Obtaining Data Values from Tourist Preferences

Satisfied customers are the main sustainability factor for the viability of any activity, and tourism has increasing relevance to the global economy and the economic development of many regions. In order to create better matches between tourist demands and preferences and the local supply, an understanding of tourists as decision makers is necessary. The aim of this work is to introduce a mathematical model that explains the decision-making process of tourists, other consumers, and tourism business managers. We used a mathematical model, taking into consideration the preferences of individuals and their strengths during the exploration and use of tourism resources. The integration of preferences into an IT tool provided extra support to the decisions of tourists and allowed better choices to be made in the execution of travel plans. In addition, the model can be used by resource managers. Understanding how tourists make decisions in each different situation can improve the allocation of available resources to satisfy their expectations. The proposed model is also adaptable to situations where it is necessary to decide among different options with a high degree of complexity.This work was supported by FCT, the Portuguese national funding agency for science, research and technology, Portugal. Projects UIDB/04674/2021. TRENMO S.A.info:eu-repo/semantics/publishedVersio

Differences in railway strategies: The empirical case of private, public-owned, and third-sector railways in Tokyo

The incorporation of public transport systems, particularly railway systems, into urban plans has been suggested as a good practice recommendation for decades. The business strategy for railway network expansion can account on the existing travel demand, the envisioned or the planned travel demand. This paper aims to explore the railway business strategy impact on population growth. An empirical assessment of the influence that business strategies of railway network expansions have on population growth is presented, by examining distinct types of business models (private-owned, public-owned, and third sector) and population growth in the Tokyo Metropolitan Area during 1970–2015, according to lag effects. Road expressways and subways were also considered. The research hypothesis states that railways with distinct business models may find different patterns of rail and land co-development. A panel-correlated standard errors model was used to examine the lagged effects, assessing three lag periods (5, 10, and 15-years). According to the findings, generally, but not consistently, private-owned, that diversified business, and third sector railways were positively associated, whereas public-owned railways were negatively associated with the population growth. The lag period assessment found inconsistent results except in private-owned railways during 1970–1990 with the 5-year lag having the greatest effect on population growth, except in the prefecture of Saitama