30 June 2023

Research pick: A time to live a time to buy - "Is time-constrained promotion actually effective? The moderating role of price discounts and previous online consumption experience"

Consumers are constantly bombarded with enticing product promotions and time-limited offers. That might be a flash sale on an e-commerce platform or a time-constrained deal at a physical store. Businesses use these marketing tools to trigger consumers and so drive sales. Research in the International Journal of Services Technology and Management asks whether consumers are so gullible or whether cynicism means such promotions are largely ineffective.

Jing-Bo Shao, Fei-Si Yao, and Min Xie of the Harbin Institute of Technology in Harbin, China, have explored the concept of restrictive marketing, which encompasses both traditional online-to-offline businesses and emerging original design manufacturer (ODM) enterprises. They have identified various factors that help to shape consumer behaviour when faced with various types of promotion and whether those factors have a positive, negative or neutral effect on their decision to purchase a product. The various factors include time constraints, price discounts, product price levels, and past online buying experience.

Fundamentally, when consumers are faced with limited time to take advantage of a promotion, they are more likely to make a purchase. This is a key finding from the research. However, the effect is moderated by previous online experience of buying online – the more experienced, then perhaps the more cynical, less gullible, and the less likely to be swayed by such a marketing tactic.

The researchers also found that perceived value plays a significant role in moderating purchase intention when faced with time constraints. Ultimately, consumers tend to decide on value before making a purchase decision rather than being triggered or nudged to make a summary decision foisted on them by a time constraint. Of course, the degree of price discounting can counter their cynicism as it will boost the perceived value of a product, making it more appealing to consumers within the limited timeframe.

Insights from this work should feed back to marketing departments keen to nudge consumers. They must understand the experience of their putative customers better in order to target them more effectively with such marketing strategies. Conversely, consumers themselves can understand how such marketing works, how well they themselves are being targeted and so seek out the best offers and discounts when they do wish to buy a product but without being led too heavily by marketing tricks.

Shao, J-B., Yao, F-S. and Xie, M. (2023) ‘Is time-constrained promotion actually effective? The moderating role of price discounts and previous online consumption experience’, Int. J. Services Technology and Management, Vol. 28, Nos. 3/4, pp.159–184.

29 June 2023

Research pick: Managing the curve of economic distance - "Revisiting economic distance and its role in foreign subsidiary survival"

Research in the European Journal of International Management, has looked at the connection between economic distance and the survival of foreign subsidiaries. The findings, based on a sample of 1771 Finnish foreign direct investments, shed light on the non-linear relationship between these factors and underscore the role of focused strategy in ensuring the success of a company’s foreign subsidiary operations.

As a concept, economic distance refers to the disparities in economic conditions and factors between a company’s home nation and foreign countries that host its subsidiaries. It is a major focus of international management research. In the paper by Pratik Arte of the Newcastle Business School at Northumbria University, UK and his late colleague Jorma Larimo who was at the University of Vaasa, Finland, it is argued that economic distance, when combined with arbitrage opportunities and associated costs, can shape the fate of foreign subsidiaries.

The researchers constructed an index to measure economic distance, drawing upon international production and organizational learning theory and using the statistical Mahalanobis method to calculate economic distance based on various factors. They tested their hypothesis using Cox’s proportional hazard model to analyzing the sample of Finnish foreign direct investments. The analysis showed an inverted U-shaped relationship between economic distance and the survival of subsidiaries. Initially, as economic distance increases, subsidiary survival improves but beyond a threshold, survival rates begin to decline as operating costs outweigh the benefits of operating in countries that are even more economically distant.

The study also highlights the role of prior experience and ownership in coping with the challenges in economically distant countries. Firms that have experience with foreign host countries, as well as wholly owned subsidiaries, could cope much better with the requisite operating costs. In contrast, joint ventures worked best between economically similar countries, where the costs and challenges were relatively lower.

This research could have implications for companies attempting to venture into foreign markets. While an economically distant country might be enticing because it presents lucrative arbitrage opportunities, the study shows that companies need to work strategically lest they fall fowl of that U-shaped curve! Prior experience and an appropriate ownership structure can mitigate some of the challenges, the research suggests.

Arte, P. and Larimo, J. (2023) ‘Revisiting economic distance and its role in foreign subsidiary survival’, European J. International Management, Vol. 20, No. 3, pp.369–407.

28 June 2023

Research pick: AI sees through biological sex using dental X-rays

In forensic science, the identification of deceased or missing individuals is often at the heart of an investigation. Dental records have long been used as a valuable tool in this process given that it is rare that two people will have matching records of their teeth present or absent, caps and crowns, or fillings, and the alignment of teeth seen in an X-ray. One thing that is perhaps not necessarily immediately obvious from dental records is the biological sex of the individual, but this would be very useful information in almost every investigation in the absence of other indicators.

Research in the International Journal of Biomedical Engineering and Technology, has made progress towards the development and training of an algorithm that can determine biological sex from dental X-rays with 94 percent accuracy. This application of what is referred to as a deep-learning method demonstrates the potential of such an approach to augmenting conventional evidence in an investigation.

B. Vijayakumari, S. Vidhya, and J. Saranya of the Mepco Schlenk Engineering College in Sivakasi, Tamilnadu, India, explain how their algorithm comprises three components: image pre-processing, gradient-based recursive threshold (GBRT) segmentation, and classification. Initially, they use a so-called prime magic square filter during the image pre-processing step to remove unwanted noise. The prime magic square filter uses a special grid of numbers overlaid on the image within the computer and compares pixel values in the image with the corresponding values in the grid to determine what are distortions or compression artefacts, which contribute to image noise and so can be brushed away to give a clean and accurate image for the subsequent analysis.

The GBRT segmentation technique refines the images, enhancing the algorithm’s ability to extract relevant information. Finally, the classification stage utilizes a Resnet50 neural network, a widely adopted deep learning architecture. The team trained the algorithm with 3000 dental X-rays for which the individual’s biological sex was known. This allowed the algorithm to discern the biological sex associated with dental X-rays presented to it in which the biological sex of the individual is not known. For the purposes of testing the team used 1000 images, a subset of the original collection where sex was known to determine whether the system would correctly assign biological sex. Teeth and jawbones are sexually dimorphic in humans to varying degrees but there are also marked effects of nutrition and socioeconomics on how our jaws and teeth grow. The new system can see through these potential discrepancies based on its training with the X-ray images.

Within the specific context of legal proceedings, there is now a need to assess the algorithm more rigorously so that reliability of the data, potential algorithm biases, and the need for expert interpretation should be taken into account. Ongoing research and validation efforts will contribute to its refinement and development for use in forensic analysis. The team also plans to extend the approach to age determination from dental X-rays.

Vijayakumari, B., Vidhya, S. and Saranya, J. (2023) ‘Deep learning-based gender classification with dental X-ray images’, Int. J. Biomedical Engineering and Technology, Vol. 42, No. 1, pp.109–121.

Special issue published: "Artificial Intelligence for Biomedical and Healthcare Systems in IoT"

International Journal of Biomedical Engineering and Technology 42(1) 2023

  • Using artificial intelligence to design healthcare system in IoT
  • CT image super-resolution reconstruction via pixel-attention feedback network
  • Artificial intelligence for stress monitoring and prediction using wearable sensors in internet of things
  • CT and MRI image fusion via dual-branch GAN
  • Research and design of online drug mall system based on SOA
  • Diagnosis results of athletes with ankle joint pain based on the neutrosophic ensemble image
  • Sports training on recovery of nerve function and nerve cell apoptosis in athletes with hemorrhagic brain injury
  • Deep learning-based gender classification with dental X-ray images

27 June 2023

Research pick: AI fuses CT and MRI scans for better diagnostics - "CT and MRI image fusion via dual-branch GAN"

Research in the International Journal of Biomedical Engineering and Technology shows how artificial intelligence (AI) can be used to fuse images from clinical X-ray computed tomography (CT) and magnetic resonance imaging scans. The method, known as the Dual-Branch Generative Adversarial Network (DBGAN), has the potential to allow a clearer and more clinically useful interpretation of CT and MRI scans to be carried out. Essentially, combining the hard, bone, structures of the CT scan with the soft tissue detail of the MRI image. The work could improve clinical diagnosis and enhance patient care for a wide range of conditions where such scans are commonly used but where each has limitations when used alone.

CT imaging utilizes X-ray technology to capture detailed cross-sectional images of the body or part of the body, which are converted into a three-dimensional representation of bone, which are opaque to X-rays. In contrast, MRI uses employs strong magnetic fields and radio waves to produce precise images of soft tissues, such as organs or diseased or damaged tissues. The potential of merging both modalities could give clinicians a more comprehensive representation of a patient’s anatomy and reveal otherwise hidden details of their physical problems.

