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This study aims to explore the underlying mechanism of human–pet interaction in pet tourism affecting tourism experiences and daily lives of tourists. The research investigates the moderating role of pet attachment in this mechanism as well.

Based on the social exchange theory and value co-creation theory, this research develops and empirically tests a theoretical framework of human–pet interaction. Data were collected through an online survey of US tourists who have pet travel experiences. The data were analyzed by partial least squares structural equation modeling.

The results show that emotional value partially mediated the relationship between human–pet interaction and travel intention/quality of life, while social value partially mediated the relationship between human–pet interaction and quality of life. The findings of multi-group analysis suggest that the travel experience of tourists with low (vs high) levels of pet attachment is strengthened by human–pet interaction, leading to favorable outcomes.

This study enriches the empirical evidence on pet tourism experience. This study extends the existing literature by demonstrating the heterogeneity of the relationship between human–pet interaction, co-creation value, quality of life and travel intention of tourists with different pet attachment levels.

本研究旨在探索宠物旅游中人与宠物互动影响游客旅游体验和日常生活的潜在机制。本研究还考察了宠物依恋在这一机制中的调节作用。

基于社会交换理论和价值共创理论, 本研究开发并实证检验了人-宠物互动的理论框架。通过对有宠物旅游经历的美国游客进行在线调查收集数据。采用偏最小二乘法-结构方程模型(PLS-SEM)对数据进行分析。

情感价值部分中介了人宠互动与旅游意向/生活质量的关系, 社交价值部分中介了人宠互动与生活质量的关系。多群组分析的结果表明, 低(vs .高)宠物依恋水平的游客的旅游体验因人-宠物互动而得到加强, 从而导致良好的结果。

本研究丰富了宠物旅游体验的实证证据。本研究通过论证具有不同宠物依恋水平游客的人-宠互动、共创价值、生活质量和旅游意向之间关系的异质性, 拓展了现有文献。

El objetivo de este estudio es explorar el mecanismo subyacente de la interacción humano-mascota en el turismo con mascotas que afecta a las experiencias turísticas y a la vida cotidiana de los turistas. El estudio también examina el papel moderador del apego a las mascotas en este mecanismo.

Basada en la teoría del intercambio social y la teoría de la cocreación de valor, esta Investigación desarrolla y prueba empíricamente un marco teórico de la interacción entre humanos y mascotas. Los datos se recopilaron a través de una encuesta en línea a turistas estadounidenses que han tenido experiencias de viaje con mascotas. Los datos fueron analizados mediante un modelo de ecuaciones estructurales basado en mínimos cuadrados parciales (PLS-SEM).

Los resultados muestran que el valor emocional medió parcialmente la relación entre la interacción humano-mascota y la intención de viajar/calidad de vida, mientras que el valor social medió parcialmente la relación entre la interacción humano-mascota y la calidad de vida. Los resultados del análisis multigrupo sugieren que la experiencia de viaje de los turistas con niveles bajos (vs altos) de apego a las mascotas se ve reforzada por la interacción humano-mascota, lo que conduce a resultados favorables.

Este estudio enriquece la evidencia empírica sobre la experiencia del turismo con mascotas. Este estudio amplía la literatura existente al demostrar la heterogeneidad de la relación entre la interacción humano-mascota, el valor de cocreación, la calidad de vida y la intención de viaje de turistas con diferentes niveles de apego a las mascotas.

We investigate the joint impacts of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of reviews and attitude toward the product/service reviewed.

We performed three studies to test our research model, presenting participants with scenarios involving product reviews and prior users' helpful and unhelpful votes across experimental settings.

A high helpfulness ratio boosts users’ trust and influences behaviors in both positive and negative reviews. This effect is more pronounced in attribute-based reviews than emotion-based ones. Unlike the ratio effect, helpfulness magnitude significantly impacts only negative attribute-based reviews.

Future research should investigate voting systems in various online contexts, such as Facebook post likes, Twitter microblog thumb-ups and up-votes for article comments on platforms like The New York Times.

Our findings have significant implications for voting system-providers implementing information techniques on third-party review platforms, participatory sites emphasizing user-generated content and online retailers prioritizing product awareness and reputation.

This study addresses an identified need; that is, the helpfulness votes as an additional trust cue and the joint effects of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of customers in reviews and their consequential attitude toward the product/service reviewed.

This study aims to evaluate the key factors affecting the behavioural intention of urban tourists towards visiting national parks by integrating the theory of planned behaviour (TPB) and expectancy theory (ET).

Data were collected from urban tourists using an online questionnaire developed through Google forms. A total of 489 valid online questionnaires were considered for this study. The proposed research model was empirically evaluated using the structural equation modelling method.

