Tourism-Led Infrastructure Development: Towards a Theoretical Framework Through Grounded Theory Synthesis

Highlights

What is the gap in our research?

• This study addresses an important but little studied dimension of the tourism-growth nexus and the often forgotten dimension of the circulating relationship between tourism and infrastructure development. In fact, little research has examined how tourism dynamics act as a catalyst for broader infrastructure development. Our research fills this theoretical gap by examining the thesis of infrastructure development through tourism (TLID).

What is the originality of our methodological approach?

• Using a double methodological approach focused on bibliometric analysis of recent research and theoretical synthesis inspired by grounded theory, this study ends with the development and presentation of a new theoretical model, called TLID model.

What’s the scope of our research contributions?

• Bidirectionality: We confirm and characterize the bidirectional relationship between tourism and infrastructure, going beyond traditional one-way models.
• Explanatory mechanisms: We identify the main drivers of this relationship, in particular economic incentives, territorial competitiveness strategies and public governance dynamics.
• Integrative framework: We propose a new conceptual framework for the TLID that explains how tourism growth stimulates infrastructure investment beyond strictly tourism-related facilities.

Abstract

In the context of the United Nations 2030 Agenda for Sustainable Development and current regional development strategies, tourism is increasingly viewed as a potential driver of economic and infrastructural transformation across regions. While the literature has largely focused on the influence of infrastructure on tourism growth, the reverse relationship—in which tourism may stimulate infrastructure development—remains insufficiently conceptualized. This article therefore examines the tourism–infrastructure development (TLID) thesis through two research questions: (1) To what extent can tourism growth contribute to the development of regional infrastructure beyond strictly tourism-related infrastructure? (2) What theoretical mechanisms explain the relationship between tourism dynamics and infrastructure investment? The study employs a bibliometric analysis of the recent literature, combined with a theoretical synthesis inspired by Grounded Theory, to identify emerging conceptual relationships in recent scientific contributions. The results highlight three main contributions. First, they confirm the bidirectional nature of the relationship between tourism and infrastructure. Second, the analysis identifies several key explanatory mechanisms, notably economic incentives, territorial competitiveness strategies, and public governance dynamics. Third, the study proposes an integrative conceptual framework for tourism-led infrastructure development. These findings enrich the literature on tourism and territorial development and have useful implications for the design of public policies related to infrastructure investment.

1. Introduction

Since the adoption of the 2030 Agenda for Sustainable Development, infrastructure has evolved from a mere technical support for economic activity to a central component of a comprehensive development strategy linking productivity, inclusion, resilience, sustainability, and territorial transformation. Goal 9 calls for infrastructure that is “good quality, reliable, sustainable, and resilient,” and Goal 11 emphasizes the importance of inclusive, safe, and sustainable cities and territories. Targets 8.9 and 12.b explicitly recognize sustainable tourism as a means of creating jobs, promoting local cultures, and monitoring development impacts. In essence, the 2030 Agenda does not relegate tourism to a peripheral position within the broader framework of structural dynamics. Instead, it situates tourism within a network of interdependencies, where mobility, urban services, innovation, investment, and governance collectively influence the sustainability trajectory of destinations (De & Ambitieux, 2015).

The development of tourism, and thus its contribution to achieving the Sustainable Development Goals, must be supported by adequate investments in infrastructure, technology, and human resources (Berčák et al., 2024; Hall, 2019; Berbeka et al., 2024). Consequently, the sector has the capacity to exert influence on infrastructure development, particularly in the domains of transportation, urban accessibility, essential services, and the low-carbon transition (Tomaselli & Giammanco, 2026; Khadaroo & Seetanah, 2008; Wendt et al., 2021). The dual role of infrastructure, both a prerequisite for tourism and an object of transformation driven by tourism, constitutes the starting point for the present discussion (Dwyer & Kim, 2003; Ritchie & Crouch, 2003; Prideaux, 2000).

In the academic literature, the most common approach is based on a relatively well-established causal relationship: “Development of tourism based on infrastructure” looks at how infrastructure affects tourism and other aspects of a destination. This includes things like how easy it is to get to, the quality of transportation, how many places there are to stay, and the quality of city services. It also looks at how these things affect the destination’s popularity, how much it costs to get there, and how competitive it is compared to other places (Dwyer & Kim, 2003; Prideaux, 2000; Ritchie & Crouch, 2003).

However, in accordance with the tourism-led growth hypothesis (TLGH), which posits that tourism can serve as a catalyst for long-term growth through foreign revenue, employment, investment, and cross-sectoral spillover effects, the impact of tourism development on infrastructure investment is gradually emerging as a significant causal factor (Balaguer & Cantavella-Jordá, 2002; Brida et al., 2016; Lin et al., 2019; C. F. Tang & Tan, 2018; Zuo & Huang, 2018). The emergence of the tourism-led infrastructure development (TLID) hypothesis continues to shift the focus of research in this field toward a more dynamic and circular relationship, positioning tourism not only as a beneficiary of existing infrastructure but also as a catalytic sector for structural transformation that drives infrastructure development (Telfer & Sharpley, 2015). The generation of flows, revenue, capacity needs, and quality expectations by tourism can contribute, either directly or indirectly, to the reconfiguration of public and private trade-offs regarding transportation networks, urban services, digital connectivity, recreational facilities, safety, accessibility, and public amenities. Recent approaches to smart destinations substantiate this logic, indicating that contemporary tourism competitiveness is contingent on digital infrastructure, information systems, real-time connectivity, and coordination ecosystems among public and private actors and users (Buhalis & Amaranggana, 2014).

A growing body of research is increasingly focusing on the relationship between tourism and infrastructure, particularly in terms of innovation, sustainability, and structural development. This focus is evidenced by a range of research methods, including systematic reviews, bibliometric mapping, and thematic syntheses. The integration of these methods signifies the field’s entry into a phase of maturity. However, the fragmented nature of the extant literature on this topic, comprising studies in loosely connected subfields (transportation, urban services, digital infrastructure, tourism facilities, accessibility, competitiveness, territorial regeneration, etc.), prevents the development of a comprehensive theory of tourism-driven infrastructure development and calls for methods of consolidation, classification, and generalization (Khadaroo & Seetanah, 2008; Dwyer & Kim, 2003; Brida et al., 2016). The second research gap is attributable to the limited integration between quantitative bibliometrics and qualitative theoretical construction. The former has a tendency to prioritize mapping research over explaining it, particularly with regard to the causal relationships between tourism’s effects and infrastructure development (Donthu et al., 2021; Zupic & Čater, 2015). Moreover, at present, there is no adequate conceptual model that brings together the mechanisms of tourism-induced infrastructure development while incorporating the mediating and contextual factors that shape this relationship. This phenomenon can be attributed to an absence of integration of causal mechanisms (Brida et al., 2016; Hall, 2019). Grounded Theory was selected because it enables the inductive generation of theoretical explanations from heterogeneous and fragmented bodies of knowledge. In the context of TLID research, this approach is particularly suitable for identifying latent relationships, integrating dispersed findings, and developing a coherent conceptual framework where established theory remains limited (Corbin & Strauss, 1990; B. Glaser & Strauss, 2017). This will enable the inductive generation of a theory from the bibliographic material itself. This shift in focus will enable a transition from a mere review of existing inventory to a more theoretical inquiry, a domain that remains underdeveloped within the field of TLID (Matteucci & Gnoth, 2017; Wolfswinkel et al., 2013).

In principle, the impact of tourism development on infrastructure development is predicated on a logic of functional interdependence. On the one hand, an increase in tourist flows has been observed as accessibility, connectivity, service quality, and the overall visitor experience have been enhanced. Conversely, the intensification of these flows gives rise to heightened demands with regard to capacity, reliability, efficiency, and regional coordination. Consequently, the mobilization of tourist flows has been demonstrated to stimulate various aspects of tourism development, including transportation infrastructure, digital infrastructure, tourism facilities, and connectivity systems. This, in turn, has been shown to enhance the performance of the tourism sector (Chan et al., 2022; Khadaroo & Seetanah, 2008; Prideaux, 2000).

Empirically, this relationship remains significantly influenced by various structural dimensions, including the tourism infrastructure itself, the relationship between tourism and economic performance, saturation effects and nonlinear dynamics, institutional and governance conditions, and spatial and contextual heterogeneity (Alonso-Muñoz et al., 2023; Butler, 2025; Fan & Ha, 2025).

