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The work on bridge resilience assessment includes quantitative and qualitative approaches to compare the multiple bridges based on their resilience. But still, the bridge resilience obtained by these assessment approaches is inefficient when prioritising multiple bridges to improve their resilience. Therefore, this study aims to develop a methodology for prioritising the bridges to improve their resilience.

The research methodology follows three sequential phases. In the first phase, criteria importance through intercriteria correlation (CRITIC) technique is used to compute the criteria weights. The criteria considered are age, area, design high flood level, finish road level FRL and resilience index of bridges. While 12 river-crossing bridges maintained by one bridge owner are considered as alternatives. Then, in the second phase, the prioritisation of each bridge is evaluated using five techniques, including technique for order of preference by similarity to ideal solution, VIKOR (in Serbian, Visekriterijumska Optimizacija I Kompromisno Resenje), additive ratio assessment, complex proportional assessment and multi-objective optimisation method by ratio analysis. Finally, in the third phase, the results of all five techniques are integrated using CRITIC and the weighted sum method.

The result of the study enables bridge owners to deal with the particular bridge that requires resilience improvement. The study concluded that it is not enough to consider only the bridge resilience index to improve its resilience. The prioritisation exercise should consider various other criteria that are not preferred during the bridge resilience assessment process.

The proposed methodology is a novel framework based on the existing multi-criteria decision-making (MCDM) techniques for contributing knowledge in the domain of bridge resilience management. It can efficiently overcome the pitfall of decision-making when two bridges have the same resilience index score.

India liberalized its economy in 1991, which resulted in intense global competition, quality-conscious and demanding customers. Additionally, significant technological advancements lead to enhancements in products and processes. These forced Indian organizations to adopt innovative business strategies in the past 30 years. Meanwhile, the Lean Six Sigma methodology has significantly grown with vast applicability during the past 30 years. Thus, the purpose of this study is to develop the learning on Lean Six Sigma methodology in the Indian context through investigation of literature.

A three-stage systematic literature review approach was adopted to investigate the literature during the present study. In total, 187 articles published in 62 journals/conference proceedings from 2005 to 2022 (18 years) were shortlisted. The first part of the article summarizes the significant milestones towards the quality journey in the Indian context, along with the evolution of the Lean Six Sigma methodology. The second part examines the shortlisted papers on Lean Six Sigma frameworks, their applicability in industrial sectors, performance metrics, outcomes realized, publication trends, authorship patterns and leading researchers from the Indian perspective.

Lean Six Sigma has emerged as a highly acclaimed and structured business improvement strategy worldwide. The Indian economy has seen remarkable growth in the past decade and is one of the fastest-growing economies in the 21st century. Lean Six Sigma implementation in India has significantly increased from 2014 onward. The study revealed that researchers have proposed several different frameworks for Lean Six Sigma implementation, the majority of which are conceptual. Furthermore, the balanced applicability of Lean Six Sigma in manufacturing and service sectors was observed with the highest implementation in the health-care sector. Additionally, the widely adopted tools, techniques along with performance metrics exploring case studies were reported along with a summary of eminent and leading researchers in the Indian context.

This study is confined to reviewed papers as per the research criteria with a significant focus on the Indian context and might have missed some papers due to the adopted papers selection strategy.

The present study is one of the initial attempts to investigate the literature published on Lean Six Sigma in the Indian context, including perspective on the Indian quality movement. Therefore, the present study will provide an understanding of Lean Six Sigma methodology in the Indian context to graduating students in engineering and management and entry-level executives. The analysis and findings on Lean Six Sigma frameworks, research approach, publications details, etc., will be helpful to potential research scholars and academia. Additionally, analysis of case studies on Lean Six Sigma implementation by Indian industries will assist the managers and professionals in decision making.

The utilization of the new track construction (NTC) machine in the dedicated freight corridor (DFC) project in India proved to be counterproductive due to various uncertain and dynamic factors. This study aims to develop the model and simulate the productivity of the NTC machine considering system dynamic factors encountered during the construction phase of the project.

The study employs a fuzzy system dynamics (FSD) model to analyse the productivity of the NTC machine. Initially, 21 variables related to the construction productivity of equipment-intensive activities are identified using exploratory factor analysis (EFA). A stock-and-flow diagram is then developed to examine the interdependencies among these variables. The FSD model integrates hard relationships via mathematical formulas and soft relationships using fuzzy measures and integrals. The model’s structure and behaviour are validated through dimension consistency, structure verification and pattern verification tests.

The results indicate that key system variables, such as site restrictions, weather and site conditions, unscheduled breaks and functional range, significantly influence the productivity of the NTC machine. The study also indicates the importance of human expertise, operator’s experience and crew coordination skill as influencing system variables in equipment productivity.

This study provides insights in managing complex and dynamic factors affecting the productivity of the NTC machine used large-scale rail construction projects. This study offers a novel application of FSD to address productivity challenges of this special equipment in the new rail track construction projects.

This study aims to explore the underdog brand biography dimensions that emerging-country consumers identify with (Study 1) and attempts to uncover the effects of these dimensions on brand affinity and purchase intention moderated by self-identity and brand trust (Study 2).

Study 1, using data from 359 young Indians, reveals three underlying dimensions integral to underdog brand biography in emerging markets. Study 2 uses an experimental setup with a single-factorial design among 332 young Mexican consumers to investigate the direct effects of three identified underdog brand biography dimensions on purchase intention, mediated by brand affinity and moderated by consumer self-identity and brand trust.

