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This research investigates students’ information-seeking behaviours at the Indian Maritime University (IMU) and assesses the impact of AI chatbots on their marine science knowledge and awareness. The study aims to provide insights into the role of AI-driven solutions in enhancing knowledge sharing and the challenges faced in using AI tools for marine information retrieval.

The study used a stratified random sampling method, encompassing 152 respondents from IMU’s B.Sc. in Nautical Science and B. Tech in Marine Engineering programs. Data collection involved a structured electronic survey questionnaire. The analysis encompassed descriptive statistics using SPSS.

Information needs were met through diverse channels, with 57.9% of respondents using AI-driven chatbots for marine information retrieval. AI significantly recommended research papers (61.8%). The chatbot positively impacted marine science awareness and knowledge, with a mean satisfaction rating of approximately 3.3. Challenges included insufficient access to AI tools, data privacy concerns and accuracy issues.

This study contributes original insights into the information-seeking behaviours of marine students at IMU and the impact of AI chatbots on their knowledge and awareness. It highlights the multifaceted nature of marine information retrieval, the effectiveness of AI-driven solutions in enhancing knowledge sharing and the challenges that need to be addressed for the broader adoption of AI tools in this context.

This study aims to understand how the facesheet size, orientation and core size influence the analytical failure mechanism mode of glass fibre reinforced polymer (GFRP)/polyvinyl chloride (PVC) sandwich structures subjected to three-point bending. The purpose of this study was to develop failure-mode map of GFRP/PVC sandwich structures. Sandwich structures with different facesheet and core thicknesses were used to develop the failure map.

The sandwich structure and facesheet were fabricated using a vacuum-assisted resin infusion method with core sizes of 10, 15 and 20 mm and facesheet thicknesses of 1.5 and 3 mm and were arranged in three different orientations: angle-ply, cross-ply and quasi-isotropic. The key failure modes that occur in sandwich structures were used to predict possible failures in the developed material. Analytical equations were used in MATLAB for each observed failure mode. The probable failure modes, namely, face yielding, core shear and indentation equations, were used to construct the failure maps and were compared with the experimental data.

The boundary of the two failure modes shifts with changes in the facesheet and core thicknesses. The theoretical stiffness of sandwich panels was higher than the experimental stiffness. Based on strength-to-weight ratio, specimens E10-4, A15-8 and E20-8 exhibited the best optimum values owing to their shorter distance to the boundary lines.

In this study, a failure map was used to predict the possible failure modes for different GFRP facesheet orientations and thicknesses and PVC core thickness sandwich structures. Little is known about the prediction of the failure modes of unidirectional GFRP arranged in different orientations and thicknesses and PVC core thicknesses for sandwich structures. Few studies have used failure mode maps with unidirectional GFRP oriented in angle-ply, cross-ply and quasi-isotropic directions as a facesheet for sandwich structures compared to bidirectional mats. This study can serve as a guide for the correct selection of materials during the design process of sandwich structures.

Libraries, as a peaceful arena for promoting knowledge and culture, are often challenged by various means, which are mostly linked to the material handling. However, literature shorts fall in either recognizing how material handling comes under threat or evaluating the influence of promising solutions on the library’s performance. Thus, this study aims to present a comprehensive understanding of material handling in the library through the identification of characteristics, key performance indicators (KPIs) and challenges of this driving factor.

This research benefits from a triangulation of qualitative methods, including systematic literature review, case study, in-depth semi-structured interview (SSI) and focus group meetings, to present a comprehensive understanding of material handling in the library.

The initial findings highlight the characteristics, i.e. incremental inventory, no packaging, open access order, etc., and the KPIs of material handling in the library: flexibility, productivity, service quality and cost. In addition, the challenges that limit the libraries’ performance are discovered based on field observation through five Nordic libraries (Norway and Finland), which are further studied for discovering the potential remedies. Corollaries advise that material handling challenges in the library are potentially tackled through three pillars, known as Triple E’s: employee, equipment and environment.

The performance of libraries is notably linked to the material handling processes and this agenda has received limited attention by academia. This study is among the initial research efforts in this context seeking to develop a comprehensive understanding of the characteristics, KPIs and challenges of material handling in the library and facilitate the improvement of library’s performance.

The aim of this study is to employ the failure mode and effect analysis (FMEA) for risk management in cross-country pipelines, coupled with the utilization of Geographic Information System (GIS). The objective is to enhance the significance of the project, considering the potential severe consequences of pipeline failures. These consequences encompass environmental damages, loss of life and disruptions to critical services like energy and water supply. By identifying the most frequent causes of pipeline failures and developing a predictive model, the intention is to contribute toward the prevention of such incidents and minimize their impact.

