Search results

Small talk, often regarded as a superficial interaction unrelated to work, is a pervasive and inescapable aspect of daily life and professional settings. In China, where the notion of guanxi – the cultivation of strategic relationships – is deeply valued, workplace small talk (WST) is a strategic tool used by employees to strengthen their interpersonal networks. This study aims to investigate the positive impact of WST on task performance within the Chinese workplace and explores the mechanisms underpinning this relationship.

This study adopted a time-lagged research design to test its hypotheses using data from 516 employees across various Chinese firms.

This study revealed that WST exerts both direct and indirect positive effects on task performance. It boosts task performance indirectly via two mediators: relational energy and positive affect. This study also delineated a chain mediation model wherein WST sequentially elevates task performance by first enhancing relational energy and then fostering positive affect.

Counter to the prevailing focus on the negative repercussions of WST, this study sheds light on its beneficial outcomes, proposing novel pathways connecting WST to task performance. These insights contribute to both academic discourse and the development of practical management strategies.

Effective cooperative communication and knowledge management capabilities are particularly important in the cross-team cooperation. Based on the social exchange theory, this paper aims to further explore the role and influence mechanism of cooperative communication and knowledge sharing on co-innovation performance in open innovation projects (OIPs).

This paper takes China’s high-tech enterprises as the research object by using a paired questionnaire survey based on 168 pairs of OIPs. Hayes’ PROCESS programme and the bootstrap technique are used to test the hypothesis model and the significance of the mediation effect.

This study finds that cooperative communication is an effective mechanism for the internal and external interaction of OIPs. Knowledge sharing plays an intermediary role in the relationship between cooperative communication and co-innovation performance; both explicit knowledge sharing and tacit knowledge sharing have a significant positive impact on co-innovation performance. And the impact of cooperative communication on co-innovation performance is based on effectively promoting the knowledge sharing of partners.

This research incorporates cooperative communication, knowledge sharing and co-innovation performance into a unified research framework to study the co-innovation at the project level, enriches the research scenario on the mechanism of cooperative behaviour, deepens the understanding of the role and influence mechanism of cooperative communication and knowledge sharing on co-innovation performance in OIPs, verifies the mediating role of knowledge sharing to co-innovation, and also helps extend the social exchange theory to a new research setting.

The main objective of the study was to identify main trends, research directions and important authors in the field of supply chain management (SCM) and logistics in the context of digital transformation and automation through the application of bibliometric analysis. The study is based on the analysis of academic publications and research studies covering the topics of digital transformation (incl. automation) of the logistics sector and SCM. For this purpose, bibliometric methods are applied, including keyword frequency analysis, identification of the most cited sources and authors. The chapter identifies main trends and research directions in the field of digital transformation of the logistics sector and SCM. Also, the most influential sources and authors making significant contributions to the development of this field are identified. Top 10 best authors, citations and documents got illustrated. The results of the study can be useful for researchers involved in the digital transformation of the logistics sector and SCM, as well as for practitioners developing strategies and solutions in the field of logistics and SCM. The bibliometric analysis provides valuable information on status and trends in research on digital transformation of the logistics sector and SCM (444 documents analyzed), which can be useful for further research and strategy development in this area. Based on the results of the study, it was possible to identify that the increase in research on digital transformation of the logistics sector and SCM is related to the emergence and subsequent epidemic of the COVID-19 virus.

This study examines two distinct bearing stiffness calculation methods, both of which are based on the displacement-load function. Previous research typically incorporated one type of bearing stiffness into their system mechanics or vibration analysis. However, these two methods of calculating stiffness lead to different vibration models. This implies that the choice for vibration investigation is not merely about selecting one of the two types of stiffness, but also about how to appropriately implement that chosen stiffness within a model. The primary objective of this work is to compare these two methods of bearing calculation and to discuss the suitable applications of each method in both static and dynamic analyses.

This study compares two distinct methods for calculating bearing stiffness. It explores the relationships between varying bearing stiffnesses, their internal structures, and contact features. Furthermore, it examines the impact of external loads on the static properties and dynamic characteristics of different bearing stiffnesses. Finally, based on the outcomes observed under various operating conditions, the study discusses the suitability of each method for static and dynamic analysis.

Mean stiffness is more suitable for calculating load transmissibility in a static state or capturing the delivery performance at instantaneous equilibrium positions in a dynamic state. Since the variation of the equilibrium positions is ignored, the alternating stiffness model is better suited for capturing the fluctuating properties of the vibration behaviors, especially under variable external load conditions.

We compare the two bearing calculation methods and discuss the appropriate applications of each method for static and dynamic analysis.

This research addresses the challenges encountered when securing bone plates in the human body to treat tibial plateau fractures, specifically focusing on preventing posterolateral fractures. The goal is to develop a 3D buttress plate that offers better stability, facilitating anatomical reduction and rigid fixation. The newly fabricated T-buttress plate enables early knee motion and reduces postoperative complications, marking a significant advancement over existing internal fixation plates.

A new buttress plate model was designed using modeling software, featuring an asymmetric curved design with three fragments. Finite element analysis was used to simulate the biomechanical performance of this new model, comparing it with symmetric flat and symmetric curved plates. Accurately predicting the biomechanical behavior of the implant posed challenges, especially during extensive simulations. Optimal parameters for the asymmetric curved plate were identified from the simulation results, and the 3D buttress plate was then fabricated using the metal fused filament fabrication (MFFF) process. This process presents challenges due to the novel nature of the asymmetric design.

The results indicate that the newly developed buttress plate exhibits superior strength and performance compared to current internal fixation plates. Biomechanical simulations show that the asymmetric curved design provides better stability and support. Moreover, the yield and ultimate tensile strengths were found to be 685 MPa and 855 MPa, respectively.

