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Interest rate derivatives (IRDs) are the essential components of financial risk management and are used across various industry sectors. The objective is to analyze the differences in approach to managing interest rate risks between the Indian corporates that execute IRDs and the ones that do not.

Interest rate fluctuations require Indian corporates to hedge their exposures in foreign currency interest rates. This is all the more true for mid-sized corporates because of their balance sheet exposures. Additionally, they may not have the resources to formulate risk management policies. This paper analyzes data collected from financial statements of a diverse set of companies that use IRD and helps in formulating such a strategy.

The results indicate significant differences for some of the parameters like information asymmetry and agency cost between users and non-users of IRDs. The study further suggests causality between users of derivatives and parameters like size, growth and debt.

The study compares users and non-users of IRDs, thereby identifying factors unique to users of IRDs. It also studies causality relations which explain the motivation to do IRDs. Thus, it enables risk managers to use this as a reference point to decide on their strategies.

While there are multiple studies across geographies and sectors including commercial banks in India on the usage of interest rate swaps, this study focuses on Indian mid-tier corporates. Furthermore, the study distinguishes between users and non-users based on financial parameters, which in turn would provide a framework for decision-hedging strategies.

New business practices and the globalization of markets force firms to take innovation as the fundamental pillar of their competitive strategy. Research and Development (R&D) plays a vital role in innovation. As technology advances and product life cycles become shorter, firms rely on R&D as a strategy to invigorate innovation. R&D project portfolio selection is a complex and challenging task. Despite the management's efforts to implement the best project portfolio selection practices, many projects continue to fail or miss their target. The problem is that selecting R&D projects requires a deep understanding of strategic vision and technical capabilities. However, many decision-makers lack technological insight or strategic vision. This article aims to provide a method to capitalize on the expertise of R&D professionals to assist managers in making informed and effective decisions. It also provides a framework for aligning the portfolio of R&D projects with the organizational vision and mission.

This article proposes a new strategic approach for R&D project portfolio selection using efficiency-uncertainty maps.

The proposed strategy plane helps decision-makers align R&D project portfolios with their strategies to combine a strategic view and numerical analysis in this research. The proposed strategy plane consists of four areas: Exploitation Zone, Challenge Zone, Desperation Zone and Discretion Zone. Mapping the project into this strategic plane would help decision-makers align their project portfolio according to the corporate perspectives.

The new approach combines the efficiency and uncertainty dimensions in portfolio selection into an integrated framework that: (i) provides a complete representation of the stochastic decision-making processes, (ii) models the endogenous uncertainty inherent in the project selection process and (iii) proposes a computationally practical and visually unique solution procedure for classifying desirable and undesirable R&D projects.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

The study aims to look into the mechanism by which perceived human resource management (HRM) practices impact nurses' engagement, by specifically looking into the role of psychological availability and psychological safety.

A cross-sectional questionnaire survey was conducted among nurses (n = 465). Data were collected from nurses of National Accreditation Board for Hospitals and Healthcare Providers (NABH) accredited hospitals by employing two stage sampling.

Results indicate significant positive association between HRM practices and employee engagement. Role of psychological safety and psychological availability as mediators was also confirmed. The study supported the proposition that HRM practices affected employee engagement through psychological safety and then psychological availability thus approving serial mediation.

This research also contributes to a more comprehensive understanding of the ways to achieve employees' psychological safety, availability, and thus nurse engagement.

Key enabling technologies (KETs) are a set of six technological components that work together to address social challenges and build advanced for sustainable economies. Industry 5.0, the next industrial development, is designed to capitalize on specialists' unique creativity while also collaborating with powerful, intelligent, and precise technologies. Industry 5.0 outsourced repetitive and monotonous activities to robots/machines requiring employees to perform activities that involve critical thinking and are based on the 6R (Recognize, Reconsider, Realize, Reduce, Reuse, and Recycle), to improve production quality. With numerous supporting technical advancements, advanced and quick manufacturing concentrating on the interaction of machines and humans may be produced. Maintaining healthcare and nursing care, evaluating patients' health requirements using KETs, and giving care with manpower are all major advancements in Industry 5.0 today. Future studies may focus on providing healthcare using mainly technology and, therefore, no human workers. This chapter highlights healthcare advances in Industry 5.0, where KETs and people collaborate to create and innovate. In this framework, the purpose of this chapter is to present the deployment of KETs in the nursing patient care process.

The study aims to identify organizational variables of quality 4.0 for an Indian manufacturing company in the case of digital transformation. Furthermore, the organization enhances its quality 4.0 performances to its success based on the degree of relevance of these variables, insight into these variables and sub-factors to prioritize them.

Initially, two rounds of the survey were conducted with 11 decision-makers from the company made to receive organizational variables scores and prioritize the factors and sub-factors. Analytic Hierarchy Process (AHP) based research methodology has been proposed to assign the criterion weights and prioritize the identified variables.

