Production Ability and economic growth     

《Research Policy》2022,51(8):104153

Cities and countries undergo constant structural transformation. Industries need many inputs, such as regulations, infrastructure or productive knowledge, which we call capabilities. And locations are successful in hosting industries insofar as the capabilities that they can provide. We propose a capabilities-based production model and an empirical strategy to measure the Sophistication of a product and the Production Ability of a location. We apply our framework to international trade data and employment data in the United States, recovering measures of Production Ability for countries and cities, and the Sophistication of products and industries. We show that both country- and city-level measures have a strong correlation with income and economic growth at different time horizons. Product Sophistication is positively correlated with indicators of human capital and wages. Our model-based estimations predict product appearances and disappearances through the extensive margin.  相似文献   

The time and frequency of unrelated diversification     

《Research Policy》2022,51(8):104323

Economic diversification—the process by which locations enter new economic activities—is known to be a combination of related and unrelated diversification. Related diversification is—on average—more frequent, but unrelated diversification is nevertheless considered important to avoid economic lock-in. Here, we study the frequency and timing of unrelated diversification using two international trade datasets at the country level. We find that related diversification is more frequent for countries at low levels of development but becomes less frequent as countries climb the complexity ladder. These findings contribute to our understanding of the role of relatedness in the diversification of economies at different levels of complexity.  相似文献   

Competing Standard-Setting Organizations: A Choice Experiment     

《Research Policy》2022,51(2):104427

Standard-setting organizations (SSOs) establish goal-directed networks for innovators to jointly shape technology and markets through standards. The degree to which this can succeed depends to a large extent on network characteristics, which may differ substantially between SSOs. Many technological fields face intense competition between SSOs. Choosing the right one is thus a key strategic decision for innovators. Simultaneously, SSOs must reflect members’ preferences in their network set-ups and governance. Yet, little is known about these preferences. Based on extant literature, we derive hypotheses about how three themes of network attributes (membership base, rules, transaction costs) and contextual factors drive decision makers’ preferences. We conduct a comprehensive choice experiment with 141 standardization professionals in the Internet of Things field. Based on our data, we provide a more realistic indication of what firms value in SSOs than has been previously available. We also discuss our results’ implications for studying networks in other contexts.  相似文献   

Big data-assisted social media analytics for business model for business decision making system competitive analysis     

《Information processing & management》2022,59(1):102762

Business is based on manufacturing, purchasing, selling a product, and earning or making profits. Social media analytics collect and analyze data from various social networks such as Facebook, Instagram, and Twitter. Social media data analysis can help companies identify consumer desires and preferences, improve customer service and market analytics on social networks, and smarter product development and marketing investments. The business decision-making process is a step-by-step process that enables employees to resolve challenges by weighing evidence, evaluating possible solutions, and selecting a route. In this paper, Big Data-assisted Social Media Analytics for Business (BD-SMAB) Model increases awareness and affects decision-makers in marketing strategies. Companies can use big data analytics in many ways to enhance management. It can evaluate its competitors in real-time and change prices, make deals better than its competitors' sales, analyze competitors' unfavorable feedback and see if they can outperform that competitor. The proposed method examines social media analysis impacts on different areas such as real estate, organizations, and beauty trade fairs. This diversity of these companies shows the effects of social media and how positive decisions can be developed. Take better marketing decisions and develop a strategic approach. As a result, the BD-SMAB method enhance customer satisfaction and experience and develop brand awareness.  相似文献   

Reuse of knowledge by efficient data analytics to fix societal challenges     

《Information processing & management》2022,59(1):102764

Technology-intensive industries spend huge resources in the production of products to commercialize successful products. If the appetite on the market continues to change, the capacity to rapidly and cost-effectively refresh the offerings is an important competitive advantage. Even if components and designs need to be modified as new models are released, their underlying technology and designs can generally be reused to allow rapid economic development. Data are considered an important raw material that can influence multidisciplinary analysis, government, and business efficiency. In this paper, the Efficient data analytics (EDA) method has been suggested to fix societal challenges. The proposed methods aim to share the authors' views and perspectives on the emerging opportunities and challenges of the efficient data revolution.EDA provides four key aspects of technology reuse: strategy, method, culture, and information technology. The dimensions are further broken down into concepts supporting this technology reuse, including design on the technology platform and the reuse assessments. In practice, the system can evaluate an organization's existing reuse capabilities and offer an overall theoretical review of activities promoting technology reuse. To prove the system's concepts, industrial scenarios highlighting real questions of technological growth are used. Besides, the possible societal benefits of EDA in six ways are illustrated: enhanced decision management and incident prediction, data-informed technologies and innovative market models, direct social and climate benefits, community engagement, accountability, and public trust. Some best practice is suggested to capture these advantages. The experimental results suggested EDA increases reusability knowledge in the organization (96.3%), operational cost (95.1%), prediction ratio (97.4%), Community engagement ratio (94.1%), and public trust (98.5%).  相似文献   

