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Machine Learning and Intelligent OptimizatioN applied to Tourism and Hospitality

Machines can learn from big data. Algorithmic optimization can deliver better and better solutions. The machine learning and intelligent optimization revolution is changing the world, now. Come and learn how to embrace the change, lead this algorithmic revolution and create opportunities.

In 2019 you can get all papers and equations from the web. But reading papers/blogs/social is not comparable with meeting and discussing with top experts, and with creating human connections between researchers, practitioners, and businesses.

This is why, in addition to lectures, we organize events where you can present your project and ideas and discuss face-to-face.
This is why we organize parties every evening (not because we like grappa and speck).

The school at July 5-9, 2019 is a full-immersion five-day residential course in an inspiring location, providing a stimulating environment for students, practitioners and business participants. The lecturers are world-renowned experts in scientific methods and tools for tourism and hospitality. In particular, the school focuses on methods based on data-driven models ("big data") and optimization.

Machine learning or learning from data is a theory for deriving flexible models by starting only from the data produced by the business. After a model is available, computers can simulate the effects of zillions of possible decisions, by predicting the output, and by creating and selecting one among the best decisions. Intelligent optimization is this automated process of creating in an intelligent manner a large series of possible solutions, aiming at improving the current way of doing business.

Download flyer of LION-APP in PDF, flyer of LION-APP in Word

Important dates

  • Registration deadline May 31, 2019
  • Workshop: Oral/Poster Presentation Submission deadline March 31, 2019
  • Workshop: Notification of Decision for Oral/Poster Presentation: May 15, 2019

LION-APP Courses

(in alphabetical order)

Demand Forecasting and Opinion Mining to Optimize Hotel Profit and Organization,
Professor Amir Atiya, Cairo University

Amir Atiya image LION-APP

In this short course I will review how hotel reservation systems work, including explanation of the reservation channels. These reservation-based data provides large amounts of information that allow us to optimize the hotel processes, especially the optimization of revenue. I will explain the analytics behind hotel revenue optimization. For successful revenue optimization, an accurate forecast of incoming reservations and occupancy is needed. I will review the major time series forecasting approaches, as applied to hotel data.

Hotel reviews on reservation sites are very informative for the guest, and guide him towards better hotel selection. Moreover, they give the hotel feedback that helps him to improve his services. Machine learning models have been introduced for automatic analysis of the reviews, leading to the so-called opinion mining concept. I will explain the concept, and provide an overview of machine learning models for opinion mining.

Machine Learning and Optimization in Tourism and Hospitality,
Professor Roberto Battiti and Mauro Brunato, University of Trento

Roberto Battiti image LION-APP Mauro Brunato image LION-APP

Like most businesses, tourism and hospitality are undergoing a phase of disruptive innovation caused by the wider adoption of computers, networks and, above all, sophisticated and powerful algorithms. Algorithms automate business processes in a partial or total manner, by starting from repetitive and simple tasks but progressively reaching also more complex and “creative” tasks, traditionally associated with human decision making. The concepts of “automated creativity” or “automated business innovation” sound like contradictions. We like to think that only human people can discover truly innovative ways of solving problems and radically improving business performance. In this course we summarize two theoretical advancements in the past years which permit this disruptive innovation: machine learning and intelligent optimization.

Managers and decision makers reach decision by some level of anticipation (expectation, prediction) of the effects of different choices. These decisions are based on a series of “What if?” questions, with answers given by expertise, gut feeling, or some level of logical and mathematical modelling. Machine learning or learning from data is a theory for deriving flexible models by starting only from the data produced by the business. After a model is available, computers can simulate the effects of zillions of possible decisions, by predicting the output (for example the total profit of the hotel), and by creating and selecting one among the best decisions. Intelligent optimization is this automated process of creating in an intelligent manner a large series of possible decisions, aiming at improving the current way of doing business.

