METHODS FOR SUSTAINABLE TOURISM PLANNING

This course provides students with solid methodological and quantitative modeling skills that are essential for analyzing economic and business systems and for supporting managerial decision-making.

Methods for Sustainable Tourism Planning introduces tools and approaches from management science in order to develop advanced competences in quantitative analysis and decision support for the governance of tourism destinations. The course is aligned with the degree program’s focus on sustainability and innovation in tourism.

By the end of the course, students will be able to design, analyze, and assess sustainable tourism planning policies and interventions by integrating data, quantitative models, and multiple criteria — economic, social, and environmental — into transparent and well-grounded decision-making processes.

More specifically, students will have developed the following knowledge and skills.

1. Knowledge and understanding
- Understand the main operational metrics of tourism pressure, including density, carrying capacity, and demand peaks, as well as the underlying monitoring logic.
- Know the main approaches to tourism demand forecasting, with particular reference to time series analysis and hierarchical models.
- Understand discrete choice models and the tools used to incorporate residents’ and visitors’ preferences into planning processes.
- Know the main causal identification strategies for policy evaluation, including difference-in-differences, synthetic control, and regression discontinuity design, together with key methodological risks such as anticipation and interference.
- Understand the foundations of multi-criteria decision analysis and optimization models for tourism planning.
- Know the basic elements of spatial analysis, visitor flow management, and data governance in public-sector settings.

2. Applying knowledge and understanding
- Build a system of key performance indicators (KPIs) to monitor congestion, impacts, and sustainability performance at the destination level.
- Develop tourism demand forecasting models and produce scenarios to support both operational and strategic decisions.
- Estimate and interpret choice models in order to assess visitor flow management measures, including diversion policies and willingness to pay.
- Apply impact evaluation methods to estimate the effects of tourism policies or investment interventions.
- Formulate and solve allocation and management problems, including those with sustainability constraints, and develop decision syntheses through MCDA tools.

3. Making judgements
- Critically assess model assumptions, limitations, and robustness, with particular attention to sensitivity analysis, validation, and data quality.
- Address and discuss trade-offs among conflicting objectives in a reasoned way, including those between residents and visitors, economic development and environmental protection, and short-term versus long-term goals.

4. Learning skills
- Critically review technical reports, academic literature, and open-data sources relevant to tourism analysis and planning.
- Update methods and tools in response to technological developments, including data analytics and artificial intelligence, as well as evolving policy needs.

Students are expected to have a basic background in statistics and econometrics, introductory knowledge of data analysis, and familiarity with computational tools such as spreadsheets and/or statistical software.
The course is taught in English.

The course is organized into thematic modules and adopts a data-driven, decision-oriented approach.

1. Monitoring pressure and forecasting demand
Analysis of the main tourism pressure and overtourism metrics; development of demand forecasting pipelines based on time series models and hierarchical reconciliation techniques, with applications to policy support.
2. Behavioral modeling and resident sentiment
Introduction to discrete choice models, with a focus on multinomial logit and nested logit specifications; estimation of willingness to pay and diversion ratios; integration of stated preference data, including discrete choice experiments, and resident sentiment analysis.
3. Causal inference and policy evaluation
Presentation of the main methods for causal policy evaluation, including Difference-in-Differences, also under staggered adoption, synthetic control, and Regression Discontinuity Design; discussion of the main challenges related to causal identification.
4. Optimization and multi-criteria decisions
Formulation of decision problems and introduction to optimization methods for tourism planning; use of Multi-Criteria Decision Analysis (MCDA) to balance objectives and stakeholder trade-offs.
5. Spatial spillovers and policy implementation
Analysis of visitor flow management and operational monitoring and control tools; introduction to spatial autocorrelation and spatial spillovers; discussion of data governance issues and communication of results to support policy implementation.
6. Artificial intelligence for sustainable tourism
Examination of the opportunities and risks associated with the use of artificial intelligence in sustainable tourism, with particular attention to data quality, bias, and transparency; discussion of use cases supporting forecasting, monitoring, and communication.

Course materials and reference readings, including research articles, institutional reports, datasets, and notebooks or worksheets, will be indicated by the instructor and made available through the Moodle platform.

