Artificial Intelligence (AI) is being used widely in many different areas of our lives, including healthcare, education, finance, retail, tourism, and e-commerce. It is allowing business to change the way in which they interact with their customers through the advent of chatbots. Research in the International Journal of Trade and Global Markets has looked at how the evolution of AI-driven chatbots can be integrated into the systems businesses use to interact with their customers.

Minh T.H. Le, Khoi Minh Nguyen, Ngan Thanh Nguyen, Nghi Hoang Vo, Khang Trieu Tran, and Duc Trung Dao of the University of Economics Ho Chi Minh City in Vietnam analysed 335 completed questionnaires which asked correspondents about their experience with AI chatbots. AI chatbots can operate day and night, seven days a week, and give customers prompt responses to their queries. The team explains that such chatbots seem to improve customer experience by boosting quality perception, customer satisfaction, and personalization. Moreover, these AI services appear to cultivate trust and loyalty among customers, which has a positive effect on overall brand relationships.

Earlier studies have tended to focus on the technology itself. This latest work considers the human response. The team explains that the use of AI chatbots allows businesses to streamline operations, tailor their customer interactions, and also to gain useful insights about consumer behaviour. This, they add, is helping with business automation and sales forecasting.

One negative point that arose from the analysis that many people are still worried about the lack of "emotional intelligence" in AI chatbots. This represents an ongoing challenge to maintaining customer satisfaction and trust and is an issue that future developments in AI may well address. Indeed, now is the time for companies that wish to make the most of this emerging technology to encourage and support appropriate development in the AI sector that balances the technological demands with the human experience.

Le, M.T.H., Nguyen, K.M., Nguyen, N.T., Vo, N.H., Tran, K.T. and Dao, D.T. (2024) 'Enhancing the customer experience AI-chatbot: service quality, emotional intelligence, and personalisation', Int. J. Trade and Global Markets, Vol. 19, No. 2, pp.111–132.
DOI: 10.1504/IJTGM.2024.137744

While discussion is ongoing regarding the definition of Artificial Intelligence (AI) and the ethics of certain forms of that technology, it cannot be argued that it is transforming processes across a wide range of industries. Research in the International Journal of Business Information Systems would suggest that some businesses are facing challenges in their efforts to incorporate AI tools into their day-to-day and long-term processes.

Sam Solaimani, Reza Dabestani, Thomas Harrison-Prentice, Edward Ellis, and Michael Kerr of Nyenrode Business University in Breukelen and Abhishek Choudhury and Naser Bakhshi of Deloitte in Amsterdam, The Netherlands, have reviewed the research literature. They used a mixed-methods approach to identify the various factors associated with the integration of AI into business. The study focuses on exploration, implementation, and scaling and offers new insights into how these affect adoption of AI technology.

The team explains that during the exploration phase, the company's culture is important in determining how AI is adopted. A clear business plan and strong support from top management are vital to a successful strategy in this area. The team emphasises how AI projects can be implemented but suggests that leaders within the company must ensure AI adoption matches the company's goals.

In the implementation stage, it is the technical landscape that is important with problem orientation and data quality being the key parts of identifying obstacles and issues. Good planning and resource allocation are needed in this stage to make sure the deployment of AI will be successful from the technological perspective.

The team then considers the scaling phase. This area considers data governance, safeguards associated with the precision and accuracy of the algorithms used and their outputs, and, inevitably, cybersecurity. They conclude that: "[Our] contribute to the scholarly discourse on critical success factors relevant to AI adoption and help firms sharpen their focus and leverage their resources efficiently towards a more effective adoption of AI."

Solaimani, S., Dabestani, R., Harrison-Prentice, T., Ellis, E., Kerr, M., Choudhury, A. and Bakhshi, N. (2024) 'Exploration and prioritisation of critical success factors in adoption of artificial intelligence: a mixed-methods study', Int. J. Business Information Systems, Vol. 45, No. 4, pp.429–453.
DOI: 10.1504/IJBIS.2024.138052

Millions of people around the world live with diabetes mellitus. Many of them have medication and specific dietary management approaches to help them maintain stable blood sugar levels. However, recent innovations, such as inhaled insulin, the hormone made by the pancreas, which controls blood sugar, have sparked hope for more effective and user-friendly treatments.

Diabetes is characterized by insufficient insulin production or ineffective insulin utilization. It causes many health problems and risks for those with one of the various forms of the disease. Risks include cardiovascular disease and microvascular complications such as eye, nerve, and kidney disorders. There is also the risk of acute problems that can lead to sudden death.

Conventional treatments rely on daily insulin injections or insulin pumps used in conjunction with regular blood glucose monitoring. Such regimens can be complicated and are associated with discomfort, time constraints, and the need for precise dosing, to avoid unpredictable blood sugar levels and severe complications.

Inhalable insulin offers a new approach to diabetes management. Using devices, similar to those used by people with asthma or other chronic lung diseases, including nebulizers and metered-dose inhalers it is possible to dispense a precise amount of insulin into the patient's lungs from where the hormone will be absorbed into the bloodstream quickly and effectively allowing for rapid action when needed.

One such drug, Afrezza, a fast-acting inhalable insulin, was given US Food & Drug Administration (FDA) approval in 2014 and remains the only inhaled insulin product on the market. It represented an important step towards a new approach to diabetes treatment. Some earlier inhaled therapies had not proven themselves safe nor effective. Afrezza has a more reliable pharmacokinetic profile, which will give patients greater convenience and improved control of their blood sugar levels.

Writing in the International Journal of Nano and Biomaterials, a team from India explains that insulin inhalers could improve patient adherence to their drug regimen and thus outcomes by providing a non-invasive and user-friendly alternative to traditional administration methods. Priya Patel and Bhavisha Kacha of the Department of Pharmaceutical Sciences at Saurashtra University in Gujarat, India, add that nanotechnology could help drive the next steps in developing even more effective inhaler-type drug delivery systems for treating diabetes mellitus.

Patel, P. and Kacha, B. (2024) 'Inhaled insulin: current steps towards diabetes treatment', Int. J. Nano and Biomaterials, Vol. 10, No. 3, pp.171–188.
DOI: 10.1504/IJNBM.2024.137687

A detailed analysis of Vietnam's real estate market aimed to identify the factors that contribute to the formation of real estate bubbles. The study, published in the International Journal of Economics and Business Research covered the period from 2011 to 2021 and focused on various economic variables and regional factors influencing property prices and the overall stability of the real estate market.

Le Phuong Lan of the Foreign Trade University and Nguyen Quynh Anh of Tien Phong Bank both in Hanoi, Vietnam, point out that in the wake of the COVID-19 pandemic, which itself revealed vulnerabilities in Vietnam's real estate sector, the new work shows that proactive measures are needed to mitigate against financial risks in this sector and to attempt to avoid unsustainable increases in property prices.

The researchers looked at macroeconomic indicators, such as economic growth, inflation, lending interest rates, money supply, credit growth, migration rates, and provincial competitiveness. They then used their findings to develop a predictive model that would hopefully allow them to spot any patterns as the real estate market evolves.

Critically, economic growth seems to be the real driver for activity across the real estate sector, The team points out that fluctuations in the growth rate of Vietnam's Gross Domestic Product (GDP), is linked to changes in the overall demand for property and investment in property. Conversely, inflationary pressures and variations in lending interest rates, because they affect borrowing costs, are another important factor that influences buying and selling behaviour in the real estate market. Unfortunately, the team also showed that liquidity within the financial system in general has a major effect on real estate speculation. The greater the money supply and credit growth, the greater the property price inflation. The team found some regional disparities where migration rates and provincial competitiveness affected movement in the real estate sector in specific geographic areas.

Their conclusion is that measures to enhance transparency and regulatory oversight should be put in place to improve the way in which market participants garner information and to protect them and the sector from at least some of the common risks. They add that prudent monetary policy and effective macroeconomic management could also be used to maintain stability and confidence in the real estate sector and the broader financial system.

Lan, L.P. and Anh, N.Q. (2024) 'Impacts of macroeconomic factors on the real estate bubble in Vietnam's big cities with industrial zones', Int. J. Economics and Business Research, Vol. 27, No. 3, pp.511–532.
DOI: 10.1504/IJEBR.2024.138079

A study in the International Journal of Economics and Business Research has looked at the various factors affecting fluctuations in the price of natural rubber in Thailand, the world's largest producer of the product. The study considers both domestic and external influences on rubber prices, showing just how the Thai market is affected by global changes and trends.

Part Sungkaew of King Mongkut's University of Technology North Bangkok, in Thailand, points out that exports are critical to the Thai rubber industry. Just 18 percent of production is used domestically. Even then, domestic use is largely accounted for by foreign companies operating within Thailand. In other words, external factors such as exchange rates, export volumes, and oil prices all play part in determining the price. Moreover, despite Thailand being the leading producer, Sungkaew found that the market favours foreign buyers.

An important factor that affects price is the volume of natural rubber stock within Thailand and abroad. This factor makes the Thai industry vulnerable to global market dynamics, with price changes in other major producing countries such as Malaysia and Indonesia affecting prices in Thailand. In addition, the rise of China as a major consumer further complicates the changing market, suggesting a shift in the balance of power in the global natural rubber market.

Rubber farm cooperatives have offered some relief through cost-saving measures and efficiency drives. However, the impact of these is very subtle. The actions of the rubber farmers themselves has a very small role to play in the global natural rubber market.

There have also been government interventions aimed at trying to prevent falling prices, driven by changing stocks and demand. But, the study found that the predominance of large buyers persists. The Thai government is under pressure to create policies to support value-added rubber products and the domestic industries in an attempt to mitigate against price fluctuations and stabilise the market.

Sungkaew, P. (2024) 'Factors affecting natural rubber prices in Thailand', Int. J. Economics and Business Research, Vol. 27, No. 3, pp.489–510.
DOI: 10.1504/IJEBR.2024.138077

The exchange of knowledge has always been an important part of the research process. Digital platforms have made this easier than ever but at the same time added to the information burden. There are efficient tools available to researchers that allow them to collaborate and share knowledge more effectively. Research in the International Journal of Business Innovation and Research has investigated the various factors that lead to academics participating or otherwise in such systems.

Osama F. Al Kurdi of Ahlia University in Manama, Bahrain, has carried out a quantitative study using Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyse feedback from academics on their use of online research communities. He has thus been able to identify seven important variables including attitudes towards knowledge, intention to share knowledge, perceived behavioural control, self-efficacy, subjective norms, and the role of tools and technology.

As one might expect, the most important variable driving use of online research collaboration is the individual's attitude to this kind of approach to research. The research would therefore suggest that to boost use of such systems, the service providers need to do their best to foster positive attitudes within academic institutions.

Beyond the obvious implications of the research, the paper also has broader significance for theoretical frameworks and practical applications. The theoretical integration of elements from the Theory of Planned Behaviour and social exchange theories provides insights into knowledge-sharing behaviour in an academic setting. Individual attitude needs to be considered together with social and technological influences. The ultimate aim is to improve knowledge sharing with a view to improving innovation.

Al Kurdi, O.F. (2024) 'Factors affecting the use of online research collaboration platforms for knowledge sharing: evidence from knowledge-intensive organisations', Int. J. Business Innovation and Research, Vol. 33, No. 4, pp.433–456
DOI: 10.1504/IJBIR.2024.137604

Crime is an age-old and never-ending problem for societies worldwide and crime detection and crime fighting have always chased after the criminals who often stay one step ahead. Research in the International Journal of Knowledge-Based Development has turned to emotional data alongside machine learning (ML) and deep learning (DL) techniques to develop technology that might one day help us better understand the criminal mind and perhaps even predict criminal activity so that it might be prevented.

A. Kalai Selvan and N. Sivakumaran of the Department of Instrumentation and Control Engineering & Head at the National Institute of Technology,in Tiruchirappalli, Tamil Nadu, India had two main objectives: the prediction of crime using ML models based on emotional data and the identification of future crime hotspots using DL methods applied to crime incident data.

By analysing voice-based emotional cues using ML algorithms, the team has achieved a detection accuracy of 97.2% for various crimes. Additionally, DL techniques, particularly convolutional stacked bidirectional long short-term memory (LSTM), allowed them to detect crime hotspots with an accuracy of 95.64%.

The researchers point out how the significance of emotional states in speech patterns allowed them to explore speech-based emotion detection. They took into account linguistic origin, paralinguistic cues, and the characteristics of the speaker. This allowed them to integrate the emotional data they obtained with other factors such as location and the type of crime that takes place in a hotspot. While, the notion sounds rather futuristic, the rapid advances in algorithms that can extract and identify patterns in data is in no way a matter only for science fiction. The team says that their approach could monitor activity in crime hotspots, detect crimes, and forecast future criminal activities.

Future work might allow similar machine learning techniques to be used for emergency response systems, rather than only in crime fighting. By analysing the emotional content of a person calling the emergency services, the system might be able to distinguish between genuine emergencies and non-emergency or even fraudulent calls, which could reduce the burden on the services considerably. It is only a matter of time before the research takes the prediction accuracy closer and closer to the ideal 100 percent of the ultimate crime-fighting AI emotion detector.

Kalai Selvan, A. and Sivakumaran, N. (2024) 'Crime detection and crime hot spot prediction using the BI-LSTM deep learning model', Int. J. Knowledge-Based Development, Vol. 14, No. 1, pp.57–86.
DOI: 10.1504/IJKBD.2024.137600

A comprehensive review of lithium-ion batteries in electric vehicles and energy-storage systems offers a valuable resource for researchers in this area, according to the authors writing in the International Journal of Vehicle Information and Communication Systems.

Electric vehicles (EVs) are an important part of sustainable personal transport as we try to move from a world drive on fossil fuels to one powered by solar, wind, and other renewables. Lithium-ion batteries continue to play a vital role in the ongoing success of EVs, and will do so until an even better alternative storage technology is developed.

Mandar Maruti Bidwe and Swanand Gajanan Kulkarni of the SKN Sinhgad College of Engineering in Korti, Pandharpur, Maharashtra, India, conducted a detailed review of the research literature covering the period 2010 to 2022. They hope that their work will shine headlights on the lithium-ion battery roadmap and help researchers navigate the terrain towards future sustainable of electric transportation and energy storage.

The team's review looked at various aspects of lithium-ion battery technology and shows that it is important to understanding the diverse materials used in different types of battery and the impact these material choices have on performance, lifetime, and sustainability. The team explains that materials such as lithium cobalt oxide offer high energy density but are hindered by limited availability and lower thermal stability. By contrast, materials such as lithium iron phosphate are much safer and longer-lasting, but do not necessarily have the energy density some applications demand.

There is an ongoing need to model the behaviour of different types of battery in order to develop technology that optimises battery performance and management systems without too much compromise in terms of sustainability and resource safety and ethics. The review points to various papers that have focused on such models and assesses which might be used to best effect by researchers. This is critical given that challenges exist, not least in terms of the recycling and sustainability. The team points to several research gaps in these areas that could help focus efforts.

Research into lithium-ion batteries is multidisciplinary and given its central role in the electrification of transport it will be a focus for several years yet. This review offers waymarkers on the roadmap for research and development.

Bidwe, M.M. and Kulkarni, S.G. (2024) 'Lithium-ion battery: a review', Int. J. Vehicle Information and Communication Systems, Vol. 9, No. 2, pp.135–163.
DOI: 10.1504/IJVICS.2024.137854

TikTok is a social media platform known for its short-form videos. Content creators, who have built a significant following on the site, often work with corporate brands to promote products to their audience, often through affiliate marketing. This involves a so-called influencer sharing products in their videos with affiliate links and then earning a commission from the company for purchases made through those links. It might be said that success lies in creating authentic content that attracts users and takes advantage of the current trends. However, for an influencer to be successful, they need to be transparent about their affiliate relationships in order to build and maintain the trust of their audience.

Writing in the International Journal of Technology Marketing, Minh T.H. Le of the College of Business at the University of Economics in Ho Chi Minh City (UEH), Vietnam, discusses how the effectiveness of affiliate marketing might be improved by users hoping to influence young people. Le's study was based on a standardized questionnaire distributed across internet platforms. The results were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Her research identified some of the factors affecting consumer trust and buying decisions, including the opinions of other followers.

She found that the perceived expertise of content creators and feedback from their followers is important to consumer trust. Le explains that a marketing campaign can pivot on this point. However, the entertainment value of an influencer video, is perhaps the most important factor leading to better user engagement and whether that user buys the products touted by the influencers they follow.

The detailed findings discussed in IJTMKT offer practical guidance for marketers and businesses who are attempting to make the most of digital marketing. The advice suggests that companies need to understand how Key Opinion Leaders, Key Opinion Consumers, and influencers operate and the effect they have on everyday users. Given that TikTok appeals to a wide audience seeking amusement as well as product recommendations, it is worth exploring in detail its potential as a marketing channel.

Le, M.T.H. (2024) 'Enhance the effectiveness of affiliate marketing on Tiktok for young people', Int. J. Technology Marketing, Vol. 18, No. 2, pp.162–184.
DOI: 10.1504/IJTMKT.2024.137669

The digital library is a searchable store of text, audio and visual materials, and more. However, as the amount of data that must be stored and made searchable increases, efficient management and retrieval can be a major headache for the digital library. Research in the International Journal of Information and Communication Technology could lead to a new solution to the problem by integrating image processing, big data analytics, and deep learning techniques.

Xiaoyan Wang and Meimei Jia of Nanyang Normal University, Nanyang, Henan, China, like others, recognise the complexities of enhanced multimedia search and retrieval and have turned to the modern tool of deep learning to help. The team has developed a cross-media semantic search framework. This finds and uses the correlations between different types of media to assist in search and retrieval. Their deep learning algorithm can analyse and organize multimedia resources to improve search accuracy and system performance. Indeed, the use of this cross-modal correlation analysis and hierarchical knowledge inference in refining search results gave the team an almost 12 percent boost in search performance when compared with conventional approaches.

The approach will be useful for generic digital libraries and could be extended to personal devices such as smartphones, enabling greater access to useful information silos for the lay public. In more specialist applications, the same approach might be used in medical and scientific information systems. This could allow complex medical imagery, such as MRI scans and diagnostic test data and chemical databases, to be more readily searchable. In enterprise knowledge management systems, with such a system, companies could better handle their ever-accumulating data and information. Moreover, in any field where vast amounts of multimedia data accumulate every day and need efficient search and retrieval methods to make the most of the information they hold, an improved system will benefit users.

Wang, X. and Jia, M. (2024) 'Development of a unified digital library system: integration of image processing, big data, and deep learning', Int. J. Information and Communication Technology, Vol. 24, No. 3, pp.378–391.
DOI: 10.1504/IJICT.2024.137942

Technology is changing all areas of education not least language learning. Research in the International Journal of Information and Communication Technology has looked at the potential of Computer-assisted Language Learning (CALL).

Learning a new language has usually relied on the traditional classroom setting and a native speaker of the language to teach students the vocabulary and grammar. However, there have for many years language learning systems that use voice recordings and books. In recent years, these systems have migrated to smartphones. The number of learners answering the CALL has risen because of the accessibility and convenience. Such systems now use artificial intelligence and algorithmic processing to help learners get to grips with their language second, or third, or more, language of choice. Indeed, the new tools offer an immersive and interactive language-learning experience.

Ning Li of the Public Teaching Department at Henan Vocational College of Tuina in Luoyang, Henan, China, explains that one aspect of language learning by app is the potential of the software to provide learners with an assessment of their progress and oral proficiency. If the system can analyse the words spoken by the learner in their non-native tongue, then they can be guided to the next level in their education appropriately or given advice on checking and rechecking their understanding and ability.

CALL systems can offer tailored teaching and thus have the potential to address individual learning needs, accelerating language acquisition for those learners who can cope and slowing the teaching process for those who need more time. Of course, variability in accent and dialect represent a challenge for the assessment algorithms and new innovations and refinements are still needed to make CALL as effective as traditional teaching and learning methods.

CALL could open up linguistic opportunities far and wide. With improvements in AI such systems will be able to assess learners before they are released into the wilds of international conversation.

