Competitiveness of Frontier Regions and Tourism
Destination Management
Ksenija Vodeb
The competitiveness of border regions is often lower than the competitive ability of a country's interior regions. Mostly being areas that mark the end of one entity and the beginning of another, border regions demonstrate weaker economic performance. Tourism, as a method of development, provides opportunities to develop tourism destinations in places where tourism attractions and resources, and comparative and competitive advantages exist. This paper deals with models for assessing competitiveness in the field of tourism and destination management as a vital element in achieving a higher level of competitiveness for a tourism destination. Our research focuses on tourism supply providers in the border regions of Slovenia and Croatia. We assess their attitudes on tourism, regional competitiveness, and potential tourism destinations as the outcome of cooperation between the two countries. Results indicate the possibility of enhancing competitiveness through a strategic approach in planning and managing cross-border tourism destinations.
Key Words: tourism destination, competitiveness in tourism, tourism
destination management, cross-border cooperation jEL Classification: oio, M20
Introduction
There is no clear, standard definition of competitiveness or structural approach to understanding competition. According to Wei-Chang Hong (2008) there were published in refereed journals more than 4000 regular papers regarding the competitiveness from 1985 to 2006.
Competitiveness is a concept present in the modern business operations of all industries and sectors, and because of the indirect effect it has on the profitability of business entities, it is the focus of study and analysis for many researchers and professionals. Many authors seek to define this concept and describe its regularities and basic characteristics to make it easier to understand and apply in practice. For example, Michael Porter (1996, 24; 1997, 38; 1998, 3), one of the greatest names in
Dr Ksenija Vodeb is an Associated Professor at the Faculty of Tourism
Studies, University of Primorska, Slovenia.
Managing Global Transitions 10 (1): 51-68
this field who has, for decades, sought to penetrate the essential truth of competitiveness, claims that competitiveness has become a central preoccupation of the states and industries of every nation.
Porter's generic competitive strategies (1996) were generally accepted in the theory of competitiveness until Poon (1993) introduced the tourism point of view. She is rather critical with respect to Porter's generic competitive strategies, since for her, these are inadequate tools to explore competitive success for tourism players. His analysis is, according to Poon, more applicable to the manufacturing sector than to services (Vanhove 2005).
All authors agree upon and venture from the same starting point: the changing environment. Research (Huang 2006; Jogaratham and Law 2006; Jurowski and Olsen 1995) has shown the environment in the sphere of tourism and hospitality to be uncertain, unstable and highly changeable. Given this state of high complexity, organisations must actively strive to carry out environmental scanning consistently. They must continuously ask themselves: 'What is happening around us, and how does it affect our business?' by collecting, analysing and interpreting data and information from political, socio-cultural, technological, environmental and competitive organisational domains (Teare and Olsen 1999,105).
Despite numerous studies on and much debate about the competitiveness of tourism destinations, cross-border areas have been neglected for the most part. Specific reasons do exist, however, as to why it is essential to examine these regions more closely. These are (in our case) the abundance of tourism attractions in the observed area, the interest displayed by guests and tourism-supply providers, the level to which an integrated tourism product is interesting to third markets, and the opportunity of valorising borderland regions in compliance with the principles of sustainable tourism development.
Cross-border cooperation is of obvious importance for the mutual strengthening of the tourism industries of neighbouring countries (Grun-dy-Warr and Perry 2001, 64).
In this paper, we take a look at the possibilities of cross-border collaboration in enhancing the competitiveness of tourism destinations from the perspective of borderland tourism-supply providers.
Competitiveness Assessment Models
Because of the concept's remarkable pervasiveness and complexity, its actual occurrence will, to a substantial extent, depend upon the way it is
assessed. Ritchie and Crouch (1993, 27ff) conclude that certain aggregate measurements can be applied in general economic management, but are not very useful in analysing and managing international competitiveness in tourism. They report that studies on the factors used in defining and assessing the competitiveness of a country have uncovered the potential impact that these factors have on the ability of a country to compete on the tourism market, and on enhancing its integrative abilities for international competitiveness.
In Slovenia, competitiveness has been explored on the example of tourism and hotel companies (Nemec Rudež 2004, 45). Recently the competitive analysis for Slovenia as a destination was made using an integrated model. The result shows that Slovenia is more competitive in its natural, cultural and created resources, but less competitive in the management of tourism and, according to the integrated model, demand conditions, with both uncompetitive elements reducing the Slovenian tourism industry's ability to add value (Gomezelj Omerzel and Mihalic 2008).
