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Independent travelers are those vacationers who have booked only a minimum of their transportation and accommodation arrangements prior to departure on the vacation. Independent travel is an important and growing sector of worldwide tourism. Choice of vacation itinerary for the independent vacation represents a complex series of decisions regarding purchase of multiple leisure and tourism services. This chapter builds and tests a model of independent traveler decision-making for choice of vacation itinerary. The research undertaken employs a two-phase, inductive–deductive case study design. In the deductive phase, the researcher interviewed 20 travel parties vacationing in New Zealand for the first time. The researcher interviewed respondents at both the beginning and the end of their New Zealand vacations. The study compares pre-vacation research and plans, and actual vacation behaviors, on a case-by-case basis. The study examines case study narratives and quantitative measures of crucial variables. The study tests two competing models of independent traveler decision-making, using a pattern-matching procedure. This embedded research design results in high multi-source, multi-method validity for the supported model. The model of the Independent Vacation as Evolving Itinerary suggests that much of the vacation itinerary experienced in independent travel is indeed unplanned, and that a desire to experience the unplanned is a key hedonic motive for independent travel. Rather than following a fixed itinerary, the itinerary of an independent vacation evolves as the vacation proceeds. The independent traveler takes advantage of serendipitous opportunities to experience a number of locations, attractions and activities that they had neither actively researched nor planned.

This paper aims to focus on time-related factors influencing on an itinerary planning system. The research objective is to produce an itinerary planning system which balances between the limited time of traveler and the number of tourist attractions they can visit. This system should facilitate travelers by presenting candidate itineraries that visit attractions as much as possible under several time-related factors.

To achieve the goal, an itinerary planning system has been designed and developed. The system considers several time-related factors including acceptable total travel time specified by travelers, time-related factors at an attraction (e.g. time zones, opening hours and visiting time) and time-related factors of traveling (e.g. road obstructions, weather, date and time and rest time). A routing algorithm which is aware of these time-related factors has been introduced to find candidate itineraries.

The performance of developed itinerary planning system has been evaluated by measuring speed and accuracy of seven traveling situations under different time-related factors. The experimental results indicate that the proposed routing algorithm spends less planning time than the traditional exhaustive routing algorithm. The efficiency of the proposed algorithm over the exhaustive algorithm is approximately 46 per cent while the accuracy is equal. Additionally, this designed system is evaluated by usability testing from nine experts. The evaluation is performed by measuring the user satisfaction level with the ability of user–system interaction. The results show that the overall system usability is in very satisfied level.

The designed itinerary planning system has three limitations. First, Google maps technology could not find information of some tourist attractions because these places were marked with several coordinates on the map. Second, holiday periods are manually kept into the database of system; therefore, it is necessary to annually and manually update the information. Third, the developed system is an online planner; thus, the speed of system depends on the bandwidth of users.

The designed itinerary planning system considers time-related factors as much as possible and more than the existing planning systems. This implies that the designed system is one of the most accurate planning systems in practice. Thus, the tourism business could rely on the developed itinerary planning system to help travel agents plan a travel itinerary properly and receive an accurate and up-to-date travel explanation to their customers.

This research proposes the novel design and implementation of an itinerary planning system which can suggest candidate itineraries, which visit maximum attractions under several time-related factors.

Travelers are increasingly planning trips using smart travel planning apps to manage travel-related activities. They obtain their preferred tour itineraries with the use of these apps and subsequently choose their tour destinations. Therefore, the purpose of this study is to investigate the effects of smart tour itineraries on travelers and explain what drives the continual use of them.

Drawing on the unified theory of acceptance and the use of technology model and experiential consumption (UTAUT), the authors conducted this study in Malaysia with a sample of 307 travelers who are familiar with the use of mobile apps.

The results confirmed that all the UTAUT dimensions except the facilitating condition are significantly related to the intention to use the itinerary. Both the hedonic and utilitarian values in personal consumption significantly motivate the travelers in the behavioral intention to use the itinerary.

This paper offers a good explanation of how the itinerary plans can be used by examining the theories behind the current app’s usage. Many researchers have examined the adoption of the smart travel apps, which has rarely been tied to the antecedents that drive how the travelers use itineraries that are designed by the smart travel apps. This study contributes to the research regarding using the mobile travel apps by developing an integrative model to explain the traveler intentions to use smart travel itineraries.

