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Stories are a part of being human. They are powerful tools to create social bonds, elicit emotions, and consolidate personal and shared memories. Their role, characteristics, and effects are studied in a variety of scientific fields. In tourism, they can enhance destination distinctiveness, as well as the tourist experience. However, the cognitive processes through which stories contribute to elicitation of emotions or memorability, the very reasons why they are considered important in tourism, are still little understood. This chapter discusses some of the cognitive processes involved in storytelling drawing insights from cognitive psychology and neuroscience, which may help in better understanding and managing the tourist experience.

This paper aims to develop a comprehensive model on intra- and interpersonal emotion regulation (ER) in hospitality and tourism (H&T) service encounters.

A critical review and reflection of ER research from multiple disciplines was conducted. Methodologies appropriate for investigating ER were also reviewed.

A comprehensive framework was proposed to outline key influential factors, processes and consequences of intra- and interpersonal ER in service encounters in the H&T industry. Methodologies integrating advanced tools were suggested to measure complex and dynamic emotion generation and regulation processes in social interactions from a multimodal perspective.

The researchers developed a comprehensive conceptual model on both intra- and interpersonal ER based on a critical review of the most recent psychological research on ER. Various theoretical and methodological considerations are discussed, offering H&T scholars a solid starting point to explore dynamic emotion generation and regulation processes in complex social settings. Moreover, the model provides future directions for the expansion of ER theories, which have been mostly developed and tested based on laboratory research.

The proposed model addresses two critical issues identified in emotion research in the H&T field: the lack of a dynamic perspective and the neglect of the social nature of emotions. Moreover, the model provides a roadmap for future research.

The purpose of this study is to examine Bitcoin's price behavior across market conditions, focusing on the influence of Bitcoin's historical prices, news sentiment and market indicators like oil prices, gold and the S&P index. The authors also assess the stability of Bitcoin-inclusive hedging portfolios under different market conditions, for example, bearish, bullish and moderate market states.

This study uses the Quantile Autoregressive Distributed Lag model to explore the effects of different factors on Bitcoin's prices across various market situations. This method allows for a detailed analysis of historical trends, investor expectations and external market influences on Bitcoin's price movements and systematic stability.

Key findings reveal historical prices and investor expectations significantly influence Bitcoin in all market scenarios, with news sentiment exhibiting substantial volatility. This study indicates that oil prices have minimal impacts on Bitcoin, whereas gold is a stabilizing asset in bear markets, with the S&P index influencing short-term fluctuations. At the same time, Bitcoin's volatility varies with market conditions, proving more efficient as a hedging tool in bear and stable markets than in bull ones.

This study highlights the intrinsic correlation between Bitcoin's prices, news sentiment and financial market indicators, enhancing understanding of Bitcoin's market dynamics. The authors demonstrate Bitcoin's weak direct correlation with commodities like oil, the stabilizing role of gold in crypto portfolios and the stock market's indirect effect on Bitcoin prices. By examining these factors' impacts across various market conditions, the findings offer strategies for investors to improve hedging and portfolio management in cryptocurrency markets.

Since the 1980s, the Canadian federal public service has implemented employment equity legislation. ¹ However, the management of diversity in the workplace and its issues have undergone significant changes over the past 30 years. ² A recent 2021 directive from the Clerk of the Privy Council Office ordered that each department and agency have an accessibility, diversity, equity, and inclusion (ADEI) management strategy. ³ What about the measures and strategies implemented by the federal administrations in relation to culture? Based on a field survey and institutional documentary sources, the article will deal with ADEI management at Heritage Canada and Library and Archives Canada. It will present some innovations in diversity management and put them in perspective with some recent developments in the mandate entrusted to these two institutions. It will thus highlight that the evolution of the mandate of a public cultural administration in favor of the audiences it serves can impact choices and strategies for both the employees and the organizational environment.

This study aims to analyse the motivations and underlying assumptions of decision makers driving the adoption of sustainability-oriented targets in executive compensation (SCTs) to better understand SCTs’ impact on sustainability performance.

