Tachia Chin, Yi Shi, Rosa Palladino and Francesca Faggioni
Cross-cultural cognitive paradoxes have frequently broken the existing boundaries of knowledge and stimulated demands for knowledge creation (KC), and such paradoxes have…
Abstract
Purpose
Cross-cultural cognitive paradoxes have frequently broken the existing boundaries of knowledge and stimulated demands for knowledge creation (KC), and such paradoxes have triggered and will continue to trigger novel risks in the context of international business (IB). Given the nascency of relevant issues, this study aims to develop a more comprehensive understanding of KC across cultures by proposing a Yin-Yang dialectical systems theory of KC as micro-foundation to more systematically frame the risk/paradox-resolving mechanism elicited by cultural collisions.
Design/methodology/approach
This paper is conceptual in nature. The authors first critically review the literature to lay a broad theoretical foundation. Integrating the philosophy- and praxis-based views, the authors reposition knowledge as a Yin-Yang dialectical system of knowing, with yin representing the tacit while yang represents the explicit. Next, the authors justify the underling logic of realising KC through a contradiction-resolving process. On this basis, the authors draw upon the Yijing’s Later Heaven Sequence (LHS) as the source domain of a heuristic metaphor to reconceptualise KC as a dynamic capability in the IB context.
Findings
Using the LHS paradigm to metaphorically map the intricate patterns of interaction and interconnectivity among the involved individuals, organisations and all related stakeholders, this research identifies and theorises the overall dynamic capability of KC in the IB context, which comprises five sets of processes: contradiction, conflict, communication, compromise and conversion.
Practical implications
This research highlights that KC is simultaneously activated and constrained by human actions as well as by the socially constructed context in which it emerges, which helps individuals, organisations and policy makers more clearly frame the novel risks induced by cross-cultural cognitive conflicts in the IB context.
Originality/value
The authors synthesise Yin-Yang dialectics with the approach of collective phronesis, proposing a novel, praxis-oriented Yin-Yang dialectical systems theory of KC. It provides a deeper understanding of the epistemological paradox inherent in all knowledge, thus enabling KC to be rationalised by a sounder logical reasoning. By fusing the macro and micro perspectives on KC, the authors also enrich existing theory and future theory building in the domain of knowledge management.
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Inyoung Jung, Jiachen Li, Seongseop (Sam) Kim and Heesup Han
The outdoor event market was devastated during the COVID-19 pandemic because of social distancing measures. Therefore, this study aimed to explore stereotyped tendencies and…
Abstract
Purpose
The outdoor event market was devastated during the COVID-19 pandemic because of social distancing measures. Therefore, this study aimed to explore stereotyped tendencies and behavioral intentions associated with the prosocial and sustainable practices of outdoor event participants to assess shifts in industry paradigms.
Design/methodology/approach
This study adopted structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to relatively examine sequential and combined effects of cognitive (knowledge of COVID-19, awareness of consequences, ascribed responsibility and perceived threat of COVID-19), affective (positive and negative anticipated emotions) and normative drivers (social and moral norms) on intention to practice social distancing requirements. The impact of cultural differences was further explored by comparing attendees from China and USA.
Findings
The SEM results showed that most cognitive drivers significantly affected affective drivers and normative drivers, leading to the intention to practice social distancing requirements. In addition, China and the USA showed significant differences on six paths including the path from moral norm to intention to practice social distancing requirements. Further, fsQCA results revealed the important combination of the factors that affects social distancing intention.
Research limitations/implications
This study provides meaningful theoretical and practical implications for outdoor events scholars and managers. The research suggests a changing direction in event studies and shares ideas on how to manage and make outdoor events a new success after the pandemic.
Originality/value
This is the first study to adopt a mixed method of SEM and fsQCA attempt to explore the driving forces of outdoor participants’ pro-social behavior from cognitive, affective and normative perspectives.
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Although artificial intelligence (AI) is an essential component of hospitality in the technological empowerment era, AI’s effectiveness as an attraction in this context remains…
Abstract
Purpose
Although artificial intelligence (AI) is an essential component of hospitality in the technological empowerment era, AI’s effectiveness as an attraction in this context remains unclear. Grounded in Herzberg’s motivation theory and complexity theory, this study aims to explore configurational paths whereby combinations of qualities lead to success for different types of AI-themed hotels.
Design/methodology/approach
This study innovatively blends topic modeling and fuzzy-set qualitative comparative analysis (fsQCA) to investigate configurational paths whereby combined qualities produce positive guest evaluations of 12 AI-themed hotels as evidenced by 7,431 customer reviews.
Findings
The results indicate that AI could serve as a “theme” to attract customers under certain circumstances. First, “attractive” and “must-be” qualities are first identified for different types of AI-themed hotels. Furthermore, 6, 15 and 15 configurational paths inspiring favorable guest evaluations of luxury-independent, budget-independent and chain AI-themed hotels, respectively. Technology-related qualities are found to be especially attractive for luxury-independent AI-themed hotels, whereas the role of technology is minimal for budget AI-themed hotels. The impact of technology is salient for chain AI-themed hotels when combined with other factors. In addition, the effect of price differs among the configurational paths for the three hotel types.
