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Research Articles

Root-cause analysis of process-data quality problems

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Pages 51-75 | Received 27 Nov 2020, Accepted 18 Jun 2021, Published online: 31 Aug 2021

References

  • Abbasi, A., Sarker, S., & Chiang, R. H. (2016). Big data research in information systems: Toward an inclusive research agenda. Journal of the Association for Information Systems, 17(2), i–xxxii. https://doi.org/10.17705/1jais.00423
  • Alexander, C. (1977). A pattern language: Towns, buildings, construction. Oxford university press.
  • Andrews, R., Emamjome, F., ter Hofstede, A. H., & Reijers, H. A. (2020). An expert lens on data quality in process mining. In 2nd International Conference on Process Mining (ICPM), Department of Mathematics of the University of Padua, Italy, (pp. 49–56).
  • Andrews, R., Suriadi, S., Wynn, M. T., ter Hofstede, A. H., & Rothwell, S. (2018). Improving patient flows at St. Andrew’s War Memorial Hospital’s emergency department through process mining. In Jan vom Brocke, Jan Mendling ed., Business process management cases (pp. 311–333). Springer.
  • Andrews, R., Van Dun, C. G., Wynn, M. T., Kratsch, W., Röglinger, M., & ter Hofstede, A. H. (2020). Quality-informed semi-automated event log generation for process mining. Decision Support Systems, 113265.
  • Andrews, R., Wynn, M. T., Vallmuur, K., ter Hofstede, A. H., Bosley, E., Elcock, M., Rashford, S. (2019). Leveraging data quality to better prepare for process mining: An approach illustrated through analysing road trauma pre-hospital retrieval and transport processes in Queensland. International Journal of Environmental Research and Public Health, 16(7), 1138. https://doi.org/10.3390/ijerph16071138
  • Armstrong, P. (1986). Management control strategies and inter-professional competition; the cases of accountancy and personnel management. In D. Knights & H. Willmott (Eds.), Managing the labour process. Aldershot Crower, pp. 19-43).
  • Ash, J. S., Berg, M., & Coiera, E. (2004). Some unintended consequences of information technology in health care: The nature of patient care information system-related errors. Journal of the American Medical Informatics Association, 11(2), 104–112. https://doi.org/10.1197/jamia.M1471
  • Bose, R. J. C., Mans, R. S., & van der Aalst, W. M. P. (2013). Wanna improve process mining results? In IEEE symposium on computational intelligence and data mining (pp. 127–134). Singapore.
  • Bose, R. J. C., & van der Aalst, W. M. P. (2010). Trace alignment in process mining: Opportunities for process diagnostics. In International conference on BPM (pp. 227–242). Hoboken, NJ, USA.
  • Boudreau, M., & Robey, D. (2005, February). Enacting integrated information technology: A human agency perspective. Organization Science, 16(1), 3–18. https://doi.org/10.1287/orsc.1040.0103
  • Bozkaya, M., Gabriels, J., & van der Werf, J. M. (2009). Process diagnostics: A method based on process mining. In International conference on information, process, and knowledge management, (pp. 22–27). Cancun, Mexico.
  • Brown, J. R., & Fehige, Y. (2019). Thought experiments. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Winter 2019, ed). Metaphysics Research Lab, Stanford University. https://plato.stanford.edu/archives/win2019/entries/thought -experiment/ (last visited 26/ 11/2020)
  • Cabena, P., Hadjinian, P., Stadler, R., Verhees, J., & Zanasi, A. (1997). Discovering data mining: From concept to implementation. Prentice Hall PTR New Jersey.
  • Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188. https://doi.org/10.2307/41703503
  • Cheng, H.-J., & Kumar, A. (2015). Process mining on noisy logs–can log sanitization help to improve performance? Decision Support Systems, 79, 138–149. https://doi.org/10.1016/j.dss.2015.08.003
  • CrowdFlower Inc. (2017). 2017 data scientist report. rowdFlower Incorporated. https://visit.figure-eight .com/rs/416-ZBE-142/images/CrowdFlower DataScienceReport.pdf (last visited 26/ 11/2020).
  • D’Adderio, L. (2004). Inside the virtual product: How organizations create knowledge through software. Edward Elgar Publishing.
  • Danermark, B., Ekstrom, M., Jakobsen, L., & Karlsson, J. (2001). Explaining society: An introduction to critical realism in the social sciences. Routledge.
  • Davenport, T. H. (2006). Competing on analytics. Harvard Business Review, 84(1), 98–107. http://hosteddocs.ittoolbox.com/competinganalytics.pdf
  • Dourish, P. (2004). Where the action is: The foundations of embodied interaction. MIT Press.
  • Emamjome, F., Andrews, R., ter Hofstede, A., & Reijers, H. (2020b). Signpost – a semiotics-based process mining methodology. In Proceedings of the 28th European conference on information systems (ECIS2020), (pp. 1–10). Marrakech, Morocco.
  • Emamjome, F., Andrews, R., & ter Hofstede, A. H. (2019). A case study lens on process mining in practice. In On the Move to Meaningful Internet Systems: OTM Confederated International Conferences, (pp. 127–145). Rhodes, Greece
