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This chapter examines the significant role of non-fungible tokens (NFTs) and blockchain technology in fostering a sustainable economy in the metaverse. Blockchain allows the saving and transfer of decentralized and secure data. As a primary component of the metaverse economy, NFTs are distinct and secure virtual assets saved on the blockchain. These assets facilitate possessing, trading, and monetizing digital assets. These advancing technologies have also revolutionized the method by which creators and artists test and exchange their digital work, introducing a novel period of ownership and value in the digital realm. However, the negative environmental effects of some blockchain technologies constitute a considerable constraint, pushing a shift to a sustainable economy. Platforms like The Sandbox have implemented initiatives to address environmental concerns. As a case study, The Sandbox play-to-earn model with tokenized assets showcases its ability to create value and encourage user participation. It shows the ability of NFTs and blockchain to support a sustainable economy.

The integration of blockchain technology (BT) in supply chain management (SCM) is at the forefront of technological advancements, yet it faces significant barriers that hinder its widespread adoption. This study aims to delve into these challenges, employing the diffusion of innovations (DOI) theory to systematically investigate and propose a strategic framework for overcoming the technological barriers to BT adoption within SCM.

Through a comprehensive systematic literature review (SLR) of 155 publications, complemented by rigorous content analysis and expert interviews, this research identifies and categorizes 16 primary technological barriers, including scalability and privacy issues, that impede BT integration.

The proposed framework, informed by DOI theory, outlines tailored strategies across three critical adoption stages: initiation, where the focus is on mitigating high energy consumption and scalability issues; adoption decision, emphasizing the formulating international standards for blockchain architecture, embedding abstraction layers within software projects; and implementation, concentrating on enhancing security, interoperability and system efficiency.

This research contributes significantly to both academic literature and practical applications. Academically, it extends the DOI theory within the SCM context and enriches the blockchain literature by providing a nuanced understanding of the specific barriers to BT adoption. Practically, it offers a roadmap for industry practitioners, delineating actionable strategies to navigate the adoption process effectively. This study not only bridges the gap between theoretical insights and practical implementations but also serves as a vital resource for policymakers and standard-setting bodies in facilitating and regulating BT adoption in SCM, thereby fostering innovation and competitive advantage in the marketplace.

Consumer well-being (CWB) is a flourishing area of research. It is an important field of study for the Sustainable Development Goals (SDGs), particularly SDG-3 (Good Health and Well-Being). However, despite some recent reviews, there is a lack of a comprehensive overview of the broad themes emerging in the CWB literature. The study aims to thoroughly integrate and organize the fragmented existing literature on CWB by uncovering its emergent themes and their impact.

To address this gap, this study presents a systematic literature review (SLR) of 166 peer-reviewed journal articles from 2013–2023 following the Scientific Procedures and Rationales for Systematic Literature Reviews protocol from the Scopus and Web of Science databases.

This study’s SLR uncovered seven themes: subjective well-being; psychological well-being; food well-being; financial well-being; environmental well-being; social well-being; and societal well-being. Further, this study identifies that these themes impact consumers on three levels: micro, meso and macro. Thus, this study provides a comprehensive overview of the emergent themes along the levels of impact.

This paper anticipates that the study, which is a thorough overview of the CWB literature, will provide managers, academics and students with an introduction to the topic.

To the best of the authors’ knowledge, this is one of the first articles that shows the themes of the CWB literature along the respective levels of impact and draws avenues for future research.

El bienestar del consumidor (CWB) es un área de investigación en auge. Es un campo de estudio clave para los Objetivos de Desarrollo Sostenible (ODS), en particular el ODS-3 (Salud y Bienestar). Sin embargo, a pesar de algunas revisiones recientes, falta una visión general completa de los amplios temas emergentes en la literatura de CWB. El objetivo de este estudio es integrar y organizar exhaustivamente la literatura existente sobre CWB, revelando sus temas emergentes y su impacto.

Para abordar esta brecha, el estudio presenta una revisión sistemática de la literatura (SLR) de 166 artículos de revistas revisados por pares, publicados entre 2013 y 2023, siguiendo el protocolo SPAR-4-SLR, extraídos de las bases de datos Scopus y Web of Science.

