Research in the International Journal of Business Information Systems investigates user perception of mobile device security and offers several recommendations for users and manufacturers of such devices.

Nelson Tochukwu Agu, Joshua Ebere Chukwuere, and Tlhalitshi Volition Montshiwa of North-West University in Mahikeng, South Africa, offer several alarming insights into awareness of mobile security issues among students in the region. Their primary finding from a survey of 142 students at NWU is that some students mistakenly believe that mobile phones are inherently secure and others do not realise that such devices can be less secure than traditional desktop or laptop computers. The work suggests that there is a need for increased vigilance and education regarding mobile device security.

The team also found that while most users have a basic understanding of mobile device security, many of them lack knowledge of even common threats such as viruses, worms, Trojans, and phishing attacks. The researchers believe that this knowledge gap is particularly troubling, as it implies a lack of vigilance in safeguarding mobile devices against these various threats. Many such threats could detrimentally affect the individuals involved, but many have much broader implications allowing the spread of malware to other users and for malicious third parties to compromise devices and so build networks, botnets, under their control for illicit purposes, such as distributed denial of service (DDOS) attacks on organisational and governmental networks, for instance.

The team also found that even those users who understand password protection, many of them neglect additional security measures such as encryption, PINs, patterns, or biometric authentication. They point out that users are happy to engage in risky behaviour, such as ignoring system security warnings, clicking on links or downloading attachments from unknown sources, as well as over-sharing personal information on social media platforms, which might be useful to a third-party hoping to carry an identity theft or in fraudulent activity, based on social engineering in which a confidence trick is played out on an individual or member of an organisation rather than an attack being technological in nature, such as hacking or cracking to break into and compromise a computer system.

The researchers suggest that education of users is critical to bolster mobile phone security, but they insist that device manufacturers should also bear responsibility in addressing this issue and should be proactive in this educational process.

Agu, N.T., Chukwuere, J.E. and Montshiwa, T.V. (2023) 'Understanding users' perceptions of security in mobile devices using the two-step cluster analysis', Int. J. Business Information Systems, Vol. 44, No. 1, pp.81–101.
DOI: 10.1504/IJBIS.2023.133513

A research study in International Journal of Behavioural and Healthcare Research has found a profound connection between the dynamics of the work environment and the widespread problem of burnout syndrome among professors in Brazilian academic institutions. The study considers six key facets of work life outlined by the areas of work life scale (AWS) – workload, control, reward, community, fairness, and values, and uses them to discern insights into their predictive potential of academic burnout.

The team of Adriana Porto (Lutheran University of Brazil), Luis Felipe Dias Lopes (Federal University of Santa Maria), and Claudimar Pereira da Veiga (Fundação Dom Cabral) used the Maslach Burnout Inventory General Survey (MBI-GS) tool, which they tailored and calibrated for the Brazilian context, to delve into the measurement of three distinct dimensions of burnout: exhaustion, cynicism, and efficacy.

The team used data from 558 professors to look at aspects of the work environment and its impact on burnout within Brazilian academia. The findings validate the assertion that understanding the six areas of work life can significantly influence how burnout manifests and evolves within this sector.

Burnout, while commonly used in the vernacular represents a complex syndrome characterized by chronic workplace stress that has not been effectively managed. It can lead to physical, emotional, and mental exhaustion. These problems, in turn, can lead to cynicism and detachment from one's work as well as a diminished sense of personal accomplishment and efficacy. Chronic burnout has far-reaching implications for those affected having a detrimental impact on well-being and physical health. It can also affect the workplace in which they find themselves leading to problems with productivity in the workplace, affecting those whom the workers serve. And, ultimately society at large and the wider economy, healthcare, education, and public services.

There is an urgent need for organizations to understand the multi-faceted nature of burnout and its connection with the work environment. Proactive measures addressing workload, control, rewards, community, fairness, and values can help create nurturing work environments that mitigate burnout risks. The research offers an invaluable roadmap for organizations to design interventions focused on enhancing employee well-being, and so fostering a healthier, more productive workforce and positively contributing to society more broadly.

Porto, A., Lopes, L.F.D. and da Veiga, C.P. (2023) 'Areas of worklife as predictors of the burnout syndrome', Int. J. Behavioural and Healthcare Research, Vol. 9, No. 1, pp.1–17.
DOI: 10.1504/IJBHR.2023.133535

Research in the International Journal of Enterprise Network Management reveals unexpected factors that influence an employee's intentions to quit their job in information technology. The findings challenge the received wisdom and could shed light on the dynamic role of online professional networking and social media profile updates.

