Publicações

Research on dark tourism and industrial heritage has largely evolved in parallel, despite their shared focus on sites shaped by death, suffering, and socio-environmental transformation. This study aims to map and synthesise the empirical and conceptual literature at this intersection in order to clarify how the darker dimensions of industrial and mining heritage are conceptualised, experienced, and interpreted, and to develop an integrated framework for their analysis. Following the PRISMA 2020 framework, it systematically reviews 33 peer-reviewed studies published between 2009 and the first quarter of 2026. Three main findings emerge. First, sanitisation—the marginalisation of suffering and exploitation in favour of narratives of technological achievement—is a dominant feature of industrial heritage interpretation and research. Second, visitors consistently experience emotional responses to dark heritage, with distinct affective profiles linked to environmental damage, human suffering, and labour histories. Third, labour exploitation remains under-theorised despite its centrality, reflecting its structural and long-term character, which challenges event-based dark tourism models. Building on these findings, the study proposes a tripartite typology of industrial darkness and introduces the concept of the evidence landscape to explain how sites communicate difficult pasts beyond formal interpretation.

Over the last decades, OECD countries have steadily reduced their level of infrastructure investment. Furthermore, the economic and financial shocks that occurred in the last decade have adversely affected many economies around the world, in terms of fiscal deterioration and public debt buildup. Under this context, governments around the world are going to invest massively in new projects to sustain economic and social development, with private capital becoming considerably relevant in complementing public investment. Therefore, governments have been resorting to various forms of asset-based structured finance solutions to finance public infrastructure projects. This paper examines how project finance, asset securitization, and structured leases can support the financing of public infrastructure projects, namely, to improve resilience and meet the Sustainable Development Goals. We provide an overview of the theoretical and empirical background of infrastructure investment as an asset class and the core financial economic foundations of asset-based structured finance. In addition, we characterize the main structured finance instruments and present the main reasons behind and limitations of their usage. Finally, we describe the recent trends in asset securitization, non-recourse project financing (project finance and PPPs), and structured leasing markets, and examine the deals originated in the worldwide markets over the 2000-2020 period.

Over the next decade, governments around the world will invest massively in new projects, aiming at closing the long-identified infrastructure gap, in order to sustain economic and social development, and recover from recent adverse shocks. This paper examines this topic from two perspectives: (i) how should these projects be valued and selected? and (ii) how should these projects be financed? We discuss conceptual, methodological and governance issues raised in the context of infrastructure investment project valuation with variable capital structures. The commonly used free cash flow (FCF) valuation approach may prove inappropriate, or even imprudent, for valuing, namely, very long-term infrastructure projects financed with variable capital structure arrangements. Under this framework, the literature recommends using the Capital Cash Flow (CCF) or the Adjusted Present Value models to mitigate some of the biases of the standard FCF approach. We show that despite dealing with tax benefits differently, FCF and CCF models are algebraically equivalent, the latter being a way to value future cash flows using the same assumptions made in the context of the FCF methodology, while overcoming some of its shortcomings.

In 2014, the Banco Espírito Santo (BES) conglomerate collapsed, marking the first
bank resolution inspired by the European Union’s Bank Recovery and Resolution
Directive (BRRD). Explanations for these events range from the aftermath of the
2008 financial meltdown to last-minute regulatory failures or capture. In this arti-
cle, we offer empirical findings supporting a different perspective. The 2014 debacle
stemmed from structural issues dating back to the Espírito Santo family’s reacquisi-
tion of BES in the early 1990s and the business strategy pursued over the subse-
quent two decades. While the financial meltdown post-2008 may have accelerated
the events of 2014, it was not the root cause but rather an immediate trigger. Regula-
tory failures were evident but began well before the 2010s. This case carries broader
implications for banking regulation in the European Union and beyond.

This study develops and tests an association-based model explaining how consumers interpret AI-enabled personalization in fashion e-commerce and how these interpretations relate to behavioral intentions. Integrating perspectives from Social Exchange Theory, the Antecedents of Trust Model, Self-Determination Theory, Psychological Contract Breach Theory, and Surveillance Capitalism, we examine the joint associations of perceived personalization, transparency, data control, and privacy concerns with brand trust, perceived surveillance, privacy violation perceptions, and purchase intention. Using PLS-SEM with data from 664 online shoppers, we find that personalization, transparency, and data control are each positively associated with brand trust, while personalization and privacy concerns are positively associated with surveillance perceptions. Brand trust is negatively associated with both surveillance and privacy violation perceptions, and privacy violation is negatively associated with purchase intention. Data control is directly associated with lower surveillance perceptions, whereas transparency operates indirectly through brand trust. Mediation analysis reveals that surveillance is associated with lower purchase intention only indirectly through privacy violation (full mediation), identifying perceived privacy violation as the central psychological pathway in the personalization-privacy paradox. Multi-group analysis identifies segment-level variations by gender and education: personalization is a stronger trust cue for men, while transparency is a stronger trust cue for women; trust buffers violation more strongly for higher-educated consumers. The results highlight a trust-first personalization strategy in which relevance must be paired with meaningful transparency and data-control features to mitigate surveillance and violation appraisals, supporting positive consumer outcomes in fashion e-commerce.