Wenzhe Zhai, Wenhao Song, Jinyong Chen, Guisheng Zhang, and Mingliang Gao of Shandong University of Technology in Zibo, China, and Qilei Li of Queen Mary University of London, United Kingdom have used DBGAN to carry out their CT and MRI fusion. DBGAN is an advanced AI technique based on deep-learning algorithms. It features a dual-branching structure consisting of multiple generators and discriminators. The generators are responsible for creating fused images that combine the salient features and complementary information from CT and MRI scans.

The discriminators essentially assess the quality of the generated images by comparing them with real images and discarding those that are of lower quality until a high-quality fusion is achieved. This generative adversarial relationship between generators and discriminators allows the AI to fuse the CT and MRI images efficiently and realistically so that artefacts are minimised and visual information maximised.

The duality of the DBGAN approach uses a multiscale extraction module (MEM) which focuses on extracting important features and detailed information from the CT and MRI scans and a self-attention module (SAM) which highlights the most relevant and distinctive features in the fused images.

The team has carried out thorough testing of their proposed DBGAN approach with both subjective and objective assessments. It proves itself to have superior performance compared to existing techniques in terms of image quality and diagnostic accuracy. Given that CT and MRI scans individually have strengths and weaknesses, the use of AI could allow radiographers to fuse synergistically both types of scan, combining the strengths of each and discarding the weaknesses. Fundamentally, the team explains, the DBGAN fusion retains the bone structure details commonly accessible with a CT image and the soft tissue information provided by an MRI scan.

Zhai, W., Song, W., Chen, J., Zhang, G., Li, Q. and Gao, M. (2023) ‘CT and MRI image fusion via dual-branch GAN’, Int. J. Biomedical Engineering and Technology, Vol. 42, No. 1, pp.52–63.

Special issue published: "Recent Multidisciplinary Research Advancements in Information Technology and Applied Management for Sustainable Development"

International Journal of Applied Management Science 15(2) 2023

  • DNA-SKA: a DNA congruous secure symmetric key generation algorithm
  • Machine learning-based-HR appraisal system (ML-APS)
  • Binary and multi-class classification of Android applications using static features
  • Accessing the usability and accessibility of Indian higher education institution's websites
  • Intellectual capital efficiencies and performance of SMEs in KSA

26 June 2023

Research pick: Innovative accountants use hi-tech but keep the human touch - "The effect among innovative accountant competency, business management efficiency, financial reporting quality, and firm growth"

Research in the International Journal of Business Innovation and Research suggests that innovative accountants can play an important role in the growth and success of a firm. The study, by Kanthana Ditkaew Rajamangala of the University of Technology in Lanna Tak, Thailand, looked at the skills of accountants and found that their competency influenced company growth through two key factors: business management efficiency and financial reporting quality. The study also looked at the link between innovative accountant competency and the public image of the company, with a particular focus on how financial reporting quality plays a mediating role in that image.

Rajamangala surveyed some 441 accounting directors and used a structural equation model (SEM) to evaluate the data obtained. She found that the competence of innovative accountants within a company affects growth but that this is mediated by both business management efficiency and the quality of financial reporting. Financial acumen essentially helps drive growth by improving business operations underpinned by high-quality financial reports.

The implications of this work are quite far-reaching. In emphasizing the importance of innovative accountants within an organization, Rajamangala’s work suggests that organizations ought to prioritize the development and nurturing of innovative skills among their accountants. By doing so, they can foster a culture of innovation that drives growth and improves the overall perception of the firm.

In the near future “blockchain” technology, “artificial intelligence”, and other disruptive innovations will begin to play a role in company accounting offering new approaches to conventional transaction recording and predictions about a company’s finances. Those accountants who recognise the potential of such innovations and use them to their advantage will also be serving their companies better than those who ignore the opportunities and fail to innovate.

There is always a lot of hyperbole surrounding new technology and concerns that it will lead to redundancies in certain sectors. In the face of this, strong support for the accountant’s function requires the administrative committee to collaborate on the strategy and participate in the evolution of accounting, Rajamangala’s work suggests. Hi-tech provides us with novel and powerful tools, but we will always need the human touch.

Ditkaew, K. (2023) ‘The effect among innovative accountant competency, business management efficiency, financial reporting quality, and firm growth’, Int. J. Business Innovation and Research, Vol. 30, No. 4, pp.580–607.

23 June 2023

Research pick: Defining the unexplainable in artificial intelligence - "A scientific definition of explainable artificial intelligence for decision making"

How do we take a look inside AI’s black box and define what we see?

The term “artificial intelligence”, usually abbreviated as “AI”, means a lot of different things to a lot of different people. Initially, the phrase was used to allude to the potential of machines, computers, specifically, somehow gaining sentience on a par with human consciousness. This notion inspired a lot of philosophical debate about what it means to be human and whether or not a machine can have self-awareness. The same notion was at the heart of a lot of science fiction throughout the twentieth century and to the present day, although the idea of entities other than humans having human-like consciousness has been around for millennia.

As we enter a new phase in the development of AI technology, the concepts surrounding what we mean by that term are changing. We now consider neural networks that can be trained genetically to undergo machine learning and to take on certain properties we now refer to as AI. However, many of these tools, computer algorithms backed by enormous information databases do not come close to displaying consciousness and they many such as the now infamous large language models come close to behaving like a human. When prompted with text, they can produce a seemingly authentic response that is, superficially at least, coincident with the response a human might give to that same prompt.

Of course, these models are only as good as the training they have been given and the algorithms they run to generate their responses. At this point in the history of this kind of AI we are fast approaching the notion of a “black box” AI. A system that given a prompt, generates a response that even the programmers and developers of the system cannot predict. Such systems and their responses reaching the point where they cannot be explained, although this is not to suggest that the system is in any way approaching the sci-fi singularity of self-awareness, emotional behaviour, and any kind of concept of right or wrong.

We develop and train the algorithms, ask it to make a prediction, and we take the responses. The problems may well arise when those responses are used to make important decisions across society, in economics and finance, in industry, across healthcare and medical research, in the wider realm of science, in politics and most worryingly in the military machine. If the programming and training are unexplainable, then we or machines prompting AI systems for a response may get what turns out to be a very wrong response. If we have given such prompt-response systems control of important systems, then we may come unstuck when a prompt generates an entirely inappropriate response in a healthcare environment, in a factory, or on the world stage.

Fabian Wahler and Michael Neubert, writing in the International Journal of Teaching and Case Studies, recognise the importance of defining and understanding AI and where it might take us, sooner, rather than later. They have homed in on a definition of explainable AI that might be used in future work by both practitioners and academics alike. The work seeks to remove the ambiguity of current definitions and to increase trust and reliability in decision making by making black-box systems understandable, interpretable, and transparent to human users.

Wahler, F. and Neubert, M. (2023) ‘A scientific definition of explainable artificial intelligence for decision making’, Int. J. Teaching and Case Studies, Vol. 14, No. 1, pp.88–116.

Free sample articles newly available from International Journal of Teaching and Case Studies

The following sample articles from the International Journal of Teaching and Case Studies are now available here for free:
  • Education 3.0: the impact of collaborative online teaching platforms on student academic performance and engagement
  • We flipped the classroom, now we flip the case study: lessons from teaching undergraduate strategic management
  • Culinary Jet Concierge: flying through turbulence
  • Malaysian delicacy: the Story of Patin
  • Arini Global: international expansion of a small olive oil producer

22 June 2023

Free sample articles newly available from International Journal of Blockchains and Cryptocurrencies

The following sample articles from the International Journal of Blockchains and Cryptocurrencies are now available here for free:
  • COVID-19 pandemic and cryptocurrencies: fresh evidence from time-frequency analysis
  • The possible contributive value of cryptocurrencies to Small Island Developing States
  • Supply chain provenance with offline verification through a low-requirement, blockchain-based framework
  • Decentralised domain authentication
  • How to obtain the fair value for cryptocurrency and digital assets
  • Crowdsourcing clinical research utilising blockchain-based incentivisation systems

Free open access article available: "Contextual impact on indigenous entrepreneurs around the world: geographic location, socio-cultural context and economic structure"

The following paper, "Contextual impact on indigenous entrepreneurs around the world: geographic location, socio-cultural context and economic structure" (International Journal of Entrepreneurship and Small Business 49(1) 2023), is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Research pick: Indigenous entrepreneurs - "Contextual impact on indigenous entrepreneurs around the world: geographic location, socio-cultural context and economic structure"

The global population of indigenous people surpasses the total population of the USA and is almost equal to that of the European Union, but despite this a stifling “Western” perspective on most aspects of culture, society, and economics, means that many indigenous people are often marginalised as minorities and caught in the poverty trap, as well facing many other hardships. Research in the International Journal of Entrepreneurship and Small Business now highlights the role of entrepreneurship in empowering indigenous communities.

