The following International Journal of Reasoning-based Intelligent Systems article, "Intelligent instructional resource management incorporating emotional and semantic features of user comments", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Reasoning-based Intelligent Systems article, "Cross-border e-commerce credit risk early warning model based on deep learning", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Critical Infrastructures article, "Investigation of the effect of inlet and outlet of the water flow on the productivity of a solar collector", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of International Journal of Information and Communication Technology article, "Educational resource allocation optimisation driven by multimodal feature fusion", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Residual-enhanced transformer for affective multi-part music generation", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "UAV target detection and tracking technology based on deep learning algorithms", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Making music in groups, even among people with no musical background, can give the team a boost, according to research in the International Journal of Applied Management Science. The findings suggest that making music together can improve one’s sense of effectiveness as well as satisfaction in subsequent teamwork. The findings add to a growing body of research that is exploring unconventional methods for team development, a field that has typically been dominated by training programmes, coaching, and workplace simulations.
In the musical experiments, people were asked to create music collectively. Each group performed a simple rhythm and then improvised a melody together. None of the participants had prior training, and before starting, they were introduced to only the most basic of musical concepts. Despite such minimal preparation, the act of making music together had measurable effects, the research found.
Those participants who had actively performed music together subsequently reported higher levels of team effectiveness, the belief that their group could work well together. They also reported greater team satisfaction, compared with peers who were merely audience to the music-making. Among performers, the sense of gaining insights through the music-making proved the strongest predictor of how effective they judged their team to be. Audience members, in contrast, showed weaker and less consistent links between the musical task and their evaluation of teamwork.
In professional settings, team-building exercises have often been based on structured activities, such as problem-solving and role-play, designed to enhance collaboration. This research suggests that unconventional approaches to team-building, such as making music together, may provide a power alternative.
Music requires coordination: players must stay in rhythm, adjust to one another, and listen carefully to shifts in pace or tone. It can involve improvisation, the ability to respond flexibly when the pattern changes or when mistakes occur. These qualities have direct parallels in modern workplaces, where teams succeed not only through technical knowledge but also through adaptability, communication, and trust. The researchers argue that group music-making offers a natural rehearsal for these skills.
Tal-Shmotkin, M. (2025) ‘An innovative tool for team development: the use of musical activity’, Int. J. Applied Management Science, Vol. 17, No. 3, pp.237–251.
The following International Journal of Information and Communication Technology article, "MA-HGCN: modality attentive hierarchical graph convolutional network for EEG-fNIRS brain-computer interface system", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Open-pit coal mine detection in large-scale remote sensing images", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Patient signal feature extraction technology for intelligent nursing bed", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Technology, Policy and Management article, "CEO's IT background, attention configuration and digital innovation", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research concerning the behaviour of business students shows that the factors most commonly associated with classroom participation, attendance, speaking up, and joining in, may matter less for academic achievement than the emotions of learners.
The research, conducted with 118 business students, discusses in the International Journal of Monetary Economics and Finance how different forms of engagement affected academic performance during the pandemic. Engagement, a concept widely used in educational research, refers to the level of involvement and connection students bring to their studies. It is generally understood to operate across four dimensions: behavioural, social, cognitive, and emotional.
Behavioural engagement covers outward signs such as attendance, punctuality, and finishing assignments and projects. Social engagement refers to interactions with peers and lecturers, whether in discussion or collaboration. Cognitive engagement relates to the intellectual effort students devote to grappling with material. Finally, emotional engagement describes the student’s feelings of enthusiasm, interest, or their sense of belonging in the learning environment.
The research found that only the internal dimensions, cognitive and emotional engagement, had an obvious positive impact on academic performance. Students who invested intellectual effort and maintained an emotional connection to their studies tended to achieve stronger results, even if they were less visibly active in class. In contrast, behavioural and social engagement showed no measurable effect on outcomes.
This pattern, the research suggests, reflects the unique conditions imposed by the COVID-19 pandemic of 2020 and beyond. Teaching moved largely online and so the conventional external markers of engagement, such as classroom discussion, group exercises, and collaborative tasks, were no longer useful as they barely existed in these uncertain times. In their absence, success depended largely on a student’s ability to sustain motivation and intellectual focus while they were in isolation. The study’s findings indicate that students who were able to marshal their internal resources fared better academically than those who relied on external forms of participation. Obviously, such insights could have a bearing on education in the future when we face a similar crisis again.
Anatan, L. (2025) ‘Impact of engagement on business students’ academic performance’, Int. J. Monetary Economics and Finance, Vol. 18, Nos. 2/3, pp.206–214.
The following International Journal of Environment, Workplace and Employment article, "Human resource competencies in the automotive Industry 4.0 - results of a systematic literature review", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Computational Systems Engineering article, "Vocational college employment training and career planning model design based on improved collaborative filtering", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A study in the International Journal of Globalisation and Small Business has shown that how effective an advertising campaign is depends not only on the content of the campaign, but also on who is receiving it. Demographic factors, such as age, education, location, and employment status, are most important in shaping consumer responses to advertising by family-run businesses, particularly in a country such as Kosovo where family businesses form a large part of the economy.
The researchers survey more than 400 consumers and analysed advertising data from 24 family-owned brands. They identified clear differences in how various groups interpret and act upon marketing messages. For instance, younger, urban, and highly educated consumers are more likely to recognise brands, while older, rural, and less-educated individuals are more inclined to make choices based on trust perceptions based on advertising.
