Manesh Muraleedharan, Mounika P.A. and Alaka Chandak
Kerala, a southern state in India, is acknowledged for its socio-economic reforms such as quality health care, gender parity, high literacy rate and more. However, recent trends…
Abstract
Purpose
Kerala, a southern state in India, is acknowledged for its socio-economic reforms such as quality health care, gender parity, high literacy rate and more. However, recent trends show that the state has the highest incidence of various noncommunicable diseases in the country, including diabetes, hypertension and heart coronary artery disease. This research paper aims to examine the link between the Kerala population’s lifestyle, diet and genetic factors and its correlation with a heightened cardio-metabolic risk.
Design/methodology/approach
Using Dixon Wood’s interpretive synthesis, this qualitative literature review is systematically used by searching, gathering articles, theme building, comparing and criticising the evidence.
Findings
The result shows that only minimal evidence is available regarding the genetic makeup of the Kerala community, food patterns and its link to the high prevalence of non-communicable diseases (NCDs). However, limited and contradicting evidence and studies restricted to a particular region in the state demand more research on this domain.
Originality/value
It is vital to review the diet habits of Keralites due to the alarmingly high prevalence of NCDs. To the best of the authors’ knowledge, this is the first comprehensive review of the diet habits of Kerala and their link to NCDs.
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Mounika Mude and J. Reeves Wesley
Research on work–family interface (WFI) is almost two decades old. It is widely believed that the archetype of work and family after COVID has changed. Post-COVID emphases and…
Abstract
Purpose
Research on work–family interface (WFI) is almost two decades old. It is widely believed that the archetype of work and family after COVID has changed. Post-COVID emphases and outcomes would be different. Accordingly, a bibliometric analysis of the research would help to understand the state of the research and positive WFI patterns that guide further investigations. The present study used measures such as journals, citations, etc. to determine the bibliometric patterns from 2003 to August 2023 using VOSviewer software.
Design/methodology/approach
Data were obtained from Scopus. 1,601 works were found in the first search. This figure was narrowed down to 525 based on a few conditions. The most commonly referenced journals, sources, authors, etc. were used for the analysis.
Findings
Research on positive WFI has increased in recent years. The total number of articles in positive WFI was 525 between 2003 and August 2023. Greenhaus, Powell and Carlson were the most cited authors in this field. Carlson had produced the highest number of documents in WFI. Most WFI authors focused on antecedents, treating positive WFI as the outcome variable.
Research limitations/implications
This is the first bibliometric analysis conducted on a positive WFI, although there have been a few on work–family conflict. However, other sources such as the Australian Business Deans Council (ABDC) and Web of Science may throw different results on journals, citations, etc. Hence, future researchers might emphasize if the same results originate from data in other databases. Other analytical tools may be used in the place of VOSviewer.
Originality/value
This is the first article on bibliometric analysis of positive WFI. This paper’s primary objective is to understand the patterns of literature available on positive WFI and its significance comprehensively.
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Rajkumar Devapiriam, Karthik S. and Santhy K.
The purpose of this study is to fabricate and compare the mechanical and thermal properties of Sansevieria and Kaans fiber reinforced polyester matrices composites.
Abstract
Purpose
The purpose of this study is to fabricate and compare the mechanical and thermal properties of Sansevieria and Kaans fiber reinforced polyester matrices composites.
Design/methodology/approach
Treated Sansevieria and Kaans fiber was used as reinforcement for the fabrication of polymer matrix composites. Kaans fiber, which was available plenty in the delta region, but physical and mechanical properties of Kaans fiber were low when it compared with Sansevieria fiber. To make use of Kaans fiber for the fabrication of composite, the physical and mechanical properties have to be enhanced. So Egg shell powder was selected as a filler material to enhance the Kaans fiber reinforced composite. The selected fibers were properly weaved after alkali treatment. A three-layered (0°/45°/0°) Sansevieria fiber reinforced polymer (S-FRP) and Kaans fiber reinforced polymer (K-FRP) composite plates were fabricated using the compression molding method. As per American Society for Testing and Materials standards, the specimens were cut and mechanical, thermal and absorption properties of Sansevieria and Kaans fiber composites were investigated experimentally.
Findings
Tensile and flexural test reveals that K-FRP composite has good ductility and bending property than S-FRP composite plate. But from the other test results, S-FRP possesses high elongation capability than K-FRP. Thermo gravimetric analysis, moisture absorption and swelling test too done which clearly appeared S-FRP composite plate has prevalent execution than K-FRP composite plate.
