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Purpose: To investigate the key technologies facilitating the transition towards Industry 5.0 and analysing the contributions of Nvidia, a prominent leader in this field, to these technological advancements.

Significance of the study: Technology companies such as Nvidia play a critical role in this transformation through their innovative solutions. This study addresses the need to understand this evolving landscape and the significant impact of the Nvidia.

Methodology: This study is a qualitative approach that examines the existing literature and secondary case studies pertaining to Industry 5.0, and Nvidia. This study examines Nvidia’s high-performance graphics processing units (GPUs), the digital twin platform Omniverse, and the humanoid robot technology development platform, Isaac.

Findings: The next generation of GPUs with the Blackwell architecture is expected to further advance the development of large language models. The Nvidia Omniverse platform contributes significantly to the development of digital twins, a crucial technology for Industry 5.0. The Nvidia Isaac platform focuses on the development of humanoid robot technology, which is a key component of Industry 5.0. Utilizing realistic simulations with Isaac Sim, imitating human behavior with GR00T, and leveraging the high-performance processing power of Jetson Thor, the platform facilitates the creation of robots capable of safe and effective human–robot collaboration. Nvidia has emerged as a leader in the artificial intelligence (AI), robotics, and gaming sectors because of its innovative and agile company culture.

Practical implications: Companies can leverage Nvidia’s technological solutions to optimize production processes and enhance both efficiency and sustainability. The human–machine collaboration emphasized by Industry 5.0 will necessitate the reshaping of workforce skillsets and operational approaches.

This study aims to address the issue of perfunctory sharing that arises in knowledge governance due to a lack of willingness to share knowledge between individuals within the same organization. This knowledge-sharing process does not occur simultaneously for both parties but follows a sequential progression. Additionally, this governance model fully considers the willingness of both parties to share and effectively addresses the two knowledge characteristics that influence their willingness to do so.

This study follows inductive logic and primarily adopts an interpretive case study approach to conduct a longitudinal exploratory case study. An incubator enterprise with active knowledge-sharing activities and significant knowledge governance effects is selected as the research subject. The governance system is explained through the lens of prospect theory at the mechanism level.

In the study of the knowledge-sharing process, the authors observed a new challenge: perfunctory behavior, whereby individuals engage in knowledge-sharing activities that lack substantial effects as a way to avoid genuine sharing. From this, a new knowledge-sharing model was extracted, the cold start and hot feedback model, which follows a sequential (rather than simultaneous) progression. Using the deterministic effect of prospect theory and the principle of reference dependence, the governance mechanism of corporate knowledge sharing was analyzed from the perspective of knowledge-sharing willingness.

Based on prospect theory, this study primarily explains how the governance mechanism influences the willingness to share knowledge from the perspective of four principles. In the future, threat rigidity theory and commitment escalation theory can be combined to further analyze the willingness to share knowledge from the perspectives of pressure and cost. Empirical research methods can also be used to test and enrich the research results of this paper.

After considering the willingness to share knowledge, a new knowledge-sharing model and corresponding knowledge-sharing governance model are proposed, and prospect theory is extended to the knowledge-based theory research field.

This paper aims to explore how value co-destruction (VCD) impacts on guests perceived value in Airbnb, peer-to-peer (P2P) accommodation platform.

This study applies an interpretive exploratory research approach to explore VCD on consumer perceived values. Data were collected via personal in-depth semi-structured interviews with guests who have experienced in staying Airbnb. Thematic analysis was conducted to analyse data.

Drawing on the theory of consumption values, the findings show that five dimensions of value; functional, social, economic, emotional and epistemic value are destroyed due to negative interactions between guests and hosts. Moreover, this study revealed that host’s unaccepted behaviours, miscommunication, lack of resources, expectations and issues in procedures lead to destroy guest’s perceived value. The findings of the study provide several insights for the tourism and hospitality sector, P2P accommodation platforms and policymakers to prevent from VCD and optimise the customer experience.

This study provides a greater understanding of how and which activities lead to destroy guest’s perceived values after experiencing VCD. To the best of the author’s knowledge, this study is the first to apply theory of consumption values in the P2P accommodation context and research field related to “VCD”.

