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The purpose of this study is to investigate the impact of leaders’ use of motivational language on psychological relatedness and its effect on employee well-being in flexible and remote working conditions.

A survey among 375 full-time working professionals in the US was conducted with varying frequencies of remote work arrangements. For the analysis, we used a series of PROCESS analyses to examine the moderating effect of leaders’ motivational language use on the relationship between participants’ remote work status and relatedness, with employee well-being as the dependent variable.

The findings revealed a significant moderating effect of leaders’ perlocutionary (direction-giving) language use on the relationship between employees’ remote work status and relatedness. Specifically, the relationship between remote work status and relatedness was stronger when the use of perlocutionary (direction-giving) language gradually increased. Such enhanced relatedness, in turn, generated higher satisfaction and psychological well-being. The study shows the strategic advantage of direction-giving language in enhancing relatedness, thereby contributing to higher levels of employee satisfaction and psychological well-being in remote work environments.

The originality of this article lies in its integration of motivational language theory and self-determination theory to explore the well-being of employees within flexible and remote work status. Furthermore, we conceptualize remote work as a continuous variable with different degrees of flexibility, ranging from occasional telecommuting to fully remote work, allowing for a nuanced understanding of how leaders’ use of motivational language interacts with varying levels of remote work arrangements to influence employee well-being.

The study aims to investigate how artificial intelligence (AI)-powered virtual streamers can supercharge brands in live-streaming virtual commerce (v-commerce). Built upon social identity theory (SIT) and experiential value theory, we developed a framework to investigate the impact of AI-powered virtual streamers’ personalization and human-like personalities and live-streaming v-commerce’s system quality and content quality on brand image, mediated by parasocial interaction and experiential value.

A survey was designed and distributed to the target respondents via social media channels. SmartPLS version 4.0.9.4 was used to analyze a total of 354 responses after the data were obtained via purposive sampling.

The results show that personalization, human-like personality, system quality and content quality are positively associated with parasocial interaction and experiential value, which subsequently impact brand image.

This study addresses the gap of relatively sparse academic literature on the implications of AI-powered virtual streamers in live-streaming v-commerce on brand image.

The overarching goal of the study was to formulate an integrated research model to empirically demonstrate the complex interplay between heuristics, project characteristics, information system usage quality, empathy, and mindfulness in predicting users'/donors' donation behaviour and well-being in the context of donation-based crowdfunding (DBC) mobile apps.

The data were collected from 786 respondents and analysed using the multi-stage SEM-ANN-NCA (Structural equation modelling-artificial neural network-necessary condition analysis) method.

Increased perceived aesthetics, narrative structure, self-referencing, project popularity, project content quality, and initiator reputation would foster empathy. Empathy and mindfulness lead to donation behaviour, and, ultimately emotional well-being.

This study offers a clear framework by ranking the key contextual predictors and assessing the model’s necessity logic to facilitate crowdfunders' donation behaviour and well-being on DBC platforms. This research provides practical insights for bank marketers and further aids financial service providers in formulating an optimal DBC mobile app strategy.

The paper aims at analyzing the co-movements between stock returns and oil prices (West Texas Intermediate, Brent) controlling or not for COVID-19.

It uses continuous wavelet transforms and wavelet coherence over the period July 19, 2019 to August 16, 2021 based on daily data. Continuous wavelet transforms provide an over complete representation of stock returns signals by letting the translation and scale parameters of the wavelets vary continuously.

There are not significant evidence supporting the fact that the COVID-19 has altered the relationship between stock returns and oil prices except perhaps in the case of South Africa. In fact, Southern African Development Community stock markets react more to oil prices than to health shock such as the COVID-19.

The findings of the study are original and have not been published anywhere prior.

The present study investigates information-sharing behaviour and awareness of students towards the infringement of copyright and associated rights while information sharing. The purpose of this study is to seek answers to the issue of whether or not students infringe on the rights of others and, if they do, whether they do so deliberately or unwittingly. Even though the Copyright Act and copyrighted works are often disregarded, students, teachers and peers are long-term trading and adapting new e-resources for their use.

