Journal of Hospitality and Tourism Technology

Battiti, Roberto; Brunato, Mauro; Battiti, Filippo

2020 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-08-2019-0108

Many hotels allocate guests to specific rooms immediately after reservation. This happens because individual rooms are sold (and there is no concept of room type) or because the assignment is done by hand at reservation or because of a connection with a channel manager, which is immediately fixing the room number after a reservation request. This early allocation is suboptimal, and it causes the unnecessary rejection of some reservations when the hotel has a high occupancy level. The purpose of this paper is to investigate different room allocation algorithms, including an optimal one (called RoomTetris), aiming at higher occupancy levels and profitability.Design/methodology/approachThe methodology is based on theoretical results and experimentation. The optimality or the proposed RoomTetris algorithm is demonstrated. Experiments are executed in different contexts, including realistic ones, through the adoption of a hotel simulator, to measure the improvements in the occupancy rate of the optimal and heuristic strategies with respect to random or sub-optimal assignments of rooms.FindingsThe main results are that smart allocation algorithms can greatly reduce the rejection rate (reservation requests which cannot be fit into the hotel room plan) and improve the occupancy level, the percentage of available rooms or beds sold for the various periods.Research limitations/implicationsThis analysis can be extended by considering cancellations and overbookings. A second possibility to add flexibility in room allocation for hotels having more than one type of rooms is that the hotel can upgrade and offer a high-price room to the customer, which given an even large flexibility to fix rooms by shifting customers to other compatible types. In addition, more complex integrations with revenue management can also be considered, for cases in which the cost of a room depends on the number of guests.Practical implicationsGiven that the difference in occupancy rate of the optimal algorithm is particularly large in high season and high-request periods, periods which are usually associated to higher rates and higher volumes, the proposed algorithm will improve the main financial performance indicators such as revenue per available room by an even bigger multiplier, depending on the hotel pricing policy. Because the room allocation process can be completely automated, the adoption of appropriate smart allocation algorithms represents a low-hanging fruit to be picked by efficient hotel managers.Originality/valueTo the best of the knowledge this is the first proposal of an optimal algorithm (with proof of optimality) for the considered problem.

Azis, Nasir; Amin, Muslim; Chan, Syafruddin; Aprilia, Cut

2020 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-01-2020-0005

The purpose of this study is to investigate how smart tourism technologies and memorable tourism experiences affect tourist satisfaction and tourist destination loyalty.Design/methodology/approachA total of 600 questionnaires were distributed, 360 were returned (60% response rate) and a covariance-based structural equation modeling technique was used to test the hypotheses.FindingsThe results of this study explain that smart tourism technologies and memorable tourism experiences play essential roles in enhancing tourist satisfaction and tourist destination loyalty.Practical implicationsThis study specifies that tourists have pleasant memories and are satisfied at a tourist destination; as a result, they are more likely to revisit and recommend a tourist destination to their friends, family and other tourists. If a tourist has a negative experience with smart city info-structure facilities, a tourist might reach an overall conclusion to not revisit or recommend the location to other tourists.Originality/valueThis study provides empirical evidence to support the importance of smart tourism technologies and memorable tourism experiences in enhancing tourist satisfaction and tourist destination loyalty.

Zhang, Tingting; Jahromi, Melissa F.; Hua, Nan; Lu, Lu

2020 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-04-2019-0056

Social commerce is relatively a nascent notion that highlights the transactions of e-commerce facilitated through social media. This study aims to investigate the motivational factors driving customer brand engagement in social commerce activities within the hospitality sectors.Design/methodology/approachGuided by self-determination theory, this research examined both intrinsic and extrinsic motivation factors by surveying 588 hospitality customers in a structured questionnaire.FindingsThe results showed that intrinsically customers were motivated by knowledge, accomplishment and stimulation; while extrinsically customers were motivated by external and introjected regulation to affect their cognitive, affectional and behavioral engagement with hospitality brands through social commerce activities.Originality/valueGiven the emerging trends in customer brand engagement practices within the context of social commerce, this study investigates an understudied phenomenon and its relational drivers, which reveals its theoretical significance.

Guo, Lingyun; Hu, Xiayu; Wei, Xuguang; Cai, Xiaonan

2020 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-02-2020-0043

This paper aims to help hosts or service providers of sharing economy-based accommodation (SEA) to attract new customers and retain existing customers by exploring the antecedents and outcomes of customers’ participation intention.Design/methodology/approachA questionnaire-based empirical study was conducted to explore the proposed relationships in SEA. Partial least squares modeling with SmartPLS was used to estimate the model and interpret the results.FindingsThe study shows that personal factors (utilitarian and hedonic motivation) positively influence customers’ participation intention. The relationship between environmental stimuli (perceived information fit-to-task and perceived visual appeal) and participation intention is negatively moderated by hedonic motivation. Furthermore, the results suggest a positive effect of participation intention on customer engagement behavior and the partial mediating role of experience evaluation.Practical implicationsThis paper provides industry practitioners of SEA with valuable insights on attracting new customers and retaining regular customers. First, they can distinguish customers in terms of motivation and provide information based on their requirements. Second, they can encourage customers to evaluate their experience and provide feedback, which would help in promoting the accommodation and service and building a long-term and harmonious relationship with the customers.Originality/valueThis study first investigates the interaction effect of personal motivation and environmental stimuli on participation intention in SEA. It further examines the influence of participation intention on customer engagement behavior and the mediating role of experience evaluation.

Çiftçi, Şükrü Fırat; Çizel, Beykan

2020 Journal of Hospitality and Tourism Technology

doi: 10.1108/jhtt-02-2019-0037

The main purpose of this study is to investigate the factors affecting e-trust perception of tourists using Web-based travel intermediaries (WBTIs). Cognitive and affective attitude components are believed to be important in assessing the e-trust perception of tourists. However, this paper aims to investigate if self-efficacy would be an important predictor for e-trust in the context of WBTIs.Design/methodology/approachThe quantitative research method is used in this study. Data were collected by the survey method from the tourists who visited Istanbul/Turkey and made their bookings via Web-based travel intermediaries. Hierarchical linear regression analysis is used to investigate to which extent age/gender/years of usage, self-efficacy, cognitive and affective components are affecting tourists’ e-trust perception.FindingsAccording to the study results, self-efficacy, the attitude components, in addition to the demographic variables, predict a significant amount of variance (45%) in e-trust for Web-based travel intermediaries. Besides attitude components, self-efficacy is put forward as significantly important in the perception of e-trust.Originality/valueThe novelty of the current study is that it uses hierarchical regression to test if self-efficacy would be an important predictor for e-trust while examining the effect of various predictive variables in sequential order. Therefore, the relative importance of this e-trust predictor can be evaluated based on how much it contributes to the prediction over and above other important antecedents of e-trust according to the literature. This study provides evidence that the social cognitive theory may be useful in understanding e-trust in online tourist behavior.