Prescott C. Ensign of the Lazaridis School of Business and Economics in Waterloo, Ontario, Canada, has conducted a study to investigate this phenomenon and sheds new light on the various factors that influence the establishment and operation of businesses by indigenous people. Ensign’s findings underscore the significance of addressing the unique challenges and opportunities faced by indigenous entrepreneurs, while also emphasizing the interconnectedness of contextual factors that affect the outcomes of their efforts. Entrepreneurship might help individuals and their communities overcome some of the political and economic disadvantages they encounter. Indeed, entrepreneurship has emerged as a potential avenue for empowerment and wealth creation among these indigenous populations.

The research, aimed at investigating the dynamics of indigenous entrepreneurship, develops a conceptual framework of the various factors. Ensign’s framework offers an analytical tool and allowed him to carry out a qualitative examination of over fifty instances of indigenous entrepreneurship in remote, rural, and urban areas across twelve countries.

Geographic embeddedness is an important factor as are indigenous cultural factors and the mainstream economic structures that surround them. All of these might conspire to shape the success and operation of a business. However, the Western-Eurocentric perspective is a common hindrance, the work suggests. By recognizing and valuing indigenous culture and practices, Ensign’s research suggests that more effective and empowering strategies might be developed to better support entrepreneurship within indigenous communities.

There is an overarching urgency to change the perspective to one that emphasizes the importance of the indigenous entrepreneurial ecosystem and allows it to thrive, one that encompasses the unique challenges and opportunities specific to indigenous entrepreneurs rather than assuming such businesses can be treated with the aforementioned “Western” ethos.

Policymakers and stakeholders from both the indigenous and non-indigenous communities can best work together and can contribute to the economic well-being and overall empowerment of indigenous communities by recognising the barriers and limitations and finding ways to overcome them. A business model that is heterogeneous and not homogenous is now needed to create a more inclusive and culturally diverse world of entrepreneurship.

“Findings also provide evidence that indigenous entrepreneurship is growing and prevails in many forms around the world,” writes Ensign. “This is positive considering current and past actions of oppression, neglect, marginalisation, and constraints that target indigenous people. Indigenous entrepreneurs are overcoming these and moving ahead.”

Ensign, P.C. (2023) ‘Contextual impact on indigenous entrepreneurs around the world: geographic location, socio-cultural context and economic structure’, Int. J. Entrepreneurship and Small Business, Vol. 49, No. 1, pp.150–186.

Free sample articles newly available from International Journal of Behavioural Accounting and Finance

The following sample articles from the International Journal of Behavioural Accounting and Finance are now available here for free:
  • Gender diversity, country norms and capital markets post-COVID-19
  • The impact of IFRS convergence on key financial indicators of Public Sector Undertakings listed on NSE, India
  • Asia-pacific financial market inefficiency: evidence through behavioural models
  • Relationship between economic performance and capital structure: some empirical evidence
  • The influence of investor sentiment on stock prices among industries in the US

21 June 2023

Research pick: Relationships for managerial success go beyond demographics - "Diversity at work: how relational demography and influence tactics impact the effectiveness of leaders"

Strong relationships between managers and their staff matter more than gender or ethnicity in effective management.

Research in the International Journal of Behavioural Accounting and Finance, reveals the crucial role played by the relationship between managers and their staff. It suggests that while ethnicity and gender might affect those relationships, they do not necessarily impact the ability of managers to inspire employees in terms of cooperation and compliance. However, gender and ethnicity may well affect how those relationships form and progress in the first place. The researchers highlight the interplay between diversity, influence tactics, and leader effectiveness with and organization and how these affect the organisations desired outcomes.

Thomas D’Angelo of Pace University in New York, New York, Marco Lam, Heidi Dent, and Julia Goldsmith of Western Carolina University in Cullowee, North Carolina, USA and Martin Kissler of the Fachhochschule Dortmund in Germany, using an experimental design that focused on how the combination of relational demography and influence tactics influences the effectiveness of leaders. Specifically, they tested in their experiment how well a manager could be in persuading subordinates to create so-called “budgetary slack”, something that would be in contravention of any legitimate company’s policies and working practices. The participants were presented with manipulated photographs of superiors, that changed gender and ethnicity in the images.

The study revealed that neither gender nor ethnicity on their own directly influenced managerial effectiveness. Instead, the quality of the superior-subordinate relationship emerged as the crucial factor determining subordinates’ willingness to comply with their superiors’ requests, even when they were aware that their compliance would violate company policy. The findings suggests that relationship strength is a much greater motivator of action, surpassing any influence of the demographic characteristics of those involved.

“When it comes to getting things done, our results show that relationships matter,” the team writes. “This is especially true for tasks outside the scope of day-to-day operations or that require subordinates to take actions that might run counter to their ethical or moral beliefs.” In other words, the relationships that managers forge with their subordinates is critical to ensuring commitment to specific tasks.

These insight have implications for how organisations might handle and encourage the requisite relationships between their managers and employees. By cultivating positive relationships and implementing effective influence tactics, organisations can encourage their leaders to, in turn, encourage greater commitment in their employees.

D’Angelo, T., Lam, M., Dent, H., Kissler, M. and Goldsmith, J. (2023) ‘Diversity at work: how relational demography and influence tactics impact the effectiveness of leaders’, Int. J. Behavioural Accounting and Finance, Vol. 7, No. 1, pp.24–40.

Free sample articles newly available from International Journal of Vehicle Information and Communication Systems

The following sample articles from the International Journal of Vehicle Information and Communication Systems are now available here for free:
  • Dynamic formulation of a two link flexible manipulator and its comparison analysis with a knuckle joint cantilever
  • Collaborative decision making system in intelligent transportation system using distributed blockchain technology
  • Effect of feature and sampling ratio on tool wear classification during boring operation using tree-based algorithms
  • Multivariate short-term traffic flow prediction based on real-time expressway toll plaza data using non-parametric techniques
  • Improved coverage measurements through machine learning algorithms in a situational aware channel condition for indoor distributed massive MIMO mm-wave system

Special issue published: "Intelligent Transportation and Connected And Automated Vehicles Empowered by Artificial Intelligence"

International Journal of Vehicle Information and Communication Systems 8(1/2) 2023

  • Automatic control method of automobile steering-by-wire based on fuzzy PID
  • Route forecasting-based authentication scheme using A* algorithm in vehicular communication network
  • Real-time load balancing and dynamic profile management in mobile data networks
  • Vehicle parallel integrated control strategy based on coordinated SAS and ABS
  • Research on automatic early warning of UAV attitude abnormal state based on MEMS sensor
  • Research on the application of multiple target cluster intelligent algorithm in the design of door-to-door carriage of cargoes in railway carriage enterprises
  • Application of model predictive control on metro train scheduling problems
  • Research on pattern recognition of automobile anti-lock braking system
  • Research on primary traffic congestion point identification method based on fuzzy logic
  • Research on the interactive design of electric vehicle interior based on voice sensing and visual imagery
  • An automatic moving vehicle detection system based on hypothesis generation and verification in a traffic surveillance system

Free sample articles newly available from International Journal of Mining and Mineral Engineering

The following sample articles from the International Journal of Mining and Mineral Engineering are now available here for free:
  • Ferronickel slag produced in New Caledonia: characterisation and carbonation in seawater
  • Measurement of the phosphorite ore pulp density based on the image recognition method
  • An attempt towards the safe utilisation of dangerous sediments deriving from mine water: a case study from the Polish part of the Upper Silesian Basin
  • Economic evaluation of materials handling systems in a deep open pit mine
  • How do operators and environment conditions influence the productivity of a large mining excavator?
  • Development of integrated roof monitoring system and continuous miner working index for improving mine safety

20 June 2023

Research pick: A framework for weighing up innovation - "An innovation ontology for idea forecasting and measurement"

Research in the International Journal of Industrial and Systems Engineering, offers a new approach to evaluating and classifying innovative ideas within a company. The work introduces an ontology, a conceptual framework, for defining and measuring how radical a new idea is so that decision-makers within the company can assess its potential impact and push the company down a particular road rather than an alternative.

Earlier researchers have grappled with how to identify and evaluate radically new ideas with an innovating company. Obviously, it is impossible to test all possible ideas. Previous discussions often revolved around assessing the level of risk or waiting until the effects of an innovation could be quantified. However, these approaches have proven to be limited in their effectiveness. Objective probabilities are frequently unavailable for radical ideas, rendering risk assessment inadequate. Additionally, relying on retrospective assessment of outcomes does not aid decision-making in the early stages of idea selection.

