The tourism industry has been forced to develop technological innovations to maintain its competitiveness and offer attractive services in a context in which the Metaverse is an emerging concept with little development explored in the literature. In order to identify the factors that influence its adoption by tourism companies, research was carried out based on the TOE (Technology-Organization-Environment) framework applied to 278 Spanish companies. The statistical tool PLS-SEM was used to analyze the data employing the SmartPLS 4 software, previously assessing the validity and reliability of the scales. In addition, this symmetric approach was complemented with a complexity analysis using the fsQCA methodology, allowing us to approach business decision-making from a non-symmetric perspective. The results indicate that technological competence, relative advantage, knowledge of the decision-maker, top management support and competitive pressure are the most important determinants of Metaverse adoption, confirming the existence of different solutions that can lead to the same outcome. This study offers theoretical and managerial implications relevant for the future of the tourism sector.
AbedSS (2020) Social commerce adoption using TOE framework: An empirical investigation of Saudi Arabian SMEs. International Journal of Information Management53: 102118.
2.
AboelmagedMG (2014) Predicting e-readiness at firm-level: an analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms. International Journal of Information Management34(5): 639–651.
3.
AddyMNKwofieTEEAgbonaniDM, et al. (2023) Using the TOE theoretical framework to study the adoption of BIM-AR in a developing country: the case of Ghana. Journal of Engineering, Design and Technology22: 1913–1935, ahead-of-print(ahead-of-print).
4.
AgnihotriABhattacharyaSSakkaG, et al. (2025) Driving metaverse adoption in the hospitality industry: an upper echelon perspective. International Journal of Contemporary Hospitality Management37(4): 1199–1230.
5.
AligarhFSutopoBWidarjoW (2023) The antecedents of cloud computing adoption and its consequences for MSMEs’ performance: a model based on the Technology-Organization-Environment (TOE) framework. Cogent Business & Management10(2): 2220190.
6.
AlnoorAAbbasSSadaaAM, et al. (2025) Navigating the power of blockchain strategy: analysis of technology-organization-environment (TOE) framework and innovation resistance theory using PLS-SEM and ANN insights. Technological Forecasting and Social Change214: 124044.
7.
AlrajaMNImranRKhashabBM, et al. (2022) Technological innovation, sustainable green practices and SMEs sustainable performance in times of crisis (COVID-19 pandemic). Information Systems Frontiers24(4): 1081–1105.
8.
Álvarez LópezCCarrasco PereraÁ (2023) ¿Qué es un Metaverso? In Guía jurídica del metaverso. 1st editionTecnos, 176.
9.
AminiMJahanbakhsh JavidN (2023) A multi-perspective framework established on diffusion of innovation (DOI) theory and technology, organization and environment (TOE) framework toward supply chain management system based on cloud computing technology for small and medium enterprises. Organization and Environment (TOE) Framework Toward Supply Chain Management System Based on Cloud Computing Technology for Small and Medium Enterprises (January 2023). International Journal of Information Technology and Innovation Adoption11: 1217–1234.
10.
AndriesPStephanU (2019) Environmental innovation and firm performance: how firm size and motives matter. Sustainability11(13): 3585.
11.
Asante BoakyeEZhaoHKwame AhiaBN, et al. (2025) Modeling the adoption enablers of blockchain technology–based supply chain financing: an integrative dual DOI–TOE analysis. Journal of the International Council for Small Business6: 1–22.
12.
AtesHPolatM (2025) Exploring adoption of humanoid robots in education: UTAUT-2 and TOE models for science teachers. Education and Information Technologies30: 1–42.
13.
AwaHOOjiaboOUEmechetaBC (2015) Integrating TAM, TPB and TOE frameworks and expanding their characteristic constructs for e-commerce adoption by SMEs. Journal of Science and Technology Policy Management6(1): 76–94.
14.
AzeemMAhmedMHaiderS, et al. (2021) Expanding competitive advantage through organizational culture, knowledge sharing and organizational innovation. Technology in Society66: 101635.
15.
Barreiro-PereiraFAbdelkader-Benmesaud-CondeT (2025). Impact of the COVID-19 pandemic on the European union economy, energy and environment. En COVID-19 and Public Policy. Emerald Publishing Limited. pp. 17–33.
16.