Li, N. (2024) 'Research on scoring mechanism of spoken English self-study system taking into account artificial intelligence technology and speech knowledge recognition algorithm', Int. J. Information and Communication Technology, Vol. 24, No. 3, pp.350–365.
DOI: 10.1504/IJICT.2024.137941

The responsibility for maintaining online safety relies on content moderators particularly in times of crisis. However, not all platforms even have moderation systems in place and so disinformation, misinformation, propaganda, and fake news often circulate freely. The time of the COVID-19 pandemic was a case in point, but the propagation of fake news occurs during times of political change and in the wake of other kinds of crises and socioeconomic upheaval. However, there is much content online that is illegal rather than simply being fake and that must be removed summarily.

Some social media platforms and websites do have individuals and even teams who are tasked with checking user-generated content to ensure it does not contravene the law. Elena Martellozzo, Paula Bradbury, Ruth Spence, and Jeffrey DeMarco of Middlesex University, London, UK, and Paul Bleakley of the University of New Haven, West Haven, USA, point out that during and after the COVID-19 pandemic there was a surge in the volume of illegal content. They report details of their findings and the implications in the International Journal of Technology, Policy and Management.

The researchers have looked at the experience of content moderators during this period and their findings offer new insights into how this important online role can affect the moderators' mental well-being. Indeed, the upward trend in illegal material being shared online, exacerbated by lockdown measures during the pandemic, put the content moderators under immense pressure. There was a heightened risk of personal burnout, mental health problems, and even trauma when it came to particular kinds of illegal content that required moderation. The new findings suggest that there is an urgent need to improve the working conditions and personnel backup for such moderators.

Lessons drawn from the pandemic era should provide service providers and their staff, including their content moderators, useful guidance for the improvement of working conditions. Employers must prioritize mental health support, fair compensation, and comprehensive training, the research suggests. This is especially important given the role played by content moderators in helping to remove illegal content from the internet.

The researchers add that clear communication, professional development opportunities, and tailored support mechanisms, particularly for those working remotely or in a hybrid work environment, are important considerations for employers and service providers.

Martellozzo, E., Bleakley, P., Bradbury, P., Spence, R. and DeMarco, J. (2024) 'Supporting digital key workers: addressing the challenges faced by content moderators during and after the COVID-19 pandemic', Int. J. Technology, Policy and Management, Vol. 24, No. 2, pp.212–228.
DOI: 10.1504/IJTPM.2024.137818

The advent of crowdfunding, whereby innovative ideas find financial backing from the collective support of online communities, such as Indiegogo and Kickstarter, has allowed countless projects to become viable in recent years. Many of those projects, while attractive and ultimately successful, may never have garnered support from conventional investors and backers. Of course, not all crowdfunding enterprises are successful, and a study in the International Journal of Electronic Business has looked at how much effect first impressions has on what a campaign might ultimately achieve.

Mathupayas Thongmak of the Thammasat Business School at Thammasat University in Bangkok, Thailand, has focused on Indiegogo as a well-known crowdfunding platform. She points out that to date, the rate of success among crowdfunding campaigns remains relatively low. The present study offers insights that might help putative campaigners develop a more effective strategy for success.

Presentation is almost all when it comes to a successful campaign. Potential backers wading through many project options commonly rely on first impressions to decide whether to investigate a given campaign further. In other words, an attractive thumbnail image, text introduction, and category choice, are vital. Without them, most backers scanning for opportunities will simply swipe left, to use the parlance of dating apps, where such a swipe amounts to a rejection.

Earlier work has looked at the factors that coincide with a successful crowdfunding campaign, but Thongmak has used descriptive statistics, word clouds, tree maps, and hierarchical regression analysis to analyse data from more than 300 campaigns to look at what characterises successful outcomes. It seems that timing is almost everything, but appropriate category choice can affect success rate for campaigners significantly. Moreover, the most likely to succeed are campaigns in the technology and innovation sectors, with health and fitness products featuring prominently, followed by home, travel, and outdoor equipment. It is worth noting that text on a thumbnail image did not affect success rate. As such, Thongmak suggests that campaigners should use their thumbnail image to make their project stand out more from the other images through the choice of a more creative design and colour scheme.

Thongmak, M. (2024) 'Does first impression count? A look at Indiegogo campaigns on the 'Explore All Projects' page', Int. J. Electronic Business, Vol. 19, No. 2, pp.181–208.
DOI: 10.1504/IJEB.2024.137688

Research in the International Journal of Shipping and Transport Logistics has looked at the various factors that affect the overall effectiveness of shipping alliances in the container shipping industry. These alliances, formed as cooperative agreements between container carriers, have become an important part of the industry, providing benefits such as expanded market access, operational efficiency, and keeping companies afloat in turbulent times.

Hui Ting Lu, Kum Fai Yuen, and Kim Hock Tan of Nanyang Technological University in Singapore and Guanqiu Qi of Chung-Ang University in South Korea surveyed 180 executives from major shipping lines involved in prominent alliances. They used the survey results to identify 20 factors associated with successful alliances. They then measured the impact of these factors, such as opportunistic behaviour and constructive coordination, on outcomes for the companies involved in the alliances.

In order to formalise their results, the team categorized the critical success factors as: alliance rationale and conditions, partner search and selection, partnership design, partnership implementation, and partnership outcome evaluation. Within these different phases, the team found that alliance rationale and conditions in particular influenced constructive coordination among partners.

The team also used various theoretical frameworks, such as transaction cost theory, resource-based view, knowledge-based theory, sociological approaches, and general management and leadership theory to provide a comprehensive understanding of critical success factors and how they relate to those different phases and the outcomes among shipping alliances.

The team found that the initial phases of alliance building depended on strong foundations built through careful partner selection and the ongoing strength of the alliance needed a good working relationship for its implementation but also continuous evaluation of the pros and cons. The researchers also found that success depended on the ability for partners to adapt to external factors such as regulatory changes and cybersecurity threats to maintain coordination and achieve their goals.

The container shipping industry must ride the waves of changing markets. The research highlights a continued need for improved understanding of how alliances between different companies can work and to allow them to navigate safely through smooth seas and dire straits.

Lu, H.T., Yuen, K.F., Tan, K.H. and Qi, G. (2024) 'Critical success factors of strategic alliance in the shipping industry', Int. J. Shipping and Transport Logistics, Vol. 18, No. 2, pp.111–137.
DOI: 10.1504/IJSTL.2024.137890

An analysis of glacial data spanning four decades has provided valuable insights into the changes taking place in the glaciers of the Pir Panjal range within the Kashmir basin in India. The research, published in the International Journal of Hydrology Science and Technology, analysed data for the period 1980 to 2020. It reveals significant losses in glacial mass and points out just how important this could be for the people and ecosystems that rely on the melt waters from these glaciers. It also highlights the flood risks associated with sudden catastrophic changes in the glaciers as they melt.

Mohmad Ashraf Ganaie and Syed Kaiser Bukhari of the National Institute of Technology Srinagar, Jammu and Kashmir, India, identified 122 glaciers that by 2020 had decreased notably in size since 1980. For example, a glacial region of almost 26 kilometres in 1980 had shrunk to just under 16 square kilometres by 2020. One particular glacial watershed, Vishaw, which encompasses 55 glaciers, had lost more than 6 square kilometres.

Topography plays an important role in how rapidly glaciers have receded during this period of time. The smaller glaciers, those less than or equal to 0.5 square kilometre, were found to be receded faster than the bigger glaciers. Moreover, south-facing glaciers and those at lower elevations demonstrated too were receding more rapidly, the team found. The different rates of glacial loss suggest that there are many complex factors at play.

The Himalayan glaciers are a vital source of water for those in their shadow. They play a major role in sustaining river flow and supporting human activities such as agriculture and hydroelectric power generation, as well maintaining the natural, local ecosystems, wildlife, and habitats. The impact of glacial loss will be gradual, but with accelerating loss due to climate change there is the risk of melted glacial lakes suddenly release huge volumes of water downstream, which could devastate human settlements and the ecosystems in its path.

Historically, there have been limited numbers of remote sensors and monitoring of the glaciers in this region. There is now a pressing need to understand the changes taking place and the effect these changes will have on water resource management, flood risk, and the local environment.

Ganaie, M.A. and Bukhari, S.K. (2024) 'Inventory and status of glaciers in the Pir Panjal Range Kashmir basin between 1980 and 2020', Int. J. Hydrology Science and Technology, Vol. 17, No. 3, pp.319–347.
DOI: 10.1504/IJHST.2024.137781

Employee engagement among independent gig workers is an important issue facing organisations working with remote teams and individuals. A study in the International Journal of Management Concepts and Philosophy which looked at the connections between gig workers and their client teams, suggests there is a need to improve engagement to improve working conditions, well-being, and mental health for remote workers.

The gig economy is a labour market where individuals work on short-term contracts or as long-term freelancers. Freelancers have been a part of the economy for many years, but in the digital era, applications and platforms have opened up many jobs that were previously restricted to the conventional workplace. Gig workers enjoy flexibility but also face challenges like job security and benefits.

Rebecca Wason of Algoma University in Sault Ste. Marie, Ontario, Canada, has used a structured questionnaire based on William Kahn's three facets of employee engagement – meaningfulness, safety, and availability – and found significant differences in gig worker engagement levels. It seems that gig workers commonly feel satisfied with their work, but often feel isolated from their peers and management.

The research found that many respondents felt a lack of clarity from their managers regarding the significance and purpose of their work was a major problem. In addition, Wason found that some respondents felt that they had insufficient guidance on organisational culture and norms. This, the work suggests, leads to difficulty in integrating within client teams as well as a problem with forming social bonds. This leads to feelings of exclusion and detachment.

Effective communication, clear task assignment, and supportive organisational structures are all important in improving gig worker engagement. Addressing such issues could improve the working lives of gig workers, as well the outcomes for the organisations for which they work.

Wason, R. (2024) 'Disengaged: the problem of employee engagement in gig workers', Int. J. Management Concepts and Philosophy, Vol. 17, No. 2, pp.149–160.
DOI: 10.1504/IJMCP.2024.137637

The global COVID-19 pandemic caused much suffering and tragedy and continues to do so. One aspect of our everyday lives that was massively disrupted was education. Conventional classroom teaching methods had to be digitised urgently during lockdowns when schools were forced to close to reduce the risk of spreading the potentially lethal coronavirus. A study in the International Journal of Mobile Learning and Organisation has looked out how new strategies had to be developed during this time and how educators were forced to tackle the emergence of cyberbullying among middle school students that the shift to online learning led to.

In their work, Sasipim Poompimol, Suthiporn Sajjapanroj, and Thanyaluck Ingkavara of Mahidol University in Nakhon Pathom, Patcharin Panjaburee of Khon Kaen University in Khon Kaen, Chanayuth Changpetch of Mahasarakham University in Maha Sarakham, and Preeyada Tapingkae of Bansanpasak School in Chiang Mai, Thailand, introduced a digital board game along with multimedia debriefing sessions that could be used as educational tools for online and distance learning. These tools can be used to reduce the incidence of cyberbullying during a major crisis and afterwards, where online learning has become part of the new normal.

The team's case study involved 56 middle school students. The team found that the students' understanding and perceptions of cyberbullying after participating in gaming sessions with multimedia debriefing was much greater than when compared to those gaming sessions without the debriefing. Self-reported questionnaires and interviews further indicated positive experiences with the multimedia debriefing method and effectiveness of this game-based approach to learning in improving the students' understanding of cyberbullying and hopefully leading to a fall in the number of such incidents.

The research also has implications beyond addressing the problem of cyberbullying. A similar approach might also be used to address mental health and digital well-being issues that arise when students are isolated from classmates and find themselves learning in their homes rather than the classroom, where there might be family or other environmental pressures on them. Innovation of this kind allows teachers to improve the learning experience for students. This will be relevant in the post-pandemic world and in the future when we have to face another such crisis.

Poompimol, S., Panjaburee, P., Sajjapanroj, S., Changpetch, C., Tapingkae, P. and Ingkavara, T. (2024) 'Ubiquitous game-based learning with a multimedia debriefing on cyberbullying during the COVID-19 pandemic', Int. J. Mobile Learning and Organisation, Vol. 18, No. 2, pp.135–168.
DOI: 10.1504/IJMLO.2024.137610

Sustainable competitive advantage and business are critical to long-term viability in the hospitality industry in India, according to a study published in the International Journal of Business Excellence. The study focused on the National Capital Region but could equally apply more widely. Such insight is important to those working in the sector, given its highly competitive nature and ever-changing consumer preferences.

Deepali Anand and Alka Munjal of Amity University in Noida, India looked at the sector regarding hotels given star ratings in the region. They investigated how hoteliers boost their competitive advantage through cost leadership and differentiation. Cost leadership involves minimizing production and distribution costs while still offering a high-quality service to hotel guests. This is typically done through measures such as economies of scale and improved technology that can improve efficiency. On the other hand, differentiation focuses on giving customers a unique "offering" or "value proposition" that improves brand loyalty and the chances of a customer using the hotel repeatedly or sticking with a given of hotels if visiting other areas.

The hospitality industry, by its very nature, is obviously service-oriented. Aspiring to excellence at whatever star-rating a given hotel has, is critical to its long-term success. This involves excellent customer relations, organizational growth, employee satisfaction, and the quality of what the hotel offers its guests. However, demands of the modern traveller are constantly changing, albeit the basic need remains the same – a room with a bed and bathroom facilities. In India, there are also government initiatives that are there to support the hospitality sector. Hotels can benefit from these, but must, in their part, adapt to change and so innovate when it comes to how they operate.

The team considered whether hotels could benefit from prioritizing cost leadership, differentiation, or a combination of both. And, yes, these strategies do affect how hotels are run. Understanding the effect of different strategies can then decide whether a given hotel will have greater or less success in a competitive market environment.

Anand, D. and Munjal, A. (2024) 'Effect of sustainable competitive advantage on business excellence in the hotel industry', Int. J. Business Excellence, Vol. 32, No. 4, pp.545–560.
DOI: 10.1504/IJBEX.2024.137569

Research in the International Journal of Networking and Virtual Organisations has investigated compulsive online shopping behaviour in India, with a specific focus aimed at unzipping the triggers and antecedents related to the purchase of jeans.

D. Manimegalai of the Department of Management Studies and S. Senthilkumar of the College of Management at the SRM Institute of Science and Technology in Tamil Nadu, India, carried out an online survey with more than 200 participants. They identified several factors that drive compulsive shopping tendencies among different demographic groups, including both male and female consumers.

The team has identified, through a detailed statistical analysis of their survey results, what compels shoppers to by denim trousers. Internal triggers, such as emotions and personal experiences, interact with external stimuli like online usage patterns and social influences to shape the purchasing decisions of online shoppers. Their findings could help marketing executives better understand consumer behaviour and so develop strategies to sell more jeans online.

The researchers point out that there are almost three-quarters of a billion pairs of jeans sold each year in India. That suggests on average that the population as a whole has a new pair of jeans every two years. But, the assumption is that everyone from toddlers to senior adults wears jeans. However, the research does suggest that there is a lot of compulsive behaviour and presumably a lot of adults with disposable income buying many more pairs of genes than that glib average would suggest.

Such repetitive buying may have future financial implications as well as highlighting latent social and psychological well-being issues. This would be especially the case if the compulsive buying extended to other products and led to increasing levels of debt. Indeed, the findings hint at the role of loneliness, anxiety, and novelty-seeking tendencies in driving compulsive shopping. The work thus highlights a responsibility and the need for targeted interventions and support mechanisms.

Manimegalai, D. and Senthilkumar, S. (2024) 'The triggers on compulsive online shopping of jeans', Int. J. Networking and Virtual Organisations, Vol. 30, No. 2, pp.206–219.
DOI: 10.1504/IJNVO.2024.137541

A study in the International Journal of Shipping and Transport Logistics has outlined strategies to help liner shipping companies navigate the global market more effectively. The work was undertaken by Umur Bucak of the Department of Maritime Business Administration at Kocaeli University in Turkey against a challenging seascape. The study identifies key trends that are shaping the sector and offers practical insights for how companies might maintain competitiveness and build bridges to span the many challenges they face.

Bucak focused on the impact of geopolitical tensions, environmental regulations, and crises, such as the COVID-19 pandemic. The work emphasises how liner shipping companies must be able to change course quickly to benefit from changes in the market.

Using a combination of expected utilities theory and competitive advantage theory, Bucak was able to assess the prevalent market trends, which include digital transformation, decarbonisation initiatives, and supply chain integration. These trends are all key to making strategic decisions in the industry.

In order to determine effective strategies that would align with these trends, Bucak then used a hybrid methodology involving a fuzzy Analytic Hierarchy Process (AHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The work showed that the prioritization of rapid shipping between ports emerged as particularly beneficial and reflects the industry's focus on speed and reliability amid rising freight rates and port congestion. The research also considers the economic implications of the trends identified by Bucak. By providing a framework for decision-making, his work could assist industry practitioners anchor themselves in a competitive market.

The study thus represents a significant step towards understanding and responding to changes within the liner shipping market. By using methodological innovations and theoretical frameworks, the research offers new and invaluable guidance for companies seeking to thrive amidst market shifts.

Bucak, U. (2024) 'Expected utilities of liner shipping market trends: how can companies benefit?', Int. J. Shipping and Transport Logistics, Vol. 18, No. 1, pp.92–110.
DOI: 10.1504/IJSTL.2024.137588

A study of economic indicators in the wine industry across the European Union has shown significant variation between member states. Many of these are influenced by factors such as vineyard size and specialization.

Writing in the Journal for Global Business Advancement, a team from Cyprus explains how they used the Farm Accountancy Data Network (FADN) methodology to examine the economic indicators crucial for assessing the financial health of wine-producing farms. Aleksandra Figurek, Alkis Thrassou, and Demetris Vrontis of the University of Nicosia in Cyprus, EU, focused on metrics such as farm net value added (FNVA), FNVA per annual working unit (AWU), farm net income (FNI), and family farm income (FFI/FWU) for wine producers participating in the FADN. The team's analysis provides insights into productivity and profitability by looking at the ratio between total output and input utilization, including intermediate consumption and specific expenses.

Despite this diversity between EU member states, the FADN methodology uses a standardized framework for analysing financial performance. It is this that allowed the team to identify best practices and areas for improvement, which could be useful for various stakeholders across the wine industry in different parts of the EU.

The transition to the Farm Sustainability Data Network (FSDN) for many wine producers highlights the opportunity to expand data collection efforts to include environmental and social practices. This integrated approach enables a more comprehensive assessment of agricultural performance, which could help stakeholder decision-making at the local, micro, and macro levels. Additionally, the implementation of the new Common Agricultural Policy (CAP) (2023 to 2027), which prioritizes environmental sustainability and support for smaller farmers, aims to align agricultural growth with ecological and technological goals while enhancing competitiveness. The data analysis could thus help evaluate the efficacy of the CAP.

This research shows how new data methodologies can be used to study what programs are improving economic performance in wine production across the EU. By using such data-driven insights and seeing how this fits in with the ever-changing policy frameworks, the EU wine industry might at once address the challenges it faces and capitalize on the opportunities for sustainable growth and competitiveness in the global market.

Figurek, A., Thrassou, A. and Vrontis, D. (2023) 'Economic performance of wine production in EU: a multi-indicator comparative analysis', J. Global Business Advancement, Vol. 16, No. 1, pp.3–30.
DOI: 10.1504/JGBA.2023.137469

A recent study in the International Journal of Learning and Change has looked at how consumers interpret masculinity in advertising. The study reveals some intriguing findings and sheds light on how active engagement is shaped by an analysis of the portrayals of masculinity in advertisements on the well-known video-sharing platform YouTube.

Toms Kreicbergs and Deniss Šceulovs of Riga Technical University in Riga, Latvia, took YouTube comments as a source of qualitative data and found that consumers consider various factors beyond the immediate presentation. Such factors included the broader cultural context and comparisons with the approach of others in the advertising world. Surprisingly, the study highlights that the depiction of masculinity often takes precedence over the advertised product itself. This suggests that the marketing is often more important than the product itself in influencing consumer perception and purchasing intention.

At a time when societal norms surrounding masculinity are evolving, it is interesting to note that traditional depictions persist alongside emerging ideals that otherwise challenge gender stereotypes. With increasing awareness and acceptance of diverse gender identities, consumers are scrutinizing advertisements for their portrayal of masculinity, seeking authenticity and inclusivity and by turn increasingly making their buying decisions in this context.

