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The UK Coalition government introduced a raft of welfare reforms between 2010 and 2015. As part of its response to the financial crisis, reforms were designed to cut public expenditure on social security and enhance work incentives. Policy makers are required by legislation to have due regard to the need to eliminate discrimination, advance equality of opportunity and foster good relations between different people. This Public Sector Equality Duty is an evidence-based duty which requires public authorities to assess the likely effects of policy on vulnerable groups. This chapter explores the extent to which the Department for Work and Pensions adequately assessed the equality impacts of key welfare reforms when policy was being formulated. The chapter focuses on the assessment of the impact of reductions to welfare benefits on individuals with protected characteristics – age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion and belief, sex and sexual orientation – including individual and cumulative impacts. It also considers mitigating actions to offset negative impacts and how the collection of evidence on equality impacts was used when formulating policy. The chapter shows that the impacts of the reforms were only systematically assessed by age and gender, and, where data were available, by disability and ethnicity with no attempt to gauge cumulative impacts. There is also evidence of Equality Impact Assessments finding a disproportionate impact on individuals with protected characteristics where no mitigating action was taken.

The proliferation of homelessness and housing precariousness, along with a dramatic growth in food banks, are two signs that while parts of the UK economy may be recovering from the 2008 financial crisis and recession, the same cannot be said for the living conditions of much of the poor and working class population. Much of the media discussion has centered on the ways in which these social ills have been caused by government policy, particularly cuts to social and welfare services introduced under the banner of “austerity.” I argue in this paper, however, that a narrow focus on austerity risks obscuring some of the longer-term structural transformations that have taken place under neoliberal capitalism, namely: (1) financialization and (2) the privatization of social reproduction. Situating these two trends within a longer history of capitalism, I argue, allows us to understand the contemporary housing and food crises as specific (and highly gendered) manifestations of a more fundamental contradiction between capital accumulation and progressive and sustainable forms of social reproduction. Doing so further helps to locate the dramatic proliferation of household debt, which has been supported by both processes, as both cause and consequence of the crisis in social reproduction faced by many UK households.

Purpose – This paper focuses on a unique historical case study of industry evolution in order to develop a road map where historical and strategic research could develop a common ground for trans-disciplinary inquiry.

Design/methodology/approach – The industry I explore is the Universal Credit Card Industry since its inception with the Diners Club in 1949 until its maturity in late 1990s. My empirical objective here is to develop a historically detailed and theoretically rich case study in which evolutionary processes are discovered as a result of the historical narrative.

Findings – The historical account of the industry demonstrates how the evolution of alternative business models as organizing forms has led to the establishment of interorganizational platforms with unique ecosystems. These alternative business models, through various experimentations, have ultimately produced two critical interorganizational organizations, one based on an open-loop system represented by Visa and MasterCard, and the other based on a closed-loop system represented by Diners Club and the American Express. The historical account also shows that in a given industry competition is not only among specific firms in the industry but also among the business models and the platforms created by these models.

Originality/value – I conclude that historical analyses reveal the nature of competition not only among firms but also among alternative business models where traditional strategy research rarely covers.

Lone mothers commonly face social stigma alongside practical challenges in fulfilling both principal breadwinner and primary carer roles. This chapter draws on findings from qualitative research involving a sample of lone mothers in the north of England to discuss how they negotiate competing employment and parenting demands within a socio-political context characterized by “worker citizenship”. This model positions them firmly as workers while increased benefits conditionality is reinforced by media stereotypes that conflate lone motherhood with welfare dependency.

A comparative research design was developed to explore experiences of mothers in two nearby locations with contrasting socio-economic profiles using a Bourdieusian approach to class analysis. Factors affecting lone mothers’ subjective perceptions of a historically de-legitimated identity were investigated during semi-structured interviews with women in diverse situations.