BekeleHRajS (2025) Digitalization and digital transformation in the tourism industry: a bibliometric review and research agenda. Tourism Review80(4): 894–913.
17.
Berrones VeintimillaASCobo TorresMB (2022) Metaversos y la promoción de la oferta turística: Caso de estudio cantón Baños de Agua Santa [Bachelor Thesis]. Universidad Técnica de Ambato. Facultad de Ciencias Administrativas. Carrera de Mercadotecnia. https://repositorio.uta.edu.ec:8443/jspui/handle/123456789/36219
18.
BorgmanHPBahliBHeierH, et al. (2013) Cloudrise: exploring cloud computing adoption and governance with the TOE framework. In: 2013 46th Hawaii International Conference on System Sciences. IEEE, pp. 4425–4435.
19.
BremserC (2018). Starting points for big data adoption. En Proceedings of European Conference on Information Systems (ECIS).
20.
BridaJGCárdenas-GarcíaPJ (2025) Introduction: special focus on tourism, economic development and environmental impact. Tourism Economics31(1): 72–75.
21.
BryanJDZuvaT (2021) A review on TAM and TOE framework progression and how these models integrate. Advances in Science, Technology and Engineering Systems Journal6(3): 137–145.
22.
BuhalisDLeungDLinM (2023) Metaverse as a disruptive technology revolutionising tourism management and marketing. Tourism Management97: 104724.
23.
Carrero LugoGPSastre RuidiazLA (2021) Factores que influyen en la adopción de tecnologías Rfid para el control de inventarios en las pymes de manufactura de Bogotá [Master Thesis]. Maestría en Gerencia de la Cadena de Abastecimiento Virtual. https://repository.universidadean.edu.co/handle/10882/10972
24.
CarvalhoPAlvesH (2023) Customer value co-creation in the hospitality and tourism industry: a systematic literature review. International Journal of Contemporary Hospitality Management35(1): 250–273.
25.
ChandraSKumarKN (2018) Exploring factors influencing organizational adoption of augmented reality in e-commerce: empirical analysis using technology–organization– environment model. Journal of Electronic Commerce Research19(3): 237–265.
26.
ChenZ (2025) Beyond boundaries: exploring the Metaverse in tourism. International Journal of Contemporary Hospitality Management37(4): 1257–1275.
27.
ChiMChenYXuY, et al. (2024) Modelling barriers to metaverse adoption in the hospitality and tourism industry. Information Technology & Tourism26(4): 711–743.
28.
ChinWW (2010). How to write up and report PLS analyses. In Handbook of Partial Least Squares. Springer. pp. 655–690.
29.
ChinWMarcoulidesG (1998) The partial Least Squares approach to structural equation modeling. Modern Methods for Business Research8: 295–358.
30.
ChittipakaVKumarSSivarajahU, et al. (2022) Blockchain Technology for Supply Chains operating in emerging markets: an empirical examination of technology-organization-environment (TOE) framework. Annals of Operations Research327: 1–28.
31.
Collado-AgudoJHerrero-CrespoÁSan Martín-GutiérrezH (2023) The adoption of a smart destination model by tourism companies: an ecosystem approach. Journal of Destination Marketing & Management28: 100783.
32.
Comprehensive Technological Research (2022) La Nueva Revolución Digital para Principiantes: Usos prácticos del Metaverso, Web 3.0, Blockchain, Criptodivisas, NFTs, DeFi, Realidad virtual y aumentada. 1st edition. Comprehensive Technological Research.
33.
Cruz-JesusFPinheiroAOliveiraT (2019) Understanding CRM adoption stages: empirical analysis building on the TOE framework. Computers in Industry109: 1–13.
DarbanKKabbajSEljaiM (2024) Assessing the adoption readiness of Moroccan consumers for AI-powered assistance and CRM systems. Procedia Computer Science236: 541–549.
36.
DasSDBalaPK (2023) What drives MLOps adoption? An analysis using the TOE framework. Journal of Decision Systems33: 1–37.
37.
Dávila ChediakAN (2023). Análisis del metaverso Y las interacciones en videojuegos de tipo sandbox: estudio de caso: grand theft AUTO V online.
38.
De JorgeR (2022) Introducción al metaverso para el sector turístico, pp. 64–66.
39.
EkongUOIfinedoPAyoCK, et al. (2012). E-commerce adoption in Nigerian businesses: an analysis using the technology-organization-environmental framework. In Leveraging Developing Economies with the Use of Information Technology: Trends and Tools. IGI Global, pp. 156–178.