Within this theoretical framework, tourism does not inherently lead to the development of infrastructure; rather, it is facilitated by several mediating factors, particularly economic growth, job creation, regional development, and public and private investment. These factors can act as intermediaries for resources, incentives, and institutional mechanisms that not only enable investment but also make it politically viable (Alcalá-Ordóñez et al., 2024; Amaghionyeodiwe, 2012; Tai et al., 2022). The presence of moderating effects, such as governance and institutional conditions, saturation and sustainability constraints, and contextual factors, lends further credence to the notion of contingency in the relationship. These moderating effects serve to illustrate how comparable tourism volumes can give rise to divergent infrastructure trajectories depending on the context (Cheung & Li, 2019; Hall, 2019; Zuo & Huang, 2018).

By reframing the relationship between tourism and infrastructure within a framework of bidirectionality, sustainability, potential saturation, reversibility, and territorial differentiation, while emphasizing the structuring role of governance mechanisms and spatial contingencies in the production of heterogeneous infrastructural effects, the proposed TLID Framework represents a substantial advance over existing models. The study’s contributions lie in its ability to transcend the limitations of extant theories and models in this field. It does so by (1) moving beyond the tourism-led growth (TLEG) hypothesis, which focuses on the tourism–growth relationship (Balaguer & Cantavella-Jordá, 2002); (2) the destination competitiveness model, which primarily views infrastructure as a determinant of attractiveness (Dwyer & Kim, 2003); and (3) the tourism destination life cycle model, which focuses more on the evolutionary trajectories of tourism areas (Butler, 2025).

The central research question of this study is as follows. While infrastructure development is influenced by a range of economic, institutional, demographic, and policy-related factors, it is imperative to elucidate the mechanisms, conditions, and spatial and institutional configurations through which tourism functions as a catalyst for infrastructure development.

The objective of this research is to transcend the simplistic dichotomy between the prevailing perspective that infrastructure propels tourism and the burgeoning view that tourism can catalyze infrastructure investment. The overarching ambition is to construct an explanatory framework that can facilitate the development of a TLID analytical model through a causal, mediated, and conditional process.

The study has four goals:

• To map the intellectual structure of TLID research;
• To identify the main thematic categories and bibliometric trajectories within the field;
• To develop, based on the literature, a well-founded explanation of the mechanisms linking tourism and infrastructure investment;
• To propose an integrative conceptual framework capable of explaining the roles that shape this relationship.

To this end, the article addresses the following questions:

(RQ1)

What are the main ideas in the tourism and infrastructure literature?

(RQ2)

How has this literature changed, both in terms of its impact and its ideas?

(RQ3)

What are the reasons for the development of new infrastructure due to tourism?

(RQ4)

To what extent can we apply these mechanisms to different stages of destination development?

In order to address these inquiries, the present study elected to place its primary reliance on the principles of Grounded Theory, while concurrently acknowledging the value of bibliometric analysis and systematic literature reviews (Zupic & Čater, 2015; Donthu et al., 2021; Wolfswinkel et al., 2013). Given the breadth, interdisciplinarity, and fragmentation of the field of analysis, a systematic literature review is essential to provide a suitable basis for the analysis and model building described in this study. This process involves defining explicit selection criteria, reducing review bias, and ensuring the traceability of the corpus. The objective of the bibliometric analysis is to provide an objective reading of the intellectual structure of the field, its centers of influence, and its trajectories of evolution. However, in accordance with the theoretical framework of this article, this mapping is not an end in itself; rather, it serves as a foundation for a Grounded Theory synthesis. The application of this synthesis aims to identify the causal categories, processual relationships, and conditional configurations that structure TLID from the corpus.

This integration of a systematic literature review, bibliometrics, and Grounded Theory aims to consolidate a fragmented research field, to produce a medium-range theory better suited to explaining causal mechanisms than simple bibliometric maps, and to inform future empirical research on the relationships between tourist flows, governance, investment, and the infrastructural transformation of destinations (Matteucci & Gnoth, 2017; Deering & Williams, 2025).

As an intermediate explanatory framework situated between universal generalization and empirical description, medium-range theory endeavors to identify causal mechanisms that are transferable within defined contexts. The relevance of this concept to our analysis stems from its ability to link tourism flows, governance, investment, and infrastructure transformations without claiming abstract universality, while guiding future comparative empirical validation.

Subsequent to this introduction, the structure of this article will include the methodological protocol for data collection and analysis and the results of the bibliometric and Grounded Theory analysis, followed by a discussion of the results and implications and, finally, the contributions, limitations, and research prospects in the conclusion.

2. Materials and Methods

2.1. Research Design

Due to the complexity and evolving nature of the research field, this study adopts a hybrid sequential design, combining quantitative bibliometric analysis with qualitative Grounded Theory analysis. More specifically, the study follows the BIBGT (Bibliometrics and Grounded Theory) approach proposed by Walsh and Rowe (2023), which combines bibliometric techniques with the analytical principles of Classical Grounded Theory to conduct systematic, transparent, and theory-building literature reviews based on secondary data. First, it allows for the identification of the thematic and structural configuration of the literature on tourism-driven infrastructure development. Then, the principles of Grounded Theory, such as theoretical sampling, constant comparison, and iterative coding, are applied to the selected corpus in order to inductively develop an emerging conceptual framework based on the conceptual and empirical data contained in the literature (Walsh & Rowe, 2023). Rather than generating theory from primary field data, as in Classical Grounded Theory, this adaptation applies the same inductive logic to the published scientific literature in order to explain an under-theorized phenomenon. This dual approach serves to bridge the gap between bibliometric mapping at the macro level and more in-depth interpretive work. Unlike a conventional systematic qualitative literature review, which primarily synthesizes existing knowledge, this approach seeks to generate higher-order conceptual categories and explanatory relationships through an iterative coding process, ultimately leading to the development of a novel theoretical framework. Nevertheless, this methodological adaptation is limited by its reliance on secondary data, which constrains theoretical sampling and empirical contextualization compared with Classical Grounded Theory based on primary field data. Consequently, the resulting framework should be regarded as theoretically grounded rather than empirically validated. The research is organized into two complementary phases, combining the “macro: thematic maps” perspective with the “micro: in-depth content analysis” perspective (Figure 1).

The bibliometric phase employs metadata to identify theoretical pillars and delineate thematic clusters, thereby providing a compass that guides the qualitative phase. In this phase, the findings of the articles are compared and critiqued to identify the underlying mechanisms, relationships, and processes that explain how tourism acts as a catalyst for the development of infrastructure (Corbin & Strauss, 1990; B. Glaser & Strauss, 2017). From this perspective, bibliometric analysis is not an end in itself but rather a foundation that guides and justifies the qualitative analysis.

Consequently, particular attention was paid to the quality of the study corpus. In accordance with this objective, the PRISMA guidelines were adhered to during the data collection process, particularly with regard to the identification, screening, and inclusion of articles that constituted the study corpus (Page et al., 2021) (Figure 2). In addition, to enhance the transparency and methodological traceability of the research, the study protocol was pre-registered on the OSF (Open Science Framework) platform in the “OSF Preregistration” format.

2.2. Data Collection and Search Strategy

The data collection process employs a systematic and rigorous strategy to ensure the comprehensiveness and reliability of the corpus under study. A search of two databases, Scopus and Web of Science, was conducted, as they are well-regarded for their comprehensive coverage of high-quality, peer-reviewed publications in the field of tourism and related disciplines (Clarivate, 2025; Elsevier, 2025). The following search equation was developed by combining the main keywords to identify studies focused on the relationship between tourism and infrastructure development:

(“tourism development” OR “tourism growth” OR “tourism-led growth” OR “tourism expansion” OR “sustainable tourism” OR “destination development” OR “tourist destination” OR “tourism-induced” OR “tourism-driven”) AND (“infrastructure development” OR “infrastructure investment” OR “transport infrastructure” OR “tourism infrastructure” OR “infrastructure quality” OR “public infrastructure”).

To ensure the timeliness and quality of the included studies, several automatic filters were applied, including publication type (journal articles only), language (English), publication period (2021–2025), and access to full text. This time frame facilitates a more nuanced comprehension of post-pandemic restructuring, digital acceleration, sustainability requirements, and recent investments, thereby constituting a current and relevant corpus for analyzing the TLID thesis.

