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  • Research in the International Journal of Computational Systems Engineering has looked at the challenges facing online education systems in terms of improving efficiency and avoiding redundancy in cloud computing platforms. Muchao Zhang of Nanjing Xiaozhuang University, China, offers a new approach to integrating educational data from various sources, models, and formats, all with the aim of improving cloud the efficiency.

    Zhang shows how cloud platforms, known for their scalability, flexibility, and security, have already become an essential component of online education. However, the diverse nature of educational data, video lectures and digital textbooks, for instance, creates problems. Different data formats and structures can lead to redundancy, confusion, and inefficient allocation of computing resources. This then reduces the potential for the educational content to be as streamlined as possible.

    To address this, Zhang has developed an approach that combines algorithms to help integrate the disparate data types. The various algorithms can each resolve a different issue associated with data integration. For example, the PMI-Simhash algorithm helps identify similarities between data sets, the BSM model aids in classifying the information more accurately, and the US-EM algorithm improves the matching of entities across different systems without needing manual intervention. The result is an integrated approach that minimizes redundancy and ensures that educational resources are much better organized than they otherwise would be.

    Zhang has how these algorithms can work together using an online painting course for art students. The approach merges multimodal data, text, images, and video, and proved highly effective in terms of accuracy, speed, and resource usage. By improving the accuracy of data matching, Zhang's approach could ensure that students access the right resources at the right time, improving both the learning experience and resource management.

    Zhang, M. (2025) 'Online education resource integration method for painting teaching of art majors based on cloud platform', Int. J. Computational Systems Engineering, Vol. 9, No. 5, pp.1–10.
    DOI: 10.1504/IJCSYSE.2025.144358

  • A team from India, Netherlands, Poland, and Switzerland has looked at how to improve data analysis and to reduce the inherent bias in social network analysis. Writing in the International Journal of Applied Management Science, the researchers recognise that in quantitative surveys and social network analysis, the accuracy of data can often be skewed by biases in how respondents answer the questions. One particular form of bias, known as declarative bias, poses a significant threat to the reliability of survey results, particularly when addressing complex social issues.

    Declarative bias occurs when survey participants, consciously or unconsciously, provide answers influenced by social expectations, fatigue, or external pressures rather than reflecting their true attitudes or beliefs. This type of bias is particularly problematic when the research seeks to inform public policy, as it can lead to misleading conclusions about society's attitudes and behaviour and thus inappropriate policies.

    Response time testing could offer an answer. The assumption is that a more immediate response tends to reflect a stronger, more internalized opinion, while a slower response may reflect uncertainty or a response swayed by external factors, such as social desirability or reading into the questions themselves to work out what the right answer might be. By distinguishing between these types of responses, the researchers suggest that it might be possible to segregate strong answers from the flimsy.

    They tested their approach on an international survey conducted in Spain and Sweden to explore attitudes toward the COVID-19 pandemic. Their results were striking. By homing in on high-confidence, fast responses, the team could see a much greater diversity of opinion. By contrast, a conventional analysis, where declarative bias was present, showed much more homogeneous opinions.

    The findings have implications for public policy and health interventions based on surveys of the public or stakeholders on a given topic. For instance, public health policies based on the assumption of uniform public opinion on issues such as the pandemic might fail to address the subtleties of diverse opinions from different groups. By reducing declarative bias in the analysis of surveys, it should be possible to form policy that takes into account diverse opinions and needs.

    Fernandez, G.P., Norré, B.F., Reykowska, D., Dutta, K., Nguyen-Phuong-Mai, M., Fernandez, J. and Ohme, R. (2024) 'Social network of confident attitudes with response time testing', Int. J. Applied Management Science, Vol. 16, No. 5, pp.1–31.
    DOI: 10.1504/IJAMS.2024.144419

  • Research in the International Journal of Shipping and Transport Logistics has looked at the environmental sustainability of the Yangtze River Economic Belt (YREB) and raises important points about the region's ability to balance rapid economic growth with ecological preservation. Zhimei Lei, Shanshan Cai and Shaoxin Zhuo of Kunming University of Science and Technology, Yui-yip Lau of The Hong Kong Polytechnic University, and Ming Kim Lim of the University of Glasgow, UK, explain that the YREB encompasses eleven provinces and cities. The region thus plays a pivotal role in the national economy of China. However, its development has often been marred by significant environmental challenges, such as pollution, resource depletion, and ecological degradation.

