Economic boost from financial inclusivity

Financial inclusion has emerged as a driver of development rather than a secondary outcome, according to research in the International Journal of Intelligent Enterprise. Financial inclusion defines the extent to which individuals and firms have fair, affordable, and reliable access to financial services such as banking, credit, insurance, and equity markets.

The IJIE paper reviewed the research literature in this area and found that a clearer understanding of impact can be drawn if a distinction is made between financial development and financial inclusion. Financial development refers to the size, depth, and efficiency of a country’s financial system, in other words, how effectively it mobilises savings and allocates capital to productive uses. Financial inclusion, by contrast, focuses on who is able to participate in that system. A financial sector can be highly sophisticated while still excluding large parts of the population due to income, geography, gender, and social status.

Various studies show that the effects of inclusion are identified at multiple levels. At the household level, access to formal financial services allows people to save securely, borrow for emergencies or investment, and finance a family member’s education or assist with the startup of a small business. This reduces dependence on informal lending networks, which are often expensive, unstable, and unregulated in the developing world. At the company level, limited access to credit constrains expansion. Businesses without formal finance tend to rely on retained earnings or potentially risky informal borrowing, which restricts productivity growth and innovation.

The research also found a link between financial inclusion and broader distributional outcomes. By widening access to financial tools, groups that were once excluded can build assets and smooth income over time. Ultimately, this reduces inequality and poverty. Numerous papers reviewed also showed that gender inclusion increases female participation in economic activity and leadership roles, which then has an effect on institutional performance and policy design.

Rani, V.S., Sundaram, N. and Prasad Babu, P. (2026) ‘A survey of impact of financial inclusion for various sectors in different countries’, Int. J. Intelligent Enterprise, Vol. 13, No. 2, pp. 128–146.

New Open Access article available: "Empirical study of consumer-to-consumer social commerce users with a structural equation modelling approach"

The following International Journal of Business Excellence article, "Empirical study of consumer-to-consumer social commerce users with a structural equation modelling approach", is freely available for download as an open access article.

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

Free sample articles newly available from European Journal of International Management

The following sample articles from the European Journal of International Managementare now available here for free:

• Blockchain implications for management and international business theories: toward a new paradigm
• Two decades of foreign direct investment in Africa: a systematic literature review, integrative framework, and agenda for future research
• Team climate and performance in global virtual teams: exploring the effects of cultural intelligence and emotional intelligence on team climate satisfaction
• Dynamic capabilities and international performance: a meta-analytic regression analysis
• China's industrial policy and its implications for international business
• Openness towards language differences and cultural differences in multicultural teams: how do they interact?
• How to sample in necessary condition analysis (NCA)
• A state-of-the-art review on international strategic alliances: do we really know what we are researching?
• Global value chains and liability of international connectivity: MNE strategy post COVID-19

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.

• Building energy efficiency intelligent scheduling integrating big data analysis and artificial intelligence
• Brand value fluctuation prediction and risk management of rural characteristic industries based on GAN-LSTM
• Research on multi-view attitude measurement method for shipboard equipment with multiple feature points
• Optimisation of resource scheduling in English translation teaching platform based on greedy heuristic task migration algorithm and corpus
• MICPO: a modified crested porcupine optimiser with dynamic balancing for superior PV parameter accuracy and convergence

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.

• Development of Xiamen's tourism industry based on GIS spatial analysis and grey correlation analysis method
• Personalised knowledge recommendation system for English teaching based on MoE-RAG algorithm
• Data security collaboration mechanism of college student innovation and entrepreneurship education platform combining federated learning and differential privacy
• Dynamic evaluation of professional core OBE based on meta-learning and knowledge distillation
• Joint modelling and governance of knowledge graphs and reasoning rules for vocational skill assessment

Research pick: Predicting HE higher and higher - "Analysis of factors affecting college students’ academic performance based on linear regression"

Academic success at university could depend on the changing interaction between students’ habits over time rather than fixed traits such as intelligence or total study hours. This conclusion is discussed in the International Journal of Computational Systems Engineering in a paper that challenges the conventional methods of predicting and measuring educational success.

In the research, the team looked at why some students consistently perform better than others and have developed a statistical model that treats learning behaviour as dynamic rather than static. The study suggests that standard approaches to educational analysis commonly overlook the fact that student routines, motivation, and workloads change during their time at university. Student habits frequently fluctuate in response to deadlines, stress, extracurricular commitments, and changing levels of engagement. Moreover, these factors influence each other dynamically from term to term, and static models cannot, by definition, take this into account.

The research used an extended linear regression model to estimate how strongly particular variables, such as attendance, study time, and motivation, affect examination results or scores. One of the clearest findings from this kind of analysis involved cramming before examinations. Educational advice often portrays intensive last-minute revision as inherently inferior to consistent long-term study. The study’s findings suggest a more nuanced relationship. Short-term intensive study was associated with stronger immediate improvements in results than long-term study habits alone. However, the researchers stress that cramming was only really effective when supported by stable routines and regular review throughout the term. The study also found that too many extracurricular activities reduced the effectiveness of cramming by limiting both available time and mental energy.

The study raises questions about how educational institutions understand student achievement. Universities frequently rely on static indicators such as attendance rates, exam results, and cumulative study hours when assessing academic potential. The researchers argue that these measures may overlook the importance of timing, behavioural change, and the interaction between short-term and long-term learning strategies.