The study’s finite element analysis model has limitations due to its reliance on assumptions about material properties, boundary conditions and loading scenarios. It also excludes biological factors, patient variability and the bone’s heterogeneous nature, which may affect the accuracy and applicability of the results in real-life situations.

The development of an asymmetric curved buttress plate using MFFF is a novel innovation aimed at improving biomechanical performance and patient outcomes in orthopedic surgery, offering significant potential impact in the medical field.

Online patient reviews are of considerable importance on online health platforms. However, there is limited understanding of how these reviews are generated and their impact on patients' choices of physicians. Therefore, this study aims to investigate the antecedents and consequences of online patient reviews on online health platforms.

This study introduced an online interaction model with multiple stages aimed at examining how physicians' service quality affects patients' review behavior and, consequently, influences patients' choices of physicians.

The results revealed that technical quality and emotional care significantly influenced the effort that patients exert and their use of positive emotional words when writing reviews, which, in turn, positively influenced patients' selection of physicians. Moreover, it was found that the voice channel had a significant moderating effect on the relationship between physician service quality and patient review behavior.

The study’s findings can help online health platform managers improve the platform system by optimizing the integrated text and voice interaction functions. The findings can also support physicians in improving service quality, managing online reviews and attracting patients’ choices.

This study enriches the literature on physician service quality, patient online reviews and choices in online health platforms. Furthermore, this study offers a novel perspective on the social exchange process in online healthcare settings by highlighting the role of media in shaping physician–patient interactions.

This study aims to explore the eye movement behavior of preadolescent children accessing and diagnosing information.

The researchers tracked the eye movements of 30 children with an eye-tracking apparatus. Using the kit of factor-referenced cognitive tests to measure perceptual speed and associative memory, they measured information-searching behavior with screen recordings, the data of which were analyzed by IBM SPSS Statistics 26.

Regarding information accessibility, there was a correlation between the child’s age, associative memory and the number of round-trip choices, and there were differences in the total fixation area among children of different age groups. Regarding diagnosticity, perceptual speed was positively correlated with the total fixation area, and the number of round-trip choices was negatively correlated with fixation duration.

Empirical evidence suggests that during information encoding, perceptual speed is the most important influencing factor. Extensive research indicates that children predominantly rely on recall and familiarity when searching for new information, both of which play roles in associative memory. Through an examination of the psychological and behavioral indicators of children, the study elucidated the cognitive processes involved in information processing and how children engage with information at both visual and cognitive levels.

This paper aims to explore the relationship between digital transformation, international competition and productivity progress by examining the dual margins of export, thereby identifying the digital development pathway for key industrial chains within the context of regional medical and health cooperation.

By constructing models incorporating both the extensive margin and intensive margin, this paper delves into the reasons underlying changes in product trade value and variety within international market competition. Utilizing export data for medical products from China to Belt and Road Initiative partner countries spanning from 2007 to 2020, an industry–destination–time panel benchmark model is established to assess the impact of digital transformation on product expansion and international competition.

The findings reveal the following insights. First, digital transformation positively impacts the intensive margin of medical products, whereas it does not exert a positive influence on the extensive margin. Second, the impact mechanism test indicates that digital transformation fosters the intensive export margin by enhancing the technical efficiency of exports but exhibits an inverted U-shaped effect on technological progress. Third, digital transformation demonstrates a notable non-linear characteristic, with a substantial increase in the lifting effect once a certain threshold is surpassed.

While previous research has extensively explored the effects of digital transformation on export trade, this study uniquely integrates the concepts of the intensive and extensive margins of export, thereby enriching the research insights derived from existing literature. It focuses on the nonlinear effects and threshold dynamics of digital transformation, particularly in relation to total factor productivity. Additionally, the paper makes a contribution to the understanding of the Health Silk Road by incorporating the health index.

This paper aims to address the issue of privacy leakage indirectly caused by non-private data shared by travellers on location-based social media (LBSM) in data mining.

This paper proposes a privacy-preserving location data collection approach based on local differential privacy (LDP) and validates the feasibility of the approach through experiments on three real-world public check-in datasets.

The experimental results demonstrate the effectiveness of our proposed approach, which preserves privacy while retaining over 90% of the data utility.

This research has the potential to assist tourism practitioners in establishing improved collaborations with trusted third parties, enabling the exploration of user location data insights without undue concerns regarding indirect privacy breaches during data mining, thereby enhancing travellers’ experience and aiding businesses’ decision-making.

This paper is likely to be the first to represent a promising solution for addressing privacy leakage concerns related to non-sensitive data in data mining. It provides a location data collection technology that strikes a balance between user privacy and data utility for tourism practitioners.

The COVID-19 pandemic has amplified the importance of effectively leading a remote workforce in volatile, uncertain, complex and ambiguous (VUCA) environments. This study examines the effectiveness of transformational–transactional leadership (Full-Range Leadership Model, FRLM) and its recent extension of instrumental leadership (eFRLM) in remote work contexts.

We surveyed 529 remote working followers, providing perceptions on (1) their leaders’ manifestation of eFRLM dimensions and factors, (2) their leaders’ leadership effectiveness and (3) their organizational environment as VUCA.

Results show that instrumental leadership represents a strongly effective leadership dimension in remote work contexts, explaining unique variance beyond transformational–transactional leadership. Moreover, VUCA environments moderated the association between eFRLM leadership behaviors and leadership effectiveness, with instrumental leadership being particularly effective in more pronounced VUCA environments and transformational–transactional leadership being less effective.

Overall, instrumental leadership appears crucial to consider when predicting leadership effectiveness in virtual and uncertain contexts.