The research highlights the Elaboration Likelihood Model, a framework from consumer psychology which distinguishes between two modes of processing advertising messages: the central route, in which individuals engage deeply with content, and the peripheral route, where decisions are made based on cues such as aesthetics or familiarity. The research suggests that younger and better-educated individuals are more likely to take the central route, scrutinising message content, while others may respond more intuitively, guided by trust and emotional resonance.
A second model was also considered, the Psychological Reactance Theory. This, the researchers say, helps explain the resistance of some urban and educated consumers to overtly persuasive or emotionally manipulative advertising. These groups, they found, tend to prefer subtlety and authenticity over high-pressure tactics. The findings have implications for advertisers seeking to build credibility among such initially sceptical audiences. The findings might have wider implications, but within Kosovo, tight-knit community structures and collective cultural norms continue to shape perceptions of business credibility, especially in rural areas.
Pllana, D.Z., Gërguri-Rashiti, S. and Limani, E. (2025) ‘Exploring the moderating role of demographics in consumer responses to advertising: evidence from family business brands in Kosovo’, Int. J. Globalisation and Small Business, Vol. 15, No. 5, pp.1–28.
The following International Journal of Globalisation and Small Business article, "Exploring the moderating role of demographics in consumer responses to advertising: evidence from family business brands in Kosovo", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
As environmental responsibility and social ethics become increasingly important, a question might arise in the boardroom: does the company’s sustainability efforts materially affect the financial information on which investors rely? Research in the International Journal of Business and Emerging Markets sets about answering that question. It does so by examining data from European firms over the course of a decade and providing empirical evidence that voluntary disclosure and strong performance in sustainability metrics improve the value relevance of financial statements.
The researchers focused on Environmental, Social, and Governance (ESG) criteria. This is a set of standards measuring a company’s impact and management of environmental stewardship, social responsibility, and internal governance practices. ESG performance has grown in prominence as investors and regulators seek to understand how these non-financial factors influence long-term corporate viability. The value relevance of financial statements refers to the extent to which their information correlates with a company’s market valuation and so helps stakeholders in investment decisions. Ultimately, the research found, firms voluntarily reporting ESG information tended to present financial statements more aligned with market perceptions of their value.
Moreover, firms with higher ESG performance scores, indicating better sustainability practices, demonstrate even stronger correlations between their financial disclosures and market value. This suggests that sustainability efforts are not merely reputational or regulatory compliance exercises but contribute meaningfully to the transparency of financial reporting.
The findings are rather timely. Europe’s Corporate Sustainability Reporting Directive (CSRD) and the European Sustainability Reporting Standards (ESRS) are already mandating for more consistent and comprehensive sustainability disclosures. They aim to standardize how ESG data is presented to improve comparability across companies and sectors. Moreover, globally, the International Financial Reporting Standards (IFRS) Foundation and its International Sustainability Standards Board (ISSB) are developing analogous reporting standards to harmonize sustainability information worldwide, reducing duplication and improving clarity for investors.
Christofi, K., Kythreotis, A., Chourides, P., Soltani, M. and Di, Z. (2025) ‘The impact of sustainability disclosure on financial statement value relevance: evidence from Europe’, Int. J. Business and Emerging Markets, Vol. 17, No. 5, pp.1–22.
A new research-led recommendation model could make vocational education more effective in guiding students towards suitable employment after graduation, according to research in the International Journal of Computational Systems Engineering. The approach has developed in response to increasing concerns in China and globally regarding youth unemployment and the efficacy of vocational training systems. As such, the algorithm reflects a more subtle approach to matching students with career paths that align better with their individual strengths and preferences.
The researchers explain that the core of their approach is based on an improved form of collaborative filtering. This is an algorithmic technique often used by streaming services and e-commerce platforms to suggest content or products based on a user’s past behaviour and preferences. The new approach overcomes various shortcomings of such systems when used in career recommendation by integrating two additional computational methods into the process: K-means clustering and the Kruskal algorithm. K-means clustering is a statistical technique that groups individuals based on shared characteristics, such as similar training choices or job applications. The Kruskal algorithm optimises how those groupings are connected and interpreted within a broader system.
The resulting model, K-means and Kruskal-enhanced Collaborative Filtering, was trained on three years of employment data from vocational school graduates. Ultimately, it was able to achieve a recommendation accuracy of more than 94 percent, significantly outperforming more conventional systems. According to the researchers, the model also excelled in standard performance metrics.
These various technical improvements represent improvements in real-world recommendations. For students, the new algorithm is more accurate in offering personalised career suggestions. And, for vocational institutions, it offers a more responsive tool to support their students in their transition from studies into the workforce. There is a third benefit and that is to employers who will gain access to candidates whose training and preferences more closely match the needs they ask for on their specific roles.
Wang, J. (2025) ‘Vocational college employment training and career planning model design based on improved collaborative filtering’, Int. J. Computational Systems Engineering, Vol. 9, No. 13, pp.1–10.
A novel algorithmic system that works subtly in the background to mutual benefit, and adapts quickly to local conditions, could be useful in data processing where noise terms can be replaced with useful estimates of their values.
In the unpredictable world of data-driven modelling, some algorithms charge through problems like rhinos, others blend in and adapt like chameleons. A new approach to a long-standing challenge in system identification, how to work with missing and noisy data, falls firmly into the latter camp and is discussed in the International Journal of Modelling, Identification and Control.
The method is designed for Controlled Autoregressive Moving Average (CARMA) models, mathematical structures widely used to capture and forecast the behaviour of dynamic systems in fields as diverse as control engineering, economics, and climate science.