40.
FanMNdaviJWQalatiSA, et al. (2022) Applying the time continuum model of motivation to explain how major factors affect mobile learning motivation: a comparison of SEM and fsQCA. Online Information Review46(6): 1095–1114.
41.
FarahnakLREhrhartMGTorresEM, et al. (2020) The influence of transformational leadership and leader attitudes on subordinate attitudes and implementation success. Journal of Leadership & Organizational Studies27(1): 98–111.
FirmanAChauKYWalawalkarAM, et al. (2025) Navigating the future: envisioning metaverse adoption in Indonesian tourism through the technological–organizational–environmental (TOE) framework. Journal of Theoretical and Applied Electronic Commerce Research20(2): 118.
44.
FissPC (2011) Building better causal theories: a fuzzy set approach to typologies in organization research. Academy of Management Journal54(2): 393–420.
45.
FornellCLarckerDF (1981) Structural equation models with unobservable variables and measurement error: algebra and statistics. Journal of Marketing Research18(3): 382–388.
46.
FrankDChrysochouPMitkidisP (2023) The paradox of technology: negativity bias in consumer adoption of innovative technologies. Psychology and Marketing40(3): 554–566.
47.
García PortelaS (2022). El Metaverso y su influencia en el futuro del sector turístico.
48.
GhobakhlooM (2020) Determinants of information and digital technology implementation for smart manufacturing. International Journal of Production Research58(8): 2384–2405.
49.
Gil-CorderoELedesma-ChavesPHanH, et al. (2023a) Analysis of university professors in economic sciences: PMH scale and technostress as main antecedents of academic self-perception. Journal of Men’s Health19(2): 17–28.
50.
Gil-CorderoEMaldonado-LópezBLedesma-ChavesP, et al. (2023b) Do small-and medium-sized companies intend to use the Metaverse as part of their strategy? A behavioral intention analysis. International Journal of Entrepreneurial Behavior & Research.
GoertzGMahoneyJ (2012) Tale of Two Cultures-Contrasting Qualitative and Quantitative. Princeton University Press.
54.
GursoyDMalodiaSDhirA (2022) The metaverse in the hospitality and tourism industry: an overview of current trends and future research directions. Journal of Hospitality Marketing & Management31(5): 527–534.
55.
GutierrezHMelgarejoM (2017) Clasificación Automática del Avance de Megaproyectos de Inversión Pública en Colombia, desde un Enfoque Técnico, Organizacional y Ambiental. Ingenieria22(3): 377.
56.
HaasCKempaK (2023) Low-carbon investment and credit rationing. Environmental and Resource Economics86: 1–37.
57.
HairJFRisherJJSarstedtM, et al. (2019) When to use and how to report the results of PLS-SEM. European Business Review31(1): 2–24.
58.
HasaniTRezaniaDMohammadiM (2024) Towards a framework for successful metaverse adoption in Small and Medium-sized Enterprises: an exploratory study. International Journal of Engineering Business Management16: 18479790241257118.
59.
HassanMFANgahAHTioMBY (2023) Third-party logistics intention to provide cold transportation services. In: The Mediating Effect of Top Management Support and Organizational Readiness in TOE Framework. OPSEARCH, pp. 1–23.
60.
HenselerJHubonaGRayPA (2016) Using PLS path modeling in new technology research: updated guidelines. Industrial Management and Data Systems116(1): 2–20.
61.
HermundsdottirFAspelundA (2021) Sustainability innovations and firm competitiveness: a review. Journal of Cleaner Production280: 124715.
62.
HouBHongJZhuR (2019) Exploration/exploitation innovation and firm performance: the mediation of entrepreneurial orientation and moderation of competitive intensity. Journal of Asia business studies13(4): 489–506.
63.
HsuH-YLiuF-HTsouH-T, et al. (2018) Openness of technology adoption, top management support and service innovation: a social innovation perspective. Journal of Business & Industrial Marketing34(3): 575–590.
64.
HwangISeoR (2025) Organizational support for digital transformation in the metaverse: a contingent pathway from user experience to digitalization resistance. R & D Management55(2): 420–437.
KangH (2021) Sample size determination and power analysis using the G* Power software. Journal of educational evaluation for health professions18: 17.
