Research from Kuwait, published in the International Journal of Public Sector Performance Management, has looked at the financial challenges faced by small and medium-sized enterprises (SMEs) there. Economic disruption and the post-pandemic environment have increased the risk of financial default among such businesses. Kuwait is among the richest nations, but its dependence on oil exports has made its economy highly vulnerable to global shifts, and SMEs have had to bear much of the burden.

Financial default, a situation in which businesses are unable to meet their debt obligations, is a growing concern for SMEs in Kuwait. The research, based on interviews with numerous SME managers, has identified several factors that have contributed to the financial instability of these businesses. The economic fallout from the COVID-19 pandemic, disruptions to daily operations, and changes in consumer behaviour were among the most significant factors, the researchers found.

In the wake of these crises, many SMEs found it difficult to access funding from traditional sources such as banks, which typically offer loans to support business operations. This lack of access to funding has left many companies with limited resources to adapt or recover. The researchers suggest that their findings point to a need for SMEs to adopt better financial management practices in order to mitigate the risk of default in future crises. SMEs in Kuwait, the research suggests, need to place greater emphasis on sound financial practices like budgeting, cost management, and cash flow forecasting. They say that by improving these areas, businesses may be better equipped to handle unexpected challenges.

Additionally, there is a need for businesses to explore alternative funding methods such as crowdfunding and angel investments rather than relying on bank loans. Of course, those approaches may not be appropriate for every kind of SME.

These findings also point to a need for increased government support and regulatory reform. The research suggests that greater transparency, regulatory simplification, and stronger public-private partnerships could help create a more stable financial environment for SMEs in Kuwait.

Alhaimer, R., Alshami, A., Alkhaldi, A., Alsadeeqi, A., Aloumi, D. and Malik, S. (2025) 'Evaluating public policy interventions in mitigating financial default risk among SMEs', Int. J. Public Sector Performance Management, Vol. 15, No. 5, pp.1-18.
DOI: 10.1504/IJPSPM.2025.145590

Research in the International Journal of Entrepreneurship and Small Business has identified the ingredients that lead to financial success among women-owned small-scale culinary businesses in Riau, Indonesia. The research used a combination of theoretical frameworks to shed light on how women entrepreneurs in this sector can overcome significant challenges to achieve greater financial stability and growth.

Okta Karneli, Harlen, and Yusni Maulida of the Universitas Riau, and Muammar Revnu Ohara of the Universitas Lancang Kuning, also in Riau, and Pratiwi Dwi Suhartanti of the Institut Bisnis dan Teknologi Kalimantan in South Kalimantan, Indonesia, explain that women are playing an increasingly important role in Indonesia's local economy. Understanding the recipe for their success is important to understanding the sector and how others might grow their businesses within it.

Women entrepreneurs in Indonesia's culinary sector face various many barriers, such as limited access to financial resources, insufficient education in financial management skills, and difficulties scaling operations. The researchers surveyed 355 women running business in the sector in Riau to understand how entrepreneurial orientation, adaptive capacity, and social networks might improve the bottom line for such businesses.

One of the key findings of the study is the strong link between entrepreneurial orientation and financial success. Innovative women willing to take risks and working proactivity within the sector proved to the be most successful, as one might expect. The entrepreneurs displaying these characteristics were better positioned to seize new opportunities, expand their market reach, and improve financial performance. The finding suggests that cultivating an entrepreneurial mindset is important to success for business operating in this dynamic sector.

The research also revealed that adaptive capacity is important. Businesses that could adjust to changing market conditions were generally more successful and could sustain long-term profitability. In the face of changing consumer tastes and economic uncertainties, being adaptable is critical to success. Finally, the team found that social networks – connections with suppliers, customers, and other entrepreneurs – helps provide the underlying support, resources, and information need to help businesses thrive.

Karneli, O., Harlen, Maulida, Y., Ohara, M.R. and Suhartanti, P.D. (2025) 'Women entrepreneurs in Indonesia's culinary sector: a study on entrepreneurial orientation and financial capability', Int. J. Entrepreneurship and Small Business, Vol. 55, No. 5, pp.1–28.
DOI: 10.1504/IJESB.2025.145581

In Lisbon's busy streets, tuk tuk companies have been slow to adapt to the digital age. Many rely on what researchers consider outdated and error-prone manual processes for managing their fleets of tourist transport vehicles. Research in the International Journal of Business Information Systems could help them navigate their way to a more efficient and effective future.

