Fuzzy multiple attribute decision-making model for synergic knowledge innovation in supply chain

The procedure of supply chain development is the process of continuously congregating knowledge and transforming knowledge.First,the precondition of synergic knowledge innovation in the supply chain is narrated.Then the characteristics of synergic knowledge innovation in the supply chain are analyzed,including complexity,accumulating and evolving process,and the cooperation of members and network integration.Due to the characteristics of multi-factors and uncertainties of the supply chain system,the fuzzy multi-attribution group decision-making model is introduced to solve the involved problem of synergic knowledge innovation in the supply chain.After elaborating on steps of using the fuzzy multiple attribute decision-making(MADM)model,the procedure of decision making for synergic knowledge innovation in the supply chain is explained from an example in the application of a fuzzy MADM model.The fuzzy MADM model,which amalgamates intuition and resolution decision-making can effectively improve the rationality of decision-making for synergic knowledge innovation in the supply chain.

Factors influencing knowledge contribution:An empirical investigation of social networking website users

Purpose: In the Web 2.0 era,leveraging the collective power of user knowledge contributions has become an important part of the study of collective intelligence. This research aims to investigate the factors which influence knowledge contribution behavior of social networking sites(SNS) users.Design/methodology/approach: The data were obtained from an online survey of 251 social networking sites users. Structural equation modeling analysis was used to validate the proposed model.Findings: Our survey shows that the individuals' motivation for knowledge contribution,their capability of contributing knowledge,interpersonal trust and their own habits positively influence their knowledge contribution behavior,but reward does not significantly influence knowledge contribution in the online virtual community.Research limitations: Respondents of our online survey are mainly undergraduate and graduate students. A limited sample group cannot represent all of the population. A larger survey involving more SNS users may be useful.Practical implications: The results have provided some theoretical basis for promoting knowledge contribution and user viscosity.Originality/value: Few studies have investigated the impact of social influence and user habits on knowledge contribution behavior of SNS users. This study can make a theoretical contribution by examining how the social influence processes and habits affect one's knowledge contribution behavior using online communities.

Construction and application of knowledge graph for grid dispatch fault handling based on pre-trained model

With the construction of new power systems,the power grid has become extremely large,with an increasing proportion of new energy and AC/DC hybrid connections.The dynamic characteristics and fault patterns of the power grid are complex;additionally,power grid control is difficult,operation risks are high,and the task of fault handling is arduous.Traditional power-grid fault handling relies primarily on human experience.The difference in and lack of knowledge reserve of control personnel restrict the accuracy and timeliness of fault handling.Therefore,this mode of operation is no longer suitable for the requirements of new systems.Based on the multi-source heterogeneous data of power grid dispatch,this paper proposes a joint entity–relationship extraction method for power-grid dispatch fault processing based on a pre-trained model,constructs a knowledge graph of power-grid dispatch fault processing and designs,and develops a fault-processing auxiliary decision-making system based on the knowledge graph.It was applied to study a provincial dispatch control center,and it effectively improved the accident processing ability and intelligent level of accident management and control of the power grid.

Threat Modeling and Application Research Based on Multi-Source Attack and Defense Knowledge

Cyber Threat Intelligence(CTI)is a valuable resource for cybersecurity defense,but it also poses challenges due to its multi-source and heterogeneous nature.Security personnel may be unable to use CTI effectively to understand the condition and trend of a cyberattack and respond promptly.To address these challenges,we propose a novel approach that consists of three steps.First,we construct the attack and defense analysis of the cybersecurity ontology(ADACO)model by integrating multiple cybersecurity databases.Second,we develop the threat evolution prediction algorithm(TEPA),which can automatically detect threats at device nodes,correlate and map multisource threat information,and dynamically infer the threat evolution process.TEPA leverages knowledge graphs to represent comprehensive threat scenarios and achieves better performance in simulated experiments by combining structural and textual features of entities.Third,we design the intelligent defense decision algorithm(IDDA),which can provide intelligent recommendations for security personnel regarding the most suitable defense techniques.IDDA outperforms the baseline methods in the comparative experiment.

