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One in six people globally are affected by infertility, and many turn to fertility treatment in a bid to have a child(ren). While many countries offer work-related legislative protections and provisions for those who are successful in conceiving a child, in the form of maternity and paternity-related supports and protection again discrimination – the same cannot be said for those struggling to conceive. There are similar inequalities when it comes to workplace policy and support. Drawing on data from our two-year research study on “complex fertility journeys” and employment, this chapter sets out the work-life challenges that arise when individuals find themselves navigating the considerable “reproductive work” of fertility treatment alongside the demands of paid employment, and how affected employees respond. It also touches on the challenges experienced by line managers tasked with offering support. The chapter concludes with implications for practice in terms of making organizations more “fertility friendly,” which should extend beyond support for attending fertility treatment appointments to include awareness raising, manager training, and support for the varied outcomes of treatment cycles, including involuntary childlessness.

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

Purpose: This study examines the effect of uncertainties on the hospitality industry from different perspectives across the globe. The hospitality industry faces several contemporary issues and challenges that have the potential to impact its growth and development. This study aims to analyse the current problems and uncertainties in the hospitality sector.

Need for the Study: The hospitality industry plays a significant role in the global economy with various services, including accommodation, food and beverage, events, and tourism. However, the sector faces several contemporary issues and challenges that have the potential to impact its growth and development. This study provides an overview of the most significant problems and challenges facing the hospitality industry today.

Methodology: A systematic literature review was conducted to identify and synthesise relevant studies on the effect of uncertainties issues on the hospitality industry. A systematic search of the Web of Science and Scopus databases was conducted to determine relevant studies published between 2010 and 2021. Studies were screened and selected based on pre-defined inclusion and exclusion criteria. A thematic analysis was performed to categorise the uncertainties and issues in the hospitality industry.

Findings: The study identified several uncertainties and issues facing the hospitality industry, including the pandemic uncertainties, financial crisis, whether positive and negative impacts, terrorism attacks on hotels and tourist places, uncertainties in government policies, situational risks like uncertainties, ambiguity, cultural differences, changes in tourist preferences and changing habits of the tourist.

Purpose of This Chapter: >The study examines the importance and effect of working over office hours and lengthy commutes on work–life balance because both consume time away from the official working hours. The study utilized perceived organizational support to measure the moderating role of working over office hours, lengthy commutes, and work–family balance.

Design / Methodology / Approach: An inferential statistics cross-sectional study collected data from 437 full-time employees of IT-BPM companies in 5 metropolitan cities in India. The study used the PLS-SEM to examine the hypotheses.

Findings: The results show a negative relationship between working over office hours and lengthy commutes on work–family balance. This study also found the moderating effect of perceived organizational support on working over office hours and lengthy commutes on the work–family balance. Also, the study revealed that half of the respondents spend three hours, and one-fourth of the respondents spend four and half hours working over office hours and lengthy commutes.

Research Limitations: This research is limited to IT-BPM companies in India. Nevertheless, the findings highlight the factors associated with IT-BPM employee work–family balance, and only two factors were identified.

Practical Implications: This study enhances the work–family balance’s theoretical and practical effects. The results provide a competitive benchmark for IT-BPM managers, administrators, and governing bodies of employee well-being.

Originality: To the best of the author’s knowledge, this study is the first to adopt extrinsic variables in work–family border theory to measure the work–family balance of IT-BPM employees.