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Food choices profoundly affect one's dietary, nutritional and health outcomes. Using alcoholic beverages as a case study, the authors assess the potential of genetic data in predicting consumers' food choices combined with conventional socio-demographic data.

A discrete choice experiment was conducted to elicit the underlying preferences of 484 participants from seven provinces in China. By linking three types of data (—data from the choice experiment, socio-demographic information and individual genotyping data) of the participants, the authors employed four machine learning-based classification (MLC) models to assess the performance of genetic information in predicting individuals' food choices.

The authors found that the XGBoost algorithm incorporating both genetic and socio-demographic data achieves the highest prediction accuracy (77.36%), significantly outperforming those using only socio-demographic data (permutation test p-value = 0.033). Polygenic scores of several behavioral traits (e.g. depression and height) and genetic variants associated with bitter taste perceptions (e.g. TAS2R5 rs2227264 and TAS2R38 rs713598) offer contributions comparable to that of standard socio-demographic factors (e.g. gender, age and income).

This study is among the first in the economic literature to empirically demonstrate genetic factors' important role in predicting consumer behavior. The findings contribute fresh insights to the realm of random utility theory and warrant further consumer behavior studies integrating genetic data to facilitate developments in precision nutrition and precision marketing.

The COVID-19 pandemic continues to challenge healthcare systems worldwide. The authors examined the lived experiences and perceptions of healthcare workers (HCWs) in managerial and senior positions to explore the pandemic's effects on well-being and valued organisational responses.

Using purposive sampling, the authors conducted 39 semi-structured interviews with senior staff including health service administrators, heads of department and senior clinicians at a designated COVID-19 facility in New South Wales, Australia. Interviews were conducted from November 2020 to February 2021 to reflect on experiences during the height of the pandemic in 2020 (mid-March to the end of May 2020).

Workplace experiences affecting HCWs' well-being included being shunned by others, fear of infecting family, fear of the unknown, concerns about personal protective equipment, lack of direction from above and increased workload. Organisational interventions to protect the health and safety of HCWs and their patients included redeployment, improved communication, effective management committees, education and mental health supports.

Organisations can minimise worker-identified factors threatening their well-being during a health crisis by applying broad-ranging initiatives including inclusive and open communication, promoting flexible work practices, providing up-to-date guidelines and policies and fostering camaraderie between workers.

The voices of senior clinical and managerial staff have been largely unheard during the COVID-19 pandemic. The authors addressed this deficit by describing their experiences and insights regarding the pandemic's impact on well-being and the organisation's responses to simultaneously safeguarding its staff and providing quality patient care.

This study aims to analyze the effect of cognitive load and social value orientation on managers’ preferences when they face with two types of restructuring choices in financially distressed firms: the first belonging to the family of organizational restructuring (massive layoffs) and the second to the family of financial restructuring (debt increases).

The authors investigate experimentally the impact of managers’ cognitive load and social value orientation on the decision to restructure leveraged buyout (LBO) firms in financial distress by using either massive layoffs or debt increases.

By investigating the impact of managers’ cognitive load and social value orientation on the restructuring decision of an LBO firm in financial distress, the research reveals that, on average, cognitively loaded managers prefer massive layoffs over increased debt levels. The massive layoffs seemingly provide a relatively easier way to avoid conflict with influential, residual claimants. In contrast, social value–oriented managers actively avoid massive layoffs and prefer to increase debt.

These results imply that the performance mechanisms emphasized to improve agency relations, for example, in LBOs, have their own limitations during periods of financial distress. This study shows that one of these limits is related to cognitive distortions and personality traits.

In this research, the originality lies in understanding how managers’ internal factors affect their restructuring decision-making, in the case of LBO firms in financial distress.

This paper critically evaluates potential barriers to employment opportunities for ethnic minority (EM) individuals in Scottish Local Authorities – both in terms of access to job and development opportunities. It provides a fundamental discussion of concepts around race and ethnicity, and the levels of social injustice, with an explicit focus on institutional racialisation, discrimination and segregation. The paper explores organisational approaches towards recruitment, including positive action and workforce development.

This paper adopts a subjectivist (ontology) and interpretivist (epistemology) stance, based on a small-scale, in-depth investigation. The data have been gathered through semi-structured interviews with equality diversity and inclusion (EDI) officers in four Scottish Local Authorities, utilising thematic analysis.

The finding suggests that participating local authorities have a long way to go to ensure the elimination of barriers to employment for EM people. This is largely based on concerns around limitations in the application of positive action and elimination of disadvantages in recruitment and access to career and development opportunities?

The paper aims to contribute by exploring the availability of employment opportunities for EMs through the eyes of EDI Officers in four local authorities. Their thorough understanding, over- and insight into potential equality issues from an employment perspective are invaluable, focussing on more tangible organisational issues and approaches.