There has been much research in employee intention to quit as it can have a significant impact on a wide range of organisations. Conventionally, researchers have focused on factors such as job satisfaction and organizational commitment. These are the standard key indicators that can help predict which employees might be planning to leave and so allow organisations to perhaps manage staff turnover more effectively. However, there was an obvious gap in understanding how online activities, such as updating job profiles on social media platforms and engaging in professional networking sites, affect a person's intention to leave a job.

Ashish Kumar Biswas of Narsee Monjee Institute of Management Studies (Deemed to be University) in Hyderabad, R. Seethalakshmi of VIT-AP University in Amaravati, and Prabha Mariappan of Veltech University in Chennai, India, have employed a quantitative survey approach involving almost 600 participants and used a structural equation model to test their hypothesis and hopefully help fill this gap in our understanding of employee intention to quit.

The team found that, as one might anticipate, an increased engagement in professional networking sites ultimately influences an individual's intention to leave their current job and find employment elsewhere. This is not necessarily an obvious factor as many people might daydream about finding a new job and investigate their options, perhaps even uploading their CV (curriculum vitae or résumé) to a job-seekers web site, but a certain level of activity might nudge them towards quitting whereas casual interaction with such websites would not necessarily reinforce the tendency. Online activity of this kind cannot be ignored as an influential factor in affecting an individual's intentions in much the same way as job satisfaction and level of engagement should not be ignored, especially if they are dwindling. Moreover, the research suggests that employee commitment to a job is dynamic and can fluctuate with changing circumstances.

The team suggests that even highly committed employees might intensify their job search efforts, but this doesn't necessarily translate to higher turnover rates. In contrast, those members of staff who are not committed to their jobs may choose to stay with their current employer for various reasons, such as a competitive job market or personal obligations, and perhaps because they do not see the opportunities that might exist via social media and job-seekers websites.

Biswas, A.K., Seethalakshmi, R. and Mariappan, P. (2023) 'An emerging approach towards intention to quit among IT employees', Int. J. Enterprise Network Management, Vol. 14, No. 3, pp.283–298.
DOI: 10.1504/IJENM.2023.132967

Cyberattacks are a major problem for all kinds of organizations with the potential to compromise e-commerce, government, and healthcare. Research in the International Journal of Critical Infrastructures, highlights how Internet of Things (IoT) devices, which are not necessarily as well protected as conventional computers in terms of firewalls, antivirus, and malware protection, can represent an important vulnerability in a system. Such threats extend beyond potential financial loss where they can disrupt infrastructure, government, and even threaten human lives, particularly in healthcare facilities.

Taofeek Mobolarinwa Balogun, and Hayretdin Bahsi of Tallinn University of Technology in Tallinn, Estonia, and Omer F. Keskin and Unal Tatar of the University at Albany, State University of New York, USA offer a comparative framework for modelling the threat of cyber attack on IoT devices and networks.

The team's new framework can be used to evaluate particular vulnerabilities within an IoT network from the perspective of a putative third-party attacker. The framework can critically assess what factors are involved in determining the level of sophistication needed to carry out a successful cyberattack that causes damage to the system. It is more common not to consider the sophistication of an attacker but simply to harden firewalls and keep antimalware software up to date and hope these are sufficient to protect the system from attack. The factors considered include accessibility, stealth, technical ability, and time. Given enough of each, a sufficiently sophisticated attacker might be able to breach any security. Knowing just how sophisticated an attacker needs to be gives the IoT network manager the opportunity to increase the requisite level of defence.

The team demonstrated that two distinct IoT network types: SCADA (Supervisory Control and Data Acquisition) infrastructure and healthcare IoT infrastructure represent different levels of sophistication. SCADA networks demand greater expertise and sophistication compared with healthcare IoT networks. This suggests that there is a need for a bespoke approach to fortifying different types of critical systems. Understanding this requirement is an important part of allowing decision-makers at national and organizational levels to counter threats proactively without the need to over-extend security on more sophisticated systems that are intrinsically less vulnerable.

