The following Journal of Business and Management article, "Mapping the nexus: a bibliometric review of psychological distress and leadership research", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A study of 500 Thai retailers has found that businesses with stronger big data analytics capabilities tend to be better at identifying market needs, innovating, and executing effective marketing strategies. Moreover, large retailers report higher capability levels than smaller firms, according to research in the International Journal of Services and Operations Management.
The research looked at how some 500 retailers turned customer, transaction, and sales-channel data into practical business capabilities. The findings suggest that the adoption of digital technology is not sufficient to improve outcomes, companies need big data analytics capability to make the most of that technology. Indeed, the research shows that having the ability to process and interpret large volumes of information to make better decisions was closely tied to market orientation, customer needs, and changing market conditions.
The team explains that their findings highlight the importance of integrating data analysis into everyday operations. This is particularly important as companies have to coordinate bricks-and-mortar outlets with their online presence. Better integration, the team suggests, could help businesses adapt services and respond more consistently to changing demand.
The gap between large and smaller retailers, however, raises questions about unequal access to digital expertise, technology investment, and managerial resources. Smaller and medium-sized enterprises (SMEs) perhaps need targeted support to develop the skills and organisational routines required to turn data into useful decisions.
Supapon, S. and Sukhawatthanakun, K. (2026) ‘Data-driven retail service operations: big data analytics capability, market orientation, innovation and marketing capabilities in Thailand’s retail sector’, Int. J. Services and Operations Management, Vol. 55, No. 5, pp.1–23.
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Researchers have developed an automated system for detecting fake news that achieved accuracy rates above 98% in tests on two datasets; in other words missing just one or two fake news items in every 100. They provide details of their approach in the International Journal of Information and Computer Security.
The new system uses a transformer encoder, an artificial intelligence (AI) model that identifies relationships between words and their context. This is combined with a deer-hunting optimisation algorithm (DHOA), a computational technique for finding effective model settings, based on modelling the way in which human hunters track and pursue prey. The researchers removed web addresses, punctuation, and common, or “stop”, words before applying their analysis to the text. The DHOA component automatically fine-tunes the model's settings rather it requiring manual selection and calibration.
Automated detection could accelerate manual fact-checking, which is often expensive and time-consuming, allowing social media platforms to screen out misleading claims quickly to avoid their rapid spread.
The next step will be to test the system on real-world social media content to see whether it can distinguish between deceptive material closely resembling legitimate reporting. As it stands, the approach is limited to text, rather than checking for the manipulation of images, deepfake videos or inconsistencies between text and visual evidence. Future work might explore how those different media types might be processed and analysed as well as looking for relationships between content and the users who post it as important clues as to whether a given item is fake news or not.
Jonnala, Y.D. and Devi, J.S. (2026) ‘Automatic fake news detection using an optimised transformer with deer hunting optimisation algorithm’, Int. J. Information and Computer Security, Vol. 31, No. 1, pp.24–48.
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The following International Journal of Environment and Pollution article, "Study on detection method for harmful chemical residues in regenerated cellulose food packaging materials", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A study of electronic banking users has found that cybersecurity depends not only on knowledge of digital threats but also on attitudes, memory, and the user’s relationship with technology. Details are published in the International Journal of Information and Computer Security. The researchers looked at how customers translate cybersecurity knowledge into behaviour. The work addresses a gap in this area of research, which has previously focused largely on employees rather than customers.
The team used structural equation modelling, a statistical technique for testing relationships between variables, to analyse survey data from 772 electronic banking users in India. The survey asked questions about the users’s extended knowledge, attitude, and behaviour. The resulting framework shows what people know and what they believe influences their actions.
Perhaps obviously, the team found that a bank’s efforts to educate customers with regard to cybersecurity as well as the initiatives of customers themselves, help build overall knowledge. Customers with a positive attitude towards security, who can recall relevant information and have greater knowledge of the risks and how to avoid them, were like to exhibit safer online behaviour.
However, the more technically minded a customer, the more likely there were to have a positive attitude towards their banking security, but the more likely they were to take risks, assuming their familiarity and confidence would protect them from scams and malicious third parties.
Prasanna, S., Mariappan, V., Pradeepa, S.P.N., Mani, R. and Saravanan, S. (2026) ‘Cyber-savvy or cyber-sloppy? Exploring Indian e-banking users’ security behaviour’, Int. J. Information and Computer Security, Vol. 31, No. 1, pp.1–23.
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The following International Journal of Applied Management Science article, "Creative implementation and technology orientation: associations with perceived performance in Saudi dental practices", 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 Logistics Systems and Management article, "Criteria for success in end-of-life tire recycling supply chains", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
An artificial intelligence (AI) model can score English essays with improved accuracy across different writing topics, according to work published in the International Journal of Continuing Engineering Education and Life-Long Learning. The tool could help schools assess student work more efficiently while reducing inconsistencies in marking.
The system, known as DTS-Score, combines several machine-learning techniques to analyse the meaning and structure of essays, including their paragraph organisation. In tests, it achieved a weighted kappa coefficient of 0.866. This is a measure of agreement between scoring outcomes, where 1.000 would represent a perfect output. A further development might allow the accuracy of the system to be compared with marking undertaken by teachers themselves.
The researchers developed the model to address a common problem in automated essay assessment. That is, systems trained on one essay topic may perform less reliably when evaluating writing on another subject. Their approach uses transfer learning, a technique that allows a model to apply knowledge acquired from one task to a different but related one. In large educational establishments, such a system could help process substantial volumes of student essays, flagging those that appear to stray from the assigned topic and allowing teachers to focus their attention on writing that may require closer scrutiny.
Chen, H. (2026) ‘Intelligent English composition scoring method based on transfer paragraph segmentation and Pearson detection’, Int. J. Continuing Engineering Education and Life-Long Learning, Vol. 36, No. 13, pp.1–25.
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The following Global Business and Economics Review article, "Operational risk management and the credibility of ESG disclosures: a critical analysis", is freely available for download as an open access article.
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