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The purpose of this study is to identify LGBTQ+ perceptions of and experiences with hazards, vulnerabilities and disasters in the San Francisco Bay Area in the USA and to co-develop applied projects to “queer” disaster knowledge production and risk reduction activities in the region.

This is a community science project in which we collaborate with community members to enhance both community and scientific knowledge with the goal of utilizing it to produce a positive change to pressing social issues and their underlying causes. We do this through a series of four focus group workshops to identify community priorities, hazards, vulnerabilities and local action. We follow this with further ethnographic research and projects to apply findings from phase one.

The authors have found that: LGBTQ+ people in the Bay Area have unique experiences with hazards, vulnerabilities and disasters; there are significant gaps in the representation of LGBTQ+ hazard exposure in local scientific models that we can address through alternative methodologies; and tabletop exercises, learning modules and podcasts help orient and train disaster response agencies and personnel on LGBTQ+ inclusive operations.

This initiative entails novel approaches to community science for disaster risk reduction and creative collaboration with community-based organizations to foster the development of LGBTQ+ inclusive disaster risk reduction and response.

This introduction provides the methodological framework for the book, approaching the business of football through the lens of its most reliable consumers – the fanbase. Fan cultures necessarily inform the normative understanding of a football club, due to the popularly held belief that it is the fan’s – or some reified idea of the fan – that is the permanent feature of a football club and that provides its identity. Players and owners come and go, but the relationship between the club and the fan is, theoretically, never-ending. In truth, this is never a real fan who could exist, but a constructed image of the fan built out of other narratives and that, at some level, football fans associate themselves. This fan is no one in particular, but is drawn from a close reading of football culture and identifying the directives of the traditional fan. Utilising a combination of critical theory and the existing literature on football club ownership, our goal is to reveal the distinction between how people talk about the social dimension of football clubs, and how they actually relate to their fans and the wider world in the era of late capitalism. A club is not simply the romanticised notions held by those within the games, but, as with all businesses, it is also the product of it conducts itself in a series of other networks of exchange. Often irreconcilable with the aforementioned romantic notions, these networks often get hidden by the prevailing discourse.

The use of generative artificial intelligence (genAi) language models such as ChatGPT to write assignment text is well established. This paper aims to assess to what extent genAi can be used to obtain guidance on how to avoid detection when commissioning and submitting contract-written assignments and how workable the offered solutions are.

Although ChatGPT is programmed not to provide answers that are unethical or that may cause harm to people, ChatGPT’s can be prompted to answer with inverted moral valence, thereby supplying unethical answers. The authors tasked ChatGPT to generate 30 essays that discussed the benefits of submitting contract-written undergraduate assignments and outline the best ways of avoiding detection. The authors scored the likelihood that ChatGPT’s suggestions would be successful in avoiding detection by markers when submitting contract-written work.

While the majority of suggested strategies had a low chance of escaping detection, recommendations related to obscuring plagiarism and content blending as well as techniques related to distraction have a higher probability of remaining undetected. The authors conclude that ChatGPT can be used with success as a brainstorming tool to provide cheating advice, but that its success depends on the vigilance of the assignment markers and the cheating student’s ability to distinguish between genuinely viable options and those that appear to be workable but are not.

This paper is a novel application of making ChatGPT answer with inverted moral valence, simulating queries by students who may be intent on escaping detection when committing academic misconduct.

The first-aid courses organized by the Youth Red Cross Carinthia (Austria) had a quality problem, necessitating a professionalization in teaching and time structure. This research aimed to enhance the quality and effectiveness of these courses by implementing modified lesson studies with non-professional trainers. The paper presents the realization process, empirical research and results obtained by applying the first-aid curriculum.

Around 22 lesson study first-aid courses (14 classes with 2 cycles, 8 with 3 cycles) were conducted and evaluated in different Austrian school types. An observation sheet was created to evaluate attention and competencies. Interviews were conducted with both teachers and students to validate the results.

The research findings demonstrate that lesson studies can significantly enhance the quality and effectiveness of first-aid courses. Inexperienced and experienced first-aid teachers significantly improved their teaching skills. Newly educated first-aid teachers showed substantial improvement, leading to the introduction of an induction period and coaching opportunity within the Youth Red Cross Carinthia.

