives

(I could start initiatives/ projects

well with X.

valued -2, -1, 1, 2)

success of initiatives

(My initiatives/ projects with X

have been successful.

valued -2, -1, 1, 2)

formal contracts communication

behavior

relational

preferences

cooperative behavior

Figure 3. Hypothesized Constructs and Variables



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the effect of cooperative behavior. In Figure 3, the sentences in paren-theses refer to the question as formulated in the questionnaire.

Research SiteThe case for the empirical research is a midsized tourist destination

in the European Alps. The destination consists of ten small municipal-ities and in 2005 had a population of approximately 17.000 people aswell as a total area of 563.18 km2. The destination is well-known as a winter sport resort for visitors from German-speaking countries(Germany, Austria, Switzerland) and has recently gained popularityin further European markets like the BENELUX countries. Whilethe destination still counts only approximately two million tourist over-

nights per year and the local economy is not solely depending on tour-ism, local and regional authorities consider investments in tourism akey issue for the next generation. Hence, public authorities are ab-sorbed with issues regarding land use planning, road and traffic, andpublic costs due to strong seasonality. Simultaneously tourism entre-preneurs are challenged by workforce recruitment from borderingregions and staff professionalization, price positioning and differentia-tion as well as day tourism and alliances and current mergers betweenthe four ski area companies and numerous small hotels and guesthouses.These central issues have stimulated a series of planning projects and

workshops over the past five years or so with the aim of increasing jointcollaboration between the destinations organizations and institutions.Hence, the analyzed destination is an ideal case study for capturingthe facets of cooperative behavior currently happening at differentlevels for different reasons and among different actors representingdifferent stakeholder groups and institutions.

Survey Instrument and Data Collection

The field work for this study includes in-depth interviews supportedby a semi-structured questionnaire. In a first step, twelve prominent ac-tors were interviewed from a group of private companies and publicauthorities, which a year earlier had participated in a process of desti-nation strategy development. Among other questions, the respondentscould name a maximum of five other prominent actors, thus produc-ing a snowball sample (Scott, 2000, 56), which ended with 42 completeinterviews and two non-participants. The snowball sample ended withthe last respondent naming other actors which had already been inter-viewed. Returning back to all the 42 actors and confronting them with

the relationships to the other 41 would have not been purposeful be-cause of the following reasons. First, nominating prominent actors im-plies a minimal acquaintance with the named individual and hence ahigh probability that the respondent could answer reliably and com-pletely. As a matter of fact, few respondents named some individuals whom they did not know personally (12 out of 171 nominations).



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Confronting the respondents with relationship oriented questionsreferring to all the 41 actors would unnecessarily prolong the researchas well as the duration of the interviews and yield useless data. Second,we can assume that nominating other individuals implies a particular

relationship. One that is in fact related to some kinship, possibly orig-inated from a cooperative process. Hence, by asking the respondents toname other actors they reckon to be important, we have a reliable indi-cation not only for acquaintance but also for previous and/or currentformal and/or informal cooperation.

For the named actors, every respondent could either confirm (2, 1)or reject (2, 1) the attribute (i.e. the variable) with regard to thenamed person (see Table 1). The variable communication intensityis coded with a slightly different scale (4 = daily, 3 = weekly,2 = monthly, 1 = yearly). The data collected in the eleven network

matrices all refer to the same relations among actors. So, the networksform a set of multiplex data, with simultaneous multiple relations(Hanneman & Riddle, 2005).

The respondents could choose whether to fill out an online survey towhich they had direct access or to be interviewed personally or by tele-phone. The majority of the respondents preferred to be interviewed byphone. This approach proved to be effective, because the respondentsmostly preferred to deliver information if they could speak personallyand explain their answers, which at the end delivered a clear and dis-tinct choice along the Likert-scale.