Originality/value
This original research study enlists the mechanical, thermal properties and absorption properties of fabricated S-FRP and K-FRP composite plates.
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Mamookho Elizabeth Makhatha, Makgadiete Grace Salemane and Akinsanya Damilare Baruwa
In response to the growing demand for a polymer with improved chemical and thermal stability in the construction sector, this study aims to thoroughly explore the characteristics…
Abstract
Purpose
In response to the growing demand for a polymer with improved chemical and thermal stability in the construction sector, this study aims to thoroughly explore the characteristics of silver nanoparticles (AgNP) and their various concentrations. The primary goal is to determine the effect of these nanoparticles on the chemical and thermal stability of unsaturated polyester (UPE) resin doped with dimethyl-para-toluidine (DMPT) when exposed to high temperatures.
Design/methodology/approach
Silver nanoparticles were first synthesized from the chemical reaction between silver nitrate and trisodium citrate before its addition to the resin. The nanocomposites were thoroughly examined using advanced analytical methods such as Fourier transform (FTIR), Raman spectroscopy and scanning electron microscope to determine chemical stability. Thermal stability tests were carried out using thermogravimetric analysis, differential thermal analysis and derivative thermogravimetry methods; viscosity and peak exotherm were also examined.
Findings
The data shows that increasing nanoparticle concentration improves resin chemical stability, reduces peak exotherm duration and increases viscosity. Clearly, only 1.5% AgNP concentration outperformed neat UPE resin, while 0.5% and 1% AgNP concentrations fall short in terms of thermal stability.
Originality/value
The enhanced resin highlights the subtle influence of nanoparticle addition, which has a greater impact on the chemical structure of the composite rather than its thermal properties.
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Ping Huang, Haitao Ding, Hong Chen, Jianwei Zhang and Zhenjia Sun
The growing availability of naturalistic driving datasets (NDDs) presents a valuable opportunity to develop various models for autonomous driving. However, while current NDDs…
Abstract
Purpose
The growing availability of naturalistic driving datasets (NDDs) presents a valuable opportunity to develop various models for autonomous driving. However, while current NDDs include data on vehicles with and without intended driving behavior changes, they do not explicitly demonstrate a type of data on vehicles that intend to change their driving behavior but do not execute the behaviors because of safety, efficiency, or other factors. This missing data is essential for autonomous driving decisions. This study aims to extract the driving data with implicit intentions to support the development of decision-making models.
Design/methodology/approach
According to Bayesian inference, drivers who have the same intended changes likely share similar influencing factors and states. Building on this principle, this study proposes an approach to extract data on vehicles that intended to execute specific behaviors but failed to do so. This is achieved by computing driving similarities between the candidate vehicles and benchmark vehicles with incorporation of the standard similarity metrics, which takes into account information on the surrounding vehicles' location topology and individual vehicle motion states. By doing so, the method enables a more comprehensive analysis of driving behavior and intention.
Findings
The proposed method is verified on the Next Generation SIMulation dataset (NGSim), which confirms its ability to reveal similarities between vehicles executing similar behaviors during the decision-making process in nature. The approach is also validated using simulated data, achieving an accuracy of 96.3 per cent in recognizing vehicles with specific driving behavior intentions that are not executed.
Originality/value
This study provides an innovative approach to extract driving data with implicit intentions and offers strong support to develop data-driven decision-making models for autonomous driving. With the support of this approach, the development of autonomous vehicles can capture more real driving experience from human drivers moving towards a safer and more efficient future.
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Kieran D. Beaumont, Joseph R. Kubalak and Christopher B. Williams
Material extrusion (MEX) additive manufacturing often requires support structures to enable manufacture of steep overhanging features. Multi-axis deposition (often enabled by a…
Abstract
Purpose
Material extrusion (MEX) additive manufacturing often requires support structures to enable manufacture of steep overhanging features. Multi-axis deposition (often enabled by a robotic arm) offers novel toolpath planning methods that can significantly reduce or eliminate supports. However, there is currently a lack of established design guidelines for the process.