Huang, R. (2026) ‘Analysis of factors affecting college students’ academic performance based on linear regression’, Int. J. Computational Systems Engineering, Vol. 10, No. 8, pp.1–13.

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

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

• Monitoring and sustainable management of soil microbial environmental quality based on machine learning
• Evaluation of factors affecting expansion of weak-base ASP flooding based on grey correlation analysis combined with BP neural network
• Ecological services and improvement strategies of forest healthcare space environment under the background of carbon neutrality
• Optimisation of rural green supply chain promoting social sustainable development: a case study based on intelligent environmental impact assessment
• Investigation of the coordinated development of carbon emissions, energy, and sustainable growth based on fuzzy system theory
• Optimised bidding strategy for data centres participating in the electrical energy and fast frequency regulation market under the background of carbon peak and carbon neutrality
• Public service system for green and sustainable development in marketing based on blockchain technology

Free Open Access special issue on "Digitalisation, Information Systems and Artificial Intelligence in Business Processing" published by International Journal of Business Intelligence and Data Mining

The International Journal of Business Intelligence and Data Mining has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Prediction of carbon emissions throughout the lifecycle of zero carbon substations based on Lasso-GRNN neural network model
• A comprehensive management method of audit data based on knowledge graph
• Research on safety risk perception of electrochemical energy storage power station under the background of environmental sustainable development
• Study on multimodal ideological and political teaching material push on MOOC online learning platform

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.

• Multi-cluster data mining and analysis of tourist behaviour patterns for scenic area management
• Basketball player tracking method based on multi-source data and attention mechanism
• Optimisation of railway logistics high quality development path based on new quality productivity
• Personalised digital course recommendation system for higher vocational colleges based on deep learning
• LDCIR-Trans: a lightweight dependency-constrained iterative refinement model for machine translation

Research pick: Battery boost - "Bayesian optimised route and SOH estimation effect for Li-ion battery management system of electric vehicles based on LSTM"

An AI model that combines Long Short-Term Memory (LSTM) neural networks with Bayesian optimisation can improve both the accuracy and efficiency of electric vehicle battery state-of-health (SOH) estimates, a key measure used in battery management systems to track degradation over time. Details are provided in the International Journal of Vehicle Information and Communication Systems.

Lithium-ion batteries gradually lose capacity through repeated charging cycles. SOH expresses this decline as a percentage of the original charging capacity. Accurate SOH estimation is important for drivers charging the vehicles ahead of a road trip. If SOH has fallen, then the distance they will be able to travel will be less than when the vehicle’s battery was new. It is also a matter of safety, as degraded batteries are more vulnerable to overheating, electrical faults, and, in rare cases, thermal runaway, a self-reinforcing reaction that can lead to fire.

Electric vehicles have Battery Management Systems (BMS) to monitor voltage, current, and temperature. However, converting this data into a reliable SOH estimate is difficult because battery degradation is influenced by complex chemical processes, temperature changes, and driving behaviour.

The new model can retain earlier patterns in a sequence, helping capture long-term behaviour in battery performance. The model links “health features” extracted from the vehicle data to standardised battery capacity. By using the probabilistic statistical technique of Bayesian optimisation, the new model can home in on particular data points rather than processing all possibilities. This reduces unnecessary computation while maintaining performance and gives a useful improvement on accuracy and halves the average error rate.

By obtaining a more accurate SOH estimate, the vehicle can manage its battery better and indicate when maintenance and replacement are needed. The BMS system can thus operate closer to safe performance limits. There is also the potential for extending battery life by adjusting charging rates and extent as the battery ages.

Xiao, Z. (2026) ‘Bayesian optimised route and SOH estimation effect for Li-ion battery management system of electric vehicles based on LSTM’, Int. J. Vehicle Information and Communication Systems, Vol. 11, No. 2, pp.146–162.

International Journal of Business Governance and Ethics invites special issue proposals

The editorial team of the International Journal of Business Governance and Ethics has released a call for special issue proposals for their journal. Details are available here.

Research pick: Modelling Alzheimer’s from Amyloid to Tau - "Tau protein transmission simulation modelling in Alzheimer’s disease integrated with neuro-symbolic learning"

AI can be used to model the spread of Alzheimer’s disease through the brain and has now provided researchers with a more biologically grounded way to predict cognitive decline. Details are reported in the International Journal of Simulation and Process Modelling. The work takes into account a shift in neuroscience that now seeks to treat dementia as a dynamic network disorder rather than a static accumulation of toxic proteins.

Nevertheless, the research focuses on Tau, a protein increasingly seen as central to the progression of Alzheimer’s disease. Although the condition is also associated with amyloid plaques, scientists now believe Tau pathology correlates more directly with neurone death and the deterioration of memory and reasoning. Amyloid plaques are perhaps the trigger, but the accumulation of misfolded Tau proteins, which multiply like prions, is thought to be the abnormality that leads to the cognitive problems seen in Alzheimer’s disease.

The new model, NSTP-Net, combines two forms of AI. One is a graph neural network, a type of deep learning designed to analyse interconnected systems. In this case, the brain is represented as a network of linked regions, enabling the model to simulate how disease-related signals travel across neural pathways. The second component uses symbolic reasoning, in which established biological knowledge is encoded directly into the system as logical rules. These include the tendency of Tau to spread along synaptic connections, the vulnerability of highly active brain regions, and the role of genetic risk factors.

