Mingming Hu, Lijing Lin, Minkun Liu and Shuai Ma
This study aims to explore image-based visual price determinants (image features and visual aesthetic perception) and how image features affect Airbnb listing price on a sharing…
Abstract
Purpose
This study aims to explore image-based visual price determinants (image features and visual aesthetic perception) and how image features affect Airbnb listing price on a sharing accommodation platform.
Design/methodology/approach
The study uses an SOR model and a hedonic price model to examine the connections between the characteristics of image features, visual aesthetic perception and Airbnb listing prices. The model is then examined by an econometric model using data from Insideairbnb.com.
Findings
Empirical results revealed that image features have a significant positive effect on visual aesthetic perception, visual aesthetic perception has a significant positive effect on Airbnb listing price and visual aesthetic perception has a significant mediating effect between image features and Airbnb listing price.
Originality/value
This study contributes to the relationship and effect mechanism among image features, visual aesthetic perception and Airbnb listing price and has some implications for both property operators and the sharing accommodation platform.
目的
本研究探讨了基于图像的视觉价格决定因素(图像特征和视觉美学感知)以及图像特征如何影响共享住宿平台Airbnb价格。
设计/方法/途径
本研究采用SOR模型和hedonic价格模型来检验图像特征特征、视觉美感与Airbnb房源价格之间的关系。然后使用Insideairbnb.com上的数据, 通过计量经济学模型对该模型进行检验。
研究结果
实证结果显示:1)图像特征对视觉美学感知有显著的正向影响; 2)视觉美学感知对Airbnb价格有显著的正向影响; 3)视觉美学感知在图像特征和Airbnb价格之间有显著的中介效应。
独创性/价值
本研究有助于探讨图像特征、视觉美学感知和Airbnb价格之间的关系和影响机制, 对房源经营者和共享住宿平台都有一定的借鉴意义。
Objetivo
Este estudio explora los determinantes visuales del precio basados en las imágenes (características de las imágenes y percepción estética visual) y cómo afectan las características de las imágenes al precio de los anuncios de Airbnb en una plataforma de alojamiento compartido.
Diseño/metodología/enfoque
El estudio emplea un modelo SOR y un modelo de precios hedónicos para examinar las conexiones entre las características de los rasgos de la imagen, la percepción estética visual y los precios de Airbnb. A continuación, se examina el modelo mediante un modelo econométrico utilizando datos de Insideairbnb.com.
Resultados
Los resultados empíricos revelan que 1) las características de la imagen tienen un efecto positivo significativo sobre la percepción estética visual, 2) la percepción estética visual tiene un efecto positivo significativo sobre el precio de los anuncios de Airbnb, y 3) la percepción estética visual tiene un efecto mediador significativo entre las características de la imagen y el precio de los anuncios de Airbnb.
Originalidad/valor
Este estudio contribuye al mecanismo de relación y efecto entre las características de la imagen, la percepción estética visual y el precio del anuncio de Airbnb, y tiene algunas implicaciones tanto para los operadores inmobiliarios como para la plataforma de alojamiento compartido.
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Doris Chenguang Wu, Chenyu Cao, Ji Wu and Mingming Hu
Wine tourism is gaining increasing popularity among Chinese tourists, making it necessary to thoroughly examine tourist behavior. While online reviews posted by wine tourists have…
Abstract
Purpose
Wine tourism is gaining increasing popularity among Chinese tourists, making it necessary to thoroughly examine tourist behavior. While online reviews posted by wine tourists have been extensively studied from the perspectives of destinations and wineries, the perspective of the tourists themselves has been overlooked. To address this gap, this study aims to identify significant attributes intrinsic to the tourism experiences of Chinese wine tourists by adopting a text-mining approach from a tourist-centric perspective.
Design/methodology/approach
The authors use topic modeling to extract these attributes, calculate topic intensity to understand tourists’ attention distribution across these attributes and conduct topical sentiment analysis to evaluate tourists’ satisfaction levels with each attribute. The authors perform importance-performance analyses (IPAs) using topic intensity and sentiment scores. Furthermore, the authors conduct semistructured in-depth interviews with Chinese wine tourists to gain insights into the underlying reasons behind the key findings.
