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The environment in high-tech industries is highly dynamic, and after COVID-19, it has become even more unpredictable. Hence, it has become critical for firms to develop strategies to cope with a highly dynamic environment. This paper aims to analyze how the impact of the scientific collaboration networks with URIs (universities and research institutes) on firm innovation performance is contingent on technological and market dynamics.

Using a sample of 174 Chinese firms in the new-energy vehicle industry during 2004–2015, the authors applied a random-effects negative binomial modeling approach to model these relationships.

A broad and strong scientific collaboration network promotes firm innovation network effects are contingent on technological and market dynamics. While technological dynamics strengthen the effect market dynamics weaken it due to the different purposes of collaboration for firms and URIs.

Firms should adjust the structure of scientific collaboration networks with URIs when facing different environments. The government should encourage firms to jointly research with diverse URIs and play an active role in stabilizing market environments.

This study contributes to the academic debate on university-industry scientific collaborations. Applying the temporary competitive advantage (TCA) framework, we provide nuances to the literature that studies the factors that condition the effects of networks. This study also adds to the research on firm scientific collaboration networks by measuring networks based on the coauthorship between firms and URIs.

This paper investigates whether a J-curve can be detected in the time series data on China’s bilateral trade with the G-7 countries. It utilizes cointegration and causality tests to ascertain both the long-run relatedness, and the short-run dynamics, between the real exchange rate, national income, and the trade balance. There is some evidence that a real depreciation eventually improves the trade balance with some countries. But there is no indication of a negative short-run response which characterizes the J-curve.

The purpose of this paper is to examine the harmful effect of abusive supervision on employee creativity through feedback-seeking behavior (FSB) and the moderation of this mediation by proactive personality.

This study conducted hierarchical regression and path analysis to analyze the 341 manager–employee dyads data gathered from 11 companies in China.

The results reveal that abusive supervision had a detrimental effect on employee creativity partially mediated by employee FSB, and employees' proactive personality moderated the mediation.

Although the findings of this research are based on multiple sources data, it is hard to draw causal inferences because the nature of the data is cross-sectional.

Organizations should be aware of the deleterious effect of abusive supervision on employee creativity and should seek to inhibit supervisors' abusive behavior in the workplace.

This study re-examines the relationship between abusive supervision and employee creativity in the Chinese context from the social exchange perspective. The mediating role of FSB and the moderating role of proactive personality offer new insights in-to the mechanisms and boundary conditions associated with the relationship between abusive supervision and employee creativity.

This paper aims to classify the sentiment of online tourism-hospitality reviews at an aspect level. A new aspect-oriented sentiment classification method is proposed based on a neural network model.

This study constructs an aspect-oriented sentiment classification model using an integrated four-layer neural network: the bidirectional encoder representation from transformers (BERT) word vector model, long short-term memory, interactive attention-over-attention (IAOA) mechanism and a linear output layer. The model was trained, tested and validated on an open training data set and 92,905 reviews extrapolated from restaurants in Tokyo.

The model achieves significantly better performance compared with other neural networks. The findings provide empirical evidence to validate the suitability of this new approach in the tourism-hospitality domain.

More sentiments should be identified to measure more fine-grained tourism-hospitality experience, and new aspects are recommended that can be automatically added into the aspect set to provide dynamic support for new dining experiences.

This study provides an update to the literature with respect to how a neural network could improve the performance of aspect-oriented sentiment classification for tourism-hospitality online reviews.

本文旨在从方面级对在线旅游-酒店评论的情感进行分类。提出了一种基于神经网络模型的面向方面的情感分类新方法。

本研究使用集成的四层神经网络构建面向方面的情感分类模型：BERT 词向量模型、LSTM、IAOA 机制和线性输出层。该模型在一个开放的训练数据集和从东京餐厅推断的 92,905 条评论上进行了训练、测试和验证。

与其他神经网络相比, 该模型实现了显着更好的性能。研究结果提供了经验证据, 以验证这种新方法在旅游酒店领域的适用性。

该研究提供了有关神经网络如何提高旅游酒店在线评论的面向方面的情感分类性能的新文献。

应该识别更多的情感从而来更加细化衡量旅游酒店体验, 并推荐新的方面/维度可以被自动添加到方面集中, 为新的用餐体验提供动态支持。

Few studies on hospitality firm survival consider the impact of online media exposure. This paper aims to investigate how the online news coverage of restaurants, characterized in terms of the number of articles, channel (Web page or mobile app), topic (operations or products) and consistency (mix of news tones), influences their survival.

A yearly panel data set covering 682 news-reported restaurants in Shanghai, China, over the period 2011–2019 is analyzed using a Cox model, and an extended cross-sectional data set containing 9,488 restaurants is used for robustness checks.

A larger number of online news articles, regardless of channel or topic, significantly improves restaurants’ chances of survival, and this positive impact of online exposure is greater if that news is published by mobile apps (rather than on Web pages) or reports topics related to operations (rather than products). Although, generally, news inconsistency is not good for restaurant survival, when the number of online news items is eight or more, inconsistency becomes good for survival.

This research guides restaurant operators to use news exposure in an online marketing environment to increase the firm’s chances of long-term survival.

