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This study aims to propose a calibration method to enhance the positioning accuracy in dual-robot collaborative operations, aiming to address the challenge of drilling hole spacing errors in spacecraft core cabin brackets that require an accuracy of less than 0.5 mm.

Initially, the cooperative error of dual robots is defined. Subsequently, an integrated model is constructed that encompasses the kinematic model errors of the dual robots, as well as the establishment errors of the base and tool frames. A calibration method for optimizing the cooperative accuracy of dual robots is proposed.

The application of the proposed method satisfies the collaborative drilling requirements for the spacecraft core cabin. The average cooperative positioning error of the dual robots was reduced from 0.507 to 0.156 mm, with the maximum value and standard deviation decreasing from 1.020 and 0.202 mm to 0.603 and 0.097 mm, respectively. Drilling experiments conducted on a core cabin simulator demonstrated that after calibration, the maximum hole spacing error was reduced from 1.219 to 0.403 mm, with all spacing errors falling below the 0.5 mm threshold, thus meeting the requirements.

This paper addresses the drilling accuracy requirements for spacecraft core cabins by using a calibration method to reduce the cooperative error of dual robots. The algorithm has been validated through experiments using ER 220 robots, confirming its effectiveness in fulfilling the drilling task requirements.

This study aims to explore how digital intermediaries interact with individual intermediaries to assist corporate social entrepreneurs (CSEs) in building inclusive markets. In response to the challenge of social exclusion, CSEs craft strategies by leveraging their existing capabilities and resources. However, when it comes to building inclusive markets, CSEs face the liabilities of institutional voids and must rely on intermediaries to establish efficient trading channels. This study focuses on the process by which CSEs firstly construct technology affordances of digital intermediaries, and then actualise affordances through the interactions of digital and individual intermediaries in overcoming technology constraints and triggering involvement cycle in the context of rural e-commerce.

Using a single-case study design, the authors unfolded the process of a rural e-commerce project conducted by a Chinese e-commerce giant. The authors interviewed 35 informants from 2016 to 2018; each interview lasted 45–90 minutes. In addition, archival and observational data were collected for triangulation. After thorough examination, the data was coded and a grounded framework was developed.

This study provides a detailed process of how the interactions of digital and individual intermediaries facilitate CSEs in building inclusive markets through a rural e-commerce project. The authors find that CSEs generate corporate strategy in building inclusive markets by constructing three affordances of digital intermediaries: equality facilitator, harmony maintainer and stickiness creator. Subsequently, in actualising these affordances, CSEs fill institutional voids through the interactions between digital and individual intermediaries. Specifically, the technology constraints of digital intermediaries trigger a four-phase cycle involving individual intermediaries: identification, activation, coaching and empowerment. This involvement cycle effectively overcomes the technology constraints of digital intermediaries. The interactions between digital and individual intermediaries facilitate the dual goals achievement of CSEs and finally restructure the market architecture.

Firstly, this study stands among the pioneering research endeavours exploring the interactions between digital and individual intermediaries in facilitating CSEs to develop inclusive markets. Diverging from existing literature, which often enhances or refines the role of a single intermediary in filling institutional voids, the authors posit that digital and individual intermediaries dynamically complement each other in actualising affordances. This complementary dynamic stands as a substitute for the evolution of a single intermediary in building inclusive markets. Secondly, by zooming out the process of constructing and actualising affordances, this study contributes to the literature on technology affordance in both contextual and relational aspects. Contextually, the authors identify three tenets of affordances generated by the corporate strategy of CSEs. Relationally, the authors argue that affordances can be predeveloped by CSEs and then fully actualised through interactions between digital and individual intermediaries, challenging the conventional view that sees affordances as a relational concept solely determined by users and artefacts during the actualisation process. Thirdly, this study makes a contribution by untangling the process of CSEs in reshaping the market context to make it more inclusive. Departing from the conventional focus on the role of institutional intermediaries for CSEs in filling institutional voids, the authors explore how CSEs develop digital intermediaries and induce their interactions with individual intermediaries to restructure market architecture during the process of constructing and actualising affordances. In conclusion, this study adds valuable insights to the literature on institutional voids, technology affordance and CSE in building inclusive markets.

In 2012, Vivian assumed the role of General Manager at the eBay China Development Center of Excellence (CCOE) with the objective of steering the growth of CCOE by initiating a cultural transformation plan. Vivian encountered numerous challenges in reshaping the organization as a new and female leader, especially facing her diminished authority when headquarters decided to realign reporting lines. This case, which illustrates real-world business scenarios, is designed to empower students to understand practices of organization transformation and leadership.

Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). However, the phases and periodicity of drought changes in the ESAC remain largely unknown. Thus, this paper aims to identify the periodic characteristics of meteorological drought changes.

