A research team writing in the International Journal of Environment and Sustainable Development has looked at agriculture in Ghana and puts forward a compelling case for rethinking how water is managed in such areas as the country's Upper West Region.

As Sub-Saharan Africa struggles to cope with environmental and demographic pressures, the team argues that combining circular water management with nanotechnology could provide a sustainable and scalable solution to the deepening crisis of water scarcity and food insecurity. Despite the fact that agriculture is the backbone of rural economies across Sub-Saharan Africa, underpinning livelihoods, food supply, and contributing significantly to gross domestic product, it is increasingly vulnerable. Climate change has made rainfall less predictable. Population growth is intensifying demand for food and water. Over-reliance on rain-fed farming, coupled with widespread environmental degradation and the mismanagement of water resources, has led to declining yields and more problems for rural communities.

The research involved interviews with experts and focus group discussions to look at how innovation might help agricultural water use. The work advocates for circular water management: a system in which water is reused and recycled through closed loops, minimizing waste and conserving resources. The use of nanotechnology could facilitate this kind of approach by providing effective contaminant removal or desalination of retrieved irrigation water. Nano-membranes and filters can isolate harmful substances at a fraction of the cost and energy required by water-processing systems. Circular water management could thus reduce a farm's reliance on unpredictable rainfall and limits the need for additional water extraction from rivers and aquifers.

The researchers focused on Ghana in their study, but the findings could be used across Sub-Saharan Africa, where smallholder farmers face almost identical challenges. By boosting resilience and productivity through reduced water use, the approach could help reduce poverty, improve nutrition, and create jobs.

Boon, E.K., Gross, T.K.F., Oppong-Boateng, R. and Karintseva, O. (2025) 'Circular water management solutions for optimising irrigated agricultural production in Ghana: the relevance of nanotechnology', Int. J. Environment and Sustainable Development, Vol. 24, No. 2, pp.115–144.
DOI: 10.1504/IJESD.2025.145318

A new modelling technique discussed in the International Journal of Masonry Research and Innovation shows how building risks associated with land subsidence in The Netherlands can be determined.

Land subsidence, when the ground sinks due to either natural or human-induced factors, or both, is becoming an increasingly serious issue in many parts of the world, particularly in low-lying regions like The Netherlands. According to Alfonso Prosperi, Michele Longo, Paul A. Korswagen, Mandy Korff, and Jan G. Rots of Delft University of Technology in Stevinweg, The Netherlands, this phenomenon, exacerbated by climate change, threatens buildings, infrastructure, and the very fabric of urban environments.

For building on shallow systems, such as strip foundations, subsidence can cause minor but recurring cracks, compromising both the functionality and aesthetics of a building. The new work looks at how advanced numerical modelling strategies can predict the impact of subsidence on buildings, with a focus on the particularly vulnerable two-storey masonry buildings that make up a significant portion of the Dutch housing stock. This research has important implications for urban planning, risk assessment, and the long-term resilience of cities in the face of ongoing climate changes.

The team compared two approaches for modelling subsidence: the coupled and the uncoupled methods. Both strategies use nonlinear finite element (FE) analysis, a computer simulation, to predict how structures might respond to physical forces. The challenge in such simulations lies in accurately representing the relationship between the soil and the building, the soil-structure interaction. Understanding this is critical for predicting how ground movements will affect a building.

In the coupled model, the building and surrounding soil are treated as a single system. This method integrates the building with the ground, using contact interfaces to allow the structure to interact with the soil. In the uncoupled model, the building and soil are kept separate, they are treated as independent systems.

The team tested both models under identical conditions. Initially, their results were similar when the simulated soil volume was small. However, as the volume of soil increased, the models began to diverge. The coupled model showed that including a larger volume of soil could reduce predicted damage by up to 50%, highlighting how the broader soil environment significantly influences the structural response.

One particularly important insight from the study is the role of angular distortion, the degree to which a structure bends, as a reliable indicator of putative damage. This finding could help engineers and urban planners better assess risks and determine which buildings are at greatest risk of subsidence-related damage.

Prosperi, A., Longo, M., Korswagen, P.A., Korff, M. and Rots, J.G. (2025) 'Comparison of simplified coupled and uncoupled 3D finite element models for soil-structure interactions in masonry structures with strip foundations undergoing subsidence', Int. J. Masonry Research and Innovation, Vol. 10, No. 7, pp.1–41.
DOI: 10.1504/IJMRI.2025.146106

In Hanoi, Vietnam, where rapid urban development is reshaping the city, a study in the International Journal of Public Law and Policy, has looked at the quality of public administrative services in the construction sector. The research surveyed hundreds of residents and asked them about their experience of the bureaucratic processes that underpin the city's growth, from acquiring construction permits to navigating zoning regulations.

