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For ranking aggregation in crowdsourcing task, the key issue is how to select the optimal working group with a given number of workers to optimize the performance of their aggregation. Performance prediction for ranking aggregation can solve this issue effectively. However, the performance prediction effect for ranking aggregation varies greatly due to the different influencing factors selected. Although questions on why and how data fusion methods perform well have been thoroughly discussed in the past, there is a lack of insight about how to select influencing factors to predict the performance and how much can be improved of.

In this paper, performance prediction of multivariable linear regression based on the optimal influencing factors for ranking aggregation in crowdsourcing task is studied. An influencing factor optimization selection method based on stepwise regression (IFOS-SR) is proposed to screen the optimal influencing factors. A working group selection model based on the optimal influencing factors is built to select the optimal working group with a given number of workers.

The proposed approach can identify the optimal influencing factors of ranking aggregation, predict the aggregation performance more accurately than the state-of-the-art methods and select the optimal working group with a given number of workers.

To find out under which condition data fusion method may lead to performance improvement for ranking aggregation in crowdsourcing task, the optimal influencing factors are identified by the IFOS-SR method. This paper presents an analysis of the behavior of the linear combination method and the CombSUM method based on the optimal influencing factors, and optimizes the task assignment with a given number of workers by the optimal working group selection method.

The study showcases the social impact (online attention) of funded research compared to nonfunded for the BRICS nations. The key themes achieving online attention across the funded and nonfunded publications have also been identified.

A total of 1,507,931 articles published across the BRICS nations for a period of three (03) years were downloaded from the Clarivate Analytics' InCites database of Web of Science (WoS). “Funding Acknowledgement Analysis (FAA)” was used to identify the funded and nonfunded publications. The altmetric score of the top highly cited (1%) publications was gauged from the largest altmetric data provider, “Altmetric.com”, using the DOI of each publication. One-way ANOVA test was used to know the impact of funding on the mentions (altmetrics) across different data sources covered by Altmetric.com. The highly predominant keywords (hotspots) have been mapped using bibliometric software, “VOSviewer”.

The mentions across all the altmetric sources for funded research are higher compared to nonfunded research for all nations. It indicates the altmetric advantage for funded research, as funded publications are more discussed, tweeted, shared and have more readers and citations; thus, acquiring more social impact/online attention compared to nonfunded publications. The difference in means for funded and nonfunded publications varies across various altmetric sources and nations. Further, the authors’ keyword analysis reveals the prominence of the respective nation names in publications of the BRICS.

The study showcases the utility of indexing the funding information and whether research funding increases social impact return (online attention). It presents altmetrics as an important impact assessment and evaluation framework indicator, adding one more dimension to the research performance. The linking of funding information with the altmetric score can be used to assess the online attention and multi-flavoured impact of a particular funding programme and source/agency of a nation so that necessary strategies would be framed to improve the reach and impact of funded research. It identifies countries that achieve significant online attention for their funded publications compared to nonfunded ones, along with the key themes that can be utilised to frame research and investment plans.

The study represents the social impact of funded research compared to nonfunded across the BRICS nations.

This study aims to explore the perceptions of accountancy students on the use of technology, blended learning and flipped classroom in two emerging UK higher education institutions (HEIs).

The primary data for the study were collected using a questionnaire survey and descriptively analysed.

The findings revealed that there is some use of technology in terms of the Blackboard and PowerPoint presentations but blogs and wikis have very limited use. An aspect that does not seem to be integrated fully yet is the use of blended technology and a flipped classroom.

The study findings offer a picture of how technology, blended learning and the flipped classroom technique were utilised with accountancy students prior to the coronavirus disease 2019 (COVID-19) pandemic. This information is valuable for accounting educators and by extension to other aspects of business studies disciplines in providing a comparison between the pre-COVID-19 scenario and the current one and thus enabling an evaluation of advancement in the application of these teaching strategies as a result of the pressure imposed by social distancing. Such intelligence will facilitate the identification of areas where enhancing learning outcomes has been possible and point to opportunities for improved student experience.

Where COVID-19 brought about significant structural change in teaching and learning in the HE environment, this study represents a pre-COVID-19 consideration of student perceptions on blended learning and flipped classroom. This study thus has the potential to anchor future relevant studies that consider the post-COVID-19 environment.

