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This case study focuses on an alternative minimum-security model, the Safety Income (SI) Model, representing a nuanced departure from both established policies and UBI. StI is a welfare system that supplements households earning below the standard median income with 50% of the difference between the standard median and their current earnings. The quantitative case study presents the set-up of SI and assesses the cost of its implementation in South Korea. By employing a computable general equilibrium model method, the study compares the impacts of SI, UBI and the existing scheme in South Korea on income disparities, labor market outcomes and Gross Domestic Product.

In the past decade, the Universal Basic Income (UBI) concept has gained international significant traction as a potential remedy for poverty and inequality. However, the practical implications of UBI implementation remain under extensive debate. It is unclear if UBI is an effective model for poverty alleviation.

The analyses show that SI outperforms the other two welfare systems across all studied economic indicators. SI demonstrates more substantial reductions in income inequality compared with UBI and the existing scheme, minimal impact on unemployment rates compared with other schemes and a relatively modest decrease in GDP, making it a more favorable choice for South Korea when developing the minimum-security system within the specified budget constraint.

This research contributes to the discourse surrounding basic income, economic security, poverty alleviation and inclusive social policies.

Over the past years, non-fungible tokens (NFTs) have sparked growing interest in the sport industry. NFTs are unique digital assets verified using blockchain technology. Each NFT has a distinct identifier that sets it apart from other tokens, documenting its uniqueness and ownership. NFTs promise innovative growth opportunities by generating revenue via novel products such as digital collectibles which can be owned and traded on dedicated platforms. Despite this promising outlook, it currently seems unclear how sports NFTs should be designed and which features they should offer to align with consumer values, effectively meet their needs and ultimately drive Purchase Intention. This study will therefore attempt to answer the following research question: Which consumer values and consumer needs have a positive impact on PI of sports NFTs? Based on the results, the study seeks to offer advice on concrete characteristics sports NFTs should possess in order to foster mainstream adoption.

To address the current gap in the literature and provide an answer to the research question, this paper uses structural equation modelling exploring the impact of consumer values and consumer needs or wants on purchase intention regarding sports NFTs.

The results of this study indicate that social needs or wants (SNW) have the strongest impact on purchase intention, as well as on experiential and functional needs or wants. NFTs should therefore possess characteristics that foster community, interaction and connection with other team or athlete supporters while enhancing the overall consumer experience. Incorporating these elements into future NFTs can help sports organizations tap into the social SNW of consumers by providing opportunities for connection, interaction and collective experiences within supporter communities.

Due to the low response rate of Baby Boomers, the results of the study cannot be applied to this cohort. Additional research, potentially using physical in-stadium surveys and targeted specifically at the BB cohort may shed light on their particular values, needs or wants and impact on sports NFT purchase intention. Moreover, Generation Z respondents may statistically be underrepresented in the sample due to the fact that only respondents aged 18 and older were included in the study. Hence, the part of Generation Z, which was born after March 2006 and had not yet come of age at the time of this research, was explicitly excluded from the survey. Results should be applied carefully to the population of sports team or athlete supporters due to the method of data collection which was based on convenience sampling and may therefore not be representative. Since the survey was exclusively administered online, people with no Internet access are not represented in this research.

Sports organizations and marketers can leverage the strong impact of SNW identified in this study to position their NFT portfolio accordingly. Using athletes themselves or other influencers as product ambassadors may trigger purchase intention of consumers. Additionally, it is crucial that socializing agents, such as family, friends, colleagues and other team supporters with a strong influence on consumers own or promote NFTs. Marketers can support this adoption process by encouraging testimonials, reviews and user-generated content that showcase how NFTs have positively impacted others. Reaching a critical mass of adoption among supporters as a first step will ultimately impact consumers’ desire to satisfy ENW and FNW as well. Consumers may then recognize the benefits of using NFTs to enhance their overall consumer experience and to make their lives easier, for instance by using NFTs as season tickets or to collect loyalty points they can redeem later.

