Exploring the Tourism Competitiveness of a Destination: A Case Study of Georgia

Abstract

The global expansion of the tourism industry has intensified competition between destinations, necessitating a deeper understanding of their competitive positioning. The aim of this study is to develop a research model that analyzes the competitive environment of a specific tourism destination and its relative position within the market, using Georgia as a case study. The competitive environment is analyzed based on the preferred travel destinations of the leading tourism-generating countries (or segments) of the destination under study. This approach is grounded in the expectation that a destination’s competitiveness in the global tourism market may differ from its position within a market composed of destinations favored by its primary visitor segments. To achieve this, the study applies the segment-centric geo-competitive environment of a tourism destination (SGE-TD) framework, which consists of three sequential analytical steps: (1) identifying competing destinations that define the study destination’s competitive environment, (2) outlining the key characteristics of this environment, and (3) identifying leading destinations and close competitors. This research has both methodological and practical implications. Methodologically, the paper introduces a structured and target-oriented framework incorporating an innovative SGE-TD approach, which defines a competitive environment based on top popular travel destinations among the top tourism generators of the study destination, along with corresponding analytical tools, which can be applied to similar studies.

1. Introduction

The tourism industry is one of the largest sectors of the global economy, with significant growth potential. In 2019, its contribution to global GDP was 10.3%, declining to 9.1% in 2023, but it is projected to rise to 11.4% by 2034 [1,2]. Additionally, the industry plays a vital role in employment, accounting for one in every ten jobs worldwide [1].

The evolving nature of global tourism has intensified competition between destinations. This competitive environment is shaped by dynamic social, economic, and natural factors, as well as the emergence of new destinations in international markets. Consequently, competitive conditions continue to evolve, diversifying the set of competing destinations.

In Georgia, tourism has traditionally been a key sector of the national economy and is considered a driver of sustainable development. The industry contributed 8.4% to Georgia’s GDP in 2019 and 7.1% in 2023 [3]. Following the collapse of the Soviet Union, Georgia emerged as a recognized tourism destination in the international market, benefiting from increased openness and accessibility for foreign visitors. However, global awareness of the destination remains relatively low, resulting in a relatively low competitive position in the World Tourism Market, ranking 44th [4]. As a result, further development of the industry is closely linked to its competitive performance and strategic positioning in the international tourism market.

The expansion of global tourism and the increasing complexity of its competitive landscape have prompted international organizations, national economies, and research institutions to develop standardized frameworks for statistical accounting, big data analysis, competitive indicators, indices, rankings, and reporting methodologies [1,4,5,6,7,8]. Academic research on tourism competitiveness has evolved alongside studies on business competitiveness, with increasing attention paid to destination-specific competitive frameworks. As Hefny notes, since the early 1990s, research has progressively shed light on the characteristics and framework of destination competitiveness [9].

The wide range of existing research focuses on multiple competitive variables, segmentations, competitive positions, competitive environments, etc. (for a detailed discussion, see the Literature Review section). The complicated multivariable competitive environment still leaves gaps for further studies, such as studies on the competitive environment of a specific destination developed by specific market segments of the same destination. Understanding how these factors interact can provide deeper insights into market dynamics and help stakeholders make more informed decisions. Additionally, exploring the interplay between these factors can reveal unique opportunities for destination marketing and development. By analyzing case studies and gathering empirical data, researchers can contribute valuable knowledge that shapes strategies for enhancing competitiveness in the tourism sector.

The aim of this study was to develop a research model designed to analyze the specific competitive environment of the studied tourist destination and assess its competitive position in this environment. The proposed research design was tested using Georgia as a case study. The structure of the paper is as follows: First, the thematic literature on conceptual approaches and models is reviewed, highlighting the relevance of the applied segment-centric geo-competitive environment of a tourism destination (SGE-TD) framework. Next, the study identifies countries that constitute Georgia’s foreign tourism market and segments these tourism-generating countries based on their preferred travel destinations. Subsequently, competitive indicators are selected and analyzed to characterize Georgia’s tourism competitive environment. The study then examines the key features of this environment, including its principal components, driving forces, the competitive positions of leading destinations, and the destinations identified as close competitors to Georgia. Finally, the research findings are generalized and discussed.

From a practical perspective, this study provides insights into Georgia’s competitive tourism environment, highlighting its key components, driving indicators, leading destinations, and close competitors. These outcomes suggest strategic approaches to enhancing Georgia’s competitive positioning in the global tourism market. The research findings in general may also serve as a basis for positioning more in-depth studies on specific methodological and practical challenges related to a destination’s competitiveness.

2. Literature Review

The exploration of tourism destination competitiveness, as a category of the general competitive environment with a focus on the territorial component, involves many interrelated concepts, definitions, and research designs that were developed over the decades, still leaving gaps for further studies.

