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Using Environmental, Social and Governance (ESG) Factors for the promotion of Sustainable Tourism Development

Featuring excerpts from one of my latest article focused on the intersection of ESG performance and the promotion of the sustainable tourism agenda – published through Business Strategy and the Environment:

Suggested citation: Camilleri, M.A. (2025). Environmental, social and governance (ESG) factors for sustainable tourism development: The way forward toward destination resilience and growth, Business Strategy and the Environmenthttps://onlinelibrary.wiley.com/journal/10.1002/bse.70366

1 Introduction

Sustainable tourism is based on the principles of sustainable development (Fauzi 2025). It covers the complete tourism experience, including concerns related to economic, social and environmental issues (Bang-Ning et al. 2025; Wang and Zhang 2025). Its long-term dual objectives are to improve the tourists’ experiences of destinations they visit and to address the needs of host communities (Kim et al. 2024). Arguably, all forms of tourism have the potential to become sustainable if they are appropriately planned, led, organised and managed (Camilleri 2018). Destination marketers and tourism practitioners who pursue responsible tourism approaches ought to devote their attention to enhancing environmental protection within their territories, to mitigating the negative externalities of the tourism industry on the environment and society, to promoting fair and inclusive societies to enhance the quality of life of local residents, to facilitating exposure to diverse cultures, while fostering a resilient and dynamic economy that generates jobs and equitable growth for all (Rasoolimanesh et al. 2023; Scheyvens and Cheer 2022).

Conversely, irresponsible tourism practices can lead to the degradation of natural habitats, greenhouse gas emissions and the loss of biodiversity through air and water pollution from unsustainable transportation options, overconsumption of resources, waste generation and excessive construction (Banga et al. 2022; H. Wu et al. 2024). Indeed, any nation’s overdependence on tourism may give rise to economic difficulties during economic crises, such as increased cost of living for residents, seasonal income and precarious employment conditions, leakage of revenues when profits go to foreign-owned businesses and displacement of traditional industries like fishing and agriculture, among other contingent issues (Mtapuri et al. 2022; Mtapuri et al. 2024).

In addition, tourism may trigger social and cultural externalities like overcrowding and an increased strain on public services, occupational hazards for tourism employees and inequalities due to uneven distribution of benefits, displacement of local communities to give way to tourism infrastructures, the loss of authenticity in local traditions, an erosion of local identities and traditional lifestyles under external influence, as well as increased crime rates or illicit activities (Ramkissoon 2023).

In light of these challenges, this research seeks to provide a better understanding of how environmental, social and governance (ESG) dimensions can be embedded within sustainable tourism, to strengthen long-term destination resilience and economic growth. Debatably, although the use of the ESG dimensions is gaining traction in various corporate suites, their application in tourism and hospitality industry contexts is still limited. Notwithstanding, ESG research is still suffering from inconsistent conceptualisations, measurements and reporting systems (Legendre et al. 2024).

To address this gap, this contribution outlines five interrelated objectives: (1) It relies on a systematic review methodology to investigate the intersection of ESG principles and sustainable tourism; (2) It synthesises the findings and maps thematic connections related to environmental stewardship, social equity and governance structures in tourism destinations; (3) It evaluates ESG-based strategies that address carrying capacity limitations, overtourism, climate vulnerabilities, sociocultural tensions and institutional accountabilities; (4) It advances theoretical insights; and (5) It develops a comprehensive conceptual framework, to guide policymakers, practitioners and stakeholders in embedding ESG considerations into tourism planning and development, thereby promoting environmental sustainability, socioeconomic resilience and corporate governance.

Guided by these objectives, this timely research addresses four central research questions. Firstly, it asks: [RQ1] How have high-impact scholarly works conceptualised and operationalised ESG dimensions in order to promote sustainable travel destinations? Secondly, it seeks to answer this question: [RQ2] What empirical evidence exists on the effectiveness of ESG-aligned strategies in enhancing destination resilience and fostering long-term economic growth? The third question interrogates: [RQ3] What academic implications arise from this contribution, and how might its insights shape the future research agenda? Finally, the study seeks to address this question: [RQ4] How and in what ways are the ESG pillars interacting within sustainable tourism policy and practices? This research question recognises that the ESG dimensions may or may not always align harmoniously with the sustainable tourism agenda.

Although the sustainable tourism literature has often been linked to the United Nations Sustainable Development Goals (SDGs) and to broader corporate social responsibility (CSR) frameworks, the explicit integration of ESG principles into this field is still underdeveloped (Back 2024; Legendre et al. 2024; Lin et al. 2024; Shin et al. 2025). Much of the existing literature examines the environmental, social and governance (E, S and G) dimensions in isolation (Moss et al. 2024), with scholars often addressing, for example, environmental sustainability through climate adaptation strategies or governance via destination management systems, without adequately considering their interdependence or combined impact on tourism outcomes (Comite et al. 2025; Kim et al. 2024). This pattern was clearly evidenced in the findings of this research.

This article synthesises the findings of recent high-impact publications focused on sustainable tourism through the ESG performance lens, in order to advance a holistic conceptual model that bridges academic scholarship and policy application. In sum, this proposed theoretical framework clarifies how environmental stewardship, social inclusivity and governance accountability are shaping sustainable tourism trajectories. In conclusion, it puts forward original theoretical as well as the managerial implications. Theoretically, it enriches the sustainable tourism literature with an ESG-integrated analytical framework grounded in systematic evidence. Practically, it offers an actionable, governance-oriented blueprint that aligns environmental, social and economic objectives for responsible tourism planning and development. Hence, it provides a tangible roadmap that embeds ESG dimensions and their related criteria into sustainable tourism strategies for destination resilience and long-term competitiveness.

2 Background

The evolution of sustainable and responsible tourism paradigms can be traced back to the environmental consciousness that characterised the 1960s and 1970s. At the time, several governments were concerned over the ecological and cultural consequences of mass tourism. Early initiatives, such as the European Travel Commission’s 1973 campaign for environmentally sustainable tourism, sought to mitigate the negative externalities of rapid sector growth. Subsequently, South Africa’s 1996 national tourism policy introduced the concept of responsible tourism, that essentially emphasised community well-being as an integral component of destination management. The United Nations World Tourism Organization (UNWTO) has since positioned sustainable tourism as a catalyst for global development.

Eventually, the declaration of 2017 as the International Year of Sustainable Tourism for Development has underscored its potential to contribute directly to the United Nations SDGs. Specific targets like SDG 8 (decent work and economic growth), SDG 12 (responsible consumption and production), SDG 14 (life below water) and SDG 15 (life on land) highlight the sector’s capacity to create jobs, preserve ecosystems, safeguard cultural heritage and benefit vulnerable economies (Mahajan et al. 2024), particularly in small island states and least developed countries (Grilli et al. 2021). However, an ongoing achievement of these objectives necessitates balancing environmental, social and economic interests, a process that is often complicated by the diverse, and at times conflicting, priorities of a wide array of stakeholders (Civera et al. 2025).

Governments are important actors in this process. They can influence sustainable tourism outcomes through regulation, education, destination marketing and public–private partnerships (Dossou et al. 2023; Mdoda et al. 2024). Generally, their underlying policy rationale is to ensure that tourism development supports long-term economic growth while protecting cultural and natural assets, in order to improve community well-being (Andrade-Suárez and Caamaño-Franco 2020; Breiby et al. 2020). Yet this ambition is often undermined by market pressures, limited institutional capacities and the difficulty of translating high-level sustainability commitments into enforceable measures at the local levels.

In this light, the ESG framework a concept that was popularised by a United Nations Global Compact (2004) report, entitled, “Who Cares Wins”, offers a coherent approach for the integration of environmental stewardship, social equity and institutional accountability for the advancement of responsible tourism planning and development. Hence, in this context, practical tools are required in order to translate inconsistent guiding principles into actionable destination management strategies. For instance, the carrying capacity acts as a practical control mechanism within such a theoretical framework (Mtapuri et al. 2022; O’Reilly 1986). It ensures that tourism figures remain compatible with the preservation of natural, cultural and heritage assets. For the time being, there are challenges as well as opportunities for governments to translate the holistic vision of sustainable tourism policies into robust governance systems that maintain economic vitality and the integrity of their destinations.

4 Results

The thematic analysis indicates that the sustainable tourism concept is interconnected with each of the ESG’s dimensions. The findings suggest that sustainable tourism integrates environmental stewardship, social responsibility and sound governance to advance ecological preservation, community well-being and organisational accountability. Hence, it supports long-term destination resilience. The bibliographic results report that each of the ESG components is not only essential for sustainable tourism but also interdependent pillars that enable the sector to thrive in a responsible manner. Therefore, it is imperative for governments to safeguard natural and cultural heritage, empower local communities and foster transparent and effective governance, to ensure the sustainable development of destinations as well as their economic growth (Chong 2020; Grilli et al. 2021; Mamirkulova et al. 2020). The ESG framework, along with its criteria, serves as an important lens through which stakeholders can shape and evaluate sustainable tourism policies and practices (Işık, Islam, et al. 2025). Table 1 features the most conspicuous themes that emerged from this study. Additionally, it presents definitions for each theme along with illustrative research questions examined by the academic contributions identified in this systematic review.

4.1 The Environmental Dimension of Sustainable Tourism

The tourism industry is dependent on natural ecosystems. Therefore, it is in the tourism stakeholders’ interest to protect the environment and to minimise their externalities (J. S. Wu et al. 2021). There is scope for them to promote the conservation of land and water resources (Sørensen and Grindsted 2021). Water scarcity is a pressing global concern that is amplified in many tourist hotspots (WTTC 2023). However, tourism development and its related infrastructural expansion ought to respect ecological thresholds and preserve green spaces, particularly in urban areas. Hotels, resorts and attractions could implement water-saving technologies such as rainwater harvesting, low-flow fixtures and wastewater recycling (Foroughi et al. 2022). These sustainable measures reduce stress on local water supplies and help preserve aquatic ecosystems. In addition, tourism entities can avail themselves of renewable energy sources like solar panels, wind turbines, et cetera, and may adopt energy-efficient appliances and lighting solutions (Abdou et al. 2020; Zhan et al. 2021).

The rapid growth of tourism has historically been linked to environmental degradation through waste accumulation and pollution (Bekun et al. 2022). Circular economy strategies including improved waste management and pollution control through responsible waste disposal as well as reducing, reusing and recycling certain resources, can help decrease the industry’s externalities, but also create healthier spaces for tourists and staff (Camilleri 2025; Dey et al. 2025; Jain et al. 2024).

Tourism significantly contributes to the generation of greenhouse gas emissions through transportation and accommodation (Kim et al. 2024). Addressing climate change within sustainable tourism is critical to reducing the sector’s ecological footprint and enhancing destination resilience to climate impacts (Comite et al. 2025; Scott 2021). Many tourism businesses invest in carbon offset programs including reforestation, renewable energy projects and community-based conservation as mechanisms to offset their emissions (Banga et al. 2022). Eco-certifications such as Global Sustainable Tourism Council (GSTC), Green Globe, EarthCheck, GreenKey and LEED, among others, encourage the adoption of low-carbon practices. They enable practitioners and consumers to make environmentally conscious choices (Dube and Nhamo 2020; Gössling and Schweiggart 2022). Moreover, green transportation policies can encourage public transit, cycling, walking and the adoption of electric and hybrid vehicles for tourism-related travel, thereby reducing carbon footprints (Kim et al. 2024).