Study 1 reveals three dimensions underlying underdog brand biographies: unfavorable circumstances, striving in adversities and passion, and persistent will to succeed. Study 2 reveals that consumers with higher self-identity demonstrate greater purchase intentions for an underdog brand than a top dog one.

The results indicate that marketers can successfully use underdog narratives to influence consumer decision-making, thereby increasing brand affinity and purchase intention.

This study delineates the link between different dimensions of underdog brand biographies with brand affinity and purchase intention in emerging countries and builds on the understanding of the moderating role played by self-identity and brand trust.

Implementing big data analytics and client customization programs is causing a significant revolution in the insurance sector. This study examines how big data analytics may revolutionize the insurance industry, emphasizing how consumer customization can improve customer experiences, maximize risk assessment, and spur company expansion.

An empirical study with statistical analysis using tools like correlation and regression was carried out to ascertain the relationships between the various sets of variables—personalized customer experiences and customer satisfaction and customer profiling leads to more effective targeting of marketing efforts. We explore essential ideas like client segmentation, profiling, and retention via a thorough analysis of the literature and case studies, showcasing best practices and inspirational tales from top insurers.

The empirical study found that there is a very high correlation between transparency in data and stakeholders' trust. The study found that insurers may preserve their innovation-driven culture, strengthen customer relationships, and achieve sustainable development in a competitive market by embracing future technological innovations and resolving current challenges.

Insurance companies may seize new chances for individualized client experiences and long-term success in a market that is becoming increasingly competitive by utilizing cutting-edge technology like artificial intelligence and the Internet of Things. To effectively manage the changing terrain of consumer customization in the digital age, insurance professionals, academics, and legislators will find this study highly insightful.

The study is an original contribution based on literature and case studies analysis, showcasing best practices and inspirational tales from top insurers.

Sites of armed conflict produce significant human suffering. Children are some of the most tragic victims of these conflicts, and their suffering is often used as a colloquial measure of suffering at large. Children in conflict zones are likely to experience trauma and associated negative mental and physical health consequences such as post-traumatic stress disorder (PTSD). One way that children and youth cope with their circumstances in these environments is through creative outlets such as art and poetry. Not only does trauma influence the content of children’s art, but the creation of art also influences children’s responses to trauma and conflict. Furthermore, in the same way that children may humanize those living in conflict zones, so too does their art. While the art of children typically lacks the sophistication of high art or classic poetry, there is a genuineness to their work that resonates with others and allows them to see the conflict through a child’s eyes. This chapter covers the relationships between armed conflict, trauma, and children, followed by art as a form of resistance generally, then finally the role of art and poetry as a form of children’s resistance.

The unique nature, complicated design, hazardous activities and complex work environment involved in the high-rise construction projects constitute significant risks worldwide. In the Indian context, construction safety management in high-rise construction projects is crucial due to the presence of significant occupational risks and hazards at the workplace. Occupational hazards lead to accidents that severely affect human health and result in substantial financial losses.

The study aims to present a hybrid risk assessment method (RAM) and the technique for order of preference by similarity to ideal solution (TOPSIS) method to detect and evaluate occupational risks in different construction activities through a questionnaire survey approach.

Aroundsix types of construction activities and corresponding ten risks are identified and evaluated during the study. Based on the calculation of risk scores, the findings imply that “roof work activities,” “finishing work,” “mechanical, electrical and plumbing work (MEP)” are hazardous construction activities, while, among the corresponding ten risks, “workers falling from height” is the most prominent risk among the majority of activities. Other risks include “risk due to fire and electric accidents” and “struck by falling objects,” which are the major risks in high-rise construction projects.

Theoriginality of the paper lies in its activity-based risk assessment and ranking of hazards in high-rise construction projects. By integrating theoretical insights with practical applications, the study attempts to enhance occupational safety and reduce accidents on construction sites, thereby significantly contributing to both academia and industry practices.

This study aims to elucidate the dyeing kinetics and thermodynamic relationships of CI Reactive Red 24 (RR24) on cotton fabrics, achieve the recycling of inorganic salts and water resources and obtain comprehensive data on color parameters, fastness and other characteristics of fabrics dyed with the recycled dyeing residual wastewater.

The dyeing wastewater obtained through advanced oxidation technology was used as a medium for dyeing cotton fabrics with RR24. The absorbance value of the dyeing residue served as an evaluation index, and the relevant kinetic and thermodynamic parameters were calculated based on this absorbance. The color parameters and fastness of the fabric samples were measured to compare the performance of different dyeing media.

Dyeing cotton with RR24 in both media follows pseudo-second-order kinetics. When dyeing with wastewater media, the dye adsorption in the first 45 min increased by 0.082–1.29 g/kg compared with conventional dyeing. Furthermore, the half-dyeing time was shortened by 4.19–11.99 min and the equilibrium adsorption amount was reduced by 0.277–0.302 g/kg. The adsorption of RR24 on cotton fabrics conformed to the Freundlich model. Fabrics dyed using recycled wastewater exhibit a deeper color, with reduced red light and enhanced blue light, resulting in an overall deeper apparent color.

These dyeing kinetics and thermodynamic properties are beneficial for comprehending and interpreting the dyeing performance and behavior of reactive dyes in dyeing wastewater. They lay a theoretical foundation for the treatment and recycling of dyeing wastewater.