    The team examined almost two decades of data on sustainability levels across the YREB, using an innovative evaluation framework and a "pressure-state-response" (PSR) model. This latter tool allowed the team to link environmental pressures to the condition of the environment and the responses to the problems set in motion by policymakers. As such, the work integrates both qualitative indicators, such as government policies and key speeches, and quantitative data, making it particularly well-suited for the complex realities of the YREB.

    Improving environmental sustainability over the study period could be seen in the data with the middle and upper regions of the YREB showing the most progress. However, the research also showed that there are persistent regional disparities. The lower regions of the YREB, in particular, lag behind in terms of environmental sustainability, which could have long-term implications for the overall ecological health of the area. Moreover, despite some obvious progress, there is no clear improvement in sustainability levels even between neighbouring provinces.

    This, the researchers suggest, implies that effective collaboration across the YREB is not occurring. The team explains the disparities as perhaps being due to a combination of intra-regional and inter-regional factors: levels of industrialization, policy implementation approaches, and investment in green technologies. The implication is that there is a pressing need for more coordinated action between the YREB's provinces and cities. The team adds that the creation of a platform for sharing environmental data and research could be used to improve governance and decision-making across the whole region.

    Lei, Z., Cai, S., Zhuo, S., Lau, Y-y. and Lim, M.K. (2024) 'Analysis of the differences and spatial-temporal dynamic evolution of the environmental sustainability of the Yangtze River Economic Belt in China', Int. J. Shipping and Transport Logistics, Vol. 19, No. 5, pp.1–41.
    DOI: 10.1504/IJSTL.2024.144404

  • Research in the International Journal of Economics and Business Research has looked at the relationship between employee empowerment and job satisfaction, with a particular focus on the banking sector in Greece. As digital technologies reshape the modern workplace, are traditional concepts of empowerment being put to the test, the study asks. George Papageorgiou, Kyriakos Christofi, Aikaterini Gelinou, Andreas Efstathiades, and Elena Tsappi of the European University Cyprus in Nicosia, Cyprus, found which strategies can boost job satisfaction in an increasingly digitalized environment and offer managers insights for navigating this transformation.

    The team identified four important empowerment practices that apparently contribute positively to an employee's level of job satisfaction. First, a well-defined organizational mission, combined with performance-based rewards, strengthens how much the employee aligns themselves in a positive way with company goals, thus giving them more of a sense of purpose. Secondly, organisations that allow employees a degree of autonomy in decision-making gives them a sense of so-called ownership over their role. This too increases engagement and involvement in the organisation's success. Thirdly, by delegating certain managerial responsibilities to lower-level employees, an organisation can promote a sense of trust and accountability even in more junior employees. Finally, effective communication between departments ensures that employees feel informed and supported by the organisation and their colleagues above and below them in the hierarchy.

    However, the team also found that problems can arise when there is excessive standardization. While consistency and efficiency are important to success within an organisation, overly rigid structures can stymie initiative and limit career growth opportunities. The team suggests that as workplaces become more digitalized, organisations must find the right balance between structured processes and allow sufficient flexibility to encourage innovation and employee development.

    The team adds that job-enrichment strategies, such as decentralization, team-based collaboration, and the use of digital tools, can boost engagement and job satisfaction. Specifically, with regard to the latter, technologies that allow flexible work arrangements and facilitate communication across different locations can improve engagement and satisfaction.

    Papageorgiou, G., Christofi, K., Gelinou, A., Efstathiades, A. and Tsappi, E. (2025) 'Employee empowerment and job satisfaction in the evolving digital banking workplace', Int. J. Economics and Business Research, Vol. 29, No. 8, pp.41-60.
    DOI: 10.1504/IJEBR.2025.144288

  • Electronic waste, including PCBs, is a rapidly growing problem as consumers endlessly replace their electronic gadgets. Regulations can go so far to nudge this waste into a recycling stream, but there is still the pressing need for the technology to process the waste.

    The retrieval and extraction of useful metals from electronic waste will be a critical part of creating a sustainable future if that is to be technology led. Many metals are relatively rare or found only in geopolitically sensitive regions of the world. More to the point, we have tonnes of discarded devices, circuit boards, and wiring sitting in recycling dumps and landfills. If there were a simple way to extract metals, such as copper, from these resources, that use less energy and fewer resources than mining the ores, then that would offer us a more environmentally friendly option to sourcing copper.