Ecologically sensitive zones such as national parks and marine reserves, which are home to wildlife, fragile species and habitats are some of the most visited places by tourists (Partelow and Nelson 2020; Tranter et al. 2022). Hence, they should be protected from overtourism by implementing visitor limits, buffer zones and conservation fees to reduce human impact (Leka et al. 2022). Restoration projects like reforestation, coral reef rehabilitation and wetland conservation are good examples of proactive environmental stewardship linked to tourism (Herrera-Franco et al. 2020; Muhammad et al. 2021). Environmental sustainability also depends on shaping tourist behaviours and fostering responsible activities like environmental awareness campaigns, community involvement in conservation efforts as well as engagement in low-impact alternatives like birdwatching, hiking and sustainable diving, among other stewardship practices (Khuadthong et al. 2025; J. S. Wu et al. 2021).

4.2 The Social Dimension of Sustainable Tourism

Sustainable tourism outcomes extend beyond environmental stewardship principles. Its social dimension encompasses criteria related to the preservation of cultural heritage; community engagement and empowerment; social equity, inclusion and cohesion; as well as responsible tourist behaviours, among other aspects (Bellato et al. 2023; Bianchi and de Man 2021; Joo et al. 2020a; Xu et al. 2020; Yang and Wong 2020; Rasoolimanesh et al. 2023). Sustainable tourism practices are clearly evidenced through improved relationships between tourists and local host communities, resulting in tangible benefits to both parties (Ramkissoon 2023).

The tourism industry can be considered a catalyst for cultural appreciation as well as a threat to cultural authenticity (Bai et al. 2024; H. Wu et al. 2024). Therefore, host destinations need to safeguard their cultural heritage, historical landmarks and monuments. Regulations and visitor management policies ought to be in place to limit wear and degradation of archaeological and religious sites, as well as historically important buildings and architectures (Mamirkulova et al. 2020). The social dimension of sustainable tourism entails that destination marketers preserve their cultural heritage and authenticity. They may do so by showcasing indigenous tastes and aromas of the region, including local foods and wines, and by promoting traditional music, dance, arts, crafts, et cetera, to appeal to international visitors (Andrade-Suárez and Caamaño-Franco 2020). This helps them keep their cultural legacy and maintain a competitive edge (Bellato et al. 2023). As a result, incoming tourists would be in a better position to appreciate local customs and folklore. Notwithstanding, their behaviours can play a crucial role in shaping social dynamics within destinations, as their activities might support community well-being and promote equitable access to tourism benefits (Mamirkulova et al. 2020).

However, policymakers are expected to manage visitor flows within a destination’s carrying capacity to prevent overcrowding, and to avoid social tensions, while fostering inclusivity, mutual respect and positive interactions between visitors and host communities (Back 2024; Koens et al. 2021). Perhaps, destination management organisations should educate visitors about cultural sensitivity issues to demonstrate their respect to host communities (Foroughi et al. 2022; Joo et al. 2020b; Mdoda et al. 2024). For example, they may raise awareness of appropriate behaviours in specific contexts, including dress codes and etiquette to mitigate cultural clashes, discourage exploitative tourism practices like invasive photography in certain settings and prevent unethical animal encounters, in order to foster mutual respect, enhance positive exchanges and safeguard community values (Ghaderi et al. 2024).

The sustainable tourism concept encourages participatory tourism planning. It prioritises the empowerment of indigenous communities in tourism decision-making and policy formulation (Ramkissoon 2023). The involvement of local residents may require capacity building to equip them with relevant skills to participate in the tourism sector, and to foster their economic advancement (Mamirkulova et al. 2020). The proponents of sustainable tourism frequently refer to the provision of fair employment opportunities, including for native populations, in terms of equitable wages and salaries, as well as decent working conditions, in order to enhance community livelihoods and social cohesion (Mtapuri, Camilleri, et al. 2022). Very often, they report that destinations would benefit from sustainable tourism practices that build social capital and reduce economic leakage, by incentivising local entrepreneurs and community-based tourism initiatives to ensure that financial returns remain within the community (Chong 2020; Partelow and Nelson 2020).

The systematic review postulates that the sustainable tourism concept is meant to promote social justice and reduce inequalities (Bianchi and de Man 2021). The extant research confirms that it fosters social inclusivity across various demographic groups in society by supporting gender equality, thereby enriching the sector’s diversity (Bellato et al. 2023; A. Khan et al. 2020). The industry’s labour market may include individuals hailing from different backgrounds in society, including young adults, women, senior citizens, immigrants and disabled people (Bianchi and de Man 2021; Camilleri et al. 2024). Tourism businesses are encouraged to develop infrastructures and services that accommodate people with accessibility requirements in order to broaden their destinations’ reach and social value (Sisto et al. 2022).

4.3 The Governance Dimension in Sustainable Tourism

The integration of environmental and social dimensions of sustainable tourism ultimately depends on transparent, accountable and participatory governance mechanisms (Joo et al. 2020b; Putzer and Posza 2024). Effective governance provides the institutional framework through which environmental stewardship and social responsibility are translated into actionable policies, coordinated initiatives and measurable outcomes (Back 2024; Ivars-Baidal et al. 2023).

Governments are entrusted to set the foundation for sustainable tourism through national and local tourism policies that clearly define sustainability goals, action plans and regulatory measures (Gössling and Schweiggart 2022). Such policies may be related to environmental and/or social regulations. They may enforce environmental impact assessments (EIAs), zoning laws and they could be meant to protect cultural heritage (Farsari 2023). Moreover, they may be intended to encourage or incentivise environmental sustainability practices (e.g., through eco-label or certification schemes) (Bekun et al. 2022). Alternatively, they may be focused on the destinations’ carrying capacity limits and/or on their overtourism aspects, if they specify visitor limits, and/or refer to taxes, levies or fees imposed on visitors or tourists (Leka et al. 2022).

Sustainable tourism governance depends on multisector cooperation (Farsari 2023) that may usually involve government departments and agencies, the private sector that may comprise accommodation service providers, airlines, tour operators, travel agencies as well as local communities, NGOs and international organisations, among others. Policymakers need to balance diverse stakeholders’ interests and to instil their shared responsibilities (Siakwah et al. 2020). Good governance can ultimately ensure that public–private partnerships would translate to long-term, sustainable tourism strategies related to responsible planning and development that consider specific socioenvironmental aspects of destinations: green building standards and the use of renewable energy, and/or emergency and crisis management issues (Scheyvens and Cheer 2022).

Policymakers are expected to conduct regular assessments and evaluations of tourism practitioners’ environmental, social and economic outcomes operating in their jurisdictions. They need to scrutinise corporate ESG disclosures, particularly in certain domains (e.g., in European contexts, where they ratified the corporate sustainability reporting directive) (Camilleri 2025). Governments should monitor business practices to safeguard their employees’ well-being, environmental sustainability and the communities’ interests (Putzer and Posza 2024). They may avail themselves of sustainability indicators and benchmarking tools such as GSTC’s criteria that are used to measure progress in sustainable tourism, in terms of sustainable management (planning, monitoring, governance); socioeconomic benefits to the local community, cultural heritage preservation and environmental protection (Wang and Zhang 2025). Such responsible and ethical practices increase trust and lead to continuous improvements in the tourism industry.

Discussion

The holistic integration of environmental, social and governance dimensions in sustainable tourism collectively contributes to enhance destination resilience and sustainable economic growth. The conservation of natural attractions such as beaches, forests and coral reefs will enable destinations to remain competitive. Therefore, there is scope in implementing climate-friendly measures, including reforestation and sustainable water management, among others, to reduce vulnerability to floods and storms. At the same time, they may curb ocean-level increases. Pollution prevention, waste minimization and circular economy strategies can help destinations maintain environmental quality, that is crucial for their ongoing tourism appeal. Notwithstanding, eco-certifications of responsible destinations can attract environmentally conscious travelers, who may be willing to pay more to visit sustainable tourism destinations.

The effectiveness of eco-certifications is amplified when combined with socially responsible practices. The integration of community empowerment, cultural heritage preservation, and social inclusiveness into tourism planning and development can contribute to increasing the sustainability of a destination. Hence, the tourism industry could add value to the environment as well as to local communities. By aligning sustainable development with local priorities and by promoting responsible tourism practices, destinations can provide authentic cultural and heritage experiences, thereby enhancing their visitor satisfaction and revisit intentions, in the future. In turn, this reinforces both market differentiation and long-term social resilience. Furthermore, as entrepreneurship flourishes, the local communities would benefit from circulating incomes and reduced economic leakages. Such outcomes are conducive to tourism growth.

However, policymakers must implement effective tourism governance to ensure that these economic gains are sustainable. Transparent governance fosters trust among stakeholders and facilitate sustainable growth and competitiveness. By implementing strategic planning and regulations, local authorities can ensure that tourism development| does not overwhelm infrastructure or degrade natural and cultural assets. This creates a balanced environment where entrepreneurship and community benefits coexist with long-term destination resilience. Therefore, sound governance prevents over-tourism and unmanaged expansion, whilst protecting the destinations’ assets. Robust tourism governance frameworks foster stable policy environments, attract further investments and enable long-term planning. Additionally, strong crisis management capabilities can equip destinations to handle unforeseen circumstances including pandemics, natural disasters and economic shocks.

The above analysis underlines that environmental, social and governance dimensions are deeply interlinked to one another and mutually-reinforcing within sustainable tourism. An integrative ESG approach conceptualizes sustainable tourism as a synergistic framework that reconciles ecological integrity, social equity, and institutional effectiveness, as illustrated in Figure 1.

Theoretical implications

This study adds value to the growing body of literature focused on sustainable tourism governance (Gössling & Schweiggart, 2022; Işık et al., 2025; Rasoolimanesh et al., 2023). It clearly identifies key theoretical underpinnings of articles focused on the intersection of ESG dimensions and sustainable tourism practices. The bibliographic findings suggest that the stakeholder theory (Bellato et al., 2023; Ivars-Baidal et al., 2023; Matsali  et al., 2025; Mdoda  et al., 2024) and the institutional theory (Bekun et al., 2022; Dossou et al., 2023; Hall et al., 2020; Saarinen, 2021; Zhan et al., 2021) shed light on the role of government policies, corporate responsibility and community engagement in shaping the sustainable tourism agenda and different settings (Lin et al., 2024; Zhang et al., 2025). Interestingly, the Social Identity Theory clarifies how various stakeholder groups, including residents, tourists and industry practitioners, are aligning their behaviors with shared norms and identities that promote corporate ESG values (Yang & Wong, 2020). Drawing on Cognitive Appraisal Theory, it indicates that stakeholders’ evaluation of ESG-related risks and opportunities influences their emotional responses and subsequent engagement in sustainability initiatives (Foroughi et al., 2022). The Theory of Empowerment further explains how participatory governance and transparent decision-making can enhance community agency, fostering stronger local support for ESG-driven tourism strategies (Joo et al., 2020a).

In line with the Theory of Planned Behavior and the Attitude–Behavior–Context (ABC) Theory, the findings highlight that pro-sustainability intentions are by attitudes toward ESG as well as by perceived behavioral control and contextual enablers such as policy frameworks and market incentives (Joo et al., 2020b; Khuadthong et al., 2025; Wu et al., 2021). Moreover, the Value–Belief–Norm Theory demonstrates how environmental values and moral obligations underpin behavioral commitments to ESG-aligned tourism (Kim et al., 2024).

