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This article seeks to enhance the understanding as to why head coaches and general managers (GMs) in the National Basketball Association (NBA) and the National Football League (NFL) exit from their positions.

Three hypotheses were investigated using a series of quantitative and qualitative data from the past 30 years. The samples analyzed are comprised of 891 GM and coach annual observations for the NBA clubs and 949 GM and coach observations for the NFL clubs. Analyses include a logit analysis for coach exit/retention, a logit analysis for GM exit/retention and textual analysis via topic modeling via latent Dirichlet allocation.

Results show a correlation between a coach exiting and a GM exiting simultaneously, thus amplifying the importance of these two roles in enhancing or destroying the success of a club and supporting the need for a deeper understanding of both roles, particularly the GM. The results further highlight cultural differences across clubs in terms of GM and coach turnover, a factor that often is heavily influenced by club ownership.

The results support the role of owners in exits, confirm the importance of winning in avoiding an exit, find a high level of interrelationship between GM and coach exits and show that past culture of firings influences future exit decisions.

Purpose: The purpose of this paper is to consolidate knowledge and benchmark the progress being made across the 32 International Federations (IFs) in the Summer Olympic Programme.

Design/methodology/approach: A website content analysis, analytical hierarchy of information, and social media research was conducted to triangulate the barriers and drivers of environmental sustainability (ES) progress. This data was then analysed to empirically substantiate the findings of previous methods by exploring potential drivers of IF ES progress and communication and refining the ranking of IF ES progress.

Results and findings: World Sailing is by far the most advanced IF in terms of ES progress, followed by World Athletics. Only 4 out of 32 have any sort of strategic ES plans. Only golf, surfing, football, sailing, and hockey have received any academic attention. There is a significant lack of understanding of environmental practices across sport, and their drivers/barriers. There is limited accountability with regards to ES progress and activities throughout the Olympic Movement. This has resulted in uneven diffusion of environmental activities.

Originality: This paper is a new contribution to sport management and ES literature. It provides a benchmark of understanding for ES in the Summer Olympic Programme for the first time using a hierarchy of information to ground results. The exploration and comparison of the perspectives of separate sports adds to the paper's originality.

The purpose of this study is to explore the ideological gaps across a range of policing interactions with the public.

In a survey distributed via Mechanical Turk (MTurk) (n = 979), the authors explore the role that respondents' political ideology plays in the agreement of 13 aspects of policing services, their demeanor and decorum.

Attitudes toward policing interactions are slightly positive. Conservatives steadfastly hold positive attitudes about police. Liberals vacillate from negative to positive attitudes across the 13 policing interaction statements.

Although small, there is an ideological consensus that police adequately protect citizens and are knowledgeable about the law.

Even at record lows of public confidence in the police, some subsections of the sample, such as conservatives, firmly hold positive attitudes about police. The unwavering support for police by conservatives continues across the multi-item measure of policing interactions, whereas liberals illustrated less uniformity in their attitudes.

Expanding on the real-world financial market framework and considering the current market turmoil, with cryptocurrencies (where contracts for difference (CFDs) are extremely common) (Hasso et al., 2019) displaying unprecedented volatility, the authors aim to test in an online laboratory setting whether displaying a risk warning message is truly effective in reducing the level of risk taken and whether the placement of this method makes a difference.

To explore the impact of risk disclosure framing on risk-taking behavior, the authors conducted an online pair-wise lottery choice experiment. In addition to manipulating risk awareness through the presence or absence of risk warning messages of varying intensity, the authors also considered dynamic inconsistency, cognitive ability and questionnaire-based financial risk tolerance (FRT) scores. The authors aimed to identify potential relationships between these variables and experimentally elicited risk aversion. The authors' study offers valuable insights into the complex nature of risky decision-making and sheds light on the importance of considering dynamic inconsistency in addition to risk awareness and aversion.

The authors' results provide statistical evidence for the efficacy of informative and very salient messages in mitigating risky decision, hinting at several policy implications. The authors also provide some statistical evidence in support of the relationship between cognitive abilities and risk preferences. The authors detect that individual with low cognitive abilities scores display great risk aversion.

This study investigates the impact of risk warning messages on investment decisions in an online laboratory setting – a unique approach. However, the authors go beyond this and also examine the potential influence of dynamic inconsistency on decision-making, adding further value to the literature on this topic. To ensure a comprehensive understanding of the participants, the authors collect data on cognitive ability and FRT using questionnaires. This study provides a simple and cost-effective framework that can be easily replicated in future research – a valuable contribution to the field.

This paper aims to analyze the ethical responses of the fashion industry to the first wave of the COVID-19 pandemic when the entire world was shocked by the rapid spread of the virus. The authors describe lessons from emergency ethics of care in the fashion industry during the initial months of COVID-19, which can assist fashion managers in improving ethical decisions in future operations.

Rapid qualitative research methods were employed by conducting real-time, in-depth interviews with key informants from multinational fashion companies operating in Spain, a severely affected region. A content analysis of news articles published during the first months of 2020 was conducted.

Five critical disruptions in the fashion industry were identified: (1) changes in public needs, (2) transportation and distribution backlogs, (3) defective and counterfeit supplies, (4) stakeholder relationships at stake and (5) managers' coping challenges. Additionally, five business survival responses with a strong ethics of care component were identified, implemented by some fashion companies to mitigate the damage: (1) adapting production for public well-being, (2) enhancing the flexibility of logistic networks, (3) emphasizing quality and innovation, (4) reinventing stakeholder collaborations and (5) practicing responsible leadership.

Despite the well-documented controversies surrounding unethical practices within the fashion industry, even during COVID-19, our findings inform managers of the potential and capability of fashion companies to operate more responsibly. The lessons learned can guide fashion companies' operations in a post-pandemic society. Furthermore, they can address other grand challenges, such as natural disasters, geopolitical conflicts and climate change.

This paper aims to study whether international niche market leaders (INMLs) gained their leading position as early mover or diligent follower, and assess whether they leveraged hard or soft forms of technological, supply pre-emption and customer lock-in advantage mechanisms.

Empirical material stems from qualitative and quantitative data on a sample of 20 niche companies from the Basque Country (Spain) that operate in business to business markets.

The sample predominantly followed an early entrant strategy and applied soft measures to reach niche market leadership.

Findings imply that early entering fosters conquering leadership in niche markets, that pioneer advantage is easier to sustain in niches than in mainstream markets, and that soft measures are more effective in niche markets than in larger markets. A limitation to our findings is that they follow from explorative research on a sample of firms from a reduced geographic setting.

Hidden champions and INMLs can be important sources of technological progress and economic value for the localities that host them. Therefore, despite their traditional low profile and the fact that they are not always the largest firms around, policymakers may want to pay more attention to this type of companies.

Tot he best of the authors’ knowledge, this is the first paper to research entry timing and its outcome for market leadership with regard to niche players or hidden champions-type of firms. It introduces an original taxonomy to operationalize and distinguish between hard and soft measures to leverage advantage mechanisms related to market entry timing.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.