These models work best when both input and output data are complete and reliable. In reality, such an ideal is rarely achieved, if ever. Network interruptions, faulty sensors, and environmental disruptions frequently leave gaps in the record, while background noise, often with patterns of its own, can distort what remains. Conventional algorithms might falter under such conditions, producing biased results or unstable models that bear little resemblance to the real system. The new research takes a niftier approach, quietly adjusting to the data landscape and turning potential setbacks into advantages.
Its ingenuity lies in the combination of three distinct techniques. An auxiliary model estimates the unmeasured components of the system, extracting useful signals from what would otherwise be statistical clutter, an almost karmic reversal of bad data into good. An interpolation method then fills in the missing inputs by inferring plausible values from surrounding measurements. Finally, the process is quickened using Nesterov Accelerated Gradient optimisation, a mathematically elegant way of anticipating the best next step rather than taking each one blindly.
Together, these steps form the Interpolation-based Nesterov Accelerated Gradient (INAG) algorithm, a system that not only produces more accurate parameter estimates but does so faster than comparable methods, even in the presence of “coloured noise”, random fluctuations with structure and memory.
For engineers, better system identification means better control, whether in regulating industrial processes, stabilising power grids, or fine-tuning autonomous vehicles. For economists and climate scientists, it offers a way to make more reliable forecasts from incomplete or noisy data, potentially improving policy and planning.
Lu, H., Chen, J., Xu, F. and Mao, Y. (2025) ‘The Nesterov accelerated gradient algorithm for CARMA models with lost input data based on interpolation method’, Int. J. Modelling, Identification and Control, Vol. 46, No. 1, pp.38–46.
Research in the International Journal of Information and Communication Technology discusses a new framework that could be used to define how news and information are delivered. The approach could help us overcome some of the associated problems of media saturation and information overload. The approach allows for real-time, adaptive decisions about the flow of information in an age of media convergence as traditional journalism, digital platforms, and interactive technologies become increasingly intertwined.
The new approach side-steps the static, off-the-shelf distribution methods of conventional media and develops a system that can adjust output based on audience behaviour dynamically, tailoring content presented as user one’s interests change.
The approach integrates multimodal perception, the ability to interpret data from multiple sources such as text, images, and user interaction patterns, with reinforcement learning, a branch of artificial intelligence in which systems learn by trial-and-error guided by feedback. This combination allows the system to detect and respond to the gradual change in what an individual finds engaging over time, a concept known in psychology interest drift.
The researchers explain that their system works on three interconnected levels. First, it uses temporal attention mechanisms, which monitor how an individual’s focus changes over time, along with deep feature extraction to identify subtle behavioural patterns. This allows the system to anticipate shifts in audience engagement and adjust accordingly.
Second, it employs a hierarchical reinforcement learning architecture. In this design, complex decision-making is broken into layers, making it easier to balance competing objectives. Using a blend of deep learning methods and evolutionary algorithms, which mimic natural selection to find optimal solutions, the system maximises audience reach, ensures timely delivery, and minimises computational and network resource use.
The third layer introduces an adaptive regulation process using mathematical optimisation techniques. This component fine-tunes the balance between performance and resource consumption in real time, enabling the system to remain efficient even under fluctuating conditions.
The implications for journalism in areas where timeliness and accuracy are essential, such as public health, politics, and in emergencies and crises could be enormous. An adaptive, responsive delivery model should improve audience engagement and comprehension, the work suggests.
Zhang, Y., Liu, Y. and Guo, Z. (2025) ‘Optimising news dissemination pathways in the media convergence era: an interactive digital media technology approach’, Int. J. Information and Communication Technology, Vol. 26, No. 29, pp.110–126.
Forests play a far more important role in global climate regulation and ecosystem stability than previously understood, according to authors of an Industry Note in the International Journal of Agriculture Innovation, Technology and Globalisation.
Almost one third of the Earth’s land surface is forested, and we have recognised for many decades that forests act not only as sinks for atmospheric carbon dioxide, but they also act as components of the planet’s climate system, they affect temperatures, rainfall, and atmospheric composition through a complex mix of biological and physical processes. The Industry Note emphasise how we are increasing our understanding of these complex processes and finally acknowledging how non-linear, dynamic, and deeply interconnected they are.
The authors point out that while forests help mitigate climate change by absorbing carbon dioxide, when they are degraded or destroyed, they can accelerate warming. Beyond climate regulation, forests support biodiversity, purify water, protect soil, and provide resources and livelihoods to millions of people.
The article looks at the three main types of forest: tropical, temperate, and boreal, and considers the distinct climate and economic roles of each. Tropical forests, of the three, hold the largest share of biodiversity and sequestered carbon. However, they are the most threatened, largely due to deforestation and agricultural expansion. Temperate forests, common in mid-latitude regions, are valuable both as carbon sinks and for their timber production. Boreal forests, found in northern regions such as Canada and Russia, store immense amounts of carbon in soil and permafrost, making them important for long-term climate stability.
The Note points out that since 2000, global forest cover has declined by almost one eighth. We have lost an area about twice the size of Texas or more than the area of Germany, Italy, and Spain combined. In tropical regions, deforestation is mainly driven by land clearing for agriculture. In temperate and boreal areas, wildfires and large-scale logging are more common causes. Climate change further increases risks, making forests more vulnerable to droughts, pests, and fire. These pressures reduce the forests’ ability to absorb carbon and alter their structure and function, with consequences for biodiversity and environmental stability. The Industry Note emphasises that sustainable forest management is now a matter of urgency if we are not to see continued harms from the loss of this natural resource.