Data Treatment and Analysis

The subsequent analyses used the eleven asymmetric, valued networks with the original codification from the interviews. Obviously,not every link between actors implies an initiative/cooperation. In 12out of 171 nominations the respondents had never cooperated with

Table 1. Rotated Factor Loadings for Out-Degree Centralities

Variables Factor 1(eigenvalue41.9%)

Factor 2(eigenvalue18.8%)

Factor 3(eigenvalue9.3%)

Institutional connectionfi factor 2 .07 .73 .24Professional contactfi factor 2 .10 .74 .14Political contactfi factor 2 .09 .69 .26Communication intensityfi factor 3 .12 .34 .80

Contact easefi

factor 3 .25 .15

.82Information exchangefi not assignable .50 .49 .31Sympathyfi factor 1 .80 .07 .18Trustfi factor 3 .47 .12 .74Understandingfi factor 3 .59 .02 .70Starting initiativesfi factor 1 .72 .04 .53Success of initiativesfi factor 1 .74 .24 .35



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the named persons before. Thus, missing data are not valued and arerepresented with a zero in the analyses.

The analysis consists of three steps. First, for the eleven asymmetric,valued matrices, Freemans centrality degrees produced distinct out-de-

gree and in-degree centrality lists. The merged out- and in-degree listsfor the eleven variables generated two separate lists, one with only out-degree and one with only in-degree values. A factor analysis with prin-cipal component analysis and VARIMAX factor rotation yielded threefactors for out-degrees and two factors for in-degrees. For the researchat hand, the results from the factor analysis provided the empiricalbackground to discuss the hypothesized constructs and define the vari-ables for the third analysis.

Second, an average transformation procedure merged the originalasymmetric, valued matrices assigned to the respective factors resulting

from the factor analysis. The average transformation procedure addedthe cell values of the matrices and divided them by the number ofmatrices, reducing two or more matrices to one.

Third, regressions and correlation analyses of the network matricesused a QAP (quadratic assignment procedure). The algorithms adoptquadratic assignment procedures to develop standard errors to test forsignificance of association. In a first step, they compute coefficientsand related measures between the cells of the two data matrices by con-sidering the cell values in the rows as well as in the columns of therespective matrices. In a second step they synchronously and randomlypermute rows and columns of one matrix and recalculate the correla-tions or the regressions as well as the other measures (Borgatti, Everett,& Freeman, 2002; Hanneman & Riddle, 2005). Step-wise elimination ofnon-significant variables for the multiple regression produced a dis-tinct model, while the correlations between the variables allowed to ex-clude covariance of independent variables in the regressions. The finalmodel presents all independent variables having significant values, themodel fit producing a significant value (at least p < 0.01), and thePearsons correlation coefficient between the two independent

Table 2. Rotated Factor Loadings for In-Degree Centralities

Variables Factor 1(eigenvalue 81.0%)

Factor 2(eigenvalue 9.8%)

Institutional connectionfi factor 1 .74 .22Professional contactfi factor 1 .93 .27Political contactfi factor 1 .97 .10Communication intensityfi factor 1 .98 .04

Contact easefi

factor 1 .98 .12Information exchangefi factor 2 .10 .98Sympathyfi factor 1 .89 .40Trustfi factor 1 .97 .14Understandingfi factor 1 .95 .23Starting initiativesfi factor 1 .94 .07Success of initiativesfi factor 1 .90 .21



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variables being


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with the independent variables interpersonal communication andinformation exchange passes the test against covariance.

DISCUSSION

Validity of Hypothesized Constructs

The results from the factor analysis show that not all the hypothe-sized constructs are valid. While formal contracts in the factor analysisof the out-degree lists consist of exactly the three items hypothesized inFigure 3, the other constructs look slightly different. As expected, thevariables in the construct communication behavior relate to differentfactors. In particular, information exchange plays its own separate role,

as indicated by the factor analysis from the out-degree list andconfirmed by the factor analysis from the in-degree list. In contrast,communication intensity and contact ease refer to trust and under-standing. Hence, for the case of the tourism destination, the variableswith regard to information and communication do not connect to theformal, contract-based environment but rather to the informal, rela-tion-based environment of the prominent actors. Finally, cooperativebehavior is a stand-alone construct, however, with the addition of sym-pathy, a variable expressing social affinity and bridging to the stronginfluence of relation-based collaboration. Figure 4 visualizes the final

results.In summary, contrasting the contract-based approach with a relation-

based approach proves to be a valid and useful differentiation.Whereas the relation-based approach shows a strong effect on cooper-ative behavior, the contract-based one is not influential. Hence, in thetourism destination, relevant actors cooperate with one another de-tached from formal professional or political bonds, on the basis of mu-tual trust and understanding reinforced by efficient and frequentcommunication.