  • Emamjome, F., Andrews, R., ter Hofstede, A. H., & Reijers, H. A. (2020a). Alohomora: Unlocking data quality causes through event log context. In European Conference on Information Systems (ECIS2020), Marrakech, Morocco.
  • Feenberg, A. (2012). Questioning technology. Routledge.
  • Fox, F., Aggarwal, V. R., Whelton, H., & Johnson, O. (2018). A data quality framework for process mining of electronic health record data. In IEEE international conference on healthcare informatics (pp. 12–21), New York City, NY, USA.
  • Goes, P. B. (2014). Editor’s comments: Big data and IS research. MIS Quarterly, 38(3), iii–viii. https://www.jstor.org/stable/26634980
  • Habermas, J. (1984). The theory of communicative action: Jurgen Habermas;, trans. by Thomas Mccarthy. Heinemann.
  • Hutchby, I. (2013). Conversation and technology: From the telephone to the internet. John Wiley & Sons.
  • Layder, D. (1998). Sociological practice: Linking theory and social research. Sage.
  • Mans, R. S., van der Aalst, W. M. P., Vanwersch, R. J., & Moleman, A. J. (2013). Process mining in healthcare: Data challenges when answering frequently posed questions. In In Editors: David Riaño, Richard Lenz, Silvia Miksch, Mor Peleg, Manfred Reichert, Annette ten Teije., Process support and knowledge representation in health care (pp. 140–153). Springer.
  • Marsden, J. R., & Pingry, D. E. (2018). Numerical data quality in IS research and the implications for replication. Decision Support Systems, 115, A1–A7. https://doi.org/10.1016/j.dss.2018.10.007
  • Massa, S., & Testa, S. (2005, July). Data warehouse-in-practice: Exploring the function of expectations in organizational outcomes. Information and Management, 42(5), 709–718. https://doi.org/10.1016/j.im.2004.06.002
  • Mingers, J., & Willcocks, L. (2014). An integrative semiotic framework for information systems: The social, personal and material worlds. Information and Organization, 24(1), 48–70. https://doi.org/10.1016/j.infoandorg.2014.01.002
  • Mingers, J., & Willcocks, L. (2017). An integrative semiotic methodology for is research. Information and Organization, 27(1), 17–36. https://doi.org/10.1016/j.infoandorg.2016.12.001
  • Mutch, A. (2010). Technology, organization, and structure: A morphogenetic approach. Organization Science, 21(2), 507–520. https://doi.org/10.1287/orsc.1090.0441
  • Nemati, H. R., & Barko, C. D. (2003). Key factors for achieving organizational data-mining success. Industrial Management & Data Systems, 103(4), 282–292. https://doi.org/10.1108/02635570310470692
  • O’Neill, S. (2008). Interactive media: The semiotics of embodied interaction. Springer Science & Business Media.
  • Peirce, C. S. (1974). Collected papers of Charles Sanders Peirce (Vol. 2). Harvard University Press.
  • Price, R., & Shanks, G. (2016). A semiotic information quality framework: Development and comparative analysis. In Editors: Leslie P. Willcocks, Chris Sauer, Mary C. Lacity., Enacting research methods in information systems (pp. 219–250). Springer.
  • Queensland Audit Office. (2015). Emergency department performance reporting: Report 3, 2014–2015.  The State of Queensland, Queensland Audit Office. https://www.qao.qld.gov.au/sites/default/files/reports/rtp_emergency_department_performance_reporting.pdf
  • Salancik, G. R., & Pfeffer, J. (1978). A social information processing approach to job attitudes and task design. Administrative Science Quarterly, 23(2), 224–253. https://doi.org/10.2307/2392563
  • Strong, D., & Volkoff, O. (2010). Understanding organization-enterprise system fit: A path to theorizing the information technology artifact. MIS Quarterly, 34(4), 731–756. https://doi.org/10.2307/25750703
  • Suriadi, S., Andrews, R., ter Hofstede, A. H., & Wynn, M. T. (2017). Event log imperfection patterns for process mining: Towards a systematic approach to cleaning event logs. Information Systems, 64, 132–150. https://doi.org/10.1016/j.is.2016.07.011
  • van der Aalst, W. M. P. (2016). Process mining: Data science in action. Springer.
  • van der Aalst, W. M. P., Adriansyah, A., De Medeiros, A. K. A., Arcieri, F., Baier, T., & Blickle, T., … others (2011). Process mining manifesto. In International conference on business process management, (pp. 169–194). Clermont-Ferrand, France.
  • Van Eck, M. L., Lu, X., Leemans, S. J., & van der Aalst, W. M. P. (2015). Pm2: A process mining project methodology. In International conference on advanced information systems engineering (pp. 297–313). Stockholm, Sweden.
  • Volkoff, O., & Strong, D. (2013). Critical realism and affordances: Theorizing it-associated organizational change processes. MIS Quarterly, 37(3), 819–834. https://doi.org/10.25300/MISQ/2013/37.3.07
  • Volkoff, O., Strong, D. M., & Elmes, M. B. (2007). Technological embeddedness and organizational change. Organization Science, 18(5), 832–848. https://doi.org/10.1287/orsc.1070.0288
  • Wixom, B. H., & Watson, H. J. (2001). An empirical investigation of the factors affecting data warehousing success. MIS Quarterly, 25(1), 17–41. https://doi.org/10.2307/3250957

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