67.
KarjaluotoHShaikhAALeppäniemiM, et al. (2020) Examining consumers’ usage intention of contactless payment systems. International Journal of Bank Marketing38(2): 332–351.
68.
KaurMSinghDAnandA, et al. (2023) Do attributes of happy Seeder technology influence its adoption speed? An investigation using duration analysis in Northern India. International Journal of Agricultural Sustainability21(1): 2198324.
69.
KevinZKraemerKXuS, et al. (2004) Information technology payoff in e-business environments: an international perspective on value creation of e-business in the financial services industry. Journal of Management Information Systems21: 17–54.
70.
KhuongNVAnhLHTGiangLHQ, et al. (2025) Business strategy, enterprise risk management, organisational innovation performance and organisational performance: comparing fsQCA with PLS-SEM. International Journal of Business Governance and Ethics19(3/4): 406–431.
71.
KılıçarslanÖYozukmazNAlbayrakT, et al. (2025) The impacts of Metaverse on tourist behaviour and marketing implications. Current Issues in Tourism28(4): 622–642.
72.
KimJErdemMKimB (2025) What factors motivate customers to embrace a metaverse hotel?International Journal of Contemporary Hospitality Management37(2): 399–417.
73.
KooCKwonJChungN, et al. (2022) Metaverse tourism: conceptual framework and research propositions. Current Issues in Tourism26: 1–7.
74.
KrausSNiemandTBeslerM, et al. (2018) The influence of leadership styles on the internationalisation of «born-global» firms and traditionally global-expanding firms. European Journal of International Management12(5-6): 554–575.
75.
KumarAKrishnamoorthyB (2020) Business analytics adoption in firms: a qualitative study elaborating TOE framework in India. International Journal of Global Business and Competitiveness15(2): 80–93.
76.
KumarAShankarA (2024) Building a sustainable future with enterprise metaverse in a data-driven era: a technology-organization-environment (TOE) perspective. Journal of Retailing and Consumer Services81: 103986.
77.
KumarASinghRKSwainS (2022) Adoption of technology applications in organized retail outlets in India: a TOE model. Global Business Review: 09721509211072382.
78.
KupeliBSalmanGGKaraosmanogluE, et al. (2024) Exploring self-service technology adoption: case of airline check in. Technology in Society77: 102558.
79.
KusaRDudaJSuderM (2022) How to sustain company growth in times of crisis: the mitigating role of entrepreneurial management. Journal of Business Research142: 377–386.
80.
KwokAO (2023) The next frontier of the Internet of Behaviors: data-driven nudging in smart tourism. Journal of Tourism Futures11: 307–313.
81.
KyeBHanNKimE, et al. (2021) Educational applications of metaverse: possibilities and limitations. Journal of Educational Evaluation for Health Professions18: 32.
82.
LeeU-KKimH (2022) UTAUT in metaverse: an “Ifland” case. Journal of Theoretical and Applied Electronic Commerce Research17(2): 2–635.
83.
LeungXYZhangHLyuJ, et al. (2023) Why do hotel frontline employees use service robots in the workplace? A technology affordance theory perspective. International Journal of Hospitality Management108: 103380.
84.
LiaoHShiYLiuX, et al. (2019) A non-probabilistic model of carbon footprints in remanufacture under multiple uncertainties. Journal of Cleaner Production211(9-10): 1127–1140.
85.
LiuLWuDPengN (2025) The Impact of COVID-19 and digital transformation on stock price volatility from the perspective of cultural and tourism industries. International Review of Economics & Finance101: 104144.
86.
LowCChenYWuM (2011) Understanding the determinants of cloud computing adoption. Industrial Management & Data Systems111(7): 1006–1023.
87.
MadzíkPFalátLCopušL, et al. (2023) Digital transformation in tourism: bibliometric literature review based on machine learning approach. European Journal of Innovation Management26(7): 177–205.
88.
MalikSChadharMVatanasakdakulS, et al. (2021) Factors affecting the organizational adoption of blockchain technology: extending the technology–organization–environment (TOE) framework in the Australian context. Sustainability13(16): 16.
89.
MartiLPuertasR (2025) Relationship between tourism development and the socioeconomic progress of tourist destinations. Competitiveness Review: An International Business Journal35(1): 175–189.
90.