Recently, the concept of frugal innovation (FI) has gained relevance in both academic and societal discourse. Whether disruptive frugal digital innovation is contributing to the growth of small and medium-sized businesses in Africa is a subject of debate. Generally speaking, frugal inventions are linked to developing nations where sizable consumer groups at the base of the pyramid have unfulfilled needs. Africa, a continent with growing economies, has witnessed a surge in disruptive FI, which makes this chapter an important discourse. Digital technologies such as the Internet of Things (IoT), social media, cloud computing, and Artificial Intelligence (AI) are finding their way in the market, and how it is affecting human development and small enterprises has been a subject for debate. This book chapter presents findings on how FI has led to sustainable human development and growth of micro, small-, and medium-sized enterprises (MSMEs) as revealed by a review of existing literature on the subject. According to findings from the literature, MSMEs' connections and interactions with partners, suppliers, and consumers have improved as a result of the adoption of disruptive digital platforms. Additionally, while operating in challenging settings in Africa, digital technologies offer certain intrinsic traits and information technology capabilities that allow firms to grow and flourish. Digital platforms are viewed as transparent, collaborative instruments that provide economic opportunities throughout the ecosystem. The results also show that disruptive digital technologies offer MSMEs an inexpensive, simple-to-use, and simple-to-deploy solution in order to compete with stronger incumbents across a range of industries.

Given the cruciality of construction workers' safe behaviors, the possible influential factors on workers' behaviors should be studied, and one of these factors is characteristics. The authors identified emotional intelligence (EI), motivation and job burnout as characteristics that might affect a worker's safety behavior, and the aim of this study is to investigate these possible relationships.

Workers' EI, motivation and job burnout status were assessed by a structured interview. Furthermore, workers' safety behaviors were assessed by a checklist derived from national codes, regulations and other research studies. Then, the researcher's observations took place, and the data were acquired.

EI and motivation of workers were able to predict safety behaviors, and the effect of job burnout on safety behaviors was not significant. In addition, motivation's influence on job burnout was not significant. Therefore, in order to promote safety behaviors, the EI and motivation of workers need to be taken into consideration.

The results indicate why construction managers should consider the workers' EI and motivation competencies and how this consideration could lead to safer and better performance in construction projects.

The possible effects of EI, motivation and job burnout on the safety behaviors of construction workers haven't been paid enough attention. Moreover, the authors couldn't find a study similar to the present one that was conducted in Iran. Also, an original model was presented, and safety behaviors were studied through fieldwork rather than using questionnaires.

This paper aims to empirically examine the link between negative social media sentiments (SMS) and firm risk, measured by total risk.

This paper collected data from Fortune 500 companies in the USA from 2010 to 2017. The analyses used the pooled ordinary least squares, Fama–McBeth regression, fixed-effects regression and propensity score matching.

The results show that negative SMS increase firm risk. In addition, this paper considers the effect of corporate social responsibility (CSR) disclosures on the relationship between negative SMS and firm risk. This paper finds that the effects of negative SMS on firm risk are attenuated in firms with better CSR disclosures.

This study offers fresh perspectives for investors and managers on firm risk and the influence of social media on firm outcomes, providing valuable insights for scholars and practitioners to understand the impact of negative social media sentiments on firm risk, along with the crucial roles played by CSR in this relationship.

The construction industry has long been criticized for unethical conduct. The owner usually manages the contractor's opportunistic behaviors by employing a professional supervisor, but there is a risk of covert collusion between the supervisor and contractor. Based on the principal–agent theory and collusion theory, this paper aims to investigate optimal collusion-proof incentive contracts.

This paper presents a game-theoretic framework comprising an owner, supervisor and contractor, who interact and pursue maximized self-profits. Built upon the fixed-price incentive contract, cost-reimbursement contract, and revenue-sharing contract, different collusion-proof incentive contracts are investigated. A real project case is used to validate the developed model and derived results.

This paper shows that the presence of unethical collusion undermines the owner's interests. Especially, the possibility of agent collusion may induce the owner to abandon extracting quality information from the supervisor. Furthermore, information asymmetry significantly affects the construction contract selection, and the application conditions for different incentive contracts are provided.

This study still has some limitations that deserve further exploration. First, this study explores contractor–supervisor collusion but ignores the possibility of the supervisor abusing authority to extort the contractor. Second, to focus on collusion, this paper ignores the supervision costs. What's the optimal supervision effort that the owner should induce the supervisor to exert? Finally, this paper assumes that the colluders involved always keep their promises. However, what if the colluders may break their promises?

Several collusion-proof incentive contracts are explored in a project management setting. The proposed incentive contracts can provide the project owner with effective and practical tools to inhibit covert collusion in construction management and thus safeguard construction project quality.

This study expands the organization collusion theory to the field of construction management and investigates the optimal collusion-proof incentive contracts. In addition, this study is the first to investigate the effects of information asymmetry on contract selection.

