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Breakthrough technological innovation is of vital significance for firms to acquire and maintain sustainable competitive advantages. The construction of an innovation ecosystem and the interaction with heterogeneous participants have emerged as a new dominant model for driving sustained breakthrough technological innovation in firms. This study aims to explore the effects of collaborative modes within the innovation ecosystem on firms’ breakthrough technological innovation and the ecological legitimacy mechanisms involved.

The research employs data from 212 innovative firms and conducts empirical research using a two-stage structural equation modeling (SEM) and artificial neural network (ANN) analysis.

The results indicate that firm-firm collaboration (FF), firm-user collaboration (FU), firm-government collaboration (FG), firm-university-institute collaboration (FUI) and firm-intermediary collaboration (FI) all have significant positive effects on breakthrough technological innovation (BTI), with FU being particularly crucial. Furthermore, the results confirm the positive moderating effects of ecological legitimacy (EL) on the relationships between FF and BTI, as well as between FU and BTI. Conversely, EL has a negative moderating effect on the relationship between FUI and BTI, as well as between FI and breakthrough technological innovation. Additionally, EL does not have a significant influence on the relationship between FG and BTI.

Through resource dependence theory (RDT), this study unveils the black box of how collaboration modes within innovation ecosystems impact breakthrough technological innovation. By introducing ecological legitimacy as a contextual factor, a new research perspective is provided for collaboration innovation within innovation ecosystems. The study employs a combination of SEM and ANN for modeling, complementing nonlinear relationships and obtaining robust results in complex mechanisms.

To enhance the understanding of the antecedents of students' career adaptability, this study employs the crossover model to explore the potential transfer of career adaptability from headteachers to students and the underlying mechanisms involved.

This study examined the proposed moderated mediation model using matched survey data collected from 37 headteachers and 1,598 students in Chinese higher vocational colleges.

Headteachers’ career adaptability is positively related to students’ career adaptability via students’ psychological capital. An increased frequency of headteacher–student interactions strengthened the indirect relationship between headteachers' career adaptability and students' career adaptability.

The findings suggest that, under certain conditions, headteachers’ career adaptability could be transferred to students via students’ psychological capital.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

With the continuous deepening of China's mixed-ownership reform, the participants in the reform have gradually expanded from state-owned enterprises to private enterprises. Whether state-owned equity participation in private enterprises can facilitate the development of environmental, social and governance (ESG) performance in private enterprises is a question that needs urgent examination. This study aims to investigate the impact of state-owned equity participation on the ESG performance of private enterprises.

Using Chinese listed companies as the research sample, this study uses econometric methods such as multiple regression to analyze the relationship between state-owned equity and the ESG performance of private enterprises. Additionally, it explores the underlying mechanisms and influencing factors of this relationship.

There is a significant inverted U-shaped relationship between state-owned equity and the ESG performance of private enterprises. Mechanism analysis reveals that resource effects and governance effects play a mediating role in this nonlinear relationship. Furthermore, the authors find that environmental regulation and managers' attention to the environment positively moderate the relationship between state-owned equity participation and ESG performance.

A reasonable equity structure is crucial for enhancing corporate ESG performance. Moderate state-owned equity participation helps to leverage resource integration and governance advantages, which will assist private enterprises in maximizing ESG performance and achieving sustainable development.

In advancing the process of mixed-ownership reform, the government should maintain an appropriate proportion of state-owned equity to avoid excessive intervention in enterprise decision-making. At the same time, it should ensure that enterprises can genuinely undertake their social and environmental responsibilities while pursuing economic benefits. This is of great significance for promoting sustainable economic and social development.

This study integrates state-owned equity, ESG and nonlinear relationships into a single research framework. It explores the internal mechanisms and influencing factors of their relationship, overcoming the limitations of previous studies and provides a new perspective for understanding the impact of state-owned equity on corporate ESG performance.