Through a qualitative approach, 15 in-depth interviews are conducted in a two-tier governance setting. Participants include management and supervisory board members, compensation consultants and other stakeholders involved in proxy voting.

SCT implementation is primarily determined by meeting shareholders’ expectations rather than those of other stakeholders. Decision makers react in a differentiated way to increased expectations by implementing either primarily symbolic or substantive measures and encounter different implementation challenges like insufficient data quality and a lack of experience within supervisory boards, both of which potentially contribute to decoupling.

The study offers valuable insights for companies in designing SCTs and emphasises the significance of addressing decoupling to effectively enhance sustainability performance through SCTs and provides a foundation for future studies aimed at analysing this phenomenon.

Using a neo-institutional theory lens, this study marks one of the first interview-based investigations to distinguish between symbolic and substantial SCTs. It delves deeply into the role of decoupling and the associated challenges, offering fresh perspectives within the under-researched framework of a two-tier corporate governance structure. Moreover, this study aims to meticulously capture the real-world design practices and implementation processes of SCTs through experts, an aspect that was emphasised as a limitation in previous studies.

Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

This study aims to illustrate the mechanisms underlying the effect of stress on flow states in the context of a multilevel organization, in which case employees' perseverative cognition and reactions to challenge–hindrance stressors are affected by leader mindfulness.

Study 1 employed a three-wave time-lag survey, and study 2 conducted a diary study across 10 workdays to replicate the results of study 1. Multilevel structural equation modeling and Monte Carlo simulation were performed using Mplus 8.0 software to test all hypotheses.

Problem-solving pondering transmits the nonlinear effect of challenge stressors on flow, and affective rumination mediates the negative effect of hindrance stressors on flow. Leader mindfulness amplifies the tendency of followers to ruminate on the positive aspects of challenge stressors, consequently increasing their positive reactions and flow. Although leader mindfulness fails to influence followers to ruminate less on hindrance stressors, it negates the harmful effect of affective rumination on the flow experience.

This study is one of the first to examine the associations between stressor types and flow in the workplace. The authors also develop a new theory that highlights the ability of leader mindfulness to shape subordinates' stress, cognitions and reactions through social modeling and the authors identify the boundaries of its beneficial effects.

The current research elucidates the role of empathy in design of artificial intelligence (AI) systems in healthcare context, through a structured literature review, analysis and synthesis of academic literature published between 1990 and 2024.

This study aims to advance the domain of empathy in AI by adopting theory constructs context method approach using the PRISMA 2020 framework.

The study presents a current state-of-the-art literature to review the connections between empathy and AI and identifying four clusters showing the emerging trajectories in the field of AI and empathy in healthcare setting.

Despite a rise in empirical research, the potential pathways enhancing AI accountability by incorporation of empathy is unclear. The research aims to contribute to the existing literature on AI and empathy in the healthcare sector by carving out four distinct clusters depicting the future research avenues.

This study aims to critically discuss and reorient the diversity, equity and inclusion (DEI) debate toward the idea of addressing and rectifying the pervasive structural inequalities that DEI, in its undiluted form rooted in social justice (SJ), aims to combat. Drawing on Bourdieu, the study first examines the diffusion and contestation of DEI into international business (IB). It then proposes a Bourdieu-inspired agenda to advance the transposition of SJ principles into IB.

The study interpretively reconstructs the process of DEI’s ideational diffusion. It examines how the interplay between ideas and field dynamics in IB shapes ideational processes and outcomes.

In response to rising global inequalities – to which multinational enterprises (MNEs) have significantly contributed – SJ movements have propelled DEI into the wider social and political arena, including corporate boardrooms. Within IB, a diluted version of DEI – IB-DEI – emerged as a paradigm to improve MNEs’ performance, but failed to address underlying structural inequalities. As the social impacts, utility and legitimacy of DEI have been challenged, the DEI debate has come to a flux. The study proposes conceptual and contextual extension of DEI within IB and advancing socially engaged research and practice that help reinforce DEI’s core SJ purpose – tackling structural inequalities.

The study is one of the few to openly tackle SJ-IB contradictions on DEI, while advancing the application of Bourdieu to critical studies of IB.