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Article
Publication date: 9 June 2023

Yuyan Luo, Xiaojing Yu, Fei Xie, Zheng Yang and Jun Wang

The purpose is to provide decision support for tourists recommending scenic spots and corresponding suggestions for the management of scenic spots.

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Abstract

Purpose

The purpose is to provide decision support for tourists recommending scenic spots and corresponding suggestions for the management of scenic spots.

Design/methodology/approach

Based on the Baidu index data generated, this paper analyzes the temporal and spatial characteristics of network attention of 5A scenic spots in Sichuan Province. The online comment data are used to build the assessment model of scenic spots based on network attention, and the comment information of tourists is mined and analyzed through statistical analysis. At the same time, the key attributes of scenic spots from the perspective of network attention are evaluated and analyzed by using the probabilistic linguistic term set. Finally, this paper further constructs a recommendation model based on the key attribute set of scenic spots.

Findings

This paper uses different types of tourism network information, integrates multi-types of data and methods, fully excavates the value information of tourism network information, constructs the research framework of “scenic spot assessment + scenic spot recommendation” from the perspective of network attention, analyzes the network attention characteristics of scenic spots, evaluates the performance of scenic spots, and implements scenic spot recommendation.

Originality/value

This paper integrates multi-source data and multidisciplinary theoretical methods to form a scenic spot research framework of “assessment + recommendation” from the perspective of network attention.

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Article
Publication date: 9 November 2021

Yuyan Luo, Tao Tong, Xiaoxu Zhang, Zheng Yang and Ling Li

In the era of information overload, the density of tourism information and the increasingly sophisticated information needs of consumers have created information confusion for…

507

Abstract

Purpose

In the era of information overload, the density of tourism information and the increasingly sophisticated information needs of consumers have created information confusion for tourists and scenic-area managers. The study aims to help scenic-area managers determine the strengths and weaknesses in the development process of scenic areas and to solve the practical problem of tourists' difficulty in quickly and accurately obtaining the destination image of a scenic area and finding a scenic area that meets their needs.

Design/methodology/approach

The study uses a variety of machine learning methods, namely, the latent Dirichlet allocation (LDA) theme extraction model, term frequency-inverse document frequency (TF-IDF) weighting method and sentiment analysis. This work also incorporates probabilistic hesitant fuzzy algorithm (PHFA) in multi-attribute decision-making to form an enhanced tourism destination image mining and analysis model based on visitor expression information. The model is intended to help managers and visitors identify the strengths and weaknesses in the development of scenic areas. Jiuzhaigou is used as an example for empirical analysis.

Findings

In the study, a complete model for the mining analysis of tourism destination image was constructed, and 24,222 online reviews on Jiuzhaigou, China were analyzed in text. The results revealed a total of 10 attributes and 100 attribute elements. From the identified attributes, three negative attributes were identified, namely, crowdedness, tourism cost and accommodation environment. The study provides suggestions for tourists to select attractions and offers recommendations and improvement measures for Jiuzhaigou in terms of crowd control and post-disaster reconstruction.

Originality/value

Previous research in this area has used small sample data for qualitative analysis. Thus, the current study fills this gap in the literature by proposing a machine learning method that incorporates PHFA through the combination of the ideas of management and multi-attribute decision theory. In addition, the study considers visitors' emotions and thematic preferences from the perspective of their expressed information, based on which the tourism destination image is analyzed. Optimization strategies are provided to help managers of scenic spots in their decision-making.

Details

Kybernetes, vol. 52 no. 3
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 16 July 2021

Yuyan Luo, Zheng Yang, Yuan Liang, Xiaoxu Zhang and Hong Xiao

Based on climate issues and carbon emissions, this study aims to promote low-carbon consumption and compel consumers to actively shift to energy-saving appliances. In this big…

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Abstract

Purpose

Based on climate issues and carbon emissions, this study aims to promote low-carbon consumption and compel consumers to actively shift to energy-saving appliances. In this big data era, online reviews in social and electronic commerce (e-commerce) websites contain valuable product information, which can facilitate firm business strategies and consumer comparison shopping. This study is designed to advance existing research on energy-saving refrigerators by incorporating machine learning models in the analysis of online reviews to provide valuable suggestions to e-commerce platform managers and manufacturers to effectively understand the psychological cognition of consumers.

