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  • 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


Associate Prof. Marco Valeri appointed as new Editor in Chief of International Journal of Complexity in Leadership and Management

Associate Prof. Marco Valeri from Niccolò Cusano University in Italy has been appointed to take over editorship of the International Journal of Complexity in Leadership and Management.

Prof. Matti Muhos appointed as new Editor in Chief of International Journal of Management and Enterprise Development

Prof. Matti Muhos from the University of Oulu in Finland has been appointed to take over editorship of the International Journal of Management and Enterprise Development.

Prof. Tianliang Li appointed as new Editor in Chief of International Journal of Computer Aided Engineering and Technology

Prof. Tianliang Li from the Wuhan University of Technology in China has been appointed to take over editorship of the International Journal of Computer Aided Engineering and Technology.

Prof. Filippo Vitolla appointed as new Editor in Chief of International Journal of Financial Services Management

Prof. Filippo Vitolla from LUM University Giuseppe Degennaro in Italy has been appointed to take over editorship of the International Journal of Financial Services Management.

Editor in Chief invites submissions for the International Journal of Power and Energy Conversion

Dr. Abdessamad Didi, Editor in Chief of the International Journal of Power and Energy Conversion, cordially invites general submissions to IJPEC, particularly those that "empower tomorrow" by navigating the complex landscape of energy challenges and sustainable solutions.

Dr. Didi expands as follows:

"Today, the increasing demand for energy poses a significant challenge, and the effective utilisation of this energy requires a complex process involving several essential elements. This includes mobilising qualified human resources, establishing well-equipped structures and leveraging the knowledge and expertise of all involved stakeholders. The harmonious coordination of these diverse elements is crucial to ensuring the success of this endeavour.

From this perspective, power and energy conversion (whether thermal, nuclear, solar, etc.) play a central role. The mastery of these aspects is currently within our reach, allowing us to positively influence the future of energy management. This involves not only adopting cutting-edge conversion technologies but also implementing sustainable energy practices and policies.

Simultaneously, it is essential to consider all anomalies and potential challenges that may arise in this process. This requires constant vigilance and the implementation of adaptive correction mechanisms. The lessons learned from these experiences will contribute to continuously improving our practices and strengthening our resilience for future challenges.

Furthermore, one of the perspectives that generates significant interest is water production through seawater desalination. While this approach requires considerable power and energy, it offers a valuable solution to meeting the growing demand for drinking water. The ongoing development of more efficient and sustainable desalination technologies is therefore a strategic area for the future.

In summary, managing energy and power today requires a holistic approach, involving synergies among human resources, conversion technologies, continuous process monitoring and innovative initiatives such as seawater desalination. It is through a thorough understanding of these elements and consistent implementation that we can shape a more sustainable future for humanity on Earth. All of these aspects can have a profound impact on our success, and in this regard, we aim to contribute to the advancement of science through the International Journal of Power and Energy Conversion, and invite researchers to contribute to our journal to promote scientific progress and create a promising future."

You can visit IJPEC's homepage for more information on the journal and for guidance on how to submit articles.