This study is the first attempt to determine the relationship between consumer values, consumers’ needs or wants and their impact on purchase intention regarding sports NFTs.

The rapid development and widespread application of artificial intelligence tools have raised concerns about how designers are embracing these technologies. This study investigates the factors influencing designers' behavioral intention to use and disclose the use of generative artificial intelligence.

A quantitative research approach was employed, designing a structured questionnaire based on Self-Determination Theory to assess the impact of various psychological and social dimensions. The questionnaire included dimensions such as autonomy, competence, relatedness, social influence, value fit and social innovativeness. A Partial Least Squares Structural Equation Modeling analysis was conducted on 309 valid responses from diverse design fields.

Competence and relatedness are significant factors influencing designers' continuance intention to use generative artificial intelligence. Although autonomy does not significantly affect continuance intention, it plays a crucial role in the decision to disclose artificial intelligence participation. Social influence and value fit significantly shape autonomy, competence and relatedness, while the impact of social innovativeness is relatively limited.

This study clarifies the factors influencing designers' continuance intention and disclosure of generative artificial intelligence tools from both individual and social dimensions, enhancing the understanding of the relationship between designers and generative artificial intelligence tools. It provides valuable insights for the development of artificial intelligence technology and the future trends in the design industry, offering significant theoretical and practical value.

This paper addresses the challenges associated with forecasting electricity consumption using limited data without making prior assumptions on normality. The study aims to enhance the predictive performance of grey models by proposing a novel grey multivariate convolution model incorporating residual modification and residual genetic programming sign estimation.

The research begins by constructing a novel grey multivariate convolution model and demonstrates the utilization of genetic programming to enhance prediction accuracy by exploiting the signs of forecast residuals. Various statistical criteria are employed to assess the predictive performance of the proposed model. The validation process involves applying the model to real datasets spanning from 2001 to 2019 for forecasting annual electricity consumption in Cameroon.

The novel hybrid model outperforms both grey and non-grey models in forecasting annual electricity consumption. The model's performance is evaluated using MAE, MSD, RMSE, and R², yielding values of 0.014, 101.01, 10.05, and 99% respectively. Results from validation cases and real-world scenarios demonstrate the feasibility and effectiveness of the proposed model. The combination of genetic programming and grey convolution model offers a significant improvement over competing models. Notably, the dynamic adaptability of genetic programming enhances the model's accuracy by mimicking expert systems' knowledge and decision-making, allowing for the identification of subtle changes in electricity demand patterns.

This paper introduces a novel grey multivariate convolution model that incorporates residual modification and genetic programming sign estimation. The application of genetic programming to enhance prediction accuracy by leveraging forecast residuals represents a unique approach. The study showcases the superiority of the proposed model over existing grey and non-grey models, emphasizing its adaptability and expert-like ability to learn and refine forecasting rules dynamically. The potential extension of the model to other forecasting fields is also highlighted, indicating its versatility and applicability beyond electricity consumption prediction in Cameroon.

The inclusion of esports as an official event in the Hangzhou Asian Games is an important step towards the institutionalisation of esports. The significance of this event marks that Asia once again takes a lead in the global esportisation. This chapter investigates a series of history events in the inclusion process of esports into the comprehensive Games in Asia using process sociology and actor network theory (ANT). This study will analyse the type characteristics of esports events in Hangzhou Asian Games, whilst examining how key stakeholders' interact and balance in the network composed of international sports organisations, host of the event, emerging esports organisations and esports game companies. The chapter also examines the functions of global game industrial economic geography, local cultural politics, esports geopolitics and Olympic values in esports sportization, aiming to reveal the implications of esports inclusion in the Asian Games on the debate of whether esports meets the criteria to be classified as a ‘sport’ and its enlightenment of digital strategy to the inclusion esports in the Olympics.

This study investigates the barriers to adopting green human resource management (GHRM) under uncertain conditions by integrating the resource-based view (RBV) and stakeholder theory.