From a governance perspective, the Evolutionary Governance Theory clarifies how institutional arrangements, stakeholder relationships and regulatory norms adapt over time to embed ESG principles in tourism planning (Partelow & Nelson, 2020). The review suggests that tourism stakeholders’ decision-making including during uncertain situations, can be enriched through Decision Theory and by referring to the Interval-Valued Fermatean Fuzzy Set approach (Rani et al., 2022). These theories enable robust, data-informed prioritization of ESG objectives.

Furthermore, the findings underscore the recursive relationship between the human agency and the structural constraints. The results suggest that stakeholder actions can influence ESG governance systems. This argumentation is congruent with the Structuration Theory (Saarinen, 2021). Meanwhile, the Resource-Based View (Wang & Zhang, 2025; Zhu et al., 2021) and Dynamic Capabilities Theory (Wang & Zhang, 2025) frame ESG adoption as a strategic asset, where unique sustainability capabilities can enhance competitive advantage and long-term destination resilience.

Managerial implications

This research yields clear implications for policymakers, industry practitioners and local communities of tourist destinations. It postulates that the ESG dimensions can provide these stakeholders with a strategic framework to balance growth with long-term resilience. It confirms that ESG policies necessitate a comprehensive approach, that combines environmental conservation, social inclusion, and responsible governance considerations, rather than addressing them individually. Arguably, there may be variations in the importance, focus and implementation of ESG dimensions in tourism, in different contexts, due to the host countries’ economic capacities regulatory frameworks, social priorities and/or environmental challenges. As a result, the effects or outcomes of ESG initiatives are not uniform across destinations (Lin et al., 2024).

In addition, the size of the businesses can also influence their commitment to account and disclose ESG-related aspects of their performance. Large multinational travel and hospitality firms could benefit from economies of scale, in terms of greater financial, human, and technological resources, resulting in their ESG alignment and compliance with societal norms and regulatory frameworks. They can afford dedicated sustainability teams, advanced data management tools, and external consultants to ensure accurate measurement, benchmarking and disclosure of ESG performance. In stark contrast, the smaller firms may face resource constraints, limited expertise, and higher relative costs for data collection and reporting. Such non-commercial activities can hinder their ability to systematically track, measure and communicate ESG performance, placing them at a comparative disadvantage, relative to their larger counterparts.

From an environmental perspective, policy makers should operationalize carrying capacity thresholds and implement adaptive management systems to safeguard ecosystems, optimize resource utilization, and enhance climate resilience. Continuous monitoring and evaluation of environmental impacts are essential to ensure that tourism activities remain within sustainable limits. Proactive interventions including the promotion of low-carbon transportation, the adoption of renewable energy, efficient resource management, and waste reduction are critical for aligning tourism development with ESG objectives. Such strategies preserve biodiversity and can contribute to the long-term sustainability of destinations.

The social dimension emphasizes the equitable distribution of tourism benefits and the preservation of cultural integrity. Overtourism threatens community well-being through inflated living costs, cultural commodification and resident–visitor tensions. Hence, managers should foster participatory governance structures that empower local communities, entrepreneurs and cultural custodians in decision-making processes. Technological innovations including artificial intelligence (AI) solutions that monitor visitor flows can further support socially responsible destination management. At the same time, stakeholder engagement ensures that tourism operations retain their legitimacy in society.

Robust governance mechanisms underpin these strategies. Practitioners can align policies with international sustainability standards in order to facilitate transparent accountability. The implementation of ESG performance indicators, enforceable visitor limits and adaptive regulatory measures, such as dynamic pricing or quotas enable evidence-based decision-making and continuous improvements in responsible destinations. The strengthening of institutional capacities and local skills ensures that governance frameworks are effective and sustainable over time.

Financial innovation is essential for sustainable tourism development. Policy makers ought to invest in green technologies and infrastructures to protect the natural environment from externalities. They can provide incentives and funds to support practitioners in their transition to long-term sustainability. By embedding ESG principles, destinations are in a better position to enhance their resilience to environmental and social shocks, strengthen their reputation and image, whilst maintaining their competitiveness in the global tourism market.

Policymakers are encouraged to increase their enforcement of regulations to trigger responsible behaviors. At the same time, they need to nurture relationships with stakeholders. The hoteliers should embed social innovations and environmentally sustainable practices into core strategies and operations. As for local communities, it is in their interest to actively participate in tourism planning and development, to ensure they preserve their cultural heritage and share tourism benefits in a fair manner. Collectively, this contribution’s integrated ESG approach positions destinations for sustained economic growth while safeguarding environmental and social well-being.

Conclusion

This article reinforces the significance of integrating ESG principles into sustainable tourism strategies. By addressing environmental concerns, fostering social inclusivity, improving governance frameworks, and ensuring economic viability, stakeholders can contribute to a more resilient and responsible tourism sector. This research demonstrates that sustainable tourism is most effectively achieved through the integration of environmental, social, and governance (ESG) dimensions, which together foster long-term destination resilience and economic growth. Environmentally, sustainable tourism requires the preservation of natural ecosystems, efficient resource use, and proactive measures to reduce pollution and greenhouse gas emissions. Practices such as water-saving technologies, renewable energy adoption, waste reduction, and circular economy strategies not only mitigate ecological impacts but also enhance the attractiveness and competitiveness of destinations.

From a social perspective, sustainable tourism supports community empowerment, cultural preservation, inclusivity, and social equity. By engaging local residents in planning and decision-making, promoting equitable employment, and safeguarding cultural heritage, destinations can foster positive resident–visitor interactions and enhance the overall visitor experience. Responsible tourist behavior, participatory governance, and cultural sensitivity further reinforce social cohesion while ensuring that tourism benefits are broadly shared within host communities.

Effective governance underpins both environmental and social outcomes by providing transparent, accountable, and coordinated frameworks for sustainable tourism. Policymakers and destination managers play a critical role in enforcing regulations, monitoring ESG performance, and balancing stakeholder interests. Multi-sector collaboration, the application of sustainability indicators, and adaptive management strategies enable destinations to anticipate and respond to environmental, social, and economic shocks.

Collectively, the ESG approach positions sustainable tourism as a synergistic model that aligns ecological integrity, social responsibility, and institutional effectiveness. By embedding ESG principles into core strategies, destinations can deliver unique, high-quality experiences, strengthen community livelihoods, and maintain global competitiveness. This integrative framework demonstrates that environmental stewardship, social equity, and sound governance are mutually reinforcing, offering a pathway for destinations to achieve enduring sustainability, resilient growth, and enhanced market differentiation.

The full paper is available here:

Researchgate: https://www.researchgate.net/publication/397949208_Environmental_social_and_governance_ESG_factors_of_sustainable_tourism_development_The_way_forward_toward_destination_resilience_and_growth

Academia: https://www.academia.edu/145139975/Environmental_social_and_governance_ESG_factors_for_sustainable_tourism_development_The_way_forward_toward_destination_resilience_and_growth

Open Access Repository @University of Malta: https://www.um.edu.mt/library/oar/handle/123456789/141666

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The use of Generative AI for travel and tourism planning

📣📣📣 Published via Technological Forecasting and Social Change.

👉 Very pleased to share this timely article that examines the antecedents of the users’ trust in Generative AI’s recommendations, related to travel and tourism planning.

🙏 I would like to thank my colleagues (and co-authors), namely, Hari Babu Singu, Debarun Chakraborty, Ciro Troise and Stefano Bresciani, for involving me in this meaningful research collaboration. It’s been a real pleasure working with you on this topic!

https://doi.org/10.1016/j.techfore.2025.124407

Highlights

  • •The study focused on the enablers and the inhibitors of generative AI usage
  • •It adopted 2 experimental studies with a 2 × 2 between-subjects factorial design
  • •The impact of the cognitive load produced mixed results
  • •Personalized recommendations explained each responsible AI system construct
  • •Perceived controllability was a significant moderator

Abstract

Generative AI models are increasingly adopted in tourism marketing content based on text, image, video, and code, which generates new content as per the needs of users. The potential uses of generative AI are promising; nonetheless, it also raises ethical concerns that affect various stakeholders. Therefore, this research, which comprises two experimental studies, aims to investigate the enablers and the inhibitors of generative AI usage. Studies 1 (n = 403 participants) and 2 (n = 379 participants) applied a 2 × 2 between-subjects factorial design in which cognitive load, personalized recommendations, and perceived controllability were independently manipulated. The initial study examined the probability of reducing the cognitive load (reduction/increase) due to the manual search for tourism information. The second study considers the probability of receiving personalized recommendations using generative AI features on tourism websites. Perceived controllability was treated as a moderator in each study. The impact of the cognitive load produced mixed results (i.e., predicting perceived fairness and environmental well-being), with no responsible AI system constructs explaining trust within Study 1. In study 2, personalized recommendations explained each responsible AI system construct, though only perceived fairness and environmental well-being significantly explained trust in generative AI. Perceived controllability was a significant moderator in all relationships within study 2. Hence, to design and execute generative AI systems in the tourism domain, professionals should incorporate ethical concerns and user-empowerment strategies to build trust, thereby supporting the responsible and ethical use of AI that aligns with users and society. From a practical standpoint, the research provides recommendations on increasing user trust through the incorporation of controllability and transparency features in AI-powered platforms within tourism. From a theoretical perspective, it enriches the Technology Threat Avoidance Theory by incorporating ethical design considerations as fundamental factors influencing threat appraisal and trust.

Introduction

Information and communication technologies have been playing a key role in enhancing the tourism experience (Asif and Fazel, 2024; Salamzadeh et al., 2022). The tourism industry has evolved as a content-centric industry (Chuang, 2023). It means the growth of the tourism sector is attributed to the creation, distribution, and strategic use of information. The shift from the traditional model of demand–driven to the content-centric model represents a transformation in user behaviour (Yamagishi et al., 2023; Hosseini et al., 2024). Modern travellers are increasingly dependent on user-generated content to decide on their choices and travel planning (Yamagishi et al., 2023; Rahaman et al., 2024). The content-focused marketing approach in tourism emphasizes the role of digital tools and storytelling to assist in creating a holistic experience (Xiao et al., 2022; Jiang and Phoong, 2023). From planning a trip to sharing cherished memories, content helps add value to the travellers and tourism businesses (Su et al., 2023). For example, MakeMyTrip (MMT) integrated generative AI trip planning assistant which facilitates conversational bookings assisting the users with destination exploration, in-trip needs, personalized travel recommendations, summaries of hotel reviews based on user content and voice navigation support positioning the MMT’s platform more inclusive to the users. The content marketing landscape is changing due to the introduction of generative AI models that help generate text, images, videos, and interesting code for users (Wach et al., 2023; Salamzadeh et al., 2025). These models assist in expressing the language, creativity, and aesthetics as humans do and enhance user experience in various industries, including travel and tourism (Binh Nguyen et al., 2023; Chan and Choi, 2025; Tussyadiah, 2014).

