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Although numerous signal modalities are available for emotion recognition, audio and visual modalities are the most common and predominant forms for human beings to express their emotional states in daily communication. Therefore, how to achieve automatic and accurate audiovisual emotion recognition is significantly important for developing engaging and empathetic human–computer interaction environment. However, two major challenges exist in the field of audiovisual emotion recognition: (1) how to effectively capture representations of each single modality and eliminate redundant features and (2) how to efficiently integrate information from these two modalities to generate discriminative representations.

A novel key-frame extraction-based attention fusion network (KE-AFN) is proposed for audiovisual emotion recognition. KE-AFN attempts to integrate key-frame extraction with multimodal interaction and fusion to enhance audiovisual representations and reduce redundant computation, filling the research gaps of existing approaches. Specifically, the local maximum–based content analysis is designed to extract key-frames from videos for the purpose of eliminating data redundancy. Two modules, including “Multi-head Attention-based Intra-modality Interaction Module” and “Multi-head Attention-based Cross-modality Interaction Module”, are proposed to mine and capture intra- and cross-modality interactions for further reducing data redundancy and producing more powerful multimodal representations.

Extensive experiments on two benchmark datasets (i.e. RAVDESS and CMU-MOSEI) demonstrate the effectiveness and rationality of KE-AFN. Specifically, (1) KE-AFN is superior to state-of-the-art baselines for audiovisual emotion recognition. (2) Exploring the supplementary and complementary information of different modalities can provide more emotional clues for better emotion recognition. (3) The proposed key-frame extraction strategy can enhance the performance by more than 2.79 per cent on accuracy. (4) Both exploring intra- and cross-modality interactions and employing attention-based audiovisual fusion can lead to better prediction performance.

The proposed KE-AFN can support the development of engaging and empathetic human–computer interaction environment.

This study aims to explore medical students’ attitudes to electroconvulsive therapy (ECT). The authors sought to determine correlates of baseline attitudes to ECT and whether specific forms of ECT teaching improved attitudes to ECT during students’ psychiatry placement.

At the beginning of their placement, fourth-year medical students completed a questionnaire capturing background information and baseline attitudes. A second questionnaire, in the second half of the placement, recorded educational and clinical experience gained on ECT during placement, in addition to attitudes at this timepoint. The authors measured attitude using a five-point Likert scale and defined a positive shift in attitude as an improvement of ≥ 1 point between the two time points.

At Timepoint 1, 66% reported a positive attitude to ECT. This was associated with having attended a lecture and with having read a professional article on ECT at some time before the psychiatry placement. Attitudes significantly improved during the placement (66% vs 95% positive). Students who attended a lecture on ECT were more likely to have a positive shift in attitude, as were students who experienced three or more teaching modalities.

Personal, social and medical problems arise from treatment-resistant psychiatric disorders. ECT is a safe and effective treatment for such disorders.

It is hoped that this study will contribute to the development of medical education, so that lectures on ECT, and three or more teaching modalities, are incorporated into the undergraduate medical curriculum.

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.

This study's purpose is to explore the difference in employee voice behavior along with its modalities and employee perceived control in a remote vs an in-office work situation.

Employees who worked remotely and in-person at a local municipal government in the Great Lakes Region of the United States were surveyed.

Findings suggest voice behavior and perceived control are stable attitudes and not impacted by a move from in-person to remote work. Participants indicated both Zoom staff meetings and Zoom one-to-one meetings with their supervisor were important; however, only Zoom one-to-one meetings with the supervisor were indicated to be satisfactory.

This study suggests that organizations considering moving some of their operations to a fully remote work situation would not experience differences in employee voice or perceived control. Implications related to utilizing specific communication modalities are also discussed.

This is the only study that focuses on differences in employee voice, its modalities and perceived control comparing in-person vs remote work.

This paper aims to facilitate the research and development of resilient navigation approaches, explore the robustness of adversarial training to different interferences and promote their practical applications in real complex environments.

In this paper, the authors first summarize the real accidents of self-driving cars and develop a set of methods to simulate challenging scenarios by introducing simulated disturbances and attacks into the input sensor data. Then a robust and transferable adversarial training approach is proposed to improve the performance and resilience of current navigation models, followed by a multi-modality fusion-based end-to-end navigation network to demonstrate real-world performance of the methods. In addition, an augmented self-driving simulator with designed evaluation metrics is built to evaluate navigation models.

Synthetical experiments in simulator demonstrate the robustness and transferability of the proposed adversarial training strategy. The simulation function flow can also be used for promoting any robust perception or navigation researches. Then a multi-modality fusion-based navigation framework is proposed as a light-weight model to evaluate the adversarial training method in real-world.

