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Abundant health knowledge resources are available on social media to facilitate technology-enhanced knowledge learning among older adults. The objective of this study is to investigate the predictors and the underlying formation mechanism of older adults' intention to learn health knowledge on social media. We propose a novel model to examine how older adults' emotional state (i.e., health anxiety) and cognitive state (i.e., e-health literacy) during knowledge acquisition influence threat appraisal (i.e. perceived severity and perceived susceptibility) and coping appraisal (i.e. self-efficacy and perceived benefits), thereby shaping older adults' intention to learn health knowledge. Survey data from 337 Chinese older adult users of social media was collected to test the research model. Results reveal that perceived susceptibility, self-efficacy and perceived benefits exert positive effects on older adults' health knowledge learning intention, while the impact of perceived severity on health knowledge learning intention is not statistically significant; health anxiety is positively correlated with perceived severity and perceived susceptibility, and e-health literacy is a powerful predictor of self-efficacy and perceived benefits. This paper enriches the literature related to technology-enhanced knowledge learning and online health behavior among older adults. Effective strategies are proposed based on the findings for practitioners dedicated to promoting health knowledge via social media and older adults who apply health knowledge to address health-related needs.

[Purpose/Significance] Under the background of the rapid penetration of the Internet and the aging transformation, the digital divide and Internet addiction of the seniors coexist, and the emerging phenomenon of Internet addiction of the seniors has many potential hazards, which need to be studied urgently. [Method/Process] This study crawled from the Internet published cases of the seniors’ Internet addiction and experts’ analysis opinions, adopted the grounded theory qualitative analysis method, studied the influential factors, behavioral characteristics, adverse consequences and coping strategies of the seniors’ Internet addiction, and constructed a behavioral model and a coping model of Internet addiction among the seniors. [Result/Conclusion] Individual factors (needs and abilities) and contextual factors (IT factors and living factors) jointly affect the formation of the seniors’ Internet addiction behaviors. It is necessary to adopt the multi-subject linkage and collaborative governance, adopt the strategies of satisfying the needs of emotional relationship, promoting the seniors’ digital inclusion, transforming the Internet care for the seniors and optimizing the seniors’ living space, so as to guide the seniors to use the Internet correctly and build an age-friendly digital inclusive society.

With the popularization of massive open online courses (MOOCs) in the e-learning landscape, more and more older adults are participating in MOOC learning activities. Understanding older adults' learning motivations in MOOCs will help MOOC developers design suitable learning systems and appropriate course content for older learners. Using a content analysis method, this study identifies six types of learning motivations of older adults in MOOCs: solving problems, acquiring knowledge, improving cognition, seeking fun, benefiting others, and social contact, among which improving cognition is unique to older adults. Based on the above classification, we found that the learning motivations among older adults vary with age and gender. The findings enrich the theories of education for older adults and of learning motivation, and can be used to improve the design of MOOCs for older adults.

With the development of the sharing economy, online ride-sharing has become a primary form of commuting. Using secondary transaction data, this study investigates the associations between the heterogeneous features and mutual trust in sharing economy-driven online ride-sharing transactions. Based on an examination of 12,404 ride-sharing orders in Beijing, we propose a set of trust distribution maps using order location data to reveal heterogeneous spatial patterns of the relationship between online ride-sharing transactions and mutual trust. The results show that the historical order completion rate and order distance are positively associated with mutual trust in ride-sharing transactions, whereas order time and departure density negatively and significantly influence mutual trust. Furthermore, we use machine learning algorithms to predict trust. The implications for theory and practice and future research directions are discussed. [ABSTRACT FROM AUTHOR]