Interest in research on tourism destination competitiveness (TDC) has grown alongside the global expansion of the tourism industry. Over the past three decades, more than 1130 articles on tourism destination competitiveness have been published in reputable journals [10]. These studies address various facets of the subject, including theoretical foundations, competitive environment modeling, destination market segmentation, the identification of competitive variables and indicators, and the determination of competitive environments for competing destinations.

The concept of competitive strategy was introduced by Harvard Business School professor Michael Porter in 1979 through his widely recognized Porter’s Five Forces framework. This model highlights the key competitive forces that a company must consider to strengthen its market position [11,12]. Later, Porter expanded on this idea with the Diamond Model [13], which evaluates an industry’s international competitiveness. Rugman and D’Cruz (1993) extended the Diamond Model further with the Double Diamond Model (DDM), incorporating competitive strategy on global, regional, and national levels [13].

Dwyer and Kim [14,15] developed a TDC Model designed to facilitate comparisons between countries and tourism sectors. Initially tested in Australia [16], this model emphasized key elements of competitiveness from the broader literature while addressing the unique issues associated with destination competitiveness. Their subsequent work refined the methodology, expanding the range of competitive indicators used in the analysis [17].

Ritchie and Crouch [18] proposed the TDC and Sustainability Model, which focuses on the macro and micro levels of the competitive environment. This model identifies seven key components that influence a destination’s competitiveness and sustainability, highlighting the synergy between comparative and competitive advantages [18]. This dual perspective of competitiveness is essential for understanding a destination’s market position [19]. A special study was dedicated to systematizing and explaining the definitions popularized in connection with the development of these concepts and models [20]. Lusticky and Bednarov focused their research on the Conceptual Model of Destination Competitiveness (CMDC) developed by Ritchie and Crouch and the Integrated Model of Destination Competitiveness (IMDC) developed by Dwyer and Kim, underlining the gap between research and planning practice and suggesting an improvement for the model, enabling regional destination managers to reduce the gap and enhance the destination’s competitive position via intensive collaboration with destination stakeholders [21].

Various studies have explored specific components of the TDC model, particularly those related to the supply side of tourism destinations at different levels, such as countries, regions, or specific locations. Their competitive indicators include factors like natural and cultural attractions, infrastructure, and services [22,23,24]. On the demand side, segmentation research focused on demographic, behavioral, psychographic, firmographic, and technographic factors, as well as geographical segmentations based on factors such as population density and climate [25,26,27,28,29]. Many destinations use country of origin as a segmentation criterion to tailor their marketing strategies to specific tourist profiles [30]. Research on diverse aspects of tourists as buyers and territorial classification by their origin and visiting places significantly depends on the specifics of destinations and tourism sectors [31].

The competitive environment of a destination is multi-dimensional, encompassing core resources and attractors, supporting factors, destination policy, planning, development, and management. Ritchie and Crouch [19] categorized these factors into the global (macro)- and competitive (micro)-environments. The macro-environment includes economic, technological, ecological, political, sociocultural, and demographic factors, while the micro-environment refers to the immediate forces influencing tourism activities within the destination itself [19].

Some studies have criticized previous research for focusing too narrowly on either comparative or competitive advantages. Gonzalez-Rodríguez et al. [32] proposed a hybrid approach that integrates both dimensions, offering a more holistic view of destination competitiveness [32].

In terms of research methodologies, scholars have applied classical and innovative analytical tools to assess destination competitiveness. Cracolici et al. [33] used the Crouch–Ritchie model to analyze destination efficiency and competitiveness, while Lusticku and Bednarov [21] explored factors of competitiveness using the Integrated Model of Destination Competitiveness. These approaches provide valuable insights into how competitiveness influences destination performance.

Vodeb K. emphasizes that “There is a vast body of literature about competition, competitive advantage, and competitive identity in tourism” [34]. Also, there is a dearth of studies linking tourism competitiveness (TC) to tourism performance” [34,35]. “Destinations could be compared by their ability to adapt and maintain competitive positions in the tourism market, as changes in tourism affect destination performance and success” [34].

A popular methodology dedicated to the assessment of tourist destination competitiveness through the Crouch–Ritchie model and the Travel and Tourism Competitiveness Index (TTCI) recommends the use of methods of data envelopment and bootstrapped truncated regression [32]. Benchmarking is another popular method used in competitiveness assessments. It involves identifying and comparing the strengths and weaknesses of a destination relative to its competitors [35]. Another study conducted by Fernández et al. proposes the construction of a synthetic index based on TTDI variables to classify 80 countries by their level of tourism competitiveness [36].