Considering how interlaced tourism is with other activities and because of a tendency to either neglect or over-emphasise the indirect effects of tourism on the economy, some authors (Mihalic 2002, 2) call for caution in assessing the tourism competitiveness of any country. In current studies, the competitiveness, that is, the significance of tourism is analysed on the basis of physical indicators (number of overnights, number of guests), the tourist trade's share in the domestic product, and the importance of tourism for the country's balance of payments. The authors point out the difficulty in defining the tourism sector, because it comprises companies from various classes of the existing statistical classification, and often what is analysed is only the performance of hotel companies, and not the competitiveness of tourism mediators and organisers.
In an international setting, we can refer to Porter's competitiveness model from 1990, which has had a huge impact in the economic literature. His study is based on explaining why some companies in certain branches or market segments are capable of successfully competing with foreign rivals. Here, Porter distinguishes between the activities of individual companies and determinants, which he calls 'national advantages.' A company's performance depends upon the existence of competitive advantages (e. g. lower production costs or product differentiation). Companies need to develop generic strategies based on either of
the two determinants, while the selection of a strategy will be based on the response of management to the five factors of competitiveness (Five Competitive Forces Analysis) - the power of customers and suppliers, the threat of potential entrants and substitutes, and rivalry among companies (Porter 1998,314).
The World Economic Forum has provided the so-called wef model, which claims that every economy has, at its disposal, certain inputs or competitiveness factors, which, combined in a certain way, may generate useful output. These competitiveness factors include (Mihalic 2002,3):
•	domestic economic power (macro economic indicators of the economy),
•	internationalisation (participation in international business),
•	the government (support of government policies to competitiveness),
•	finances (capital market development, quality of financial services),
•	infrastructure (level of development, adequacy),
•	management (innovativeness, profitable business),
•	science and technology (scientific and research abilities, the success of basic and applicative research),
•	people (the availability and qualifications of the work force).
This model has not been applied to the field of tourism.
The model of the greatest interest to us is the Calgary tourism competitiveness model developed by Ritchie & Crouch (1993,48) mentioned earlier. Their model focuses on the following competitiveness factors:
1.	Destination Appeal - how appealing or unappealing a destination is.
2.	Destination Management - sales efforts and managerial efforts.
3.	Destination Organisation - organisational structures, strategic alliances.
4.	Destination Information - information system, research.
5.	Destination Efficiency - price-to-quality ratio, productivity.
The authors presented the model in 1993 in the form of a hypothesis and conducted tests. The model is still being perfected.
The authors underline the importance of information as a basis for decision-making for tourism managers. Destinations that collect and use
information efficiently are deemed to have the ability of improving their competitive positions.
The Calgary Tourism Competitiveness model (Ritchie and Crouch 1993, 50) looks like this:
1.	Destination prosperity = fn competitiveness (sector 1, sector 2,
tourism...)
2.	Tourism competitiveness (tc) = fn (how appealing or unappealing
a destination is [Appeal]) (destination management [Mgmt]) (destination organisation [Org]) (destination information [Info]) (destination efficiency [Effic])
3.	Appeal = fn (appealing, unappealing destination) [Attract] [Deter]
4.	Mgmt = fn (marketing efforts, managerial efforts)
[Mktg] [Manager]
5.	Org = fn (Destination Management abilities, strategic alliances)
[dmo] [Alliance]
6.	Info = fn (internal management information systems, research
abilities) [mis] [Research]
7.	Effic = fn (integrative experience, productivity) [ioe] [Prod]
The Keyser-Vanhove model of tourism competitiveness provides a greater opportunity for including external factors, in particular, government policies, into a competitiveness analysis. The general opinion among economists today is that while tourism may contribute to increasing the wealth of a country, practical examples warn us that this is not always necessarily so. This has to do with those destinations that are not successful in transforming tourism into a profitable industry or manage to do so only in the short run. Vanhove (2005,115) points out that benefits from tourism development depend upon the competitive position of a country's tourism sector on the international tourism market. That is why he believes the first step in analysing competitiveness to be an analysis of a country's competitive position, which, in fact, involves analysing comparative advantages (factors). This is about identifying factors such as the vicinity of tourism generating markets, pristine nature, favourable prices, etc., which is followed by an analysis of tourism traffic indicators and an analysis of factors that are actually comparative advantages. The second step involves analysing the below factors (Vanhove 2005,73):
•	macro economic factors,
•	supply factors,
•	transport,
•	demand factors,
•	tourism policies.
