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Article

Tourism Planning in Underdeveloped Regions—What Has Been Going Wrong? The Case of Extremadura (Spain)

by
Ana Leal-Solís
1 and
Rafael Robina-Ramírez
2,*
1
Department of Finance and Accounting, Faculty of Business, Finance and Tourism, University of Extremadura, 10071 Cáceres, Spain
2
Department of Business and Sociology, Faculty of Business, Finance and Tourism, University of Extremadura, 10071 Cáceres, Spain
*
Author to whom correspondence should be addressed.
Land 2022, 11(5), 663; https://doi.org/10.3390/land11050663
Submission received: 22 March 2022 / Revised: 14 April 2022 / Accepted: 27 April 2022 / Published: 29 April 2022
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Abstract

:
The article proposes a planning model to develop tourism from a holistic perspective that includes economic, population and social aspects. Following a participatory methodology, the objective of the study is to propose a tourism planning model that contributes to the development of rural territories based on the involvement of tourism planners in the study. A total of 205 tourism planners and 443 tourism offices participated in the study. The data obtained were analysed using the PLS-SEM method. The results indicate that tourism planning has to be carried out by a professional team with diverse technical profiles that monitors the objectives set and adapts them to changes in the environment.

1. Introduction

In the middle of the last century, tourism planning was practically non-existent due to the legislative and political lack of control that governed the sector [1,2]. With the beginning of tourism research, tourism plans proliferated, and by 1979 there were more than 1600 plans worldwide [3]. Since that time, tourism planning has played a strategic role as a driver of the tourist resources in local territories [4].
Tourism planning’s new strategic perspective has allowed the development of interdisciplinary plans that encompass strategies not only from the tourist perspective but also from the economic, environmental, social and demographic ones [5]. Orderly strategic planning has contributed to the harmonious growth of territories and has already been used in France, England and Austria, and in mainly rural areas, such as Galicia and the consolidation of the Camino de Santiago in Spain [6].
International bodies such as the UNWTO have defined a diversified, differentiated, competitive and sustainable tourism development model [7] to meet the current needs of tourists and society. This planning model integrates resource management in order to meet economic, social and aesthetic needs, while maintaining cultural identity, landscape, essential ecological processes, biological diversity and living systems [8].
This new dimension of tourism planning is based on more flexible strategies that address the differentiation of consolidated destinations based on tourism competitiveness strategies [9] or, in the case of destinations in the development phase, seek to increase the foreign exchange income, economic activity and employment [10]. However, there are still limits in the planning process that contribute to its failure [11,12]. The complexity of the matter is due to the multiple factors that directly or indirectly affect tourism [12,13,14], such as the lack of study of the territory in question, as well as the delimitation of objectives and strategies fully adapted and integrated within the destination framework [15,16]. In many developing regions, that complexity remains a challenge to properly plan tourism [17].
Such is the case of Extremadura. As the most underdeveloped region in Spain, it faces the challenge of defining an adequate tourism planning model. Before the COVID-19 pandemic, the south-west region received more than 5% of the 83 M of tourists who visited Spain in 2019 [18]. For decades, Extremadura has been trying to promote tourism development [19,20], seeing it as a complement to agricultural income and as helping to curb the depopulation suffered by many areas of the region [21,22]. However, it was not until the beginning of this century that Extremadura has managed to increase tourism activity exponentially [23], trying to position itself as one of the preferred destinations of the national demand [24].
Aware that tourism is a great opportunity for some areas in which there are no other alternatives for economic activity [6], the autonomous government known as ‘Junta de Extremadura’ drew up the Strategic Tourism Plan for Extremadura in 2010 [25], whose main objective was to consolidate tourism as a strategic economic sector based on competitiveness [25,26,27]. At that time, Extremadura was not yet positioned even as a competitive destination, since it was a destination in the development stage [28]. Subsequently, the first Extremadura Tourist Plan 2017–2020 [26] and the second Extremadura Tourist Plan 2021–2023 [27] improved the planning, management and promotion of Extremadura tourist destinations, setting the long-awaited improvement of competitiveness as a goal [26,27]. However, these plans continue to be a frustrated endeavour [24], as Extremadura continues to hold one of the last positions in the competitiveness ranking of Spanish destinations [28,29].
Based on the previous studies on strategic tourism planning and the mistakes made in tourism planning around the world [8,16,30], the research aims to produce a tourism planning model that takes into account the importance that certain elements of planning have, such as the development of strategic objectives [30,31]. The authors acknowledge that there are no studies that analyse the elements that define these failures and even fewer that propose solutions compiled from social agents who are experts in planning [32].
In order to define the strategies that would allow us to provide solutions to the failure of tourism planning in underdeveloped regions, a review of the existing literature to date on the research topic was carried out. The variables obtained were refined into two focus groups established with 21 tourism planners from different corners of Spain [33]. Finally, 443 tourism offices and 205 tourism planners participated in the study, and the data obtained were analysed with the statistical tool Smart PLS Path Modeling [33,34].

2. Background and Context

In any planning process, it is necessary to carefully address the dysfunctional and functional elements that contribute to slowing down the development of a territory. By the term ‘dysfunctional elements’ we understand the negative impacts on the territory of an environmental, economic, patrimonial, social and population nature, such as degradation of the environment, higher rents, tourism, loss of cultural identity, among others [35,36,37]. By ‘functional elements’ we understand those factors of a participatory and multidisciplinary nature that contribute to harmonising the tourist resources in the territory according to a pattern of tourism development or planning, such as the participation of the resident community or different tourism entrepreneurs in the area [31,37,38]. Both functional and dysfunctional elements are part of the initial study that needs to be carried out throughout the territory and will allow us to establish the objectives of a tourism plan [19,21,31,35].

2.1. Determining Strategic Objectives in Tourism Planning

In most tourism planning, the objectives tend to focus mainly on short-term economic criteria that are unrealistic and not integrated into the framework of the destination [12,15,16].
The objectives have to be designed in accordance with the desired tourism development plan in the region [15,16]. For this, it is necessary to take into account, realistically, the capacities of both the territory and the resident community [1,39]. In addition, the objectives have to be monitored and updated according to new events and information generated by the environment [40,41]. This is of great value in any tourism planning [42], since tourist destinations are subject to constant changes that require a level of adaptation and effective reaction capacity to undertake and recover an unwanted impact [42].
Likewise, following Godfrey and Clarke (2000) [43], in order to achieve tourism development, planning, economic, spatial and social objectives ought to be established. The economic objective should be to increase foreign exchange inflows, circulation of capital flows, work related to the sector or the economy, spatial objectives to achieve an adequate spatial distribution of tourist activities and the use of resources and social capital to ensure that the resident population also participates in the benefits of the activity [10]. The following hypotheses are therefore proposed:
Hypothesis 1 (H1). 
Dysfunctional elements of tourism planning (DE) influence the determination of objectives in tourism planning (OB).
Hypothesis 2 (H2). 
A study of the territory (ST) affects the determination of the objectives in tourism planning (OB).
Hypothesis 3 (H3). 
The functional and multidisciplinary elements of tourism (FE) affect the determination of the objectives in tourism planning (OB).

