Naveen Joshi, Vijaya Lakshmi R. and Jitendra Kumar Singh
This study aims to explore the collective influence of several factors, namely, thermal radiation, Brownian motion, magnetic field and variable viscosity parameter, on the…
Abstract
Purpose
This study aims to explore the collective influence of several factors, namely, thermal radiation, Brownian motion, magnetic field and variable viscosity parameter, on the boundary layer flow, heat and mass transfer of an electrically steering nanofluid over a radially stretching exterior subjected to convective heating. In addition, the impacts of thermal and solutal buoyancy forces and activation energy are taken into account. The enlarging velocity is assumed to vary linearly with radial distance.
Design/methodology/approach
Through the similarity transformation technique, the governing highly nonlinear partial differential equations are transformed into a set of nonlinear ordinary differential equations, which are then numerically solved using the Runge–Kutta–Fehlberg method with a shooting technique.
Findings
Graphical depictions are provided to analyze the velocity, temperature and nanoparticle concentration fields under the influence of various pertinent parameters. Furthermore, local skin friction, local Nusselt and Sherwood numbers are quantitatively presented and discussed. A comparison with previous results demonstrates good agreement.
Originality/value
This study uniquely integrates multiple factors influencing boundary layer flow in electrically conducting nanofluids, offering a nuanced understanding of heat and mass transfer over radially stretching surfaces. By using advanced numerical methods, it provides valuable insights and quantitative data that can inform practical applications in engineering and materials science.
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Thamarassery Abduljaleel Jessin, A. Rajeev and R. Rajesh
Due to increasing uncertainty in the global business scenario, research on supply chain resilience is gaining significance. The outbreak of the COVID-19 pandemic has accelerated…
Abstract
Purpose
Due to increasing uncertainty in the global business scenario, research on supply chain resilience is gaining significance. The outbreak of the COVID-19 pandemic has accelerated and magnified the issues already pertaining in the supply chain thereby increasing the vulnerabilities in the network. This study attempts to build the concept of pseudo-resilience in supplier selection and evaluation for supply chain sustainability.
Design/methodology/approach
A combination of multi-criteria decision-making methods AHP and R is adopted, and an integrated method called Combined AHP–R method is used to identify and include the property of pseudo-resilience into supplier selection processes.
Findings
The authors identified various factors contributing to pseudo-resilience considering supplier selection process and found the most important attribute. Using the combined AHP–R method, the suppliers were evaluated, considering the attributes contributing to the pseudo-resilience of supply chains and best supplier was selected.
Originality/value
To the best of our knowledge, this is the first study addressing a supplier selection problem for sustainable supply chains, considering pseudo-resilience. Also, this is the first study to apply the AHP–R method for supplier selection in the resilience or sustainability context.
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Marie A. Yeh, Robert D. Jewell and Cesar Zamudio
This study aims to investigate age and gender differences in young consumers’ attribute preferences that underlie their choice decisions. This research proposes and finds that…
Abstract
Purpose
This study aims to investigate age and gender differences in young consumers’ attribute preferences that underlie their choice decisions. This research proposes and finds that attribute preferences are moderated by age but not gender. Understanding how children at different ages evaluate a product’s attributes is essential to new children’s product development.
Design/methodology/approach
Hierarchical Bayesian choice-based conjoint analysis was used to assess attribute importance via a series of choice tasks among children and adults. Adults completed the study by survey, whereas children were interviewed and led through the choice tasks.
Findings
This research finds that the preference structure for a product’s attributes differs systematically based on the age of children. Younger children chose based on perceptually salient attributes of a product, whereas older children chose based on cognitively salient attributes. When children’s attribute preferences are compared to adults, older children value attributes more similarly to adults than younger children. While gender differences were proposed and found, further analysis indicated that these differences were driven by adults in the sample and that no gender differences existed in the children’s age categories.
Originality/value
This study is the first to study children’s preference structure in complex choices with different ages preferring different attributes. By using conjoint analysis, this research is able to understand children’s underlying decision process, as utility scores are obtained providing a level of precision for understanding the underlying process of children’s choices that other studies have not used.