Gen AI enhances natural flow of interactions by offering personalized experiences that align with consumer profiles and preferences (Blanco-Moreno et al., 2024). Gen AI is gaining significant momentum for its transformative impact within the tourism sector, revolutionizing marketing, operations, design, and destination management (Duong et al., 2024; Rayat et al., 2025). Accordingly, empirical studies suggest that Generative AI has the potential to transform tourists’ decision-making process at every stage of their journey, demonstrating a significant disruption to conventional tourism models (Florido-Benítez, 2024). Nonetheless, concerns have been raised about the potential implications of generative AI models, and their generated content might possess inaccurate or deceptive information that could adversely impact consumer decision-making (Kim et al., 2025a, Kim et al., 2025b). In its report titled “Navigating the future: How Generative Artificial Intelligence (AI) is Transforming the Travel Industry”, Amadeus highlighted key concerns and challenges in implementation Gen AI such as data security concerns (35 %), lack of expertise and training in Gen AI (34 %), data quality and inadequate infrastructure (33 %), ROI concerns and lack of clear use cases (30 %) and difficulty in connecting with partners or vendors (29 %). Therefore, the present study argues that with the intuitive design, the travel agents could tackle the lack of expertise and clear use of Gen AI. The study suggests that for travel and tourism companies to build trust in Gen AI, they must tackle the root causes of user apprehension. This means addressing what makes users fear the unknown, ensuring they understand the system’s purpose, and fixing problems with biased or poor data. Also, previous studies highlighted how the integration of Gen AI and tourism throws certain issues such as misinformation and hallucinations, data privacy and security, human disconnection, and inherent algorithmic biases (Christensen et al., 2025; Luu et al., 2025). Moreover, if Gen AI provides biased recommendations, the implications are adverse. If the users perceive that the recommendations are biased, they avoid using them, leading to high churn and abandoning platforms (Singh et al., 2023). Users’ satisfaction will decline, replaced by frustration and anger as biased output damages the promise of personalized services. This negatively impacts brand reputation and loss of significant market competitive advantage (Wu and Yang, 2023). Such scenarios will likely lead to stricter regulations, mandatory algorithmic audits, and new consumer protection laws forcing the industry to prioritize fairness as well as explainability to avoid serious consequences. Interestingly, research studies draw attention to an interesting paradox, that consumers are heavily relying on AI-generated travel itineraries, even when they are aware of Gen AI’s occasional inaccuracies (Osadchaya et al., 2024). This reliance might stem from a belief that AI’s perceived objectivity and capacity for personalized recommendations indicate a significant transformation of trust between human and non-human agents in the travel decision-making process (Kim et al., 2023a, Kim et al., 2023b). Empirical findings indicate that AI implementation in travel planning contributes to the objectivity of the results, effectively mitigates cognitive load, and supports higher levels of personalization aligned with user preferences (Kim et al., 2023a, Kim et al., 2023b). Despite the growing body of literature explaining the role of trust in Gen AI acceptance and its influence on travellers’ decision making and behavioural intentions, the potential biases in AI-generated content continue to pose challenges to users’ confidence (Kim et al., 2021a, Kim et al., 2021b). Therefore, this research aims to examine the influence of generative AI in tourism on consumers’ trust in AI technologies, particularly their balance between technological progress and ethical responsibility, concerning the future of tourism (Dogru(Dr. True et al., 2025).

Existing research has focused more on the technology of AI as a phenomenon rather than translating those theories into studies on how the ethics involved would affect perceptions and trust (Glikson and Woolley, 2020). In addition, there is still the black box phenomenon, which is the inability of the user to understand what happens in AI. It also emphasizes the need for more integrative studies between morally sound AI development, user trust, and design in tourism (Tuo et al., 2024).

Moreover, scant research has examined the factors that inhibit tourists from embracing Generative AI technologies, resulting in limited understanding of travellers’ reluctance to Generative AI adoption for travel planning (Fakfare et al., 2025). Despite a growing body of literature examining the antecedents and outcomes of Generative AI (GAI) adoption, large body of research has been based on established frameworks such as Information Systems Success (ISS) model (Nguyen and Malik, 2022), Technology Acceptance Mode; (TAM) (Chatterjee et al., 2021), and the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh, 2022).

However, the extensive reliance on traditional acceptance models might face the risk of ignoring the critical socio-technical aspects, which are paramount in the context of GAI (Yu et al., 2022). While most of the studies explore the overarching effects of user acceptance and use of GenAI using TAM, UTAUT, and Delone and McLean IS success models, there has been a lack of consideration of ethical factors as well as responsible AI systems. Addressing these gaps could significantly broaden our theoretical understanding of how individuals evaluate and adopt generative AI technologies within users’ ethical behaviour and socio-technical perspective.

Therefore, this research aims to fill this gap by investigating factors that facilitate or inhibit trust in generative AI systems, considering responsible AI and Technology Threat Avoidance Theory, and advancing the following research questions:

RQ1

How does the customer experience of using generative AI in tourism reflect the impact of enablers (such as responsible AI systems) and inhibitors (such as ambiguity and anxiety) on trust in generative AI?

RQ2

Does perceived controllability moderate the enablers and inhibitors of trust in generative AI in tourism?

This research includes responsible AI principles and the technology threat avoidance theory to explicate the relationship between generative AI and trust in tourism. Seen from the conceptual lens of Ethical Behaviours, responsible AI principles are crucial for enhancing trust in Gen AI within tourism (Law et al., 2024). When users perceive Gen AI recommendations as fair, transparent, and bias-free, they are more likely to perceive the systems as trustworthy, which in turn mitigates user skepticism and promotes trust (Ali et al., 2023). Also, when Gen AI promotes sustainable and environmentally friendly practices, it demonstrates ethical responsibility and enhances trust in alignment with shared social values (Díaz-Rodríguez et al., 2023). By operationalizing responsible AI principles like transparency, fairness, and sustainability, Gen AI transforms from a black-box tool into a more trustworthy and responsible system for travel decisions (Kirilenko and Stepchenkova, 2025). From the socio-technical perspective, the Technology threat avoidance theory (TTAT) supports the logic of how perceived ambiguity and perceived anxiety act as inhibitors of trust. In tourism, users’ experience holds paramount importance (Torkamaan et al., 2024). When users encounter Gen AI content that is difficult to comprehend, recommendations are unstable or ambiguous, and users’ data is exposed to privacy concerns, these apprehensions will turn into a threat to using Gen AI (Bang-Ning et al., 2025). According to TTAT, when users perceive a greater threat, they are more inclined to engage in avoidance behaviours, which also erodes trust in the system. Hence, TTAT explains why users might hesitate or avoid using Gen AI tools, even if they offer functional benefits such as personalized recommendations and reduced cognitive load (Shang et al., 2023).

The study adopted an experimental research design that would help us to explore the independent phenomenon (use of Gen AI for content generation) and observe and explain its role to establish a cause-and-effect relationship between factors of responsible AI systems and TTAT (Leung et al., 2023). The experimental setting helps us to understand the differences empirically between human and non-human generated content from users’ travel decision-making perspective towards destinations. The study enriched the literature on both the ethical aspects and environmental aspects (perceived fairness and environmental well-being) and the perceived risks (perceived ambiguity and perceived anxiety) perspective in the tourism context. The situation of perceived controllability as a moderator is tested in the literature, offering help to managers on how to develop AI systems responsible for lowering user fear and building trust. The study also facilitated practitioners in understanding how the personalized recommendations & cognitive load facilitated by Gen AI in content generation impact the Gen AI Trust of the tourists.

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Section snippets

Responsible AI systems

Responsible AI adequately incorporates ethical aspects of AI system design and implementation and ensures that the systems are transparent, fair, and responsible (Díaz-Rodríguez et al., 2023). Responsible AI includes ethical, transparent, and accountable use of artificial intelligence systems, ensuring they are fair, secure, and aligned with societal values. It is also an approach to design, develop, and deploy AI systems so that they are ethical, safe, and trustworthy. It is a system that

Cognitive load, personalized recommendations, and perceived fairness

Cognitive load is the mental effort to process and choose information (Islam et al., 2020). A cognitive load can also be high when people interact with complex systems such as AI. Thus, high cognitive load may affect the ability of users to judge whether the AI-based decisions can be considered fair, since they may not grasp enough of the workings of the system and its specific decisions (Westphal et al., 2023). On the other hand, whereas perceived fairness refers to the users’ feelings about

Research methods and analysis

The experiments adopted in this study are scenario-based. Participants’ emotions cannot be manipulated easily in an ethical manner (Anand and Gaur, 2018). Also, the scenario-based approach helps test the causal relationship between constructs used for experimentation in a given scenario. This approach also reduces the minimal interference from extraneous variables. In this method, respondents answered questions based on hypothetical scenarios developed in each scenario. Therefore, scenarios

Discussion

Study 1 shows that cognitive load is detrimental to an individual’s notion of justice or environmental wellbeing, indicating that such factors may be difficult for a user to rate properly based on expending greater cognitive effort. However, cognitive load can also limit the extent of open-mindedness and critical evaluation of AI-assisted communication (T. Li et al., 2024), which could leave people resorting to mental shortcuts or simple fairness and environmental fairness issues. Under such

Theoretical implications

Trust is an important element in the design of organizations and systems, and the current study’s theoretical implications extend the understanding of trust in generative AI systems by integrating constructs of responsible AI and Technology Threat Avoidance Theory. This research underscores the significance of moral factors in creating and using AI systems by exploring relationships between perceived justice, environmental concern, and trust. In this context, the study notes that the degree of

Practical implications

To develop and retain users’ confidence, professionals in the field should observe responsible AI principles, particularly perceived equity and ecological sustainability. It is possible for consumers to be amused by and trust that AI recommendations are perceived as fair. This involves developing algorithms that align with users’ interests while promoting green aspects in AI. It also becomes important for management to note that during AI interface design, cognitive load should be considered so 

Limitations and future research

This study has certain limitations. First, the use of self-reported measures could pose certain biases, as the participants’ experiences with generative AI or social desirability could affect their judgment. The reliance on self-reported data introduces potential biases from participants’ prior engagements with generative AI, social desirability bias, or limited technological competence. Secondly, focusing on a particular context (i.e., tourism) can be seen as a limitation when it comes to

Conclusion

A thorough examination of advancing artificial intelligence in the tourism industry draws attention to the fact that there is no way of avoiding the issue of encouraging responsible AI use. Extending user satisfaction with rhetoric based on AI suggests that user perceptions are not only shaped by the quality of the recommendations but also by the ethical implications of the system and users’ affective states. A range in the effect of personalized suggestions on some parameters that influenced

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Call for papers: Community-driven (Social) Innovation in Collaborative Ecosystems

I am delighted to share this call for papers for the European Academy of Management’s (EURAM2026’s) SIG01: Business for Society (B4S).

My colleagues, Mario Tani, University of Naples Federico II, Naples, Italy; Gianpaolo Basile, Università Telematica Universitas Mercatorum, Rome, Italy; Ciro Troise, University of Turin, Turin, Italy; Maria Palazzo, Università Telematica Universitas Mercatorum, Rome, Italy; Asha Thomas, Wrocław University of Science and Technology AND I, are guest editing a track entitled: “Relationships, Values, and Community-driven (Social) Innovation in Collaborative Ecosystems” (T01-14).

We are inviting conceptual, empirical and methodological papers on the interplay between open innovation, digital platforms and the power of the crowd in navigating today’s grand challenges.

