Idea Response and Adoption in Open Innovation Communities: The Signaling Role of Linguistic Style

Organizations are increasingly using open innovation communities to gain external ideas and foster user innovation. However, mass user generated content is making idea selection a tricky and time-consuming work. From the perspective of linguistic styles, this article explores the effect of writing style cues in the content of ideas (i.e., negative emotionality, self-interest oriented, cognitive oriented, future oriented) on idea response and adoption. 1,579 ideas collected from the Fantasy Westward Journey Online Ⅱ forum are used to extract writing style cues. The hypothesis tests, via logistic regression models, demonstrate that the linguistic styles of ideas can indeed function as a signaling role and deliver novel insights into the relationship between these linguistic cues and the likelihood of idea responses and adoption. Specifically, a community member’s use of self-interest oriented, cognitive oriented and future oriented writing styles has a positive effect on idea response; negative emotionality and cognitive oriented writing styles signal more possibility of idea adoption. This study offers theoretical implications by extending the innovation management research stream to the big data era and also provides managerial implications that can lead to more effective exploitation of open innovation communities

Manipulating refractive index, homogeneity and spectroscopy of Yb3+^{3+}-doped silica-core glass towards high-power large mode area photonic crystal fiber lasers

Output power scaling of single mode large mode area (LMA) photonic crystal fiber (PCF) amplifiers urgently requires the low refractive index of Yb³⁺-doped silica glasses whilst maintaining high optical homogeneity. In this paper, we report on a promising alternative Yb³⁺/Al³⁺/F¯/P⁵⁺-co-doped silica core-glass (YAFP), which is prepared by modified sol-gel method developed by our group and highly suitable for fabricating high power LMA PCF amplifiers. By controlling the doping combinations of Al³⁺/F¯/P⁵⁺ in Yb³⁺- doped silica glass,it not only ensures low refractive index (RI) but also maintains the excellent optical homogeneity and spectroscopic properties of Yb³⁺. The spectroscopic properties of Yb³⁺ ions have not deteriorated by the co-doping of F¯ and P⁵⁺ in YAFP glass compared with that of Yb³⁺/Al³⁺ co-doped silica glass. A large-size (⌀5 mm × 90 mm) YAFP silica-core glass rod with low average RI difference of 2.6 × 10¯⁴ (with respect to pure silica glass), and low radial and axial RI fluctuations of ~2 × 10¯⁴, was prepared. A LMA PCF with 50 μm core diameter was obtained by stack-capillary-draw techniques using YAFP core glass. Its core NA is 0.027. An average amplified power of 97 W peaking at 1030 nm and light-light efficiency of 54% are achieved from a 6.5 m long PCF in the pulse amplification laser experiment. Meanwhile, quasi-single-mode transmission is obtained with laser beam quality factor M² of 1.4

Texture painting from video

Texture mapping is an important research topic in computer graphics. Traditional static texture-maps are limiting for capturing a dynamic and up-to-date picture of the environment. This paper presents a new technique called texture painting from video. By employing live video as the texture resource, we are not only able to create an accurate and photo-realistic rendering of the scene, but also can support dynamic spatio-temporal update in the structure of texture model, database, and rendering system. We present our approaches towards the system requirements and experimental results for both simulation and real datasets

Leveraging Linguistic Signaling to Prompt Feedback in Open Innovation Communities

Organizations are increasingly using open innovation communities (OICs) to gain external ideas. The success of OICs in promoting innovation, however, depends not just on posting activity by participants, but, crucially, on whether or not responses are subsequently received. Drawing on signaling theory, our study tries to explore how to leverage linguistic signals expressed in idea descriptions to influence feedback from two key parties: the moderator and peers. Linguistic features are divided into affective signaling (i.e., linguistic style matching, negative emotion, and impoliteness) and informative signaling (i.e., post length and quality). The research model is empirically tested on a large dataset collected from the Huawei community. Results show that both affective and informative signaling are effffective in invoking feedback from the moderator. We also find that only negative emotion is positively associated with feedback from peers, while the effects of other signals show different trends. This research provides practical insights into how to maintain the viability of OICs. Keywords: feedback, signaling theory, ideas, open innovation communitie