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Lakshmi Devaraj, Thaarini S., Athish R.R. and Vallimanalan Ashokan
This study aims to provide a comprehensive overview of thin-film temperature sensors (TTS), focusing on the interplay between material properties and fabrication techniques. It…
Abstract
Purpose
This study aims to provide a comprehensive overview of thin-film temperature sensors (TTS), focusing on the interplay between material properties and fabrication techniques. It evaluates the current state of the art, addressing both low- and high-temperature sensors, and explores the potential applications across various fields. The study also identifies challenges and highlights emerging trends that may shape the future of this technology.
Design/methodology/approach
This study systematically examines existing literature on TTS, categorizing the materials and fabrication methods used. The study compares the performance metrics of different materials, addresses the challenges encountered in thin-film sensors and reviews the case studies to identify successful applications. Emerging trends and future directions are also analyzed.
Findings
This study finds that TTS are integral to various advanced technologies, particularly in high-performance and specialized applications. However, their development is constrained by challenges such as limited operational range, material degradation, fabrication complexities and long-term stability. The integration of nanostructured materials and the advancement of wireless, self-powered and multifunctional sensors are poised to drive significant advancements in this field.
Originality/value
This study offers a unique perspective by bridging the gap between material science and application engineering in TTS. By critically analyzing both established and emerging technologies, the study provides valuable insights into the current state of the field and proposes pathways for future innovation in terms of interdisciplinary approaches. The focus on emerging trends and multifunctional applications sets this review apart from existing literature.
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Geeta Lakshmi, Hao Quach and Siobhan Goggin
Finance courses are major offerings in UK business schools, at various levels. Seldom do these courses move beyond theoretical modeling and textbook approaches. This is…
Abstract
Finance courses are major offerings in UK business schools, at various levels. Seldom do these courses move beyond theoretical modeling and textbook approaches. This is corroborated by the paltry literature on challenge-based learning (CBL) in the finance arena.
In this chapter, we describe the experience of implementing an investment fund designed by experienced members of staff and set up and run by students in one of the UK business schools in 2018. The seed capital of the Fund was donated by a variety of sources and has enabled students to use this as a jump start for their investment skills. The ethos of the Fund is not to teach students just how to invest but to put students in a real-life investment setting where they deal with the running of day-to-day activities of managing investments through a practical framework. In doing so they discover, adapt, and apply theoretical models to funds while preparing performance reports. Students have been successful in getting jobs by demonstrating their involvement, and the Fund has put them in touch with investment banks and future employers. The functioning of the Fund is analyzed in this chapter.
The chapter suggests the practical steps involved in setting up such a schema of CBL, which might aid other higher education institutions and promote entrepreneurial, creative, and team building activity.
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Cynthia M. Montaudon-Tomas, Anna Amsler and Ingrid N. Pinto-López
This chapter analyzes the way in which challenge-based learning (CBL) is conceptualized and used in a private university in Puebla, Mexico, to promote social innovation. The…
Abstract
This chapter analyzes the way in which challenge-based learning (CBL) is conceptualized and used in a private university in Puebla, Mexico, to promote social innovation. The university has recently changed its educational model, incorporating more integrative teaching and learning methodologies. The university has considered the 2030 Sustainable Development Goals (SDGs), especially the first goal to end poverty and the 10th regarding reducing inequality. These goals are relevant because the university is located in the state of Puebla, which has ranked fifth in the country (out of 32) in terms of poverty, especially in rural areas, where 58% of the population is living in poverty or extreme poverty conditions (CONEVAL, 2018). An example of a successful CBL project will be presented, showing how students have worked with their professors, community experts, and other stakeholders. In 2020, the university was recognized by the Times Higher Education World University Ranking as the number one university in Mexico to fight poverty based on the United Nations SDGs because of its CBL activities and social projects. Through these projects, students, administrators, and professors put into practice and develop different skills such as teamwork, analysis, facing new realities, innovating to design solutions to the problems in their environment, and beyond.
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Meltem Aksoy, Seda Yanık and Mehmet Fatih Amasyali
When a large number of project proposals are evaluated to allocate available funds, grouping them based on their similarities is beneficial. Current approaches to group proposals…
Abstract
Purpose
When a large number of project proposals are evaluated to allocate available funds, grouping them based on their similarities is beneficial. Current approaches to group proposals are primarily based on manual matching of similar topics, discipline areas and keywords declared by project applicants. When the number of proposals increases, this task becomes complex and requires excessive time. This paper aims to demonstrate how to effectively use the rich information in the titles and abstracts of Turkish project proposals to group them automatically.