A wide variety of analytical methods were adjusted to the variables and indicators presented in the aforementioned models of tourism destinations competitiveness. A special statistical tool was developed, focused on the tourism decision process, which starts from the demand schedule for holidays and ends with the choice of a specific holiday destination, and was tested in the case of Italy as a tourism destination [37]. Studies have also employed Multi-Criteria Decision Analysis (MCDA) methods, such as ELECTRE I, to evaluate tourism destinations [38]. The Importance–Performance Analysis (IPA) model [39], as well as Importance–Performance–Competitor Analysis (IPCA), have been used to compare destinations and highlight areas for strategic improvement [39,40].

Some scholars have further refined the categorization of competitive indicators. Ferreira and Perks [41] identified three primary themes influencing destination competitiveness: core, facilitating, and supporting indicators. These themes provide a foundation for understanding the socioeconomic dynamics between developed and developing countries. Additionally, the 4 Cs Tourism Destination Competitiveness Matrix [42] identifies four key dimensions: capacity, competence, communication, and creativity. These dimensions are essential for evaluating the competitiveness of destinations, as they address aspects like infrastructure, human resources, marketing, and innovation. Another study dedicated to destination competitiveness across OECD countries aimed to conceptualize destination competitiveness in terms of tourism’s direct contribution to GDP and energy efficiency [43,44].

The role of information technologies in tourism competitiveness has also garnered attention in recent studies. Researchers have explored how digital tools and innovations enhance competitiveness in European destinations [45].

A growing body of literature evaluates the competitiveness of specific countries as tourism destinations. These studies have been conducted on destinations such as Hong Kong [46], Italy [47], Greece [48], Portugal [49], Serbia [50,51], India [52], Japan [53], China [54], Georgia [55], OECD countries [43], the Mediterranean region [56], the Caribbean region [57], in developing countries [58] etc.

Georgia, as a relatively emerging tourism destination, presents a special unique case. The leading segments of tourism in Georgia are represented by Armenia, Türkiye, and Russia, composing more than 50% of the foreign visitors, making up less than 3% of the global travelers, while the global leading tourism generators—the US, China, Germany, and the UK—make up more than 25% of the global tourism market, contributing just less than 2.8% to the Georgian market [3,7]. This reality underlines the need for a tailored approach to studying the competitive environment of destinations with specific tourism markets, which is typical for many destinations in general.

3. Methodology

The diverse and multifaceted studies on the competitive tourism environment still leave gaps for further scientific exploration. The studies conducted in this field define the competing destinations based on different, non-systematized indicators, such as empirically selected comparable destinations [26,30]; destinations within one country [33]; destinations based on facilities, cultural heritage assets, and natural history [35,59]; neighboring countries or countries within the surrounding region [16,29,44,55,60,61,62]; countries with developing economies [58]; countries ranked above 50th place per TTDI scores [1,50]; the preferred countries for visitors of the study country [16]; and countries with some comparable indicators and/or the positions of countries in the global market according to separate indicators [15,32,47,49], etc.

In this line, a new approach named segment-centric geo-competitive environment of a tourism destination (SGE-TD) was introduced by Khelashvili I. [61]. The competitive environment was determined by the range of countries that are popular travel destinations for those specific countries, which, in turn, are the leading tourism generators (or segments) for a study destination [61]. This approach allows for an adequate evaluation of a studied destination’s competitive position in the identified and most relevant competitive environment. Such an approach is justified by the highly expected fact that a destination’s competitive position in the global tourism market differs from its position in the market composed of destinations that are popular precisely among the leading segments of the studied destination.

The SGE-TD concept lies between the concepts of competitive macro- and micro-environments. It is considered in the category of international regional approaches [36,43] focused on determining competing destinations (countries) and the relevant competitive environment.

Another component that needs to be defined for the study is the range of competitive variables and the relevant indicators. The researchers underlined that despite a voluminous body of literature identifying and measuring “determinants” of destination competitiveness, there is no consensus regarding just what destination competitiveness means [15,18,63].

The World Economic Forum, in collaboration with the University of Surrey, has been providing comprehensive reports on The Travel and Tourism Development Index (TTDI, formerly TTCI) since 2007. Fernandez et al. developed a methodology for tourism competitiveness based on this index, constructing a synthetic index to rank countries attracting the most international tourists based on their level of tourism competitiveness [56]. This index addresses issues such as variable aggregation, arbitrary weighting, and duplicity of information [36,56]. The latest edition includes 5 dimensions, 17 pillars, and 102 individual indicators, covering 119 economies (Travel and Tourism Development Index 2024) [1,64]. Due to the methodology, coverage, and content of these indices, as well as the availability of relevant data for most countries, the TTDI was chosen for this study.

4. The Research Design and Applied Methodology

The research design consists of the following steps:

• Identifying competing tourist destinations for the destination under study (Georgia, in this case);
• Analyzing the identified competing travel destinations composing the competitive environment for the study destination;
• Identifying the features of the studied competitive environment, focusing on the driving forces and the competitive position of the study destination.