According to the results of this research, TPB constructs are significantly and positively associated with the behavioural intention of urban tourists towards visiting national parks in India and out of ET constructs, only expectancy and valence are significantly and positively associated with behavioural intention while instrumentality does not.

This study manifests the behaviour of urban tourists towards national parks and contributes to academics by incorporating existing literature. The findings of this study also help policymakers in formulating innovative strategies for national parks. It presents an integrated framework that lays the platform for a new study domain on urban tourists' intentions to visit national parks, which will be useful to urban managers, officials and the tourism sector. Furthermore, as the scope of this study is confined to assessing the intentions of urban tourists toward visiting national parks, it is difficult to generalize the findings.

To the best of the authors' knowledge, this is the first research of its kind to provide an understanding of the behavioural intention of urban tourists towards visiting the national parks in India by optimizing the TPB and ET.

Prefabricated construction is an innovative technique for decreasing carbon emissions in the construction industry. However, as the investors of housing projects, a majority of developers are unwilling to adopt prefabricated housing in practice. To promote prefabricated housing, this study aims to develop an integrated framework of fuzzy-decision making trial and evaluation laboratory (fuzzy-DEMATEL) and system dynamics (SD) to understand the underlying influencing mechanism of developers' willingness.

Through literature review, a total of 17 influencing factors were identified. Then, the interrelationships among the factors were evaluated by 10 experienced professionals, and the impacts given and received by each factor were further analyzed through fuzzy-DEMATEL. Based on the technology acceptance model (TAM), a SD model was developed to explore the influencing mechanism.

The major cause factors were identified, including mandatory implementation policies, economic incentive policies, environmental protection policies, component standardization and developers' economic strength. This group of factors was expected to be given priority attention in the case of limited resources. On the other hand, the results indicated that economic incentive policies and mandatory implementation policies could affect the developers' willingness via perceived usefulness, while the others mainly influenced perceived ease of use.

Little research has focused on the interrelationships among the influencing factors of developers' willingness to adopt prefabricated housing. This study contributed to understanding the mechanism of developers' willingness from a systematic view and providing the priority of influencing factors. Several strategies were proposed to improve the practical implementation of prefabricated housing development.

Retail investors are prone to be affected by information dissemination in social media with the rapid development of Web 2.0. The purpose of this study is to recognize the factors that may impact users' retweet behavior, namely information dissemination in the online financial community, through machine learning techniques.

This paper crawled data from the Chinese online financial community (Xueqiu.com) and extracted author-related, content-related, situation-related, stock-related and stock market-related features from the dataset. The best information dissemination prediction model based on these features was determined by evaluating five classifiers with various performance metrics, and the predictability of different feature groups was tested.

Five prevalent classifiers were evaluated with various performance metrics and the random forest classifier was proven to be the best retweet prediction model in the authors’ experiments. Moreover, the predictability of author-related, content-related and market-related features was illustrated to be relatively better than that of the other two feature groups. Several particularly important features, such as the author's followers and the rise and fall of the stock index, were recognized in this paper at last.

This study contributes to in-depth research on information dissemination in the financial domain. The findings of this study have important practical implications for government regulators to supervise public opinion in the financial market.

The inherent risks and their interactive impacts in megaproject development have been found in numerous cases worldwide. Although risk management standards have been recommended for the best practice in engineering construction projects, there is still a lack of systematic approaches to describing the interactions. Interactions such as social, technical, economic, ecological and political (STEEP) risks have complex and dynamic implications for megaproject construction. For a better understanding and effective management of megaprojects such as the Edinburgh Tram project, the dynamic interaction of concomitant risks must be studied.

A systems dynamic methodology was adopted following the comprehensive literature review. Documentary data were gathered from the case study on Tram Network Project in Edinburgh.

A casual loop of typical evolution of key indicators of risks was then developed. A hypothesised model of social and ecological (SE) risks was derived using the system dynamics (SD) modelling technique. The model was set up following British Standards on risk management to provide a generic tool for risk management in megaproject development. The study reveals that cost and time overruns at the developmental stage of the case project are caused mainly by the effects of interactions of risk factors from the external macro project environment on a timely basis.

This article presented a model for simulating the socio-ecological risk confronting the management and construction of megaprojects. The use of SD provided the opportunity to explain the nature of all risks, particularly the SE risks in the past stages of project development.

Propagation characteristics of millimeter wave (mmW) frequencies that are being explored for implementing 5G network are quite different from sub 3GHz frequencies in which 4G network is operating, and hence antenna design for mmW 5G network is going to be significantly different. The purpose of this paper is to bring forth the unique challenges and opportunities of planar antenna design for mmW 5G network.