Nuestra SLR reveló siete temas: (a) bienestar subjetivo; (b) bienestar psicológico; (c) bienestar alimentario; (d) bienestar financiero; (e) bienestar ambiental; (f) bienestar social; y (g) bienestar societal. Además, identificamos que estos temas afectan a los consumidores en tres niveles: (i) micro, (ii) meso y (iii) macro. Así, este estudio proporciona una visión completa de los temas emergentes a lo largo de los niveles de impacto.

Anticipamos que este estudio, que ofrece una revisión exhaustiva de la literatura de CWB, proporcionará a gestores, académicos y estudiantes una introducción al tema.

Según nuestro conocimiento, este es uno de los primeros artículos que muestra los temas de la literatura de CWB junto con sus respectivos niveles de impacto y traza rutas para futuras investigaciones.

消费者幸福感(CWB)是一个蓬勃发展的研究领域, 对可持续发展目标(SDGs), 尤其是 SDG-3(良好健康与幸福感), 具有重要意义。然而, 尽管近期已有一些综述, CWB 文献中出现的广 泛主题仍缺乏全面概述。本研究旨在深入整合和组织现有 CWB 文献, 通过揭示其新兴主题及其影响, 填补这一空白。

为解决这一问题, 本研究按照 SPAR-4-SLR 协议, 从Scopus和Web of Science数据 库中选取了 2013 年至 2023 年的 166 篇经过同行评审的期刊文章, 进行系统文献综述(SLR)。

我们的文献综述揭示了七个主题:(a)主观幸福感; (b)心理幸福感; (c)食品幸福感; (d)金融幸福感; (e)环境幸福感; (f)社会幸福感; (g)社会整体幸福感。此外, 我们发现这些 主题在三个层面上影响消费者:(i)微观层面; (ii)中观层面; (iii)宏观层面。因此, 本研究提供 了沿影响层面的新兴主题的全面概述。

我们期待这篇全面概述 CWB 文献的研究能为管理者、学者和学生提供关于该主题的全 面介绍。

据我们所知, 这是首篇阐释 CWB 文献主题及其相应影响层次的文章之一, 并为未来研究指 明了方向。

This study aims to investigate the different effects of physical and social servicescapes on brand love for internet-famous restaurants, focusing on their pathways and strengths of influence.

Structural equation modeling was applied to analyze data from 387 online questionnaires in China.

Results indicate that social servicescape directly influences brand love for internet-famous restaurants, while physical servicescape does not. The effect of physical servicescape on brand love for internet-famous restaurants is mediated by perceived coolness and perceived enjoyment, whereas social servicescape’s influence is mediated solely by perceived enjoyment. Overall, physical servicescape has a stronger impact on brand love for internet-famous restaurants compared to social servicescape.

The findings help internet-famous restaurants create effective physical and social servicescapes to enhance brand love, underscoring that physical servicescape is more crucial than social servicescape for cultivating this love.

This study contributes to the literature by analyzing the heterogeneous pathways and strengths of physical and social servicescapes influencing brand love for internet-famous restaurants, while highlighting the mediating role of perceived coolness and expanding the application scope of cognitive appraisal theory.

This paper aims to investigate the effectiveness of immersive virtual reality (VR) media and the influence of user’s age in the context of destination marketing by exploring their impact on cognition (presence), affection (arousal), and behavioral (intention to visit and intention to recommend the destination) outcomes.

A laboratory experiment was conducted to compare the impact of using immersive VR (vs. 2D desktop) to experience a 360-degree virtual tour of Valencia on consumers’ behavior. The sample included 187 participants. Both self-reported and physiological measures were collected during the experimentation.

Results showed that participants in the immersive condition experienced a stronger sense of presence and higher physiological arousal than those exposed to nonimmersive content. Presence significantly mediated both the intention to visit and the intention to recommend the promoted venue. Physiological arousal mediated the relationship between media typology and the intention to recommend the destination. Upon introducing age as a moderating variable, the effect of physiological arousal on behavioral outcomes proves to be significant.