This chapter discusses the utility of authentic leadership for the UN's Sustainable Development Goals and argues that the capacity-building value of authentic leadership enables change and improves performance. The authors view authentic leadership as a genuine, transparent, positive, ethical form of leadership that strives to address grand challenges. They outline its application in two cases: well-being (SDG3) and education (SDG4). Daskou and Tzokas conclude with a criticism of the value of authentic leadership in the successful delivery of the SDGs. Daskou and Tzokas recommend investigating how authentic leaders' balanced information processing and internalised moral perspective contribute to positive self-development, better education outcomes and well-being among students, educators and employees.

This research examines stock traders' disposition effects and contrarian/momentum behavior in the Taiwan Stock Exchange (TWSE). Specifically, we first investigate disposition effects across all trader types and then examine the relationships between disposition effects, trader types, and order characteristics. Next, we explore contrarian and/or momentum behavior and analyze the relationships among the contrarian/momentum behavior, investor type, and order characteristics. Finally, the links among trader types, order characteristics, and investment performance are detected. This chapter yields the following findings. (1) Individual investors exhibit the strongest disposition effects compared to other investors. (2) Foreign investors, investment trusts, and individual investors tend to use large orders to sell loser stocks. (3) Investment trusts are inclined to be momentum traders, while individual investors tend to perform contrarian strategies. (4) Institutional aggressive and large orders perform better than individuals' orders. (5) The performance of foreign investors' selling decisions is better than that of retail investors.

The COVID-19 pandemic was an eye-opening experience that put to the test our crisis management competencies across many institutions, including those offered by institutions of higher education. This study aims to review the literature on international business (IB) risks and IB education (IBE) to question whether business graduates are equipped to make decisions in today’s volatile, uncertain, complex and ambiguous (VUCA) marketplace.

While the IB literature has discussed the importance of various sources of risks on global business operations, IBE did not effectively adopt an integrative approach to building the needed risk management competencies related to those risks into our education. The authors argue that this integrative approach to teaching IB is critically needed to prepare future global managers for addressing crises, like that of the pandemic and others. Specifically, this study proposes that this integrated risk management competency can be developed through the building of “synergistic mindsets”.

This study presents a conceptual framework for the components of the synergistic mindset, with intelligence that directly links to present IB risks. These components are cultural intelligence (CQ), emotional intelligence (EQ), public policy intelligence (PPQ), digital intelligence (DQ) and orchestration intelligence (OQ).

Insights related to IBE effectiveness in addressing today’s VUCA market demands and IB risks are discussed.

The global environments that surround contemporary business activities are uncertain, fast-changing, and frequently exposed to abrupt unexpected events with the potential to inflict extreme impacts where the ability to respond and adapt the organization effectively becomes a primary strategic concern. However, various firms that operate across diverse industry contexts approach this adaptive challenge in distinct ways that lead to quite diverse outcomes with many negative performers and some high performers with positive risk features. The heterogeneous approaches appear to consistently form extreme left-tailed performance distributions with inverse risk-return features but we are not really able to explain why and how these regularly observed phenomena come about. Hence, we want to study these organizational artifacts by collecting an extensive updated dataset to test the proposed relationships, explore alternative explanations, and learn from the extreme exemplars often referred to as outliers. There are extensive literatures in (strategic) management and finance that have dealt with the distribution of firm returns from slightly different angles but with some emerging commonalities that can inspire further analyses of the performance data. As a precursor for this, we discuss the odds of effective strategic adaptation in complex dynamic environments and introduce resilience as a proper outcome when simple solutions are scarce, and consider conditions that may facilitate these aims. The premises for the ensuing analyses are laid out and the main contents of the following chapters are presented.

With the intensification of market competition, there is a growing demand for weak signal identification and evolutionary analysis for enterprise foresight. For decades, many scholars have conducted relevant research. However, the existing research only cuts in from a single angle and lacks a systematic and comprehensive overview. In this paper, the authors summarize the articles related to weak signal recognition and evolutionary analysis, in an attempt to make contributions to relevant research.

The authors develop a systematic overview framework based on the most classical three-dimensional space model of weak signals. Framework comprehensively summarizes the current research insights and knowledge from three dimensions of research field, identification methods and interpretation methods.

The research results show that it is necessary to improve the automation level in the process of weak signal recognition and analysis and transfer valuable human resources to the decision-making stage. In addition, it is necessary to coordinate multiple types of data sources, expand research subfields and optimize weak signal recognition and interpretation methods, with a view to expanding weak signal future research, making theoretical and practical contributions to enterprise foresight, and providing reference for the government to establish weak signal technology monitoring, evaluation and early warning mechanisms.

The authors develop a systematic overview framework based on the most classical three-dimensional space model of weak signals. It comprehensively summarizes the current research insights and knowledge from three dimensions of research field, identification methods and interpretation methods.