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The paper aims to provide companies with a better understanding of the needs of institutional investors to improve the disclosure of sustainability information by companies. The study investigates the changed information needs of institutional investors resulting from the Sustainable Finance Disclosure Regulation (SFDR).

This study uses an internet-based survey instrument amongst institutional investors to gain insights into their needs regarding sustainability information. The authors received 155 responses in total and use descriptive statistics and t-tests to analyse the survey data.

The results demonstrate that the implementation of the SFDR challenges institutional investors, as it affects their decision process. Additionally, the findings still indicate a lack of available corporate sustainability information, making it even more challenging for institutional investors to make appropriate investment decisions. Respondents suggest that information on climate-related risks is more important than the European Union (EU) Taxonomy metrics for meeting the SFDR requirements.

The findings are mainly restricted to the opinion of European investors. However, the evidence contributes to the existing literature by investigating institutional investors' information needs in the new regulatory landscape.

As the study provides insights into institutional investors' needs, reporting companies recognise the relevance of transparently providing sustainability information to be further considered in the investment process of institutional investors despite the regulation. The findings can help regulators develop uniform and global sustainability reporting standards.

This paper is the first to provide evidence on sustainability information requested on the institutional investors' side. The survey gathers primary data from professional investment members unavailable in databases or reports.

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.

The purpose of this study was to gain a deeper understanding of the experiences and challenges of Middle Eastern refugee mothers in using technology for language learning in regional Australian context.

This study used a qualitative research design and used a narrative enquiry technique to understand participants’ experiences of language acquisition with limited access to technology in new resettlement setting.

The findings presented in this paper were derived from a qualitative investigation conducted on a sample of 21 refugee mothers from Middle Eastern countries. The research aimed to explore the role of a language education programme on their integration within the regional Australian context. Participants discussed a variety of aspects of their everyday lives within their new resettlement context while offering insights on the language education programme and its impacts on their educational progress. The theme “lack of access/use of technology in English language learning” emerged from the narratives. This paper draws on selected interview data from the participants.

This study fills the gap in the literature on Middle Eastern refugees in regional Australia by exploring how lack/limited technology access can impact language acquisition of women from under-represented contexts.

This study aims to provide a precise understanding of how corporate sustainability information is used in socially responsible investing (SRI). The study is motivated by the lack of a recognised body of knowledge on this issue. This study, therefore, collates and reviews relevant studies (67 studies) to provide guidance to investors interested in SRI and identify a research agenda for academics desiring to contribute to this area.

This study conducts a systemic literature review employing recognised key words and searching the Web of Science. HistCite is utilised to ensure important cited studies are not missed from the collection. The review was conducted from two perspectives: (1) sources of sustainability information and (2) how the information is used in SRI.

The review identifies five major sources of sustainability information, including corporate reports, ESG ratings, industry affiliation, news and private communication with firms. These sources of information play different roles in the cross section of SRI strategies (i.e. negative and positive screening, active ownership and integration). This study provides guidance on how to use this information in SRI and provides recommendations for future research on how analysts interact with the information, how different informational characteristics impact implementation, ways to improve data quality, improvements to analysis methods and where data use needs to be extended into new strategies.

This review contributes to the SRI literature by inventorying studies of an important, yet omitted aspect, namely, sustainability information. This work also enriches the literature on corporate sustainability information by investigating how this information can be used for a specific purpose, namely, SRI. Given the increasing interest in SRI, this review will provide much-needed guidance for a range of practitioners, including investors and regulators.

This paper aims to investigate the key enablers and inhibitors that influence the intention to use fitness wearables using the value-based adoption model (VAM).

Data were collected using a structured online questionnaire from 323 respondents who had never used fitness wearables. A purposive sampling technique was used in this study. Smart PLS was employed to test the research framework and hypotheses using a two-step approach.

The findings support some of the hypotheses developed with R² values of 0.622 for perceived value (PV) and 0.567 for intention to use fitness wearable. Perceived enjoyment, perceived social image and perceived usefulness had a positive effect on PV. In addition, health information sensitivity (HIS) was positively related to perceived privacy risk and health information accuracy was positively related to perceived usefulness. Surprisingly, this study did not find any significant relationship between perceived fee, perceived privacy risk, perceived health increase and perceived design aesthetics with PV.

This study's findings can help designers and manufacturers design fitness wearables by considering factors that users find valuable, thus satisfying consumers' needs.

This study tries to model behavioural intention of fitness wearable usage of individual users by using the VAM with the addition of two new antecedences, HSI and health information accuracy, to better explain the behaviour.

Workforce insufficiencies can impair firms' competitiveness in the hospitality industry. The problem of finding suitably trained employees has been aggravated by changes in consumer preferences, and the development of advanced technologies has led to the ‘smartization’ of upscale hotels. The consequent updating of business models means that decisive indicators of worker competence and employability are different from those applied previously. Thus, the aim of this study is to develop an indicator framework for assessing workforce employability with consideration of competence with artificial intelligence (AI) applications.

The initial indicators for the framework are obtained based on an intensive review of the relevant literature and roundtable meetings with academics and practitioners. The Delphi method is used to collect the data, and a hybrid fuzzy approach, which combines the modified Z-number and modified trapezoidal fuzzy number set techniques, is applied to quantify the information originating from the experts’ judgments. The interquartile range approach is applied to optimize the validity of the indicators.

The assessment framework is applied to evaluate workforce employability at an upscale hotel from the perspective of hotel executives. The capability of the workforce for the adoption of advanced technologies, including familiarity with AI, are considered.

