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The goal of this study is to predict the farmers’ concerns about agricultural index-insurance (AII) for weather risk mitigation of horticultural crops in hilly regions. The key impetus of analysis is to prioritize the AII requirements based on the farmers’ perspectives using the requirements prioritization approach.

The integrated approach has been applied in this paper. Initially, the MoSCoW prioritization technique has been employed to prioritize the AII attributes utilizing a four-dimensional agriculture insurance scale. Later, the rank sum weighting method was deployed to assign the ultimate rank to AII attributes based on the farmers’ responses.

Findings specified that out of 15 AII attributes, majority of 11 attributes were placed in “must have” and “should have” categories that related to claim, design, premium and grievance management dimensions. However, three AII attributes are placed in the “could have” category. Additionally, findings of rank-sum weighting method-based ranking can help insurers in redesigning farmers-oriented AII services for risk mitigation of horticulture crops by incorporating these ranks as per their priority level.

The prioritized AII attributes are helpful for insurers and managers in order to solve the problems associated with design, premium, claim and grievance management of AII.

Findings deliver significant insights to insurers to incorporate the prioritized AII attributes ranked by farmers.

This is the initial known analysis that integrated the MoSCoW and rank sum weighting method to prioritize the AII requirements prioritization among Indian farmers.

This research addresses the critical challenge of fostering customer loyalty within the highly competitive landscape of the insurance industry. The study investigates the interplay between customer satisfaction, loyalty, and the influence of technology and service quality in the context of insurance services and in periods of crisis.

A quantitative research approach was employed, utilizing a structured questionnaire distributed among diverse insurance customers in Lebanon during crisis conditions. The data were analyzed using SPSS-Amos, incorporating descriptive statistics, correlation analysis, and structural equation modeling (SEM).

This research emphasizes the crucial role of customer satisfaction in fostering loyalty in the insurance sector, especially during crises. High satisfaction levels, influenced by user-friendly online platforms, positively correlate with increased customer loyalty. Technology plays a vital role in maintaining and improving satisfaction, making it a key driver during challenging times. Positive interactions between service quality and satisfaction further highlight the multifaceted impact of technology on shaping customer loyalty.

The research findings provide valuable insights with practical implications for insurers aiming to boost customer loyalty. The study recommends strategic investments in critical areas like claims processing, customer service, communication strategies, digitalization initiatives, and employee training. The study provides insights applicable particularly to insurance companies navigating crisis conditions.

This research contributes both to academic understanding and practical applications by shedding light on the distinctive challenges and opportunities faced by insurers in cultivating customer loyalty within the insurance industry during crisis. The elucidations provided serve as a foundation for developing targeted strategies to address these challenges and to leverage opportunities for enhanced customer loyalty.

Clause 19 [Insurance] provides the requirements for insurance of the Works, Goods, liability for breach of professional duty, injuries to persons (including employees) and damage to property, as well as insurance required by Laws etc. Drafting a cohesive insurance strategy providing adequate cover for all relevant risks is a job for insurance specialists. If not drawn up by specialists, relevant risks might not be adequately covered or the global cost of providing insurance might increase (e.g. because some risks are insured by the Employer as well as the Contractor). Drawing up an insurance strategy may provide the best cover at the lowest cost but only if the work is done by suitably quali?ed specialists.

The objective of this paper is to examine crop yield predictions and their implications on MPCI in Ghana. Farmers in developing countries struggle with their ability to deal with agricultural risks. Providing aid for farmers and their households remains instrumental in combatting poverty in Africa. Several studies have shown that correctly understanding and implementing risk management strategies will help in the poverty alleviation agenda.

This study examines the importance of crop yield distributions in Ghana and its implication on multiperil crop insurance (MPCI) rating using the Lasso regression model. A Bonferroni test was employed to test the independence of crop yields across the regions while the Kruskal-Wallis H test was conducted to examine statistical differences in mean yields of crops across the ten regions. The Bayesian information criteria and k-fold cross-validation methods are used to select an appropriate Lasso regression model for the prediction of crop yields. The study focuses on the variability of the threshold yields across regions based on the chosen model.

It is revealed that threshold yields differ significantly across the regions in the country. This implies that the payment of claims will not be evenly distributed across the regions, and hence regional disparities need to be considered when pricing MPCI products. In other words, policymakers may choose to assign respective weights across regions based on their threshold yields.