From their work, Thi Hong Viet Bui, Thuý Nguyen Thị Lệ, Viet Hoang Dinh, and Nguyet Minh Nguyen of the National Economics University, and Nhu Dung Co of the People's Committee of Ba Dinh District in Hanoi, Vietnam, conclude that citizen satisfaction is rooted not in grand buildings or modern offices, but in the everyday quality of service delivery. This is an important finding for policymakers overseeing the growth of the city.

The team used the SERVQUAL model, a widely used tool for measuring service quality by comparing expectations with actual experiences. They applied it to their survey of 362 citizens to evaluate five key dimensions: tangibles (physical facilities and equipment), reliability, responsiveness, assurance, and empathy. The analysis revealed that in the context of Hanoi's construction administration, tangibles play a surprisingly minor role in shaping satisfaction. What matters most to residents is the clarity of procedures, the fairness of service fees, and the professionalism of administrative staff.

The team explain that their respondents placed particular emphasis on the importance of transparent and accessible information, timely service, and respectful treatment. These elements, which are less obvious than the presence of public buildings or signage, had a much greater effect on whether citizens felt satisfied with their encounters with government services.

The research also showed that demographic factors also influenced perceptions. Educational level, marital status, and prior familiarity with administrative procedures all played a part in shaping how individuals felt about public service quality. Overall, the findings suggest that a one-size-fits-all approach to public service reform would be inappropriate and instead governments and policymakers must take into account the different needs and expectations of a diverse urban population.

Bui, T.H.V., Lệ, T.N.T., Dinh, V.H., Co, N.D. and Nguyen, N.M. (2025) 'Evaluating the governance of public services in urban construction: insights from Hanoi's experience', Int. J. Public Law and Policy, Vol. 11, No. 5, pp.1–18.
DOI: 10.1504/IJPLAP.2025.146092

Research in the International Journal of Data Science has used machine learning to predict the lifecycle of businesses operating in the digital economy. The work might help firms and policymakers understand enterprise longevity, the rise, the demise or the likelihood of acquisition, in a fast-changing technological landscape.

Shulei Yin of Qilu Normal University in Jinan, Shandong, China, used a gradient boosting regression tree (GBRT) model to handle the requisite complex, nonlinear relationships within large datasets. She applied it with two tools from survival analysis: the Kaplan-Meier survival curve and the accelerated failure time (AFT) model. Each tool brings something to the approach. The GBRT model refines prediction accuracy. The Kaplan-Meier curve can estimate the survival probability of firms over time. The AFT model quantifies how external variables, such competition or enterprise scale, can hasten or slow different phases of a company's development.

The result of this combination are predictions that offer much greater accuracy than earlier, simpler models. The work is timely given that the traditional business life cycle of start-up, growth, maturity, and decline have become unstable economically speaking. Digital technologies such as cloud computing, artificial intelligence, and big data analytics have lowered entry barriers and condensed innovation timelines. This means that some companies can scale-up quickly, switch strategies on a whim, or simply lose their market abruptly when the environment and consumer favour shift. Such volatility makes it more difficult for anyone involves in digital activities, whether in the private or public sector actors to predict how things might pan out for a company on which they come to rely for their own operations.

The study thus offers the potential for more certainty in the digital business world. If it is possible to predict which start-ups will thrive and survive, then others can adjust their own strategies accordingly. They can make supply-chain and resource choices based on predicted longevity and avoid signing up for enterprises that might vanish from the scene as abruptly as they appear.

Yin, S. (2025) 'Life cycle prediction and survival model construction of digital economy enterprises integrating survival analysis', Int. J. Data Science, Vol. 10, No. 6, pp.1–19.
DOI: 10.1504/IJDS.2025.146190

A review of digital technologies in the International Journal of Agricultural Resources, Governance and Ecology suggests that integration of mobile, 5G, wireless and the so-called metaverse could be a turning point in global agriculture. The use of this kind of technology is becoming essential in the face of population growth, climate change, and resource scarcity.

5G offers fast data transmission and almost ubiquitous connectivity for devices. In agricultural terms, this means smart sensors embedded in fields and greenhouses can transmit real-time data on soil conditions, crop health, and the weather to individual farmers or a central farming-control system. This allows more timely interventions to be undertaken when necessary, reducing waste and increasing precision in the use of water, fertilizers, and pesticides. All of which should cut costs, improve efficiency, and lead to better yields.