2.2. The Planning Process: A Study of the Territory

The planning for any destination is under an obligation to begin with a prior study of the socioeconomics of the destination and the environment [40,41]. Generally, this is limited to a description of the tourist resources and attractions of the destination [44], without considering the resident community [45,46] or the relevant physical, financial and organisational resources [40].
Consequently, in order to create a sustainable tourism industry [47] that would have a positive impact on the development of the destination [21,46] and would help the destination face possible economic crises, such as the current one [48], destination planning has to be carried out by professionals with multidisciplinary technical profiles [17,49], such as tourism agents, tourism inspectors, geographers, architects, environmental agents, historical and cultural heritage agents or economists, among others. This will contribute to the creation of a holistic vision in determining the planning objectives. The following hypotheses are therefore proposed:
Hypothesis 4 (H4). 
The study of the territory to be planned (ST) influences the dysfunctional elements of tourism planning (DE).
Hypothesis 5 (H5). 
The functional and multidisciplinary elements of tourism (FE) affect the study of the territory to be planned (ST).

2.3. Dysfunctional Elements of Tourism Planning

Tourism planning in a developing region must offer a balanced transition between the current situation of the planned destination and its future [38,49,50,51]. Otherwise, incorrect planning can lead to a problematic economic, social and environmental imbalance [5,16,52].
According to Blasco et al. (2021) [53], these negative impacts can translate into the destruction of natural resources or their degradation [54]; an increase in both the cost of living and housing [55]; low wages and low-quality jobs [56]; the commercialisation of the heritage landscape [57]; crowds, congestion, loss of tranquillity, noise pollution; an increase in social problems, such as crime, drug trafficking and prostitution [36,58,59]. All of these problems can lead to tourismophobia in the resident population [60,61]. This will lead to not achieving the number of tourist arrivals desired [61], which translates into not being positioned as a consolidated tourist destination [24]. In this way, tourism will not complement the regional income [19,21,22].
However, it is not enough to know and apply planning techniques; for the plan to be successfully completed, certain requirements and factors have to be addressed [62]. By this, we refer to multiple elements that are typical of tourist activity [13,63], which, due to their complex variety, are sometimes more of a burden than a virtue if they are not taken care of by qualified professionals [17].

2.4. Functional and Multidisciplinary Elements of Tourism

As we have mentioned, the multidisciplinary quality that characterises tourism [63,64] requires that its planning take into account multiple functional elements [60], such as environmental and commercial elements or those related to certain infrastructure or transport [14], whether private or public, and on a national, regional or local scale [65].
Regarding the scale, if it is also a regional or local scale, the resident community has to be taken into account [66], as this is the most appropriate scale to integrate their participation [67]. The existing proximity of the tourist resources in the local and regional territories facilitates the community’s aim to fix common goals, and it strengthens the implementation of a global strategy and its implementation [16,68,69]. In addition, tourism greatly influences the life of the community where it occurs [70]. Thus, it is necessary that the resident population is part of tourism planning from the initial preliminary study to the end [13]. The following hypothesis is therefore proposed:
Hypothesis 6 (H6). 
The functional and multidisciplinary elements of tourism (FE) influence the dysfunctional elements of tourism planning (DE).

3. Materials and Methods

3.1. Population and Sample

The sampling was applied to tourism planning professionals in Spanish regions with similar tourist characteristics. In all of those regions, tourism is promoted by provincial councils and tourism councils, and planning professionals are the different professionals who work in these entities and participate in the development of tourism planning in their region.
Likewise, the sample also included the tourist offices spread throughout the Extremadura region because they are the most direct agents that bear the consequences of incorrect tourism planning.
Table 1 shows the total number of tourism planners, as well as tourist offices of local and regional governments throughout Spain. That information was obtained from the regional governments involved in the research. We then sent them a letter explaining the scientific object of the study. A total of 205 planners out of a population of 302 decided to participate. A total of 443 tourism offices out of 1462 also participated, as shown in Table 1.
Figure 1 shows the origin of the different agents and offices that have participated and collaborated in the selection of variables for the study and that we detail below.

3.2. Selection Criteria for Variables

From a participatory process in the selection of variables, a tourism planning model was designed. We started with a review of the existing literature to date on the research topic. To corroborate these variables, during the month of June 2021, the research team sent a letter to present the scientific study in order to invite both planning of the local and regional administrations of both Extremadura and other regions of Spain. A total of 31 planners responded favourably. They were then contacted by phone for a more detailed initial conversation that explained the sections of the research collected in the article. A total of 21 out of 31 tourism planners eventually agreed to participate in the primary selection of indicators. Several reasons were given for not being involved, such as a lack of time or a lack of experience, as they had worked as a tourism planner for less than three months. Tourism agencies in the region were also contacted. In total, there were 38 agencies distributed among the different autonomous communities and provincial governments of Spain that chose to participate in the study (see Table 2).
In the first half of July, two Zoom focus groups were held with the above planning agents. Zoom was used because of the geographical dispersion and the latent effects of the pandemic caused by COVID-19, which prevented a face-to-face meeting with them. In the first meeting, a set of indicators was provided, and a debate was opened on the main dysfunctions of tourism planning in Extremadura. In the second meeting, the original indicators were adjusted to the economic–social conditions of the Extremadura region. In this way, the selected indicators were grouped into different constructs (see Table 3 and Figure 2): dysfunctional elements of tourism planning (DE); functional and multidisciplinary elements of tourism (FE); the planning process; the study of the territory (ST); and the determination of the objectives in tourism planning (OB).
The model that represents the study is detailed below.

3.3. Treatment of Variables

We used the multivariate PLS technique to process the information obtained from the questionnaires. This statistical technique is observed when dependency relationships are established between latent variables and indicators [71]. To generate the statistical model, the partial least squares (PLS) SmartPLS 3 Version 26 technique was applied. This version is especially recommended for composite site models [71]. SEM-PLS modelling was defined based on two approaches: the measurement model and the structural model. To proceed with the analysis of the structural model, we analysed the reliability between the indicators and the constructs, as well as the validity of the measurement model [72]. In this case, we used reflective elements because they are interchangeable [47,73].
Likewise, this technique is ideal in social science analysis [74] thanks to the precision of its predictions; this means that the model could be replicated in other settings [75].