The researchers validated their model against data from 428 participants in the Alzheimer’s Disease Neuroimaging Initiative. NSTP-Net was able to reduce prediction error by about 22 per cent compared with existing methods when forecasting Tau spread over an 18-month period. It also showed strong performance in predicting which patients with mild cognitive impairment, measurable memory problems not yet severe enough to qualify as dementia, would later progress to Alzheimer’s disease.

Huo, M., Chen, Y. and Wang, H. (2026) ‘Tau protein transmission simulation modelling in Alzheimer’s disease integrated with neuro-symbolic learning’, Int. J. Simulation and Process Modelling, Vol. 23, No. 6, pp.1–12.

Research pick: From coal face to the green race - "From coal to green: skills pathways for key emerging sectors in just transition regions"

Research in the World Review of Entrepreneurship, Management and Sustainable Development has looked at changes in the labour market in regions of Greece affected by the rapid phasing-out of coal and the move to renewables. The research suggests that current European Union approaches to green skills risks underestimating how unevenly job skills are spread across different sectors undergoing this energy transition.

The research was done in the context of the European Green Deal and its Just Transition Mechanism. These both aim to support workers and regions shifting away from fossil fuels. The research used survey data from more than 500 companies across three sectors, energy, construction, and ICT, to build a skills gap index. This statistical measure comparing existing workforce capabilities with those required by employers could help avoid many of the emerging problems of the energy transition.

The work shows that there is a big divergence between sectors. The energy sector, undergoing the most direct structural change away from fossil fuels, has the largest and most complex skills gaps. Specifically, employers report shortages in the necessary financial expertise needed to structure investments in emerging technologies such as hydrogen systems, alongside technical and strategic capabilities for managing evolving energy networks. In construction, there is a narrower but still important gap that is concentrated in green building practices. In ICT, there are also smaller skills gaps overall, but this might simply be a reflection of limited awareness of the problem among those surveyed.

A central finding of the work is that almost all skills identified (over 91 per cent) are not easily transferable between the three sectors being considered. This, the researchers say, challenges the big assumption that green skills can be treated as a single, unified labour category suitable for broad training programmes. There is much to be done at the energy coalface, as it were, in terms of awareness and training to ease the transition to a low-carbon future despite grand political statements and policies.

Galanos, G., Agiropoulos, C., Kyrlis, I. and Zlatini, K. (2026) ‘From coal to green: skills pathways for key emerging sectors in just transition regions’, World Review of Entrepreneurship, Management and Sustainable Development, Vol. 22, No. 2, pp.1–37.

Research pick: Sandpiper model predicts rainfall - "Optimised deep convolutional spiking neural network for accurate long-term and short-term rainfall forecasting in climate prediction systems"

AI can predict rainfall intensity better than several widely used forecasting models in tests using historical weather data from India. The new model reported in the International Journal of Mobile Communications shows that combining different forms of AI, along with advanced data-cleaning and optimisation techniques, can make rainfall prediction more accurate and reliable, particularly when expressed in practical categories such as light, moderate, or heavy rain.

The system uses a deep convolutional spiking neural network to identify spatial patterns in weather maps. The spiking aspect of the neural network was inspired by how brain cells communicate using short electrical pulses over time. Before the network training step, the researchers cleaned the data using a method called anisotropic diffusion Kuwahara filtering. This process reduces noise, random errors, while preserving important patterns. This is important in weather datasets, which often contain missing or uneven measurements.

The new model was evaluated using the India Rainfall Analysis dataset, which contains historical records from selected regions. Instead of predicting exact rainfall amounts, the system classifies conditions into rainfall categories. This type of classification is often more useful in practice, because decisions in agriculture, water management, and disaster response are frequently based on thresholds rather than precise measurements.

In the performance tests, the system worked better than established AI methods such as machine learning tools, like recurrent neural networks and gradient-boosting models. The new system raised fewer false alarms and did not miss major rainfall events, as was a problem with earlier models.

The team has improved the model using the sandpiper optimisation algorithm. This additional tweak models the behaviour of foraging waders (shorebirds) known as sandpipers. In machine learning terms, this additional tweak helps the model reduce prediction errors by optimising its internal settings.

Amanullah, M., Ananthajothi, K. and Agoramoorthy, M. (2026) ‘Optimised deep convolutional spiking neural network for accurate long-term and short-term rainfall forecasting in climate prediction systems’, Int. J. Mobile Communications, Vol. 27, No. 3, pp.300–315.

Research pick: Industrial ecosystems and innovation - "Nexus between innovation ecosystem and innovation performance"

A study of Kenya’s manufacturing sector suggests that industrial innovation there depends more on exogenous factors rather than what happens inside a firm. The findings, published in the International Journal of Business Innovation and Research, show there is a strong relationship between an “innovation ecosystem” and how well companies develop new products, improve their processes, and stay competitive.

An innovation ecosystem is the wider network in which a company operates. It includes government policies, access to finance, access to transport and energy, relationships with suppliers and customers, and links to universities and research institutions. These various elements determine how easily a company might generate new ideas and turn them into commercially viable goods or services. Innovation performance measures the outcomes of all these efforts.

The findings suggest that firms embedded in a strong ecosystem with reliable business services, effective trade support, and opportunities for knowledge sharing perform better in terms of innovation than companies without this external support. Fundamentally, companies in this kind of environment can adapt to changing market conditions and sustain growth.