Online media exposure has hitherto been ignored in the literature on the survival of hospitality firms. This paper provides a new perspective on hospitality firm survival and also contributes to the literature on media exposure by conceptualizing a unique factor, namely, the consistent online exposure.

This study explores how perceived interactivity effects in Livecommerce influences consumers' shopping intentions in live stream commerce. The authors specifically examine the mediating roles of immersion and hedonic/utilitarian gratification, as well as the moderating role of product involvement in identifying the boundary conditions.

A scenario-based online survey was conducted among American consumers via Prolific.co, an online crowdsourcing platform. The final sample included 187 respondents (male, 63.1 per cent; Caucasian, 61.5 per cent).

The results indicate that perceived interactivity significantly influenced consumers' shopping intentions. Consumers' sense of immersion and hedonic/utilitarian gratification were identified as serial mediators between perceived interactivity and consumers' shopping intentions. It was also found that individuals' product involvement moderated the serial effects of perceived interactivity on consumers' shopping intentions in live stream commerce.

This study provides empirical evidence that perceived interactivity plays an important role in creating an effectively immersive media experience in live stream commerce, which further contributes to higher shopping intentions via perceived utilitarian and hedonic gratifications. It was also found that varying levels of product involvement can have differing effects. Managerial implications are provided.

The purpose of this paper is to explore the restrictive effect of abusive supervision on employees’ feedback-seeking behavior (FSB) through organizational-based self-esteem (OBSE) and the moderation of this mediation by leader-member exchange (LMX).

This study conducted hierarchical regression and path analysis to analyze the 312 manager–employee dyads data gathered from five companies in China.

The authors found that abusive supervision had a detrimental effect on employee FSB, partially through OBSE, and that both the direct and indirect effects were moderated by LMX.

Organizations should seek to inhibit supervisors’ abusive behavior in the workplace. Supervisors should not occasionally mistreat subordinates with whom they have a good relationship.

This study reveals the underlying influence mechanism of abusive supervision on employee FSB using the self-concept theory and suggests that OBSE is critical in determining how abusive supervision influences employee FSB. Furthermore, LMX quality (especially high LMX) moderates the above mediation.

The purpose of this paper is to develop a novel method for analyzing wheel-rail (W-R) contact using thermo-mechanical measurements and study the effects of heating on the characteristics of W-R contact under different creepages.

This study developed an implicit-explicit finite element (FE) model which could solve both partial slip and full sliding problems by setting different angular velocities on the wheels. Based on the model, four material types under six different creepages were simulated.

The results showed that frictional heating significantly affected the residual stress distribution under large creepage conditions. As creepage increased, the temperature of the wheel tread and rail head rose and the peak value was located at the trailing edge of the contact patch.

The proposed FE model could reduce computational time and thus cost to about one-third of the amount commonly found in previous literature. Compared to other studies, these results are in good agreement and offer a reasonable alternative method for analyzing W-R contact under various conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2019-0298

The complicated nature of megaprojects requires appropriate analysis of multiple stakeholders to achieve project objectives and to accommodate stakeholder interests. During the last two decades, many stakeholder theories and empirical studies have sprouted. Although previous studies have contributed to the development of stakeholder theory, it seems that these theoretical advances have not been fully adopted and acknowledged in practices, especially in megaprojects. The purpose of this paper is to explore the evolution of stakeholder analysis and engagement practices adopted in the Australian megaprojects over the last two decades.

Four mega construction projects are described and analysed in this study. Secondary data were first assembled in order to get general knowledge of each case. Interviews were conducted with the project directors. Project documents were collected from the project teams and reviewed. Wherever the project information was unclear, e-mails were sent to the directors and the team members to confirm the details.

Project teams have started to apply snowball rolling and stakeholder attribute assessment methods to analyse stakeholders. However, there is still a way to adopt the “network” analysis perspective because the project teams are reluctant to use complicated tools which need specialists’ assistance. The stakeholder engagement practices have evolved to an extent where the project teams monitor the dynamics of stakeholders’ requirements. Projects teams have identified the importance of continuity to manage stakeholders in these massive projects. However, a structured method selection mechanism for stakeholder engagement has not been developed.

This study will help academics to understand the adoption progress and status of stakeholder management methods.

The purpose of this research is to seek better relational strategies between formal and informal stakeholder relationships to improve megaproject performance.

The conceptual model was developed with twenty hypotheses based on the literature review. Then a questionnaire survey was conducted, and the collected data were analyzed by Partial Least squares Structural Equation Modeling (PLS-SEM) for validating the proposed model. Finally, the findings were discussed by a comparative study to explain the different effects of the formal and informal relationship on megaproject performance, and the managerial implications are presented for the stakeholders to implement the relationship management in the megaprojects.

The research finding reveals that formal relationship plays a dominating role in cost, quality, and labor protection; meanwhile, it is still more reliable in improving coordination, safety and environmental protection. Both formal and informal relationship is equally important towards collaboration and scheduling while the informal relationship is more effective in communication and project transparency.

The study extends the knowledge of relationship management in the domain of the megaproject performance. It provides a comprehensive and systematic understanding of the impact of formal and informal stakeholder relationships on ten aspects of the megaproject performance by the proposed conceptual model and PLS-SEM results. The research findings contribute to the theory of relationship management on how the different influences between formal and informal stakeholder relationships lead to better megaproject performance from inter-organizational level to project and societal level.