The study presents destination marketing organizations with a compelling use case for immersive technologies. It also offers design principles, potential applications and targeting strategies for VR marketing in hospitality management.

To the best of the authors’ knowledge, this study is the first to investigate the combined effect of physiological arousal and presence on behavioral intentions in VR destination marketing, while also examining the impact of age as an individual characteristic.

The integration of big data with artificial intelligence in the field of digital health has brought a new dimension to healthcare service delivery. AI technologies that provide value by using big data obtained in the provision of health services are being added to each passing day. There are also some problems related to the use of AI technologies in health service delivery. In this respect, it is aimed to understand the use of digital health, AI and big data technologies in healthcare services and to analyze the developments and trends in the sector.

In this research, 191 studies published between 2016 and 2023 on digital health, AI and its sub-branches and big data were analyzed using VOSviewer and Rstudio Bibliometrix programs for bibliometric analysis. We summarized the type, year, countries, journals and categories of publications; matched the most cited publications and authors; explored scientific collaborative relationships between authors and determined the evolution of research over the years through keyword analysis and factor analysis of publications. The content of the publications is briefly summarized.

The data obtained showed that significant progress has been made in studies on the use of AI technologies and big data in the field of health, but research in the field is still ongoing and has not yet reached saturation.

Although the bibliometric analysis study conducted has comprehensively covered the literature, a single database has been utilized and limited to some keywords in order to reach the most appropriate publications on the subject.

The analysis has addressed important issues regarding the use of developing digital technologies in health services and is thought to form a basis for future researchers.

In today’s world, where significant developments are taking place in the field of health, it is necessary to closely follow the development of digital technologies in the health sector and analyze the current situation in order to guide both stakeholders and those who will work in this field.

This paper aims to focus on the selection of an appropriate nature-inspired texture pattern for cutting tool tribological surface. The selection process uses the recognized skin textures of different snakes scrolling on highly rough and projected surface conditions to analyze suitability of texture based on the texture geometry and machining conditions. The work also aims to propose a texture pattern selection process to incorporate on cutting tool tribological surface.

The selection of alternative nature-inspired texture patterns based on the texture pattern geometry and machining properties leads to a multi-criteria decision-making problem. Thirteen criteria are considered for selecting an appropriate texture pattern among 14 alternatives, i.e. nature-inspired texture patterns. In the present work, an integrated analytical hierarchy process (AHP)-TOPSIS, AHP-multi-objective optimization on the basis of ratio analysis (MOORA) and AHP-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) approaches have been proposed for the selection of an appropriate nature-inspired texture pattern. AHP is used for the formulation of decision-making matrix and criteria weight calculations and ranking of alternatives is done by three methods. Spearman’s correlation compared and found positive relations between rank assigned by methods. Experimental validation is done in Lathe for selected texture effects.

The texture parameters C-1 (Width of texture) and C-2 (Depth of texture) are found significant, while T-2 (Blended Krait) and T-6 (Banded Racer-1) texture is found optimal to generate on cutting tool surface.

Only some nature-inspired texture patterns have been recognized before the selection; an infinite number of textures are available in nature. The size of the texture pattern is difficult to identify by the selection process because each texture pattern may have different effects on tribological surfaces.

The proposed selection methodology of nature-inspired texture patterns will help identify optimal texture geometry for specific tribological applications. The nature-inspired texture patterned tool has a significant impact on the cutting force and temperature due to its tribological effect on the cutting tool surface; it decreases the power required for machining. The machining characteristics like roughness are found to decrease by using nature-inspired texture patterned tools.

Various nature-inspire texture studies to generate specific effects on the tribological surfaces may be started study for the surface of aircraft, ships, bearings, etc. Small and big fabrication industries may benefit by decreasing the cost of machining using nature-inspired texture-patterned tools. Research society will pay attention to nature’s inspiration.

