The following International Journal of Services and Operations Management article, "How lighthouse companies are pioneering Indonesia's Industry 4.0 and 5.0 revolution? A soft system methodology 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 Business Innovation and Research article, "Innovating for performance: the role of lean construction and strategic partnerships in construction firms", is freely available for download as an open access article.
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Digital payments are a routine part of daily life for many people. As such, the risk of online fraud is rising alongside this convenience. Identity theft, email compromise, scams, and misleading investment schemes all exploit technological weaknesses and often user naivety and can lead to big financial losses.
Research in the American Journal of Finance and Accounting has looked at technological threat avoidance theory (TTAT), a framework used to understand how individuals respond to technology-related risks. The study sheds new light on what motivates users to protect themselves from online financial threats, if they do at all. It considers user attitudes towards fraud and the perception of potential financial loss with the aim of identifying the specific influences that lead to a user taking protective action.
The team surveyed users of online payment platforms and found that rather than an abstract fear of fraud, the decisive factor in whether or not people took preventative measures was simply the perceived financial loss. This finding suggests that awareness campaigns focused on general threats may be less effective than approaches that point out the direct financial consequences of online fraud.
Online fraud costs us roughly US$1 trillion per annum, and it is likely that figure is rising year on year. There are millions of reported cases and probably many more that are never reported. The losses that people bear when a victim of online fraud erodes overall trust in the digital systems on which we rely. Moreover, widespread, organised fraud can disrupt financial infrastructure, threatening broader economic stability and making it almost impossible for regulators to maintain oversight and control.
Facing such problems, the digital economy needs technological innovation in payment systems to incorporate effective strategies to influence user behaviour. Such strategies need to make it difficult for users to compromise themselves through technological naivety. Policymakers, platform developers, and financial educators also need to help in the design of interventions that align perceived risk with actual behaviour and so strengthen the individual against threats as well as help maintain trust in digital financial systems.
Peswani, R. and Vijay, P. (2026) ‘Minimising exposure to cyber frauds in digital finance: perspectives from technology threat avoidance theory’, American J. Finance and Accounting, Vol. 9, No. 1, pp.76–98.
The following International Journal of Computational Systems Engineering article, "RBF neural network model construction for enterprise financial big data analysis", is freely available for download as an open access article.
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The following Journal of Business and Management article, "The effect of in-store employee retail technology on employee well-being: based on the job demands-resources model", is freely available for download as an open access article.
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The following Journal of Business and Management article, "The COVID-19 pandemic effects on FDI in select emerging economies", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Personalised learning path generation mechanism based on RL and knowledge graph", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Analysis of tourist emotions and behaviour patterns using deep learning", is freely available for download as an open access article.
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The migration to electronic medical records, used by healthcare providers, hospitals, and medical insurers, continues. However, this switch from paper records is leading to an accumulation of data, a lot of which is in free-text form that cannot be processed easily by an algorithm searching for knowledge and looking for patterns.
A study in the International Journal of Business Process Integration and Management has looked at using basic text-mining methods to convert this free text, which might be as unsophisticated as the jottings of a doctor or nurse, into something more organised. This kind of processing could make decisions in medicine faster and more consistent as well as potentially opening up new avenues for medical research and epidemiology.
The research focused on the specific medical condition of lower back pain and the reports associated with it. Lower back pain is a big problem for a lot of people and a major reason people miss days in work or file for disability. Experts can evaluate symptoms and consider what medical scans show and make a diagnosis and offer a prognosis. Administrators have to read through reports manually to determine fees and payments. A system to convert free text to structured text would be a boon, allowing dates and diagnoses to be searched, checked, and analysed much more easily.
The team used pattern-matching rules to look for regular expressions that allow software to detect specific phrases or formats in text. This could then be used to extract clinical and administrative details. This rule-based text mining was combined with machine learning algorithms that can learn from past data and make predictions about new cases.
The researchers tested their system on 255 anonymised reports. Medical specialists validated the extracted information, confirming a precision rate of 98 per cent. The structured information was then used to train three established predictive models: AdaBoost, which combines multiple simple models to improve accuracy; Random Forest, which aggregates the results of many decision trees; and Support Vector Machines, which identify boundaries between categories in complex datasets.
