Teach your children well

A study of junior high schools in Indonesia has found that educational leadership influences how well they cultivate entrepreneurial skills in their students. Indeed, these kind be improved by encouraging innovation from the top and by fostering collaborative environments in which students, teachers, and communities all work together to shape educational outcomes. The details are reported in the International Journal of Business Innovation and Research.

The research surveyed 350 schools and examined the relationship between entrepreneurial leadership and entrepreneurial performance. Entrepreneurial leadership refers to a style of management that prioritises vision, innovation, and the mobilisation of others. In schools, this translates into principals and senior staff who support experimentation in teaching, promote creative problem-solving, and encourage initiative among both students and educators.

Entrepreneurial performance, on the other hand, is defined more broadly than business creation. It includes the ability of a school to generate innovative activities, equip students with problem-solving and adaptive skills, and contribute to longer-term socio-economic objectives such as employability and resilience in changing labour markets.

The study’s main finding is that leadership alone is not the sole driver of such outcomes in educations. Rather, its effects are mediated by what researchers describe as value co-creation. This term derives from service management theory and refers to a process in which value is produced through interaction, rather than being delivered unilaterally by an organisation to passive recipients. In the educational context, this implies a shift away from viewing teaching as a one-way transfer of knowledge, towards a model in which students, teachers, school leaders, and other stakeholders work together to design appropriate learning experiences and solve problems.

In countries where entrepreneurship plays a significant role in economic development, schools are increasingly seen as a foundation for developing the entrepreneurial mindset in students. The research indicates that policy initiatives which focus solely on embedding entrepreneurship in the curriculum may not work as well as those that also improve and guide leadership practices and institutional culture.

Indira, S.S., Sasmoko S., Bandur, A. and Pradipto, Y.D. (2026) ‘Business perspectives on value cocreation as a mediator for entrepreneurial performance in educational contexts’, Int. J. Business Innovation and Research, Vol. 39, No. 8, pp.1–24.

Adapting to AI adoption

Research in the International Journal of Business Information Systems suggests that the adoption of artificial intelligence (AI) is remarkably uneven across Italian firms. While some may have made a deliberate choice not to use AI, of the many that are planning to use it, some still lack the organisational structures needed to deploy the technology effectively.

This is one of the first systematic studies of AI adoption in Italy. It found that there are lots of early innovators eagerly integrating AI into their operations, but others are moving more cautiously and remain in the preliminary stages of exploration. This uneven uptake is seen elsewhere and reflects a broader international pattern, as businesses look for AI opportunities but struggle with the complexities of this rapidly evolving area of computing.

Despite the growing interest and investment in, specifically, generative AI, this research shows that many firms do not have a structured approach to the technology. The researchers propose an “AI Readiness Level” (AIRL) framework that could help organisations develop their AI strategy.

This notion of readiness is not just about technical capability, it takes into account the quality of a company’s data infrastructure, the availability of skilled personnel, leadership support, and external factors such as regulatory pressures or market competition. AIRL provides a model of the progressive stages of development, from initial awareness to full operational integration.

The team points out that firms that have adopted AI have reported improvements in operational efficiency, enhanced customer engagement, and more informed decision-making through predictive analytics. The research suggests that adopting AI is less a matter of installing new software than carrying out organisational transformation. Companies need to align their technological capabilities with workforce skills, management strategies, and governance structures, the authors explain. Those that fail to do so risk falling behind competitors that are already using this technology to their advantage.

Garlatti Costa, G., Pugliese, R. and Venier, F. (2026) ‘Exploring artificial intelligence adoption among Italian firms: the AI readiness level’, Int. J. Business Information Systems, Vol. 51, No. 7, pp.1–22.

Greening the supply chain

Research in the International Journal of Environment and Pollution has looked at carbon-reduction strategies across supply chains. The findings suggest that uncertainty in consumer demand need not preclude environmental gains.

