Intrinsic and extrinsic values of destinations

This study re-evaluates the concept of destination value to develop and propose a solution to the theoretical dilemmas encountered in tourism research. For this purpose, a hierarchical structure including the intrinsic and extrinsic values of destinations was developed first. A mixed methodology was adopted to achieve the research objectives. In the qualitative part of the study, data was gathered through literature review and document analysis. In the quantitative part, data was collected from field experts. Then importance weights for the themes and subthemes forming destination value were measured by fuzzy criteria weighting using pairwise comparisons technique. The key results obtained with this study supported the validity of the distinction between the intrinsic and extrinsic values of destinations. Analysis revealed that any approach based on intrinsic and extrinsic destination values is suitable when dealing with the information from a range of disciplines.


Introduction
The concept of value is frequently examined in the fields of economics, anthropology, sociology, moral philosophy, theology and mathematics. For example in social sciences, Kluckhohn (1951, p. 395) described value as the "perception of desirable" that plays a role in influencing the individuals' choices. In this respect, the value associated with the desirable is related to the ideas shaped by individuals' previous experiences. From this point of view, value is the criteria of individuals' judgements about legitimacy of their desires and if they are logical, useful or worth making an effort for.
However, accepting that a tourist destination can be examined in the same way as an enterprise, or a product could prevent us from realizing the problems. Treating tourist destinations as packaged product is synonymous to accepting them unsustainable at the outset. On the other hand, to consider a tourist destination as a kind of enterprise means that its primary purpose is to make and increase profits. It should not be forgotten that what is defined as a destination does not desire to make a profit, to increase profit or to have a competitive advantage over other destinations.
Besides, in a recent study (Kunst & Ivandić, 2021), contradictions were identified between the destination competitiveness theory and measuring destination competitiveness. This study highlights that the stated contradictions were caused by the deficiencies of the measurement tool. However, these contradictions may also stem from the gaps in the destination competitiveness theory. For instance, increasing the number of tourists and tourism revenues through competitive advantage seems to have positive contributions to the economy. However, at some point, the costs of such actions make their economic benefits of destination insignificant. This may be solved with additions such as sustainability. This example regards destination competitiveness one of the theoretical dilemmas in tourism research. The main reason for this is the incompatibilities between theories dealing with geographical structures such as destinations, social structures such as societies or economic structures such as enterprises and individual theories dealing with tourists' behaviours.
Considering these, the term destination value, as defined within the scope of this study, refers to all of elements that will make a tourist destination worth visiting. The reason for such a conceptualization is to develop and propose a solution to the theoretical dilemmas that are considered relevant to the current tourism research.
In accordance with the above stated goal, this paper is structured under six interrelated parts. After the introduction, the second part, literature review, provides a definition of destination value concept and, sub-concepts of intrinsic and extrinsic values. The third part explains the methodology of the study. In this respect, methodology section was tailored under two stages, as qualitative and quantitative research. The destination value model was also presented in the qualitative stage. Whereas the fourth part discusses the results of the conducted analysis, it also mentions about the distinction between intrinsic and extrinsic values of destinations. The fifth part of the paper summarizes the findings and proposes solutions to the mentioned shortcomings of tourism research. Finally, the sixth part of the paper presents limitations of the study and makes some suggestions for future research.