Novel snake-skin-inspired texture patterns are recognized and hybrid MCDM methods are proposed to select optimal texture pattern. Proposed method used single time normalization to effectively rank the alternatives. The insights gained from this research can be extrapolated to address similar challenges in selecting nature-inspired textures for various applications.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0163/

This study aims to focus on key approaches to education for sustainability (EfS) leadership development in the context of Malaysian and Japanese universities. The authors identify key indicators of effective EfS leadership development approaches using both descriptive and inferential analyses, identify and compare the preferred leadership learning methods of academics and examine the impact of marital status, country of residence and administrative position on the three EfS leadership development approaches.

The study is quantitative in approach and survey in design. Data were collected from 664 academics and analysed using the efficient partial least squares (PLSe2) methodology. To provide higher education researchers with more analytical insights, the authors re-estimated the models based on the maximum likelihood methodology and compared the results across the two methods.

The inferential results underscored the significance of four EfS leadership learning methods, namely, “Involvement in professional leadership groups or associations, including those concerned with EfS”, “Being involved in a formal mentoring/coaching program”, “Completing formal leadership programs provided by my institution” and “Participating in higher education leadership seminars”. Additionally, the authors noted a significant impact of country of residence on the three approaches to EfS leadership development. Furthermore, although marital status emerged as a predictor for self-managed learning and formal leadership development (with little practical relevance), administrative position did not exhibit any influence on the three approaches.

In addition to the theoretical and methodological implications drawn from the findings, the authors emphasize a number of practical implications, namely, exploring the applicability of the results to other East Asian countries, the adaptation of current higher education leadership development programmes focused on the key challenges faced by successful leaders in similar roles, and the consideration of a range of independent variables including marital status, administrative position and country of residence in the formulation of policies related to EfS leadership development.

This study represents an inaugural international comparative analysis that specifically examines EfS leadership learning methods. The investigation uses the research approach and conceptual framework used in the international Turnaround Leadership for Sustainability in Higher Education initiative and uses the PLSe2 methodology to inferentially pinpoint key learning methods and test the formulated hypotheses.

Considering the influence of deformation error, the target poses must be corrected when compensating for positioning error but the efficiency of existing positioning error compensation algorithms needs to be improved. Therefore, the purpose of this study is to propose a high-efficiency positioning error compensation method to reduce the calculation time.

The corrected target poses are calculated. An improved back propagation (BP) neural network is used to establish the mapping relationship between the original and corrected target poses. After the BP neural network is trained, the corrected target poses can be calculated with short notice on the basis of the pose correction similarity.

Under given conditions, the calculation time when the trained BP neural network is used to predict the corrected target poses is only 1.15 s. Compared with the existing algorithm, this method reduces the calculation time of the target poses from the order of minutes to the order of seconds.

The proposed algorithm is more efficient while maintaining the accuracy of the error compensation.

This method can be used to quickly position the error compensation of a large parallel mechanism.

This paper aims to present the mechanical design and kinematics of a novel rigid-flexible coupling hybrid robot to develop a promising aeroengine blades in situ repair technology.

According to requirements analysis, a novel rigid-flexible coupling hybrid robot is proposed by combining a three degrees of freedom (DOF) parallel mechanism with a flexible continuum section. Then the kinematics models of both parallel mechanism and flexible continuum section are derived respectively. Finally, based on equivalent joint method, a two-step numerical iterative inverse kinematics algorithm is proposed for the whole robot: (1) the flexible continuum section is equivalently transformed to a 2-DOF spherical joint, thus the approximate analytical inverse kinematic solution can be obtained; (2) the accurate solution is derived by an iterative derivation of both parallel mechanism and flexible continuum section.

To verify structure scheme and the proposed kinematics modeling method, numerical simulations and prototype experiments are implemented. The results show that the proposed kinematics algorithm has sufficient accuracy and computational efficiency in the whole available workspace, that is end-effector position error and orientation error are less than 0.2 mm and 0.01° respectively, and computation time is less than 0.22s.

A novel rigid-flexible coupling hybrid robot for aeroengine blades in situ repair is designed. A two-step numerical iterative inverse kinematics algorithm is proposed for this unique hybrid robots, which has good accuracy and computational efficiency.