Andrew N. Forde and Mark S. Fox of the Department of Industrial and Information Engineering at the University of Toronto, Ontario, Canada, have found a way to address the shortcomings of earlier approaches. They have a fresh perspective that treats radical ideas as uncertainties and then employs subjective probabilities in the process of making a decision about whether a given idea should be taken further. This approach acknowledges that different decision-makers may hold varying beliefs about the potential outcomes of an idea, making probabilistic assessments subjective.

“Idea evaluation and selection is a problem that takes place in the present. Implementing all ideas to determine the best one is impractical and it remains impossible to select ideas from the future; thus hindsight is not a viable decision-making tool,” the team writes.

The study aims to define what elements are essential to predict the future and evaluate an idea’s performance within it. Their ontology tackles the inherent complexity by encompassing fifteen distinct categories of innovation. It then formulates properties based on competency questions around the idea.

The research could have far-reaching implications for various industries. By establishing a common framework for evaluating and classifying innovative ideas, the team offers a solid approach to handling subjectivity among decision-makers. As organizations hope to extract the best value from their innovators to get them ahead in a wide rang of rapidly evolving markets, such research if applied appropriately could give them the tools they need.

Forde, A.N. and Fox, M.S. (2023) ‘An innovation ontology for idea forecasting and measurement’, Int. J. Industrial and Systems Engineering, Vol. 44, No. 2, pp.141–185.

19 June 2023

Research pick: Zooming in on Gen Zs online shopping list - "The dual role of online trust: a study of Generation Z through online purchase intentions in Vietnam"

A study in the Journal for International Business and Entrepreneurship Development, has revealed the various factors that influence the likelihood of Generation Z individuals in Vietnam to make online purchases. Generation Z, often referred to as Gen Z or “Zoomers” is usually considered to include those people born between the mid to late 1990s and the early 2010s. The Zoomers are the generation following the Millennial generation and represent a thriving group for marketing and advertising online. The research focused on online trust and self-efficacy, or self-belief, and provides valuable insights for businesses seeking to tap the burgeoning online market.

Vuong-Bach Vo, Giang-Do Nguyen, and Trinh-Cong Nguyen Ho of the International University and Thu-Hien Thi Dao of Nguyen Tat Thanh University in Ho Chi Minh City, Vietnam, used the social cognitive theory and the decomposed theory of planned behaviour to examine the various factors involved in online buying decisions. Their results derived from online interviews with 366 young online consumers in Vietnam.

Online trust emerged as a pivotal factor in shaping online purchase behavior among the younger generation, the team reports. Defined as the confidence individuals have in the reliability, security, and credibility of online platforms, this trust plays a dual role in influencing online purchase intention. It not only directly affects an individual’s decision making but also moderates the relationship between the individual’s belief in their own abilities, their self-efficayc, and their intention to buy online. Indeed, the team found that self-efficacy itself was an important factor in whether or not a Zoomer would be inclined to buy online. The study showed that boosting self-efficacy could have a positive influence online purchases. The work also showed that subjective norm, the influence of social factors and peer opinion also affected online buying decision.

The study contributes to a deeper understanding of the key factors that shape the online buying behaviour of Generation Z in Vietnam and so has practical and theoretical implications. Specifically, the findings underscore the significance of online trust and self-efficacy, highlighting the need for businesses to build trust and enhance a user’s own belief in their abilities in order to foster a thriving online shopping environment. Of course, being “digital natives” like the Millennials, means that members of Gen Z are usually entirely familiar and confident with the online world. Nevertheless, there is always scope for businesses to improve an interface to make it more engaging and enticing for the young, especially in a world of information overload and countless digital options.

Vo, V-B., Nguyen, G-D., Dao, T-H.T. and Ho, T-C.N. (2023) ‘The dual role of online trust: a study of Generation Z through online purchase intentions in Vietnam’, J. International Business and Entrepreneurship Development, Vol. 15, No. 1, pp.4–28.

Free sample articles newly available from International Journal of Happiness and Development

The following sample articles from the International Journal of Happiness and Development are now available here for free:
  • Diversity, culture, and membership in social organisations
  • How's life? An international classification based on life satisfaction and its determinants
  • Why some people are not as happy as they could be: the role of unobservable subjective factors
  • What makes employees happy at work? Evidence from cross-sectional data in India
  • Does fiscal deficit, public debt, economic growth and energy consumption affect health expenditure in India: an empirical evidence based ARDL bound testing approach

16 June 2023

Research pick: AI turns over a new leaf and bears fruit in agriculture - "LightNet: pruned sparsed convolution neural network for image classification"

A study in the International Journal of Computational Science and Engineering, introduces a new deep learning architecture called LightNet, designed to overcome the challenges of training deep learning models and revolutionize the agricultural sector. The study, focuses on plant disease management and fruit classification and addresses the normally high computational resource demands that have hindered the implementation of deep learning models on limited-resource devices for disease identification in images of leaves and fruit.

Deep learning, a powerful technique in artificial intelligence, has gained popularity across various applications. However, its resource-intensive nature has made it unsuitable for devices with limited computing power and storage capacity. Moreover, there is a dearth of efficient approaches for tackling real-world agricultural problems using deep learning.

Edna C. Too of the Department of Computer Science at Chuka University in Kenya has developed LightNet, a compact convolutional neural network (CNN) that uses two innovative strategies, skip connections and pruning. This increases efficiency considerably by allowing smoother information flow through the network while reducing unnecessary connections and parameters. The approach allows the system to outperform seemingly more powerful tools. For instance, it is half the size, double the efficiency, and three times faster than DenseNet.

The researchers evaluated LightNet using two real-world datasets: PlantsVillage, which focuses on plant disease detection, and Fruits-360, which involves fruit classification and grading. The results of the evaluation demonstrate just how well the system works for plant disease detection and fruit classification tasks. The potential is immense. By providing an efficient and accurate solution for deep learning in these real-world applications, LightNet offers a way for growers and suppliers to be better equipped to counter major problems across the sector. As it requires a lower-resource device there is the potential for it to be used in the field, as it were, at lower cost than other more resource-intense systems, ultimately improving crop management and food security.

Too, E.C. (2023) ‘LightNet: pruned sparsed convolution neural network for image classification’, Int. J. Computational Science and Engineering, Vol. 26, No. 3, pp.283–295.

Free sample articles newly available from International Journal of Social Media and Interactive Learning Environments

The following sample articles from the International Journal of Social Media and Interactive Learning Environments are now available here for free:
  • Time and tide wait for no student: what adolescents spend time online and social networks affect their academic performance
  • Examining social media in the online classroom: postsecondary students' Twitter use and motivations
  • An investigation of teachers' perceptions and integration of Web 2.0 tools into literacy instruction
  • Implementation and evaluation of flipped learning approach with an educational social network
  • Detecting students at risk using machine learning: applications to business education

Research pick: A bee line for predicting road traffic accidents - "Traffic accident prediction based on an artificial bee colony algorithm and a self-adaptive fuzzy wavelet neural network"

Researchers have developed a novel artificial intelligence (AI) model that combines an algorithm based on the scouting and foraging behaviour of bee colonies with a fuzzy wavelet neural network to accurately predict road traffic accidents

The artificial bee colony algorithm is a swarm intelligence algorithm that has been used to solve complex optimization problems in the past. Now, writing in the International Journal of Computing Science and Mathematics, Zhicheng Li of the Department of Urban Rail Transit and Information Engineering at Anhui Communications Vocational and Technical College in Hefei, China, has introduced self-adaptive mutation operations to overcome the algorithm’s known limitations. The use of a fuzzy wavelet neural network reduces the time needed to solve a problem and improves improves its search skills for finding a solution.

The artificial bee colony algorithm consists of worker bees, onlooker bees, and scout bees. Worker bees explore solutions based on specific rules, while onlookers select promising solutions using information shared by the workers. The scouts introduce new random solutions to boost the diversity of possible solutions in processing the data. Through an iterative process, the algorithm converges toward an optimal or near-optimal solution to the problem, in this case the nature of road traffic accidents. The fuzzy wavelet neural network uses fuzzy logic and various statistical tools within a conventional neural network to handle uncertainty and imprecision within the data.

Li has carried out computer simulations with the system to see how well it might predict fatalities in road traffic accidents based on the various factors associated with a particular incident.

“Computer simulations show that this prediction method fully exploits the nonlinear approximation ability of the wavelet neural network model, effectively improves convergence speed and training efficiency, and reduces computational complexity,” writes Li.

The work has the potential to improve our ability to anticipate and prevent lethal road traffic accidents by allowing limited resources to be more usefully assigned to proactive measures and road safety strategies. There are, in addition, implications for the arrival of driverless vehicles on our roads.