The preliminary search yielded a total of 1130 documents, with 732 found on Scopus and 398 on Web of Science. Following the implementation of automatic filters, a total of 259 subjects were retained for further analysis. Following a thorough review, 79 duplicates were eliminated, resulting in a final corpus of 180 articles that served as the foundation for the subsequent bibliometric analysis. A subset of 41 articles was then selected for qualitative analysis following a rigorous selection process.

2.3. Screening Process and Study Selection

Two authors independently reviewed the 180 articles using the Rayyan platform (Ouzzani et al., 2016) based on predefined inclusion and exclusion criteria (

Table 1. Screening process.

Inclusion Criteria	Exclusion Criteria
Studies explicitly addressing the relationship between tourism and infrastructure development Articles examining tourism as a driver (or catalyst) of infrastructure investment or development Studies focusing on infrastructure in a tourism context Peer-reviewed journal articles published in English	Studies focusing exclusively on transport engineering or infrastructure without any tourism context Articles addressing tourism without any link to infrastructure development Conference papers, book chapters, editorials, and non-peer-reviewed publications Studies lacking sufficient theoretical or empirical content Articles not written in English Duplicates or incomplete records

Source: authors.

). This step involved a thorough review of the title, abstract, and keywords to determine the relevance of the article (for inclusion) or its irrelevance (for exclusion). After eliminating 130 articles deemed irrelevant by both authors and nine articles where there was disagreement, 42 articles were included, resulting in an observed agreement rate of 95%. The inter-rater reliability was assessed using Cohen’s kappa coefficient, which measures consensus beyond chance. The index indicates near-perfect agreement (k = 0.87), as defined by the scale proposed by Landis and Koch (1977). This outcome validates the efficacy and reliability of the selection process, as outlined in the supplementary Cohen’s kappa report (see Supplementary Material S1).

This rigorous process ensures that the final corpus is relevant and methodologically sound for bibliometric and qualitative analysis.

2.4. Data Analysis

A bibliometric analysis was conducted to examine the intellectual, conceptual, and structural evolution of the research field. This phase utilizes a combination of quantitative mapping techniques, incorporating co-occurrence analysis and thematic clustering, to identify dominant themes, cluster structures, and trends in the literature. The analysis was conducted using the R package Bibliometrix (version 4.4.1) to generate an overview of the studied corpus. VOSviewer (version 1.6.20) was then used to visualize the network (Aria & Cuccurullo, 2017; Van Eck & Waltman, 2010).

In order to gain an in-depth understanding of the mechanisms rooted in the literature that underpin tourism-led development, 42 articles were selected from the initial corpus of the bibliometric analysis through a meticulous systematic process. The present approach is guided by the results of the bibliometric analysis, and it employs an iterative coding process (open coding, axial coding, and selective coding) to inductively generate a theory grounded in the literature using NVivo 12 (Corbin & Strauss, 1990; B. Glaser & Strauss, 2017) (see Supplementary Material S1 for details of the coding). The operationalization of Grounded Theory followed the principles of constant comparison and theoretical abstraction. Throughout the coding process, concepts, categories, and relationships emerging from each article were continuously compared with those identified in previously analyzed studies. This iterative procedure enabled the progressive refinement of categories and the inductive construction of higher-order conceptual relationships.

During the open coding phase, key concepts and recurring patterns were identified across the selected studies. The process entailed the disaggregation of the data into meaningful units and the allocation of initial codes that reflected pertinent aspects of the relationship between tourism and infrastructure (B. G. Glaser, 2016). These codes were then organized into categories based on the identification of relationships between concepts. This transcends a rudimentary delineation, attaining a conceptual evaluation that facilitates the organization of data into coherent dimensions (Vollstedt & Rezat, 2019).

The final step in the methodological framework is selective coding, through which the categories identified during the preceding phases are systematically integrated around a central and overarching phenomenon (Corbin & Strauss, 1990). This integration process led to the emergence of an original conceptual model that theorizes tourism as a catalyst for infrastructure development. This conceptualization provides a novel theoretical framework that facilitates a more comprehensive understanding and analysis of the multidimensional nature of infrastructure development driven by tourism.

The coding process employs an iterative approach, whereby categories and relationships are continuously refined based on the extant literature. Saturation was achieved when no further theoretical insights were identified for a given category, signifying that the analysis had attained an adequate degree of in-depth and comprehensive scrutiny (B. Glaser & Strauss, 2017). Theoretical saturation was assessed through continuous monitoring of category development and was considered reached when successive coding iterations failed to generate new conceptual elements or modify existing relationships. Furthermore, the analysis followed an open, axial, and selective sequential coding approach; inter-coder reliability was ensured through independent coding and consensus-based reconciliation; and theoretical saturation was deemed to have been reached when successive iterations yielded no new categories, properties, or relationships, indicating conceptual stability and analytical exhaustiveness.

3. Results

3.1. Bibliometric Findings

3.1.1. Overview

Table 2. Key information.

Description	Results
Main Information About Data
Time Span	2021–2025
Sources (Journals, Books, Etc.)	114
Documents	180
Annual Growth Rate %	64.73
Average Document Age	2.01
Average Citations Per Document	6.406
Document Contents
Keywords Plus (Id)	444
Author’s Keywords (De)	801
Authors
Authors	695
Authors of Single-Authored Documents	19
Author Collaboration
Single-Authored Docs	21
Co-Authors Per Doc	3.99
International Co-Authorships %	13.33
Document Types
Article	180

Source: bibliometrix.

presents a description of the bibliometric characteristics of the studied corpus, offering a general overview of the structure and evolution of the research field. The bibliometric corpus comprises 180 articles published by 114 sources, produced by 695 authors, and covering the period from 2021 to 2025, reflecting a broad and diverse theoretical foundation.

The mean growth rate of scientific output is estimated at nearly 65%, indicating a mounting academic interest within the scientific community regarding infrastructure development driven by tourism. The mean age of the documents, 2 years, is indicative of the nature of the studies included in the analysis. The mean number of citations per document (6.406) indicates a moderate impact, attributable to the recent nature of the corpus studied. The co-occurrence of these two indicators suggests that the research field is undergoing active development. It is an area that is experiencing notable expansion and attracting growing interest from researchers. However, it is still in the process of consolidating its theoretical and empirical foundations. The substantial conceptual diversity, as evidenced by the 801 author keywords and 444 Keywords Plus, mirrors the interdisciplinary character of this field, which establishes a nexus between tourism studies, infrastructure planning, and sustainable development research. The low proportion of documents authored by a single author (21 articles) and the average number of authors per document (3.99) reflect the collaborative trend in scientific production in this field, particularly concentrated in the same countries (13.33% international co-authorship). Figure 3 provides a complementary illustration of the life cycle of scientific production in this research field.

The logistic growth model, a widely used approach for describing the life cycle of scientific fields through an S-shaped growth trajectory characterized by emergence, expansion, maturity, and saturation, applied to the publication data, indicates that the field is currently experiencing rapid expansion. The model suggests a possible peak around 2027 and an estimated saturation level of approximately 764 publications; however, these values should be viewed with caution as indicative projections rather than definitive predictions, as future publication patterns may evolve in response to changing scientific and institutional conditions (Tjørve & Tjørve, 2010). The quality of the model fit (R² = 0.992) attests to the statistical credibility of this growth trajectory. This outcome validates the hypothesis that the field is progressing in a manner that is both highly consistent and predictable. This observation is indicative of the dynamism inherent in contemporary scientific endeavors and suggests a likely stabilization of the extant literature in forthcoming years.

The results of the outlook analysis indicate that this field of research is expected to continue on a significant growth trajectory in the coming years. This phenomenon underscores its significance within the broader discourse on tourism and economic development. This expansion should not be regarded exclusively as a bibliometric outcome; rather, it reflects the progressively acknowledged necessity for theoretical refinement, wherein infrastructure is regarded as a structural determinant of tourism-driven growth. Consequently, as the academic community’s interest in examining the interplay between tourism, infrastructure, and development continues to flourish, this domain emerges as a promising terrain for the cultivation of an emerging, well-defined and theoretically sophisticated field of research.

3.1.2. Leading Journals and Authors

Table 3. Sources’ local impact.