The article aims to investigate how washing practices focused on appeasing sceptics of diversity work in for-profit organizations play out in corporate online communication of diversity and inclusion efforts, and how these enable communication to a wide audience that includes social equity advocates.

Online corporate communication data of diversity and inclusion themes were compiled from the websites of eight Swedish-based multinational corporations. The data included content from the companies’ official websites and annual reports and sustainability reports as well as diversity and inclusion-themed blog posts. A thematic analysis was conducted on the website content.

The study showcases how tensions between conflicting external demands are navigated by keeping the communication open to several interpretations and thereby achieving multivocality. In the studied corporate texts on diversity and inclusion, this is achieved by alternating between elements catering to a business case audience and those that appeal to a social justice audience, with some procedures managing to appease both audiences at the same time.

The article complements previously described forms of washing by introducing an additional type of washing – business case washing – an articulation of the business case rhetoric that characterizes the diversity management discourse. While much has been written about washing to satisfy advocates of social change and equity, washing to appease shareholders and boardroom members, who are focused on profit and economic growth, has received less attention. The article suggests that online corporate communication on diversity and inclusion, by appeasing diverse audiences, can be seen as aspirational talk.

Alexa’s integration in rural primary schools has improved the pedagogy and has created an engaging and objective learning environment. This study investigates the integration, with a specific focus on exploring its various aspects. The impact of Alexa’s on students' English vocabulary, comprehension and public speaking are examined. This study aims to provide insights the teachers and highlight the potential of artificial intelligence (AI) in rural education.

This content analysis study explores the use of Alexa in primary education in rural areas of India. The study focuses on the types of the questions asked by the students and examines the pedagogical implications of these interactions. By analyzing the use of Alexa in rural educational settings, this study aims to contribute to our understanding of how voice assistants are utilized as educational tools in underprivileged areas.

Alexa significantly improved students' English vocabulary, comprehension and public speaking confidence. Alexa increased school enrollment and retention. Virtual voice assistants like Alexa may improve pedagogy and help India’s rural education. This study shows AI improves rural education.

The study only covers rural India. Self-reported data and observations may bias the study. The small sample size may underrepresent rural educational institutions in India.

Alexa is used to study rural India’s primary education. Voice assistants in rural education are understudied. The study examines Alexa’s classroom use, student questions, and policy and teacher education implications. AI’s education transformation potential addresses UNESCO’s teacher shortage. This novel study examines how AI can improve rural education outcomes and access.

This study explores the tourists' behavioral intention toward tasting ethnic food by proposing 'enjoyment’ as an indirect mechanism in improvising the model of Wang. In other words, when affective and cognitive components are triggered positively while reading online gastronomy reviews on social media platforms, enjoyment is aroused, subsequently enhancing the desire to taste ethnic foods displayed online.

Data from 385 visitors from Kashmir, India, were gathered using a purposive sample technique. The research model was put to the test using PLS-SEM.

Direct and indirect mechanisms influence Behavioral Intention. Enjoyment acts as a mediator. Overall, the results validated the presence of three direct and full mediation paths.

This study will help tourism practitioners justify their promotional activities on social networking sites, particularly in endorsing regional ethnic dishes. For example, tourism authorities could collaborate with bloggers on social media and offer incentives to promote attractive images of ethnic food. Similarly, ethnic food outlets can improve online exposure and interactivity by encouraging travelers to leave feedback after visits.

Unlike other studies, this research broadens our understanding by focusing on direct and indirect mechanisms. The inclusion of a mediator enhanced the total variance of the dependent variable.

This paper intervenes in the consequences of a myth propagated in academic discourse about the dancesport world, according to which half of the men in Latin dancesport are gay. I challenge two assumptions that surround this myth: that cisgender gay men do not contribute to the reification of the heteronormative gender binary, and that the dancesport scene is inclusive of gay people. These assumptions are based on a blatant lack of understanding of the position of gay men within the dancesport world – that is, the ways in which subjects are constituted through the effects of power.

This work is based on empirical research I conducted in the dancesport community, including ethnographic and autoethnographic fieldwork, extant documents (e.g. books, blogs, Judging Regulations) and interviews with experts and participants of the dancesport scene (2021/2022). To analyse the data, I relied on the principles of dispositive analysis, grounded theory and dance analysis.