“This track explores the strategic shift from firm-centric models to dynamic, collaborative ecosystems. We examine how deep stakeholder engagement, shared values, and community-driven innovation can generate sustainable economic, social, and environmental value”.

Further details about this conference track are available here: https://lnkd.in/djN8KpDw [T01-14].

Keywords: EURAM2026; Business For Society B4S; Collaborative Ecosystems; Open Innovation Community Driven Innovation; Stakeholder Engagement; Digital; Digital Platforms; Digital Transformation; Crowdsourcing; Sustainable Development Goals (SDGs); UNSDGs; SDG9 [Industry, Innovation And Infrastructure]; SDG11 [Sustainable Cities And Communities]; SDG12 [Responsible Consumption And Production]; SDG17 [Partnerships For The Goals].

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My contribution as foreign expert reviewer

I have just returned back to base after a productive two-day foreign expert meeting.

Once again, it was a positive experience to connect with European academic colleagues, to review and discuss research proposals worth thousands of Euros.

My big congratulations go to the successful scholars who passed the shortlisting phase, based on our evaluation scores.

The best proposals will eventually receive national government funds for transformative projects that will add value to society and the natural environment.

#Academia #AcademiaService #ForeignExpert #ForeignExpertReviewer #Review #AcademicReviewer #ResearchProposal #ResearchProjects

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Scaling up small enterprises: What’s the growth formula?

Pleased to share that I have recently coauthored an open-access article about the growth hacking capabilities of small and medium-sized enterprises (SMEs). It has been published in collaboration with my Italian colleagues from the University of Turin, via the Journal of Business Research.

Our research confirms that SMEs can leverage their growth potential through return-generating investments in disruptive innovations and by harnessing big data analytics. In sum, it suggests that core competencies, resources, and capabilities in these areas, can enhance the SMEs’ financial and operational performance.

READ FURTHER: The full paper can be accessed here: https://www.sciencedirect.com/science/article/pii/S0148296325001110

Suggested citation: Giordino, D., Troise, C., Bresciani, S. & Camilleri, M.A. (2025). Growth hacking capability: Antecedents and performance implications in the context of SMEs, Journal of Business Research, 192, https://doi.org/10.1016/j.jbusres.2025.115288 

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Users’ perceptions and expectations of ChatGPT

Featuring an excerpt and a few snippets from one of my latest articles related to Generative Artificial Intelligence (AI).

Suggested Citation: Camilleri, M.A. (2024). Factors affecting performance expectancy and intentions to use ChatGPT: Using SmartPLS to advance an information technology acceptance framework, Technological Forecasting and Social Changehttps://doi.org/10.1016/j.techfore.2024.123247


The introduction

Artificial intelligence (AI) chatbots utilize algorithms that are trained to process and analyze vast amounts of data by using techniques ranging from rule-based approaches to statistical models and deep learning, to generate natural text, to respond to online users, based on the input they received (OECD, 2023). For instance, Open AI‘s Chat Generative Pre-Trained Transformer (ChatGPT) is one of the most popular AI-powered chatbots. The company claims that ChatGPT “is designed to assist with a wide range of tasks, from answering questions to generating text in various styles and formats” (OpenAI, 2023a). OpenAI clarifies that its GPT-3.5, is a free-to-use language model that was optimized for dialogue by using Reinforcement Learning with Human Feedback (RLHF) – a method that relies on human demonstrations and preference comparisons to guide the model toward desired behaviors. Its models are trained on vast amounts of data including conversations that were created by humans (such content is accessed through the Internet). The responses it provides appear to be as human-like as possible (Jiang et al., 2023).

GPT-3.5’s database was last updated in September 2021. However, GPT-4.0 version comes with a paid plan that is more creative than GPT-3.5, could accept images as inputs, can generate captions, classifications and analyses (Qureshi et al., 2023). Its developers assert that GPT-4.0 can create better content including extended conversations, as well as document search and analysis (Takefuji, 2023). Recently, its proponents noted that ChatGPT can be utilized for academic purposes, including research. It can extract and paraphrase information, translate text, grade tests, and/or it may be used for conversation purposes (MIT, 2023). Various stakeholders in education noted that this LLM tool may be able to provide quick and easy answers to questions.

However, earlier this year, several higher educational institutions issued statements that warned students against using ChatGPT for academic purposes. In a similar vein, a number of schools banned ChatGPT from their networks and devices (Rudolph et al., 2023). Evidently, policy makers were concerned that this text generating AI system could disseminate misinformation and even promote plagiarism. Some commentators argue that it can affect the students’ critical-thinking and problem-solving abilities. Such skill sets are essential aspects for their academic and lifelong successes (Liebrenz et al., 2023Thorp, 2023). Nevertheless, a number of jurisdictions are reversing their decisions that impede students from using this technology (Reuters, 2023). In many cases, educational leaders are realizing that their students could benefit from this innovation, if they are properly taught how to adopt it as a tool for their learning journey.

Academic colleagues are increasingly raising awareness on different uses of AI dialogue systems like service chatbots and/or virtual assistants (Baabdullah et al., 2022Balakrishnan et al., 2022Brachten et al., 2021Hari et al., 2022Li et al., 2021Lou et al., 2022Malodia et al., 2021Sharma et al., 2022). Some of them are evaluating their strengths and weaknesses, including of OpenAI’s ChatGPT (Farrokhnia et al., 2023Kasneci et al., 2023). Very often, they argue that there may be instances where the chatbots’ prompts are not completely accurate and/or may not fully address the questions that are asked to them (Gill et al., 2024). This may be due to different reasons. For example, GPT-3.5’s responses are based on the data that were uploaded before a knowledge cut-off date (i.e. September 2021). This can have a negative effect on the quality of its replies, as the algorithm is not up to date with the latest developments. Although, at the moment, there is a knowledge gap and a few grey areas on the use of AI chatbots that use natural language processing to create humanlike conversational dialogue, currently, there are still a few contributions that have critically evaluated their pros and cons, and even less studies have investigated the factors affecting the individuals’ engagement levels with ChatGPT.

This empirical research builds on theoretical underpinnings related to information technology adoption in order to examine the online users’ perceptions and intentions to use AI Chatbots. Specifically, it integrates a perceived interactivity construct (Baabdullah et al., 2022McMillan and Hwang, 2002) with information quality and source trustworthiness measures (Leong et al., 2021Sussman and Siegal, 2003) from the Information Adoption Model (IAM) with performance expectancy, effort expectancy and social influences constructs (Venkatesh et al., 2003Venkatesh et al., 2012) from the Unified Theory of Acceptance and Use of Technology (UTAUT1/UTAUT2) to determine which factors are influencing the individuals’ intentions to use AI text generation systems like ChatGPT. This study’s focused research questions are:

RQ1

How and to what extent are information quality and source trustworthiness influencing the online users’ performance expectancy from ChatGPT?

RQ2

How and to what extent are their perceptions about ChatGPT’s interactivity, performance expectancy, effort expectancy, as well as their social influences affecting their intentions to continue using their large language models?

RQ3

How and to what degree is the performance expectancy construct mediating effort expectancy – intentions to use these interactive AI technologies?

This study hypothesizes that information quality and source trustworthiness are significant antecedents of performance expectancy. It presumes that this latter construct, together with effort expectancy, social influences as well as perceived interactivity affect the online users’ acceptance and usage of generative pre-trained AI chatbots like GPT-3.5 or GPT-4.

Many academic researchers sought to explore the individuals’ behavioral intentions to use a wide array of technologies (Alalwan, 2020Alam et al., 2020Al-Saedi et al., 2020Raza et al., 2021Tam et al., 2020). Very often, they utilized measures from the Theory of Reasoned Action (TRA) (Fishbein and Ajzen, 1975), the Theory of Planned Behavior (TPB) (Ajzen, 1991), the Technology Acceptance Model (TAM) (Davis, 1989Davis et al., 1989), TAM2 (Venkatesh and Davis, 2000), TAM3 (Venkatesh and Bala, 2008), UTAUT (Venkatesh et al., 2003) or UTAUT2 (Venkatesh et al., 2012). Few scholars have integrated constructs like UTAUT/UTAUT2’s performance expectancy, effort expectancy, social influences and intentions to use technologies with information quality and source trust measures from the Elaboration Likelihood Model (ELM) and IAM. Currently, there is still limited research that incorporates a perceived interactivity factor within information technology frameworks. Therefore, this contribution addresses this deficit in academic knowledge.

Notwithstanding, for the time being, there is still scant research that is focused on AI-powered LLM, like ChatGPT, that are capable of generating human-like text that is based on previous contexts and drawn from past conversations. This timely study raises awareness on the individuals’ perceptions about the utilitarian value of such interactive technologies, in an academic (higher educational) context. It clearly identifies the factors that are influencing the individuals’ intentions to continue using them, in the future.


From the literature review

Table 1 features a summary of the most popular theoretical frameworks that sought to identify the antecedents and the extent to which they may affect the individuals’ intentions to use information technologies.

Table 1. A non-exhaustive list of theoretical frameworks focused on (information) technology adoption behaviors

Figure 1. features the conceptual framework that investigates information technology adoption factors. It represents a visual illustration of the hypotheses of this study. In sum, this empirical research presumes that information quality and source trustworthiness (from Information Adoption Model) precede performance expectancy. The latter construct together with effort expectancy, social influences (from Unified Theory of Acceptance and Use of Technology) as well as the perceived interactivity construct, are significant antecedents of the individuals’ intentions to use ChatGPT.


The survey instrument

The respondents were instructed to answer all survey questions that were presented to them about information quality, source trustworthiness, performance expectancy, effort expectancy, social influences, perceived interactivity and on their behavioral intentions to continue using this technology (otherwise, they could not submit the questionnaire). Table 2 features the list of measures as well as their corresponding items that were utilized in this study. It also provides a definition of the constructs used in the proposed information technology acceptance framework.

Table 2. The list of measures and the corresponding items used in this research.


Theoretical implications

This research sought to explore the factors that are affecting the individuals’ intentions to use ChatGPT. It examined the online users’ effort and performance expectancy, social influences as well as their perceptions about the information quality, source trustworthiness and interactivity of generative text AI chatbots. The empirical investigation hypothesized that performance expectancy, effort expectancy and social influences from Venkatesh et al.’s (2003) UTAUT together with a perceived interactivity construct (McMillan and Hwang, 2002) were significant antecedents of their intentions to revisit ChatGPT’s website and/or to use its app. Moreover, it presumed that information quality and source trustworthiness measures from Sussman and Siegal’s (2003) IAM were found to be the precursors of performance expectancy.

The results from this study report that source trustworthiness-performance expectancy is the most significant path in this research model. They confirm that online users indicated that they believed that there is a connection between the source’s trustworthiness in terms of its dependability, and the degree to which they believe that using such an AI generative system will help them improve their job performance. Similar effects were also evidenced in previous IAM theoretical frameworks (Kang and Namkung, 2019; Onofrei et al., 2022), as well as in a number of studies related to TAM (Assaker, 2020; Chen and Aklikokou, 2020; Shahzad et al., 2018) and/or to UTAUT/UTAUT2 (Lallmahomed et al., 2017).

In addition, this research also reports that the users’ peceptions about information quality significantly affects their performance expectancy/expectancies from ChatGPT. Yet, in this case, this link was weaker than the former, thus implying that the respondents’ perceptions about the usefulness of this text generative technology were clearly influenced by the peripheral cues of communication (Cacioppo and Petty, 1981; Shi et al., 2018; Sussman and Siegal, 2003; Tien et al., 2019).