BCMF: A bidirectional cross-modal fusion model for fake news detection     

《Information processing & management》2022,59(5):103063

In recent years, fake news detection has been a significant task attracting much attention. However, most current approaches utilize the features from a single modality, such as text or image, while the comprehensive fusion between features of different modalities has been ignored. To deal with the above problem, we propose a novel model named Bidirectional Cross-Modal Fusion (BCMF), which comprehensively integrates the textual and visual representations in a bidirectional manner. Specifically, the proposed model is decomposed into four submodules, i.e., the input embedding, the image2text fusion, the text2image fusion, and the prediction module. We conduct intensive experiments on four real-world datasets, i.e., Weibo, Twitter, Politi, and Gossip. The results show 2.2, 2.5, 4.9, and 3.1 percentage points of improvements in classification accuracy compared to the state-of-the-art methods on Weibo, Twitter, Politi, and Gossip, respectively. The experimental results suggest that the proposed model could better capture integrated information of different modalities and has high generalizability among different datasets. Further experiments suggest that the bidirectional fusions, the number of multi-attention heads, and the aggregating function could impact the performance of the cross-modal fake news detection. The research sheds light on the role of bidirectional cross-modal fusion in leveraging multi-modal information to improve the effect of fake news detection.  相似文献   

Fake news detection via knowledgeable prompt learning     

《Information processing & management》2022,59(5):103029

The spread of fake news has become a significant social problem, drawing great concern for fake news detection (FND). Pretrained language models (PLMs), such as BERT and RoBERTa can benefit this task much, leading to state-of-the-art performance. The common paradigm of utilizing these PLMs is fine-tuning, in which a linear classification layer is built upon the well-initialized PLM network, resulting in an FND mode, and then the full model is tuned on a training corpus. Although great successes have been achieved, this paradigm still involves a significant gap between the language model pretraining and target task fine-tuning processes. Fortunately, prompt learning, a new alternative to PLM exploration, can handle the issue naturally, showing the potential for further performance improvements. To this end, we propose knowledgeable prompt learning (KPL) for this task. First, we apply prompt learning to FND, through designing one sophisticated prompt template and the corresponding verbal words carefully for the task. Second, we incorporate external knowledge into the prompt representation, making the representation more expressive to predict the verbal words. Experimental results on two benchmark datasets demonstrate that prompt learning is better than the baseline fine-tuning PLM utilization for FND and can outperform all previous representative methods. Our final knowledgeable model (i.e, KPL) can provide further improvements. In particular, it achieves an average increase of 3.28% in F1 score under low-resource conditions compared with fine-tuning.  相似文献   

中美欧内部数字治理格局比较研究          下载免费PDF全文

李昊林  王娟  谢子龙  王卓明  宋洁 《中国科学院院刊》2022,37(10):1376-1385

考察各国内部的数字治理格局,在认清现状的基础上,厘清其各自的内在生成逻辑,对于中国更好参与国际数字化发展而言至关重要。文章利用数字生态视角对中国、美国、欧盟（以下简称“中美欧”）内部数字治理格局进行了比较研究,试图阐明中美欧各自的数字生态发展模式,并分析发展模式与其数字规制体系之间的关系。研究发现,美国形成全要素领先的发展模式及以鼓励创新为核心的规制体系;欧盟国家多元的发展模式影响欧盟层面形成了以市场建构为核心的规制体系;中国的发展模式表现出应用驱动的特征,规制体系以发展与安全为双核心。文章据此对中国如何优化调整自身数字规制体系,转型升级自身数字生态发展模式提出建议。  相似文献   

数字化水平对制造企业商业模式创新的跨层次作用研究     

李盼盼  乔晗郭韬 《科研管理》2022,43(11):11-20

为揭示数字化水平对制造企业商业模式创新的影响,根据动态能力理论和商业模式冰山理论构建了地区数字化水平与动态能力对商业模式创新跨层次影响的理论模型,基于59个城市的415家制造企业样本数据,采用多层线性模型开展实证研究,并选取典型案例对实证结果进行了验证。研究表明：地区数字化水平对商业模式创新具有正向影响;吸收能力、适应能力和创新能力均对商业模式创新具有正向影响;吸收能力、适应能力与创新能力均正向调节地区数字化水平对商业模式创新的影响。本研究拓展了商业模式冰山理论的应用范畴,丰富了商业模式创新前因的研究成果,并为数字化环境下企业商业模式创新实践提供了指导依据。  相似文献   

Fine-grained citation count prediction via a transformer-based model with among-attention mechanism     

《Information processing & management》2022,59(2):102799

Previous studies have confirmed that citation mention and location reveal different contributions of the cited articles, and that both are significant in scientific research evaluation. However, traditional citation count prediction only focuses on predicting citation frequency. In this paper, we propose a novel fine-grained citation count prediction task (FGCCP), which aims to predict in-text citation count from each structural function of a paper separately. Specifically, we treated this task as a “sequence to sequence” issue and a multi-task learning job, in which both the inputs and the outputs are based on the sequence pattern of citations from different structural functions. To fulfill FGCCP, we proposed a transformer-based model (i.e. MTAT) in which a novel among-attention mechanism is employed. Based on an empirical study of full-text documents from PubMed Central Open Access Subset, our model achieves satisfactory prediction accuracy, and surpasses common machine learning and deep learning models on FGCCP. Moreover, we also discuss the potential role of the among-attention mechanism and the reason why our proposed model outperforms state-of-the-art strategies. FGCCP may provide more detailed decision-making evidence and evaluation basis for researchers in scientific research evaluation. In addition, MTAT is a general model which can be easily deployed in other multi-task learning jobs.  相似文献