Literature Review
The Concept of Destination Value According to Adler (1956, p. 272), value insights in sociology can be classified into four basic types and certain mixed types. These are; a) values as independent truths, eternal ideas, and dogmas; b) values considered to be in objects, materials or non-materials; c) values within man himself, originating in his biological needs or his mind; and d) values equated with actions. In this respect, destination value, as defined in the scope of this study, is considered to be the types b and d values, out of the ones listed above.
One of the assumptions of the destination value approach developed within the scope of this study has similar aspects with the proposition that tourists participate in this mobility to absorb destination value (Bayraktaroğlu, 2019). When we accept that the value is a kind of information and define memory as "a permanent record of a prior experience" (Braun-LaTour, Grinley, & Loftus, 2006); it could be claimed that value of a destination for a tourist is a recorded travel experience. In one aspect, this assumption evokes MacCannell's (1973) idea claiming that tourists are the kind of people seeking authenticity. When it is accepted that an authentic entity is worthy, it could also be accepted that this entity is a carrier of value and acts as a mediator in an individual's value adoption process. By taking this approach one step further, it could also be concluded that authenticity-seeking tourists are also seeking value.
In addition, Willams and Zelinsky's (1970) proposal of 'heliotropic' or Gray's (1970) synonymous proposal of 'sun lust' assert that tourists "are more motivated by the desire to experience different or better amenities for a specific purpose than those available in their living environment". In the same way, Gray also proposes to take 'wanderlust' cultural motives into account. These new horizon opening ideas in the early stages of tourism research contain traces of value. Another further assumption implied that tourists want to absorb the presumed value of the things mentioned above. It is also possible to accept the value as the information that involves "push and pull factors" (Dann, 1977) or "seeking and escaping" (Iso-Ahola, 1982). In addition to this, traces of destinations regarding value could be found in the definitions regarding "destination attributes" used by researchers such as Litvin and Ng Sok Ling (2001) and, Klenosky (2002). Within the scope of this study, the destination value is accepted basically as a kind of information that takes place in entities, things, experiences and also ideas.
Within the scope of this study, tourist destinations are defined as condition-dependent spaces. "Being visited" is accepted as the core condition to assess a space as a tourist destination. In this context, it is not difficult to claim for destinations that they can exist as long as they keep attracting new visitors. Thus, it could also be claimed that destinations have some characteristics making them worth visiting. From this point of view, the term destination value refers to all of the elements that make a tourist destination worth visiting.
In this respect, the concept of destination value can be regarded as a term that exposes the possibility of analysing the ongoing theoretical dilemmas, especially the difference between viewpoints that can be called bottom-up or top-down. It also offers an opportunity to overcome the differences "between theories that start from a certain notion of social structure, or social order, or some other totalizing notion, and theories that start from individual motivation" (Graeber, 2001, p. 20).

Intrinsic and Extrinsic Values of Destinations
Intrinsic value is a term with various similar meanings. Generally, two separate major views (subjective and objective views) are accepted regarding intrinsic value. One of these is "human valuing" and the other is not humanly conferred (Sandler, 2012). In this study, things with intrinsic value are considered have contain value on their own (O'Neill, 1992, p. 119). Naess (1984) thinks that the welfare of the life of non-human creatures in the world has a value in itself. This value is independent of the provision of any instrumental benefit for human being. From this perspective, it could be said that the term intrinsic value is used to refer to the value of an object due to "its merit". In this context, intrinsic value is used synonymously with "objective value" (O'Neill, 1992, p. 120). It can be seen that definitions of intrinsic value include the value of something "in itself", "as an end", "for its own sake" (Kagan, 1998), "as such" or "on its own" (Ronnow-Rasmussen, 2015). Within the scope of this study, a similar approach was adopted for the intrinsic values of a destination. From this point of view, the intrinsic value of a destination refers to what is indispensable for a space in the context of the tourism phenomenon. In other words, the intrinsic values of a destination are the features that make a place worth visiting for all the values that it offers, even if there is no industrialized tourism activity.
There are also various definitions of extrinsic value. The fundamental definition of extrinsic value deals with the things which are not valuable for its own sake (Ronnow-Rasmussen, 2015). In this perspective "the values that need to be justified by other values" are accepted as extrinsic values (Harold, 2005). Another definition discussed in this study is "instrumental value" or instrumental feature of extrinsic value proposed by Lewis (1955). An instrumental feature of the extrinsic value and its bases on the "utilitarian benefits" (Shamim, Ghazali, & Jamak, 2015) are important for explaining the destination value defined in the study. For example, Seddighi and Theocharous (2002) reported that "acts of political instability" is playing an important role in the tourists' destination selection. In this perspective, political stability is seen as an extrinsic value of a destination. Simply, the extrinsic value of a destination is the type of destination value that plays a catalyser or an activator role in tourism and especially in industrialized tourism.

Methodology
A mixed methodology was adopted for achieving the objectives of the study. The approach used in this study could be summarized as an explanatory sequential design (Creswell, 2014;Ivankova, Creswell, & Stick, 2006). In the first part (qualitative) of the study, the destination value model was developed based on the relevant literature and document review. In the second part (quantitative) of the study, the model developed in the first part was tested through fuzzy criteria weighting by pairwise comparisons technique. The qualitative data (for the first part) and the quantitative data (for the second part) were both collected and analysed separately.