游客越来越多地使用智慧旅游计划App来管理他们的旅游相关活动。他们通过这样的App获得行程从而选择他们旅游目的地。因此, 本论文旨在研究智慧旅游行程对游客的影响, 并探究哪些因素驱使他们继续使用智慧旅游行程。

本论文采用UTAUT模型, 在马拉西亚取样, 共搜集到307位熟悉移动App的游客数据。

研究论文结果肯定了UTAUT各项因素除了辅助条件, 其他因素都显著与使用智慧行程息息相关。享乐型价值和实用型价值都对游客个人使用行为有着显著效果。

本论文通过检验App使用理论解释了行程计划如何被使用。许多研究学者已经检验了智慧旅游App的使用, 但是很少真正与游客如何使用App生成行程的驱动因素相结合。本论文对理论有贡献, 通过开发整合模型以解释游客使用智慧旅游行程的行为。

The growth of online data and services on the Web have have led to the Web become an indispensable tool for the tourist industry. It is not denied that various approaches bring benefits for visitors, in supporting their searching for tourist attractions, such as interesting places for the visit, eating or staying. However, like a coin has two sides, too much information would present a difficulty for people when planning their journeys. Generally, tourists usually have problems when trying to find satisfactory accommodation if references to nearby restaurants, sights or event locations are lacking. In addition, travelers suffer from the information overload when they look for information about potential destinations, events and related services. Providing relevant and up‐to‐date information for the tourists with different personal interests is still a challenging task for the tourist guide information systems. The purpose of this paper is to propose a semantic approach for searching tourist information and generating travel itinerary.

The paper focus on introducing an ontological model for representation of tourist resources as well as traveler's profile. Based on this model, smart user interfaces facilitating the semantic search have been implemented in the mobile travel guide application. In addition, the authors propose an algorithm for generating travel itinerary which combines semantic matching with ant colony optimization technique.

The Semantic Tourist informAtion Access and Recommending (STAAR) system, which has been implemented to promote the travel activity in Hanoi, reveals the advantages of the semantic approach in the development of smart application with ontology‐based, user‐friendly interface and high precision information search features. An experiment was conducted to show that the proposed algorithm generates travel itinerary relevant to both criteria of itinerary length and user interest.

This paper presents a novel algorithm for planning a travel itinerary that is optimized on the length as well as semantically matching the user interests.

This study aims to adopt a holistic approach to understand cruise revenue management (RM) practices that cover ticket and onboard revenues, through a cross-disciplinary literature review and practitioner interviews. An integrated cruise RM framework was developed and served as a blueprint for future cruise studies and practices.

A multi-stage approach was adopted, including a systematic literature review, two-waves of interviews with 26 cruise industry practitioners and the development of a holistic RM framework.

This study clarifies cruise RM functions across product planning, delivery stages and identifies ticket and onboard RM components. These are incorporated into the integrated framework, with weather and itinerary/ route attractiveness as additional considerations. Interviews revealed that there is no difference in the RM cycle before and during the COVID-19 pandemic, although strategies and tactics may vary in response to the market situation.

Suggestions are made regarding product and service bundling and ways for ticket and onboard revenue teams to work together to optimize total revenue. Future research directions are also provided under the categories of RM applications and concepts, ticket core activities, onboard core activities and overall issues.

To the best of the authors’ knowledge, this is the first paper to conduct a cross-disciplinary systematic literature review of cruise RM without imposing publication dates or specific databases and the first to develop an integrated cruise “total” RM framework that includes ticket and onboard revenues.

Social media has fundamentally changed the leisure travel behavior of Singapore residents. The purpose of this paper is to focus on Facebook and its impact on travel behavior. The study focuses on Singapore residents.

A total of 16 input and five output variables were tested, with a sample of 203 Facebook users residing in Singapore. Primary data modeling was done using ADANCO, a structural equation modeling tool that uses composite modeling approach for hypothesis testing. The analysis performed an estimated structural model and then determined the best model fit by measuring reliability, validity and path analysis and estimating model parameters.

Research findings indicate that Facebook has had a strong behavioral influence on the frequency of travel, itinerary planning and social sharing, while it had no impact during the destination-selection stage of travel planning.

Facebook’s influence on leisure travel behavior confirms the theory of planned behavior proposed by Icek Ajzen. From Facebook’s perspective, the outcome of this study is helpful in recommending the best use of the platform for destination providers.

This chapter introduces its readers to the concept of tourism. It sheds light on the rationale for tourism, as it explains the tourists’ inherent motivations to travel. It also describes different aspects that together make up the tourism industry. Tourists travel to destinations that are accessible to them. They require accommodation if they are visiting a place for more than 24 hours. Leisure and business travellers may also visit attractions, and engage in recreational activities. Hence, the tourist destinations should have the right amenities and facilities. In this light, this chapter clarifies how destinations may offer different products to satisfy a wide array of tourists. Tourism products can include urban (or city) tourism, seaside tourism, rural tourism, ecotourism, wine tourism, culinary tourism, health tourism, medical tourism, religious tourism, cultural (or heritage) tourism, sports tourism, educational tourism, business tourism (including meetings, incentives, conferences and events), among others.

This study investigates the impact of tourists’ perception of consumer-generated content (CGC) on their travel behaviors. Online questionnaire survey was conducted on the clients of travel agency along with onsite interviews of visitors at several busy tourist destinations/spots in Taiwan including Alishan, Sun-Moon Lake, and airports. In total 316 responses were generated. The findings indicate that usability of social media is the strongest factor that contributes to respondents’ perceived functional and hedonic quality. Functional quality of social media then draw respondents’ awareness that eventually increases their intention to visit a destination of interest. The results also indicate that functional quality is more important than hedonic in terms of increasing the propensity of using social media.