Source	h_Index	g_Index	m_Index	TC	NP	PY_Start
Sustainability	6	10	1	115	21	2021
International Journal of Sustainable Development and Planning	5	6	1	38	6	2022
Geojournal of Tourism and Geosites	3	4	0.75	22	13	2023
Island Studies Journal	3	3	0.75	17	3	2023
Ecological Indicators	2	3	0.5	54	3	2023
Economies	2	3	0.333	107	3	2021
Heliyon	2	2	0.5	9	2	2023
International Journal of Professional Business Review	2	2	0.4	11	2	2022
Journal of Infrastructure, Policy and Development	2	2	0.667	8	4	2024
Journal of Outdoor Recreation and Tourism-Research Planning and Management	2	2	0.5	6	2	2023

Source: bibliometrix.

and

Table 4. Authors’ local impact.

Author	h_Index	g_Index	m_Index	TC	NP	PY_Start
Dimitriou d	2	2	0.4	44	2	2022
Lin y	2	3	0.667	20	3	2024
Liu y	2	2	0.5	30	2	2023
Sergeyeva a	2	2	0.4	22	2	2022
Aachrine b	1	1	0.5	1	1	2025
Ababneh a	1	1	0.167	17	1	2021
Abaisi d	1	1	0.5	3	1	2025
Abbadie m	1	1	0.5	1	1	2025
Abdal	1	1	0.25	1	1	2023
Abdelmoaty m	1	1	0.25	14	1	2023

Source: bibliometrix.

offer a comprehensive overview of the top 10 most influential sources and authors in this field, providing a clear picture of the structure and dynamics of intellectual output in the research field of tourism-driven infrastructure development.

An analysis of publication sources reveals a relatively fragmented publishing landscape. The distribution of academic contributions across a wide range of journals reflects the multidisciplinary nature of the intersection between tourism and infrastructure development. Notwithstanding this dispersion, certain sources are particularly salient in this field. The term “Sustainability” occupies the preeminent position, boasting an h-index of 6 and a cumulative citation count of 115, accompanied by a substantial volume of publications. Among the other relevant journals, we can cite the International Journal of Sustainable Development and Planning, the Geojournal of Tourism and Geosites, and the Island Studies Journal, which also demonstrate significant impact based on their citation metrics and publication activity. The existence of journals such as Ecological Indicators, Economies, and the Journal of Infrastructure, Policy and Development further underscores the interdisciplinary nature of this field, which serves as a nexus between tourism studies, environmental research, and economic development. Despite this diversity, the h-index values, which demonstrate considerable similarity across sources, indicate that scientific output is distributed across several disciplines.

With regard to the authors, as illustrated in Table 4, there appears to be a lack of significant distinction between them. While the number of publications and impact factors do not clearly distinguish between contributors, the number of citations provides some insight. For instance, the article “DIMITRIOU D” has received 44 citations, along with those by other authors such as “LIN Y; LIU Y; SERGEYEVA A.”

However, it is important to understand that these results only show what happened during a relatively short period (2021–2025). This does not allow for an assessment of how many times something has been cited, so comparisons between sources or authors are not very reliable. The moderate impact factor values confirm this. This means that the field has not yet reached maturity. No journal or author has managed to become clearly dominant. Research shows that the development of tourism infrastructure is a growing field of study with many different academic disciplines. It is still in its early stages, but it is becoming more popular in academia.

3.2. Conceptual Structure of the Field

To examine the intellectual organization of our subject, we used two techniques: a co-occurrence network created by VOSviewer and thematic mapping produced by the Bibbliometrix package. These approaches show how research themes are connected and how they have developed in the field of tourism-driven infrastructure development.

A co-occurrence analysis was performed using the VOSviewer software, based on terms extracted from the titles and abstracts of the documents included in the study, with a minimum threshold of 10 occurrences as the filtering criterion. The application of this threshold enabled the establishment of a network that grouped the most relevant and frequent terms within the corpus. This facilitated the systematic identification of the main thematic groups that constitute the intellectual landscape of this field. As illustrated in Figure 4, the structure under consideration is characterized by its relative density and interconnectedness. The 103 selected items have been organized into six clusters, a methodological approach that reflects the multifaceted nature of the subject.

The red cluster revolves around terms such as “sustainable tourism,” “policymaker,” “economic growth,” “resident,” and “quality.” These terms reflect a focus on governance, as tourism development can be studied through political, economic, and social dimensions. The prominence accorded to terms related to satisfaction and the local community may reflect an increasing emphasis on a more inclusive vision of tourism. The relationship between sustainability and economic development confirms the former’s role as a catalyst for the latter. This prompts the consideration of whether sustainability is merely a tool for growth. Rather than demonstrating an ongoing structural conflict, the observed co-occurrence of these concepts suggests a conceptual tension between the pursuit of profitability and the necessity for systemic transformation.

The green cluster encompasses terms such as “region,” “tourist destination,” “infrastructure,” “resilience,” “accessibility,” and “local community.” The text captures the structural and regional perspective of tourism development, focusing on the role of infrastructure in the regional ecosystem. The advent of crisis and resilience themes, such as “pandemic,” may indicate an increasing research interest in tourism, wherein infrastructure is increasingly examined in relation to the socio-ecological domain. Nevertheless, this tendency is predominantly descriptive in nature. Despite the term’s ubiquity, resilience still lacks the conceptual consolidation necessary to constitute a robust and operational theoretical framework.

Words like “experience,” “perception,” “satisfaction,” and “demand” are all part of the blue cluster. This group focuses on what tourists think of a place and how they decide if it is worth visiting. The focus on experiential aspects suggests an increasing interest in how infrastructure and services affect the value tourists find in a place. Even though there seems to be a difference between this marketing vision and a political vision, the co-occurrence of these themes suggests that new requirements and tourists’ expectations are forcing a change in infrastructure needs. The tourist experience appears to occupy a more central position in the literature, suggesting that infrastructure is no longer seen as the final goal, but also as a means to create value for the tourist. This division of responsibility may hinder a truly integrated approach.

The group identified in purple includes terms such as “ecological environment,” “ecological security,” “construction,” and “China.” This cluster underscores the environmental dimension of tourism infrastructure, with a more specific focus on ecological risk management and land-use planning. The correlation between specific terminology and particular geographic regions underscores the profound grounding of this research in tangible realities. Despite the evident environmental concerns, these issues are addressed in a parallel manner rather than being integrated into broader sustainability frameworks. This observation suggests a compartmentalization that may limit the comprehensive scope of environmental studies in this sector.

The terms “community,” “participant,” “location,” “natural resource,” and “tourist attractions” (illuminated in light blue) exemplify the pivotal role of local communities and regional particularities in tourism development. The employment of qualitatively oriented terms, such as “interview,” indicates a predilection for contextual approaches and case studies. This approach can be regarded as a deliberate effort to rebalance the focus, as other clusters predominantly adopt a structural perspective, whereas this one proposes a bottom-up approach. However, the limited connectivity of this cluster suggests that community realities remain relatively underrepresented within the field’s primary analytical frameworks.

The term “yellow cluster” is employed to denote the set of methodological and editorial terms that include, but are not limited to, “article,” “author,” “basis,” and “prospect.” These terms are employed in the context of scientific production and publication. The concept of “region,” “tourist destination,” and “local community” indicates potential conceptual linkages with the other clusters.

A systematic analysis of the six clusters reveals their classification into three overarching themes: governance and sustainability; infrastructure and regional systems; and tourist experience and behavior. Concurrently, the persistence of loosely correlated thematic areas, particularly those related to community engagement and ecological vulnerabilities, suggests ongoing fragmentation within the field of study. This fragmentation may reflect the emerging nature and the rapid growth of scientific output between 2021 and 2025, a post-COVID-19 phase in which theoretical convergence appears to remain incomplete.

The thematic map in Figure 5 offers a complementary perspective by positioning themes according to their importance (centrality) and their development (density). The intersection of these two criteria enables the identification of motor themes, niche themes, emerging/declining themes, and basic themes.

The strategic placement of sustainable tourism within the driver themes quadrant suggests an increasing prominence of these concepts within the literature, indicating that they occupy fundamental positions in organizing pillars that organize the broader spectrum of research. These themes are both highly developed and central, suggesting their fundamental role in the structuring of this field of research. The concepts of destination image and tourism industry function as pivotal mediating themes, connecting numerous research axes. However, despite this cross-cutting function, these themes exhibit lower conceptual density relative to the predominance of sustainability paradigms.

