Networking in the Tourism Industry : The Case of Three Neighbouring Mediterranean Tourism Destinations

The aim of this study is to get a better understanding of the benefits of networking activities among firms operating in the tourism industry. The study classifies a sample of 421 tourism firms from three Mediterranean countries – Croatia, Italy and Slovenia – into three distinct groups based on their networking activities – Non-networkers (group 1), Great Networkers (group 2) and Limited Networkers (group 3) – and seeks to identify similarities and differences among these groups. The research results show that tourism firms from these three groups differ from each other based on the firm’s country of origin, industry, age, size, and performance. According to the results, we may be able to advise firms operating in the tourism industry regarding how to increase their collaboration with their internal and external environment in order to achieve better firm performance.


INTRODUCTION / Uvod
Firms are faced with limited internal resources, which forces entrepreneurs and business managers to access the external resources that are embedded in their social networks (Partanen et al., 2008).The positive benefits of networks have been identified in the initial stages of the firm's life-cycle as well as in its later stages at the inter-organizational level (Birley, 1985;Aldrich and Zimmer, 1986;Butler, Phan and Hansen, 1990;Jack, 2005, Yanagida, 1992;Shaw, 2006;Peltier and Naidu, 2012).Networks have been found to present an important source of support for entrepreneurs by providing them and their firms with a wide range of opportunities (Johannisson, 1986).
In the last decade, there has been increased interest in using the network approach to study the evolution of the tourism industry, especially in the field of destination management.However, there remains a lack of empirical support for the frequently claimed positive benefits of networked collaboration in tourist destinations (Van der Zee and Vanneste, 2015).
Tourist destinations might be seen as networks of connected private and public organizations, which can be considered stakeholders of the destinations (Baggio and Cooper, 2008).Since only a networked collaboration among various stakeholders within tourism destinations (e.g.tourism firms, travel agents, tourism offices, etc.) allows for the delivery of a holistic product to tourists, the tourism industry represents the ideal context to investigate the importance of networking (Scoot, Cooper and Baggio, 2008).
Hence, the aim of this study is to shed light upon the importance of networking among firms operating in the tourism industry.The purpose of the study is to classify tourism firms from three destinations -Croatia, Italy and Slovenia -into distinct groups based on their networking activities and to identify similarities and differences among these groups.

NETWORKING AND ITS BENEFITS / Prednosti umrežavanja
Networking can be defined as the process of developing and expanding personal networks, which represents a form of environmental scanning (Smeltzer, Van Hook and Hutt, 1991;Ostgaard and Birley, 1994).Intranetwork relationships may largely influence business performance, since they may facilitate or constrain the activities of the individuals embedded in them (Aldrich and Zimmer, 1986).
Organisational networks are mostly defined as patterns of relationships between different organisations, firms and even their competitors.Between the firms in question, a variety of interactions happen on a daily basis, such as cooperation with the customers, suppliers and competitors (Jarillo, 1989;Butler, Phan and Hansen, 1990;Larson, 1991;Neergaard and Ulhøi, 2006;Shaw, 2006;Peltier and Naidu, 2012).There is evidence that organizational networks have shown rapid growth in the past few decades (Biggiero 2001).In order to survive on the market, firms are forced to establish networks, since only collaboration enables resource exchange and the firm's access to opportunities.As such, organizational networks may represent an essential element of the firms' survival strategies (Peltier and Naidu, 2012).
Firms develop strategic alliances with the other organizations, and they devote large amounts of their money, time and energy to the maintenance of these relationships in order to improve their strategic position on the market (McGee, 1994;Merenda, Wood and Naumes, 1994).Interorganizational relationships ensure entrepreneur's access to management capabilities, technology, customers, various distribution channels, suppliers, and other resources enabling the growth of a company.Therefore, mutual cooperation among various firms increases their innovation and profitability (Merenda, Wood and Naumes, 1994).Moreover, organizational networks increase the efficiency and the competitiveness of individual firms (Butler, Phan and Hansen, 1990), since mutual cooperation enables firms to develop competencies and capabilities that may foster their competitiveness (Esposito, Lo Storto and Raffa, 1993).
The extensive research on organizational networks has thus revealed a positive relationship between the mutual cooperation within organizational networks and the business performance.Larson (1991) emphasised that appropriately selected and well-managed networks represent a strategic necessity for the firm.Jarillo (1989) argued that networking, in terms of developing relationships with other organizations, provides the new ventures with access to resources, which consequently increases firm growth and also enables wellestablished firms to achieve higher levels of flexibility.Due to resource exchange through inter-organizational relationships, small and medium-sized firms may be successful despite their size (Human and Provan, 1996), which may not only enable them to benefit from the advantages resulting from their flexibility but also encourage them to benefit from the advantages resulting from a wide range of resources.Consequently, many small firms are much more flexible than their larger counterparts, since their managers tend to interact more frequently with their immediate environment than do the managers from larger, well-established firms (Smeltzer and Fann, 1989).

