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Adoption of digital technology at different levels of economic activity is an important indicator of development. Countries are adopting digital technology at business and government levels to increase efficiency and accountability of service delivery to appropriate user groups. Many countries are using digital technology in banking, education, and many other sectors and recasting the relationship among customers, workers, and employers. The digital transformation progressively changes productivity across all sectors and industries. The empirical investigation shows that mainly the role of per capita income (state of living) and supply-side factors explain cross-country variations in Digital Adoption Index (DAI) in business using a static panel data model with fixed effect (FE) approach for 169 countries over the period 2014–2016. In this context, this study makes an attempt to understand the state of digital adoption in business across 169 countries in 2016 using World Bank data. The empirical results state that only major variable like labour force are positively and statistically significant with DAI across the countries. Although there are caveats that the International Monetary Fund has made about the digital economy, they state that we should think carefully about how to devise policies that will allow us to fully exploit the digital revolution’s benefits while minimizing job dislocation.

This chapter provided systematic and comprehensive analysis on trawl fisheries management and conservation measures in the Straits of Malacca. Detailed analysis is conducted on Malaysian fishery management framework particularly domestic country's trawl fishery status, legal structure, input-control strategies, ecosystem protection plan, pollution, law enforcement, and complementary measures that designed to reduce and prevent overfishing in the exclusive economic zone (EEZ) of Malacca Straits. Gaps and challenges found in existing trawl fisheries literature are presented followed by recommendations for improvement in the management and conservation of trawl fisheries.

The purpose of this study is to carry out a comprehensive analysis of magneto-hydrodynamics (MHD), nanofluidic flow dynamics and heat transfer as well as thermodynamic irreversibility, within a novel butterfly-shaped cavity. Gaining a thorough understanding of these phenomena will help to facilitate the design and optimization of thermal systems with complex geometries under magnetic fields in diverse applications.

To achieve the objective, the finite element method is used to solve the governing equations of the problem. The effects of various controlling parameters such as butterfly-shaped triangle vertex angle (T), Rayleigh number (Ra), Hartmann number (Ha) and magnetic field inclination angle (γ ) on the hydrothermal performance are analyzed meticulously. By investigating the effects of these parameters, the authors contribute to the existing knowledge by shedding light on their influence on heat and fluid transport within butterfly-shaped cavities.

The major findings of this study reveal that the geometrical shape significantly alters fluid motion, heat transfer and irreversibility production. Maximum heat transfer, as well as entropy generation, occurs when the Rayleigh number reaches its maximum, the Hartmann number is minimized and the angle of the magnetic field is set to 30° or 150°, while the butterfly wings angle or vertex angle is kept at a maximum of 120°. The intensity of the magnetic field significantly controls the heat flow dynamics, with higher magnetic field strength causing a reduction in the flow strength as well as heat transfer. This configuration optimizes the heat transfer characteristics in the system.

Further research can be expanded on this study by examining thermal performance under different curvature effects, orientations, boundary conditions and additional factors. This can be accomplished through numerical simulations or experimental investigations under various multiphysical scenarios.

The geometric configurations explored in this research have practical applications in various engineering fields, including heat exchangers, crystallization processes, microelectronic devices, energy storage systems, mixing processes, food processing, air-conditioning, filtration and more.

This study brings value by exploring a novel geometric configuration comprising the nanofluidic flow, and MHD effect, providing insights and potential innovations in the field of thermal fluid dynamics. The findings contribute a lot toward maximizing thermal performance in diverse fields of applications. The comparison of different hydrothermal behavior and thermodynamic entropy production under the varying geometric configuration adds novelty to this study.

The purpose of this paper is to evaluate the extent to which a sample of US-based higher education institution’s (HEI’s) climate targets and associated climate action planning efforts align with the definitions of and practices associated with science-based targets (SBTs) that are typically used to organize corporate climate efforts. This analysis will be used to explore similarities and tease out differences between how US-based HEIs and corporations approach sustainable target setting and organize sustainable action.

The degree of intersection between a sample of HEI climate action plans from Ivy Plus (Ivy+) schools and the current SBT initiative (SBTi) general corporate protocol was assessed by using an objective-oriented evaluative approach.

While there were some areas of overlap between HEI’s climate action planning and SBTi’s general corporate protocol – for instance, the setting of both short- and long-term targets and large-scale investments in renewable energy – significant areas of difference in sampled HEIs included scant quantitative Scope 3 targets, the use offsets to meet short-term targets and a low absolute annual reduction of Scope 1 and 2 emissions.

This paper unites diverse areas of literature on SBTs, corporate sustainability target setting and sustainability in higher education. It provides an overview of the potential benefits and disadvantages of HEIs adopting SBTs and provides recommendations for the development of sector-specific SBTi guidelines.

This study aims to undertake a comprehensive examination of heat transfer by convection in porous systems with top and bottom walls insulated and differently heated vertical walls under a magnetic field. For a specific nanofluid, the study aims to bring out the effects of different segmental heating arrangements.

An existing in-house code based on the finite volume method has provided the numerical solution of the coupled nondimensional transport equations. Following a validation study, different explorations include the variations of Darcy–Rayleigh number (Ra_m = 10–10⁴), Darcy number (Da = 10^–5–10^–1) segmented arrangements of heaters of identical total length, porosity index (ε = 0.1–1) and aspect ratio of the cavity (AR = 0.25–2) under Hartmann number (Ha = 10–70) and volume fraction of φ = 0.1% for the nanoparticles. In the analysis, there are major roles of the streamlines, isotherms and heatlines on the vertical mid-plane of the cavity and the profiles of the flow velocity and temperature on the central line of the section.