PDF: An, Z. and Chang, S. X. (2024) ‘Industry note: Forests are key to climate change mitigation and sustainable development‘, Int. J. Agriculture Innovation, Technology and Globalisation, Vol.4, No.4 pp.423-428.
Research in the International Journal of Shipping and Transport Logistics has looked at the problems of transporting hazardous materials where accidental and deliberate threats might cause serious problems, particularly in terms of potential terrorist activity.
Risk models for hazardous materials, hazmat, transport have usually focused on accidents caused by mechanical failure, human error, or environmental conditions. These models have been used to decide which routes transportation, whether road, rail, or marine, should take. The aim being to minimise the risks to life and the environment associated with accidental spills, fires, or explosions. However, since the early 2000s, intentional attacks on hazmat-transport has been of growing concern. Such terrorist activity has the potential for mass casualties, widespread environmental harm, and severe economic disruption.
The method discussed in IJSTL takes us a step further on by acknowledging the ubiquitous threat of terrorism and incorporating worst-case scenarios into the risk assessment from the first stages of planning onwards. The strategy takes into account tactical factors such as whether vehicles travel alone or in convoys, the spacing between them, the types of roads used, how quickly vehicles can travel under attack, and the likely weapons or tactics an attacker might employ.
The researchers explain that the model can be built into a Geographic Information System (GIS), a mapping tool that allows complex layers of data, such as road conditions, population density, and known security risks, to be analysed together. This level of information integration should allow route planners to identify transport routes that strike a balance between minimising for both accident and terrorism, rather than simply accounting for only one.
The team undertook a case study in one particularly troubled part of the world and demonstrated that their analysis would lead to different routing decisions. Routes that were considered optimal under traditional accident-only models were often very different when terrorism risk was taken into account. The terrorism-aware model favoured wider, well-maintained, multi-lane roads that allow higher travel speeds, reducing the time vehicles spend in potentially dangerous areas.
Yilmaz, Z. and Verter, V. (2025) ‘Simultaneous consideration of the accident and terror risks for hazardous materials transportation’, Int. J. Shipping and Transport Logistics, Vol. 21, No. 1, pp.1–38.
Research in the International Journal of Human Factors and Ergonomics has examined outpatient prescribing and found that overworked pharmacists as well as systemic workplace flaws can lead to dispensing errors. According to the World Health Organization (WHO), such errors remain a major and preventable cause of patient harm worldwide.
The researchers conducted their study in a large outpatient medical centre. They combined situational analysis, in-depth interviews, and detailed surveys to build a human-centred picture of medication and prescribing safety. Instead of framing mistakes as individual failings, the study focused on the environmental, cognitive, and systemic pressures shaping how well pharmacists performed in their roles.
Pharmacists commonly reported greater workloads than other healthcare professionals, with high time pressure and prolonged periods of standing, bending, and repetitive motion being problems they raised. Indeed, half of pharmacists reported persistent musculoskeletal discomfort over the past year, most commonly in the neck, shoulders, and knees. Notably, these symptoms did not vary significantly with years of experience nor specific job role. This, the researchers suggest, means that physical strain is an inherent feature of the current work environment for pharmacists rather than a temporary issue.
The study identified several key risk factors for dispensing errors: tiredness, frequent interruptions during work and pharmaceutical names and packaging that are very similar. These factors reflect both human vulnerabilities, such as cognitive overload, and systemic weaknesses such as inefficient workflow and poor packaging design.
The WHO has warned that medication-related harm is one of the top preventable causes of injury and death, and if counted as a disease, it would rank among the leading causes of mortality. Dispensing errors are thus part of a wider global challenge. Many such mistakes might be avoided by better working conditions for pharmacists and improved systems from the manufacturer’s production and packaging plant to the pharmacy shelves.
Su, K-W., Tsai, Y-T. and Feng, Q-K. (2025) ‘The multidimensional determinants of outpatient pharmacy dispensing errors: a mixed approach’, Int. J. Human Factors and Ergonomics, Vol. 12, No. 1, pp.20–40.
As laptops, notebook computers, become outdated as operating systems and software advance, and the hardware needed to support their myriad features becomes more demanding. As such, there is a growing problem of electronic waste (e-waste) from this particular sector as consumers replace effectively redundant devices with new ones. Millions of devices are discarded annually, so finding effective strategies to manage their environmental and social impact has become a global priority.
Research in the International Journal of Operational Research has focused on remanufacturing, the process of disassembling used devices, restoring or replacing, and even upgrading components, and rebuilding them to near-new condition. This approach not only reduces waste and conserves raw materials but also offers wider benefits such as creating jobs and making technology more accessible to lower-income users, given that a refurbished laptop may well be a lot cheaper than the latest model, but should in many cases be perfectly capable of running those advanced operating systems and software.
One of the big challenges in remanufacturing is deciding what to do with individual laptop components at end-of-life. These components vary widely in quality, and their potential for reuse is far from straightforward. High-quality parts are typically worth the cost of repair, but lower-quality ones present more difficult economic decisions. Yet, discarding them outright leads to the loss of materials that could otherwise be salvaged.
There is a lot of uncertainty in the various processes. So, the team has developed a sophisticated decision-making framework using a multi-period nonlinear integer programming model. This is a mathematical model designed to determine, over several time periods, the most cost-effective and resource-efficient use for each component, whether through reuse, conditional repair, or disposal. The approach uses advanced approximation techniques, metaheuristics, essentially a sophisticated form of trial-and-error to reduce the computing resources needed for the assessment. Metaheuristics can test, virtually, possible solutions and identify high-quality outcomes without having to examine every possibility in full detail.
