Search results

The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

A novel semiconducting macromolecule-polyperylene tetraamide (PPTI) was first synthesized with a simple method using 3, 4, 9, 10-perylene tetracarboxylic acid (PTCA) and hydrazine hydrate (N2H4).

The Ag nanoparticle was doped on the surface or inside of the PPTI film to obtain a highly sensitive hydrazine sensor-Ag/PPTI, which was synthesized within one step. The structure of Ag/PPTI was characterized through various techniques such as Fourier transform infrared (FT-IR), thermogravimetric analyzer (TGA), X-ray diffraction (XRD), X-ray photoelectron spectroscopy measurements (XPS) and scanning electronic microscopy (SEM).

According to cyclic voltammetry results, Ag/PPTI/GCE indicated good electrocatalytic activity toward the oxidation of hydrazine. The amperometric detection of hydrazine was then applied on Ag/PPTI/GCE. It exhibited a wide linear range from 0.05 to 50 µM, a low detection limit (S/N = 3) of 0.05 µM and high sensitivity of 0.45 µA/(µM•cm2).

In authors’ perception, this approach emerges as an effective technique for developing efficient chemical sensors for environmental pollutants.

This paper aims to Test the capabilities/accuracies of four deep learning pre trained convolutional neural network (CNN) models to detect and classify types of highway cracks, as well as developing a new CNN model to maximize the accuracy at different learning rates.

A sample of 4,663 images of highway cracks were collected and classified into three categories of cracks, namely, “vertical cracks,” “horizontal and vertical cracks” and “diagonal cracks,” subsequently, using “Matlab” to classify the sample to training (70%) and testing (30%) to apply the four deep learning CNN models and compute their accuracies. After that, developing a new deep learning CNN model to maximize the accuracy of detecting and classifying highway cracks and testing the accuracy using three optimization algorithms at different learning rates.

The accuracies result of the four deep learning pre-trained models are above the averages between top-1 and top-5 and the accuracy of classifying and detecting the samples exceeded the top-5 accuracy for the pre-trained AlexNet model around 3% and by 0.2% for the GoogleNet model. The accurate model here is the GoogleNet model as the accuracy is 89.08% and it is higher than AlexNet by 1.26%. While the computed accuracy for the new created deep learning CNN model exceeded all pre-trained models by achieving 97.62% at a learning rate of 0.001 using Adam’s optimization algorithm.

The created deep learning CNN model will enable users (e.g. highway agencies) to scan a long highway and detect types of cracks accurately in a very short time compared to traditional approaches.

A new deep learning CNN-based highway cracks detection was developed based on testing four pre-trained CNN models and analyze the capabilities of each model to maximize the accuracy of the proposed CNN.

Spatial integration and industrial clustering have become an important feature of the culture tourism business. When the core elements in both the culture industry and tourism industry are integrated, a model based on system science is constructed that combines the resources and capacity of the two entities to envisage the ways of creating integrated products and services from the two sectors. Guided by the system science, this study proposes a culture tourism system revealing the clustering and hierarchical structure of the industrial elements. The system contains two subsystems: internal system and external system. The agglomeration model of the system includes 26 indices and the PEF methods, which involved the Parallelogram Law, Entropy-weight Method, and Fuzzy Membership Function. Finally, this study deploys an empirical study involving all provincial territories (N=31) in mainland China. It analyzes the variability and degree of balanced development of the system. In addition, through the resultant data this research adds a typology of culture tourism system along with policy recommendations.

The author investigates and debates around authenticity in relation to the heritage communities of a Chinese intangible cultural heritage (ICH) item ‘Nüshu’. Nüshu is a monosyllabic phonetic system of writing created and used by women in the Jiangyong County, Hunan Province, in Southern China. Drawing on insights from both online and offline ethnographies, this study argues that in the field of ICH, disputes over heritage authenticity are fiercely negotiated by different stakeholders, including powerful state and supra-state actors. However, the emergence of digital platform has become a way for Nüshu participants to perform their identity and competence and lay claim to their own heritage authenticity.

The utilisation of emerging technologies for the inspection of bridges has remarkably increased. In particular, non-destructive testing (NDT) technologies are deemed a potential alternative for costly, labour-intensive, subjective and unsafe conventional bridge inspection regimes. This paper aims to develop a framework to overcome conventional inspection regimes' limitations by deploying multiple NDT technologies to carry out digital visual inspections of masonry railway bridges.