Effective inter-agency information sharing can facilitate the internal administration and external service delivery of government agencies, as well as help them address some complex social issues and then promote social development. Thus, how to promote the success of inter-agency information sharing has attracted the attention of researchers and public administrators. A lot of research has investigated the influential factors of inter-agency information sharing; however, few studies have taken account of the governmental administrative systems, which may influence the collaborations among agencies. Given the composition of the Chinese governmental administrative systems, this study investigated and compared the factors that influence the inter-agency information sharing in vertical and horizontal dimensions. An extended technology–organization–environment (TOE) framework was used to organize the influential factors. The results show that marked differences in influential factors between vertical and horizontal inter-agency information sharing indeed exist. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is an ongoing global pandemic, which has caused global social and economic disruption. In addition to physical illness, people have to endure the intrusion of rumors psychologically. Thus, it is critical to summarize the correlating infodemic, a significant part of COVID-19, to eventually defeat the epidemic. This article aims to mine the topic distribution and evolution patterns of online rumors by comparing and contrasting COVID-19 rumors from the two most popular rumor-refuting platforms—Jiaozhen in China and Full Fact in the United Kingdom (UK)—via a novel topic mining model, text clustering based on bidirectional encoder representations from transformers (BERT), and lifecycle theory. This comparison and contrast can enrich the research of infodemiology based on the spatio-temporal aspect, providing practical guidance for governments, rumor-refuting platforms, and individuals. The comparative study highlights the similarities and differences of online rumors about global public health emergencies across countries. [ABSTRACT FROM AUTHOR]

Online health communities (OHCs) are important online health communication channels for older adults with diabetes to access health information. When seeking health information, they often disclose a variety of contextual information (e.g., socio-economic situations) in their questions. Selective contextual information disclosure is a type of communication strategy for users in OHCs to elicit replies from others. In this study, we adopted text analysis to investigate what contextual information older adults with diabetes disclose to articulate their information needs and used the fixed-effect Poisson model to examine the relationships between different types of contextual information disclosure and informational support receipt. Our analyses were based on a dataset of 4,505 questions and corresponding replies from an online diabetes community. The results showed that cognitive information is the most frequently disclosed contextual information, while older adults tend to disclose demographic information in their questions less. Providing demographic and situational details in questions can enhance informational support receiving, resulting in an increased number of informational supports. However, disclosing cognitive, affective, informational channels, or support information does not significantly affect the informational support receiving. These findings can contribute to extending our existing understanding of information seekers’ communication strategies in OHCs. [ABSTRACT FROM AUTHOR]

Intensifying competition in recent times requires business‐to‐consumer (B2C) e‐commerce platforms to develop operational agility for competitive advantage. Despite the agreement on an increasing competitive landscape, the process for realising information technology (IT)‐driven operational agility on e‐business platforms has received little scrutiny. Through an investigation of M.com, a leading multisided online retailing platform in China, this study provides a clear thesis of resource interdependencies and IT‐enabled capabilities forged during operational processes to realise operational agility. Our investigation, observations, and reflections from practice substantiate a model of how a platform like M.com cultivates IT‐driven resource‐interdependent competencies and capabilities tantamount to realising operational agility. The model shows how IT enables three capabilities—localised, synergistic, and optimised—which reflect the effective co‐ordination of three resource interdependencies (pooled, sequential, and reciprocal) during M.com's complex operations and processes, and explicates the consequences. For research, we postulate that IT‐enabled operational agility in complex organisational forms, cultivated through the development of resource‐interdependent capabilities to deliver effective sensing and response mechanisms, forms effective strategies for the B2C platform in dynamic marketplace conditions. [ABSTRACT FROM AUTHOR]