The main feature of the proposed research design is to specify the competitive environment of the studied destination by defining the preferred destinations of the leading tourist segments of the same studied destination. This approach differs from the practiced approaches of selecting competing destinations for research based on geographical factors, general popularity, accessibility, industry profiles, and other criteria and helps to determine the most realistic competitive position of the study destination and uncover insights for more general strategic planning.

Step 1: Identifying Competing Tourist Destinations for the Destination Under Study

To determine the destinations that constitute Georgia’s competitive environment, we apply the segment-centric geo-competitive SGE-TD approach [61]. First, we identify Georgia’s leading tourism-generating countries, followed by identifying the primary travel destinations for tourists from each of these countries.

For the first task of this stage, it was assumed that tourists from these countries should collectively account for at least 80% of all foreign visitors to Georgia in order to ensure adequate representation. According to the latest statistics for 2023, the number of countries that annually send 20,000 or more tourists to Georgia is 23. The share of tourists from these countries accounts for 87.6% of all foreign tourists visiting Georgia (see Figure 1), which justifies the use of data related to these countries for further analysis.

The stark reality underscores the importance of market diversification, which is essential for strengthening Georgia’s competitive position in its foreign tourism market.

To achieve the objective of the second task of the same step, we determined the top 10 preferred tourism destinations (countries) from each of the 23 segments previously outlined. This analysis revealed 61 tourism destination countries, which collectively constitute Georgia’s geo-competitive environment, as defined by the SGE-TD concept (see

Table 1. Top tourism destinations for Georgia’s tourism-generating countries.

			Top 10 Destinations Ranked by Priorities
			1	2	3	4	5	6	7	8	9	10
Tourism Generating Countries	1	Russia	Türkiye	Thailand	UAE	Egypt	Uzbekistan	Kazakhstan	China	Georgia	Tunisia	Azerbaijan
	2	Türkiye	Greece	Romania	Saudi Arabia	Georgia	Iran	Bulgaria	Germany	UK	Azerbaijan	Italy
	3	Armenia	Georgia	Russia	Iran	Türkiye	Egypt	Kazakhstan	Poland	US	Lebanon	Romania
	4	Israel	Türkiye	US	Egypt	Spain	Austria	Poland	Romania	Cyprus	Germany	UK
	5	Azerbaijan	Iran	Georgia	Türkiye	Russia	Kazakhstan	Saudi Arabia	Romania	Uzbekistan	Bulgaria	US
	6	Kazakhstan	Uzbekistan	Russia	Türkiye	Egypt	Georgia	China	Kyrgyzstan	Azerbaijan	South Korea	Thailand
	7	Ukraine	Poland	Romania	Bulgaria	Türkiye	Czech Re.	Germany	Egypt	Croatia	Russia	Austria
	8	Belarus	Poland	Türkiye	Lithuania	Georgia	Russia	Egypt	Ukraine	Kazakhstan	Bulgaria	Romania
	9	Iran	Türkiye	UAE	Azerbaijan	Armenia	Georgia	Canada	Kuwait	China	India	Russia
	10	Poland	Italy	UK	Germany	Türkiye	Spain	Croatia	Greece	Hungary	Austria	Czech Rep.
	11	India	UAE	Thailand	US	Saudi Arabia	Kuwait	Singapore	Malaysia	UK	Indonesia	Bahrain
	12	Saudi Arabia	Kuwait	Bahrain	UAE	Egypt	Türkiye	Jordan	Qatar	UK	Thailand	Austria
	13	Germany	Austria	France	Italy	Spain	Netherlands	Türkiye	Poland	Denmark	Greece	Croatia
	14	Uzbekistan	Kazakhstan	Tajikistan	Türkiye	Russia	Saudi Arabia	Kyrgyzstan	South Korea	Georgia	Azerbaijan	Latvia
	15	China	Hong Kong	Macau	Thailand	Japan	South Korea	Vietnam	Malaysia	Singapore	US	Cambodia
	16	US	Mexico	Canada	UK	Spain	Italy	France	Puerto Rico	Germany	Dominica	Japan
	17	Philippines	Hong Kong	Japan	Singapore	Thailand	UAE	China	South Korea	Malaysia	US	Taiwan
	18	UK	Spain	France	Italy	Ireland	Greece	US	Türkiye	Portugal	Germany	Netherlands
	19	Jordan	Saudi Arabia	Türkiye	UAE	Egypt	Kuwait	Lebanon	Bahrain	US	Cyprus	Israel
	20	France	Spain	Italy	UK	Greece	Germany	Portugal	US	Belgium	Morocco	Türkiye
	21	Latvia	Lithuania	Poland	Estonia	France	Russia	Sweden	Türkiye	Germany	UK	Greece
	22	Greece	Türkiye	Albania	Italy	Bulgaria	UK	Cyprus	France	Germany	Spain	Netherlands
	23	Lithuania	Poland	Latvia	UK	Türkiye	Germany	Greece	Estonia	Russia	Italy	Czech Rep.