Design/methodology/approach
This study investigates the relationship between achievable, support-free overhangs and the multi-axis build direction. Although altering build directions mid-print can increase the layer-to-layer overlap of an overhanging feature, the deposition paths on the overhanging surface may be less supported with respect to gravity. To interrogate these effects, a 6-degree-of-freedom robotic arm MEX platform printed test pieces with overhang angles (relative to the build direction) increasing from 0° to 75° at build directions varying from 0° (i.e., XY-planar) to 60° with respect to the global Z-axis.
Findings
Characterization of printed surface quality revealed no statistically significant difference in the fidelity of the overhanging surface as the build direction was changed. These results suggest that the overhang threshold observed in traditional XY-planar printing (typically 45°) remain consistent regardless of build direction (e.g. a build direction of 60° successfully printed a relative overhang of 45°), indicating that deposition quality was not negatively impacted by gravitational forces.
Originality/value
This study provides insight into how tool orientation can be optimized to maximize part accuracy and minimize support material requirements; after quickly screening for the XY-planar overhang threshold, designers can freely select multi-axis build directions throughout part geometries, provided the overhanging surfaces are below that relative threshold.
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Adil Ellikkal and S. Rajamohan
In today’s highly competitive world, the purpose of this research is to emphasize the increasing significance of management education and advocate for the adoption of innovative…
Abstract
Purpose
In today’s highly competitive world, the purpose of this research is to emphasize the increasing significance of management education and advocate for the adoption of innovative teaching approaches, specifically focusing on artificial intelligence (AI)-driven personalized learning (PL). This study aims to explore the integration of self-determination theory (SDT) principles into management education, with a primary focus on enhancing student motivation, engagement and academic performance (AP).
Design/methodology/approach
This interdisciplinary research adopts a multifaceted approach, combining perspectives from AI, education and psychology. The design and methodology involve a thorough exploration of the theoretical foundations of both AI-driven education and SDT. The research demonstrates how these two elements can synergize to create a holistic educational experience. To substantiate the theoretical claims, empirical data-driven analyses are employed, showcasing the effectiveness of AI-enabled personalized learning (AIPL). The study integrates principles from SDT, such as autonomy, competence and relatedness, to create an environment where students are intrinsically motivated, receiving tailored instruction for optimal outcomes.
Findings
The study, rooted in SDT, demonstrates AIPL’s transformative impact on management education. It positively influences students’ autonomy, competence and relatedness, fostering engagement. Autonomy is a key driver, strongly linked to improved AP. The path analysis model validates these relationships, highlighting AI’s pivotal role in reshaping educational experiences and intrinsically motivating students.
Practical implications
This study holds substantial significance for educators, policymakers and researchers. The findings indicate that the AIPL model is effective in increasing student interest and improving AP. Furthermore, this study offers practical guidance for implementing AI in management education to empower students, enhance engagement and align with SDT principles.
Originality/value
Contribute original insights through an interdisciplinary lens. Synthesize AI and SDT principles, providing a roadmap for a more effective educational experience. Empirical data-driven analyses enhance credibility, offering valuable contributions for educators and policymakers in the technology-influenced education landscape.
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Simran Kaur, Anil Panghal, M.K. Garg, Sandeep Mann, Sunil K. Khatkar, Poorva Sharma and Navnidhi Chhikara
The purpose of this paper is to review the nutritional and food value of pumpkin Cucurbita, along with different health benefits. Cucurbita (pumpkin) is an herbaceous vine, member…
Abstract
Purpose
The purpose of this paper is to review the nutritional and food value of pumpkin Cucurbita, along with different health benefits. Cucurbita (pumpkin) is an herbaceous vine, member of Cucurbitaceae family. It is an edible, heat-sensitive plant, which has an abundant amount of active compounds such as carotenoids, alkaloids, flavonoids, polyphenols, tannins, tocopherols, phytosterols and cucurbitacin, accounted for numerous health benefits, namely, antidiabetic, antioxidant, anticarcinogenic, hypotensive, hyper protective activities.
Design/methodology/approach
Major well-known bibliometric information sources such as Web of Science, Scopus, Mendeley and Google Scholar were searched with keywords such as nutrition value of Cucurbita, Cucurbita utilization, bioactive compounds of pumpkin, health benefits, processing, food formulations and current scenarios were chosen to obtain a large range of papers to be analyzed. A final inventory of 105 scientific sources was made after sorting and classifying them according to different criteria based on topic, academic field, country of origin and year of publication.
