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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.

The purpose of this paper is to call for a scrutiny of the dualist approach to business-to-business (B2B) and business-to-customer (B2C) marketing in industries driven by consumer-generated content. It posits that individual consumer-centric factors are influential for B2B marketing as well in sectors such as the travel industry and investigates the determinants of tourists’ intention to use social media websites for travel planning.

Integrating constructs from IS and marketing literature, the paper proposes information quality and perceived enjoyment as antecedents of perceived usefulness, attitude and intention to use. The research model is tested using data from social media users with experience in travel planning.

Results show that perceived usefulness and information quality are stronger predictors of attitude and behavioral intention than perceived enjoyment. Enjoyment was not found to be strongly influential. Relevancy and reliability of information and its usefulness concerning travel-planning needs were found more influential.

Data were collected from social media users, raising possible issues of representativeness.

The paper offers clarity regarding antecedents of downstream user behavior which can be of significant value. Demarcations in B2B and B2C perspectives blur in the context of social media, enabling more effective integration.

The paper brings in and validates the roles of information quality and enjoyment as influencers of behavior. Identifying the travel industry as a sector having greater likelihood of B2BC convergence, the paper extends IS adoption research to user-interactive sites in the travel-planning context, which can benefit the consumer as well as the supply side.

The purpose of this paper is to examine what influence travelers’ adoption of online reviews, and whether the online reviews will influence their travel planning decisions.

Data were collected from 193 respondents from eWOM websites and analyzed using structural equation modeling.

The results revealed that eWOM has a significant influence on travel decisions. Furthermore, travelers were willing to adopt information from eWOM and this information was useful in their travel planning and decisions. Gender and time spent on online reviews were found to affect travel planning and decisions. Travelers also found that the reviews and issues raised in eWOM had credibility and were of good quality.

The study was not able to incorporate all factors which may be relevant to this study and so further theoretical development may be necessary to develop the conceptual model. The sample size, while adequate, can be expanded further.

Operators and administrators of eWOM can use these findings to develop more user-friendly interfaces so that more positive reviews and sales can be generated.

The results showed that travelers who adopt the information in eWOM will, in turn, use eWOM in their travel planning. This confirms the importance of eWOM and travelers in general will translate their pre-travel decisions into actual travel planning.

This research extended existing eWOM and information system adoption studies and focused on the travel planning context. This research validated the significant roles of eWOM argument quality and credibility in predicting the information usefulness of eWOM.

This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in India by extending the technology adoption model (TAM) with context-specific variables.

To understand the customers’ behavioral intention and AUE of AI-powered chatbots for tourism, the mixed-method design was used whereby qualitative and quantitative techniques were combined. A total of 36 senior managers and executives from the travel agencies were interviewed and the analysis of interview data was done using NVivo 8.0 software. A total of 1,480 customers were surveyed and the partial least squares structural equation modeling technique was used for data analysis.

As per the results, the predictors of chatbot adoption intention (AIN) are perceived ease of use, perceived usefulness, perceived trust (PTR), perceived intelligence (PNT) and anthropomorphism (ANM). Technological anxiety (TXN) does not influence the chatbot AIN. Stickiness to traditional human travel agents negatively moderates the relation of AIN and AUE of chatbots in tourism and provides deeper insights into manager’s commitment to providing travel planning services using AI-based chatbots.

This research presents unique practical insights to the practitioners, managers and executives in the tourism industry, system designers and developers of AI-based chatbot technologies to understand the antecedents of chatbot adoption by travelers. TXN is a vital concern for the customers; so, designers and developers should ensure that chatbots are easily accessible, have a user-friendly interface, be more human-like and communicate in various native languages with the customers.

This study contributes theoretically by extending the TAM to provide better explanatory power with human–robot interaction context-specific constructs – PTR, PNT, ANM and TXN – to examine the customers’ chatbot AIN. This is the first step in the direction to empirically test and validate a theoretical model for chatbots’ adoption and usage, which is a disruptive technology in the hospitality and tourism sector in an emerging economy such as India.

This paper aims to investigate antecedents of using non-travel-specific social media (specifically Facebook) for travel decision-making before a leisure trip.

Based on an online survey of 426 young travel consumers from Italy and Sweden, this work applies structural equation modeling and multi-group analysis.

The study finds support for most of the conventional TAM-related constructs: perceived usefulness, perceived enjoyment and intention, while ease of use is not found relevant in this context.

Results shed light on the antecedents of using non-travel specific social media in two countries. Future research might focus on validating the factors identified and add others that might shape usage in the selected countries. Future studies could further investigate possible differences arising from culture, country of origin and age. The analysis can also be extended to other countries.

The analysis might help managers in the hospitality and tourism sector by providing an understanding of the cognitive factors which determine travelers’ decision to use Facebook for trip planning. Thus, managers should get to know these factors in their effort to influence social media in hospitality and tourism settings.

The findings offer interesting perspectives on the applicability of conventional models to the context of non-travel-specific social media platforms. The exploration of cross-cultural differences also adds to the extant body of knowledge.

Social interaction is a vital facet of life for all age‐groups; for older individuals, the exercise of interpersonal exchange, and the expectation of an accompanying sense of well‐being, can assume an even greater importance when other aspects of life no longer provide opportunities for positive reward. Sociability experiences are likely to influence major indicators of both emotion and cognition, such as life and context satisfaction. The demonstration of personal competence, as may be found in the exercise of problem‐solving strategies, is also an important facility for seniors. This study of both domestic and international senior tourists has examined preferences for travel planning as the expression of a measure of personal control that are associated with sociability needs in regard to family and friends, cultural contacts, entertainment and nightlife, and to retail experiences. Also examined was the extent to which various sociability needs and planning control preferences influence measures of destination satisfaction, intention to return and also a willingness to recommend the destination. This study has found that seniors with higher sociability needs for cultural contact and associated with family and friends would more likely perceive the necessity to prepare for their trip, and also would express higher levels of satisfaction; destination satisfaction was also found to be associated with both the expressed intention to return to the destination, and also a willingness to recommend the destination to others; travel planning was not found to be associated with destination evaluative measures. Implications of these findings for destination managers and for researchers in the senior travel domain are considered.

The aim of this paper is to investigate the relationship between consumer self‐confidence, product expertise, and travel experience in the context of travel information search during vacation planning.

The research design is based on a panel study to monitor trip planning processes of Austrian travelers. A structural model is used to assess to what degree consumer self‐confidence, product expertise, and travel experience affect travel information search and to examine the influence of consumer self‐confidence on product expertise.

Findings from the study show that consumer self‐confidence significantly affects product expertise. Travel experience, on the other hand, positively influences product expertise that again is positively related to travel information search. No significant relationship is established between travel experience and travel information search.

While most of the previous studies investigated information search using cross‐sectional data, this study addresses the need for more accurate research on information search adopting a panel design. One major limitation of the study is the small sample size. Results from a larger sample might be different in regards to the magnitude of the relationships.

This study contributes to the overall understanding of how knowledge and ability‐related factors impact travel information sourcing. The tourism literature reveals no other study that has simultaneously quantified consumer self‐confidence and product expertise during trip planning.

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.