MartinsDOliveiraLAmaroAC (2022) From co-design to the construction of a metaverse for the promotion of cultural heritage and tourism: the case of Amiais. Procedia Computer Science204: 261–266.
91.
MetaxasTJuárezLAndrinosM (2022) Measuring the impact of Greece as a safe branding tourist destination: evidence from Spain and Greece. Sustainability14(8): 4440.
92.
MisangyiVFGreckhamerTFurnariS, et al. (2017) Embracing causal complexity: the emergence of a neo-configurational perspective. Journal of Management43(1): 255–282.
93.
MonacoSSacchiG (2023) Travelling the metaverse: potential benefits and main challenges for tourism sectors and research applications. Sustainability15(4): 3348.
94.
MorawiecPSołtysik-PiorunkiewiczA (2023) ERP system development for business agility in industry 4.0—a literature review based on the TOE framework. Sustainability15(5): 4646.
95.
NaSHeoSHanS, et al. (2022) Acceptance model of artificial intelligence (AI)-based technologies in construction firms: applying the Technology Acceptance Model (TAM) in combination with the Technology–Organisation–Environment (TOE) framework. Buildings12(2): 90.
96.
NazirMARizwanHZhuX (2025) A thematic analysis of factors influencing small and medium enterprise adoption of social media marketing: a TOE framework perspective. Qualitative Market Research: An International Journal28(1): 178–204.
97.
NelsonPRTaylorPAMacGregorJF (1996) Missing data methods in PCA and PLS: score calculations with incomplete observations. Chemometrics and Intelligent Laboratory Systems35(1): 45–65.
98.
NgKSPWongJWCXieD, et al. (2022a) From the attributes of smart tourism technologies to loyalty and WOM via user satisfaction: the moderating role of switching costs. Kybernetes.
99.
NgPMLLitKKCheungCTY (2022b) Remote work as a new normal? The technology-organization-environment (TOE) context. Technology in Society70: 102022.
100.
NguyenTHLeXCVuTHL (2022) An extended technology-organization-environment (TOE) framework for online retailing utilization in digital transformation: empirical evidence from Vietnam. Journal of Open Innovation: Technology, Market, and Complexity8(4): 200.
101.
NguyenPMBPhamXLTruongGNT (2023) A bibliometric analysis of research on tourism content marketing: background knowledge and thematic evolution. Heliyon9(2): e13487.
102.
NuseiraMTAljumahbA (2020) Digital marketing adoption influenced by relative advantage and competitive industry: a UAE tourism case study. Marketing11(2): 23–37.
103.
OliveiraTMartinsMF (2011) Literature review of information technology adoption models at firm level. Electronic Journal of Information Systems Evaluation14(1): 1.
104.
OzdemirODogruTKizildagM, et al. (2023) A critical reflection on digitalization for the hospitality and tourism industry: value implications for stakeholders. International Journal of Contemporary Hospitality Management35: 3305–3321.
105.
PanYFroeseFLiuN, et al. (2022) The adoption of artificial intelligence in employee recruitment: the influence of contextual factors. International Journal of Human Resource Management33(6): 1125–1147.
106.
PappasIOWoodsideAG (2021) Fuzzy-set qualitative comparative analysis (fsQCA): guidelines for research practice in information systems and marketing. International Journal of Information Management58: 102310.
107.
ParkS-MKimY-G (2022) A metaverse: taxonomy, components, applications, and open challenges. IEEE Access10: 4209–4251.
108.
ParraDTGuerreroCD (2020) Technological variables for decision-making IoT adoption in small and medium enterprises. Journal of Information Systems Engineering and Management5(4): em0124.
109.
PateliAMylonasNSpyrouA (2020) Organizational adoption of social media in the hospitality industry: an integrated approach based on DIT and TOE frameworks. Sustainability12(17): 7132.
110.
Pettinelli ObrequeÁFJofré DíazEM (2016) Evaluación de impacto en el desarrollo de las tecnologías de información y comunicación (TICS) en microempresas chilenas. https://repositorio.udec.cl/jspui/handle/11594/2391
111.
PhungGTrinhHHNguyenTH, et al. (2023) Top-management compensation and environmental innovation strategy. Business Strategy and the Environment32(4): 1634–1649.
112.
PodsakoffPMMacKenzieSBLeeJ-Y, et al. (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology88(5): 879–903.
113.