Two such trial-and-error algorithms were auditioned for the job: Discrete Particle Swarm Optimisation (DPSO) and Genetic Algorithm (GA). DPSO is inspired by the behaviour of birds, fish, or insect flocks, shoals, and swarms. GA is based on natural selection and allows improved solutions to evolve over successive generations. Both were integrated into a decision support tool built in Microsoft Excel using Visual Basic. This choice should enable usability for business practitioners without expertise in complex mathematics.
The team found that on smaller problems, the algorithms produced answers that were close to the mathematically proven optimal ones. For larger-scale cases, GA proved more reliable, while DPSO occasionally settled on less effective outcomes. An important finding from the tests was that repair costs are a major factor in profitability of remanufactured laptops. This highlights the need for systems that can respond flexibly to changing economic conditions.
Anandh, G., PrasannaVenkatesan, S., Goh, M. and Kushwaha, G.C. (2025) ‘Optimising end-of-life laptop remanufacturing decisions using meta-heuristics‘, Int. J. Operational Research, Vol. 53, No. 4, pp.525-555.
Researchers have developed a new way to model how inventory behaves when both customer demand and supplier deliveries are unpredictable, and when missed sales cannot be recovered. The approach provides more accurate estimates than common industry rules-of-thumb, and so might help businesses avoid costly overstocking and damaging shortages.
The work, discussed in the International Journal of Integrated Supply Management, builds on the Economic Order Quantity (EOQ) model. This is a well-known tool for helping stock controllers decide how much to order. The standard EOQ assumes that demand is steady and deliveries arrive on time. The new model is more realistic and recognises that demand and supply can vary from day to day.
In their model, each day’s demand and supply are treated as a series of simple “yes or no” events: a unit is either sold or not, and a unit is either delivered or not. In probability terms, these are called Bernoulli trials. When combined over several days, familiar statistical patterns emerge in the distribution for demand and the geometric distribution for delivery times. This approach allows the model to capture both steady daily sales and highly irregular, demand.
The researchers were able to calculate an exact “steady-state” picture of how much stock a business is likely to have on hand in the long run, after short-term fluctuations even out. To do this, they used a Markov chain, a type of mathematical model in which the next step depends only on the current state, not the full history.
From this steady-state analysis, the model gives precise numbers for important measures: the average inventory level, how long an inventory cycle lasts, how often the business runs out of stock, and the “fill rate”. Fill rate is the share of customer demand that can be met immediately from stock. One key result is a new formula for average inventory that has been shown to work better than the current estimation tools, especially when demand is patchy and deliveries are unreliable.
The researchers explain that this matters in many real-world situations where lost sales are permanent. A supermarket cannot sell yesterday’s spoiled fruit, a retailer cannot ship a promotional item after the promotion ends, and a factory may lose an urgent order for spare parts if they are not in stock at the moment they are needed. In all such cases, even small errors in estimating average inventory can have significant financial and reputational costs.
Gebennini, E., Grassi, A. and Santillo, L.C. (2025) ‘Discrete-time EOQ with lost sales, binomial demand, and geometric lead time: inventory level distribution and performance analysis’, Int. J. Integrated Supply Management, Vol. 18, No. 5, pp.1–35.
The following International Journal of Integrated Supply Management article, "Discrete-time EOQ with lost sales, binomial demand, and geometric lead time: inventory level distribution and performance analysis", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Hydrology Science and Technology article, "Impact of spatial filtering to GRACE-FO-derived TWS changes: a case study of European river basins", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Shipping and Transport Logistics article, "Can air transportation reach to zero carbon emissions: comparative econometric analysis between transportation modes in the USA", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Business and Emerging Markets article, "The impact of sustainability disclosure on financial statement value relevance: evidence from Europe", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Wireless and Mobile Computing article, "Research on adaptive artificial potential field obstacle avoidance technology for unmanned aerial vehicles in complex environments", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research in the International Journal of Hydrology Science and Technology has shown that conventional approaches to measuring water storage across Europe’s complex river systems may significantly under-represent the scale and severity of changes linked to climate change.
The Earth’s gravitational field is not uniform, it changes slightly depending on the presence of mountains, where the oceans, are even levels of groundwater. Indeed, when large amounts of water move through heavy rainfall, melting glaciers, or groundwater depletion, they change the local gravitational field by a small amount. Conventionally, these changes have been detected by a technique known as satellite gravimetry. NASA’s GRACE (Gravity Recovery and Climate Experiment) and GRACE-FO (Follow-On, its successor), use satellites flying in tandem to measure the tiny gravitational changes. In turn, the technique can then be used to monitor changes in natural water storage in a region, such as Europe.
However, the new research has compared traditional and data-driven filtering techniques used to interpret data from GRACE-FO. The researchers found that newer, model-independent approaches offer more accurate results, particularly in capturing droughts and floods in Europe’s complex system of rivers.
The main issue with the old approach is that the data from the satellites has low spatial resolution and is affected by signal interference from neighbouring regions. This latter issue, known as leakage, makes interpreting the raw data a technical challenge. To reduce noise and clear up the signals, researchers apply mathematical filters, such as Gaussian smoothing. The new study shows that this conventional method can introduce errors in regions with irregular geography, such as coastlines and densely interlaced river basins, characteristics common across the continent of Europe.
The researchers have evaluated two data-driven techniques: the “method of scale” and the “method of deviation,” which use only the satellite data rather than putatively biased external hydrological models. They showed that method of scale reduce measurement uncertainty to less than 15%.
