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The loading mechanism of textures considering turbulence has not been fully covered. This paper aims to investigate the effect of turbulence on the textured loading capacity under water lubrication and to analyze the causes of the turbulence effect.

Computational fluid dynamic models with different textured shapes are established after validation. The transition shear stress transport (SST) model, which is suitable for predicting the transition process of fluid from laminar state to turbulent state, is adopted in the present study. To illustrate the effect of turbulence, the loading capacity of textures predicted by transition SST model and laminar model is compared.

The loading capacity is higher after considering turbulence because more lubricant enters into textures and the flow rate of lubricant to textured outlet increases. There exists an optimal textured depth ratio and density for loading capacity and the change of flow state would not affect the optimal values. The degree of fluid blockage at textured outlet has a dominant influence on loading capacity. As the textured shape changes to triangle or ellipse from rectangle, the vortices at the textured bottom move forward and the blockage at a textured outlet is enhanced, which makes loading capacity improved under the action of blocking effect.

The enhancement of the blocking effect is found to be crucial to the improvement of textured loading capacity after considering turbulence. Present research provides references to understand the loading mechanism of textures under turbulent conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2020-0149/

This paper aims to investigate the modification of surface of a copper alloy by friction stir surface processing (FSSP).

The metallographic condition of the surface modification was observed using microscopy. Electrochemical corrosion tests were carried out on the modified surface and the corroded surface was observed by scanning electron microscopy (SEM).

The test results showed that FSSP resulted in refinement of the surface grains of the copper alloy. The degree of refinement was increased with rotation speed and increased in the descending distance of the stirring tool. The corrosion resistance of the modified surface was superior to the base metal except for the surface generated by a rotation speed of 800 rpm and a descending distance 0.1 mm. For the surface modification of the rotation speed of 800 rpm, its corrosion resistance was lower than for the other two rotation speeds. When the rotation speed is specified, the corrosion resistance is improved with increased descending distance. When the descending distance is specified, the corrosion resistance is improved with the rotation speed.

In this study, it was confirmed that the corrosion resistance of the surface modification was best at the rotation speed 1200 rpm and descending distance 0.2 mm.

With the rapid advancement of artificial intelligence (AI) technology permeating various sectors, corporate management has increasingly directed their focus toward AI-driven innovation. Particularly, in response to escalating environmental standards, chief executive officers (CEOs) of manufacturing companies are turning to AI as a strategic tool to address challenges in green innovation. This paper aims to reveal the complex relationship between CEO AI orientation and green innovation through the attention-based view. Furthermore, it seeks to explore strategies to enhance corporate green innovation leveraging CEO AI orientation.

The paper uses computer-assisted text analysis to extract data from annual reports of listed Chinese manufacturing companies and assesses them using negative binomial regression.

The empirical findings indicate the inverted U-shaped relationship between CEO orientation and green innovation. Initial green innovation performance increases with CEO AI orientation, reaching a peak before declining. Moreover, as CEO AI orientation increases, companies with higher levels of human resource slack are likely to reach the peak of green innovation earlier.

Firstly, this paper introduces CEO AI orientation as a novel factor within the framework of the attention-based view for understanding green innovation. Secondly, the study investigates both the benefit effect and the cost effect (resource constraints) of CEO AI orientation on green innovation, examining the inverted U-shaped relationship between CEO orientation and green innovation. Thirdly, this paper explores the moderating effect of human resource slack on the relationship between CEO AI orientation and green innovation, setting the boundaries of CEO AI orientation’s impact on green innovation.

The purpose of this study is to address the low localization accuracy and frequent tracking failures of traditional visual SLAM methods in low-light and weak-texture situations, and we propose a mobile robot visual-inertial localization method based on the improved point-line features VINS-mono algorithm.

First, the line feature information is introduced into VINS-mono. Subsequently, the EDlines line feature extraction algorithm is optimized with a short line merging strategy and a dynamic length suppression strategy to reduce redundant short lines and fragmented segments. In the back-end sliding window optimization, line feature reprojection errors are incorporated, and Huber kernel functions are added to the inertial measurement unit residuals, point-line feature residuals and loop closure constraints to reduce the impact of outliers on the optimization results.