Eduarda Perdigão and Bráulio Alturas of the Instituto Universitário de Lisboa, in Lisbon, Portugal, have focused on how a tailored information system that could transform the daily management of companies such as Citytuk, one of the popular guided tour services in Lisbon.

Previously, tuk tuk companies relied on drivers to fill out daily service sheets by hand. This data was then transcribed manually into a central system by managers. Such an approach is inherently slow and prone to mistakes. For a growing business in the competitive tourism sector, such inefficiencies are not sustainable, the team suggests. The researchers have now identified an opportunity to enhance productivity and improve decision-making by replacing the manual process with a more streamlined, automated system.

The result of this research is Tuksy, a new application designed to simplify and modernize tuk tuk operations. Tuksy consists of two components: a mobile app for drivers to input service data directly, and a desktop app for managers to track and analyse that data in real-time. This digital solution eliminates the need for paper records, so reduces errors and frees up valuable time for both drivers and managers.

The system represents more than just a solution for one company's operational challenges, it represents a model for how other small businesses in the tourism sector might embrace technology and boost their efficiency.

Perdigão, E. and Alturas, B. (2025) 'Developing an app proposal for tuk tuk service management', Int. J. Business Information Systems, Vol. 48, No. 4, pp.433–451.
DOI: 10.1504/IJBIS.2025.145549

Virtual reality (VR) has steadily become a key tool in sports training, offering immersive environments that simulate real-world physical exercises. However, its application in aerobics training has faced significant challenges, particularly in accurately capturing and recognizing complex body movements. A study in the International Journal of Computational Systems Engineering has overcome some of these barriers obstacles by improving the precision of motion capture and the recognition of different actions during aerobics exercises.

Conventional VR motion capture systems rely on algorithms that align 3D representations of physical objects, so-called point cloud data, to track body movements. However, these systems often struggle with two critical issues: noise and incomplete data. Noise refers to unwanted interference that can distort the data collected by sensors, while incomplete data arises when certain body movements are not fully captured. In aerobics, where precision in movement is key to safe and effective exercising, these issues compromise the effectiveness of VR-based training systems.

Hui Wang of the School of Physical Education at Yan'an University in Yan'an, China, has addressed these challenges by developing two new models. The first focuses on enhancing the Iterative Closest Point (ICP) algorithm, which is used to align point cloud data. ICP is a well-established method, but it is prone to inefficiencies, particularly when faced with noisy or incomplete data. By optimizing the algorithm, Wang has improved accuracy and speed of capture.

The second model focuses on refining action recognition. A neural network is used to analyse the complex relationships between body joints over time by tracking the interactions between different body parts. Wang improved the neural network used by incorporating a perturbation mechanism to deal with noise, which further improved its ability to capture subtle movements and interdependencies between non-adjacent joints during aerobics.

Accuracy up to 99 percent was achieved, indicating a remarkable ability to recognize and classify aerobics movements with minimal error. Moreover, the experimental group using these advanced models outperformed the control group in various performance metrics, particularly in terms of the standardization of movements, the work explains. This enhanced motion recognition technology could significantly improve both the learning experience for students and the ability of instructors to offer targeted feedback, leading to more efficient and personalized training in aerobics.

Wang, H. (2025) 'The application of VR-based fine motion capture algorithm in college aerobics training', Int. J. Computational Systems Engineering, Vol. 9, No. 6, pp.1–10.
DOI: 10.1504/IJCSYSE.2025.145446

Hashtags, the keywords preceded by the "#" symbol, are widely used on social media platforms like Instagram to categorize content and increase its visibility. While their primary function is to help posts reach broader audiences, a study in the International Journal of Web Based Communities shows that hashtags also play a significant role in shaping how users perceive the trustworthiness of the post's source. This research challenges the common practice of "hashtag stuffing", the use of excessive or irrelevant hashtags to boost engagement. It then explores the unintended consequences it may have on the credibility of a given post and the person or company using them.

On Instagram, as with other platforms, hashtags are often used to tap into trending topics or relevant themes, enabling users to increase the visibility of their posts. This study suggests that beyond increasing visibility, hashtags play a significant role in how users judge the credibility of a post.