    Jayashree Mohanty, Puspita Biswal, Subhashree Subhasmita Mishra, and Tamasa Rani Das Mohapatra of the C.V. Raman Global University in Bhubaneswar, Odisha, India, have now demonstrated an approach to extracting copper from printed circuit boards that does not require the PCBs to be dismantled. Their approach, reported in the International Journal of Environmental Engineering, uses pieces of chopped up PCBs as one electrode in an acidic solution, the electrolyte, with the other electrode is a stainless steel plate. By passing an electric current through the electrodes and the solution it is possible to dissolve the copper as positive ions into the solution. The current then drives these ions towards the negative electrode, the steel plate, where they are deposited as metallic copper. This copper plating can be readily removed from the steel electrode.

    This simplified electrochemical copper extraction process avoids the usually energy-intensive mechanical shredding or chemical leaching process used in recycling and so uses less energy overall as well as minimizing processing waste and chemical pollutants. It thus has the potential to extract copper from the electrical waste stream much more effectively than was previously possible.

    The team add a not-so-secret sauce to their copper extraction recipe, a salt called sodium sulfate. This substance, added to the electrolyte, buffers the solution and at a certain concentration improves the current density and efficiency increasing the amount of copper dissolved from the PCBs and deposited on to the steel cathode. The researchers found that a concentration of 0.03 molar sodium sulfate gave them the highest current efficiency, at 77%, However, the highest copper purity (99%) was obtained at 0.02 molar. There will thus be a compromise in process efficiency and retrieval rates using this additive.

    Mohanty, J., Biswal, P., Mishra, S.S. and Mohapatra, T.R.D. (2025) 'Electrochemical recovery of copper from the waste computer printed circuit board', Int. J. Environmental Engineering, Vol. 13, No. 1, pp.1–11.
    DOI: 10.1504/IJEE.2025.143562

  • Research in the International Journal of Information and Communication Technology has examined the relationship between local government debt and economic growth. Lian Pan of Hunan International Economics University in Hunan, China, used the Panel Smooth Transition Regression (PSTR) model to analyse data in combination with a federated learning data enhancement algorithm. Pan could thus explore how different economic structures influence the effects of borrowing. The findings suggest that while local government debt can support growth, its impact depends on the structure of the local economy. This raises important questions for policymakers.

    One of the findings from the research is that industrial composition can shape the outcomes of government borrowing. In areas with well-established industries, debt-financed investment can contribute to economic expansion. However, in less diversified economies, the benefits are less obvious. Indeed, debt may place additional strain on financial resources. The research indicates that simply managing the level of debt is not enough, it is equally as important to define clearly the allocation of borrowed funds.

    The findings come at a time when many local governments are facing increasing financial pressures. Economic shifts, rising borrowing costs, and "changing revenue structures" have made fiscal planning even more complex than it was ever before. Some authorities, facing shortfalls, turn to less sustainable sources of revenue, such as land sales or off-budget financing. The study highlights the risks associated with such approaches and stresses the need for greater transparency and more structured debt management practices.

    It is worth noting, that the use of federated learning, a machine learning method, has allowed for more precise analysis while maintaining data privacy. By integrating this approach with the PSTR model, Pan's work has enhanced our ability to assess financial relationships without exposing sensitive information. The method could be further refined through vertical federated learning. This would account for variations in the data distribution across different regions. Addressing these differences could improve the accuracy of economic models and their application to policymaking.

    Pan, L. (2024) 'Correlation analysis between local government debt and economic growth combined with PSTR model', Int. J. Information and Communication Technology, Vol. 25, No. 9, pp.22–42.
    DOI: 10.1504/IJICT.2024.143319

  • Facial emotion recognition could have broad applications across healthcare, education, marketing, transportation, and entertainment. It might be used to help monitor patients remotely or in over-stretched hospitals or emergency response settings, or patients unable to communicate well for any number of reasons. It could be used to personalize learning, allowing a computerised training system to respond more appropriately to the user. Similarly, such a system could improve customer service and might even be used to create immersive entertainment experiences.

    Computer systems that can identify emotions from our facial expressions are in development, but still face man challenges. The earliest systems relied on a single method, such as mapping a person's face and matching it to a database of annotated expressions. Some approaches based on this simplified method are more accurate than others, but none yet captures all the nuance of human emotion as it is expressed in our faces.

