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Article
Publication date: 26 August 2020

Yi Yang and Wei Pan

This paper aims to examine the potentials of using automated guided vehicle (AGV) technology in modular integrated construction (MiC) to realise logistics automation in module…

1307

Abstract

Purpose

This paper aims to examine the potentials of using automated guided vehicle (AGV) technology in modular integrated construction (MiC) to realise logistics automation in module manufacturing and transport.

Design/methodology/approach

This paper adopts a scenario approach through three phases (i.e. scenario preparation, development and transfer), with six steps performed iteratively. The scenarios were systematically developed using a six-aspect socio-technical framework. Data were collected through a comprehensive literature review, site visits and interviews with relevant stakeholders and professionals. Implications regarding strength, weakness, opportunities and challenges and future research directions are provided.

Findings

The developed scenarios of “smart manufacturing” and “last-mile delivery” demonstrated how AGVs could be used to enhance efficiency and productivity in module manufacturing and transport. The synergies between AGVs and emerging information technologies should pave a good foundation for realising logistics automation in MiC. Future research should address: how to define the tasks of AGVs, how will the use of AGVs impact MiC practices, how to design AGV-integrated module manufacturing/transport systems and how to integrate people factors into the use of AGVs in MiC.

Practical implications

This paper reveals the socio-technical benefits and challenges of using AGVs in MiC.

Originality/value

This study extends the understanding of using logistics automation in MiC as emerging research directions, with the intention of directing scholars’ and practitioners’ interest into future exploration. It is the first attempt in its kind. Its findings could be extended to constitute a comprehensive development roadmap and prospects of automation in modular construction.

Details

Construction Innovation , vol. 21 no. 1
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 18 May 2021

Fengjun Tian, Yang Yang, Zhenxing Mao and Wenyue Tang

This paper aims to compare the forecasting performance of different models with and without big data predictors from search engines and social media.

1624

Abstract

Purpose

This paper aims to compare the forecasting performance of different models with and without big data predictors from search engines and social media.

Design/methodology/approach

Using daily tourist arrival data to Mount Longhu, China in 2018 and 2019, the authors estimated ARMA, ARMAX, Markov-switching auto-regression (MSAR), lasso model, elastic net model and post-lasso and post-elastic net models to conduct one- to seven-days-ahead forecasting. Search engine data and social media data from WeChat, Douyin and Weibo were incorporated to improve forecasting accuracy.

Findings

Results show that search engine data can substantially reduce forecasting error, whereas social media data has very limited value. Compared to the ARMAX/MSAR model without big data predictors, the corresponding post-lasso model reduced forecasting error by 39.29% based on mean square percentage error, 33.95% based on root mean square percentage error, 46.96% based on root mean squared error and 45.67% based on mean absolute scaled error.

Practical implications

Results highlight the importance of incorporating big data predictors into daily demand forecasting for tourism attractions.

Originality/value

This study represents a pioneering attempt to apply the regularized regression (e.g. lasso model and elastic net) in tourism forecasting and to explore various daily big data indicators across platforms as predictors.

Details

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

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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

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Article
Publication date: 10 January 2020

Shi Yang Pan, Jing Cheng and Tong Chun Li

The meshfree node-based smoothed point interpolation method (NS-PIM) is extended to the forward and inversion analysis of a high gravelly soil core rock-fill dam during…

174

Abstract

Purpose

The meshfree node-based smoothed point interpolation method (NS-PIM) is extended to the forward and inversion analysis of a high gravelly soil core rock-fill dam during construction periods.

Design/methodology/approach

As one member of the meshfree methods, the NS-PIM has the advantages of “softer” stiffness and adaptability to large deformations which is quite indispensable for the stability analysis of rock-fill dams. In this work, the present method contains a reconstruction procedure to deal with the existence or nonexistence of the construction layers. After verifying the validity of the NS-PIM method for nonlinear elastic model during construction period, the convergence features of the NS-PIM and FEM methods are further investigated with different mesh schemes. Furthermore, the NS-PIM and FEM methods are applied for the forward analysis of a high gravelly soil core rock-fill dam and the convergence features under complex stress conditions are also studied using the rock-fill dam model. Finally, the NS-PIM method is used to calculate the Duncan–Chang parameters of the deep overburden under the high gravelly soil core rock-fill dam based on the back-propagation neural network method.

Findings

The results show that: the NS-PIM solution for construction analysis still possesses the property of upper bound solution even under complex stress conditions and can provide comparatively more conservative results for safety evaluation. Furthermore, it can be used to evaluate the accuracy of results and mesh quality together with the FEM solution which has the property of lower bound solution; the inversion analysis in this work provides a set of material parameters for the deep overburden under high rock-fill dam during construction period and the calculated results show good agreement with the measured displacement values and it is feasible to apply the NS-PIM to the forward and inversion analysis of high rock-fill dams on deep overburden during construction periods.

Research limitations/implications

In further study, the feasibility of three-dimensional problems, elastic–plastic problems, contact problems and multipoint inversion can still be probed in the NS-PIM solution for the forward and inversion analysis of high rock-fill dams on deep overburden.

