Eloy Gil-Cordero

Purpose: The main objective of this study is to analyse the barriers that limit the adoption of artificial intelligence (AI) in SMEs. To do so, seven risk categories will be examined: functional (FUR), hedonic (HR), security (SR), social (SOR), financial (FR), performance (PR) and psychological (PYR). The choice of these seven categories is based on a comprehensive review of the literature on technology adoption and perceived risks, and these categories are considered to comprehensively capture the main risks associated with AI as perceived by SMEs. Additionally, the influence of factors such as technostress (TE), distrust (DT) and hesitancy (HES) on the adoption process will be investigated. Design/methodology/approach: This study offers a contribution to the analysis of barriers limiting the adoption of AI in small and medium-sized enterprises (SMEs), addressing the problem from a dual methodological approach integrating PLS-SEM and fsQCA techniques. Seven categories of perceived risks (functional, hedonic, security, social, financial, performance and psychological) along with psychological and organisational factors such as technostress, distrust and hesitation were investigated using a representative sample of 395 SMEs. This dual methodological approach allowed us to identify not only significant causal relationships but also complex configurations that determine technological adoption. Findings: The results reveal that distrust is a decisive factor affecting the intention not to adopt AI. This finding highlights the importance of creating strategies that increase trust in automated processes. Functional risk and hedonic risk were also identified as significant barriers, highlighting how perceived usefulness and subjective experience of pleasure influence willingness towards technology adoption. In contrast, financial risk and performance risk were not significant in this research, suggesting that SMEs may be more driven by factors related to knowledge and familiarity with technologies than by strictly economic or performance concerns. These findings challenge previous perceptions and open new perspectives to explore how organisational capabilities modulate technology decisions. Research limitations/implications: The result underlines the need for initiatives that reduce hesitation and effectively communicate the benefits of AI, especially in key sectors of the economy. Taken together, these findings are fundamental for the design of public policies and business strategies aimed at fostering digital transformation in this strategic sector. Practical implications: In terms of managerial implications, the adoption of AI by companies must first face the process of hesitation and distrust. The implementation of these processes must be clearly and accurately disseminated within the business structure, going through a process of proper understanding by managers. Any attempt that does not entail adequate knowledge or that generates a certain degree of hesitation may constitute a major failure that, through an inadequate strategy, will end up affecting the client. Companies providing AI services must develop a comprehensive strategy of enrichment and enhancement of the product, determining not only the advantages of its application in business strategies but also the positive effects on the company's value proposition. Social implications: Differences in the perception of risks, such as financial, functional and psychological risks, may intensify the technology gap between different social groups, especially those with different levels of access to technology education. This could lead to significant disparities in how different sectors of society benefit from AI applications, limiting their inclusive reach and positive impact on the general population. Moreover, there are growing concerns about the impact of AI on employment and labour skills, as the perception that this technology could lead to dependency or replace human functions negatively influences its uptake. Originality/value: This study represents one of the first investigations to comprehensively address the risks associated with the use of AI by firms, and to address the level of direct risk that this represents with respect to their behaviour. The treatment of non-adoption issues is an innovation in the academic approach, allowing for more comprehensive conceptual modelling of findings. This study provides a theoretical basis for a comprehensive analysis of the risks affecting the adoption of AI in firms, marking an academic innovation by focussing the analysis on non-adoption behaviour.

In the context of peer-to-peer accommodation services, Airbnb has emerged as a transformative force in the tourism sector. This study examines whether Airbnb represents a sustainable business model during periods of economic instability. We employed a hybrid analytical framework combining Partial Least Squares Structural Equation Modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze responses from 581 Spanish users. The extended UTAUT2 model incorporated electronic word-of-mouth (e-WOM), trust, and perceived COVID-19 risk as additional predictors of behavioral intention. PLS-SEM results showed that only performance expectancy had a statistically significant effect. In contrast, fsQCA revealed that effort expectancy, hedonic motivation, price-value, e-WOM, and trust are necessary conditions influencing usage intention. This divergence highlights the value of asymmetrical methods like fsQCA in capturing complex behavioral patterns that may not be observable through symmetrical approaches alone, making the two methods highly complementary. From a managerial standpoint, the results suggest that enhancing trust and leveraging e-WOM are vital for sustaining Airbnb’s competitive advantage. The study contributes by integrating two complementary analytical approaches and by modeling intention under crisis conditions. This research offers actionable insights for platform providers and tourism policymakers and sets a precedent for future studies on digital accommodation platforms.