This basis is used to identify the comparative advantages and weaknesses of a destination or country.
Mihalic (2002, 5) points out that quantitative indicators such as the number of overnights and the number of guests cannot be the basis of any serious economic analysis into the competitiveness and performance of the tourist trade. The evidence she provides to support this is the discrepancy between the foreign currency inflow index and the foreign-tourist overnights index, which shows that foreign currency inflow is, to a substantial extent, independent of the number of foreign-tourist overnights. She goes on to prove that a difference exists between the indexes of revenue, profit and guest numbers, confirming her hypothesis that tourism analysis cannot be based (exclusively) on physical-turnover indicators, because of the ability of tourism companies to generate a substantial part of their revenues from activities that are not directly related to tourists and tourist expenditure.
Tourism Destinations and Competitiveness
Destinations are defined as competitive tourism unities caught between markets and the needs of guests, local factors and companies or products (Bieger 2000,35; Laws 1995, 56; Pechlaner 1999,332; Kušen 2000,314).
Magaš (2000, 58) defines a tourism destination as a spatial unit, appealing in terms of tourism, which can be shaped as a tourism site, tourism resort, tourism area or tourism region. This definition is given from a geographical perspective, whereas his definition from the contextual aspect of a tourism destination states (Magaš 1997, 21): A tourism destination is an optimum combination of fixed and variable factors and opportunities for tourism activities aligned with market preferences and independent of administrative boundaries.
A tourism destination, in its simplest terms, is a particular geographic region within which the visitor enjoys various types of travel experiences (Goeldner and Ritchie 2006).
Ritchie and Crouch (in Pedro Bueno 1999, 322) argue that competitiveness in destinations depends on their capacity (knowledge) to create conditions for market competition among enterprises.
Pechlaner (1999, 334), however, makes the point that only by creating unique competitive advantages is it possible to convince traditionally oriented destinations in the advantages of globalisation: the optimisation of organisation services, specialisation through cooperation, quality-offensive by suppliers and related industries, and lesser dependence on a small number of markets through internationalisation.
Determining a destination's competitiveness entails determining general conditions such as marketplaces, locations and companies. It is becoming clear, however, that destination competitiveness depends on the perspective of potential guests, and not on result-oriented indicators that provide only a view of the situation and offer very poor support to a destination's development. Finally, destination appeal also depends on the perspective of potential guests, making it necessary for a destination to exhaust all opportunities possible in effectively entering the marketplace and to impact on service quality by directly approaching service providers (Pechlaner 1999, 337f).
Preferences and trends of the tourism market are highly changeable but essential for the competitiveness of the destination. Campbell and Harald (2009) warned that there is an increasing demand for new products in tourism. Lower cost no longer means low service and low quality. Attention has moved towards providing high quality products at a reasonable price. Tourism has become a mature industry with a focus on what the tourist wants and with the emphasis on innovation as an instrument for creating new and memorable experiences.
The time for new a concept has come: the time for coopetition. It is beyond the competition and cooperation that we used to know earlier. It is an innovative approach in planning and organizing the tourism destinations, not only in border regions.
First introduced in 1995, coopetition is emerging as an important means to facilitate economic growth through tourism. The definition of this word is the need for cooperation among tourism destinations in order to better market the tourism product effectively and meet the competition at the regional or global level (Edgell, Del Mastro, Smith and Swanson 2008).
Tourism Destination Management and Competitive Strategies
When speaking of destination management, we are referring to destination management strategies, which are of great interest here and deserve to be looked at more closely.
Managing a destination as a combination of competitive products on
the marketplace calls for a direct relationship with entrepreneurs concerned with supply, on the one hand, and with organisational and financial preconditions, on the other, to facilitate the development of a competitive market and increase destination appeal (from the perspective of potential guests). Being different from the competition also guarantees guest satisfaction (Pechlaner 1999,337).