Comparison and verification experiments are carried out on the EuRoC MAV Data set and real weakly textured environment. In the real low-light and weak-texture scenarios, the improved mobile robot localization system achieves over 40% higher accuracy compared to VINS-mono.

The main contribution of this study is to propose a new visual-inertial SLAM method combining point-line features, which can achieve good localization effect in low-light and weak-texture scenes, with higher accuracy and robustness.

This study aims to present the critical role of knowledge management in digital entrepreneurship by reviewing the literature and proposing future research directions for digital entrepreneurship and knowledge management through an interdisciplinary framework.

This study uses the Derwent Data Analyzer to identify and visualise the extant studies on digital entrepreneurship. This study qualitatively analyses the hot topics and trends in digital entrepreneurship research to understand digital entrepreneurship from the knowledge management perspective.

The authors found two dominant trends in existing research: logical and development trend exploration at the theoretical background and empirical research at the practical dimension. To understand digital entrepreneurship from a knowledge management perspective, the authors summarised the theoretical logic and internal and external reasons why knowledge management is required in digital entrepreneurship. Moreover, the authors analysed the new features of digital entrepreneurship under five aspects: management concept, object, content, scope and focus. The authors concluded that existing research on integrating knowledge management and digital entrepreneurship is primarily conducted from three perspectives: technology, platform and ecosystem.

This study provides an in-depth analysis of digital entrepreneurship from a knowledge management perspective. The findings can further promote the theoretical research and practical development of digital entrepreneurship and knowledge management. This approach provides a new direction for interdisciplinary study and enriches entrepreneurship research. In addition, this study proposes a knowledge management framework for digital entrepreneurship research. The findings contribute to understanding the role and function of knowledge management in digital entrepreneurship.

This study aims to explore the patterns and transformational dynamics of the executive–interpreter network in the innovation processes of small- and medium-sized enterprises in hospitality.

Grounded in social network theory and adopting a case-based approach, this study features a multi-case design focusing on three Chinese boutique hotels. Data were collected through Web page and document reviews, participant observations and semistructured interviews.

Results capture how executive–interpreter network dynamics contribute to innovation in small- and medium-sized hotels. Key factors in social networks (e.g. size, scope and strength) shift throughout innovation. This study presents a design-driven approach as a means of innovation. Findings also delineate the network development conditions under which innovation dynamically occurs in boutique hotels.

Practical implications center on how network dynamics help small- and medium-sized hotels innovate more effectively. These insights can assist hotel operators and prospective market entrants in improving their hotels’ performance and competitiveness.

This study blends social network theory with a design-driven approach to explore innovation mechanisms in small- and medium-sized hotels. It offers empirical evidence for practitioners regarding design-driven innovation. Findings enrich the body of knowledge on both design-driven innovation theory and hospitality innovation.

The current study aims to identify work-related use of information and communication technologies after-hours (W_ICTs) from passive and active perspectives and examine mechanisms and different effects of information and communication technologies on employee innovation behavior.

Experience sampling method (ESM) was employed to capture dynamic within-person variance in daily-behaviors and daily-mood. In total, 92 employees completed an identical online survey each day for ten workdays.

The findings showed that the influence patterns and mechanisms of passive and active W_ICTs were utterly different. Passive W_ICTs was negatively associated with employee innovation behavior via emotional exhaustion, while active W_ICTs was positively associated with employee innovation behavior through perceived insider status. Furthermore, differential leadership significantly narrowed the positive relationship between passive W_ICTs and emotional exhaustion. However, differential leadership did not significantly moderate the relationship between active W_ICTs and perceived insider status.

This study is an important step forward in dividing W_ICTs into passive and active W_ICTs and discovers a dual path of two types of W_ICTs on employee innovation behavior. Findings of this study have heuristic value for future research.