Findings
The comprehensive review of different literature, data sources and research papers seeks to find and discuss various nutritional benefits of pumpkin. It contains all necessary macro- and micro-nutrients, amino acids, vitamins, antioxidants and bioactive compounds with a relatively low amount of antinutrients. The recent upsurge in consumer interest for health-promoting products has opened up new vistas for plant products containing bioactive compounds in different food formulations.
Originality/value
This paper contains information regarding the chemical composition, nutritive value, phytochemical studies, pharmacological properties, bio-accessibility, food and industrial applications of pumpkin. Worldwide, pumpkin is used as food additive in various food products such as candy, weaning mix, corn grits, kheer, jam, crackers, bread, etc. Effect of different processing methods such as high temperature, pH, blanching, oven drying, freeze-drying to retain or minimize its losses in case of color, texture, flavor, and the carotenoids are of concern. The review paper highlights the nutritional, therapeutic, potential and processing attributes.
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Digital technology, which is regarded as a prominent and transformational force in modern society, encompasses a wide variety of technology that utilize digital data to process…
Abstract
Purpose
Digital technology, which is regarded as a prominent and transformational force in modern society, encompasses a wide variety of technology that utilize digital data to process, store and transfer various types of information. Digital technologies have continually been introduced as cutting-edge information tools in order to achieve effective management of vast information that arises from the prefabrication supply chain. However, without a sufficient performance evaluation, drawbacks of technology investment, such as financial losses and ineffective resource allocation, keep occurring, which hinders the widespread implementation of digital technologies. This study demonstrates a comprehensive evaluation of digital technologies’ effects on the prefabrication supply chain based on multi-criteria decision analysis (MCDA) theory.
Design/methodology/approach
Specifically, the targeted digital technologies and project constraints were first identified through a systematic literature review. The effects of the digital technologies were then scored using a questionnaire survey. The TOPSIS model was established to quantitatively rank the effectiveness of selected digital technologies.
Findings
Overall, BIM technology shone out in the rankings and is regarded as the most beneficial digital solution by multi-stakeholders to the existing constraints, such as working efficiency. Collaboration patterns between different stakeholders and technology integration trend were also indicated.
Originality/value
Compared with existing outcomes, this study specifically focused on examining the effects of digital technologies on the prefabrication supply chain, the most significant link in the process for prefabricated structures. New findings indicate the overall performance that considered both multi-stakeholders’ preferences and project constraints. The quantitative evaluation presents a comprehensive understanding of digital technologies’ effects, enabling industrial participants to reach well-informed, strategic and profitable investment decisions.
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This study investigates near field communication (NFC) payment method adoption in the Republic of Kosova, aiming to understand factors influencing consumer behavior toward NFC…
Abstract
Purpose
This study investigates near field communication (NFC) payment method adoption in the Republic of Kosova, aiming to understand factors influencing consumer behavior toward NFC technology adoption. Using the Unified Theory of Acceptance and Use of Technology (UTAUT-3) model and perceived risk theory, the research seeks to establish relationships between various factors and user intentions regarding NFC payment technology.
Design/methodology/approach
Using a quantitative approach, the research used a comprehensive questionnaire of 40 questions rated on a seven-point Likert scale across 16 constructs aligned with the research objectives. A convenience sampling method was used, distributing electronic questionnaires to 200 individuals representing diverse demographics in the Republic of Kosova.
Findings
The study identified significant support for numerous hypotheses, demonstrating substantial correlations between factors like performance expectancy, effort expectancy, social influence, habit, facilitating conditions and personal innovativeness with behavioral intention to use and behavioral intention to adopt NFC payments.
Research limitations/implications
Because convenience sampling was used, there are restrictions on the study’s sample size. Moreover, although the study delves into noteworthy elements impacting the adoption of NFC payment systems, it might not cover all possible factors that could influence consumer behavior in this regard.
Practical implications
Policymakers, NFC product developers, companies in the technology and payment sectors and Republic of Kosova customers all gain strategically from the research’s findings. Policymakers may make informed judgments about legislation, improve product development and marketing tactics and empower consumers to accept NFC payments by having a better understanding of consumer preferences and behaviors related NFC technology.
Social implications
Understanding consumer preferences and behaviors regarding NFC technology can refine product development and marketing strategies, inform policymaking and empower consumers’ decisions about adopting NFC payments.
Originality/value
This study’s innovative approach in combining the UTAUT-3 model and perceived risk theory contributes significantly to the understanding of factors influencing users’ intentions in adopting emerging payment technologies, filling a gap in NFC payment literature.