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The tourism industry is undergoing a metamorphosis as an outcome of the integration of new technologies, which has an impact on products, business experiences, ecosystems and tourism complexes. As a result, to adjust to these changes, the sector needs to develop new business alliances, models and skill sets. Emerging technologies such as virtual reality (VR), augmented reality (AR), artificial intelligence (AI), and data analytics are set to bring in a new chapter in the history of travel experiences. Deepening global linkages, optimising operating efficiency, and transforming visitor experiences are all being brought about by these advancements. The report also evaluates the wider effects of this digital revolution, such as the levelling of access to travel information, the introduction of fresh business strategies and the crucial role of cyber security. With practical advice drawn from empirical research, real-world case studies and industry expert interviews, this study prepares businesses and travel destinations for success in the digital age. ‘From Pixels to Paradise’ is an indispensable tool for all those involved in the travel and tourism sector, helping them navigate the digital environment and take advantage of the opportunities brought about by the convergence of travel and technology. This study tries to map out a route towards a more sustainable, engaging and technologically improved tourism experience against the backdrop of significant industry changes.

This paper aims to analyze and model consumer behavior on hotel online search interest in the USA.

Discrete Fourier transform was used to analyze the periodicity of hotel search behavior in the USA by using Google Trends data. Based on the obtained frequency components, a model structure was proposed to describe the search interest. A separable nonlinear least squares algorithm was developed to fit the data.

It was found that the major dynamics of the search interest was composed of nine frequency components. The developed separable nonlinear least squares algorithm significantly reduced the number of model parameters that needed to be estimated. The fitting results indicated that the model structure could fit the data well (average error 0.575 per cent).

Knowledge of consumer behavior on online search is critical to marketing decision because search engine has become an important tool for customers to find hotels. This work is thus very useful to marketing strategy.

This research is the first work on analyzing and modeling consumer behavior on hotel online search interest.

While relevant research has considered aggregated data from mobile devices and personal computers (PCs), tourists’ search patterns on mobile devices and PCs differ significantly. This study aims to explore whether decomposing aggregated search queries based on the terminals from which these queries are generated can enhance tourism demand forecasting.

Mount Siguniang, a national geopark in China, is taken as a case study in this paper; another case, Kulangsu in China, is used as the robustness check. The authors decomposed the total Baidu search volume into searches from mobile devices and PCs. Weekly rolling forecasts were used to test the roles of decomposed and aggregated search queries in tourism demand forecasting.

Search queries generated from PCs can greatly improve forecasting performance compared to those from mobile devices and to aggregate search volumes from both terminals. Models incorporating search queries generated via multiple terminals did not necessarily outperform those incorporating search queries generated via a single type of terminal.

Major players in the tourism industry, including hotels, tourist attractions and airlines, can benefit from identifying effective search terminals to forecast tourism demand. Industry managers can also leverage search indices generated through effective terminals for more accurate demand forecasting, which can in turn inform strategic decision-making and operations management.

This study represents one of the earliest attempts to apply decomposed search query data generated via different terminals in tourism demand forecasting. It also enriches the literature on tourism demand forecasting using search engine data.

To analyze and discuss the role of ICTs and the emerging trends and issues in marketing tourism experiences.

Previous conceptual frameworks are reviewed and key issues and trends are identified as central for ICT-based tourism marketing. Case studies are presented to illustrate how the marketing issues could be translated into practical tourism marketing strategies.

(1) Based on the literature, a conceptual model that outlines a technology-empowered marketing approach for co-created tourism experiences is presented. (2) The identified key trends in marketing tourism experiences include the changing overall role of marketers, a growth in mobile marketing opportunities, the emergence of smart destinations and their varied implications for marketing. (3) The case studies show the integrated and strategic role of social media platforms, hashtags, photography, location-based geofilters, augmented reality and videography in marketing tourism experiences.

