C. Chong, Siti Zaleha Abdul Rasid, Haliyana Binti Khalid
{"title":"Typology of Big Data Analytics Capabilities in Malaysian Manufacturing Firms","authors":"C. Chong, Siti Zaleha Abdul Rasid, Haliyana Binti Khalid","doi":"10.1109/ICRIIS53035.2021.9617012","DOIUrl":null,"url":null,"abstract":"Firms' big data analytics capabilities (BDAC) are vital for firms to be more successful than their competitors over a long period. Although much literature has proven the relationship between BDAC and firms' competitiveness, there is a limited discussion on the precise degree to which sort of BDAC profiles are flawless. This paper segregates BDAC profiles for Malaysian manufacturing firms into three clusters which are low, medium and high performers in the level of leveraging BDAC. This paper aims to answer two research questions: 1) are there three clusters of firms in exercising BDAC? and 2) would the firm with a high level of BDAC accomplish better firm performance? An analysis of variance (ANOVA) demonstrates that these three clusters differ significantly in achieving firm performance. The finding recommends that manufacturers with exercising a high level of BDAC resources were probably outperforming other competitors to achieve greater firm performance. The implications of the study to academicians, policymakers and industry players have been discussed in this article and followed by, the research limitations, as well as recommendations for future study and conclusion, have been elaborated in the last session.","PeriodicalId":269873,"journal":{"name":"2021 7th International Conference on Research and Innovation in Information Systems (ICRIIS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 7th International Conference on Research and Innovation in Information Systems (ICRIIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRIIS53035.2021.9617012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Firms' big data analytics capabilities (BDAC) are vital for firms to be more successful than their competitors over a long period. Although much literature has proven the relationship between BDAC and firms' competitiveness, there is a limited discussion on the precise degree to which sort of BDAC profiles are flawless. This paper segregates BDAC profiles for Malaysian manufacturing firms into three clusters which are low, medium and high performers in the level of leveraging BDAC. This paper aims to answer two research questions: 1) are there three clusters of firms in exercising BDAC? and 2) would the firm with a high level of BDAC accomplish better firm performance? An analysis of variance (ANOVA) demonstrates that these three clusters differ significantly in achieving firm performance. The finding recommends that manufacturers with exercising a high level of BDAC resources were probably outperforming other competitors to achieve greater firm performance. The implications of the study to academicians, policymakers and industry players have been discussed in this article and followed by, the research limitations, as well as recommendations for future study and conclusion, have been elaborated in the last session.