The research suggests that humour can effectively convey traditional masculinity without eliciting negative reactions. However, there is a need to embrace progressive and diverse representations as these are increasingly important to society and so to advertisers hoping to sit easily within the evolving cultural world. To be successful, advertisers need to write copy and produce advertisements that resonate with what we might refer to as the modern audience. Indeed, brands that successfully navigate this fragmented landscape might ultimately build stronger connections with consumers who value authenticity and representation and become loyal followers of said brands and perhaps even word-of-mouth advocates of those brands and what they perceive them to stand for.

In contrast to what one might expect, the research indicates that on the whole consumers react positively to the portrayal of masculinity in advertising. The finding suggests that such advertisements might serve as a cultural touchstone for those who see them. This finding challenges previous assumptions about consumer attitudes toward gender portrayals in marketing and underscores the evolving nature of societal norms. There is thus a need for a more comprehensive approach to understanding consumer attitudes by incorporating surveys, focus groups, and expert interviews alongside existing methods.

Kreicbergs, T. and Šceulovs, D. (2024) 'A qualitative study of consumer perceptions about masculinity in advertising: content, sentiment, and discourse analysis', Int. J. Learning and Change, Vol. 16, Nos. 2/3, pp.327–348.
DOI: 10.1504/IJLC.2024.137503

Research in the International Journal of Reasoning-based Intelligent Systems discusses a new approach to the identification of ingredients in photographs of food. The work will be useful in our moving forward on food safety endeavours. Sharanabasappa A. Madival and Shivkumar S. Jawaligi of Sharnbasva University in Kalburgi, Karanataka, India, used a two-stage process of feature extraction and classification to improve on previous approaches to ingredient identification in this context.

The team explain that their approach used Scale-Invariant Feature Transform (SIFT) and Convolutional Neural Network (CNN)-based deep features to extract both image and textual features. Once extracted, the features are fed into a hybrid classifier, which merges Neural Network (NN) and Long Short-Term Memory (LSTM) models. The team explains that precision of their model can be further refined through the application of the Chebyshev Map Evaluated Teamwork Optimization (CME-TWO) algorithm. All of this leads to an accurate identification of the ingredients.

Food management in a globalised world is critical to worldwide supply chains, to food security, traceability and detection of fake food and food fraud. We, as consumers and diners, need to know that the ingredients in the food we eat, especially in the context of diverse dietary preferences and health considerations, are valid.

The team found that their approach works more effectively than current ingredient identification systems. Specifically, they demonstrated that the HC + CME-TWO model performs the best by a large margin, which can thus be taken as indicating a significant advancement in this area. It is the use of a hybrid classifier and the fine-tuning of weightings using the CME-TWO algorithm that leads to the marked improvement in accuracy and reliability. Moreover, the team says that there is still room for improvement in terms of shortening processing times through optimization.

The work focuses on food safety but could be used to address the challenges facing regulators and others attempting to ensure food authenticity, especially among high-value foods.

Madival, S.A. and Jawaligi, S.S. (2024) 'Food ingredient recognition model via image and textual feature extraction and hybrid classification strategy', Int. J. Reasoning-based Intelligent Systems, Vol. 16, No. 1, pp.74–90.
DOI: 10.1504/IJRIS.2024.137455

A study in the International Journal of Computational Systems Engineering has introduced a new approach to identifying depression through the analysis of online comments, particularly on social media platforms, including Reddit, one of the earliest and still-popular microblogging systems. K.G. Saranya, C.H. Babitha Reddy, M. Bhavyasree, M. Rubika, and E. Varsha of PSG College of Technology in Coimbatore, India, have used machine learning techniques, specifically the BERT model, to pick out signs of depression in the language patterns used online discussions.

The BERT (Bidirectional Encoder Representations from Transformers) model is a type of natural language processing (NLP) model developed by researchers at Google in 2018. It belongs to the family of Transformer models, which have become increasingly popular in NLP tasks due to their effectiveness in capturing long-range dependencies in text.

In contemporary health discussions, mental wellbeing has come to the fore, especially since the peak of the COVID-19 pandemic. The current research could fill critical gaps in conventional mental health diagnostics. Where traditional approaches remain challenging, there is a need for more wide-ranging methods that might be used to identify issues as they arise without the need to head into the clinic for full-blown assessment prior to a healthcare intervention.

The BERT model has promise in accurately distinguishing between individuals exhibiting signs of depression and those who are not. The team explains that their approach integrates collaborative filtering techniques to recommend tailored therapies based on identified depression patterns It has an accuracy rate of 87 percent which obviously leaves room for improvement, which is where further investigation or help would come into its own.

The implications of this research are far-reaching. By harnessing the power of AI and computational methods, early diagnosis of mental health problems, specifically depression in this instance, could become more accessible and efficient. The ability to detect depression through online interactions could free up healthcare workers to work with more challenging cases, but more importantly for the individual, allow earlier diagnosis and intervention to support them when they face, previously unrecognised mental problems.

The next step will be to expand the dataset to other online communities with different userbases, ethos, and approach to allow accurate and applicable diagnoses to be made essentially independently of the platform being analysed. The team will continue to refine the algorithms used and thus to improve accuracy and develop approaches to offer personalized interventions and treatments tailored to the individual.

Saranya, K.G., Reddy, C.H.B., Bhavyasree, M., Rubika, M. and Varsha, E. (2024) 'Depression prediction and therapy recommendation using machine learning technique', Int. J. Computational Systems Engineering, Vol. 8, Nos. 1/2, pp.120–127.
DOI: 10.1504/IJCSYSE.2024.137475

Web applications increasingly underpin other technologies and systems not least cloud computing services and the Internet of Things networks, smart infrastructure, and much more. Safeguarding user privacy on various systems and networks that use web applications has emerged as a critical concern among computer security experts.

Among the many threats they have to address and defeat are so-called cache side-channel attacks within virtualization systems as these are gaining prominence and being exploited widely by malicious and criminal third parties. Commonly, such attacks will allow the third party to steal a cryptographic key from a user and thus gain access to any data protected by that key.

Writing in the International Journal of Security and Networks, Sangeetha Ganesan of the Department of Artificial Intelligence and Data Science at the R.M.K College of Engineering and Technology in Tamil Nadu, India, explains how the almost ubiquitous web development programming language JavaScript enables access to various APIs and sensors. It is the prevalence of this language, however, that leads to privacy concerns where vulnerabilities are found and exploited by malicious third-parties. For instance, cache side-channel attacks exploit shared cache memory to allow a third party to illicitly access private, personal or otherwise sensitive information held within the cache from various users on the system by exploiting vulnerabilities in Javascript.

Unlike more conventional threats, cache side-channel attacks work by detecting the subtle differences in access times between cached and uncached values to allow the third party to extract information. Some of the malware available to such third parties is very fast and effective and so countermeasures are urgently needed to protect vulnerable systems from abuse.

To address this growing problem, Ganesan has developed the Browser Watcher system. This security solution can defend against time-based cache side-channel attacks. It works by prioritising the security of the putative victim's secret keys. When it detects an ongoing attack, the system promptly flushes the Last Level Cache, which effectively thwarts any attempt to steal data from the cache. This proactive approach might lead to a temporary drop in computing performance, but that is a price worth paying for securing one's data when under attack.

Ganesan, S. (2024) 'Enabling secure modern web browsers against cache-based timing attacks', Int. J. Security and Networks, Vol. 19, No. 1, pp.43–54.
DOI: 10.1504/IJSN.2024.137330

A new method for classifying electronic music has been developed by researchers in China. The approach offers a novel solution in an age of exploding digital content to curating music libraries and streaming services. Writing in the International Journal of Arts and Technology, Hongyuan Wu and Lin Zhu of the College of Music at Chong'qing Normal University, explain how such services are currently overwhelmed in terms of valid classification methods.

Traditional approaches are simplistic, based on labelling, and not keeping up with modern use and tastes. The team points out that classifying electronic music by genre is particularly difficult as this broad genre has wide and diffuse boundaries between different styles that are often highly subjective and influenced by cultural nuances.

The team's new approach uses a complex decision tree framework to achieve high accuracy and speed up processing times, making a leap from 33-and-a-third to 45, you might say! The process starts with noise removal using principal component analysis and then segments the track into small chunks. The features from each chunk are then extracted using a method known as short-time Fourier transform. The team then fine-tunes their decision tree model to achieve the most precise classification possible.

Indeed, their tests have shown that their method can be very effective, with a classification accuracy up to 98.6 percent. The implications go far beyond academic interest, with potential applications across the music and other industries. Music streaming services and online libraries rely heavily on accurate genre classification and could take advantage of this new approach to allow them to organize their collections and market music more subtly to their users. Users might include everyday music fans or those involved in the media or elsewhere who need specific styles of music to accompany their creative outputs.

For instance, the classification approach should make it easier for everyday users to explore music, discover new sounds or retrieve golden oldies. In marketing and advertising and other areas, understanding music preferences based on genre classification is critical for targeted campaigns based on music taste.

Wu, H. and Zhu, L. (2024) 'Adaptive classification method of electronic music based on improved decision tree', Int. J. Arts and Technology, Vol. 15, No. 1, pp.1–12.
DOI: 10.1504/IJART.2024.137296

A study in the International Journal of Arts and Technology has looked at the relationship between traditional Javanese music and the introduction of technology and western instrumentation into this genre. The work undertaken by Aris Setiawan of the Faculty of Performing Arts at the Indonesia Institute of the Arts in Surakarta, Indonesia, focuses on the integration of advancements in music technology within the context of gamelan music. The research offers insights into the opportunities and challenges offered by this novel fusion in the context of tradition and preservation and innovation in Javanese musical heritage.

Setiawan explains that central to his study is the emergence of campursari, this is the emerging musical genre that blends traditional Javanese gamelan instruments with Western counterparts. The emergence of campursari has been embraced by many music fans and labelled garbage by those worried about a loss of cultural authenticity and the preservation of traditional music practices in Indonesia. Raging debates of a similar sort have been experienced in other parts of the world where modern instruments and playing have clashed with the classical. Purists commonly eschew the fusion, but others embrace it and find the styles and sounds that emerge to be engaging, challenging, and above all else, enjoyable.

Campursari's incorporation of Western instruments has raised questions about tonal clashes and the impact on the authenticity of gamelan music. However, beyond aesthetic considerations, Setiawan's work explores the broader implications of technology's role in cultural preservation. He has used a phenomenological approach to investigate the individual and group response to the integration of technology into gamelan music development. A particular focus was on the modern multi-pad percussion technology and how it sits with traditional gamelan instruments, such as the kendang.

Setiawan suggests that technology, particularly the multi-pad percussion device, can complement traditional instruments like the kendang, known for its complexity. The fusion might allow many more people to enjoy creating music without extensive training. Such a notion does indeed move away from the classical or traditional ethos, but it will not detract from the approach of those who wish to continue in the classical tradition. Just as Mozart and Motorhead can sit alongside each other on an esoteric playlist, so too might the multi-pad and the kendang sit together rhythmically in this new musical form.

However, despite the new aesthetic, there remain concerns among some critics and scholars that there could be an erosion of tradition and a loss of cultural practices associated with traditional music performance. A balanced approach to allow the integration of technology into traditional music education is needed. Ultimately, the goal will be to preserve the rich tradition of gamelan music while allowing musical innovators to bang their own drum and perhaps blow their own trumpet when they do so.

Setiawan, A. (2024) 'Gamelan, technology, and controversy', Int. J. Arts and Technology, Vol. 15, No. 1, pp.38–60.
DOI: 10.1504/IJART.2024.137304

In retail, fragrance cues are nothing to be sniffed at. Indeed, the scent of vanilla, baking bread, even fresh linen, can affect customer behaviour, according to a study in the International Journal of Indian Culture and Business Management.

In the competitive realm of retail, understanding consumer decision-making is very important. A study by Shuvam Chatterjee and Pawel Bryla of the University of Lodz in Poland has looked at so-called olfactory marketing – the strategic use of scents in the retail environments – to see how much influence they might have on the shopping experience and how much customers spend in those shops. The team focused on a Kolkata shopping mall for their case study.

In many ways, our sense of smell is often perceived as a lesser sense when compared with sight and hearing. However, our sense of smell is very deep-rooted in our evolution and connects to what we might think of as primitive responses and behaviour. Recent research suggests it significantly affects our emotions and memories, and, in the shopping context, putatively on purchase behaviour. Fragrance cues, such as the smell of fresh bread in a retail setting, can evoke a strong emotional response, influencing product recognition, recall, and purchase intent.

Fresh linen and cotton blossom scents are often used to evoke feelings of cleanliness, relaxation, and comfort, Citrus is considered invigorating and refreshing. Vanilla is warm and sweet and evokes feelings of nostalgia and relaxation. Lavender, eucalyptus, and chamomile are known for being reminiscent of calming and soothing feelings. Sandalwood, on the other hand, has a rich, woody aroma that is perceived as quite exotic and often used in luxury boutiques and high-end hotels. Oceanic scents are reminiscent of sea air and commonly used in spas and wellness centres.

The IJICBM work shows a direct correlation between the presence of fragrance cues in the shopping mall and customer behaviour. If fragrance is coupled with other environmental factors such as music, the layout of the shop, and the ambient temperature, there can be a strong effect on how long a customer browses in a given shop and ultimately how much money they spend. In addition, the team determined that while age influenced purchasing decisions in this context, gender did not seem to affect how much time or money was spent.

Shop managers and marketers could benefit from working on olfactory marketing. By enhancing the shopping experience in this way, the researchers say that it is possible to boost the emotional connection with the brands on sale and perhaps even improve long-term customer loyalty. Of course, fragrance selection should be done with care as there may well be odours that could negatively affect the perception and behaviour of some customers and counter the benefits achieved with other shoppers who have responded positively.

Chatterjee, S. and Bryla, P. (2024) 'Olfactory marketing as a technological innovation tool for the Indian retail industry – a study of Shoppers Stop retail store in Kolkata, India', Int. J. Indian Culture and Business Management, Vol. 31, No. 3, pp.261–273.
DOI: 10.1504/IJICBM.2024.137276

European industries could soon benefit from a novel approach that introduces hybrid-autonomous assembly and disassembly systems to tackle the many pressing environmental concerns and enhance production flexibility. That is the suggestion of research published in the International Journal of Mechatronics and Manufacturing Systems. The new approach looks to integrate autonomous robotics systems with manual assembly stations, which could lead to improved adaptability and efficiency in a wide range of manufacturing processes.

Uwe Frieß, Lena Oberfichtner, Arvid Hellmich, Rayk Fritzsche, and Steffen Ihlenfeldt of the Fraunhofer Institute for Machine Tools and Forming Technology IWU, Germany, point out that mounting environmental, social and political pressures are driving change across industry. The need to achieve carbon neutrality and have a less detrimental impact on the environment are both high on the agenda. There is also a pressing need to reduce the risks associated with reliance on single suppliers especially where resources that are not widely available or are difficult to obtain are required. Overall, the traditional landscape of industrial assembly is changing.

The concept of hybrid-autonomous systems enables batch-individual task allocation and dynamic planning. In other words, workers use their knowledge and skills in concert with computers and robotic systems to determine which tasks need to be undertaken at what stage of a process and whether by people or robots doing the jobs. If there is a sudden change in requirements, the system can adjust quickly to keep the processes running smoothly. This, the research suggests, could address many of the challenges posed by fluctuating demand and diverse product specifications.

It is the adaptability of these systems that is their defining feature. By seamlessly blending autonomous robots with conventional manual labour, different industries can gain flexibility and efficiency and not compromise on stringent production requirements.

Hybrid-autonomous assembly systems might also integrate high-performance camera systems, pattern recognition, and artificial intelligence enabling real-time monitoring and adjustment of assembly processes. This is a marked departure from conventional automation. The promise is not simply economic. By reducing reliance on single suppliers and optimizing resource utilization, hybrid-autonomous systems could improve sustainability in manufacturing.

Frieß, U., Oberfichtner, L., Hellmich, A., Fritzsche, R. and Ihlenfeldt, S. (2023) 'Autonomous assembly and disassembly by cognition using hybrid assembly cells', Int. J. Mechatronics and Manufacturing Systems, Vol. 16, No. 4, pp.381–398.
DOI: 10.1504/IJMMS.2023.137377

An analysis of the research literature published between 1974 and 2019 provides insight into how international corporate governance research evolved over the decades before the covid pandemic.

Jaime Guerrero-Villegas and Mar Bornay-Barrachina of the Department of Management at the University of Cádiz, and Leticia Pérez-Calero and Mónica Santana of the Department of Management and Marketing at the Pablo de Olavide University in Seville, Spain, used sophisticated bibliometric techniques to outline changes in the themes and theories within the field.

The team writes in the European Journal of International Management that the earlier research papers tended to focus on Agency Theory and homed in on the impact of risk-taking on the decision-making processes. In more recent work, there was a transition towards the exploration of the human and social aspects of governance. In those papers, theories such as upper echelons and dependence theory gained more prominence underscoring the importance of board composition and executive dynamics in how corporate strategy is shaped. This was particularly relevant in the context of international commerce.

The team has identified four distinct periods, with the more recent period, 2016 to 2019, having the greatest diversity of research themes. Indeed, the findings suggest that there has been a growing interest in understanding how boards of directors influence the internationalization efforts of companies. In addition, topics such as corporate social responsibility (CSR) and the challenges faced by family-owned businesses in international markets came to the fore in the later research analysed.

The analysis also shows that while traditional views regarding board independence have declined over the years there has been an increase in research into board diversity, in particular regarding gender. Those studies suggest that company boards with diverse membership see improved strategic decision-making, approaches to market entry, and the fostering of innovation.

The EJIM review and analysis of almost half a century of research into International Corporate Governance reveals how it has evolved in that time. The findings have implications for future research as well as international management practice.

Guerrero-Villegas, J., Pérez-Calero, L., Santana, M. and Bornay-Barrachina, M. (2024) 'International corporate governance: a science mapping approach', European J. International Management, Vol. 22, No. 4, pp.616–646.
DOI: 10.1504/EJIM.2024.137340

In the search for safer working conditions in the mining sector, a recent review published in the International Journal of Mining and Mineral Engineering has highlighted what might become a rich seam for future safety endeavours. The study, which looked at 54 research articles, not only categorizes existing safety measures but also identifies gaps in the existing literature, which could lead to more targeted investigations.

Erik Sundström and Magnus Nygren of the Department of Social Sciences, Technology and Arts at Luleå University of Technology in Luleå, Sweden, have examined closely the various safety initiatives within the global mining industry, uncovering ten important themes. These themes encapsulate the breadth of safety measures covered in the research literature. Foremost among these themes is the cultivation of a safety culture and the promotion of safe behaviour among workers. This underpins the significance of fostering a more proactive approach to safety within mining operations worldwide.

However, beyond simply categorizing existing strategies, the work also has the potential to shape how future research is planned and carried out. By homing in on overlooked subjects, such as the influence of societal norms on safety strategies and changes in safety culture, the team offers a guide for more nuanced investigations in the field.

Given that mining operations now increasingly use digitalization and automation, the study emphasizes that there is a need to focus on where technological advancements and worker safety meet. Understanding how innovations affect safety measures is critical to ensuring the well-being of workers in the face of a rapidly changing industrial landscape. Additionally, the research suggests that there is a need for a deeper examination of how safety practices are shared efficiently across and among organizations.

The review offers a snapshot of current safety research in the mining sector but also lays the groundwork for advancing the field towards greater protection and sustainability. By addressing overlooked topics and embracing interdisciplinary perspectives, future studies could not only improve safety but also lead to a more sustainable mining industry.

Sundström, E. and Nygren, M. (2023) 'Understanding the mining safety research field: exploring safety measures and programs in international research', Int. J. Mining and Mineral Engineering, Vol. 14, No. 3, pp.315–340.
DOI: 10.1504/IJMME.2023.137309

Research in the International Journal of Business Innovation and Research has looked at the role of social learning with respect to the professional performance of medical representatives in Indonesia during the COVID-19 pandemic.

Daniel Kisahwan of PT. Eisai Indonesia in Jakarta, Alex Winarno of Telkom University in Bandung, and Deni Hermana of the University of Indonesia in Jawa Barat, Indonesia drew on implicit and social learning theories to explore how social environments affected engagement and success among medical representatives.

Medical representatives, colloquially known as drug reps, are pharmaceutical sales professionals who promote medical products and pharmaceuticals to healthcare workers. Their results shed new light on the factors influencing that drug rep performance during the pandemic and might help us understand what happens in a future pandemic and how the pharmaceutical industry might better respond during such a crisis.

