Search results

The landscape of health information acquisition has shifted from offline to online, and online question-and-answer (Q&A) communities have emerged as prominent sources of health information; however, it is unclear how users identify satisfactory health information. This paper identifies factors that influence users’ adoption of health information in the context of online Q&A communities.

Based on the elaboration likelihood model (ELM) and opinion leader theory, we construct a research model to examine how information quality (complexity, image structure and emotional change) and source credibility (authentication status, follower number) affect health information adoption behavior. We verify the hypotheses by Poisson regression and zero-inflation Poisson regression using the data collected from an online Q&A community.

The empirical results indicate that both information quality and source credibility positively affect users’ adoption of health information.

This research can assist designers and managers of online Q&A communities to better comprehend users’ health information needs and their preferences for adoption. This enhanced understanding can facilitate the provision of superior online health information.

This study identifies a methodology to explore the issues of enterprise innovation ecosystem health (EIEH).

First, this study constructs the indicator system of EIEH based on the research objective; second, the dynamic vertical projection method (DVPM) and entropy weight method are proposed to analyze the status and influencing factors of EIEH; finally, the future development of EIEH is analyzed using GM (1,1).

In terms of methodology, the DVPM can effectively analyze EIEH, which can not only analyze the development status and potential of EIEH every year but also analyze the comprehensive state of EIEH for many years. In terms of practice, the value and grade of EIEH in China have been gradually increasing from 2016 to 2020, but the overall development is unbalanced, and five key factors affecting EIEH have been identified. The EIEH in China is predicted to steadily grow from 2021 to 2025.

The analytical method employed in this study can effectively analyze EIEH, which provides a new analytical perspective for the evaluation of EIEH and enriches the research content of the enterprise innovation ecosystem (EIE). By analyzing the results, we can gain a comprehensive understanding of the state of different EIEs, enabling each EIE to design tailored remedial measures to enhance EIEH and achieve sustainable development.

This study aims to assess how ethical sales behaviour affects switching costs typology, mediated by trust and moderated by brand affiliation, monthly contributions and the number of dependent beneficiaries in medical schemes in South Africa.

A quantitative study targeted a non-probability judgement sample of 250 main members of medical schemes, elicited near health-care facilities in South Africa’s Gauteng province. Data was collected in a face-to-face survey and analysed using structural equation modelling on AMOS version 29 and PROCESS procedure for Statistical Package of Social Science release 2.041.

The results show that ethical sales behaviour negatively affects trust and positively affects evaluation, monetary and personal relational loss costs. Trust positively affects personal relational loss costs, economic risk, evaluation, monetary and benefit loss costs. Moreover, trust mediates the effect of ethical sales behaviour on evaluation, monetary and personal relational loss costs. Finally, the number of dependent beneficiaries, monthly contributions and brand affiliation significantly moderate these interactions.

The paper validates the application of commitment-to-trust theory in mediating how the effects of the general theory of marketing ethics on switching costs typology differ according to the number of dependent beneficiaries, monthly contributions and brand affiliation with medical schemes.

Current multi-source image fusion methods frequently overlook the issue of detailed features when employing deep learning technology, resulting in inadequate target feature information. In real-world mission scenarios, such as military information acquisition or medical image enhancement, the prominence of target feature information is of paramount importance. To address these challenges, this paper introduces a novel infrared-visible light fusion model.

Leveraging the foundational architecture of the traditional DenseFuse model, this paper optimizes the backbone network structure and incorporates a Unique Feature Encoder (UFE) to meticulously extract the distinctive features inherent in the two images. Furthermore, it integrates the Convolutional Block Attention Module (CBAM) and the Squeeze and Excitation Network (SE) to enhance and replace the original spatial and channel attention mechanisms.

Compared to other methods such as IFCNN, NestFuse, DenseFuse, etc., the values of entropy, standard deviation, and mutual information index of the method presented in this paper can reach 6.9985, 82.6652, and 13.6022, respectively, which are significantly improved compared with other methods.