Companies interact continuously with regulators, customers, suppliers, and research bodies, and innovation emerges from these interactions, rather than being due simply to internal research and development. The new perspective offered by this research challenges traditional management approaches and shows that companies ought to prioritise collaboration, learning, and flexibility rather than conventional management controls and hierarchy.

The researchers point out that the implications of their study are particularly acute for Kenya, where manufacturing has struggled to maintain competitiveness. Historically, Kenya has focused on exporting raw or semi-processed materials rather than higher-value finished goods. But this has limited both profitability and job creation, and there has been a decline in growth in manufacturing in recent years. The researchers explain that low levels of innovation may be to blame and suggest that responsibility for improvement does not rest solely with individual companies but with the industrial ecosystems discussed.

Gachanja, I.M. (2026) ‘Nexus between innovation ecosystem and innovation performance’, Int. J. Business Innovation and Research, Vol. 39, No. 9, pp.1–20.

Prof. Jiageng Ruan appointed as new Editor in Chief of International Journal of Transport Technology and Innovation

Prof. Jiageng Ruan from Beijing University of Technology in China has been appointed to take over editorship of the International Journal of Transport Technology and Innovation.

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.

• Visual element layout generation for packaging design driven by human-machine collaborative reinforcement learning
• Attribute-based sharing method for cloud data with fine-grained dynamic access control
• Bayesian-optimised multiscale image inpainting for digital preservation of murals
• Augmented reality mobile real-time assistance system for sports training
• Sports social media influence prediction model with temporal transformer and causal reasoning

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.

• A study on compensation for voltage unbalance in distribution transformer areas considering three-phase load imbalance using hybrid PV-ESS inverters
• Student mental health assessment based on social sentiment analysis and multi-branch neural networks
• A generative adversarial error correction system for English writing
• Optimising English translation vocabulary selection based on corpus statistics and probabilistic modelling
• Multimodal generative adversarial networks for dynamic mitigation of foreign language anxiety

Research pick: Encryption and intrusion detection close to the edge - "Dual-modal system for real-time encryption and anomaly detection of 5G communication data integrating AES-GCM and LSTM"

Research into 5G cellular network security suggests that we need to unify encryption and intrusion detection to better protect those networks rather than treating encryption and detection as separate processes. The research in the International Journal of Information and Communication Technology focuses on the demands of 5G networks, which offer high data speeds, very low latency, and massive device connectivity. These capabilities allow us to use sophisticated mobile applications and have autonomous vehicles, smart cities, and industrial automation. But they come at a cost of increased exposure to fast-changing security threats from malware and malicious third parties.

The researchers have identified a structural limitation in conventional security design. Encryption typically protects data confidentiality, while intrusion detection systems independently monitor network traffic for malicious behaviour. In high-speed 5G environments, this separation can introduce delays and reduce the system’s ability to respond to attacks in real time.

To address this, the researchers have developed a dual-modal architecture that combines AES-GCM with a Long Short-Term Memory (LSTM) neural network. AES-GCM is a symmetric encryption method that scrambles data to prevent unauthorised access while also verifying that information has not been altered during transmission. The LSTM component is a type of deep learning model designed to analyse sequences of data over time, allowing it to identify patterns in network traffic and detect anomalies.

The system integrates these functions so that encryption and anomaly detection operate in parallel. Data is secured while being continuously monitored, rather than processed in separate stages. According to the researchers, this combined approach offers a detection accuracy of 98.1% and a false positive rate of just 0.5%, meaning it rarely mislabels normal activity as malicious. Encryption and decryption times are reported at 18.4 milliseconds and 21.7 milliseconds, respectively, performance levels considered suitable for real-time communication systems.

The team adds that this new model works under varying network loads. In high-bandwidth conditions, encryption delays are lower, suggesting the system adjusts dynamically to traffic intensity. They also add that energy consumption is reduced compared with encryption-only methods. This could be critical for edge computing environments where processing occurs on the device and where power resources might be limited.

Wang, H. (2026) ‘Dual-modal system for real-time encryption and anomaly detection of 5G communication data integrating AES-GCM and LSTM’, Int. J. Information and Communication Technology, Vol. 27, No. 41, pp.21–44.

Free Open Access issue published by International Journal of Reasoning-based Intelligent Systems

The International Journal of Reasoning-based Intelligent Systems has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Stock prediction and selection method based on LSTM-BPNN and multi-factor quantisation
• Adaptive music generation by integrating improved VAE and improved GMVAE
• Application of support vector machine algorithm in quality evaluation of audio format conversion in music transmission
• Collaborative optimisation algorithm of international trade supply chain driven by artificial intelligence
• Object detection for construction site safety monitoring based on Yolov8 model

Research pick: Strike a pose for a health boost - "Integrating yoga and nutrition: a complementary therapy for addressing obesity in clinical practice"

A growing body of research is reframing yoga from a general wellness practice into a structured therapeutic intervention with measurable effects on obesity, type 2 diabetes, hypertension, coronary heart disease and chronic obstructive pulmonary disease (COPD), according to the authors of a paper in the International Journal of Sport Management and Marketing. The evidence base is still developing, but numerous studies suggest that yoga can affect physiological and psychological health outcomes.