Conversely, themes such as “digitalization, hotel facilities, and ecotourism potential” are situated in the quadrant with high density and low centrality (niche themes). Despite the apparent depth of its internal development, the theme’s connection to the broader thematic structure in the field is limited, suggesting specialized and isolated trajectories that have yet to achieve substantial integration into academic discourse.

The lower-left quadrant encompasses “remote sensing, GIS, and travel behavior.” This cluster with low density and centrality indicates, within the classical analytical framework of thematic mapping, either research tracks that are rapidly emerging (emerging themes) or those that are losing momentum (declining themes). The ambiguity inherent in this quadrant necessitates a meticulous contextual interpretation, given the recent nature of the corpus studied. From this perspective, the observed thematic configuration suggests that the hypothesis of decline appears less relevant than that of emergence, although this interpretation should be considered indicative rather than inclusive, where these themes are poised to become established in the literature with potential for development and the adoption of methodological innovations, particularly in the contextual, spatial, and behavioral integration of research on tourism infrastructure.

The lower-right quadrant of the map, which is occupied by basic themes such as “tourism development, tourism infrastructure, and sustainability competitiveness,” gives rise to significant theoretical issues. While these themes occupy a central position from a structural standpoint, their internal development remains relatively limited. Their relatively low density suggests that, despite their importance, these themes remain conceptually fragmented and are often addressed from a descriptive or case-by-case perspective. This finding aligns with the observations from the co-occurrence analysis, which suggest that research related to infrastructure occupies a prominent place within the field but has not yet been fully theorized. This paradox between high centrality and relatively low density highlights potentially important areas for future theoretical exploration and empirical investigation. The field has the potential to enrich the research landscape.

The mapping provides a comprehensive representation of a field characterized by both coherence and fragmentation. The organization is centered around central clusters that are not yet fully developed, such as sustainable tourism and infrastructure development. Furthermore, other specialized research areas have not yet reached the level of theoretical integration within the broader intellectual map. This duality, combining the solidity of its theoretical foundation with the dispersion of its peripheral trajectories, appears to be consistent with the characteristics of an emerging academic field in full development. At present, this field is in the process of establishing theoretical foundations and theorizing robust frameworks for theoretical deepening and empirical validation.

This fragmentation, as evidenced by the quadrant analysis, may reflect the evolving nature of the body of work, necessitating a theoretical distance to leverage the subject’s maturity. This perspective is consistent with the necessity to establish avenues for future research that are intended to assist in addressing the existing research gap, particularly by means of integrating digitalization, societal approaches, and environmental concerns within a more unified conceptual framework.

3.3. Grounded Theory Results

3.3.1. Open and Axial Coding: Category Structure

The Grounded Theory analysis commenced with the open coding process. During this preliminary phase, a substantial number of concepts (codes) derived from the literature excerpts extracted by NVivo 12 were identified in the studied corpus (representative literature excerpts together with their corresponding initial codes are provided in Supplementary Material S2). Thematic analysis of the literature reveals the prevalence of four dominant themes: infrastructure development, tourism dynamics, governance mechanisms, and sustainability constraints.

During the axial coding phase, and subsequent to a continuous process of iterative comparison, these concepts were grouped along the conceptual axis and progressively organized into higher-order categories (see Appendix A). This transition reflects the inductive analytical process underlying the Grounded Theory approach.

To enhance the transparency of the coding process, an illustrative coding chain is presented here. For example, literature excerpts referring to “tourism-driven infrastructure investment”, “investing in transport infrastructure”, and “infrastructure as a prerequisite for tourism development” were initially coded as open codes and subsequently integrated into the higher-order category “tourism infrastructure as enabling driver” (Appendix A). During selective coding, this category was integrated with the other major categories to explain the enabling role of tourism in the proposed TLID conceptual model (Figure 6).

This process identified the five major structural dimensions of the relationship between tourism and infrastructure development.

• Tourism infrastructure as an enabling driver

The results of the study indicated the pivotal role of infrastructure in the development of tourism. A multitude of studies have demonstrated that transportation and digital infrastructure have the capacity to facilitate travel, improve connectivity and accessibility, and support tourism services.

The current literature agrees on the importance of infrastructure as a facilitator of tourism development through transportation connectivity and digital integration (Arteeva et al., 2022; R. Tang & Sun, 2026). From this perspective, several studies have demonstrated that infrastructure investments significantly improve tourist flows, as well as the accessibility and attractiveness of destinations, thereby enhancing their competitiveness (Al-Azri et al., 2024; Gherdan et al., 2025). Digital infrastructure is increasingly establishing itself as a structural dimension of the modern tourism ecosystem rather than merely a complementary component. Digitalization enhances tourism experience and expands destination accessibility through digital platforms (Aarabe et al., 2025; Arteeva et al., 2022). The cumulative weight of these findings calls for a shift in perception regarding the role of tourism infrastructure—from a mere passive condition to an active structural determinant influencing the organization of tourism systems, their performance, and their evolutionary trajectory.

• Tourism and economic performance outcomes

A review of the extant literature reveals a complex relationship between tourism development and economic outcomes, one that goes far beyond the conventional revenue-generation approach. From a macroeconomic perspective, a body of research has demonstrated a significant direct link between tourism activity and GDP growth, as well as the creation of employment opportunities (Al-Azri et al., 2024). It has been demonstrated through further research that tourism has the potential to augment a destination’s competitiveness and reinforce its regional appeal in the context of rapid transformation. The theoretical importance of data indicating that the economic spillovers of tourism tend to stimulate new cycles of investment in infrastructure is particularly significant, as it triggers a self-reinforcing economic mechanism likely to have cumulative effects on development (Gherdan et al., 2025; Moskvichova et al., 2021). These findings support the notion that tourism is both an economic sector and a catalyst for development in the broader sense (Dong & Zeng, 2025; Omirzakova & Wendt, 2025).

• Saturation effects and nonlinear dynamics

Despite its positive impacts, the results of the study highlight several significant limitations in the relationship between tourism and infrastructure, which is not linear. The tensions and contradictions inherent in this relationship limit the analysis of tourism-driven infrastructure development and thus warrant discussion. Moreover, an excess of tourism demand can result in infrastructure saturation and environmental degradation, thereby underscoring the structural weaknesses of tourism systems operating beyond their optimal capacity (Baloch et al., 2023). In this context, concepts such as carrying capacity, pressure on infrastructure, and overtourism emerge as essential analytical issues that deserve to be systematically integrated into destination management frameworks (Al-Mohmmad & Butler, 2021; Baloch et al., 2023). In contrast, infrastructure expansion, when employed as a remedial measure to address capacity limitations, has the potential to engender unanticipated adverse externalities. These externalities may encompass ecological stress and expedited resource consumption, thereby jeopardizing the exacerbation of the sustainability challenges it is designed to ameliorate (Bardhan & Sarkar, 2024). In sum, these findings underscore the imperative need to integrate threshold effects and sustainability constraints as central elements of tourism planning and policymaking.

• Institutional and governance conditions

Governance and institutional quality are emerging as essential elements of infrastructure effectiveness. The findings highlight that infrastructure investments remain insufficient without coordination or integration among stakeholders (Wardana et al., 2025). Arteeva et al. (2022) show that robust governance structures are associated with improved infrastructure performance and more favorable outcomes in the tourism sector, while Junaid et al. (2024) indicate that weak governance and poor institutional coordination significantly limit development potential. The findings highlight the importance of collaborative governance mechanisms that bring together public and private actors around common development objectives as a mode of governance particularly conducive to the long-term sustainability of tourism development by promoting resource complementarity, risk sharing, and strategic alignment (Al-Azri et al., 2024). These observations highlight the central role of institutional determinants in shaping the dynamics of the relationship between tourism and infrastructure.

• Contextual and spatial heterogeneity

The final category underscores the significance of spatial and contextual elements as catalysts for the relationship between tourism and infrastructure. The nature of this relationship is subject to variation depending on geographic conditions, levels of regional development, and local characteristics.