Research limitations/implications
This study expands the understanding of AI applications within the hospitality context by exploring the role of AI in AI-themed hotels and comparing its effectiveness in attracting customers across various hotel types. It also provides operational strategies for adopting AI for different types of hotels and for other hospitality and tourism sectors.
Originality/value
This study represents an early attempt to integrate topic modeling and fsQCA to clarify customers’ perceptions of AI-themed hotels and the combined impacts of various qualities. The findings expand on Kano’s model by classifying technology-related qualities into attractive qualities within AI-themed hotels.
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Abdulaziz Ahmad, Weidong Wang, Shi Qiu, Wenjuan Wang, Tian-Yi Wang, Bamaiyi Usman Aliyu, Ying Sun and Abubakar Sadiq Ismail
Unlike previous research that primarily utilized structural equation modelling (SEM) to evaluate safety hazards in subway projects, this research aims to utilize a hybrid approach…
Abstract
Purpose
Unlike previous research that primarily utilized structural equation modelling (SEM) to evaluate safety hazards in subway projects, this research aims to utilize a hybrid approach to investigate and scrutinize the key indicators of safety hazards leading to accidents, thereby hindering the progress of subway projects in China, taking into cognizance the multiple stakeholder’s perspective.
Design/methodology/approach
By administering a survey questionnaire to 373 highly involved stakeholders in subway projects spanning Changsha, Beijing and Qingdao, China, our approach incorporated a four-staged composite amalgamation of exploratory factor analysis (EFA), confirmatory factor analysis (CFA), covariance-based structural equation modelling (CB-SEM) and artificial neural network (ANN) to develop an optimized model that determines the causal relationships and interactions among safety hazards in subway construction projects.
Findings
The optimized model delineated the influence of individual safety hazards on subway projects. The feasibility and applicability of the model developed was demonstrated on an actual subway project under construction in Changsha city. The outcomes revealed that the progress of subway projects is significantly influenced by risks associated with project management, environmental factors, subterranean conditions and technical hazards. In contrast, risks related to construction and human factors did not exhibit a significant impact on subway construction progress.
Research limitations/implications
While our study provides valuable insights, it is important to acknowledge the limitation of relying on theoretical approaches without empirical validation from experiments or the field. In future research, we plan to address this limitation by assessing the SEM using empirical data. This will involve a comprehensive comparison of outcomes derived from CB-SEM with those obtained through SEM-ANN methods. Such an empirical validation process is crucial for enhancing the overall efficiency and robustness of the proposed methodologies.
Originality/value
The established hybrid model revealed complex non-linear connections among indicators in the intricate project, enabling the recognition of primary hazards and offering direction to improve management of safety in the construction of subways.
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Yingnan Shi and Chao Ma
This study aims to enhance the effectiveness of knowledge markets and overall knowledge management (KM) practices within organisations. By addressing the challenge of internal…
Abstract
Purpose
This study aims to enhance the effectiveness of knowledge markets and overall knowledge management (KM) practices within organisations. By addressing the challenge of internal knowledge stickiness, it seeks to demonstrate how machine learning and AI approaches, specifically a text-based AI method for personality assessment and regression trees for behavioural analysis, can automate and personalise knowledge market incentivisation mechanisms.
Design/methodology/approach
The research employs a novel approach by integrating machine learning methodologies to overcome the limitations of traditional statistical methods. A natural language processing (NLP)-based AI tool is used to assess employees’ personalities, and regression tree analysis is applied to predict and categorise behavioural patterns in knowledge-sharing contexts. This approach is designed to capture the complex interplay between individual personality traits and environmental factors, which traditional methods often fail to adequately address.
Findings
Cognitive style was confirmed as a key predictor of knowledge-sharing, with extrinsic motivators outweighing intrinsic ones in market-based platforms. These findings underscore the significance of diverse combinations of environmental and individual factors in promoting knowledge sharing, offering key insights that can inform the automatic design of personalised interventions for community managers of such platforms.
Originality/value
This research stands out as it is the first to empirically explore the interaction between the individual and the environment in shaping actual knowledge-sharing behaviours, using advanced methodologies. The increased automation in the process extends the practical contribution of this study, enabling a more efficient, automated assessment process, and thus making critical theoretical and practical advancements in understanding and enhancing knowledge-sharing behaviours.
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Yuanyuan Wu, Eric W.T. Ngai and Pengkun Wu
This study aims to investigate the impact of news quality on users’ risk perceptions toward online news and its subsequent influence on perceived believability and user engagement…
Abstract
Purpose
This study aims to investigate the impact of news quality on users’ risk perceptions toward online news and its subsequent influence on perceived believability and user engagement in sharing news. Additionally, we explore the moderating effects of fake news awareness and social tie variety.
Design/methodology/approach
Drawing upon the social amplification of risk framework, this study investigates the relationship between news quality and users’ news-sharing behaviors, along with its underlying mechanism. An online questionnaire involving 399 eligible participants was employed for hypotheses testing, and the structural equation model served as the main analytical method.