Very often, academic colleagues noted that individuals would probably rely on the information that is presented to them, if they perceive that the sources and/or their content are trustworthy (Bingham et al., 2019; John and De’Villiers, 2020; Winter, 2020). Frequently, they indicated that source trustworthiness would likely affect their beliefs about the usefulness of information technologies, as they enable them to enhance their performance. Conversely, some commentators argued that there may be users that could be skeptical and wary about using new technologies, especially if they are unfamiliar with them (Shankar et al., 2021). They noted that such individuals may be concerned about the reliability and trustworthiness of the latest technologies.

The findings suggest that the individuals’ perceptions about the interactivity of ChatGPT are a precursor of their intentions to use it. This link is also highly significant. Therefore, the online users were somehow appreciating this information technology’s responsiveness to their prompts (in terms of its computer-human communications). Evidently, ChatGPT’s interactivity attributes are having an impact on the individuals’ readiness to engage with it, and to seek answers to their questions. Similar results were reported in other studies that analyzed how the interactivity and anthropomorphic features of dialogue systems like live support chatbots, or virtual assistants can influence the online users’ willingness to continue utilizing them in the future (Baabdullah et al., 2022; Balakrishnan et al., 2022; Brachten et al., 2021; Liew et al., 2017).

There are a number of academic contributions that sought to explore how, why, where and when individuals are lured by interactive communication technologies (e.g. Hari et al., 2022; Li et al., 2021; Lou et al., 2022). Generally, these researchers posited that users are habituated with information systems that are programed to engage with them in a dynamic and responsive manner. Very often they indicated that many individuals are favorably disposed to use dialogue systems that are capable of providing them with instant feedback and personalized content. Several colleagues suggest that positive user experiences as well as high satisfaction levels and enjoyment, could enhance their connection with information technologies, and will probably motivate them to continue using them in the future (Ashfaq et al., 2020; Camilleri and Falzon, 2021; Huang and Chueh, 2021; Wolfinbarger and Gilly, 2003).

Another important finding from this research is that the individuals’ social influences (from family, friends or colleagues) are affecting their interactions with ChatGPT. Again, this causal path is also very significant. Similar results were also reported in UTAUT/UTAUT2 studies that are focused on the link between social influences and its link with intentional behaviors to use technologies (Gursoy et al., 2019; Patil et al., 2020). In addition, TPB/TRA researchers found that subjective norms also predict behavioral intentions (Driediger and Bhatiasevi, 2019; Sohn and Kwon, 2020). This is in stark contract with other studies that reported that there was no significant relationship between social influences/subjective norms and behavioral intentions (Ho et al., 2020; Kamble et al., 2019).

Interestingly, the results report that there are highly significant effects between effort expectancy (i.e. ease of use of the generative AI technology) and performance expectancy (i.e. its perceived usefulness). Many scholars posit that perceived ease of use is a significant driver of perceived usefulness of technology (Bressolles et al., 2014; Davis, 1989; Davis et al., 1989; Kamble et al., 2019; Yoo and Donthu, 2001). Furthermore, there are significant causal paths between performance expectancy-intentions to use ChatGPT and even between effort expectancy-intentions to use ChatGPT, albeit to a lesser extent. Yet, this research indicates that performance expectancy partially mediates effort expectancy-intentions to use ChatGPT. In this case, this link is highly significant.

In sum, this contribution validates key information technology measures, specifically, performance expectancy, effort expectancy, social influences and behavioral intentions from UTAUT/UTAUT2, as well as information quality and source trustworthiness from ELM/IAM and integrates them with a perceived interactivity factor. It builds on previous theoretical underpinnings. Yet, it differentiates itself from previous studies. To date, there are no other empirical investigations that have combined the same constructs that are presented in this article. Notwithstanding, this research puts forward a robust Information Technology Acceptance Framework. The results confirm the reliability and validity of the measures. They clearly outline the relative strength and significance of the causal paths that are predicting the individuals’ intentions to use ChatGPT.


Managerial implications

This empirical study provides a snapshot on the online users’ perceptions about ChatGPT’s responses to verbal queries, and sheds light on their dispositions to avail themselves from its natural language processing. It explores their performance expectations about their usefulness and their effort expectations related to the ease of use of these information technologies and investigates whether they are affected by colleagues or by other social influences to use such dialogue systems. Moreover, it examines their insights about the content quality, source trustworthiness as well as on the interactivity features of these text- generative AI models.

Generally, the results suggest that the research participants felt that these algorithms are easy to use. The findings indicate that they consider them to be useful too, specifically when the information they generate is trustworthy and dependable. The respondents suggest that they are concerned about the quality and accuracy of the content that is featured in the AI chatbots’ answers. This contingent issue can have a negative effect on the use of the information that is created by online dialogue systems.

OpenAI’s ChatGPT is a case in point. Its app is freely available in many countries, via desktop and mobile technologies including iOS and Android. The company admits that its GPT-3.5 outputs may be inaccurate, untruthful, and misleading at times. It clarifies that its algorithm is not connected to the internet, and that it can occasionally produce incorrect answers (OpenAI, 2023a). It posits that GPT-3.5 has limited knowledge of the world and events after 2021 and may also occasionally produce harmful instructions or biased content. OpenAI recommends checking whether its chatbot’s responses are accurate or not, and to let them know when and if it answers in an incorrect manner, by using their “Thumbs Down” button. They even declare that their ChatGPT’s Help Center can occasionally make up facts or “hallucinate” outputs (OpenAI, 2023a,b).

OpenAI reports that its top notch ChatGPT Plus subscribers can access safer and more useful responses. In this case, users can avail themselves from a number of beta plugins and resources that can offer a wide range of capabilities including text-to-speech applications as well as web browsing features through Bing. Yet again, OpenAI (2023b) indicates that its GPT-4 still has many known limitations that the company is working to address, such as “social biases and adversarial prompts” (at the time of writing this article). Evidently, works are still in progress at OpenAI. The company needs to resolve these serious issues, considering that its Content Policy and Terms clearly stipulate that OpenAI’s consumers are the owners of the output that is created by ChatGPT. Hence, ChatGPT’s users have the right to reprint, sell, and merchandise the content that is generated for them through OpenAI’s platforms, regardless of whether the output (its response) was provided via a free or a paid plan.

Various commentators are increasingly raising awareness about the corporate digital responsibilities of those involved in the research, development and maintenance of such dialogue systems. A number of stakeholders, particularly the regulatory ones, are concerned on possible risks and perils arising from AI algorithms including interactive chatbots. In many cases, they are warning that disruptive chatbots could disseminate misinformation, foster prejudice, bias and discrimination, raise privacy concerns, and could lead to the loss of jobs. Arguably, one has to bear in mind that, in many cases, many governments are outpaced by the proliferation of technological innovations (as their development happens before the enactment of legislation). As a result, they tend to be reactive in the implementation of substantive regulatory interventions. This research reported that the development of ChatGPT has resulted in mixed reactions among different stakeholders in society, especially during the first months after its official launch. At the moment, there are just a few jurisdictions that have formalized policies and governance frameworks that are meant to protect and safeguard individuals and entities from possible risks and dangers of AI technologies (Camilleri, 2023). Of course, voluntary principles and guidelines are a step in the right direction. However, policy makers are expected by various stakeholders to step-up their commitment by introducing quasi-regulations and legislation.

Currently, a number of technology conglomerates including Microsoft-backed OpenAI, Apple and IBM, among others, anticipated the governments’ regulations by joining forces in a non-profit organization entitled, “Partnership for AI” that aims to advance safe, responsible AI, that is rooted in open innovation. In addition, IBM has also teamed up with Meta and other companies, startups, universities, research and government organizations, as well as non-profit foundations to form an “AI Alliance”, that is intended to foster innovations across all aspects of AI technology, applications and governance.

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Metaverse keywords for dummies

Individuals can use the Metaverse for leisure, entertainment, socializing, as a marketplace to buy items and for education, among other purposes. Currently, technology giants including Meta, Microsoft, Nvidia, Roblox, Snap and Unity, among others, are building the infrastructure of Metaverse. At the time of writing many commentators are envisaging that the Metaverse’s virtual environments will be replicating the real world. For instance, the Metaverse’s virtual reality (VR) environment can be used to deliver lectures to students located in remote locations. Course instructors can utilize its immersive 3D capabilities in synchronous and asynchronous learning environments. They can interact with their students’ avatars in real time to provide immediate feedback. In addition, they may avail themselves of the Metaverse virtual settings to catapult their students in learning scenarios that are constrained by the limits of reality, or by their own imagination, to enable them to learn in a practical, yet safe environment. Table 1 features a clear (and comprehensible) definition of some of the most popular terms related to the ‘Metaverse’.

Table 1. Key terms related to the adoption of the Metaverse

KeywordDefinition  
AvatarAn avatar represents a human figure with a fictitious, animated character in electronic games as well as in the internet’s websites including in social media and in the Metaverse. They may usually appear to be similar in their physical features and expressions as their real-world counterparts. However, online users may want to customize their avatars to disguise themselves by creating very imaginative characters.
Digital twinThe digital twin refers to a virtual representation of a real-world product, system, or process that spans its lifecycle. It can be considered as a digital counterpart. A digital twin can be utilized for practical purposes including for monitoring, testing of simulations, maintenance et cetera. Its underlying objective is to generate useful insights on how to improve real life objects and their systems. It is intended to mimic the lifecycle of a physical entity it represents (from its inception up to its disposal). However, the digital twin could exist before the existence of a physical entity. The initial stages of a digital twin (in the creation phase) enable the intended entity’s entire lifecycle to be simulated and tested. Hence, the development of digital twins involves continuous improvements in product designs, operational processes and engineering activities, as they are acquiring new capabilities through trial-and-error phases, simulations and machine learning. The rationale of digital twins is to increase the efficiency of products and systems, to enhance their performance outcomes.
Extended reality (XR)XR refers to an umbrella term that incorporates augmented reality (AR), virtual reality (VR) and mixed reality (MR) that mirror the physical world or a digital twin. It refers to the combination of real and virtual environments that can comprise different objects and systems. Each of them will have their own roles, features and attributes. A multisensory XR system conveys signals to the human beings’ nervous systems through visual, auditory, olfactory and haptic cues that are very similar to real life feelings and experiences (Yu et al., 2023). Such technologies could be designed to support their users’ well-being. They may involve digital therapeutics that can affect the individuals’ perceptions, state of mind and behaviors.
Mixed reality (MR)MR is an inter-reality system comprising a physical reality as well as 3D digital worlds, where real and virtual objects could co-exist and interact in real time. MR integrates AR and VR technologies to provide holographic representations of objects in a virtuality continuum (Yoo et al., 2022). It is being used for different applications including for educational purposes, to deliver experiential learning. Students can benefit from natural and intuitive 3D representations based on the latest advancements in input systems, sensors, processing power, display technologies, graphical processing, and cloud computing are creating elaborate experiences with mixed realities.
Non-fungible tokensNon-fungible tokens (NFTs) are a form of cryptocurrency where data is digitally stored in a blockchain. NFTs are considered as a unique modality of digital non-interchangeable (i.e. non-fungible) assets, that are authenticated and certified to a specific owner. NFTs may represent electronic content including the video games’ audiovisual material, collectibles, avatars, et cetera, that can be acquired, sold or traded. The blockchain technology ensures that the digital assets cannot be replicated in any way. However, owners of NFTs can trade and sell their NFTs. The blockchain allows prospective buyers to confirm the provenance of the virtual content and to clearly track and establish the ownership of the tokens. Hence, they can monetize them with other customers through the Metaverse.
Virtual realityWhile AR uses the existing real-world environment and incorporates virtual information in it, virtual reality (VR) will completely immerse its users in a simulated environment comprising sensory modalities including auditory and video feedback as well as haptic sensations. VR relies on pose tracking and on 3D near-eye displays to give them an immersive feel of a virtual world. It enables users to experience sights and sounds that are similar or totally different from the real world. Individuals can use VR helmets and headsets like Meta Quest, Play Station VR, HTC Vive, or HP reverb, among others, that provide a small screen in front of the eyes, that will place them in a virtual environment. A person using virtual reality equipment may experience a synthetic world by moving around, and by interacting with its virtual objects that may be present in specially designed 3D rooms or even in outdoor environments. For example, medical students can use VR to practice how to perform heart surgeries.
Web 3.0Web 3.0 represents the evolution of the web into a decentralized network. Many commentators are anticipating that online users will be in a position to access their own data, including documents, applications and multimedia, in a secure, open-source environment, that will be facilitated by Blockchain’s distributed ledger technology. They envisage that online users will probably rely on the services of Decentralized Autonomous Organizations (DAO), that will be entrusted to provide a secure digital ledger that tracks their customers’ digital interactions across the internet, via a network of openly available smart contracts stored in a decentralized Blockchain. Therefore, smart contracts could provide increased security, scalability and privacy (e.g. as online users can protect their intellectual properties through non-fungible tokens).
(Developed by the Camilleri & Camilleri, 2023).