NETWORKING IN TOURISM / Umrežavanje u turizmu
As one of the largest industries in the world, the tourism industry links various stakeholders, such as tourism firms, tourists, national tourism offices, infrastructure providers and other types of supporting organizations who are directly or indirectly involved in tourism.It also has strong links to other related and supporting industries.Tourism might therefore be seen as a network of interrelated organizations interacting to produce and deliver a service (Van der Zee and Vanneste, 2015; Scott, Cooper and Baggio, 2008;Baggio, 2008).
The final tourism product is the result of a wide range of services and products provided by various complementary and competing stakeholders operating in the industry (McCabe, Sharples and Foster, 2012).Because the tourist perceives the destination as an integrated entity, managing a tourist destination is a very complex task (Van der Zee and Vanneste, 2015).Tourists expect a smoothly organized service, which requires a high level of coordination and collaboration among different tourism elements representing the comprehensive tourism experience (Van der Zee and Go, 2013).Thus, the tourism industry is a complex environment in which networking among diverse partners seems essential in order to supply integrated tourist products and provide the best service to the end user.
The numerous benefits attributed to tourism networks in past research are mainly related to the integration of tourism destinations and the performance and quality enhancement of tourism destinations (Zach and Racherla, 2011).By fostering innovation, knowledge sharing and competitiveness of the involved interrelated stakeholders, the networked collaboration can help tourism firms to be more resilient and to function better in a fast-changing, turbulent and competitive world (Luthe, Wyss and Schuckert, 2012; Novelli, Schmitz and Spencer, 2006; Cawley, Marsat and Gilmor, 2007).
The need to form networks of close collaborative relationships appears to be even stronger in tourism as compared to other industries, since tourism firms are mostly small and mediumsized organizations, fragmented over a geographic region.In order to survive and successfully function in the competitive environment, these firms need to form agglomerations of interrelated independent entities (Ammirato et al., 2015;Smeral, 1998).There is evidence that small businesses in tourism tend to use both social networks (e.g., informal, personal contacts) and formal networks (e.g., associations) to support their businesses (Copp and Ivy, 2001).These types of networks are usually formed spontaneously and evolve and change over time.Since new products are often developed in cooperation with other organizations, the clusters in question are often related to higher levels of firm innovativeness (McCabe, Sharples and Foster, 2012).There is also evidence that the frequency of contacts among the interrelated tourism firms, at both the formal and informal level, strongly influences the destination's success.In fact, more frequent interactions might lead to more efficient information, knowledge and skills transfer (Gnoth, 2004).Thus, by increasing the firms' social capital, networks can improve the competitive position of tourism firms and enhance the overall tourist experience (Halme, 2001;Fuglsang and Eide, 2013).
Based on the above findings, we can argue that the main benefits of networked collaboration in tourism result from the knowledge and information transfer and from the access to limited resources.By establishing relationships with entities from both the supply and demand side, tourism firms might be able to improve the quality of their final tourism product and enhance the tourism experience.Our study represents an attempt to shed light upon the importance of networked collaboration among complementary and competing stakeholders in three Mediterranean destinations: Croatia, Italy and Slovenia.

METHODOLOGY / Metodologija
In the methodology chapter, we present variables and measurement, data collection process, sample description and data analysis.We perform a cluster analysis to model clusters of tourism firms in regard to their network activities.

Variables and measurement / Varijable i mjerenje
Based on the literature review and work with a focus group, a questionnaire was designed for owners or managers of tourism firms.The questionnaire was first prepared in the Slovenian language and then translated to Croatian and Italian.
All variables were measured using existing five-point Likerttype scales where 1 = strongly disagree and 5 = strongly agree.Control variable data were collected about the country and the firms' industry, age and size.The respondents were also asked to evaluate the firm performance in the last three years, in terms of market share growth and profit growth.