Pulido-FernándezJ-ISánchez-RiveroMLópez-SánchezY (2011) Comparative analysis of the sustainability of tourism in Spain’s regions. Environmental Engineering & Management Journal (EEMJ)10(12): 1845–1855.
114.
PumplunLTauchertCHeidtM (2019). A new organizational chassis for artificial intelligence - exploring organizational readiness factors. 112582.
115.
QalatiSVelaELiW, et al. (2021) Effects of perceived service quality, website quality, and reputation on purchase intention: the mediating and moderating roles of trust and perceived risk in. Cogent Business & Management8(1): 1869363.
116.
RaginCC (2009) Qualitative comparative analysis using fuzzy sets (fsQCA). Configurational comparative methods: Qualitative comparative analysis (QCA) and related techniques51: 87–121.
117.
RaginCCDrassKDaveyS (2008). User’s Guide to Fuzzy-Set/Qualitative Comparative Analysis. University of Arizona. pp. 1–87.
118.
RahimiRAOhGS (2024) Beyond theory: a systematic review of strengths and limitations in technology acceptance models through an entrepreneurial lens. Journal of Marketing Analytics.
119.
RaimeeNMohamedISRozzaniN (2021) Determinants of web-technology investment in Malaysian logistics industry: an application of technological, organizational and environmental (TOE) model. Business Management and Strategy12(1): 91–107.
120.
RajAJeyarajA (2023) Antecedents and consequents of industry 4.0 adoption using technology, organization and environment (TOE) framework: a meta-analysis. Annals of Operations Research322(1): 101–124.
121.
RamMSelvabaskarSGuhanR, et al. (2023) The effect of digital communication technologies in retail supply chain management: evidence from Indian small retailers. Journal of Future Sustainability3(3): 125–132.
122.
RamtiyalBSoniGJainV, et al. (2025) Unraveling the aspects of metaverse adoption in the supply chains of small-scale enterprises with TOE framework. International Journal of Logistics Management.
123.
RatherRA (2023) Metaverse marketing and consumer research: theoretical framework and future research agenda in tourism and hospitality industry. Tourism Recreation Research50: 1–9.
124.
RattenVTajeddiniKThorstenM (2019). Turismo, hostelería y transformación digital: La relevancia para la sociedad.
125.
RauschnabelPAFelixRHinschC, et al. (2022) What is XR? Towards a framework for augmented and virtual reality. Computers in Human Behavior133: 107289.
126.
ReinhardtRHietscholdNGurtnerS (2019) Overcoming consumer resistance to innovations–an analysis of adoption triggers. R & D Management49(2): 139–154.
127.
RiarMXiNKorbelJJ, et al. (2022) Using augmented reality for shopping: a framework for AR induced consumer behavior, literature review and future agenda. Internet Research33(1): 242–279.
RippaPFerruzziGHolienkaM, et al. (2020) What drives university engineering students to become entrepreneurs? Finding different recipes using a configuration approach. Journal of Small Business Management61: 1–31.
130.
RivasSLLGonzálezJAWongAM (2021) Marco TOE para diferenciar la asimilación del ERP en franquicias y empresas familiares mexicanas. Economía, Población y Desarrollo11(65): 3–36.
131.
RogersE (1995) Diffusion of Innovations. 4th edition. New York: ACM The Free Press (Sept. 2001), pp. 15–23.
132.
RoldanJLCepedaG (2017) PLS-SEM. CFP, Universidad de Sevilla.
133.
RussoIConfenteI (2019) From dataset to qualitative comparative analysis (QCA)—challenges and tricky points: a research note on contrarian case analysis and data calibration. Australasian Marketing Journal27(2): 129–135.
134.
SallehKJanczewskiL (2016) Adoption of big data solutions: a study on its security determinants using sec-TOE framework. CONF-IRM 2016 Proceedings. https://aisel.aisnet.org/confirm2016/66
135.
Sánchez CaleroAde la CSegura ÁlvarezMMedina LabradaJR, et al. (2021) Metodología para la gestión de la innovación tecnológica en destinos turísticos. Observatorio de las Ciencias Sociales en Iberoamérica2(12): 246–260.
136.
SarstedtMRingleCMHenselerJ, et al. (2014) On the emancipation of PLS-SEM: a commentary on Rigdon (2012). Long Range Planning47(3): 154–160.
137.
