R&D, intellectual capital, organizational learning, and firm performance: a study of Chinese software companies

This research establishes a theoretical model to test the interrelationships among R&D investment, intellectual capital, organizational learning, and firm performance. Based on the collection and investigation of a panel dataset gleaned from 26 software companies in 28 time periods, we find that: (1) R&D investment of software enterprises and firm performance are positively correlated; (2) intellectual capital fully mediates the R&D investment– performance relationship; and (3) organizational learning of software security vulnerabilities moderates the relationship between R&D investment and intellectual capital in the form of human capital. Based on our findings, we draw both theoretical and managerial implication

The Strength Of Individual Relationships And Employee Knowledge Sharing Behavior

Firm’s core competitiveness results primarily from its ability to innovate. Knowledge sharing plays an important role in promoting sustained innovation. This research examines the factors enabling knowledge sharing in a Research and Development (R&D) department of a Chinese commercial elevator firm. We find that the strength of individual relationships, contextual performance, and IT capability are positively correlated with the strong knowledge sharing behavior, while controlling for gender, education, and job tenure. Based on our findings, we draw both theoretical and managerial implications

OVSNet : Towards One-Pass Real-Time Video Object Segmentation

Video object segmentation aims at accurately segmenting the target object regions across consecutive frames. It is technically challenging for coping with complicated factors (e.g., shape deformations, occlusion and out of the lens). Recent approaches have largely solved them by using backforth re-identification and bi-directional mask propagation. However, their methods are extremely slow and only support offline inference, which in principle cannot be applied in real time. Motivated by this observation, we propose a efficient detection-based paradigm for video object segmentation. We propose an unified One-Pass Video Segmentation framework (OVS-Net) for modeling spatial-temporal representation in a unified pipeline, which seamlessly integrates object detection, object segmentation, and object re-identification. The proposed framework lends itself to one-pass inference that effectively and efficiently performs video object segmentation. Moreover, we propose a maskguided attention module for modeling the multi-scale object boundary and multi-level feature fusion. Experiments on the challenging DAVIS 2017 demonstrate the effectiveness of the proposed framework with comparable performance to the state-of-the-art, and the great efficiency about 11.5 FPS towards pioneering real-time work to our knowledge, more than 5 times faster than other state-of-the-art methods.Comment: 10 pages, 6 figure

An Explorative Study of the Effectiveness of Mobile Advertising

This study examines factors related to the effectiveness of mobile advertising. Using a large data set with 115, 899 records of ad tap through from a mobile advertising company, we identify that the influencing factors for ad tap through are application type, mobile operators, scrolling frequency, and the regional income level. We use a logit model to analyze how the probability of ad tap through is related to the identified factors. The results show that application type, mobile operators, scrolling frequency, and the regional income level all have significant effects on the likelihood whether users would tap on certain types of advertising. Based on the findings, we propose strategies for mobile advertisers to engage in effective and targeted mobile advertising

Network Structure and Creativity of Employees under HR Multi-model Form -Taking a company\u27s software development team as an example

Taking an IT outsourcing company\u27s project team as an example, by building team members’ social networks and extracting their network characteristics, we can put employees’ behavioral variables and social network variables into the same economic model to do variable regression analysis. The study found that employees’ network structure characteristics have certain influence on employees’ knowledge sharing and creativity, and employees’ knowledge sharing partially mediated the network structure characteristics and creativity. Based on structure characteristics of the R&D networks, this paper explains the organizing, coordinating, communicating role of employees from the parent company in the IT outsourcing project team under HR multi-model. We also proposed measures and strategies to promote employees’ creativity under HR multi-model

Image Clustering with External Guidance

The core of clustering is incorporating prior knowledge to construct supervision signals. From classic k-means based on data compactness to recent contrastive clustering guided by self-supervision, the evolution of clustering methods intrinsically corresponds to the progression of supervision signals. At present, substantial efforts have been devoted to mining internal supervision signals from data. Nevertheless, the abundant external knowledge such as semantic descriptions, which naturally conduces to clustering, is regrettably overlooked. In this work, we propose leveraging external knowledge as a new supervision signal to guide clustering, even though it seems irrelevant to the given data. To implement and validate our idea, we design an externally guided clustering method (Text-Aided Clustering, TAC), which leverages the textual semantics of WordNet to facilitate image clustering. Specifically, TAC first selects and retrieves WordNet nouns that best distinguish images to enhance the feature discriminability. Then, to improve image clustering performance, TAC collaborates text and image modalities by mutually distilling cross-modal neighborhood information. Experiments demonstrate that TAC achieves state-of-the-art performance on five widely used and three more challenging image clustering benchmarks, including the full ImageNet-1K dataset

Biological Routes to Gold Nanoplates

Much effort has been devoted to the synthesis of gold nanoparticles with different shapes, including the zero-dimensional nanospheres, one dimensional nanorods, and two-dimensional nanoplates. Compared to zero or one dimensional nanostructures, the synthesis of two-dimensional nanostructures in high yield has always been more involved, often requiring complex and time-consuming steps such as morphology transformation from the nanospheres, or the seeded growth process. Herein we report a high yield method for gold nanoplate synthesis using the extract of unicellular green alga Chlorella vulgaris, which can be carried out under ambient conditions. More than 90% of the total nanoparticle population is of the platelet morphology, surpassing the previously reported value of 45%. The control of the anisotropic growth of different planes; as well as the lateral size, has also been partially optimized.Singapore-MIT Alliance (SMA