The team surveyed more than 200 drug reps in the major cities of Indonesia cities. They found a significant correlation between the social context and the performance of these professionals. Social context in this sense refers to the relationships, dynamics, and influences within the professional networks and social circles of the drug reps.

The findings suggest that social learning played a crucial role in shaping how they operated and their successes and failures during this period. Role models within a drug rep's social circles might guide how they operate in their job and whether or not they endeavoured to work to the best of their abilities during challenging times, such as the pandemic period. The study also highlights differences in social learning processes among experienced and inexperienced medical representatives, underlining the importance of individual attributes in determining how well they perform in their jobs.

The paper highlights a distinguishing feature of this research in that it involved the development of a framework through which the team could elucidate how work engagement and performance were influenced by social learning within pharmaceutical companies. This framework, based on the experiences and perspectives of those working in these environments, offers insights for human resource practices such as social learning, education, and training. The same framework might also find application beyond the pharmaceutical sector.

Kisahwan, D., Winarno, A. and Hermana, D. (2024) 'Implicit and social learning theory: an explanation of why experienced medical representatives have higher engagement and performance', Int. J. Business Innovation and Research, Vol. 33, No. 3, pp.418–432.
DOI: 10.1504/IJBIR.2024.137272

A study in the International Journal of Business Excellence examining the relationship between gender diversity on corporate boards and corporate social responsibility spending has found a positive correlation. The research focused on 738 firms across India listed on the national stock exchange over a seven-year period.

Corporate social responsibility refers to initiatives at a company that essentially take responsibility for the company's impact on the environment and social well-being. These initiatives might encompass a wide range of actions, including reducing carbon emissions, improving labour practices, supporting community development, promoting diversity and inclusion, and engaging in philanthropy. The aim being to ensure that businesses operate in an ethical and sustainable manner and rather than considering success by looking at their financial bottom line, they can take into account their wider impact on society and the environment.

Sudheer Reddy, Aditya Jadhav, and Krishna Prasad of the T A Pai Management Institute in Manipal, Karnataka, India, found that the presence of women directors on corporate boards was correlated with greater spending on corporate social responsibility. This phenomenon was consistent even within loss-making firms, indicating that women board members may exert influence towards larger contributions regardless of financial performance.

Additionally, the research identifies a negative impact of board independence on such spending, suggesting that a higher degree of independence may hinder social responsibility initiatives. Conversely, a larger board size correlates with greater spending, hinting at the potential positive influence of diverse perspectives on corporate social initiatives.

The team's findings highlight the role of gender diversity on corporate boards in shaping corporate social responsibility agendas, particularly in emerging markets such as that of India. Understanding the dynamics of board composition becomes crucial in the global business environment, which is increasingly prioritizing sustainability and so-called stakeholder engagement. This can fulfil ethical obligations but also boost brand reputation, mitigate risks, and improve long-term relationships with stakeholders, including the people who work with the companies up and down the supply chain, their customers, and, of course, the wider public.

Reddy, S., Jadhav, A. and Prasad, K. (2024) 'Board gender diversity and corporate social responsibility: evidence from India', Int. J. Business Excellence, Vol. 32, No. 3, pp.380-393.
DOI: 10.1504/IJBEX.2024.137261

Researchers in China have developed a novel approach to higher education student management that integrates machine vision and intelligent detection technologies. They report details in the International Journal of Information and Communication Technology. The system could address the problems commonly encountered in traditional approaches to management that often cannot cope effectively in meeting the diverse needs of students. Moreover, the system should strengthen safety and improve how a higher-education establishment responds to emergencies.

Yawei Han of Sichuan University in Chengdu Sichuan, China, explains how the new system uses machine vision techniques, including frustum plane calculations and spherical bounding boxes. The system uses the Bresenham algorithm, a computational technique primarily used for drawing lines on a grid-based display, such as a computer screen, to efficiently determine which grid points to plot to form a straight line between two given points. Its use allows for precise conversion of an image into a format that the computer can use for analysis. One important aspect of the new approach is its method for assessing and improving nodes (which are points or elements in a system) using factors like how far away they are and how complex they are. This adaptive approach makes the system more reliable than it would otherwise be.

Overall, the ability of the system to accurately convert vector-based representations of lines into pixel-based raster images for image processing will allow the system to simplify image handling and improve visualization for the identification of students and behaviour.

The new system emphasises inclusivity and responsive communication channels in a way that focuses on the needs of students in a way that conventional approaches have not. Using machine vision and intelligent monitoring technologies can enhance managerial efficiency and bring the focus back to the students. Furthermore, the system highlights the value of utilizing student behaviour data to guide management strategies. Employing various algorithms to model student behaviour, enables targeted interventions and personalized support. There remains the potential to improve sensitivity and database integration. Enhancements in these areas could further strengthen the system's capabilities and performance.

Han, Y. (2024) 'College student management based on machine vision and intelligent monitoring system', Int. J. Information and Communication Technology, Vol. 24, No. 2, pp.228–244.
DOI: 10.1504/IJICT.2024.137221

Research in the International Journal of Global Energy Issues sheds a green light on an innovative approach to addressing the design challenges faced by care facilities for older people amidst societal ageing and growing environmental concerns. The work, from Yi Wu from the School of Urban Construction Engineering at Chongqing Technology and Business Institute in Chongqing, China, focuses on incorporating green technologies into the interior environments of senior care buildings to improve both the well-being of the residents and boost energy efficiency.

Wu has undertaken detailed demographic projections and noise level measurements across different locations and her analysis of the data demonstrates how significant enhancement in overall energy efficiency might be made.

As the global population "ages", there are increasing challenges that face society worldwide. Wu points out that Western developed nations have long grappled with their ageing populations, countries such as China are now facing similar issues due to rapid demographic shifts driven by economic and societal change.

Elderly care buildings, including senior apartments and nursing homes, are essential in meeting the diverse needs of an ageing population, encompassing psychological, physiological, and behavioural aspects. However, amid concerns over resource depletion and environmental degradation, improving the energy efficiency of such homes is becoming increasingly important. Green technologies offer a practical approach to addressing energy consumption and pollution concerns simultaneously. The development of elderly care infrastructure requires not only innovative architectural designs but also supportive national policies and public engagement to improve such housing. Wu suggests that policy measures should include setting realistic development targets, refining regulations, conducting quality assessments, and establishing industry frameworks is critical.

There is an opportunity where the integration of environmental sustainability and elderly care infrastructure is met. By embracing green technologies and implementing supportive policies, societies can create more resilient and inclusive environments for their ageing populations and hopefully mitigate the environmental impact of the changing demographic. Collaborative efforts across different sectors are now needed to address the challenges sustainably.

Wu, Y. (2024) 'Indoor environment design of old-age green buildings based on environmental energy efficiency', Int. J. Global Energy Issues, Vol. 46, Nos. 3/4, pp.327–344.
DOI: 10.1504/IJGEI.2024.137087

Research in the International Journal of Electronic Marketing and Retailing introduces a new model aimed at assessing the credibility and relevance of online healthcare information. With the proliferation of online health advice, the challenge of distinguishing trustworthy sources from false information has become increasingly important for patients and their carers.

S. Sri Hari of the Illinois Institute of Technology in Chicago, USA, S. Porkodi and R. Saranya of the University of Technology and Applied Sciences, and N. Vijayakumar of the Technical Administrative Training Institute in Muscat, Oman have developed a model that uses sentiment analysis on reader comments to gauge the reliability of digital healthcare content. Using content relevance analysis, word scoring using a lexicon analyzer, and classification via a maximum entropy model, the model generates what the team refers to as a veracity score, which can help users make a better-informed decision about the information they find online.

The researchers tested their model using healthcare content and found it to work effectively in evaluating the veracity of information. The new model could have significant implications for content marketing efforts within the healthcare sector, providing users with tailored recommendations while enhancing the credibility of digital healthcare information. The model's ability to identify and highlight trustworthy content benefits patients and carers as consumers.

The model's impact could affect all age groups, youngsters, the middle-aged, and an ageing population. The identification of reliable healthcare information among the vast number of online medical and health resources is critical. The model could allow better-informed decision-making and mitigate the problems that might arise through the spread of misinformation.

Future work will expand the model's capabilities by developing tools to analyse multimedia content and incorporate additional mechanisms to identify misinformation and disinformation.

Hari, S.S., Porkodi, S., Saranya, R. and Vijayakumar, N. (2024) 'Intelligent model to improve the efficacy of healthcare content marketing by auto-tagging and exploring the veracity of content using opinion mining', Int. J. Electronic Marketing and Retailing, Vol. 15, No. 2, pp.240–260.
DOI: 10.1504/IJEMR.2024.136978

There are an estimated 280 million people in the world with debilitating levels of visual impairment. A new tool to empower them with a richer understanding of their surroundings is discussed in the International Journal of Engineering Systems Modelling and Simulation.

S. Pavithra, T. Helan Vidhya, D. Gururaj, and P. Shanmuga Priya of the Department of Electronics and Communication Engineering at Rajalakshmi Engineering College and V. Prabhakaran of the Department of Biomedical Engineering at Aarupadai Veedu Institute of Technology in Chennai, Tamil Nadu, India, have demonstrated that integrating digital image processing and voice technology allows them to a certain degree bridge the gap between visual impairment and a person's surroundings.

The core of their approach lies in a system that captures real-time images and translates them into audio descriptions. It utilises sophisticated image recognition algorithms powered by machine learning and allows the computer to identify objects within a scene with remarkable accuracy, the team reports. The researchers explain that the process is helped by platforms such as TensorFlow and ensures that users receive detailed descriptions tailored to their immediate surroundings.

The new technology goes way beyond simple object recognition. It functions as a personal assistant, providing users with timely updates on relevant information and potential hazards that they may encounter in navigating their environment whether at home or elsewhere. The team also points out that a distress call mechanism can be used in the system to add an extra layer of safety, being activated in an emergency situation in order to summon help.

The researchers have tested their system rigorously, demonstrating high accuracy rates in identifying both primary (90 percent accuracy) and secondary objects (80 percent). Moreover, they have demonstrated that it can be adapted to different environments, whether indoor or outdoor. It distinguishes itself in this way from current solutions that may be limited in scope or responsiveness.

The team hopes that their new technology will improve the quality of life for visually impaired people by addressing the shortcomings of current assistive technologies. By enabling real-time interaction with the world, this innovation will foster independence and inclusion, the researchers suggest.

Pavithra, S., Prabhakaran, V., Vidhya, T.H., Gururaj, D. and Priya, P.S. (2024) 'Machine learning and image processing technique to describe outdoor scenes for visually impaired people', Int. J. Engineering Systems Modelling and Simulation, Vol. 15, No. 2, pp.63–67.
DOI: 10.1504/IJESMS.2024.136970

In collaborative work between police organizations and experts in ergonomics and biomechanics, a new equipment vest has been developed to address the issue of musculoskeletal disorders, particularly lower back pain, among police officers. The work undertaken in Sweden is described in detail in the International Journal of Human Factors and Ergonomics. The new vest design aims to redistribute the weight of essential equipment, such as communication equipment weapons, and handcuffs, from the traditional duty belt to a more ergonomically designed vest.

The standard duty belt worn by officers has been identified as a contributor to lower back pain due to its unfavourable load on the lumbar spine, particularly during sitting or driving. This seems to be a universal issue and one that research might address. Additionally, the ballistic vest worn underneath the uniform presents challenges in regulating body temperature.

Kristina Eliasson and Teresia Nyman of the Department of Medical Sciences, Occupational and Environmental Medicine at Uppsala University, Roy Tranberg of the Department of Orthopedics in the Institute of Clinical Sciences, part of the Sahlgrenska Academy at the University of Gothenburg, and Louise Bæk Larsen of the Department of Rehabilitation in School of Health and Welfare at Jönköping University undertook thorough analysis and testing during the development process. They carried out interviews, held focus groups, and took pressure measurements with 95 active-duty police officers. Their findings allowed them to make iterative design changes with ongoing user feedback. This resulted in a vest better tailored to the needs of Swedish police officers.

The researchers suggest that the redistribution of equipment on the newly developed vest will reduce musculoskeletal discomfort and make important improvements to the physical component of being a police officer. Ultimately, the new vest design aims to enhance the well-being and comfort of police officers on active duty, potentially influencing occupational equipment standards globally.

This project highlights the importance of a dedicated project management team to coordinate efforts so that any changes are inclusive and take into account the views of those who are to use the new equipment as well as their physical measurements. Such a user-centric development process could also be used as a model for future occupational equipment projects, not only in law enforcement but across various types of workplace from healthcare to industry and other occupations in between.

Eliasson, K., Nyman, T., Tranberg, R. and Larsen, L.B. (2024) 'A user-centred development process for an equipment vest for the Swedish police force', Int. J. Human Factors and Ergonomics, Vol. 11, No. 1, pp.56–77.
DOI: 10.1504/IJHFE.2024.137126

A study in the International Journal of Sport Management and Marketing has revealed the impact of virtual brand communities associated with the success of a popular fitness product brand.

Melissa Davies of Ohio University in Athens, Ohio, Eric Hungenberg of the University of Tennessee – Chattanooga in Chattanooga, Tennessee, Thomas J. Aicher of the University of Colorado in Colorado Springs, Colorado, Brianna L. Newland of New York University in New York, New York, USA, have investigated the user community surrounding well-known fitness product brand Peloton Interactive Inc.

The company markets connected fitness products and services including stationary exercise bikes, indoor rowing machines, and treadmills. They also sell related accessories, such as heart rate monitors and workout apparel. Additionally, the company offers subscription-based services that provide users with access to live and on-demand fitness classes led by instructors, accessible through its proprietary software platform. Classes include cycling, running, strength training, yoga, and meditation, all of which can be undertaken interactively from the comfort of one's home or, indeed any suitable place.

The researchers examined the influence of virtual brand communities on branding outcomes. They surveyed 663 Peloton users and analysed their responses using structural equation modelling to discern any relationships between brand community and brand outcomes.

Their results indicate that Peloton users who felt a strong sense of community were more active on brand-related social media and used Peloton products more often. This sense of community correlated with favourable brand outcomes, including brand love, equity, advocacy, and word-of-mouth communication. All of which highlights the importance of a brand developing an emotional connection with consumers and users.

The study also explored the interplay between engagement in virtual brand communities, product usage, and brand community perception. Individuals who perceived they had interests in common with other users and enjoyed using the social spaces facilitated by the brand were more likely to have a strong sense of community. This, again, would lead to increased product engagement and brand affection. This has practical implications for brands in the connected fitness industry as it emphasizes the need to prioritize the creation and nurturing of virtual brand communities, something in which the company in question has apparently been rather successful.

Davies, M., Hungenberg, E., Aicher, T.J. and Newland, B.L. (2024) 'Work[out] from home: examining brand community among connected fitness brand users', Int. J. Sport Management and Marketing, Vol. 24, No. 2, pp.113–136.
DOI: 10.1504/IJSMM.2023.10059412

Artificial Intelligence (AI) has very quickly transitioned from science fiction to practical applications, particularly in industrial sectors like manufacturing, logistics, and retail. A study in the International Journal of Technology Transfer and Commercialisation looks at the AI landscape and sheds light on its evolution, implications, and integration challenges across industries.

In his study, Ibrahim Saleem Alotaibi of the College of Administrative and Financial Sciences at the Saudi Electronic University in Riyadh, Kingdom of Saudi Arabia, highlights a significant shift driven by AI technologies such as machine learning and deep learning. Industries are increasingly adopting AI-driven automation to meet market demands and improve operational efficiency. However, he also demonstrates that this transition from conventional approaches presents various challenges at different levels.

One key challenge is the need for substantial investment and skilled technicians to implement AI-driven processes effectively. Moreover, there are concerns about software failures, cybersecurity risks, and data privacy that add enormously to the complexity of the integration process. In addition, to such technical issues, as the legal and regulatory frameworks mature, there will be issues of how companies must comply with laws around AI and its implementation. This too will require much consideration by the companies, particularly in regions where laws associated with AI use are present in parallel with stringent data protection laws.

In his study, Alotaibi underscores the leading role played by China in the adoption of AI tools, particularly in manufacturing and logistics. Despite its rapid embracing of AI technologies, there remain many questions about sustainability given the computing resources that are needed to train and run the most powerful AI tools. Of course, this issue will ultimately present itself to all regions utilising high-level AI across all industries.

As businesses navigate the complexities of AI integration, responsible deployment becomes crucial. Those involved in developing, implementing, and using AI tools must prioritize risk assessment, ethical frameworks, and collaborative approaches to address the technical, societal, and regulatory challenges that the increasingly widespread adoption of AI will bring.

Even precluding the hyperbole, AI offers many incredible opportunities for innovation and efficiency across industries. Its wider integration nevertheless requires careful consideration of the implications and the challenges presented. Alotaibi's research emphasizes the importance of taking a considered and inclusive approach to realizing the full potential of AI to mitigate the risks associated with its use.

Alotaibi, I.S. (2023) 'Impact of artificial intelligence in manufacturing and logistics: an exploratory study', Int. J. Technology Transfer and Commercialisation, Vol. 20, No. 4, pp.355–386.
DOI: 10.1504/IJTTC.2023.136890

A study in the International Journal of Indian Culture and Business Management has provided new insights into the influence of cultural values and ethnic identity on consumer attitudes towards global brands in India. Harsandaldeep Kaur and Pranay Moktan of the University School of Financial Studies at Guru Nanak Dev University in Amritsar, Punjab, hoped to fill the gaps in our understanding of these factors by developing a comprehensive framework for investigation.

The team surveyed 456 respondents and used structural equation modelling to analyze the relationships between ethnic identity, masculinity, collectivism, and consumer attitudes towards global brands. The results showed significant associations among the various factors. For instance, ethnic identity was found to influence both masculinity and collectivism, which in turn affected consumer attitudes towards global brands. Additionally, collectivism and masculinity were found to mediate to some extent the relationship between ethnic identity and consumer attitudes.

In the context of this work, "masculinity" refers to a cultural dimension that influences consumer attitudes towards global brands and relates to traditional gender roles, behaviours, and characteristics associated with masculinity. The term "collectivism" refers to a cultural orientation or value system that emphasizes the importance of group harmony, interdependence, and cooperation within a society.

The implications of the research extend particularly to global brand managers operating in diverse markets. The findings thus underscore the importance of considering cultural values and ethnic identity in brand strategies, as they significantly shape consumer perceptions. Brands that align with cultural values and traditions are likely to resonate more often with consumers. This suggests that companies need to take a much more nuanced and tailored approach to their marketing and commercial strategies.

It is worth noting, that the study highlights the aspirational nature of global brands in developing countries, where consumers often aspire to lifestyles associated with other regions considered to be more advanced economically. This aspirational mindset underscores the universal appeal of global brands, particularly in regions characterized by cultural diversity, the research suggests.

The researchers suggest that by recognizing and incorporating the various highlighted factors into their strategies, managers and marketers can enhance brand appeal and connect more effectively with their target consumers in diverse markets, like that found in India.

Kaur, H. and Moktan, P. (2024) 'The curious case of global branding: investigating the link between ethnic identity and consumer attitudes towards global brands', Int. J. Indian Culture and Business Management, Vol. 31, No. 2, pp.123–144.
DOI: 10.1504/IJICBM.2024.136803

Research in the International Journal of Ad Hoc and Ubiquitous Computing introduces a new approach to tackling the challenges posed by deepfake technology, which generates manipulated media content that closely resembles authentic footage. The novel method combines the miniXception and long short-term memory (LSTM) models to analyse suspicious content more effectively and identify deepfake images with greater than 99 percent accuracy.

While fake and fraudulent videos and images have been with us for many years, the term "deepfake" more commonly refers to manipulated videos or images that have been created using artificial intelligence and deep learning techniques. These technologies allow users to superimpose or replace, the original contents of an image or video with other content. Commonly a person's face and voice might be faked in a video. Such deepfakes might be used for entertainment purposes as is the case with many apps that allow everyday users to create "amusing" content featuring their friends and family or indeed celebrities.

However, the more insidious use of deepfakes has gained popular attention because of the potential to deceive viewers, often leading to concerns about misinformation, privacy infringement, and the manipulation of public and political discourse. Such videos represent a significant threat to democracy where voters and consumers alike might be exposed to seemingly legitimate political content that is faked propaganda with malicious intent. Identifying deepfake content is more important than ever at a time of heightened political tensions and fragility. There is an urgent need for powerful detection methods and awareness about their existence and potential consequences.

