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This work focuses on optimizing and predicting the tenacity of twin-sheath single-core hybrid yarn. This study aims to predict and maximize yarn performance by investigating key factors influencing yarn tenacity.

Three critical parameters − ultra-high molecular weight polyethylene (HPPE) denier, stainless steel micron size and twist per meter − were considered for making multicomponent yarn and optimized using the Box-Behnken design (BBD), a response surface methodology variant. The hybrid yarn studied consists of a stainless-steel core, a polyester inner layer and an HPPE outer layer with opposite twists. The ASTM D2256 method was applied on Instron 3365 machine to measure yarn tenacity.

The optimized yarn setup involved 200 twists per meter, 400 Den HPPE and 45-micron stainless steel, resulting in a 127.5 cN/Tex tenacity. The quadratic model best fits the data, with R² values close to 1.00 (R² = 0.9935, adjusted R² = 0.9817, projected R² = 0.8956), a lower PRESS value of 445, a higher adequacy precision of 19.6816 and a higher TPC percentage of 35.23%. The analysis of variance results confirmed the model significance (F-value = 84.75, P-value < 0.0001), and the average relative error was found to be 3.43%, indicating predictive accuracy.

This study demonstrates the effectiveness of the BBD in optimizing hybrid yarn tenacity, providing valuable insights in terms of core yarn and outer sheath yarn linear density with twist per meter. The work presents a novel approach to hybrid yarn optimization and prediction, expanding the potential for further research and development in textile engineering.

This study aims to explore and unfold the problems in designing and delivering employer-initiated financial education programs (FEPs) from the perspective of working women who attend such programs.

The researchers conducted in-depth interviews and utilized an interpretive qualitative approach to explore the expectations and experiences of women employees regarding such programs.

The results of this study demonstrate that employer-led FEPs may not benefit women employees due to specific misaligned actions of both employers and employees at every stage, which make the programs ineffective.

While this study encompasses women from varied age groups and marital statuses, the researchers acknowledge that the sample size is limited and represents a specific socioeconomic group.

The findings of this study have policy and practical implications for addressing perceived issues in FEPs initiated by employers for women employees.

The novel contributions of this study include suggesting a process model for building FEPs, highlighting the existing problems at each step in designing and delivering an FEP and expanding the application of Self-Determination Theory in FEPs.

The research on financial satisfaction has risen substantially in recent years due to its importance in personal financial planning and individuals’ subjective well-being. Hence, this study aims to map the existing literature on financial satisfaction to present the current state of knowledge and identify substantial gaps.

The present review uses 109 articles published between 1985 and March 2024 and retrieved from the Scopus database. The study deploys a systematic literature review (SLR), bibliometric analysis and content analysis to attain the objectives. Through bibliometric analysis, the present study highlights the most influential authors, journals, countries and affiliations, augmenting the literature on financial satisfaction. Moreover, the study presents the detailed antecedents and consequences of financial satisfaction through content analysis.

The study outlines that most studies in the financial satisfaction area revolve around its antecedents and consequences. The review details multiple antecedents affecting financial satisfaction, such as socioeconomic, psychological, social, personality, religious, financial literacy, financial behavior and technological factors. The prominent consequences of financial satisfaction include subjective well-being, life satisfaction, happiness, emotional and financial well-being, relationship quality, work engagement and sustainable growth.

The present research is an inaugural SLR that comprehensively maps the existing intellectual structure on financial satisfaction. In addition, it offers future research directions for further developments on the subject.

Most countries are progressing towards digitalisation of the citizen records. India too has progressed extensively in this regards. Different strategies and recent confinement during the pandemic have enabled accelerated the digitalisation to the extent that even the street vendors use digital and mobile payment systems. The objective of this chapter is to understand the progress of other countries through an academic review. It is clear from the different articles that the key indicator of the digitalisation is adoption; different countries are at different levels of adoption. India is on top of the list with 61 crore Permanent Account Number (PAN) cards, 8,840 crore digital transactions, 77.86 crore Aadhaar cards of the total population of 1,460 crore population.

The research proposes a customised framework for improving logistics service quality (LSQ) in Tanzania's railway transportation, focusing on customer engagement and integrating customer-desired services.

The survey method obtained data from railway customers regarding the LSQ offered. Both probability and purposive sampling techniques were used to get the sample size. The open- and closed-ended questionnaires gathered the pertinent data. The data were analysed qualitatively and quantitatively using the IBM® SPSS® 21.0 and AMOS 21.0 software packages, respectively. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to analyse data and establish relationships between variables.

