As prior conceptualizations of blockchain have emphasized its role as a disruptive operational tool, fundamental questions regarding ethical governance, value creation and trust dynamics in hospitality and tourism remain open. This paper examines how blockchain reshapes trust, transparency and value creation, positioning it as governance infrastructure for responsible digital transformation.
Using a reflective and integrative approach following Torraco (2005) and Grant and Booth (2009), the study synthesizes peer-reviewed literature and industry reports from 2016 to 2025, drawing from Scopus, Web of Science and Google Scholar. Thematic analysis organizes findings around five strands: efficiency and security, customer experience and trust, sustainability and transparency, organizational adoption and integration with emerging technologies.
The synthesis reveals that blockchain can strengthen digital trust through decentralization, traceability and transparency while supporting verifiable ESG reporting and ethical data governance. However, adoption remains constrained by regulatory fragmentation, interoperability challenges and tensions between decentralization ideals and implementation realities. The analysis identifies a fundamental trust deficit stemming from information asymmetries, intermediary opacity and post-pandemic credibility concerns.
This paper contributes to theory by reframing blockchain as an ethical infrastructure operationalizing Corporate Digital Responsibility (CDR) principles.
For practitioners, blockchain offers actionable paths for transparency, automated transactions and customer trust, though managers must address interoperability and ROI measurement before scaling.
Socially, blockchain may empower travelers and suppliers through verifiable systems supporting fairness across tourism value chains.
This paper bridges theory and practice by explicitly identifying trust deficits and articulating research directions for empirical validation.
Mahala Geronasso· Journal of Hospitality and T...· 1 citation
This study investigates how capital expenditure (CAPEX) intensity and leverage jointly relate to performance and risk in publicly listed U.S. hotel and restaurant firms. Using panel data for 67 corporations (23 hotels, 44 restaurants) from 2013 to 2023, the analysis models lagged CAPEX intensity and leverage alongside firm size, sales growth, and operating cash flow in firm-level regressions and portfolio-level time-series analyses. The sample consists predominantly (78%) of asset-heavy property owners rather than asset-light franchisors, with important implications for interpretation. Results reveal that higher CAPEX intensity is positively associated with subsequent accounting performance (return on assets, earnings before interest and taxes [EBIT]/total assets, liquidity ratios, and market-to-book), with associations substantially stronger for asset-heavy hotel corporations than restaurant corporations or asset-light franchisors. Leverage exhibits a negative relationship with accounting performance, particularly pronounced in the capital-intensive asset-heavy hotel sector. Portfolio-level autoregressive models demonstrate strong persistence in operating performance, indicating that firms sustaining higher investment intensity tend to remain in favorable performance regimes across years. Simultaneously, Generalized Autoregressive Conditional Heteroskedasticity models reveal pronounced and persistent volatility clustering in risk-adjusted equity returns, suggesting that intensive CAPEX programs are accompanied by extended periods of heightened uncertainty for investors. The findings underscore fundamental tensions in hospitality finance: while sustained investment is associated with long-term value creation, it must be balanced against leverage constraints and managed investor expectations around short-term volatility during turbulent periods such as the COVID-19 shock. These results should be interpreted as conditional associations rather than causal effects, given inherent endogeneity concerns in observational investment data.