Swarbrook and Horner (2001, 64) point out the importance of destination management, the responsibilities of which are divided among different organisations. Each of these, depending on their competencies and level of operations, contributes to achieving guest satisfaction in a destination. They include central government agencies, regional government agencies, associated public-private partnership organisations, private companies, and universities and faculties. Manete and Cerato (1999, 187) define destination management as the organisation of tourism products linked to market segments that are targeted based on tourism development strategies. Poon (1993, 288) argues that destinations should apply competitive strategies to accelerate the development of a new and sustainable tourism. These strategies involve:
•	giving the environment top priority;
•	placing tourism in a leading position;
•	reinforcing distribution channels on the marketplace, and
•	building a dynamic private sector.
The strategic approach is to ensure solutions with synergistic effects. When the strategic planning of a destination is grounded on the resource base that a given area possesses, in order to develop partnerships between different interest groups (the home public, government, industries) it is necessary that we single out the advantages with which we are competing on the market, that is, which we provide to our market segment with an equivalent scale of attractions and appeal that the destination has to offer (Hunt 2000,137).
Survey Results and Discussion
This survey was conducted within the framework of a doctoral dissertation on the topic 'Tourism Management in Designing the Tourism Offering in Border Regions.' We explore the attitudes of tourism supply providers in the borderland regions of Slovenia and Croatia, the so-called decision-makers, on matters of cross-border cooperation and increasing
the competitiveness of the tourism offering by forming integrated joint tourism products.
The questionnaire consisted of 41 questions, some containing secondary questions, making a total number of 65 variables.
The hypothesis tested in this research reads:
H1 The competitive ability of cross-border regions on the international market increases with the increase in the degree of cooperation.
The questionnaire contained ten contextual sets of questions used to assess the attitudes and opinions of our targeted respondents. A five-point Likert scale was employed for the measurement of notions.
The questionnaire used to collect data was self-administered. The survey was simultaneously conducted in all seven borderland areas between Slovenia and Croatia according to the number of addresses of tourism-supply providers obtained over the Internet. The planned sample for Croatia consisted of 272 respondents. We collected 68 properly completed questionnaires, giving a 25% response rate. The planned sample for Slovenia consisted of 327 respondents. The response rate was 22. 6% with only 74 properly completed questionnaires collected. This fairly low response rate is attributed to changes of addresses and activities, as well as to a lack of interest for participating in the surveys, as we learned from telephone calls to most of the respondents who failed to send us a completed questionnaire.
The questionnaire primarily targeted 'small-scale' tourism-supply providers (owners of hotels, restaurants, holiday-flats, motor-camps, private farms; tourism associations, cultural clubs; airports; nature park managers; sports-equipment rentals in a destination, etc.). We found their addresses on the Internet, as part of the tourism offering of individual regions. Addresses of all tourism-supply providers were taken into consideration providing they met the established criteria (being located in the border regions and providing any type of tourism offering).
The data analysis methods can be divided into two groups:
•	data analysis using factor analysis, and
•	basic statistical methods (descriptive statistical methods, mean values and frequencies).
In factor analysis we explore the association among variables by seeking to reveal a new number of variables (smaller than the number measured) representing that which is common to the variables examined. In our case, the objective was to identify the variables affecting cross-border
table i Data for Croatia - tourism in the destination
Item	AV	1	2	3	4	5
1. attitude on development	4.01	1.5	5.9	11.8	51.5	29.4
4. tourism's impact on development	4.70	0	0	0	29.4	70.6
21. involvement of residents in decision-making	4.30	0	1.5	1.5	61.8	35.3
on tourism						
22. tourism strategy	3-45	1-5	13.2	29.4	50	5-9
table 2 Tourism issues in the destination						
Item	AV	1	2	3	4	5
3.1 too few attractions	2.88	11.8	32.4	22.1	23.5	10.3
3.2 traffic links	2.33	33.8	26.5	19.1	13.2	7.4
3.3 access to information	2.44	23.5	32.4	26.5	11.8	5.9
3.4. distinctiveness of the destination	2.51	23.5	29.4	25	16.2	5.9
3.5 identity	2.48	25	23.5	35.3	10.3	5.9
3.6 tourism services and facilities	3.11	11.8	22.1	23.5	27.9	14.7
3.7 negative attitude of residents	2	42.6	29.4	16.2	8.8	2.9
3.8 residents are not interested in being involved	2.35	23.5	38.2	23.5	8.8	5.9
in tourism						
3.9 information not made available to residents	2.58	19.1	30.9	30.9	10.3	8.8
3.10 other	2-73	7-4	14.7	75	2.9	0
cooperation. We tested variable grouping and the number of factors until an optimum result was achieved: the largest possible number of original variables in meaningful combinations and with high intercorrelations (over 0.40 in the factor matrix). Variables with the highest positive values were attributed to individual factors.
