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Article
Publication date: 12 April 2024

Siyu Ji, Bo Pu and Wenyuan Sang

It is unclear what constitutes the tourism live streaming (TLS) servicescape and how it affects users' travel intention (TI). The study aims to explore the composition of the TLS…

386

Abstract

Purpose

It is unclear what constitutes the tourism live streaming (TLS) servicescape and how it affects users' travel intention (TI). The study aims to explore the composition of the TLS servicescape, the influence mechanism of the TLS servicescape on users' TI and the formation of users' TI.

Design/methodology/approach

Based on stimulus organism response theory (SOR), we develop a mediation model to explore the influence of TLS servicescape on users' TI. This study collected data from 432 Chinese TLS users through an online questionnaire, and we used the structural equation model and the SPSS PROCESS macro to test the proposed model. In addition, we tested the variable relationships using fuzzy-set qualitative comparative analysis (fsQCA).

Findings

TLS servicescape is a second-order variable that can be categorized into physical element (PE), social element (SOE), symbolic element (SYE) and natural element (NE). TLS servicescape influences TI by affecting social presence (SP) and customer engagement (CE). The fsQCA reveals seven combinations of PE, SOE, SYE, NE, SP and CE that form a high TI for TLS users.

Originality/value

Using multiple data analysis methods, the study emphasizes the significance of the TLS servicescape for TLS. It explores how to evoke users' TI in TLS and provides a reference for TLS marketing.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 36 no. 10
Type: Research Article
ISSN: 1355-5855

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Article
Publication date: 28 October 2021

Bo Pu, Lu Zhang, Wenyuan Sang and Siyu Ji

This study aims to explore the influence of appearance comparison on fitness intention. Specifically, it analyzes the mediating effect of appearance-based exercise motivation and…

1009

Abstract

Purpose

This study aims to explore the influence of appearance comparison on fitness intention. Specifically, it analyzes the mediating effect of appearance-based exercise motivation and perceived behavioral control between appearance comparison and fitness intention.

Design/methodology/approach

434 samples were obtained by the network survey in China. Hierarchical regression analysis and the Hayes' SPSS PROCESS macro were used to verify the hypotheses.

Findings

Appearance comparison has a positive influence on fitness intention. Appearance-based exercise motivation mediates appearance comparison and fitness intention. Appearance comparison can produce a positive effect on fitness intention via appearance-based exercise motivation and perceived behavioral control in sequence.

Practical implications

The findings have some practical implications for both individuals and fitness center managers. First, people can view appearance comparison rationally, understand the process of its transformation into fitness intention and enhance fitness intention. Second, fitness center managers can make some reasonable marketing plans according to this study.

Originality/value

This study explores the positive effects of appearance comparison combining social comparison theory, social cognitive theory and the theory of planned behavior. It contributes to extant literatures about appearance comparison and fitness intention by promoting the understanding of the influence mechanism of fitness intention.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 34 no. 8
Type: Research Article
ISSN: 1355-5855

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Article
Publication date: 10 January 2023

Jianhua Zhu, Luxin Wan, Huijuan Zhao, Longzhen Yu and Siyu Xiao

The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development…

571

Abstract

Purpose

The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development of intelligent manufacturing in China. However, many enterprises blindly invest in TIOII, which affects their normal production and operation.

Design/methodology/approach

This study establishes an efficiency evaluation model for TIOII. In this paper, entropy analytic hierarchy process (AHP) constraint cone and cross-efficiency are added based on traditional data envelopment analysis (DEA) model, and entropy AHP–cross-efficiency DEA model is proposed. Then, statistical analysis is carried out on the integration efficiency of enterprises in Guangzhou using cross-sectional data, and the traditional DEA model and entropy AHP–cross-efficiency DEA model are used to analyze the integration efficiency of enterprises.

Findings

The data show that the efficiency of enterprise integration is at a medium level in Guangzhou. The efficiency of enterprise integration has no significant relationship with enterprise size and production type but has a low negative correlation with the development level of enterprise integration. In addition, the improved DEA model can better reflect the real integration efficiency of enterprises and obtain complete ranking results.

Originality/value

By adding the entropy AHP constraint cone and cross-efficiency, the traditional DEA model is improved. The improved DEA model can better reflect the real efficiency of TIOII and obtain complete ranking results.