Reviewed Literature
Within the scope of the study, a discussion was made on the literature of value. As a result, a definition of destination value is developed. In this direction, a hierarchical model was prepared due to the factors and sub-factors forming the destination value. Literature and document reviews were conducted to create a hierarchical model. While determining the reviewed literature, studies that were discussed, defined or aimed to measure the concepts such as destination attractiveness, tourist attractions, tourism resources, travel motivations, tourist motives are taken into consideration (Table 1). audio and visual records of interviews with 522 tourism professionals were produced. Outputs from this project were published in a ten-volume book.

Modelling Procedures
In this qualitative part, thematic content analysis (Emmons & King, 1992;Winter, 1992) was adopted to reach the objectives of the study. An element pool was created from the items determined as a result of the literature review and document analysis. Subsequently, the items in this pool were subjected to a thematic classification. While making this classification, keeping the number of forming elements at the lowest level by interpreting the scope of the elements as broadly as possible was aimed. Thus, the hierarchical model was accomplished in four themes, two side-themes and 22 sub-themes (or forming elements).
The hierarchical model was changed in three steps (times of coding) from the beginning to the end of the qualitative stage of the study. These steps are the procedure followed to increase the trustworthiness of qualitative research via intra-coder reliability. Intra-coder reliability is a suitable alternative with member-check or participant validation, especially when a researcher working alone or dealing with complex and unstructured data (Morse, 1997;Saldaña, 2016). Intra-coder reliability allows a researcher to evaluate the consistency of data s/he is coding. In this technique, it is recommended to code and recode the data at different times (Miles, Huberman, & Saldaña, 2014). It is suggested that the consistency between individual times of coding should be at least 85-90%, depending on the complexity of the data and structure (Morse, 1997). It is also recommended that the findings related to these times of coding with experts should be assessed. Thus, valuable feedback is obtained throughout the analytical processes executed and the trustworthiness of the results are increased (Austin & Sutton, 2014;Barbour, 2001).
The findings of the first coding (coding time 1) were discussed with an expert panel consisting of two professors and one associate professor owning more than 25 years of professional experience in their field. This expert panel concluded that a simpler model could be possible by combining some of the elements and interpreting some others more broadly.
The findings of the second coding (coding time 2) were discussed with the same expert panel. As a result, some changes were made. As an example, traditions which were considered as a sub-element of community and culture-based value, was expanded and named as lifestyles. The name of the industrial value theme was changed to industry based value to avoid misunderstanding. Another change was made by subtracting the prices factor handled under industry based value. As discussed in the previous titles, prices were accepted as a measurement unit of the value. Therefore, it was not considered as an element forming the destination value. After the third coding (coding time 3) which started for such purposes, the themes and the forming elements (sub-themes) of the model were formed as follows (numbers= themes, letters= forming elements or sub-themes), (changes are highlighted in italics); (1) Nature-based value consisting of (a) climate and weather, (b) physical geography, (c) biodiversity, (d) environmental liveability and (e) environmental protection and landscaping; (2) community and culture-based value consisting of (a) narratives, (b) artefacts, (c) food and beverage culture, (d) religion and beliefs, (e) traditions, (f) special events; (3) political value consisting of (a) political will, (b) international relations, (c) safety and security, (d) local political atmosphere, (e) legal system, (f) education and research; (4) industry-based value consisting of (a) infrastructure, (b) hospitality, (c) transportation, (d) human resources, (e) popularity. 7

Destination Value Model
As a result of the above-mentioned procedures, destination value was divided into two as the intrinsic and extrinsic value of a destination. Nature-based values and community & culture-based values were defined as the values that affect the intrinsic value of a destination, while political values and industrybased values were defined as the values that affect the extrinsic value of a destination. Figure 1 illustrates the intrinsic and extrinsic value distinction. This illustration was inspired by the atomic model of Rutherford (1911). With this model, it was emphasized that metaphorically, intrinsic values in the core have a more important role than extrinsic values in terms of destination value. For these reasons, we found the illustration to be metaphorically appropriate. This illustration also shows the distinction between intrinsic and extrinsic values. Thus, the final model was structured as follows (numbers= themes, letters= forming elements or sub-themes);