A total quality management (TQM) technique for risk management; FMEA, was employed in this study integrated with GIS. Eight specific failures were identified and analyzed, exploring their effects and severity, causes and likelihood of occurrence as well as control and detection value. To find the likelihood of occurrence along the pipeline, the GIS was utilized to survey a 10 km wide area along the pipeline of 180 km long. Occurrence spatial mapping for each individual failure was generated. Subsequently, the risk priority number (RPN) was calculated for each failure, presenting the values as separate maps. By overlaying the RPN maps, a final map was generated, illustrating the areas with the highest risk along the pipeline.

A modified risk management model has been developed to detect potential pipeline failures before they escalate into catastrophic events. The results provide a visual representation of the average failure modes along the pipeline, clearly highlighting regions with varying probabilities of failure based on RPN values. The RPN has been meticulously calculated across the entire pipeline, with results presented through both 2D spatial mapping and a comprehensive line graph. This comprehensive approach sets our study apart from others in the field. Our emphasis on a thorough and inclusive risk assessment methodology represents a key novelty in this research. The findings underscore the paramount importance of proactive maintenance and regular inspection practices, with these measures emerging as critical strategies for enhancing the reliability and safety of pipeline infrastructure.

This research study aims to enhance the safety and quality of cross-country pipelines. The main limitations of the study include the inability to consider the risks associated with the flow characteristics inside the pipeline and the exclusion of the future master plan from our analysis.

The current integrated model is significant for pipeline operative companies and the oil and gas industries. These pipelines are susceptible to failures that can have alarming negative impacts on the environment, human safety and public health. It can improve the quality of risk management and elevate the safety integrity level of their pipelines. Focusing on the high-risk areas, taking action and implementing proactive measures can reduce the risk of failure and improve the safety and reliability of the pipeline system. It utilizes GIS-detailed surveying of the areas along the pipeline without the necessity of making on-site visits.

This study introduces a novel framework incorporating FMEA for quality risk management with advanced spatial mapping GIS software. This approach stands out as a unique contribution to the field, as prior studies have not undertaken the comprehensive task of highlighting risks along the entire pipeline using such a sophisticated methodology. This research makes a significant contribution to the field of crude oil transportation through pipelines, ultimately mitigating the risk of undesirable events.

Spiritual tourism is becoming a significant growth area of the Indian travel market, with more Indians opting to go on pilgrimage to popular religious cities. There are many spiritual destinations where some of this life's essences can be sought to enjoy harmony and peace. The study aims to prioritize motivators driving the intentions of the tourists to visit the spiritual destination.

The current study applied the analytical hierarchical process, a multi-criteria decision-making technique, on the sample of visitors from all the six spiritual destinations to rank the motivational factors that drive the intentions of the tourist to visit a spiritual destination.

The study's results postulated that spiritual fulfillment motives and destination atmosphere are the top prioritized motivations, while destination attributes and secular motives emerged as the least prioritized.

The research study provides valuable insights to the spiritual tourism industry stakeholders to target the tourists' highly prioritized motivations to augment the visits to a particular spiritual destination.

Previous research has explored the motivations and modeled their relationships with tourists' satisfaction and intentions. But, the present study has applied a multi-criteria decision-making technique to add value to the existing knowledge base.

This study proposes a new framework for business process improvement (BPI) by identifying areas of improvement based on customer complaints.

The proposed framework comprises several stages. The first stage captures the voice of customer (VoC) in the form of customer complaints. The complaints are processed using text mining and sentiment analysis. Negative sentiments indicate areas for improvement by matching words with SERVQUAL dimensions. The FMEA method is used to identify business processes that need to be improved.

The opposing quality dimensions of SERVQUAL can be incorporated into a database for later identifying consumer complaints. FMEA can be used to identify potential failures in aspects that correspond to consumer complaints; therefore, improvement areas can be identified. The proposed framework, applied to a garment manufacturer, shows that the SERVQUAL dimensions, which were originally intended for service companies, can be adapted to manage customer complaints to support BPI in manufacturing companies.

The framework can be used by either the manufacturing or service industries to handle customer complaints and use the complaint analysis results to identify improvement areas to avoid the same complaints occurring in the future.

In this study, the construction of a database based on the SERVQUAL dimension to match sentiment results, where negative sentiment indicates improvement, and the use of FMEA to indicate specific business processes that should be improved is novel and has not yet been proposed by previous studies.

Organizations are continually improving their practices to improve operational performance. They already employ Lean Manufacturing techniques (LM) to reduce unnecessary waste. Industry 4.0 techniques enhance operational performance in association with LM. Despite the proven benefits of LM principles and the advancements offered by Industry 4.0 technologies, many organizations struggle to integrate these approaches effectively. This research paper explores how LM principles can be combined with Industry 4.0 technologies to provide valuable guidance for businesses looking to adopt lean automation strategies.

A systematic literature review on LM and Industry 4.0 was done to investigate the possible technical integration of both methods. Ninety-two articles are extracted systematically from the Scopus and Web of Science databases. This study states a systematic literature review, including quantitative analysis of bibliographic networks and cluster analysis, to identify emergent ideas and their further implementation.