A board of experts, which consisted of 28 practitioners and two academics, was invited to participate in the research. The fuzzy Delphi and fuzzy decision-making trials and evaluation laboratory were utilized to achieve the study's objectives.

The findings indicate that barriers encompass 14 criteria and five attributes. Among the 14 criteria, the banking industry's lack of green culture, lack of trust in green benefits, employee's capacity to change, lack of support from top management and absence of a comprehensive plan to implement GHRM are significant barriers. The attributes are management, human resources, organizational, regulatory and customer barriers.

Implementing GHRM in Indonesian banking necessitates practical policies and gradual adaptation strategies. Companies should establish standard operating procedures, reward systems and periodic habit changes to embed green practices effectively.

This study is among the first to employ stakeholder theory and the RBV in examining the barriers to green human resources adoption in the banking industry.

The article investigates different types of strategies for managing user-generated content (UGC) and provides some insights into their implications.

A unique sample of Italian hotels with current and prospective customers in the digital environment is investigated. A taxonomy of user-provider interactions mediated by UGC is developed. A mixed approach was designed to meet the study aims. Firstly, an exploratory factor analysis was performed in order to illuminate different strategies of UGC and electronic word-of-mouth (E-WOM) management. Secondly, a cluster analysis was implemented in order to explain hoteliers' behavior toward users' contents.

The study results suggested the existence of three clusters, which reflected three different types of interactions between hotels and customers in the digital domain. Interestingly, most of Italian hotels were found to adopt a reductionist approach to UGC and E-WOM management, turning out to be ineffective to exploit them for the purpose of quality improvement and hospitality service excellence.

Hotels were found to be largely unaware of the importance of UGC and web-based communication with customers to improve their digital business strategy. Tailored management approaches are needed to realize the full potential of hotels' online content responsiveness for the purpose of value co-creation and service co-production.

This is one of the first studies investigating the strategic and management perspectives embraced by hotels to handle their interactions with customers in the digital arena.

Heating, ventilating, air-conditioning and cooling (HVAC) systems are crucial in daily health-care facility services. Design-related defects can lead to maintenance issues, causing service disruptions and cost overruns. These defects can be avoided if a link between the early design stages and maintenance feedback is established. This study aims to use experts’ experience in HVAC maintenance in health-care facilities to list and evaluate the risk of each maintenance issue caused by a design defect, supported by the literature.

Following semistructured interviews with experts, 41 maintenance issues were identified as the most encountered issues. Subsequently, a survey was conducted in which 44 participants evaluated the probability and impact of each design-caused issue.

Chillers were identified as the HVAC components most prone to design defects and cost impact. However, air distribution ducts and air handling units are the most critical HVAC components for maintaining healthy conditions inside health-care facilities.

The unavailability of comprehensive data on the cost impacts of all design-related defects from multiple health-care facilities limits the ability of HVAC designers to furnish case studies and quantitative approaches.

This study helps HVAC designers acquire prior knowledge of decisions that may have led to unnecessary and avoidable maintenance. These design-related maintenance issues may cause unfavorable health and cost consequences.

This study aims to investigate the integration of blockchain technology into the food supply chain within the restaurant industry. It focuses on how blockchain can be applied to enhance transparency and trust in tracking food sources, ultimately impacting customer satisfaction.

A service design workshop (Study 1) and three between-subjects experiments (Studies 2–4) were conducted.

Results indicate that blockchain adoption significantly improves traceability and trust in the food supply chain. This improvement in turn enhances customer satisfaction through perceived improvements in food safety, quality and naturalness. This study also notes that the effects of blockchain technology vary depending on the type of restaurant (casual or fine dining) and its location (tourist destinations or residential areas).

The findings offer practical insights for restaurant owners, technology developers and policymakers. Emphasizing the benefits of blockchain adoption, this study guides decision-making regarding technology investments for enhancing customer service and satisfaction in the hospitality sector.

This research contributes novel insights to the field of technology innovation in the hospitality industry. It extends the understanding of signaling theory by exploring how blockchain technology can serve as a tool for signal transmission in restaurant food supply chains.