Obesity has been a major focus of recent research. Obesity is a metabolic condition defined by excessive fat accumulation that increases a person’s risk of cardiovascular disease, diabetes, stroke and certain types of cancer. Unlike simple weight gain, obesity is understood as a complex interaction of diet, a sedentary lifestyle, and genetic susceptibility. It is becoming a major issue in public health around the world.

Intervention studies indicate that dietary improvement is key to reducing obesity, but when combined with yoga practice, it can be particularly beneficial. In programmes lasting six to twelve months, participants have experienced weight lost and improvements in cardiometabolic markers, including blood glucose regulation and cardiovascular function. Physical activity has repeatedly been shown to moderate the activity of two hormones, ghrelin, the hunger hormone and leptin, the satiety hormone. Yoga may well improve leptin sensitivity, boosting one’s fullness cues and so supporting longer-term weight regulation.

In the clinical literature, yoga is typically defined as a combination of physical postures, controlled breathing and meditation. Traditional systems such as Ashtanga yoga also incorporate ethical discipline and concentration, aligning with modern multidimensional approaches to health that integrate physical activity with stress management and behavioural change. Indeed, the psychological impact of yoga practice has been demonstrated in some studies to reduce anxiety, irritability, and depressive symptoms and to improve what we might term ’emotional stability’ and ‘perceived wellbeing’. Given that psychological stress is often a trigger for over-eating, yoga practice may well tackle obesity from the physical and psychological angles.

Chekatla, M.V., Bhaumik, A., Gousuddin, M. and Chekatla, V. (2025) ‘Integrating yoga and nutrition: a complementary therapy for addressing obesity in clinical practice’, Int. J. Sport Management and Marketing, Vol. 25, Nos. 2/3, pp.202–229.

Free sample articles newly available from International Journal of Decision Sciences, Risk and Management

The following sample articles from the International Journal of Decision Sciences, Risk and Management are now available here for free:

• Does integrated building information modelling support construction supply chains? A systematic review of theories, methods and actors
• Resilience of complex systems in modern contexts: sense-making of deviations and enabling the human for mitigating unwanted events and incidents
• The problem of negative total faced in the COPRAS method of multi-criteria decision-making techniques and a solution proposal Hasan Kazak
• An empirical assessment of the factors causing delays in project completion in the construction sector of Lahore Pakistan
• Doctors' attitudes toward social media use amid the COVID-19 pandemic using an extended technology acceptance model
• An interdisciplinary crisis management approach based on day-to-day business operations and project delivering for typical cruise companies
• Risk attitudes of forest dependent communities: evidence from Andhra Pradesh, India

Free Open Access special issue on "The Application of Advanced Materials for Smart and Sustainable Manufacturing – Part 1" published by International Journal of Materials and Product Technology

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

• Design modelling and digital visualisation application of carbon fibre composite materials under 3D printing manufacturing process
• Mechanical properties of materials during the removal of reinforced concrete internal support beams
• Role of wearable conjugated material pneumatic wrist in sports rehabilitation
• Exploring the application of intelligent responsive nanomaterials for temperature- and light-controlled colour change in dynamic decorative lighting systems
• Collaborative innovation in product recycling and remanufacturing within the context of a circular supply chain

Free sample articles newly available from International Journal of Web Engineering and Technology

The following sample articles from the International Journal of Web Engineering and Technology are now available here for free:

• Intelligent interior design based on deep learning and CF algorithm
• Cloud storage framework for multivariate regression-based data mining: optimised LIFR and FIFR model
• Evaluation of students' innovation and entrepreneurship based on genetic neural network algorithm under sustainable development in higher education institutions
• Cross-chain data exchange and information security protection management in blockchain
• Development strategy of rural e-commerce in the context of new media: construction of traceability system based on improved DPoS 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.

• Construction of multimodal public opinion knowledge graph for regional economic fluctuations
• Password recovery parallelisation and acceleration technology for autonomous and controllable platforms
• Intelligent risk analysis framework for civil and commercial contract clauses based on BERT
• A personalised knowledge tracking graph neural network driven by learning psychological motivation
• Deep learning-driven literary evaluation: fusing visualised representations and text embeddings

Free sample articles newly available from International Journal of Sustainable Aviation

The following sample articles from the International Journal of Sustainable Aviation are now available here for free:

• Experimental and computational study on a morphed trailing edge airfoil for enhanced lift and stall characteristics
• Aviation impact on air quality: evidence from countries with highest air traffic
• A literature review on artificial intelligence in aviation sector
• Barriers to in-flight communication effectiveness: a qualitative inquiry with pilots in Türkiye
• Operational performance in sustainable aviation: an in-depth analysis of turnaround times of future commercial narrowbody liquid hydrogen aircraft

New Open Access article available: "Evaluation of Hunan Province's agricultural productivity based on the TOPSIS model"

The following International Journal of Environment and Waste Management article, "Evaluation of Hunan Province's agricultural productivity based on the TOPSIS model", 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 of multimodal perception and quantitative assessment model of interactive participation in English classroom
• English diversified and high-fidelity translation based on adaptive label smoothing algorithm
• Computer music sound signal synthesis and separation based on time-frequency cross domain feature selection
• Research on intelligent management of the full lifecycle of power communication equipment based on knowledge graphs
• An optimal daily fund scheduling model based on ARIMA

Research pick: Highway to hella improved energy systems - "Optimal scheduling energy for ‘wind-solarload-storage’ AC-DC hybrid distribution network system based on multi-agent algorithm"

AI could boost AC/DC hybrid electricity systems and make renewable-heavy power grids more stable, efficient and resilient, according to research in the International Journal of Global Energy Issues, which has considered the future operation of low-carbon high-voltage networks.

