Hanqing Gong, Lingling Shi, Xiang Zhai, Yimin Du and Zhijing Zhang
The purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience.
Abstract
Purpose
The purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience.
Design/methodology/approach
By integrating case-based reasoning (CBR) and ontology technology, a multilevel assembly ontology is proposed. Under the general framework, the knowledge of the assembly domain is described hierarchically and associatively. On this basis, an assembly process case matching method is developed.
Findings
By fully considering the influence of ontology individual, case structure, assembly scenario and introducing the correction factor, the similarity between non-correlated parts is significantly reduced. Compared with the Triple Matching-Distance Model, the degree of distinction and accuracy of parts matching are effectively improved. Finally, the usefulness of the proposed method is also proved by the matching of four practical assembly cases of precision components.
Originality/value
The process knowledge in historical assembly cases is expressed in a specific ontology framework, which makes up for the defects of the traditional CBR model. The proposed matching method takes into account all aspects of ontology construction and can be used well in cross-ontology similarity calculations.
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Aixin Zhang, Wenli Deng, Qiuyang Li, Zilong Song and Guizhen Ke
This paper aims to demonstrate that, in line with the emerging trend of multifunctional yarn development, cotton yarn can effectively harness renewable solar energy to achieve…
Abstract
Purpose
This paper aims to demonstrate that, in line with the emerging trend of multifunctional yarn development, cotton yarn can effectively harness renewable solar energy to achieve photothermal conversion and thermochromism. This innovation not only maintains the comfort associated with natural fiber cotton yarn but also enhances its ultraviolet (UV) light resistance.
Design/methodology/approach
In this work, 4% zirconium carbide (ZrC) and thermochromic powder were adhered to cotton yarn through polyurethane (PU) by sizing coating method. After sizing, the two cotton yarns are twisted by ring spinning to obtain composite yarns with photothermal conversion and thermochromic functions.
Findings
The yarn obtained by cotton/6%PU/8% thermochromic dye single yarn and cotton/6%PU/4% ZrC single yarn composite is the best match. After 5 min of infrared light, the temperature of the composite yarn rose to the maximum, increasing by 36.1°C. The ΔE* value before and after irradiation of infrared lamp is 26.565, which proves that the thermochromic function is good. The yarn dryness unevenness was significantly reduced by 27.2%. The composite yarn has a UPF value of up to 89.22, and its performance characteristics remain stable after 100 minutes of washing.
Originality/value
The composite yarn’s photothermal conversion and thermochromism functions are mutually reinforcing. Using sunlight can simultaneously achieve heating and discoloration effects without consuming additional energy. The cotton yarn used in this application is versatile, and suitable for a wide range of uses including clothing, temperature visualization detection and other scenarios.
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Yuke Yuan, Chung-Shing Chan, Sarah Eichelberger, Hang Ma and Birgit Pikkemaat
This paper investigates the usage and trust of Chinese social media in the travel planning process (pre-trip, during-trip and post-trip) of Chinese tourists.
Abstract
Purpose
This paper investigates the usage and trust of Chinese social media in the travel planning process (pre-trip, during-trip and post-trip) of Chinese tourists.
Design/methodology/approach
Through a combination of structured online survey (n = 406) and follow-up interviews, the research identifies the diversification of the demand-and-supply patterns of social media users in China, as well as the allocation of functions of social media as tools before, during and after travel.
Findings
Social media users are diverse in terms of their adoption of social media, use behaviour and scope; the levels of trust and influence; and their ultimate travel decisions and actions. Correlations between the level of trust, influence of social media and the intended changes in travel decisions are observed. Destination marketers and tourism industries should observe and adapt to the needs of social media users and potential tourist markets by understanding more about user segmentation between platforms or apps and conducting marketing campaigns on social media platforms to attract a higher number of visitors.
