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The information and communications technology (ICT) industry is revolutionizing the world. However, achieving net zero emissions and sustainable development goals is equally important. This study uses intellectual capital-based and natural resource-based theories to determine whether green information technology capital (GITC) mediates the relationship between corporate social responsibility (CSR) and environmental performance. The role of the top management teams (TMT) green commitment as a moderator between CSR and GITC is also hypothesized.

Data were collected using multi-wave and multi-respondent strategies from 275 ICT firms to examine these relationships. Structural equation modeling was used for analysis.

The findings demonstrate that CSR significantly and positively impacts environmental performance, with GITC significantly mediating this relationship. Furthermore, the statistical results confirm that TMT’s green commitment significantly strengthens the connection between CSR and GITC.

The significance of TMT’s green commitment as a boundary condition that enhances the effectiveness of strategically aligned CSR practices provides novel theoretical insights to extend the CSR literature. Additionally, it offers practical implications for the managers of ICT firms, which are discussed in detail.

This study aims to examine the impact of peer-to-peer (P2P) accommodation platforms’ green marketing on consumers’ pro-environmental behavioural intention through the mediation of consumer trust and engagement, following the social influence theory and the stimulus–organism–response model.

A questionnaire survey was designed to collect data from American P2P accommodation consumers. Data collection was conducted through an outsourced survey company. Partial least squares structural equation modelling was used to analyse the data.

The study reveals that P2P accommodation platforms’ green marketing orientation was positively associated with consumer trust in the platform and consumer engagement with the platform. Both consumer trust and consumer engagement positively enhanced consumers’ pro-environmental behavioural intention in the P2P accommodation consumption, serving as effective mediators between consumers’ perceptions of green marketing orientation and pro-environmental behavioural intention.

The study offers practical insights for P2P accommodation platforms and operators in engaging in green marketing and fostering consumers’ pro-environmental consumption behaviours in P2P accommodations.

The study addresses the grand question of whether business operators’ responsible production behaviour can possibly lead to consumers’ responsible consumption behaviour in the P2P accommodation sector. It contributes to the literature on P2P accommodation by providing evidence to show green marketing practices of P2P accommodation platforms can lead to consumers’ pro-environmental behavioural intention. It provides both theoretical value for knowledge advancement and practical value to guide more sustainable industry practices.

This paper aims to explore the intersection of artificial intelligence (AI) and marketing within the context of knowledge management (KM). It investigates how AI technologies facilitate data-driven decision-making, enhance business communication, improve customer personalization, optimize marketing campaigns and boost overall marketing effectiveness.

This study uses a quantitative and systematic approach, integrating citation analysis, text mining and co-citation analysis to examine foundational research areas and the evolution of AI in marketing. This comprehensive analysis addresses the current gap in empirical investigations of AI’s influence on marketing and its future developments.

This study identifies three main perspectives that have shaped the foundation of AI in marketing: proxy, tool and ensemble views. It develops a managerially relevant conceptual framework that outlines future research directions and expands the boundaries of AI and marketing literature within the KM landscape.

This research proposes a conceptual model that integrates AI and marketing within the KM context, offering new research trajectories. This study provides a holistic view of how AI can enhance knowledge sharing, strategic planning and decision-making in marketing.

This study aims to empirically investigate how knowledge paradox affects collaboration performance. Knowledge paradox, which arises from the simultaneous need for knowledge sharing and protection, is common in interorganizational collaboration. Using the ambidexterity perspective, this paper aims to reexamine the effect of the knowledge paradox on collaborative performance to explore the moderating roles of structural and contextual ambidexterity.

This study used a sample of 153 firms involved in vertical and horizontal collaboration, collected via questionnaires. Hypotheses were tested using hierarchical regression analysis.

This study demonstrates that the stronger the knowledge paradox is, the higher the potential for value creation. Thus, knowledge paradox has a positive impact on collaborative performance. The functions of structural ambidexterity and contextual ambidexterity strengthen this positive relationship.

