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Purpose: This chapter is based on risk management of the insurance sector with reinsurance as its linchpin. Such is the importance of the insurance sector that its risk management must be considered.

Need for the study: Risk management of various sectors is gaining much attention. The insurance sector, known to manage the risk of multiple sectors, also requires its own chance to be controlled with the same or even more intensity. Considering the importance of reinsurance coupled with the dependency of primary insurers on reinsurers and the absence of research on reinsurers, the need to conduct a comprehensive study on the topic is felt.

Methodology: It will be a conceptual chapter based on the rigorous literature on the topic integrated with the researcher’s insights to bring forth the framework of reinsurers for the readers.

Findings: It is found that insurers can themselves become the victims of the financial crisis in case they insure risks that surpass their economic boundaries. Not only this, the failure of insurance companies can have a ripple effect on the country’s economy. Therefore, insurers must possess financial resilience; to remain so, they need to have prudent management of the risk they are undertaking.

Practical implications: The study covers a relatively less researched area of reinsurance and hence has a vast scope of research in the future. The study would be helpful to stakeholders like regulators and primary insurers. It will unveil the paradigm of reinsurance and enlighten the stakeholders on how to use it effectively.

The study aims is to explore the cointegration level among major Asian stock indices from pre- COVID-19 to post COVID-19 times.

Johansen cointegration test is employed to know the long run relationship among the stock market indices of Hong Kong, Indonesia, Malaysia, Korea, India, Japan, China, Taiwan, Israel and South Korea. The empirical testing was done to analyze whether any significant change has been induced by the COVID-19 pandemic on the cointegrating relationship of the selected markets or not. Through statistics of trace test and maximum eigen value, total number of cointegrating equations present among all the indices during different study periods were analyzed.

The presence of cointegration was found during all the sample periods and the findings suggests that the selected stock markets are associated with each other in general. During COVID-19 crisis period the cointegration level was reduced and again it regained its original level in the next year and again reduced in the subsequent next year. So, the cointegrating relationship among selected stock market indices remains dynamic and no evidence of impact of COVID-19 on this dynamism was found.

The study has explored the level of cointegration among the major stock indices of Asian nations in the pre, during, post-crisis and the most recent periods. The interconnectedness of the stock markets during the COVID-19 times has been compared with similar periods in different years immediately preceding and succeeding the COVID-19 times which has not been done in any of the existing study.

The purpose of this paper is to examine the nexus of social support (SS), work–life balance (WLB) and satisfaction with life (SWL) in hybrid work (HW) scenario in learning organizations.

The data were collected via questionnaire method from 531 employees working in learning organizations (IT/ITES sector) in India. The hypotheses were tested using hierarchical regression.

The findings of the study showed that HW was positively related to SS dimensions, WLB and SWL. Further, the study established the mediating role of SS between HW and WLB as well as WLB as a mediator between HW-SWL relationships.

This study has certain limitations owing to the cross-sectional nature of the data and the specific sector under study. The findings have significant implications for policy making to determine the conditions under which both employees and organizations can benefit from HW. Further, the study has implications for uncertain and volatile environments as had been created by COVID-19 pandemic, where HW arrangements may not be a choice but become necessity.

This study contributes to the conservation of resources theory. It identifies the importance of true autonomy and flexibility for employees.

Farmers producer organisations (FPOs) play the most crucial role in the agriculture supply chain system, aiming to redress the balance between farming and marketing activities of agricultural produce. The purpose of this study is to assess the performance of FPOs using data envelopment analysis (usually referred to as DEA) on 34 FPO units selected from the state of Rajasthan.

One of the most commonly used techniques to examine business performance is the application of DEA. The application of DEA requires the selection of inputs and outputs. This study takes three inputs and three outputs based on the insights drawn from the field survey. While the input variables consist of total assets, paid-up capital and the number of economic activities, the three output variables are turnover, net profit and number of members benefitted. Broadly, these variables encapsulate the operational performance of the business units.