Details

Chinese Management Studies, vol. 18 no. 1
Type: Research Article
ISSN: 1750-614X

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Article
Publication date: 20 August 2024

Siyu Zhang, Ze Lin and Wii-Joo Yhang

This study aims to develop a robust long short-term memory (LSTM)-based forecasting model for daily international tourist arrivals at Incheon International Airport (ICN)…

125

Abstract

Purpose

This study aims to develop a robust long short-term memory (LSTM)-based forecasting model for daily international tourist arrivals at Incheon International Airport (ICN), incorporating multiple predictors including exchange rates, West Texas Intermediate (WTI) oil prices, Korea composite stock price index data and new COVID-19 cases. By leveraging deep learning techniques and diverse data sets, the research seeks to enhance the accuracy and reliability of tourism demand predictions, contributing significantly to both theoretical implications and practical applications in the field of hospitality and tourism.

Design/methodology/approach

This study introduces an innovative approach to forecasting international tourist arrivals by leveraging LSTM networks. This advanced methodology addresses complex managerial issues in tourism management by providing more accurate forecasts. The methodology comprises four key steps: collecting data sets; preprocessing the data; training the LSTM network; and forecasting future international tourist arrivals. The rest of this study is structured as follows: the subsequent sections detail the proposed LSTM model, present the empirical results and discuss the findings, conclusions and the theoretical and practical implications of the study in the field of hospitality and tourism.

Findings

This research pioneers the simultaneous use of big data encompassing five factors – international tourist arrivals, exchange rates, WTI oil prices, KOSPI data and new COVID-19 cases – for daily forecasting. The study reveals that integrating exchange rates, oil prices, stock market data and COVID-19 cases significantly enhances LSTM network forecasting precision. It addresses the narrow scope of existing research on predicting international tourist arrivals at ICN with these factors. Moreover, the study demonstrates LSTM networks’ capability to effectively handle multivariable time series prediction problems, providing a robust basis for their application in hospitality and tourism management.

Originality/value

This research pioneers the integration of international tourist arrivals, exchange rates, WTI oil prices, KOSPI data and new COVID-19 cases for forecasting daily international tourist arrivals. It bridges the gap in existing literature by proposing a comprehensive approach that considers multiple predictors simultaneously. Furthermore, it demonstrates the effectiveness of LSTM networks in handling multivariable time series forecasting problems, offering practical insights for enhancing tourism demand predictions. By addressing these critical factors and leveraging advanced deep learning techniques, this study contributes significantly to the advancement of forecasting methodologies in the tourism industry, aiding decision-makers in effective planning and resource allocation.

研究目的

本研究旨在开发一种基于LSTM的强大预测模型, 用于预测仁川国际机场的日常国际游客抵达量, 结合多种预测因素, 包括汇率、WTI原油价格、韩国综合股价指数 (KOSPI) 数据和新冠疫情病例。通过利用深度学习技术和多样化数据集, 研究旨在提升旅游需求预测的准确性和可靠性, 对酒店与旅游领域的理论和实际应用有重要贡献。

研究方法

本研究通过利用长短期记忆(LSTM)网络引入创新方法, 预测国际游客抵达量。这一先进方法解决了旅游管理中的复杂管理问题, 提供了更精确的预测。方法论包括四个关键步骤: (1) 收集数据集; (2) 数据预处理; (3) 训练LSTM网络; 以及 (4) 预测未来的国际游客抵达量。本文的其余部分结构如下:后续部分详细介绍了提出的LSTM模型, 呈现了实证结果, 并讨论了研究的发现、结论以及在酒店与旅游领域的理论和实际意义。

研究发现

本研究首次同时使用包括国际游客抵达量、汇率、原油价格、股市数据和新冠疫情病例在内的大数据进行日常预测。研究显示, 整合汇率、原油价格、股市数据和新冠疫情病例显著增强了LSTM网络的预测精度。研究填补了现有研究在使用这些因素预测仁川国际机场国际游客抵达量的狭窄范围。此外, 研究证明了LSTM网络在处理多变量时间序列预测问题上的能力, 为其在酒店与旅游管理中的应用提供了坚实基础。

研究创新

本研究首次将国际游客抵达量、汇率、WTI原油价格、KOSPI数据和新冠疫情病例整合到日常国际游客抵达量的预测中。它通过提出同时考虑多个预测因素的全面方法, 弥合了现有文献的差距。此外, 研究展示了LSTM网络在处理多变量时间序列预测问题方面的有效性, 为增强旅游需求预测提供了实用见解。通过处理这些关键因素并利用先进的深度学习技术, 本研究在旅游业预测方法的进步中做出了重要贡献, 帮助决策者进行有效的规划和资源配置。

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Article
Publication date: 9 August 2023

Siyu Su, Youchao Sun, Chong Peng and Yuanyuan Guo

The purpose of this paper is to identify the key influencing factors of aviation accidents and to predict the aviation accidents caused by the factors.

181

Abstract

Purpose

The purpose of this paper is to identify the key influencing factors of aviation accidents and to predict the aviation accidents caused by the factors.