    Research in the International Journal of Biometrics introduces a new approach based on machine learning that could address this problem and make an emotion detector viable for a wide range of applications. The biggest issue that is addressed by the new work is that it can extract a complex emotion from real-world situations where environmental factors, incomplete data, or complex emotions might affect the accuracy of the results. However, the new approach brings together facial expression recognition and uses the person's speech and tone of voice or even what they might be writing to give a more accurate result.

    In their experiments, researchers Jian Xie and Dan Chu of Fuyang Normal University in Anhui, China, achieved a recognition accuracy of 98.6% with their approach. The system was particularly adept at identifying happiness or a neutral emotional state when compared with earlier systems. The system could not cope quite as well with the identification of disgust and surprise, however.

    Xie, J. and Chu, D. (2025) 'Character emotion recognition algorithm in small sample video based on multimodal feature fusion', Int. J. Biometrics, Vol. 17, Nos. 1/2, pp.1–14.
    DOI: 10.1504/IJBM.2025.143720

  • In an evolving job market shaped by technological disruption and changing industry demands, there is a pressing demands to ensure that higher education aligns with workforce needs. Research in the International Journal of Information and Communication Technology introduces a predictive model designed to address this issue. It offers an adaptable approach to talent demand forecasting and job matching. By integrating artificial intelligence (AI) with structured data analysis, the work of Xiaoli Mei of Jiangxi University of Technology in Jiangxi, China, offers an approach that could help educators, employers, and policymakers respond to labour market trends.

    Mei's work builds a knowledge graph, a structured representation of information, to organize and integrate vast amounts of data from online recruitment platforms. The new approach uses graph neural networks to spot relationships between various factors in the job market. This should improve understanding of the relationships between job requirements, candidate qualifications, and industry trends. This new model can process complex employment patterns with greater precision than earlier manual methods. Those earlier methods were limited to relying on rigid keyword-based systems that might overlook the broader context of job descriptions and skill requirements.

    The new model is armed with high fault tolerance, which means it is effective even when dealing with incomplete or inconsistent data. This will be invaluable in real-world applications, where missing or ambiguous information is common. By maintaining strong performance despite data gaps, the system offers a more reliable tool for workforce planning, recruitment, and career guidance.

    Ultimately, the research could help close the gap between higher education supply and employment demand. There is thus the potential to train undergraduates, particularly on more vocational courses, who might then be better prepared for industry roles. Policymakers will benefit from the research, as it will allow them to spot emerging skill demands and workforce trends, governments might then develop targeted labour market policies to address shortages in specific sectors. Additionally, jobseekers themselves might gain from more intelligent job recommendations, which will hopefully lead to better employment outcomes and reduced mismatches between their qualifications and the available jobs.

    Mei, X. (2024) 'Prediction of talent demand and job matching based on knowledge graph and attention mechanisms', Int. J. Information and Communication Technology, Vol. 25, No. 9, pp.76–87.
    DOI: 10.1504/IJICT.2024.143327

  • A study in the International Journal of Business Performance Management has looked closely at how digital marketing strategies have influenced business performance in Laos, especially among small and medium-sized enterprises (SMEs). The research focuses on tools such as online advertising, social media marketing, content marketing, and mobile marketing.

    Viengsavang Thipphavong and Xayphone Kongmanila of the National University of Laos in Vientiane, Laos, used a structural equation model (Smart PLS4) to analyse their data and found that online advertising has a clear impact on both financial and operational performance. Social media marketing, on the other hand, had an broader influence as it positively affects financial performance, operational efficiency, and a company's IT capabilities.

    The study showed that content marketing was linked primarily to improvements in the companies' IT infrastructure, while mobile marketing, while beneficial to operational and IT performance, did not directly impact financial outcomes. This has implications for smaller companies that might do better to not invest too heavily in the kind of digital tools that will not help them generate greater profits.

    The researchers suggest that businesses in Laos, SMEs in particular, should focus on using online advertising and digital marketing tools to improve their financial and operational performance. They add that government might play a role too by improving digital infrastructure, supporting online marketing education, and encouraging the growth of e-commerce. Such steps would, the team suggests, create a more favourable environment for businesses to adopt digital marketing strategies and enhance their overall performance.

    As digital tools become more accessible, companies in emerging markets such as Laos are increasingly able to reach wider audiences and streamline operations without incurring significant marketing costs. For Laos, where internet penetration and digital adoption are yet to mature, this presents a clear opportunity. As more people access the mobile internet, businesses have the potential to expand their customer base and improve operational efficiency with relatively modest investment.