Li, Z. (2023) ‘Traffic accident prediction based on an artificial bee colony algorithm and a self-adaptive fuzzy wavelet neural network’, Int. J. Computing Science and Mathematics, Vol. 17, No. 3, pp.254–265.

Prof. Domingo Enrique Ribeiro-Soriano appointed as new Editor in Chief of International Journal of Technoentrepreneurship

Prof. Domingo Enrique Ribeiro-Soriano from Universitat de València in Spain has been appointed to take over editorship of the International Journal of Technoentrepreneurship. The departing Editor in Chief, Prof. Hermenegildo Gil-Gómez, will continue to support the journal as a member of its Editorial Board.

15 June 2023

Free sample articles newly available from Journal for International Business and Entrepreneurship Development

The following sample articles from the Journal for International Business and Entrepreneurship Development are now available here for free:
  • Critical factors for knowledge management implementation: a TISM validation
  • Leveraging technological factors and strategic alliances to achieve sustainable development goals
  • Multilevel analysis of factors influencing innovation through m-TISM approach
  • Artificial intelligence and hospitality industry: systematic review using TCCM and bibliometric analysis
  • Analysis of strategic motives for formation of alliances using total interpretive structural modelling
  • An empirical evaluation of entrepreneurial orientation in the context of innovation in new ventures

International Journal of Hydromechatronics achieves initial CiteScore of 6.0

Inderscience's Editorial Office is pleased to announce that the International Journal of Hydromechatronics has not only been indexed by Scopus, but has been listed with a considerable initial CiteScore of 6.0.

The journal's Editor in Chief, Prof. Yimin Shao, said, "It is a great pleasure to see IJHM earn a first Citescore of 6.0 from Scopus. This impressive feat would not have been possible without the support and dedication of our colleagues from Inderscience, esteemed Executive Editors, Associate Editors and Editorial Board Members, our diligent reviewers, loyal readers, and all the experts who have made great contributions to the journal. I would like to extend my heartfelt thanks to each and every one of you for your unwavering support. Let us continue to strive for even greater success in the future."

14 June 2023

Special issue published: "Defining Frontiers of Business Research in New Globalised Vietnam"

Journal for International Business and Entrepreneurship Development 15(1) 2023

  • The dual role of online trust: a study of Generation Z through online purchase intentions in Vietnam
  • The relationship between firm financial distress, firm life cycle and firm cash holdings of non-financial listed Vietnamese companies
  • Recovery of international destination image and its consequence on trust and travel planning behaviour towards online generated contents in Vietnam
  • Leading to an organisation's competitive advantage: antecedents and outcomes of the industry and university collaborative relationships
  • Perception and attitude toward applying e-learning in workplace training - an empirical study in Ho Chi Minh City enterprises
  • Fostering organisational high performance through leadership and organisational learning: evidence from tourism firms in Vietnam

Free sample articles newly available from International Journal of Private Law

The following sample articles from the International Journal of Private Law are now available here for free:
  • Zuwendung and reversion of entitlement in terminable ownership. The organic perspective of real effects contract and concept determined by function
  • The economic costs of restraint of trade agreements: modest lessons for South Africa from Germany and other selected jurisdictions
  • Corporate democracy: a panacea for job insecurity in Nigeria
  • Time limitations for intellectual property in criminal and civil litigation: a comparative study of England and Jordan
  • Thoughts about tort law and its compensation, deterrence and sanctioning functions

Research pick: Sentimental movie analysis spots fake reviews - "Identification of relevant features influencing movie reviews using sentiment analysis"

In the information-overload era, authenticity is critical but elusive, while fake news, disinformation, and fraudulent reviews are common but not always easily spotted.

Research in the International Journal of Data Mining, Modelling and Management focuses on one particular aspect of this problem how to identify a fake review, specifically a fake movie review, using sentiment analysis techniques to discern meaning from a given review and determine whether it is genuine or not. The work has implications for movie buffs the world over who might then navigate the endless reviews with confidence. The results should also improve the credibility of the movie industry by helping to identify and remove such fraudulent reviews.

Isha Gupta and Neha Gupta of the Faculty of Computer Applications at the Manav Rachna International Institute of Research and Studies in Faridabad, India, and Indranath Chatterjee of the Department of Computer Engineering at Tongmyong University in Busan, South Korea, have analyzed vast amounts of text data to uncover the specific words that contribute to biases in reviews and their influence on overall viewer sentiment. The team used a “valence-aware” dictionary, one that understands the emotional tone or polarity conveyed by particular words or phrases. Valence can be of a positive, negative, or neutral nature.

The researchers were thus able to identify the influential words in a review associated with a specific genre whether the review was of a comedy, horror, action, drama, or thriller. By using a statistical method known as Pearson’s correlation analysis, they could also identify influential features that distinguish each genre. This sheds light on the language used to describe different kinds of movies. Ultimately, the approach gives the team a quantitative assessment of the sentiment conveyed in a given movie review. Around one in five of the characteristic features of the reviews analysed were common across different genres, suggesting that “subtle changes in the feature set showing distinct discrimination among the words used for positive and negative reviews and also for each genre,” the team writes. ” there is a shallow degree of correlation present genre-wise.”

The significance of this research extends beyond understanding viewer sentiments. The study’s findings have important implications in the realm of identifying fake movie reviews. This approach to analyzing the language and sentiment expressed in a movie review, could allow service providers that host reviews to automatically assess the credibility and reliability of a given review and to flag or remove any from their system that is deemed to be fake or not credible in some way. Such a system would not represent censorship of genuine reviews, of course, but ensure that movie fans and industry professionals would have access to authentic information rather than fake reviews, which might otherwise influence movie choice and the consumer experience and at the bottom-line, industry profits, uptake of sequels and franchises, and overall commercial success.

Gupta, I., Chatterjee, I. and Gupta, N. (2023) ‘Identification of relevant features influencing movie reviews using sentiment analysis’, Int. J. Data Mining, Modelling and Management, Vol. 15, No. 2, pp.169–183.

Special issue published: "Organisational and Governance and Performance in Emerging Markets"

Journal for Global Business Advancement 15(5) 2022

  • IFRS adoption, accounting transparency, and financial performance of common stocks in the MENA region
  • Effect of pay-for-performance on performance: mediating role organisational justice
  • An empirical analysis of the influence of team success on Indian sports fans' purchase behaviour
  • Impact of organisation environment on control system and technological innovation for improving the firm performance of gold mining projects: case of Eastern African community
  • The impact of macroeconomic variables (MEV) on the stock market returns in MENA countries
  • A unique monetary reaction rule: the case of Lebanon

13 June 2023

Research pick: Detecting deviators from the norm - "An accurate identification method of abnormal users in social network based on multivariate characteristics"

Research in the International Journal of Web Based Communities introduces a new and accurate approach to identifying abnormal users in social networks by examining several characteristics of user behaviour at once. By tapping into the APIs (Advanced Programming Interfaces) of various social networks, Jian Xie of the College of Education at Fuyang Normal University in Fuyang, China, was able to gather comprehensive data about users, including details about their accounts, the content they post, and the specific ways they behave. An analysis of this data allowed him to ascribe a set of attributes to users. By applying attribute reduction, he could then eliminate any redundant features and so build a targeted attribute feature set with which to analyse suspicious accounts.

Xie then used the assimilated data to train the XGBoost model, a powerful machine learning algorithm, to create a highly objective function that can quickly flag abnormal behaviour on a social network. Xie was able to identify abnormal users with 95 percent accuracy, sufficient to alert the system’s administrators to any putative issues that could then be manually investigated and action taken to block malicious users, for instance. The error level achieved was low as was the speed with which abnormal users could be identified, within fractions of a second, in fact. Xie’s approach is faster and more accurate than the previous methods he notes in his paper.

The findings have implications across social networking, where the identification of abnormal users, whether they are malicious third parties, trolls, spammers, bullies, misinformation accounts, fake accounts, hijacked usernames or bots, plays an important role in maintaining the safety of legitimate users and protecting the overall integrity of the digital community.

“This method has the characteristics of high feature extraction accuracy, low identification error rate, and low identification time of abnormal users in social networks,” Xie concludes. He suggests that the approach could lay the foundations for developing powerful social network security policies.

Xie, J. (2023) ‘An accurate identification method of abnormal users in social network based on multivariate characteristics’, Int. J. Web Based Communities, Vol. 19, Nos. 2/3, pp.80–92.

International Journal of Powertrains to invite expanded papers from 2023 International Conference on Advanced Vehicle Powertrains for potential publication

Extended versions of papers presented at the 2023 International Conference on Advanced Vehicle Powertrains (10-12 November 2023, Tianjin, China) will be invited for review and potential publication by the International Journal of Powertrains.