Ye Han and Peter Haried of the University of Wisconsin-La Crosse, La Cross, Wisconsin, Shuang Wu of Rowan University, Glassboro, New Jersey, USA, carried out experiments and found that hashtags act as "heuristic cues." In psychological terms, a heuristic is a mental shortcut people use to quickly make decisions or judgements without having to analyse every piece of information. In this context, hashtags serve as cues that shape how trustworthy a post seems, even if the viewer does not scrutinize the content itself in detail.

When a post includes hashtags, users tend to assume that the source is more likely to share additional information or similar content. This perception increases the post's credibility, reinforcing trust. However, this trust is undermined when hashtags are deemed irrelevant or excessive, as is the case with hashtag stuffing. Users may begin to question the authenticity of the post, leading them to engage in more critical analysis of the content, ultimately reducing the post's perceived trustworthiness.

This finding underscores a critical tension for Instagram users, particularly commercial enterprises and so-called influencers who all rely on visibility and reach. While using more hashtags may help posts reach a wider audience, the study suggests that excessive or irrelevant hashtags can backfire. Users may interpret such posts as less credible, as the hashtag choices can signal an attempt to manipulate engagement rather than offer valuable or pertinent content.

The research also suggests that the visual nature of Instagram posts affects how users interact with hashtags. If the image is clear and straightforward, users are more likely to engage with hashtags, trusting that the content is well-supported by relevant tagging. In other words, hashtags should be directly related to the post's content to maintain both trust and engagement. This balanced approach prevents users from feeling overwhelmed by irrelevant information and ensures a more authentic connection with the audience, the research suggests.

Han, Y., Wu, S. and Haried, P. (2025) 'The hidden impact of hashtags on Instagram: navigational heuristics on source trustworthiness', Int. J. Web Based Communities, Vol. 21, Nos. 1/2, pp.155–185.
DOI: 10.1504/IJWBC.2025.145135

A study in the International Journal of Knowledge and Learning has looked at how individual personality traits influence how much users disclose personal information on social networking sites. Self-disclosure, revealing personal details to others, is generally considered a key component of online social networking interaction.

Understanding what motivates people to share in this way could help platform providers improve the user experience and engagement. The work might also have applications in psychology, social media studies, but perhaps also it could ultimately benefit the bottom-line for the platforms.

Nam Tien Duong of Ho Chi Minh City University of Economics and Finance, Vietnam, has looked at the intersection of personality, self-presentation, and social networking behaviour. He found that social network users are driven by specific interpersonal needs that shape how much they reveal about themselves. These needs, grounded in Maslow's hierarchy of needs, emphasize the social and emotional drive for connection and affection. Social networking platforms have offered us a unique space to meet these needs through active self-expression online.

The research has drawn on two primary interpersonal needs that shape behaviour: the need for belonging and the need for self-presentation. The need for belonging involves the desire to connect with others and feel recognized, while the need for self-presentation is about managing the image we project to others. The study emphasizes that self-presentation plays an important part in motivating self-disclosure, though its impact varies depending on an individual's personality traits, particularly extraversion and narcissism.

Extraversion refers to a person's tendency to seek out social interaction and enjoy group activities. According to the findings, individuals with high levels of extraversion are more likely to disclose personal information. Their enthusiasm for engaging with others translates into a greater willingness to share personal details. In contrast, introverts, who are less inclined toward social interactions, tend to disclose less about themselves, even when they may still have a strong desire for social inclusion.

Another personality trait that significantly influences self-disclosure is narcissism. Narcissists, who possess a strong desire for admiration and validation, often share more personal information to highlight their perceived individuality. This behaviour is driven by a need to garner attention and reinforce their sense of self-importance, which stands in contrast to those who may share less for more intimate or relational reasons.

Duong, N.T. (2025) 'Why do people disclose themselves on social networking sites? Evidence from Vietnamese Facebook users', Int. J. Knowledge and Learning, Vol. 18, No. 2, pp.186–203.
DOI: 10.1504/IJKL.2025.145086

As digital devices become more integrated into children's lives, concerns about their impact on physical and mental health continue to grow. In modern households, smartphones, tablets, and computers are now commonplace, leading to increased exposure to online content. This shift has raised important questions about how much screen time is appropriate and what effects it has on children's well-being.