Source: WB [6], TRUSTYOU [8].

).

To assess the validity of considering Georgia’s international tourism competitive environment (SGE-TD of Georgia) separately from the global competitive tourism environment, a comparison was conducted using two alternative calculations.

The first calculation shows the presence of the top 10 most popular tourist destinations globally within the list of the top 10 preferred destinations for countries generating foreign tourism to Georgia. The second calculation is similar but includes ranking scores for destination preferences, ranging from 10 for the most popular to 1 for the least popular destination.

P%(ps) = (SUM DS/SUM DG) 100% = (79/230) × 100% = 34.3%;

(1)

P(rs)% = [SUM DS(s)/SUM DG(s)] 100% = (453/1265) × 100% = 35.8%

(2)

where

P%(ps)—share of top preferred global destinations among the 10 preferred

destinations of the studied segments by presence scores;

DS (ps)—number of the top preferred global destinations present among

the top 10 preferred destinations of the studied segments;

DG—top 10 preferred tourism destinations in the global market.

The calculation in (2), which incorporates ranking scores for globally popular destinations present in the top 10 preferred destinations of the studied segments, yielded similar results. Both calculations indicate that the preferred travel destinations among Georgia’s tourism-generating countries do not align with those in the global tourism market. Approximately 35% of the preferred destinations overlap, with around 75% being different.

These calculations validate the consideration of Georgia’s SGE-TD as distinct from the global tourism market.

Regarding the selectivity of destinations within Georgia’s SGE-TD, it is important to highlight that despite the considerable differences between destinations, Turkey stands out as particularly popular. It is followed by 31 relatively popular destinations (with ranking scores of 5 and higher), including Georgia itself (see Figure 2,

Table 2. Selectivity of the world’s top tourist destinations by Georgia’s top 23 tourism-generating countries.

Rank	Score	Top 10 Globally Popular Tourism Destination Countries	Top Tourism-Generating Countries for Georgia
			1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23
			RUS	TUR	ARM	ISR	AZE	KAZ	UKR	BEL	IRN	POL	IND	SAU	DEU	UZB	CHN	USA	PHL	GBR	JOR	FRA	LVA	GRC	LTU
1	10	FRA	TUR	GRC	GEO	TUR	IRN	UZB	POL	POL	TUR	ITA	UAE	KWT	AUS	KAZ	HGK	MEX	HGK	ESP	SAU	ESP	LTU	TUR	POL
2	9	ESP	THA	ROM	RUS	USA	GEO	RUS	ROM	TUR	UAE	GRB	THA	BHR	FRA	TJK	MCU	CAN	JPN	FRA	TUR	ITA	POL	ALB	LVA
3	8	USA	UAE	SAU	IRN	EGY	TUR	TUR	BGR	LTU	AZE	DEU	USA	UAE	ITA	TUR	THA	GRB	SGP	ITA	UAE	GRB	EST	ITA	GRB
4	7	ITA	EGY	GEO	TUR	ESP	RUS	EGY	TUR	GEO	ARM	TUR	SAU	EGY	ESP	RUS	JPN	ESP	THA	IRL	EGY	GRC	FRA	BGR	TUR
5	6	TUR	UZB	IRN	EGY	AUS	KAZ	GEO	CZE	RUS	GEO	ESP	KWT	TUR	NLD	SAU	SKR	ITA	UAE	GRC	KWT	DEU	RUS	GRB	DEU
6	5	MEX	KAZ	BGR	KAZ	POL	SAU	CHN	DEU	EGY	CAN	HRV	SGP	JOR	TUR	KGZ	VNM	FRA	CHN	USA	LBN	PRT	SWE	CYP	GRC
7	4	GRB	CHN	DEU	POL	ROM	ROM	KGZ	EGY	UKR	KWT	GRC	MYS	QAT	POL	SKR	MYS	PRC	SKR	TUR	BHR	USA	TUR	FRA	EST
8	3	DEU	GEO	GRB	USA	CYP	IZB	AZE	HRV	KAZ	CHN	HUN	GRB	GRB	DNK	GEO	SGP	DEU	MYS	PRT	USA	BEL	DEU	DEU	RUS
9	2	GRC	TUN	AZE	LBN	DEU	BGR	SKR	RUS	BGR	IMD	AUS	IDN	THA	GRC	AZE	USA	DOM	USA	DEU	CYP	MAR	GRB	ESP	ITA
10	1	AUS	AZE	ITA	ROM	GRB	USA	THA	AUS	ROM	RUS	CZE	BHR	AUS	HRV	LVA	KHM	JPN	TWN	NLD	ISR	TUR	GRC	NLD	CZE
Presence score			1	4	2	5	2	1	3	1	1	8	2	3	6	1	1	6	1	7	2	7	5	6	5
Ranking score			6	13	25	25	14	6	10	6	6	32	12	11	35	6	8	38	8	45	14	39	25	39	22
SUM of Presence scores			80							Sum of Ranking Scores					445
Max			230							Max					1265
P%(ps)			34.8%							P%(rs)					35.2%

Authors: I.Khelashvili; L.Okroshidze.

