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With a growing number of older workers in the labor force, cultivating an age-friendly working environment becomes increasingly important. Inspired by the job demands–resources (JD-R) model, this study aims to investigate whether the negative effects of perceived age discrimination (PAD) on work-related outcomes would be explained by job resources and demands.

A total of 333 Hong Kong Chinese employees aged 40 and above (M = 46.62, SD = 6.21; 60% female) completed an online survey that covered measures on workplace age discrimination, job resources and demands, work engagement, intention to stay and work strain.

PAD at work was associated with reduced job resources and increased job demands. The results of the mediation analyses showed support from supervisor and coworkers could account for the effects of PAD on work engagement and intention to stay, whereas emotional demand or workload could explain the effects of PAD on work engagement and work strain.

The findings of this research unveil the underlying mechanisms between age discrimination and work-related outcomes through job resources and job demands. Cultivating a supportive organizational climate toward older employees and offering awareness-based training programs are necessary to mitigate age biases in the workplace.

Building on the JD-R model, this study revealed the possible mechanism underlying the negative effects of PAD. Perceptions of age discrimination decrease older workers' job resources and increase their job demands, subsequently lower their work engagement and intention to stay and increase their work strain.

Conventional electric heaters mostly use U-shaped electric heating tubes and the hollow tube electric heaters are new type ones that rely on the heat transfer tubes as heating elements. However, in the original design, the fluid flows through the annular gaps between the shell wall and the supporting plates, the chambers between supporting plates are generally stagnant zones. The purpose of study is to overcome these deficiencies.

A modified approach is proposed in which the heating tubes are surrounded by holes on the supporting plates, thus the stagnant flow zone can be eliminated and the heating surfaces of both inside and outside the tube can be fully used. Numerical simulations were carried out on four schemes of hollow tube electric heaters, i.e. plate blocked, countercurrent, parallel and split. The results show that the two schemes of parallel and split can reduce the temperature difference between the two sides of the fixed tube plate, and thus reduce thermal stress and prolong the service life.

The split scheme of electric heater has the highest comprehensive index, moderate heat transfer coefficient and minimum pressure drop on the shell side. Its average heat transfer coefficient and comprehensive index are, respectively, 15.7% and 52.9% higher and its average pressure drop and tube wall temperature are, respectively, 57.6% and 19 K lower than those of the original plate blocked scheme, thus it can be recommended as the best scheme of the hollow tube electric heaters.

Based on the original design of hollow tube electric heater with plate blocked scheme, three plate perforated schemes were proposed and investigated. The thermal and flow features of the four schemes were compared in terms of heat transfer coefficient, pressure drop and comprehensive index h_o·Δp_o^−1/3. The split scheme can reduce the temperature difference between two sides of the fixed tube plate with reduced thermal stress. It has moderate tube wall temperature and heat transfer coefficient, the smallest shell side pressure drop and the highest comprehensive index h_o·Δp_o^−1/3, and it can be recommended as the optimal scheme.

This study aims to assess the level of development of the digital economy by constructing a comprehensive measurement system. It explores regional differences within China’s digital economy, highlighting the varying degrees of digital infrastructure, industrialization, governance and innovation capabilities across provinces.

A multidimensional analytical framework including digital infrastructure, industrialization, digitization, governance and innovation was developed. Entropy methods were used to calculate the weights of each dimension. The coupled coordination degree model and the Tobit model with random effects panel are applied to analyze the current situation, discrepancies and influencing factors.

This study reveals significant regional differences in the development of China’s digital economy, characterized by a pattern of “strong in the east, weak in the west; high in the south, low in the north.” This geographical imbalance exacerbates the “polarization effect” and the “siphon effect,” where resources and growth tend to concentrate in already developed areas, further intensifying regional inequalities. The development of the digital economy is driven by principles of innovation, coordination and sharing, which facilitate the creation and dissemination of new technologies and collaboration across different sectors. However, this progress is also constrained by considerations of environmental sustainability (green) and economic openness.

This paper contributes to the body of knowledge by providing a novel multidimensional measurement system for the level of digital economy development. The unique application of the coupled coordination degree model and Tobit model to analyze regional differences and influencing factors provides insights into the dynamics of China’s digital economy.