The research looked at one of the main engineering challenges that has emerged with the shift towards renewable energy: how to operate electricity grids reliably when large amounts of power come from intermittent sources such as wind and solar.

Modern electricity systems are increasingly evolving into AC/DC hybrid networks, which combine traditional alternating current (AC) infrastructure, such as power stations, with direct current (DC) systems used by technologies such as solar panels, batteries, electric vehicles and power electronics. Hybrid systems can improve efficiency and make renewable integration easier, but they are also much more difficult to control because both electricity supply and demand fluctuate constantly.

The researchers argue that traditional centralised control systems are no longer appropriate for such networks. Conventional grid management relies on a central operator collecting information from across the network and calculating instructions for generators, storage systems, and other equipment. But the growing number of renewable devices and variables now make real-time optimisation far too slow and computationally complex.

The research has looked at how a framework based on multi-agent reinforcement learning (MARL), a form of artificial intelligence (AI) in which software agents learn decision-making behaviour through repeated interaction with their environment might solve this problem. In this approach, different parts of the electricity system, including wind farms, solar installations, and battery storage units, are treated as independent components where rapid, local decisions and the over-arching system coordinates these decisions within the grid as a whole.

Simulations predict a reduction in operating costs of more than 10 percen and an increase in renewable energy use of more than 13 per cent. Efficiency is also improved, with losses reduced by more than 15 per cent compared with traditional centralised optimisation methods.

Wei, B., Yang, C., Liu, K., Tang, W. and Zhang, X. (2026) ‘Optimal scheduling energy for ‘wind-solarload-storage’ AC-DC hybrid distribution network system based on multi-agent algorithm’, Int. J. Global Energy Issues, Vol. 48, No. 8, pp.24–42.

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.

Research pick: The career kaleidoscope - "Women’s empowerment and innovations in work behaviour: based on the kaleidoscope model"

A study in the International Journal of Business Innovation and Research has looked at women’s employment in Saudi Arabia. It suggests that workplace empowerment is closely linked to an employee’s ability to generate and implement new ideas. The research thus offers evidence that organisational inclusion strategies may have direct consequences for innovation performance.

The researchers surveyed almost 500 women working across both public and private sector organisations in Saudi Arabia. They found that those that report higher levels of empowerment were more likely to demonstrate innovative work behaviour.

To test this relationship, the authors used a statistical technique known as partial least squares structural equation modelling. This allowed them to consider multiple interacting variables at once. They could then estimate what direct and indirect effects were affecting the outcomes whether empowerment, psychological engagement, or organisational context.

They point out that empowerment operates not just as a matter of workplace fairness or representation, but drives innovation. They found that this happens through two pathways. The first is creative process engagement, wherein an individual actively involves themselves in generating ideas, experimenting with different approaches to tasks, solving problems, and reflecting on outcomes.

The second mechanism is the kaleidoscope model where shifting priorities such as authenticity are balanced with personal values, work and personal life are balanced, and challenges are met in terms of the pursuit of growth and development opportunities. The study found that empowered women could balance all three angles of the kaleidoscope well to shape their career decisions to support innovation at work.

The team also found that organisational context also had a role to play. Formal and informal rules, practices, and power structures that shape workplace behaviour influenced empowerment and its relationship with innovation. They add that supportive and transparent policies led to stronger links between empowerment and creative engagement. This suggests that institutional environments might facilitate or hinder employee potential by choosing a particular approach to women in the workplace.

Aldossary, S.M. and Aldhmour, F.M. (2026) ‘Women’s empowerment and innovations in work behaviour: based on the kaleidoscope model’, Int. J. Business Innovation and Research, Vol. 39, No. 9, pp.21–49.

New Open Access article available: "Power information network attack chain identification and disaster recovery early warning mechanism based on graph neural network"

The following International Journal of Intelligent Information and Database Systems article, "Power information network attack chain identification and disaster recovery early warning mechanism based on graph neural network", is freely available for download as an open access article.

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

Free sample articles newly available from International Journal of Business Process Integration and Management

The following sample articles from the International Journal of Business Process Integration and Management are now available here for free:

• Addressing cartels in emerging markets: a critical analysis of legal implications and policy reforms
• Digital transformation in managing outgoing student applications: enhancing administrative efficiency in higher education institutions
• Examining the pandemic shifts in payment: awareness and inclination in digital payments across demographics
• Unveiling the power of shared leadership in project realms: a synergy of planning, knowledge, cohesion, and trust
• Identifying performance measures relationships in business processes based on data mining
• Improvement of training procurement business process using DMAIC at PT. Transportasi Jakarta (Transjakarta)
• Unveiling the impact: how lantern product value attributes drive purchase intentions among peoples

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.

• High quality controllable music generation technology based on improved transformer
• Timbre interpretable representation modelling method integrating self-supervised learning and music theory descriptors
• Digital art image design method based on fractal geometry and lightweight convolutional networks
• The design of multi-modal intelligent vocabulary memory system for fragmented learning
• Urban green space landscape planning and design based on superpixel segmentation algorithm

Free Open Access special issue on "The Central Role of China in the Global Automotive Industry – Part 1" published by International Journal of Automotive Technology and Management

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

• The great unbundling: from integrated architecture to orchestrated fluidity in the software defined vehicle era
• Electric vehicle adoption in China's post-subsidy era: a mixed-methods study of non-fiscal incentives

New Open Access article available: "From coal to green: skills pathways for key emerging sectors in just transition regions"

The following World Review of Entrepreneurship, Management and Sustainable Development article, "From coal to green: skills pathways for key emerging sectors in just transition regions", is freely available for download as an open access article.