The results of this AHP model demonstrate that “Committed Leadership” is recognized as the top positioned variable and most significant organizational variable, followed by Collaboration and Quality culture, which are developed at the next level. These essential organizational variables with their sub-categories' priorities are identified as contributing attributes.

The findings facilitate quality 4.0 in the digitalization era, which take into contemplating the current state of the business. Furthermore, the understanding of variables provides insightful guidance to analyze, solve complex problems and assess the efficacy of quality 4.0 in digital transformation.

The novelty of this study is to pinpoint, and evaluate the responsible organizational variables and prioritize them that lead to high productivity and competitive advantage considering the AHP method.

This research aims to examine the complementary impact of Lean Manufacturing (LM) and Green Manufacturing (GM) on operational and environmental performance.

A survey was conducted in the Zimbabwean manufacturing industry. A total of 302 valid responses were obtained and analysed using partial least square structural equation modelling (PLS-SEM).

Both LM and GM impact environmental and operational performance; however, GM's effect on operational performance is indirect through environmental performance.

This study only focusses on the Zimbabwean manufacturing industry, and the results may not readily apply to other developing countries.

The companies that have successfully implemented LM are able to implement GM more easily because of their complementary nature.

The integration of LM and GM reduces most forms of waste, causing an improved environmental and operational performance. In addition, this will improve community relations and customer satisfaction.

This research investigates the complementary nature of LM and GM on how LM and GM impact organisational performance and whether a combined Lean-Green implementation leads to better organisational performance than when LM and GM are implemented individually. The research also examines whether being environmentally compliant leads to improved organisational performance, particularly in a developing country.

This study aims to investigate the factors affecting micro, small and medium entrepreneurs’ (MSMEs) behavioural intention to participate in takaful schemes in Sri Lanka.

This research adopted a quantitative approach using primary data from a questionnaire. Out of 470 questionnaires, 432 were collected (91.91%) from MSMEs in Kalmunai business region in Sri Lanka. The data obtained were analysed using partial least square-structural equation modelling.

This study revealed that the extension model of the theory of planned behaviour (TPB) can be effectively applied to behavioural intentions towards a takaful scheme by MSMEs. Out of eight hypotheses, seven were significant, including: attitude towards behavioural intention; subjective norm; perceived behavioural control; knowledge; religiosity; income; trust in takaful as a significant influence. However, awareness of intention was not found to be significant.

This study suggests advantages for takaful providers in Sri Lanka, especially marketing departments, for enhancing sale of products, refurbishing marketing strategies and understanding the purchasing motivation of business entrepreneurs. This study guides takaful companies as to where they should concentrate to enhance market penetration.

Previous studies have concentrated on only three factors which comprise TPB. This paper’s main contribution is on the uniqueness of the Muslim minority context in a pluralistic context, providing a marketing model for takaful operators based on the different relevant dimensions.

This study assesses the quality of health-insurance services and their impact on customer satisfaction, examining the mediating role of utilitarian value and brand image in this relationship.

Survey data were collected from 345 health-insurance companies' customers selected through convenience sampling and were analyzed using SmartPLS.

Service quality statistically significantly influences customer satisfaction with health insurance in Saudi Arabia, whereas brand image and utilitarian value partially mediate this relationship. The structural path between service quality and brand image was statistically significant and positive. The utilitarian dimension positively affects customer satisfaction and service quality.

This study is significant to the management, as it provides insight into the expectations of health-insurance users. The focus is to gain a competitive advantage by improving customer service and brand image.

This investigation contributes to the field by exploring the mediating role of utilitarian value and brand image in the relationship between health-insurance quality and customer satisfaction based on the information provided by insurance policyholders in Saudi Arabia.

Buoyed by the increasing demand for improved productivity and environmentally conscious manufacturing, research in the area of lean production and green manufacturing has experienced significant growth since Dües et al. (2013). Taking the latter as the point of reference, a review of recent developments in the complementary and conflicting areas between lean production and green manufacturing that has been missing is presented.

A systematic search was done to identify articles on lean production and green manufacturing from Scopus, Web of Science and Google Scholar. The population-intervention-outcome format was used to develop and answer the research questions. ATLAS.ti 22 was used to analyse 141 qualifying papers and identify the research themes.

Lean production and green manufacturing have strong synergy, and when integrated, they tend to deliver superior organisational performance than their individual implementations. This is consistent with the pre-2013 results, and other areas of synergy and divergence were also identified.

The study considers only papers published in the manufacturing sector after Dües et al. (2013). A review of lean production and green manufacturing in integrated product-service systems may also be relevant, especially due to the continuing trend since its introduction.

Any new adopter of lean production should consider implementing it simultaneously with green manufacturing.

This study establishes the persistence of the pre-2013 patterns of synergy and divergence between lean production and green manufacturing, and identifies new considerations for their joint implementation.