Stakeholder orientation and organizational performance in an emerging market

There has been research that studies Chinese firms’ stakeholder orientation but fails to identify Chinese firms’ specific stakeholder groups. In addition, little research in this line has been conducted so far to reflect recent Chinese constitutional transition. This study seeks to fill these gaps. It extends previous studies assuming that a fixed set of stakeholders is suitable for firms in different countries context, and identifies Chinese firms’ key stakeholder groups by adopting the descriptive approach of stakeholder theory. Based on this identification, the authors further examine how these stakeholder orientations influence organizational performance and how they interact. Interviews with managers from 107 firms show that customer, employee, shareholder, supplier, and competitors are perceived as Chinese firms’ most important stakeholders; empirical studies using data collected from 307 Chinese firms reveal that orientations towards these stakeholders enhance organizational performance. Moreover, there are synergy effects existing among customer orientation, supplier orientation, and competitor orientation, and between customer orientation and competitor orientation, while shareholder orientation has significant hindering effects upon competitor orientation as a reflection of recent institutional changes taking place in China

Distributed Energy Infrastructure Development: Geospatial & Economic Feasibility in Rural West Virginia

Energy transition from conventional to centralized power plants, including coal-fired units, is critical for West Virginia’s long-term energy and economic future. The socioeconomic downturn in West Virginia was deeply connected with the dependence on the centralized coal industry and the coal economy. Most traditional coal communities in rural West Virginia struggle to maintain economic viability, potentially leading to outmigrations and poor energy resilience. I investigated the possibility of introducing community-sized distributed energy systems in these rural communities to improve energy resilience and accommodate the future transition from centralized coal-generated energy. My goal was to identify rural regions where distributed energy can be utilized at an optimal cost, thus improving energy resiliency within these communities and positively impacting the economy. This study provided a geospatial modeling approach with Multi-Criteria Decision Analysis (MCDA) and Geographic Information System (GIS) suitability assessment to identify the feasible locations of small-scale distributed generation for wind, solar, and hydropower energies. The net value comparison analysis was conducted utilizing the levelized cost of energy (LCOE) and levelized avoided cost of energy (LACE) to determine the differences in investment costs for each distributed generation type compared with traditional coal-generated electricity. I expected the spatial analysis results to reveal optimal sites for the specific distributed energy types. I found that wind and solar distributed generation have stronger presences in southern and eastern West Virginia counties, while suitable small hydropower development locations are spread across the state. This study provided insight into future distributed energy and its infrastructure development possibilities in rural West Virginia

Acoustic test facility at Tianjin spacecraft AIT center of China

The China Academy of Space Technology (CAST) designs and builds a new world-class Assembly, Integration and Test Center (AITC) at Tianjin, China. Modal, vibration and acoustic test facilities are built to support the future environmental testing needs of China space station program. The Reverberation Acoustic Test Facility (RATF) is about 4000 m3 in volume and can achieved an empty chamber acoustic overall sound pressure level (OASPL) higher than 156 dB. It is the largest acoustic facility in Asia. Beijing Institute of spacecraft Environment Engineering (BISEE) started its design and construction work from 2012 and put it into use at October of 2015. The RATF will provide an efficient support for environment testing needs of China and world’s space program in the future

Discovering Discriminative Geometric Features with Self-Supervised Attention for Vehicle Re-Identification and Beyond

In the literature of vehicle re-identification (ReID), intensive manual labels such as landmarks, critical parts or semantic segmentation masks are often required to improve the performance. Such extra information helps to detect locally geometric features as a part of representation learning for vehicles. In contrast, in this paper, we aim to address the challenge of {\em automatically} learning to detect geometric features as landmarks {\em with no extra labels}. To the best of our knowledge, we are the {\em first} to successfully learn discriminative geometric features for vehicle ReID based on self-supervised attention. Specifically, we implement an end-to-end trainable deep network architecture consisting of three branches: (1) a global branch as backbone for image feature extraction, (2) an attentional branch for producing attention masks, and (3) a self-supervised branch for regularizing the attention learning with rotated images to locate geometric features. %Our network design naturally leads to an end-to-end multi-task joint optimization. We conduct comprehensive experiments on three benchmark datasets for vehicle ReID, \ie VeRi-776, CityFlow-ReID, and VehicleID, and demonstrate our state-of-the-art performance. %of our approach with the capability of capturing informative vehicle parts with no corresponding manual labels. We also show the good generalization of our approach in other ReID tasks such as person ReID and multi-target multi-camera (MTMC) vehicle tracking. {\em Our demo code is attached in the supplementary file.

The research of polishing nozzle quality based on discrete element method

In order to get further study for the effect of abrasive grains to the wall of the workpiece during polishing process, a new method of discrete element that carry out the numerical simulation with DEM is put forward, and the visual calculation is performed for the abrasive grain movement in the nozzle. The interaction of particles-particles or particles-workpiece wall during the polishing process and the tracks of single grain in the workpiece are analyzed by observing the distribution of abrasive grain in the workpiece at different time. The surface removal mechanism of abrasive grains to the workpiece material is discussed by analyzing the collision process of particles to the workpiece wall. The wear level of the abrasive grains to the inner surface of the workpiece is studied through the force of abrasive grain to the workpiece wall consumption, and finally explore the cutting effect of particles to workpiece wall. As a consequence, the abrasive flow processing experiment is carried out. The surface roughness of the large hole and small hole of the nozzle are detected by stylus measurement. The conclusion shows that the surface roughness for the large hole and the small hole before the experiment is1.741 μm and 1.201 μm, its 0.801 μm, 0.651 μm after it. Further roughness tests are performed on the surface of the pores by means of a grating surface measuring instrument. The result indicates that the surface roughness reduces from 2.67 μm to 0.697 μm, 0.728 μm, 0.782 μm. Apparently, the surface roughness of the hole is sharply reduced, which has a smooth and flat inner surface, the effectiveness and reliability of the abrasive flow are verified