The study collected data from students in India through a survey using Google Forms from January 2022 to May 2022. It analysed it using SPSS software to identify behaviour patterns, trends and factors influencing actions and awareness regarding potential copyright issues during data sharing.

The study finds that many students in India engage in copyright infringement, either deliberately or unwittingly. Many students are unaware of copyright laws and regulations and do not understand the consequences of their actions.

The study’s findings are limited to students in Tamil Nadu, India, and may not represent students in other countries or regions. The findings can inform policies and educational programmes that promote ethical and legal behaviour among students and help reduce the incidence of copyright infringement.

This study’s originality and value stem from its unique approach of merging information sharing, seeking and copyright concepts.

This study examines the effects and driving mechanisms of relational bonds (i.e. financial, social, and structural bonds), live-streaming shopping atmosphere factors (i.e. suspense, entertainment, perceived crowdedness, and vicarious experience), consumer empowerment and customer commitment on consumers’ impulse consumption behavior. Additionally, the study examines the moderating influence of product involvement and collectivism.

An online survey was conducted with 665 valid respondents. The authors empirically validated the collected data through the partial least squares structural equation modeling (PLS-SEM) technique, complemented by the artificial neural network (ANN) analysis.

The results suggest that financial bonds, structural bonds, suspense, entertainment, and vicarious experience promote consumer empowerment, which in turn leads to customer commitment and impulse consumption behavior. Second, collectivism moderates the relationship between customer commitment and impulse consumption behavior.

This study provides empirical evidence that relational bonds and live-streaming shopping atmosphere factors play predictive roles in enhancing consumer empowerment, which further promotes impulse consumption behavior through customer commitment. Also, collectivism is found as a moderator.

This study aims to better understand the morphological characteristics of single particle and the health risk characteristics of heavy metals in PM_2.5 in different functional areas of Handan City.

High resolution transmission electron microscopy was used to observe the aerosol samples collected from different functional areas of Handan City. The morphology and size distribution of the particles collected on hazy and clear days were compared. The health risk evaluation model was applied to evaluate the hazardous effects of particles on human health in different functional areas on hazy days.

The results show that the particulate matter in different functional areas is dominated by spherical particles in different weather conditions. In particular, the proportion of spherical particles exceeds 70% on the haze day, and the percentage of soot aggregates increases significantly on the clear day. The percentage of each type of particle in the teaching and living areas varied less under different weather conditions. Except for the industrial area, the size distribution of each type of particle in haze samples is larger than that on the clear day. Spherical particles contribute more to the small particle size segment. Soot aggregate and other shaped particles contribute more to the large size segment. The mass concentrations of hazardous elements (HEs) in PM_2.5 in different functional areas on consecutive haze pollution days were illustrated as industrial area > traffic area > living area > teaching area. Compared with the other functional areas, the teaching area had the lowest noncarcinogenic risk of HEs. The lifetime carcinogenic risk values of Cr and As elements in each functional area have exceeded residents’ threshold levels and are at high risk of carcinogenicity. Among the four functional areas, the industrial area has the highest carcinogenic and noncarcinogenic risks. But the effects of HEs on human health in the other functional areas should also be taken seriously and continuously controlled.

The significance of the study is to further understand the morphological characteristics of single particles and the health risks of heavy metals in different functional areas of Handan City. the authors hope to provide a reference for other coal-burning industrial cities to develop plans to improve air quality and human respiratory health.

A tangible representation of the housing market hotness, namely, the index derived via Carrilo 2013’s concept, is widely used but difficult to construct, as it requires listing data of a geography which is not only inaccessible but also cumbersome to summarize. The purpose of this paper is to serve as a methodological extension of Carrilo 2013, presenting a process by which the seller’s bargaining power index can be easily constructed using open-source data.