This paper not only expands the theoretical application of the knowledge paradox and ambidexterity theory in the context of interorganizational relationships but also provides significant managerial implications. By comprehending the dynamics of the knowledge paradox and the role of ambidexterity, managers can make well-informed decisions to enhance their collaborative performance.

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 examines the relationships among residents' event impact perceptions, attitude towards events, attitude towards sponsors and sponsor-related behavioural intentions (i.e. purchase intention and word-of-mouth).

Focusing on the Naha Marathon in Okinawa, Japan, as a research context, data were collected from residents of Okinawa who were familiar with the Naha Marathon and its sponsors (N = 322). Structural equation modelling was employed to test the hypotheses, developed based on theories of social exchange, image transfer and planned behaviour.

The findings revealed that residents’ perceptions of social event impacts, rather than economic and environmental impacts, were associated with attitudes towards the event. Such an effect was indirectly associated with purchase intentions and word-of-mouth intentions via attitude towards the sponsors.

The current research contributes to the literature on sport sponsorship, especially in participation-based sports, by exploring how event sponsors can enjoy fruitful returns on investment. The findings can extend our understanding by highlighting the importance of positive community engagement for sponsors. Sponsors who aim to enhance consumer behaviour should prioritize strategies aligning with the positive social impacts of events.

Online games are highly popular Internet applications. Some games enable players to save game progress and accumulate experiences or changes to avatars during gameplay, whereas some other games do not, requiring players to restart from the beginning each time. That is, games differ in avatar accumulability. However, we do not know whether games should be designed to permit avatar accumulability or not and how it affects players’ gameplay experience and therefore game outcomes, indicating gaps. Research addressing these gaps can inform game makers in designing games that effectively strengthen their players’ game loyalty.

We used social identity theory (SIT) to construct a theoretical model. To test this model, three waves of survey data were gathered from the same 778 participants.

These findings uniquely indicate that avatar accumulability fosters avatar identification and increases players’ focused immersion, thus increasing players’ loyalty.

Game providers could include game features that enable players to accumulate their avatars’ in-game skins, levels, items (weapons and equipment) and experience points. This accumulability can help strengthen players’ game loyalty.

Overall, our study extends SIT by adding a new trigger (avatar accumulability) and two novel consequences of avatar identification (image protection and focused immersion) in avatar-related systems (games or gamified systems). The new trigger offers an actionable means to apply SIT, while the novel consequences verify the value of applying SIT to study online games.

As the search engine platform, Baidu has already developed keyword advertising as one of its main business scopes, while in-feed advertising is emerging as another intelligent choice for the company. Our purpose is to validate the effectiveness of keyword and retargeted in-feed advertising on offline sales and whether the effectiveness of these two advertising strategies relies on keyword attributes work.

We utilize data from the ad campaigns of a prominent manufacturer within the machinery and equipment (hereinafter referred to as “the company”) on Baidu. To scrutinize the research hypotheses, we have employed linear regression models. Subsequently, we address potential endogeneity issues and use various techniques to ascertain the reliability of the results.

Empirical evidence indicates that both keyword and in-feed advertising enhance offline sales. Upon examining the moderating role of keyword attributes (specificity and length), we observe that specific keywords (price and word-of-mouth (WOM)) accelerate the boosting effect of advertising on sales; similarly, the longer the keywords, the more obvious the enhanced impact of advertising on sales. Moreover, the positive influence of specific keywords (price and WOM) on advertising effectiveness is more outstanding when the keywords are longer.

To our knowledge, no empirical investigation has yet to analyze keyword and retargeted in-feed advertising concurrently within the search engine context. Our research is the inaugural work to reveal that they serve as mutual substitutes regarding their impact on sales. Furthermore, this paper pioneers examining the moderating effects exerted by keyword attributes (specificity and length) on the effectiveness of these two ad types. The findings presented herein offer valuable insights into the harmonious coexistence and collaboration among companies, advertisers, users and search engine platforms.

This paper explores the engagement of architecture and design-related disciplines within the built environment with social media. The study aims to identify key themes, assess the methodologies used and compare the approaches across different disciplines.