Balogun, T.M., Bahsi, H., Keskin, O.F. and Tatar, U. (2023) 'A comparative framework for cyber threat modelling: case of healthcare and industrial control systems', Int. J. Critical Infrastructures, Vol. 19, No. 5, pp.405–431.
DOI: 10.1504/IJCIS.2023.133282

Research in the International Journal of Computer Applications in Technology introduces a hybrid classification algorithm aimed at improving the recognition of human activities using smartphone data. The work could have implications for various fields, including healthcare and personal support.

Ahmad Taher Azar of both the Prince Sultan University in Riyadh, Saudi Arabia and Benha University in Benha, Egypt, hoped to demonstrate a tool for accurately categorizing six distinct human activities: lying, sitting, standing, walking, walking upstairs, and walking downstairs. He used supervised machine learning techniques that merged Random Forest Decision Trees (RFDT) and Neural Networks (NN) to this end.

The hybrid approach was able to classify six human activities with an accuracy rate of 96 per cent. This surpasses the performance of individual machine learning techniques like NN or RFDT and is comparable with the current state-of-the-art methods. However, what sets this algorithm apart is its efficiency in processing. The hybrid algorithm can infer behaviour from smartphone behaviour in just 0.073 seconds compared to the accuracy achieved with a Convolutional Neural Network (CNN), which can take well over 1.5 seconds to do the same job and reach a similar level of accuracy.

Azar's work emphasises how useful such an efficiency improvement could be in that it would allow real-time processing of smartphone data even on devices without a built-in dedicated computer processing unit for coping with such tasks. This capacity has considerable implications, particularly in scenarios where immediate and accurate activity recognition is essential, such as in healthcare and personal support applications. A particularly timely application would be for patient support and monitoring on so-called "virtual wards" where the patient usually remains in their home and is looked after by healthcare professionals remotely using telemedicine tools for monitoring and advising.

It is worth noting that there remain several challenges for this kind of research. The identification of basic movements such as climbing the stairs or lying down is achievable provided the person has their smartphone about their person at all times. However, there is a need for deeper recognition of emotional state and other factors important to that person's health and wellbeing.

Azar, A.T. (2023) 'Hybrid machine learning approach for human activity recognition', Int. J. Computer Applications in Technology, Vol. 72, No. 3, pp.231–239.
DOI: 10.1504/IJCAT.2023.133307

Research in the Journal of Design Research, introduces an innovative approach that combines co-creation and follow-up interviews to use nostalgia effectively in the realm of design and innovation. The objective is to harness nostalgia as a valuable tool for creating meaningful and user-centric experiences, products, and services.

Co-creation is a collaborative tool used by designers who collaborate closely with users during the initial, and sometimes all, stages of the process to understand more clearly the wants and desires of their putative users. Renu Zunjarwad of the Herberger Institute for Design and the Arts at Arizona State University has illustrated the approach by examining the cultural significance of street-food in Mumbai and comparing it with production, distribution, and consumption practices of street-food in Phoenix, Arizona, USA.

Zunjarwad's research highlights the importance of focusing on the cultural networks surrounding an artefact in design research. She concludes that co-creation is a powerful technique for exploring abstract concepts such as trust, nostalgia, and social anxiety. When effectively implemented, co-creation can provide valuable insights for developing user-centric experiences and products.

The work forms part of a larger project investigating how nostalgia, authenticity, and tradition influence Indian street-food practices in the global context. Key research questions centre on the role of nostalgia in shaping street-food practices in the era of globalization and the contribution of design to these experiences.

While co-creation can be employed at any stage of the design and product development process, it is most effective when used early to identify broader opportunities based on the wants of the potential consumers of the product. However, successful co-creation requires careful planning, collaboration, and facilitation to generate unique value and thence solutions that focus on the customer rather than simply the bottom-line. The benefits can be substantial although the approach requires more time and energy than conventional design processes by virtue of involving more people who are beyond the company's regular staff.

Zunjarwad adds that co-creation can itself be used in research. "Co-creation is a powerful technique to explore difficult-to-observe concepts like trust, nostalgia, and social anxiety. It can deliver impactful insights to build user-centric experiences, products, and services when implemented well," she writes.

Zunjarwad, R. (2023) 'Nostalgia and co-creation', J. Design Research, Vol. 21, No. 1, pp.62–78.
DOI: 10.1504/JDR.2023.133265

In a commercial world dominated by social media, research in the International Journal of Internet Marketing and Advertising reveals a mysterious, invisible force that lurks behind many a purchase decision when social media personalities, or influencers, are involved. This force of "benign envy" could be used to guide marketing and advertising strategies towards the most effective influencers and allow more persuasive campaigns to be developed for a range of products and services.