The potential evapotranspiration was calculated using the Penman–Monteith formula recommended by the Food and Agriculture Organization of the United Nations, whereas the standardized precipitation evaporation index (SPEI) of drought was simulated by coupling precipitation data. Subsequently, the Bernaola-Galvan segmentation algorithm was proposed to divide the periods of drought change and the newly developed extreme-point symmetric mode decomposition to analyze the periodic drought patterns.

The findings reveal a significant increase in SPEI in the ESAC, with the rate of decline in drought events higher in the ESAC than in China, indicating a more pronounced wetting trend in the study area. Spatially, the northeast region showed an evident drying trend, whereas the southwest region showed a wetting trend. Two abrupt changes in the drought pattern were observed during the study period, namely, in 1965 and 1983. The spatial instability of moderate or severe drought frequency and intensity on a seasonal scale was more consistent during 1966–1983 and 1984–2018, compared to 1961–1965. Drought variation was predominantly influenced by interannual oscillations, with the periods of the components of intrinsic mode functions 1 (IMF1) and 2 (IMF2) being 3.1 and 7.3 years, respectively. Their cumulative variance contribution rate reached 70.22%.

The trend decomposition and periods of droughts in the study area were analyzed, which may provide an important scientific reference for water resource management and agricultural production activities in the ESAC. However, several problems remain unaddressed. First, the SPEI considers only precipitation and evapotranspiration, making it extremely sensitive to temperature increases. It also ignores the nonstationary nature of the hydrometeorological water process; therefore, it is prone to bias in drought detection and may overestimate the intensity and duration of droughts. Therefore, further studies on the application and comparison of various drought indices should be conducted to develop a more effective meteorological drought index. Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. Evapotranspiration is calculated by various methods that provide different results. Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. Hargreaves, Thornthwaite and Penman–Monteith) and their application scenarios. Third, this study focused on the temporal and spatial evolution and periodic characteristics of droughts, without considering the driving mechanisms behind them and their impact on the ecosystem. In future, it will be necessary to focus on a sensitivity analysis of drought indices with regard to climate change. Finally, although this study calculated the SPEI using meteorological data provided by China’s high-density observatory network, deviations and uncertainties were inevitable in the point-to-grid spatialization process. This shortcoming may be avoided by using satellite remote sensing data with high spatiotemporal resolution in the future, which can allow pixel-scale monitoring and simulation of meteorological drought evolution.

Under the background of continuous global warming, the climate in arid and semiarid areas of China has shown a trend of warming and wetting. It means that the plant environment in this region is getting better. In the future, the project of afforestation and returning farmland to forest and grassland in this region can increase the planting proportion of water-loving tree species to obtain better ecological benefits. Meanwhile, this study found that in the relatively water-scarce regions of China, drought duration was dominated by interannual oscillations (3.1a and 7.3a). This suggests that governments and nongovernmental organizations in the region should pay attention to the short drought period in the ESAC when they carry out ecological restoration and protection projects such as the construction of forest reserves and high-quality farmland.

The findings enhance the understanding of the phasic and periodic characteristics of drought changes in the ESAC. Future studies on the stress effects of drought on crop yield may consider these effects to better reflect the agricultural response to meteorological drought and thus effectively improve the tolerance of agricultural activities to drought events.

This research aims to examine the link between distributed leadership and team ambidexterity and the sequential mediation of team climate innovation and knowledge management in this relationship.

This study draws on a sample of 546 knowledge workers involved within 157 service research and development (R&D) teams of knowledge-intensive firms (KIFs) and uses partial least squares-structural equation modelling (PLS-SEM) through SMART PLS 4 to analyse the data collected.

Findings reveal that distributed leadership has a significant direct impact on team ambidexterity. Besides, they indicate that team climate innovation and knowledge management in teams mediate this link. Results also highlight the sequential mediation of team climate innovation and knowledge management in teams, linking distributed leadership to team ambidexterity.

This study explores the relationship between distributed leadership and ambidexterity at the team level and proposes a sequential mediation model linking these variables through team climate innovation and knowledge management in teams. It offers practical insights for KIFs’ managers on the importance of using a distributed leadership approach and building a team climate innovation to motivate R&D teams, encourage dynamic participation in knowledge management practices and cultivate both exploitative and exploratory learning activities.

This study aims to examine the relationship between managerial ability and innovation efficiency, the mediating effect of digital transformation and the moderating effect of internal control.

This study collected A-share manufacturing listed companies in China from 2008 to 2019 and analyzed the data by means of multiple regression analysis, mediating effect test, moderating effect test and heterogeneity test. Finally, the authors conducted robustness test by remeasuring key variables and adding control variables.

The empirical results show that the higher managerial ability can improve innovation efficiency, internal control has a positive moderating effect and digital transformation plays a partial mediating effect on the relationship between managerial ability and innovation efficiency. Specially, it is found that the mediating effect of digital transformation is not significant in non-state-owned firms.

This study suggests that it is necessary to focus on the managerial ability in terms of both cultivation and supervision, to further deepen the digital transformation from the aspects of firms, government and society, especially to support the digital transformation of non-state-owned firms, and to make efforts to improve the corporate governance mechanism and internal control system, so as to better comprehensively realize the improvement of enterprise innovation efficiency.