Understanding the factors influencing user intention to continue contributing knowledge in social Q&A communities

Purpose:A social question & answer(SQA) community's long-term sustainability depends on its members' willingness to stay and contribute their knowledge continuously in the community.This research aims to investigate the critical factors which influence users' intention to continue contributing knowledge in the SQA community.Design/methodology/approach:Grounded on information systems(IS) continuance theory,this study put forward a model of the factors that influence SQA community members' intention to continue contributing knowledge.Survey was conducted to gather data from knowledge contributors of four major Chinese SQA communities(Baidu Knows,Sina iAsk,Soso Ask and Yahoo! Knowledge).By using the partial least squares(PLS) technique,research hypotheses derived from the proposed model were empirically validated.Findings:Except enjoyment in helping others and knowledge self-efficacy,all other factors including extrinsic reward,reputation enhancement,realization of self-worth,perceived usefulness,attitude towards knowledge contribution,and satisfaction exert significant impacts on users' continuance intentions in an SQA community.Research limitations:First,important factors such as the ease of use of information systems which may influence users' continuance intentions were not investigated in the study.Second,the study sample needs to be enlarged,and users of smaller SQA communities should also be included,to make the results more representative.Practical implications:This study will help SQA community designers and managers develop or improve incentive mechanisms to attract more people to contribute their knowledge and promote the development of the SQA community.Originality/value:This study improves the previous research models and puts forward a model of user continuance intention to contribute knowledge in an SQA community.It will extend the understanding of SQA community users' intention to continue contributing knowledge by distinguishing these users' different roles and focusing only on knowledge contributors.

Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance

With the development of intelligent vehicles and autonomous driving technology,the safety of vulnerable road user(VRU)in traffic has been more guaranteed,and many research achievements have been made in the key area of collision avoidance decision-making methods.In this paper,the knowledge mapping method is used to mine the available literature in depth,and it is found that the research focus has shifted from the traditional accident cause analysis to emerging deep learning and virtual reality technology.This paper summarizes research on the three core dimensions of environmental perception,behavior cognition and collision avoidance decision-making in intelligent vehicle systems.In terms of perception,accurate identification of pedestrians and cyclists in complex environments is a major demand for VRU perception;in terms of behavior cognition,the coupling of VRU intention identification and motion trajectory prediction and other multiple factors needs further research;in terms of decision-making,the intention identification and trajectory prediction of collision objects are not included in the risk assessment model,and there is a lack of exploration specifically for cyclists'collision risk.On this basis,this paper provides guidance for the improvement of traffic safety of contemporary VRU under the conditions of intelligent and connected transportation.

A Knowledge Model System for Wheat Production Management

A knowledge model with temporal and spatial characteristics for the quantitative design of a cultural pattern in wheat production, using systems analysis and dynamic modeling techniques, was developed for wheat management, as a decision-making tool in digital farming. The fundamental relationships and algorithms of wheat growth indices and management criteria to cultivars, ecological environments, and production levels were derived from the existing literature and research data to establish a knowledge model system for quantitative wheat management using Visual C^＋＋. The system designed a cultural management plan for general management guidelines and crop regulation indices for timecourse control criteria during the wheat-growing period. The cultural management plan module included submodels to determine target grain yield and quality, cultivar choice, sowing date, population density, sowing rate, fertilization strategy, and water management, whereas the crop regulation indices module included submodels for suitable development stages, dynamic growth indices, source-sink indices, and nutrient indices. Ewluation of the knowledge model by design studies on the basis of data sets of different eco-sites, cultiwrs, and soil types indicated a favorable performance of the model system in recommending growth indices and management criteria under diverse conditions. Practical application of the knowledge model system in comparative field experiments produced yield gains of 2.4% to 16.5%. Thus, the presented knowledge model system overcame some of the difficulties of the traditional wheat management patterns and expert systems, and laid a foundation for facilitating the digitization of wheat management.