Through machine learning and intelligent, optimization hotel managers have extremely powerful tools in their pockets to improve total profitability and customer satisfaction. It is up to them to understand the new possibilities (the overall vision), decide which possible changes they are considering (e.g., acting on prices, availability of different types, reservation rules, kind of offer, etc.), collect and organize the relevant data about the past performance, deliver them to ML tools to build models and run zillions of software experiments via intelligent optimization (IO) to identify improving solutions.

In this course we will highlight some fundamental tools and use simulation-based optimization software for exercises with the participants about managing a test hotel and measuring the improvement in profitability that can be obtained by LION techniques in realistic contexts.

Smart Tourism - Management and Marketing for the Whole Ecosystem,
Professor Dimitrios Buhalis, Bournemouth University

Dimitrios Buhalis image LION-APP

Professor Dimitrios Buhalis of Bournemouth University will explain that Smart Tourism revolutionizes tourism and hospitality and change market conditions and industry structure. This leads to tourism and hospitality organisations to readdress the sources of competitiveness and repositioning their strategy and operations in their marketplace. Network economics and strategies suggest that organization need to reengineer their processes to take advantage of their ecosystem. Technology has emerged as the pervasive and robust platform for the tourism organisation and destination distribution and management. The Web 2.0 and consumer generated content based social media engagement are revolutionising global tourism. New developments such as Augmented Reality provide incredible opportunities for tourism organisations to develop their competitiveness. Only tourism organisations and destinations that can take full advantage of the opportunities will be able to capitalise on the benefits in the future and enhance their competitiveness. This seminar will challenge participants to think of their use of technology and their digital foot print to maximise their visibility, engagement, conversion and loyalty. Participants will be encouraged to think of how they can cocreate tourism experiences and how they can develop benefits for all participants in the marketplace.

Smartness takes advantage of interconnectivity and interoperability of integrated technologies to reengineer processes and data in order to produce innovative services, products and procedures towards maximising value for all stakeholders. This reengineering enables shaping products, actions, processes and services in real-time, by engaging different stakeholders simultaneously to optimise the collective performance and competitiveness and generate agile solutions and value for all involved in the value system. Looking into the future this seminar will emphasise the importance ofnetwork competitiveness and how to maximise the benefits for all stakeholders. Smartness is the glue of interconnected and mutually beneficial systems and stakeholders and provides the infostructure for the value creation for all. Participants will be encouraged to consider how they can optimise their competitiveness based on optimising the performance of their networks in smart destinations and smart tourism and hospitality ecosystems.

Designing Tourism Places,
Professor Daniel R Fesenmaier, University of Florida

Daniel Fesenmaier image LION-APP

Over the past four decades many researchers have examined various components of the tourism system. This work along with other advances in science and technology delineates four essential advances which now enable tourism planners. First, the development of a considerable body of research in a variety of disciplines and areas of application ranging from psychology, social psychology, environmental psychology, geography, landscape architecture, urban and regional planning, economics, marketing, and communications provides a reasonably comprehensive understanding of the touristic experience and the factors influencing these experiences. Second, the development of the Internet and related technologies now enables researchers to collect and analyze traveler-related data almost anywhere and in real time; this new capability affords new opportunities to understand how travelers respond to various stimuli while in situ, thereby overcoming a number of important limitations of previous methods. Third, the coalescence of the basic theories and new technologies gives rise to a new understanding of design, which argues that it (i.e., design) is not simply a property of the artefact (i.e., event or place which supports the traveler experience), but rather it is a way of thinking. As such, design thinking is a basic process driving innovation and new ways for supporting the creation of customer value, i.e., the tourism experience. Finally, the development of new, highly sophisticated systems (including the Internet of Things (IoT) and the Quantified Traveler) for seamlessly tracking and communicating with visitors enables the tourism industry to manage the visitor experience in much more personal and innovative ways.