Effects on Cooperation and Sympathy

The adjusted constructs after the factor analysis and the QAP regres-sion results deserve a thorough discussion.

First, sympathy goes along with starting initiatives and success of ini-tiatives and not with trust and understanding. Two phenomena explain

Table 4. QAP Correlation Coefficients all Coefficients Significant at p < 0.01

Variables (1) (2) (3)

Cooperation and sympathy (1)Formal contracts (2) 0.15Relational communication (3) 0.87 0.18Information exchange (4) 0.17 0.36 0.25



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this rather counter-intuitive result. For one, trust and understandingare different from sympathy because they are part of cooperation asa recurring and reinforcing process (Doz, 1996; Ring & Van de Ven,1994). In fact, trust and understanding (slowly) evolve with the helpof supporting and facilitating communication and therefore must con-stantly pass the test against betrayal and misunderstanding. In contrast,sympathy expresses a subjective feeling or emotion towards anotherperson, and is suggested it is a component for cooperative behavior

(Frank, 2001), not a condition or outcome of the cooperation process.In fact, from an economic point of view, sympathy is an inversefunction of distance (Sally, 2002; Smith, 1759) and therefore an inter-dependent utility function (Fontaine, 2008), while trust and under-standing persist despite distance. Recent behavioral game theorytakes into account that interdependencies during the games lead tosympathy, just as cooperation processes occur (Binmore, 1998; Camerer,1997; Green, 2002; Sally, 2001).

Second, information exchange relates neither to communicationintensity nor to contact ease. As operationalized in the in-depth inter-

views and presented in the method section information exchange in-cludes the following additional explanations: exchanging informationabout things happening. . .or about people. . .maybe gossip as well.Combined with the fact that information exchange has a weak negativeinfluence on cooperation and sympathy, this activity is less a process ofenforcing relations or socializing and more a stand-alone rule, inducedby the community as a social system. The rule of information exchange

formal contracts

cooperation and sympathyrelational communication

information exchange

informationexchange

institutional

connection

professional

contact

political contact

starting initiatives success ofinitiatives

sympathy

trust understanding

communication

intensitycontact ease

-

+

Figure 4. Confirmed Constructs and Influence on Cooperation and Sympathy



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requires the actors to (regularly) adhere to it, as in a sort of ritual. Inthis sense, information exchange is attributable to the norms and obli-gations occurring in the development of social capital theory (Burt,1995; Coleman, 1988; Granovetter, 1985; Putnam, 2000), and more

specifically as shared codes and language as part of the cognitivedimension of social capital (Nahapiet & Ghoshal, 1998). This helps ex-plain the variables slightly negative effect on cooperative behavior andsympathy, suggesting that (self-)imposed rules in order to maintainones personal integration in a community do not necessarily increasesympathy towards others. In fact, they increase distance because onefeels obliged to exchange information with people one dislikes or evenwith people perceived as rivals (Mauss & Evans-Pritchard, 1954). Con-currently, the less people exchange information with others, the lessthey may be biased and therefore the higher the tendency to initiate

an unbiased cooperation.Third, the variables in the new construct relational communication

correspond to the notions presented in the literature research aboutrelation-based cooperation. Communication intensity and ease of get-ting in contact support trust and understanding. All of them are astrong fundament for cooperative behavior. Thus, for the surveyed ac-tors, cooperation inside the destination is subject to interpersonalbonds and their development.

CONCLUSION

Implications

The results in this paper point to a series of implications for practiceand for research. Although an analysis of the six major theories oncooperative behavior could not be carried out systematically, some spe-cific results refer directly to them.