A Dynamic Knowledge Model for Nitrogen Fertilizationin Wheat Management

By analyzing and extracting the research progress on nitrogen fertilization in wheat, a dynamic knowledge model for management decision-making on total nitrogen rate, ratios of organic to inorganic and of basal to dressing nitrogen under different environments and cultivars in wheat was developed with principle of nutrient balance and by integrating the quantitative effects of grain yield and quality targets, soil characters, variety traits and water management levels. Case studies on the nitrogen fertilization model with the data sets of different eco-sites, cultivars, soil fertility levels, grain yield and quality targets and water management levels indicate a good performance of the model system in decision-making and wide applicability.

Research on knowledge reasoning of TCM based on knowledge graphs

With the widespread use of Internet,the amount of data in the field of traditional Chinese medicine(TCM)is growing exponentially.Consequently,there is much attention on the collection of useful knowledge as well as its effective organization and expression.Knowledge graphs have thus emerged,and knowledge reasoning based on this tool has become one of the hot spots of research.This paper first presents a brief introduction to the development of knowledge graphs and knowledge reasoning,and explores the significance of knowledge reasoning.Secondly,the mainstream knowledge reasoning methods,including knowledge reasoning based on traditional rules,knowledge reasoning based on distributed feature representation,and knowledge reasoning based on neural networks are introduced.Then,using stroke as an example,the knowledge reasoning methods are expounded,the principles and characteristics of commonly used knowledge reasoning methods are summarized,and the research and applications of knowledge reasoning techniques in TCM in recent years are sorted out.Finally,we summarize the problems faced in the development of knowledge reasoning in TCM,and put forward the importance of constructing a knowledge reasoning model suitable for the field of TCM.

应用ISI Web of Knowledge正确选择SCIE微生物研究领域投稿期刊

在介绍ISI Web of Knowledge,ISI Web of Science,Journal Citation Reports,Science CitationIndex Expanded等情况的基础上,较为详细地分析了如何获取SCIE微生物研究领域来源期刊信息,如何利用SCIE和JCR检索与分析系统来选择投稿期刊以及如何快捷投稿的方法。

Process Auxiliary Decision-making Based on Rough Sets and Regulation Distance Computing

Computer aided process planning（CAPP） is an important content of computer integrated manufacturing, and intelligentizing is the orientation of development of CAPP. Process planning has characters of empirical and time-consuming to finalize, and the same technical aim always can be achieved by different process schemes, so intelligentizing of process decision making always be a difficult point of CAPP and computer integrated manufacturing （CIM）. For the purpose of intelligent aided process decision making and reuse of process resource, this paper proposed a decision making method based on rough sets（RS） and regular distance computing. The main contents and methods of process planning decision making are analyzed under agile response manufacturing environment, the concept of process knowledge granule is represented, and the methods of process knowledge granule partitioning and granularity analysis are put forward. Based on the theory of RS and combined the method of process attributes importance identification, the paper brought forward a computing model for process scheme regulation distance under the same attribute conditions, and conflict resolution strategy was introduced to acquire process scheme fit for actual situation of enterprise＇s manufacturing resources, so as to realize process resources＇ conflict resolution and quick excavate and reuse of enterprises＇ existing process knowledge, to advance measures of process decision making and improve the rationality and capability of agile response of process planning.

Innovations in education:A prospective study of storytelling narratives to enhance hepatitis C virus knowledge among substance users

BACKGROUND Even though substance users have the highest hepatitis C virus(HCV)burden,many lack knowledge about the infection.Lack of knowledge is an important obstacle to pursuing HCV care.Although printed materials are conventionally utilized to disseminate HCV-related knowledge,narrative story-telling videos may be an alternative.Data are extremely limited,however,in the ability of storytelling videos to increase HCV knowledge among substance users.In this study,we hypothesized that a story-telling narrative video would increase substance user’s immediate and 1-month HCV-related knowledge compared to a printed format.AIM To assess immediate and 1-month HCV-related knowledge retention among substance users comparing education delivered via a storytelling narrative video compared to a printed format.METHODS We conducted a prospective matched,case-control study among substance users actively prescribed buprenorphine enrolled from two sites.The intervention site received the video and the control site,the brochure.Participants(n=176)were matched on age,gender,and race.We obtained extensive patient and stakeholder input on the video’s design,validated the video’s content,and developed a recruitment plan to guide participant enrollment.Knowledge was assessed by administration of a 25-item instrument immediately before,immediately after,or one month after the intervention.Data were analyzed using nonparametric and generalized linear mixed-effects models.RESULTS We recruited a total of 176 substance users,90 and 86 individuals,from each site,respectively.One-month follow up occurred in 92%and 94%of enrollees in the control and intervention groups,respectively.In comparison with the pre-intervention scores,immediate knowledge recall increased significantly for both the intervention(P<0.0001)and control(P<0.0001)groups.Multivariate modeling revealed a significant improvement in HCV-related knowledge and retention(P=0.033)among participants who viewed the storytelling video.CONCLUSION Storytelling narratives emphasizing HCV education appear to be an effective method to increase HCV-related knowledge among substance users.They should become an educational cornerstone to promote HCV management among this population.