The paper proposes a research method to verify the perception bias of consumers on the freshness preservation effects of vacuum packaging (VP) and modified atmosphere packaging (MAP) chilled pork packages, the influence of “sensory experience” on correcting consumers' perception bias of packaging performance and willingness-to-pay (WTP) enhancement channels.

Using data from 458 and 188 participants who completed the contingent valuation method (CVM) and auction experiment, respectively, the study aimed to uncover consumers' packing quality perception bias and WTP, and investigated the societal factors that contribute to variations in WTP.

The CVM experiment revealed that although consumers' high perception bias rate toward MAP to maintain freshness, as compared to lab test results, came along with low WTP premium to cost rate with sensory experience in the auction experiment, the proportion of consumers with quality perception bias decreased from 49.85% to 34.46%, while the WTP premium to cost rate for MAP increased largely by 36.7%. Perceptive embedding has a positive effect on chilled pork packaging WTP, while normative embedding decreases WTP.

The findings emphasize the need of public policies to promote positive consumption attitudes, while whittling the negative consumption norms, to increase the WTP for packaged child pork and promote the chilled pork market formation.

Fake news in cyberspace has greatly interfered with national governance, economic development and cultural communication, which has greatly increased the demand for fake news detection and intervention. At present, the recognition methods based on news content all lose part of the information to varying degrees. This paper proposes a lightweight content-based detection method to achieve early identification of false information with low computation costs.

The authors' research proposes a lightweight fake news detection framework for English text, including a new textual feature extraction method, specifically mapping English text and symbols to 0–255 using American Standard Code for Information Interchange (ASCII) codes, treating the completed sequence of numbers as the values of picture pixel points and using a computer vision model to detect them. The authors also compare the authors' framework with traditional word2vec, Glove, bidirectional encoder representations from transformers (BERT) and other methods.

The authors conduct experiments on the lightweight neural networks Ghostnet and Shufflenet, and the experimental results show that the authors' proposed framework outperforms the baseline in accuracy on both lightweight networks.

The authors' method does not rely on additional information from text data and can efficiently perform the fake news detection task with less computational resource consumption. In addition, the feature extraction method of this framework is relatively new and enlightening for text content-based classification detection, which can detect fake news in time at the early stage of fake news propagation.

Batteries installed on electric vehicles (EVs) should normally be removed when their capacity falls to 70-80 per cent, but they are still usable for other purposes, such as energy storage. This paper studies an EV battery closed-loop supply chain (CLSC) consisting of a battery manufacturer and a remanufacturer. The manufacturer produces new batteries by using natural resources, while the remanufacturer collects returned batteries and makes decisions based on the return quality, that is, to reuse or recycle. The purpose of this paper is to maximise the individual profits through optimising the amount of manufacturing and remanufacturing, respectively, and optimising the purchase price of returned batteries.

Based on the Nash equilibrium, this paper develops a three-period model in the CLSC. In period 1, batteries are made from raw materials; in period 2, returned batteries from period 1 are sorted into low quality and high quality. Some high-quality returns can be reused for other purposes while those non-reusable returns are recycled into materials. In period 3, all the returns are recycled into materials. The analytical results are derived.

The result of the analyses suggest that first, among the variables that affect the (re-)manufacturing decision, the purchase price for returned batteries plays a critical role. In particular, the price of low-quality returns has more influence than the price of high quality returns. Second, the higher purchase price for re-usable returns does not necessarily lead to a higher return rate of reusable returns. Third, the manufacturer’s profit is normally higher than the remanufacturer’s. This suggests the need to design incentives to promote the remanufacturing sector. And finaly, although it is appreciated that maximising the utilisation of batteries over the life-cycle would benefit the environment, the economic benefit needs further investigation.

Although the CLSC has been widely studied, studies on the EV battery CLSC are scarce. The EV battery CLSC is particularly challenging in terms of the reusability of returns because used EV batteries cannot be reused for the original purpose, which complicates CLSC operations. This paper explores the interrelationship between manufacturer and remanufacturer, explaining the reasons why recycling is still underdeveloped, and suggests the possibility of enhancing remanufacturing profitability.

