Search results

According to the resource dependence theory and peer effect theory, this paper explores the mechanism of the focal firm’s knowledge coherence on technological distance among its supply chain partners.

Based on patent data of 301 Information Technology and Communication Services firms over 18 years from 1998 to 2015, this paper conducts panel regression analysis.

Empirical results find the positive relationship between the focal firm’s knowledge coherence and technological distance among its supply chain partners. Furthermore, conclusions indicate that the focal firm’s degree centrality and ego network density negatively and positively moderate this relationship respectively.

The findings of this paper contribute to the existing research in supply chain network innovation and offers guidelines to choose partners with varying technological compositions according to their knowledge bases and network structure characteristics.

Human resources transformation is an essential concept that significantly changes how organizations manage their personnel in an ever-changing business environment. This research intends to explore the potential of artificial intelligence (AI) technologies to facilitate human resource (HR) transformation in automobile companies in China.

The research employs qualitative approaches such as interviews and case studies to gain insights and viewpoints from key stakeholders. The interviews were semi-structured and carried out in person, enabling an in-depth investigation of their experiences and perspectives. The duration of each interview ranged from 30 to 40 minutes.

The study explored three main themes: employee acceptability, career growth and performance, using system thinking theory. The findings highlight the various effects of AI technology on HR changes in automobile businesses. First, AI helps increase employee approval by simplifying activities and improving user experience. Second, it greatly impacts professional advancement by providing tailored learning and skill-building chances. Third, AI integration has a favorable effect on organizational performance indicators such as efficiency, agility and adaptability.

This research's findings significantly contribute to scholars and practitioners engaged in HR reforms. Comprehending the subtle impacts of AI technology on employee acceptability, career advancement and organizational effectiveness helps guide strategic decision-making. Furthermore, these results emphasize the need to connect AI-based HR initiatives with overall corporate goals to enhance impact and efficiency

This research provides new insights into how AI technologies interface with HR transformation. The study offers a thorough understanding of intricate dynamics and identifies new possibilities for using AI in HR practices via system thinking theory. The research enhances academic discussion on HR transformation in the age of AI-driven innovation.

This paper aims to explore the underlying mechanisms and boundary conditions through which equipment manufacturing enterprises can capture market value from digital transformation, with a specific focus on the roles of knowledge search and knowledge recombination.

This study uses a double fixed-effects model to test the hypotheses, using a unique data set of “firm-year” observations from 739 publicly listed equipment manufacturing companies in China, spanning the period from 2018 to 2022.

Digital transformation drives market value creation in equipment manufacturing enterprises through both breakthrough knowledge recombination (BKR) and progressive knowledge recombination (PKR). In addition, the analysis of marginal conditions reveals that diversified knowledge search serves as a substitute for digital transformation in promoting BKR, while also positively moderating the relationship between digital transformation and PKR.

Grounded in the knowledge-based view theoretical framework, this study introduces the novel concepts of BKR and PKR and systematically examines how digital transformation impacts market value in equipment manufacturing enterprises.

This study aims to investigate the temperature rise characteristics of vibrating rolling bearings under the influence of the polarization force of unbalanced eccentric blocks. A thermal-fluid-solid mechanics coupled finite element model is established to analyze the effects of different loads and rotational speeds on bearing temperature to prevent overheating, wear and thermal damage.

A thermal-fluid-solid mechanics coupled finite element model of the vibrating rolling bearing is developed based on the principles of heat transfer. Finite element analysis software is used to conduct numerical simulations and study the temperature distribution of the bearing system under different loads and speeds. The model’s accuracy is verified by experimentally measuring the actual temperature of the bearing under the same working conditions.

This study successfully established a thermal-fluid-solid mechanics coupled finite element model of a vibrating rolling bearing, verifying its accuracy and reliability. The research results provide an essential reference for optimizing bearing design, preventing overheating and extending service life.

By analyzing the temperature rise characteristics under various load and rotational speed conditions, the law governing the internal temperature distribution of bearings is revealed. This finding offers a theoretical foundation for comprehending the thermal behavior of bearings.

This study offers a scientific foundation for the maintenance and fault diagnosis of shaker rolling bearings, aiding in the timely identification and resolution of thermal damage issues. Through the optimization of bearing design and usage conditions, the equipment’s lifespan can be prolonged, maintenance expenses can be minimized and production efficiency can be enhanced.

A thermal-fluid-solid mechanics coupled finite element model of a vibrating rolling bearing was established, considering the interaction of multiple physical fields. The influence of the polarization force from the unbalanced eccentric block on the bearing temperature is analyzed in detail, which is close to the actual working conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0396/