"Influencers" are typically social media users with a large following, sharing engaging or endearing content, and for whom it might be said they hold sway over their audience's opinions and behaviour. Influencers commonly have expertise in a particular niche and are sufficiently charismatic and authentic in that niche, whether fashion, beauty, fitness, travel, technology, or other areas of lifestyle, that they can "nudge" their audience in a particular direction.

Xiaofan Yue, Nawal Hanim Abdullah, Mass Hareeza Ali, and Raja Nerina Raja Yusof of the School of Business and Economics at the Universiti Putra Malaysia, in Selangor, have used well-established social comparison theory to investigate the connection between benign envy and an audience's desire to purchase products promoted by influencers. Fundamentally, consumers who identify with a particular influencer and perceive themselves as being a peer or otherwise similar to that influencer will be more inclined to follow that influencer's recommendations.

To maximize the effectiveness of their influencer marketing, companies need to select carefully those influencers they wish to showcase their products and services to that these align with the influencer's own preferences, values, and way of life. Moreover, a campaign must also match with the benign envy felt by the influencer's audience.

Cynically, perhaps, the consumer must feel that buying the product will somehow elevate them so that they sit more squarely alongside the influencer they follow. Influencers often embody the ideal self-image of their audience and the lifestyle and status they crave. Consumers following influencer recommendations will somehow imagine they are closing in on this ideal by making the right purchases guided by their influencer, regardless of how real that ideal actually is. Indeed, as with many kinds of aspirational endeavour of this kind, a single purchase may well make the consumer feel better, but its impact is often short-lived, and there's always another recommendation from their influence to envy.

Yue, X., Abdullah, N.H., Ali, M.H. and Yusof, R.N.R. (2023) 'The role of audiences' benign envy in influencer marketing', Int. J. Internet Marketing and Advertising, Vol. 19, Nos. 3/4, pp.215–230.
DOI: 10.1504/IJIMA.2023.133344

The internet has opened up countless business opportunities that were once the preserve of corporate entities, allowing individuals and small groups to offer goods and services as well as to share resources. Often an "app" is involved that provides connectivity between individuals that would otherwise not meet or encounter each other. Two areas that spring to mind are car-sharing, taxi-type services and holiday and short-term lets of rooms and buildings, the most well-known examples in those areas are perhaps AirBnB and Uber.

An area that is emergent but not yet mature is "last-mile" deliveries where individuals can take on the packages and parcels couriered to a depot and deliver them to their neighbours for a small fee rather than relying on conventional couriers to fulfil the complete delivery. Such peer-to-peer (P2P) crowdsourced delivery services are gaining traction worldwide and offer a way for the big couriers to cut out the inefficient last part of their logistics and offload it into locals where it might bolster a growing micro-economy.

Research in the International Journal of Logistics Systems and Management has looked at how well the implementation of P2P crowdsourced delivery is going in Egypt. The findings shed light on the potential benefits and the remaining challenges.

Karim Soliman of the College of International Transport and Logistics at the Arab Academy for Science, Technology, and Maritime Transport in Cairo, employed a deductive approach and quantitative research methods to gauge public sentiment towards this innovative delivery model. Soliman writes that encouragingly, respondents of various ages and education were already familiar with crowdsourcing, even if they were not familiar with the term itself.

Soliman notes that in Egypt P2P delivery services are being used within the same city, as one might expect. Users are less keen to use such services between cities or internationally, although one might posit that this would defeat the object of using "last-mile" P2P delivery and would represent a much larger-scale crowdsourced delivery service. Such a service may well emerge if it has not already been in place for many years in various forms. The research also suggests that there is a need to develop professional guidelines for those offering P2P delivery to enhance trust and confidentiality and also to address the matter of insurance.

Soliman, K. (2023) 'Exploratory analysis of the viability of crowdsourced delivery in Egypt: developing a peer-to-peer platform', Int. J. Logistics Systems and Management, Vol. 45, No. 4, pp.447–470.
DOI: 10.1504/IJLSM.2023.132987

A review in the International Journal of Medical Engineering and Informatics has surveyed current early detection methods for Alzheimer's disease, a prevalent neurodegenerative condition affecting millions of people worldwide. The work looks into the progression, causes, and diagnosis of Alzheimer's and emphasizes that a multi-modal approach coupled with advanced machine learning techniques could lead to much earlier diagnosis for many patients. Early diagnosis offers better options for planning and ongoing care. As the world population continues to age, the burden of Alzheimer's disease looms larger than ever.