Research limitations/implications
This paper demonstrated the case of social media usage in mainland China, which has been regarded as one of the fastest growing and influential tourist-generating markets and social media expansions in the world. This study further addressed the knowledge gap by correlating social media usage and travel planning process of Chinese tourists. The research findings suggested diversification of the demand-and-supply pattern of social media users in China, as well as the use of social media as tools before, during and after travel. Users were diversified in terms of their adoption of social media, use behaviour, scope, the levels of trust, influence and the ultimate travel decisions.
Practical implications
Destination marketing organizations should note that some overseas social media platforms that are not accessible in China like TripAdvisor, Yelp, Facebook and Instagram are still valued by some Chinese tourists, especially during-trip period in journeys to Western countries. Some tactics for specific user segments should be carefully observed. When promoting specific tourism products to Chinese tourists, it is necessary to understand the user segmentation between platforms or apps.
Originality/value
Social media is a powerful tool for tourism development and sustainability in creating smart tourists and destinations worldwide. In China, the use of social media has stimulated the development of both information and communication technology and tourism.
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Xu Zhang, Mingling Zhai, Yanyan Wang, Yulei Gao, Haoliang Zhao, Xiang Zhou and Jun Gao
In order to verify the feasibility of different techniques, this chapter further studies the adaptability of two massive straw biomass applications in rural areas in China.
Abstract
Purpose
In order to verify the feasibility of different techniques, this chapter further studies the adaptability of two massive straw biomass applications in rural areas in China.
Methodology/approach
The methods of assessing biomass power generation project with Life Cycle Assessment (LCA), survey and field test of one biogas station, and game-theoretic analysis are adopted.
Findings
The following conclusions can be drawn: The air pollution costs account for more than 60% of the total environmental cost, followed by depreciation expense and maintenance fee of 18%, compared to that of biomass power generation at 0.01711 CNY/kWh. The adopted greenhouse sunlight technology of Solar Biogas Plant in Xuzhou, China, raises the inside average temperature by 11.0 °C higher than outside and keeps the pool temperature above 16 °C in winter, ensuring a gas productivity of biogas project in winter up to 0.5–0.7 m3/m3 by volume. This chapter also analyzes the information cost incurred by asymmetric information in biomass power generation via game theory method and illustrates the information structure with game results. It provides not only a foundation for the policy research in promoting straw power generation but also theoretical framework to solve the problem of straw collection.
Social implications
These studies will propose solutions to relevant problems arisen in the running process.
Originality/value
These studies are all based on real cases, field research, and appropriate theoretical analyses, so, they can reduce the relevant costs and promote the application of relevant technologies.
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Dan Liu, Tiange Liu and Yuting Zheng
By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the…
Abstract
Purpose
By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.
Design/methodology/approach
First, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.
Findings
Subsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.
Originality/value
This study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.
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Pingping Xiong, Yue Zhang, Bo Zeng and Tian-Xiang Yao
Aiming at the traditional multivariate grey forecasting model only considers the modelling of real numbers; therefore, the purpose of this paper is to construct an MGM(1, m) model…
Abstract
Purpose
Aiming at the traditional multivariate grey forecasting model only considers the modelling of real numbers; therefore, the purpose of this paper is to construct an MGM(1, m) model based on the interval grey number sequences according to the grey modelling theory.
Design/methodology/approach
First, the multivariable grey number sequences are transformed into the kernel and grey radius sequences which are two feature sequences of interval grey number sequences. Then the MGM(1, m) model for kernel sequences and grey radius sequences are established, respectively. Finally, the simulation and prediction of the upper and lower bounds of the interval grey number sequences are realized by the reductive calculation of the predicted values of the kernel and grey radius.
Findings
The model is applied to the prediction of visibility and relative humidity, the identification factors of the haze. The results show that the model has high accuracy on the simulation and prediction of multivariable grey number sequences, which is reasonable and practical.