4. Results

4.1. Data Analysis and Model

The validation of the results obtained and the hypotheses of the proposed conceptual model was carried out using the partial least squares (PLS) technique collected in the structural equation models (SEM) based on the variance. This analysis technique is defined by two models: the measurement model and the structural model. Before performing the analysis of the structural model, the reliability and validity of the measurement model must be analysed [75]. Following Carmines and Zeller (1979) [76], the reliability of the established indicators has to be analysed individually with each of their latent variables. In this sense, the loads (λ) must be greater than 0.707, as occurred in our case (see Table 4).
The indicators (ST4: application and use of technology; OB3: resilient objectives) were eliminated, since they presented values (λ < 0.707), and the rest were endorsed by the approval of all the participants.
Likewise, Cronbach’s alpha coefficient, defined as the reliability index of the latent variables [18], was analysed. The convergent validity of the latent variables was evaluated by inspecting the mean variance extracted (AVE) (accepted if >0.5), while the discriminant validity of the latent variables was verified using the Fornell–Larcker criterion [75]. This criterion is considered valid when the square root of the average value extracted (AVE) of each indicator is greater than the correlations with the other latent variables [76,77]. In our case, Table 4 shows that the square root of the average variance extracted (AVE) for each indicator is greater than its highest correlation with any other construct (see Table 5).
Finally, discriminant validity was analysed using the Heterotrait–Monotrait Ratio (HTMT), which allows a more rigorous analysis of the discriminant validity criteria [77,78]. For this, its value should not exceed 0.90 [76]. As we can see in the following table, all the results obtained were less than 0.90, which means that the model is totally valid (see Table 6).

4.2. Structural or Internal Model Analysis

The structural analysis deals with the relationships between the constructs, the explained variance (R2) of the endogenous latent variables and the p-value of the regression coefficients (t test) as indicators of the explanatory power of the model [75]. The results obtained allowed us to accept all the hypotheses, since all the parameters were statistically significant (p value > 0.05).
After ensuring that the relationships between the constructs and indicators were accepted, the structural or internal model was evaluated by examining the relationships between the constructs in order to predict the viability of the model [75,76]. According to the result of the values obtained from the determination coefficient that measures the explanatory capacity of the dependent variable (R2) [78], we can say that the connection is weak (R2 > 0.19), moderate (R2 > 0.33) or strong (R2 > 0.67) [79]. In our case, the connection between the variables is moderate (0.33 < R2 < 0.67) (see Table 7).
Furthermore, following the Stone–Geisser (Q2) test [80], the predictive relevance of the model was analysed. In this test, the value indices 0.02, 0.15 and 0.35 indicate small, medium and high predictive relevance, respectively. In our case, as a result, we can affirm that all the constructs have high predictive relevance, since the Q2 values are all greater than 0.35 [79,81], as can be seen in Table 8.

5. Discussion

According to the results, the measurement model is completely satisfactory. The reliability of each individual item and the sample values and composite reliability were found to be adequate. The independent explanatory variables are satisfactory. The hypotheses raised based on the causal relationships between the different variables were cleared with structural equations. All were finally accepted and support the review of the literature discussed at the beginning of the paper.
This research sought, in an innovative way, to determine the factors that make tourism planning a failure in the developing regions, such as Extremadura. Therefore, an appropriate model was defined based on the results obtained.
First of all, the set of items that make up each construct was valid (λ > 0.7), and the resulting model has an explanatory power (R2 = 0.653). The hypotheses were cleared with structural equations, all being finally accepted and supporting the review of the literature at the beginning. According to the experts consulted, the connection between the multidisciplinary quality of tourism and the previous study to be carried out in the territory to be planned is the strongest (H5: FE → ST, β: 0.720, T: 22.182). This fact warns us of the importance of taking into account the multidisciplinary nature of tourism. Therefore, it is necessary that a study considers the functional elements, such as geographical, technical, accessibility, the load capacity of the destination, etc. This study will mark the way forward for the objectives that will be set a posteriori during planning (H2: ST → OB, β: 0.408) and that must include both economic, social and environmental aspects [9,10,42]. This should be carried out in such a way that the objectives of the plan are marked from a totally multidisciplinary perspective, since the functional elements influence this determination (H3: FE -> OB, β: 0.411) [41]. Likewise, realistic objectives ought to be established, taking into account the capacities of the destination [1] and being in accordance with the desired tourism development in the region to be planned [15,16] (OB1; λ = 0.946).
This was not the case in our region of study, Extremadura. Both in the Strategic Tourism Plan for Extremadura, and in the Extremadura Tourism Plan 2017–2020, one of the objectives was to strengthen the competitiveness of tourism in the region [24,25,26]. Such an objective is typical of mature destinations that seek to differentiate themselves [10]. Extremadura is a developing region, so such an objective is not realistic. Similarly, if this objective were based on a rigorous study, it would have taken into account that Extremadura, as a young destination, cannot establish such an ambitious objective without first addressing other aspects that are not resolved yet, such as accessibility or seasonality [10,24]. In this sense, personal interviews were carried out in order to obtain more precise information and thus corroborate the data obtained. An in-depth interview is a technique to collect information through a long, unstructured personal conversation in which the interviewees freely express their opinions on the subject under study [82]. Thus, taking into account the interviews carried out, we can affirm that the plans studied here are not supported by a deep initial preliminary study. Therefore, parts of the proposed objectives were not based on it (Interview 1: ‘Before making a plan, is required a study of the area, something that the Extremadura Tourism Plan 2017–2020 lacks’. Interview 2: ‘The study that supposedly the regional government has done to plan the sector has been very poor’. Interview 3: ‘Normally the study is based on a simple list of the tourist attractions of Extremadura’. Interview 4: ‘I have never attended any study before making any plan. Our objectives are set by the National Plan in force at the time’). We must also point out the scant consideration of tourism technicians who rarely participate in the tourism planning process despite being professionals in the sector (Interview 5: ‘There is an enormous lack of consideration towards the tourism profession on the part of politicians’. Interview 6: ‘Politicians do not respect the professional opinion of technicians, they only ask the tourism business community, which does not have a global vision of development of tourism’. Interview 7: ‘At some time, as an expert tourism technician, they have counted on me to plan. It depends on who governs’. Interview 8: ‘Tourism technicians and inspectors have a great deal to contribute to the tourism planning’). Thus, in the case of Extremadura, this fact could be resolved by incorporating a team of professionals with a variety of technical profiles who seek totally holistic tourism planning in Extremadura [17,48] (ST3; λ = 0.934).
According to Martínez-Quintana (2020) [4], a tourism plan will be evaluated at the end of its implementation, thus preventing it from being limited to a mere bureaucratic formulation. In this way, the main objective that moves the improvement of tourist activity in developing regions, such as Extremadura, will be achieved: to ensure that tourism becomes a sustainable activity over time, a source of income complementary to the income of residents and palliative of the depopulation that these regions suffer [21], enhancing the quality of life for present and future generations of Extremadura [83,84].
The following table shows the connection between the theory developed, the hypotheses raised and the results obtained (see Table 9).