This paper aims to explore the role of blockchain (BCT) and Artificial Intelligence (AI) technologies in enhancing and incentivizing environmentally responsible, socially inclusive and economically viable tourism practices within the hospitality and tourism (H&T) industry.

This study is based on a critical reflection research approach that enables a synthesis of information derived from existing literature's insights and the authors' experiences and observations. By examining frameworks and theories in the literature, critical reflection also helps develop a more comprehensive understanding of the topic.

This study portrays how BCT could be used to track the sustainability credentials of tourism providers and how AI can optimize energy usage in hotels. This study depicts how adopting technology-driven sustainable practices in the H&T industry can increase profitability, improve reputation, compliance with regulations, efficiency and a better guest experience.

The study suggests targeted actions and policy frameworks that can be tailored to different stakeholder groups (hospitality businesses, policymakers and tourists) to overcome barriers and maximize the positive societal and environmental impacts of adopting BCT and AI for sustainable tourism.

The originality of this study lies in its ability to offer new perspectives and novel recommendations on the diverse uses of AI and BCT in the context of sustainable tourism. Furthermore, the study provides strategic and policy elements (Targeted actions and policy frameworks) for stakeholders to integrate sustainable tourism practices using BCT and AI successfully. This study differs from earlier review studies that primarily focused on adopting emerging technologies and ignoring the sustainability angle in the use of technology.

This paper aims to investigate how the technical logics of a World Bank-led performance management reform interacted with the social, political and historical logics within a developing country (DC) regulatory organisation. The institutional environment both within and outside the organisation was considered to understand the performance management reform experience.

An interview-based, longitudinal, qualitative case study approach was used to locate accounting in its technical, social and political space. A large regulatory organisation in Bangladesh was investigated as a case study to reveal how traditional organisational practices and public sector norms mediated a performance management reform. Informed by the institutional logics (IL) and economies of worth perspectives, interviews were used to locate IL at macro-level and associated organisational actors’ strategic responses that ultimately shaped the implementation of a performance management system (PMS).

This paper reveals how accounting, as a social and political practice, influences accountability reform within a regulatory organisation. It provides an account of both the processes and resultant practices of an accounting reform initiative. While a consultative and transparent performance management process was intended to enhance accountability, it challenged the traditional organisational authority structure and culture. The new PMS retained, modified and adjusted a number of its characteristics over time. These adjustments reflected an amalgamation of the influence of institutional pressures from powerful constituents and the ability of the local agents (managers) in negotiating and mediating the institutionalisation of a new PMS.

The findings of this paper carry major implications for policy makers, particularly with respect to the design of future reform programs on PMS.

This paper offers a theoretical mapping of IL and its organisation-level interpretations and practices. Thus, the authors locate power and influence at field and firm levels. The findings of this study reflect historical, political and cultural backgrounds of the case study organisation and how these contextual forces were active in shaping the meaning of reform logics. Though the institutional environment and agents were unique to the case study organisation, this research offers a “process generalisation” that reveals how a best practice PMS was translated and transformed by the traditional organisational practices in a DC regulatory context.

Against the backdrop of the global reshaping of supply chains, supply chain ecosystems have emerged as a critical force in ensuring the high-quality development of enterprises and fostering stable economic growth. However, a systematic theoretical understanding of how to construct these supply chain ecosystems remains nascent. This study aims to explore the mechanism of the process of building supply chain ecosystems between digital innovation platform enterprises and digital trading platform enterprises from the perspective of dynamic capabilities.

An explanatory case study is conducted based on a theoretical framework grounded on dynamic capabilities view. Two preeminent digital platform enterprises in China (Haier and JD.com) are studied. The authors primarily conducted this research by collecting a large volume of these Chinese public materials.