This is the first lesson study conducted in a non-academic context. It highlights the adaptation process of Carinthian first-aid courses. It illustrates how lesson studies impact lesson clarity, instructional variety, student engagement in the learning process, student outcome, student feedback and teaching effectiveness in a non-academic context. It contributes to the literature on the application of lesson study in first-aid education and provides insight into the benefits of this approach in enhancing the quality of first-aid training.

This paper aims to empirically investigate how knowledge coordination is carried out within and across expert teams in the outsourcing service desk context from the standpoint of the information and communication technologies (ICT) provider.

The authors draw on an embedded case study to unravel the mechanisms used by expert teams to achieve knowledge coordination. Data collection included semi-structured interviews and document analysis over eight months.

Four groups of coordination mechanisms were found according to their nature and role in helping MESA achieve its organizational goals. The authors also identified how this set of mechanisms responds to the task-resource dependency and how it evolves over time to provide reliable ICT services. Furthermore, the analysis of four knowledge coordination dimensions inside each group uncovers the complexity of coordination in the studied context, with the “who” dimension being predominant across the groups. The analysis further reveals that the content (what) and mode of coordination (how) of each group respond to elements in the knowledge coordination process relevant for the different stages of the ICT service delivery process.

The case study addresses how people in outsourced services coordinate their knowledge to manage the interdependencies among the involved organizations and thus, achieving their goals. This study extends previous research that had analyzed the consequences of knowledge coordination for providers and customers by delving into the mechanisms used in this process from the provider’s point of view.

This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.

This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.

The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.

This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.

Earned value management systems (EVMS), also called integrated project and program management systems, have been greatly examined in the literature, which has typically focused on their technical aspects rather than social. This study aims to hypothesize that improving both the technical maturity of EVMS and the social environment elements of EVMS applications together will significantly impact project performance outcomes. For the first time, empirical evidence supports a strong relationship between EVMS maturity and environment.

Data was collected from 35 projects through four workshops, attended by 31 industry practitioners with an average of 19 years of EVMS experience. These experts, representing 23 organizations, provided over 2,800 data points on sociotechnical integration and performance outcomes, covering projects totaling $21.8 billion. Statistical analyses were performed to derive findings on the impact of technical maturity and social environment on project success.

The results show statistically significant differences in cost growth, compliance, meeting project objectives and business drivers and customer satisfaction, between projects with high EVMS maturity and environment and projects with poor EVMS maturity and environment. Moreover, the technical and social dimensions were found to be significantly correlated.

Key contributions include a novel and tested performance-driven framework to support integrated project management using EVMS. The adoption of this detailed assessment framework by government and industry is driving a paradigm shift in project management of some of the largest and most complex projects in the U.S.; specifically transitioning from a project assessment based upon a binary approach for EVMS technical maturity (i.e. compliant/noncompliant to standards) to a wide-ranging scale (i.e. 0–1,000) across two dimensions.

Research on electric sports (eSports) has experienced significant growth in recent years as a consequence of increasing connectivity, institutionalization, and technological advances. However, the interdisciplinary nature of the eSports as a field and the burgeoning growth in eSports articles have rendered it necessary to conduct a systematic review of extant literature to take stock of the knowledge accumulated. To this end, we aim to undertake a comprehensive review of extant literature that takes stock of published research to derive opportunities for future research in the realm of eSports. In so doing, we contribute to the advancement of the field by mapping out the knowledge trajectory of eSports research and elucidating areas that have remained underexplored thus far.

To conduct systematic review of the eSports literature, we employed a framework that included six essential steps: protocol, search, appraisal, synthesis, analysis, and report. This comprehensive approach enables us to meticulously investigate the existing body of literature on eSports and identify key trends and topics addressed within the field. By conducting the multidisciplinary systematic literature review, we thoroughly assess the current state of eSports literature and subsequently outline potential research avenues that can contribute to eSports fields.

This study draws on a six-phase framework – member preparation, team formation, character selection, team coordination, team performance, and team reflection – to illustrate the roles played by different levels of analysis unit (i.e. characters, players, and teams) and three distinct yet interconnected stages (i.e. inputs, process, and outputs) within eSports games as well as the research opportunities it brings.

We conducted a rigorous systematic review of the eSports literature by using quantitative citation analysis and qualitative content analysis. Furthermore, we adopted team dynamic view of eSports to identify potential research avenues for future research that contribute to advancing our understanding of the eSports tournaments.

Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts.

Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results.

The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally.

Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience.

Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost.

Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.

This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.