    Thipphavong, V. and Kongmanila, X. (2025) 'The impact of digital marketing on the business performance of firms In Laos', Int. J. Business Performance Management, Vol. 26, No. 7, pp.1–22.
    DOI: 10.1504/IJBPM.2025.144089

  • An examination of Vietnam's financial sector for the period 1990 to 2022 provides empirical evidence of the relationship between banking development, trade openness, inflation, and economic growth. The findings, published in the International Journal of Economics and Business Research, suggest that a well-functioning banking system plays an important role in supporting economic activity. They also highlight some of the challenges facing developing nations associated with financial sector expansion in a globalized economy.

    Thao Huong Phan and Thao Viet Tran of Thuongmai University and Trang Mai Tran of the Vietnam Academy of Social Sciences, in Ha Noi, Vietnam, discuss how Vietnam's banking sector remains the dominant channel for capital allocation, given the relatively underdeveloped nature of its financial markets. Banks provide credit to businesses and individuals, facilitating investment and economic activity. Their research found a positive relationship between banking sector growth and economic expansion, both in the short and long term.

    Trade openness, defined as the extent to which an economy engages in international trade, has previously been linked to economic growth. By participating in global markets, businesses gain access to new customers, technologies, and competitive pressures that can improve their overall productivity and their bottom line.

    Of course, this kind of international exposure also comes with risks, particularly if domestic financial institutions are not well-equipped to manage the inevitable external shocks. The researchers suggest that Vietnam's banking sector needs to strengthen its ability to address such problems through improved risk management and regulatory oversight.

    Inflation, another key factor in economic stability, also plays a role in financial sector performance. While moderate inflation can signal a growing economy, excessive inflation undermines purchasing power and creates uncertainty for investors. The study suggests that sound monetary policy, including responsible credit expansion and liquidity management, will also be important in ensuring financial stability.

    As Vietnam continues to integrate into the global economy, its financial sector will need to adapt to new demands. Strengthening banking regulations, enhancing risk management practices, and ensuring adequate liquidity controls will be important in maintaining financial stability, the work suggests.

    Phan, T.H., Tran, T.V. and Tran, T.M. (2025) 'Banking development contributes to economic growth and inflation control in Vietnam', Int. J. Economics and Business Research, Vol. 29, No. 7, pp.1-16.
    DOI: 10.1504/IJEBR.2025.144102

News

European Journal of International Management announces 2024 Best Paper and Best Reviewer Awards

The European Journal of International Management's Editor in Chief and Outreach Editor, Associate Prof. Nicole Franziska Richter and Dr. Sven Horak, are pleased to announce the following 2024 Best Paper Awards:

The Editors congratulate the authors on their significant contributions to research in the field of international management.

The Editors are also pleased to announce the following winners of the Best Reviewer Awards, and thank them for their continued efforts:

  • Sang-Joon Kim, Ewha Womans University, Seoul
  • Ilaria Galavotti, Università Cattolica del Sacro Cuore, Piacenza
  • Sabrina Goestl, Western University, Canada
  • Dirk Morschett, University of Fribourg, Switzerland
  • Ursula F. Ott, Nottingham Trent University, UK
  • Thomas Rockstuhl, Nanyang Technological University, Singapore
  • Stefan Schmid, ESCP Europe Business School, Germany

International Journal of Data Mining and Bioinformatics is now an open access-only journal

We are pleased to announce that the International Journal of Data Mining and Bioinformatics is now an Open Access-only journal. All accepted articles submitted from 23rd January 2025 onwards will be Open Access, and will require an article processing charge of US $1600.

Prof. Renato Pereira appointed as new Editor in Chief of International Journal of Intellectual Property Management

Prof. Renato Pereira from the University of Lisbon in Portugal has been appointed to take over editorship of the International Journal of Intellectual Property Management.

Prof. Junfeng Xia appointed as new Editor in Chief of International Journal of Computational Biology and Drug Design

Prof. Junfeng Xia from Anhui University in China has been appointed to take over editorship of the International Journal of Computational Biology and Drug Design.

Prof. Andry Sedelnikov appointed as new Editor in Chief of International Journal of Mathematical Modelling and Numerical Optimisation

Prof. Andry Sedelnikov from Samara National Research University in Russia has been appointed to take over editorship of the International Journal of Mathematical Modelling and Numerical Optimisation.