When we’re old and wise

China is facing a rapidly ageing population, with almost a quarter of its population over the standard retirement age in many regions of 60 years. This coincides with a declining birth rate and given more flexible retirement policies, the workforce itself is getting older. Research in the International Journal of Economics and Business Research recognises that within this workforce, older, experienced knowledge workers are a growing human resource asset. Understanding their needs and ensuring they are not so disenfranchesed that they take retirement as early as possible is now high on the organisational agenda and a critical part of modern management.

The research emphasises career capital, a concept that brings together human capital, social capital, and decision-making capital. Human capital refers to an individual’s skills, knowledge, and experience. Social capital encompasses professional networks and relationships. Decision-making capital involves accumulated judgement and problem-solving abilities. The research found that these all contribute to ongoing professional effectiveness in the later stages of employment.

Two psychological factors specifically were identified as important in mediating the relationship between career capital and workplace success: self-efficacy and job crafting. Self-efficacy is an individual’s belief in their abilities, while job crafting refers to the adjustment they make to tasks and work relationships to align with personal strengths and interests. The accumulation of skills, networks, and decision-making abilities are all fully realised when older employees feel capable and empowered to shape their roles.

In an effort to ensure older employees are not disenfranchised and continue to play an important role, the researchers suggest that the various dynamics at play need to be integrated into a new model of human resource management. This model should pay attention to different forms of career capital, activation of self-efficacy and adaptability, and flexible organisational support strategies tailored to age-specific needs. If such an approach is implemented, organisations will be able to sustain productivity, encourage innovation, and preserve the professional value of older knowledge workers.

Wei, J-l. and Chen, C-s. (2026) ‘Exploring the impact of older knowledge workers’ career capital on career success: with self-efficacy and job crafting as mediators and perceived organisational support as a moderator’, Int. J. Economics and Business Research, Vol. 30, No. 1, pp.1–28.

Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• An AI-driven dual neural network framework for enhancing and evaluating university teachers' informatisation teaching capacity under TPACK
• Gradient optimisation and cross-language transfer mechanism of English translation model based on LSTM-transformer
• Emotions and dissemination trends of Sichuan handicraft intangible cultural heritage inheritance groups based on ALBERT and TCN
• Deep learning-based automatic labelling of English syntactic variation and cross-dialect comparison
• Real-time health-aware emergency optimisation scheduling under fault scenarios in PV-fuel cell microgrids

Free sample articles newly available from International Journal of Happiness and Development

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• Exploring the emotional terrain: a comprehensive systematic literature review of the effects of emotional intelligence on stress and performance
• Psychometric assessment of the Persian version of the future time perspective questionnaire in college students
• Happy-NE-R leadership for companies in emerging economies
• Impact of income on life satisfaction in India: a generalised ordered probit model approach

New Open Access article available: "Exploring artificial intelligence adoption among Italian firms: the AI readiness level"

The following International Journal of Business Information Systems article, "Exploring artificial intelligence adoption among Italian firms: the AI readiness level", is freely available for download as an open access article.

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Research pick: AI second guess that emotion - "Aspect-level sentiment classification with emotional keywords attention network"

Research in the International Journal of Computational Intelligence Studies has looked at how we might improve artificial intelligence (AI) systems for interpreting human emotion in written communication. The new system is capable of identifying sentiment not only in broad terms, positive, negative, and neutral, but also at a more detailed, aspect-specific level.

Sentiment analysis usually evaluates entire sentences or documents as a single unit. This can hide the subtleties of human expression. For instance, a restaurant review may praise the food while criticising the service. Previous AI models could struggle to separate these differing opinions, often assigning a generalised sentiment score. The new model overcomes this limitation by emphasising emotionally charged keywords, the words that carry the most significant emotional weight in a sentence. It does this using an attention network, a computational mechanism that allows AI to prioritise certain inputs over others.

This focus on the most emotional terms in a piece of text allows the AI to classify sentiment directed at specific aspects of a text. In the restaurant example, the model can distinguish the positive sentiment aimed at the food from the negative sentiment about the service, producing a more nuanced interpretation. Moreover, the system’s ability to pay attention to the most emotionally charged words is a useful advance in natural language processing.

Such a tool could help businesses that rely on customer feedback, social media analysis, and online reviews. With it a company could spot concerns being discussed online as they arise and so make a timely response to help manage their image and refine their marketing. They might even be able to offer targeted responses to individuals or groups to improve customer satisfaction and perception.