Read the full paper in its entirety here:

Suggested citation: Camilleri, M.A. & Camilleri, A.C. (2023).  Metaverse education: Opportunities and challenges for immersive learning in virtual environments,  2023 The 4th Asia Conference on Computers and Communications (ACCC 2023),  IOP Publishing, Bristol, United Kingdom (Scopus).

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Responsible artificial intelligence governance and corporate digital responsibility

This post discusses on the salient aspects of my latest article, entitled: “Artificial intelligence governance: Ethical considerations and implications for social responsibility“, published through Wiley’s Expert Systems.

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Customer satisfaction and loyalty with online consumer reviews

This text is drawn from excerpts of an article published through Elsevier’s International Journal of Hospitality Management.

Suggested citation: Camilleri, M.A. & Filieri, R. (2023). Customer satisfaction and loyalty with online consumer reviews: Factors affecting revisit intentions, International Journal of Hospitality Management, https://doi.org/10.1016/j.ijhm.2023.103575

Abstract

While previous research investigated the effects of online consumer reviews on purchase behaviors, currently, there is still a lack of knowledge on the impact of the reviews’ credibility, content quality and information usefulness on the customers’ satisfaction levels with them. Data were gathered from a sample of 512 participants. A partial least squares approach was utilized to evaluate the reliability and validity of the constructs and to identify the causal effects in this contribution’s structured model. The findings reveal that information usefulness is a very strong predictor of satisfaction. They also confirm highly significant indirect effects, between information quality and customer satisfaction, when information usefulness meditates this link. This study suggests that prospective customers appreciate quality reviews of consumers who have already experienced the hospitality services. It raises awareness about the usefulness of review sites as online users refer to their content before committing themselves to purchasing products and services. 

Keywords: customer satisfaction; customer loyalty; information usefulness; information quality; source credibility; information adoption model.

Introduction

The advances of the Internet are presenting online users and prospective customers of hospitality businesses with a great opportunity for interactive engagement through blogs, microblogs, discussion fora, social networking sites and online communities. Many consumers are sharing their insights about their service experiences through review platforms like AirBnB, Booking.com, TripAdvisor, and the like. Very often, they praise or complain about different aspects of their service encounters (Akdim et al., 2022; Filieri and McLeay, 2014; Rita et al., 2022). Such testimonials are intended to support potential consumers to reduce their uncertainty before committing themselves to make purchase decisions.

The electronic content featured in review sites as well as in social media can be read by online users hailing from different regions across the globe. Interactive platforms enable their users to feature positive and negative publicity (Moro et al., 2020; Sun and Liu, 2021; Shin et al., 2023) via qualitative service evaluations and/or via quantitative scores, also known as ratings.  Online users can subscribe to review networks to voice their testimonials on their satisfaction and/or on their dissatisfaction levels with the services they experienced (Kim et al., 2023; Zheng et al., 2023). In the latter case, they will intentionally engage in negative word-of-mouth (WOM) publicity to tarnish the reputation and image of the business (Qiao et al., 2022).

This topic has been attracting the interest of a number of scholars in marketing, information systems, as well as in travel, tourism and service industries (Donthu et al., 2021). Various researchers sought to investigate the consumers’ acceptance of online reviews. Frequently, they explored the internalization processes whereby individuals take heed, or take into consideration user generated content, like electronic WOM (eWOM) publicity, that is usually cocreated by consumers who have already experienced products and services, in order to enhance their extant knowledge about the service quality provided by hospitality businesses (Song et al., 2022; Zhang et al., 2021).

This argumentation is consistent with the information adoption model (IAM). Sussman and Siegal (2003) suggest that individuals tend to rely on quality information if they believe that it is useful to them. The authors argued that persons are influenced by knowledge transfer if they understand and comprehend the flows of information they receive. Hence, individuals would be in a position to determine the best courses of action that better serve their needs, particularly if they perceive that other individuals are providing reliable and trustworthy advice to them (Erkan and Evans 2016).

Information adoption factors, including details relating to the quality of the content and the credibility of the informational sources, may significantly affect the individuals’ perceptions about the usefulness of online reviews (Cheung et al., 2008; Filieri, 2015). Hence, the argument quality of consumer testimonials, as well as the credibility of the sources, are two major determinants that can influence online users’ satisfaction levels (Filieri et al., 2015; Zhao et al., 2019), with the sites hosting online reviews, and may even determine their revisit intentions to them (Kaya et al., 2019; Ladhari and Michaud, 2015; Rodríguez et al., 2020).

This empirical research investigates perceptions toward consumer review sites. It focuses on online users’ beliefs about the quality of their information, as well as on the credibility and usefulness of their content. It examines these constructs exogenous effects on their satisfaction levels and on their loyalty with consumer review platforms, as shown in Figure 1.

(Source: Camilleri and Filieri, 2023)

Hence, this study validates key factors, namely, information quality (Cheung et al., 2008; Kumar and Ayodeji, 2021; McClure and Seock, 2020; Talwar et al., 2021), source credibility (Argyris et al., 2021; Filieri, 2015), and information usefulness (Camilleri et al., 2023; Filieri, 2015). These measures are drawn from valid information and/or technology adoption models (Sussman and Siegal, 2003), and are combined with consumer satisfaction (Maxham and Netemeyer, 2002) and consumer loyalty (Tran and Strutton, 2020; Zeithaml, et al., 1996). The latter two constructs are associated with the service-dominant logic (Zeithaml et al., 2002; Parasuraman et al., 2005).

Arguably, regular users of review platforms are likely to take heed of the consumers’ recommendations as they perceive the usefulness of their advice (on their service encounters) (D’ Acunto et al., 2020; Xu, 2020; Ye et al., 2009). The researchers presume that the individuals who utilize these websites will usually trust past customers’ experiences. Hence, this study hypothesizes that the respondents who habitually rely on consumer reviews, are satisfied with the quality of their content, and that they perceive that their sources are credible and useful. As a result, the research participants may be intrigued to revisit them again in the future. Hence, the research questions of this contribution are:

RQ1: How and to what extent are information quality and source credibility affecting the usefulness of consumer reviews?

RQ2: How and to what extent are informative and helpful reviews influencing online users’ satisfaction levels and loyalty behaviors, in terms of their revisit intentions to these platforms?

RQ3: How and to what degree is information usefulness mediating the information quality – customer satisfaction/customer loyalty and/or source credibility – customer satisfaction/customer loyalty causal paths?

Previous research examined the perceptions about eWOM and focused on online review websites by using IAM (Cheung et al., 2008; Filieri, 2015). However, for the time being, no other studies sought to explore the effects of IAM’s key constructs on electronic service quality’s (eSERVQUAL’s) endogenous factors of satisfaction and loyalty. Therefore, this study raises awareness on the usefulness of review sites as prospective customers are referring to their content before committing themselves to purchasing products or prior to experiencing the businesses’ services. In this case, the researchers theorized that they would probably revisit the review platforms, if they were satisfied with their quality information and source credibility.

A survey questionnaire was employed to collect data from subscribers of popular social media networks. A structured equations modelling partial least squares SEM-PLS methodology was utilized to examine the proposed research model in order to confirm the reliability and validity of the constructs used in this study. This composite based SEM approach enabled the researchers to shed light on the significant effects that are predicting the respondents’ likelihood to rely on user generated content and to determine whether they influenced their satisfaction levels and revisit intentions.

The following section features an original conceptual framework and formulates the hypotheses of this empirical investigation. Afterwards, the methodology provides details on the data collection process for this quantitative study. Subsequently, the results illustrate the findings from SmartPLS’s analytical approach to reveal the causal effects in this study’s research model. In conclusion, this article identifies theoretical and managerial implications. The researchers discuss about the limitations of this study and outline future research avenues.

Table 1. A definition of the key factors used in this study

TermDefinition
Information Quality:  This factor measures perceptions on the quality of information (in terms of the consumer reviews’ reliability and appropriateness).
Source Credibility:  This factor measures perceptions on the credibility of the sources (in terms of the consumer reviewers’ trustworthiness and proficiency in sharing service their experiences with others).
Information Usefulness:  This factor measures perceptions on the utilitarian value of information (featured in consumer reviews).
Customer Satisfaction:  This factor refers to positive or negative feelings about products or services (in this case, it is focused on electronic services provided by review websites).
Customer Loyalty:  This factor refers to the willingness to repeatedly engage with specific businesses (in this case, it is focused on review websites).
(Source: Camilleri and Filieri, 2023)

Theoretical implications

This contribution puts forward a research model that integrated IAM’s key factors including information quality (Cheung et al., 2008; Filieri, 2015; McClure and Seock, 2020; Talwar et al., 2021)), source credibility (Filieri et al., 2021; Ismagilova et al., 2020) and information usefulness (of consumer reviews) (Camilleri and Kozak, 2023; Moro et al., 2020) with eSERVQUAL’s satisfaction (Kaya et al., 2019; Kumar and Ayodeji, 2021) and loyalty outcomes (Kumar and Ayodeji, 2021; Tran and Strutton, 2020).

The results from SmartPLS 3 confirm the reliability and validity of all measures that were used in this study. The findings indicate highly significant direct as well as indirect effects that are predicting the online users’ satisfaction levels and loyalty with review sites. This research suggests that the quality of the user generated content as well as the sources’ credibility (in terms of the trustworthiness and expertise of the online reviewers) are positive and significant antecedents of the individuals’ perceptions about the usefulness of information. These findings reveal that both information quality and source credibility are significant precursors of information usefulness, thereby validating mainstream IAM theoretical underpinnings (Cheung et al., 2008; Chong et al., 2018; Erkan and Evans, 2016; Filieri, 2015; Sussman and Siegal, 2003).