Practical implications

This paper introduced a method for the forward and inversion analysis of high rock-fill dams during construction period using the NS-PIM solution. The property of upper bound solution ensures that the NS-PIM can provide more conservative results for safety evaluation. The inversion analysis in this work provides a set of material parameters for the deep overburden under high rock-fill dam during construction periods.

Originality/value

First, the analysis from forward to inversion for high rock-fill dams during construction period using the NS-PIM solution is accomplished in this work. A procedure dealing with the existence or nonexistence of the construction layers is also developed for the construction analysis. Second, it is confirmed in this work that the NS-PIM still possesses the property of upper bound solution even under complex stress conditions (the forward analysis of high rock-fill dams during construction period). Thus, more conservative results can be provided for safety evaluation. Furthermore, it can be used to evaluate the accuracy of results and mesh quality together with the FEM solution which has the property of lower bound solution. Third, the calculated material parameters of the deep overburden in this work can be used for further studies of the high rock-fill dam.

Details

Engineering Computations, vol. 37 no. 5
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 21 November 2023

Tianyao Ping, Wei Pan and Zhiqian Zhang

Modular construction is an innovative method that enhances the performance of building construction projects. However, the performance of steel modular construction has not been…

409

Abstract

Purpose

Modular construction is an innovative method that enhances the performance of building construction projects. However, the performance of steel modular construction has not been systematically understood, and the existing measurement methods exhibit limitations in effectively addressing the features of steel modular building construction. Therefore, this study aims to develop a new performance measurement framework for systematically examining the performance of steel modular construction in building projects.

Design/methodology/approach

This study was conducted through a mixed-method research design that combines a comprehensive review of the state-of-the-art practices of construction performance measurement and a case study with a 17-story steel modular apartment building project in Hong Kong. The case project was measured with data collected from the project teams and other reliable channels, and the measurement practices and findings were referenced to establish a systematic performance measurement framework for steel modular construction.

Findings

Considering steel modular construction as a complex socio-technical system, a systematic performance measurement framework was developed, which considers the features of steel modular construction, focuses on the construction stage, incorporates the views of various stakeholders, integrates generic and specific key performance indicators and provides a benchmarking process. Multifaceted benefits of adopting steel modular construction were demonstrated with case study, including improved economic efficiency (e.g. nearly 10% cost savings), improved environmental friendliness (e.g. approximately 90% waste reduction) and enhanced social welfare (e.g. over 60% delivery trips reduction).

Originality/value

This paper extends the existing performance measurement methods with a new framework proposed and offers experience for future steel modular construction. The measured performance of the case project also contributes in-depth understanding on steel modular construction with benefits demonstrated. The study is expected to accelerate an effective uptake of steel modular construction in building projects.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 12 January 2024

Li Chen, Yiwen Chen and Yang Pan

This study aims to empirically test how sponsored video customization (i.e. the degree to which a sponsored video is customized for a sponsoring brand) affects video shares…

1094

Abstract

Purpose

This study aims to empirically test how sponsored video customization (i.e. the degree to which a sponsored video is customized for a sponsoring brand) affects video shares differently depending on influencer characteristics (i.e. mega influencer and expert influencer) and brand characteristics (i.e. brand establishment and product involvement).

Design/methodology/approach

This study uses a unique real-world data set that combines coded variables (e.g. customization) and objective video performance (e.g. sharing) of 365 sponsored videos to test the hypotheses. A negative binomial model is used to analyze the data set.

Findings

This study finds that the effect of video customization on video shares varies across contexts. Video customization positively affects shares if they are made for well-established brands and high-involvement products but negatively influences shares if they are produced by mega and expert influencers.

Research limitations/implications

This study extends the influencer marketing literature by focusing on a new media modality – sponsored video. Drawing on the multiple inference model and the persuasion knowledge theory, this study teases out different conditions under which video customization is more or less likely to foster audience engagement, which both influencers and brands care about. The chosen research setting may limit the generalizability of the findings of this study.

Practical implications

The findings suggest that mega and expert influencers need to consider if their endorsement would backfire on a highly customized video. Brands that aim to engage customers with highly-customized videos should gauge their decision by taking into consideration their years of establishment and product involvement. For video-sharing platforms, especially those that are planning to expand their businesses to include “matching-making services” for brands and influencers, the findings provide theory-based guidance on optimizing such matches.

Originality/value

This paper fulfills an urgent research need to study how brands and influencers should produce sponsored videos to achieve optimal outcomes.

Details

European Journal of Marketing, vol. 58 no. 4
Type: Research Article
ISSN: 0309-0566

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Article
Publication date: 12 November 2021

Marcello Mariani and Rodolfo Baggio

The purpose of this work is to survey the body of research revolving around big data (BD) and analytics in hospitality and tourism, by detecting macro topical areas, research…

4587

Abstract

Purpose

The purpose of this work is to survey the body of research revolving around big data (BD) and analytics in hospitality and tourism, by detecting macro topical areas, research streams and gaps and to develop an agenda for future research.

Design/methodology/approach

This research is based on a systematic literature review of academic papers indexed in the Scopus and Web of Science databases published up to 31 December 2020. The outputs were analyzed using bibliometric techniques, network analysis and topic modeling.

