R & D

Project Description:

In 2021, within the framework of the RESEARCH–CREATE–INNOVATE programme, the company’s R&D proposal with code T2EDK-00726 was approved for the implementation of the MyTravel booking system.

MyTravel is an innovative booking platform based on artificial intelligence algorithms designed to identify optimal “matches” between tourism service providers (hoteliers, accommodation providers, etc.) and customers, effectively creating a best-fit auction mechanism.

In addition, a second objective of the project was the adaptation of these algorithms to generate and recommend personalized tourism guides (points of interest, attractions, entertainment venues, cultural and historical sites, etc.) tailored to each visitor’s personal preferences. The project was successfully completed in August 2023.

MyTravel 2.0, approved within the framework of the RESEARCH–INNOVATE programme under proposal code EKPAR03-0014883, represents the proposed extension of the “MyTravel” project into new use cases. It is designed to leverage the proven mechanisms of forward and reverse auctions in order to strengthen economic activity, improve tourist satisfaction, and promote sustainable development in remote regions of Greece.

By extending the auction systems to vehicle rentals, maritime transportation, marina bookings, and integrated travel packages, while also enhancing the tourism guide system, we aim to create a comprehensive, user-friendly platform that benefits both tourists and local businesses.

This project aligns with our commitment to continuous innovation and development, ensuring the long-term impact of our technologies on the tourism industry of our country.

The primary objective is the integration of complex combinatorial booking systems based on auctions into various sectors such as vehicle rentals, maritime transportation, and integrated travel packages.

A secondary objective is the enhancement of the personalized tourism guide generation system by taking into account real-world constraints such as the user’s mode of transportation, available time, and the operating schedules of various points of interest. In this way, the generated guide will be more complete and accurate.

Objectives:

1 . Expansion of the auction model based on qualitative and quantitative criteria to additional services related to the tourism product. Indicative examples include transportation bookings, sailing yacht reservations, and alternative tourism activities.

The existing model will be extended to support different categories of services. To achieve this, the current algorithms will evolve to support complex user searches involving multiple combined tourism services.

The matching algorithms will automatically rank the combined offers presented to users based on their estimation of the best overall offer for each user. To meet the requirements of combinatorial products, a new version of the algorithms will be developed incorporating cost-function optimization mechanisms.

2. By operating the initial MyTravel platform in real market conditions, we will focus on creating statistical profiles of user preferences (using data analysis techniques), tourism provider recommendations, and successful auction patterns. These insights will be made available to participating stakeholders (e.g., tourism service providers), enabling them to derive valuable information and recommendations for decision-making.

3. An additional extension will be explored in the area of proposed tourism experiences. Emphasis will be placed on creating complete tourism experiences where services or products participating in the auctions may also be combined, allowing users to optionally “purchase” them (e.g., purchasing an excursion package).

Furthermore, regarding tourism recommendations and the need for personalization, an interesting extension will be for generated recommendations to also consider the transportation means available to the user (e.g., 4×4 vehicle, bicycle, car, boat, walking, etc.), as well as the user’s available time and time constraints related to visits (e.g., museum opening hours).

Expected Results:

1 .Expansion of the auction paradigm based on qualitative and quantitative criteria to additional tourism-related services such as transportation bookings, sailing yacht reservations, and alternative tourism activities.

The existing model will be extended to support multiple service categories. Existing algorithms will evolve to support complex searches involving multiple combined services.

The matching algorithms will automatically rank combined offers according to their estimation of the best combined offer for each user. To support combinatorial products, a new version of the algorithms incorporating cost-function optimization will be developed.

2. Using operational data from the MyTravel platform, we will focus on generating statistical profiles of user preferences (through data analysis techniques), tourism provider recommendations, and successful auction outcomes. Participating stakeholders (e.g., tourism service providers) will be able to utilize this information to gain valuable insights and recommendations for strategic decision-making.

3. A further extension will be explored regarding the generation of proposed tourism experiences. The focus will be on creating complete tourism experiences where services or products participating in auctions may be combined and optionally purchased by users (e.g., excursion packages).

Additionally, the generated recommendations will take into account both the transportation means available to the user (e.g., 4×4 vehicle, bicycle, car, boat, walking, etc.) and the user’s available time, as well as time restrictions related to visits at specific locations (e.g., museum visiting hours).

All of the above will be implemented as extensions to the already existing and operational platform www.MyTravel.biz.

The successful implementation of MyTravel serves as the primary driving force behind the need to expand the system according to the specifications of MyTravel 2.0 and its ambitious objectives for generalizing the core concept into a broader ecosystem of complex combinatorial tourism bookings.