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Defines ergonomics and discusses various issues such as anthropometry, seat design, workplace principles, manual materials handling, and cumulative trauma disorders. These important issues need to be appreciated if the objective of the facilities manager is to reduce work‐related injuries, improve productivity, and improve the quality of life of the workers.

A parabolic trough solar collector is an advanced concentrated solar power technology that significantly captures radiant energy. Solar power will help different sectors reach their energy needs in areas where traditional fuels are in use. This study aims to examine the sensitivity analysis for optimizing the heat transfer and entropy generation in the Jeffrey magnetohydrodynamic hybrid nanofluid flow under the influence of motile gyrotactic microorganisms with solar radiation in the parabolic trough solar collectors. The influences of viscous dissipation and Ohmic heating are also considered in this investigation.

Governing partial differential equations are derived via boundary layer assumptions and nondimensionalized with the help of suitable similarity transformations. The resulting higher-order coupled ordinary differential equations are numerically investigated using the Runga-Kutta fourth-order numerical approach with the shooting technique in the computational MATLAB tool.

The numerical outcomes of influential parameters are presented graphically for velocity, temperature, entropy generation, Bejan number, drag coefficient and Nusselt number. It is observed that escalating the values of melting heat parameter and the Prandl number enhances the Nusselt number, while reverse effect is observed with an enhancement in the magnetic field parameter and bioconvection Lewis number. Increasing the magnetic field and bioconvection diffusion parameter improves the entropy and Bejan number.

Nanotechnology has captured the interest of researchers due to its engrossing performance and wide range of applications in heat transfer and solar energy storage. There are numerous advantages of hybrid nanofluids over traditional heat transfer fluids. In addition, the upswing suspension of the motile gyrotactic microorganisms improves the hybrid nanofluid stability, enhancing the performance of the solar collector. The use of solar energy reduces the industry’s dependency on fossil fuels.

The seasonality in the behavior of travelers is something that goes back to the origin of the trips themselves. This seasonality is due to multiple factors, some easy to counteract and others difficult to solve. But, regardless of the causes, it is a phenomenon that generates significant negative impacts on society and the environment in which the phenomenon of tourist seasonality occurs. All tourist destinations have seasonality, but in some cases, it is very high and in others it has a minimal incidence. The objective of this chapter is to ponder the impacts and consequences of seasonality in regions with a strong tourism development, allowing to put into context the aspects of society impacted by this phenomenon and the positive implications that the reduction of seasonality would have. For this, an analysis of a theoretical model with two regions in opposite situations is carried out, raising the possible effects of a high seasonality. The cases of the Balearic Islands and the Canary Islands are also reviewed, as real examples of the regional typologies taken into consideration in the theoretical model. This seeks to ponder the problems attributable to seasonality. As a final reflection, the enormous typology of negative impacts generated and the need to continue analyzing the seasonality and its impacts are emphasized.

In 2017, US federal agencies awarded over $86 billion in contracts to small businesses owned by members of under-represented groups (minorities, women, service-disabled veterans, and certified businesses located in economically distressed areas). The vast scale and scope of public procurement coupled with policies for supporting small disadvantaged businesses may drive federal agencies toward greater inclusiveness in awarding contracts, which may shape broader societal patterns of economic participation and social equity. However, the level of inclusiveness varies considerably across different federal agencies. The authors posit that differences in three key organizational mechanisms associated with federal agencies’ decision-making processes – administrative discretion, workplace discrimination, and legislative oversight – influence an agency’s level of inclusiveness in awarding contracts. They test these ideas using the annual small business procurement activities of 41 federal agencies, large and small, from 2002 to 2011. The authors find empirical evidence for economically significant effects of discretion, discrimination, and oversight on an agency’s inclusiveness in awarding contracts and discuss the scholarly, managerial, and policy implications.

There is abundant literature analyzing the determinants of banks’ profitability through its main component: the net interest margin. Some of these determinants are suggested by seminal theoretical models and subsequent expansions. Others are ad-hoc selections. Up to now, there are no studies assessing these models from a Bayesian model uncertainty perspective. This paper aims to analyze this issue for the EU-15 countries for the period 2008-2014, which mainly corresponds to the Great Recession years.

It follows a Bayesian variable selection approach to analyze, in a first step, which variables of those suggested by the literature are actually good predictors of banks’ net interest margin. In a second step, using a model selection approach, the authors select the model with the best fit. Finally, the paper provides inference and quantifies the economic impact of the variables selected as good candidates.

The results widely support the validity of the determinants proposed by the seminal models, with only minor discrepancies, reinforcing their capacity to explain net interest margin disparities also during the recent period of restructuring of the banking industry.

The paper is, to the best of the knowledge, the first one following a Bayesian variable selection approach in this field of the literature.

This paper aims to present a study on stability analysis of Jeffrey fluids in the presence of emergent chemical gradients within microbial systems of anisotropic porous media.

