M. Haverila, Md. Samim Al-Azad, Kai C. Haverila, Muhammad Mohiuddin, Zhan Su
{"title":"Moving Toward Economic and Digital Sustainability in Marketing Analytics","authors":"M. Haverila, Md. Samim Al-Azad, Kai C. Haverila, Muhammad Mohiuddin, Zhan Su","doi":"10.4018/jgim.349129","DOIUrl":null,"url":null,"abstract":"Despite analytical advancements, firms have yet to realize the full potential of big data marketing analytics (BDMA) because the poor quality data restricts customer predictions and insightful decisions. Technology and market uncertainty create challenges in understanding business needs, choosing analytical tools, determining customer insights, and market trends. This study aims to assess the quality of marketing analytics, including technology and information quality. Data were collected from 236 North American respondents working in firms with at least limited experience in the deployment of BDMA. The analysis tool was PLS-SEM. The findings supported the hypothesis that technology and market uncertainty negatively influence the quality of analytical outcomes. This study makes a significant theoretical and methodological contribution to BDMA literature by assessing the quality of analytics as an integrated formative construct.","PeriodicalId":46306,"journal":{"name":"Journal of Global Information Management","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Global Information Management","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.4018/jgim.349129","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Despite analytical advancements, firms have yet to realize the full potential of big data marketing analytics (BDMA) because the poor quality data restricts customer predictions and insightful decisions. Technology and market uncertainty create challenges in understanding business needs, choosing analytical tools, determining customer insights, and market trends. This study aims to assess the quality of marketing analytics, including technology and information quality. Data were collected from 236 North American respondents working in firms with at least limited experience in the deployment of BDMA. The analysis tool was PLS-SEM. The findings supported the hypothesis that technology and market uncertainty negatively influence the quality of analytical outcomes. This study makes a significant theoretical and methodological contribution to BDMA literature by assessing the quality of analytics as an integrated formative construct.
期刊介绍：
Authors are encouraged to submit manuscripts that are consistent to the following submission themes: (a) Cross-National Studies. These need not be cross-culture per se. These studies lead to understanding of IT as it leaves one nation and is built/bought/used in another. Generally, these studies bring to light transferability issues and they challenge if practices in one nation transfer. (b) Cross-Cultural Studies. These need not be cross-nation. Cultures could be across regions that share a similar culture. They can also be within nations. These studies lead to understanding of IT as it leaves one culture and is built/bought/used in another. Generally, these studies bring to light transferability issues and they challenge if practices in one culture transfer.
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