Until now, deepfake detection has been hindered by low accuracy rates and difficulties in generalizing across different datasets. Yong Liu, Xu Zhao, and Ruosi Cheng of the PLA Strategic Support Force Information Engineering University in Henan, Tianning Sun of the Zhejiang Lab, Zonghui Wang of Zhejiang University, China, and Baolan Shi of the University of Colorado Boulder in Boulder, Colorado, USA, have proposed a model that improves on the accuracy of earlier approaches.

The team conducted cross-dataset training and testing, employing transfer learning methods to improve the model's ability to generalize across various datasets. They used focal loss during training to balance samples and enhance generalization still further. Their tests demonstrate the promise of this approach, showing a detection accuracy of 99.05% on the FaceSwap dataset. This is better than previous methods, such as CNN-GRU, and requires fewer parameters to achieve this level of success.

Liu, Y., Sun, T., Wang, Z., Zhao, X., Cheng, R. and Shi, B. (2024) 'Detection of deepfake technology in images and videos', Int. J. Ad Hoc and Ubiquitous Computing, Vol. 45, No. 2, pp.135–148.
DOI: 10.1504/IJAHUC.2024.136851

A study in the International Journal of Services and Operations Management introduces a practical approach to quality control that could help reshape manufacturing and reduce the number of end-of-line rejects in production as well as the need to rework components and products. Such additional, and often costly, processes are undertaken in what can be referred to as the hidden factory.

P. Raghuram, Ashwin Srikanth, and P. Rithan Mandesh of the Department of Mechanical Engineering at Amrita School of Engineering in Coimbatore, India, have developed a Quality Filter Mapping (QFM), an approach to manufacturing methodology that addresses one of the big problems facing companies with high production volumes, stringent quality standards all hoping to improve their profit margins and their sustainability credentials.

Conventionally, quality control is a reactive process in manufacturing. Components are made, assemblies undertaken and at any stage where tolerances are not met, a component or assembly will be rejected. At this point, depending on the nature of the product, the reject may be fed to a parallel process to be reworked in some way so that it reaches the necessary standard. This approach is costly and wasteful.

QFM represents a shift towards a proactive quality control strategy, the research suggests. The team uses Pareto analysis in their new approach. The Pareto Principle, also known as the 80/20 rule, is named for Italian economist Vilfredo Pareto, He observed that approximately 80% of effects come from 20% of causes. In the context of quality control, Pareto analysis involves identifying the most significant factors contributing to a problem or outcome. By focusing efforts on addressing these critical factors, organizations can achieve substantial improvements in efficiency and effectiveness.

Through this analysis, major defects can be identified and their root causes traced using cause-and-effect diagrams. The underlying causes can then be mapped along the material flow in the assembly plant. This, the team suggests, seamlessly integrates quality control into the production process itself.

QFM offers significant cost savings by preventing the flow of defective components at an early stage in the manufacturing process rather than identifying them at the end of the line. This reduces the need for extensive end-of-line inspections and reworking in the hidden factory and so can reduce waste and improve efficiency throughout the whole manufacturing process. The team has taken an engine assembly line as a case study to demonstrate the effectiveness of the QFM approach.

QFM also promotes a culture of continual improvement and root cause analysis within organizations, contributing to heightened standards and customer satisfaction. The approach might also help companies address the broader challenges of evolving customer demand and fluctuating order volumes.

Raghuram, P., Srikanth, A. and Mandesh, P.R. (2024) 'Eliminating end-of-line rejections – a quality filter mapping approach', Int. J. Services and Operations Management, Vol. 47, No. 1, pp.123–140.
DOI: 10.1504/IJSOM.2024.136797

Understanding the dynamics of online brand advocacy is increasingly important in today's digital landscape, particularly for businesses targeting Generation Z (Gen Z) consumers. A study in the International Journal of Internet Marketing and Advertising surveyed 221 students intending to explore the factors influencing online brand advocacy behaviour and its impact on purchase intentions and also examining the involvement of social media.

Generation Z usually refers to the demographic cohort succeeding the so-called Millennials and preceding Generation Alpha. While there is no specific definition of Gen Z, it usually refers to individuals born between the mid-to-late 1990s and the early 2010s, often stated as 1997 to 2012.

It is worth noting that the Millennials (born from 1981 to 1996) are often thought of as the original "digital natives" having been born after the invention of the World Wide Web and the emergence of ubiquitous computer technology. However, all subsequent generations have also grown up in an era characterized by rapid technological advancement, ubiquitous internet access, and widespread social media usage. Gen Z exhibits distinctive characteristics and behaviour shaped by what we might refer to as their digital upbringing. This technological environment influences their worldview, their approach to communication, and their preferences as consumers.

The work of Vivek Mishra of IIIT Bhubaneswar and Biswajit Das of the KIIT School of Management, also in Bhubaneswar, India offers several insights. First, it shows that brand-related factors such as brand social benefits, distinctiveness, prestige, and warmth significantly influence behaviour among Gen Z individuals. Additionally, online brand advocacy correlates positively with purchase intent, indicating its role in driving actual purchasing decisions, with social media involvement having a moderating effect.

The findings highlight the evolving nature of consumer behaviour showing how there has been a shift from traditional loyalty to advocacy. Moreover, they reveal how the latter represents an invaluable tool for companies to build trust and loyalty in a competitive market environment. Understanding and utilizing advocacy could improve the chances of long-term success for a brand.

Mishra, V. and Das, B. (2024) 'What drives Generation Z to advocate for a brand online?', Int. J. Internet Marketing and Advertising, Vol. 20, No. 1, pp.1–25.
DOI: 10.1504/IJIMA.2024.136800

A new approach to the evaluation of teaching effectiveness in universities has been introduced in the International Journal of Networking and Virtual Organisations. In response to the various reforms and economic advancements in China, higher education has experienced some profound transformations in recent years. It is growing rapidly and university enrolment, once accessible only to the elite is transitioning towards mass education. Thus evaluation tools are increasingly important so that society can rely on good, solid education.

The new technique uses a social network to obtain a more comprehensive assessment than was previously possible. According to the researchers, Xiyang Li of Hunan City University Hunan and Quanzhong Yang of Luoyang Polytechnic, China, their method could provide universities with a systematic tool for evaluating instructional practices and so potentially improving educational quality.

The team first looked at the ways in which teaching effectiveness is currently judged with the aim of understanding what factors are used in evaluation. From this starting point, the researchers have established a set of principles to guide the creation of a new evaluation system.

To help in this process, they have used various computational techniques, including calculating something called "entropy matching degree." This measurement helps gauge how well different factors align or correspond. Additionally, they utilize the Support Vector Machine (SVM) algorithm, a computer program designed to develop a solid evaluation framework. This helps in organizing and analyzing data to accurately assess the quality of teaching. Then, by building a social network, they can look at how the different factors are perceived by different groups of people within education.

This network-driven approach generates evaluation results with a confidence level of 99%, says the team, and with minimal entropy matching errors, which suggests it could be a practical approach to educational evaluation.

Li, X. and Yang, Q. (2024) 'Evaluation of teaching effectiveness in higher education based on social networks', Int. J. Networking and Virtual Organisations, Vol. 30, No. 1, pp.1–14.
DOI: 10.1504/IJNVO.2024.136771

An analysis in the Journal for International Business and Entrepreneurship Development has looked at the various approaches to cybersecurity and data protection taken by key global players, namely the European Union (EU), the United States of America (USA), and China. As nations address historical data concerns and evolving cyber threats, the practical implications for businesses and individuals are significant. In this context, they consider the impact of the emergence of large language models (LLMs), such as ChatGPT, often, and perhaps erroneously, referred to as artificial intelligence (AI) tools.

Cybersecurity and data privacy have become central concerns, affecting business operations and user safety worldwide. The EU's General Data Protection Regulation (GDPR) stands out as one of the more well-known and effective cyber strategies that have nudged businesses to strengthen cybersecurity measures and improve data management practices for compliance and consumer trust.

In contrast, the USA currently lacks a unified legislative framework for cybersecurity, relying instead on various regulations many of which are rather outdated in the digital landscape as it stands. Nevertheless, the USA does maintain high levels of preparedness against cyberattacks through legal, technical, and organizational measures.

China, on the other hand, has taken a stringent and strident position on cybersecurity and data protection, balancing the safeguarding of its citizens with strict regulations. These, of course, have raised concerns in many quarters about individual rights.

In their paper, Teddy Lynn Ladd of Wipro Enterprise Futuring in Plano, Texas, Shawn M. Carraher of KFUPM in Dhahran, KSA, Sherry E. Sullivan of BGSU, Bowling Green, Ohio, and Shawn M. Carraher Jr. of TAMU in Commerce, Texas, USA, suggest that LLMs have an important role to play.

These tools offer a new way to understand and navigate the complex current regulations and future legislation, which could help organizations in their compliance efforts as well as improve cybersecurity for those organizations, governments, and individuals. LLMs might be prompted to help in the interpretation of regulations and provide assistance in developing proactive rather than reactive strategies to address the challenges involved in compliance and cybersecurity. They might even be useful in allowing organisations to surmount the financial burdens and resource constraints, particularly for multinational corporations, that are necessitated by the need for cybersecurity and regulatory compliance.

Ladd, T.L., Carraher, S.M., Sullivan, S.E. and Carraher Jr., S.M. (2023) 'Cybersecurity and data protection in the European Union, the USA, and China: does ChatGPT really make a difference?', J. International Business and Entrepreneurship Development, Vol. 15, No. 3, pp.355–390.
DOI: 10.1504/JIBED.2023.136751

A recent study in the International Journal of Information and Computer Security has introduced an innovative approach to addressing the persistent challenge of zero-day phishing attacks in cybersecurity. Zero-day threats represent a significant challenge for computer security systems. Such threats can be used to exploit previously unidentified vulnerabilities in software, networks, and computer systems before those security systems can be patched or updated to address the new exploit. Although they have only a brief window to circumvent conventional malware detection, antivirus software, and firewalls this can be sufficient to allow a data breach or other malicious process to be undertaken.

Thomas Nagunwa of the Department of Computer Science at the Institute of Finance Management in Dar Es Salaam, Tanzania, has proposed a machine learning (ML) model that is designed to detect these emerging and ever-evolving threats in real time. It could offer a much-needed and pragmatic solution to enhancing computer security in a range of environments.

One of the biggest threats to computer security often exploits social engineering wherein the user's gullibility or lack of understanding is used to breach the first line of defence. In the case of a "phishing" attack, for instance, an unwary user is persuaded or coerced into unwittingly clicking a malicious link in an email or on a website. Often such phishing attacks will use zero-day tactics, approaches that have not been widely recognised at the point or time of implementation. Commonly, such exploits evade detection because their characteristics and format have not been added to the conventional blacklists used by security systems to otherwise block them.

The newly developed model aims to overcome these limitations by using a diverse set of features extracted from the structural characteristics of phishing websites. Those features are categorized into five groups, including web page structure, URL characteristics, WHOIS records, TLS certificates, and web page reputation. Notably, features derived from third-party services and web page reputation proved particularly influential in predicting phishing attacks, highlighting the significance of external sources and reputation-based indicators in enhancing detection capabilities.

Nagunwa evaluated the performance of his model against both traditional machine learning and deep learning algorithms, with promising results. Accuracy above 99% with minimal false positives and false negatives was achievable. Critically, working in a browser in real-time did not slow the loading of websites to the point at which they would compromise the user browsing experience.

Nagunwa, T. (2024) 'AI-driven approach for robust real-time detection of zero-day phishing websites', Int. J. Information and Computer Security, Vol. 23, No. 1, pp.79–118.
DOI: 10.1504/IJICS.2024.136735

The Internet of Things (IoT) is a relatively familiar concept. It refers to the network of interconnected devices embedded with sensors, software, and other technologies that enable them to collect and exchange data over the Internet. These devices can range from everyday objects such as household appliances, wearable devices, and industrial machines to vehicles and infrastructure components like traffic lights and smart meters.

The underlying concept of the IoT is the creation of a seamless network in which physical objects can communicate and interact with each other without requiring human intervention. This connectivity enables IoT devices to gather real-time data, analyze it, and respond accordingly, leading to increased efficiency, automation, and convenience in various aspects of life and industry.

The IoT represents a move away from the conventional way in which we perceive and interact with the world around us, as it integrates the physical and digital realms to create networked systems that can enhance productivity, improve decision-making, and drive innovation across numerous sectors.

When we talk specifically of the IoT of vehicles, that represents its own digital ecosystem, which we might call the IoV, the Internet of Vehicles. Work in the International Journal of Internet Technology and Secured Transactions introduces innovative security schemes to tackle the growing security challenges facing the Internet of Vehicles (IoV). The aim is to enhance the integrity and resilience of connected vehicles in the face of evolving smart technologies where vehicles have increasing autonomy and connectivity. Given that any connectivity has associated security risks, such as authentication breaches, data confidentiality breaches, and routing attacks, it is important that the IoV can be made secure.

Roumissa Sahbi and Salim Ghanemi of Badji Mokhtar Annaba University, in Annaba and Mohamed Amine Ferrag of Guelma University, in Guelma, Algeria, have proposed security solutions that use Software Defined Networking (SDN) and Elliptic Curve Cryptography (ECC). This allows them to identify and block potential attacks within the IoV system and so boost security.

With the Internet of Things (IoT) linking smart devices across different domains, the need for strong security measures is critical. The proposed security schemes offer a way to protect the IoV network against different kinds of threats. The team has used formal and informal security analyses with tools like AVISPA and BAN logic to verify the effectiveness of their protocols in mitigating attacks.

Sahbi, R., Ghanemi, S. and Ferrag, M.A. (2024) 'Security of internet of vehicles in smart cities: authentication and confidentiality aspects', Int. J. Internet Technology and Secured Transactions, Vol. 13, No. 3, pp.232–269.
DOI: 10.1504/IJITST.2024.136655

Research in the International Journal of Internet Technology and Secured Transactions, uses a hybrid approach to boosting the security of online applications, particularly within the realm of cloud computing. By merging two distinct techniques – homomorphic encryption and the squirrel search algorithm (SSA) – the study demonstrates a significant enhancement in the security of cloud computing models.

Homomorphic encryption is a form of encryption that allows mathematical operations to be performed on encrypted data without first having to decrypt data. This means that computations can be carried out on encrypted text, to yield useful results that, when decrypted, match the results of the same operations as if they had been performed on the plain text.

The SSA is a nature-inspired optimization algorithm that mimics the dynamic foraging behaviour of flying squirrels. It's classified as a metaheuristic algorithm, meaning it solves problems iteratively using randomness and guided search instead of using a conventional approach.

R.S. Kanakasabapathi and J.E. Judith of the Department of Computer Applications at the Noorul Islam Centre for Higher Education in Kumarcoil, India, hoped to boost cloud data storage systems using an advanced encryption technique. Encryption obviously plays a key role in safeguarding data from unauthorized access or breaches. The team has assessed the effectiveness of their approach, measuring upload and download time and encryption and decryption time. They demonstrated that the hybrid approach outperforms the Rivest-Shamir-Adleman (RSA) and ECC-based cryptography.

Ultimately, minimizing encryption and decryption times while maximizing data protection and so ensuring the integrity and confidentiality of cloud-stored information is critical. Given that there are ongoing concerns surrounding the security of cloud computing, ever-expanding volumes of data being stored and processed in the cloud, innovative approaches are needed to safeguard that data as each wave of malicious actors comes to the fore who might compromise or illicitly access that data.

Kanakasabapathi, R.S. and Judith, J.E. (2024) 'Improving cloud security model for web applications using hybrid encryption techniques', Int. J. Internet Technology and Secured Transactions, Vol. 13, No. 3, pp.291–308.
DOI: 10.1504/IJITST.2024.136677

Single-use plastics cause pollution, harm wildlife, deplete resources, pose health risks, and create waste management challenges, necessitating urgent action for reduction and better management. A study in the Global Business and Economics Review has identified drivers for the consumer shift away from single-use plastics.

The work conducted by Rajendran Geetha and Chandrasekaran Padmavathy of the Vellore Institute of Technology in Vellore, India, improves our understanding of the factors influencing consumers' decisions to avoid single-use plastic (SUP) bags. The team used Stimulus-Organism-Response (S-O-R) theory to analyse the various external influences and internal motivations.

External factors such as green advertisements, retailer incentives, and government policies were found to play significant roles. Green advertisements were effective in motivating individuals to choose what are commonly referred to as eco-friendly alternatives, while incentives such as discounts and rewards from retailers also encouraged them to avoid SUP bags and opt for reusable cloth and reinforced, "bag-for-life" type bags. Additionally, government policies such as bans and taxes on SUP bags have had a significant impact on consumer choice, emphasizing the importance of regulatory interventions in promoting sustainability and nudging consumers to use alternatives.

The findings provide insights for policymakers, advertisers, retailers, and communities on the importance of environmental messaging and individual perceptions in promoting sustainable behaviour. Millions if not billions of SUP bags are manufactured every year the world over. Most, as the name would suggest, are used once, and then discarded. Ultimately, they add a heavy burden to the waste stream and many of those that don't end up in landfill or being incinerated with other waste will reach environmental niches or the seas where they cause immense problems to different kinds of ecosystems and living things.

Implications drawn from the study suggest a need for a comprehensive approach. Advertisers can use environmental appeals, while retailers can incentivize behavioural change through discounts and rewards. Government and policymakers are urged to implement regulations and awareness campaigns to address plastic pollution effectively.

The study underscores the urgency of addressing environmental challenges and calls for collective efforts to build a sustainable ecosystem. Understanding and acting upon these findings are essential steps toward a greener future.

Geetha, R. and Padmavathy, C. (2024) 'Effects of external and internal influences on intentions to avoid single-use plastic bags', Global Business and Economics Review, Vol. 30, No. 2, pp.176–188.
DOI: 10.1504/GBER.2024.136423

A study published in the International Journal of Entrepreneurship and Small Business has investigated entrepreneurship education within higher education institutions. The results shed light on the critical role of such educators in engaging with students and communities while navigating various institutional perspectives.

Ethné Swartz of Montclair State University, New Jersey, Dianne H.B. Welsh of the University of North Carolina (Greensboro), Steven Tello of the University of Massachusetts Lowell, Lowell, USA, and Norris Krueger of Kyushu University, Fukuoka, Japan, collected and analysed survey data to understand the dynamics of entrepreneurship education.

The team found a correlation between institutional roles and the level of engagement in boundary-spanning activities. Boundary spanning refers to connections between disparate groups, departments, or organizations within a larger system. It involves individuals or units that operate at the interface between different domains, facilitating communication, collaboration, and information exchange across various boundaries. In the context of entrepreneurship education, boundary spanning often entails interactions between educators, students, academic departments, industry partners, and community organizations to promote learning, innovation, and engagement.

Intriguingly, faculty members, despite their active involvement, showed lower levels of engagement compared to other stakeholders. This raises concerns about the factors influencing faculty commitment, with tenure requirements being identified as a potential deterrent due to their heavy emphasis on research outcomes.

The study underscores the need for further investigation into the motivations and challenges within entrepreneurship education. It highlights the evolving nature of the educator's role and emphasizes the importance of aligning roles with core values, whether focusing on teaching, networking, or student-centred activities.

The work also draws attention to the increasing complexity of the institutional environment in which entrepreneurship education operates. It points to the growing significance of governing boards in navigating such complexities. In essence, the study provides insights into the challenges faced by entrepreneurship educators and the changing institutional context shaping their roles.

These findings have broader implications beyond academia for society and he wider economy. Understanding and supporting entrepreneurship educators are therefore important in fostering innovation and community engagement.

Swartz, E., Welsh, D.H.B., Krueger, N. and Tello, S. (2024) 'Engagement through boundary spanning: insights from US entrepreneurship educators', Int. J. Entrepreneurship and Small Business, Vol. 51, No. 3, pp.281-300.
DOI: 10.1504/IJESB.2024.136392

Sarcasm, a complex linguistic phenomenon often found in online communication, often serves as a means to express deep-seated opinions or emotions in a particular manner that can be in some sense witty, passive-aggressive, or more often than not demeaning or ridiculing to the person being addressed. Recognizing sarcasm in the written word is crucial for understanding the true intent behind a given statement, particularly when we are considering social media or online customer reviews.