Design/methodology/approach

This study proposes an online e-commerce review mining and management strategy model based on “data acquisition and cleaning, data mining and analysis and strategy formation” through multiple machine learning methods, namely, Bayes networks, support vector machine (SVM), latent Dirichlet allocation (LDA) and importance–performance analysis (IPA), to help managers.

Findings

Based on a case study of one of the largest e-commerce platforms in China, this study linguistically analyzes 29,216 online reviews of energy-saving refrigerators. Results indicate that the energy-saving refrigerator features that consumers are generally satisfied with are, in sequential order, logistics, function, price, outlook, after-sales service, brand, quality and space. This study also identifies ten topics with 100 keywords by analyzing 18 different refrigerator models. Finally, based on the IPA, this study allocates different priorities to the features and provides suggestions from the perspective of consumers, the government and manufacturers.

Research limitations/implications

In terms of limitations, future research may focus on the following points. First, the topics identified in this study derive from specific points in time and reviews; thus, the topics may change with the text data. A machine learning-based online review analysis platform could be developed in the future to dynamically improve consumer satisfaction. Moreover, given that consumers' needs may change over time, e-commerce platform types and consumer characteristics, such as user profiles, can be incorporated into the model to effectively analyze trends in consumers' perceived dimensions.

Originality/value

This study fills the gap in previous research in this field, which uses small-sample data for qualitative analysis, while integrating management ideas and proposes an online e-commerce review mining and management strategy model based on machine learning methods. Moreover, this study considers how consumers' emotional and thematic preferences for products affect their purchase decision-making from the perspective of their psychological perception and linguistically analyzes online reviews of energy-saving refrigerators using the proposed mining model. Through the improved IPA model, this study provides optimizing strategies to help e-commerce platform managers and manufacturers.

Details

Kybernetes, vol. 51 no. 9
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 2 January 2025

Difei Hu, Mengting Zhang, Yuyan He and Hong Wei

National identity has a profound impact on building a modern state, maintaining social stability and promoting economic development. Based on three waves of data collected from…

21

Abstract

Purpose

National identity has a profound impact on building a modern state, maintaining social stability and promoting economic development. Based on three waves of data collected from the World Values Survey (WVS) in Hong Kong between 2005 and 2018, this study aims to examine the changes in the national identity awareness of Hong Kongese over time.

Design/methodology/approach

The data used in this paper originate from the WVS. The WVS is a cross-country time-series survey that has been carried out in seven waves in 85 countries around the world, since 1981. There are three waves of data involving Hong Kong, which were obtained from the surveys in 2005, 2014 and 2018.

Findings

This study examined the changes in the national identity awareness of Hong Kongese over time and found that this has shown both continuity and rupture. Extreme groups lacking national identity have emerged and become more common over the decades and the elites’ national identity is much stronger than that of the lower and middle classes. It also shows that political trust, social capital, subjective well-being and possession of authoritarian personality have strong explanatory power for the changes in Hong Kongese national identity over time, but their explanatory strength varies across eras.

Originality/value

Based on three waves of surveys conducted by the WVS in Hong Kong in 2005, 2014 and 2018, respectively, this paper charts these changes over time and explores the differences in how they are influenced by political trust, social capital, subjective well-being and authoritarian personality.

Details

Social Transformations in Chinese Societies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1871-2673

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Article
Publication date: 4 April 2023

Yuyan Wang, Fei Lin, T.C.E. Cheng, Fu Jia and Yulin Sun

The purpose of this study is to investigate which of the two carbon allowance allocation methods (CAAMs), i.e. grandfathered system carbon allowance allocation (GCAA) and baseline…

368

Abstract

Purpose

The purpose of this study is to investigate which of the two carbon allowance allocation methods (CAAMs), i.e. grandfathered system carbon allowance allocation (GCAA) and baseline system carbon allowance allocation (BCAA), is more beneficial to capital-constrained supply chains under the carbon emission allowance repurchase strategy (CEARS).