The contributions of this research involve the identification of an updated list of determinants for the evaluation of workforce employability for hotels in today’s world, highlighting the value of AI applications to help ameliorate labor shortage problems. The results should benefit practitioners, allowing them to improve the efficiency of their operations, services and management practices, leading to sustainability and competitiveness in the upscale hotel industry.

The study investigates the relationship between corporate social responsibility (CSR) and dividend policy in the context of Indian firms, as well as how regulatory interventions in the form of mandated CSR can moderate this relationship.

A sample of the largest 500 companies listed on the National Stock Exchange from 2008 to 2019 is used in the study. The authors employ the system generalized method of moments since this estimation technique yields accurate and consistent findings in a dynamic panel data setting.

The authors find that CSR is positively associated with dividend payments. Increased incomes and lower financial constraints are the likely factors causing this relationship. Additional analysis suggests that the positive relationship is stronger for mature firms and for firms with higher information asymmetry. Financial reporting quality works in tandem with CSR to boost dividends. Regulatory interventions in the form of mandated CSR weaken the relationship. Finally, the speed of adjustment of dividends is relatively faster for socially responsible firms.

The positive association between CSR and dividends suggests that the interest of shareholders and other non-financial stakeholders can be reconciled. Additionally, businesses should attempt to strategically implement their CSR plans in accordance with the requirements of Section 135 of the Companies Act, 2013 to avoid any unfavourable moderating effects of the legislation. The results also show that CSR disclosures complement rather than serve as a substitute for financial disclosures.

The study is the first to evaluate the relationship between CSR and dividends in the context of India, which is a pioneer in passing legislation that mandates CSR for firms surpassing a threshold. The authors also identify financial constraints as a channel through which CSR affects dividends.

With the function to store individual’s data input, personal health record (PHR) enhanced the accessibility to personal health information. This study aims to assess the factors that impact the intention of Malaysian internet users to use PHR and create a modified technology acceptance model (TAM) for eHealth.

Multivariate statistical analysis was performed on a total of 216 responses using the partial least square technique based on the cross-sectional survey among Malaysian internet users.

Behavioral intention was positively associated to PHR. Subjective norm significantly influenced both attitude and intention to use, whereas trust and perceived usefulness significantly influenced attitude. There was no significant positive impact in the relationships between compatibility and perceived ease of use and intention to use; nevertheless, they positively influenced perceived usefulness. Attitude exhibited mediating influence between trust, perceived usefulness and subjective norm and intention to use. Nonetheless, perceived risk did not affect behavioral intention. Thus, PHR acceptance was well-justified by the modified TAM in evaluating eHealth acceptance.

The eHealth vendors can enhance their marketing and development strategies on related products.

Literatures and empirical evidence on eHealth are still scarce, especially in emerging markets. The role of attitude may not be well-researched in health-care context, therefore was included in this study’s modified TAM. Critical determinants, namely, trust and risk, were added to the model.

This study aims to identify the main factors affecting export competitiveness and its barriers, focusing on the minerals industry so that a scale is achieved for measuring export competitiveness in this industry.

The research was conducted with a mixed method approach in the minerals industry. Among the active companies involved in this industry, 34 export companies and export management companies were selected and evaluated. In the qualitative phase, 18 experts and managers of the industry were interviewed to identify the factors affecting the export competitiveness of these companies and the barriers ahead of them. In the quantitative phase, a questionnaire was distributed among 412 managers and experts in this industry to categorize the identified factors and to measure the relationships among them. For data analysis in the qualitative phase, theme analysis was used. For the quantitative phase, factor analysis and structural equation modeling were adopted.

In addition to identifying the main components affecting the competitiveness of companies in exporting minerals as well as the main barriers ahead of them, the findings of the current research categorized these components using factor analysis. These components were categorized into factors, such as manufacturing factors, demand conditions, related and supporting industries, structural factors, competitive strategy and governmental supports. Afterward, their impacts on export competitiveness were measured and supported.

Although some studies have been conducted to examine the competitiveness in different industries, no research has been found that has examined and identified the main factors affecting export competitiveness and their impacts in the minerals industry with a mixed quantitative and qualitative approach. The findings of this research may help managers and policymakers, at the industrial and national levels, to reach a scale for assessing the export companies involved in this industry by identifying the most essential factors of export competitiveness of minerals. Furthermore, the findings of this research can act as a model for future researchers to develop a scale for export competitiveness in other industries.

This study aims to investigate the factors that influence the continuance intention to use personal cloud storage services among Generation Y.

A quantitative online survey was carried out to collect data from 271 respondents. Structural equation modelling with SmartPLS 4.0 software was used to run the analysis and examine the hypothesized relationships in the research model.

The study revealed that both satisfaction and habit exert a significant influence on continuance intention, whereas self-efficacy does not demonstrate a significant effect. In addition, satisfaction was found to be influenced by confirmation, perceived usefulness and perceived security. Furthermore, confirmation and cloud storage service quality were found to impact perceived usefulness, while confirmation also had an effect on perceived security. However, the hypothesized moderating role of perceived privacy risk in the relationship between perceived usefulness, perceived security and satisfaction was not supported.

This study advances the field by adapting an expanded expectation-confirmation model that delineates the nuanced impacts of habit, user satisfaction and self-efficacy on Generation Y’s continuance intention to use personal cloud storage services. It challenges the conventional wisdom regarding self-efficacy’s influence on technology adoption, offering a more intricate portrayal of its role. This research contributes a distinctive theoretical perspective, emphasizing the complex interplay of factors that inform sustained user engagement with cloud technologies.