Indicative recommended readings include:
- UNWTO reports on sustainability and measurement in tourism;
- academic and institutional contributions on overtourism and visitor flow management;
- technical notes and background materials on causal evaluation methods, with particular reference to Difference-in-Differences and synthetic control, as well as on Multi-Criteria Decision Analysis (MCDA) approaches.

Student assessment is organized in two stages: ongoing assessment and final assessment.
Throughout the course, students are encouraged to monitor and self-assess their learning through exercises and tests made available on the e-learning platform.
Final assessment is based on a written exam aimed at verifying the acquisition of analytical, problem-solving, and decision-support skills.
The exam requires students to formulate and/or analyze, and, where appropriate, solve one or more quantitative models related to typical tourism planning and management problems.

More specifically, students may be asked to:
• state and discuss the assumptions underlying the proposed models;
• explain the role, purpose, and limitations of a model as a simplified representation of a real-world context;
• interpret and discuss the results obtained, including their effectiveness and decision-making relevance.

Problems similar to those included in the final exam will be made available on the university e-learning platform.

Where the written exam does not allow a sufficiently clear assessment of:
• command of the technical language of the discipline;
• understanding of the fundamental concepts;
• the degree of autonomy and awareness shown in reasoning, justification, and connection of the acquired knowledge;
an additional oral exam may be required. This oral component serves as a complementary assessment tool in order to:
• clarify any ambiguities emerging from the written exam;
• directly verify conceptual understanding, use of specialist terminology, and critical reasoning skills;
• ensure a fair, consistent, and comprehensive evaluation of the competences actually acquired.

written and oral

The instructor is responsible for ensuring the authenticity and originality of all examinations and coursework. In cases of suspected academic misconduct, an additional on-site assessment may be required during the exams, which may differ from the standard format.

Final grading criteria
A. Marks in the 18–22 range will be awarded where students demonstrate:
• sufficient knowledge and understanding of the course contents, with reference to the main methods and tools for sustainable tourism planning;
• sufficient ability to apply analytical models and methods to basic problems in monitoring, forecasting, and decision support;
• limited ability to interpret data and results and to formulate independent judgments regarding planning policies and interventions;
• sufficient communication skills, especially in the use of the technical language of quantitative analysis and tourism planning.
B. Marks in the 23–26 range will be awarded where students demonstrate:
• fair knowledge and understanding of the course contents, with reference to quantitative methods and decision-support tools for sustainable tourism;
• fair ability to apply analytical models and methods to planning problems involving visitor flow management, forecasting, and policy evaluation;
• fair ability to interpret data and results and to formulate independent judgments in a coherent and reasoned way;
• fair communication skills, especially in the appropriate use of disciplinary technical terminology.
C. Marks in the 27–30 range will be awarded where students demonstrate:
• good or excellent knowledge and understanding of the course contents, with full command of the main methodological approaches to sustainable tourism planning;
• good or excellent ability to apply quantitative models and tools to complex problems of analysis, evaluation, and decision support;
• good or excellent ability to critically interpret data and results, discuss model assumptions and limitations, and formulate well-grounded independent judgments;
• fully appropriate communication skills, with rigorous and confident use of the technical language of the discipline.

The course is primarily delivered through lectures and is further supported by teaching materials and learning modules made available on the university’s Moodle e-learning platform.

These modules guide students through the analysis and solution of case studies based on real-world sustainable tourism planning problems, enabling them to compare their own individual or group solutions with those discussed by the instructor and with approaches adopted in professional and institutional practice.

1) Students should register for the course on the dedicated page (Methods for Sustainable Tourism Planning) of the university e-learning platform moodle.unive.it

2) Accessibility, Disability and Inclusion
Accommodation and support services for students with disabilities and students with specific learning impairments

Ca’ Foscari abides by Italian Law (Law 17/1999; Law 170/2010) regarding support services and accommodation available to students with disabilities. This includes students with mobility, visual, hearing and other disabilities (Law 17/1999), and specific learning impairments (Law 170/2010). If you have a disability or impairment that requires accommodations (i.e., alternate testing, readers, note takers or interpreters) please contact the Disability and Accessibility Offices in Student Services: disabilita@unive.it.

This subject deals with topics related to the macro-area "Circular economy, innovation, work" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development