This paper presents a UFEFusion framework that synergizes with the CBAM attention mechanism to markedly augment the extraction of detailed features relative to other methods. Moreover, the framework adeptly extracts and amplifies unique features from disparate images, thereby elevating the overall feature representation capability.

This paper aims to study the possibility of electroplating copper coatings on chemically and chemical-galvanically nickel-plated acrylic fibers, to be further processed into yarn, fabrics, knitwear and nonwoven materials.

Electrically conductive fibers with different copper contents have been obtained, and the effect of electrolyte pH, its composition, current strength at the first and second cathodes, as well as the metallization time on the electrophysical, physical and mechanical properties of copper-containing fibers, has been studied.

The studies have shown that with an increase in the copper content, the electrical conductivity, the uniformity of the coating and the uniformity of the electrophysical properties (for chemical-galvanically nickel-plated fiber) increase. In the case of copper plating of chemically nickel-plated fiber, the coefficient of variation in electrical resistance increases with increasing plating time, even though the copper content increases, and the coefficient of variation in copper content and electrical resistance decreases. The physical and mechanical properties of copper-containing fibers differ slightly from the original (subjected to copper plating) and industrial Nitron fibers. With copper plating, the strength of the fiber practically does not decrease, and the elongation decreases somewhat, compared with the mass-produced Nitron fiber.

The physical and mechanical properties of copper-containing fibers are quite high, which makes it possible to be successfully further processed into yarn, fabrics, knitwear and nonwoven materials.

This empirical study aims to investigate how employee responses to corporate social responsibility (CSR) (i.e. perception of and participation in CSR initiatives) can affect career adaptability in the Vietnamese service industry. Furthermore, the mediating mechanism of psychological capital (PsyCap) and the moderating role of moral identity are explored in this relationship.

The target population for this study includes employees working for service enterprises in which CSR practices are conducted, such as tourism, hospitality, retail, education and others in Vietnam. The data from 685 responses were analyzed for measurement model analysis and structural model analysis using SPSS, AMOS and SmartPLS.

The findings of this study reveal that CSR perception and CSR participation have significant positive effects on career adaptability through PsyCap. This study also confirms that the positive association between CSR perception and PsyCap is more pronounced among employees with a higher level of internalized moral identity and symbolic moral identity.

The collection of data involving multiple dimensions at once did not allow the study to accurately assess the effect of variables over time. Further studies that want to look closely at the impact of perception of and participation in CSR should collect data longitudinally and follow up the target sample over a period of time. Besides, moral identity is a context-dependent construct associated with various social and cultural institutions. Meanwhile, Western moral identity emphasizes individual-oriented morality; Eastern cultures consider a socially oriented person to be highly moral; therefore, this study’s findings might not be appropriate for Western culture. To enrich the existing CSR framework, future studies may attempt to unveil the intervening mechanism of other psychological factors, such as psychological safety, or explore the predictions for other career-related outcomes, such as career satisfaction in the CSR context. Finally, both CB-SEM and PLS-SEM methods can be combined to analyze complex models, especially high-order models.

By leveraging influence processes within the model, service managers can foster human resource development in the workplace by raising the active involvement of employees in CSR activities.

This research enriches the literature on CSR and employee-related outcomes by formulating a conceptual model focusing on employee responses to CSR as key antecedents. This study also contributes to the existing understanding of the CSR context by empirically investigating micro-level CSR in an emerging economy like Vietnam.

This paper aims to regulate the oil retention rate and tribological properties of pored polytetrafluoroethylene (PPTFE) using polyvinyl alcohol (PVA)-based oil gel.

PPTFE was first prepared by using citric acid (CA) as an efficient pore-making agent. Subsequently, PVA and chitosan solution was introduced into the pores and experienced a freezing-thawing process, forming PVA-based gels inside the pores. Then, the PPTFE/PVA composite was impregnated with polyethylene glycol 200 (PEG200), yielding an oil-impregnated PPTFE/PVA/PEG200 composite.

It was found that the oil-impregnated PPTFE/PVA/PEG200 composite exhibited advanced tribological properties than neat PTFE with reductions of 53% and 70% in coefficient of friction and wear rate, respectively.