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

Free sample articles newly available from International Journal of Environment, Workplace and Employment

The following sample articles from the International Journal of Environment, Workplace and Employment are now available here for free:

• Integrating consumer behaviour into the circular economy: a proposed multidimensional scale
• Career development and employee loyalty affect company commitment and performance in small and medium-sized enterprises in the northeast region of Vietnam
• Illuminating operational excellence in automotive manufacturing company (an empirical evidence from Indonesia)
• An examination of the environmental and climatic consequences stemming from the integration of the Metaverse into converging digital ecosystems
• Impact of perceived glass ceiling on burnout among female public administrators in Tunisia: the moderating role of work-life balance

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.

• Research on innovative design of power grid data security transmission system based on chaotic encryption algorithm
• Analysis and research on entrepreneurial models and policy innovation paths facing the digital energy market
• Exploration of a teaching model for choreographic course based on Laban Movement Analysis theory in the context of artificial intelligence
• Fuzzy adaptive coordinated control for power oscillation suppression in multi-VSG systems
• Knowledge graph construction for online courses using enhanced BERT and BiLSTM

New Open Access article available: "Lightweight CNN-transformer hybrid network for English speech recognition"

The following International Journal of Business Intelligence and Data Mining article, "Lightweight CNN-transformer hybrid network for English speech recognition", is freely available for download as an open access article.

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

Research pick: Under the influence - "Virtual influencer marketing: mediating roles of product involvement and brand familiarity"

As if real influencers were not enough, now companies are using computer-generated personalities to persuade consumers to buy their products. A study in the International Journal of Electronic Marketing and Retailing has looked at these CGI-AI figures, which are designed and programmed to act like human social media personalities, and how they affect purchase intention when it comes to sports products.

The work uses the stimulus-organism-response framework, a model in psychology and marketing that helps explain how external stimuli affect a person’s mental state and drive behaviour. The research found that exposure to virtual influencers (the stimulus) can affect the thoughts and feelings of the consumer (the organism), leading to decisions such as making a purchase (the response).

Survey data from consumers in the Phillipines indicates that virtual influencer marketing can have a statistically significant effect on purchase intention. This effect is both direct and indirect. Indirectly, virtual influencers increase product involvement, the degree to which a consumer finds a product personally relevant, and brand familiarity, meaning how well a consumer knows a brand. Both factors lead to a greater likelihood of a purchase, the researchers found.

It seems that virtual influencers operate by deepening engagement rather than being overtly persuasive as a human influencer might. The team suggests that several psychological mechanisms underpin this process. Parasocial interaction, a term describing one-sided relationships in which audiences feel emotionally connected to media figures, helps explain why consumers may respond to virtual personalities as if they were real. Perceived realism, how lifelike and believable the influencer appears, also contributes, alongside attractiveness and perceived trustworthiness.

The findings highlight a shift in digital marketing strategies and offer an alternative to human influencers who have their own opinions and expect to be rewarded or remunerated for their efforts. Unlike human influencers, virtual figures can be tightly controlled, avoiding reputational risks and ensuring consistent messaging. This makes them appealing to brands seeking reliability in an increasingly competitive online environment.

The obverse of this, however, is that the price of such control raises questions about authenticity. As consumers form emotional connections with artificial entities, the nature of trust in advertising may change or there may even be a backlash against this kind of marketing.

Biason, R., Elnagar, A.K., Tolete, C., Elsaadany, H.A.S., Hasan, S. and Santos, L. (2026) ‘Virtual influencer marketing: mediating roles of product involvement and brand familiarity’, Int. J. Electronic Marketing and Retailing, Vol. 17, No. 6, pp.1–23.

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.

• Fusion of BDCN and multi scale U-Net for pattern and line manuscript generation technology in colourful cultural and creative products
• Optimisation of energy supply chain and global value chain based on genetic algorithm
• Energy efficiency optimisation of port clusters based on improved NSGA-III multi-objective criteria
• Research on anomaly detection in energy engineering bidding based on spatiotemporal graph neural network
• Campus network public opinion sentiment analysis technology based on XLNet-BiGRU-Att algorithm

New Open Access article available: "Stylised 2D animation generation method based on generative adversarial networks"

The following International Journal of Arts and Technology article, "Stylised 2D animation generation method based on generative adversarial networks", is freely available for download as an open access article.

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

Research pick: The healthy option, with or without ads? - "With or without ads? A question for health apps"

Developers of mobile health applications are making calculated trade-offs in how they earn money, with consequences that extend beyond their balance sheets to the experience, privacy, and accessibility of users, according to research in the International Journal of Electronic Marketing and Retailing that has looked at app markets in Portugal.

‘Mobile health’ refers to smartphone applications that help individuals monitor their health and illnesses, track fitness, access medical advice, or manage treatment. Such tools are widely promoted as a way to improve healthcare efficiency by enabling continuous data collection and encouraging patients to take a more active role in their wellbeing. However, the long-term viability of the commercial apps depends on how their developers monetise patient usage.

