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Stress computation in finite element materially non‐linear analysis is an important problem that has perhaps been receiving less attention than it deserves. Not only does it consume a significant share of total computer time, but also inaccuracies and ‘savings’ thereupon may well jeopardize the gains aimed at by sophisticating elsewhere the numerical strategy. A well established algorithm for stress computation is reviewed in detail, illustrating a number of computational hazards and proposing simple solutions.

Everyday conversation has not yet been assigned its full role in public discussion of citizen’s issues, despite the growing number of studies about it. Casual conversations are not usually regarded as a particularly privileged place for political discussions mainly because of its apparent lack of organization following the principles and rules of the deliberative tradition in Political Studies. However, due to its closeness, informality, and personal proximity, it is particularly adequate to rise political aspects of everyday lives that otherwise would not be publicly disclosed. But how to grasp the spontaneity of everyday conversation? This chapter argues that focus groups, as a research method, are fit to observe and understand real-time ordinary conversation on political issues. In what follows, the argument goes threefold: (1) it contrasts “conversation” with “deliberation” from a micro-point of view; (2) all conversation, as a discourse embroiled in power relations, is political in a broad sense (3) as it brings forward personal views and experiences, casual conversations defies the borders between public and private issues.

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.

Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.

Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.

Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.

Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.

Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.

Entrepreneurial orientation (EO) has emerged as a core concept in the field of entrepreneurship. Yet, there continue to be questions about the nature of EO and how best to conceptualize and measure it. This chapter makes the case that EO has grown beyond its roots as a firm-level unidimensional strategy construct and that a new multidimensional version of EO is needed to capture the diverse manifestations and venues for entrepreneurial activity that are now evident around the world – global entrepreneurial orientation (GEO). Building on the five-dimension multidimensional view of EO set forth when Lumpkin and Dess (1996) extended the work of Miller (1983) and Covin and Slevin (1989, 1991), the chapter offers an updated definition of EO and a fresh interpretation of why EO matters theoretically. Despite earnest efforts to reconcile the different approaches to EO, in order to move the study of EO and the theoretical conversation about it forward, we maintain that as a group of scholars and a field, we need to acknowledge that two different versions of EO have emerged. Given that, we consider original approaches to measuring EO, evaluate formative measurement models, consider multiple levels of analysis, call for renewed attention to EO configurations, and discuss whether there is a theory of EO.

For several years, the classic car market has been attracting considerable media and public attention, but the research literature is virtually nonexistent. The purpose of this paper is to address the factors that determine the values of classic car models and explain the remarkable price differences among them.

The paper develops and tests a set of research hypotheses about the effects of model characteristics on market values in the context of a generalized hedonic price model that also accounts for heterogeneity among classic car brands.

It is demonstrated that classic car model values reside at several levels and are determined by observable characteristics pertaining to aesthetics, rarity, engineering and performance. In addition, we show that classic car marques play a critical role in the determination of model values and account for considerable variation in values, even after controlling for observable model attributes

This is one of the first empirical studies to address classic car model value formation. The findings reveal how measurable, observable factors determine classic car model values and augment our understanding of a very interesting but understudied market.

In this study, workplace spirituality is discussed in the context of remote work and the COVID-19 pandemic. First, the focus is on the changes in the meaning and function of employees in the organization during the evolutionary process of industrialization and management paradigms. Afterward, conceptual frameworks for spirituality and workplace spirituality are presented, and in the last section, academic studies that deal with workplace spirituality with distance or hybrid work arrangements are included. Early studies offer insights and recommendations on conceptualizing, developing, and managing workplace spirituality. They all emphasize that spirituality is necessary for remote work as a tool to overcome stress and mental health problems and increase employee well-being. Unfortunately, the remote work and workplace spirituality literature is relatively narrow and needs to be expanded.

This study analyzes the role of migrant networks in the migration flows in relation to the educational level of the migrants and economic growth of the states of origin and destination in Brazil.

Fixed effects estimator applied to microdata.

The results show migrant networks have a significant and positive impact on migration flows of the different educational levels. The economic growth in the destination state accentuates this effect, while the economic growth in the origin state has distinct impacts according to the educational level of the new migrant.

The authors investigate the importance of migrant networks in the internal immigration within a developing country with large internal movement of people. In Brazil, the socio-economic condition of the population varies considerably in relation to its geography, which explains the country’s large internal migration flows.