This improvement has practical implications for understanding three European river basins, the Rhone in France, the Neman on the Belarus-Lithuania border, and the Vuoksi-Neva in Finland and Russia. The new approach provides a clearer and more precise view of how water levels respond to extreme weather events.
Europe is already experiencing more frequent and severe droughts, with disproportionate effects on its smaller river basins. These catchments are limited in water storage and often highly sensitive to climatic fluctuations, but nevertheless form the backbone of many regional water systems. More accurate monitoring is critical to policymakers attempting to respond to changes.
Lenczuk, A. (2025) ‘Impact of spatial filtering to GRACE-FO-derived TWS changes: a case study of European river basins‘, Int. J. Hydrology Science and Technology, Vol. 20, No. 5, pp.1-30.
The following International Journal of Information and Communication Technology article, "Optimising news dissemination pathways in the media convergence era: an interactive digital media technology approach", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of XXX article, "FAF-Text: English text detection based on feature selection and adaptive fusion mechanism", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research in the International Journal of Shipping and Transport Logistics has analysed four decades of freight transportation data across the USA and shows how different modes of transport contribute to carbon dioxide emissions. The work reveals a complex picture wherein transportation is indeed a major source of greenhouse gases, alongside electricity generation, but air, rail, road, water, and pipeline make different contributions to the problem.
The researchers used an Autoregressive Distributed Lag model to consider both short-term and long-term relationships between transportation activity and emissions. This allowed them to smooth out the information even when the underlying data are uneven. Such a level of detail is uncommon in climate and transport studies, which often focus on a narrower time frame or fewer transport categories.
Surprisingly, a negative relationship between both air and pipeline transport and carbon emissions over the period 1980 to 2022 showed that even as these two forms of freight activity increased, emissions actually declined slightly: by 0.03% for every 1% rise in air transport activity, and by 0.06% for pipeline transport. Such figures seem small, but they could be statistically meaningful when scaled across the vast transport systems of the USA and over several decades. The findings suggest that adoption of cleaner technologies, especially in aviation, is having an effect. Innovation in the road and rail sectors could reap similar rewards, the research suggests.
The various interdependencies suggest that emissions, energy consumption, and transport activity are all so closely intertwined that coordinated policy responses is now essential rather than isolated reforms if we are to achieve net-zero.
The researchers suggest that by breaking down the environmental impact of individual transport modes, it is possible to develop more targeted climate strategies. For example, expanding pipeline infrastructure or accelerating the rollout of sustainable aviation technology may deliver greater emissions reductions than blanket policies applied across all transport sectors.
Ergen, H., Aslan, A. and Ayvaz, E.E. (2025) ‘Can air transportation reach to zero carbon emissions: comparative econometric analysis between transportation modes in the USA’, Int. J. Shipping and Transport Logistics, Vol. 21, No. 1, pp.71–99.
The following International Journal of Information and Communication Technology article, "Traditional settlement spatial landscape generation and optimisation using multidimensional GlS data driven method: a case study of Fujian province", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Imparting traditional wisdom and political knowledge through deep tracking and knowledge graph model", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Career planning and pathway generation based on multimodal learning analytics", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Application and performance analysis of LSTM networks in polyphonic popular music generation", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Artificial intelligence-driven visual feature extraction and transfer learning for automatic identification of paintings and photographs", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research conducted at a Chinese university and reported in the International Journal of Computational Systems Engineering has looked at how machine learning and big data techniques might be used to identify the most influential factors in English language learning for non-English majors. The researchers analysed the academic progress of 1,805 students using a refined machine learning model and found that student motivation was the single most important driver of improvement, outweighing even the teaching methods or mode of instruction.
The findings emerged from an analysis using an advanced decision tree algorithm, an enhanced CHAID (Chi-squared Automatic Interaction Detector) decision tree coupled with a genetic algorithm that filters out irrelevant data and has improved predictive accuracy.
A decision tree is a machine learning model that maps the relationships between variables in a branching format. The CHAID variant is particularly suited to education research, as it handles categorical variables well, including learning environments and teaching styles. By enhancing the CHAID algorithm with genetic programming, the researchers were able to evolve the decision model iteratively, improving its ability to identify key patterns in the student data.
The primary metric analysed was the percentage of students making notable progress. Just under 20 percent of students in the sample, 352 individuals, met this threshold. The model was then tasked with identifying what differentiated these students from the majority.
The answer, the researchers found, lay first and foremost in student motivation. Whether driven by career ambitions, academic goals, or personal interest, a student’s reason for studying English had the strongest correlation with measurable improvement. Teaching methods, ranging from interactive approaches to more traditional lecture formats, ranked second in influence, followed by the mode of instruction, whether face-to-face or online learning.
English continues to serve as a bridge language in academia, commerce, and international dialogue, so effective English instruction is a priority in educational institutions around the world. The study provides a new insight into how teaching might be improved, specifically in China, but perhaps elsewhere too.
Cai, H. (2025) ‘A study on the optimisation of university English teaching based on an enhanced decision tree model in the context of big data’, Int. J. Computational Systems Engineering, Vol. 9, No. 12, pp.1–11.
The following International Journal of Continuing Engineering Education and Life-Long Learning article, "College students' willingness to continue using MOOC platform: configuration analysis based on FSQCA method", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Computational Systems Engineering article, "Social network user browsing trajectory detection based on soft computing to promote a healthy environment", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research in the International Journal of Continuing Engineering Education and Life-Long Learning has looked at why some students persist with Massive Open Online Courses (MOOCs) while many others quietly drop out. It is an issue that has long dogged the promise of online education.