According to the review by Wenliang Tang and Muhammad Umair Assad of East China Jiaotong University, Junliang Xu of Jiangxi Telecommunications and Information Industry Co., Ltd., Jieming Liu of Jiangxi Zhongxin Yunnong Technology Co., Ltd. in Jiangxi, China, and Yifan Gao of Victoria University of Wellington, New Zealand, such capability extends beyond passive monitoring. 5G also enables the remote operation of advanced machinery, such as autonomous tractors and agricultural drones. In areas where labour shortages or extreme conditions make manual work difficult or dangerous, remote-controlled equipment offers a safer and often more efficient alternative. These changes could be particularly transformative in developing countries, where post-harvest losses are high and efficient resource use is critical.

In parallel, the metaverse, a digital environment in which users can interact in real-time through virtual or augmented realities, is finding unexpected applications in farming. Virtual reality (VR) can provide interactive training platforms for farmers, allowing them to practice new techniques or understand complex machinery without the need to travel or risk costly mistakes in the field. These tools are especially valuable in rural areas with limited access to conventional educational infrastructure.

A more advanced application of the metaverse in agriculture is the use of digital twins: virtual replicas of physical farms created through real-time data feeds. Such digital environments would allow farmers to simulate different agricultural scenarios, such as the introduction of a new crop or changes in irrigation strategies, before making real-world decisions. The virtual nature of the metaverse also opens up the possibility of new ways for farmers to collaborate. Farmers, researchers, and policymakers can convene in digital spaces regardless of physical distance, to discuss best practices and develop solutions to common problems together.

Tang, W., Assad, M.U., Gao, Y., Xu, J. and Liu, J. (2025) 'Enabling future agriculture: integration of 5G and Metaverse technologies for smart farming innovations', Int. J. Agricultural Resources, Governance and Ecology, Vol. 20, No. 5, pp.1–25.
DOI: 10.1504/IJARGE.2025.146099

Research in the International Journal of Entrepreneurship and Small Business suggests that entrepreneurship may be far more than a vehicle for economic growth. Two back-to-back studies show that entrepreneurial thinking, especially in how individuals perceive and respond to challenges, can also foster psychological resilience and enhance personal well-being. The findings suggest that we should redefine the value of entrepreneurship in society as it could have implications for education, policy, and development strategies.

One study, drawing on case analyses from entrepreneurs in Vietnam and Japan, introduces the idea of "partial constraint", which is a departure from conventional views that treat obstacles like supply shortages or policy hurdles as uniformly restrictive. Instead, the study dissects what constraints have an effect on entrepreneurs and which do not, and shows how they can selectively isolate and recombine different factors to open up new business solutions. This allows entrepreneurs not only to continue operating under pressure, but also to build a sense of agency, resilience. The study shows that resilience isn't a fixed personality trait but can be cultivated through problem-solving and resourcefulness.

The other study looks at the relationship between entrepreneurial cognition and subjective well-being. Traditionally, entrepreneurship has been linked to economic indicators: job creation, innovation, and contribution to gross domestic product. This latest research questions the assumption that well-being is merely a by-product of entrepreneurial success. Indeed, the findings suggest that "entrepreneurial thinking" itself, marked by traits such as optimism, creativity, perseverance, and comfort with uncertainty, may directly contribute to life satisfaction and happiness.

Entrepreneurs often face unpredictable and high-pressure environments, but those who think entrepreneurially interpret such challenges as opportunities rather than threats. This cognitive reframing appears to foster a sense of meaning and control, both central to psychological well-being.

Together, the two studies challenge prevailing assumptions in both economic and psychological domains. They argue for a new definition of entrepreneurial success, one that includes mental and emotional outcomes.

The work could have implications for policymakers, especially in countries facing high youth unemployment or systemic inequality. The findings suggest that promoting entrepreneurship could serve two purposes: economic empowerment and psychological resilience. Entrepreneurship could be strategically positioned not just as a livelihood option, but as a tool for strengthening mental health and community adaptability.

Nguyen, N.C., Matta, D., Hasnaoui, J.A., Lodorfos, G. and Matta, R. (2025) 'Dynamic resource analysis and the development of psychological resilience: an entrepreneurial perspective', Int. J. Entrepreneurship and Small Business, Vol. 55, No. 6, pp.1–19.
DOI: 10.1504/IJESB.2025.146150

Nguyen, N.C., Hasnaoui, J.A., Lodorfos, G., Matta, D. and Laine, I. (2025) 'Resilience, optimism, and entrepreneurial well-being: a review and research agenda', Int. J. Entrepreneurship and Small Business, Vol. 55, No. 6, pp.20–40.
DOI: 10.1504/IJESB.2025.146149

A new system that improves on the detection of pronunciation errors among non-native speakers could improve English language learning. The technology, discussed in the International Journal of Computing Science and Mathematics, uses speech recognition tools and statistical modelling. It could offer English learners feedback and track their progress, particularly in regions where there is limited access to face-to-face human instruction.

