Personality traits may help predict whether a person will ignore others while using their smartphones, according to a study of healthcare workers in the International Journal of Business Innovation and Research.

The study involved 177 co-workers and looked at how prevalent 'phubbing' is. Phubbing is a portmanteau of the words 'phone' and 'snub' and is the practice of ignoring someone in preference to using one's phone despite being in a situation in which face-to-face conversation and interaction would be the norm. The study might help social scientists and others understand better the notion of smartphone addiction.

The research assessed participants using the so-called Big Five personality traits - openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism. Personality and phone addiction were self-reported, while co-workers provided evidence of phubbing by others. The team found that people scoring higher in openness, extraversion and neuroticism were more likely to display phubbing behaviour. Conscientiousness, a tendency towards responsibility, self-discipline, and consideration of one's obligations, was associated with less phubbing. There was no significant relationship between phubbing and agreeableness, oddly enough.

If a condition we might call mobile phone addiction exists, then it might be described as an inability to refrain from phone use despite the potential for offline human interaction. To be a true addiction, there has to be associated harm, and the researchers suggest that psychological harm may well occur, either to the phubber or the phubbed. This phenomenon partly explains the relationships between personality and phubbing, the team reports. That said, the researchers emphasise that understanding individual differences behind problematic smartphone use could help organisations address antisocial phone behaviour without treating smartphone use itself as inherently harmful.

Social media used inside organisations may help engage employees and increase staff retention, according to a paper in the International Journal of Applied Systemic Studies, which looked at this phenomenon in China. Employee engagement refers to a worker's emotional and motivational connection with their organisation, the team explains, while retention is the organisation's ability to keep employees and reduce staff turnover rates.

The researchers used a statistical method known as structural equation modelling to test the relationships between various factors. They considered whether an employee's perception of technology affected their working relationship. Indeed, perceived ease of use and perceived usefulness strengthened the impact of social media technology on engagement and retention.

The findings are particularly relevant to China, where social media platforms are important workplace communication channels. The distinctive cultural and regulatory environment there provided the researchers with a useful setting for studying digital employment practices.

Social media, the team points out, can facilitate communication, knowledge sharing, and recognition. It can thus help employees feel more connected to colleagues, their superiors, and the organisation in general. If this improves employee retention, then it has the benefit to the organisation of keeping hold of experienced and talented staff and reducing recruitment and training costs.

However, the study shows that introducing social media tools may not be sufficient for optimal employee engagement and retention. The team explains that organisations need to ensure employees find these tools easy to use and patently useful.

Research in the International Journal of Arts and Technology monitored electrical brain activity and heart rate in people watching patriotically themed Chinese films. They found that the main incidental music in such films can increase the positive emotional response and patriotic sentiment in the audience and at the same time reduce negative emotional responses.

The findings could be used by film-makers offering content in the context of tourism, specifically cultural tourism. Such insights have potential in boosting the impact of film-themed attractions, reconstructed locations, tourism and educational programmes. The researchers add that their approach essentially uses the "internet of bodies", a human analogue of the "internet of things", in which technologies collect and analyse data about human behaviour and physiological states. In the cultural tourism setting, this technology would combine information gathered while people watch films with data on their behaviour and interactions at related physical sites.

The extension into social media interactions might also be used to amplify emotional responses through discussion and engagement beyond the film itself.

The approach does raise ethical questions about how physiological and behavioural data should be collected and used when technologies designed to measure audience responses become part of cultural experiences. It might be that prior consent of audience members should be necessary before anyone is subsumed into an internet of bodies system, and individuals should have the ability to opt out.

Research published in the International Journal of Environment and Sustainable Development analysed interviews with over 300 Chinese hotel interns to see how perceptions regarding hotel work affect whether graduates pursue a career in the industry or not. The findings suggest that negative perceptions do indeed deter graduate interns from pursuing hospitality as a career.

