Passport – a global database for market, industry, and consumer analysis

Library News September 26, 2025
VILNIUS TECH Library invites you to explore global market trends with Passport (Euromonitor International) – an international market research platform covering 210 countries and nearly the entire global consumer market. Here you will find data and analyses on industries, companies, the economy, and consumer behavior. Passport helps to develop informed strategies, create forecasts, prepare SWOT or PEST analyses, and build analytical skills valued by employers.
 
Passport stands out with its unique features:
  • A global and local market metrics database supported by written analysis;
  • A uniquely comprehensive primary and secondary research program conducted in each country;
  • Standardized international definitions for global data comparison;
  • Consolidated regional and global data for a complete picture;
  • A single online gateway to strategic business information across your commercial environment, easily shared with as many teams in your organization as you wish.
Why use Passport?
  • Global coverage – data from more than 200 countries and 99.9% of the world’s consumers.
  • Comprehensive information – both quantitative (statistics, forecasts) and qualitative (analytical reports, expert insights).
  • Wide range of topics – from industry sectors (food, beverages, beauty, health, technology, finance, etc.) to consumer lifestyles, purchasing habits, and demographics.
  • Forecasts and trends – not only showing the current situation but also analyzing how markets will evolve in the future.
  • Academic value – useful for coursework, master’s or doctoral theses, presentations, and research projects.
Who can benefit?
  • Students – in economics, business, marketing, sociology, public administration, tourism, or other fields of study.
  • Lecturers – for lecture material and practical examples.
  • Researchers – for comparative international studies, data analysis, and strategic insights.
Passport content includes:
  • Market sizes and shares, market entry studies;
  • Company, product, and brand data;
  • Historical data and forecasts;
  • Global and regional overviews;
  • Industry analysis;
  • Country reports;
  • Company profiles;
  • Consumer segmentation and insights;
  • Economic factors and analyses;
  • Policy recommendations;
  • Competitor analysis and benchmarking;
  • SWOT and PEST analyses;
  • Visual report summaries for identifying trends;
  • Data processing tools;
  • Risk assessment;
  • Innovation;
  • Statistical modeling;
  • Export strategy.
Join VILNIUS TECH Library’s e-resources and try Passport – a reliable tool to support your research or studies!
 
User guides Passport > Passport Help Centre > Help guide and videos > Passport

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Link to Passport webinars (past and upcoming): https://www.euromonitor.com/webinar
 
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Related news

New doctoral dissertation
New doctoral dissertation
VILNIUS TECH Library invites you to follow the published new dissertations. The dissertation „Control of Robot Path Using an Artificial Intelligence System by Fusing Sensor Signal“ („Roboto trajektorijos valdymas dirbtinio intelekto sistema suliejant jutiklių signalus“) prepared at VILNIUS TECH by Vygantas Ušinskis. The dissertation was prepared in 2021–2026. Scientific consultant – Prof. Dr  Vytautas Bučinskas. The dissertation was defended at the public meeting of the Dissertation Defence Council of the Scientific Field of Mechanical Engineering in the Aula Doctoralis Meeting Hall of Vilnius Gediminas Technical University at 10 a.m. on 30 April 2026. The dissertation examines the problem of local robot navigation, where sensor data must be processed in real time to assess the environment and generate an adaptive motion trajectory. The research object is a local navigation system with sensor fusion for mobile robots operating in tunnels and confined channels. Navigation is divided into four parts: environment assessment, localisation, path planning, and motion execution. The analysis of localisation technologies enables the selection of an effective sensor set for obstacle detection. Heuristic and artificial intelligence methods allow generating an optimal trajectory that avoids collisions and maintains the goal. The work addresses navigation and obstacle detection in human-inaccessible environments using a cost-efficient combination of active and passive sensors, with experimental validation of the system’s performance. The dissertation consists of an introduction, three main chapters, conclusions, references, and a list of the author’s scientific publications on the topic of the dissertation. The introduction presents the problem, relevance, research objective and tasks, methodology, scientific novelty, practical significance, and defended statements, as well as the author’s publications and the structure of the dissertation. The First Chapter presents a literature review, including an overview and comparison of global and local path-planning methods, localisation technologies and their combinations, and sensor-fusion approaches used in mobile robots. Key factors affecting reliable navigation are identified, forming the basis for the dissertation tasks. The Second Chapter describes the developed research methodology for autonomous tunnel navigation: the operating principles of the red, green and blue (RGB) channel-camera- and laser-based optical obstacle detection system, sensor-fusion techniques, and the application of modified Vector Field Histogram (VFH) and machine-learning-based path-planning methods. The Third Chapter presents the research results: optical system experiments, path-planning simulations, a comparison between machine-learning and modified VFH methods, and the testing of the constructed robot prototype in a laboratory environment. Five research papers have been published on the topic of the dissertation: three in journals indexed in the Web of Science database, and two in conference proceedings. Additionally, five conference presentations related to the dissertation topic have been delivered in Lithuania and abroad. Doctoral dissertation readers can search via VILNIUS TECH Virtual Library.  
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