The researchers focused on three principal monetisation strategies: upfront download fees, in-app purchases, and in-app advertising. A download fee is a direct payment required before a user can install the app. In-app purchases allow users to pay for additional features or content after downloading, while advertising generates income by displaying promotional material within the app, which might be tailored using personal data.

Each approach carries distinct costs for users. While download fees are explicit and easily understood, advertising-based models introduce indirect costs. These may include time spent viewing adverts, interruptions to the user experience, and concerns about how personal health data may be used to target ads. In-app purchases, meanwhile, can create uneven access to functionality, with some features effectively locked behind paywalls.

The researchers found that advertising commonly substitutes for upfront fees. This reflects a strategic trade-off on the part of the developers: charging upfront generates immediate income but risks discouraging users from installing the app, whereas free access supported by advertising can attract a larger audience, increasing the app’s value to advertisers.

By contrast, in-app purchases tend to complement rather than replace advertising. Applications offering optional paid features are more likely to include ads as well. This allows them to build a broad user base but to boost their income with additional revenue from a subset of users willing to pay for enhanced services.

Cardoso, C., Machado, C.S. and Lemos, N. (2026) ‘With or without ads? A question for health apps’, Int. J. Electronic Marketing and Retailing, Vol. 17, No. 3, pp.362–375.

Free Open Access issue published by International Journal of Global Energy Issues

The International Journal of Global Energy Issues has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Soil and water conservation and ecological restoration in watershed and implications to energy implications and policies
• Optimal scheduling energy for 'wind-solar-load-storage' AC-DC hybrid distribution network system based on multi-agent algorithm
• Enhancing design efficiency of intelligent garden space allocation: an adaptive layout algorithm by multi-objective ant colony optimisation
• The impact of tax burden reduction for electricity quota trading system in China
• Modelling and computer simulation analysis of cascading failure probability of heterogeneous complex power grid for green energy system
• Research on key soil and water loss characteristics and mitigation strategies for power grid projects in Jiangsu plain's water network region

Research pick: Online, all the time? That might be fine? - "The influence of diverse usage motives on the amount of social media use: the moderating effects of age and gender"

There is an assumption that social media use is mainly habitual or driven by addiction-like mechanisms, but findings published in the International Journal of Electronic Marketing and Retailing suggest that engagement with such platforms might be better explained in terms of a person’s structured response to distinct psychological and social needs. The work could have implications for how the platforms, policymakers, and users themselves interpret their time spent online.

The researchers analysed responses from 384 participants about their social media use using Structural Equation Modelling. This statistical approach tests complex causal relationships between psychological factors and observable behaviour. It allowed the team to examine how different motivational variables work together to influence social media use in a way that earlier analyses might have missed.

The work builds on Uses and Gratifications Theory, a framework in media studies that argues that individuals are active agents who choose media platforms to satisfy specific needs rather than passive recipients of content. Within this framework, the researchers categorise motivations for social media use into four groups: coping, social motive, enhancement, and conformity.

“Coping” refers to using social media to manage negative emotional states such as stress, anxiety, or sadness. “Social motive” captures the use of platforms to maintain relationships, communicate with others, and experience a sense of belonging. “Enhancement” describes engagement aimed at increasing positive emotions, enjoyment, or self-esteem. “Conformity” refers to behaviour shaped by external pressure, including following trends or responding to perceived social expectations.

The study demonstrated that coping and social motives are the strongest and most consistent predictors of overall social media usage. This suggests that users tend to spend more time on social media when they are either trying to regulate negative emotions or seeking interpersonal connection. Enhancement motives, linked to enjoyment and self-image, also had a part to play, but their effect was less consistent between users. Finally, conformity, despite its theoretical relevance in earlier research, had only a weak association with overall time spent on platforms.

From a policy and design perspective, the work shows that social media usage is more complex than is often assumed in public debate. If social media use is closely tied to emotional regulation and social connectedness, then interventions focused solely on reducing screen time may overlook the underlying psychological drivers of engagement. For some individuals, this might then do more harm than good.

The work also raises the possibility that a blanket approach to restriction or deterrence might not distinguish between different patterns of use. In such cases, the challenge for policymakers and designers should then be to recognise when and why usage becomes disproportionate in more subtle ways.

Kirezli, O. and Aydin, A.E. (2026) ‘The influence of diverse usage motives on the amount of social media use: the moderating effects of age and gender’, Int. J. Electronic Marketing and Retailing, Vol. 17, No. 3, pp.342–361.

New Open Access article available: "Cross-disciplinary learning in environmental engineering and landscape architecture"

The following International Journal of Collaborative Engineering article, "Cross-disciplinary learning in environmental engineering and landscape architecture", is freely available for download as an open access article.

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

New Open Access article available: "Virtual influencer marketing: mediating roles of product involvement and brand familiarity"

The following International Journal of Electronic Marketing and Retailing article, "Virtual influencer marketing: mediating roles of product involvement and brand familiarity", 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.

• Image retrieval of hand-drawn sketches in Shu embroidery pattern based on CycleGAN and triplet network
• Swimming-assisted training and physical fitness enhancement system based on improved YOLOv5 and improved ST-GCN
• Dynamic identification model of financial fraud of listed companies based on XGBoost and graph neural network
• Smart tourism decision support system based on dual-heuristic algorithms
• Extraction system of BiLSTM-CRF joint transfer learning