In tests, AdaBoost achieved perfect accuracy in predicting when rest should be prescribed. Random Forest reached 91 per cent accuracy and 93 per cent recall, a measure of how many relevant cases are correctly identified, in return-to-work assessments. The Support Vector Machine recorded a 98 per cent recall rate in classifying disability cases.
Beyond performance metrics, the researchers argue that the approach reduces processing time and limits transcription errors. Because the extraction rules are explicit, the system remains interpretable. This is important, as decisions still need to be explained to patients and others regardless of how structured or unstructured the data is.
Zwawi, R., Elhadjamor, E.A., Ghannouchi, S.A. and Ghannouchi, S-E. (2025) ‘Optimising text mining applications for enhanced medical decision making’, Int. J. Business Process Integration and Management, Vol. 12, No. 4, pp.295–306.
The following International Journal of Information and Communication Technology article, "Natural language processing for automatic error detection in Chinese language learning", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Prediction of uncertain passenger flow in scenic spots by fusing multi-source data and integrated learning", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "A study on AI-assisted interactive experiences for the preservation of ethnic culture in a mixed reality platform", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Interactive study of AI-music experiences in virtual reality on psychological comfort", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "A multi-agent reinforcement learning approach to heterogeneous resource allocation in lifelong education", is freely available for download as an open access article.
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As self-driving, autonomous, vehicles head out on to public roads, one of the field’s most persistent challenges remains collision avoidance in unpredictable traffic. A study in the International Journal of Vehicle Design discusses an artificial intelligence (AI) control system that has a 97 per cent success rate in avoiding obstacles, with a maximum response time of about half a second.
Urban roads present a shifting landscape of pedestrians, stalled vehicles, roadworks and erratic drivers. For a self-driving car, safe operation depends not only on accurate sensors but also on rapid decisions made under such uncertain conditions. Conventional obstacle-avoidance systems often rely on fixed rules or straightforward processing of sensor data. These approaches can sometimes fail in heavy rain, fog, or headlight glare.
Other systems that use reinforcement learning, a branch of AI in which the algorithm learns by trial and error, such as Deep Deterministic Policy Gradient, need a lot of computing power and often struggle to work quickly enough for real-world driving conditions.
The new approach described in IJVD builds on a reinforcement learning framework called Soft Actor-Critic, or SAC. In this computing system, the software actor proposes driving actions while the software critic evaluates whether or not the given manoeuvre would be sensible or not. SAC is designed to learn so that positive outcomes boost the actor-critic interactions that led to them. The system also embeds entropy, a statistical measure of randomness that allows it to continue to explore the best manoeuvres rather than settling prematurely on a single solution. This helps the system remain adaptable in uncertain environments.
The model also incorporates a self-organising cluster mechanism inspired by the collective movement of a flock of birds, that famously avoid mid-air collisions. At close range, a mathematically defined repulsion force pushes vehicles apart to prevent impact. At medium distances, a velocity calibration rule aligns speed with an ideal braking curve to reduce the risk of rear-end collisions. Additional rules govern wall and obstacle avoidance. This layered design allows multiple autonomous vehicles to coordinate their movements without relying on a single lead vehicle.
Ma, Y., Qian, Y., Ma, T., Li, Y. and Wan, J. (2025) ‘Intelligent obstacle avoidance control method for autonomous vehicles based on improved SAC algorithm’, Int. J. Vehicle Design, Vol. 99, No. 5, pp.1–19.
The following International Journal of Information and Communication Technology article, "Animation generation of traditional ethnic elements based on memory-enhanced self-supervised networks", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Cross-node knowledge transfer and generalisation based on federated meta-learning in fog computing", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Transfer learning-based adaptive music teaching system for modulating students' emotions", is freely available for download as an open access article.
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A study in the Journal of Business and Management has shown that self-esteem plays an important part in determining whether someone wishes to pursue a leadership role. The findings have implications for both organisational success and career development, underscoring, as they do, how self-esteem affects personal motivation.
The research suggests that self-esteem affects a person’s regulatory focus, a psychological framework that influences how individuals approach challenges and goals. There are two main types of regulatory focus: promotion focus and prevention focus. Promotion focus is characterised by a drive for growth, achievement, and opportunity-seeking. In contrast, prevention focus is concerned more with the avoidance of failure, staying safe, and fulfilling one’s basic duties and no more.