This chapter conceptually outlines the technology-empowered tourism marketing approach and the role of marketers and various other players in tourism experience co-creation. The case studies provide practical implications for ICT-based tourism marketing.

The purpose of this paper is to present a new random vibration-based assessment method for coupled vehicle-track systems with uncertain parameters when subjected to random track irregularity.

The uncertain parameters of vehicle are described as bounded random variables. The track is regarded as an infinite periodic structure, and the dynamic equations of the coupled vehicle-track system, under mixed physical coordinates and symplectic dual coordinates, are established through wheel-rail coupling relationships. The random track irregularities at the wheel-rail contact points are converted to a series of deterministic harmonic excitations with phase lag by using the pseudo excitation method. Based on the polynomial chaos expansion of the pseudo response, a chaos expanded pseudo equation is derived, leading to the combined hybrid pseudo excitation method - polynomial chaos expansion method

The impact of uncertainty propagation on the random vibration analysis is assessed efficiently. According to GB5599-85, the reliability analysis for the stability index is implemented, which can grade the comfort level by the probability. Comparing to the deterministic analysis, it turns out that neglect of the parameter uncertainty will lead to potentially risky analysis results.

The proposed method is compared with Monte Carlo simulations, achieving good agreement. It is an effective means for random vibration analysis of uncertain coupled vehicle-track systems and has good engineering practicality

The term “social media” generally refers to the multi-point creation and distribution of electronic communication. It is understood in opposition to broadcasting. This chapter explains the history of media studies as a means of comprehending these newer media in the context of tourism. They need to be studied in the light of existing media, even as we seek a new form of truly interdisciplinary work that brings existing approaches together. Taking its agenda from social movements as well as intellectual ones, and its methods from social sciences and humanities, Media Studies 3.0 should focus on gender, race, class, sexuality, sustainability, and pleasure across national lines—an apt setting for those working on tourism.

This study aimed to adapt existing text-mining techniques and propose a novel topic recognition approach for textual patient reviews.

The authors first transformed multilabel samples for adapting model training forms. Then, an improved method was proposed based on dynamic mixed sampling and transfer learning to improve the learning problem caused by imbalanced samples. Specifically, the training of our model was based on the framework of a convolutional neural network and self-trained Word2Vector on large-scale corpora.

Compared with the SVM and other CNN-based models, the CNN+ DMS + TL model proposed in this study has made significant improvement in F1 score.

The improved methods based on dynamic mixed sampling and transfer learning can adequately manage the learning problem caused by the skewed distribution of samples and achieve the effective and automatic topic recognition of textual patient reviews.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-01-2021-0059.

The purpose of this paper is to investigate the relative value relevance of accounting measures based on Chinese Accounting Standards (CAS) and International Financial Reporting Standards (IFRS) in relation to both A‐share and B‐share markets during three distinct phases (1994‐1997, 1998‐2000 and 2001‐2004) over which CAS were progressively harmonized with IFRS.

Using data for 86 Chinese listed companies which issued both A‐ and B‐shares, the authors employ the price model to test for the association between CAS‐based and IFRS‐based accounting information, and A‐share and B‐share prices. The J‐test was employed to determine the relative value relevance of the information based on the two sets of accounting standards.

Overall, the authors find that for both the A‐share and B‐share markets, both CAS‐based and IFRS‐based accounting information are value relevant, but IFRS‐based information is more value relevant than the CAS‐based information. However, the magnitude of the differences between the explanatory powers of the CAS‐ and IFRS‐based accounting information narrowed significantly in the 2001‐2004 period in both the A‐share and B‐share markets. The results are robust to the deflator used and the stock exchange on which the companies are listed.

The results have implications for China and other transitional economies attempting to integrate IFRS with a uniform accounting system.

The paper provides the first comprehensive empirical evidence as to whether or not the progressive harmonization of CAS with IFRS improved the value relevance of CAS‐based accounting in China and contributes to the debate on the (ir)relevance of IFRS in emerging and transitional economies.