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1 – 10 of over 13000
Article
Publication date: 30 November 2021

Lei Li, Anrunze Li, Xue Song, Xinran Li, Kun Huang and Edwin Mouda Ye

As academic social Q&A networking websites become more popular, scholars are increasingly using them to meet their information needs by asking academic questions. However…

Abstract

Purpose

As academic social Q&A networking websites become more popular, scholars are increasingly using them to meet their information needs by asking academic questions. However, compared with other types of social media, scholars are less active on these sites, resulting in a lower response quantity for some questions. This paper explores the factors that help explain how to ask questions that generate more responses and examines the impact of different disciplines on response quantity.

Design/methodology/approach

The study examines 1,968 questions in five disciplines on the academic social Q&A platform ResearchGate Q&A and explores how the linguistic characteristics of these questions affect the number of responses. It uses a range of methods to statistically analyze the relationship between these linguistic characteristics and the number of responses, and conducts comparisons between disciplines.

Findings

The findings indicate that some linguistic characteristics, such as sadness, positive emotion and second-person pronouns, have a positive effect on response quantity; conversely, a high level of function words and first-person pronouns has a negative effect. However, the impacts of these linguistic characteristics vary across disciplines.

Originality/value

This study provides support for academic social Q&A platforms to assist scholars in asking richer questions that are likely to generate more answers across disciplines, thereby promoting improved academic communication among scholars.

Article
Publication date: 9 January 2017

Doris Chenguang Wu, Haiyan Song and Shujie Shen

The purpose of this paper is to review recent studies published from 2007 to 2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging…

5236

Abstract

Purpose

The purpose of this paper is to review recent studies published from 2007 to 2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging topics and methods studied and to pointing future research directions in the field.

Design/methodology/approach

Articles on tourism and hotel demand modeling and forecasting published mostly in both science citation index and social sciences citation index journals were identified and analyzed.

Findings

This review finds that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, whereas disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior and consumer confidence indicators, among others. More sophisticated techniques such as nonlinear smooth transition regression, mixed-frequency modeling technique and nonparametric singular spectrum analysis have also been introduced to this research area.

Research limitations/implications

The main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting.

Practical implications

This review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices.

Originality/value

The value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.

Details

International Journal of Contemporary Hospitality Management, vol. 29 no. 1
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 22 July 2021

Han Liu, Ying Liu, Gang Li and Long Wen

This study aims to examine whether and when real-time updated online search engine data such as the daily Baidu Index can be useful for improving the accuracy of tourism demand…

Abstract

Purpose

This study aims to examine whether and when real-time updated online search engine data such as the daily Baidu Index can be useful for improving the accuracy of tourism demand nowcasting once monthly official statistical data, including historical visitor arrival data and macroeconomic variables, become available.

Design/methodology/approach

This study is the first attempt to use the LASSO-MIDAS model proposed by Marsilli (2014) to field of the tourism demand forecasting to deal with the inconsistency in the frequency of data and the curse problem caused by the high dimensionality of search engine data.

Findings

The empirical results in the context of visitor arrivals in Hong Kong show that the application of a combination of daily Baidu Index data and monthly official statistical data produces more accurate nowcasting results when MIDAS-type models are used. The effectiveness of the LASSO-MIDAS model for tourism demand nowcasting indicates that such penalty-based MIDAS model is a useful option when using high-dimensional mixed-frequency data.

Originality/value

This study represents the first attempt to progressively compare whether there are any differences between using daily search engine data, monthly official statistical data and a combination of the aforementioned two types of data with different frequencies to nowcast tourism demand. This study also contributes to the tourism forecasting literature by presenting the first attempt to evaluate the applicability and effectiveness of the LASSO-MIDAS model in tourism demand nowcasting.

Details

International Journal of Contemporary Hospitality Management, vol. 33 no. 6
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 18 April 2022

Shuyang Li, Shu Jiang, Miao Tian, Yun Su and Jun Li

The purpose of this paper is to gain an in-depth understanding of the research progress, hotspots and future trends in the field of functional clothing.

Abstract

Purpose

The purpose of this paper is to gain an in-depth understanding of the research progress, hotspots and future trends in the field of functional clothing.

Design/methodology/approach

The records of 4,153 pieces of literature related to functional clothing were retrieved from Web of Science by using a comprehensive retrieval strategy. A piece of software, CiteSpace was used as a tool to visualize the results of specific terms, such as author, institution and keyword. By analyzing the knowledge maps with several indicators, the intellectual basis and research fronts for the functional clothing domain could then be demonstrated.

Findings

The result indicated that functional clothing was a popular research field, with approximately 500 papers published worldwide in 2020. Its main research area was material science and involved public environmental and occupational health, engineering, etc. showing the characteristic of multi-interdisciplinary. Textile Research Journal and International Journal of Clothing Science and Technology were the top two journals in this field. The USA, China, Australia, England and Germany have been active and frequently cooperating with each other. Donghua University, the Hong Kong Polytechnic University and NASA, with the largest number of publications, were identified as the main research drivers. According to the co-citation analysis, thermal stress, nanogenerator and electrospinning were the topics of most cited articles during the past 20 years.