Findings
The study identifies eleven attributes for domestic wine tourists and seven attributes for outbound wine tourists. From the reviews of both domestic and outbound tourists, three common attributes have been identified: “scenic view”, “wine tasting and purchase” and “wine knowledge”.
Practical implications
According to the results of the IPAs, there is a pressing need for enhancements in the wine tasting and purchasing experience at domestic wine attractions. Additionally, managers of domestic wine attractions should continue to prioritize the positive aspects of the family trip experience and scenic views. On the other hand, for outbound wine attractions, it is crucial for managers to maintain their efforts in providing opportunities for wine knowledge acquisition, ensuring scenic views and upholding the reputation of wine regions.
Originality/value
First, this study breaks new ground by adopting a tourist-centric perspective to extract significant attributes from real wine tourism reviews. Second, the authors conduct a comparative analysis between Chinese wine tourists who travel domestically and those who travel abroad. The third novel aspect of this study is the application of IPA based on textual review data in the context of wine tourism. Fourth, by integrating topic modeling with qualitative interviews, the authors use a mixed-method approach to gain deeper insights into the experiences of Chinese wine tourists.
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Jun Liu, Junyuan Dong, Mingming Hu and Xu Lu
Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic…
Abstract
Purpose
Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic points on the dynamic objects in the image in the mapping can have an impact on the observation of the system, and thus there will be biases and errors in the position estimation and the creation of map points. The aim of this paper is to achieve more accurate accuracy in SLAM algorithms compared to traditional methods through semantic approaches.
Design/methodology/approach
In this paper, the semantic segmentation of dynamic objects is realized based on U-Net semantic segmentation network, followed by motion consistency detection through motion detection method to determine whether the segmented objects are moving in the current scene or not, and combined with the motion compensation method to eliminate dynamic points and compensate for the current local image, so as to make the system robust.
Findings
Experiments comparing the effect of detecting dynamic points and removing outliers are conducted on a dynamic data set of Technische Universität München, and the results show that the absolute trajectory accuracy of this paper's method is significantly improved compared with ORB-SLAM3 and DS-SLAM.
Originality/value
In this paper, in the semantic segmentation network part, the segmentation mask is combined with the method of dynamic point detection, elimination and compensation, which reduces the influence of dynamic objects, thus effectively improving the accuracy of localization in dynamic environments.
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Mingming Hu, Mengqing Xiao and Hengyun Li
While relevant research has considered aggregated data from mobile devices and personal computers (PCs), tourists’ search patterns on mobile devices and PCs differ significantly…
Abstract
Purpose
While relevant research has considered aggregated data from mobile devices and personal computers (PCs), tourists’ search patterns on mobile devices and PCs differ significantly. This study aims to explore whether decomposing aggregated search queries based on the terminals from which these queries are generated can enhance tourism demand forecasting.
Design/methodology/approach
Mount Siguniang, a national geopark in China, is taken as a case study in this paper; another case, Kulangsu in China, is used as the robustness check. The authors decomposed the total Baidu search volume into searches from mobile devices and PCs. Weekly rolling forecasts were used to test the roles of decomposed and aggregated search queries in tourism demand forecasting.
Findings
Search queries generated from PCs can greatly improve forecasting performance compared to those from mobile devices and to aggregate search volumes from both terminals. Models incorporating search queries generated via multiple terminals did not necessarily outperform those incorporating search queries generated via a single type of terminal.
Practical implications
Major players in the tourism industry, including hotels, tourist attractions and airlines, can benefit from identifying effective search terminals to forecast tourism demand. Industry managers can also leverage search indices generated through effective terminals for more accurate demand forecasting, which can in turn inform strategic decision-making and operations management.
Originality/value
This study represents one of the earliest attempts to apply decomposed search query data generated via different terminals in tourism demand forecasting. It also enriches the literature on tourism demand forecasting using search engine data.