Design/methodology/approach

This paper proposes an improved gray correlation analysis (IGCA) theory to make the relational analysis of aviation accidents and influencing factors and find out the critical causes of aviation accidents. The optimal varying weight combination model (OVW-CM) is constructed based on gradient boosted regression tree (GBRT), extreme gradient boosting (XGBoost) and support vector regression (SVR) to predict aviation accidents due to critical factors.

Findings

The global aviation accident data from 1919 to 2020 is selected as the experimental data. The airplane, takeoff/landing and unexpected results are the leading causes of the aviation accidents based on IGCA. Then GBRT, XGBoost, SVR, equal-weight combination model (EQ-CM), variance-covariance combination model (VCW-CM) and OVW-CM are used to predict aviation accidents caused by airplane, takeoff/landing and unexpected results, respectively. The experimental results show that OVW-CM has a better prediction effect, and the prediction accuracy and stability are higher than other models.

Originality/value

Unlike the traditional gray correlation analysis (GCA), IGCA weights the sample by distance analysis to more objectively reflect the degree of influence of different factors on aviation accidents. OVW-CM is built by minimizing the combined prediction error at sample points and assigns different weights to different individual models at different moments, which can make full use of the advantages of each model and has higher prediction accuracy. And the model parameters of GBRT, XGBoost and SVR are optimized by the particle swarm algorithm. The study can guide the analysis and prediction of aviation accidents and provide a scientific basis for aviation safety management.

Details

Engineering Computations, vol. 40 no. 7/8
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 20 September 2022

Sunhyuk Kim, Grimm Noh and Siyu Miao

Employee voice behavior is an important source of corporate competitiveness but employees often face difficulties in voicing their opinions. This research analyzes how authentic…

518

Abstract

Purpose

Employee voice behavior is an important source of corporate competitiveness but employees often face difficulties in voicing their opinions. This research analyzes how authentic leadership may increase psychological safety perceived by employees, consequently encouraging employees to actively share their ideas. In addition, the authors explore the unique concept of Zhongyong thinking, a way of thinking that is common in cultures rooted in Confucianism. The authors analyze how Zhongyong thinking may affect the relationship between psychological safety and employee voice behavior.

Design/methodology/approach

For the empirical analysis of authentic leadership and employee voice behavior in the Chinese context, the authors distributed surveys to employees working in various different industries in various provinces in China. The authors distributed 250 surveys in total and 213 surveys were used for analyses.

Findings

The authors' empirical analyzes illustrate that authentic leadership increases employee voice behavior, partially mediated by psychological safety. The authors also analyzed how psychological safety's effect on employee voice behavior could be moderated by Zhongyong thinking. The results demonstrate that the effect of psychological safety on voice behavior is weaker when employees are capable of exercising Zhongyong thinking.

Originality/value

Zhongyong thinking is still a relatively new concept that has not been studied thoroughly, and to the authors' knowledge, Zhongyong thinking has never been studied as a moderator in the relationship between psychological safety and employee voice behavior.

Details

International Journal of Organization Theory & Behavior, vol. 25 no. 3/4
Type: Research Article
ISSN: 1093-4537

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Article
Publication date: 1 July 2020

Maozeng Xu, Zhongya Mei, Siyu Luo and Yi Tan

This paper aims to analyze and provide insight on the algorithms for the optimization of construction site layout planning (CSLP). It resolves problems, such as the selection of…

1449

Abstract

Purpose

This paper aims to analyze and provide insight on the algorithms for the optimization of construction site layout planning (CSLP). It resolves problems, such as the selection of suitable algorithms, considering the optimality, optimization objectives and representation of layout solutions. The approaches for the better utilization of optimization algorithms are also presented.

Design/methodology/approach

To achieve the above, existing records (results = 200) were selected from three databases: Web of Science, ScienceDirect and Scopus. By implementing a systematic protocol, the articles related to the optimization algorithms for the CLSP (results = 75) were identified. Moreover, various related themes were collated and analyzed according to a coding structure.

Findings

The results indicate the consistent and increasing interest on the optimization algorithms for the CLSP, revealing that the trend in shifting to smart approaches in the construction industry is significant. Moreover, the interest in metaheuristic algorithms is dominant because 65.3% of the selected articles focus on these algorithms. The optimality, optimization objectives and solution representations are also important in algorithm selection. With the employment of other algorithms, self-developed applications and commercial software, optimization algorithms can be better utilized for solving CSLP problems. The findings also identify the gaps and directions for future research.

Research limitations/implications

The selection of articles in this review does not consider the industrial perspective and practical applications of commercial software. Further comparative analyses of major algorithms are necessary because this review only focuses on algorithm types.

