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India has a distinct family hierarchy and a vertical collectivistic culture. Indian traditional cultural norms discourage young adults from having romantic or sexual relationships before marriage. Romantic liaisons and marriages are fiercely opposed outside the caste and social network. Despite this cultural practice, research in the last decade demonstrated that more young adults in India engage in premarital romantic relationships and prefer a marriage of choice. However, they strongly wish their parents to approve of their partner and arrange their marriage. This increasing trend of love-cum-arranged marriages could be considered how Indian culture adapts to the demands of modernization strongly impelled by globalization. This chapter discusses the dynamics of change in the romantic and marital agency among young adults in India. First, the authors provide a brief historical introduction to the Indian marital system. Then, the authors discuss the changing cultural dimensions that promote marital choice and independence in partner selection (e.g., filial piety). Further, the authors provide an overview of the trends in premarital romantic relationships in India. In addition, the authors discuss the distress and conflict in Indian families due to the increasing premarital romantic and sexual relationships among Indian youth, as evidenced by eloped marriages, forced marriages, and honor killings.

To understand how Indian first-time mothers in STEM (Science, Technology, Engineering and Math) organisations returning to work cope with the perceived ideological psychological contract breaches from a work–home resources perspective.

This paper utilises interpretative phenomenological analysis (IPA) within the work–home resources (W-HR) model to analyse returning first-time mothers' lived experiences.

This study shows that significant life/work events such as childbirth/lack of career growth can trigger resource depletion at work and home and materialise in first-time mothers perceiving ideological psychological contract breaches at work. It has also been observed that key resource usage and macro support structures aid employees in attenuating work–home conflict by balancing contextual demands and personal resources. This study's participant accounts reveal that the recovery of volatile resources was possible by psychologically detaching and being silent.

The study offers a distinctive perspective by investigating the ideological PC breach experienced by first-time Indian mothers upon their organisational re-entry from a work–home resource model lens. Situated in a unique socio-cultural space and bringing forth the rich lived experiences of women working in the Indian STEM field, this paper explores how key resources shape the coping responses of first-time mothers in this context.

This study aims to delve into the mechanisms through which financial statements readability (FSR) may impact the probability of stock price crashes. It specifically examines how information asymmetry and stock liquidity mediate this relationship.

The study uses data from 107 nonfinancial firms listed on the Egyptian Stock Exchange between 2016 and 2019 to investigate the mediating roles of information asymmetry and stock liquidity using structural equation modeling (SEM). To enhance robustness, the author incorporates the Bootstrap method, conducting 5,000 iterations for consistent validation of results.

The findings of this study identify two crucial mediators in the correlation between the readability of financial statements and stock price crash risk. First, information asymmetry partially mediates this association. Complex financial statements allow managers to hide adverse news, thereby increasing information asymmetry. Consequently, investors face challenges in assessing the company’s risk and performance, elevating the probability of stock price crashes when such concealed information is disclosed. Second, the results indicate that stock liquidity plays a key mediating role. Less-readable financial statements hinder stock liquidity, making it more difficult for investors to trade shares efficiently. This reduced liquidity amplifies the influence of negative news, potentially increasing the crash risk. Importantly, our findings demonstrate robustness across various measures, encompassing two readability indicators and two crash risk proxies, validated through both SEM and Bootstrap methods.

Although this research provides valuable insights, it is critical to acknowledge its limitations. The relatively limited sample size may affect the broader applicability of the findings. Moreover, this study was carried out in the Egyptian setting, where financial reporting is conducted in Arabic. This linguistic and cultural specificity could influence the interpretation and generalizability of the findings beyond the Egyptian and Arab contexts. To overcome this limitation, this paper recommends conducting comparative research in diverse linguistic and cultural environments.

The outcomes of this research carry substantial implications for policymakers and regulators, emphasizing the need for ongoing efforts to enhance financial reporting standards. Clear and readable financial reports contribute not only to market transparency but also to the overall stability and resilience of financial markets. Policymakers are encouraged to consider our findings when shaping or revising standards to ensure readability and transparency, potentially reducing the risk of market disruptions. Furthermore, companies should recognize the adverse impact of complex financial reports, prioritizing transparent and readable reporting to foster investor trust and mitigate crash risks.

This research comprehensively analyzes the intricate relationships among FSR, information asymmetry, stock liquidity and stock price crash risk. Focusing on the mediating roles of information asymmetry and stock liquidity, this paper provides novel insights, advancing theoretical understanding and practical implications for risk management and financial reporting. This study expands the current body of knowledge on how FSR is related to the probability of stock price crashes.

Identifying the flow regime is a prerequisite for accurately modeling two-phase flow. This paper aims to introduce a comprehensive data-driven workflow for flow regime identification.

A numerical two-phase flow model was validated against experimental data and was used to generate dynamic pressure signals for three different flow regimes. First, four distinct methods were used for feature extraction: discrete wavelet transform (DWT), empirical mode decomposition, power spectral density and the time series analysis method. Kernel Fisher discriminant analysis (KFDA) was used to simultaneously perform dimensionality reduction and machine learning (ML) classification for each set of features. Finally, the Shapley additive explanations (SHAP) method was applied to make the workflow explainable.