While spotting that someone is being sarcastic in the offline world is usually fairly easy given facial expression, body language and other indicators, it is harder to decipher sarcasm in online text. Work in the International Journal of Wireless and Mobile Computing hopes to meet this challenge. Geeta Abakash Sahu and Manoj Hudnurkar of the Symbiosis International University in Pune, India, have developed an advanced sarcasm detection model aimed at accurately identifying sarcastic remarks in digital conversations, a task crucial for understanding the true intent behind online statements.

The team's model comprises four main phases. It begins with text pre-processing, which involves filtering out common, or "noise", words like "the", "it", and "and". It then breaks down the text into smaller units. To address the challenge of dealing with a large number of features, the team used optimal feature selection techniques to ensure the model's efficiency by prioritizing only the most relevant features. Features indicative of sarcasm, such as 'information gain,' 'chi-square,' 'mutual information,' and 'symmetrical uncertainty,' are then extracted from this pre-processed data by the algorithm.

For sarcasm detection, the team used an ensemble classifier comprising various algorithms including Neural Networks (NN), Random Forests (RF), Support Vector Machines (SVM), and a Deep Convolutional Neural Network (DCNN). The performance of the latter was optimized using a newly proposed optimization algorithm called Clan Updated Grey Wolf Optimization (CU-GWO).

The team found that their approach could outperform existing methods across various performance measures. Specifically, it improves on specificity, reduces false negative rates, and has superior correlation values when compared with standard approaches.

Beyond its immediate implications for natural language processing and sentiment analysis, the research holds promise for enhancing sentiment analysis algorithms, social media monitoring tools, and automated customer service systems.

Sahu, G.A. and Hudnurkar, M. (2024) 'Metaheuristic-assisted deep ensemble technique for identifying sarcasm from social media data', Int. J. Wireless and Mobile Computing, Vol. 26, No. 1, pp.25–38.
DOI: 10.1504/IJWMC.2024.136558

TikTok is a popular social media platform where users can create and share short videos, often featuring music, dance, comedy, and other creative content.

Research in the International Journal of Mobile Communications has compared TikTok usage between China and the United States of America and offers invaluable insights into user behaviour and motivations on the social media platform and how they differ between these two regions. The study involved surveying around 150 each Chinese and US users and introduced the Comprehensive Gratifications Engagement Model to reveal how users interact with TikTok content.

Jian Shi, Mohammad Ali, and Fiona Chew of Syracuse University, New York, USA make several points based on their study. First, TikTok users engage more in self-promotion and with the platform's video content compared with other short-video apps such as Snapchat. This would suggest that part of TikTok's unique appeal is its potential for working as a goal-oriented activity.

Secondly, differences in user engagement between TikTok users in China and the USA were apparent, particularly when it comes to the degree of gratification people hope for in using the app, users in the USA seek a greater degree of gratification than those in China, the team reports. Understanding such cultural differences is essential for companies hoping to tailor marketing strategies on social media in different countries.

Fundamentally, TikTok is widely used as a pastime to help someone escape their everyday life, to relax, to learn, but also as a tool for procrastination and as a status-seeking tool and to impress others. Thankfully, it's not all about self-aggrandisement, people also want to meet and discover interesting people on the app and to make connections and thus to feel like they belong to an interesting community. There remains an element of social in this form of social media. The specifics as detailed in the paper showed the nuanced differences between users in China and the USA.

Shi, J., Ali, M. and Chew, F. (2024) 'Understanding gratifications for engaging with short-video: a comparison of TikTok use in the USA and China', Int. J. Mobile Communications, Vol. 23, No. 2, pp.175–200.
DOI: 10.1504/IJMC.2024.136627

Insomnia is a pervasive sleep disorder affecting millions of people worldwide. It has long been considered a significant health concern characterized by difficulty falling asleep or remaining asleep for a sufficiently long period. While almost everyone suffers sleeplessness on occasion. It can often be alleviated by changing one's bedtime routine, avoiding late food and drink, relaxation and breathing exercises, switching off one's gadgets earlier in the evening, reducing stress overall, and with short-term medication. Chronic insomnia if left untreated can ultimately lead to health issues, such as ongoing fatigue during the day and an increased risk of other health conditions. Approaches to address the problem of insomnia are thus keenly sought.

Research in the International Journal of Industrial and Systems Engineering offers a promising advancement in sleep aid technology. Shan Hu, Liyan Zhang, Weiqi Guo, Dong Zhang, Qi Jia, Zitong Yang, and Min Guo of Hubei University of Technology in Wuhan, Hubei, China, have used neural network science to develop a sleep aid that "understands" the individual user's needs and uses sophisticated processes to model their sleep patterns and then play soothing, music at appropriate points to help overcome the person's insomnia. The team suggests that their work might change how sleep aid products are designed by prioritizing the user rather than their problem.

The team's approach integrates sophisticated techniques such as the Analytic Hierarchy Process (AHP), Quality Function Deployment (QFD), and Function Behaviour Structure (FBS) models to develop a more effective approach. AHP is used to assess the user's needs and give a weighting to each factor. Convolutional neural networks then allow the team to craft a personalized sleep state model that can be tailored to individual sleep patterns and then be optimized for effective sleep assistance. The sleep, or rather "lack-of-sleep" patterns are initially monitored using a heart monitor and skin conductivity measurements the data from which are fed into the model.

Critically, what emerges from this project is that design has to focus on the user as well as the device to get the best results. "This method can improve the user experience of intelligent sleep aid products from the perspective of user needs and provide a feasible reference for the design research of intelligent sleep aid products," the team writes.

Hu, S., Zhang, L., Guo, W., Zhang, D., Jia, Q., Yang, Z. and Guo, M. (2024) 'Research on the design of smart sleep aid interactive products', Int. J. Industrial and Systems Engineering, Vol. 46, No. 2, pp.151–168.
DOI: 10.1504/IJISE.2024.136413

Bulk acoustic wave (BAW) filters are used in various electronic devices, including smartphones, tablets, Wi-Fi routers, and communication systems to help produce smooth and reliable high-frequency radio signals for 5G communications. They are thus important in ensuring efficient communication and data transmission. BAW filters are widely used in the radio frequency front ends of diverse devices, such as magnetoelectric transducer antennae for wireless communication. BAW filters are also used in physical sensors, actuators, and biochemical sensors.

In high-power applications an issue known as the self-heating effect can arise in BAW filters. Self-heating BAW filters when they are powered leads to a degradation in performance known as insertion loss, a fall in signal power. Research in the International Journal of Nanomanufacturing has investigated this phenomenon. Mitigating the detrimental effects of self-heating could improve the overall efficiency of a component or device as well as improving durability.

Bin Ruan and Tingting Liu of Southwest University of Science and Technology, in Mianyang, Shaohua Yang, Qinwen, and Weiheng Shao of the China Electronic Product Reliability, and Environmental Testing Research Institute in Guangzhou, and Ming Wu of Pandhus Microsystem Co., Ltd also in Mianyang, China, have investigated self-heating at high-frequency power levels. The team built a dedicated test system to measure the maximum surface temperature and the insertion loss of BAW filters at different power levels.

The relatively simple but important finding from their tests is that as power levels increased, so did heating, and thus, insertion loss. The correlation between higher power and greater insertion loss represents a fundamental trade-off in filter design. As power levels increase, the filter's components may experience greater stress, leading to increased losses.

Armed with this knowledge, it might be possible to use various approaches to mitigate insertion loss while maintaining adequate power handling capabilities. For instance, choosing alternative materials, refining fabrication techniques, and implementing innovative filter configurations might all be used to reduce self-heating and so reduce insertion loss. For instance, incorporating advanced materials with improved thermal properties or refining the geometry of the filter structure might help dissipate heat more effectively, reducing losses at higher power levels.

Ruan, B., Liu, T., Yang, S., Huang, Q., Wu, M. and Shao, W. (2023) 'Study on the effect of self-heating effect of bulk acoustic wave filter on the interpolation loss in the band', Int. J. Nanomanufacturing, Vol. 18, Nos. 3/4, pp.178–188.
DOI: 10.1504/IJNM.2023.136571

Writing in the International Journal of Global Environmental Issues, a team from Japan explains that "Wetlands play an important role in a sustainable urban future." They add these these environmental regions provide what might be called ecological services to the cities in which they are sited as well as sustaining wildlife and even allowing the transmission and development of indigenous culture.

In this context the wetland parks of Suzhou, China, have emerged as exemplars of urban sustainability, offering crucial ecological services and preserving cultural heritage. Lihui Zhou and John Joseph Puthenkalam of Sophia University, Japan in their study shed light on the significance both locally and globally of such wetlands.

Suzhou is located in the Jiangsu Province of eastern China and boasts a rich tapestry of wetlands. These wetlands, which include a network of rivers, lakes, and marshes, have played a vital role in the region's ecology and culture for centuries. They serve as crucial habitats for a variety of plant and animal species, providing breeding grounds for migratory birds and supporting diverse aquatic life. They also play an important role in flood control, water purification, and sediment retention. In addition to this environmental and ecological significance, Suzhou's wetlands hold immense cultural value with the city's ancient and renowned classical gardens, many of which are UNESCO World Heritage Sites, intricately connected with the wetlands.

Despite facing threats from urbanization and industrialization, Suzhou has made efforts to preserve and restore its wetlands in recent years. Wetland restoration projects, ecological conservation programs, and sustainable development planning have allowed the city to balance economic growth and environmental protection.

The research explores how tailored restoration efforts have boosted the ecological and cultural impact as sustainable urban development takes place. The Suzhou model thus demonstrates how local conditions can help with restoration strategies, ultimately enhancing the ecological resilience and cultural relevance of such sites.

By prioritizing wetland conservation, Suzhou has been able to safeguard its local ecosystems, nurture cultural heritage, and promote environmental education. Such initiatives might even resonate beyond Suzhou, emphasizing the broader implications of wetland park development for urban sustainability worldwide.

Zhou, L. and Puthenkalam, J.J. (2023) 'Analysis of the role of wetland parks in urban sustainability: a case study of Suzhou, China', Int. J. Global Environmental Issues, Vol. 22, No. 4, pp.375–392.
DOI: 10.1504/IJGENVI.2023.136301

Effective communication played a pivotal role in guiding public behaviour and health protocols during the COVID-19 pandemic and will do so again during any future global health crisis. A paper in the International Journal of Technology Management has explored the significance of strategies driven by technological understanding in persuading individuals to adopt new behaviour and adhere to health guidelines. The work could offer insights that might allow us to shape a more effective global response to a future pandemic.

The phrase "the new normal" became common parlance in the early days of the COVID-19 pandemic. New norms and practices were urgently required to help us reduce the risk of contracting the virus and passing it on to others. Different countries took different approaches, some with more success than others, the virus continued to spread and mutate into novel variants. How bad the health costs might have been if the new normal in different regions had been managed differently is open to debate. Indeed, the new normal seems a thing of the past despite the ongoing presence of the virus in society.

Talayeh Ghofrani of the Eastern Mediterranean University in Famagusta, Cyprus emphasizes the importance of persuasive messaging. She has focused on the intersection of technology and communication strategies in light of the rapid advancement and development of digital platforms and the increasing and more widespread social media use as the coronavirus spread across the globe.

The work identifies four important factors associated with successful and persuasive communication: the targeted audience, presentation model, message content and context, and the type of technologies employed. Ultimately, whether the message was received and understood by individuals at critical times depended on the complex relationship between these different factors. The subtleties perhaps explain why messages were often misinterpreted or even deliberately obfuscated when a political agenda stood in the way of healthcare in many places.

Ghofrani's work suggests that digital platforms are a powerful tool for tailoring persuasive messages during times of crisis to allow us to mobilize the public response appropriately. An improved strategy given a sensible and non-corrupt government response would ultimately improve the ability of health organizations to engage more effectively with diverse populations and promote adherence to recommended health measures. It might even be able to defeat the misinformation, the spread of rumours, and so-called "fake news" all of which worsened the challenges during the COVID-19 pandemic and could do so again in a future crisis.

Ghofrani, T. (2024) 'The impact of new media technologies on persuasive communication in the time of global crisis', Int. J. Technology Management, Vol. 94, Nos. 3/4, pp.419-435.
DOI: 10.1504/IJTM.2024.136420

A study in the European Journal of International Management has looked into the relationship between learning from failure and the internationalization process in entrepreneurial ventures. The researchers show a subtle link that perhaps challenges the received wisdom regarding success and failure suggesting that a cyclical process exists where the global expansion of entrepreneurial firms is intricately linked to experiential learning.

Leila Hurmerinta, Niina Nummela, and Eriikka Paavilainen-Mäntymäki of the Turku School of Economics at the University of Turku in Turku, Finland, explain that this process involves a reciprocal transfer, analysis, and internalization of experiential knowledge. Failures within the entrepreneurial landscape act as stimuli whether they are failures of the entrepreneur themselves or their peers.

Indeed, entrepreneurs play a pivotal role as gatekeepers of experiential learning, absorbing, digesting, and transferring knowledge within their organization to enhance the positive effects of learning from failure. Moreover, contrary to the received wisdom, this research indicates that entrepreneurs need not experience failure personally to gain valuable insights. Failures encountered by peers, other companies in the same industry, or fellow entrepreneurs, even in different sectors, can serve as valuable sources for long-term learning and ultimately help nudge the company towards success.

The team adds that the timing of the learning process regarding failure emerges as a critical factor, with delayed learning leading to reactive as opposed to proactive decisions without sufficient analytical thinking. The work offers a dynamic model that illustrates the interaction between non-linear internationalization and experiential learning with feedback loops depicted in the model highlighting how experience might either fuel or inhibit the internationalization process. In this context, the importance of near-failures is also revealed.

By offering a conceptual, theory-based cyclical model, the researchers thus shed light on the role of learning from failure and also suggest new avenues of exploration for future research where the subjective and context-dependent nature of both success and failure are investigated.

Hurmerinta, L., Nummela, N. and Paavilainen-Mäntymäki, E. (2024) 'Boosted by failure? Entrepreneurial internationalisation as a cyclical learning process', European J. International Management, Vol. 22, No. 3, pp.337–353.
DOI: 10.1504/EJIM.2024.136483

A novel smartwatch system clocks your activity more precisely and could offer you a better perspective on your activity levels than simply counting your 10,000 steps or how long you stay storing in bed.

Writing in the International Journal of Ad Hoc and Ubiquitous Computing, a team from India and the UK, have introduced a novel system designed to reshape how smartwatches interpret and categorize our daily activities. The system has the potential to improve the way we monitor our physical activity as well as perhaps leading to new applications in the broader wearable technology sector.

Ankita Dewan of IIT Ropar in Rupnagar, India, Venkata M.V. Gunturi of the University of Hull, UK, and Vinayak Naik of BITS Pilani in Goa, India, have focused on distinguishing between non-exercise activity thermogenesis (NEAT) and non-NEAT activities recorded by smartwatches. NEAT activities, also known as non-exercise physical activity (NEPA), involve energy expenditure during routine tasks like doing common hobbies, working on a laptop, using a smartphone, cooking, eating, standing instead of sitting, walking around, climbing stairs, doing chores, and fidgeting.

The opposite, which might call non-NEAT, non-NEPA, activities encompasses more formal exercising such as running, cycling, swimming, and gym activities, for instance. These are usually intentional and structured exercises aimed at improving cardiovascular fitness, strength, and overall health.

Unlike previous studies that overlooked specific NEAT activities, this new approach uses lower-frequency data sampling to address the limitations of earlier models. The team has thus been able to delve into critical parameters including classification features, data sampling frequency, upload rate, and window length to improve classification accuracy. At the same time, they have also considered how to reduce power consumption and so extend battery life for the smartwatch. At a current of 33 Amps per hour, 87% is feasible. However, 97% accuracy is possible at a higher energy cost of 37 Amps per hour.

The system defines several novel activity categories not usually adopted by fitness apps, which tend to focus on walking, running, and cycling, for instance. These NEAT activities are cooking, sweeping, mopping, climbing stairs, eating, driving or being a passenger in a car, working on a laptop or phone, and watching TV. The smartwatch's sensors can be tuned to recognise such activities.

The research presents a practical and innovative approach to activity recognition, addressing challenges in existing models. The implications lie in the potential for improved user experience, battery efficiency, and more informed decision-making regarding parameter settings to help the user determine how active they are with a view to modifying their habits and perhaps improving their overall physical health.

Dewan, A., Gunturi, V.M.V. and Naik, V. (2024) 'NEAT activity detection using smartwatch', Int. J. Ad Hoc and Ubiquitous Computing, Vol. 45, No. 1, pp.36–51.
DOI: 10.1504/IJAHUC.2024.136141

A study in the International Journal of Economics and Business Research has investigated customer loyalty dynamics in the retail banking sector in Cyprus. The work challenges established assumptions by emphasizing the significance of emotional connections over transactional factors. The investigation highlights affective commitment and attitudinal loyalty as important factors influencing a customer's decision to stay with their current banking provider.

Maria Georgiou, Sofia Daskou, and Michailina Siakalli of Neapolis University Pafos in Cyprus, and Athanasios Anastasiou of the University of Peloponnese in Tripolis, Greece, have shown that contrary to the received wisdom, behavioural loyalty and continuance commitment have little effect on customer retention in the retail banking area.

This finding suggests that emotional bonds and genuine loyalty hold more sway than other factors like switching costs or habitual purchasing patterns and so can help guide customer retention strategy. Conversely, if customers are shown such evidence about their behaviour then they might usefully find a way to see through such strategies and make a better-informed choice about whether or not to stay with a given bank or find an alternative that better suits their needs.

In parallel with such insights, the research also shows that a strong banking system is important at the national level. The work emphasizes that a well-functioning banking system can ensure financial efficiency but also contribute to economic growth and development. Banks that are facilitating household financial planning and ensuring liquidity across the economy play a vital role in the flow of capital, payments, goods, and services across the nation.

The study's examination of relational constructs provides insights into the behaviour of Cypriot retail banking customers. Affective commitment and attitudinal loyalty emerge as pivotal motivators for customer retention, the research suggests. It is worth noting that normative commitment is identified as a unique yet negatively correlated contributor to customer loyalty. Normative commitment is an individual's perceived sense of obligation or moral responsibility to remain committed to, in this case, their bank.

For businesses and policymakers, they must recognise the importance of emotional bonds and genuine loyalty in the banking sector. A better-informed customer might also be made aware of this for the mutual benefit of the broader economy as well as their circumstances.

Georgiou, M., Daskou, S., Siakalli, M. and Anastasiou, A. (2024) 'An explanatory study of predictive factors of customer retention with Cypriot retail banks', Int. J. Economics and Business Research, Vol. 27, No. 1, pp.127–150.
DOI: 10.1504/IJEBR.2024.136166

Research in the International Journal of Intelligent Engineering Informatics proposes the use of system behavioural modelling and unattended or semi-supervised machine learning to help solve the problem of cyber security in smart cities. By training machine learning models on relevant datasets, the researchers suggest that security systems can be improved so that they can identify and mitigate cyber threats. An ongoing challenge is to ensure the reliability and completeness of those very datasets to allow for anomalies to be detected with confidence.

The development of technologically connected and enabled 'smart cities' could help us face better rapid urbanization and growing populations. Connectivity allows Internet of Things (IoT) systems to be used more effectively and to harness the power big data analytics to tackle various urban issues, such as traffic congestion, air pollution, water management, housing issues, urban planning, healthcare, and equitable accessibility to resources for everyone. However, as with any integrated and networked technology, IoT devices can be vulnerable to unauthorized access by those with malicious intent. This is most worrying in the area of safety systems, but also of concern across many others such as transport and healthcare.

N. Girubagari and T.N. Ravi of the Thanthai Periyar Government Arts and Science College in Tiruchirappalli, Tamil Nadu, India, point out that cyber attacks in this context go way beyond the kind of the privacy concerns of individuals. They might affect smart infrastructure, communications, and e-governance. As such, intelligent detection systems based on machine learning to safeguard against cyber threats are needed urgently.

The team looks at various anomaly detection methods and assesses their pros and cons. The paper highlights existing obstacles and gaps in research that are currently stymieing the full potential of the smart city. The work evaluates and contrasts methods for identifying anomalies in big data-based cybersecurity, utilizing survival analysis to assess the benefits and drawbacks of current techniques. The long-term objective is, of course, the efficient detection of cyber attacks in real-world scenarios. The research emphasizes that performance assessment for machine learning methodologies is important at this juncture.