A factor analysis was made of all questionnaires (142). The descriptive part of data analysis was conducted separately for Slovene respondents and for their Croatian counterparts to allow for a comparison of average values.
We see that the item tourism's impact on development has the highest average value (av) (4.70), with 70.6% of responses having maximum values (highly positive). This indicates that respondents are aware of the extent to which tourism can facilitate development in their region, i. e. they see tourism as a method of development.
With regard to tourism issues in their destinations, respondents gave
table 3 Assessing destination competitiveness using the Calgary model
Item	Av	1	2	3	4	5
34.1 appeal	4.32	0	0	4.4	58.8	36.8
34.2 management	2.92	4.4	30.9	30.9	29.4	4.4
34.3 organization	2.66	10.3	35.3	35.3	16.2	2.9
34.4. information	2.88	4.4	25	50	19.1	1.5
34.5 efficiency	3.01	2.9	32.4	29.4	30.9	4.4
table 4 Residents' attitudes towards tourism						
Item	Av	1	2	3	4	5
24.1 the operations of most companies are tourism-related	3.57	5.9	27.9	4.4	26.5	35.3
24.2 residents want more tourists	4.17	2.9	5.9	10.3	32.4	48.5
24.3 local residents are not tolerant towards tourists	1.60	61.8	22.1	11.8	2.9	1.5
24.4. residents see no promising outlook for their involvement in tourism	2.05	44.1	26.5	11.8	14.7	2.9
24.5 regional competitiveness can be enhanced through cooperation	4.13	1.5	1.5	14.7	47.1	35.3
responses that differ highly, but show no substantial deviations. The item services and facilities of the tourism offering have the highest av (3.11). Interestingly, in most responses (42.6) the item negative attitude of residents was rated as 1 (Not an issue at all). Generally speaking, not one of the items measuring Tourism Issues in the Destination showed any visible deviations.
In assessing destination competitiveness according to the Calgary model, the highest av was measured for the item appeal (4.32), for which 58.8% responded with a rating of 4 (Satisfied), and as many as 36.8%, with a rating of 5 (Fully satisfied). The item efficiency (av 3.01) shows 32.4% of respondents to be dissatisfied. Some dissatisfaction is also evident with the items management and organisation.
The highest av was measured for the item residents want more tourists (4.17), followed by regional competitiveness can be enhanced through cooperation (4.13). Almost half (47.1%) of all respondents gave the latter item a rating of 4 (I largely agree). About 48.5% agree that residents want more tourists. The sharpest deviation was recorded for the item local residents are intolerant towards tourists, with 61.8% of respondents opting for 1 (I strongly disagree).
table 5 Data for Slovenia - tourism in the destination
Item	av	1	2	3	4	5
1. attitude on development	3.82	0	13.5	16.2	44.6	25.7
4. tourism's impact on development	4.62	0	0	1.4	35.1	63.5
21. involvement of residents in decision-making	4.18	0	1.4	6.8	63.5	28.4
on tourism						
22. tourism strategy	2.95	5-4	24-3	41.9	25.7	2.7
table 6 Tourism issues in the destination						
Item	av	1	2	3	4	5
3.1 too few attractions	2.83	18.9	18.9	33.8	16.2	12.2
3.2 traffic links	2.39	28.4	28.4	24.3	13.5	5.4
3.3 access to information	2.71	13.5	31.1	32.4	16.2	6.8
3.4. distinctiveness of the destination	3.01	6.8	31.1	29.7	18.9	13.5
3.5 identity	2.91	12.2	25.7	29.7	23	9.5
3.6 tourism services and facilities	3.06	9.5	31.1	20.3	21.6	17.6
3.7 negative attitude of residents	2.83	10.8	37.8	17.6	24.3	9.5
3.8 residents are not interested in being involved	3.22	12.2	16.2	21.6	36.5	13.5
in tourism						
3.9 information not made available to residents	3.16	12.2	13.5	35.1	24.3	14.9
3.10 other	3.00	5.4	4.1	82.4	1.4	6.8
In this dimension, the results recorded are very similar to those obtained from Croatian respondents. With an av of 4.62, the item tourism's impact on development ranks first, with as many as 63.5% reporting this impact to be highly positive. The lowest av was measured for the item cooperation is planned for in the tourism strategy (2.79), testifying to the poor knowledge of relevant information.