6. Conclusions

Since the end of the 20th century, tourism has become an activity that is capable of diversifying and reactivating the economy of rural areas that have problems of an aging population and of depopulation [84]. This study provides, in an innovative way, a tourism planning model that supports the successful achievement of such a purpose. According to Chin and Newsted (1999) [85], this model is strongly predictive, so it can be extrapolated to any region with similar characteristics. In future tourism planning, these regions have to consider aspects that the literature proposed and that now, this empirical study corroborates. As confirmed by the hypotheses, tourism planning must be carried out by professionals with different profiles, basing the objectives on a rigorous initial study. Thus, in light of the results obtained, we present the result of the hypotheses in three theoretical conclusions and three practical recommendations that ought to be taken into account by regional and provincial administrations.

6.1. Theoretical Conclusions

In the first place, planning in a developing destination requires defining objectives [30,31] that are realistic given the possibilities and seeking a balanced transition towards the intended tourism model (H1. DE -> OB) [5,16,38,50,51,52]. It should be taken into account that strategic objectives in tourism planning are not universal and that each destination or region ought to consider its own situation (H1. DE -> OB) [86,87].
Therefore, to achieve this, the objectives have to be based on an initial study [40] that includes the capacities, attributes, resources and attractions of the destination (H2. ST -> OB) [39,43]. In this way, the objectives will be fully integrated into and will be appropriate for the destination in question (H2. ST -> OB) [1,15,16].
Third, the nature of the objectives has to be economic, environmental, spatial and social [10], so that a global model of tourism development is established in the region through the established objectives (H3. FE -> OB).

6.2. Practical Recommendations

The results of our research indicate that the study that will guide the objectives to be established is strongly influenced by the functional and multidisciplinary elements of tourism (H5. FE -> ST) [61,63,64]. This means that for the tourism plan to be fully integrative and holistic, it has to be carried out by a professional team with various technical profiles (H3. FE -> OB) [17,49]. In addition, the objectives require to be monitored and updated by the professional team (H6. FE -> DE) [39,40,41,42]. To this end, we propose a monitoring system for objectives before, during and after the completion of the tourism plan. Before carrying out the plan, the formal objectives of the predecessor plan must be analysed and adapted to the time frame of the new plan [15,16,38,86]. The initial study will include these old goals to find out why they were not achieved (H2. ST -> OB) [39,86,87]. The rest of the objectives will be based on the initial preliminary study [1,12,15,16,38,86,87].
During the execution of the plan, we propose to review the objectives periodically in formal meetings of the members of the planning team. If necessary, they will reorient themselves and adapt to the changes that are happening at the time (H1. DE -> OB; H3. FE -> OB) [14,16,60,61]. In this case, alert systems will be necessary to notify us of these changes [14,16,52,61,64,65], e.g., whether the target number of arrivals is being met or not and why; whether there are changes in tourism trends that may affect our region; or whether there are external factors that affect these new trends. Conducting surveys to collect such information will be necessary. Collaboration with an entity that is responsible for compiling all this information through surveys, such as the Tourism Observatory, would be beneficial (H4. ST -> DE).
After the execution of the plan, all the objectives will be reviewed [39]. A report will be prepared that explains in detail how the proposed objectives have been achieved. In the case of the objectives not achieved, the reason for this will be studied in order to take it into account in the future plan.
Given that the regional planning level is the most appropriate one for involving the resident community in the planning process [66], the study is obliged to always integrate their participation [13,16,66,67,68]. The development of tourism systems and institutions that consider local associations and networks will be of great help. The purpose is to ensure a sustainable benefit over time rather than the immediate achievement of maximum profitability [86] and to seek to consolidate the region as a tourist destination [34,83]. Finally, achieving the objectives will allow us to implement the model in the regions involved in the research by assessing the results along the tourism planning period, which will be key to avoid economic or political pressure from the local and regional tourist authorities [10,68,86,87].

6.3. Limitations and Future Lines of Research

The main limitations of our study are related to conducting in-depth interviews and surveys. Due to the social situation caused by COVID-19, the interviews were carried out through virtual meetings and telephone calls, missing the opportunity for a face-to-face discussion. In addition, we also found that the participants lacked time and interest in the research.
Extremadura was the first region analysed in this study, but future studies can continue with the same methodology in other regions in order to compare the results. It would also be interesting to use this methodology with mature destinations where the tourism planning has been a success and with others where it has resulted in failure. In this way, a planning model of its own could be established for each type of destination by virtue of the results obtained.

Author Contributions

Data collection, conclusion, figures and tables reformulated: A.L.-S.; Paper design, supervision of the paper and discussion: R.R.-R. All authors have read and agreed to the published version of the manuscript.

Funding

The publication of this work was possible thanks to the funding provided by the European Regional Development Fund andby the Consejería de Economía, Ciencia y Agenda Digital from Junta de Extremadura through grant GR21161.

