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To extend research into sport consumer behaviors related to online sports betting, this study is designed to identify and examine the relationship between online sports betting motivations and online sports betting intentions. By applying a push-pull framework from online sport consumption and gambling studies, nine motivations to engage in online sports betting were identified. These motivations were hypothesized to motivate online sports betting intentions.

A quota sampling technique based on the sports bettor demographics available in the American Gaming Association (AGA, 2019) and the Pew Research Center (2022) obtained a total of 550 completed surveys that met the inclusion and exclusion criteria. For data analyses, confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to examine the measurement model and the hypothesized model, respectively.

The results revealed that four motivations (i.e. monetary gain, excitement, convenience and negative technology-readiness) were related to online sports betting intention, while five motivations (i.e. sport fandom, positive technology-readiness, impulsivity, socialization and promotion) were not.

The results provide foundational theoretical knowledge of what motivates sports fans to participate in online sports betting. Furthermore, the findings assist practitioners in their allocation of resources by enhancing their understanding of online sports betting motivations.

This research finds out to what extent companies’ names are influenced by the place’s attributes versus the official branding policies of a place and, consequently, whether and how local companies “buy into” the place’s strategies put forth by official bodies.

This paper is both conceptual and empirical, as a mixed quantitative and interpretive approach is used. The companies’ names of a tourist industry (the tour and guiding companies) in three destinations are compared and pitched against the branding of these cities. The companies' names are classified into categories to ascertain whether they reflect (or diverge from) the official strategies. Finally, a conceptual model is developed to explain the findings: the strategic naming model (SNM).

Our main finding is that the overall business features of a place being stronger determinants to the naming strategies than tourist destination branding initiatives. The intrinsic features of a place seem thus to be “above” destination branding policies. The researched features account for different naming strategies, such as highly original names, flat names or non-strategic names.

As the work is based on a convenience sample, it cannot claim strong representativity. The fact that each of the three data sets was processed by a different researcher might bring up personal biases.

This work is a call for a more intensive use of naming strategies to the companies’ advantages, as naming is found out to be strategy used to a very low degree. Thanks to this research, companies will understand the different naming possibilities and be able to apply them to their strategies by choosing names which express “uniqueness” or “belonging”. Practitioners will also be aware of whether they are communicating towards the industry or towards the market.

No works were found that empirically pursue our research goals. Therefore, this research might be considered as a novelty. The proposed SNM model explains and relates the most usual company naming techniques, which were unrelated up to date.

This chapter discusses the contributions and challenges involving regulatory technology (regtech) in financial services. It explores the salient areas where regtech can and should focus, observing existing and forthcoming industry, technology, and legal developments. This chapter outlines regtech use cases to clarify the shaping of that industry sector. It draws on developments in industry and academia, where significant research sets the tone and direction of technological solutions and regulatory drivers. A brief critical account of the benefits and challenges in regtech is offered. This chapter presents potential future directions, focusing on the salient areas of environmental, social, and governance (ESG), cryptocurrency, and decentralized compliance.

Artificial intelligence (AI) applications are increasingly used for day-to-day operations in healthcare. Each has a relatively limited scope or task, and several find application in managerial and organizational processes. More and more, AI and machine learning (ML) devices have received US FDA approval in the last decade. This chapter covers the main AI applications in healthcare, with a focus on organizational AI solutions (administrative AI), the main AI developers, their investment and real-world data and case studies in healthcare and other sectors. AI can be applied in resource management and procurement, resource allocation, clinical case management, staff work shift scheduling and handling of emergencies. AI applications are becoming ubiquitous in hospital (e.g. emergency room and operating theatre) and outpatient settings (e.g. ambulatory care and dentistry clinics). Their implementation is expected to bring direct benefits for patient care and satisfaction. This chapter gives a broad definition of AI in healthcare settings, with a focus on administrative applications and their use in case study data.

Prior research has extensively explored the dynamics of knowledge creation and transfer within entrepreneurial ecosystems (EEs). However, the research on knowledge integration within EEs, particularly by entrepreneurs, remains scant. Garnering and effectively using knowledge in such a dynamic and complex environment can provide entrepreneurs with a valuable asset for gaining a competitive advantage. To address this gap, this study aims to explore how entrepreneurs garner and capitalise on knowledge within the EE environment by using a transactive memory system lens.

This study is based on 26 semi-structured interviews with different actors and members of the same ecosystem – the northern Finnish health tech ecosystem. The data were analysed using the Gioia methodology.

This study results found that transactive memory processes (i.e. knowledge specialisation, credibility and coordination) and structures (i.e. differentiated-, shared- and meta-knowledge) influence knowledge organising in EEs.

This study provides a conceptual interplay between the EE and the transactive memory system’s processes and structures.

As the onset of the Russia–Ukraine military conflict on February 24, 2022, individuals from Ukraine have been relocating in search of safety and refuge. This study aims to investigate how the influx of Ukrainian refugees has impacted the stock markets and exchange rates of Ukraine's neighboring states.

The authors focused on the neighboring countries that share a western border with Ukraine and have received the highest number of refugees: Hungary, Poland, Romania and Slovakia. The analysis covered the period from April 24 to December 31, 2022. After this period, the influence of the refugees is small, insignificant. Wavelet coherence, wavelet power spectrum and the time-varying parameter vector autoregressions method were used for data processing.

The key finding are as follows: a link exists between the dynamics of refugees from Ukraine and volatility of the stock indices and exchange rate of the host countries; volatility was significant in the first weeks after the start of the conflict in all the analyzed states; and the highest volatility was recorded in Hungary and Poland; the effect of refugees was stronger on stock indices than that on exchange rates.

To the best of the authors’ knowledge, it is the first research that presents the impact of refugees from Ukraine on stock markets and exchange rates volatility in the countries analyzed.

How do participants navigate the sexual politics of multiracial dating and how does this relate to belonging? The results of this study illustrate that the 21 participants interviewed faced internal and external struggles and triumphs due to their mixed-race identity. For participants, trying to situate themselves into just one racial identity when they straddled both became a point of contention with romantic partners and themselves. Moreover, participants struggled with feeling like they were “enough” and if they belonged. Furthermore, mixed-race women and non-binary people were forced to navigate the racial expectations of others as well as the fetishization of their mixed-race identity. In turn, this impacted confidence levels, self-esteem, and sense of belonging and authenticity. The findings contribute to research on desirability and critical mixed-race studies by examining how mixed-race women and non-binary people perceive their own desirability.

This study explores the phenomenon of compassionate leadership, a promising concept in management literature. Despite significant contributions towards the understanding of its antecedents and consequences, the specific role of compassion concerning the leader behavior under extreme pressure remains unexplored.

Drawing empirically on the case of three banks under three different logics, the authors trace how heads of banking branches, namely, middle managers, deal with the paradoxical phenomenon of integrating their human nature with the coetaneous need to achieve aggressive objectives. The authors analyzed interviews using the interpretive research method (Hatch and Yanow, 2003).

The authors identified that the logic of savings banks and credit cooperatives, together with specific human elements, created a healthier environment to develop compassionate behaviors compared to commercial banks. The authors found coherence when linking the institutional message of putting the spotlight on a personalized treatment of customers, and the middle manager compassionate actions towards customers and subordinates.

Suggestions for future theorizing and research are advanced, along with constructive practical implications to rehumanize the dark side of banking for both employees and customers.

The findings provided in this paper are original because they provide further evidence of linking business logics with compassionate leadership of middle managers and its impact on employees and customers.