Second Part -Testing the Structure of Destination Value Model Fuzzy Sets Theory
Fuzzy sets theory was developed by Zadeh (1965) to overcome this presumed "imprecision" and "vagueness" inherent in human judgements. Fuzzy sets are distinguished from traditional sets using crisp numerical values because they also rationalize the use of linguistic variables during the modelling.
In this study, a fuzzy set A in a universe of discourse X is characterized by a membership function of () (Chen, Lin, & Huang, 2006;Kaufmann & Gupta, 1991). (1) (1) Nature-based value consisting of (a) climate and weather, (b) physical geography, (c) biodiversity, (d) environmental liveability and (e) environmental protection and landscaping; (2) community and culture-based value consisting of (a) narratives, (b) artefacts, (c) food and beverage culture, (d) religion and beliefs, (e) traditions, (f) special events; (3) political value consisting of (a) political will, (b) international relations, (c) safety and security, (d) local political atmosphere, (e) legal system, (f) education and research; (4) industry-based value consisting of (a) infrastructure, (b) hospitality, (c) transportation, (d) human resources, (e) popularity;

Intrinsic values
Extrinsic values 0, ,  (Chen et al., 2006, p. 292) When x is accepted as a crisp value, the PTFN representation of the crisp value x is (x, x, x, x; 1, 1) as shown in Figure 3 ) m n m m m m n n n n m n m n m n m n ) m n m m m m n n n n m n m n m n m n mm mm m n m m m m n n n n n n n n This technique called graded mean integration approach (2) for defuzzification is preferred because it follows the steps of weighting with crisp numbers and allows for the defuzzification of individual or consolidated judgements given by participants (Kahraman, Öztayşi, Uçal Sarı, & Turanoğlu, 2014;Zeng, An, & Smith, 2007).
The main purpose of using fuzzy set theory could be summarized as ensuring "a better performance for specific applications" made in this study. Because it is accepted that "fuzzy logic allows decision-making with estimated values under incomplete or uncertain information" (Kahraman, Ertay, & Büyüközkan, 2006, p. 396).

Data Analysis
In the following sections, the method used in the study is explained step by step. The main reason for this is that various approaches were used together in this study. Therefore, the explanation of the stages of analysis and the equations used are a necessity of ethical principles.
The data collected were analysed by integrating fuzzy calculations into algorithms prepared by Goepel (2018) on MS Excel in order to calculate the equations presented in the following sections. The calculations were carried out in four phases (Figure 4). First phase -consistency calculations related to expert judgements Calculations were first made separately for destination value and the sub-factors determining it and then structured as two parallel processes in terms of mass tourism, in two contexts: culture and history destinations; and sea, sand, sun destinations.

Figure 4. Data Analysis Process
These calculations are based on the comparison of the number of elements and the eigenvalues (λ) of the elements. For the calculation of eigenvalue, first, matrix multiplication is made between the pairwise comparison matrix and the w column vector. Then, eigenvectors (E) are generated (3). Finally, the eigenvalue related to the comparisons is obtained by calculating the arithmetic mean of eigenvectors (4).
In Satty's process (1980), the consistency index (CI) is calculated by (5). Then, the CR is calculated by dividing the CI by the value corresponding to the number of elements from the RI (6). We used this for calculating individual consistency.
In this study, Alonso/Lamata linear fit resulting (7) were used to calculate the consolidated CR. According to Alonso and Lamata (2006), this technique aims to eliminate the inflexible and restrictive characteristics of traditional consistency criteria for comparison matrices, especially when the size of the matrices increases.
In Satty's original method, we see that the matrices with a CR of 0.10 or less are considered to be consistent (Saaty & Vargas, 2012, p. 9). The use of matrices with an inconsistency ratio of less than 0.20 is considered suitable for the calculations (Saaty, 1977). In the literature, it is seen that the inconsistencies between 0.10 and 0.20 are acceptable and the matrices with these values are used in the calculations according to the needs of the structure discussed (Byun, 2001;Dawotola, van Gelder, & Vrijling, 2009;S. Lee & Walsh, 2011;Liang & Peng, 2017). In this study, matrices that have CRs less than 0.15 were accepted as consistent. The reason for this is the flexibility needed due to the size of the structure subjected to pairwise comparisons.

