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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.

Organic coatings are widely used for protecting metal equipment and structures from corrosion. Accurate detection and evaluation of the protective performance and service life of coatings are of great importance. This paper aims to review the research progress on performance evaluation and lifetime prediction of organic coatings.

First, the failure forms and aging testing methods of organic coatings are briefly introduced. Then, the technical status and the progress in the detection and evaluation of coating protective performance and the prediction of service life are mainly reviewed.

There are some key challenges and difficulties in this field, which are described in the end.

The progress is summarized from a variety of technical perspectives. Performance evaluation and lifetime prediction include both single-parameter and multi-parameter methods.

This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.

The two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.

The results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.

The conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.

This paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.

This study aims to improve detection efficiency of fluorescence biosensor or a graphene field-effect transistor biosensor. Graphene field-effect transistor biosensing and fluorescent biosensing were integrated and combined with magnetic nanoparticles to construct a multi-sensor integrated microfluidic biochip for detecting single-stranded DNA. Multi-sensor integrated biochip demonstrated higher detection reliability for a single target and could simultaneously detect different targets.

In this study, the authors integrated graphene field-effect transistor biosensing and fluorescent biosensing, combined with magnetic nanoparticles, to fabricate a multi-sensor integrated microfluidic biochip for the detection of single-stranded deoxyribonucleic acid (DNA). Graphene films synthesized through chemical vapor deposition were transferred onto a glass substrate featuring two indium tin oxide electrodes, thus establishing conductive channels for the graphene field-effect transistor. Using π-π stacking, 1-pyrenebutanoic acid succinimidyl ester was immobilized onto the graphene film to serve as a medium for anchoring the probe aptamer. The fluorophore-labeled target DNA subsequently underwent hybridization with the probe aptamer, thereby forming a fluorescence detection channel.

This paper presents a novel approach using three channels of light, electricity and magnetism for the detection of single-stranded DNA, accompanied by the design of a microfluidic detection platform integrating biosensor chips. Remarkably, the detection limit achieved is 10 pm, with an impressively low relative standard deviation of 1.007%.

By detecting target DNA, the photo-electro-magnetic multi-sensor graphene field-effect transistor biosensor not only enhances the reliability and efficiency of detection but also exhibits additional advantages such as compact size, affordability, portability and straightforward automation. Real-time display of detection outcomes on the host facilitates a deeper comprehension of biochemical reaction dynamics. Moreover, besides detecting the same target, the sensor can also identify diverse targets, primarily leveraging the penetrative and noninvasive nature of light.

Since smartphones became ubiquitous, online grocery and food purchases through take-away delivery platforms have steadily increased in China. Nevertheless, whether the development of take-away delivery can ameliorate urban–rural wage inequality still requires further analysis. The purpose of this paper is to clarify whether this positive effect exists.

This paper makes estimations based on city and individual levels combining the Chinese Household Income Project (CHIP) 2008, CHIP 2013, CHIP2018 survey data and the take-away delivery site data. At the city level, the Oaxaca-Blinder (O-B) decomposition method is employed to construct wage inequality index of urban and rural labors. At the individual level, this paper analyzes urban–rural wage differentials with high or low formal education level.

The rapid establishment of take-away delivery sites has resulted in an increase of 52.425 yuan on average in the annual wage of rural labors with low formal education level. When the cumulative number of sites increases by 1 unit, the annual wage inequality index decreases by 0.007 on average. Labors with the characteristics of rural household registration and low education can enjoy more dividends. Through inter-/within-industry decomposition, this paper elaborates formal education, age and cross-industry transfer as the main factors for the improvement of urban–rural wage inequality. Narrowing effect of wage differences between different groups in multiple sample slices also contributes to the mechanism analyses.

To the best of the author’s knowledge, this paper is the first to analyze the impact of take-away delivery development on the urban–rural wage inequality from the perspective of the establishment of take-away delivery sites. This empirical study will enrich the existing theoretical perspectives on urban–rural divide under the emergence of new forms of employment. The results indicate that new forms of employment represented by take-away delivery can not only promote economic growth, but also eliminate urban–rural inequality.

This research investigates the personal experiences of hybrid workers, exploring their perspectives on their health and well-being when undertaking hybrid working arrangements. The research further explores how organisations can proactively support the health and wellbeing of hybrid workers, mitigating any potential health risks.

A cross-sectional, qualitative online survey was used to collect data from 412 hybrid workers. The data were analysed thematically. This approach allows for nuanced insights into the personal experiences of hybrid workers to be understood.

Findings indicate that employees who undertake hybrid work experience both positive and negative effects on their subjective well-being; hybrid work arrangement has the potential to act as a job resource or job demand. The study further identifies actions that can support healthy hybrid work that will be of value to organisations offering these working arrangements.

Although empirical research has previously examined the relationship between remote work and employee well-being, there is a lack of in-depth understanding about employees’ experiences of well-being whilst undertaking hybrid work – an emerging and relatively unexplored working arrangement. This research therefore addresses a significant gap in the literature by providing a deep understanding of how hybrid work influences employee well-being. Furthermore, previous research has not yet explored how hybrid worker health can be enabled and supported by organisations and individuals themselves.

Radical changes in consumer habits induced by the coronavirus disease (COVID-19) pandemic suggest that the usual demand forecasting techniques based on historical series are questionable. This is particularly true for hospitality demand, which has been dramatically affected by the pandemic. Accordingly, we investigate the suitability of tourists’ activity on Twitter as a predictor of hospitality demand in the Way of Saint James – an important pilgrimage tourism destination.

This study compares the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) time-series model with that of the SARIMA with an exogenous variables (SARIMAX) model to forecast hotel tourism demand. For this, 110,456 tweets posted on Twitter between January 2018 and September 2022 are used as exogenous variables.