In aspect-based sentiment analysis, a fundamental task is extracting aspect terms from opinionated sentences. Aspect term extraction (ATE) has been found to play a critical role among several scenarios, such as service quality improvement and recommendation systems. While deep learning-based methods have achieved great progress in ATE, they mainly consider sequential semantic information and generally ignore the utilisation of syntactic relations of the whole sentence on overall meanings. Furthermore, performances of these methods may also be diminished by poor handling of relation and text noises. To address these issues, we propose a fused sequential and hierarchical representation (FSHR) model, wherein both sequential and hierarchical representations are generated, which facilitates not only the capture of linear semantic information for predicting meaning-related aspect terms but also the utilisation of syntactic relations over the entire sentence to better identify structure-related aspect terms. Moreover, to refine the aspect representation, we incorporate relation-gate mechanism which selectively activates meaningful syntactic dependency paths and design the multi-way aspect attention which prompts the model to focus on relevant text segments about particular aspects. Eventually, sequential and hierarchical representations are adaptively fused for aspect prediction. Experiment results on four datasets demonstrate that FSHR outperforms competitive baselines, and further extensive analyses reveal the effectiveness of our model. [ABSTRACT FROM AUTHOR]

Technology is the catalyst for sustainable development. In this context, a key challenge for technology organizations is to balance sustainable development with conventional, profit-driven development. However, despite its significance, such a balance has largely been overlooked in the extant literature. In this study, we examine this balance through the novel lens of ambidexterity in order to understand how it is achieved. Accordingly, we conducted a case study at China Mobile, the world's largest telecommunication company, which recently launched a comprehensive Green-IT program with impressive results. Our study focused on four major stakeholders of the program: Top Management Team, Business Units, Supplier Network, and Customer Network. Two models were later derived by means of synthesized analyses of these four stakeholders: the process model, consisting of four phases, depicts an incremental and iterative development process and defines a step-by-step guideline to achieving a sustainable and profitable balance; the integrated model, consisting of four types of ambidexterity, delineates collective actions of the four major stakeholders and defines an overall guideline for them to collaborate. Both models are, to our best knowledge, the first of their kind in this new research field of sustainability and provide significant insights for future exploration. [ABSTRACT FROM PUBLISHER]

Background: Online health care services effectively supplement traditional medical treatment. The development of online health care services depends on sustained interactions between health care professionals (HCPs) and patients. Therefore, it is necessary to understand the demands and gains of health care stakeholders in HCP-patient online interactions and determine an agenda for future work.Objective: This study aims to present a systematic review of the antecedents and consequences of HCP-patient online interactions. It seeks to reach a better understanding of why HCPs and patients are willing to interact with each other online and what the consequences of HCP-patient online interactions are for health care stakeholders. Based on this, we intend to identify the gaps in existing studies and make recommendations for future research.Methods: In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a systematic retrieval was carried out from the Web of Science, PubMed, and Scopus electronic databases. The search results were confined to those papers published in English between January 1, 2000 and June 30, 2018. Selected studies were then evaluated for quality; studies that did not meet quality criteria were excluded from further analysis. Findings of the reviewed studies related to our research questions were extracted and synthesized through inductive thematic analysis.Results: A total of 8440 records were found after the initial search, 28 papers of which were selected for analysis. Accessibility to HCPs, self-management, and unmet needs were the main triggers for patients to participate in online interaction. For HCPs, patient education, career needs, and self-promotion were the major reasons why they took the online approach. There were several aspects of the consequences of HCP-patient online interactions on health care stakeholders. Consequences for patients included patient empowerment, health promotion, and acquisition of uncertain answers. Consequences for HCPs included social and economic returns, lack of control over their role, and gaining more appointments. HCP-patient online interactions also improved communication efficiency in offline settings and helped managers of online health care settings get a better understanding of patients' needs. Health care stakeholders have also encountered ethical and legal issues during online interaction.Conclusions: Through a systematic review, we sought out the antecedents and consequences of HCP-patient online interactions to understand the triggers for HCPs and patients to participate and the consequences of participating. Potential future research topics are the influences on the chain of online interaction, specifications and principles of privacy design within online health care settings, and roles that sociodemographic and psychological characteristics play. Longitudinal studies and the adoption of text-mining method are worth encouraging. This paper is expected to contribute to the sustained progress of online health care settings. [ABSTRACT FROM AUTHOR]