The results highlighted that the DWT + KFDA method exhibited the highest testing and training accuracy at 95.2% and 88.8%, respectively. Results also include a virtual flow regime map to facilitate the visualization of features in two dimension. Finally, SHAP analysis showed that minimum and maximum values extracted at the fourth and second signal decomposition levels of DWT are the best flow-distinguishing features.

This workflow can be applied to opaque pipes fitted with pressure sensors to achieve flow assurance and automatic monitoring of two-phase flow occurring in many process industries.

This paper presents a novel flow regime identification method by fusing dynamic pressure measurements with ML techniques. The authors’ novel DWT + KFDA method demonstrates superior performance for flow regime identification with explainability.

This study aims to improve the acceleration in the additive manufacturing (AM) process. AM tools, such as extrusion heads, jets, electric arcs, lasers and electron beams (EB), experience negligible forces. However, their speeds are limited by the positioning systems. In addition, a thin tool must travel several kilometers in tiny motions with several turns while realizing the AM part. Hence, acceleration is a more significant limiting factor than the velocity or precision for all except EB.

The sawtooth (ST) scanning strategy presented in this paper minimizes the time by combining three motion features: zigzag scan, 45º or 135º rotation for successive layers in G00 to avoid the CNC interpolation, and modifying these movements along 45º or 135º into sawtooth to halve the turns.

Sawtooth effectiveness is tested using an in-house developed Sand AM (SaAM) apparatus based on the laser–powder bed fusion AM technique. For a simple rectangle layer, the sawtooth achieved a path length reduction of 0.19%–1.49% and reduced the overall time by 3.508–4.889 times, proving that sawtooth uses increased acceleration more effectively than the other three scans. The complex layer study reduced calculated time by 69.80%–139.96% and manufacturing time by 47.35%–86.85%. Sawtooth samples also exhibited less dimensional variation (0.88%) than zigzag 45° (12.94%) along the build direction.

Sawtooth is limited to flying optics AM process.

Development of scanning strategy for flying optics AM process to reduce the warpage by improving the acceleration.

Foreign subsidiaries of multinational enterprises (MNEs) operate in complex and competitive international environments, implement market and non-market strategies, manage resources and value-added activities and contribute to the overall performance of their parent firms. Thus, the research question on the determinants of MNE foreign subsidiaries’ performance is of interest to managers and academic researchers. The empirical literature has flourished over the recent decades; however, the domains are fragmented, and the findings are inclusive. The purpose of this study is to systematically review, analyse and synthesize the empirical articles in this area, identify research gaps and suggest a future research agenda.

This study uses the qualitative content analysis method in reviewing and analysing 150 articles published in 24 scholarly journals during the period 2000–2023.

The literature uses a variety of theoretical perspectives to examine the key determinants of subsidiary performance which can be grouped into six major domains, namely, home- and host country-level factors; distance between home and host countries; the characteristics of parent firms and of subsidiaries; and governance mechanisms (the establishment modes and ownership strategy, subsidiary autonomy and the use of home country expatriates for transferring knowledge from the headquarters and controlling foreign subsidiaries). A range of objective and subjective indicators are used to measure subsidiary performance. Yet, the research shows a lack of broader integration of theories and presents inconsistent theoretical predictions, inconclusive empirical findings and estimation bias, which hinder our understanding of how the determinants independently and jointly shape the performance of foreign subsidiaries.

This study provides a comprehensive, nuanced and systematic review that synthesizes and clarifies the determinants of subsidiary performance, offers deeper insights from both theoretical, methodological and empirical aspects and proposes some promising avenues for future research directions.

This chapter discusses the contributions and challenges involving regulatory technology (regtech) in financial services. It explores the salient areas where regtech can and should focus, observing existing and forthcoming industry, technology, and legal developments. This chapter outlines regtech use cases to clarify the shaping of that industry sector. It draws on developments in industry and academia, where significant research sets the tone and direction of technological solutions and regulatory drivers. A brief critical account of the benefits and challenges in regtech is offered. This chapter presents potential future directions, focusing on the salient areas of environmental, social, and governance (ESG), cryptocurrency, and decentralized compliance.

This study aims to explore the relationship between chief executive officer (CEO) power and stock price crash risk in India. Furthermore, it seeks to analyse how insider trades may moderate the impact of CEO power on stock price crash risk.

A study of 236 companies from the S&P BSE 500 Index (2014–2023) have been analysed through pooled ordinary least square (OLS) regression in the baseline analysis. To enhance the results' reliability, robustness checks include alternative methodologies, such as panel data regression with fixed-effects, binary logistic regression and Bayesian regression. Additional control variables and alternative crash risk measure have also been utilised. To address potential endogeneity, instrumental variable techniques such as two-stage least squares (IV-2SLS) and difference-in-difference (DiD) methodologies are utilised.

Stakeholder theory is supported by results revealing that CEO power proxies like CEO duality, status and directorship reduce one-year ahead stock price crash risk and vice versa. Insider trades are found to moderate the link between select dimensions of CEO power and stock price crash risk. These findings persist after addressing potential endogeneity concerns, and the results remain consistent across alternative methodologies and variable inclusions.

This study significantly advances research on stock price crash risk, especially in emerging economies like India. The implications of these findings are crucial for investors aiming to mitigate crash risk, for corporations seeking enhanced governance measures and for policymakers considering the economic and welfare consequences associated with this phenomenon.