Design/methodology/approach
This study proposes a model that effectively groups Turkish project proposals by combining word embedding, clustering and classification techniques. The proposed model uses FastText, BERT and term frequency/inverse document frequency (TF/IDF) word-embedding techniques to extract terms from the titles and abstracts of project proposals in Turkish. The extracted terms were grouped using both the clustering and classification techniques. Natural groups contained within the corpus were discovered using k-means, k-means++, k-medoids and agglomerative clustering algorithms. Additionally, this study employs classification approaches to predict the target class for each document in the corpus. To classify project proposals, various classifiers, including k-nearest neighbors (KNN), support vector machines (SVM), artificial neural networks (ANN), classification and regression trees (CART) and random forest (RF), are used. Empirical experiments were conducted to validate the effectiveness of the proposed method by using real data from the Istanbul Development Agency.
Findings
The results show that the generated word embeddings can effectively represent proposal texts as vectors, and can be used as inputs for clustering or classification algorithms. Using clustering algorithms, the document corpus is divided into five groups. In addition, the results demonstrate that the proposals can easily be categorized into predefined categories using classification algorithms. SVM-Linear achieved the highest prediction accuracy (89.2%) with the FastText word embedding method. A comparison of manual grouping with automatic classification and clustering results revealed that both classification and clustering techniques have a high success rate.
Research limitations/implications
The proposed model automatically benefits from the rich information in project proposals and significantly reduces numerous time-consuming tasks that managers must perform manually. Thus, it eliminates the drawbacks of the current manual methods and yields significantly more accurate results. In the future, additional experiments should be conducted to validate the proposed method using data from other funding organizations.
Originality/value
This study presents the application of word embedding methods to effectively use the rich information in the titles and abstracts of Turkish project proposals. Existing research studies focus on the automatic grouping of proposals; traditional frequency-based word embedding methods are used for feature extraction methods to represent project proposals. Unlike previous research, this study employs two outperforming neural network-based textual feature extraction techniques to obtain terms representing the proposals: BERT as a contextual word embedding method and FastText as a static word embedding method. Moreover, to the best of our knowledge, there has been no research conducted on the grouping of project proposals in Turkish.
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R. Dhanalakshmi, Dwaraka Mai Cherukuri, Akash Ambashankar, Arunkumar Sivaraman and Kiran Sood
Purpose: This chapter aims to analyse and highlight the current landscape of performance management (PM) systems, and the benefits of integrating modern technology such as smart…
Abstract
Purpose: This chapter aims to analyse and highlight the current landscape of performance management (PM) systems, and the benefits of integrating modern technology such as smart analytics (SA) and artificial intelligence (AI) into PM systems. The chapter discusses the application of AI in PM tasks which successively simplify many offline PM tasks.
Methodology: To carry out this analysis, a systematic literature review was performed. The review covers literature detailing PM components as well as research concerned with the integration of SA and AI into PM systems.
Findings: This study uncovers the merits of using SA and AI in PM. SA technology provides organisations with a clear direction for improvement, rather than simply state failure in performance. AI can be used to automate redundant tasks while retaining the human element of decision-making. AI also helps reduce the time required to take action on feedback.
Significance: The findings of this research provide insights into the use of SA and AI to make PM tasks fast, scalable, and error-free.
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Introduction: The internet of things (IoT) is the emerging technology of interconnected objects that can be termed as ‘things’ used to exchange data, connecting with different…
Abstract
Introduction: The internet of things (IoT) is the emerging technology of interconnected objects that can be termed as ‘things’ used to exchange data, connecting with different devices on the internet. It is the future where connected devices are controlled remotely. The insurance sector is one of the leading industries providing financial protection services to their customers to recover losses. Like others, the insurance industry uses the services very efficiently to solve their customer-centric problems and provide the best services to them. IoT in insurance is enhancing customer services.
Purpose: To determine how the insurance industry utilises the different IoT technologies to provide the best services and solutions to their users. The insurance sector is working on other areas of expertise to offer outstanding facilities to their clientele.
Methodology: We reviewed published material covering five years on IoT and insurance and customer services in the media, newspapers, journal publications, and the web. We determined how the insurance sector adapted the new terminology to contribute its best services to the users.
Findings: We observed that IoT services and technologies benefit the insurance industry and the clientele. This shows excellent results in the growth of the sector and heightened facilities for the consumers.