In future work, the researchers hope to conduct additional experiments to test performance and establish a methodology for precise and comprehensive anomaly identification in smart city systems.

Girubagari, N. and Ravi, T.N. (2023) 'Methods of anomaly detection for the prevention and detection of cyber attacks', Int. J. Intelligent Engineering Informatics, Vol. 11, No. 4, pp.299–316.
DOI: 10.1504/IJIEI.2023.136097

Research in the International Journal of Information Technology and Management sheds light on the potential of OpenStack, an open-source cloud-computing platform, in the realm of educational virtualization.

OpenStack, often shortened to O~S, is used as a standardized Infrastructure-as-a-Service (IaaS) solution for both public and private cloud environments. The platform allows users to access virtual servers and manage hardware components such as computer processors, storage, and networking. It could also offer major benefits to educational establishments such as cost savings and the optimization of hardware resource utilization.

Faouzi Mechraoui of the University of Leuven Limburg in Leuven, Belgium, and Pedro Martins and Filipe Caldeira of the Polytechnic of Viseu in Portugal have reviewed OpenStack's capabilities in the virtualization of resources and how it can provide a flexible and scalable infrastructure for data management, scaling, and networking configurations. Specifically, their review explores the deployment of IaaS using OpenStack.

The team looked at the functional and architectural aspects of OpenStack and discusses how it can be used to build large-scale virtual environments. The research highlights an experimental virtualization setup within an educational scenario, showcasing OpenStack's adaptability to specific use cases at Viseu. They point out that the system might equally be used in governmental settings too.

OpenStack has many advantages among them how well it can be aligned with user needs and how well it adheres to emerging open standards. These benefits ensure compatibility with current approaches to virtualization, which thus position OpenStack as a practical and reliable solution. As technology evolves around it, OpenStack will be able to stand as a versatile solution.

The team suggest that the next step in an evaluation of OpenStack will be to undertake benchmarking tests to evaluate OpenStack's performance under stress. The ultimate goal is the implementation of OpenStack to virtualize entire on-premise educational systems. This would allow students to manage their "instances" within the system, creating a dynamic and hands-on learning environment.

Mechraoui, F., Martins, P. and Caldeira, F. (2024) 'OpenStack: a virtualisation overview', Int. J. Information Technology and Management, Vol. 23, No. 1, pp.1–12.
DOI: 10.1504/IJITM.2024.136181

Research in the International Journal of Education Economics and Development has used the entrepreneurial intention model to investigate what if any influence of parental self-employed status has on the aspirations of their offspring. The researchers obtainted data and questionnaire results from 319 respondents at a public university in Spain. The data and answers were analysed through structural equation modelling, using multi-group analysis (MGA) to discern the differences between those individuals with self-employed parents and those without.

Kwaku Amofah, Jones Lewis Arthur, and Edward Owusu of Sunyani Technical University in Sunyani, Ghana, and Ramon Saladrigues Solé of the University of Lleida in Lleida, Spain, demonstrated that respondents with self-employed parents were much more likely to have a positive attitude towards entrepreneurship, perceived behavioural control, entrepreneurial skills, and environmental support compared to those without such parental background. However, the MGA showed that, despite these differences, the overall entrepreneurial intention in both groups was comparable.

The results reinforce the role of parental self-employment in this kind of study. They also underscore the importance of conducting multi-group analysis to reveal the nuances and variations among different groups. The researchers thus suggest that their work has implications for education and policy-making, particularly when it comes to entrepreneurship teaching and learning. By shedding light on the impact of parental self-employment on key elements of the entrepreneurial mindset, the team suggests the need for a more subtle approach to teaching entrepreneurship skills as well as recognizing influences that might be shaping a student's perception and intention when starting their own business.

The insights regarding family background, individual perceptions, and environmental support are important in shaping entrepreneurial ambitions. The current findings will contribute to defining educational strategies and policies. The team also uncovered a discernible gender gap in entrepreneurial intention. This, the work suggests, highlights the need to explore further and to consider other cultural and contextual factors that might influence entrepreneurial intentions in different settings.

An additional notable contribution of this research lies in its approach in that the exploration using the integrated form of the entrepreneurial intention model was shown to be rather useful whereas it has received less attention in previous studies.

Amofah, K., Saladrigues Solé, R., Arthur, J.L. and Owusu, E. (2024) 'Entrepreneurial intentions: the role of parental self-employment', Int. J. Education Economics and Development, Vol. 15, Nos. 1/2, pp.234–266.
DOI: 10.1504/IJEED.2024.136223

Traditional fingerprint identification methods can struggle with accurately identifying feature points in smaller regions. This is usually where a subset of fingerprints that are of limited size might typically be found in a restricted regions of a larger fingerprint image. Ultimately this usually leads to lower recognition accuracy and weaker evidence gleaned from a crime scene investigation, for instance.

Research in the International Journal of Data Mining and Bioinformatics hopes to overcome that problem. The paper introduces a machine vision technique that has been refined to work on small fingerprint areas. It could overcome many of the challenges faced by crime scene investigators and improve the overall precision of fingerprint recognition. The same technology might also be extended to biometric security systems.

Qiqun Liu and Tan Liu of Henan Vocational College of Agriculture in Zhengzhou Henan, China, have introduced this new approach to small-area fingerprint recognition in order to overcome the limitations of conventional techniques particularly with respect to the recognition of feature points in boundary regions.

The key component of their new approach is a descriptor that provides an analysis of estimated values of the important fingerprint parameters. By using this descriptor, the method extracts detailed feature points and establishes a so-called frequency field. This can then be used to direct enhancements of the small-area fingerprint image to improve clarity. An additional process then extracts detailed features from the enhanced small-area fingerprint image.

The researcher's experiments give a good indication of the effectiveness of this method, allowing them to accurately extract detailed features from seemingly obscure fingerprint images. Notably, the average recognition time has been reduced to just over half a minute compared with the much longer times of more conventional approaches when presented with the same kinds of image. Moreover, the technique offers a more uniform distribution of feature points and so excels in the identification of ridge features on image edges.

The same machine vision technology might be extended beyond forensic science to applications in biometric security systems and access control. The efficiency and accuracy improvements wrought by the new approach could thus be used to enhance the reliability of biometric authentication systems.

Liu, Q. and Liu, T. (2024) 'A high precision recognition method for small area fingerprints based on machine vision', Int. J. Data Mining and Bioinformatics, Vol. 28, No. 1, pp.40–57.
DOI: 10.1504/IJDMB.2024.136226

Conventional search and rescue operations after major disasters face many problems. A team from Malaysia writing in the International Journal of Vehicle Autonomous Systems, now suggests a practical solution that involves a real-time human detection system using a fixed-wing Unmanned Aerial Vehicle (UAV).

Cheok Jun Hong and Vimal Rau Aparow of the University of Nottingham Malaysia, in Selangor and Hishamuddin Jamaluddin of Southern University College in Skudai, Johor, Malaysia, have brought together UAV technology with readily available small-scale tools such as the Raspberry Pi computer. This allows them not only to better manage system functions than with conventional technology but also to stream aerial imagery from an attached camera.

What makes this novel approach particularly attractive is the ability to offload the computationally intensive human detection tasks to a server at the edge, enabled by 4G cellular network technology. The team explains that the server employs the YOLOv3 deep neural network, trained on VisDrone and SARD datasets, and can precisely identify people from the images gathered by the UAV's camera and transmit results to ground control. With a positive identification, a rescue team can then be sent to the exact spot where a rescue is needed.

The system brings together deep learning algorithms and mobile-edge computing and represents a shift away from conventional search and rescue approaches that could speed up the whole process during a major incident. There are also benefits to precluding the need for manned aircraft or people to cover a lot of ground in hazardous environments.

The team explains that their convolutional neural network with the YOLOv3 architecture can achieve a mean Average Precision (mAP) of almost 80 per cent for identifying people in the images from the UAV camera. By using the TensorRT toolkit the researchers can further optimize the approach and speed up inference by some three times when compared with the original neural network but without loss of accuracy. Of course, while the system can have a greater range than a radio-enabled system, it does rely on the stability and existence of the 4G network across the search and rescue area.

The researchers initially designed the system for human search and rescue scenarios, but it could be adapted to other applications, such as public safety and crime prevention. It could be repurposed for patrolling a site vulnerable to criminal activity or even used in tracking criminals.

Hong, C.J., Aparow, V.R. and Jamaluddin, H. (2023) 'Real-time human search and monitoring system using unmanned aerial vehicle', Int. J. Vehicle Autonomous Systems, Vol. 17, Nos. 1/2, pp.106–132.
DOI: 10.1504/IJVAS.2023.136180

A team in Turkey has tested different machine-learning algorithms for predicting electricity demand from different sources. They trained the algorithms on electricity demand data for the period 2000-2022 and used them to successfully make predictions for 2023 with differing degrees of accuracy.

The researchers tested the predictive power of long short-term memory (LSTM), artificial neural network (ANN), linear regression (LR), support vector regression (SVR), decision tree regression (DTR), random forest regression (RFR), and eXtreme gradient boosting (XGBoost) and demonstrated that LSTM is the most accurate. Such an algorithm could be used to model energy usage and production for long-term electricity planning around the world.

Writing in the International Journal of Oil, Gas and Coal Technology, Mehmet Hakan Özdemir and Batin Latif Aylak of the Turkish-German University in Istanbul, Murat Ince of Isparta University of Applied Sciences, Isparta, and Okan Oral of Akdeniz University in Antalya, Turkey, suggest that understanding supply and demand in terms of the different non-renewable and renewable energy sources is critical at this point in human history.

Given that non-renewable sources such as fossil fuels are finite and irreplaceable, renewable sources such as wind, solar, hydro, geothermal, and biogas which can be replenished are high on the generation agenda. Machine learning, with its ability to discern intricate relationships and patterns from large bodies of data, offers a powerful and flexible approach to prediction. In contrast to traditional statistical methods, machine learning algorithms, trained on appropriate data sets, can consider the entirety of the available data and thus discern conclusions about complex interactions that traditional analytical methods cannot reach.

Machine learning could thus help us in our energy policy decisions and steer the electricity generation industry towards a path to a more sustainable future. The insights gleaned from the research not only inform decision-makers but also highlight just how transformative machine learning algorithms can be in redefining how we solve problems of this kind.

Özdemir, M.H., Aylak, B.L., Ince, M. and Oral, O. (2024) 'Predicting world electricity generation by sources using different machine learning algorithms', Int. J. Oil, Gas and Coal Technology, Vol. 35, No. 1, pp.98–115.
DOI: 10.1504/IJOGCT.2024.136028

Online shopping and home delivery have displaced the traditional trip to the shops for many people. This has been an ongoing process in retail that has seen the closure of high-street shops and many of the big department store chains as customers turn to shopping online. The process was somewhat accelerated during the pandemic when many people simply could not go shopping because of the prevalence of the disease and lockdown restrictions.

Writing in the International Journal of Revenue Management, a team in the USA discusses how suppliers are hoping to take advantage of this changing retail environment in which shoppers have everything from groceries and medication to devices and tools delivered to their homes rather than buying at a bricks-and-mortar store. They are looking at how retailers are exploring innovative strategies to enhance their resilience and revenue generation.

One novel approach known as the 'driver-becoming-salesperson' strategy, could, despite its rather clumsy name, become an important component in on-the-doorstep upselling and cross-selling. The delivery driver hands over the goods ordered but with additional offers for associated products made directly to the customer at their own home.

Conventionally, the last-mile phase of the delivery process has been viewed as nothing more than a logistics operation. Drivers are hired, vehicles are serviced and packed with goods and an efficient route is planned around the sales region to get those goods to the customers as quickly and efficiently as possible. The passive hope is that satisfied customers will shop with the retailer again. However, a more proactive approach would represent a paradigm shift by adding a new role for the delivery personnel – sales agent.

The concept is simple but may well be sophisticated in its implementation. The idea capitalizes on the direct, face-to-face interaction the driver can have with the customer when fulfilling the order. With appropriate skills, training, and the wares to offer, the delivery personnel might bring the showroom experience to the customer. Of course, door-to-door salespeople have existed ever since we have had doors, but this driver-as-upseller approach aligns more with the evolving landscape of e-commerce and modern retailing where storefronts are almost always virtual for many shoppers.

Timothy L. Urban and Robert A. Russell of the Collins College of Business at The University of Tulsa in Oklahoma, USA, have modelled this scenario by looking at two well-known complex problems, a vehicle-routing problem and the multiple-knapsack problem. By merging these two problems, they hoped to come up with an optimal way for sellers to select products that their drivers might then upsell from their delivery vehicles. The model that combines logistics and selling takes into account product attributes, customer preferences, and route efficiency. The results from the model highlight the fact that it is relatively easy to find an efficient route, but finding the right customers for upselling is the key to success.

The 'driver-upseller' strategy offers a pragmatic approach to help retailers adapt more effectively to the way people now shop. It will make an opportunity of the logistical paradigm of the last-mile delivery allowing for ad hoc customer engagement and upselling at the time of delivery. As online sales continue to grow, retailers that embrace such an approach are likely to boost their competitiveness, their sales, and customer satisfaction.

Urban, T.L. and Russell, R.A. (2024) 'Upselling at delivery', Int. J. Revenue Management, Vol. 14, No. 1, pp.1–32.
DOI: 10.1504/IJRM.2024.135962

Researchers in Switzerland and the UK have delved into the intricate world of digital interactions, using a unique combination of theories to shed light on the often-overlooked aspects of how customers engage with online services. By merging two theoretical frameworks, Activity Theory (AT) and Service-Dominant Logic (SDL), the study focuses on deciphering how user actions contribute to the overall value of digital services.

When one uses a voice assistant or interacts with a smart application, one is not simply completing a task but also creating value in different ways. Writing in the International Journal of Web Engineering and Technology, researchers break down this value creation into various dimensions. These are dematerialization (moving away from physical interactions), objectification (transforming actions into tangible outcomes), institutionalization (establishing patterns), modularization (breaking down tasks into manageable parts and streamlining processes), and platformization (building on existing digital structures and helping enhance them). These different dimensions can benefit both the customer and the service provider.

Uwe V. Riss and Michael Ziegler of the Eastern Switzerland University of Applied Sciences in St. Gallen, Switzerland, and Lindsay J. Smith of the University of Hertfordshire in Hatfield, UK focused on understanding how user activities, defined by AT, integrate into the theoretical framework of service systems represented by SDL. Their findings shed light on the various dimensions of customer value with a specific application to voice assistants.

The team explains that this integration provides a deeper insight into customer interactions within service systems, essential for investigating customer experience in the context of service ecosystems. The study underscores the significance of smart products, highlighting the inseparable intertwining of service and material interaction in what we might call digital ecosystems. Moreover, the work reconciles the different focuses of AT and SDL, which are both centred on customers using services within action objectives or service ecosystems but with differences. AT emphasizes specific actions and outcomes, while SDL concentrates on the interplay of various service providers.

The common thread, the work suggests, is the concept of cocreation of value, either as the success of action in AT or as resource integration in SDL. The research thus brings together the understanding offered by each approach. Given that the customer experience plays a pivotal role in representing digital ways of value creation, it is important to encompass customer activities with that understanding.

Riss, U.V., Ziegler, M. and Smith, L.J. (2023) 'Value dimensions of digital applications and services: the example of voice assistants', Int. J. Web Engineering and Technology, Vol. 18, No. 4, pp.319–343.
DOI: 10.1504/IJWET.2023.136174

A study in the European Journal of International Management has looked at the complex relationship between gender, governance, and corruption in Europe. The research analysed evidence from 35 European countries between the years 2010 and 2020 to discern the nuanced relationship between heightened gender inequality and increased corruption. Fundamentally, the research found that a substantial female presence in decision-making positions, especially in societies with robust legal frameworks, was associated closely with transparency and lower levels of corruption.

Andrea Cámara-Payno, Julieta Díez-Hernández, Martyna Novak, and Elena Temiño-Santamaría of the University of Burgos in Burgos, Castilla y Leon, Spain, found that contrary to expectations, they did not identify gender-based disparities in attitudes toward corruption. Rather, greater representation of women in decision-making roles contributed to enhanced overall gender equality and, it was this that was associated with lower levels of corruption.

It is well-documented that among the European nations, Denmark, Finland, and Norway have good gender equality and adherence to the rule of law. It is unlikely to be a coincidence that these nations have a higher proportion of women in both public and corporate spheres of influence and that this correlates with more effective corruption control than is seen in other nations that are more dominated by men. This, the research suggests, actually challenges traditional gender theory that would otherwise indicate that gender ultimately becomes of little consequence in terms of attitudes to corruption once a good degree of equality has been achieved.

The issue is complex, of course, and gender equality and decision-making are just part of broader considerations in the context of combating corruption. Nevertheless, the study emphasizes the importance of improving gender equality and the rule of law in the fight against corruption. The promotion of equal opportunities is thus an important part of societal evolution.

Cámara-Payno, A., DíezHernández, J., Novak, M. and Temiño-Santamaría, E. (2024) 'The attitude towards corruption in the EU under a gender perspective', European J. International Management, Vol. 22, No. 2, pp.254–280.
DOI: 10.1504/EJIM.2024.135934

A study in the International Journal of Human Rights and Constitutional Studies has explored the various factors that might contribute to procrastination among female university students.

For many people, it can take a lot of willpower or the threat of some kind of penalty to ensure they keep themselves on track in terms of studying and working rather than finding alternative, unrelated activities with which to distract themselves from the task at hand. S. Chandni, V. Sethuramalingam, and N. Rajavel of the Department of Social Work at Bharathidasan University in Tamil Nadu, India, have investigated procrastination among 277 female university students living in university hostel-type accommodation. They utilized statistical analyses such as cross-tabulations, one-way ANOVA, t-tests, and Step-wise Regression to process data about the use of social media, mobile phones, and demographic factors on procrastination.

The team found that the age of the students significantly affected how much they procrastinate. Younger students were more prone to delaying tasks on which they were purportedly focused. Additionally, the number of years someone had been studying was also a factor that influenced procrastination. The longer a student had been at university the more inclined were they to procrastinate. Perhaps more intriguingly, family income was identified as a contributing factor. A higher level of procrastination among the students was associated with lower family incomes.

Less surprisingly, perhaps, was that the team found a direct correlation between time spent on social media and the degree of procrastination. Given that social media has become a ubiquitous distraction for so many people it is perhaps not surprising that young students succumb to its whiles just as do so many other people. Those students with dual-SIM phones displayed a greater degree of procrastination than those with single-SIM devices. Why that should be is not entirely clear, except perhaps to say that high-end phones and the choice to have a dual-SIM device may well be associated with a greater degree of "tech savvy" and an inclination to enjoy the functionality of more sophisticated devices.

Procrastination among students, and others, linked to social media use specifically, poses a challenge for educators, and in the wider world, perhaps employers, where it might be detrimentally affecting academic performance, personal growth, and even job prospects.

There is perhaps now a need for policymakers and healthcare professionals to look at this particular aspect of social media activity and to find novel ways to support students, and others, in overcoming what might be considered a problematic addiction in circumstances where it is seriously detrimental to the individual user, their education and their life prospects.

Chandni, S., Sethuramalingam, V. and Rajavel, N. (2024) 'Right to good mental health: procrastination and social media addiction among girl students', Int. J. Human Rights and Constitutional Studies, Vol. 11, No. 1, pp.99–112.
DOI: 10.1504/IJHRCS.2024.136091

A study in the International Journal of Shipping and Transport Logistics has introduced a new Shipping Industry Risk Sentiment Index (SRSI). This tool has been designed to analyse sentiment in the news media concerning South Korea's shipping industry. The SRSI utilizes an innovative method involving text analysis of news articles from Korean newspapers, focusing on terms related to the six C's of credit – character, capacity, capital, company, conditions, and collateral.

Sunghwa Park of Gyeongsang National University in Gyeongsangnam-do, Hyunsok Kim of Pusan National University in Busan, Janghan Kwon and Taeil Kim of the Korea Maritime Institute in Busan, South Korea, explain how the index can reveal spikes in financial risk sentiment. The team employed statistical models such as the autoregressive distributed lag (ARDL) model and impulse response functions. They found that increased news reporting associated with global financial crises and court receiverships of major Korean shipping companies are associated with these spikes.