A lot of notable contemporary work has been investigated for this study and reported in this paper. A comparison of 4G and 5G technologies has been carried out to understand the difference between the air interface of two technologies that governs the antenna design. Important research gaps found after collating the work already done in the field have been bullet pointed for the use by many researchers working in this direction.

Several antenna design considerations have been laid out by the authors of this work, and it has been claimed that mmW 5G antenna design must satisfy these design considerations. In addition, prominent research gaps have been identified and thoroughly discussed.

As research in the field of mmW antenna design for 5G applications is still evolving, a lot of work is currently being done in this area. This study can prove to be important in understanding different challenges, opportunities and current state-of-art in the field of mmW planar antenna design for 5G cellular communication.

The need for infrastructure is growing as urbanization picks up speed, and the infrastructure REITs financing model has been crucial in reviving the vast infrastructure stock, alleviating the pressure on government funds and diversifying investment entities. This study aims to propose a framework to better assess the risks of infrastructure REITs, which can serve for the researchers and the policy makers to propose risk mitigation strategies and policy recommendations more purposively to facilitate successful implementation and long-term development of infrastructure REITs.

The infrastructure REITs risk evaluation index system is established through literature review and factor analysis, and the optimal comprehensive weight of the index is calculated using the combination weight. Then, a risk evaluation cloud model of infrastructure REITs is constructed, and experts quantify the qualitative language of infrastructure REITs risks. This paper verifies the feasibility and effectiveness of the model by taking a basic REITs project in China as an example. This paper takes infrastructure REITs project in China as an example, to verify the feasibility and effectiveness of the cloud evaluation method.

The research outcome shows that infrastructure REITs risks manifest in the risk of policy and legal, underlying asset, market, operational and credit. The main influencing factors in terms of their weights are tax policy risk, operation and management risk, liquidity risk, termination risk and default risk. The financing project is at a higher risk, and the probability of risk is 64.2%.

This research contributes to the existing body of knowledge by supplementing a set of scientific and practical risk evaluation methods to assess the potential risks of infrastructure REITs project, which contributes the infrastructure financing risk management system. Identify key risk factors for infrastructure REITs with underlying assets, which contributes to infrastructure REITs project management. This research can help relevant stakeholders to control risks throughout the infrastructure investment and financing life cycle, provide them with reference for investment and financing decision-making and promote more sustainable and healthy development of infrastructure REITs in developing countries.

Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that incorporating online review data can enhance the performance of tourism demand forecasting models, the reliability of online review data and consumers’ decision-making process have not been given adequate attention. To address the aforementioned problem, the purpose of this study is to forecast tourism demand using online review data derived from the analysis of review helpfulness.

The authors propose a novel “identification-first, forecasting-second” framework. This framework prioritizes the identification of helpful reviews through a comprehensive analysis of review helpfulness, followed by the integration of helpful online review data into the forecasting system. Using the SARIMAX model with helpful online review data sourced from TripAdvisor, this study forecasts tourist arrivals in Hong Kong during the period from August 2012 to June 2019. The SNAÏVE/SARIMA model was used as the benchmark model. Additionally, artificial intelligence models including long short-term memory, back propagation neural network, extreme learning machine and random forest models were used to assess the robustness of the results.

The results demonstrate that online review data are subject to noise and bias, which can adversely affect the accuracy of predictions when used directly. However, by identifying helpful online reviews beforehand and incorporating them into the forecasting process, a notable enhancement in predictive performance can be realized.

First, to the best of the authors’ knowledge, this study is one of the first to focus on the data issue of online reviews on tourism arrivals forecasting. Second, this study pioneers the integration of the consumer decision-making process into the domain of tourism demand forecasting, marking one of the earliest endeavors in this area. Third, this study makes a novel attempt to identify helpful online reviews based on reviews helpfulness analysis.

In public firms, the largest shareholder can make decisions on cash dividends in favor of its own interests at the expense of other investors. While the second largest shareholder can actively participate in corporate governance and protect the interests of investors, its impact has not been fully understood. This research investigates how shareholding ratio and ownership type of the second largest shareholder moderate the relationship between controlling shareholder's shareholding ratio and cash dividends.

The authors conducted econometrics analysis based on a panel data of China's A-share listed companies from 2007 to 2017.

The authors find that the controlling shareholder's shareholding ratio has a significant negative impact on cash dividends. However, this influence is conditional on the shareholding ratio of the second largest shareholder. The negative impact is weakened when the second largest shareholder holds a large proportion of shares or when the shareholding gap between the second largest and the controlling shareholder is small.

This research extends the existing literature by highlighting the nuanced moderating effect of the second largest shareholder on the relationship between the controlling shareholder and cash dividends, thus making a unique contribution to the understanding of corporate governances in the emerging financial market in China.