The primary limitation is the unavailability of regional climate data which could have helped in a better explanation of the variation across the regions.

This is the first study to examine the implications of regional crop yield variations on multiperil crop insurance rating in Ghana.

This chapter reviews new technologies, new types of players and new types of financial products that together are fundamentally affecting supply and demand dynamics in the financial sector and contributing to the emerging digital financial landscape. The aim of this chapter is to set a common understanding on the underlying forces of digital disruption in the financial sector before exploring the challenges to monetary and financial stability that are arising. In later chapters, the book will examine how central banks might deal with the challenges and help shape the emerging digital financial landscape.

Clause 1 [General Provisions] contains the provisions that in many contracts are bundled together under the ‘miscellaneous’ or ‘other provisions’ heading and includes a list of definitions, some interpretation principles, rules on communication between the Parties, documents forming the Contract, assignment, confidentiality etc. But Clause 1 also contains other provisions, like the Employer's right to use documentation and other deliverables provided by the Contractor (in other contracts usually referred to as a license to use), and a substantive Sub-Clause on limitation of liability.

Customer–provider relationships unfold through multiple touchpoints across different channels. However, some touchpoints are more important than others. Such important touchpoints are viewed as “moments of truth” (MOTs). This study examines the impact of a series of touchpoints on an MOT, and the role MOTs play in determining future profitability and other behavioral outcomes (e.g. customer retention and customer cross-buy) in a business-to-business (B2B) context.

Building upon social exchange theory, a conceptual model is proposed and tested that examines the impact of human, digital, and physical touchpoints and past MOTs on customer evaluation of a current MOT and on future customer outcomes. This research employs a longitudinal methodology based on a unique panel dataset of 2,970 B2B customers.

Study results show that all touchpoints significantly contribute to MOTs, while human and physical touchpoints maintain their primacy during MOTs. The impact of MOTs on future customer outcomes is also demonstrated.

This study highlights the need for prioritizing human and physical touchpoints in managing MOTs, and for carefully managing MOTs across time.

Given its B2B outlook and longitudinal approach, this research contributes to the multichannel and interactive marketing literature by determining relevant touchpoints for B2B customers.

This chapter focuses on how alternative data can change the nature of financial forecasting through improved short-term forecasting techniques and decreased informativeness from longer term sources. Increased use of social media data leads the charge in transforming this transition. Alternative data are data not from standard financial statements or formal reports. This chapter looks at alternative data from new sources (e.g., social media, Internet of Things [IoT], and digital footprints) and alternative data from new collection methods like web scraping for textual analysis, image analysis, and vocal analysis). It first discusses standard data in financial forecasting. Next, this chapter examines alternative data in financial forecasting. Finally, it discusses alternative data used in studying finance more broadly.

Artificial intelligence (AI) applications are increasingly used for day-to-day operations in healthcare. Each has a relatively limited scope or task, and several find application in managerial and organizational processes. More and more, AI and machine learning (ML) devices have received US FDA approval in the last decade. This chapter covers the main AI applications in healthcare, with a focus on organizational AI solutions (administrative AI), the main AI developers, their investment and real-world data and case studies in healthcare and other sectors. AI can be applied in resource management and procurement, resource allocation, clinical case management, staff work shift scheduling and handling of emergencies. AI applications are becoming ubiquitous in hospital (e.g. emergency room and operating theatre) and outpatient settings (e.g. ambulatory care and dentistry clinics). Their implementation is expected to bring direct benefits for patient care and satisfaction. This chapter gives a broad definition of AI in healthcare settings, with a focus on administrative applications and their use in case study data.

Fintech has revolutionized personal finance, introducing innovative tools that offer unprecedented access, efficiency, and security in managing finances. This chapter explains fintech's personal finance applications, from intuitive budgeting apps and advanced robo-advisors to peer-to-peer payment platforms. It articulates how these tools have shifted the control and management of finances into the hands of consumers, providing real-time financial data, customized investment strategies, improved credit scores, and streamlined transactions that eliminate the need for traditional intermediaries. Furthermore, this chapter features a select list of FinTech50 firms and highlights how individuals can leverage their services. This comprehensive guide is invaluable for individuals seeking to leverage fintech for personal finance optimization and for professionals keen on understanding and navigating the rapidly evolving fintech landscape.