Data collection process and sample description / Postupak prikupljanja podataka i opis uzorka
Data were collected among the tourism companies using a quantitative method.The existing databases of business entities in these three countries were used to draw up a list of tourism firms.Later, a representative sample was formed, including all the companies whose e-mail addresses were available (2800 Slovenian, 1700 Croatian and 3100 Italian companies in the tourism sector).In September 2014, the online surveys were sent to the companies via e-mail.After five reminders, out of all the questionnaires sent, 220 returned questionnaires (7.86% response rate) from Slovenia, 143 (8.41% response rate) from Croatia and 60 (1.94% response rate) from Italy were considered for further research.The questionnaires were anonymous.

Data analysis / Analiza podataka
Selected data were analyzed using Statistical Package for the Social Science (SPSS) version 21.0.Various statistical methods were used, including exploratory factor analysis and cluster analysis.Principal component analysis was used to compute new variables for Network activities.The factor scores were formed and saved using the regression technique.Further, cluster analysis was employed to group the tourism firms into appropriate clusters.The Non-hierarchical K means that a clustering method was used.Analysis of variance was conducted to analyze the significant differences, and the post hoc Bonferroni test was used to identify differences between clusters in regard to each factor.

Factor analysis / Faktorska analiza
First, the factor analysis for the group of 14 network variables was performed.We entered three dimensions in the analysis: Acquisition capacity (three variables), Exploitation capacity (three variables) and Cooperation (eight variables).As the dimensions and the scales were already tested in previous studies, the principal component technique was used separately for each dimension.Finally, four factors were extracted.The first two dimensions formed the first two factors -F1) Acquisition capacity and F2) Exploitation capacity -while the Cooperation dimension decomposed into two Factors, F3) Cooperation with customers and suppliers and F4) Cooperation with environment.In the Table 1 factor loadings, total variance explained, Cronbach alpha coefficient KMO and Bartlett's test results are presented.
F1) Acquisition capacity, F2) Exploitation capacity, F3) Cooperation with customers and suppliers, and F4) Cooperation with environment Our next objective was to form clusters related to these four factors and to analyze the characteristics of and differences between these clusters.We were especially interested in the differences in the country, industry, age, size and performance items.

Cluster analysis / Klaster analiza
Cluster analysis is used when we want to identify groups of objects that are similar to each other but different from objects in other groups.The purpose of this type of analysis is to reach homogeneity within a group and difference between groups.We used our database to form clusters of firms with similar network activities (acquisition capacities, exploitation capacities, and cooperation).Based on these groups, we were able to describe the characteristics of tourism firms within the individual group.By employing the Non-hierarchical K means clustering method, the two-, three-, four-and five-cluster solution was performed, based on the factor scores of the four factors (extracted from the factor analysis).The three-cluster solution was the most appropriate.By performing ANOVA analysis, we realised that the values of F1, F2, F3 and F4 were significantly different (p = 0.000) among all four clusters (Table 2).
Moreover, according to the results of the Bonferroni post hoc test, we found significant differences between the clusters (p <0.05) for each factor, F1 to F4 (Table 3).
Our final decision was thus the three-cluster solution.In Table 4, the mean values for the four factors are presented as well as the size of the clusters.The means for all four network factors in Cluster 1 are very low and are all negative; thus, we labelled this cluster as Non networkers.In contrast, in Cluster 2 all the means values are high and positive; thus, we labelled this cluster Great networkers.The third cluster is characterised by low mean values for all four network factors; thus, we labelled this cluster Limited networkers.
After the three-cluster solution was chosen, we continued with the analysis of the patterns of individual clusters.We were interested in identifying the demographic characteristic of the tourism firms within clusters (Table 5).
The results are interpreted with regard to the sample characteristics.Most of the 220 Slovenian companies (50%) were placed in the cluster Limited networkers, and many of them (24%) are among the Non networkers.Also, Croatian companies are concentrated in the cluster Limited networkers (50.3%), while there are only a few (14%) in the Non networkers cluster.
Among the Italian companies, most of them (70%) were placed in the cluster Great networkers, while only two (0.3%) were among the Non networkers.This means that Italian tourism enterprises are much more actively connected in networks and collaborative.Also, in the accommodation industry, there are very few companies (20 of 128 or 15.6%) that can be designated as Non networkers.Most (57 of 128 or 44.5%) are located in the cluster of Limited networkers.The distribution of companies involved in the transport, entertainment and restaurant sectors is quite similar.We can see that the travel agencies and tour operators are most active in networking.Among these companies, 30 of 66 (45.5%) are located in the Great networkers cluster.A look at the distribution of enterprises by size shows that only large companies (over 250 employees) are very active in network activities, as the majority of them (11 of 17 or 64.7%) are located in the Great networkers cluster.For other companies, we can see that a larger share of smaller companies are in the Non networkers cluster (for companies with 0-10 employees, 52 279 or 18.6%; for companies with 11 to 50 employees, 17 of 92 or 18.4%).Thus, it appears that larger tourism firms are more involved in networks and better able to exploit and apply knowledge that is placed in the network.
For all companies older than two years, a similar proportion is located in the Great networkers and Limited networkers clusters.Moreover, many (from 12.7% up to 23.6%) of them are situated in the Non networkers cluster as well.What is interesting is that of the younger companies (less than two years), only one (out of 22) is situated in the Non networkers cluster.Obvious, younger firms are aware that they will not be able to survive in the market without being successfully integrated into the existing networks.They are conscious of the advantages that can be gained from a successful cooperation as well as the benefits of efficient acquisition and exploitation of the knowledge and information from their partners.
With regard to company performance, which was measured by profitability and market share growth in the last three years, we can also identify a correlation with networking.Companies whose market share in the last three years was declining have the largest group (16 of 35 or 45.7%) in the Non networkers cluster.For the rest, we see that firms whose market share in the last three years was moderately or quickly increasing have the largest share (44 of 104 or 42.3% and 16 out of 22 or 72.7%, respectively) in the Great networkers cluster.We can see that there a similar situation in regard to profitability.Among the companies that have much greater profitability than their competitors, none are in the Non networkers cluster.