Acknowledgments

We want to express our gratitude to the tourist planners and tourist offices involved in the research.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Liu, A.; Wall, G. Planning tourism employment: A developing country perspective. Tour. Manag. 2006, 27, 159–170. [Google Scholar] [CrossRef]
  2. Jurado Almonte, J.M.; Pazos-García, F.J. Población y turismo rural en territorios de baja densidad poblacional en España. Bol. de la Asoc. de Geógr. Esp. 2016, 71, 247–272. [Google Scholar]
  3. Cui, J.; Li, R.; Zhang, L.; Jing, Y. Spatially Illustrating Leisure Agriculture: Empirical Evidence from Picking Orchards in China. Land 2021, 10, 631. [Google Scholar] [CrossRef]
  4. Costa, C. Tourism planning, development and the territory. In Tourism Management Dynamics; Buhalis, D., Costa, C., Eds.; Routledge: New York, NY, USA, 2006. [Google Scholar]
  5. Wang, Z.; Lawal, M. Tourism Imaginary and Landscape at Heritage Site: A Case in Honghe Hani Rice Terraces, China. Land 2021, 10, 439. [Google Scholar] [CrossRef]
  6. Nieto Masot, A.; Ríos Rodríguez, N. Rural Tourism as a Development Strategy in Low-Density Areas: Case Study in Northern Extremadura (Spain). Sustainability 2021, 13, 239. [Google Scholar] [CrossRef]
  7. UNEP; UNWTO. Making Tourism More Sustainable—A Guide for Policy Makers. 2005. Available online: https://www.unwto.org/es/desarrollo-sostenible (accessed on 21 March 2022).
  8. Hall, C.M. Tourism Planning: Policies, Processes and Relationships; Pearson Education: Upper Saddle River, NJ, USA, 2008. [Google Scholar]
  9. Foronda Robles, C.; García López, A.M. La apuesta por la calidad como elemento diferenciador en los destinos turísticos: Planes renovados. Cuad. de Tur. 2009, 23, 89–110. [Google Scholar]
  10. Velasco, M. Entre el poder y la racionalidad: Gobierno del turismo, política turística, planificación turística y gestión pública del turismo. Pasos 2016, 14, 577–594. [Google Scholar] [CrossRef]
  11. Vila, M.; Costa, G.; Rovira, X. The creation and use of scorecards in tourism planning: A Spanish example. Tour. Manag. 2010, 31, 232–239. [Google Scholar] [CrossRef]
  12. Gunn, C.A. Tourism Planning: Basics, Concepts, Cases, 3rd ed.; Taylor & Frances: Washington, DC, USA, 1994. [Google Scholar]
  13. Sánchez, M.; Castro-Serrano, J.; Robina-Ramírez, R. Stakeholders’ Participation in Sustainable Tourism Planning for a Rural Region: Extremadura Case Study (Spain). Land 2021, 10, 553. [Google Scholar] [CrossRef]
  14. Sola Teyssiere, J. La ordenación del turismo y sus relaciones con la legislación de ordenación del territorio, del urbanismo y de la protección del medio ambiente. Adm. de Andal. Rev. Andal. de Adm. Pública 2004, 53, 109–134. [Google Scholar] [CrossRef]
  15. Cozma, A.C.; Coros, M.M. Regional Planning for Rodna as a Tourist Destination. Studia Univ. Babeş-Bolyai. Negot. 2020, 65, 49–68. [Google Scholar] [CrossRef]
  16. Martins, M. Tourism Planning and Tourismphobia: An Analysis of the Strategic Tourism Plan of Barcelona 2010-2015. J. Tour. Herit. Serv. Mark. 2018, 4, 3–7. [Google Scholar]
  17. Sabir, B. Developing a Multidisciplinary Tourism Planning Approach on Cultural Routes. J. Multidiscip. Acad. Tour. 2019, 4, 37–47. [Google Scholar] [CrossRef]
  18. Sánchez-Oro Sánchez, M.; Robina-Ramírez, R.; Portillo-Fernández, A.; Jiménez-Naranjo, H.V. Expectativas turísticas y motivaciones para visitar destinos rurales. El caso de Extremadura (España). Rev. Esp. de Investig. Sociol. 2021, 175, 105–128. [Google Scholar]
  19. Nieto Masot, A.; Ríos Rodríguez, N.; Cárdenas Alonso, G. Planificación turística en Extremadura. Análisis de sus territorios turísticos. Cuad. de Tur. 2020, 46, 291–317. [Google Scholar] [CrossRef]
  20. Nieto Masot, A.; Cárdenas Alonso, G. 25 años de políticas europeas en Extremadura: Turismo rural y método Leader. Cuad. de Tur. 2017, 39, 389–416. [Google Scholar] [CrossRef] [Green Version]
  21. Robina-Ramírez, R.; Sánchez-Oro Sánchez, M.; Cabezas Hernández, M.T.; Calleja-Aldana, M. Host and Guest Social Exchange in Developing Tourist Sites: The Case of the International Tagus Natural Park. Sustainability 2020, 12, 7248. [Google Scholar] [CrossRef]
  22. Cuadrado-Roura, J.R.; López Morales, J.M. El turismo, motor del crecimiento y de la recuperación de la economía española. Estud. Tur. 2014, 200, 19–38. [Google Scholar]
  23. Robina-Ramírez, R.; Sánchez-Hernández, M.I.; Díaz-Caro, C. Hotel manager perceptions about corporate compliance in the tourism industry: An empirical regional case study in Spain. J. Manag. Gov. 2020, 25, 627–654. [Google Scholar] [CrossRef]
  24. Sánchez Martín, J.M.; Rengifo Gallego, J.I. Evolución del sector turístico en la Extremadura del siglo XXI: Auge, crisis y recuperación. Lurralde 2019, 42, 19–50. [Google Scholar]
  25. Junta de Extremadura. Plan Estratégico de Turismo Para Extremadura 2010–2015. 2010. Available online: https://st11.ning.com/topology/rest/1.0/file/get/404704190?profile=original (accessed on 21 March 2022).
  26. Junta de Extremadura. Plan Turístico de Extremadura 2017–2020. 2017. Available online: http://www.juntaex.es/filescms/con02/uploaded_files/planes/Plan_Turistico_Extremadura.pdf (accessed on 21 March 2022).
  27. Junta de Extremadura. Estrategia de Turismo Sostenible de Extremadura 2030. II Plan Turístico de Extremadura 2021–2023. 2022. Available online: https://extremadura.ccoo.es/0f6c1d2e1ab1a9cc4414edc661d171b2000068.pdf (accessed on 21 March 2022).
  28. Exceltur. Informe Monitur 2010. 2011. Available online: https://www.exceltur.org/wp-content/uploads/2014/10/MONITUR-2010_INFORME.pdf (accessed on 21 March 2022).
  29. Exceltur. Informe Monitur 2018. 2019. Available online: https://www.exceltur.org/monitur/# (accessed on 21 March 2022).
  30. Simão, J.N.; Partidário, M.R. How Does Tourism Planning Contribute to Sustainable Development? Sustain. Dev. 2012, 20, 372–385. [Google Scholar] [CrossRef]
  31. Burns, P.; Montalvillo Sancho, M. Local perceptions of tourism planning: The case of Cuéllar, Spain. Tour. Manag. 2003, 24, 331–339. [Google Scholar] [CrossRef]