The research findings highlight the positive impact of integrating lean production with Industry 4.0 techniques, benefiting organizations in achieving their goals. A lean automation integration framework is proposed based on the literature review and the findings.

This study provides industry administrators and practitioners valuable guidance for enhancing organizational productivity. These implications can provide businesses with competitive advantages, enhance customer satisfaction, and enable them to adapt to the dynamic demands of the contemporary business environment.

This literature review study has substantially contributed to the technological integration of lean and Industry 4.0. The work has also identified potential emerging areas that warrant further research.

The purpose of this paper is to examine the mechanical characteristics and optimization of wear parameters of hybrid (TiO₂ + Y₂O₃) nanoparticles with Al matrix using squeeze casting technique.

The hybrid aluminium matrix nanocomposites (HAMNCs) were fabricated with varying concentrations of titanium oxide (TiO₂) and yttrium oxide (Y₂O₃), from 2.5 to 10 Wt.% in 2.5 Wt.% increments. Dry sliding wear test variables were optimized using the Taguchi method.

The introduction of hybrid nanoparticles in the aluminium (Al) matrix was evenly distributed in contrast to the base matrix. HAMNC6 (5 Wt.% TiO₂ + 5 Wt.% Y₂O₃) reported the maximum enhancement in mechanical properties (tensile strength, flexural strength, impact strength and density) and decrease in porosity% and elongation% among other HAMNCs. The results showed that the optimal combination of parameters to achieve the lowest wear rate was A3B3C1, or 15 N load, 1.5 m/s sliding velocity and 200 m sliding distance. The sliding distance showed the greatest effect on the dry sliding wear rate of HAMNC6 followed by applied load and sliding velocity. The fractured surfaces of the tensile sample showed traces of cracking as well as substantial craters with fine dimples and the wear worn surfaces were caused by abrasion, cracks and delamination of HAMNC6.

Squeeze-cast Al-reinforced hybrid (TiO₂+Y₂O₃) nanoparticles have been investigated for their impact on mechanical properties and optimization of wear parameters.

A review of relevant literature supported the need to examine the nature of the relationships (if any) between visionary leadership, continual improvement and product quality. This study examined the relationship between visionary leadership and product quality and investigated the mediating role of continual improvement in the relationship between visionary leadership and product quality.

Visionary leadership, continual improvement and product quality were measured through a questionnaire developed based on a theoretical framework derived from the literature and distributed to quality assurance managers in small and medium-sized companies in the engineering, electrical and information technology sectors in Jordan.

The results indicated that the levels of visionary leadership, continual improvement and product quality are good and more from the perspective of quality assurance managers in these companies. The results also indicated that there is a positive, statistically significant relationship between visionary leadership and continual improvement and between continual improvement and product quality. Moreover, the results indicated that the relationship between visionary leadership and product quality is partially mediated by continual improvement. This indicates that there is a direct, positive and statistically significant relationship between visionary leadership and product quality.

To the author’s knowledge, this is the first study that examined the relationship between visionary leadership, continual improvement and product quality and investigated the mediating role of continual improvement in the relationship between visionary leadership and product quality. This study concluded that visionary leadership is the driver of all improvement initiatives and activities, which in turn improve the final products. The study contributes to the literature by revealing that visionary leadership leads to continual improvement and thus product quality, supporting the sequential relationship between them. Accordingly, the study provides useful theoretical insights and practical implications.

The purpose of this study is to explore how past and future temporal focus of CEOs in the hospitality industry influence their intention to invest in metaverse technology and the underlying mechanism under boundary conditions of perceived competitive pressure.

This multi-informant study collected data over three waves from a sample of 235 CEOs and their subordinates in India’s hospitality industry. A PLS-SEM was applied to the study data. Further, the study also used phenomenological interviews to capture CEOs’ perspectives on the study’s conceptual model.

Findings suggest that the past temporal focus of CEOs decreases technology orientation, and future temporal focus increases the technology orientation of firms, consequently impacting the intention to invest in the metaverse. CEOs’ perceived competitive pressure moderates the mediating relationship, such that the negative impact of past temporal focus on technology orientation is decreased and that of future temporal focus on the CEO is increased.

By exploring the role of a CEO’s past and future temporal focus on influencing technology orientation and, hence, adoption of new technology, the study extends upper-echelon theory to the field of metaverse adoption in the hospitality industry and responds to scholars’ calls to explore the industry’s technology adoption from the lens of the upper echelon.

The study has significant implications for the success of the adoption of metaverse technology in the hospitality industry. Findings imply that the board members should encourage CEOs to have future temporal focus.

The study provides novel insights into the adoption of metaverse technology by the hospitality industry, where CEO attributes such as their temporal focus influence intention to invest in metaverse.