These developments in theory, methodology, and application provide the foundation for a new paradigm which can be characterized as Design Science in Tourism (DST) and supports a framework for designing systems and artefacts to improve travel experiences. DST is explicitly focused on the development of new artifacts and, as such, it provides the foundation for enabling tourism managers to develop innovative processes, systems and places. The tourism design system is comprised of six key components: (1) Themes, (2) Stories, (3) Atmospherics; (4) Affordances; (5) Co-creation; and, (6) Technology. As illustrated, each of these components represent a specific aspect of the system which determines which sensations are received and how they are interpreted and communicated so as to create memorable visitor experiences. Thus, one of the most important findings of this research over the past forty years is the clear linkage between environmental stimuli, sensation, emotions and decision making and the nature of tourism experiences.

Daniel Fesenmaier image LION-APP
The goal of this course is provide a foundation for identifying, describing and analyzing the linkages between these six components and the design of tourism places. The objective of the course is to prepare students to think critically about the relationships between these components of design, traveler behavior and the travel industry. Further, the course will encourage students to think creatively about how to design new functions of the tourism system. Last, this course will encourage students to consider the future of tourism and how these new smart technologies will shape it.

Introduction to Revenue Management and Dynamic Pricing,
Professor Jochen Gönsch, Universität Duisburg-Essen
and Professor Claudius Steinhardt, Universität der Bundeswehr München

Jochen Gönsch  image LION-APP Claudius Steinhardt  image LION-APP

Revenue management emerged after the deregulation of the US aviation industry in the 1970s. It instantly became a must-have in the airline industry. Today, it is also a critical success factor for hotels, car rentals, retailing and increasingly also industries like manufacturing. The field entails a series of quantitative methods to optimize revenue and profit by balancing uncertain, stochastic demand and inflexible capacity. In this course, we intuitively introduce the basic challenge of profit optimization. Then, we give an overview on key approaches including price-/capacity-based Revenue Management and overbooking and highlight the core ideas and key challenges underlying them. Finally, we give a brief outlook on current research topics.

Persuasive technologies for tourism and hospitality,
Professor Ulrike Gretzel, University of Southern California

Ulrike Gretzel image LION-APP

Persuasive technologies are those that elicit specific behaviors, manage to change attitudes or encourage users into forming habits by using fundamental principles of persuasion, such as social influence, scarcity or authority. Websites, recommender systems, mobile apps, robots, online games, social media platforms, etc. all rely on their persuasive capacity to keep users engaged and encourage particular responses or behaviors. This requires intricate knowledge of the social psychology of users and an understanding of how persuasion principles can be integrated into interfaces and algorithms. It also demands a basic understanding of the business models of the systems or tools to determine specific persuasion goals.

This course will provide an overview of persuasion principles and their applicability to different aspects of technology design. Specifically, it will discuss the persuasive potential of various technologies in the context of particular use scenarios and will point out specific challenges to persuasion for technology use/design in tourism and hospitality settings. It will further highlight the importance of persuasive technologies from a business perspective and debate benefits for users. It will also explore the incredible potential of persuasive technology to initiate positive behavior change (e.g. in the context of health or environmental sustainability) and will discuss ethical implications of persuasion, as the implementation of persuasive designs might lead to unwanted consequences such as technology addiction.

Robonomics and Tourism,
Professor Stanislav Ivanov, Varna University of Management

Stanislav Ivanov image LION-APP

The next 15-20 years will witness the massive introduction of robots – both as consumer robots (including companion robots) and industrial robots as result of the advances in robotics, artificial intelligence and automation. Economists expect this with mixed feelings. While some extort the benefits artificial intelligence and robotics will bring to societies, others predict a darker scenario. The massive introduction of robots and the transition of the economic system to robonomics (robot-based economy) will cause many people to lose their jobs, new jobs would be created, production facilities will scale down and change their geographic location, and the sources of employees’, companies’ and countries’ competitive advantages will change drastically. This will have profound implications on the nature of work, level and sources of incomes, leisure time, politics, international trade and relations, ownership rights, etc., hence leading to major social, economic and political challenges and tension. Societies will be forced to find unconventional solutions to these challenges – birth right patents, universal basic income, constant and fluid free life-long education of population, robot-based tax system, redefinition of human rights, etc. In this course, Professor Stanislav Ivanov will elaborate on the economic principles and drivers of robonomics, will pinpoint its benefits and challenges, and sketch some of the solutions to its challenges. Furthermore, the course will outline the implications of robonomics for the travel, tourism and hospitality companies – robots as tourists and service providers, impacts on servicescape, marketing, operations, human resource managements, performance, competitiveness, etc.