  32. Martínez Ávila, M.; Fierro Moreno, E. Aplicación de la técnica PLS-SEM en la gestión del conocimiento: Un enfoque técnico práctico. RIDE Rev. Iberoam. Para La Investig. Y El Desarro. Educ. 2018, 8, 130–164. [Google Scholar]
  33. Sánchez-Oro Sánchez, M.; Robina-Ramírez, R. Los Grupos Focales (“Focus Group”) Como Herramienta de Investigación Turística; Servicio de Publicaciones de la Universidad de Extremadura: Cáceres, Spain, 2020. [Google Scholar]
  34. Jiménez-Naranjo, H.V.; Coca-Pérez, J.L.; Gutiérrez-Fernández, M.; Fernández-Portillo, A. Determinants of the Expenditure Done by Attendees at a Sporting Event: The Case of World Padel Tour. Eur. J. Manag. Bus. Econ. 2016, 25, 133–141. [Google Scholar] [CrossRef] [Green Version]
  35. Robina-Ramírez, R.; Sánchez-Oro Sánchez, M.; Jiménez-Naranjo, H.V.; Castro-Serrano, J. Tourism governance during the COVID-19 pandemic crisis: A proposal for a sustainable model to restore the tourism industry. Environ. Dev. Sustain. 2022, 24, 6391–6412. [Google Scholar] [CrossRef]
  36. Stylidis, D.; Biran, A.; Sit, J.; Szivas, E.M. Residents’ support for tourism development: The role of residents’ place image and perceived tourism impacts. Tour. Manag. 2014, 45, 260–274. [Google Scholar] [CrossRef]
  37. Mansilla, J.A.; Milano, C. Becoming centre: Tourism placemaking and space production in two neighborhoods in Barcelona. Tour. Geogr. 2019, 21, 214–234. [Google Scholar] [CrossRef]
  38. Almeyda-Ibáñez, M.; George, B.P. The evolution of destination branding: A review of branding literature in tourism. J. Tour. Herit. Serv. Mark. 2017, 3, 9–17. [Google Scholar]
  39. Garau, G.; Carboni, D.; El Meligi, A.K. Economic and environmental impact of the tourism carrying capacity: A local-based approach. J. Hosp. Tour. Res. 2021, 1, 10963480211031426. [Google Scholar] [CrossRef]
  40. Faulkner, B. Towards a framework for tourism disaster management. Tour. Manag. 2001, 22, 135–147. [Google Scholar] [CrossRef]
  41. Adebayo, A.D.; Butcher, J. Constraints and Drivers of Community Participation and Empowerment in Tourism Planning and Development in Nigeria. Tour. Rev. Int. 2021, 25, 209–227. [Google Scholar] [CrossRef]
  42. Serrano-González, J.; Pérez González, E.M.; Oliveira, C.; Álvarez-García, J. La estrategia de planificación turística de la Villa de La Orotava (Tenerife, Islas Canarias, España): El registro de la percepción y la participación social como base para la sostenibilidad de una Citta Slow. Rev. Espac. 2020, 41, 372–386. [Google Scholar]
  43. Godfrey, K.; Clarke, J. The Tourism Development Handbook: A Practical Approach to Planning and Marketing; Continuum: London, UK, 2000. [Google Scholar]
  44. Holden, A. Environment and Tourism, 3rd ed.; Routledge: Oxon, UK; New York, NY, USA, 2016. [Google Scholar]
  45. Martínez-Quintana, V. Planificación colaborativa local y de naturaleza en épocas de crisis. In Turismo Post-COVID 19. El Turismo Después de la Pandemia Global. Análisis, Perspectivas y Vías de Recuperación; Bauzá Martorell, F., Melgosa Arcos, F.J., Eds.; Ediciones Universidad de Salamanca: Salamanca, Spain, 2021. [Google Scholar]
  46. Falak, S.; Lo, M.C.; Yeo, A. A Repositioning Strategy for Rural Tourism in Malaysia—Community’s Perspective. Procedia Soc. Behav. Sci. 2014, 144, 412–415. [Google Scholar] [CrossRef] [Green Version]
  47. Rasoolimanesh, S.M.; Ringle, C.M.; Jaafar, M.; Ramayah, T. Urban vs. rural destinations: Residents’ perceptions, community participation and support for tourism development. Tour. Manag. 2017, 60, 147–158. [Google Scholar] [CrossRef]
  48. Robina-Ramírez, R.; Medina-Merodio, J.A.; Moreno-Luna, L.; Jiménez-Naranjo, H.V.; Sánchez-Oro Sánchez, M. Safety and Health Measures for COVID-19 Transition Period in the Hotel Industry in Spain. Int. J. Environ. Res. Public Health 2021, 18, 718. [Google Scholar] [CrossRef] [PubMed]
  49. Lai, K.; Li, Y.; Feng, X. Gap between tourism planning and implementation: A case of China. Tour. Manag. 2006, 27, 1171–1180. [Google Scholar] [CrossRef] [PubMed]
  50. Bhatia, A.K. The Business of Tourism: Concepts and Strategies; Sterling Publishers: New Delhi, India, 2006. [Google Scholar]
  51. Stokes, R. Tourism strategy making: Insights to the events tourism domain. Tour. Manag. 2008, 29, 252–262. [Google Scholar] [CrossRef]
  52. Gee, C.Y. International Tourism: A Global Perspective; World Tourism Organization: Madrid, Spain, 1997. [Google Scholar]
  53. Blasco, D.; Palou Rubio, S.; Poch Espallargas, M. Emergence and Spread of Critical Discourses Opposing Tourism: The Case of Girona, an Urban Satellite Destination of Barcelona. Tour. Plan. Dev. 2021, 1–15. [Google Scholar] [CrossRef]
  54. Andereck, K.L.; Valentine, K.M.; Knopf, R.C.; Vogt, C.A. Residents’ perceptions of community tourism impacts. Ann. Tour. Res. 2005, 32, 1056–1076. [Google Scholar] [CrossRef]
  55. D’Angella, F.; Go, F.M. Tale of two cities’ collaborative tourism marketing: Towards a theory of destination stakeholder assessment. Tour. Manag. 2009, 30, 429–440. [Google Scholar] [CrossRef]
  56. Johnson, J.D.; Snepenger, D.J.; Akis, S. Residents perceptions of tourism development. Ann. Tour. Res. 1994, 21, 629–642. [Google Scholar] [CrossRef]
  57. Ap, J. Residents’ perceptions on tourism impacts. Ann. Tour. Res. 1992, 19, 665–690. [Google Scholar] [CrossRef]
  58. Bujosa, A.; Rosselló, J. Modelling environmental attitudes toward tourism. Tour. Manag. 2007, 28, 688–695. [Google Scholar] [CrossRef]
  59. Kayat, K.; Sharif, N.M.; Karnchanan, P. Individual and collective impacts and residents’ perceptions of tourism. Tour. Geogr. 2013, 15, 640–653. [Google Scholar] [CrossRef]
  60. Milano, C.; Novelli, M.; Cheer, J. Overtourism and Tourismphobia: A Journey Through Four Decades of Tourism Development, Planning and Local Concerns. Tour. Plan. Dev. 2019, 16, 353–357. [Google Scholar]
  61. Moscardo, G. Exploring social representations of tourism planning: Issues for governance. J. Sustain. Tour. 2011, 19, 423–436. [Google Scholar] [CrossRef]
  62. Salazar, D.; Romero, G. Planificación. ¿Éxito Gerencial? Multiciencias 2006, 6, 1–18. [Google Scholar]
  63. Meneghello, S. The Tourism–Landscape Nexus: Assessment and Insights from a Bibliographic Analysis. Land 2021, 10, 417. [Google Scholar] [CrossRef]