MOOCs have been with us since the late 2000s. Initially, they were touted as the means to democratize education by making high-quality university-level content available globally, often for free. They have to some extent fulfilled that early promise and countless MOOCs have since given access to millions of learners, often in remote, underserved, or economically constrained contexts. Fundamentally, MOOCs allow students to learn at their own pace and on their own terms. Yet despite the obvious putative reach and their appeal, MOOCs continue to suffer from notably low retention and completion rates. There is a gap between the initial enthusiasm of new students and their ongoing engagement or otherwise.
In the current work, the team has turned to a statistical technique known as Fuzzy Set Qualitative Comparative Analysis (FSQCA) to look for multiple causes of MOOC dropouts. FSQCA can be used to examine how combinations of conditions work to produce a given outcome. In the case of MOOCs, the approach has looked at how different complex and context-dependent factors lead to students persisting or failing to complete a course.
Five interrelated factors are thought to affect outcomes. First, the quality of the online system, its reliability and usability. Second, the content quality of the course itself, the learner’s engagement, referred to as learning presence. Third, the influence of other students or mentors. Fifth, self-efficacy, the students’ belief in their ability to succeed. No single factor could be used to reliably predict whether a student would stick with a course or drop out.
The FSQCA approach found three distinct configurations, or “recipes” in the jargon of the system, that affected outcomes. For example, one recipe recognised combined strong content quality, high self-efficacy, and positive social influence. Another emphasized system usability and learner engagement. Each recipe suggests that course retention depends on various factors, either in or out of balance.
The findings have implications for how MOOCs are developed and improved. Platform providers, universities, and instructional designers must think more holistically about their potential students. Improving technical infrastructure or offering well-produced video lectures alone will not lead to better retention. Instead, interventions must be multifaceted, they must build technically user-friendly platforms, but also foster support communities, enhance instructional design, and assist students in building confidence over time.
Chen, J. and Chen, G. (2025) ‘College students’ willingness to continue using MOOC platform: configuration analysis based on FSQCA method’, Int. J. Continuing Engineering Education and Life-Long Learning, Vol. 35, No. 7, pp.1–18.
The following International Journal of Computational Systems Engineering article, "A study on the optimisation of university English teaching based on an enhanced decision tree model in the context of big data", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A new approach to sniffing out user behaviour on social networks could improve how service providers understand and respond to their users’ needs. The work discussed in the International Journal of Computational Systems Engineering offers a more accurate way to track “browsing trajectories”, the path a user takes through a sequence of pages and content. Critically, the approach cleans up this data by filtering out the digital noise that has always been the bane of such analyses.
Social networks generate huge amounts of data, much of it ambiguous, inconsistent or irrelevant. For researchers and developers trying to spot patterns in this activity, for example, those running content-recommendation systems or monitoring user wellbeing, this is a significant problem. Current systems struggle to distinguish between signal and noise, which means any analysis leads to less effective personalisation and an increased risk of information overload for users.
The new approach integrates several computational tools, including “fuzzy logic”, which can handle uncertainty in a way that binary logic cannot. Fuzzy logic can thus model ambiguity in human behaviour online. A second tool is the use of a “random forest learning algorithm”, which can handle large and complex datasets and offer several decision trees by combining outputs to improve how well the system predicts behaviour. The third tool is “matched filtering”, a technique borrowed from signal processing, that detects patterns within noisy data.
When combined, these tools allowed the researchers to isolate meaningful user behaviour among irrelevant or redundant data and so boost the signal-to-noise ratio. In subsequent simulations, the team was able to achieve up to 93 percent behaviour-prediction accuracy. Such precise analysis of browsing trajectories might help social platforms serve content that more closely matches what users are actually looking for, increasing satisfaction while reducing exposure to irrelevant or disruptive material.
Cai, Q. (2025) ‘Social network user browsing trajectory detection based on soft computing to promote a healthy environment’, Int. J. Computational Systems Engineering, Vol. 9, No. 12, pp.12–21.
The following European Journal of International Management article, "The role of digitalisation in firms' international value creation: an integrative conceptual framework and a research agenda", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Modelling and trend analysis of student idea propagation paths facilitated by intelligent recommendation algorithms", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Intelligent generation of robotic dance motions via convolution-enhanced transformer networks", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Legal framework development through adversarial transfer learning for consumer grievance classification in algorithmic price discrimination contexts", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Intelligent optimisation of traditional village element layout using generative adversarial networks", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
As international companies face increasingly volatile conditions around the world especially in the face of rapid technological change, a study in the European Journal of International Management has looked at how they might systematically understand the way in which digital technologies are reshaping business strategies.
The research introduces the concept of Digital International Value Creation, a model that explains how businesses can use their digital capabilities to create added value in their international operations. Far beyond improving back-end efficiency, digitalisation, defined here as the transformation of an organisation’s products, services, and processes into internet-compatible formats, is now an integral component of corporate activity.
Information and communication technology has, of course, supported international firms for many years by enabling more coordinated and efficient global operations. However, the current study argues that recent digital advances represent a structural shift. The new tools are creating new modes of international expansion, particularly for firms that were once limited by their geographic or organisational constraints.
The researchers outline three pathways already being taken by companies. The first involves enhancing existing operations with digital tools. The second considers how digital-native firms have been expanding globally from the outset. This involves historically parochial firms now using digital platforms to enter global markets for the first time. The research shows that whichever path is being taken, digital adoption alone is insufficient for ongoing global success. Rather, success depends heavily on how well firms align their technological strategies with their internal structures and the external environments in which they operate. The researchers add that political stability, legal frameworks, and cultural compatibility can all affect how well digital tools perform in different regions.