First, cooperative behavior among actors and stakeholder groups intourism destinations is an interpersonal business. Cooperative behav-

ior is not based on clinical games and does not follow pure rationaltheoretic principles. This explains why alliances, mergers or simplycollective initiatives and projects are not realized despite the logicbased on rational economic principles. Hence, when selecting andapproaching the appropriate constellation of representatives e.g. fordestination planning and development, considering the people first,and secondly the institutions they represent, is an effective and prom-ising approach.

Second, tourism destination communities distinguish themselves lessby formal rules and norms of cooperation and more by autonomous

key actors, a phenomenon described in policy research with the helpof actor-centered institutionalism (Scharpf, 1997) or collective memory(Rothstein, 2000), where past individual experiences affect futurebehavior more than the individuals affiliation to his institution. For-mal, contract-based connections and cooperation may permeate smallcommunities such as tourist destinations as well. In fact, companies



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develop and install cooperation agreements, while public institutionslike municipalities create their norms and laws. Institutions are definedas the rules of the game in a society, or, more formally, the humanlydevised constraints that shape human interaction (North, 1990).

However, the origin of effective cooperation is produced spontane-ously in the course of social interactions in networks of personal rela-tions, a less complex structure of personal interactions whichgenerally occurs in smaller groups (Nee, 1998, 87). Communicationintensity reinforced through multiple rounds of cooperation as wellas effectiveness of getting in contact (in line with transaction cost eco-nomics) foster collaboration. Hence, in order to increase cooperationor launch collective action, planners must pay attention to previouslyinstalled bonds of trust and understanding among actors, recognizablethrough intense communication; a fundamental condition which has

been described in an exploratory study, so far (Saxena, 2006).Third, information exchange among actors leads neither directly to

cooperation nor indirectly to trust or understanding. Launching a col-lective action between companies whose actors already exchange infor-mation but do not exhibit kinship would likely fail. The rule of socialexchange theory, according to which anticipated reciprocity leads theactors to offer information in order to gain reputation and influenceand a reward, works inversely. The more information exchange takesplace, the less the involved actors will exhibit cooperative behavior,as they already feel that they have complied with the social norms, orthey think that exchanging information with perceived competitors isthe rule to follow if one wants to be accepted in the community. Asa matter of fact, information exchange is a formal process under cir-cumstances of interdependencies (Levine & White, 1961), in orderfor the actors to stay up to date.

Fourth, cooperation processes require reciprocal sympathy. Identify-ing and highlighting interdependencies among the actors and theirinstitutions helps induce cooperative behavior. In fact, resource depen-dence plays a central role as cooperative actions take place. However,

before and after the cooperative games occur, actors are locked inbounded rationality and are required to repeatedly learn from everyexperience with their counterparts. The interdependencies which leadto the necessary sympathy during the process are characteristic to com-munity-structured tourism destination, as organizations and institu-tions are embedded in a system built on and affected by goods withpublic character (Olson, 1965).

Limitations and Further Research

The paper has its limitations. First, the results are valid for one des-tination and could reflect the idiosyncratic behavior of individuals in alocal/regional culture that is different from those in other destina-tions. Second, the research in this paper reflects only a point in time.No longitudinal data are available.



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Further research in this field could address the following topics:First, the application of the research in this paper or similar ap-proaches to other destinations could increase the external validity ofthe results presented herein. Second, longitudinal studies that observe

particular dimensions like trust and understanding as well as commu-nication could help describe the mechanisms that foster or hindercooperative behavior. Third, in this paper, information exchange is dis-cussed as a possible rule adopted in communities. Further research onwhy and how people exchange information could reject or confirm theobservation presented herein and reinforce the importance of socialexchange theory. Fourth, analyses of interdependencies among localactors and their need to cooperate combined with sympathy as a con-trol variable could reject or confirm the behavioral game theory con-text, in which cooperation occurs among actors in communities.

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Submitted 26 October 2009. Resubmitted 12 August 2010. Final version 10 November 2010.Accepted 23 November 2010. Refereed anonymously. Coordinating Editor: John Tribe

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