Practical implications

The findings identified smart clothing and protective clothing to be the research frontiers in the field of functional clothing, which deserved further study in the future.

Originality/value

The outcomes offered an overview of the research status and future trends of the functional clothing field. It could not only provide scholars with convenience in identifying research hotspots and building potential cooperation in the follow-up research, but also assist beginners in searching core scholars and literature of great significance.

Details

International Journal of Clothing Science and Technology, vol. 34 no. 5
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 12 July 2023

XiaoXi Wu, Jinlian Shi and Haitao Xiong

This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.

Abstract

Purpose

This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.

Design/methodology/approach

This study used CiteSpace to conduct a bibliometric analysis of 1,213 tourism forecasting articles.

Findings

The results show that tourism forecasting research has experienced three stages. The institutional collaboration includes transnational collaboration and domestic institutional collaboration. Collaboration between countries still needs to be strengthened. The authors’ collaboration is mainly based on on-campus collaboration. Articles with high co-citation are primarily published in core tourism journals and other relevant publications. The research content mainly pertains to tourism demand, revenue management, hotel demand and tourist volumes. Ex ante forecasting during the COVID-19 pandemic has broadened existing tourism forecasting research. The future forecasting research focuses on the rational use of big data, improving the accuracy of models and enhancing the credibility of forecasting results.

Originality/value

This paper uses CiteSpace to analyze tourism forecasting articles to obtain future research trends, which supplements existing research and provides directions for future research.

意图

本文旨在分析旅游预测领域的研究重点、演化过程和未来的研究方向。

设计/理论/方法

本研究使用 CiteSpace 软件对 1213 篇旅游预测文章进行了文 献计量学分析。

结果

结果表明, 旅游预测研究经历三个阶段。机构合作包含国际机构合作和 国内机构合作, 需要持续加强国家之间的合作, 作者之间的合作多以校内合作为 主。高引用文章不仅发表在旅游领域的核心期刊还发表在其他专业的核心期刊上。 旅游预测研究的主要内容为旅游需求、收入管理、酒店需求和游客量。新冠疫情 期间的事前预测拓宽了现有的旅游预测研究。未来预测的研究重点在于合理利用 大数据, 提高模型的准确定以及提高预测结果的可信度。

创意/价值

本文使用 CiteSpace 分析旅游预测文章得到未来研究趋势, 既是对 现有研究的补充, 又为今后的研究提供方向。

Objetivo

Este artículo pretende analizar los aspectos más destacados de la investigación, el proceso evolutivo y las futuras orientaciones de la investigación en el campo de la previsión turística.

Diseño/metodología/enfoque

Este estudio utilizó CiteSpace para realizar un análisis bibliométrico de 1213 artículos sobre previsión turística.

Resultados

Los resultados muestran que la investigación sobre previsión turística ha experimentado tres etapas. La colaboración institucional incluye la colaboración transnacional y la colaboración institucional nacional. La colaboración entre países aún debe reforzarse. La colaboración entre autores se basa principalmente en la colaboración dentro del campus. Los artículos con una alta cocitación se publican principalmente en las principales revistas de turismo y en otras publicaciones relevantes. El contenido de la investigación se refiere principalmente a la demanda turística, el revenue management, la demanda hotelera y los volúmenes turísticos. La previsión previa y durante la pandemia de la COVID-19 ha ampliado la investigación existente sobre previsión turística. La futura investigación sobre previsiones se centra en el uso racional de los big data, la mejora de la precisión de los modelos y el aumento de la credibilidad de los resultados de las previsiones.

Originalidad/valor

Este artículo utiliza CiteSpace para analizar artículos de previsión turística con el fin de obtener futuras tendencias de investigación, lo que complementa la investigación existente y proporciona orientaciones para futuras investigaciones.

Open Access
Article
Publication date: 4 May 2020

Dharyll Prince Mariscal Abellana, Donna Marie Canizares Rivero, Ma. Elena Aparente and Aries Rivero

This paper aims to propose a hybrid-forecasting model for long-term tourism demand forecasting. As such, it attempts to model the tourism demand in the Philippines, which is a…

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Abstract

Purpose

This paper aims to propose a hybrid-forecasting model for long-term tourism demand forecasting. As such, it attempts to model the tourism demand in the Philippines, which is a relatively underrepresented area in the literature, despite its tourism sector’s growing economic progress.

Design/methodology/approach

A hybrid support vector regression (SVR) – seasonal autoregressive integrated moving averages (SARIMA) model is proposed to model the seasonal, linear and nonlinear components of the tourism demand in a destination country. The paper further proposes the use of multiple criteria decision-making (MCDM) approaches in selecting the best forecasting model among a set of considered models. As such, a preference ranking organization method for enrichment of evaluations (PROMETHEE) II is used to rank the considered forecasting models.

Findings

The proposed hybrid SVR-SARIMA model is the best performing model among a set of considered models in this paper using performance criteria that evaluate the errors of magnitude, directionality and trend change, of a forecasting model. Moreover, the use of the MCDM approach is found to be a relevant and prospective approach in selecting the best forecasting model among a set of models.

