A Dynamic Network Measure of Knowledge Evolution: A Case Study of MIS Quarterly

Citation measures are the central metrics to assessing the impact of an article, the viability of research streams, the career success of scholars, as well as the quality and status of journals and academic units. While measuring the magnitude of the future usage, they cannot capture the substantial effects that an article may have on the subsequent use of its predecessors - whether it amplifies or disrupts the existing literature. We embrace that it is imperative to not only assess its impact but also assess how an article reinforces the existing research streams or breaks into a new stream to understand its true effect. Accordingly, we introduce a new, dynamic measure, and conduct a case study using all articles published between 1979-2016 at MIS Quarterly to illustrate the validity of the new measure, and conclude with some future research topics and implications

Inferring Fluid Dynamics via Inverse Rendering

Humans have a strong intuitive understanding of physical processes such as fluid falling by just a glimpse of such a scene picture, i.e., quickly derived from our immersive visual experiences in memory. This work achieves such a photo-to-fluid-dynamics reconstruction functionality learned from unannotated videos, without any supervision of ground-truth fluid dynamics. In a nutshell, a differentiable Euler simulator modeled with a ConvNet-based pressure projection solver, is integrated with a volumetric renderer, supporting end-to-end/coherent differentiable dynamic simulation and rendering. By endowing each sampled point with a fluid volume value, we derive a NeRF-like differentiable renderer dedicated from fluid data; and thanks to this volume-augmented representation, fluid dynamics could be inversely inferred from the error signal between the rendered result and ground-truth video frame (i.e., inverse rendering). Experiments on our generated Fluid Fall datasets and DPI Dam Break dataset are conducted to demonstrate both effectiveness and generalization ability of our method

Measurement and Analysis of the Swarm Social Network With Tens of Millions of Nodes

Social graphs have been widely used for representing the relationship among users in online social networks (OSNs). As crawling an entire OSN is resource-and time-consuming, most of the existing works only pick a sampled subgraph for study. However, this may introduce serious inaccuracy into the analytic results, not to mention that some important metrics cannot even be calculated. In this paper, we crawl the entire social network of Swarm, a leading mobile social app with more than 60 million users, using a distributed approach. Based on the crawled massive user data, we conduct a data-driven study to get a comprehensive picture of the whole Swarm social network. This paper provides a deep analysis of social interactions between Swarm users, and reveals the relationship between social connectivity and check-in activities.Peer reviewe

Innovation: Integration of Random Variation and Creative Synthesis

Sarah Harvey has developed an important model called creative synthesis for the use of dialectical reasoning in creative endeavors. This model is put in direct opposition to the evolutionary model called random variation, which, according to Harvey, promotes incremental innovation, while creative synthesis promotes radical innovation. In emphasizing the affirmative stage of the dialectical process, creative synthesis offers a description of how groups can be consistently successful in creative endeavors through collective attention, enabling ideas, and building on similarities. We propose that creative synthesis is not a rival to but an extension of random variation and that the same dialectical reasoning used by Harvey allows us to integrate the two models into a more versatile hybrid: evolutionary synthesis. We contend that the hybrid model better reflects the complexity of reality and avoids the problem of routinization. It appears that innovation is all about Darwin and Marx.Keywords: Evolutionary Theory, Evolutionary synthesis, Creativity, Creative synthesis, Evolution, Innovation, Dialectics, Random variatio

Management Innovation and Firm Performance: An Integration of Research Findings

While the effect of technological innovations (TI) on firm performance is established, performance contributions of management innovations (MI) is as yet undetermined. Theoretical discourse on the motivation for the adoption of MIs questions their performance outcome, and an integration of empirical research of the MI-performance relationship is lacking. This study thus examines three questions: (1) is the adoption of MI beneficial to organizations; (2) is the impact of MI on performance at par with that of TI; and (3) what are the potential sources of inconsistency in the MI-performance relationship? We quantitatively integrate the empirical findings using 52 independent samples from 44 articles published in peer-reviewed journals via two different procedures―support score and meta-analysis―for complementarity and reliability. The results from both procedures indicate that: (1) MI positively affects performance; (2) the direction and strength of the effect of MI on performance does not differ from that of TI; and (3) industrial sector (manufacturing vs. service) and construct measurement (both innovation and performance) moderate the MI-performance relationship. We discuss the implications of our findings for future research on innovation and performance in organizations

Energy transfer in zinc porphyrin–phthalocyanine heterotrimer and heterononamer studied by fluorescence resonance energy transfer (FRET)

Two or eight zinc triphenyl porphyrins were conjugated with Zn-phthalocyanine or H2-phthalocyanine to form ZnPc–(ZnTPP)2, ZnPc–(ZnTPP)8, H2Pc–(ZnTPP)2 and H2Pc–(ZnTPP)8. Energy transfers from the porphyrin moiety to phthalocyanine part were quantitatively studied with the modality of fluorescence resonance energy transfer (FRET). By measuring the fluorescence increment from the phthalocyanine moiety and the decrease from porphyrin part under selective excitation at the B band of the porphyrin part in those conjugated compounds and their equimolar mixture of compositions, energy transfer efficiencies were estimated to be 90% for H2Pc–(ZnTPP)8 and ZnPc–(ZnTPP)8, and 60%, 30% for ZnPc–(ZnTPP)2 and H2Pc–(ZnTPP)2, respectively

The relationship between team autonomy and new product development performance under different levels of technological turbulence

Operations management researchers have frequently suggested that autonomy can motivate teams to actively and flexibly adapt to fast-changing environments, fostering innovation and creative problem solving. However, empirical studies have not consistently supported the benefits of team autonomy. We articulate the behavioral and mechanistic effects of team autonomy by integrating operations management and behavioral literatures. Further, we view team autonomy as a bipolar factor and argue that both the behavioral and mechanistic effects of team autonomy on operational outcomes are non-linear. Drawing on information processing theory, we propose that the benefits of team autonomy depend on the degree of technological turbulence. A study of 212 new product development projects supports these propositions. Specifically, the relationship between team autonomy and operational outcomes is ∩-shaped in technologically turbulent environments and U-shaped in technologically stable environments. Further, operational outcomes mediate the relationships between team autonomy and product success. We discuss the theoretical implications regarding new product development, operations management, the bipolarity of autonomy, and information-processing theory.Keywords: Mechanistic effect, New product development, Team autonomy, Behavioral effect, Technological turbulenc