Previous research mainly uses graph neural networks on syntactic dependency graphs, often neglecting emotional cues in sarcasm detection and failing to integrate image features for multimodal information effectively. To address these limitations, this study proposes a novel multimodal sarcasm detection model based on the directed graph isomorphism network with sentiment enhancement and multimodal fusion (DGIN-SE-MF).

The approach extracts image and text features through vision transformer and BERT, respectively. To deeply integrate the extracted features, the author develops a text-guided multi-head attention fusion mechanism module. Subsequently, a directed graph is constructed through SE and the multimodal factorized bilinear pooling method to integrate image features into the graph. The DGIN then fuses the image and text features, using a weighted attention mechanism to generate the final representation.

The model is validated on three datasets: English, Chinese and an Indonesian–English dataset. The results demonstrate that the proposed model consistently outperforms other baseline models, particularly on the Chinese and English sarcasm datasets, achieving F1 scores of 88.75 % and 83.10 %, respectively.

The proposed model addresses the inadequacies of previous methods by effectively integrating emotional cues and image features into sarcasm detection. To the best of the authors’ knowledge, this is the first work to leverage a DGIN-SE-MF for this task, leading to significant improvements in detection performance across different languages.

This study aims to outline the transformative impacts of technological developments (TD) on architectural education (AE). The focus is on studying the dynamics of convergence and erosion, aiming to understand the impact of current digital transformations such as the COVID-19 pandemic, sustainability considerations and technology integration on AE.

A scientometric analysis and bibliometric search were performed to understand the current knowledge in the field. The Web of Science (WoS) was selected for its comprehensive collection of significant research articles and integrated analytical tools for generating representative data. The study involved an extensive bibliometric analysis of 131 journal articles on TD in AE from 2000 to 2023. Subsequently, the VOSviewer software was employed to illuminate the transformative impacts of technological advancements on AE. Robust methodologies, including citation analysis and co-citation networks, unravel quantitative dimensions such as publication trends, influential authors, prolific journals, geographic distribution and prevalent themes or technological domains within the discourse.

The findings reveal significant evolution in AE due to TD, with notable shifts influenced by factors such as the COVID-19 pandemic, sustainability concerns and the integration of modern technologies. Key findings include the increasing adoption of online platforms and technologies like Building Information Modeling (BIM), the crucial role of design thinking methodologies and the recognition of innovative modules such as architectural photogrammetry and augmented reality (AR) applications. Furthermore, keyword clusters were classified into six groups: “AE pedagogy and curriculum development,” “Development of architectural design process and studio,” “Educational approaches and digitalization in architectural design,” “Transition to online AE,” “Development/emergence of photogrammetry at architectural education” and “use of AR.”

Although several studies have addressed TD in AE from various perspectives and methods, they have yet to investigate the subject using scientometric analysis from a holistic perspective. A holistic exploration of TD in AE still needs to be improved in the existing literature. In contrast to previous investigations, this study is the first to leverage the quantitative analytical capabilities of VOSviewer. The originality lies in uncovering quantitative dimensions such as publication trends, influential authors and prevalent themes, providing a comprehensive understanding of the nuanced dimensions of this evolving intersection.

The aim of this paper is to investigate the factors that influence consumers’ intentions to buy green food and develop conceptual framework that combines Health belief model (HBM) and Norm activation theory (NAT).

The research used purposive sampling to collect primary responses from Indians and Lebanese in Ghana at restaurants and retail stores in Accra. Based on the NAT and HBM constructs, questionnaires were designed and distributed to 787 respondents. Data were analyzed using partial least squares and structural equation modeling to test the hypotheses developed through a literature review.

The findings showed that perceived benefit (PBN), perceived threat (PTT) and cue to action (CAT) are key factors that drive consumers’ intentions to purchase green food by Indians and Lebanese in Ghana. However, there are perceived barriers (PBB) that prevent individuals from buying green food, such as high prices, doubts about authorization and content, shortage of green food, inadequate selling techniques, supposed fulfillment and deficiencies. Therefore, more work is needed to address these barriers.

This research can be used to create advertising messages that emphasize the health and wellbeing benefits of environmental impact on communities, and stimulate customer motivation to purchase green food.

This is a unique study that combines HBM and NAT to investigate the factors that influence consumers’ intentions to buy green food among Indians and Lebanese in Ghana and developed a conceptual framework to offer valuable insights for marketing practitioners to develop effective marketing strategies to induce buying intentions towards green foods. The construct of NAT has been found as useful moderators of pro-environmental behavior.