Website evaluation in tourism and hospitality,
Professor Rob Law, The Hong Kong Polytechnic University

Rob Law image LION-APP

The recent development of the Internet supports practitioners in tourism and hospitality to disseminate information, reach potential customers worldwide, and facilitate bookings through business websites. From the perspective of suppliers, a website is a worldwide distribution channel of products or service to consumers. From the perspective of consumers, the Internet enables them to access websites and make reservations anytime and anywhere. Therefore, a functional and easy-to-use website is crucial for managers to facilitate the process of reservation, thereby meeting the needs of consumers, and increasing revenue.

Website usefulness is of great importance when consumers evaluate a website. Website usefulness consists of website functionality and website usability. Website functionality refers to information provision (i.e. website contents and features), whereas website usability denotes information use and processing (i.e. design). Overall, a good website should be useful and easy to use. Easily accessible information, consistent appearance of content, and a good navigation system all contribute to the enhanced usefulness and ease-of-use of a website. Besides basic information about reservation, the information available on websites can be extended to a relational level, such as by integrating social networking sites, providing customized service and information on loyalty program, which will enhance customer relationships.

In this presentation, the historical background of the Internet will be introduced. Then, some recent research findings related to website, such as website visibility, website evaluation approaches, and website performance measurements will be illustrated with some real-life examples. After that, an overall picture of the progress and future development directions of websites will be presented. Specifically, terminologies used for website evaluation, measurements of website functionality and usability, chronological development of the mainstream website evaluation models from 1990s to present will be reviewed. The adoption of digital footprints in tourism will also be delivered in this presentation.

The ultimate goal of this presentation is to provide industry practitioners, post-graduate students, and other tourism professionals the insights on improving websites, such as exerting effort in achieving high-level information communication in order to bring more convenience and personalized service to consumers, and in the meantime, increase business revenue.

Multi-Criteria Recommender Systems in Tourism and Hospitality,
Professor Nikolaos Matsatsinis, Technical University of Crete

Nikolaos  Matsatsinis image LION-APP

Recommender systems are software applications that attempt to reduce information overload. Their goal is to recommend items of interest to the end users based on their preferences. To achieve that, most Recommender Systems exploit the Collaborative Filtering approach. In parallel, Multiple Criteria Decision Analysis (MCDA) is a well-established field of Decision Science that aims at analyzing and modeling decision maker’s value system, in order to support him/her in the decision making process.

In this course, we will present:
The basic concepts of Multiple Criteria Decision Analysis (MCDA) and Aggregation - Disaggragation approach.
Two recommender systems. Initially, a Multicriteria Recommender Systems whose purpose is to recommend items of interest to users based on their preferences will be presented. To achieve that, most Recommender Systems apply a widely used algorithm, named the Collaborative Filtering algorithm. In parallel, Multiple Criteria Decision Analysis (MCDA) is a well-established field of Decision Support Systems that aims at analyzing and modeling a user’s value system. In this system, a hybrid framework that incorporates techniques from the field of MCDA together with the collaborative filtering algorithm is proved to enhance the performance of existing Recommender Systems. More specifically, the Disaggregation-Aggregation approach of MCDA is exploited that builds user’s value system through iterative interactive procedures, where the attributes of the problem and the user’s global judgment policy are analyzed and then aggregated into a value system. Subsequently, system’s users are clustered into groups of similar preferences and the collaborative filtering algorithm adapted to multiple attributes is applied, to successfully propose items of interest to these users. The proposed methodology improves the performance of Recommender Systems as a result of two main causes. First the creation of user profiles prior to the application of collaborative filtering algorithm and second, the integration of multiple criteria in the recommendation process. Next, we will present the methodology and results, of a new hybrid multi-criteria hotel recommendation system. The problem of hotel recommendations using multi-criteria methods, as there are many parameters that users consider important and which should be taken into account for an accurate and efficient final recommendation. Within the methodology, we combine three different methods of analysis (MUSA, Sentiment Analysis, Filtering). A variant of WAP method is also used to create a preferential user profile for the system. We end up producing personalized product recommendations to system users, which are commensurate with their preferences. Additionally, the user is able to filter the available alternatives with a selection from a set of standard criteria. The use of the minimum satisfaction threshold, that is calculated using sentiment analysis in customer reviews, guarantees the quality of the recommendations. The recommendation system uses real reviews and ratings for hotels, as well as static hotel features that have been extracted, using data mining methods, from online hotel reservation platform. Inputs of the system are user choices, based on standard criteria, as well as classification of specific criteria in order to create her preferential model. The evaluation of the recommendation system is done by measuring the accuracy of forecasting of evaluations in a real-user experiment. For the case study, we used data for hotels in the prefecture of Chania, Crete.