Second phase -fuzzy criteria weighting by pairwise comparisons
In this study, we decided to use a reminiscent approach in calculations which Kahraman et al. (2014, p. 52) used in their study and described as " Buckley's (1985) fuzzy AHP method has received no criticism." In Step 1, for fuzzification, the scale of relative importance used in the pairwise comparisons prepared by (Zheng et al., 2012, p. 232) In Step 2, the consolidated pairwise comparison matrix (B) which contains the answers of each participant (k) was created. For calculating the weighted geometric mean (3.10), each aij(k) of pairwise comparison matrices was used and multiplied with the related participant's weight multiplier (wk). In this study, the individual weight multiplier is accepted as 1 (wk=1).
In order to calculate the relative weights () i P of the elements, the row geometric mean method (3.11) was used, and the consolidated weights were calculated due to the normalization of row vectors () i R (12).
and the mean relative error (MRE) (16 and 17) (Tomashevskii, 2015) was calculated in addition to CR.
Eigenvector technique: The GCI is a technique that measures cardinal consistency such as the abovementioned Alonso/Lamata CR. The difference between the two is that Alonso/Lamata CR is based on the eigenvector and GCI is a distance-based technique. Another type of consistency that would arise when considering the consistency of pairwise comparisons matrices is the ordinal consistency, also called transition. Satty's (1980) CR, Alonso/Lamata CR or GCI does not take transition into account when measuring cardinal consistency. In this study, ordinal consistency was also measured by dissonance (Ψ) calculations (Siraj, 2011, pp. 47-52;71). For this purpose, the congruence matrix was formed. Dissonance calculations were then performed. Ψ = 0 means perfect congruence. Siraj (2011, p. 148) produced some findings related to transition in matrices when Ψ ≈ 0,20. In this study, Ψ < 0,20 was used as an acceptable value.
MRE is used to identify errors in eigenvector based consistency calculations. Tomashevskii (2015) suggests that errors in the weights sometimes reduce the consistency, even if the GCI is within the appropriate limits. The approach proposed for this purpose is to take MRE into account (16,17).

Fourth phase -model integration
For model integration, it is necessary to calculate the universal weights of the sub-factors of each factor in the model. When the Pi is accepted as the defuzzified local weight of each factor, it is possible to measure universal weights (Gi). When Si is considered to be the parent factor weight of Pi, this calculation is made by equation (18).

Data Collection Tool
Based on the hierarchical model ( Figure 5), the factors of the destination value were subjected to pairwise comparisons with the fundamental scale of absolute numbers developed by Saaty (1980). The original scale is a 9-point ratio scale which was prepared to show the importance of element A in comparison with element B (Saaty, 2008, p. 86).
Within the scope of the study -with the help of the modification made in the scale -the unidirectional original scale structure was arranged in two directions and thus, the number of comparisons to be made was reduced by half. In this context, in the pre-test which was conducted on 12 researchers working in a tourism faculty of a state university in Turkey. We saw that all participants, except one, understood the use of the scale without any explanation. In the ongoing process, similar examples of the scale used in this study were also found in the literature (Hummel, Bridges, & IJzerman, 2014;Song et al., 2018).
Thus, a total of 56 pairwise comparisons were included in the questionnaire, six of which were for factors determining destination value. In the questionnaires, the concept of destination value, the elements that forming this concept, the definitions related to each sub-component of these elements, the purpose of the research, and explanations regarding the use of the scale were included.
Prior to this, the participants in the participant pool had received permission to take part in the study. Details regarding the purpose, objectives and use of the questionnaire were then presented to them. Communication with participants in Turkey was done face to face or by phone. Participants out of Turkey were contacted via e-mail.

Profile of the Participants
Within the scope of the research, the purposive sampling method was found appropriate. A pool of 177 experts, including academicians, hospitality company and travel agency managers, and professional tourist guides, was established to measure the importance weights of the factors determining the destination value and its sub-factors. Data collection was performed between 31 July 2018 and 11 December 2018.
Thirty-nine experts could not be reached. Four of them did not want to participate in the study. Thus, questionnaires were sent as hard copies or via e-mail to the 134 experts who agreed to participate. In addition, further information relating to the questionnaire and the research topic was provided by telephone or face to face.
Participants who did not respond for a while were sent a couple of reminders. Despite the reminders, 45 participants still failed to respond despite having agreed to participate in the study. Thus, 30 of the 89 returning participants, who gave inconsistent or incomplete answers, were not included in the analysis.
Of the 59 participants, 21 made comparisons in terms of both sea, sand, sun destinations and, culture and history destinations. 19 gave comparisons for only sea, sand, sun destinations, and 19 other participants gave comparisons for only culture and history destinations. In the context of mass tourism, the details regarding the participants who made comparisons for each destination type are given in Appendices 2 and 3. These tables show that responses from four professional tourist guides, a hotel manager, a tourism educator and 34 academics were used in the concept of sea, sand, sun destinations; the judgements of five professional tourist guides, two hotel managers, a tourism educator and 32 academics were used in the concept of culture and history destinations.