Wenna Dou of the University of Civil Engineering and Architecture in Beijing, China, has focused on Chinese learners of English, a group that often faces challenges in mastering the nuances of English pronunciation due to phonetic and prosodic differences between the two languages.

At the core of this system lies the use of Mel Frequency Cepstral Coefficients (MFCC), a technique commonly employed in speech analysis that simulates how the human ear processes sound. By converting speech into digital signals and emphasizing features such as pitch and frequency, the method captures intonation points. These are key moments in spoken language where pronunciation is most susceptible to error.

To assess these intonation points, Dou used a statistical framework known as the Hidden Markov Model (HMM). HMMs are particularly effective in analysing time-dependent data, such as speech, because they model changing systems based on a series of probabilities. By using a segmentation process that breaks speech into smaller units, Dou has improved the system so that it can cope with longer sections of speech and maintain accuracy without being stymied by complexity.

Dou has also introduced a "degree component signal detection method." This enhancement refines the system's ability to identify spectral features, the variations in sound frequency, that often indicate mispronunciation. These features are then compared to a database of standard English pronunciations. The resulting system can quickly flag pronunciation errors with more than 97% accuracy, according to Dou's tests.

As English continues to serve as a global medium for education, business, and international collaboration, tools that promote clearer speech and mutual intelligibility are in increasing demand. Automated feedback mechanisms, especially those with real-time capability, offer learners immediate and objective insights into their spoken language skills and lead them towards improving.

Dou, W. (2025) 'A method for capturing English oral pronunciation errors based on speech recognition', Int. J. Computing Science and Mathematics, Vol. 21, No. 1, pp.32–47.
DOI: 10.1504/IJCSM.2025.146081

Inner drive plays a more decisive role than external conditions in shaping the intention of Indian women to become entrepreneurs, according to research in the International Journal of Business Innovation and Research. The findings could have implications for policymakers in encouraging business development especially as women-owned businesses have the potential to generate employment, reduce poverty, and serve as nodes of empowerment in both urban and rural settings.

Bijay Prasad Kushwaha of the Vellore Institute of Technology in Vellore, Raj Kumar Singh of Graphic Era Hill University and Vikas Tyagi of Himgiri Zee University in Dehradun, India, and Bhagwati Prasad Chaudhary of Lumbini Banijya Campus in Butwal, Nepal, surveyed more than 400 women who were either in the process of launching or planning to launch their own business ventures. The data obtained offers new insights into the underlying motivations and what hinders entrepreneurial ambition among women in one of India's most dynamic urban economies, the Chandigarh Tri-city region of Chandigarh, Panchkula, and Mohali, in northern India.

Women make up half of India's population but are significantly underrepresented in the business world. The team wanted to know why and so divided the various motivational factors into two broad categories. Thre first, internal factors that encompass personal attributes, such as self-confidence, motivation, and resilience. The second, external factors refer to the broader environment, including the availability of financial capital, support from institutions, and prevailing market conditions.

They found that internal factors, especially those related to a woman's psychological disposition and social context, are more influential than the external factors. This suggests that personal belief in one's abilities, coupled with encouragement from family and community, serves as a stronger catalyst for entrepreneurship than the presence of supportive infrastructure alone.

Perhaps counterintuitively, not only did external factors have little real impact, the statistically significant impact they did have was exerted as a negative influence on entrepreneurial intent. Bureaucratic red tape, lack of institutional clarity, or gender-based discrimination, for instance, were more likely to discourage women from starting businesses, even when they have the motivation and support to do so.

Kushwaha, B.P., Singh, R.K., Tyagi, V. and Chaudhary, B.P. (2025) 'How to empower women? Modelling the factors increasing women's entrepreneurial intention', Int. J. Business Innovation and Research, Vol. 37, No. 1, pp.108–129.
DOI: 10.1504/IJBIR.2025.146040

In a sector as complex and capital-intensive as oil and gas, the decision-making process surrounding supplier selection is pivotal to operational success and long-term competitiveness. Research from Oman's oil and gas sector published in the International Journal of Services and Operations Management (IJSOM) highlights the need for more structured, data-driven approaches to supplier evaluation. This research explores the application of advanced decision-making techniques to improve transparency, reduce risk, and enhance operational efficiency within the industry.