Use of Wikis in Organizational Knowledge Management

This article presents the mapping of wiki tool functions in the organizational processes of knowledge management. Mapping these functions and their individual weights in the overall process will identify opportunities for decision-making and the optimization of knowledge sharing, a recognized asset in differentiation and organizational competitiveness. This is an exploratorydescriptive case study based on data collected from a questionnaire applied to 80 IT workers employed at a multinational company in Brazil. The use of mixed methods in data analysis was complemented by content analysis of the research corpus created. A theoretical model is graphically developed following Nonaka and Takeuchi’s knowledge spiral model (1997), a conventional model in knowledge management. In addition, an indicator of the individual contribution of each step in the conversion process of tacit into explicit knowledge is introduced. This case study alone does not enable a generalization of the findings. Therefore, a replication of the process and especially multiple testing of the constructed indicator are indispensable to its validation. Validation of the use of the wiki tool functions will allow the future development of measurements that can be directly employed in the organizational decision-making process. Statistically, a theoretical model is qualitatively discussed, which enables the construction of an initial indicator of the weight of individual contribution of steps in the knowledge generation process using the knowledge spiral model.

组织支持对专利密集型企业研发人员创新绩效的影响——以知识贡献为中介

基于社会交换理论,以46家专利密集型企业的150名专利研发人员为调研对象,并采用研发人员参与研发的专利数量作为创新绩效的衡量指标,探讨组织支持与研发人员创新绩效之间的关系以及知识贡献(显性知识贡献和隐性知识贡献)的中介作用和成长需求强度的调节作用。结果表明:组织支持与研发人员绩效呈正相关,研发人员的创新绩效可以从更高水平的隐性知识贡献中受益,组织支持对隐性知识贡献的积极效应部分由成长需求强度来调节。由此提出企业应该通过制定相关民主政策等方法来塑造高水平的组织支持、注重组织内部评估体系以增强员工贡献的意识等相关建议。

虚拟社区激励措施对用户知识贡献倾向的影响机理研究

基于SOR理论和隐马尔科夫模型,采用马蜂窝旅游虚拟社区用户知识贡献行为数据和激励数据,探讨外在激励如何通过用户知识贡献倾向影响其知识贡献行为。研究表明:依据构建的隐马尔科夫模型,挖掘用户具有沉默、参与、积极3种隐含的知识贡献倾向;同一知识贡献倾向下,用户首次回答问题时间越早、旅游经验越丰富、累计贡献数量越多,用户知识贡献数量就越多;物质激励、精神激励以及二者联合激励与用户动态变化知识贡献倾向匹配,才能取得正向的激励作用。

创新生态下知识主体协同组合对区域创新的贡献路径及演化趋势:基于动态定性比较分析(QCA)方法

厘清如何协同知识主体、辨析创新贡献路径是提高中国创新水平和增强创新能力的关键。在对案例进行研究和过程追踪的基础上,利用模糊定性比较分析(fsQCA)方法对2004—2019年中国29个省份的知识主体组合和时间演化进行分析;同时,对多个省份的不同知识主体进行动态定性比较分析,以寻求不同时期条件组态的贡献变化情况。结果表明:多元协同治理型的均衡知识主体贡献是促进区域创新发展的相对合理组态,而在2004—2019年期间,29个省份知识主体的创新贡献存在要素波动,并且不同时段的组态贡献存在不均衡的情况,以企业知识主体为主导的理论市场推动型呈现整合主导轨迹、以高校知识主体为主导的基础研发支柱型呈现缓冲主导轨迹;企业和高校在创新贡献中长期占重要地位,知识主体贡献结构较为稳固集中,但逐渐呈现出散点趋势。因此,需要根据区域现实情况因地制宜,在优化创新环境的基础上有效发挥知识主体的组合效能,推动区域创新能力的提升与发展。