The research employs a semi-systematic literature review coupled with thematic analysis. This approach allows for a comprehensive examination of existing studies, identifying key themes, trends and gaps in the current knowledge base. Through this methodology, the paper synthesises diverse perspectives and insights from a wide range of sources.

Social media data is a valuable tool for understanding architecture and the built environment, but there is a significant divergence in methodologies across disciplines. There is a growing advocacy for mixed-method approaches that would benefit from critical engagement with data that’s underpinned by theoretical frameworks. Such approaches enhance research robustness, support multidisciplinary collaboration and improve the applicability of social media data in design practices.

Despite the proliferation of literature on social media and the built environment, there remains a lack of nuanced understanding regarding thematic variations within individual design disciplines and the specific research methodologies they employ. This paper critically reviews existing research to offer current insights, research gaps and potential future research directions on social media and architecture/design-related disciplines in the built environment.

This study aims to investigate the “digitalization paradox” in manufacturing digital transformation, where significant investments in digital technology may not necessarily lead to increased returns. Specifically, it explores the intricate relationship between digital technology convergence, financial performance, productivity and technological innovation in listed Chinese manufacturing firms, drawing upon theories of digital innovation and knowledge networks.

Using a large panel data from 747 listed firms in China’s manufacturing sector and their 428,927 patents spanning from 2013 to 2022, this research first quantifies manufacturing firm-level digital technology convergence through patent network analysis. Furthermore, this study employs hierarchical regression analysis and the instrumental variable method to investigate the curvilinear relationship between digital technology convergence and financial performance. Furthermore, the moderating role of firms’ productivity and technological innovation is tested.

Three types of firm-level digital technology convergence (DTC) are delineated and quantified: local authority in digital convergence (DegreeDTC), convergence with heterogeneous digital knowledge (BetweenessDTC) and shortest-path convergence with digital technologies (ClosenessDTC, where a higher value signifies a more conservative and shorter path in adopting digital technologies). Network visualization shows that manufacturing firms' DTC has consistently increased over time. Contrary to traditional assumptions, our research reveals a U-shaped relationship between DTC (specifically, DegreeDTC and BetweenessDTC) and financial performance. This relationship is characterized by a negative correlation at lower levels and a positive one at higher levels. The joint effect of firms’ productivity and technological innovation significantly strengthens this relationship. These findings are robust across a series of robustness checks.

Our findings offer practical insights for both managers and policymakers. We recommend a balanced approach to digital innovation management within the technology convergence paradigm. Manufacturing firms can generate economic value by strategically choosing to either shrink or expand their digital technology application areas, thereby reducing uncertainties related to emerging convergent businesses. Additionally, the study underscores the synergistic strategy of combining innovation with productivity. Within the DTC business context, integrating productivity with technological innovation not only enhances cost flexibility but also improves problem-solution matching, ultimately amplifying synergistic benefits.

To the best of our knowledge, this is the first study to apply a digital technology co-occurrence network to unveil nuanced relationships in “DTC – finance performance” within the manufacturing sector. It challenges conventional thinking regarding the common positive effect of digital innovation and technological convergence. This study provides a comprehensive analysis of DTC, financial performance, productivity and technological innovation dynamics, as well as offers managerial implications for managers and policymakers.

• (1)

  We quantify manufacturing firm-level DTC through patent network analysis and find consistent increases over time.

• (2)

  A significant U-shaped relationship between DTC and financial performance, being negative at lower levels and positive at higher levels.

• (3)

  The joint effect of firms’ productivity and technological innovation reinforces this relationship by distributing costs and enhancing synergistic benefits.

• (4)

  We challenge existing literature by uncovering a complex relationship in “DTC – finance performance”, contrary to popular belief of a monotonic effect of digital innovation or technological convergence.

We quantify manufacturing firm-level DTC through patent network analysis and find consistent increases over time.

A significant U-shaped relationship between DTC and financial performance, being negative at lower levels and positive at higher levels.

The joint effect of firms’ productivity and technological innovation reinforces this relationship by distributing costs and enhancing synergistic benefits.

We challenge existing literature by uncovering a complex relationship in “DTC – finance performance”, contrary to popular belief of a monotonic effect of digital innovation or technological convergence.