New Scopus additions and CiteScores for Inderscience journals

Scopus has now released its 2022 CiteScores. Inderscience's Editorial Office is pleased to report that many Inderscience journals have improved their CiteScores, particularly the International Journal of Integrated Supply Management, International Journal of Technology Enhanced Learning and International Journal of Structural Engineering. The International Journal of Work Innovation and International Journal of Hydromechatronics have been newly indexed by Scopus and have received their first CiteScores, with the latter title earning a particularly impressive CiteScore of 6.0.

The Editorial Office thanks all of the editors, board members, authors and reviewers who have helped to make these successes possible.

12 June 2023

Research pick: How green is your t-shirt? - "Carbon footprint of t-shirts made of cotton, polyester or viscose"

Research in the International Journal of Global Warming has looked at the study, the carbon footprint of t-shirts made from different materials. The textile and clothing industry is vast and so has a significant impact on climate change through gathering resources, processing and manufacturing of products, and supply to the market. The team undertaking the work is based at Zhejiang Sci-Tech University in Hangzhou, Zhejiang, China, and examines the entire lifecycle of these popular garments whether made from the wholly natural fibre, cotton, the semi-synthetic material viscose, or entirely synthetic polyester. They consider the various stages from raw material extraction to end-of-life disposal.

Junran Liu, Yiqi Guo, Ying Zhang, and Laili Wang, Zhejiang Sci-Tech University worked with Lirong Sun of the Office for Social Responsibility of China National Textile and Apparel Council in Beijing, and Wei Bao of the College of Textile and Clothing at Qingdao University, in Shandong. The team unravelled the various costs in terms of resources and energy and found that the manufacturing of yarn of any time, used in fabric production, plays a significant role in the carbon footprint of a t-shirt. Yarn manufacture accounts for up to a half of the total emissions associated with these clothing products. Fabric manufacturing phase contributes to about 20 percent of the carbon footprint. The t-shirt’s usage phase, which encompasses washing and drying, accounts for between 31 and 48 percent of the carbon footprint. In other words, production energy is the primary driver of carbon emissions when it comes to t-shirts.

The researchers point out that there is a positive impact of using plant-derived fibres, such as cotton and viscose, in offsetting greenhouse gas emissions through carbon sequestration by the source plants as they grow. Of course, at end-of-life, the materials must somehow find a secondary use in recycling or be landfilled rather than burnt, otherwise that stored carbon is released into the atmosphere once more.

The work has implications for manufacturers and consumers. Companies aiming to decrease the carbon footprint of their t-shirts should focus on making their production technologies more sustainable by increasing their use of renewable energy sources, for instance. Similarly, consumers should aim to use renewable energy to do their laundry as well as using detergents that allow them to wash their clothes effectively at low temperature. Moreover, care and repair might usefully extend the life of a t-shirt despite its superficial nature when compared to more formal or fashion clothing.

This kind of study underscores the urgency with which we need to work together to have the clothes we need but also to address the environmental impact of the fashion industry.

Liu, J., Sun, L., Guo, Y., Bao, W., Zhang, Y. and Wang, L. (2023) ‘Carbon footprint of t-shirts made of cotton, polyester or viscose’, Int. J. Global Warming, Vol. 30, No. 3, pp.271–281.

Special issue published: "Decentralisation and New Technologies for Social Media"

International Journal of Web Based Communities 19(2/3) 2023

  • An accurate identification method of abnormal users in social network based on multivariate characteristics
  • Personalised advertising push method based on semantic similarity and data mining
  • Study on novel cross-chain mechanism in internet healthcare environment
  • A personalised recommendation method of online educational resources on social media platform
  • Dynamic monitoring of network public opinion diffusion of major public crisis based on deviation degree
  • A comprehensive retrieval method of social media information based on fuzzy mathematics
  • Design of social media information extraction system based on deep learning
  • Multiple evaluation methods of MOOC online English teaching quality based on social network
  • Mathematical modelling of abnormal account detection on social media platform based on improved edge weight
  • A novel C2C2B business model based on the sustainability of the social media community
  • Foundations of consumer engagement with social media influencers

10 June 2023

Associate Prof. Nicole Franziska Richter becomes Editor in Chief of European Journal of International Management

Associate Prof. Nicole Franziska Richter from the University of Southern Denmark has moved from her Deputy Editor role with the European Journal of International Management to become the journal's new Editor in Chief. The departing Editor in Chief, Prof. Ilan Alon will remain with the journal as an Editorial and Review Board Member.

9 June 2023

Free sample articles newly available from International Journal of Learning Technology

The following sample articles from the International Journal of Learning Technology are now available here for free:
  • The challenges of distance assessment in higher education – a case study
  • Personalised instructional feedback in a mobile-assisted language learning application using fuzzy reasoning
  • A conceptual framework to structure remote learning scenarios: a digital wall as a reflective tool for students to develop mathematics problem-solving competencies
  • Lessons learned about the application of adaptive testing in several first-year university courses

Special issue published: "Sustainability, Governance and Responsibility"

International Journal of Public Sector Performance Management 11(4) 2023

  • An empirical investigation on mitigation of bullwhip effect: practices perspective
  • The impact of customer's awareness level on the sustainability of payment banks in India
  • Forecasting the stock return of emerging economies: an empirical study based on ARIMA
  • Competitive advantage through sustainable supply chain management: an insight into Indian automotive sector
  • Role of university libraries in Sustainable Development Goals realisation
  • Achieving sustainability through GST: a step towards economic growth
  • Inclusive development and environmental sustainability
  • A pragmatic study of India: productivity analysis

Free open access article available: "O'FAIRe makes you an offer: metadata-based automatic FAIRness assessment for ontologies and semantic resources"

The following paper, "O'FAIRe makes you an offer: metadata-based automatic FAIRness assessment for ontologies and semantic resources" (International Journal of Metadata, Semantics and Ontologies 16(1) 2022), is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

8 June 2023

Special issue published: "The Design and Management of Serviceability Products and Systems, Smart Industrial and Manufacturing Systems"

International Journal of Manufacturing Technology and Management 37(2) 2023

  • Measurement of suction cups release time for press line
  • An integrated storage method of Industry 4.0 processing data based on big data mining
  • Calibration method for mechanical accuracy of drug dissolution meter based on wavelet transform
  • Full compensation method of thermal error of NC machine tool based on sequence depth learning
  • A fuzzy PID control method of step response of torque hydraulic mechanical transmission
  • Intelligent colour selection method for product packaging design based on particle swarm optimisation
  • Life-cycle cost assessment method for industrial products based on fuzzy fault tree
  • An optimisation method of factory terminal logistics distribution route based on K-means clustering
  • An enterprise logistics cost management method under the trend of Industry 4.0

Research pick: Online food - "Assessing the factors influencing continued use of online-food-delivery services and the impact on health: a multi-group analysis"

Research in the International Journal of Services and Operations Management has investigated what influences the use of online food delivery services in India and the impact that is having on public health. The online food delivery sector in India has annual revenues of well over $7 billion. A significant proportion of this sector, about 85 percent, is restaurant-to-consumer services and the remainder, is services by direct providers.

The suspicion is that increasing reliance on food other than home-cooked food could be affecting lifestyle and health by side-stepping the traditional activities involved in preparing and eating a meal with family, friends, or even alone. Additionally, there are issues surrounding the quality of food delivered to one’s door in terms of calorific content, how much of the food is considerably processed, and the presence of additives. Conversely, some food from suppliers may well be more nutritious and the time freed up from the drudge of cooking and clearing up may well allow people to be involved in other quality activities with those family and friends.

Arghya Rayof the International Management Institute Kolkata, Pradip Kumar Bala of the Indian Institute of Management Ranchi, India, and Rashmi Jain of the Feliciano School of Business in Montclair, New Jersey, USA, explain that the advent of online food delivery services has had a significant effect on the food industry and our lifestyles in recent years. The team used a mixed-method approach, starting with preliminary qualitative interviews of online food delivery service users and followed by a quantitative survey of almost 300 Generation Y users in India. Generation Y is commonly defined as people born between around 1981 to 1996.

The team found that emotional values, conditional values, monetary values, and health consciousness all had a significant impact on consumers’ intention to use online food delivery services. Moreover, continued use leads to ongoing changes in food consumption patterns. The researchers point out that their work may not necessarily extrapolate to other countries, especially those with very different food standards.

The team suggests that suppliers should improve standards given the ever-increasing use of online food delivery services if there is not to be a long-term and potentially detrimental impact on consumers. The findings also point to differences based on gender, age, and location, such data might allow those same providers to better tailor what they offer consumers to particular demographics.