This study uses an effective method that combines non-dimensionalization, normal mode analysis and linear stability analysis to examine the stability of Jeffrey fluids in the presence of emergent chemical gradients inside microbial systems in anisotropic porous media. The study focuses on determining critical values and understanding how temperature gradients, concentration gradients and chemical reactions influence the onset of bioconvection patterns. Mathematical transformations and analytical approaches are used to investigate the system’s complicated dynamics and the interaction of numerous characteristics that influence stability.

The analysis is performed using the Jeffrey-Darcy type and Boussinesq estimation. The process involves using non-dimensionalization, using the normal mode approach and conducting linear stability analysis to convert the field equations into ordinary differential equations. The conventional thermal Rayleigh Darcy number RDa,c is derived as a comprehensive function of various parameters, and it remains unaffected by the bio convection Lewis number Łe. Indeed, elevating the values of ζ and γ′ in the interval of 0 to 1 has been noted to expedite the formation of bioconvection patterns while concurrently expanding the dimensions of convective cells. The purpose of this investigation is to learn how the temperature gradient affects the concentration gradient and, in turn, the stability and initiation of bioconvection by taking the Soret effect into the equation. The results provide insightful understandings of the intricate dynamics of fluid systems affected by chemical and biological elements, providing possibilities for possible industrial and biological process applications. The findings illustrate that augmenting both microbe concentration and the bioconvection Péclet number results in an unstable system. In this study, the experimental Rayleigh number RDa,c was determined to be 4π2at the critical wave number (δcˇ) of π.

The study’s novelty originated from its investigation of a novel and complicated system incorporating Jeffrey fluids, emergent chemical gradients and anisotropic porous media, as well as the use of mathematical and analytical approaches to explore the system’s stability and dynamics.

This research investigates the influence of corporate–NGO collaborations on corporate social responsibility (CSR) disclosure measured in three different ways (i.e. extent, level and quality) in low-income developing economies. Additionally, it examines the moderating effect of corporate profitability in the relationship between corporate–NGO collaborations and CSR disclosure.

This research uses multivariate regression analysis based on data collected from 201 non-financial firms listed on the Pakistan Stock Exchange (PSE).

The findings reveal that corporations with NGO partnerships are more likely to disclose CSR information and provide high-quality information regarding workers, the environment and community-related issues. Further, corporate profitability positively moderates the corporate–NGO collaborations and CSR disclosure relationship.

Research limitations are presented in the conclusion section.

The findings underline the crucial significance of NGOs and their associated normative isomorphism logics for CSR disclosure in low-income countries with weak law enforcement and relatively ineffective state institutions, which were previously believed to lack such institutions.

While some research has suggested that companies in developing countries perceive significant pressure from NGOs to adopt social disclosure, no study has specifically explored how internally driven corporate–NGO collaboration (as opposed to external NGO activist pressures) promotes CSR disclosure specifically in developing economies.

We put forward the idea that for model selection the intrinsic priors are becoming a center of a cluster of a dominant group of methodologies for objective Bayesian Model Selection.

The intrinsic method and its applications have been developed in the last two decades, and has stimulated closely related methods. The intrinsic methodology can be thought of as the long searched approach for objective Bayesian model selection and hypothesis testing.

In this paper we review the foundations of the intrinsic priors, their general properties, and some of their applications.

When facing capacity bottlenecks, manufacturers of configurable, multi-variant products may adjust the product mix to uphold the scheduled output. However, maintaining market attractiveness by choosing the right product configurations as substitutes is a non-trivial task as it involves anticipating the substitution behaviour of customers. Substitution behaviour models currently used in quantitative production planning models for configurable products are either based on domain knowledge of experts, which makes them bias-prone, or they require extensive market research. The purpose of this study is to present a data-driven approach.

Based on data science concepts, distance measures are applied to derive distances between different product configurations from historical order data. Different design options for such a distance measure are discussed regarding configurable products and tested with automotive industry data. Furthermore, the study shows ways to validate the distance results.

The experiments show that the presented distance measure represents the expected customer substitution behaviour quite well. A context-sensitive distance measure including rank information of ordinal product features is most suitable for the automotive data sets.

This study presents a new approach to model the substitution behaviour of customers. The attractiveness of a potential substitute is represented by a distance from the customer’s first-choice configuration. The presented distance measure provides an inexpensive tool using existing data instead of expensive market research. Thus, it supports the integration of substitution into quantitative production planning models that deal with a large variety of configurable products.

Four reputed leaders for the coming years in the field of special education for individuals with emotional and behavioral disorders (EBD) each with a slightly different perspective on the field were asked to respond independently to a prompt asking what does special education mean for students with EBD and what is being done and how do we maintain tradition? The contributors' responses to the prompt are presented and then summarized across the essays. A remarkable consistency emerges across the independent essays. In addition to the tradition of providing a free and appropriate education in the least restrictive environment, the contributors identify needs to support teachers serving this population. Needs in teacher training and the expertise required to meet the needs of individuals with EBD are outlined as well as potential contributions of technology to carry out specific tasks. We conclude with a call for increased advocacy for use of the knowledge that we currently possess and that which will soon be discovered to support students with EBD as well as their teachers. We also note that the contributors' names are listed alphabetically to acknowledge the equality of each person to the final product.