Fundamentally, the team found that occupational stigma, the belief that a profession has low status or is undesirable, was most associated with weaker professional identity. Those graduates with this perception generally did not choose hotel work as a career.

The findings highlight a significant recruitment problem for China's hotel industry. Despite its reliance on a large and stable workforce, only an estimated 10 to 20 per cent of graduates in hospitality and tourism enter the sector. Moreover, internships, which are intended to provide graduates with practical experience early in their career, sometimes reinforce negative perceptions and lead to many graduates dropping out of the sector before they have even taken more than a few tentative steps on this career path.

The study did find that vocational skills sometimes offset the stigma. Interns with additional skills were less affected by negative perceptions of the industry. This suggests that practical training and professional certification might boost confidence in hotel careers and improve professional identity in the sector.

A new artificial intelligence, or AI, translation model could improve the accuracy and cultural appropriateness of Chinese-English public signs in tourist attractions, according to research in the International Journal of Environmental Technology and Management. The approach treats translation as more than a word-for-word conversion and combines machine translation with principles from eco-translatology in which language, culture, and social context are considered.

The researchers have incorporated these principles into a neural translation system based on transformer architecture, a widely used AI system for processing relationships between words in a sentence. The model thus uses cultural-language databases together with sentiment analysis. The latter uses a computer to assess the emotional or evaluative language in a piece of text. The system can then tweak the translation for linguistic, cultural, and communicative context.

In tests, the team reports an improvement over older approaches for cultural adaptability, fluency, and completeness. The findings suggest that translation systems designed for specific functions may be better suited to public-facing texts where a culturally inappropriate phrase might confuse visitors or change the intended message. The same system could support multilingual urban signs, heritage-site interpretation, and educational notices.

At this time, the model is limited to a single language pair and a corpus concentrated on Chinese scenic areas. However, the researchers plan to expand the training data and incorporate knowledge graphs, situational modelling, and causal reasoning to improve the system’s ability to be used in different cultures and settings. There is also the potential to improve the handling of historical references, deeper cultural meanings, and linguistic variation by developing deeper reasoning rather than relying on simple rules and templates.

Research in the International Journal of Sustainable Development has looked at eight of the nations involved in the Second World War, both Allied and Axis countries, and shows how that period of history helped set societies on the path to the resource-intensive modern economies we have today. The research links wartime mobilisation to the period known as the Great Acceleration in energy use, material consumption, and ultimately detrimental environmental impact.

The study looks at societal change from before the war, 1935, to the post-war recovery period and the boomer years up to 1960. Demographics, economic activity, power supply, material and resource flow, and environmental impact are all examined. Three major consequences of WWII are seen. First, acceleration, in which existing trends become even more intense. Secondly, redirection where development shifts towards new technologies and the opening up of novel resources. Thirdly, reset, in which destruction or political upheaval changed the direction of nations from the paths there were on before the war.

The researchers use the term "socio-metabolic transition" to describe the various changes in power consumption and physical resources in society. By adopting this almost biological model, they were able to connect wartime production and resource mobilisation with institutional and technological changes that persisted long after 1945.

A hybrid AI, artificial intelligence, system that models itself on grasshopper behaviour could be used to help with the allocation of medical resources, transport, and power during an urban emergency, according to research in the International Journal of Environmental Technology and Management. Tests with the new hybrid model on historical emergency datasets show it to be highly effective.

The team's LSTM-GOA system combines a long short-term memory neural network and the so-called grasshopper optimisation algorithm (GOA). LSTM is a machine-learning tool that can identify patterns in data as they change over time. GOA is an optimisation technique that searches for better solutions to complex problems based on how a swarm of grasshoppers forage and feed. In this hybrid approach, the GOA is used to tune the behaviour of the LSTM so that it makes better scheduling decisions in order to find the most appropriate solution.

