Mahak Sharma, Ruchita Gupta, Rajat Sehrawat, Karuna Jain, A. Dhir
{"title":"The assessment of factors influencing Big data adoption and firm performance: Evidences from emerging economy","authors":"Mahak Sharma, Ruchita Gupta, Rajat Sehrawat, Karuna Jain, A. Dhir","doi":"10.1080/17517575.2023.2218160","DOIUrl":null,"url":null,"abstract":"ABSTRACT The current study investigates and prioritizes 17 determinants of big data adoption (BDA) and establishes causality between these determinants’ and firms’ performance in the tourism and hospitality sector using technology, organisation & environment (TOE) framework. Semi-structured interviews and multi-criteria decision-making (MCDM) were utilized to gather data from 28 industry experts. “Big data quality” ranked as the most influential determinant, while “trading partner pressure” ranked as the least influential determinant. This study’s findings highlight the need for governments across the globe to propose and implement policies to reduce the digital divide and enhance standardization.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Enterprise Information Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/17517575.2023.2218160","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 2
Abstract
ABSTRACT The current study investigates and prioritizes 17 determinants of big data adoption (BDA) and establishes causality between these determinants’ and firms’ performance in the tourism and hospitality sector using technology, organisation & environment (TOE) framework. Semi-structured interviews and multi-criteria decision-making (MCDM) were utilized to gather data from 28 industry experts. “Big data quality” ranked as the most influential determinant, while “trading partner pressure” ranked as the least influential determinant. This study’s findings highlight the need for governments across the globe to propose and implement policies to reduce the digital divide and enhance standardization.
期刊介绍：
Enterprise Information Systems (EIS) focusses on both the technical and applications aspects of EIS technology, and the complex and cross-disciplinary problems of enterprise integration that arise in integrating extended enterprises in a contemporary global supply chain environment. Techniques developed in mathematical science, computer science, manufacturing engineering, and operations management used in the design or operation of EIS will also be considered.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
