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Today's database management systems implement sophisticated access control mechanisms to prevent unauthorized access and modifications. For instance, this is an important basic requirement for SOX (Sarbanes‐Oxley Act) compliance, whereby every past transaction has to be traceable at any time. However, malicious database administrators may still be able to bypass the security mechanisms in order to make hidden modifications to the database. This paper aims to address these issues.

In this paper the authors define a novel signature of a B⁺‐tree, a widely‐used storage structure in database management systems, and propose its utilization for supporting the logging in databases. This additional logging mechanism is especially useful in conjunction with forensic techniques that directly target the underlying tree‐structure of an index. Several techniques for applying this signature in the context of digital forensics on B⁺‐trees are proposed in the course of this paper. Furthermore, the authors' signature can be used to generate exact copies of an index for backup purposes, thereby enabling the owner to completely restore data, even on the structural level.

For database systems in enterprise environments, compliance to regulatory standards such as SOX (Sarbanes‐Oxley Act), whereby every past transaction has to be traceable at any time, is a fundamental requirement. Today's database management systems usually implement sophisticated access control mechanisms to prevent unauthorized access and modifications. Nonetheless malicious database administrators would be able to bypass the security mechanisms in order to make modifications to the database, while covering their tracks.

In this paper, the authors demonstrate how the tree structure of the underlying store engine can be used to enhance forensic logging mechanisms of the database. They define a novel signature for B⁺‐trees, which are used by the InnoDB storage engine. This signature stores the structure of database storage files and can help in reconstructing previous versions of the file for forensic purposes. Furthermore, the authors' signature can be used to generate exact copies of an index for backup purposes, thus enabling the owner to completely restore data, even on the structural level. The authors applied their concept to four real‐life scenarios in order to evaluate its effectiveness.

This paper aims to assess the willingness of individuals living in coastal communities affected by climate change to financially support mitigation policies towards the preservation of marine ecosystems and fish resources and to identify the key drivers of their behaviour.

A survey was carried out involving 994 people living in three main Italian coastal communities. To investigate the main factors affecting Italian coastal communities’ willingness to pay (WTP) to support climate change mitigation measures to protect the marine ecosystem and fishery resources, a Tobit regression model was implemented.

The results show that these communities are likely to pay to safeguard fish resources and the marine ecosystem, owing to their social and economic importance for these communities. In particular, this study’s findings highlight that the individuals’ attitudes towards climate change, social pressures and their perception of the phenomenon play a significant role on their intention to support mitigation policies. Moreover, the findings demonstrate that the communities most threatened by the negative effects of climate change are more willing to contribute financially to protect fish resources and the marine ecosystem.

A limitation is related to the adopted methodology. In particular individuals’ intention to adopt pro-environmental behaviours does not always translate into real WTP through additional taxes.

The value of the research stems from its unique collective cross-communal comparison of attitudes and intentions, its parallel identification of behavioural drivers at the individual level and its prescriptive conclusions of both scholarly and practical worth.

The study aims to provide important insights into environmental attributes that are relevant to consumer's choices in purchasing canned tuna fish, and how much these attributes and socio-demographic individual characteristics relate to the frequency of consumption.

An online survey of 251 Italians was carried out. Socio-demographic variables and environmental attributes of the product that consumers pay attention to were considered in a two-step analysis: a cluster analysis used to create a segmentation of people's profiles that are further characterised; a binary logistic regression to assess the significance of attributes in relation to the frequency of canned tuna consumption.

Among attributes that respondents pay attention to when purchasing canned tuna, the country of origin is the aspect most considered, while other characteristics with a higher content of environmental sustainability received minimal attention. Three clusters emerged: the smallest one, insensitive to sustainability issues; an intermediate group which is mindful of sustainability attributes; and the biggest cluster which is “sustainability inconsistent.” Moreover, respondents who reported concerns about the environmental impacts of tuna production are less likely to consume the product than other consumers; attention paid to the method of farming, the presence of children and a young age show willingness to consume tuna.

This study contributes to the literature on canned tuna consumption by focusing on the attention that consumers pay to environmental product attributes in their purchasing choices. The relevance of this topic might be envisaged in relation to several environmental issues associated with tuna production and consumption, and to the economics and strategies of the tuna industry, being canned tuna among the most internationally traded seafood products.

The purpose of this study is to investigate international trade determinants, paying special attention to variables related to climate change and non-tariff measures (NTMs), as they shape more and more world trade flows, with particular incidence on globalised goods, such as wine.

Based on panel data of Port wine exports to 60 countries, between 2006 and 2018, a gravity model has been estimated through Poisson pseudo-maximum likelihood. Explanatory variables include NTMs, mean temperature, temperature anomaly, gross domestic product (GDP), exchange rate, ad valorem equivalent tariffs and home bias.

The findings show that exports are inversely related to both mean temperature and temperature anomaly in importing countries. Regarding NTMs, it is found that only part of them are trade deterrent. Additionally, purchasing power in importing countries is one of the main determinants of Port wine exports.

The results show that, besides traditional economic variables, policymakers and wineries should include in their exports' decisions the impact of variables related to climate change and NTMs.

The novelty of this paper is to incorporate the impact of climatic variability of importing countries as a determinant of international trade of wine. Most former studies inspired of the gravity model consider explanatory variables such as GDP and exchange rate, and more recent ones started to consider NTMs too, however, this study may be the first paper to include the impact of climate change (quantified by mean temperature and temperature anomaly in importing countries) on exports.