Findings related to the Consistency of the Participants' Judgements
It was mentioned in the previous paragraphs that the research aimed to test the hierarchical model for destination value. Therefore, after the inconsistent questionnaires were extracted, the number of 80 (40 + 40) participants that gave comparisons for both types of destination were considered compatible for further analysis (Table 5).

Findings regarding the Distinction between Intrinsic and Extrinsic Values of Destinations
After extracting participants who made inconsistent judgement even in one factor; a total of 44 participants' judgements, 22 for each destination type, were taken into further analysis. As shown in Table 6, the result of the consistency analysis is found acceptable regarding the limits mentioned in previous paragraphs. It is also found that the absolute error values regarding each factor, which is shown as +/-in the table, are in acceptable levels.
When the combined hierarchical model ( Figure 5) of the two types of destination is examined. It is seen that importance weights of the nature-based value (wi3s= 0.465; wich= 0.274) and the community and culture-based value (wi3s= 0.231; wich= 0.461) -which are defined as factors determining the destination's intrinsic value -were found to be relatively high compared with the political value (wi3s= 0.125; wich= 0.143) and the industry-based value (wi3s= 0.179; wich= 0.122) which are defined as the factors determining the destination's extrinsic value. These results were taken as supporting evidence for the distinction of the intrinsic and extrinsic value of destination, for both types of destination discussed in the study.
Another important point in the model is that, when sea, sand, sun destinations are considered, the nature-based value (wi3s= 0.465) is the most important factor for the intrinsic value of destination. By contrast, when culture and history destinations are considered, the community and culture-based value (wich= 0.461) is the most important factor for the intrinsic value of destination. A similar shift between factors was also found among the factors of the extrinsic value of the destination. This result suggests that the model responds to changes in the type of tourism observed in different types of destination. A similar shift between factors was also observed when the sub-factors of the model were examined. For example, the climate and weather (wi3s= 0.112) factor was found to be the most important sub-factor in terms of sea, sand, sun destinations. However, in terms of culture and history destinations, artefacts (wi3s= 0.143) factor was found to have the highest importance, while climate and weather (wi3s= 0.031) was ranked of lower importance. This result is also interpreted as the evidence of the model responding to changes in the type of tourism observed in different types of destinations. These results are thought to support the functionality of the model. whose judgments used in the analysis in the contexts of sea, sand, sun destinations and mass tourists ***Participants whose judgments used in the analysis in the contexts culture & history destinations and mass tourists According to the results, the most important elements of sea, sand, sun destinations are air temperature, clean seas and coastal structures. Climate and weather, physical geography and environmental liveability factors have high importance levels in terms of sea, sand, sun destinations. Similar results were observed for culture and history destinations. A comparison chart of the distribution of importance weights for all factors is presented in Appendix 4. These findings support the theoretically defined distinction of the intrinsic and extrinsic values of the destinations.