This study’s findings reveal that the estimated relative efficiency score of the input-oriented CCR (Charnes, Cooper, and Rhodes) model ranges from 0.06 to 1. Interestingly, only one FPO has reported a relative efficiency (RE) score of one, whereas the remaining FPOs fall below the efficiency frontier. However, 15 FPOs report an RE score of one in the output-oriented CCR approach. Considering the estimates obtained in the input- and output-oriented BCC (Banker, Charnes and Cooper) models, this study found that about 20% of the FPOs report an efficiency score greater than 0.80. Moreover, three FPOs are on the frontier line. An examination of the scale efficiency score in the input-oriented model, 45% of the FPOs have an efficiency score greater than 0.80, whereas almost all FPOs achieve a scale efficiency score greater than 0.80 in the output-oriented model. Overall, the results imply that the FPOs should place greater emphasis on the efficient utilisation of the inputs to enhance the overall business performance and productivity.

The findings of this study provide vital insights into the specific inputs and outputs that determine the performance efficiency of FPOs and identify the potential areas for improving the existing inefficient FPOs.

This study contributes to the repository of the existing empirical studies in three distinct ways. First, the authors hardly found any previous studies that quantitatively assess the business performance of FPOs using the DEA technique. Second, the effort to identify the slacks associated with each input and output variable in input- and output-oriented models gives insights on improvable areas for inefficient FPOs. Third, the authors attempt to demystify the empirical obfuscations by highlighting the major challenges FPOs face in the state of Rajasthan.

Although the quality of health-care infrastructure and equipment influences patient’s overall health-care experience, health-care infrastructure and equipment are not always managed and maintained with the attention required. This is due mainly to the complexity of health-care infrastructure and equipment and shortage of maintenance budget. This study aims to determine if patient’s satisfaction of core health-care business is mediated by the quality of health-care infrastructure and equipment.

This cross-sectional study comprises 622 adult patients at the Physician OPD and Polyclinic of Komfo Anokye Teaching hospital, Tamale Teaching hospital and Cape Coast Teaching hospital in Ghana. Structural equation model Smart PLS was used to analyse the data.

The study results showed that the quality of health-care infrastructure and equipment has a positive significant influence (mediation) on the relationship between health-care delivery and patient’s satisfaction as well as the relationship between adequacy of health-care resources and patient’s satisfaction. However, it was shown not to have a positive significant influence (mediation) on the relationship between quality of health-care personnel and patients’ satisfaction as well as health-care administrative process and patient’s satisfaction.

First, the study findings are centred on cross-sectional data, which capture the opinion of the patients at a specific time period instead of over a period of time. Consequently, in future, though difficult to achieve, a longitudinal study can be piloted to provide more insight. Second, the data was collected from only one country (Ghana); thus, the ability to generalise the results may be a challenge.

The implication of this study is that there is the need to prudently maintain hospital infrastructure and equipment in good working condition as it has a positive effect on patients’ satisfaction of their overall health-care experience.

Most studies have concentrated on patient’s health-care experience. This study extends the knowledge of patient’s health-care experience by determining the mediating role of quality of health-care infrastructure and equipment on the relationship between patient’s satisfaction and core health-care business. There are limited studies of such nature in Ghana. Therefore, this study will provide invaluable empirical data for the health-care sector of a developing African country.

Despite the susceptibility of cotton crops to pest attacks in the Malwa Region of Indian Punjab, no crop insurance policy has been implemented there– not even the Pradhan Mantri Fasal Bima Yojana (PMFBY), which is a central scheme. Therefore, this paper attempts to gauge the likely impact of the PMFBY on Punjab cotton farmers and assess the changes needed for greater uptake and effectiveness of PMFBY.

The authors have conducted a primary survey to conduct this study. Initially, the authors compared the costs of cotton production with the returns in two scenarios (with and without insurance). Additionally, the authors have applied a logistic regression framework to examine the determinants of the willingness of farmers to participate in the crop insurance market.

The study finds that net returns of cotton crops are conventionally small and insufficient to cope with damages from crop failure. Yet, PMFBY will require some modifications in the premium rate and the level of indemnity for its greater uptake among Punjab cotton farmers. Additionally, using the logistic regression framework, the authors find that an increase in awareness about crop insurance and farmers' perceptions about their crop failure in the near future reduces the willingness of the farmers to participate in the crop insurance markets.

The present study looks for the viability of PMFBY in Indian Punjab for the cotton crop, which can also be extended to other crops.