The finding of a monotonic rise in the heat transfer rate with an increase in Ra_m from 10 to 10⁴ has prompted a further comparison of the rate at Ra_m equal to 10⁴ with the total length of the heaters kept constant in all the cases. With respect to uniform heating of one entire wall, the study reveals a significant advantage of 246% rate enhancement from two equal heater segments placed centrally on opposite walls. This rate has emerged higher by 82% and 249%, respectively, with both the segments placed at the top and one at the bottom and one at the top. An increase in the number of centrally arranged heaters on each wall from one to five has yielded 286% rate enhancement. Changes in the ratio of the cavity height-to-length from 1.0 to 0.2 and 2 cause the rate to decrease by 50% and increase by 21%, respectively.

Further research with additional parameters, geometries and configurations will consolidate the understanding. Experimental validation can complement the numerical simulations presented in this study.

This research contributes to the field by integrating segmented heating, magnetic fields and hybrid nanofluid in a porous flow domain, addressing existing research gaps. The findings provide valuable insights for enhancing thermal performance, and controlling heat transfer locally, and have implications for medical treatments, thermal management systems and related fields. The research opens up new possibilities for precise thermal management and offers directions for future investigations.

This paper aims to investigate the thermal performance of equivalent square and circular thermal systems and compare the heat transport and irreversibility of magnetohydrodynamic (MHD) nanofluid flow within these systems.

The research uses a constraint-based approach to analyze the impact of geometric shapes on heat transfer and irreversibility. Two equivalent systems, a square cavity and a circular cavity, are examined, considering identical heating/cooling lengths and fluid flow volume. The analysis includes parameters such as magnetic field strength, nanoparticle concentration and accompanying irreversibility.

This study reveals that circular geometry outperforms square geometry in terms of heat flow, fluid flow and heat transfer. The equivalent circular thermal system is more efficient, with heat transfer enhancements of approximately 17.7%. The corresponding irreversibility production rate is also higher, which is up to 17.6%. The total irreversibility production increases with Ra and decreases with a rise in Ha. However, the effect of magnetic field orientation (γ) on total EG is minor.

Further research can explore additional geometric shapes, orientations and boundary conditions to expand the understanding of thermal performance in different configurations. Experimental validation can also complement the numerical analysis presented in this study.

This research introduces a constraint-based approach for evaluating heat transport and irreversibility in MHD nanofluid flow within square and circular thermal systems. The comparison of equivalent geometries and the consideration of constraint-based analysis contribute to the originality and value of this work. The findings provide insights for designing optimal thermal systems and advancing MHD nanofluid flow control mechanisms, offering potential for improved efficiency in various applications.

Professional touching behavior (PTB), defined as intentional touching behavior that occurs between organizational members and that falls within the boundaries of appropriateness and professionalism in the workplace, is prevalent in organizations. Scholars from multiple disciplines, including human resources researchers, have acknowledged the importance of physical contact for facilitating interpersonal communication and relationship-building. However, PTB may not only elicit positive reactions from those who receive it but also negative reactions as well, with implications for social dynamics in organizations. PTB can, on the one hand, fulfill employees’ desires for interpersonal connection; at the same time, such physical contact at work can represent a threat to employees’ health. To explain the nature and implications of these divergent effects of receiving PTB, the authors draw upon sociometer theory and behavioral immune system (BIS) theory to model the emotional, cognitive, and physiological processes via which, and the conditions under which, receiving such behavior will result in socially functional responses and prompt subsequent prosocial behavior, and when PTB will be perceived as a health risk and prompt withdrawal behavior. The theoretical framework of this chapter expands our conceptual understanding of the consequences of interpersonal physical contact at work and has important human resources management (HRM) implications for organizational managers.

The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

This study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the past 35 years: (1) the development of a range of innovative new statistical learning methods, particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings management proxies, auditor going concern opinions (GCOs) and corporate governance attributes. Several directions for future research are discussed.

This study provides a systematic review of the corporate failure literature over the past 35 years with a particular focus on the emergence of new statistical learning methodologies and predictor variables. This synthesis of the literature evaluates the strength and limitations of different modelling approaches under different circumstances and provides an overall evaluation the relative contribution of alternative predictor variables. The study aims to provide a transparent, reproducible and interpretable review of the literature. The literature review also takes a theme-centric rather than author-centric approach and focuses on structured themes that have dominated the literature since 1987.

There are several major findings of this study. First, advanced machine learning methods appear to have the most promise for future firm failure research. Not only do these methods predict significantly better than conventional models, but they also possess many appealing statistical properties. Second, there are now a much wider range of variables being used to model and predict firm failure. However, the literature needs to be interpreted with some caution given the many mixed findings. Finally, there are still a number of unresolved methodological issues arising from the Jones (1987) study that still requiring research attention.

The study explains the connections and derivations between a wide range of firm failure models, from simpler linear models to advanced machine learning methods such as gradient boosting, random forests, adaptive boosting and deep learning. The paper highlights the most promising models for future research, particularly in terms of their predictive power, underlying statistical properties and issues of practical implementation. The study also draws together an extensive literature on alternative predictor variables and provides insights into the role and behaviour of alternative predictor variables in firm failure research.