First, the construction processes of supply chain ecosystems in both digital platform enterprises can be delineated into three stages: embryonic, development and maturity. Second, digital innovation platform enterprises’ construction process is primarily influenced by factors such as production and operational collaboration, consumer demand and research and development. This influence is exerted through interactions on digital platforms and within sub-ecosystems. Meanwhile, digital trading platform enterprises’ construction process is influenced by factors such as infrastructure development, consumer demand and financial support, driving dynamic capability formation through multi-party cooperation and ecological interactions based on conceptual identity.

In the establishment of supply chain ecosystems, digital platform enterprises should prioritize the cultivation of opportunity expansion, resource integration and symbiotic relationship capabilities. Furthermore, this study shows that digital platform enterprises need to actively adjust their interactive relationships with cooperating enterprises based on changes in the market, industry, policies and their own developmental stages.

This study addresses prior deficiencies in understanding the comprehensive construction of supply chain ecosystems and provides significant insights to enhance the theoretical foundation of supply chain ecosystem studies. Additionally, this paper uncovers the dynamic capability development behaviors and contextual features inherent in the construction process of supply chain ecosystems by digital platform enterprises.

Text classification is a widely accepted and adopted technique in organizations to mine and analyze unstructured and semi-structured data. With advancement of technological computing, deep learning has become more popular among academicians and professionals to perform mining and analytical operations. In this work, the authors study the research carried out in field of text classification using deep learning techniques to identify gaps and opportunities for doing research.

The authors adopted bibliometric-based approach in conjunction with visualization techniques to uncover new insights and findings. The authors collected data of two decades from Scopus global database to perform this study. The authors discuss business applications of deep learning techniques for text classification.

The study provides overview of various publication sources in field of text classification and deep learning together. The study also presents list of prominent authors and their countries working in this field. The authors also presented list of most cited articles based on citations and country of research. Various visualization techniques such as word cloud, network diagram and thematic map were used to identify collaboration network.

The study performed in this paper helped to understand research gaps that is original contribution to body of literature. To best of the authors' knowledge, in-depth study in the field of text classification and deep learning has not been performed in detail. The study provides high value to scholars and professionals by providing them opportunities of research in this area.

There are various uncertain and nonlinear problems in hydraulic legged robot systems, including parameter uncertainty, unmodeled dynamics and external disturbances. This study aims to eliminate uncertainties and improve the foot trajectory tracking control performance of hydraulic legged robots, a high-performance foot trajectory tracking control method based on fixed-time disturbance observers for hydraulic legged robots is proposed.

First, the robot leg mechanical system model and hydraulic system model of the hydraulic legged robot are established. Subsequently, two fixed-time disturbance observers are designed to address the unmatched lumped uncertainty and match lumped uncertainty in the system. Finally, the lumped uncertainties are compensated in the controller design, and the designed motion controller also achieves fixed-time stability.

Through simulation and experiments, it can be found that the proposed tracking control method based on fixed-time observers has better tracking control performance. The effectiveness and superiority of the proposed method have been verified.

Both the disturbance observers and the controller achieve fixed-time stability, effectively improving the performance of foot trajectory tracking control for hydraulic legged robots.

This study aims to investigate the causes of leakage in radial oil seals under dynamic eccentricity, elucidate the influence of operating parameters on leakage failure and develop methods for predicting and preventing such leakage.

Based on the principle of cam motion and considering viscoelasticity, develops a motion model of the compression and release of the shaft seal and proposes a method to determine its failure. In addition, this study quantifies the leakage gap and formulates a quantitative calculation model to accurately determine the location and shape parameters of the leakage gap.

Leakage gaps predominantly occur during the release phase of the shaft seal. Their presence can be identified by comparing the descending times of the seal and the shaft during this phase. An increase in rotation speed and eccentricity heightens the likelihood of gap formation, with both the dimensions and leakage rate of the gap increasing as these factors escalate. Eccentricity, in particular, has a more pronounced effect on gap formation.

This study clarifies the failure mechanisms of radial oil seals under dynamic eccentricity and introduces a criterion for identifying leakage gaps, providing valuable theoretical guidance for the design and optimization of radial oil seals.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0192/.