Ray, A., Bala, P.K. and Jain, R. (2023) ‘Assessing the factors influencing continued use of online-food-delivery services and the impact on health: a multi-group analysis’, Int. J. Services and Operations Management, Vol. 45, No. 1, pp.1–36.

Free sample articles newly available from International Journal of Bioinformatics Research and Applications

The following sample articles from the International Journal of Bioinformatics Research and Applications are now available here for free:
  • Classification of breast cancer images using completed local ternary pattern and support vector machine
  • Gestational age determination of ultrasound foetal images using artificial neural network
  • Configuring artificial neural network using optimisation techniques for speaker voice recognition
  • Artificial neural network model for detection and classification of alcoholic patterns in EEG
  • Optimisation of sub-space clustering in a high dimension data using Laplacian graph and machine learning
  • Privacy preserving reversible watermarking in the encrypted domain through self-blinding
  • ANN model for detection and classification of sleep and non-sleep stages
  • Nearest neighbour-based feature selection and classification approach for analysing sentiments
  • Recursive subspace based feature selection approach for early risk prediction of chronic disease in patients

Dr. Jun Li appointed as new Editor in Chief of International Journal of Lifecycle Performance Engineering

Dr. Jun Li from Curtin University in Australia has been appointed to take over editorship of the International Journal of Lifecycle Performance Engineering. The departing Editor in Chief, Prof. Hong Hao, will remain with the journal in the capacity of Advisory Editor.

7 June 2023

Free sample articles newly available from International Journal of Sustainable Materials and Structural Systems

The following sample articles from the International Journal of Sustainable Materials and Structural Systems are now available here for free:
  • Comparison between honeycomb and composite corrugated cores in sandwich panels under compression loading
  • Structural health monitoring of composites from carbon nanotube coated e-glass fibre
  • Damage reduction countermeasures for short span bridges focusing on restorability of structural joints
  • A strategic framework for resilient and sustainable urban infrastructure systems - an overview, modelling, design and assessment
  • From event to performance function-based resilience analysis and improvement processes for more sustainable systems
  • Present and future resilience research driven by science and technology
  • Resilience and sustainability of FRP-retrofitted concrete structures
  • Resilient isolation-structure systems with super-large displacement friction pendulum bearings
  • Resilience and recoverability enhancement of concrete structures

Special issue published: "Smart Bio-Signal Acquisition System – Part I"

International Journal of Nanotechnology 20(1/2/3/4) 2023

  • Deep learning-based feature extraction coupled with multi class SVM for COVID-19 detection in the IoT era
  • Fishier mantis optimiser: a swarm intelligence algorithm for clustering images of COVID-19 pandemic
  • Smart approach in impact of cumin powder on obesity among adults in urban area of Puducherry, India
  • Bioanalytical method development and validation of a novel antiseizure agent Cenobamate using LC-MS/MS
  • A dynamic programming approach for accurate content-based retrieval of ordinary and nano-scale medical images
  • Small cell lung tumour differentiation using F-18 (Fluorine-18) PET and smoothing using Gaussian 3D convolution operator
  • Analysis of high dimensional data using feature selection models
  • Improved generalised fuzzy peer group with modified trilateral filter to remove mixed impulse and adaptive white Gaussian noise from colour images
  • A novel and intelligent decision-making system for real-time healthcare tracking using commercial wearable data
  • Diagnosing cardiovascular disease via intelligence in healthcare multimedia: a novel approach
  • Wearable IoT enabled smart heart disease monitoring on WSN
  • Image feature extraction algorithm based on parameter adaptive initialisation of CNN and LSTM
  • An improved model for unsupervised voice activity detection
  • Low area FPGA implementation of modified histogram estimation architecture with CSAC-DPROM-OBC for medical image enhancement application
  • Groundwater quality index and human health risk assessment of heavy metals in and around Asansol industrial area, West Bengal, India
  • Research progress of adoption of hyperbranched polymer nano materials in textile industry
  • The combined study of improved fuzzy optimisation techniques with the analysis of the upgraded facility location centre for the Covid-19 vaccine by fuzzy clustering algorithms
  • Remote IoT correspondence for coordinating end-devices over MANET via energy-efficient LPWAN
  • Dimension adaptive hybrid recovery with collaborative group sparse representation based compressive sensing for colour images
  • A low power transistor level FIR filter implementation using CMOS 45 nm technology
  • Research on intelligent city traffic management system based on WEBGIS
  • Unsupervised voice activity detection with improved signal-to-noise ratio in noisy environment
  • COVID-19 detection and tracking using smart applications with artificial intelligence

Research pick: Avoiding bird nest powercuts - "Real-time detection system of bird nests on power transmission lines based on lightweight network"

Research in the International Journal of Wireless and Mobile Computing addresses a significant safety issue facing power supply companies – the presence of bird nests on power line towers and other infrastructure.

Haopeng Yang and Enrang Zheng of the School of Electrical and Control Engineering at Shaanxi University of Science and Technology, and Yichen Wang and Junge Shen of the Unmanned System Research Institute at the Northwestern Polytechnical University all in Xi’an, Shaanxi, China, have developed a real-time detection system capable of swiftly identifying bird nests on transmission towers.

At first glance, one might imagine that the presence of a nest on a power transmission tower, or pylon, would be harmless, but there are serious issues with damage and the potential for avian activity to “trip” safety cutouts on power systems, leading to outages for consumers. This is particularly true of substantial nests built high up on pylons by raptors, storks, and other large species.

Unfortunately, the detection of such small objects as bird nests and the passing of the information back to a control centre have represented an ongoing challenge due to their small size and the potential data loss during detection. The team’s new system, uses an algorithm that can identify and so detect bird nests at different scales allowing for rapid risk identification. An unmanned aerial vehicle (UAV), often referred to as a drone, fitted with a camera can patrol the towers, record and analyse images using an onboard computer running the team’s algorithm and report back to the controllers with information that flags specific towers with a nest problem. The team’s algorithm readily overcomes the problem of the background scenery in an image of a pylon being checked detecting only the presence of nests.

The research team says they have achieved an average accuracy rating of 90.05%. This high level of performance meets the demands of the State Grid for high-precision and real-time line maintenance inspections. The automated detection system precludes the need for costly regular manual inspections.

Yang, H., Zheng, E., Wang, Y. and Shen, J. (2023) ‘Real-time detection system of bird nests on power transmission lines based on lightweight network’, Int. J. Wireless and Mobile Computing, Vol. 24, Nos. 3/4, pp.217–225.

Free sample articles newly available from International Journal of Strategic Change Management

The following sample articles from the International Journal of Strategic Change Management are now available here for free:
  • Watch and progress strategy: a case study approach of India's Covid-19 pandemic situation
  • Adopting a grounded theory approach for managing corporate culture change
  • The impact of organic transformation: strategies and innovative ideas towards profitability - a case of Hathikuli Tea Estate
  • Is a cooperation of Latvian forest owners a viable strategic choice? Exploring a collaborative competitive advantage
  • Organisational strategy making and first-line manager challenges: a building and dwelling perspective

6 June 2023

Free sample articles newly available from International Journal of Web Engineering and Technology

The following sample articles from the International Journal of Web Engineering and Technology are now available here for free:
  • Using seagull optimisation algorithm to select mobile service in cloud and edge computing environment
  • Website user experience model: testing on journalists
  • The role of sentiment analysis in a recommender system: a systematic survey
  • A hybrid approach for aspect-based sentiment analysis using a double rotatory attention model

Free sample articles newly available from International Journal of Metadata, Semantics and Ontologies

The following sample articles from the International Journal of Metadata, Semantics and Ontologies are now available here for free:
  • Analysis of structured data on Wikipedia
  • Children's art museum collections as Linked Open Data
  • Documenting flooding areas calculation: a PROV approach
  • Persons, GLAM institutes and collections: an analysis of entity linking based on the COURAGE registry
  • An ontology-driven perspective on the emotional human reactions to social events
  • Applying cross-data set identity reasoning for producing URI embeddings over hundreds of RDF data sets

Research pick: In debt to fashion - "I saw it, I bought it! The irrational buying behaviour in retail sector"

The Indian retail industry contributes more than 10 percent to the country’s gross domestic product (GDP). A new study looks at how impulsive and non-rational consumer behaviour in the Indian clothing sector potentially leading to personal debt can have a detrimental effect on the economy as a whole. Moreover, the work points to how promoting more rational purchasing decisions could be better for consumers as well as leading to a more sustainable and responsible industry.

Of course, marketers work to promote products and they will use emotional means to do so that will often trigger a non-rational response from a would-be customer. Conversely, who, in a free society, is to tell a customer what they do and don’t need when it comes to clothes shopping. After all, people buy clothes for obvious practical reasons, but also for self-expression, for enjoyment, and many other non-practical reasons.