The team looked at a four-stage supply chain, encompassing suppliers, producers, retailers, and consumers. They used a structured economic model, the Stackelberg game, to examine the dominant “actor”, in this case the manufacturer. The dominant actor makes the initial decisions, and the other players adjust their behaviour accordingly. Such a sequential decision-making framework models the way many industries function, where firms exert influence over pricing and production conditions downstream.

In contrast to other studies that have isolated individual parts of the supply chain, this latest study adopts a system-wide perspective. In it, retailers are not merely intermediaries but are active participants shaping demand. As such, retailers then influence consumer behaviour through pricing strategies and promotional efforts, such as emphasising low-carbon products or highlighting environmental credentials. This affects consumer decisions about the price of “greener” goods, and this then feeds back into the incentives at the manufacturer level for reducing emissions and pollution earlier in production.

The challenge in green manufacturing is demand uncertainty. Firms somehow need to be able to predict how positively consumers would respond to those greener, low-carbon products. This uncertainty complicates investment decisions. The research indicates that supply chain participants can still achieve what economists term Pareto improvements, where at least one party benefits without leaving others worse off, through coordinated adjustments in pricing, subsidies and emission reduction efforts.

The results reveal a set of trade-offs. Subsidies aimed at boosting retail promotion tend to increase marketing efforts and allow retailers to charge higher prices, reflecting stronger consumer demand for environmentally friendly products. However, these same measures weaken the producers’ incentives to invest in their own emission reductions and may lead to higher wholesale prices. The overall effect, however, is emission reduction across the supply chain, suggesting that policies or strategies that appear inefficient at the manufacturer level may still deliver environmental benefits.

Shen, Q. and Hou, X. (2026) ‘Carbon reduction coordination and pricing strategy of a four-level supply chain under demand uncertainty’, Int. J. Environment and Pollution, Vol. 76, No. 5, pp.36–57.

The Internet of Things can only get better

The rapid expansion of the Internet of Things (IoT) has changed how digital systems interact with the physical world. Millions, if not billions, of connected devices, from household appliances to industrial machinery, environmental sensors, medical diagnostic tools, and more, collect and exchange data with minimal human intervention.

This growing “network” has led to the automation of many mundane tasks as well as enormous improvements in efficiency across all these areas and beyond. However, researchers writing in the International Journal of Critical Infrastructures warn that the increasing complexity of the digital world brings with it vulnerabilities. This is perhaps of growing interest and concern as artificial intelligence is incorporated into the way in which IoT devices work.

The team explains that many IoT devices have limited computing resources, and so they are constrained in terms of how well they can address security issues. As a result, many devices are security targets and can, for instance, be added to so-called botnets, networks of affected machines used to carry out bigger attacks on networks and infrastructure using Distributed Denial of Service (DDoS) attacks and other methods.

Addressing these problems is vital if critical IoT systems are to be protected in energy grids, medical environments, factories, and across so-called smart cities. The research focuses on anomaly detection as a powerful strategy for identifying potential threats and system failures. Unlike standard rule-based security systems that use predefined patterns of known threats, anomaly detection can use machine learning to identify patterns based on training data and algorithmic analysis rather than explicit programming.

As IoT technology spreads, anomaly detection in real time is an essential part of implementation and a requirement for maintaining system integrity. Failures or breaches in interconnected systems could have cascading effects, disrupting essential services and undermining public trust.

Ultimately, securing IoT networks through this kind of proactive monitoring is not just a technical necessity but a safeguard for infrastructure that depends on all those millions of devices.

Xu, J. (2026) ‘Integrating IoT and machine learning for scalable anomaly detection in smart city infrastructure’, Int. J. Critical Infrastructures, Vol. 22, No. 10, pp.1–16.

Location, emplacement, posizione

A new way for computers to recognise and translate complex place names is reported in the International Journal of Information and Communication Technology. The approach offers a roadmap to address a long-standing weakness in digital language systems used for mapping, navigation, and international communication.

Place names often carry historical, geographical, and cultural significance, and errors in translation can lead to confusion or loss of context. More accurate handling of such names could improve digital maps, navigation systems, logistics platforms, and multilingual communication tools.