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.

Purpose: To understand the factors that influence Spanish national tourists’ intention to use the metaverse with the integration of constructs of technological adoption and psychographic profiles, and to draw new conceptual and methodological lines concerning immersive virtual reality experiences in the tourism sector. Design/methodology/approach: Nowadays, the travel industry has turned its attention to metaverse systems and the opportunities they offer for tourism experiences that circumvent physical limitations. This research develops a model integrating technology adoption constructs and psychographic profiles determined by the Values and Lifestyles Scale (VALS) to identify the intention of Spanish tourists to use metaverse systems. The model is tested using fsQCA asymmetric methodology and NCA (necessary conditions analysis), developed with fsQCA 3.0 and RStudio v.4.2.2 software, respectively, with data collection from 429 national tourists in Spain. Findings: The results indicate that curiosity and novelty, together with the psychographic dimensions of innovators and intellectuals, are significant antecedents for the intention to use the metaverse. Perceived ease of use of the metaverse, combined with the psychographic dimension of manual skills and a liking for mechanical devices, are the core conditions for intention to use the metaverse, while leaders and conservatives are negated or absent psychographic dimensions. Originality/value: Recent advances in artificial intelligence (AI) have increasingly encouraged people to move their lifestyles into virtual environments while companies in the travel industry prepare for the many opportunities they offer. Although the metaverse promotes social interaction among users, there is a lack of understanding regarding the factors that will affect its intended use by tourists. This gap arises from insufficient conceptual and methodological approaches, as the relationship between individual and social behaviors has not been adequately considered within information systems (IS).

Purpose: Tourism is a dynamic phenomenon that has evolved constantly, generating both positive impacts, such as economic growth and employment opportunities and negative effects, such as environmental degradation and price increases. This study examines the role of metaverse satisfaction as a mediating variable between the perceived positive and negative impacts of tourism development. Design/methodology/approach: The study analyzes data from two culturally similar tourist destinations, Spain and Italy, involving 864 participants. A structural equation modeling approach was employed using SmartPLS software to evaluate the mediating role of metaverse satisfaction in the relationship between tourism impacts and perceptions of development. Findings: The findings confirm that metaverse satisfaction significantly mediates the relationship between positive and negative impacts on tourism development perceptions. This indicates that emerging technologies like the metaverse can mitigate the adverse effects of tourism while enhancing its positive aspects. Originality/value: This study addresses a critical gap in the literature by exploring the intersection of emerging technologies and tourism development, focusing on the metaverse – a novel and under-researched area in the tourism domain. It highlights the potential of the metaverse to act as a mediator, balancing the dual impacts of tourism. Given the increasing challenges posed by overtourism and its effects on local communities, this research provides essential insights into how technological innovations can support more sustainable and equitable tourism practices. The findings offer a unique perspective, emphasizing the urgent need to integrate advanced digital tools into tourism management strategies.

The intersection between border culture and tourism development seems to form an indissoluble relationship. The citizens of the peripheral territories of the Portuguese Algarve and of the Andalusia...

This research explores the key drivers of purchase intention for luxury goods in the new tourism era after the pandemic via constructs associated with the behavior of tourist consumers of luxury goods and the business strategy regarding them. The mixed methodology allowed for a twofold objective with the investigation of purchase intention to clearly establish what the most important determinants that affect purchase intention are, and, secondly, to determine to some extent the order, importance, and combination of these determinants. The PLS-SEM demonstrated price, vanity, communication, and social influence as increasing purchase intention. The QCA analysis evidences value and vanity as the necessary conditions for intention.

In light of the market uncertainty for hospitality and tourism companies caused by COVID-19, which even led to the legal closure of borders, a study model is proposed. Our model considers market uncertainty as a moderator of the principles of business management. This moderator leads to a sustainable competitive advantage through organizational values, participative leadership, market orientation and innovative intensity. The viability of the proposed model has been analyzed with a mixed methodology using the Smart-PLS tool, on the one hand, and two fsQCA-based samples of hospitality and tourism companies located in Spain and South Korea, on the other hand. The results show the relevance of participative leadership supported by organizational values in obtaining a sustainable competitive advantage. This will help the tourism sector to adapt to future health pandemics. Market uncertainty has not affected participative leadership in achieving this sustainable competitive advantage.