Hefei Light Source (HLS) is a synchrotron radiation light source that primarily produces vacuum ultraviolet and soft X-rays. It currently consists of ten experimental stations, including a soft X-ray microscopy station. As part of its ongoing efforts to establish a centralized scientific data management platform, HLS is in the process of developing a test system that covers the entire lifecycle of scientific data, including data generation, acquisition, processing, analysis, and destruction. However, the instruments used in the soft X-ray microscopy experimental station rely on commercial proprietary software for data acquisition and processing. We developed a semi-automatic data acquisition program to facilitate the integration of soft X-ray microscopy stations into a centralized scientific data management platform. Additionally, we created an online data processing platform to assist users in analyzing their scientific data. The system we developed and deployed meets the design requirements, successfully integrating the soft X-ray microscopy station into the full lifecycle management of scientific data.

Political skill is a critical interpersonal competency. However, the self-reported political skill scale is unsuitable for personnel selection beacuse it may lead to socially desirable responses, thereby compromising the authenticity of the test scores. Consequently, the absence of a valid assessment method limits the application of political skill in selection contexts. In this study, we applied the situational judgment test (SJT) method to measure political skill and conducted two substudies to evaluate the reliability and validity of the situational judgment test of political skill (SJT-PS). Study 1 focused on the development and initial testing of the SJT-PS. The results demonstrated that the SJT-PS possessed strong structural validity and reliability. Study 2 aimed to assess the criterion-related and incremental validity of the SJT-PS. To evaluate the predictive validity of the SJT-PS in selection contexts, we first compared the correlations between the SJT-PS and self-reported political skill with social desirability. Subsequently, we selected team-member exchange (TMX) and workplace popularity as criteria. The results indicated that the SJT-PS was less affected by social desirability, while self-reported political skill exhibited a significant positive correlation with social desirability. Additionally, the SJT-PS positively predicted TMX and workplace popularity and demonstrated incremental validity over the self-reported political skill scale.

Since social media increasingly infiltrates the workplace, it may affect employee innovation. However, how social media use (SMU) affects employee innovation performance remains controversial. Therefore, this study explores the underlying mechanisms and boundary conditions in the relationship between SMU and employee innovation performance. The research model was tested through a survey of 221 Chinese employees. The results show that SMU is positively related to employee innovation performance, with work engagement acting as a mediator in this relationship. Employee traditionality positively moderates the positive impact of work-related SMU on work engagement, while traditionality has no moderating effect on the relationship between social-related SMU and work engagement. This study focuses on the relationship between SMU and innovation performance based on conservation of resources theory, offering insights into the intrinsic mechanism by which SMU affects employee innovation. Furthermore, this study considers the moderating effect of employee traditionality based on social cognitive theory, enriching the knowledge of how traditionality influences the impacts of SMU. This study has theoretical implications for future research and practical guidance for enterprises regarding the proper use of social media.

To address the charging infrastructure challenges associated with slow electric vehicle (EV) industry growth, this study investigates the collaboration between private charging-pile-sharing platforms struggling with profitability and automotive companies. This collaboration is crucial, as it demands a balanced price and service quality management due to consumer expectations. This paper introduces a Stackelberg game model to explore the relationship between a charging platform and an automotive company. Through numerical analysis, we assess how this cooperation might improve the platform’s efficiency and benefit society, potentially overcoming existing industry hurdles. Our findings indicate that such partnerships could benefit all parties involved, despite possible negative environmental impacts. However, after collaborating, platforms may increase consumer prices and payments to suppliers, potentially lowering service quality for brand-associated consumers due to a compromise between shorter waiting times and service quality. This research offers valuable insights for stakeholders on the effects of cooperation, enabling better strategic decisions in the EV charging sector.

Motivated by the business model called “community group buying” (CGB), which has emerged in China and some countries in Southeast Asia, such as Singapore and Indonesia, we develop algorithms that could help CGB platforms match consumers with stage-stations (the picking up center under the CGB mode). By altering the fundamental design of the existing hierarchy algorithms, improvements are achieved. It is proven that our method has a faster running speed and greater space efficiency. Our algorithms avoid traversal and compress the time complexities of matching a consumer with a stage-station and updating the storage information to O(logM) and O(MlogG), where M is the number of stage-stations and G is that of the platform’s stock-keeping units. Simulation comparisons of our algorithms with the current methods of CGB platforms show that our approaches can effectively reduce delivery costs. An interesting observation of the simulations is worthy of note: Increasing G may incur higher costs since it makes inventories more dispersed and delivery problems more complicated.