Originality/value

This paper presents a comprehensive systematic review of articles published in the recent decade. It significantly contributes to the demonstration of the status and selection of CLSP algorithms and the benefit of using these algorithms. It also identifies the research gaps in knowledge and reveals potential improvements for future research.

Details

Engineering, Construction and Architectural Management, vol. 27 no. 8
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 23 January 2025

Ningning Cui and Jianyu Zhang

The profound impact of the COVID-19 pandemic on the film industry has underscored the growing significance of online movies. However, there is limited research available on the…

12

Abstract

Purpose

The profound impact of the COVID-19 pandemic on the film industry has underscored the growing significance of online movies. However, there is limited research available on the factors that influence the viewership of online films. Therefore, this study aims to use the signaling theory to investigate how signals of varying qualities affect online movie viewership, considering both signal transmission costs and prices.

Design/methodology/approach

This study uses a sample of 1,071 online movies released on the iQiyi from July 2020 to July 2022. It uses OLS regression and instrumental variable method to examine the impact of various quality indicators on the viewership of online movies, as well as the moderating effect of price.

Findings

After conducting a thorough analysis of this study, it can be deduced that the varying impacts on online movie viewership are attributed to disparities in signal transmission costs. Specifically, star influence and rating exhibit a positive effect on the viewership of online movies, whereas the number of raters has a detrimental impact. Furthermore, there exists an “inverted U-shaped” relationship between the number of reviews and online movie viewership. Additionally, within the consumer decision-making process, both price-cost and price-quality relationships coexist. This is evident as prices negatively affect online movie viewership but positively moderate the relationship between rating, number of reviews and online movie viewership.

Originality/value

The research findings of this study offer valuable insights for online film producers to effectively leverage quality signals and pricing, thereby capturing market attention and enhancing film profitability.

Details

Nankai Business Review International, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-8749

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Article
Publication date: 5 September 2018

Linhao Ouyang, Zijian Zhang, Xiaoling Huang and Shi Xie

The purpose of this study is to restore the spatial distribution of overseas remittance businesses in Shantou during the 1940s. It explores various socioeconomic factors that…

142

Abstract

Purpose

The purpose of this study is to restore the spatial distribution of overseas remittance businesses in Shantou during the 1940s. It explores various socioeconomic factors that influenced the concentration of local remittance business investment in real estate. By reconstructing the spatial distribution of remittance business activities in Shantou, this study hopes to lay a foundation for further analysis of the business strategies of Chaoshan merchants.

Design/methodology/approach

This research draws on information from the published Swatow Guide, archival sources and cadastral maps to identify the location of remittance enterprises and the native place and overseas networks of property owners.

Finding

This study reveals that the spatial distribution of the remittance enterprises was determined by the native place origins of local property owners, and that the inflow of overseas Chinese capital contributed to real estate development in Shantou.

Research limitations/implications

Despite the limited access to Chinese official archives, this paper manages to identify several building blocks and neighbors in Shantou for spatial analysis.

Practical implications

This study is the first attempt to use the geographical information system (GIS) method in Chinese urban history research and hopes to establish a larger historical database of Shantou as a sample for comparison.

Originality/value

This investigation advances the spatial study of urban history and overseas Chinese remittances in the maritime society of South China.

Details

Social Transformations in Chinese Societies, vol. 14 no. 2
Type: Research Article
ISSN: 1871-2673

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Article
Publication date: 25 January 2021

Obay A. Al-Maraira and Sami Z. Shennaq

This study aims to determine depression, anxiety and stress levels of health-care students during coronavirus (COVID-19) pandemic according to various socio-demographic variables.

1918

Abstract

Purpose

This study aims to determine depression, anxiety and stress levels of health-care students during coronavirus (COVID-19) pandemic according to various socio-demographic variables.

Design/methodology/approach

This cross-sectional study was conducted with 933 students. Data were collected with an information form on COVID- 19 and an electronic self-report questionnaire based on depression, anxiety and stress scale.

Findings

Findings revealed that 58% of the students experienced moderate-to-extremely severe depression, 39.8% experienced moderate-to-extremely severe anxiety and 38% experienced moderate-to-extremely severe stress.

Practical implications

Educational administrators can help reduce long-term negative effects on students’ education and mental health by enabling online guidance, psychological counseling and webinars for students.

Originality/value

This paper is original and adds to existing knowledge that health-care students’ depression, anxiety and stress levels were affected because of many factors that are not yet fully understood. Therefore, psychological counseling is recommended to reduce the long-term negative effects on the mental health of university students.

Details

Mental Health Review Journal, vol. 26 no. 2
Type: Research Article
ISSN: 1361-9322

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