, Appendix A).

Step 2: Analyzing the identified competing travel destinations composing the competitive environment for the study destination

Following the identification of key components in the competitive environment, such as market segments and their preferred travel destinations, the next step involves

(A)

Determining relevant competitive indicators for the study;

(B)

Analyzing the competitive environment composed of the identified competing tourism destinations.

To address Objective A, relevant competitive characteristics, indicators, pillars, and indices are considered. Given the methodology, scope, and content of these indicators—as well as data availability for the studied countries—this study utilizes data from the World Economic Forum’s Travel and Tourism Development Index [4].

For Objective B, we examined the identified competitive environment, which includes 5 competitive countries and encompasses 61 prominent tourism destinations among Georgia’s top 23 tourism-generating countries (segments). The principal component analysis (PCA) methodology was chosen as the most relevant tool for this analysis. This methodology allows for reduction of dimensionality to the principal components, while preserving most of the original information.

The PCA results revealed substantial data variation. To adequately capture this diversity, three principal components were selected for further analysis and interpretation based on their contribution to overall data variance:

• PC1 (42.5%)
• PC2 (20.4%)
• PC3 (18.9%)

Together, these components account for approximately 82% of the total variance (see Figure 3 and

Table 3. Eigenvalues.

Parameter	PC1	PC2	PC3	PC4	PC5
Eigenvalue	2.1269	1.0198	0.9386	0.7216	0.1932
% of Variance	42.538	20.396	18.771	14.431	3.8634
Cumulative (%)	42.538	62.934	81.705	96.137	100

).

This high variance coverage demonstrates that PCA effectively identifies the most critical underlying factors, reinforcing its robustness as an analytical tool for assessing competitive dynamics among tourism destinations.

The visualization of this diversity implies a 3D graphical expression (see Figure 4,

Table 4. Eigenvectors.

		Vector2	Vector3	Vector4	Vector5
Enabling Environment	0.5217	−0.3757	−0.4386	0.1972	0.5962
T&T Policies and Enabling Conditions	−0.1618	0.7367	−0.6203	0.198	0.084
Infrastructure	0.5984	−0.002	−0.3309	−0.2493	−0.6858
T&T Resources	0.4255	0.5	0.3649	−0.5341	0.3879
T&T Sustainability	0.4032	0.257	0.4245	0.7579	−0.1293

and

Table 5. The covariance matrix.

Group\Group	Enabling Environment	T&T Policies and Enabling Conditions	Infrastructure	T&T Resources	T&T Sustainability
Enabling Environment	1	−0.1686	0.6865	0.099	0.2671
T&T Policies and Enabling Conditions	−0.1686	1	−0.06151	−0.0532	−0.0866
Infrastructure	0.6865	−0.06151	1	0.4719	0.2616
T&T Resources	0.099	−0.0532	0.4719	1	0.3395
T&T Sustainability	0.2671	−0.0866	0.2616	0.3395	1

).

Step 3. Identifying the features of the studied competitive environment

The principal components identified, along with the corresponding competitive variables and scores of tourist destinations, demonstrate both the general and specific features of the competitive environment studied, as well as Georgia’s competitive position within it.

PC1 (42.54% variance) emphasizes the significance of “Infrastructure” (0.60) and “Enabling Environment” (0.52), followed by “T&T Resources” (0.43) and “T&T Sustainability” (0.40). Leading destinations in these categories, with their different contributions in different variables, include the US, the UK, Spain, France, Japan, Canada, and Denmark (scores range between 2.0–3.5; refer to see table in Appendix B).

Georgia holds a moderate position in this principal component, with a slightly negative score of −0.47, ranking 35th among all destinations. This is due to a negative score in “Infrastructure” (−0.38), partly balanced by a positive score in the “Enabling Environment” (0.37). A similar balance is seen in relation to the other variables in this vector; Georgia has a negative score in “T&T Resources” (−0.87) and a positive score in “Sustainability” (0.23) (refer to see Appendix B, Score Tables).

Georgia’s primary competitors in PC1 are Slovenia, the Czech Republic, and Hungary, while Kazakhstan and Mexico closely follow. However, when considering this relationship across the most influential variables in PC1 individually, more competing destinations emerge. For instance, in terms of the “Infrastructure” variable, Georgia competes with Slovenia, China, Estonia, Hungary, Romania, Egypt, Malaysia, the Dominican Republic, Lithuania, and Thailand (with scores ranging from between 0.00 and −0.37) (refer to Appendix B, Score Table). (Note: The two variables mentioned in PC1—T&T Resources (0.43) and T&T Sustainability (0.40)—will be further analyzed in the following PC3, where they play a leading role.)

