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There has been limited research that has explored the connection between digital supply chain (DSC) and SC innovation and SC dynamic capabilities. This paper aims to examine the mediating effect of SC innovation on the relationship between DSC and SC dynamic capabilities.

The research model and hypotheses were tested, employing (Statistical Package of Social Sciences) SPSS 25.0 and (Analysis of Moment Structures) AMOS 24.0 on data drawn from the Chinese manufacturing enterprises.

The study reveals that DSC has a significant positive effect on SC innovation and SC dynamic capabilities. SC innovation also has a significant positive effect on SC dynamic capabilities. Besides, the authors' research illustrates that SC innovation partially mediates the relationship between DSC and SC dynamic capabilities.

Since the results are derived from the data collected from China, it may not, therefore, be generalized to other settings. Moreover, future research could consider other contextual variables such as “environmental uncertainty” and “Government's Reward-Penalty Mechanism,” which may influence SC dynamic capabilities.

The study provides practical insights for senior executives and managers in the manufacturing industry. Managers should emphasize the investment of advanced digital technologies and tools (DTTs) and improvement of SC visibility and collaboration. In the digital age, companies should pay attention to the introduction of advanced technologies, tools and processes and focus on cultivating an innovative spirit to promote SC dynamic capabilities, thereby enhancing competitive advantages.

The paper illustrates that DSC is of great significance to improving SC dynamic capabilities. This study reveals compelling insights for firms to enhance SC innovation and dynamic capabilities by using DSC as an enabler.

This study aims to integrate fall-protection function into the elderly clothing to meet both the daily life and fall-protection needs of the elderly people, thereby upgrading the performance of elderly clothing.

This study identified the design strategies of elderly clothing using an Extended Kansei Engineering methodology. Extended Kansei Engineering methodology is a new design framework developed from the traditional Kansei Engineering methodology to meet the design requirements of the product-service system. This study focuses on the product section of product-service system design. According to the product design process of the Extended Kansei Engineering methodology, this study first collected and organized the design elements and Kansei words of elderly clothing. Then a questionnaire was designed using Semantic Differential Scale. Finally, the questionnaire survey was conducted and the collected data was analysed to understand the consumption preferences of elderly people. A total of 399 elderly people aged 65 and older provided valuable design insights for this survey.

The research findings include the product design strategies for the development of elderly clothing, as well as a product prototype canvas and a product prototype elderly clothing developed based on the design strategies.

The research findings can provide competitive design strategies for the development of elderly clothing, thereby upgrading the performance of elderly clothing.

This elderly clothing integrates fall-protection function to reduce the risk of injury for elderly people due to falls, thereby helping society alleviate the medical and healthcare pressure caused by falls for elderly people.

The research findings can provide competitive design strategies for the development of elderly clothing. Furthermore, the Extended Kansei Engineering methodology introduced in this study can provide product and service designers with design methods that are more in line with the development trend of modern product-service system business models.

This study examines the effects of CLS and DS on companies' WCME and analyses the differences in WCME at company and market levels.

This study adopts the DEA approach, regression, differences, and additional analyses to achieve its objectives. This study employs 235 non-financial companies and 1,175 company-year observations from eight active industries in the United States from 2016 to 2020.

The findings indicate that CLS and DS strategies positively influence companies' WCME. Additionally, WCME differed across size categories and industries, with large companies and those operating in the communication services industry showing better WCME. By contrast, WCME did not differ between the periods before and during the COVID-19 pandemic.

This study scrutinizes the impact of CLS and DS strategies on companies' WCME to bridge the gap in this field. It extends the investigation of competitive strategies as explanatory variables for a company's WCME and examines the differences in companies' WCME at the company and market levels, which may assist decision-makers in improving their strategies and efficiencies for continuous improvement.

This study enhances current knowledge by uncovering the influence of CLS and DS strategies on improving companies' WCME, an underexplored topic. It also explores companies' WCME trends and patterns regarding company size, industry type, and the pandemic period to draw interesting conclusions about the essence of WCME.

The purpose of this paper is to propose an accurate and practical imitation learning for robotics. The modified dynamic movement primitives (DMPs), global fitting DMPs (GLDMPs), is presented. Framework design, theoretical derivation and stability proof of GLDMPs are discussed in the paper.

Based on the DMPs, the hierarchical iterative parameter adaptive framework is developed as the hierarchical iteration stage of the GLDMPs to tune the designed parameters adaptively to extract richer features. Inspired by spatial transformations, the coupling analytical module which can be regarded as a reversible transformation is proposed to analyze the high-dimensional coupling information and transfer it to trajectory.

With the proposed framework and module, DMPs derive majority features of the demonstration and cope with three-dimensional rotations. Moreover, GLDMPs achieve favorable performance without specialized knowledge. The modified method has been demonstrated to be stable and convergent through inference.

GLDMPs have an advantage in accuracy, adaptability and practicality for it is capable of adaptively computing parameters to extract richer features and handling variations in coupling information. With demonstration and simple parameter settings, GLDMPs can exhibit excellent and stable performance, accomplish learning and generalize in other regions. The proposed framework and module in the paper are useful for imitation learning in robotics and could be intuitive for similar imitation learning methods.