This research is part of a growing trend in AI research towards improving the way in which computers interpret language and emotion. By enabling machines to analyse sentiment at the level of individual aspects rather than entire texts, this approach contributes to the development of more perceptive, context-aware AI.

Yuan, Z. and Yuan, J. (2026) ‘Aspect-level sentiment classification with emotional keywords attention network’, Int. J. Computational Intelligence Studies, Vol. 13, No. 5, pp.1–13.

New Open Access article available: "Integrating IoT and machine learning for scalable anomaly detection in smart city infrastructure"

The following International Journal of Critical Infrastructures article, "Integrating IoT and machine learning for scalable anomaly detection in smart city infrastructure", is freely available for download as an open access article.

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Free Open Access special issue on "Achieving Carbon Neutrality from Environmental Impact Monitoring and Assessment Technologies – Part II" published by International Journal of Environment and Pollution

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• Green logistics distribution route algorithm based on carbon emissions optimisation
• Using soil water content and energy balance model to promote sustainable development of green and low-carbon economy
• Carbon reduction coordination and pricing strategy of a four-level supply chain under demand uncertainty
• Evaluation of petroleum safety management system based on embedded intelligent image sensor
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• Environmental risk assessment and early warning system construction for forest tourism sites under the background of climate change

New Open Access article available: "Business perspectives on value co-creation as a mediator for entrepreneurial performance in educational contexts"

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New Open Access article available: "Sectoral total factor productivity and its determinants: firm-level evidence from Kazakhstan"

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Research pick: Is the AI black box right on time? - "Artificial intelligence’s effect and influence on multiple disciplines and sectors"

Irrespective of the ethics and the apocalyptic predictions, artificial intelligence (AI) has already become a central component of economic and institutional decision-making. Research in the International Journal of Intelligent Systems Design and Computing has gone beyond an industry-specific analysis of the state-of-the-AI-art and offers a detailed framework of how the many different AI tools are being adopted.

The main point that arises from the analysis is that while AI technologies are being used widely across sectors, organizations do not yet have a strategy that allows AI to be integrated in a way that balances innovation with accountability.

AI encompasses so-called machine learning for recognising patterns in data, natural language processing that can interpret and human language, and generative tools that produce text, images, video, computer code, and other output. All these tools are changing many sectors from healthcare diagnostics to processing industrial and financial data, to produce hit pop songs and accompanying videos.

Education and business operations are undergoing similar shifts. Adaptive learning platforms in education adjust course material to suit the way individual students learn. In retail and logistics, AI is being used to refine supply chains, manage inventory, and personalize the customer “experience”. Even in the world of law, law enforcement is using AI to assess crime scenes and weigh evidence, while judges are using these tools to summarise their concluding remarks from massive briefs.

One of the most pressing issues highlighted by the research is data privacy, as AI systems depend on large volumes of often sensitive and personal information. In addition, there is the notion of algorithmic transparency, wherein we are are losing the ability to understand how a given AI system is arriving at a specific decision. Indeed, many of the most advanced AI models now work essentially as black boxes, meaning their internal processes simply cannot be interpreted…perhaps without resorting to another AI to do the interpretation! Such a lack of transparency might undermine trust in high-stakes contexts such as medical diagnoses or judicial decisions.

To address the issues, the researchers propose a framework based on stakeholder theory, which maintains an emphasis on the importance of all parties affected by the decisions AI might make. In the business context, they stress that organisations should bot focus solely on efficiency or profit, they must have perspective that them to weigh the interests of employees, customers, regulators, and society at large when adopting AI. This might only come about, of course, with governance, regulations, and ethical obligations.

Idemudia, E.C. (2025) ‘Artificial intelligence’s effect and influence on multiple disciplines and sectors’, Int. J. Intelligent Systems Design and Computing, Vol. 3, Nos. 3/4, pp.254–274.