PC2 (20.40% variance) increases the combined coverage of all variations up to 62.95% (see Table 3 above). This component focuses on “T&T Policies and Enabling Conditions”, which shows the highest score in the list of all other variables (the score is 0.74). The top countries in this vector are Indonesia, India, Türkiye, and Mexico (with scores between 1.54 and 2.44). Additionally, the variable driving this principal component—“T&T Policies and Enabling Conditions”—is significantly influenced by Türkiye, Malaysia, and the UAE (scores above 1.5) (see Appendix B).

Georgia possesses a similarly moderate position in the PC2 component, although it holds a relatively high rank (29th) among all destinations. The score achieved (0.22) is its only positive one across all three principal components (see Appendix B). This position reflects its relative strength in the tourism policy indicator while leaving room for further improvement.

According to the applied calculation, Georgia’s closest competitors in PC2 are Lebanon, Azerbaijan, and Kazakhstan (scores between 0.21 and 0.24). In the position along the PC2 driving variable, that is, “T&T Policies and Enabling Conditions,” Georgia holds a more advanced position, ranked 12th in the whole considered market. In this dimension, the closest competitors are Hungary, Albania, and Poland (with scores between 0.98 and 1.07).

PC3 (variance 18.77%) accrues the combined coverage of all variance up to 81.70%, emphasizing the role of “T&T Sustainability” (0.42) and “T&T Resources” (0.37). The leading destinations in this line are the US and Indonesia (whose scores vary between 2.54 and 2.33, respectively) (see Score Table, Appendix B).

In this component, Georgia holds a relatively low position (score −0.86) and is ranked 50th among all destinations. Similar to the PC1 case, controversial scores appear in the driving variables of PC3. In part, Georgia shows a negative score in “T&T Resources” (−0.87) and a positive one in “Sustainability” (0.23) (see page Countries vs. PC—Score table, Georgia).

Georgia’s lower rank and negative positioning in this component underline areas where the country could enhance its resource base and sustainability efforts. The interpretation of this position is relevant as it identifies areas for strategic improvement. The closest competitors of Georgia in this principal component are Lebanon, Azerbaijan, and Russia (with a score of 0.31 per the latest 2019 data), as well as Greece with an equal score and Mexico (with scores between 0.20 and 0.47) (see Appendix B).

5. Discussion and Conclusions

The initial stage of the study identifies the competitive environment consisting of 61 tourist destinations popular among Georgia’s 23 leading tourist segments. It reveals that this environment differs from the competitive landscapes created by popular tourist destinations globally. These findings justify the subsequent steps of country-oriented studies.

In the next phase, to compare a meaningful number of destination countries across five tourism competitiveness dimensions, the principal component analysis (PCA) methodology was selected as the most appropriate tool, allowing the reduction of dimensionality into principal components while retaining most of the original information.

The obtained results and the compiled interpretations are summarized in Figure 5 (see Figure 5,

Table 6. Competitive position of Georgia within its SGE-TD.

PC	Contributing (Influencing) Variables	Leading Destinations	Closest Competitors of Georgia per PC-s	Georgia’s Scores
				In PC	In Variables
PC1 (42.54%)	Infrastructure (0.6)	USA (3.43), UK (2.56), ESP (2.34), FRA (2.25), JPN (2.17), CAN (2.09), DNK (2.08)	HUN (−0.24),CZE (−0.27), SVN (−0.44),KAZ (−0.52), MEX (0.53)	−0.47	−0.38
	Enabling Environment (0.52)				0.37
	T&T Resources (0.43)				−8.87
	T&T Sustainability (0.40).				0.23
PC2 (20.40%)	T&T Policies and Enabling Conditions	IDN (2.44), IND (2.03), TUR (1.91), MEX (1.54)	TUR (1.62), MYS (1.57), ARE (1.50)	0.22	0.22
PC3 (8.77%)	T&T Sustainability (0.42)	USA (2.54), IDN (2.33)	LBN (0.47), AZE (0.38), RUS (0.31), GRC (0.23), MEX (0.20)	−0.86	0.23
	T&T Resources (0.37)				−0.87

). It displays the close competitors of the study tourist destination—in this case, Georgia—across each analyzed competitive variable, which in turn is allocated per identified main principal component of the studied SGE-TD of Georgia.

According to the revealed principal components, Georgia possesses a moderate position in its SGC-TD according to PC1 and PC2 and a relatively low follower position according to PC3 (See Figure 5, Table 6). The positive score in PC2 near zero (0.22) suggests that Georgia’s “Tourism Policies” and “Enabling Conditions” are comparable to the average of other tourism destinations; however, it leaves room for improvement. The negative scores in PC1 and especially in PC3 emphasize the importance of advancing Georgia’s position, and especially of raising the acknowledgment of the country’s rich and diversified T&T Resources, as well as of strengthening infrastructure to improve competitiveness. These recommendations align with the PCA results.