The adversarial training approach provides a transferable and robust enhancement for navigation models both in simulation and real-world.

The purpose of this study is to determine what technological strategies were used within each of the phases of the ADDIE framework when developing content for professional training. The study also examined the affordances of those technologies in training.

A PRISMA systematic review methodology (Moher et al., 2015) was utilized to answer the four questions guiding this study. Specifically, the PRISMA extension Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Protocols (PRISMA-P, Moher et al., 2015) was used to direct each stage of the research, from the literature review to the conclusion. In addition, the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA principles; Liberati et al., 2009) are used to guide the article selection process.

The findings reveal that the majority of the studies were in healthcare (36%) and education (24%) and used an online format (65%). There was a wide distribution of ADDIE used with technology across the globe. The coding for the benefits of technology use in the development of the training solution revealed four trends: 1) usability, 2) learning approaches, 3) learner experience and 4) financial.

This systematic review only examined articles published in English, which may bias the findings to a Western understanding of how technology is used within the ADDIE framework. Furthermore, the study examined only peer-review academic articles from scholarly journals and conferences. While this provided a high level of assurance about the quality of the studies, it does not include other reports directly from training providers and other organizations.

These findings can be used as a springboard for training providers, scholars, funders and practitioners, providing rigorous insight into how technology has been used within the ADDIE framework, the types of technology, and the benefits of using technology. This insight can be used when designing future training solutions with a better understanding of how technology can support learning.

This study provides insight into the uses of technology in training. Many of these findings and uses of technology within ADDIE can also transfer to other aspects of society.

This study is unique in that it provides the scholarly community with the first systematic review to examine what technological strategies were used within each of the phases of the ADDIE structure and how these technologies provided benefits to developing a training solution.

This paper aims to investigate the competencies that researchers need to develop and employ for successful collaborative research.

The authors use a reflexive approach built on participant observation of six cases of collaborative research in public procurement and logistics.

The authors identify and explain two major competencies that are required for successful collaborative research. The first is boundary-spanning competence that represents the researchers' ability to move fluidly from the academic milieu to the practitioner's environment. The second is reflexivity competence that allows the researchers to learn from each collaborative research project they participate in and further improve their boundary-spanning competence.

This study goes beyond the list of skills for collaborative research reported in the literature to describe two major competencies that researchers should develop to perform successful collaborative research. This reflection may serve as a starting point for the development of a sociological understanding of the collaborative research field.

This qualitative study aimed to explore the barriers and facilitators faced by workers during the COVID-19 pandemic restrictions in Ecuador. It focused on three work modalities: on-site, telework and mixed or hybrid. It also inquired into practical implications for management based on the workers’ experiences.

Between October and December 2021, 41 semistructured interviews were conducted to delve into the experiences of Ecuadorian workers. Thematic content analysis was employed for data charting and analysis.

Barriers and facilitators varied according to each working modality, although some were shared, contingent upon the specific contextual factors and job characteristics. The findings suggest that organizations should consider implementing flexible working hours and modalities, provide safe workspaces, ensure appropriate technology and connectivity, support employees and maintain their health and well-being.

This research explores the experiences of teleworkers, on-site workers and hybrid workers during the COVID-19 pandemic in an under-researched labor market within a developing country. The study provides valuable insights that highlight the potential for management development initiatives specifically tailored to hybrid work environments.

This study aims to empirically test how sponsored video customization (i.e. the degree to which a sponsored video is customized for a sponsoring brand) affects video shares differently depending on influencer characteristics (i.e. mega influencer and expert influencer) and brand characteristics (i.e. brand establishment and product involvement).

This study uses a unique real-world data set that combines coded variables (e.g. customization) and objective video performance (e.g. sharing) of 365 sponsored videos to test the hypotheses. A negative binomial model is used to analyze the data set.

This study finds that the effect of video customization on video shares varies across contexts. Video customization positively affects shares if they are made for well-established brands and high-involvement products but negatively influences shares if they are produced by mega and expert influencers.

This study extends the influencer marketing literature by focusing on a new media modality – sponsored video. Drawing on the multiple inference model and the persuasion knowledge theory, this study teases out different conditions under which video customization is more or less likely to foster audience engagement, which both influencers and brands care about. The chosen research setting may limit the generalizability of the findings of this study.

The findings suggest that mega and expert influencers need to consider if their endorsement would backfire on a highly customized video. Brands that aim to engage customers with highly-customized videos should gauge their decision by taking into consideration their years of establishment and product involvement. For video-sharing platforms, especially those that are planning to expand their businesses to include “matching-making services” for brands and influencers, the findings provide theory-based guidance on optimizing such matches.

This paper fulfills an urgent research need to study how brands and influencers should produce sponsored videos to achieve optimal outcomes.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.