Komal Malik and Manoj Joshi of the Amity Business School at Amity University Uttar Pradesh, Lucknow Campus, used an experiential research design to survey and capture non-rational behaviour shopping behaviour among Indian consumers. “Non-rationality can be referred as the influence of emotional factors rather than tangible gains and losses associated with a choice,” the authors write. In addition, in their paper in the International Journal of Business and Globalisation, they reviewed the existing literature to provide context. The team’s analysis considered factors such as brand loyalty, gift and special occasion purchases, social affinity, lifestyle choice, the feel-good factor, offers and discounts, changing fashion, personality.

The researchers found that consumer behaviour was driven by rational as well as non-rational factors, but it was the latter, associated with impulse purchases that was often associated with consumers spending on credit. If such consumers do not have the funds or disposable income to back their purchases then repeated impulse buys, has the potential to lead to greater debt. Understanding and addressing this behaviour is crucial for both marketers and policymakers, the research suggests.

Malik, K. and Joshi, M. (2023) ‘I saw it, I bought it! The irrational buying behaviour in retail sector’, Int. J. Business and Globalisation, Vol. 34, No. 1, pp.17–27.

Free sample articles newly available from International Journal of Nanotechnology

The following sample articles from the International Journal of Nanotechnology are now available here for free:
  • Analysis on measurement of hydrogen concentration in air mixture using 3 omega method
  • Numerical study on thermophoresis of dust in air Tu Thien Ngo; Dong-Wook Oh
  • Analysis of combustion characteristics using CPFD in 0.1 MWth oxy-fuel CFB
  • Evaluation of sorption test of iodide on carbon nanotubes to support anionic radionuclide immobilisation method
  • Measurement of thermal diffusivity of gold nanofluid according to particle size and temperature
  • Measurement of thermo-optic coefficient of silicon dioxide nanofluid using interferometer
  • Study on the optical characteristics according to the anion and cation in the ionic liquid and MWCNT ionanofluid
  • Evaluation on the photothermal conversion performance of SiC nanofluid for a direct absorption solar collector
  • Effect of precipitation of silicone oil-based nanofluid on thermal conductivity
  • Thermophysical properties of Ni-based Waspaloy alloy changed with tungsten, titanium and aluminium
  • Evaluation of high-speed rotation properties of LiCl-KCl molten salt with MgO binder

5 June 2023

Research pick: Just how FAIR are your digital, scientific resources? - "O’FAIRe makes you an offer: metadata-based automatic FAIRness assessment for ontologies and semantic resources"

Currently, there is no established method for automatically assessing the level of FAIRness (Findability, Accessibility, Interoperability, and Reusability) of semantic resources. The term “semantic resources” refers to various types of data, information, or knowledge artefacts that are represented in a structured and standardized way. These resources can include ontologies (technical, structured glossaries), vocabularies, data sets, and other relevant knowledge. An example is the AgroPortal semantic resource repository, an online platform for storing and organizing semantic resources related to the domain of agri-food and environment.

Writing in the International Journal of Metadata, Semantics and Ontologies, a team from France has used the AgroPortal as a case study to help them develop a metadata-based automatic assessment methodology for such resources, which they call Ontology FAIRness Evaluator (O’FAIRe).

Emna Amdouni, Syphax Bouazzouni, and Clement Jonquet of the University of Montpellier explain that making digital scientific data openly available remains an important challenge for the scientific community and funding agencies. The FAIR movement arose in 2014 to help address this challenge and has been largely embraced. However, FAIR, as many observers have pointed out, is only representing specifications for digital objects, or entities, rather than being a standardised or technically based system. There has thus been a need for a way to independently assess how well an entity adheres to the principles of FAIR.

In this context, the team’s proposal is aligned with existing initiatives and consists of 61 questions, primarily based on metadata descriptions, and using ontology libraries or repositories to ensure unified metadata for FAIRness assessment. The team implemented O’FAIRe in AgroPortal and successfully conducted a preliminary FAIRness analysis of 149 semantic resources in the agri-food/environment domain. The proposal should allow FAIR digital entities to be assessed objectively pushing us towards a more encompassing system in which entities and resources can be read and used competently equally well by humans and computers without barriers and problems arising because of inconsistencies across and within domains.

The researchers conclude that their work addresses many of the scientific and technical challenges regarding the implementation of the 15 FAIR principles for ontologies and semantic resources. The team writes that their work might now “guide the semantic community to put the FAIR principles into practice and enable them to qualify the degree of FAIRness of their semantic resource.”

Amdouni, E., Bouazzouni, S. and Jonquet, C. (2022) ‘O’FAIRe makes you an offer: metadata-based automatic FAIRness assessment for ontologies and semantic resources’, Int. J. Metadata Semantics and Ontologies, Vol. 16, No. 1, pp.16–46.

2 June 2023

Research pick: Blogging influencers could be music to a marketeer’s ears - "Classifying bloggers based on content creation approaches: implications for influencers marketing strategies"

In the ever-changing digital landscape, bloggers have risen to prominence as influencers, playing an important role in helping consumers pick and choose the products and services on which they want to spend their time and money. However, even with the many disparate social media apps that distract consumers from “traditional” blogs, there remains a huge number who have influence across many different spheres and represent a useful resource for marketers.

The problem remains how to identify and classify the many, many bloggers for best impact in a marketing campaign. A research study in the International Journal of Internet Marketing and Advertising shows how a comprehensive framework can classify consumer bloggers based on their unique content creation approach.

Beatrice Ietto and Federica Pascucci of the Università Politecnica delle Marche in Ancona, Italy, have drawn on social-practice theory to construct their classification framework. In this theory, content creation is viewed as habitual behavior shaped by socio-cultural contexts. The team has focused on an extensive netnographic analysis of Australian music bloggers to offer new insights into the critical factors that influence a blogger’s content creation approach.

The work shows that blogger in this niche create content primarily driven by their subjective evaluation of four key dimensions: personal influences, audience influences, community influences, and commercial influences. These dimensions play a pivotal role in shaping the blogger’s content creation strategies and determining the nature of their engagement with their readership.

With the details of these insights to hand, the team created a multidimensional framework for the classification of bloggers as “passionate”, “hype followers”, “sophisticated and sub-cultural”, “celebratory and overly positive, and the “professionals”. The framework could offer marketing practitioners a useful resource for identifying and collaborating with the most appropriate bloggers that mesh well with their promotional strategies. The framework goes beyond the simplistic metrics of site “hits” and “reach” and looks at how the blog functions and how that would seamlessly work with a marketing campaign.

Ietto, B. and Pascucci, F. (2023) ‘Classifying bloggers based on content creation approaches: implications for influencers marketing strategies’, Int. J. Internet Marketing and Advertising, Vol. 18, No. 4, pp.335–358.

1 June 2023

Research pick: What’s up Whatsapp? Cracking evidence from messenger apps - "A platform independent and forensically sound method to extract WhatsApp data from mobile phones"

WhatsApp use has grown rapidly in recent years, allowing users to send text messages, voice, and video over an internet connection safe in the knowledge that third parties cannot intercept their correspondence without somehow breaking the end-to-end encryption used by the app.

The app is a boon for the security conscious, the socially vulnerable, and those with something to hide, such as rogue politicians. Of course, an app owned by a large corporate entity, in this case Meta (formerly Facebook) will be subject to legal pressure in the USA when it comes to allowing law enforcement access to those encrypted messages. Elsewhere those seeking to undertake criminal investigation may need a warrant to allow them to crack in order to obtain evidence for a prosecution or public inquiry, for instance.

Research in the International Journal of Electronic Security and Digital Forensics, offers a way to overcome this significant obstacle in obtaining admissible evidence from Whatsapp for use in court. The work could lead to fewer inconclusive investigations and more successful criminal prosecutions.

The new algorithmic approach to Whatsapp forensics developed by Aritro Sengupta and Amit Singh of India’s Ministry of Electronics and Information Technology in New Delhi and B.M. Vinjit of the National Institute of Technology in Haryana, India, sidesteps the specific hardware and software specifications of a mobile phone and allows Whatsapp data to be recovered from any device and even those seized phones that would not normally succumb to conventional forensic analysis. Moreover, the forensic analysis leaves no digital footprint and so does not compromise the evidence.

The demonstration suggests that law enforcement agencies and forensic investigators now have a forensically sound method of extracting WhatsApp data, streamlining their investigations, and bolstering their ability to build a strong case. The team will continue developing their forensic tools so that they might also be used with messenger apps other than Whatsapp.

Sengupta, A., Singh, A. and Vinjit, B.M. (2023) ‘A platform independent and forensically sound method to extract WhatsApp data from mobile phones’, Int. J. Electronic Security and Digital Forensics, Vol. 15, No. 3, pp.259–280.