Georgia, within its competitive tourism environment, appears to be in tight competition with different destinations, depending on the competitive dimensions. In relation to “Infrastructure” and “Enabling Environment”, competing destinations are Kazakhstan and Mexico, while with regard to “T&T Policies and Enabling Conditions” the competitive destinations are Türkiye, Malaysia, and the United Arab Emirates. The largest number of closest competing destinations appears in terms of “T&T Sustainability” as well as “T&T Resources” (see Table 6). In this study, we selected the ranking positions of destinations that are located in close proximity to Georgia. In particular, we selected those that are three positions above and two positions below Georgia, giving priority to the number of advanced destinations and to the country’s promotion in its competitive environment.

Regarding the specific competitive dimensions, the most important variables in the studied competitive environment include “Infrastructure”, “Enabling Environment”, “T&T Resources”, and “T&T Sustainability” (PC1, 42.54%). The best practices in these areas, which merit prior consideration and sharing, are found in the USA, UK, Spain, and France (scoring above 2.25, Table 6). “T&T Policies and Enabling Conditions” represents the next key component (PC2, 20.40%), with Türkiye, as Georgia’s neighboring country, deserving priority consideration. The third principal component (PC3, variance 18.77%) accounts for the combined coverage of all variance up to 81.70%, emphasizing the role of “T&T Sustainability” (0.42) and “T&T Resources” (0.37).

In general, the key indicators for advancing the competitive position of Georgia as a tourist destination are “Infrastructure” (PC1, score 0.38) and “T&T Resources” (PC1 and PC3, score 0.87). In comparison to its close competitors, Georgia holds positive positions in “Enabling Environment” (PC1, score—0.37), “T&T Sustainability” (PC1, score—0.23), “T&T Policies and Enabling Conditions” (PC2, score—0.97), and “T&T Sustainability” (PC3, score—0.23).

The revealed outcomes suggest options for strategies to advance the position in the county’s competitive tourism environment, which, however, can be prioritized based on the country’s general strategy for economic development and its priorities. The suggestion that these insights can contribute to Georgia’s broader economic development strategy also adds value, making the analysis more impactful. The identified competitive positions also provide a foundation for a comprehensive range of further in-depth comparative analyses for each indicator across the destinations within the identified and considered competitive environment.

The generalized methodological outcomes of the provided research imply the logic of sequential research stages, a set of conceptual approaches, and optional tools corresponding to each stage (see

Table 7. The generalized research structure.

Research Design	Research Methods
Initial step: selecting the conceptual framework relevant to the study destination	Segment-centric geo-competitive environment of a study tourism destination (SGE-TD)
Step 1: identifying competing tourism destinations for the destination under study	1.1 Selecting the leading tourism-generating countries in the study destination
	1.2 Determining the preferred tourism destinations in the selected tourism-generating countries
Step 2: analyzing the identified competing tourism destinations composing the competitive environment for the study destination	2.1 Determining relevant competitive indicators for the study
	2.2. Analyzing the competitive environment composed of the identified competing tourism destinations
Step 3: identifying the features of the studied competitive environment	Identifying the principal components of the competitive environment and competitive position of the destination under study

).

In terms of theoretical implications, this article proposes and tests the SGE-TD approach, which suggests defining competitive destinations by identifying the most preferred travel countries among the segments that are leaders in a particular tourism destination being studied. The novelty and validity of this approach lie in its high degree of cogency and accuracy in defining competing destinations and the relevant competitive environment (see Figure 5 and Table 6).

The suggested methodology and the developed research design can be applied to other tourism destinations and their geo-competitive environments. These opportunities are provided by data systematically published by international organizations on competitiveness and tourism development indices [4], data on preferred outbound destinations from tourism-generating countries [6,8,64], and data on foreign tourist arrivals (segments) published by the relevant national tourism organizations. In addition, the same research design can include more detailed variables on a competitive tourism environment, depending on the research objectives and data availability, considering that the WEF reports on 5 TTDI dimensions, include 17 pillars with 102 individual indicators for 119 countries. This design holds methodological value in its applicability to other destinations and practical implications by determining the competitive position of the studied destination through relevant key dimensions and indicators.

The limitations and potential for further research using the suggested methodology include several considerations. First, the methodology considers the present status of competitive indicators without the expected and/or predicted changes in the future. Second, the empirical study relates only to Georgia’s tourism destinations, whereas similar studies regarding other competing destinations reveal additional valuable outcomes for relative analysis. Third, the proposed SGE-TD approach can be applied not only to countries but also to other territorial units of tourism destinations and to other segments, given the availability of appropriate data and with appropriate adjustments to the analytical methods.