The purpose of this paper is to investigate why users are willing to diffuse healthcare knowledge in social media by drawing on the communicative ecology theory (CET) and prior research on interpersonal communication.

This paper conducts a large-scale scenario-based online survey in WeChat (the most popular social media platform in China) to test the proposed research model and hypotheses. The final data set consists of 1,039 useful responses from WeChat users.

The results indicate that interestingness, emotionality and institution-based trust are the strongest antecedents in predicting healthcare knowledge-diffusing likelihood, followed by usefulness, source credibility and positivity. Further, the relationship between institution-based trust and healthcare knowledge-diffusing likelihood is partially mediated by source credibility.

Healthcare practitioners who seek to motivate individuals to disseminate healthcare knowledge need to phrase or frame healthcare knowledge in a way that draws greater interest, evokes stronger emotion, increases perceived usefulness or reflects positively on themselves. Healthcare organizations should also pay attention to strengthening users’ trust in the platform and source-related information that can indicate source authority.

This study is one of the first to investigate the dissemination of healthcare knowledge in the context of social media (WeChat in particular). Compared with other types of information, healthcare knowledge is more scientific and professional to the extent that most laypersons do not have relevant expertise to directly evaluate whether the content is credible and of high quality. Rather, their sharing likelihood is dependent more on other factors than perceived information quality and credibility; those factors include platform-related factors that may play an important role but has been overlooked in prior literature on interpersonal communication. By combining CET with interpersonal communication-related research and including institution-based trust as an important determinant of healthcare knowledge dissemination, this study provides a comprehensive analysis of healthcare knowledge diffusion process.

This study investigated employees’ career planning in preparation for the impact of manufacturing transformation triggered by automation technology. Built on career construction theory, the purpose of this paper is to conceptualize career planning as an attempt to integrate oneself into the social environment. In this process of integration, career adaptability is a critical psychological resource for adaptation to anticipated changes.

Through an online survey, 476 participants answered questions regarding the following aspects: perceptions of the threats and opportunities posed by automation technology; career adaptability, that is, career-related concern, control, curiosity, and confidence in adapting to occupational transitions; and career plans and actions to address the challenge, including short-term job crafting behaviors and long-term career adjustment plan.

The results showed that opportunity and threat perceptions were associated with one’s job crafting behavior and long-term career adjustment plan and such relationships were moderated by career adaptability and work experience relevant to automation technologies. Specifically, career adaptability is a psychological resource helping individuals deal with perceived challenges, while relevant work experience moderated one’s strategies to catch opportunities.

This study contributes to the understanding of psychosocial determinants for better career planning in the midst of the industrial revolution. Policies that aim to prepare workers for the upcoming social transition may benefit from this study to leverage adaptive and proactive behaviors at a societal level.

This study embraces the call for exploring the determinants of continuous intention in TikTok. Taking the perspective of social influence, this study not only tries to explore the contextual sources of two types of social influence but also aims to unveil the influence mechanism of how social influence affects TikTok viewers’ continuous intention.

This study empirically analyzes how TikToker attractiveness, co-viewer participation, platform reputation and content appeal affect informative and normative social influence and then lead to the continuous intention of TikTok. Based on 547 valid survey data, this study adopts a mixed analytical approach for data analysis by integrating structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA).

SEM results unveil that content appeal is the most critical antecedent of informational social influence, while the TikToker attractiveness and platform reputation have no effect on it. Differently, all four external sources positively lead to normative social influence. Among them, content appeal and co-viewer participation influence the most. The influences of both two types of social influence on continuous intention are demonstrated. FsQCA results reveal seven alternative configurations that are sufficient for influencing continuance intention and further complement and reinforce the SEM findings.

Addressing the critical contextual elements of TikTok, this study explores and confirms the sources which may engender social influence. The authors also demonstrate the critical role of social influence in affecting TikTok viewers’ continuous intentions by the hybrid analytical approach, which contributes to existing academic literature and practitioners.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.