The extant literature indicates that infrastructure development is characterized by spatial disparities, which engender significant inequalities in the geographic distribution of tourism-related benefits across regions (Dong & Zeng, 2025). Iamtrakul et al. (2025) posit that context-related factors, including environmental constraints and accessibility conditions, influence the effectiveness of infrastructure investments in supporting tourism development. These findings imply that the development of tourism is inherently associated with the specific characteristics of a given locale and necessitate customized, context-specific methodologies.

3.3.2. Selective Coding: Emergent Conceptual Model

Building on the results of axial coding, selective coding allows for the systematic integration of the identified categories into a unified conceptual model designed to explain the nature and dynamics of the relationship between tourism and infrastructure development (Figure 6). Through this final stage, the higher-order categories were integrated into the TLID conceptual framework, thereby illustrating how the proposed model emerged inductively from the literature rather than from predefined theoretical assumptions.

The model presents a theoretical framework for tourism development as the primary and determining driver of infrastructure development dynamics. The model posits that the intensification of tourist flows, the enhancement of destination attractiveness, and the expansion of tourism demand collectively generate increasing systemic pressure in favor of infrastructure development, particularly in areas such as transportation connectivity, digital infrastructure, and specialized tourism facilities (Santana et al., 2023). In this theoretical framework, the mediating role attributed to economic outcomes is of particular importance. Revenue generated by tourism, job creation, and regional development is not considered a result. Rather, it is considered an intermediate mechanism that activates and sustains subsequent cycles of infrastructure investment. This, in turn, gives rise to a dynamic and potentially self-reinforcing feedback loop in development (Arteeva et al., 2022).

However, the results of the study indicate that this relationship is contingent on several moderating factors. These factors include governance and institutional quality, which influence policy effectiveness and coordination. Additionally, sustainability constraints, such as environmental limits and carrying capacity, are considered. Finally, contextual and spatial factors reflecting regional disparities are also considered (Baloch et al., 2023; Junaid et al., 2024).

Furthermore, the model under scrutiny elucidates a feedback loop in which infrastructure development has been shown to stimulate tourism performance by improving accessibility, the tourist experience, and the destination’s competitiveness (Burda et al., 2023; Hariguna et al., 2021). This iterative dynamic suggests that tourism and infrastructure co-evolve within a nonlinear and interdependent system, rather than through a simple cause-and-effect relationship.

4. Discussion

4.1. Theoretical Contributions

The findings of our axial and selective coding are significantly corroborated by the most frequently cited references in the corpus, thereby reinforcing their theoretical robustness and thus constituting a substantial theoretical contribution. First, our study has shifted the analysis of the tourism–infrastructure relationship from a linear logic to a co-evolutionary logic. This shift positions tourism not merely as a “user” sector of infrastructure but as a force of spatial structuring capable of driving investments in transportation, digital connectivity, urban amenities, and hospitality services. This extends approaches centered on connectivity and accessibility by demonstrating that tourism infrastructure is not merely an input for performance but also an output of the tourism dynamic itself (Arteeva et al., 2022; Santana et al., 2023; Tegegne et al., 2025). However, factors such as accessibility, mobility, network quality, and the availability of amenities have been identified as critical mechanisms that either facilitate or mediate the relationship between a region’s tourism potential and its actual performance (Arteeva et al., 2022; Iamtrakul et al., 2025; Santana et al., 2023).

Furthermore, the analysis of economic impacts confirms that tourism activates mediating mechanisms (growth, employment, revenue, and investment attractiveness) that explain the conversion of tourist flows into infrastructure development, thus aligning with the findings of Alqaralleh et al. (2025), which highlight the asymmetric nature of the relationship between tourism and growth. This supports our hypothesis of an effect mediated by economic conditions rather than a uniform causality. In other words, it is not only the growth in the number of visitors that matters, but its translation into revenue, employment, local tax revenue, and the legitimization of public or public–private investment (Alqaralleh et al., 2025; Moskvichova et al., 2021; Tegegne et al., 2025).

The results also confirm the effects of saturation, governance conditions, and differences in space, along with “saturation effects and nonlinear dynamics” (Baloch et al., 2023; Bardhan & Sarkar, 2024). Thus, several studies have demonstrated the mixed impact of tourism development in terms of socioeconomic benefits and ecological pressures (Santana et al., 2023) and the strong dependence of tourism accessibility on spatial configurations and transportation networks (Iamtrakul et al., 2025), as well as the impact of transportation infrastructure on reducing seasonality (Santana et al., 2023).

This theory posits that destinations do not uniformly develop infrastructure under conditions of equivalent tourism pressure, depending instead on their institutional quality, strategic coherence, and capacity to integrate development, sustainability, and territorial inclusion. In this sense, our results extend the existing literature by demonstrating that the TLID model does not reflect a linear relationship between tourism and infrastructure. Rather, it reflects a conditional dynamic shaped by feedback loops between demand, economic mediations, institutional capacities, governance, and sustainability constraints (R. Tang & Sun, 2026). Consistent with the findings of Junaid et al. (2024), Kalvelage et al. (2021), and Wendt et al. (2021), this study places moderating governance at the heart of the model while reintroducing the concepts of limits, saturation, and reversibility. Infrastructure supports growth, but it can also increase territorial vulnerabilities.

With regard to the dimension of “contextual and spatial heterogeneity,” the study underscores the contingent nature of the “TLID” model and thus the spatially differentiated effects of tourism on infrastructure, contingent on territorial configuration, degree of peripherality, mobility patterns, seasonality, and the level of local development (Storonyanska et al., 2021; Omirzakova & Wendt, 2025; Wendt et al., 2021).

This framework demonstrates that the relationship between tourism and infrastructure must be conceptualized as a dynamic feedback system. In this system, infrastructure improvements enhance tourism performance. Increased tourism activity, in turn, redefines investment priorities, sustainability trade-offs, and territorial hierarchies. This research’s main contribution is replacing the universalist view of tourism-driven infrastructure development with a relational, territorialized, and contingent perspective. The research shows that the tourism–infrastructure relationship operates as a dynamic feedback system. Improvements in infrastructure stimulate tourism performance, reshaping investment priorities, sustainability trade-offs, and socio-spatial hierarchies.

4.2. Developed vs. Emerging Destinations

As an extension of the findings suggested by the TLID model, we examine a contextual dimension inherent to the developed or emerging nature of the destinations under consideration. In both cases, the relationship is circular: infrastructure improves accessibility, connectivity, and tourism competitiveness, while the growth of visitor flows in turn generates pressure for investment, modernization, and diversification of facilities. Nevertheless, the primary distinction is found in the maturation of tourism infrastructure. In developed destinations, this link is part of an advanced cycle of consolidation, optimization, and renewal. In emerging destinations, however, it is more a matter of catching up, opening up, and the initial structuring of territories. This phenomenon aligns with the logic of the destination life cycle, wherein tourism pressure exerts a shift in investment toward the promotion of renewal, differentiation, and the regulation of tourist flows, as opposed to the initial phase of territorial opening that occurs in advanced stages of destination development (Butler, 2025; Ritchie & Crouch, 2003).

Indeed, in developed destinations, the TLID dynamic, where tourism no longer creates basic infrastructure, promotes the renewal of networks, the upgrading of mobility infrastructure, the digitization of services, the improvement of urban facilities, and the management of externalities linked to saturation (Zuo & Huang, 2018). In mature destinations, the impact of tourism on infrastructure is contingent upon thresholds, carrying capacities, and adjustment mechanisms (Butler, 2025).

Conversely, in emerging destinations, the TLID logic appears to be more visible and more structuring. Consequently, an increase in tourist flows can precipitate an acceleration in upgrades to infrastructure, including roads, airports, hotels, digital infrastructure, and urban infrastructure. This phenomenon occurs because tourism becomes a strategic activity for regional development (Lin et al., 2019). In such destinations, tourism can play a pivotal role in catalyzing public and private investments. However, this potential is contingent upon the capacity of institutions to translate visitor numbers into the capacity for territorial action (Fan & Ha, 2025). Consequently, the emerging TLID is more foundational but also more vulnerable to enclave effects, external capture, and spatial inequalities (Kalvelage et al., 2021).