Findings

The number of scientific outputs in research with hospitality and tourism settings has been expanding over the period 2015–2020, with a substantial stability of the areas examined. The vast majority are published in academic journals where the main reference area is neither hospitality nor tourism. The body of research is rather fragmented and studies on relevant aspects, such as BD analytics capabilities, are virtually missing. Most of the outputs are empirical. Moreover, many of the articles collected relatively small quantities of records and, regardless of the time period considered, only a handful of articles mix a number of different techniques.

Originality/value

This work sheds new light on the emergence of a body of research at the intersection of hospitality and tourism management and data science. It enriches and complements extant literature reviews on BD and analytics, combining these two interconnected topics.

Details

International Journal of Contemporary Hospitality Management, vol. 34 no. 1
Type: Research Article
ISSN: 0959-6119

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Book part
Publication date: 13 December 2017

Qiongwei Ye and Baojun Ma

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to…

Abstract

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

Details

Internet+ and Electronic Business in China: Innovation and Applications
Type: Book
ISBN: 978-1-78743-115-7

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Article
Publication date: 16 August 2022

Liyao Huang, Cheng Li and Weimin Zheng

Given the importance of spatial effects in improving the accuracy of hotel demand forecasting, this study aims to introduce price and online rating, two critical factors…

770

Abstract

Purpose

Given the importance of spatial effects in improving the accuracy of hotel demand forecasting, this study aims to introduce price and online rating, two critical factors influencing hotel demand, as external variables into the model, and capture the spatial and temporal correlation of hotel demand within the region.

Design/methodology/approach

For high practical implications, the authors conduct the case study in Xiamen, China, where the hotel industry is prosperous. Based on the daily demand data of 118 hotels before and during the COVID-19 period (from January to June 2019 and from January to June 2021), the authors evaluate the prediction performance of the proposed innovative model, that is, a deep learning-based model, incorporating graph convolutional networks (GCN) and gated recurrent units.

Findings

The proposed model simultaneously predicts the daily demand of multiple hotels. It effectively captures the spatial-temporal characteristics of hotel demand. In addition, the features, price and online rating of competing hotels can further improve predictive performance. Meanwhile, the robustness of the model is verified by comparing the forecasting results for different periods (during and before the COVID-19 period).

Practical implications

From a long-term management perspective, long-term observation of market competitors’ rankings and price changes can facilitate timely adjustment of corresponding management measures, especially attention to extremely critical factors affecting forecast demand, such as price. While from a short-term operational perspective, short-term demand forecasting can greatly improve hotel operational efficiency, such as optimizing resource allocation and dynamically adjusting prices. The proposed model not only achieves short-term demand forecasting, but also greatly improves the forecasting accuracy by considering factors related to competitors in the same region.

Originality/value

The originalities of the study are as follows. First, this study represents a pioneering attempt to incorporate demand, price and online rating of other hotels into the forecasting model. Second, integrated deep learning models based on GCN and gated recurrent unit complement existing predictive models using historical data in a methodological sense.

Details

International Journal of Contemporary Hospitality Management, vol. 35 no. 1
Type: Research Article
ISSN: 0959-6119

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Article
Publication date: 6 August 2024

Peng Chen, Li Lan, Mingxing Guo, Fei Fei and Hua Pan

By comparing and contrasting the two scenarios of power producers investing in renewable energy and electricity sellers investing in renewable energy, we explore the conditions…

70

Abstract

Purpose

By comparing and contrasting the two scenarios of power producers investing in renewable energy and electricity sellers investing in renewable energy, we explore the conditions under which profit growth and carbon emission reduction can be realized, and provide a theoretical basis for decision-making on renewable energy investment by electric power companies as well as for government policy formulation.

Design/methodology/approach

This paper constructs a game model of a grid supply chain consisting of a leader generator and a follower seller in the context of the C&T mechanism, considering two scenarios in which the generator and the seller invest in renewable energy. Conclusions are drawn by comparing and analyzing the equilibrium solutions in different scenarios.

Findings

The scenario where electricity sellers invest in renewable energy exhibits a higher investment volume compared to the scenario involving power generators. In scenarios where power producers invest in renewable energy, electricity sellers achieve lower profits than power generators, while scenarios with electricity seller' investments yield higher profits for them. Increasing the cost coefficient of renewable energy investment reduces investment volume, electricity prices and electricity demand, leading to decreased profits for electricity seller but increased profits for power generator. A rise in the preference coefficient for renewable energy results in increased profits for electricity seller but decreased profits for power generator.

Originality/value

Addressing a literature gap in the context of low carbon, this study examines the investment scenario of electricity sellers in low carbon technologies, complementing existing research focused on power generators and consumers. The findings enrich knowledge in low carbon investment. By analyzing the investment decisions of both power producers and electricity sellers, this study explores the practical implications of renewable energy investments on the decision-making and operational dynamics of power supply chain enterprises. It sheds light on their profitability and investment strategies.

Details

Management of Environmental Quality: An International Journal, vol. 35 no. 8
Type: Research Article
ISSN: 1477-7835

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