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• The moderating role of entrepreneurial orientation on the effect of knowledge management capabilities on organisational performance
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• Pitfalls in effective knowledge management: insights from an international information technology organisation
• What do we actually hide: conceptual and measurement challenges of knowledge hiding research

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• MVRO-based DRNN: multi-verse rider optimisation-based deep recurrent neural network for intrusion detection in latency constrained cyber physical systems
• Digital traceability system for road crude oil transport: the Tunisian case
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• Hybrid multi-agent framework for green supply chain management
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Research pick: Boosting self-efficacy to cope with workplace social undermining - "Self-efficacy as the saviour: defending psychological well-being against the destructive power of social undermining"

A study of more than 500 employees in the fast-moving consumer goods sector has demonstrated how employers might mitigate social undermining in the workplace. Social undermining is a pattern of behaviour in which colleagues or supervisors hinder an individual’s performance or professional relationships. This might include withholding critical information, spreading rumours, or criticising colleagues in a public setting. Unlike overt harassment, such actions are often subtle and cumulative, gradually weakening an employee’s capacity to function effectively within a team.

Social undermining leads to stress, anxiety, and burnout. Such problems are not only detrimental to the employee being targeted but are also linked to reduced productivity and higher staff turnover within an organisation.

The research looks at self-efficacy, an individual’s belief in their own abilities. The team found that self-efficacy acts as a psychological buffer so that those who have greater self-efficacy are less likely to succumb to the effects of social undermining. The work also found that hostility from supervisors had a more pronounced emotional impact than similar actions by peers, but strong self-efficacy could buffer targeted individuals even more effectively in such situations.

Fundamentally, employees with greater confidence in their abilities were more likely to interpret negativity from supervisors as a challenge to be managed rather than as evidence of personal failure. This personal reframing of issues reduces the psychological toll of that kind of interaction for those individuals.

In contrast, negativity from peers affects social standing and workplace relationships, making it more difficult for even those with the greatest level of self-efficacy to cope with such issues. In these cases, the harm is less about task performance and more about belonging and reputation within a group.

The findings suggest that employers might address toxic behaviour in the workplace by strengthening how well their employees can cope given that some degree of interpersonal conflict is inevitable in any organisation and might not always be something that can be stopped directly. By promoting the development of personal resources and self-efficacy, they may have a more practical way to intervene without recourse to disciplinary approaches.

Tosun, B., Güner Kibaroğlu, G. and Basim, H.N. (2026) ‘Self-efficacy as the saviour: defending psychological well-being against the destructive power of social undermining’, Middle East J. Management, Vol. 13, No. 2, pp.137–159.

Free Open Access issue published by International Journal of Economics and Business Research

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• Credit control and firm performance: evidence from Vietnam's listed real estate sector with firm size and corporate governance quality as moderators
• Modelling entrepreneurial passion, self-leadership and resilience as drivers of innovative behaviour among SMEs: a social cognitive theory perspective from Indonesia
• Expert-elicited weights in multi-criteria decision analysis: theory and practice

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• Blockchain governance: reducing trusted third parties with Decred project
• Tokenisation approaches on blockchain: state-of-the-art and classification framework
• Users' satisfaction evaluation based on ISO standards for tourism and travel mobile applications
• The personalised classification of brand promotion information based on K-means algorithm
• Multi-level secure storage method of electronic documents based on Hash function
• A performance evaluation method of new business model based on grey correlation algorithm
• Research on digital English teaching materials recommendation based on improved machine learning
• An enterprise financial credit risk measurement method based on differential evolution algorithm
• A recognition method of abnormal learning behaviour in MOOC online education based on background subtraction
• An evaluation method of government digital service quality based on big data
• Performance evaluation method of human resource management based on chaotic algorithm
• A data integrity detection method for accounting informatisation based on homomorphic hash function
• New business management model of enterprises based on data-driven

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• AdaptTrans: a complexity-aware iterative optimisation framework for efficient code translation
• Intelligent physical health testing method integrating Fast-OpenPose and BlazePose
• Hydrogen refuelling docking control driven by multi-scale perception and task decoupling
• English deep semantic understanding and generation technology integrating knowledge graph and natural language processing
• Multi-track symbolic music generation algorithm based on diffusion model and music structure constraints

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• Monitoring and actuating devices for analysis of the new security protocols of Internet of Things
• Bidirectional LSTM and self-attention mechanisms based multi-Label sentiment analysis
• A novel approach for enhancing mammographic images
• Application of deep convolutional neural networks systems in autonomous vehicles
• A collaborative approach for testing MapReduce access control issues using agent-based architecture
• Cardiovascular disease prediction using hybridisation multi perception classifier in secure IoT platform

Research pick: Dodging the distro inferno - "Fire warning of lithium battery energy storage power stations for environmental sustainable development"

A new fire detection system designed for lithium battery energy storage facilities described in the International Journal of Environmental Technology and Management could improve safety in the renewable energy sector.