Based on the mediating effect analysis of digital transformation and the moderating effect analysis of internal control, this study explores the role of managerial ability on innovation efficiency from a new perspective, expanding the related theoretical framework and research boundaries.

This paper aims to regulate the oil retention rate and tribological properties of pored polytetrafluoroethylene (PPTFE) using polyvinyl alcohol (PVA)-based oil gel.

PPTFE was first prepared by using citric acid (CA) as an efficient pore-making agent. Subsequently, PVA and chitosan solution was introduced into the pores and experienced a freezing-thawing process, forming PVA-based gels inside the pores. Then, the PPTFE/PVA composite was impregnated with polyethylene glycol 200 (PEG200), yielding an oil-impregnated PPTFE/PVA/PEG200 composite.

It was found that the oil-impregnated PPTFE/PVA/PEG200 composite exhibited advanced tribological properties than neat PTFE with reductions of 53% and 70% in coefficient of friction and wear rate, respectively.

This study shows an efficient strategy to regulate the tribological property of PTFE using a PVA-based oil-containing gel.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2024-0432/

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

Live streaming e-commerce, which integrates real-time video interaction with online shopping, has quickly become a popular sales channel. It not only allows for immediate feedback but also builds a sense of trust and connection between streamers and consumers. Drawing on the elaboration likelihood model (ELM), we investigate how central and peripheral route factors affect consumers’ trust building and purchase intentions. Additionally, we identify consumer involvement as a key moderator affecting the relationship between central route factors and trust in product as well as the relationship between peripheral route factors and trust in streamer.

To test the research model, we collected data from 423 consumers on TaoBao Live.

The findings show that information completeness, accuracy and currency positively affect trust in the product, while perceived physical characteristic similarity, streamer humor attractiveness and passion attractiveness positively affect trust in the streamer. Trust in the streamer positively influences trust in the product, which subsequently impacts purchase intention. Moreover, involvement moderates the effects of information accuracy, currency, perceived physical characteristic similarity and passion attractiveness on trust.

First, we examine the direct influence of product- and streamer-related cues on consumer trust and purchase intention through distinct pathways. Second, we adopt ELM to explain the process of consumer trust building by investigating how central and peripheral route factors influence purchase intention through consumer trust in live streaming settings. Third, we incorporate involvement as a crucial moderator, shedding light on the boundary conditions of trust building in live streaming e-commerce.

The purpose of this study is to examine the impact of adopting artificial intelligence (AI) on the quality of corporate sustainability reporting. The role of sustainability committees, including specialist environmental, social and governance (ESG) committees, in moderating this dynamic is also examined.

Regression analysis is used to analyze the quality of ESG/sustainability disclosures of listed Chinese companies from 2015 to 2022. Robustness is ensured through fixed effects analysis, while endogeneity concerns are addressed using one-year lagged measures and the three-stage least squares (3SLS) approach. Sustainability committees are categorized based on their ESG specific focus areas, and aligned with the corresponding ESG disclosure pillars. In addition, for the governance pillar, the analysis is extended by segmenting the sample based on state ownership status. Stakeholder theory and the dynamic capability view are used to frame the analysis.

The results reveal that AI adoption enhances overall sustainability reporting quality and pillar-specific ESG disclosure quality. This positive effect is amplified by the presence of sustainability committees. Examining the heterogeneous impact of these committees revealed stronger associations between sustainability committee specialization and relevant ESG pillar disclosure quality (except for governance), suggesting that use of specialist committees can improve disclosure outcomes. Notably, within non-state-owned enterprises, governance-focused committees positively moderate the AI−disclosure relationship, highlighting a nuanced effect based on ownership structure.

The findings offer empirical support for companies to leverage AI in sustainability reporting. This study finds evidence to support the creation of sustainability committees, as a key corporate governance mechanism to drive corporate sustainability reporting. The use of specialist sustainability committees can drive improvements in disclosure quality relating to specific ESG pillars. The research indicates that disclosure over governance remains poor and will require additional regulatory effort to encourage entities to provide higher quality governance-related disclosures. In terms of ownership structure, the study found that non-state-owned enterprises are more efficient in using specialist sustainability committees to improve disclosure quality.

The findings highlight the potential of AI in supporting high-quality sustainability reporting and the strategic role of sustainability committees in this dynamic. The publication of high-quality sustainability reports is critical in meeting stakeholder demands for transparency and corporate accountability on sustainability.

The findings offer insights into AI’s role in supporting high-quality sustainability reporting. By examining the moderating effects of sustainability committees, the research goes beyond examining a general impact to exploring how corporate governance mechanisms impact this relationship. In addition, the unique data on Chinese companies highlights differences between state-owned and non-state-owned enterprises, with the latter exhibiting greater potential to leverage specialist sustainability committees for improving sustainability reporting.