Alzheimer's disease is a neurodegenerative disorder characterized by cognitive impairment and memory loss. Its precise cause is not clear although there are characteristic changes in the brain that are always present and usually observed post mortem. The disease thus presents a significant challenge in its early detection when behavioural symptoms might be mild or may well be similar to those symptoms seen in a range of other conditions. There is no cure for this debilitating and ultimately lethal condition but the importance of detecting it in its early stages cannot be overstated given the devastating impact it has on the patient and those caring for them. Early diagnosis not only allows individuals to communicate their needs to loved ones but also empowers them to make crucial decisions regarding finances and legal matters that will come into play as the disease progresses.

While a definitive scientific diagnosis is really only possible post mortem, a combination of observations of behaviour as well as brain scans can give the clinicians a near-certain diagnosis once symptoms are established. C.R. Nagarathna and Kusuma Mohanchandra of the Dayananda Sagar Academy of Technology and Management in Bangalore, India, suggest from their review, that a combination of techniques will offer a more reliable diagnosis than any single method. They add that utilising machine learning tools could now enhance the data from various types of brain scan and couple those results with the observations made by an expert diagnostician in the field.

Alzheimer's is a complex disease with a range of putative causes and manifestations. Indeed, the conventional wisdom regarding the role of errant proteins in the brain has not yet been settled. One scientific camp sees protein fragments as causing damage to the brain whereas the other camp suggests the errant proteins are a symptom of an underlying disease process and not causative agents themselves. Whatever the aetiology, early diagnosis is key to improving life for patients and their carers.

Early diagnosis also offers greater hope as new therapies begin to emerge from the laboratory. An earlier intervention will almost always be preferred with the potential to slow degeneration and mitigate symptoms. There is always the hope that in the distant future a therapeutic will be designed that might even halt or reverse the disease.

Nagarathna, C.R. and Mohanchandra, K. (2023) 'An overview of early detection of Alzheimer's disease', Int. J. Medical Engineering and Informatics, Vol. 15, No. 5, pp.442–457.
DOI: 10.1504/IJMEI.2023.133091

Research in the International Journal of Electronic Security and Digital Forensics offers a new approach to combating phishing attacks in order to enhance online security and reduce cybercrime against individuals and businesses and attacks on governments so improving national security.

Phishing is a deceptive technique in which a web page, email or message is used to impersonate a trusted entity and to deceive individuals into clicking malicious links, revealing sensitive information such as usernames and passwords, bank details, and other such details. It has caused significant harm to countless victims, resulting in compromised data, identity theft, and even national security breaches.

Those propagating phishing attacks can use very sophisticated methods to make a message or page look authentic and even highly skilled and security-aware users are sometimes duped into accessing a malicious resource. Such resources might steal information directly as the user enters it or lead to them unwittingly downloading malware or another payload that then compromises their computer system, whether a personal computer or a network. Computer security systems are constantly challenged by the development of more sophisticated phishing attacks which may also exploit social engineering in subtle ways as well as malware to dupe users.

T. Kalaichelvi of the Panimalar Engineering College in Chennai, India, and colleagues have proposed a new threat-modelling technique that can pinpoint and eliminate vulnerabilities that make a computer system more susceptible to a phishing attack. The team's approach uses the STRIDE threat design methodology, a potent tool that demonstrates an impressive 96.3% accuracy rate in detecting phishing web addresses. The work offers a real solution for individuals and organizations alike to defeat the phishing threat.

The implications of the research extend beyond individual victims and encompass businesses and the world of the Internet of Things. For cybersecurity experts, developers, and IoT device manufacturers, the proposed threat modelling technique could help in securing vulnerabilities proactively at the design stage rather than reactively when vulnerabilities have been identified and exploited. Fundamentally, a multi-faceted anti-phishing approach is needed that takes into account both the technological vulnerabilities and the human factor.

Kalaichelvi, T., Mane, S.B., Dhanalakshmi, K.M. and Prasad, S.N. (2023) 'The detection of phishing attempts in communications systems', Int. J. Electronic Security and Digital Forensics, Vol. 15, No. 5, pp.541–553.
DOI: 10.1504/IJESDF.2023.133192