  64. Sancho, A. Introducción Al Turismo; OMT: Madrid, Spain, 2001. [Google Scholar]
  65. Williams, S. Tourism Geography; Routledge: London, UK, 2003. [Google Scholar]
  66. Yuksel, F.; Yuksel, A. Perceived Clientelism: Effects on Residents’ Evaluation of Municipal Services and Their Intentions for Participation in Tourism Development Projects. J. Hosp. Tour. Res. 2008, 32, 187–208. [Google Scholar] [CrossRef]
  67. Tosun, C.; Jenkins, C.L. Regional Planning Approaches to Tourism Development: The case of Turkey. Tour. Manag. 1996, 17, 519–531. [Google Scholar] [CrossRef]
  68. Vogt, C.; Jordan, E.; Grewe, N.; Kruger, L. Collaborative tourism planning and subjective well-being in a small island destination. J. Destin. Mark. Manag. 2016, 5, 36–43. [Google Scholar] [CrossRef] [Green Version]
  69. Araujo, L.M.D.; Bramwell, B. Stakeholder assessment and collaborative tourism planning: The case of Brazil’s Costa Dourada project. J. Sustain. Tour. 1999, 7, 356–378. [Google Scholar] [CrossRef]
  70. Esfehani, M.H.; Albrecht, J.N. Planning for Intangible Cultural Heritage in Tourism: Challenges and Implications. J. Hosp. Tour. Res. 2019, 43, 980–1001. [Google Scholar] [CrossRef]
  71. Sarstedt, M.; Hair, J.F.; Ringle, C.M.; Thiele, K.O.; Gudergan, S.P. Estimation issues with PLS and CBSEM: Where the bias lies! J. Bus. Res. 2016, 69, 3998–4010. [Google Scholar] [CrossRef] [Green Version]
  72. Rigdon, E.E.; Sarstedt, M.; Ringle, C.M. On comparing results from CB-SEM and PLS-SEM: Five perspectives and five recommendations. Mark. ZFP 2017, 39, 4–16. [Google Scholar] [CrossRef]
  73. Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a silver bullet. J. Mark. Theory Pract. 2011, 19, 139–151. [Google Scholar] [CrossRef]
  74. Haenlein, M.; Kaplan, A.M. A beginner’s guide to partial least squares analysis. Underst. Stat. 2004, 3, 283–297. [Google Scholar] [CrossRef]
  75. Fornell, C.; Bookstein, F. Two Structural Equation Models. LISREL and PLS applied to consumer exit-voice theory. J. Mark. Res. 1982, 19, 440–452. [Google Scholar] [CrossRef] [Green Version]
  76. Carmines, E.G.; Zeller, R.A. Reliability and Validity Assessment; SAGE Publications: California, CA, USA, 1979. [Google Scholar]
  77. Henseler, J. Bridging design and behavioural research with variance-based structural equation modelling. J. Advert. 2017, 46, 178–192. [Google Scholar] [CrossRef]
  78. Henseler, J.; Ringle, C.; Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modelling. J. Acad. Mark. Sci. 2015, 43, 115–135. [Google Scholar] [CrossRef] [Green Version]
  79. Chin, W.W. The partial least squares approach to structural equation modeling. Mod. Methods Bus. Res. 1998, 295, 295–336. [Google Scholar]
  80. Geisser, S. A predictive a roach to the random effect model. Biometrika 1974, 61, 101–107. [Google Scholar] [CrossRef]
  81. Stone, M. Cross-validatory choice and assessment of statistical predictions. J. R. Stat. Soc. 1974, 36, 111–147. [Google Scholar] [CrossRef]
  82. Spradley, J. La Entrevista Etnográfica; Holt: Nueva York, NY, USA, 1979. [Google Scholar]
  83. Moreno-Luna, L.; Robina-Ramírez, R.; Sánchez-Oro Sanchez, M.; Castro-Serrano, J. Tourism and Sustainability in Times of Covid-19: The Case of Spain. Int. J. Environ. Res. Public Health 2021, 18, 1859. [Google Scholar] [CrossRef]
  84. Engelmo Moriche, Á.; Nieto Masot, A.; Mora Aliseda, J. Economic Sustainability of Touristic Offer Funded by Public Initiatives in Spanish Rural Areas. Sustainability 2021, 13, 4922. [Google Scholar] [CrossRef]
  85. Chin, W.W.; Newsted, P.R. Structural Equation Modelling Analysiswith Small Samples Using Partial Least Squares. In Statistical Strategies for SmallSample Research; Hoyle, R.H., Ed.; Sage Publications: Thousand Oaks, CA, USA, 1999. [Google Scholar]
  86. Grădinaru, S.; Iojă, C.; Pătru-Stupariu, I.; Hersperger, A. Are Spatial Planning Objectives Reflected in the Evolution of Urban Landscape Patterns? A Framework for the Evaluation of Spatial Planning Outcomes. Sustainability 2017, 9, 1279. [Google Scholar] [CrossRef] [Green Version]
  87. Cabezas Hernández, M.T.; Leal-Solís, A. A propósito de la planificación de turismo en España: Necesidad u oportunidad. Rev. Gen. de Derecho del Tur. 2021, 3, 1–52. [Google Scholar]
Land 11 00663 g001 550
Figure 1. Map of provenance of tourism planning services. Source: Self-made.
Figure 1. Map of provenance of tourism planning services. Source: Self-made.
Land 11 00663 g001
Land 11 00663 g002 550
Figure 2. Structural model (Source: Self-made. DE: dysfunctional elements of tourism planning; OB: determination of objectives in tourism planning; ST: study of the territory to be planned; and FE: functional and multidisciplinary elements of tourism).
Figure 2. Structural model (Source: Self-made. DE: dysfunctional elements of tourism planning; OB: determination of objectives in tourism planning; ST: study of the territory to be planned; and FE: functional and multidisciplinary elements of tourism).
Land 11 00663 g002
Table
Table 1. Tourist planners and tourist offices in Spain.
Table 1. Tourist planners and tourist offices in Spain.
Planning Services in Spanish Territories Involved in the ResearchTourist PlannersTourist Offices
PopulationSamplePopulationSample
Provincial Government of Badajoz (Extremadura)1071446
Provincial Government of Cáceres (Extremadura)88785
Local Government of Extremadura (Mancomunidades)3317--
Regional Government of Extremadura17125721
Regional Government of Murcia36144127
Provincial Government of Albacete (Castilla-La Mancha)1083923
Provincial Government of Murcia (Murcia)14104127
Regional Government of Navarra4412139
Regional Government of Castilla y León18922327
Provincial Government of Salamanca (Castilla y León)974219
Provincial Government of Burgos (Castilla y León)863214
Provincial Government of Zamora (Castilla y León)742711
Provincial Government of Ciudad Real (Castilla La Mancha)862913
Provincial Government of Almería (Andalucía)653918
Provincial Government of Jaén (Andalucía)433817
Provincial Government of Sevilla (Andalucía)645124
Provincial Government of Córdoba (Andalucía)754919
Provincial Government of Toledo (Castilla-La Mancha)1093210
Provincial Government of Lugo (Galicia)853612