The interviews revealed that participants across the sample viewed being in paid employment as the most significant factor in mitigating stigma. They emphasized their work orientation and saw this as an aspect of responsible parenting. Most mothers in the more affluent location used the cultural capital of educational qualifications to secure work that could be balanced with parenting. In contrast, most mothers in the deprived location expressed frustration at being unable to access jobs that are compatible with childcare and consequently felt stigmatized for claiming benefits.

The chapter is of value in illustrating the significance of avoiding stigma as a consideration in lone mothers’ deliberations on work/family interface. It also highlights the impact of class and location on lone mothers’ ability to balance employment with childcare.

The purpose of this research is to examine the connections between liquidity risk, credit risk, and bank profitability in India.

In order to examine the interlinkage between liquidity risk, credit risk, and profitability of banks in India, the researcher has gathered data from all commercial banks in India from 2004–2005 to 2020–2021. The data sources included in this study encompass the International Country Risk Guide, World Development Indicators and Reserve Bank of India (RBI). Seemingly Unrelated Regression (SUR) has been utilised for the study.

Findings of this research identified that liquidity risk is inversely proportional to credit risk. Return on assets (ROA) and return on equity (ROE) are both impacted negatively by liquidity risk. ROA is impacted positively by credit risk, while ROE is impacted negatively by it. The profitability of banks is harmed by the interaction between liquidity risk and credit risk. It also shows that law and order, are beneficial to bank earnings and risk management. The capital risk-adjusted ratio has a negative relationship with bank profitability, indicating the need for better capital allocation.

The originality of this work lies in its unique contributions, It emphasises explicitly the Indian context, thereby providing insights tailored to this particular setting. It employs the SUR methodology, a statistical approach allowing for a more comprehensive data analysis. Additionally, it identifies and explores interaction effects, which can shed light on the complex relationships between variables.

Introduction: Lending is an age-old concept, and Peer-to-Peer (P2P) lending is not new. The reduction in the issuing of loans by banks has made people switch from traditional to online mode. The introduction of the online P2P lending industry is in its nascent stage of growth. As this industry is relatively new, understanding user experience, sentiments, and emotions would be helpful for the industry to innovate as per customer requirements.

Purpose: To explore the patterns in the sentiments expressed by users of ‘Cashkumar’ based on Google reviews.

Methodology: Sentiments have been analysed using user experience in risk, cost, ease of use, and loan processing time. Python application was used for sentiment analysis of Google reviews.

Findings: The sentiment analysis results showed that the average sentiment score was 0.7144, which indicates that the user sentiment towards ‘Cashkumar’ is positive. The reviews reflect that the users, especially borrowers were satisfied with the platform’s services and happy with loan processing time. The other factors – ease of use, cost, and risk – were not given much importance by users. Both lenders and borrowers faced a few issues, but the results of the lender’s sentiment analysis could not be generalised due to a smaller number of posted reviews.

The analysis considers the use of Benford’s Law as a forensic tool to audit the quality of accounting information reported by banks in emerging market countries. History suggests that lack of financial standards and reporting transparency can ultimately lead to bank failures in these nations. We use the Benford Distribution to analyze the first digits of bank financial statement entries and show the value of accounting standards in producing information of high quality. Benford’s Law maintains that the first digits of an unconstrained, large array of numbers might follow a lognormal pattern. It can be applied, for example, to financial statements issued by banks to infer their data integrity. To illustrate the importance of accounting standards and reporting transparency, the analysis utilizes Russian bank statement data from 2001 to 2011. The main finding is that accounting standards matter. After the Russian Central Bank required all banks to adopt International Financial Reporting Standards in 2004, the financial statement data largely conformed to Benford’s Law. While the Benford distribution can be used to infer the overall quality of bank financial statement data in emerging market countries, it is less effective in spotting troubled banks that commit reporting fraud. One possible reason is that the Benford distribution is scale invariant, and violation of Benford’s Law is a sufficient but not necessary condition for accounting irregularities.