I show that gay dancers have turned to assimilation as their only available strategy. I discuss the negative consequences of assimilation as a political strategy and how it impacted queer dancers – between invisibilisation, residual shame and a failure to challenge the heteronormative gender binary. This led gay dancers to rationalise and perpetrate harm based on the systems of oppression they had internalised.

I conclude the paper by highlighting a way beyond assimilation for queer dancers.

This paper addresses a critical gap in research on LGBT + inclusion in dancesport.

This paper seeks to demonstrate the value of using social media to capture fashion trends, including the popularity of specific features of clothing, in order to improve the speed and accuracy of supply chain response in the era of fast fashion.

This study examines the role that text mining can play to improve trend recognition in the fashion industry. Researchers used n-gram analysis to design a social media trend detection tool referred to here as the Twitter Trend Tool (3Ts). This tool was applied to a Twitter dataset to identify trends whose validity was then checked against Google Trends.

The results suggest that Twitter data are trend representative and can be used to identify the apparel features that are most in demand in near real time.

The 3Ts introduced in this research contributes to the field of fashion analytics by offering a novel method for employing big data from social media to identify consumer preferences in fashion elements and analyzes consumer preferences to improve demand planning.

The 3Ts improves forecasting models and helps inform marketing campaigns in the apparel retail industry, especially in fast fashion.

The purpose of this study is to explore the potential contribution of the metaverse to improve training and development as a function of human resource development (HRD) perspective. The authors explore the benefits and challenges of the metaverse and introduce cases of companies using the metaverse in training.

A narrative literature review was conducted to collect information on the metaverse in training. The authors reviewed peer- and non-peer-reviewed articles, book chapters, white papers, corporate websites and blogs and business magazines.

A total of 75 articles were reviewed, including 14 cases, which were summarized to demonstrate how companies are applying metaverse technology in training contexts. For a more in-depth review, three cases were selected and summarized in terms of context, process and outcomes.

The metaverse is an emergent topic in HRD. It has the potential to revolutionize the functions of training and development through the combination of advanced technologies, including virtual reality, augmented reality and mixed reality. This article is the foundational attempt to provide a comprehensive summary of existing literature and case studies that highlight the potential of the metaverse in training within the context of HRD.

Despite entrepreneurial linguistic style gaining increased attention in entrepreneurship studies, the field for digital vlogger entrepreneurs still lacks a comprehensive understanding of how linguistic patterns enhance audiences attitude and behaviour. This study aims to propose a conceptual model of “language-mental imagery-attitude-behaviour model” that leads to the examination of rich sensory language style of food travel vlogger entrepreneurs and its persuasive effect on audiences' attitude and behavioural intention.

The present study utilises a stimulus-based survey method that involves a sensory-rich vlog script extracted from a high social media engagement authentic vlog. Data are collected through an online questionnaire distributed to a sample of 355 participants via the Amazon Turk mechanism. The study employs confirmatory factor analysis and structural equation modelling to test the proposed hypotheses, with the aim of contributing to the advancement of theories of embodied cognition in entrepreneurial language by examining the attitudes and behaviours of audiences exposed to sensory-rich language. The findings of this research provide valuable insights into the effects of sensory-rich language on audience responses and can inform future research on the role of embodied cognition in entrepreneurial communication.

The findings demonstrate that vlogger entrepreneurial sensory-rich linguistic communication style positively influence audiences' attitude, behavioural involvement with food and intention to taste. Visit intention will be enhanced via the mediating effects of attitude, behavioural involvement with food and intention to taste.

This research highlights the significance of sensory-rich language for vlogger entrepreneurs in entrepreneurial communication, digital storytelling and for destination marketing enterprises in creating a digital sensory engagement marketing strategy.

The study contributes to the literature by elucidating the theories of embodied cognition in entrepreneurial communication. By examining the relationships between vlogger communication evoked mental imagery, audiences attitude and behaviours, this study provides novel insights into the effectiveness of sensory-rich language in vlogger entrepreneurial communication and its impact on audience engagement. These findings have important implications for communication scholars and practitioners alike, shedding light on the role of embodied cognition in entrepreneurial language and the potential of sensory-rich language to enhance audience engagement.