Electricity generation that uses intermittent energy sources, such as wind and solar, relies on large-scale rechargeable batteries for storage. Unfortunately, a phenomenon known as thermal runaway is a well-known issue with lithium batteries. It refers to the feedback that occurs when battery temperature rises, triggering chemical reactions that generate further heat and so on. Thermal runaway can lead to catastrophic fire or explosion, causing damage to infrastructure and releasing hazardous substances, including toxic gases and heavy metals, into the surrounding environment.

The new approach discussed in IJETM addresses the risk through a more responsive and reliable method of fire detection. It uses a combination of sensors to monitor key indicators of potential failure, including temperature changes, smoke levels and the presence of carbon monoxide.

The system integrates these multiple data streams using a mathematical approach known as Dempster–Shafer evidence theory instead of using a single measurement. The framework works with uncertain or incomplete information from different sources and so can make reliable judgements on whether the system is stable or on the verge of catastrophic failure. In so doing, it reduces the number of false alarms and improves detection of genuine fire risk. The processing unit analyses the data in real time and can trigger an alarm and response within two seconds with over 95 per cent accuracy. Both response time and accuracy improve on earlier systems.

The same multi-factorial approach might be used in other sectors that rely on interconnected, sensor-driven technologies, including industrial safety monitoring, transportation networks, and urban infrastructure, where early detection of anomalies can prevent accidents and improve efficiency.

Deng, D.L. and Du, X.C. (2025) ‘Fire warning of lithium battery energy storage power stations for environmental sustainable development’, Int. J. Environmental Technology and Management, Vol. 28, Nos. 4/5/6, pp.355–366.

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Research pick: Balancing ecology and industry in China - "Marine ecological governance and green development in Beibu Gulf of Guangxi under the digital context"

A new study of the vast Guangxi Beibu Gulf Marine Region (GBGMR) in southern China takes a close look at how environmental limits are being stretched by economic growth. It highlights the disparities between provinces and asks how more effective environmental policies might be put in place across different parts of the region.

The GBGMR is an important coastal zone spanning several provinces. It lies along southern China’s coast on the Beibu Gulf near the border with Vietnam. It acts as an ecological barrier stabilising environmental conditions as well as supporting fisheries, water supply, and industry. The GBGMR encompasses an incredibly varied geography but represents an uneven distribution of natural resources. Both these factors make it especially vulnerable to all kinds of pressures from human activity.

Research in the International Journal of Global Energy Issues has shown that while the region currently operates within what we might call environmental limits, the buffer zone is steadily shrinking based on an assessment of its Ecological Carrying Capacity (ECC). ECC is a measure of an ecosystem’s ability to support human activity without causing long-term damage to the natural environment. In their study, the team combined two indicators of impact: carbon footprint and water footprint.

Their analysis shows clear variation across regions in the GBGMR and over time. Provinces that depend on energy-intensive industries, such as coal and chemicals, face much higher ecological stress whereas areas that have diversified are more resilient and can maintain a better balance between growth and environmental limits.

The findings could help guide policymakers so that locally pertinent regulations are put in place instead of blanket measures. The team suggests that regions with high emissions should accelerate the move to sustainable energy, while water-scarce areas should prioritise conservation and move away from water-intensive industries.

Song, H., Wang, X., Zhao, J., Yuan, S. and Yu, J. (2026) ‘Marine ecological governance and green development in Beibu Gulf of Guangxi under the digital context’, Int. J. Global Energy Issues, Vol. 48, No. 7, pp.1–20.

Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• An intelligent decision support framework for financial market risk using big data and optimised XGBoost
• Optimisation of vocal music teaching strategy in colleges and universities based on neural network
• Cross-prompt English composition automatic scoring method integrating CNN, LSTM, and attention mechanism
• The solidification effect of airport road bases using an improved BP neural network and visualisation evaluation model
• Semantic analysis and translation optimisation of English sentences using long short-term memory network

New Open Access article available: "Aspect-level sentiment classification with emotional keywords attention network"

The following International Journal of Computational Intelligence Studies article, "Aspect-level sentiment classification with emotional keywords attention network", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Construction and empirical study of a multi-source data fusion model for adolescent health literacy assessment
• Hierarchical fusion of multi-scale features with transformer for crime scene trace identification
• Visual depth models coupled with 3D pose estimation for sports body training evaluation
• Antennas in the oral English test scenario: meta-learning assisted fast reconstruction
• Fuzzy logic-supported automatic error recognition and efficient optimisation in literary writing texts

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• Synthesis of nanopowders Nd2Fe14B by chemical method
• The second quantum revolution: the development of quantum subatomic nanotechnologies
• Planar nanostructures element analysis using the X-ray radiation emission induced by high energy excitation
• Al2O3 nanoparticles synthesis, and a study of its influence on the fire behaviour of nanocomposite materials based on unsaturated polyester resin
• Properties of the nanoemulsions with seed oils
• The effect of the moisture state of samples on the change in the elastic-strength parameters of epoxy polymers during natural climatic ageing
• Behavioural programs can function as biological genes participating in the social evolution
• Computer simulation of the neutralisation of superoxide radicals by the fullerenol-24 nanomolecular system
• Composite materials in a binary CuBr - SbBr3 system
• Synthesis and perspectives of Ag/In2O3 inverse opal
• Predictive protein module based on PPI network and double clustering algorithm

Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Analysis of common error patterns in German software localisation and automated detection tools
• Cross-modal retrieval of Korean intangible cultural heritage multimedia content using deep hashing networks
• Cross-platform adult learning behaviour profiling based on multimodal data fusion
• Harnessing multimodal graph neural networks to predict graduate employment anxiety
• An edge computing system for live-line detection based on multi-sensor data fusion

Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Neural differential equations based diffusion models for high-jump posture prediction
• Convergence criteria for iterative formats in high-dimensional optimisation problems discretised from mathematical partial differential equations
• Federated contrastive learning framework for cross-platform teaching quality assessment
• Multi-element animation generation via memory-augmented self-supervised learning and mixture density networks
• Sentiment analysis of English social media based on transfer learning and semantic enhancement

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Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Intelligent education recommendation under dual constraints: collaborative mechanism of federated architecture and genetic optimisation
• Integrated intelligent management and control system for million-kilowatt photovoltaic stations
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• English video scene semantic parsing technique based on sentence semantics and adaptive feature selection
• Student behaviour analysis and innovative curriculum planning based on apriori-HGNN model

Research pick: The online protection racket - "Personal data protection in the age of digital financial systems"

Research in the journal Electronic Government discusses the growing need for protecting one’s personal financial data as the online world faces increasingly sophisticated cyber threats. The researchers argue that no single measure is sufficient to secure the modern financial ecosystem. As such, they set out a framework that combines technological tools, regulatory oversight, and individual responsibility to combat the problem.

There are three foundational principles in online financial security: confidentiality, integrity, and availability. Confidentiality is about making sure that sensitive information, such as account details and biometrics, is accessible only to authorised users. Integrity involves maintaining the accuracy and reliability of data and blocking unauthorised changes. Availability ensures that only legitimate users can access their financial information and no third party.

The researchers explain that a breakdown in any one of these areas can lead to personal financial loss, reputational harm for institutions, and more broadly, an erosion of trust in digital services.

Phishing, in which attackers pose as legitimate entities to extract sensitive information via a rogue email or website, is the most common digital fraud. Malware, software designed to infiltrate or damage systems, is a close second and continues to evolve to evade antivirus systems and get around firewalls. Insider threats, involving individuals within organisations misusing access, add another layer of risk. Then there are institutional, industrial-scale breaches where data is sold to malicious third parties on the dark web.

Financial institutions operate within stringent regulatory systems to reduce the risks but even with protections in place such as data regulation laws, encryption, multi-factor authentication, and routine security audits, vulnerabilities still exist.

All the protection in the world cannot save users from themselves, though. Even the least naïve digital native can succumb to social engineering or the sleekest of phishing attacks. The researchers suggest that user education is key. Users need to learn about avoiding weak passwords, about not repeating passwords, about how to recognise phishing attempts, and about how to be consistent in their practices online to avoid being caught out.

Kumari, A. (2026) ‘Personal data protection in the age of digital financial systems’, Electronic Government, Vol. 22, No. 2, pp.220–240.