In measuring Tourism Issues in the Destination, no drastic departures from the results of Croatian respondents were observed. Indeed, the responses of the Slovene group are even more strongly divided, so that we cannot speak of having identified any particular problems. Sadly, the highest av was measured for the item residents not interested in becoming involved in tourism (3.22), yet 36.5% of respondents perceive this item as an important tourism issue in their destinations.
Similar results were obtained in this dimension in both groups. The responses of the Slovene group to the item destination appeal (an av of 3.89, and 59.5% of respondents reporting their satisfaction) are very close
table 7 Assessing destination competitiveness using the Calgary model
Item	av	1	2	3	4	5
34.1 appeal	3.89	1.4	2.7	18.9	59.5	17.6
34.2 management	2.89	8.1	23	44.6	20.3	4.1
34.3 organization	2.62	10.8	35.1	37.8	13.5	2.7
34.4. information	2.74	5.4	31.1	48.6	13.5	1.4
34.5 efficiency	2.82	8.1	29.7	37-8	20.3	4.1
table 8 Residents' attitudes towards tourism						
Item	av	1	2	3	4	5
24.1 the operations of most companies are tourism-related	2.83	20.3	25.7	18.9	20.3	14.9
24.2 residents want more tourists	3.17	10.8	28.4	14.9	24.3	21.6
24.3 local residents are not tolerant towards tourists	2.56	24.3	25.7	27	14.9	8.1
24.4. residents see no promising outlook for their involvement in tourism	2.90	10.8	31.1	28.4	16.2	13.5
24.5 regional competitiveness can be enhanced through cooperation	3.97	1.4	8.1	18.9	35.1	36.5
to the ratings of their Croatian counterparts. Similarly, the item organisation received fairly low ratings, and an av not exceeding 2.62.
The av of the item regional competitiveness can be enhanced through cooperation is 3.97, with 35.1% of respondents agreeing, and 36.5%, strongly agreeing with this statement. The item with the lowest av (2.56) is residents are not tolerant towards tourists. Still, it is higher than that obtained in the Croatian group (1.60).
No clear correlations between mean values and age and education groups were found. However a high correlation (0.79) was found between identity and distinctiveness of the destination as a tourism issue, (0.72) between assessment of collaboration experience and experiences in collaboration, (0.68) between the negative attitude of residents' towards tourism and residents interest in being involved in tourism as a tourism issue, and (0.63) between awareness of attractions in adjacent region and advantages of cross-border cooperation.
exploratory factor analysis: data interpretation with spss processing
The spss program, Version 13 was used in factor analysis. All properly completed questionnaires (142 cases) were processed. The adequate
table 9 Factor loading of individual items of cross-border cooperation dimensions
Item	fi F2 F3 F4 Cooperation and integrated tourism offering
13. considering collaboration	0.721
17.	assessment of collaboration experience	0.710 16. experiences in collaboration	0.695 8. willingness to collaborate	0.649
18.	ideas on integrated product	0.625
11.	being part of an integrated product	0.595 7. advantages of cross-border cooperation	0.581 10. increasing business through cooperation	0.576 6. awareness of attractions in adjacent region	0.551
12.	compatibility of tourism offerings	0.550
19.	knowing potential strategic partners	0.541
28. being more competitive as part of integrated product 0.527
21. involving residents in decision-making regarding	0.512 tourism
5. previous involvement in cooperation	0.497
24.5 enhancing regional competitiveness through	0.482 collaboration in tourism
33.4 representing interests as a function of tourism	0.448 organizations
Continued on the next page
number of correlations in the database matrix justified choosing factor analysis. The Bartlett Test, used to statistically test the existence of correlation among variables, showed important correlations within the correlation matrix. The value of the Kaiser-Meyer-Olkin (kmo) Measure of Sampling Adequacy was 0.814 for the variables selected. This is an excellent measure of sampling adequacy. The initial number of factors was selected with regard to theory-based expectations. Because the factors had not been empirically tested, their number was expected to drop. In choosing the number of factors, we took into account proper value, the percentage of explainable variances, and the scree plot. The scree plot showed that the possible number of factors ranged from two to five; however, because of proper values higher than 1, four factors were identified. For this number of factors and the final selection of variables, the explainable variances amount to 53.920%. Solutions us-
table 9 Continued from the previous page
Item	F1 F2	f3 f4
Residents		
3.7 adverse attitude towards tourism	0.707	
3.8 residents not interested in becoming involved in tourism	0.702	
24.4 residents see no promising outlook for their involvement in tourism	0.617	
24.3 tolerance of residents towards tourists	0.588	
