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

Abhijith Anand (), Rajeev Sharma () and Rajiv Kohli ()
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Abhijith Anand: Department of Information Systems, Sam M. Walton College of Business, University of Arkansas, Fayetteville, Arkansas 72701
Rajeev Sharma: Waikato Management School, University of Waikato, Hillcrest, Hamilton 3240, New Zealand
Rajiv Kohli: Raymond A. Mason School of Business, William & Mary, Williamsburg, Virginia 23187

Information Systems Research, 2020, vol. 31, issue 4, 1144–1163

Abstract: 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.

Keywords: business analytics; business intelligence; IT use; performance; aspirations; search (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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