Findings
The influence of news quality on users’ news-sharing behavior is sequentially mediated by risk perception and perceived believability. Individuals with a heightened awareness of fake news or a diverse social tie are more inclined to perceive greater risks associated with news-sharing behavior and question news authenticity.
Originality/value
This study contributes to the existing literature on users’ news-sharing behaviors by examining the influence of risk perception on the relationship between news quality, perceived believability and users’ news-sharing behavior. Additionally, it explores the moderating effects of fake news awareness and social tie variety. Our findings offer valuable insights into comprehending user inclinations towards news sharing and mitigating the dissemination of fake news.
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Xiubin Gu, Yi Qu and Zhengkui Lin
The purpose of this study is to investigate the pricing strategies for knowledge payment products, taking into account the quality level of pirated knowledge products, in the…
Abstract
Purpose
The purpose of this study is to investigate the pricing strategies for knowledge payment products, taking into account the quality level of pirated knowledge products, in the context of platform copyright supervision.
Design/methodology/approach
This study abstracts the knowledge payment transaction process and aims to maximize producer's revenue by constructing a pricing model for knowledge payment products. It discusses pricing strategies for knowledge payment products under two scenarios: traditional supervision and blockchain supervision. The analysis explores the impact of pirated knowledge products quality level and blockchain technology on pricing strategies and consumer surplus, while providing threshold conditions for effective strategies.
Findings
Deploying blockchain technology in platform operations can significantly reduce costs and increase efficiency. In both scenarios, knowledge producer needs to balance factors such as the quality of pirated knowledge products, the supervision level of platform, and consumer surplus to dynamically adjust pricing strategies in order to maximize his own revenue.
Originality/value
This study enriches the literature on the pricing models of knowledge payment products and has practical significance in guiding knowledge producer to develop effective pricing strategies under copyright supervision.
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Over the past 20 years, entrepreneurial ecosystems (EEs) have emerged as a significant research field, inspiring several scholars to provide valuable contributions. The chapter…
Abstract
Over the past 20 years, entrepreneurial ecosystems (EEs) have emerged as a significant research field, inspiring several scholars to provide valuable contributions. The chapter aims to map the current state of literature by highlighting the most prominent research strands and the main theoretical lenses employed in the research field. By carrying out a systematic literature review and bibliometric analysis, the study examines articles published over a period of 27 years. The time frame from 1996 to 2023 offers an extensive outlook of the field’s evolution and current trends, resulting in the identification of five research strands and different future research avenues. From the analysis of prior research works, this study provides an in-depth examination of the complex nature of EEs. The results hold theoretical and practical implications. From the scholars’ point of view, they offer future research directions to move the current level of knowledge forward. From the entrepreneurs’ perspective, they provide valuable insights to address ongoing challenges and catch new opportunities within the dynamic panorama of EEs. Therefore, the insights are poised to drive future research, inform policymakers, and enhance business strategies aimed at fostering resilient EEs. In other words, the purpose is to provide readers with a well-rounded understanding over the state of the literature on EEs and the research strands that deserve further exploration.
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Sui-Xin Fan, Xiaoni Yan, Yan Cao, Yi cong Liu, Sheng Wei Cao, Jun-Hu Meng and Junde Guo
Nano graphitic-carbon nitride (g-C3N4) is an emerging lubrication technology with excellent performance and significant potential for future applications. This study aims to…
Abstract
Purpose
Nano graphitic-carbon nitride (g-C3N4) is an emerging lubrication technology with excellent performance and significant potential for future applications. This study aims to investigate the effect of nano g-C3N4 as a lubricant additive on the wear performance of bearing steel disk.
Design/methodology/approach
Various mass fractions of g-C3N4 were introduced into the base oil. Combining tribological testing, rheological testing and surface analysis methods, the anti-wear properties and lubrication mechanisms were analyzed.
Findings
Transmission electron microscopy images revealed that the size of the nanoparticles of g-C3N4 ranges from 10 to 100 nm. Phase analysis of the g-C3N4 sample was conducted using X-ray diffraction. Further, 1.0% mass fraction of g-C3N4 in the base oil provides excellent anti-wear and friction-reducing performance. Compared to the base oil alone, it reduces the average friction coefficient by 63.8% and decreases the wear rate by 43.1%, significantly reducing the depth and width of the wear scar. Energy-dispersive X-ray spectroscopy and scanning electron microscope analysis revealed that the oil sample containing nano g-C3N4 can form a lubricating film on the sliding surface of bearing steel after wear, which enhances the lubricating properties of the base oil.
Originality/value
The synergistic effect of the base oil and nanoparticles reduces friction and wear and is expected to extend the service life of bearing steel. These findings suggest that incorporating nano g-C3N4 as a lubricant additive offers significant potential for improving the performance of mechanical components.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2024-0456/
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Irem Kose and Gulden Gumusburun Ayalp
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.”
Originality/value
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.