Design/methodology/approach

Adopting CEARS to ease the capital-constrained supply chains, this study develops two-period game models with manufacturers as leaders and retailers as followers from the perspective of profit and social welfare maximization under two CAAMs (GCAA and BCAA), where the first period produces normal products, and the second period produces low-carbon products.

Findings

First, higher carbon-saving can better use CEARS and achieve a higher supply chain profit under the two CAAMs. However, the higher the end-of-period carbon price is, the lower the social welfare is. Second, when carbon-saving is small, GCAA achieves both economic and environmental benefits; BCAA reduces carbon emissions at the expense of economic benefit. Third, the supply chain members gain higher profits and social welfare under GCAA, so the government and supply chain members are more inclined to choose GCAA.

Originality/value

By analyzing the profits and total carbon emissions of capital-constrained supply chains under GCAA and BCAA, this study provides theoretical references for retailers and capital-constrained manufacturers. In addition, by comparing the difference in social welfare under GCAA and BCAA, it provides a basis for the government to choose a reasonable CAAM.

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Article
Publication date: 14 March 2019

Hailiang Su, Fengchong Lan, Yuyan He and Jiqing Chen

Meta-model method has been widely used in structural reliability optimization design. The main limitation of this method is that it is difficult to quantify the error caused by…

237

Abstract

Purpose

Meta-model method has been widely used in structural reliability optimization design. The main limitation of this method is that it is difficult to quantify the error caused by the meta-model approximation, which leads to the inaccuracy of the optimization results of the reliability evaluation. Taking the local high efficiency of the proxy model, this paper aims to propose a local effective constrained response surface method (LEC-RSM) based on a meta-model.

Design/methodology/approach

The operating mechanisms of LEC-RSM is to calculate the index of the local relative importance based on numerical theory and capture the most effective area in the entire design space, as well as selecting important analysis domains for sample changes. To improve the efficiency of the algorithm, the constrained efficient set algorithm (ESA) is introduced, in which the sample point validity is identified based on the reliability information obtained in the previous cycle and then the boundary sampling points that violate the constraint conditions are ignored or eliminated.

Findings

The computational power of the proposed method is demonstrated by solving two mathematical problems and the actual engineering optimization problem of a car collision. LEC-RSM makes it easier to achieve the optimal performance, less feature evaluation and fewer algorithm iterations.

Originality/value

This paper proposes a new RSM technology based on proxy model to complete the reliability design. The originality of this paper is to increase the sampling points by identifying the local importance of the analysis domain and introduce the constrained ESA to improve the efficiency of the algorithm.

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Article
Publication date: 11 November 2009

Ilan Alon, Romie F. Littrell and Allan K.K. Chan

This article reviews and discusses issues in the translation of international brand names to Chinese, and provides a framework for international brand managers who want to expand…

2351

Abstract

This article reviews and discusses issues in the translation of international brand names to Chinese, and provides a framework for international brand managers who want to expand into China. Linguistic differences between Chinese and English are wide and deep, making translation of brand names difficult. Cultural context, pronunciation, written vs. oral language, and the meaning of characters are just a few examples of such difficulties. We discuss four global product‐naming strategic alternatives available to country/brand managers, along with their usage. The four approaches include (1) dual extension, (2) brand meaning extension, (3) brand feeling extension, and (4) dual adaptation. We also provide examples of brands utilizing the different approaches.

Details

Multinational Business Review, vol. 17 no. 4
Type: Research Article
ISSN: 1525-383X

Keywords

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Article
Publication date: 7 November 2024

Yuyan Wei and Devashish Pujari

Green innovation and green acquisition are key green marketing strategies. This paper aims to explore and compare the drivers of green acquisition and green innovation strategies…

102

Abstract

Purpose

Green innovation and green acquisition are key green marketing strategies. This paper aims to explore and compare the drivers of green acquisition and green innovation strategies firms adopt. Moreover, the moderating role of top management team (TMT) sustainability commitment is investigated.

Design/methodology/approach

The research model used secondary data based on 1,565 firm-year observations in the beverage and food industry in the US. The two-stage control function approach was used for data analysis.

Findings

Media attention motivates firms to pursue both green innovation and green acquisition. The TMT sustainability commitment plays a pivotal moderating role. It strengthens the link between environmental regulation stringency and green innovation but weakens the impact of media attention on green acquisition.