Corporate social responsibility (CSR) is regarded as the driving factor of innovation. However, corporate technological innovation social responsibility’s (CTISR) role and effect mechanism in leveraging radical technological innovation (RTI) has been limited. The purpose of this study is to investigate the relationships between CTISR and RTI and the moderating effect of intellectual capital and institutional support on CTISR and RTI.

Grounded in resource-based view, a research model including CTISR, intellectual capital, institutional support and RTI is proposed Content analysis is performed on the CSR reports of Chinese companies that have been publicly listed published from 2008 to 2022, to measure each company’s CTISR. A regression analysis was then applied to relate CTISR, intellectual capital and institutional support to firm-specific variables to determine their relevance and influence on RTI.

Results indicate that CTISR is positively related to RTI. The results also indicate that human capital, structural capital and institutional support strengthen this positive relationship. Furthermore, institutional support strengthens the positive interaction effect of human capital with CTISR and structural capital with CTISR, respectively.

This research explores the relationships among CTISR, intellectual capital, institutional support and RTI in a comprehensive model, which is the first known study to highlight that CTISR can enhance RTI and gives managers implications on how to align corporate technological innovation while pursuing RTI.

This study investigates the economic outcomes of the strategic deviation (SD), the fundamental and crucial question in institutional theory and strategic management. Previous studies have yielded contradictory findings. This study reconciles conflicting results by distinguishing the effects of the SD on financial and market performance, examining the mechanism of financing constraints and the boundary condition of institutional investor heterogeneity.

This research collected data from Chinese A-shares listed manufacturing firms from 2009 to 2021 from the CSMAR and Wind databases. This study conducted empirical tests using OLS models with Stata 15.

Empirical results demonstrate that the SD has different impacts on different dimensions of performance. The SD negatively impacts financial performance while positively impacts market performance. Financing constraints mediate the main effects. Moreover, transactional institutional investors positively moderate the negative effect of the SD on financial performance, whereas stable institutional investors negatively moderate the positive effect of the SD on market performance.

By systematically revealing how the SD has different effects on financial and market performance, this study reconciles the debate on the SD between institutional theorists and strategy scholars. This research makes contributions to the research stream by providing reasonable explanations for conflicting conclusions. Furthermore, by introducing the overlooked perspective of financing constraints, this research identifies crucial mediating mechanisms and highlights the double-edged effect of financing constraints, enriching our understanding of financing constraints. Finally, this study investigates the moderating effects of institutional investor heterogeneity, thereby making valuable contributions to the comprehension of boundary conditions.

The study aims to analyze how the characteristics of intellectual capital (IC) facilitate green entrepreneurship development in the context of ecology, environment and sustainability. Specifically, the evolution of IC and green entrepreneurship was explored through a systematic review, including the relationships and interactions between human, structural and relational capital and green entrepreneurship.

Meticulously combing the Web of Science Core Collection, the researcher conducted a bibliometric analysis of 800 English-language articles from 2002 to 2023. Employing co-word analysis and visualization, the literature on IC and green entrepreneurship was synthesized and systematized, exploring core topics, knowledge architectures and their evolutionary trajectories.

The IC elements such as human, structural and relational capital interact with green entrepreneurship; IC enhances the innovation and competitiveness of green entrepreneurship, while green entrepreneurship orientation influences the accumulation and reshaping of IC. The flow of IC impacts the establishment of green start-ups and the emergence of green industries, promoting sustainable growth.

The dynamic interplay between IC and green entrepreneurship is marked by intricate relationships and diverse attributes. Currently, no comprehensive theoretical model has been established to address the complexities intrinsic to this study. The evidence suggests that the green entrepreneurial orientation influences corporate initiatives to bolster human and structural capital, with structural capital serving as both a constraint and catalyst for human capital. The paper presents an embryonic framework of IC for green entrepreneurship, highlighting its critical role in the aggregation and reconfiguration of IC or venture creation and industry evolution. This contributes to a more profound understanding of IC in entrepreneurial contexts, providing a basis for future research and practical strategy.