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Financial literacy is crucial in explaining a broader set of investment behaviors. This paper investigates what financial literacy, wine knowledge, risk propensity and wine purchase behavior have in common.

The analysis is on a questionnaire distributed online to an equal number of young adults from a traditional wine-producing and consuming country (France) and a country less linked to wine by tradition (the UK).

The analysis shows how financial literacy, financial education and financial risk attitudes impact the attitudes toward wine purchase decisions. Results indicate that participants prefer to drink wine for pleasure rather than for potential financial gain. Significant relationships exist between financial literacy, wine consumption frequency and willingness to store and pay for wine.

These results allow for a better understanding of wine purchasing behavior in light of willingness to pay, invest and store.

• (1)

  Financial literacy has a positive role in influencing wine storage and investments.

• (2)

  Culture shapes the impact of financial literacy, habits and risk on wine investments.

• (3)

  Gender and age have a role in influencing wine investments.

Financial literacy has a positive role in influencing wine storage and investments.

Culture shapes the impact of financial literacy, habits and risk on wine investments.

Gender and age have a role in influencing wine investments.

Digital political advertising has been essentially unregulated for a long time. More recently, a number of notable scandals, such as the Facebook–Cambridge Analytica affair and the external meddling in Brexit and the 2016 US elections, have compelled the European Union to take regulatory action. After discussing the growing role of political advertising for political parties and candidates and the major challenges this implies in terms of electoral integrity, this chapter explores the genesis, significance as well as the limitations of the Transparency and Targeting of Political Advertising (TTPA) Regulation. Introduced in 2024, the TTPA establishes a common regulatory framework across EU Member States ensuring minimum transparency requirements that digital platforms must comply with, including disclosure about the origins, parameters and funders of political advertisements directed to European citizens. While emphasising the important step forward of this Regulation for the countering of information manipulation and foreign interference in elections and the relevant shift in the EU relationships with platform services, we point to a number of problems that remain unaddressed, including the manipulative and deceptive use of political content, hate speech, misinformation and political polarisation.

Past research has emphasised the potential for conversational artificial intelligence (AI) to disrupt services. Conversely, the literature recognises customer expectations as fundamental to service quality and customer satisfaction. However, the understanding of users’ expectations for conversational AI services is currently limited. Building upon previous research that has underscored the importance of users’ expertise, this study aims to provide valuable insights into the expectations of users with varying levels of expertise.

Forty-five semi-structured interviews were conducted, on three populations: experts, quasi-experts and non-experts from various countries including Japan, France and the USA. This includes 10 experts and 11 quasi-experts, as in professionals in conversational AI and related domains. And 25 non-experts, as in individuals without professional or advanced academic training in AI.

Findings suggest that users’ expectations depend on their expertise, how much they value human contact and why they are using these services. For instance, the higher the expertise the less anthropomorphism was stated to matter compared to technical characteristics, which could be due to a disenchantment effect. Other results include expectations shared by all users such as a need for more ethics including public interest.

The study provides insights into a key yet relatively unexplored area: it defines three major expectations categories (anthropomorphic, technical and ethical) and the associated expectations of each user groups based on expertise. To the best of the authors’ knowledge, it also highlights expectations never detected before as such in the literature such as explainability.