Individuals with high self-esteem are more likely to be promotion focused, which then drives them to seek leadership roles. Those with lower self-esteem tend to lean towards prevention focus, which makes them less inclined to pursue leadership roles.
The effect is not solely down to the individual’s personality, however. The work also showed that career encouragement and support from supervisors and peers can affect a person’s focus and the motivational pathways they might take. Encouragement can boost the positive effects of promotion focus, motivating individuals to pursue leadership. However, for those with lower self-esteem, encouragement can have the opposite effect, reinforcing their reluctance to take on leadership responsibilities due to their prevention focus. The research thus highlights a need to consider individual psychological states when offering career support so that talented people who have leadership potential are not lost to those roles because of their lower self-esteem.
The team adds that unlike static predictors, such as personality traits or gender, regulatory focus can be affected by one’s experiences and external support. This makes it a more pliable characteristic that might be influenced to the person’s benefit through good career development advice for those with the potential for leadership.
Guo, J. (2025) ‘Regulatory theory and career encouragement in explaining leadership aspiration’, J. Business and Management, Vol. 30, No. 2, pp.75–98.
The following International Journal of Information and Communication Technology article, "Multi-objective optimisation of shield synchronous grouting materials: a synergistic architecture integrating intelligent algorithms and convolutional neural network", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "AI-driven recommendation for personalised physical education training", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Social network news dissemination and detection model based on multi-scale information", is freely available for download as an open access article.
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The following Journal for International Business and Entrepreneurship Development article, "Research on women's entrepreneurship in Saudi Arabia: a bibliometric analysis and research outlook", is freely available for download as an open access article.
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Research into the COVID-19 crisis, which began in December 2019, suggests that although there was widespread loss and disruption, the international crisis also planted the seeds for grassroots innovation and resilience. A study in the International Journal of Entrepreneurial Venturing of one hundred initiatives that emerged in Belgium during the pandemic finds that when established institutions struggled to respond quickly, individuals and organisations were able to step up to create new economic and social value.
The research focuses on initiatives defined broadly to include both newly created ventures and existing organisations that adapted their activities. These ranged from informal mutual aid efforts to repurposed businesses and newly launched services. Some were started by people with no prior experience of entrepreneurship. Other initiatives were started by established entrepreneurs responding to the sudden changes in demand and regulation. What they shared was a capacity to adjust rapidly under pressure.
The pandemic created conditions of extreme uncertainty. Lockdowns and business closures, imposed to limit the spread of the virus, caused sharp falls in income, consumption, and investment. Many people perceived formal support systems as too slow or rigid to meet urgent needs. This gap became the space in which these initiatives emerged, often spontaneously and with limited resources.
The study looks at this kind of resilience and rather than treating it simply as endurance in the face of a crisis, defines it as a dynamic process of recovery, adjustment, and innovation. Resilience was, during the pandemic and in its aftermath, both the route through which initiatives developed and the results they produced. The researchers argue that action was not driven solely by compassion or urgency, but by the ability to reframe the crisis as an opportunity to meet unmet needs.
The study suggests that locally driven, resilience-based initiatives can complement government and aid responses, particularly in the early stages of a crisis. As such, for policymakers, the challenge is how to recognise and sustain such efforts without undermining their flexibility. We will face pandemic and other shocks in the future, our ability to adapt and innovate in these conditions will be key to an effective disaster response.
Wuillaume, A., Ferritto, A. and Janssen, F. (2025) ‘A note on resilience in the face of adversity when small droplets trigger big changes’, Int. J. Entrepreneurial Venturing, Vol. 17, No. 3, pp.249–273.
The following International Journal of Business Information Systems article, "The impact of strategic vigilance on enhancing organisational effectiveness: exploring the mediating role of strategic readiness", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Multi-instrument polyphonic automatic transcription method combining gated recurrent units and DeepLabv3+ model", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "An athlete motion recognition model based on machine learning and the internet of things", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Multi-objective optimisation of cigarette tobacco leaf blend formulation based on sensory-chemical correlation and machine learning", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Optimisation of PID control for tobacco feeding rail based on convolutional neural network", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Graph attention network-optimised cigarette logistics cost modelling in multiple constraints", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Application of deep reinforcement learning in sports competitive decision-making", is freely available for download as an open access article.
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The following International Journal of Information and Communication Technology article, "Latin dance action style transfer based on improved Ada IN algorithm", is freely available for download as an open access article.
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