In this paper, we examine the relationship between business intelligence (BI) quality, task characteristics and individual impact of the system from an end-user perspective at 12 public hospitals. 1,352 BI end-users answered the questionnaire. Linear regression was used to test the research model empirically. If organisations in the public health sector want high individual impact, the following factors are essential. Firstly, system quality must be high. Secondly, the system must support the tasks that the BI user solves with the system. Thirdly, task difficulty is positively and significantly related to impact. In conclusion, it is essential that the user perceives the task as being important. The user’s perception of task interdependency and task specificity does not influence individual impact. Future research should focus on different healthcare settings with different types of BI system.
Business intelligence, Public healthcare, End-user success.
[1] Raghupathi W, Raghupathi V. An overview of health analytics. J Health Med Informat 2013; 4: 2.
[2] Wixom B, Watson H. The BI-Based Organization: International Journal of Business Intelligence Research 2010; 1: 13–28.
[3] Mettler T, Vimarlund V. Understanding business intelligence in the context of healthcare. Health informatics journal 2009; 15: 254–264.
[4] Tona O, Carlsson SA, Eom S. An empirical test of Delone and McLean’s information system success model in a public organization. In: 18th Americas Conference on Information Systems 2012, AMCIS 2012. 2012, pp. 1374–1382.
[5] DeLone WH, McLean ER. Information Systems Success: The Quest for the Dependent Variable. Information Systems Research 1992; 3: 60–95.
[6] Gaardboe R, Sandalgaard N, Nyvang T. An assessment of business intelligence in public hospitals. IJISPM – International Journal of Information Systems and Project Management 2017; 5–18.
[7] Rosacker KM, Olson DL. Public sector information system critical success factors. Transforming Government: People, Process and Policy 2008; 2: 60–70.
[8] Kolasa I. Success Factors for Public Sector Information System Projects: Qualitative Literature Review. 2017, p. 326.
[9] Madsen L. Healthcare business intelligence: a guide to empowering successful data reporting and analytics. Hoboken, New Jersey: John Wiley & Sons, Inc., http://catalogimages.wiley.com/images/db/jimages/9781118217801.jpg (2012, accessed 31 July 2017).
[10] Gaardboe R, Sandalgaard N, Sudzina F. The importance of task compatibility for web-enabled Business Intelligence success in e-government. In: Proceedings of the 19th International Conference on Information Integration and Web-based Applications & Services (iiWAS2017). Salzburg: International Conference on Information Integration and Web-based Applications & Services, 2017.
[11] Gaardboe R, Svarre T. Business Intelligence Success Factors: A literature review. Journal of Information Technology Management 2018; 29: 1–15.
[12] DeLone WH, McLean ER. The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems 2003; 19: 9–30.
[13] Petter S, DeLone W, McLean ER. Information Systems Success: The Quest for the Independent Variables. Journal of Management Information Systems 2013; 29: 7–62.
[14] Leavitt HJ. Applied organizational change in industry: Structural, technological and humanistic approaches. In: March J (ed) Handbook of Organizations. 1965, pp. 1144–1170.
[15] Zuboff S. In the age of the smart machine: the future of work and power. Oxford: Heinemann, 1988.
[16] Gaardboe R, Svarre T, Nyvang T. The Relationship between Task Characteristics, BI Quality, and Task Compatibility: An Explorative Study. Complex Systems Informatics and Modeling Quarterly 2018; 14: 54–63.
[17] Seddon PB. A Respecification and Extension of the De-Lone and McLean Model of IS Success. Information Systems Research 1997; 8: 240–253.
[18] Hsieh J, Rai A, Petter S, et al. Impact of User Satisfaction with Mandated CRM Use on Employee Service Quality. MIS Quarterly 2012; 36: 1065.
[19] Gaardboe R, Svarre T. Critical Success factors for Business Intelligence Success. 2017, pp. 472–486.
[20] Lewis JR. IBM Computer Usability Satisfaction Questionnaires: Psychometric Evaluation and Instructions for Use. International Journal of Human-Computer Interaction 1995; 7: 57–78.
[21] Wang Y-S, Liao Y-W. Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success. Government Information Quarterly 2008; 25: 717–733.
[22] Lee YW, Strong DM, Kahn BK, et al. AIMQ: a methodology for information quality assessment. Information & management 2002; 40: 133–146.
[23] Morgeson FP, Humphrey SE. The Work Design Questionnaire (WDQ): Developing and validating a comprehensive measure for assessing job design and the nature of work. Journal of Applied Psychology 2006; 91: 1321–1339.
[24] Daft RL, Macintosh NB. A Tentative Exploration into the Amount and Equivocality of Information Processing in Organizational Work Units. Administrative Science Quarterly 1981; 26: 207–224.
[25] Nunnally JC, Bernstein IH. The assessment of reliability. Psychometric theory 1994; 3: 248–292.
[26] Zviran M, Pliskin N, Levin R. Measuring user satisfaction and perceived usefulness in the ERP context. Journal of Computer Information Systems 2005; 45: 43–52.
[27] D’Ambra J, Rice RE. Emerging factors in user evaluation of the World Wide Web. Information & Management 2001; 38: 373–384.
[28] Shih H-P. Extended technology acceptance model of Internet utilization behavior. Information & management 2004; 41: 719–729.
[29] Goodhue DL, Thompson RL. Task-Technology Fit and Individual Performance. MIS Quarterly 1995; 19: 213–236.
[30] Jarupathirun S, Zahedi F “Mariam”. Dialectic decision support systems: System design and empirical evaluation. Decision Support Systems 2007; 43: 1553–1570.
[31] Kim DT, Kim BG, Aiken MW, et al. The influence of individual, task organizational support, and subject norm factors on the adoption of Groupware. Academy of Information and Management Sciences Journal 2006; 9: 93–110.
[32] Marshall TE, Byrd TA, Gardiner LR, et al. Technology acceptance and performance: An investigation into requisite knowledge. Information Resources Management Journal 2000; 13: 33–45.