SarstedtMRingleCMHairJF (2017). Partial Least Squares structural equation modeling. In Handbook of Market Research, pp. 1–40.
138.
SeshadriUKumarPVijA, et al. (2023) Marketing strategies for the tourism industry in the United Arab Emirates after the COVID-19 era. Worldwide Hospitality and Tourism Themes, ahead-of-print.
139.
ShadievaGMBaratovnaSNMuminovichAS (2022) Theoretical foundations of national tourism and competitiveness. Specialusis Ugdymas2(43): 3166–3177.
140.
ShahzadKShahzadMFAhmadB, et al. (2025) Impact of metaverse experiences on consumer behavior in metaverse-enabled hospitality retailing: the role of realism, immersion, convenience, and social interaction. Journal of Hospitality Marketing & Management34: 1–22.
141.
SharmaMGuptaRSehrawatR, et al. (2023) The assessment of factors influencing Big data adoption and firm performance: evidences from emerging economy. Enterprise Information Systems17: 2218160.
142.
SongHHsuCHPanB, et al. (2025) How COVID-19 has changed tourists’ behaviour. Nature Human Behaviour9(1): 43–52.
143.
SousaNJorgeFTeixeiraMS, et al. (2024) Does technological innovativeness influence users’ experiences with virtual reality tourism?International Journal of Tourism Research26(4): e2730.
144.
StjepićA-MPejić BachMBosilj VukšićV (2021) Exploring risks in the adoption of business intelligence in SMEs using the TOE framework. Journal of Risk and Financial Management14(2): 58.
145.
SwansonEB (1994) Information systems innovation among organizations. Management Science40(9): 1069–1092.
TayalSRajagopalKMahajanV (2022) Virtual reality based metaverse of gamification. In: 2022 6th International Conference on Computing Methodologies and Communication (ICCMC). IEEE, pp. 1597–1604.
148.
TornatzkyLFleischerM (1990) The Process of Technology Innovation. Lexington, MA: Lexington books.
Vizcaíno PonferradaML (2015) Evolución del turismo en España: El turismo cultural. International journal of scientific management and tourism1(4): 75–95.
151.
WangD (2025) Examining the effects of potential tourists’ destination familiarity on destination image and travel intention: a mixed approach of PLS-SEM and fsQCA. Sage Open15(1): 21582440251319612.
152.
WangWTaoMGongS, et al. (2025) Revisiting what factors promote BIM adoption more effectively through the TOE framework: a meta-analysis. Frontiers of Engineering Management12: 1–20.
153.
WeinrichR (2019) Opportunities for the adoption of health-based sustainable dietary patterns: a review on consumer research of meat substitutes. Sustainability11(15): 4028.
154.
WongL-WLeongL-YHewJ-J, et al. (2020) Time to seize the digital evolution: adoption of blockchain in operations and supply chain management among Malaysian SMEs. International Journal of Information Management52: 101997.
155.
WoodsideAG (2014) Embrace• perform• model: complexity theory, contrarian case analysis, and multiple realities. Journal of Business Research67(12): 2495–2503.
156.
WoodsideAGNagyGMegeheeCM (2018) Applying complexity theory: a primer for identifying and modeling firm anomalies. Journal of Innovation & Knowledge3(1): 9–25.
157.
WredeMVelamuriVKDauthT (2020) Top managers in the digital age: exploring the role and practices of top managers in firms’ digital transformation. Managerial and Decision Economics41(8): 1549–1567.
158.
WuHZhongWZhongB, et al. (2025) Barrier identification, analysis and solutions of blockchain adoption in construction: a fuzzy DEMATEL and TOE integrated method. Engineering Construction and Architectural Management32(1): 409–426.
159.
YangFXWangY (2023) Rethinking metaverse tourism: a taxonomy and an agenda for future research. Journal of Hospitality & Tourism Research49: 10963480231163509.
160.
YangFXWangY (2025) Rethinking metaverse tourism: a taxonomy and an agenda for future research. Journal of Hospitality & Tourism Research49(1): 3–12.
161.
ZhangYPrebensenNK (2025) Value co-creation in tourism live shopping. Journal of Business Research186: 114964.
162.
ZhaoXXieCHuangL, et al. (2023) How digitalization promotes the sustainable integration of culture and tourism for economic recovery. Economic Analysis and Policy77: 988–1000.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
