{"title":"The Role of Organizational Support and Problem Space Complexity on Organizational Performance - A Business Intelligence Perspective","authors":"S. Hung, Kuanchin Chen","doi":"10.17705/1pais.12101","DOIUrl":null,"url":null,"abstract":"Background : In today’s business environment, BI systems are frequently bundled together or built with a good connection to existing ERP systems. Businesses implementing BI alone may not receive its full benefit if the necessary support structure and a fit of it to its problem domain are not in place. Methods : In this study, we explored organizational support and problem space complexity in three models (base, direct-effect and moderation models) to study BI’s effect on organizational performance. Results : The moderation model explains the most variance of the dependent variable – organizational performance. Problem space complexity had both a direct effect on organizational performance and the relationship between BI implementation and this dependent variable. Organizational support along with its first-order factors did not have statistical significance on organizational performance. Conclusions : The resulting moderation model provides the best explanation of organizational performance among the three models tested. The confirmed effects of problem space complexity show that matching BI implementation to the complexity of the problem in hand drives business performance. Organizational support may not be consistently required throughout all stages of BI adoption. As the BI literature has shown, the effect of organizational support on BI implementation could very much be on individuals in areas of affective commitment, extra-role performance and end-user satisfaction. Our work provides the beginning empirical evidence that such effects on individuals may not always result in business performance.","PeriodicalId":43480,"journal":{"name":"Pacific Asia Journal of the Association for Information Systems","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pacific Asia Journal of the Association for Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17705/1pais.12101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 7
Abstract
Background : In today’s business environment, BI systems are frequently bundled together or built with a good connection to existing ERP systems. Businesses implementing BI alone may not receive its full benefit if the necessary support structure and a fit of it to its problem domain are not in place. Methods : In this study, we explored organizational support and problem space complexity in three models (base, direct-effect and moderation models) to study BI’s effect on organizational performance. Results : The moderation model explains the most variance of the dependent variable – organizational performance. Problem space complexity had both a direct effect on organizational performance and the relationship between BI implementation and this dependent variable. Organizational support along with its first-order factors did not have statistical significance on organizational performance. Conclusions : The resulting moderation model provides the best explanation of organizational performance among the three models tested. The confirmed effects of problem space complexity show that matching BI implementation to the complexity of the problem in hand drives business performance. Organizational support may not be consistently required throughout all stages of BI adoption. As the BI literature has shown, the effect of organizational support on BI implementation could very much be on individuals in areas of affective commitment, extra-role performance and end-user satisfaction. Our work provides the beginning empirical evidence that such effects on individuals may not always result in business performance.