In the TLID, the mechanisms differ significantly depending on the level of development. In developed countries, the effect is primarily driven by digital sophistication and infrastructure innovation. In 36 OECD countries, ICT innovations have been shown to increase tourism spending (Gavurova et al., 2021), while in 23 European countries, digital public services have been found to support international tourism in the long term (Ha, 2025). In contrast, in developing countries, the impact is more structural. In Africa, for example, ICT infrastructure only has a significant effect once critical thresholds are exceeded (Hadood et al., 2021), while in Pakistan tourism stimulates capital, energy and poverty reduction (Khan et al., 2020).

As demonstrated in

Table 5. Comparative implications of TLID by type of tourist destination.

Analysis Axis	Developed Destinations	Emerging Destinations
Impact of tourism on infrastructure	Tourism primarily drives modernization, redevelopment, digitalization, and congestion management	Tourism stimulates basic infrastructure development, improved accessibility, and the prioritization of investment
Nature of the resulting investments	Investments in renewal, optimization, sustainability, and upgrading	Primary investments: roads, airports, lodging, urban services, and connectivity
Main risk associated with TLID	Overcrowding, network overload, high maintenance costs, loss of livability	Uneven development, tourist enclaves, limited local distribution of value
Comparative conclusion	Circular loop of competitive reproduction	Circular loop of territorial structuring

Source: authors.

, below, while the TLID model posits an accelerator effect on tourism infrastructure investment irrespective of the destination, the impact is primarily concentrated on the redevelopment and management of complexity in developed destinations, and principally on the initial structuring and equipping of the territory in emerging destinations.

In essence, the discrepancy between developed and emerging destinations does not challenge the established correlation between tourism and infrastructure; rather, it redefines the underlying mechanisms. Tourism has been identified as a catalyst for investment in various regions, leading to redevelopment in developed destinations and to the structuring of emerging destinations. Therefore, the stage of territorial maturity, defined as the level of governance and the capacity to transform tourism growth into inclusive infrastructure development, can be incorporated as an additional moderating variable into the aforementioned analytical model.

The distinction between developed and emerging destinations is proposed as a context-sensitive analytical interpretation, rather than as the result of a formal comparative test. Our synthesis indicates that TLID mechanisms vary depending on institutional capacity, infrastructure maturity, and governance conditions. However, these differences remain tentative and require systematic cross-context comparative validation.

4.3. Model Transferability

The transferability of the TLID model is contingent upon its capacity to elucidate, across diverse contexts, the manner in which tourism growth engenders cumulative pressure on territorial capacities and propels infrastructure investments. The findings of this study indicate that the transferability observed does not imply uniformity in the impact of tourism on infrastructure across different territories. Instead, the results suggest that the underlying causal sequence remains consistent, characterized by the intensification of flows, the escalation in demands for accessibility and services, the mobilization of public or private investment, and subsequent reconfiguration of facilities and networks. This logic aligns with research findings indicating that tourism competitiveness is contingent on a multifaceted array of supporting factors, including infrastructure. Moreover, the evolution of the destination itself has been shown to transform investment needs (Dwyer, 2026).

While the external validity of the TLID framework has yet to be empirically validated, its operational applicability is evident. This applicability is rooted in its causal structure, parametric flexibility, and the incorporation of contextual variables. The implementation of this approach necessitates the use of indicators specific to the given territory. Moreover, its transferability is contingent upon adaptation to the institutional, socioeconomic, and environmental contexts that are unique to the local level.

From a TLID perspective, the model is transferable between developed and emerging destinations, not as a uniform matrix, but as a contingent framework, because it captures a common relational mechanism while allowing its intensity and form to vary.

In emerging destinations, tourism has been shown to function as a catalyst for the development of fundamental infrastructure, including roads, airports, lodging facilities, and digital networks. This phenomenon occurs in response to the heightened demand for regional development. In developed destinations, this same dynamic manifests through modernization, densification, or adaptation of existing infrastructure in response to saturation, competition, and the demands of the tourist experience. C. F. Tang and Tan (2018), Almeida (2023), Lin et al. (2019), and Zuo and Huang (2018) specifically confirm that the effects of tourism on growth and, by extension, on investment capacity vary according to structural conditions, tourism specialization, and the stage of development. The transferability of the model is contingent upon its capacity to incorporate the mediating effects of governance, local value capture, and territorial inequalities (Kalvelage et al., 2021). The model can thus be exported as a meso-level theory, provided it is calibrated to the institutional, spatial, and developmental configurations of the destinations under study. The TLID model is thus transferable as an intermediate-range explanatory framework, provided it is contextualized by governance, spatial asymmetries, and territorial capacities.

The transferability of the TLID framework is contingent upon its status as a medium-range theory, whose causal mechanisms are deemed generalizable under the condition that institutional, territorial, and economic variables are functionally equivalent. However, the identification of the contextual thresholds that modulate its robustness, explanatory power, and empirical reproducibility requires validation across multiple sites. Consequently, the framework appears to be transferable to different contexts, provided it is empirically recalibrated according to territorial maturity, local value-capture mechanisms, and socio-environmental constraints. The theoretical scope would benefit from consolidation through comparative, multi-site validations. These validations would help identify the contextual thresholds for explanatory robustness and empirical comparability.

4.4. Practical Implications

From the TLID perspective, the challenge lies in converting growth in tourist flows into sustainable capacities. When infrastructure precedes tourism, the challenge is to avoid oversized investments or those with weak links to local value chains. In terms of major practical implications, the conception of tourism policies as instruments for promoting demand is a misguided approach. Instead, these policies should be conceived of as levers for infrastructure planning (Dwyer, 2026). If tourism can indeed serve as a catalyst for infrastructure development, then the management of flows, target markets, and tourism products becomes an integral component of land-use planning. Consequently, public decision-makers must proactively anticipate the repercussions of tourism growth on various aspects, including mobility, urban services, digital networks, and territorial amenities. This proactive approach is imperative to avoid a reactive management of infrastructure deficits. This perspective is consistent with research linking tourism competitiveness, accessibility, and territorial support factors (Dwyer & Kim, 2003; Khadaroo & Seetanah, 2008).

In practice, in emerging destinations, TLID means using tourism to make investments that are sustainable and benefit everyone. This requires ways to make money, making sure that tourism projects align with the region’s priorities and that the public, investors, and local communities work well together. In developed destinations, the challenge is less about creating basic infrastructure and more about adapting it. This includes managing congestion, improving quality, the digital transition, and making sure that capacity is sustainable. Research by C. F. Tang and Tan (2018), Lin et al. (2019), and Zuo and Huang (2018) suggests that a simple increase in the number of tourists is not enough. The effects of tourism on investment depend on the destination’s economic structure, specialization, and maturity.

In order to enhance the implementation of the TLID, governance should be grounded in intersectoral coordination mechanisms and hybrid financing mechanisms combining public budgets, value capture, and public–private partnerships, as well as institutionalized community participation. Such an approach would encourage the alignment of investments with specific territories, the legitimization of decision-making processes, the redistribution of benefits, and the socio-infrastructural sustainability of diversified local tourism trajectories.

From an operational standpoint, these governance principles can be translated into phased infrastructure investment portfolios. First, prioritize high-leverage infrastructure projects related to accessibility, digital connectivity, and essential services. Then, prioritize assets that support upward mobility. To align tourism returns, territorial inclusion, and fiscal sustainability, decision-makers should combine territorial assessments, multi-criteria analysis, pilot projects, ex ante/ex post indicators, and blended financing mechanisms.

Moreover, the nonlinear character of the tourism–growth relationship suggests that investment strategies should not exclusively prioritize capacity expansion but also encompass regulatory measures to manage saturation thresholds and preserve regional quality (Zuo & Huang, 2018; Butler, 2025). In practice, this means that any TLID strategy should incorporate criteria for territorial redistribution, investment sequencing, and the prevention of spatial imbalances.

Finally, the operational implementation of the TLID framework should also incorporate explicit saturation thresholds related to carrying capacity, congestion, land-use pressure, and environmental burdens. The quantification of these thresholds can be achieved through the use of region-specific indicators, including tourism density, accessibility, public investment, local value capture, spatial inequalities, and the resilience of essential regional services.