The issue of screen time has been widely debated, with research pointing to both potential risks and benefits. Excessive screen use has been linked to physical issues such as eye strain, headaches, and sleep disruption. There are also concerns about the relationship between increased screen time and physical inactivity, as children who spend more time on devices might be less engaged in outdoor play and exercise, both essential for their physical development.

On the other hand, the online world offers numerous opportunities for learning, creativity, and socialization. Educational apps, online learning platforms, and digital games can stimulate intellectual growth, promote critical thinking, and even foster social connections with peers across the globe. The challenge is finding a balance that maximizes the benefits of digital engagement while mitigating the potential negative effects on health and well-being.

Beyond physical health, the psychological effects of digital media are also a growing concern. Research indicates that extended use of devices, particularly those providing access to social media, can influence children's emotional well-being, intellectual development, and sense of identity. While some cases have linked excessive screen time to negative outcomes, the full psychological impact of digital media remains an area of ongoing research. It is important to also acknowledge the positive effects, such as improved cognitive skills and the opportunity for global social connections.

Given these concerns, researchers are exploring more personalized methods of regulating screen time, such as the use of fuzzy logic inference systems. These systems, a type of artificial intelligence, can evaluate complex and imprecise data, making them ideal for tailoring screen time recommendations and restrictions based on a child's unique characteristics.

Parents, guardians, or teachers could input data about a child's age, health, and psychological profile into the system, which would then use this information to determine appropriate screen time and content limits. Unlike generic restrictions, which may be difficult to enforce or inappropriate for all young users, fuzzy logic systems offer a more customized and flexible approach to managing screen use.

While there are existing tools that restrict screen time and block content, an adaptive approach, could be key to managing both the quantity and quality of screen time. Younger, more vulnerable users would have stricter controls and limits, while older, more mature children could access a wider range of appropriate resources, all based on their individual developmental profiles.

Alguliyev, R.M., Abdullayeva, F.J. and Ojagverdiyeva, S.S. (2024) 'Fuzzy expert system for access control of children to the internet', Int. J. Reasoning-based Intelligent Systems, Vol. 16, No. 6, pp.455–462.
DOI: 10.1504/IJRIS.2024.144062

Urban music, which originated in marginalized communities in The Caribbean and the USA, has found a global audience, resonating especially with young people, as is often the case with emerging music genres. Urban music has evolved into more than just a genre of entertainment, it has become a significant cultural force that shapes the identities, behaviour, and educational experiences of young people.

A study in the International Journal of Knowledge and Learning has examined the impact of urban music on secondary school students in Peru. The work sheds new light on its multifaceted role in adolescent life, which may well have wider implications. The findings suggest that urban music, encompassing styles such as hip-hop and reggaetón can serve as a platform for cultural expression and social belonging, influencing students in ways that are deeply linked to their socio-economic environments.

Agustin Angel Roberto Chumpitaz-Avila and Luis Fernando Castro-Llacsa of the National University of San Agustín of Arequipa in Arequipa, Peru, highlight how this musical genre has penetrated schools across Peru, including state, private, and religious institutions. This reflects the wide-reaching influence of urban music. While critics have long asserted that urban music might somehow promote antisocial behaviour, the research suggests that its influence on youth is not so easily categorized and indeed can have a strong positive influence.

Urban music does commonly have explicit lyrics that often feature violence, overtly sexual imagery, and drug use. Those social observers who malign it for these characteristics suggest that young listeners may internalize these messages. However, the current study found that while some students might adopt attitudes reflected in the music, the broader socio-economic and familial context plays a more significant role in determining their behaviour. Urban music, it seems, is a tool for young people to interpret their surroundings rather than an inherently harmful influence.

Chumpitaz-Avila, A.A.R. and Castro-Llacsa, L.F. (2025) 'Comparative analysis of the impact of urban music on students of state, private and parochial educational institutions', Int. J. Knowledge and Learning, Vol. 18, No. 2, pp.170–185.
DOI: 10.1504/IJKL.2025.145085

As digital music libraries continue to expand, the challenge of accurately categorizing musical genres remains high on the agenda. A study in the International Journal of Information and Communication Technology introduces a deep learning model designed to improve the classification of classical music genres.

By employing multi-channel learning (MCL) and Mel-spectrogram analysis, the model, known as MC-MelNet, offers what the research suggests is a more nuanced and efficient approach to genre identification. Tests carried out by its developer, Lei Zhang of the Henan Academy of Drama Arts at Henan University in Zhengzhou, China, show that it outperforms traditional classification methods.

