From user-generated data to data-driven innovation: A research agenda to understand user privacy in digital markets     

《International Journal of Information Management》2021

In recent years, strategies focused on data-driven innovation (DDI) have led to the emergence and development of new products and business models in the digital market. However, these advances have given rise to the development of sophisticated strategies for data management, predicting user behavior, or analyzing their actions. Accordingly, the large-scale analysis of user-generated data (UGD) has led to the emergence of user privacy concerns about how companies manage user data. Although there are some studies on data security, privacy protection, and data-driven strategies, a systematic review on the subject that would focus on both UGD and DDI as main concepts is lacking. Therefore, the present study aims to provide a comprehensive understanding of the main challenges related to user privacy that affect DDI. The methodology used in the present study unfolds in the following three phases; (i) a systematic literature review (SLR); (ii) in-depth interviews framed in the perspectives of UGD and DDI on user privacy concerns, and finally, (iii) topic-modeling using a Latent Dirichlet allocation (LDA) model to extract insights related to the object of study. Based on the results, we identify 14 topics related to the study of DDI and UGD strategies. In addition, 14 future research questions and 7 research propositions are presented that should be consider for the study of UGD, DDI and user privacy in digital markets. The paper concludes with an important discussion regarding the role of user privacy in DDI in digital markets.  相似文献   

The intermediating role of organizational culture and internal analytical knowledge between the capability of big data analytics and a firm’s performance     

《International Journal of Information Management》2020

Firms are increasingly relying on business insights obtained by deploying data analytics. Analytics-driven business decisions have thus taken a strategic imperative role for the competitive advantage of a firm to endure. The extent and effectiveness through which business firms can actually derive benefits by deploying big data-based practices requires deep analysis and calls for extensive research. This study extends the big data analytics capability (BDAC) model by examining the mediatory effects of organizational culture (CL) between internal analytical knowledge (KN) and BDAC, as well as the mediating effects of BDAC between CL and firm performance. The findings bring into focus that CL plays the role of complementary mediation between BDAC and KN to positively impact firm performance (FP); BDAC also plays a similar mediatory role between CL and the performance of a firm.  相似文献   

Complementing subjective with objective data in analysing expertise: A machine-learning approach applied to badminton     

Olivier Dieu  Christophe Schnitzler  Clément Llena  François Potdevin 《Journal of sports sciences》2020,38(17):1943-1952

ABSTRACT

This study aimed to assess which combination of subjective and empirical data might help to identify the expertise level. A group of 10 expert coaches classified 40 participants in 5 different expertise groups based on the video footage of the rallies. The expertise levels were determined using a typology based on a continuum of 5 conative stages: (1) structural, (2) functional, (3) technical, (4) contextual, and (5) expertise. The video allowed empirical measurement of the duration of the rallies, and tri-axial accelerometers measured the intensity of the player’s involvement. A principal component analysis showed that two dimensions explained 54.9% of the total variance in the data and that conative stage and empirical parameters during rallies (duration, intensity of the game) were correlated with axis 1, whereas duration and acceleration data between rallies were correlated with axis 2. A random forest algorithm showed that among the parameters considered, acceleration, duration of the rallies, and time between rallies could predict conative stages with a prediction accuracy above possibility.

This study suggests that performance analysis benefits from the confrontation of subjective and objective data in order to design training plans according to the expertise level of the participants.  相似文献   

Score Reporting for Examinees with Incomplete Data on Large‐Scale Educational Assessments     

Sandip Sinharay 《Educational Measurement》2021,40(1):79-91

Technical difficulties occasionally lead to missing item scores and hence to incomplete data on computerized tests. It is not straightforward to report scores to the examinees whose data are incomplete due to technical difficulties. Such reporting essentially involves imputation of missing scores. In this paper, a simulation study based on data from three educational tests is used to compare the performances of six approaches for imputation of missing scores. One of the approaches, based on data mining, is the first application of its kind to the problem of imputation of missing data. The approach based on data mining and a multiple imputation approach based on chained equations led to the most accurate imputation of missing scores, and hence to most accurate score reporting. A simple approach based on linear regression performed the next best overall. Several recommendations are made regarding the reporting of scores to examinees with incomplete data.  相似文献   

Does an interactive table of contents promote learning from videos? A study of consultation strategies and learning outcomes     

Salomé Cojean  Eric Jamet 《British journal of educational technology : journal of the Council for Educational Technology》2022,53(2):269-285

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数据结构的对象化教学方式探讨与实践     

徐翀  徐建 《中国现代教育装备》2011,(9):104-106

数据结构是高等院校计算机专业的一门重要的专业课。就目前普遍采用的面向过程的教学方式的弊端,提出了进行对象化的教学方式。结合我院实践,提出了一系列的教学步骤,并对此作了分析和探讨。  相似文献   

浅析基于ETL技术和全表扫描哈希对比的数据同步方法     

王志学  麦晓冬  符睿 《广东轻工职业技术学院学报》2011,10(2):4-7

数据同步技术随着企业对各个信息系统之间数据共享的重视而变得越来越重要,数据同步的方法有很多,本文主要介绍基于ETL技术和基于全表扫描及哈希对比两种数据同步方法。基于ETL技术的数据同步是基于中间逻辑表完成数据转换,再通过主键和时间戳的对比而完成数据同步过程。本文以Kettle工具为例进行分析;基于全表扫描及哈希对比的数据同步是基于视图完成数据转换,再通过hash算法扫描对比而完成数据同步过程。  相似文献   

异构数据库更新同步研究与实现     

肖刚 《教育技术导刊》2019,18(10):182-185

数据库同步是实现不同系统之间数据共享的有效方法。现有异构数据库同步模型能有效解决记录的同步新增,但由于同步记录查询基于数据表名和关键字值,若不考虑同步数据库节点变化,将导致数据库不适用于某些遗留系统。针对该问题,提出同步控制和主从记录映射方法,在同步控制层记录主从记录映射关系。在采用双向中间件方法的同步技术基础上,设计基于标准数据格式的数据转换,降低数据转换模块开发维护成本,并根据模型应用WCF框架实现系统。实践应用表明,该模型可实现异构数库之间同步更新。  相似文献   

对清华大学2001—2006年在各省招生名额的分析     

郭伯良  许志勇 《考试研究》2006,(4)

用多水平模型对清华大学2001—2006年在全国各地的招生名额分配进行分析,结果显示,六年来在各地的名额分配差异显著,部分省份的名额显著低于全国平均水平,部分省市的名额显著高于全国平均水平。建议对有关高校招生指标在各省的分配情况进行进一步分析。  相似文献   

高等院校评价教师系统框架之数据来源分析     

郝春林  高俊玉 《教育教学论坛》2020,(13):26-27

高校评教是高校教育教学管理中的重要一环。文章针对目前已有的评教系统数据源单一、数据使用不充分、教师反馈不及时、师生互动性欠佳、学生评教积极性不高等现状,提出了一个高校评教系统新框架,以评教结果的使用范围为目的,反推出评教数据来源应具备多次性和多样性。每学期多次评教,实现教师与学生的互动,促进学生评教积极性,促进教师及时改进教学方法。评教人员除了学生之外,还应包括督导专家和往届生。  相似文献