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Mingming Cheng, Maggie Hu and Adrian Lee
Taking a global perspective, this paper aims to examine the impact of COVID-19 on Airbnb booking activities through three critical perspectives – the initial Wuhan lockdown, local…
Abstract
Purpose
Taking a global perspective, this paper aims to examine the impact of COVID-19 on Airbnb booking activities through three critical perspectives – the initial Wuhan lockdown, local COVID-19 cases and local lockdowns.
Design/methodology/approach
Using Airbnb reviews and cancellations as proxies for Airbnb bookings on a global scale, econometrics was used to examine the impacts of the initial Wuhan lockdown, local COVID-19 cases and local lockdowns on Airbnb bookings.
Findings
The authors find that local lockdowns result in a 57.8% fall in global booking activities. Every doubling of newly infected cases is associated with a 4.16% fall in bookings. The sensitivity of bookings to COVID-19 decreases with geographic distance to Wuhan and increases with government stringency of lockdown policies and human mobility within a market.
Practical implications
The empirical evidence from this research can provide governments with insights into more accurate assessment of the financial loss of Airbnb hosts so that proper support can be offered based on the financial needs because of due to sudden lockdown.
Originality/value
This research contributes to new knowledge on peer-to-peer accommodation during a time of crisis and provides much needed global evidence to understand the impacts of COVID-19 on the accommodation industry.
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Emily Ma, Mingming Cheng and Aaron Hsiao
The study aims to provide a critical review of the origin, development and process of sentiment analysis (SA) and a demonstration for hospitality researchers and students on how…
Abstract
Purpose
The study aims to provide a critical review of the origin, development and process of sentiment analysis (SA) and a demonstration for hospitality researchers and students on how to perform SA using a sample study.
Design/methodology/approach
A critical review and sample case demonstration approach was applied. The sample study used Leximancer to perform SA using TripAdvisor review data.
Findings
A critical evaluation of the most popular SA tools was provided, highlighting their advantages and disadvantages. A step-by-step demonstration with data provided makes it possible for readers to learn this technique at own pace.
Originality/value
By providing a critical review of SA supported with a demonstration case study, this study makes a timely contribution for broader awareness and understanding, as well as the application of SA in hospitality.
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Mingming Zhang, Guanhua Hou and Yeh-Cheng Chen
The purpose of this study is to explore the impact of mobile learning platforms on users' study efficiency and develop cognitive indicators to evaluate users' study efficiency on…
Abstract
Purpose
The purpose of this study is to explore the impact of mobile learning platforms on users' study efficiency and develop cognitive indicators to evaluate users' study efficiency on mobile learning platforms.
Design/methodology/approach
Layout style was the only independent factor that was investigated. A between-group experimental design was employed. Eye movement data were recorded during the experiment, following which participants were asked to complete an after-scenario questionnaire. This study evaluated the usability of the proposed new design using both subjective and objective data. The computer system usability questionnaire V3 (CSUQ) was used to measure subjective data. For the eye-tracking measure, gaze entropy, the proportion of fixation count and duration of each AOI were calculated. Gaze entropy reflects the complexity of information organization. Fixation counts and AOI duration represent the difficulty of information processing and attention distribution, respectively during the task.
Findings
The results indicated that interface layout presents significant effects on user's learning efficiency, usability and cognitive load. Sequential layout improved efficiency and satisfaction among participants and reduced information complexity. The results provided useful insights for designers whose goal is to improve user's learning efficiency under mobile learning scheme.
Originality/value
This study investigated the effects of interface layout on usability, user performance and cognitive load using subjective ratings and eye-tracking technology. Gaze entropy was used to measure the complexity of information organized by the interface design. Fixation count and duration proportion were used to identify the difficulty of information processing and distinguish users' distribution of cognitive resources. The results indicated that a vertical layout panel design was more efficient than a horizontal layout panel design. The design implications of the eye tracking indicators and research results were then summarized. This study is expected to encourage designers to optimize their design proposals using eye tracking testing.