At the core of this research is the application of multi-criteria decision-making (MCDM) methods. MCDM methods are analytical tools that can be used to evaluate options based on different, often conflicting, criteria. MCDM is particularly important in this industry where decision-makers must balance factors such as cost, safety, regulatory compliance, past performance, and environmental impact. Conventional supplier-selection methods often rely too heavily on subjective judgement, which can lead to the wrong decisions being made.

The IJSOM findings suggest that these methods can create a nuanced framework for supplier selection. In the case study, the approach shows itself to be invaluable in cases where specific contract requirements demand a more tailored, context-sensitive evaluation of suppliers.

The researchers suggest that supplier selection should no longer be driven by price alone. The volatile nature of the oil and gas industry, shaped, as ever, by geopolitical tensions, fluctuating markets, and evolving environmental regulations, requires a broader focus. Supplier experience, commitment to health, safety, and environmental standards, and the ability to manage operational risks have become more important than initial pricing, particularly in contracts that involve sensitive operations.

The research shows that an MCDM-based framework might be beneficial not only to individual companies, but also to national regulatory bodies and tendering authorities. By embedding these methods into procurement practices, the industry could achieve greater operational resilience, better align with sustainability objectives, and strengthen its contribution to the economy.

Kamran, M.A., Afsharfar, S., Al Fori, S., Babazadeh, R. and Al Balushi, M. (2025) 'Supplier selection in oil and gas industry', Int. J. Services and Operations Management, Vol. 50, No. 5, pp.1–27.
DOI: 10.1504/IJSOM.2025.145843

A tool to help make important choices in the financing of building energy upgrades is discussed in the International Journal of Decision Support Systems. The system offers the promise of clarifying this often murky process given the Europe's ageing buildings, and could improve necessary investment.

Ioanna Andreoulaki, Aikaterini Papapostolou, Charikleia Karakosta, and Vangelis Marinakis of the National Technical University of Athens in Greece, used their home country as a case study, but their findings will be equally applicable throughout the European Union. Indeed, they demonstrate how a structured decision-making framework can better align private capital with the sustainability targets.

Buildings are responsible for about 40% of energy consumption and over a third of carbon emissions in the EU. They are thus a major focus of the bloc's climate and energy agenda. As such, the European Commission has launched initiatives such as the Energy Efficiency Directive and the Renovation Wave, aimed at accelerating the upgrade of inefficient buildings. Yet despite these policies, actual renovation rates have remained disappointingly low.

One of the main obstacles is the financial uncertainty surrounding investment in sustainable power options. Investors face a difficult task in evaluating which energy-saving measures offer the most compelling combination of cost-effectiveness, carbon reduction, and, of course, long-term financial returns. After all, they are not going to invest simply for the green credibility, but expect a profit. Conventional financial models often fall short of accounting for the full complexity of this kind of decision.

The researchers adapted multi-criteria decision analysis (MCDA) to the context of building renovations. MCDA is a structured framework that supports decision-making when multiple, sometimes conflicting, factors must be taken into account. The specific approach employed in this study is called TOPSIS—the Technique for Order of Preference by Similarity to Ideal Solution. It works by scoring and ranking alternatives according to how closely they resemble a hypothetical "ideal" option that performs best across the various criteria.

Applying this method, the researchers evaluated 48 real-world renovation projects in Greece, focusing on private office buildings in the Attica region. The projects included a diverse range of interventions, from installing energy-efficient lighting and solar panels to upgrading heating, ventilation, and air conditioning (HVAC) systems and adding smart automation for energy control.

The analysis showed a clear hierarchy in investor appeal. Heating system upgrades stood out as particularly attractive, combining relatively low upfront costs with substantial energy savings. Other high-ranking measures included efficient lighting and renewable energy integration. In contrast, building automation technologies were rated lower, largely due to higher perceived complexity and longer payback periods, even though they have great potential for long-term savings.

The results offer a roadmap for public policymakers seeking to tweak incentive schemes and encourage sustainability investment. This suggests that while market forces may naturally gravitate towards HVAC and lighting upgrades, more strategic policy support is needed to encourage investment in less immediately appealing, but important, technologies such as automation.

Andreoulaki, I., Papapostolou, A., Karakosta, C. and Marinakis, V. (2025) 'A decision-making approach based on the TOPSIS method for supporting energy efficiency financing in buildings', Int. J. Decision Support Systems, Vol. 5, No. 5, pp.1–36.
DOI: 10.1504/IJDSS.2025.145842