The results confirm that the predictions of traditional time-series models for tourist demand can be significantly improved by including tourist activity on Twitter. Twitter data could be an effective tool for improving the forecasting accuracy of tourism demand in real-time, which has relevant implications for tourism management. This study also provides a better understanding of tourists’ digital footprints in pilgrimage tourism.

This study contributes to the scarce literature on the digitalisation of pilgrimage tourism and forecasting hotel demand using a new methodological framework based on Twitter user-generated content. This can enable hospitality industry practitioners to convert social media data into relevant information for hospitality management.

2019冠狀病毒病引致消費者習慣有根本的改變; 這些改變顯示，根據歷史序列而運作的慣常需求預測技巧未必是正確的。這不確性尤以受到大流行極大影響的酒店服務需求為甚。因此，我們擬探討、若把在推特網站上的旅遊活動視為聖雅各之路 (一個重要的朝聖旅遊聖地) 酒店服務需求的預測器，這會否是合適的呢?

本研究比較 SARIMA 時間序列模型與附有外生變數 (SARIMAX)模型兩者在預測旅遊及酒店服務需求方面的表現。為此，研究人員收集在推特網站上發佈的資訊，作為外生變數進行研究。這個樣本涵蓋於2018年1月至2022年9月期間110,456個發佈資訊。

研究結果確認了傳統的時間序列模型，若涵蓋推特網站上的旅遊活動，則其對旅遊需求方面的預測會得到顯著的改善。推特網站的數據，就改善預測實時旅遊需求的準確度，或許可成為有效的工具; 而這發現對旅遊管理會有一定的意義。本研究亦讓我們進一步瞭解朝聖旅遊方面旅客的數碼足跡。

現存文獻甚少探討朝聖旅遊的數字化，而本研究不但在這方面充實了有關的文獻，還使用了一個根據推特網站上使用者原創內容嶄新的方法框架，進行分析和探討。這會幫助酒店從業人員把社交媒體數據轉變為可供酒店管理之用的合宜資訊。

The interconnected challenges of climate change and social inclusivity have placed unprecedented pressure on businesses to adopt responsible practices. While previous research has explored the individual impacts of environmental, social, and governance (ESG) performance and diversity initiatives, there remains a dearth of comprehensive investigations into how these factors collectively influence carbon emission scores. Drawing on the legitimacy theory, we explore whether ESG and diversity scores predict global companies' carbon emission scores. As concerns about the environmental impact of businesses grow, understanding the relationships between ESG performance, diversity management, and carbon emissions becomes imperative for sustainable corporate practices.

The primary dataset for this study includes 1,268 worldwide firm-year data for 2021. The sample is subjected to missing data examination as a component of the filtration process. Data preprocessing is performed before machine learning analysis, including verifying missing data. Our research resulted in the final sample, which includes 627 worldwide firm data from 2021. Data regarding all publicly traded companies was obtained from Refinitiv Eikon.

Our findings showed that corporate carbon emission performance in global corporations is influenced by ESG performance and total diversity score.

Firms involve in ESG as well as diversity practices to be able to achieve sustainable success. Yet, the forecasting of carbon emissions based on ESG scores and diversity scores remains inadequately established due to conflicting findings and enigmas prevalent in the literature.

High-nitrogen steel is a common material for the manufacture of drilling equipment such as drill collars. However, its poor surface properties often limit its applications. The purpose of this paper is to find a way to enhance the surface performance of high-nitrogen steel, which is expected to improve the wear resistance of high-nitrogen steel.

The CoCrNi and CoCrFeNi medium-entropy alloy (MEA) coatings were prepared on high-nitrogen steel substrate by laser cladding technology. The microstructure, phase composition and element distribution of the fabricated coatings were investigated using scanning electronic microscopy, electron backscatter diffraction and X-ray diffraction. The phase structure, phase stability and structural stability of the CoCrNi and CoCrFeNi MEAs were investigated in combination with phase diagram calculation and molecular dynamics. Then the wear tests were carried out for coatings.

The results show that both prepared MEA coatings have good quality and contain a single face-centered cubic phase. The wear performance of MEA coatings is improved by the refinement of grain size and the increase of dislocation density. Due to the addition of Fe atoms, the lattice distortion of the CoCrFeNi system increased, resulting in a higher dislocation density of the coating. Cr atoms in the CoCrFeNi system are the largest, and the local lattice distortions induced by them are greater. Through this study, MEA coatings with high hardness can be expanded to drilling field applications.

CoCrFeNi and CoCrNi MEA coatings were successfully prepared on the surface of high-nitrogen steel for the first time without obvious defects. The micromorphology and grain orientation of the different kinds of coatings were discussed in detail. The hardness-strengthening mechanism and structure stability of the coatings were illustrated by experiments and molecular dynamics simulations.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0116/

Based on the stereotype content model (SCM), this study aims to enrich comprehension of virtual service assistant (VSA)-enabled service delivery through two pivotal avenues. Firstly, it aims to conceptualize and test the fundamental mechanism underlying how businesses deploy services using VSAs. Secondly, this study explores whether the paradigms of service co-creation versus service recovery differentially impact customers’ perceptions of warmth and competence in VSA-enabled service delivery.

This study used a one-factorial (service paradigm: service co-creation vs service recovery) field experiment. Covariance-based structural equation modelling was used to analyze the data.

The results show that VSA service quality dimensions impact satisfaction for service co-creation and both trust and satisfaction for service recovery. The stronger link that mediates this effect is competence for service co-creation and warmth for service recovery.

This research extends the understanding of SCM to VSA-enabled services and shows the asymmetries of mediation between the paradigms of service co-creation versus service recovery to suggest the most effective approach for VSAs to successfully meet customer requirements for establishing trust and satisfaction.