Prior research on user-generated content (UGC) contributions has primarily focused on self-centered or other-centered motives, paying limited attention to the concept of enlightened self-interest, in which both motives coexist in a single organism. Additionally, the factors influencing enlightened self-interest and their effects in different circumstances are yet to be explored. Drawing on theoretical lenses rooted in the switching barriers perspective and stimulus–organism–response framework, this study posits that dedication-based switching barriers (community–member relationship quality, member–member relationship quality, and content attractiveness) positively relate to enlightened self-interest, whereas constraint-based switching barriers (switching costs) moderate the relationship between dedication-based switching barriers and enlightened self-interest in social media communities (SMCs). Members' enlightened self-interest in turn influences both the creation and co-creation of UGC.

This study comprised two quantitative studies: an online survey-based study (Study 1) and an online scenario-based experiment (Study 2). Study 1 surveyed 613 respondents, while Study 2 included 749 participants. Both studies employed structural equation modeling and bootstrapping techniques for analysis.

The findings indicate that dedication-based switching barriers positively affect users' enlightened self-interest, which in turn is positively associated with UGC creation and co-creation. Switching costs moderate the relationship between relationship quality (community–member and member–member) and enlightened self-interest.

This study complements the current understanding of how the association between dedication- and constraint-based switching barriers and users' enlightened self-interests influence user-generated contributions.

This study aimed to determine whether the brand image of fast-food restaurants moderates the relationship between satisfaction and loyalty among Chilean customers.

The study was conducted using a structural equation modeling approach and involved a sample of 1,000 fast-food customers who were surveyed through nonprobabilistic sampling with a questionnaire consisting of 21 items. The instrument underwent validation by a panel of experts, and the results obtained were processed using the statistical software Smart PLS4. Convergent validity, discriminant validity and the structural model were tested to assess the acceptance or rejection of the proposed hypotheses.

The results of the research indicate that product quality, service quality and physical environment are crucial factors influencing customer satisfaction and shaping customer loyalty. However, it was found that brand image does not moderate the relationship between satisfaction and loyalty in fast-food consumption.

The present study contributes to the field of knowledge on fast-food consumption behavior and unveils findings that help fill knowledge gaps regarding the influence of restaurant brand image on the relationship between satisfaction and consumption loyalty. Thus, it demonstrates that, for certain customers, the brand becomes an irrelevant factor for their consumption loyalty as long as the restaurant offers product quality, excellent service and a pleasant physical environment.

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.

The purpose of this study was to synthesize composite nanoparticles (TiO₂@SiO₂) via the chemical deposition method and investigate their efficacy as additives in polytetrafluoroethylene (PTFE) lubricating grease. The focus was on examining the frictional and conductive properties of the TiO₂@SiO₂ grease using a friction tester.

Composite nanoparticles (TiO₂@SiO₂) were synthesized using the chemical deposition method and incorporated into PTFE grease. Frictional and conductive properties were evaluated using a friction tester. Surface morphology and chemical composition of wear tracks were analyzed using scanning electron microscope and X-ray photoelectron spectroscopy, respectively.

Incorporating TiO₂@SiO₂ at a mass fraction of 1 Wt.% led to a significant reduction in friction coefficient and wear width. The wear depth exhibited a remarkable decrease of 260%, while the contact resistance reached its peak value. This improvement in tribological properties could be attributed to the presence of TiO₂@SiO₂, where TiO₂ served as the core and SiO₂ as the shell during the friction process. The high hardness of the SiO₂ shell contributed to enhanced load-bearing capacity. In addition, the exceptional insulation properties of SiO₂ demonstrated excellent electron-capturing capabilities, resulting in improved friction and insulation performance of the TiO₂@SiO₂ lubricating grease.

This study demonstrates the potential of TiO₂@SiO₂ composite nanoparticles as additives in lubricating greases, offering improved friction and insulation performance. The findings provide insights into the design of advanced lubricating materials with enhanced tribological properties and insulation capacity, contributing to the development of more efficient and durable lubrication systems.

Innovation ambidexterity is crucial for fostering growth and gaining a competitive advantage in small and medium enterprises (SMEs). Previous research indicates that achieving a balance between exploration and exploitation is a multifaceted phenomenon occurring across various levels. This paper aims to examine the influence of individual, organizational and institutional factors on the ambidextrous innovation of Chinese niche leaders using a configurational perspective.

This study uses secondary data collected from 69 Chinese niche leaders in the new equipment manufacturing industry. The authors use fuzzy-set qualitative comparative analysis to investigate how owner openness, age, digitization, the formal institutional environment and the informal institutional environment jointly influence innovation ambidexterity.

By using fuzzy set analysis, this study categorizes combinations of interdependent factors that promote innovation ambidexterity. In particular, the authors pinpoint three configurations that foster high innovation ambidexterity and two configurations that lack such high levels of innovation ambidexterity. The analysis results suggest that innovation paradoxes in SMEs are linked to a nested system comprising leadership, organizational factors and the institutional environment.

This study elucidates the mechanism of innovation ambidexterity through a configurational perspective. This research proposes and validates a framework that enables SMEs to develop ambidextrous innovation capabilities, thereby integrating organizational ambidexterity theory and shedding light on the intricately complex nature of innovation ambidexterity.