This research adopts an exploratory case study approach, and the empirical data is collected through exploratory workshops, interviews and document reviews. The framework is implemented and refined in five masonry bridges as part of the UK railway infrastructure. Four NDT technologies, namely, terrestrial laser scanner, infrared thermography, 360-degree imaging and unmanned aerial vehicles, are used in this study.

A digitally enhanced visual inspection framework is developed by using complementary optical methods. Compared to the conventional inspection regimes, the new approach requires fewer subjective interpretations due to the additional qualitative and quantitative analysis. Also, it is safer and needs fewer operators on site, as the actual inspection can be carried out remotely.

This research is a step towards digitalising the inspection of bridges, and it is of particular interest to transport agencies and bridge inspectors and can potentially result in revolutionising the bridge inspection regimes and guidelines.

Considering the financial service providers’ (FSPs) information asymmetry in evaluating the supplier and their distinct quit probabilities, we want to examine the supplier’s preference of the financing schemes if both the bank and the online platform exist and how the buyer sets the contract terms in the two financing schemes.

We establish a Stackelberg game model to capture the interactions among three parties, i.e. a supplier, a capital-sufficient buyer and an FSP (either a bank or an online platform), within a first-time contract.

In the non-FSPs’ quit case, the buyer’s profit is higher under the bank loan scenario, while the supplier’s profit performs adversely. The supply chain’s profit is heavily dependent on the buyer’s profit difference between the two financing schemes. Moreover, we find that the supplier borrows the money to exactly cover the production cost. The equilibrium solutions of the FSPs’ quit case and of the capital-sufficient supplier’s case are also derived.

First, we assign different risk profiles to different FSPs in our setting so that modeling a previously ignored but practically significant problem. Second, we innovatively take the FSP’s quit probability into account in our model. Third, we elucidate how these factors can influence the relative efficiency of the two types of financing schemes and the settings of the contract, which further complements and extends the current SCF research.

The purpose of this study is to investigate when and why supervisor negative feedback is associated with employees' job performance via two different pathways (i.e. emotion-focused coping and problem-focused coping) and to introduce proactive personality as a moderator.

Time-lagged data were collected using a field survey research design. Participants included 389 dyads of employees and their direct supervisors from five companies in China.

Supervisor negative feedback can lead to employees' emotion-focused coping, which in turn impairs their job performance. Meanwhile, supervisor negative feedback can trigger employees’ problem-focused coping, which subsequently promotes their job performance. Furthermore, proactive personality moderates the indirect effect of supervisor negative feedback on employee performance through emotion-focused coping.

This study explored the double-edged effects of supervisor negative feedback on employee job performance from a coping strategy perspective and investigated how proactive personality influences the choice of coping strategies.

This chapter provides an overview of the status of applied econometric research in hospitality and tourism management and outlines the econometric toolsets available for quantitative researchers using empirical data from the field. Basic econometric models, cross-sectional models, time-series models, and panel data models are reviewed first, followed by an evaluation of relevant applications. Next, econometric modeling topics that are germane to hospitality and tourism research are discussed, including endogeneity, multi-equation modeling, causal inference modeling, and spatial econometrics. Furthermore, major feasibility issues for applied researchers are examined based on the literature. Lastly, recommendations are offered to promote applied econometric research in hospitality and tourism management.

The purpose of this research is to investigate the relationships of environmental concern and risk perception with residents' waste mobile recycling behavior in the scenario of continuously increasing electronic waste (aka e-waste) around the world.

For empirically testing proposed research model, this study utilized convenience sampling strategy and collected 346 responses from residents in the People’s Republic of China (PRC) through an online survey. The hypotheses were tested utilizing the structural equation modeling (SEM) framework through Mplus 7.0 program (Muthen and Muthen, 1998–2012). Robust maximum likelihood (MLR) was used as the method of estimation.

The results revealed that environmental concern is positively associated with individuals' intentions to recycle waste mobile phones and that the relationship between concern for the environment and individuals' intention to recycle is mediated by the factors such as individuals' mobile phone recycling attitude and subjective norms. The results further indicated that individuals' information security risk perception moderates the relationship between individuals' intention for recycling and subsequent recycling behavior.

This study provides substantial theoretical and practical implications for residents' e-waste recycling behavior while considering their environmental concern and information security risk perceptions.