Recent research directions in Dynamic Pricing and Revenue Management: Optimization and Big Data Forecasting,
Professor Kalyan Talluri, Imperial College London

Kalyan Talluri image LION-APP

In this tutorial we will cover recent approaches and advances in the optimization and estimation and forecasting aspects of Dynamic Pricing and Revenue Management. The availability of massively parallel computers and theoretical advances have led to new algorithms and approaches with both practical and theoretical interest in the area of network optimization.

Likewise, new machine learning approaches and the availability of new data sources is also influencing the area of estimation and forecasting of pricing models.

Join us at Trento

How to participate

The LION-APP Summer School is based not only on frontal lessons but on intense cross-disciplinary debates among lecturers and participants that address the most advanced and emerging areas of each topic. Each faculty member presents lectures and discusses with the participants during the school, a unique opportunity to fully explore their expertise.

The school will involve a total of 40 hours of lectures. According to the academic system the final achievement will be equivalent to 8 ECTS points for the PhD Students and the Master Students attending the summer school. A Certificate of Attendance will be given to all participants at the end of LION-APP.

Regular registration fee (before Feb 28, 2019)
  • € 580
  • € 380 for master and PhD students
Late registration fee (after Feb 28, 2019)
  • € 680
  • € 480 for master and PhD students

To encourage a rich interaction, participation is limited to about 60 participants. The registration deadline is May 31, 2019, but registration is on a first-come first-served basis. Register at Unversity of Trento website.

The registration fee includes participation in all courses and collateral school and workshop activities, social activities (including social dinner, social trip, additional evening activities), lunches and coffee breaks for the entire school duration. The organization is non-profit, we aim at covering the costs.

Trento offers many possibilities for accommodation. We will place agreements with some selected hotels in January 2019 but participants are welcome to pick their favourite hotel. Only remember to book hotels in advance, July is high season and Trentino is a popular touristic destination.

If you belong to an Italian public institution you need: invoice data for IT public institutions (.doc). If you are an employee of UNITN, fill in: afferenti UNITN (.doc).

Present your ideas at the Workshop (Paper Submission deadline: March 31, 2019)

The main objective of the workshop is to spark interaction, debate, feedback by peers (younger and senior). We encourage all PhD students (or interested reseachers) participating in the school to present their work to all participants in short frontal "elevator speeches" followed by poster sessions (and, of course, by the normal social interaction!). We feel that more effective/frank/open feedback can happen in a face-to-face context w.r.t. long oral presentations.
Longer oral presentations at the workshop will be allocated only to selected novel and completed research work passing a strict refereeing process.

Paper Format

Please prepare your paper in English using the Lecture Notes in Computer Science (LNCS) template, which is available here . Papers must be submitted in PDF. The minimum number of pages is 4, the maximum is 10.

Submission System

All papers must be submitted using EasyChair.