The research highlights the predictive capabilities of the SRSI. It not only reflects risk sentiment within the shipping industry but also provides valuable insights into market situations. The SRSI's forecasting capabilities can be used to analyse the impact of risk sentiment on maritime transport freight income. The results indicate that the SRSI serves as a statistically significant predictor variable for freight income, demonstrating its usefulness in detecting credit risk in advance. These findings align with a broader trend emphasizing the positive impact of shipping sentiment indices on freight rates.

The research is underpinned by the powerful concept of big data analysis which allowed the team to measure credit risk in the shipping industry. The proposed SRSI could become an invaluable tool for government authorities, assisting in the management and supervision of risk within the shipping market and helping with decision-making. The same approach might be extended to the wider global shipping industry. This could be especially important given the interconnected nature of the shipping industry. There is thus potential for creating a Global Shipping Market News Index.

Park, S., Kim, H., Kwon, J. and Kim, T. (2023) 'Construction of Korean Shipping Industry Risk Sentiment Index using news articles', Int. J. Shipping and Transport Logistics, Vol. 17, No. 4, pp.469–486.
DOI: 10.1504/IJSTL.2023.136047

Writing in the International Journal of Networking and Virtual Organisations, a team from China has revealed a novel approach to boost privacy for cross-border e-commerce users. Na Wang, Feng Gao, and Ji Zhang of Changchun University of Architecture and Civil Engineering in Changchun introduce an encryption algorithm based on social network analysis. The new approach could help users remain secure when transferring sensitive information during international transactions.

The team has used a multi-faceted strategy. Initially, they used a logical inference mapping method for blockchain to encode both public and private keys with asymmetric encryption. Next, the social network analysis method reorganizes the user's social network structure using arithmetic coding and homomorphic encryption.

Social network analysis can be used to study social structures and relationships among entities whether these are individuals, organizations, or any other units with connections or interactions. Such an analysis focuses on mapping and measuring the various relationships to understand the patterns within the network. This approach allowed the streamlining of the user information fusion processing and the optimization of the encryption tool.

The team carried out simulations to highlight their method's anti-attack capabilities and efficiency in terms of how little time is required for the encryption process. The team's work thus introduces an optimized privacy protection model for cross-border e-commerce users, incorporating encryption and optimized encoding designs through grouping information reorganization and chaotic sequence control, the team reports. A notable feature is that the adoption of dual keys improves the system still further while simplifying key construction and optimising the design of the encryption algorithm.

The researchers explain that the implementation of this encryption approach could be used for internal data protection and cross-border payment security within enterprises. It is important to have strong data security and confidentiality in these areas. The next step is to explore and test the system in real-time settings.

Wang, N., Gao, F. and Zhang, J. (2023) 'Privacy information encryption for cross-border e-commerce users based on social network analysis', Int. J. Networking and Virtual Organisations, Vol. 29, Nos. 3/4, pp.312–327.
DOI: 10.1504/IJNVO.2023.135961

Progress has been made recently in carbon capture technology that might allow us to efficiently absorb carbon dioxide directly from the air and perhaps halt the rise of atmospheric concentrations of the greenhouse gas. The development of moisture swing sorbents as a technology in this area is discussed in the International Journal of Global Warming. The benefit when compared with conventional approaches is that such sorbents use water as their primary energy source and so themselves can be carbon neutral in mitigating climate change.

Conventional moisture swing sorbents, or humidity swing sorbents, can adsorb or desorb water vapour from the atmosphere. These materials "swing" from one behaviour to the other reversibly depending on humidity or moisture levels. Moisture swing sorbents used for carbon dioxide capture sees related materials adsorb carbon dioxide from their surroundings when they are dry but when they get wet, they release, or desorb, the gas.

Weishu Wang, Xiangxin Zhang, Jun Liu, Chenyang Liang, Jingzun Niu, and Feiyue Wang of the North China University of Water Resources and Electric Power in Henan, China, have reviewed research in this area spanning more than two decades. They focus their review on how the adsorption capacity of moisture swing sorbents for large-scale applications might be reviewed. The team looked at how sorbents have been prepared. They also identified the various factors that affect carbon dioxide adsorption and desorption performance.

Materials for moisture swing sorbents fall into two categories: resin and non-resin materials. While resin materials offer faster adsorption rates and are easier to prepare, non-resin materials offer greater carbon dioxide adsorption capacity. The review suggests that the reliance on resin materials is currently a limitation which suggests that there is an urgent need for diversification in materials choice.

The application of carbon dioxide adsorbents is not limited to atmospheric absorption. There are many closed environments, such as submarines and spacecraft, and enclosed crop production environments where the level of carbon dioxide needs to be controlled precisely.

The review suggests that moisture swing sorbents represent a promising avenue for carbon dioxide capture. Ongoing research will help diversify raw materials, lead to the optimisation of preparation methods, and explore innovative technologies for enhanced performance and broader applications, as well as in addressing climate change.

Wang, W., Zhang, X., Liu, J., Liang, C., Niu, J. and Wang, F. (2024) 'Review of moisture swing sorbents for carbon dioxide capture from ambient air', Int. J. Global Warming, Vol. 32, No. 2, pp.119–147.
DOI: 10.1504/IJGW.2024.135979

Streaming video services are rapidly displacing the traditional ways in which people watch television. Consumers want immediate access to shows and movies rather than patiently waiting for a broadcaster to schedule the programming they desire. Researchers in Egypt have surveyed the streaming video landscape, more formally known as the Subscription Video-On-Demand (SVOD) sector, and found it to now be taking centre stage in the evolving entertainment landscape.

Writing in the EuroMed Journal of Management, Neveen Badr of Nile University, and Sayed Sharaf and Abeer A. Mahrous of Cairo University in Giza, Egypt, explain how the shift in the consumption of programming is seeing traditional television use dwindling in many places. As it does so, the multi-billion-dollar SVOD market continues to expand with the likes of Disney+, Amazon Prime, Apple TV+, Netflix, perhaps the most prominent proponents although many other services are vying for consumer attention and consumer subscriptions. The research looks closely at this global expansion but also focuses on the industry in Egypt where the "Watch It" streaming service is becoming well-known.

Demographically, SVOD services find favour primarily among Generation Y (the so-called Millennials who were born roughly between 1981 and 1996) and Generation Z (the "Zoomers" born around 1997 to 2012) in markets like Egypt. Understanding their preferences is crucial for both local startups like Watch It and the internationally renowned industry leaders such as Netflix, prompting tailored content for different demographics. The study highlights the importance of customer choice and financial analysis in efforts to understand the streaming market.

Badr and colleagues point out that the ability of the larger streaming companies to weather a crisis like the pandemic, and perhaps even thrive, highlights their resilience and adaptability to changing consumer demands. However, society is changing, technology evolves, new players come and go, and even the political landscape can have an economic significance on how the SVOD industry changes. Moreover, where a crisis like the pandemic benefited those companies offering services that consumers could use at home during lockdowns, for instance, there may well be changes afoot in the ranking of the various players in the streaming market as demands become sharpened in the post-pandemic world.

Digital transformation and developing technology, changes in audience perception and demands, pricing strategies, subscription models, and content initiatives are all now emerging as key considerations for any streaming company hoping to compete in this still-burgeoning market. Most important, however, is to understand customer needs and behaviour. This would allow established companies to plan strategically for their ongoing success. But also allow competitors to emerge, grow, and provide increasingly tailored offerings to consumers.

Badr, N., Sharaf, S. and Mahrous, A.A. (2024) 'Streaming wars: an analysis of the growth and competitive landscape of the subscription video-on-demand services market', EuroMed J. Management, Vol. 6, No. 1, pp.23–41.
DOI: 10.1504/EMJM.2024.135992

A recent study focusing on European Structural and Investment Funds (ESIF) could help improve fraud detection by identifying key indicators at the national level across the European Union, EU. The findings, published in the European Journal of International Management cover the period 2014 to 2020 and involved analysing data from 454 funds across all of the then extant 28 EU member states.

Thomas Baumgärtler and Philipp Eudelle of Offenburg University in Offenburg, Germany and Jorge Gallud Cano of the Universidad de Valladolid in Valladolid, Spain used an original database and employed regression analyses across EU member states to look for correlations between fraud detection rates and indicators related to fund utilization and monitoring, the frequency of fraudulent irregularities, economic development levels, and transparency within the nation.

The findings highlight the significance of vigilant fund monitoring to help combat fraud. In particular this, the team says, is more viable in those nations with the highest Gross Domestic Product (GDP) and transparency levels. Interestingly, they observed a decrease in irregularities in countries with elevated GDP and those receiving larger funds. However, there are considerable variations in fraud and fraud detection rates among individual states, with federal states like the Federal Republic of Germany demonstrating relative success in detecting fraud within EU funds.

The researchers explain that efforts to combat fraud and protect the financial interests of the EU, must involve collaboration between the EU itself and its member states. Indeed, a "multi-eye" principle in control is essential and the team emphasizes that this coupled with a zero-tolerance policy is the most efficient way forward in combating fraud and corruption.

However, despite the availability of tools such as anti-corruption reports from the European Commission, audit reports from the European Court of Auditors, as well as the existence of the anti-fraud office known as "OLAF" (Office Européen de Lutte Antifraude), during the period investigated, the team found significant differences in understanding of fraud detection between EU member states.

Fundamentally, the research findings underline the importance of closely monitoring funds, especially in economically advanced and transparent countries. The work points to how the European Commission might improve its overseeing of fund management among member states.

Baumgärtler, T., Eudelle, P. and Gallud Cano, J. (2024) 'An international analysis of fraud detection in European structural and investment funds', European J. International Management, Vol. 22, No. 2, pp.198–229.
DOI: 10.1504/EJIM.2024.135943

Researchers in Switzerland have taken a close look at the marketing strategies of several small and medium-sized enterprises (SMEs) in the information and communications technology (ICT) sector there. Their findings, published in the International Journal of Technology Marketing, are based on a literature review and interviews with managers from 14 such SMEs. The team hoped to unravel how Swiss SMEs define their marketing strategies in the digital era, the role of digital transformation in customer value, and to identify new strategies to help them circumvent common problems.

Mona A. Meyer of Lucerne University of Applied Sciences and Arts HSLU in Lucerne, Switzerland, Marc K. Peter of the University of Applied Sciences and Arts Northwestern Switzerland FHNW in Olten, Switzerland explain how their investigation has brought to light some interesting patterns. They explain how micro-enterprises appear to recognize the relevance of marketing strategies in digital transformation but display a limited focus on the customer.

By contrast, small enterprises orientate their marketing strategies towards external factors in order to adapt to the business landscape in which they find themselves. Medium-sized enterprises, on the other hand, recognise the importance of digital marketing to attract new customers and generally take a more customer-oriented strategic marketing approach.

Based on the team's review and interviews, the team suggests possible ways to formulate marketing strategies tailored to the evolving marketing landscape in the Swiss ICT sector. They concede that all of the findings may not be universally applicable across industries but broadly underscore various points such as the finding that targeting customer segments digitally and optimizing usability and processes are imperative for success among Swiss SMEs in the ICT sector. Paradoxically, the study revealed despite any given SME successfully adapting to digitalization there are only limited improvements with respect to customer loyalty. However, SMEs across all size ranges do report other tangible benefits such as more efficient processes, cost reduction, and enhanced data transparency.

Meyer, M.A. and Peter, M.K. (2024) 'Evolving marketing strategies for Swiss SMEs in the ICT sector: a marketing strategy canvas in support of digital transformation', Int. J. Technology Marketing, Vol. 18, No. 1, pp.91–112.
DOI: 10.1504/IJTMKT.2024.135672

In the ever-changing landscape of smart city innovation, researchers have introduced the Residual Spatial-Temporal Graph Convolutional Neural Network (RST-GCNN), which could help users find an on-street parking space more efficiently. This new model could help change the urban driving experience and perhaps reduce congestion and pollution by enhancing the prediction of parking availability. As cities grapple with escalating congestion, pollution, and the perpetual quest for efficient urban living, artificial intelligence (AI) could be set to ease one of the daily struggles for drivers and perhaps help us navigate out of gridlock.

Neural networks, inspired by the structure of the human brain, are used increasingly in solving complex problems across diverse domains such as image and pattern recognition, medical diagnostics, natural language processing and translation, and speech recognition. The RST-GCNN discussed in the International Journal of Sensor Networks represents a sophisticated application of neural network technology tailored to address the ever-present urban challenge of parking availability.

Unlike conventional models, the RST-GCNN integrates a residual structure, efficiently combining spatial and temporal information derived from graph and convolution modules, according to its developers Guanlin Chen, Sheng Zhang, Wenyong Weng, and Wujian Yang of Hangzhou City University, in Hangzhou, China. The RST-GCNN can predict long-term parking occupancy rates by discerning patterns in the parking dataset.

The team has tested their approach on the real-world Melb-Parking dataset and were able to validate the system's efficacy. It has, the work suggests, superior performance in predicting parking occupancy rates compared to baseline models. The new approach holds great promise for city drivers and could be used to streamline an automated parking search process, ultimately reducing congestion and optimizing transport efficiency in busy cities where cars remain a mainstay of transportation.

In the future, the team will expand the application to larger parking datasets with a view to refining prediction accuracy still further. Future iterations will embed weather, temperature, holiday periods, and other vagaries of traffic and parking thus broadening its scope and applicability.

Chen, G., Zhang, S., Weng, W. and Yang, W. (2023) 'Residual spatial-temporal graph convolutional neural network for on-street parking availability prediction', Int. J. Sensor Networks, Vol. 43, No. 4, pp.246–257.
DOI: 10.1504/IJSNET.2023.135840

A study in the International Journal of Nanotechnology has looked at the controlled synthesis and coating of magnetic nanoparticles (MNPs), specifically using oleic acid (OA) and polyethylene glycol (PEG). These two well-studied polymers can be used in a co-precipitation approach to produce MNPs, which can be coated with different ratios of the two polymers to give different nanoparticle characteristics.

Magnetic nanoparticles can have many roles in medicine from targeted drug delivery and cellular tracking to serving as contrast agents in medical imaging, facilitating delivery of gene therapy agents, aiding in radiotherapy, and contributing to innovative hyperthermia treatments.

Nur Khalida Rahayu Zainon, Che Azurahanim Che Abdullah, and Mohd Basyaruddin Abdul Rahman of the Universiti Putra Malaysia in Selangor, Malaysia, used various characterization tools to study their coated nanoparticles. These techniques included X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and vibrating sample magnetometry (VSM). Each technique can be used to investigate chemical structures in different ways offering disparate and detailed information about the coated MNPs including structural, optical, and magnetic properties.

The team has highlighted the optimal concentration ratios for coated MNPs and demonstrated how excessive levels of coating might impede the nanoparticle targeting capabilities. Conversely, insufficient coating can lead to unwanted aggregation of the nanoparticles. Magnetic saturation is reduced slightly in coated particles because the coating itself if non-magnetic, however, the coatings add several desirable properties, such as providing a protective and biocompatible shell around the magnetic nanoparticle as well as allowing functional biological agents and therapeutics to be attached to the nanoparticles in a way that is not easy to do with naked magnetic nanoparticles.

As the field advances, considerations such as the type of MNPs, nanoparticle shape, synthesis methods, particle size distribution, biocompatibility, and particle-particle interactions will emerge as critical factors in their development for biomedical applications. The present research enhances our understanding of MNP synthesis and coating and offers useful insights into their potential in nanomedicine.

Zainon, N.K.R., Che Abdullah, C.A. and Abdul Rahman, M.B. (2023) 'Assessment of different organic coatings on magnetic nanoparticles for biomedical applications', Int. J. Nanotechnol., Vol. 20, Nos. 11/12, pp.965–979.
DOI: 10.1504/IJNT.2023.135810

A study in the International Journal of Business Competition and Growth has drawn insights from 621 survey samples to help improve our understanding of what elements of viral videos affect consumer behaviour and purchasing decisions the most. The elements highlighted include entertainment, brand awareness, source credibility, informativeness, interactivity, and incentives.

A viral video is a piece of content, typically a short video clip, that spreads rapidly and widely across the internet through social media sharing. The term "viral" in this context refers to the video's ability to quickly accumulate a large number of views, likes, shares, and comments, often reaching a massive audience in a short period.

Nguyen Hong Quan, Hoang Thi Hong Nga, Nguyen Thi Hai Ha, Pham Phuong Hien, Truong Nguyen Yen Thanh, and Nguyen Thi Kieu Trang of the Foreign Trade University in Hanoi, Vietnam, suggest that their research underscores the significance of entertainment in viral videos. It correlates higher entertainment levels with positive consumer attitudes. This aligns with earlier studies that also highlighted the role of entertainment value in influencing consumer perceptions, especially in emerging marketing channels like mobile advertising. The team also found that brand awareness, coupled with source credibility, is influential in shaping positive consumer attitudes, emphasizing the importance of reputation and recognition in today's information-driven consumer landscape.

The study also identified gender-based differences in the impact of various factors in viral videos. They thus suggest that marketing needs to consider nuanced strategies across genders. They found that males respond well to entertaining and trustworthy content, while females prefer informative videos with attractive offers and positive product feedback.

Additionally, however, brand awareness not only influences consumer attitudes positively but can boost advertising effectiveness on social platforms. Viral videos thus act as dual agents, impacting consumer behaviour and contributing to brand image, thereby bolstering brand equity.

The team offers various practical recommendations for businesses hoping to gain marketing advantages using viral videos in their advertising campaigns. They emphasise that by incorporating entertainment, informativeness, incentives, and source credibility into their strategy they can nudge consumers to engage more with their brand and ultimately purchase their products or services. Conversely, they advise businesses not to exaggerate their content and to ensure it is as authentic as possible. Businesses might collaborate with credible experts or consumers for genuine product reviews, and embed brand information strategically without overwhelming consumers to this end.

Quan, N.H., Nga, H.T.H., Ha, N.T.H., Hien, P.P., Thanh, T.N.Y. and Trang, N.T.K. (2023) 'How do viral videos on social media affect purchase intention?', Int. J. Business Competition and Growth, Vol. 8, No. 3, pp.202-222.
DOI: 10.1504/IJBCG.2023.135805

In a recent study examining the accuracy of self-estimation in evaluating technology use, researchers analyzed data from more than 300 iPhone users in China. The findings indicate a moderate correlation between self-reported usage and actual screen time. However, a notable finding is that the longer individuals engage with social media or smartphones, the less accurate their self-reporting of use becomes.

Self-estimation refers to an individual's subjective assessment or perception of their behaviour. In the present study, published in the International Journal of Mobile Communications, it refers specifically to the use of smartphones and social media.

Gefei Li and Jialong Li of Waseda University in Tokyo, Japan and E. Qinyu of the University of Shanghai for Science and Technology and Xia Li of Shanghai Jiaotong University in Shanghai, China, have examined the psychological factors influencing the precision of recall of smartphone and social media use. The team found that loneliness is one factor that correlates with discrepancies in estimating social media use, suggesting that the lonelier an individual feels, the more they overestimate their use. Conversely, those who reported greater life satisfaction were less likely to underreport their actual smartphone use. Fundamentally, the study suggests that as individuals spend more time on smartphones and social media, the reliability of their self-reporting of how long they spend on them diminishes.

The team suggests that one practical implication of these findings is that researchers should be questioning the adequacy of traditional self-reporting measures for assessing how much we use these digital technologies.

The team recommends a standardized time perception approach, which could challenge the common practice of subjective time measurement in studying behaviour. The researchers also introduce the concept of "Screen Time", which could be used to provide a more accurate measure of smartphone usage and so mitigate underreporting. This tool could offer valuable data for researchers studying the impacts of digital technology use on our digital habits.

The findings and implications of this study may well extend beyond the immediate results, suggesting that screen time reports could be a valuable resource for researchers in communication studies, cognitive psychology, and neuropsychology. By adopting a more precise measurement approach, researchers might gain a deeper understanding of the implications of digital technology use on our lives or at the very least glean more accurate data than self-estimation might offer so that future studies can give us clearer results.

Li, G., Qinyu, E., Li, J. and Li, X. (2024) 'What influences our recall of the use of social media and smartphones? An exploratory study based on a sample of Chinese iPhone users', Int. J. Mobile Communications, Vol. 23, No. 1, pp.24–42.
DOI: 10.1504/IJMC.2024.135696