Originality/value
The main contribution of this paper is to propose a method to simulate and forecast the multivariable grey number sequence that is to establish the prediction models for the whitening sequences of multivariable grey number sequences which are kernel and grey radius sequences and extend the possibility boundary of kernel by grey radius. The model can reflect the development trend of multivariable grey number sequence accurately. When the grey information is continuously complemented, the multivariable grey number prediction model is transformed into the traditional MGM(1, m) model. Therefore, the MGM(1, m) model based on interval grey number sequence is the generalisation and expansion of the traditional MGM(1, m) model.
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Minwoo Lee, Yanjun (Maggie) Cai, Agnes DeFranco and Jongseo Lee
Electronic word of mouth in the form of user-generated content (UGC) in social media plays an important role in influencing customer decision-making and enhancing service…
Abstract
Purpose
Electronic word of mouth in the form of user-generated content (UGC) in social media plays an important role in influencing customer decision-making and enhancing service providers’ brand images, sales and service innovations. While few research studies have explored real content generated by hotel guests in social media, business analytics techniques are still not widely seen in the literature and how such techniques can be deployed to benefit hoteliers has not been fully explored. Thus, this study aims to explore the significant factors that affect hotel guest satisfaction via UGC and business analytics and also to showcase the use of business analytics tools for both the hospitality industry and the academic world.
Design/methodology/approach
This study uses big data and business analytics techniques. Big data and business analytics enable hoteliers to develop effective and efficient strategies improving products and services for guest satisfaction. Therefore, this study analyzes 200,431 hotel reviews on Tripadvisor.com through business analytics to explore and assess the significant factors affecting guest satisfaction.
Findings
The findings show that service, room and value evaluations are the top-three factors affecting overall guests’ satisfaction. While brand type and negative emotions are negatively associated with guests’ satisfaction, all other factors considered were positively associated with guests’ satisfaction.
Originality/value
The current study serves as a great starting point to further explore the relationship between specific evaluation factors and guests’ overall satisfaction by analyzing user-generated online reviews through business analytics so as to assist hoteliers to resolve performance-related problems by analyzing service gaps that exist in these influential factors.
研究目的
以消费者评论为主体的社交网络口碑营销对于影响消费者决策和提高服务提供商的品牌形象、销量、和服务创新起到重要作用。然而, 很少研究探索社交媒体上的真正酒店客人评论。因此, 商务分析技术在文献中还是很少使用的, 这种技术应该更多得到科研上的应用以给酒店从业人员给与启示。因此, 本论文旨在探究影响酒店顾客满意度的因素, 通过消费者评论和商务分析, 以展示商务分析技术是如何为酒店业和科研界来使用的。
研究设计/方法/途径
本论文使用大数据和商务分析技术来进行数据分析。大数据和商务分析能够为酒店从业人员开发有效战略以提高产品和服务质量, 最后达到顾客满意。因此, 本论文分析了Tripadvisor.com的200, 431酒店评论数, 通过商务分析技术, 以探索和审视影响顾客满意度的重要因素。
研究结果
研究结果显示服务、客房、和价值比成为影响顾客满意度的前三项因素。品牌类型和负面情绪是影响顾客满意度的负面因素。其他因素成为影响顾客满意度的正面因素。
研究原创性/价值
本论文是利用消费者评论的商务分析来探究影响顾客满意度与具体衡量因素之间关系的起点范例, 以此, 帮助酒店从业商来解决服务中的欠缺因素, 提高绩效。
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Zongshui Wang, Wei Liu, Zhuo Sun and Hong Zhao
Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and…
Abstract
Purpose
Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and short-term perspectives, which includes brand diffusion, user-generated content (UGC), opinion leaders and brand events’ impact.
Design/methodology/approach
This study uses a mixed-method including text mining, keyword analysis and social network analysis to explore the brand formation process of four popular WHSs in Beijing, namely, the Palace Museum, Great Wall, Summer Palace and Temple of Heaven and more than 10,000,000 users’ data on Sina Weibo has been implemented to uncover the underlying social media branding mechanism.