我国图书馆学领域核心知识元及其组合的新颖度和贡献度分析

文章以6种图书馆学核心期刊为数据源,抽取其2012-2021年刊载的代表性论文,分析论文中研究问题、研究方法的表述特点,构建问题、方法抽取规则,建立学科领域知识元词典;再抽取2019-2021年样本刊刊载的全部论文的问题、方法主题,通过编程建立问题、方法及其组合的共现关系,并测度分析问题、方法及其组合的新颖度与贡献度间的关系;最后抽取2022年至2023年10月样本刊刊载的相关论文,计算测度2019-2021年图书馆学领域研究问题、研究方法及其组合的新颖度在此阶段与贡献度之间的关系,以探究各类问题、方法及其组合的演化发展。研究发现,从问题、方法及其组合的知识元角度进行分析的方法能够有效发现学科领域的新问题、新方法,老问题、老方法,以及问题、方法的多种组合形式;各类问题、方法及其组合的演化发展为分析学科领域研究态势提供了良好的背景知识。

数字化社会的知识“面相”与教育应对

“什么是知识”是一个非常复杂的问题。常见的回答主要从信念、经验与信息等角度理解知识,不同“知识型”既内隐知识变迁的社会逻辑,也与技术有着密切关联。受制于哲学—技艺的二元结构,古典社会的知识既具较强的本体论色彩,也有高度的个人性;伴随知识理性向技术理性的转变,工业社会的知识被打上了浓厚的方法论与技术性烙印。进入数字化社会,随着“知识生命周期”的不断缩短与现代技术的全面介入,知识愈加明显地表现出“碎片化”“资本化”与“娱乐化”倾向,即知识不断分散、粒度越小但形式越多,非系统性等特征与日突出;知识的市场价值逐渐增强,人们越来越强调其预付价值性;受大众娱乐性心理推动,知识产品中的娱乐元素不断涌入。这不仅意味着知识本身的“信任危机”,也对作为典型知识世界的教育世界提出了严峻挑战。因应于此,今日教育可循重构知识的整体性、强化知识的贡献性与重建知识的严肃性等路径予以回应。现代技术之于知识的“药理学”效应正在加速放大,亟须以批判性的方式打开面向知识与教育的更多可能。

数字资本视角下知识问答社区知识交流效果影响机制研究

目前知识问答社区繁荣发展,但也面临着用户流失、知识增长缓慢、知识质量难以保证的问题,并由此导致社区内的知识交流效果不佳。理解知识交流效果的影响机制能够帮助个体充分利用知识问答社区实现高质量知识交流,同时为知识问答社区提供持续发展的路径。为此,文章基于数字资本理论视角构建了组态分析理论模型,采用定性比较分析方法,探讨数字资本与社会资本、文化资本和经济资本的组合效应。结果表明,知识问答社区的知识交流效果与其前因条件之间存在因果复杂性:就感知贡献而言,社会资本和文化资本的组合是提升感知贡献的核心条件,但数字资本可弥补其中社会资本或文化资本的缺失;就感知学习而言,数字资本、社会资本和经济资本是提升感知学习的核心条件。

不同主体对研发投入要素使用效率研究

从成果产出的投入要素出发,将科技成果归结为R&D资本、R&D人员和剩余要素综合作用的产出,构造科技成果生产函数。运用国内2011—2020年相关面板数据对不同主体的科技成果的要素研发效率进行测算,分析不同主体的投入要素的使用效率。通过分析不同主体投入要素对科技成果产出贡献份额,为我国合理配置有效科技投入资源、提高研发资源利用效率和促进科技成果最大化产出提供参考。