The researchers compared the model with conventional rule-based approaches and other optimisation methods. The team was able to improve prediction accuracy for medical resource demand by almost 70 per cent. The system can respond to otherwise unpredictable spikes in demand following natural disasters, public health incidents, and major traffic accidents. Moreover, it can work with noisy or incomplete data sets.

The work points the way to the broad use of predictive AI in managing resources in an emergency. The team explains that city authorities could use historical data to anticipate pressures across several public services and adjust allocations accordingly. This would be more effective than relying on fixed rules or responding to changing demands after the fact.

A new diagnostic method could allow electricity substations to detect hidden insulation faults in relay-protection circuits earlier than conventional testing, according to research in the International Journal of Energy Technology and Policy.

The researchers have combined three measurements into a diagnostic model: zero-sequence current, an electrical signal indicating unintended current paths, waveform similarity, which compares measured current patterns with those expected under normal conditions, and third-harmonic content, a component of the electrical waveform that can reveal non-linear grounding faults.

In tests, they saw a 98.6 per cent detection rate for insulation faults and 94.3 per cent accuracy in locating multiple grounding points. Average diagnostic latency was less than 45 milliseconds, with a 1.5 per cent false-positive rate during normal operation. The team adds that the system can also detect insulation deterioration when resistance falls to between 50 and 100 kilohms. This offers an early warning sooner than conventional, offline methods, potentially allowing maintenance to be carried out before faults become critical.

A six-month pilot test at a 500-kilovolt substation in Nanjing with linked inspection robots demonstrated rapid communication between substation devices. Overall, the average fault-resolution time was reduced from more than four hours to just over one hour, and manual inspections were cut by 76 per cent.

Research in the International Journal of Business Information Systems discusses a sector-specific framework to help telecommunications companies assess how effectively they use big data. It addresses limitations in existing models that are often designed for organisations across other industries. The research involved 50 experts from academia and industry and refined and tested a big data maturity model revealing how well an organisation can manage, analyse, and use data.

The framework has seven dimensions: data governance, market strategy, network performance, business development, customers, investments, and innovation. These are sub-divided and assessed through five maturity levels, allowing weighted scores to be obtained that show where an organisation is performing well and where its capabilities need to be improved.

The researchers argue that generic maturity models can overlook the particular demands of telecommunications. In this sector, data is vital to network management, predictive maintenance, traffic optimisation, fraud detection, and the analysis of customer behaviour. The sector also increasingly relies on real-time data, distributed infrastructure and automated decision-making, so any framework needs to be operational rather than purely conceptual.

The researchers say the new approach could also help in the development of sector-specific maturity models for other data-intensive industries.

A review of research in the Interdisciplinary Environmental Review on single-use plastics argues that tackling the waste problem will require a shift from recycling alone to a broader circular economy approach, in which materials are kept in use through reuse, recovery, recycling, and redesign.

The researchers examined 336 research papers published over the decade 2015 to 2025. They then used bibliometric analysis, a kind of statistical pattern mapping, together with analysis of the content of studies, to follow the major themes in this area as well as the collaborations and research trends. They found that research into circular approaches to single-use plastics has grown rapidly since 2017. Recycling emerged as a dominant theme, while the literature also focused on plastic packaging, environmental impacts, and the effects of microplastics on human health.

The review identifies several factors that could determine whether circular systems will actually work in practice. These include public awareness and previous recycling behaviour, as well as policies such as green credit, which provides financial incentives for environmentally beneficial activity. There is an urgent need for effective reverse logistics to be put in place to allow used products and materials to be fed back into supply chains. There is also a need for better sorting, collection, and recovery of re-usable waste plastics.

We are pleased to announce that the International Journal of Metadata, Semantics and Ontologies is now an Open Access-only journal. All accepted articles submitted from 24 August 2026 onwards will be Open Access, and will require an article processing charge of EUR €1700.

