分析与创新管理:大数据发挥作用吗?

Arthur Paul Christenson
{"title":"分析与创新管理:大数据发挥作用吗?","authors":"Arthur Paul Christenson","doi":"10.14311/bit.2023.01.07","DOIUrl":null,"url":null,"abstract":"This particular analysis explores the connection between firms' application of data analytics (specifically it's attributes) together with the revolutionary functionality of company. The other goal is assessing whether big amount of information is always better to get business innovation. The study collected information via questionnaire survey from control staffs of 250 businesses in both developed and developing economies. Statistical tools like Multiple regression methods and t-test were used to analyse the information. The study found suggestive evidence demonstrating that data analytics is a relevant determinant of a firm getting innovator and bring innovative services and products on the industry. The study even discovered that big volume of information isn't always better info to drive innovation. The results imply that firms are required to use big data analytics to remain imaginative and also have a competitive advantage. Unlike previous studies which approached large details as whole, this particular study addresses different ingredients of big data like variety, velocity, volume, and the individual impacts of theirs on innovation of organizations across the evolved economies.","PeriodicalId":150829,"journal":{"name":"Business & IT","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analytics and innovation management: Does big data play any role?\",\"authors\":\"Arthur Paul Christenson\",\"doi\":\"10.14311/bit.2023.01.07\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This particular analysis explores the connection between firms' application of data analytics (specifically it's attributes) together with the revolutionary functionality of company. The other goal is assessing whether big amount of information is always better to get business innovation. The study collected information via questionnaire survey from control staffs of 250 businesses in both developed and developing economies. Statistical tools like Multiple regression methods and t-test were used to analyse the information. The study found suggestive evidence demonstrating that data analytics is a relevant determinant of a firm getting innovator and bring innovative services and products on the industry. The study even discovered that big volume of information isn't always better info to drive innovation. The results imply that firms are required to use big data analytics to remain imaginative and also have a competitive advantage. Unlike previous studies which approached large details as whole, this particular study addresses different ingredients of big data like variety, velocity, volume, and the individual impacts of theirs on innovation of organizations across the evolved economies.\",\"PeriodicalId\":150829,\"journal\":{\"name\":\"Business & IT\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Business & IT\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14311/bit.2023.01.07\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Business & IT","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14311/bit.2023.01.07","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

这个特别的分析探讨了公司对数据分析的应用(特别是它的属性)与公司的革命性功能之间的联系。另一个目标是评估大量信息是否总是更好地实现业务创新。该研究通过问卷调查收集了发达经济体和发展中经济体250家企业的管理人员的信息。采用多元回归法、t检验等统计工具对信息进行分析。研究发现,数据分析是企业获得创新者并为行业带来创新服务和产品的相关决定因素。研究甚至发现,在推动创新方面,大量信息并不总是更好的信息。研究结果表明,企业需要利用大数据分析来保持想象力,同时拥有竞争优势。与以往的研究不同,该研究着眼于大数据的不同组成部分,如多样性、速度、数量,以及它们对发展中经济体组织创新的个人影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analytics and innovation management: Does big data play any role?
This particular analysis explores the connection between firms' application of data analytics (specifically it's attributes) together with the revolutionary functionality of company. The other goal is assessing whether big amount of information is always better to get business innovation. The study collected information via questionnaire survey from control staffs of 250 businesses in both developed and developing economies. Statistical tools like Multiple regression methods and t-test were used to analyse the information. The study found suggestive evidence demonstrating that data analytics is a relevant determinant of a firm getting innovator and bring innovative services and products on the industry. The study even discovered that big volume of information isn't always better info to drive innovation. The results imply that firms are required to use big data analytics to remain imaginative and also have a competitive advantage. Unlike previous studies which approached large details as whole, this particular study addresses different ingredients of big data like variety, velocity, volume, and the individual impacts of theirs on innovation of organizations across the evolved economies.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信