Findings
The results show that the number of postings keeps in a stable range in most months, but, in general, there are no common rules for changing trends among the four WHSs; long-term high-frequency keywords related to history and culture account for a higher percentage; different kinds of accounts have varying impacts on information diffusion, in which media accounts lead to a bigger influence. However, more followers do not necessarily mean more interactions and most of the interaction ratio is much lower than 0.01000; brand events facilitate brand dissemination and have an impact on the creation of UGC.
Practical implications
This study is valuable for destination marketers to deeper understand brand diffusion and formation and provides valuable insights for developing effective destination marketing strategies.
Originality/value
Unlike previous studies that only concern a few parts of destination brand formation via social media (e.g. brand diffusion, brand events or opinion leaders’ impact), this study takes a more comprehensive perspective by systematically analyzing the brand formation process of WHSs on social media. By considering both long-term diffusion and short-term representative events, this study provides a more holistic understanding of the branding mechanism.
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Di Kang, Steven W. Kirkpatrick, Zhipeng Zhang, Xiang Liu and Zheyong Bian
Accurately estimating the severity of derailment is a crucial step in quantifying train derailment consequences and, thereby, mitigating its impacts. The purpose of this paper is…
Abstract
Purpose
Accurately estimating the severity of derailment is a crucial step in quantifying train derailment consequences and, thereby, mitigating its impacts. The purpose of this paper is to propose a simplified approach aimed at addressing this research gap by developing a physics-informed 1-D model. The model is used to simulate train dynamics through a time-stepping algorithm, incorporating derailment data after the point of derailment.
Design/methodology/approach
In this study, a simplified approach is adopted that applies a 1-D kinematic analysis with data obtained from various derailments. These include the length and weight of the rail cars behind the point of derailment, the train braking effects, derailment blockage forces, the grade of the track and the train rolling and aerodynamic resistance. Since train braking/blockage effects and derailment blockage forces are not always available for historical or potential train derailment, it is also necessary to fit the historical data and find optimal parameters to estimate these two variables. Using these fitted parameters, a detailed comparison can be performed between the physics-informed 1-D model and previous statistical models to predict the derailment severity.
Findings
The results show that the proposed model outperforms the Truncated Geometric model (the latest statistical model used in prior research) in estimating derailment severity. The proposed model contributes to the understanding and prevention of train derailments and hazmat release consequences, offering improved accuracy for certain scenarios and train types
Originality/value
This paper presents a simplified physics-informed 1-D model, which could help understand the derailment mechanism and, thus, is expected to estimate train derailment severity more accurately for certain scenarios and train types compared with the latest statistical model. The performance of the braking response and the 1-D model is verified by comparing known ride-down profiles with estimated ones. This validation process ensures that both the braking response and the 1-D model accurately represent the expected behavior.
Details
Keywords
Zhisheng Wang, Xiang Lin and Huiying Li
Using a video revealing unhygienic practices in Chinese five-star hotels as the case study, this study aims to understand the impact of service failure online exposure on hotel…
Abstract
Purpose
Using a video revealing unhygienic practices in Chinese five-star hotels as the case study, this study aims to understand the impact of service failure online exposure on hotel revenue performance in terms of seriousness, magnitude and duration, as well as to identify the hotel-characteristics and hotel-responsiveness factors that influence revenue recovery.
Design/methodology/approach
This study uses the actual Revenue per Available Room data of ten hotels involved in the incident and five different market segments during 2016–2019. Event study method is used to investigate the effect of online exposure on hotel revenue performance.
Findings
This study confirms the significant negative effect of online exposure and that hotels take nearly nine months to fully recover. The results indicate that hotel size, hotel age and response strategy play an important role in reducing negative impacts. Moreover, this study reveals the dynamic spillover effects of online exposure on different hotel market segments. These effects change from a competitive to a contagious effect with a decrease in class ratings.