The team suggests that companies need to re-imagine digitalisation not as a supporting function but as a central component of their international strategy. This perspective is especially pertinent for small and medium-sized enterprises (SMEs), which often face significant barriers to digital adoption but also stand to benefit from the agility and reach these technologies offer.
Halpern, C. and Fernández-Méndez, L. (2025) ‘The role of digitalisation in firms’ international value creation: an integrative conceptual framework and a research agenda’, European J. International Management, Vol. 27, No. 5, pp.1–42.
The following International Journal of Information and Communication Technology article, "Automatic generation of landscape images based on deep generative modelling", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Enhancement of accuracy and analytical efficiency of gymnastics video using convolutional neural network and semantic analysis approach", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Intelligent detection of rail transit vehicle wheelsets combined with structured light technology", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Value Chain Management article, "Barriers of SME engagement in mission-oriented innovation", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research in the International Journal of Value Chain Management sheds light on a blind spot in how society is tackling complex problems such as climate change, inequality, and food insecurity. There is, the work found, an underrepresentation of small and medium-sized enterprises (SMEs) in public innovation strategies. The researchers focused on the Uppsala region of Sweden and investigated why SMEs, which are often key sources of innovation and adaptability, struggle to engage with the kind of mission-orientated innovation that could help us address the big challenges we face.
Such challenges are large-scale, interlinked societal issues that cannot be solved by a single actor or sector. So, mission-oriented innovation, a framework being used increasingly by governments and institutions worldwide, breaks up the big challenges into smaller measurable missions. Rather than pursuing incremental technological development or narrowly defined market goals, mission-oriented innovation brings together public authorities, the private sector, and civil society in pursuit of transformative objectives. Such missions might include achieving carbon neutrality in city transport or eliminating food waste in national supply chains.
This research suggests that SMEs have all but been forgotten in defining mission-oriented innovation and yet the participation of SMEs, because of their size and flexibility, could be massively beneficial. Through interviews with the owners of SMEs and public sector representatives, the researchers found that there are three structural barriers to the inclusion of SMEs in mission-oriented innovation.
The first is a lack of awareness among many SMEs. This could be address through more effective communication from government bodies and coordinating agencies. Secondly, SMEs face constraints related to resource allocation. With a smaller workforce and tight budgets, these businesses often cannot afford the time nor the investment to participate in longer-term innovation missions. Public actors could solve this by prioritizing appropriate funding mechanisms or institutional support. Thirdly, there are domain differences. These are cultural and operational mismatches between the public and private sectors. Public institutions and SMEs often approach problems with different timelines, risk tolerances, and definitions of success, making sustained cooperation difficult.
As such, there is an urgent need to put in place mechanisms to bridge the gap between SMEs and public missions so that governments can bring a part of the economy into plans for the systemic change needed to address big issues.
Strömqvist, J., Hilletofth, P., Muhos, M., Saarela, M. and Virkkala, P. (2025) ‘Barriers of SME engagement in mission-oriented innovation’, Int. J. Value Chain Management, Vol. 15, No. 5, pp.1–23.
The following International Journal of Logistics Systems and Management article, "Logistics service system: review, case study, and framework", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Economics and Business Research article, "The asymmetric impact of global economic policy uncertainty on inflation in Egypt", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Power and Energy Conversion article, "Optimisation of FLUKA's cyclotron model for safety assessments: accuracy and uncertainty analysis in neutron ambient dose equivalent H*(10)", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Ink painting classification method based on deep feature fusion", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
As digital technologies continue to transform the logistics industry, research in the International Journal of Logistics Systems and Management has looked at their impact on the wellbeing of professional drivers, namely truckers. The researchers conducted in-depth interviews and drew in survey data in Germany to look at his digital tools are reshaping the technical aspects of the job but also the lived experience of those behind the wheel.
Drivers report that digitalisation, ranging from GPS tracking to automated route planning, can reduce physical demands, streamline communications, and even contribute to improved safety. Systems designed to optimise routes and schedules, for example, reduce stress by minimising delays and helping drivers make more informed decisions in real time. In some cases, these innovations enhance the driver’s sense of control, contributing to greater overall job satisfaction.
However, the research also shows that there are some drawbacks. Many drivers express unease about the level of surveillance enabled by digital tools. There is constant monitoring, whether through location tracking, in-cab cameras, or real-time performance metrics, and they often feel this to be intrusive and to erode their sense of independence. Given that independence is often central to the identity of professional drivers, this is not a positive outcome of the adoption of digital technologies. Indeed, some interviewees suggested that it was akin to being “micromanaged by a machine” and this was detrimental to their job satisfaction and psychological wellbeing.
The study identifies driver perceptions as a crucial determinant of how digitalisation is experienced. Those who see digital tools as supportive tend to report greater benefits, such as feeling safer or more efficient. In contrast, drivers who are more sceptical of these technologies are likely to experience them as a source of pressure or even alienation. This divide underscores the importance of the human factor in digital transitions: technological change is not experienced uniformly, and its impact depends heavily on individual attitudes and workplace culture.
For logistics companies, the implications are particularly will be difficult to navigate. Their drivers play a critical role in keeping supply chains functioning, yet their voices are often underrepresented in discussions about innovation. The research argues for a more inclusive approach to digital transformation, one that takes into account not just productivity and profit, but also encompasses driver wellbeing.
Straub, S.M. and Ruiner, C. (2025) ‘For better or for worse? How the use of digital technologies affects truck drivers’ wellbeing’, Int. J. Logistics Systems and Management, Vol. 51, No. 3, pp.420–449.