Location, travel, accommodation

Trento, Trentino - Südtirol, Italy

Trento is located in the northern Italian region of Trentino - Südtirol. Trento is an educational, scientific, financial and political centre, often ranking highly for quality of life, standard of living, and business opportunities. Close to Trento is Lake Garda, the largest lake in Italy, on the edge of the Dolomites mountains (fossile giant coral reefs). Glaciers formed this alpine region at the end of the last Ice Age. The region is well-known for historical places dating back to Roman times, cultural visits, rock climbing, mountain biking, sailing and windsurfing.

Closest airports are Verona (90 km), Bolzano (50 km), Milano-Bergamo, Treviso and Venezia (170 km). Bolzano is very small, we suggest you opt for the bigger airports. Verona, Milano-Bergamo, Treviso and Venezia offer many low-cost flights from most European cities. Directions to Trento can be found by Google maps.

Speedfly Canalone Neri (trailer) from "Il Baggi" (this is how you will feel after the LION-APP school :-)

We are aware that an important value of a school is to create opportunities for people to know each other, to discuss, to generate new ideas. Also to facilitate this informal interaction, as part of LION-APP we plan to organize (but final details will be communicated later):

  • A mountain-bike tour on the newly inaugurated path (mentioned as "the most spectacular bike path in Europe"), bikes and local guide included.
  • A boat trip on lake Garda with en evening visit of the historic greenhouses for growing lemons.
  • A social dinner in Trento with a visit of the ancient Roman archeological sites.


Contact us

Interested in sponsoring LION-APP?

You can contact the organization by emailing the main scientific organizer Prof. Roberto Battiti at the following address: roberto.battiti ((AT))
Remember to substitute ((AT)) with the usual @ to demonstrate that you are not a computer :)

If you want to reserve your place, register at Unversity of Trento website.
The registration deadline is May 31, 2019 but we expect that availability will be exhausted much sooner.


Chair and Local Chairs

  • Steering committee: Roberto Battiti (Head), Amir Atiya
  • Workshop Technical Program Committee:
    Graziano Abrate (University of Piemonte Orientale, Italy),
    Amir Atiya (Cairo University, Egypt),
    Rodolfo Baggio (Bocconi University - Milano, Italt),
    Adil Baykasoglu (Dokuz Eylul University, Turkey),
    Dimitrios Buhalis (Bournemouth University, United Kingdom),
    Lorenzo Cantoni (Università della Svizzera italiana, Switzerland),
    Jochen Gönsch (Universität Duisburg-Esse, Germany),
    Ulrike Gretzel (University of Southern California, US),
    C. Michael Hall (University of Canterbury, New Zealand),
    Stanislav Ivanov (Varna University of Management, Bulgaria),
    Robert Klein (Universität Augsburg, Germany),
    Cristiane Neri Nobre (PUC Minas, Brasil),
    Luís Nobre Pereira (University of Algarve, Faro, Portugal),
    Marina Predvoditeleva (National Research University Higher School of Economics, Moscow, Russia),
    Elisabetta Raguseo (Politecnico di Torino, Italy),
    Marianna Sigala (University of South Australia, Australia),
    Claudius Steinhardt (Universität der Bundeswehr München, Germany),
    Jean Tavares (PUC Minas, Brasil),
    Jan Van Der Borg (Università Ca' Foscari, Venezia, Italy),
    Soheil Yousefsibdari (University of Massachusetts, Dartmouth, USA)
  • Local organization committee: Mauro Brunato (Chair)
  • Social media specialist: Manuel Dalcastagnè
  • Communication and Registration: Staff per la Comunicazione - Polo di Collina, Divisione Comunicazione ed Eventi - Università degli Studi di Trento
  • Local liaison: A. Borlotti
Industrial sponsorship chair: David Moneo Ocaña, Business Development & Co-Founder of Algorth, Spain
David Moneo Ocaña image LION-APP

LION-APP Sponsors

We acknowledge sponsorship by:

Additional business sponsors have the opportunity to follow lectures, meet colleagues and participate in the events while supporting collateral activities of the school (e.g., a best paper award). Pls. contact us if interested.