Provincial Government of Pontevedra (Galicia)76279
Provincial Government of Vigo (Galicia)96388
Provincial Government of A Coruña (Galicia)973911
Provincial Government of Oviedo (Principado de Asturias)65377
Provincial Government of Gijón (Principado de Asturias)643115
Provincial Government of Valencia (Comunidad Valenciana)14115818
Provincial Government of Alicante (Comunidad Valenciana)1194820
Provincial Government of Elche (Comunidad Valenciana)973711
Regional Government of La Rioja872812
TOTAL3022051462443
Source: Self-made.
Table
Table 2. Tourist planners and tourist offices in Spain who took part in the selection of variables.
Table 2. Tourist planners and tourist offices in Spain who took part in the selection of variables.
Total Tourist Planners Who Were InvitedTotal Tourist Planners Who AcceptedTotal Tourist Offices Who Were InvitedTotal Tourist Offices Who Accepted
31213838
Source: Self-made.
Table
Table 3. Constructs and indicators.
Table 3. Constructs and indicators.
ConstructsIndicators
OBOB1: Realistic objectives fully adapted and integrated into the destination framework [1,12,15,16,38].
OB2: Objectives based on the previous study [15,16].
OB3: Resilient goals [15,16,38].
STST1: Carry out an in-depth initial study [39,40,43].
ST2: Take the resident community into account [4,30,31,44,45].
ST3: Teams of professionals with varied technical profiles [17,48].
DEDE1: Economic, social and environmental imbalance [16,51].
DE2: Failing to position itself as a consolidated tourist destination [24].
FEFE1: Take into account multiple factors when planning [14,60,63,64].
FE2: Participation of the resident community [21,45,46].
Source: Self-made.
Table
Table 4. Outer model loadings.
Table 4. Outer model loadings.
FESTDEOB
FE10.928
FE20.932
ST1 0.928
ST2 0.905
ST3 0.934
DE1 0.946
DE2 0.949
OB1 0.946
OB2 0.937
Source: Self-made.
Table
Table 5. Reliability and validity.
Table 5. Reliability and validity.
Cronbach’s Alpharho_ACRAVE
FE0.8440.8440.9270.865
ST0.9120.9140.9450.851
DE0.8860.8860.9460.897
OB0.8730.8760.9400.887
Fornell–Larcker Criteria
FESTDEOB
FE0.930
ST0.7200.922
DE0.7060.7510.947
OB0.7050.7040.7140.942
Source: Self-made.
Table
Table 6. Heterotrait–monotrait ratio (HTMT).
Table 6. Heterotrait–monotrait ratio (HTMT).
FESTDEOB
FE
ST0.820
DE0.8160.834
OB0.8190.7870.811
Source: Self-made.
Table
Table 7. Structural model analysis.
Table 7. Structural model analysis.
Path Coefficient (β)Low IntervalHigh IntervalT Statisticsp Values
FE -> ST0.7200.6670.77322.1820.000 ***
FE -> DE0.2300.1420.3244.0820.000 ***
FE -> OB0.4110.2870.5315.5860.000 ***
ST -> DE0.3900.2650.5155.0620.000 ***
ST -> OB0.4080.2810.5315.4460.000 ***
DE -> OB0.2770.1660.3824.0620.000 ***
Source: Self-made. Note: *** p < 0.001 (t (0.001; 499) = 3.106644601). Source: Self-made.
Table
Table 8. Coefficients of determination and prediction.
Table 8. Coefficients of determination and prediction.
R2Q2
ST0.5180.437
DE0.6530.574
OB0.5770.504
Table
Table 9. Hypothesis, theory and results.
Table 9. Hypothesis, theory and results.
HypothesisTheoryResults
(H1). Dysfunctional elements of tourism planning (DE) influence the determination of objectives in tourism planning (OB).The objectives have to be realistic with the territory [15,16].
The capacities of the territory and the wishes of the resident community must be taken into account [1,13,14].
Objectives have to be updated to changes in the environment [39,40,41].		DE -> OB
β: 0.277
T: 4.062
(H2). A study of the territory (ST) affects the determination of the objectives in tourism planning (OB).The proposed objectives meet short-term economic criteria and are not based on a previous study [12,15,16].
The proposed objectives are not consistent with the reality of the territory [1,15,16,38,39,40,41,42].		ST -> OB
β: 0.408
T: 5.446
(H3). The functional and multidisciplinary elements of tourism (FE) affect the determination of the objectives in tourism planning (OB).Destination planning should be carried out by professionals with multidisciplinary technical profiles [17,48].
The objectives must meet different criteria (economic, social and environmental) [39,42,43,44,45].		FE -> OB
β: 0.411
T: 5.586
(H4). The study of the territory to be planned (ST) influences the dysfunctional elements of tourism planning (DE).A socioeconomic and environmental study is necessary before planning a territory [39,40,41].
The study must take into account physical, financial, organisational and social elements [31,43,44,45,63].
Tourism development must be gradual to avoid an economic, social and environmental imbalance [48,49,50,52,56,58].		ST -> DE
β: 0.390
T: 5.062
(H5). The functional and multidisciplinary elements of tourism (FE) affect the study of the territory to be planned (ST).A holistic perspective is necessary in determining the study of the territory [17,20,46,48].
The study has to consider the multiple characteristic elements of tourism [13,17,46,48,62].		FE -> ST
β: 0.720
T: 22.182
(H6). The functional and multidisciplinary elements of tourism (FE) influence the dysfunctional elements of tourism planning (DE).To avoid future problems due to tourism development, elements related to the environment, transport, services, infrastructure or population will be taken into account in the planning [13,14,17,18,19,24,31,45,46,54,59,60,62,66].FE -> DE
β: 0.230
T: 4.082
Source: Self-made.
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Leal-Solís, A.; Robina-Ramírez, R. Tourism Planning in Underdeveloped Regions—What Has Been Going Wrong? The Case of Extremadura (Spain). Land 2022, 11, 663. https://doi.org/10.3390/land11050663

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Leal-Solís A, Robina-Ramírez R. Tourism Planning in Underdeveloped Regions—What Has Been Going Wrong? The Case of Extremadura (Spain). Land. 2022; 11(5):663. https://doi.org/10.3390/land11050663

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Leal-Solís, Ana, and Rafael Robina-Ramírez. 2022. "Tourism Planning in Underdeveloped Regions—What Has Been Going Wrong? The Case of Extremadura (Spain)" Land 11, no. 5: 663. https://doi.org/10.3390/land11050663

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