The Effects of Operational and Financial Performance Failure on BI&A-Enabled Search Behaviors: A Theory of Performance-Driven Search

• 成果类型: Article
• 署名作者: Anand, Abhijith; Sharma, Rajeev; Kohli, Rajiv
• 署名单位: University of Arkansas System; University of Arkansas Fayetteville; University of Waikato
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2020.0936
• 发表日期: 2020
• 页码: 1144-1163
• 关键词: information-technology; Data analytics; firm performance; organizational performance; business value; INNOVATIVE SEARCH; decision-making; SYSTEM USAGE; management; IMPACT

摘要

Business intelligence and analytics (BI&A) systems enable firms to analyze data and search for insights that could potentially lead to improved organizational performance. While there is evidence that BI&A systems can improve performance through search, our theoretical understanding of how and under what conditions firms leverage BI&A systems to conduct search is rather limited. In particular, while problemistic search theory posits that performance failures motivate search, how firms respond to different types of performance failures remains unclear. We draw on and extend problemistic search theory by theorizing that BI&A-enabled search is influenced by complex interactions between failures in financial and operational performance and performance-related aspirations. We refer to this notion as the Theory of Performance-driven Search (TPS) and test it using longitudinal data gathered for a four-year period from seven U.S. hospitals. We find evidence that firms employ BI&A systems to search in a narrow set of circumstances. We find that performance failures are an important antecedent of BI&A-enabled search. In particular, failures in financial performance, failures in operational performance, and their joint failures are important conditions that trigger BI&A-enabled search. We find that historical and social aspiration levels of financial and operational performance influence BI&A-enabled search during failures in operational performance. We also find that only in organizations experiencing a sustained failure in financial performance do operational performance failures trigger BI&A-enabled search and that the latency of search response is dependent on the speed of failure in financial performance. Through our findings, we make two important contributions: we extend the business value of IT literature by identifying the contextual conditions that trigger BI&A use for search and we extend problemistic search theory by theorizing for the differential effects of operational and financial performance failures.