10 research outputs found

    Measurement framework for assessing disruptive innovations

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    Assessing potential disruptiveness of innovations is an important but challenging task for incumbents. However, the extant literature focuses only on technological and marketplace aspects, and most of the documented methods tend to be case specific. In this study, we present a multidimensional measurement framework to assess the disruptive potential of product innovations. The framework is designed based on the concept that the nature of disruptive innovations is multidimensional. Three aspects are considered, i.e., technological features, marketplace dynamics and external environment. Ten indicators of the three categories are proposed and then connected based on the conceptual and literature analysis. Three innovations, namely, WeChat (successful), Modularised Mobile Phone (failed) and Virtual Reality/Augmented Reality (ongoing), are selected as case studies. A panel of industrial experts with PhD degree in engineering is surveyed. The survey results are calculated and analysed according to the framework and then compared against the developments of the innovations. We also check the robustness of this framework by surveying other groups of people, and the results are nearly identical to the previous findings. This study enables a systematic assessment of disruptive potential of innovations using the framework, providing insights for decisions in product launch and resource allocation.fi=vertaisarvioitu|en=peerReviewed

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    A Framework for Assessing Green Capacity Utilization Considering CO2 Emissions in China’s High-Tech Manufacturing Industry

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    China’s high-tech manufacturing industry has become the mainstay of the country’s domestic industrial transformation and upgrading. However, in recent years, the industry has experienced huge blind expansion under policy stimulus, which is not good for long-term industrial development. Therefore, this article attempts to explore the extent to which such an important and critical industry in China utilizes its production capacity and provides a basis for future policymaking. Coupled with the country’s increasing emphasis on the green and low-carbon development of the industry, this article extends the green and low-carbon thinking based on capacity utilization, namely green capacity utilization (CU). On this basis, the study empirically investigates the green CU of the high-tech manufacturing industry in 28 provinces in mainland China from 2010 to 2015. In performing the investigation, the inputs were divided into (quasi-)fixed and variable inputs, and an assessment framework was established based on the data envelopment analysis (DEA) method. Moreover, optimal variable inputs are also available as by-products within the assessment framework. The results were as follows: First, China’s high-tech manufacturing industry showed an excellent overall performance in green CU. Moreover, half of the provinces were at fully utilized capacity, and half were under-utilized. On average, there was a slight deterioration in green CU. Second, the results showed regional differences. The western region had the highest green CU followed by the middle and northeastern regions, and the eastern region had the lowest green CU. Third, regarding the optimal variables inputs, the total amount of labor in China’s high-tech manufacturing industry met the demand, but the distribution was uneven. Fourth, the scale of traditional energy consumption needs to be reduced both in individual provinces and in general. These conclusions have implications for the formulation of policies to promote the green development of China’s high-tech manufacturing industry

    Existence of subgraph with orthogonal (g,f)-factorization

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    The role of national carbon pricing in phasing out China's coal power

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    Summary: As the country with the world's largest coal power capacity, China is launching a national carbon market. How the carbon pricing may contribute to phasing out China's coal power is a great concern. We collect full-sample data set of China's 4540 operating coal plant units and develop a stochastic Monte-Carlo financial model to assess the financial sustainability of the plant operation. Although China's coal plants have long residual technical lifetime, their operations are close to the break-even state. Even with low carbon price of 50 CNY/tCO2 growing at 4%/y and the permits being fully auctioned, the average residual lifetime of all the plants will be reduced by 5.43 years, and the cumulative CO2 emission from 2020 to 2050 will be reduced by 22.73 billion ton. The spatial disparity in the carbon pricing effect is significant, and the western regions are more vulnerable to the carbon pricing risk than the eastern regions
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