This study shows an efficient strategy to regulate the tribological property of PTFE using a PVA-based oil-containing gel.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2024-0432/

This study aims to gain a better understanding of artificial serendipity – pre-planned surprises intentionally crafted through deliberate designs – in online marketplaces. By exploring the key features of artificial serendipity, this study investigates whether serendipity can be intentionally designed, particularly with the use of artificial intelligence (AI). The findings from this research broaden the scope of serendipity studies, making them more relevant and applicable in the context of the AI era.

A narrative study was conducted, gathering insights from 32 Chinese online consumers through diaries and interviews. The data were analysed in close collaboration with participants, ensuring an authentic reflection of their perceptions regarding the features of artificial serendipity in online marketplaces.

Findings reveal that artificial serendipity, particularly when designed by AI, is still regarded by online consumers as genuine serendipity. It provides a sense of real surprise and encourages deeper reflection on personal knowledge, affording the two central qualities of genuine serendipity: unexpectedness and valuableness. However, since artificial serendipity is pre-planned through intentional design, consumers cannot have entire control over it. Therefore, compared to natural serendipity – fortune surprises arising from accidental correspondence between individuals and contexts – artificial serendipity tends to be more surprising yet less valuable.

For research, it highlights the potential of intelligent technologies to facilitate genuine serendipity, updating our understanding of serendipity.

Also, the study provides practical insights into designing serendipity, especially in online markets. These contributions enrich both the theoretical framework and practical strategies surrounding serendipity in the era of AI.

This study stands out as one of the few to provide a nuanced understanding of artificial serendipity, offering valuable insights for both research and practice. For research, it highlights the potential of intelligent technologies to facilitate genuine serendipity, updating our understanding of serendipity. Also, the study provides practical insights into designing serendipity, especially in online markets. These contributions enrich both the theoretical framework and practical strategies surrounding serendipity in the era of AI.

This research aims to introduce the concept of information snowballing, which shows the process of how individuals with a specific interest in food sustainability acquire information about and remain abreast of sustainability-related information in everyday life and food practices.

This study employed constructivist grounded theory to investigate the information acquisition practices of consumers of sustainable food around topics related to sustainability. The author collected data through pre-screening phone calls, photo diaries and in-depth semi-structured interviews by using theoretical sampling with nine sustainable food consumers; analyzed data through constant comparison and memoing; and validated findings via methodological jotting, data triangulation and peer-debriefing throughout the process.

The findings identify three stages of information snowballing: (a) learning by lifelong exposure and serendipitous information encountering; (b) constructing information landscapes; and (c) snowballing or gradually accumulating information.

This concept advocates for spreading sustainability-related information and awareness outside the context of formal education.

This study originates the concept of “information snowballing,” which evolves from the idea of snowball sampling, a common strategy for participant recruitment. Both of these terms lean on the idea that a snowball rolling downhill picks up more and more momentum and more and more snow as it travels; recruitment and information gathering show the same process of accretion through building momentum. Information snowballing highlights the individual’s agency in seeking relevant information sources, expressing one’s interests, constructing information landscapes—all activities that precede the serendipitous encountering and snowballing of information based on a particular interest. It also connects everyday information practices to information landscapes within the context of everyday food practices.

The present study undertakes an extensive review of the causes of service failures in artificial intelligence (AI) technology literature.

A hybrid review has been employed which includes descriptive analysis, and bibliometric analysis with content analysis of the literature approach to synthesizing existing research on a certain topic. The study has followed the SPAR-4-SLR protocol as outlined by Paul et al. (2021). The search period encompasses the progression of service failure in AI from 2001 to 2023.

From identified theories, theoretical implications are derived, and thematic maps direct future research on topics such as data mining, smart factories, and among others. The key themes are being proposed incorporates technological elements, ethical deliberations, and cooperative endeavours.

This research study makes a valuable contribution to understanding and reducing service defects in AI by providing insights that can inform future investigations and practical implementations. Six key future research directions are derived from the thematic and cluster discussions presented in the content analysis.