Conclusion
The concept of destination value and the factors determining it were defined with the literature review and document analysis. In this context, a hierarchical model was developed for the factors determining destination value. As mentioned in the study, this model is not a conclusion and could still be changed. However, it was considered sufficient for the aims of this study. Additions or simplifications can be made to the model according to the views of researchers. However, it is thought that the general context will be shaped within the framework of these elements.
The distinction between the intrinsic value of destination that expresses the value desired by tourists and the extrinsic value of destination that facilitates and catalyses this value is presented as a solution to the problems arising in the context of industrialized tourism. This reflects the fact that sustainability initiatives (such as; Aygün & Baycan, 2020; Mathew & Sreejesh, 2017;Rodríguez Díaz & Espino Rodríguez, 2016), which are presented as solutions to the problems posed by industrialized tourism, have an important place in this conceptualization. In the context of destination value as a value-based approach, intrinsic value is philosophically in a more important position and the role that falls on the extrinsic value is to support the intrinsic value. In this respect, the development of destinations by bringing the intrinsic value to the fore is also important in terms of the sustainability of tourism in these destinations.
Accepting that a tourist destination can be examined in the same way as an enterprise or a product by ignoring the performance of the tourists, examining a destination in a pure manufacturer-consumer context could prevent us from seeing the problems. Products exist for consumption. They are consumed and depleted. Approaching tourist destinations as if they were a packaged product is to accept these structures as unsustainable (see. Davis & Morais, 2004;Riasi & Pourmiri, 2016;Tosun, 1998) at the outset. To consider a tourist destination as a kind of enterprise means that the primary purpose of its existence is to make and increase profits. Even though the primary objective of some of the stakeholders operating within a destination is to make a profit, it should not be forgotten that what is defined as a destination does not itself have a desire to make a profit, to increase profit or to achieve competitive advantage over other destinations. This perspective adopted in the study is accepted as the starting point of the destination value approach. It is appropriate to interpret the most prominent characteristic of this approach built on the concept defined upon the terms intrinsic and extrinsic values in the light of temperance which Democritus defines as the highest virtue.
Increasing the number of tourists and increasing tourism revenues by achieving competitive advantage seems to be positive in terms of the economy. However, taking into account the costs of these actions on tourist destinations leads to a less optimistic outlook. It is possible to give commodification of culture (Bowers & Cheer, 2017), illegal sex tourism (Ying & Wen, 2019), malpractices in medical tourism (Mirrer-Singer, 2007) or other kind of adverse situations such as overtourism (see. Perles-Ribes, Ramón-Rodríguez, Moreno-Izquierdo, & Such-Devesa, 2021), in addition to well-known environmental problems arising with the industrialized tourism. Sustainability approaches added to destination competitiveness (Ritchie & Crouch, 2010), or Porter's addition of shared value creation (Porter & Kramer, 2011) to his competitiveness paradigms, tell us that these additions aim to reduce the costs. But there is no reason not to think that these additions to competitiveness paradigms aim to minimize any public reaction via sharing the benefits, even if costs to nature or culture are not reduced. It is also known that green tourism and responsible tourism are not the "correct answers" to the problems arising from industrialized tourism development (Wheeller, 1991). A paradigm shift is needed to solve the problematic reflections of tourism that continue today. The process which is experienced through COVID-19 pandemic could be seen as an opportunity for introducing new theories and insights for tourism research and destination development.

Limitations and Future Research
The use of small samples may be problematic for many studies involving data analysis and cause-effect relationships (Darko et al., 2018). However, reaching significant sample sizes targeting generalization or statistically strong results is not a necessity for performing 'criteria weighting by the pairwise comparisons' technique which is also used within other multi-criteria decision analysis (Darko et al., 2018;Dias & Ioannou, 1996;Doloi, 2008). Some researchers suggest that these are subjective techniques that address specific problems and do not imply an obligation to work with large samples (Darko et al., 2018;Lam & Zhao, 1998), while others suggest that such techniques are based on expert opinion and, in this context, even a single competent expert has a representation characteristic (Darko et al., 2018;Tavares, Tavares, & Parry-Jones, 2008).
This study aims to support the distinction made between the intrinsic and extrinsic value of destinations, which were seen by the authors as starting concepts of the above-mentioned paradigm change. In this context, when the experts' judgements were analysed, it was found that factors forming the intrinsic value of destination were relatively more important than factors forming the extrinsic value of destination. These findings were evaluated as positive results considering the research objectives. At this point, the findings of this study are thought to be important for structuring new approaches within the framework of destination development studies. It is thought that the information obtained from different disciplines such as economics, anthropology, sociology and administrative sciences can be used together under a destination value approach within the framework of tourism research.
This approach of destination value, including sub-concepts such as intrinsic and extrinsic values of destination, can be considered as an initiative capable of unifying the eclectic knowledge spotted in the literature. It is essential to prepare models that aim to measure the destination value for destination types and different types of tourists. Preparing a theoretical assessment to synthesise different value approaches under destination value is another direction for future research.