Punjab could also use crop insurance to encourage diversification in agriculture. There is a need for special packages for diversified crops under any crop insurance policy. Crops susceptible to volatility due to climate-related factors should be identified and provided with a special insurance package.

There exist very scant studies that have discussed the viability of a central crop insurance scheme in the agricultural-rich state of India, i.e. Punjab. Moreover, they do not also focus on crop losses accruing due to pest and insect attacks.

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 intends to evaluate students’ intention to shift from cash payment to mobile payment system for academic fee payments through push, pull and mooring framework. Push factors comprise risk and service-related factors, pull factors consist of subjective and aspect-based factors and mooring factors include cost and cognitive factors.

Sample of the study consists of around 296 undergraduate and postgraduate students from different higher educational institutions located in India. The questionnaire for data collection comprises 21 Likert scale-based items distributed among seven constructs. Partial least square structural equation modeling is used to identify the significant factors influencing students’ intentions.

Five of the factors, namely, risk, service, subjective, aspect and cognitive significantly influence student’s intention to switch to mobile payment system for academic fee payments. Moderation analysis indicates that the impact of the push and pull factors on switching intention towards mobile payments has a more positive influence among male students.

This study is probably the only study that tested the specific push, pull and mooring factors influencing intention to switch to mobile payment from cash payment in the Indian education system based on the incentive, Fogg behavior and status quo bias theory for academic fee payment.

This study aims to evaluate the presence of abnormal returns due to stock splits or reverse stock splits in the Brazilian capital market context.

The event study technique was used on data from 518 events that occurred in a 30-year period (1987–2016), comprising 167 stock splits and 351 reverse stock splits.

The results revealed the occurrence of abnormal returns around the time the shares began trading stock splits or reverse stock splits at a statistical significance level of 5%. The main conclusion is that stock split and reverse stock split operations represent opportunities for extraordinary gains and may serve as a reference for investment strategies in the Brazilian stock market.

This study innovates by including reverse stock splits, as the existing literature focuses on stock splits, and by testing two distinct “zero” dates that of the ordinary general meeting that approved the share alteration and the “ex” date of the alteration, when the shares were effectively traded, reverse split or split.

The financial technology (FinTech) era has brought a revolutionary change in the financial sector’s customer experiences at the national and global levels. The importance of artificial intelligence (AI) in the context of FinTech services for enriching customer experiences has become a new norm in this modern era of technological advancement. So, it becomes crucial to understand the customer’s perspective. The current research ranks the factors and sub-factors influencing customers’ perceptions of AI-based FinTech services.

The sample size for this study was decided to be 970 respondents from four Indian cities: Mumbai, Delhi, Kolkata and Chennai. The Fuzzy-AHP technique was used to identify the primary factors and sub-factors influencing customers’ experiences with AI-enabled finance services. The factors considered in the study were service quality, trust commitment, personalization, perceived convenience, relationship commitment, perceived sacrifice, subjective norms, perceived usefulness, attitude and vulnerability. The current research is both empirical and descriptive.

The study’s three top factors are service quality, perceived usefulness and perceived convenience, all of which have a significant impact on customers’ experience with AI-enabled FinTech services discussing sub-criteria three primary criteria for customers’ experience for FinTech services include: “Using FinTech would increase my effectiveness in managing a portfolio (A2)”, “My peer groups and friends have an impact on using FinTech services (SN3)” and “Using FinTech would increase my efficacy in administering portfolio (PU2)”.

The current study is limited to four Indian cities, with 10 factors to understand customers’ preferences in FinTech. Further research can focus on other dimensions like perceived ease of use, familiarity, etc. Future studies can have a broader view of different geographical locations and consider new tech to understand customer perceptions better.

The study’s findings will significantly assist businesses in determining the primary aspects influencing customers’ experiences with AI-enabled financial services. As a result, they will develop strategies and policies to entice clients to use AI-powered FinTech services.

Existing AI research investigated several vital topics in the context of FinTech services. On the other hand, the current study ranked the criteria in understanding customer experiences. The research will substantially assist marketers, business houses, academicians and practitioners in understanding essential facets influencing customer experience and contribute significantly to the literature.