This study anticipated that the LSQ framework during the period of reviewing literature included three variables for freight transporting customers (tangible components, ways of fulfilment and information actions) and eight variables for passengers (tangible, reliability, assurance, responsiveness, comfort, empathy, connection and convenience). EFA and CFA dropped some factors. The retained factors were used as inputs to develop a framework. The qualitative analysis also established the improvement of customer’s desired services (CDS) and LSQ, which were the framework's processes for improving the LSQ. Ultimately, the study developed the LSQ framework for railway transportation.

The study was conducted on Tanzania’s railways, which incorporated challenges in the Tanzanian context. However, many challenges in the developing countries are relatively the same. Therefore, modifications can be made to adopt the developed framework and be used in other countries to cover the geographical and other challenges in particular countries.

Tanzania’s railway infrastructures are somehow not fully utilised to meet the actual needs of the transportation sector. For example, one of the railway companies has a built capacity of 4 million tonnes carrying capacity per year, but the actual cargo transported by the railway is 200,000 tonnes. This comes from several challenges within the railway companies, including the quality of their services, thus leading to a need to develop a LSQ framework.

The purpose of the study is to examine how risk factors contribute to the occurrence of defects in a process. By analyzing these risk factors in relation to process quality, the study aims to help organizations prioritize their resources and efforts toward addressing the most significant risks. These challenges, integrated with the emerging concept of Quality 4.0, necessitate a comprehensive risk assessment technique.

Fuzzy logic integrated with an analytic network process is used in the process failure mode and effects analysis for conducting risk identification and assessment under uncertainty. Through a mathematical model, the linkage of risk with Six Sigma is established and, finally, a value–risk matrix is developed for illustrating and analysing risk impact on process quality.

A case study on fused filament fabrication demonstrates the proposed methodology’s applicability. The results show its effectiveness in assessing risk factors’ impact on Six Sigma metrics: defects per million opportunities/sigma level.

By integrating qualitative assessments and leveraging available data, this approach enables a more comprehensive understanding of risks and their utilization for an organization’s quality improvement initiatives.

This approach establishes a risk-centric Six Sigma assessment method in accordance with the requirement of ISO 9001:2015 and in the context of Quality 4.0.

This paper aims to examine the level of awareness and determinants of the actual adoption of fintech services. This paper further focuses on how usages of different kind of fintech services fulfills the business needs of the micro-entrepreneurs of urban slum dwellers of Uttarakhand.

The research investigated the predictive significance of actual adoption of fintech services using the unified theory of acceptance and use of technology (UTAUT) and prospect theory framework. Data was collected from 80 micro-entrepreneurs of urban slum areas of Uttarakhand, using an adapted semi-structured questionnaire. For analysis of data partial least square structural equal modeling has been used.

This paper finds that different fintech services have different levels of awareness whereas payment, regulation and market provision-related fintech services have high awareness. The main drivers for adopting fintech are services trust (ST) and behavioral intention (BI). BI significantly influences fintech adoption, while ST positively impacts BI, actual usage and facilitating conditions; perceived risk, however, negatively affects ST. The widely used fintech services are payment-based fintech (unified payments interface), followed by regulatory fintech (Khatabook app). Fintech effectively serves the business needs of micro-entrepreneurs in the urban slums of Uttarakhand with innovative product solutions.

The findings of this study are valuable for various fintech providers. These results can serve as a roadmap to strengthen fintech services in the broader population, including niche market segments.

This study uniquely contributes to the literature that addresses the issues of entrepreneurs of the lower strata of society through the use of fintech services.

This study aims to examine whether agricultural commodities exhibited deviations in the lead-lag relationship between future and spot prices of farmer producer organizations (FPOs) traded commodities in the Indian derivative market after trade suspensions during Covid-19. The study may help buyers and sellers to get a fair price for their commodities after lockdown-trade disruptions.

The study applied the Granger causality (GC) test and the vector error correction model (VECM) to analyse short-run and long-run lead-lag relationships. Moreover, the study examined the pre-post-trade suspension effect on the lead-lag relationship of commodity prices.

The GC test results show that five out of the 13 agri-commodities have changed their lead-lag relationship from future to spot in the short run. Simultaneously, VECM captured changes in the lead-lag relationship for the same five commodities in the long run due to trade suspensions.

The findings indicate a reverse lead-lag relationship between future and spot prices for aforesaid commodities after trade suspension. The stakeholders may use the lead prices for these commodities to perform a fair trade. The study may be helpful in structuring price discovery strategy to achieve optimal price and efficient derivative trading.

To the best of the authors’ knowledge, this is the first study examining the effects of trade suspension on price discovery in FPO-traded agri-derivatives caused by the COVID-19 pandemic.