This study differentiated itself from IAM as it examined the effects of information quality, source credibility and information usefulness on the consumers’ satisfaction levels and loyalty with review websites. It reported that information usefulness – customer satisfaction was the strongest link in this empirical investigation and that customer satisfaction partially mediated the relationship between information usefulness and customer loyalty. Moreover, the results showed that there were highly significant indirect effects between information quality and customer satisfaction, between information quality and customer loyalty, between source credibility and customer satisfaction, and between source credibility and customer loyalty.

In this case, this research indicated that the respondents (i.e. online users) were satisfied with the review platforms that featured the consumers’ testimonials about their “moments of truth” with hospitality businesses. It suggested that they were likely to re-visit them again in the future. To the best of the authors’ knowledge there are no studies in the academic literature that have integrated theoretical underpinnings related to the service dominant logic (Vargo and Lusch, 2008), or to SERVQUAL- and/or eSERVQUAL-related factors (Kaya et al., 2019; Maxham and Netemeyer, 2002; Parasuraman et al., 2005; Rodríguez et al., 2020; Zeithaml et al., 1996; Zeithaml et al., 2002) with IAM constructs (Camilleri & Kozak, 2023; Chatterjee et al., 2023; Cheung et al., 2008; D’Acunto et al., 2020; Erkan and Evans 2016; Filieri, 2015; Huiyue et al., 2022; Kang and Namkung, 2019; Li et al., 2020; Sussman and Siegal, 2003; Ye et al., 2009) to explore the satisfaction levels and revisit intentions to review websites focused on consumer experiences of hospitality services. This original research addresses this knowledge gap. In conclusion, it implies that IAM’s exogenous factors can be used to investigate the online users’ perceptions about the usefulness and satisfaction with past consumers’ service evaluations, and to shed light on their intentions to habitually check out the qualitative content of review platforms/apps, prior to visiting service businesses (including hotels, Airbnbs and restaurants, among others) and/or before committing themselves to a purchase decision.

This contribution’s novel conceptual model raises awareness on the importance of evaluating the consumers’ satisfaction levels as well as their revisit intentions of review sites rather than merely determining how information usefulness and other IAM antecedents affect their information adoption.

Managerial implications

This research postulates that online users are perceiving the usefulness of consumer reviews. It clearly indicates that the respondents feel that they feature quality content and that they consider them to be informative, credible and trustworthy. The results suggest that they are satisfied with the user generated content (that sheds light on the reviewers’ opinions on their personal service encounters). In fact, their responses imply that they are likely to revisit review websites and/or to engage with their apps again.

The review platforms are helping prospective consumers in their purchase decisions. They enable them to quickly access consumer experiences with a wide array of service providers and to compare their different shades of opinions. This study shows that they are evaluating the consumer reviews to determine whether the hospitality firms are/are not delivering on their promises?

The consumers’ reviews can make or break a business. The restaurant patrons’ and/or the hotel guests’ words of praise as well as their genuine expressions of respect and gratitude can elevate the business and enhance its corporate reputation. Alternatively, the customers’ critical evaluations may tarnish the image of hospitality business (in this case). Whilst the consumers’ positive experiences with a company increases the likelihood of their loyal behaviors and of word-of-mouth publicity (that attracts new customers), poor reviews and ratings could signal that the customers are dissatisfied with certain aspects of the service delivery and may even result in their conversion to the hospitality firms’ competitors.

Hence, it is in the businesses’ self-interest: (i) to consistently deliver service quality, (ii) to meet and exceed their customers’ expectations, (iii) to continuously monitor their consumers’ reviews, (iv) to address contentious issues in a timely manner, and (v) to minimize consumer complaints (and turn them into opportunities for consumer satisfaction and loyalty).

Limitations and future research avenues

This research comprised reliable measures that are tried and tested in academia. Information quality, source credibility and information usefulness factors were utilized to explore the customers’ satisfaction and loyalty with review sites. These five constructs were never integrated together within the same empirical investigation. Future researchers are invited to validate this study in other contexts. For example, this theoretical model could explore the online users’ satisfaction and intentions to use social media networks (SNSs) and/or e-commerce websites and online marketplaces.

Alternatively, researchers can include other constructs related to IAM to assess perceptions about information understandability, information reliability, information relevance, information accuracy, and information timeliness, among others. Most of these constructs represent information quality. In addition, they may examine the individuals’ insights about source trustworthiness and/or source expertise rather than integrating them into a source credibility construct. They may also consider various constructs from eSERVQUAL like website appeal, attractiveness, design, functionality, security and consumer fulfilment aspects.

Perhaps, there is scope for future studies to consider other measures that are drawn from psychology research like the Social Cognitive Theory (Bandura, 1986), the Theory of Reasoned Action (Fishbein and Ajzen, 1975), or the Theory of Planned Behavior (Ajzen, 1991), among others, or from technology adoption models including the Technology Acceptance Model’s TAM (Davis, 1989; Davis et al., 1989), TAM2 (Wang et al., 2021), TAM3 (Al-Gahtani, 2016), the Innovation Diffusion Theory (IDT) (Moore and Benbasat, 1991; Rogers, 1995), the Motivational Model (MM) (Davis et al., 1992), the Unified Theory of Acceptance and Use of Technology’ UTAUT (Venkatesh et al., 2003) and UTAUT2 (Venkatesh et al., 2012), among others.

These theories may be used to better understand the acceptance and utilization of information technologies (like review platforms). Notwithstanding, other studies are required to shed more light on the moderating effects of demographic variables, on the usability and satisfaction levels with disruptive innovations like voice assistance, chatbots, ChatGPT, Metaverse, and the like.

Other researchers may utilize other research designs and sampling approaches to gather and analyze primary data. They could capture interpretative data through inductive research, to delve deeper in the informants’ opinions about eWOM publicity in consumer review sites. Qualitative research methodologies and interpretative designs could shed more light on important insights on how, where, when and why the customers’ user-generated content (on their service experiences) could influence the intentional behaviors of prospective consumers in today’s digital age.

All the references are featured in the article. An open access version is available here: https://www.researchgate.net/publication/372891266_Customer_satisfaction_and_loyalty_with_online_consumer_reviews_Factors_affecting_revisit_intentions

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The functionality and usability features of mobile apps

This is an excerpt from one of my latest publications.

Suggested citation: Camilleri, M.A., Troise, C. & Kozak, M. (2023). Functionality and usability features of ubiquitous mobile technologies: The acceptance of interactive travel apps. Journal of Hospitality and Tourism Technology, https://doi.org/10.1108/JHTT-12-2021-0345 Available from: https://www.researchgate.net/publication/366633583_Functionality_and_usability_features_of_ubiquitous_mobile_technologies_The_acceptance_of_interactive_travel_apps.

(C) DrMarkCamilleri.com

Prior studies relied on specific theoretical frameworks like the Interactive Technology Adoption Model – ITAM (Camilleri and Kozak, 2022), elaboration likelihood model (ELM), information adoption model (IAM) and/or technology acceptance model (TAM), among others, to better understand which factors are having an impact on the individuals’ engagement with digital media or information technologies.

In this case, this research identifies the factors that are influencing the adoption of travel apps, in the aftermath of COVID-19. It examines the effects of information quality and source credibility (these measures are drawn from IAM framework), as well as of technical functionality, relating to electronic service quality (eSERVQUAL), on the individuals’ perceptions about the usefulness of these mobile technologies and on their intentions to continue using them on a habitual basis (the latter two factors are used in TAM models), to shed light on the consumers’ beliefs about their usability and functionality features.

This study suggests that consumers are valuing the quality of the digital content that is presented to them through these mobile technologies. Apparently, they are perceiving that the sources (who are curating the content) were knowledgeable and proficient in the upkeep and maintenance of their apps. Moreover, they are appreciating their functional attributes including their instrumental utility and appealing designs. Evidently, these factors are influencing their intentions to use the travel apps in the future. They may even lead them to purchase travel and hospitality services. Furthermore, they can have an impact on their social facilitation behaviors like positive publicity (via electronic word of mouth like online reviews, as well as in-person/offline), among other outcomes.

This contribution implies that there is scope for future researchers to incorporate a functionality factor in addition to ITAM, IAM and/or TAM ‘usability’ constructs to investigate the individuals’ dispositions to utilize technological innovations and to adopt their information. It confirms that the functionality features including their ease of use, responsiveness, organized layout and technical capabilities can trigger users to increase their app engagement on a habitual basis.

Practical recommendations

The results from this study reveal that the respondents hold positive perceptions toward interactive travel apps. In the main, they indicate that these mobile technologies feature high quality content, are organized, work well, offer a good selection of products and are easy to use.

This research posits that mobile users appreciate the quality of information that is presented to them through the travel apps, in terms of their completed-ness, accuracy and timeliness of information. Yet, the findings show that there is room for improvement. There is scope for service providers (and for the curators of their travel apps) to increase their credentials on source trustworthiness and expertise among consumers.

The results suggest that information quality had a more significant effect on the respondents’ perceived usefulness of travel apps than source credibility. Moreover, they also suggest that consumers are willing to engage with travel apps as they believe that they offer seamless functionality features, including customization capabilities and fast loading screens. Most probably, the respondents are cognizant that they offer differentiated pricing options on flights, hotels and cars, from various service providers. They may be aware that many travel apps also enable their users to access their itineraries even when they are offline and allow them to keep a track record of their reward points (e.g. of frequent flyer programs) on every booking.

In this day and age, consumers can utilize mobile devices to access asynchronous content in webpages, including detailed information on tourism service providers, transportation services, tours to attractions, the provision of amenities in tourist destinations, frequently answered questions, efficient booking engines with high resolution images and videos, quick loading and navigation, detailed maps, as well as with qualitative reviews and quantitative ratings. Very often they can even be accessed through different languages.

A number of travel apps allow their users to log in with a secure, random password authentication method, to keep a track record of their credit card details and past transactions. Most of them are also sending price alerts as well as push notifications that remind consumers about their past searches. These services are adding value to the electronic service quality as opposed to unsolicited promotional messages, that are not always related to the consumers’ interests.

Generally, customers expect travel and tourism service providers to respond to their online queries in an instantaneous manner. They are increasingly demanding web chat services to resolve queries, as soon as possible, preferably in real time.

Tourism and hospitality service providers are already using augmented reality (AR) and virtual reality (VR) software, to improve their consumers’ online experiences and to emphasize their brand positioning as high-quality service providers. In the foreseeable future, it is very likely that practitioners could avail themselves of Metaverse technologies that could teleport consumers in the cyberspace, to lure them to book their flight, stays, car rentals or tours. Online (and mobile) users may be using electronic personas, called avatars to move them around virtual spaces and to engage with other users, when they are in the Metaverse.

This interactive technology is poised to enhance its users’ immersive experiences, in terms of their sensory inputs, definitions of space and points of access to information, particularly those that work with VR headsets. Hence, travel and hospitality businesses could avail themselves of such interactive technologies to gain a competitive advantage.

You can access this paper in its entirety, via: https://www.researchgate.net/publication/366633583_Functionality_and_usability_features_of_ubiquitous_mobile_technologies_The_acceptance_of_interactive_travel_apps

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