Contributions of the study / Doprinos istraživanja
The main contribution of this study is the identification of three distinct groups of tourism firms from Croatia, Italy and Slovenia based on their network activities (Non networkers, Great Networkers and Limited Networkers).The three identified groups of firms differ from each other based on country of origin, industry, age, size and performance.
The research results show that Italian tourism firms are much more inclined to networked collaboration than are Slovenian and Croatian tourism firms.Further, we found that large firms (more than 250 employees), in comparison to small and medium-sized firms, are more active in networking.It is possible to assume that the bigger tourism firms are, the more actively they participate in networks and the better able they are to efficiently exploit and apply knowledge that is embedded in the network.Regarding industry, the research results indicate that firms operating as travel agencies and tour operators are much more active, connected in networks and collaborative than firms operating in other industries.In fact, the former types of firms cannot operate efficiently without a close collaboration with other stakeholders related to a tourism destination (e.g., national tourist offices, accommodation, transport providers, etc.).In regard to firm age, we found that younger firms (less than two years) more actively cooperate with their internal and external environments than older firms.A plausible explanation might be that they are aware of the importance of networking in order to successfully survive in the competitive market.Due to numerous limitations related to novelty and lack of reference in the beginning of the entrepreneurial process, small and new firms have to establish relationships with other firms at the inter-organizational level (Peltier and Naidu, 2012).
Finally, our study provides evidence about the relationship between networking and firm performance.Among the firms whose market share in the last three years was increasing or quickly increasing, the largest number of firms were located within group 2 (Great networkers).Similarly, firms showing higher profitability than their competitors were more inclined to networked collaboration than firms exhibiting lower levels of profitability.On the other hand, firms whose market share in the last three years was declining have the largest number of firms classified within the Non networkers cluster, indicating poor network activities among these firms.
The above-presented findings indicate that there might be a positive relationship between network activities and firm performance in terms of market share and profitability.Since previous research found opportunities to be closely related to social networks, the networked collaboration among various stakeholders in the tourism industry might help tourism firms to achieve better performance in the global market.

Limitations and future research opportunities / Ograničenja I buduća istraživanja
The present study is focused on the analysis of the networking activities of selected firms from three Mediterranean destinations.In order to properly quantify all the benefits resulting from a tourism network, the network structure characteristics need to be properly analyzed.Following this reasoning, future research should focus on a detailed analysis of relationships among various stakeholders related to a specific tourism destination (e.g., intensity of interaction, level of trust, network density).The current study is mainly focused on networking at the interorganizational level, while the continuation of this research should aim to analyze more thoroughly the role of personal, informal networks, since there is evidence that tourism firm use both types of networks to support their business.
Network activity dimensions were measured with 14 items: three measuring Acquisition capacity (adapted from Tepic et al., 2012), three measuring Exploitation capacity (adapted from Tepic et al., 2012), and eight measuring the extent of cooperation with different kind of partners (adapted from Zeng et al., 2010).