The research focuses on English-derived place names, those created by adding prefixes, suffixes, or descriptive elements to existing names. While common in geographic data, these constructions are hard for automated systems to work with because they combine meaning and pronunciation in ways that do not transfer neatly across languages.

To address this, the researchers developed a computational model that integrates two complementary approaches: a knowledge graph and a phonetic generation algorithm. A knowledge graph is a structured representation of information that maps relationships between concepts, allowing the system to understand how place names are formed and how their components relate to one another. This captures the semantic dimension of language, its meaning and contextual associations.

The phonetic generation algorithm focuses on the sound of the spoken names. It converts written words into standardised representations of pronunciation, enabling the system to align how a place name is written with how it is spoken. This is particularly important in translation, where names often need to preserve recognisable sounds alongside meaning.

These two elements interact using what the team refers to as a bidirectional dynamic interaction fusion mechanism. In this system, the semantic and phonetic information feed each other to improve recognition and translation. The system also uses a Long Short-Term Memory (LSTM) network, a type of neural network commonly used for language processing.

The model demonstrated an error rate of just 1.3 per cent in recognising place names and 0.8 per cent in translating them. Its outputs are more than 95 per cent fluent and consistent.

Ma, D. (2026) ‘English-derived place name recognition and translation based on knowledge graph and phonetic generation algorithm’, Int. J. Information and Communication Technology, Vol. 27, No. 27, pp.109–132.

When we’re old and wise

China is facing a rapidly ageing population, with almost a quarter of its population over the standard retirement age in many regions of 60 years. This coincides with a declining birth rate and given more flexible retirement policies, the workforce itself is getting older. Research in the International Journal of Economics and Business Research recognises that within this workforce, older, experienced knowledge workers are a growing human resource asset. Understanding their needs and ensuring they are not so disenfranchesed that they take retirement as early as possible is now high on the organisational agenda and a critical part of modern management.

The research emphasises career capital, a concept that brings together human capital, social capital, and decision-making capital. Human capital refers to an individual’s skills, knowledge, and experience. Social capital encompasses professional networks and relationships. Decision-making capital involves accumulated judgement and problem-solving abilities. The research found that these all contribute to ongoing professional effectiveness in the later stages of employment.

Two psychological factors specifically were identified as important in mediating the relationship between career capital and workplace success: self-efficacy and job crafting. Self-efficacy is an individual’s belief in their abilities, while job crafting refers to the adjustment they make to tasks and work relationships to align with personal strengths and interests. The accumulation of skills, networks, and decision-making abilities are all fully realised when older employees feel capable and empowered to shape their roles.

In an effort to ensure older employees are not disenfranchised and continue to play an important role, the researchers suggest that the various dynamics at play need to be integrated into a new model of human resource management. This model should pay attention to different forms of career capital, activation of self-efficacy and adaptability, and flexible organisational support strategies tailored to age-specific needs. If such an approach is implemented, organisations will be able to sustain productivity, encourage innovation, and preserve the professional value of older knowledge workers.

Wei, J-l. and Chen, C-s. (2026) ‘Exploring the impact of older knowledge workers’ career capital on career success: with self-efficacy and job crafting as mediators and perceived organisational support as a moderator’, Int. J. Economics and Business Research, Vol. 30, No. 1, pp.1–28.

Free Open Access issue published by International Journal of Information and Communication Technology

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

• An AI-driven dual neural network framework for enhancing and evaluating university teachers' informatisation teaching capacity under TPACK
• Gradient optimisation and cross-language transfer mechanism of English translation model based on LSTM-transformer
• Emotions and dissemination trends of Sichuan handicraft intangible cultural heritage inheritance groups based on ALBERT and TCN
• Deep learning-based automatic labelling of English syntactic variation and cross-dialect comparison
• Real-time health-aware emergency optimisation scheduling under fault scenarios in PV-fuel cell microgrids

Free sample articles newly available from International Journal of Happiness and Development