3.9 residents not informed on opportunities for becoming involved in tourism	0.510	
Assessing destination competitiveness		
34.3 destination organization		0.635
34.2 destination management		0.562
34.4 destination information		0.558
34.5 destination efficiency		0.497
Functions of destination tourism organisations
33.3 marketing	0.528
33.1	developing ideas and destinations competitiveness	0.520
strategies
33.2	developing and shaping the offering	0.496
ing five, four and three factors were also tested, but did not give such adequate results as the selected solution with four factors. In deciding which variables to keep, we were guided by the principle of commu-nalities values (above 0.4) and high factor loading coefficients (above 0.3). The variables that remained are listed in table 9. The analysis process showed that it was necessary to exclude 25 variables of a total of 53 (taken into account in this analysis - their total number is 65, but 12 were processed descriptively) due to low communalities or low factor loading coefficients.
The four retained dimensions of cross-border cooperation (with 28 items), resulting as factors in the exploratory factor analysis are presented in table 9. We have named the first dimension Cooperation and Integrated Tourism Offering (f1); the second, Residents (f2); the third, Destination Competitiveness (F3), and the fourth, Functions of Destination Tourism Organisations (F4).
The third (F3) and fourth (F4) factors, together with two items (28
and 24.5) confirm the hypothesis stating that the competitive ability of cross-border regions on the international market increases with the increase of the degree of cooperation. This is, of course, confirmation that the respondents who were engaged in this survey believed that the competitive ability of cross-border regions increases with the increase in the cooperation degree.
Conclusion
Sometimes the competitiveness of border regions could be weaker than the competitiveness of, say, a country's central regions, because of the peripheral position of borderlands, the disruption that a border generally carries with all its connotations, and because of all issues arising out of this (depopulation, unemployment, poor development). Because tourism destinations are not necessarily restricted or disrupted by national and other borders, but their boundaries are determined by tourist perceptions, i. e. tourist needs and wants linked to a given tourism destination, we predict that in the borderlands between Slovenia and Croatia we will see an increase in tourism competitiveness providing effective cross-border cooperation. Through enhanced cooperation the specific cross-border tourism destinations could be created in places where tourism offerings are compatible. This is indicated by the results of our survey, in which we have measured the variable of the possibilities of enhancing destination competitiveness. As a result of this concept, we propose the development of an integrated tourism offering in places in which the offering, i. e. tourism attractions are compatible, and in which tourism demand exists. To this end, it would be beneficial to investigate the opinions and attitudes of tourists as yet another dimension, without which developing a tourism offering would be meaningless.
The results from the survey were analysed together for all seven cross-border areas because we wanted to catch the general condition of the issue. That is why we haven't got any different opinion from area to area, which represents a certain limitation in this research.
This survey has shown that, in the field of research, tourism has been recognised as a method of developing border regions. It also shows that competitiveness assessments using the Calgary model have given similar results on both the Croatian and the Slovene side. The awareness of respondents regarding the development function of tourism in border regions is at a very high level. Destination appeal received the highest rating, and destination organisation the lowest, in both cases. In other
words, there is no dispute regarding destination appeal. More problematic is the sphere of destination organisation, which comprises destination management and destination development strategies.
Our recommendations deriving from the results to tourism development stakeholders are to start cooperation between the tourism industry and local community, as both can gain much from reasonable joint tourism cross - border products. Of course, no instantaneous changes in market position are possible, but nor are they necessary. The local residents like to live in places that are attractive to tourists but should have a more active role in tourism development. We therefore suggest gradual enrichment of the tourism offerings regarding sustainability issues through cross-border cooperation and a joint development of cross border areas between Slovenia and Coratia.
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