The ability to classify music automatically has far-reaching implications for streaming services, music recommendation algorithms, and digital archiving. Classical music, with its intricate structures and subtle variations, presents a particular challenge for automated classification. Zhang explains that MC-MelNet addresses these issues by integrating multiple layers of analysis, capturing both the tonal and temporal characteristics of a composition.

At the core of MC-MelNet's innovation is its multi-channel learning framework, which processes multiple audio features simultaneously. Conventional approaches rely primarily on Mel-spectrograms, which break down an audio signal into different frequency components in a way that mimics human hearing. However, while effective in capturing tonal elements, Mel-spectrograms alone do not fully represent the temporal dynamics of music.

MC-MelNet overcomes this limitation by incorporating additional audio features such as Mel-frequency cepstral coefficients (MFCC) and Chroma features. MFCCs capture the timbral qualities of a sound, making them useful for distinguishing between different instruments or playing styles. Chroma features, on the other hand, focus on pitch content and harmonic structure. By combining these elements, MC-MelNet creates a richer and more detailed representation of musical compositions, allowing it to distinguish between closely related classical genres with greater accuracy.

Unlike conventional classification methods, which require manual feature extraction, MC-MelNet uses an end-to-end deep learning approach. It utilizes convolutional neural networks (CNNs) to detect spatial patterns in audio data and recurrent neural networks (RNNs), specifically long short-term memory (LSTM) networks, to process sequential musical information.

MC-MelNet might have applications beyond classical music classification. It could, for instance, be adapted for real-time sound processing and audio event detection. Enhancing the model's generalizability by training it on a more diverse dataset could make it applicable to a wider range of genres, improving automated music classification for commercial streaming platforms.

Zhang, L. (2025) 'Classification of classical music genres based on Mel-spectrogram and multi-channel learning', Int. J. Information and Communication Technology, Vol. 26, No. 5, pp.39–53.
DOI: 10.1504/IJICT.2025.145153

A distribution model designed to streamline spare parts delivery to roadside assistance vehicles could cut costs in half, according to work in the International Journal of Shipping and Transport Logistics. The model builds a solution to the well-known Travelling Salesman Problem, a complex optimisation problem that involves finding the shortest route that visits each city once and ends at the starting point. The model was tested on real data from a roadside assistance company operating a fleet of service vehicles.

Abolfazl Shafaei, Mohammad Reza Akbari Jokar, and Majid Rafiee of Sharif University of Technology in Tehran, Iran, and Ahmad Hemmati of the University of Bergen in Bergen, Norway, explain that the major logistical challenge for roadside assistance fleets is balancing inventory space with repair capabilities. Service vehicles have limited space onboard, so they must prioritize particular spare parts and specific tools. Service vehicles usually visit a central warehouse on a regular schedule to restock on spare parts every few days. This adds to overall fuel costs, vehicle wear and tear, and lost servicing time. The new system replaces these frequent trips with a centralized delivery truck that optimizes the frequency and route of spare part deliveries.

However, drivers everywhere expect fast, efficient service from the company with which they entrust their vehicle's roadside maintenance, They also expect it to be inexpensive and a high-quality service.

The team tested several delivery schedules, including daily and every five days, and found that the most efficient option for this roadside assistance company was an optimized cycle on the first, second, and fourth days. This approach reduced costs by 56%.

The new model reduces the need to stockpile items by ensuring regular deliveries to the service fleet out on the road. This frees up space for repair equipment that allows for a wider variety of roadside fixes.

Beyond the immediate time and cost savings to companies running roadside assistance fleets, the model also promises significant environmental benefits. With fewer vehicles returning to a central warehouse to restock, fuel consumption and carbon emissions can be greatly reduced. Indeed, for the test case, the team found that annual carbon dioxide emissions could be reduced by 75 percent.

Shafaei, A., Akbari Jokar, M.R., Rafiee, M. and Hemmati, A. (2025) 'Using the route planning for supplying spare parts to reduce distribution costs: a case study in a roadside assistance company', Int. J. Shipping and Transport Logistics, Vol. 20, No. 1, pp.131-158.
DOI: 10.1504/IJSTL.2025.144995