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The vulnerability of the tourism industry to an array of risks, encompassing family-related, small- and medium-sized enterprise-specific, strategic, tourism-specific and external factors, highlights the landscape within which small and medium family enterprises (SMFEs) operate. Although SMFEs are an important stakeholder in the dynamic tourism sector, they are not one homogenous group of firms, but have different strategic orientations. This study aims to investigate the interplay between strategic orientation and risk perception to better understand SMFEs risk perception as it is impacting their decision-making processes, resilience and long-term survival. The authors investigate how different strategic orientations contribute to different perspectives on risk among owner-managers.

Based on a qualitative data corpus of 119 face-to-face interviews, the authors apply various coding rounds to better understand the relationship between strategic orientations and the perceptions of risks. Firstly, the authors analysed the owner–manager interviews and identified three groups of different strategic orientations: proactive and sustainability-oriented SMFE, destination-affirmative and resilience-oriented SMFE and passive SMFE. Secondly, the authors coded the interviews for different risks identified. The authors identified that the three groups show differences in the risk perceptions.

The data unveil that the three groups of SMFEs have several differences in how they perceive risks. Proactive and sustainability-oriented SMFEs prioritize business risks, demonstrating a penchant for innovation and sustainability. Destination-affirmative and resilience-oriented SMFEs perceive a broader range of risks, tying their investments to destination development, emphasizing family and health risks and navigating competitive pressures. Passive SMFEs, primarily concerned with external risks, exhibit limited awareness of internal and strategic risks, resist change and often defer decision-making to successors. The findings underscore how different strategic orientations influence risk perceptions and decision-making processes within SMFEs in the tourism industry.

The authors contribute to existing knowledge include offering a comprehensive status quo of perceived risks for different strategic orientations, a notably underexplored area. In addition, the differences with respect to risk perception shown in the paper suggest that simplified models ignoring risk perception may be insufficient for policy recommendations and for understanding the dynamics of the tourism sector. For future research, the authors propose to focus on exploring the possible directions in which strategic orientation and risk perception influence one another, which might be a limitation of this study due to its qualitative nature.

Varying strategic orientations and risk perceptions highlight the diversity within the stakeholder group of SMFE. Recognizing differences allows for more targeted interventions that address the unique concerns and opportunities of each group and can thus improve the firm’s resilience (Memili et al., 2023) and therefore leading to sustainability destinations development. The authors suggest practical support for destination management organizations and regional policymakers, aimed especially at enhancing the risk management of passive SMFEs. Proactive SMFE could be encouraged to perceive more family risks.

Viewing tourism destinations as a complex stakeholder network, unveiling distinct risk landscapes for various strategic orientations of one stakeholder has the potential to benefit the overall destination development. The proactive and sustainability-oriented SMFEs are highly pertinent as they might lead destinations to further development and create competitive advantage through innovative business models. Passive SMFEs might hinder the further development of the destination, e.g. through missing innovation efforts or succession.

Although different studies explore business risks (Forgacs and Dimanche, 2016), risks from climate change (Demiroglu et al., 2019), natural disasters (Zhang et al., 2023) or shocks such as COVID-19 (Teeroovengadum et al., 2021), this study shows that it does not imply that SMFE as active stakeholder perceive such risk. Rather, different strategic orientations are in relation to perceiving risks differently. The authors therefore open up an interesting new field for further studies, as risk perception influences the decision-making of tourism actors, and therefore resilience.

Bringing together our analysis from the previous chapters allows us to lay out the various contradictions and issues surrounding ownership models that have arisen for fans of football clubs. Exactly when are most English football clubs supposed to have conformed to the normative model? Our analysis reveals that the context in which football clubs operate is that of global business and has developed in line with the practices of other businesses that exist outside the sporting arena. There is always going to be an uneasy tension between a fan ideal and something that has to operate within global contexts. However, in the modern game ideal and practice find themselves not merely in tension, but often completely in opposition to one another. Football finds itself in a position where something has to give, be it ownership models or the affective ties of the fans themselves. Fans can either continue to wrestle with the contradictions that arise from what they think their club is or fandom itself changes to embrace the context of the ownership. Given the moral injunction that is almost invariably built into the idealised image that fans have of their club, there is one question that we must always ask in the contemporary climate: How far is too far before all of this means nothing?

The traditional predictor of technical inefficiency proposed by Jondrow, Lovell, Materov, and Schmidt (1982) is a conditional expectation. This chapter explores whether, and by how much, the predictor can be improved by using auxiliary information in the conditioning set. It considers two types of stochastic frontier models. The first type is a panel data model where composed errors from past and future time periods contain information about contemporaneous technical inefficiency. The second type is when the stochastic frontier model is augmented by input ratio equations in which allocative inefficiency is correlated with technical inefficiency. Compared to the standard kernel-smoothing estimator, a newer estimator based on a local linear random forest helps mitigate the curse of dimensionality when the conditioning set is large. Besides numerous simulations, there is an illustrative empirical example.

Moving away from the stories of financial disaster we encountered in Chapter 2, Chapter 3 examines what it means for fans when their club is suddenly awash with more financial muscle than some nation-states due to the generosity of a wealthy benefactor who is seemingly more interested in sporting glory than in financial gain. This chapter engages with the notion of the football club as a billionaire’s plaything. Roman Abramovich’s acquisition of Chelsea in 2003 saw the West London club embark on an eye-watering spending spree and a sustained period of on-field successes, one that was unknown in the club’s history to that point. As a result, we take Chelsea during the Abramovich era as a starting point for considering how this model of ownership affects the relationship between fans and the connection that they have with their club. The evident success that financial muscle can bring shows owners what a happy fanbase is capable of, what they are capable of doing, and what they are capable of ignoring. The success of the financially doped teams of the 2000s created a precedent for winning over a fanbase with a successful football club, but nevertheless sat awkwardly with the normative ideals of how a football club should exist in the world and relate to its supporters.

Homelessness has many causes and also is stigmatized in the United States, leading to much misunderstanding of its causes and what policy solutions may ameliorate the problem. The problem is of course getting worse and impacting many communities far removed from the West Coast cities the authors examine in this study. This analysis examines the socioeconomic variables influencing homelessness on the West Coast in recent years. The authors utilize a panel fixed effects model that explicitly includes measures of healthcare access and availability to account for the additional health risks faced by individuals who lack shelter. The authors estimate a spatial error model (SEM) in order to better understand the impacts that systemic shocks, such as the COVID-19 pandemic, have on a variety of factors that directly influence productivity and other measures of welfare such as income inequality, housing supply, healthcare investment, and homelessness.

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

The police often respond to persons who are not in direct violation of the law, but are rather undergoing behavioral crises due to mental illness or substance abuse disorders. The purpose of this study is to examine how police behavior influences civilian bystanders' emotional responses and perceptions of procedural justice (PPJ) when officers interact with these populations, which traditionally have been stigmatized in American culture.

Using a factorial vignette approach, the authors investigate whether perceived public stigma moderates the relationship between police behaviors (i.e. CIT tactics, use of force) and PPJ. The authors also investigate whether emotional reactions mediate the relationship between police behaviors and PPJ.

Regardless of suspect population (mental illness, substance use), use of force decreased participants' PPJ, and use of CIT tactics increased PPJ. These effects were consistently mediated by anger, but not by fear. Interactive effects of police behavior and perceived public stigma on PPJ were mixed.

Fear and anger may operate differently as antecedents to PPJ. Officers should note using force on persons in behavioral crisis, even if legally justifiable, seems to decrease PPJ. They should weigh this cost pragmatically, alongside other circumstances, when making discretionary decisions about physically engaging with a person in crisis.