Originality/value

The novelty of this paper lies in several aspects. First, this paper pioneers the demonstration of the SVR-SARIMA model’s capability in forecasting long-term tourism demand. Second, this paper is the first to have proposed and demonstrated the use of an MCDM approach for performing model selection in forecasting. Finally, this paper is one of the very few papers to provide lenses on the current status of Philippine tourism demand.

Details

Journal of Tourism Futures, vol. 7 no. 1
Type: Research Article
ISSN: 2055-5911

Keywords

Book part
Publication date: 25 January 2023

Yang Yang, Graziano Abrate and Chunrong Ai

This chapter provides an overview of the status of applied econometric research in hospitality and tourism management and outlines the econometric toolsets available for…

Abstract

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.

Details

Cutting Edge Research Methods in Hospitality and Tourism
Type: Book
ISBN: 978-1-80455-064-9

Keywords

Article
Publication date: 8 February 2016

Elizabeth Agyeiwaah and Raymond Adongo

– The purpose of this paper is to identify the core factors that determine tourism demand in four inbound markets of Hong Kong.

Abstract

Purpose

The purpose of this paper is to identify the core factors that determine tourism demand in four inbound markets of Hong Kong.

Design/methodology/approach

The general-to-specific approach was adopted as a step-by-step approach to identify the major determinants of tourism demand in Hong Kong.

Findings

The study revealed word of mouth and income of source market are core determinants of tourism demand in all four inbound markets.

Originality/value

Knowledge of core determinants of tourism demand is useful to destination management organizations and tourism business owners for strategic planning and decision making to increase total revenues.

Details

International Journal of Tourism Cities, vol. 2 no. 1
Type: Research Article
ISSN: 2056-5607

Keywords

Article
Publication date: 11 January 2023

Yongyao Li, Guanyu Ding, Chao Li, Sen Wang, Qinglei Zhao and Qi Song

This paper presents a comprehensive pallet-picking approach for forklift robots, comprising a pallet identification and localization algorithm (PILA) to detect and locate the…

Abstract

Purpose

This paper presents a comprehensive pallet-picking approach for forklift robots, comprising a pallet identification and localization algorithm (PILA) to detect and locate the pallet and a vehicle alignment algorithm (VAA) to align the vehicle fork arms with the targeted pallet.

Design/methodology/approach

Opposing vision-based methods or point cloud data strategies, we utilize a low-cost RGB-D camera, and thus PILA exploits both RGB and depth data to quickly and precisely recognize and localize the pallet. The developed method guarantees a high identification rate from RGB images and more precise 3D localization information than a depth camera. Additionally, a deep neural network (DNN) method is applied to detect and locate the pallet in the RGB images. Specifically, the point cloud data is correlated with the labeled region of interest (RoI) in the RGB images, and the pallet's front-face plane is extracted from the point cloud. Furthermore, PILA introduces a universal geometrical rule to identify the pallet's center as a “T-shape” without depending on specific pallet types. Finally, VAA is proposed to implement the vehicle approaching and pallet picking operations as a “proof-of-concept” to test PILA’s performance.

Findings

Experimentally, the orientation angle and centric location of the two kinds of pallets are investigated without any artificial marking. The results show that the pallet could be located with a three-dimensional localization accuracy of 1 cm and an angle resolution of 0.4 degrees at a distance of 3 m with the vehicle control algorithm.

Research limitations/implications

PILA’s performance is limited by the current depth camera’s range (< = 3 m), and this is expected to be improved by using a better depth measurement device in the future.

Originality/value

The results demonstrate that the pallets can be located with an accuracy of 1cm along the x, y, and z directions and affording an angular resolution of 0.4 degrees at a distance of 3m in 700ms.

Details

Industrial Robot: the international journal of robotics research and application, vol. 50 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 6 February 2023

Hong Zhang, Lu-Kai Song, Guang-Chen Bai and Xue-Qin Li

The purpose of this study is to improve the computational efficiency and accuracy of fatigue reliability analysis.

Abstract

Purpose

The purpose of this study is to improve the computational efficiency and accuracy of fatigue reliability analysis.

Design/methodology/approach

By absorbing the advantages of Markov chain and active Kriging model into the hierarchical collaborative strategy, an enhanced active Kriging-based hierarchical collaborative model (DCEAK) is proposed.

Findings

The analysis results show that the proposed DCEAK method holds high accuracy and efficiency in dealing with fatigue reliability analysis with high nonlinearity and small failure probability.

Research limitations/implications

The effectiveness of the presented method in more complex reliability analysis problems (i.e. noisy problems, high-dimensional issues etc.) should be further validated.

Practical implications

The current efforts can provide a feasible way to analyze the reliability performance and identify the sensitive variables in aeroengine mechanisms.

Originality/value

To improve the computational efficiency and accuracy of fatigue reliability analysis, an enhanced active DCEAK is proposed and the corresponding fatigue reliability framework is established for the first time.

Details

International Journal of Structural Integrity, vol. 14 no. 2
Type: Research Article
ISSN: 1757-9864

Keywords

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