Athens University of Economics And Business

Athens University of Economics and Business brings together a School of Economics, a School of Business, and a School of Information Sciences and Technology. Across these schools, its public academic map names international and European economic studies, economics, management science and technology, business administration, accounting and finance, marketing and communication, informatics, and statistics. This structure is useful when a question appears to belong to several areas. A market question may concern prices, household choices, an organisation's strategy, financial records, a communication campaign, software behaviour, or a statistical pattern. Those are related, but they require different units of analysis and different forms of material.

The university's Athens setting can also make an economic or digital issue more specific. A study of tourism, transport, retail, housing, public communication, or a local service can begin with an observable process rather than a general ambition to understand the economy. A researcher might focus on a transaction record, consumer decision, text, online interaction, firm practice, policy document, or defined set of locations. The next step is to describe what varies or remains uncertain. This can turn a broad subject into a question that an economics, management, informatics, marketing, or statistics route can actually address without assuming that all five use the same methods.

AUEB's doctoral page locates advanced research within the eight academic departments and describes work that contributes to scientific research and publication. The listed fields provide a useful reminder that a general theme needs a disciplinary home. International and European economic studies may focus on trade, institutions, policy, or cross-border relationships. Economics can centre on a model, measure, market, household, or historical series. Management science and technology can examine a decision process, system, optimisation problem, or organisational practice. Informatics may involve a dataset, algorithm, network, interface, or software task. Statistics can begin with the quality, distribution, or interpretation of a defined set of observations.

The same distinction matters for a phrase such as digital transformation. It could mean a change in a firm's workflow, a consumer's interaction with a service, a marketing message, a financial process, a data architecture, or a rule that shapes organisational decisions. A credible study does not need to solve all of those at once. It can name one system, group, period, or case and explain what observation might support an answer. The material may include data records, company documents, interviews, platform traces, policy texts, financial statements, or a comparison across markets. Once the material is named, the relevant AUEB department becomes clearer and the connection between economics and technology becomes testable.

The university presents departments in economics, business, information sciences, and technology as distinct but adjacent academic routes. This can help an investigator keep a question at the right scale. A city-level issue might concern the availability of a service, the flow of information, a business response to regulation, consumer behaviour, a digital payment practice, or the distribution of an outcome across groups. A market question could focus on a product, platform, communication channel, decision rule, or data pattern. The setting is useful only when it helps define the object and the comparison, rather than becoming a substitute for an explanation.

A practical AUEB enquiry can be organised around four decisions: what is being examined, where it happens, what condition matters, and what would count as a meaningful comparison. The object could be a record, transaction, message, dataset, model, organisation, policy, or group. The comparison might be between periods, places, firms, designs, or categories of users. This order lets a question move between economics, business, informatics, and statistics without losing precision. It also keeps the method proportionate to the material available, whether the work uses quantitative analysis, documents, interviews, modelling, or a combination that is justified by the question itself.