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Xueyan Dong, Yuxin Tian, Mingming He and Tienan Wang
The purpose of this study was to investigate the impact of artificial intelligence (AI) adoption on knowledge workers' innovative work behaviors (IWB), as well as the mediating…
Abstract
Purpose
The purpose of this study was to investigate the impact of artificial intelligence (AI) adoption on knowledge workers' innovative work behaviors (IWB), as well as the mediating role of stress appraisal and the moderating role of individual learning abilities.
Design/methodology/approach
This study analyzed the questionnaire results of 313 knowledge workers, and data analysis was conducted by using SPSS 25.0, SPSS 25.0 macro-PROCESS and AMOS 28.0.
Findings
This study found that AI adoption has a double-edged sword effect on knowledge workers' IWB. Specifically, AI adoption can promote IWB by enhancing knowledge workers' challenging stress appraisal, while inhibiting IWB by fostering their hindering stress appraisal. Moreover, individual learning ability significantly moderated the relationship between AI adoption and stress appraisal, which further influenced IWB.
Originality/value
This study integrates the conflicting findings of previous studies and proposes a comprehensive theoretical model based on the theory of cognitive appraisal of stress. This study enriches the research on AI in the field of knowledge management, especially extending the understanding of the relationship between AI adoption and knowledge workers’ IWB by unraveling the psychological mechanisms and behavior outcomes of users' technology usage. Additionally, we provide new insights and suggestions for organizations to seek the cooperation and support of employees in introducing new technologies or driving intelligent transformation.
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Luying Ju, Zihai Yan, Mingming Wu, Gangping Zhang, Jiajia Yan, Tianci Yu, Pan Ding and Riqing Xu
The purpose of this paper is to suggest an implicit integration method for updating the constitutive relationships in the newly proposed anisotropic egg-shaped elastoplastic…
Abstract
Purpose
The purpose of this paper is to suggest an implicit integration method for updating the constitutive relationships in the newly proposed anisotropic egg-shaped elastoplastic (AESE) model and to apply it in ABAQUS.
Design/methodology/approach
The implicit integration algorithm based on the Newton–Raphson method and the closest point projection scheme containing an elastic predictor and plastic corrector are implemented in the AESE model. Then, the integration code for this model is incorporated into the commercial finite element software ABAQUS through the user material subroutine (UMAT) interface to simulate undrained monotonic triaxial tests for various saturated soft clays under different consolidation conditions.
Findings
The comparison between the simulated results from ABAQUS and the experimental results demonstrates the satisfactory performance of this implicit integration algorithm in terms of effectiveness and robustness and the ability of the proposed model to predict the characteristics of soft clay.
Research limitations/implications
The rotational hardening rule in the AESE model together with the implicit integration algorithm cannot be considered.
Originality/value
The singularity problem existing in most elastoplastic models is eliminated by the closed, smooth and flexible anisotropic egg-shaped yield surface form in the AESE model. In addition, this notion leads to an efficient implicit integration algorithm for updating the highly nonlinear constitutive equations for unsaturated soft clay.
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Dongmei Li, Mingming Liu and Guoyan Deng
This paper aims to investigate farmers' willingness to adopt new rice varieties and the factors influencing their seed‐selection behaviors.
Abstract
Purpose
This paper aims to investigate farmers' willingness to adopt new rice varieties and the factors influencing their seed‐selection behaviors.
Design/methodology/approach
The Logit model was used to analyze farmers' willingness and the determinants of the behaviors in selecting and using new varieties. A total of 402 farming households in the main rice‐producing areas of Sichuan Province were surveyed.
Findings
The results indicate that rice yield and sales, agro‐technicians' popularization, kith and kin's seed purchase behaviors have a positive impact on farmers'choice, while the present production income has a negative effect. But previous seed purchasing behaviors, soil characteristics, media publicity, seed companies' recommendation and age of farmer have either positive or negative impact on farmers' choice.
Research limitations/implications
The paper is however unable to explain the general situation of China so it considers Sichuan province as a case. Increased sample quantities may be necessary in further research.
Originality/value
The paper proposes an hypothesis of farmers' willingness and determinants in choosing new rice varieties and verifies it by Logit model. It first analyzes the farmers'decision‐making behavior in choosing new rice varieties in Sichuan, and investigates the farmers' behavior more scientifically.