The following sample articles from the International Journal of Happiness and Development are now available here for free:

• Exploring the emotional terrain: a comprehensive systematic literature review of the effects of emotional intelligence on stress and performance
• Psychometric assessment of the Persian version of the future time perspective questionnaire in college students
• Happy-NE-R leadership for companies in emerging economies
• Impact of income on life satisfaction in India: a generalised ordered probit model approach

New Open Access article available: "Exploring artificial intelligence adoption among Italian firms: the AI readiness level"

The following International Journal of Business Information Systems article, "Exploring artificial intelligence adoption among Italian firms: the AI readiness level", is freely available for download as an open access article.

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

Research pick: AI second guess that emotion - "Aspect-level sentiment classification with emotional keywords attention network"

Research in the International Journal of Computational Intelligence Studies has looked at how we might improve artificial intelligence (AI) systems for interpreting human emotion in written communication. The new system is capable of identifying sentiment not only in broad terms, positive, negative, and neutral, but also at a more detailed, aspect-specific level.

Sentiment analysis usually evaluates entire sentences or documents as a single unit. This can hide the subtleties of human expression. For instance, a restaurant review may praise the food while criticising the service. Previous AI models could struggle to separate these differing opinions, often assigning a generalised sentiment score. The new model overcomes this limitation by emphasising emotionally charged keywords, the words that carry the most significant emotional weight in a sentence. It does this using an attention network, a computational mechanism that allows AI to prioritise certain inputs over others.

This focus on the most emotional terms in a piece of text allows the AI to classify sentiment directed at specific aspects of a text. In the restaurant example, the model can distinguish the positive sentiment aimed at the food from the negative sentiment about the service, producing a more nuanced interpretation. Moreover, the system’s ability to pay attention to the most emotionally charged words is a useful advance in natural language processing.

Such a tool could help businesses that rely on customer feedback, social media analysis, and online reviews. With it a company could spot concerns being discussed online as they arise and so make a timely response to help manage their image and refine their marketing. They might even be able to offer targeted responses to individuals or groups to improve customer satisfaction and perception.

This research is part of a growing trend in AI research towards improving the way in which computers interpret language and emotion. By enabling machines to analyse sentiment at the level of individual aspects rather than entire texts, this approach contributes to the development of more perceptive, context-aware AI.

Yuan, Z. and Yuan, J. (2026) ‘Aspect-level sentiment classification with emotional keywords attention network’, Int. J. Computational Intelligence Studies, Vol. 13, No. 5, pp.1–13.

New Open Access article available: "Integrating IoT and machine learning for scalable anomaly detection in smart city infrastructure"

The following International Journal of Critical Infrastructures article, "Integrating IoT and machine learning for scalable anomaly detection in smart city infrastructure", is freely available for download as an open access article.

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

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

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

• Green logistics distribution route algorithm based on carbon emissions optimisation
• Using soil water content and energy balance model to promote sustainable development of green and low-carbon economy
• Carbon reduction coordination and pricing strategy of a four-level supply chain under demand uncertainty
• Evaluation of petroleum safety management system based on embedded intelligent image sensor
• State diagnosis technology of metal enclosed gas insulation equipment based on Apriori algorithm in cloud computing environment
• Investigation sustainable development of ecological environment and economic technology in the context of supply chain management
• Innovation-driven development path of the new energy industry based on immune optimisation and simulated annealing algorithm
• Environmental risk assessment and early warning system construction for forest tourism sites under the background of climate change

New Open Access article available: "Business perspectives on value co-creation as a mediator for entrepreneurial performance in educational contexts"

The following International Journal of Business Innovation and Research article, "Business perspectives on value co-creation as a mediator for entrepreneurial performance in educational contexts", is freely available for download as an open access article.

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

New Open Access article available: "Sectoral total factor productivity and its determinants: firm-level evidence from Kazakhstan"

The following International Journal of Services, Economics and Management article, "Sectoral total factor productivity and its determinants: firm-level evidence from Kazakhstan", is freely available for download as an open access article.

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