Practical implications

Managers can leverage the study’s findings to guide sustainable marketing decisions in response to environmental regulations and media scrutiny. Policymakers and investors can encourage firms to adopt more sustainable practices, helping align corporate strategies with Sustainable Development Goals 9 and 12.

Originality/value

Though green innovation determinants are extensively studied, most studies rely on surveys or qualitative methods rather than secondary data. Also, as an alternative to developing in-house green technologies or products, the drivers of green acquisition remain unclear despite its growing prevalence. This study addresses both gaps in the sustainable marketing literature.

Details

Journal of Business & Industrial Marketing, vol. 40 no. 1
Type: Research Article
ISSN: 0885-8624

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Article
Publication date: 8 January 2020

Hailiang Su, Fengchong Lan, Yuyan He and Jiqing Chen

Because of the high computational efficiency, response surface method (RSM) has been widely used in structural reliability analysis. However, for a highly nonlinear limit state…

193

Abstract

Purpose

Because of the high computational efficiency, response surface method (RSM) has been widely used in structural reliability analysis. However, for a highly nonlinear limit state function (LSF), the approximate accuracy of the failure probability mainly depends on the design point, and the result is that the response surface function composed of initial experimental points rarely fits the LSF exactly. The inaccurate design points usually cause some errors in the traditional RSM. The purpose of this paper is to present a hybrid method combining adaptive moving experimental points strategy and RSM, describing a new response surface using downhill simplex algorithm (DSA-RSM).

Design/methodology/approach

In DSA-RSM, the operation mechanism principle of the basic DSA, in which local descending vectors are automatically generated, was studied. Then, the search strategy of the basic DSA was changed and the RSM approximate model was reconstructed by combining the direct search advantage of DSA with the reliability mechanism of response surface analysis.

Findings

The computational power of the proposed method is demonstrated by solving four structural reliability problems, including the actual engineering problem of a car collision. Compared to specific structural reliability analysis methods, the approach of modified DSA interpolation response surface for structural reliability has a good convergent capability and computational accuracy.

Originality/value

This paper proposes a new RSM technology based on proxy model to complete the reliability analysis. The originality of this paper is to present an improved RSM that adjusts the position of the experimental points judiciously by using the DSA principle to make the fitted response surface closer to the actual limit state surface.

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Article
Publication date: 24 June 2024

Qian Li, Qi Zhang, Yuyan Shen and Xiang Zhang

The elevator installation in old communities (EIOC) can effectively improve the public infrastructure of urban communities. However, differences in the decision-making behaviours…

41

Abstract

Purpose

The elevator installation in old communities (EIOC) can effectively improve the public infrastructure of urban communities. However, differences in the decision-making behaviours of stakeholders lead to frequent conflicts, thereby hindering the implementation of EIOC. The purpose of this study is to explore the decision-making behavior of core stakeholders which are the government, community owners and elevator enterprises at different stages in the EIOC using the evolutionary game method.

Design/methodology/approach

A tripartite evolutionary game model involving the government, community owners and elevator enterprises was developed, and their evolutionary stabilisation strategies were explored in different stages. The dynamic change of the stakeholders' decision-making behaviours at different stages of the project and the influencing mechanism of the key factors on the decision-making behaviours of the three stakeholders were analysed through numerical simulation.

Findings

The results of this study showed that: Divergent interests led the government, community owners and elevator enterprises to adopt distinct decision-making behaviours at different stages, resulting in diverse attitudes and actions among stakeholders. A dynamic reward and penalty mechanism effectively motivated community owners and elevator enterprises to engage actively, fostering broad participation. However, the high regulatory cost diminished the government's regulatory effectiveness. This imbalance between penalties and incentives posed a challenge, impacting the overall effectiveness and efficiency of implementing the EIOC.

Originality/value

Existing research lacks exploration of the decision-making behaviours of stakeholders in community public infrastructure. This study developed a dynamic tripartite evolutionary game model in the EIOC from the gaming perspective. The results of this study provide a reference for dealing with the stakeholders' interests in the community public infrastructure and contribute to the theoretical basis for establishing an effective supervision mechanism.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

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