4.5. Limitations

Despite the robustness of the results obtained, the present study is not without its limitations. First, there is a risk of overestimating the autonomous capacity of tourism to drive infrastructure development. This would result in an oversimplification of the complexity of development strategy in this area. While the results indicate that tourist flows can act as triggers for investment, they consistently suggest that this relationship is strongly mediated by the economic structures, governance, and institutional capacity of the regions. In essence, tourism does not inherently result in the development of new infrastructure; rather, it engenders pressure or an opportunity that only materializes into physical development under specific circumstances. This caution aligns with studies showing the high variability of tourism-led trajectories across regions, specializations, and growth regimes (C. F. Tang & Tan, 2018; Lin et al., 2019; Zuo & Huang, 2018; Fan & Ha, 2025).

Also, because the infrastructure forms under consideration are very different, the TLID model might not be applicable. In fact, the theory often puts very different types of infrastructure (transportation, lodging, city services, and internet connection) into one plan, even though their schedules, ways of paying for them, and effects on land are different (Baloch et al., 2023; Khadaroo & Seetanah, 2008).

This infrastructure heterogeneity serves to underscore the pertinence of the TLID as an integrative framework while concomitantly necessitating enhanced analytical differentiation. Given the variability of causalities, timeframes, financing, and externalities across infrastructures, the model must specify sector-specific mechanisms, specific mediations, and contextual conditions for validity and operationalization according to territorial profiles.

Additionally, the TLID model lacks precision in delineating the point at which tourism growth transitions from being a catalyst for expansion to a factor contributing to saturation or underperformance. This question is of particular relevance to mature destinations, as Butler’s (2025) life cycle framework underscores. Moreover, the contributions of Dwyer and Kim (2003) and Kalvelage et al. (2021) underscore the notion that infrastructure constitutes a component of a more extensive system encompassing competitiveness and accessibility. This system functions to circumscribe any monolithic interpretation of causality.

The time period (2021–2025) was chosen because it captures the post-pandemic reconfiguration of relationships among tourism, infrastructure, and sustainability against the backdrop of accelerating territorial and digital transformations. Although we acknowledge the risk of overlooking historical depth and earlier foundational contributions, we believe that this recent delimitation of the study period provides a relevant analytical framework capable of ensuring a decision-oriented understanding of the field.

Another important limitation of the research is that the long-term predictive capacity of the TLID model may be compromised by difficult-to-control exogenous factors, such as funding priorities, shifts in public policy, and technological breakthroughs. These factors alter the dynamics of scientific output and reduce the robustness of longitudinal projections.

The fundamental constraint of the TLID does not lie in its irrelevance; rather, it is the necessity to conceptualize it as a conditional thesis rather than a universal law of territorial development.

5. Conclusions and Research Agenda

The objective of this research was to ascertain the extent to which tourism can function as an agent of infrastructure development. The findings yielded a deliberately nuanced response. The hypothesis of tourism-led infrastructure development cannot be interpreted as a mechanical relationship in which growth in tourist flows would automatically generate new investments, networks, or facilities. Instead, the analysis demonstrates that tourism functions as a catalyst for territorial pressure, economic legitimization, and institutional mobilization, with the capacity to precipitate infrastructural transformations when specific conditions are met. In essence, tourism does not directly contribute to the development of infrastructure; rather, it stimulates the generation of needs, investment opportunities, and public or private trade-offs. These trade-offs can, depending on the context, result in processes of opening up isolated areas, modernization, densification, or redevelopment. The scope of this dynamic, however, varies significantly depending on the stage of development of the destinations. In emerging areas, the manifestation of TLID is predominantly characterized by investments in infrastructure, including but not limited to accessibility, transportation, lodging, basic services, and connectivity. These investments are often precipitated by the region’s integration into tourist circuits. In more mature destinations, this process takes the form of a continuous adaptation of existing capacities. The focus of this adaptation is on service quality, the management of overcrowding, sustainability, and the movement upmarket. Therefore, tourism does not appear to be a universal catalyst for infrastructure development; rather, it is a conditional catalyst whose effects are contingent on governance, economic mediations, capacity constraints, and the territorial anchoring of the benefits.

A seminal aspect of the article is its theoretical reframing, which offers a novel perspective on the subject. The study demonstrates that tourism dynamics are inextricably linked to infrastructure, thereby underscoring the necessity to comprehend TLID as a relational and evolving process, rather than as a simple linear causality. The identification of the five structuring dimensions—the enabling role of tourism infrastructure, economic performance effects, saturation dynamics, institutional conditions, and contextual heterogeneity—allows for the synthesis of the literature and the establishment of a coherent analytical framework for discussion.

In contrast to conventional models of tourism-driven growth, the added value of our TLID framework lies in replacing a simple linear interpretation focused on macroeconomic effects with a relational explanatory framework. In this sense, tourism is not merely a source of growth; rather, it functions as a catalyst for infrastructure investments mediated by the tourism economy and shaped by governance. The model introduces a logic of bidirectional co-evolution between tourism and infrastructure, incorporating dimensions generally absent from previous frameworks. These additional dimensions include sustainability, saturation phenomena, risks of reversibility, and territorial contingencies that differentiate development trajectories. In contrast to models of tourism-induced growth, the TLID posits a bidirectional, conditional, and nonlinear causality, incorporating mediations, feedback loops, saturation, reversibility, and contextual differences depending on territorial governance.

The reliability of this theoretical framework is also inherent in the relevance of our methodological approach, which is grounded in Grounded Theory. This methodological advancement has facilitated a transition from a mere descriptive inventory of prior findings to an inductive reconstruction of the underlying categories, relationships, and explanatory mechanisms.

Methodologically, the article makes a substantial contribution by combining a structured literature review with a coding logic inspired by Grounded Theory. The transition from open coding to axial coding, and subsequently to selective coding, enabled the transformation of a dispersed corpus into an explanatory model of intermediate scope. This model was capable of organizing concepts, identifying mediations, and revealing the central moderators of the tourism–infrastructure relationship. This contribution is also empirical, even though it is based on a secondary synthesis. It highlights that the infrastructural effect of tourism is spatially differentiated, politically conditioned, and distributively unequal. The article demonstrates that the volume of flows alone is inadequate in explaining the observed material transformations. The effective scope of the TLID is determined by the capacity of territories to convert these flows into investment decisions, institutional coordination, and locally captured benefits.

Despite these strengths, our results must be qualified in light of several limitations. From a theoretical perspective, the focus on TLID necessarily tends to emphasize the direction from tourism to infrastructure, at the risk of downplaying the broader reciprocity of interactions between attractiveness, accessibility, and territorial development. Similarly, the category of “infrastructure” encompasses heterogeneous realities (transportation, digital infrastructure, urban facilities, and tourism services) whose timeframes, financing methods, and spatial effects are not strictly comparable. Methodologically, the proposed model constitutes an analytical generalization based on a coded synthesis of the literature, rather than a direct causal validation derived from a single comparative framework. Its robustness is therefore primarily explanatory and conceptual. It remains more limited when it comes to precisely measuring saturation thresholds, the timeframes for infrastructure adjustments, or the mechanisms of territorial distribution of benefits.

The TLID model’s theoretical framework is sound. However, its external validity will need to be tested in practice through dedicated empirical research. This research should use structural equation modeling to test direct, mediating, and moderating relationships simultaneously. It should also use comparative case studies to assess sensitivity to regional contexts and longitudinal analyses to verify the temporal persistence of the proposed mechanisms across different tourist destinations.

These limitations, however, also create significant opportunities for research. In principle, it would be advantageous to differentiate more clearly between the various types of infrastructure and the sequence of development in order to ascertain the conditions under which tourism engenders inclusive, selective, or extractive trajectories. A more robust integration with approaches to multilevel governance, territorial resilience, and sustainability would also facilitate the refinement of the proposed framework. Methodologically, the most promising avenues for further research lie in multi-context comparative studies, longitudinal designs, and mixed-methods approaches combining quantitative indicators, spatial analysis, and qualitative data. Conducting such research would facilitate empirical testing of the mechanisms identified in this study, enhance characterization of TLID variability between emerging and developed destinations, and enable a more nuanced assessment of how tourism growth translates, or fails to translate, into sustainable, equitable, and territorially anchored infrastructure development.

In essence, the study’s findings address the research question “Through what mechanisms, under what conditions, and in what configurations does tourism stimulate infrastructure?” by revealing an effect that is mediated by the tourism economy and modulated by governance, territorial maturity, and spatial contexts. However, the absence of multi-site validation and the limited differentiation in infrastructure necessitate the implementation of additional comparative, longitudinal, and sector-specific tests on an international scale.