The seller’s bargaining power index was first constructed using the open-source data by Zillow Research. Then, results verification approach including visualization, Pearson correlation test, Granger causality test and linear regression were used with the goal to generate empirical evidence and verify if the constructed index conforms with established relationships derived in past work, thereby substantiate accuracy of the constructed index.

Monthly seller’s bargaining power index was constructed for US as a whole and 250 metropolitan statistical areas through an automated process. The constructed index conforms with established evidence in terms of seasonality, trend and magnitude. The index also forms positive correlation with building permit/housing value/housing value increase rate, and negative correlation with inventory. It requires the explanatory power of multiple linear features to simulate the parameter. Seller’s bargaining power index at a national level can serve as a general indicator of economic strength, in parallel to number of building permit, housing starts and real gross domestic product. Quantitatively, the housing market of the USA is as “hot” during the COVID-19 pandemic as it was in the years before 2008. A healthy housing market appears to be one in which 75%−80% of the deals are in favor of the seller (take-it-or-leave-it). When said percentage reaches 90%, the market should be considered to be in a “bubble.”

This paper provides an easy pathway for future studies to simulate housing market hotness, and bring upon the benefit of convenience at low cost and in monthly frequency rather than quarterly or annually.

This study aims to present scientometric mapping and altmetric analysis of publications related to “Hockey” in the past three decades. By using the advanced analytical techniques of mapping coupled with altmetric analysis, this paper aims to reveal the complex network of collaborations, the dispersion of expertise worldwide and prevailing thematic trends in the field of hockey.

The data was extracted from the Web of Science (WoS) database and Altmetric Explorer for articles related to hockey over the past three decades. VOSviewer was used to conduct network analysis whereas MS-Excel was used for altmetric data analysis. The study focused on the articles retrieved using the key term “Hockey” in English language publications. The altmetric attention scores (AAS) were used to measure the level of online attention on different platforms, complementing traditional bibliometric analysis.

The study reveals a notable increase in the productivity of hockey research over the past 30 years, with a specific focus on major surges in publication output and altmetric attention in recent times. Coauthorship and country-wise mapping analysis highlight global research collaboration trends, while keyword analysis underscores thematic concentrations. Key journals such as British Journal of Sports Medicine and American Journal of Sports Medicine emerge as crucial dissemination platforms. The importance of X posts (Formerly Twitter) and Mendeley in the diffusion of hockey literature is highlighted by altmetric research.

The study provides a concise overview of research conducted on the game of hockey. This research will be advantageous for researchers and individuals involved in the hockey community, as it offers bibliographic insights and aids in identifying suitable media for disseminating their findings.

The purpose of this study is to identify sustainability assessment indicators of road infrastructure projects by analyzing and synthesizing existing literature, considering that, despite being essential to achieving the sustainable development goals, sustainability performance in road infrastructure projects is a persistent challenge. Therefore, determining how sustainability can be assessed in these projects is crucial, necessitating a systematic review of the sustainability assessment indicators of road infrastructure projects.

Using PRISMA principles, 54 peer-reviewed papers from 2010 to 2022 were retrieved from three search databases (Scopus, Research for Life and Google Scholar) as part of a systematic literature review. Data analysis techniques included both descriptive and content analysis.

The study identified 22 indicators. The results emphasized that the sustainability of road infrastructure projects should consider all three sustainability dimensions to provide development while meeting human needs, preserving the planet Earth and enhancing economic growth. Similarly, indicators should be incorporated from the design phase to implement and attain sustainability successfully.

The outcome of this study will serve as a guide to road infrastructure stakeholders to understand the relevant sustainability indicators to assess the sustainability performance of their projects.

The study’s findings provide the sustainability assessment indicators for roads, which serve as a foundation for developing a sustainability assessment indicator framework for road infrastructure projects. Future research can look at establishing the indicators for the end-of-life phase of the project lifecycle.