We are pleased to announce that the International Journal of Intelligent Information and Database Systems is now an Open Access-only journal. All accepted articles submitted from 24 August 2026 onwards will be Open Access, and will require an article processing charge of EUR €1700.

Prof. Hai Zhao from Northeastern University in China has been appointed to take over editorship of the International Journal of Signal and Imaging Systems Engineering.

Associate Prof. Yang Li from Shihezi University in China has been appointed to take over editorship of the International Journal of Metadata, Semantics and Ontologies.

Prof. Xilong Qu, Editor in Chief of the International Journal of Applied Pattern Recognition (IJAPR), cordially invites high-quality original submissions presenting advances in pattern recognition methods, systems and real-world applications.

IJAPR provides an international and interdisciplinary forum for researchers, academics, engineers, developers and industry professionals to disseminate research that combines methodological innovation, scientific rigour and practical relevance.

The journal welcomes

• Original research papers
• Review articles
• Short papers
• Application-oriented and interdisciplinary studies
• Proposals for special issues on important and emerging topics

Topics of interest include, but are not limited to

• Image, face, speech, speaker and biometric recognition
• Natural object, insect and plant recognition
• Natural language recognition and analysis
• Predictive modelling and large-scale data forecasting
• Geographic and spatial applications
• Pattern recognition in biosciences and health informatics
• Applications in library and information science
• Pattern recognition in computational science
• Real-world data analytics
• Evaluation, benchmarking, testing and standardisation of pattern recognition systems
• Emerging and interdisciplinary applications of pattern recognition

IJAPR particularly encourages submissions that address significant scientific or industrial challenges, introduce innovative methods or demonstrate clear value in practical applications.

The journal is indexed by the Web of Science Emerging Sources Citation Index (ESCI), DBLP, Computer Science Bibliography, Google Scholar and in other international databases.

Researchers working in relevant fields are warmly invited to submit their latest work to IJAPR and contribute to the advancement of applied pattern recognition research.

For further information, author guidelines and online submission, please visit the IJAPR homepage.

We are pleased to announce that the International Journal of Internet Protocol Technology is now an Open Access-only journal. All accepted articles submitted from 16 July 2026 onwards will be Open Access, and will require an article processing charge of EUR €1700.

The International Journal of Accounting, Auditing and Performance Evaluation (IJAAPE) is seeking distinguished scholars and experienced academics to join its Editorial Team under the leadership of the new Editor in Chief, Prof. Khaled Hussainey. Prof. Hussainey invites applications from committed researchers with strong publication records, editorial experience, and expertise in accounting, auditing, performance evaluation and related disciplines.

Editorial Opportunities

Regional Editors

Regional Editors are expected to promote the journal within their geographical regions, strengthen regional research networks and attract high-quality submissions. Applications are particularly welcome from scholars representing regions such as America, Australia, Africa, Asia, Europe and the Middle East.

Associate Editors

Associate Editors play an active role in managing the peer-review process, recommending editorial decisions and contributing to the strategic development of the journal. Candidates should be internationally recognised experts with a strong publication record and previous editorial or reviewing experience.

Editorial Board Members

Editorial Board Members are senior academics who contribute to the journal by reviewing manuscripts, advising on editorial matters and promoting the journal within their research communities and professional networks. Members are expected to actively support the journal's growth and reputation.

Eligibility

Applicants should have the following:

• A PhD in accounting, auditing, performance evaluation or a closely related discipline.
• A strong international publication record.
• Experience as a reviewer, editorial board member, or journal editor.
• An active international research network.

Interested applicants should submit a current CV, a brief statement indicating the position sought and outlining their relevant experience, and a summary of previous editorial experience (where applicable) to the Editor in Chief, Prof. Khaled Hussainey, at k.hussainey@bangor.ac.uk. The application deadline is 31 July, 2026.

Prof. Khaled Hussainey from Bangor University in the United Kingdom has been appointed to take over editorship of the International Journal of Accounting, Auditing and Performance Evaluation.