Practical implications
Low-class hotel managers should take effective actions to avoid possible negative spillovers from others’ service failure incidents. Hotel managers could consider the synergy of different strategies rather than a single response strategy to minimize losses.
Originality/value
This study theoretically broadens knowledge about the negative impact of online exposure on Chinese hotel revenue. Additionally, the findings examine the dynamic spillover effects on hotels in different segments. Furthermore, they extend the existing findings on the negative impact of online public opinion crises.
目的
本研究以一段揭示中国五星级酒店不卫生行为的视频为案例, 旨在了解网上曝光的服务失败事件在严重程度、规模和持续时间方面对酒店收入绩效的影响, 并确定影响收入恢复的酒店特征和酒店回应因素。
设计/方法/途径
本研究使用了2016–2019年期间10家涉及酒店和5个不同的细分市场的实际每间可用房收入(RevPARs)数据。采用事件研究法(ESM)来研究网上曝光对酒店收入绩效的影响。
研究结果
本研究证实了网上曝光的显著负面效应, 酒店需要近9个月的时间才能完全恢复。结果表明, 酒店规模、酒店年龄和回应策略在减少负面影响方面发挥了重要作用。此外, 本研究还揭示了在线曝光对不同酒店细分市场的动态溢出效应。这些效应随着酒店星级的下降而从竞争效应变为传染效应。
实践意义
低星级酒店管理者应采取有效行动, 避免其他酒店的服务失败事件可能带来的负面溢出效应。酒店管理者可以考虑不同策略的协同作用, 而不是单一的回应策略来减少损失。
原创性/价值
本研究从理论上拓宽了关于网上曝光对中国酒店收入绩效的负面影响的知识。与此同时, 本研究的结果考察了不同细分市场的酒店的动态溢出效应。此外, 还扩展了现有的关于网络舆情危机的负面影响的研究结果。
Diseño/metodología/enfoque
Este estudio utiliza los datos reales de ingresos por habitación disponible (RevPAR) de 10 hoteles implicados en el incidente y cinco segmentos de mercado diferentes durante 2016-2019. Se utiliza el método de estudio de sucesos (ESM) para investigar el efecto de la exposición en línea en el rendimiento de los ingresos de los hoteles.
Objetivo
Utilizando como caso de estudio un vídeo que revela prácticas antihigiénicas en hoteles chinos de cinco estrellas, este estudio pretende comprender el impacto de la exposición online de fallos en el servicio sobre el rendimiento de los ingresos hoteleros en términos de gravedad, magnitud y duración, así como identificar las características y los factores de respuesta del hotel que influyen en la recuperación de los ingresos.
Resultados
Este estudio confirma el importante efecto negativo de la exposición online, tardando los hoteles casi nueve meses en recuperarse totalmente. Los resultados indican que el tamaño del hotel, su antigüedad y la estrategia de respuesta desempeñan un papel importante en la reducción del impacto negativo. Además, este estudio revela los efectos indirectos dinámicos de la exposición online en diferentes segmentos del mercado hotelero. Estos efectos cambian de un efecto competitivo a un efecto contagioso con una disminución de las calificaciones de la categoría o clase hotelera.
Implicaciones prácticas
Los revenue managers de los hoteles de categoría baja deberían tomar medidas eficaces para evitar posibles repercusiones negativas de los fallos en el servicio de otros hoteles. Los directores de hotel podrían considerar la sinergia de diferentes estrategias en lugar de una única estrategia de respuesta para minimizar las pérdidas.
Originalidad/valor
Este estudio amplía teóricamente los conocimientos sobre el impacto negativo de la exposición online en los ingresos de los hoteles chinos. Además, los resultados examinan los efectos indirectos dinámicos en hoteles de diferentes segmentos. Además, amplían los resultados existentes sobre el impacto negativo de las crisis de opinión pública online.