Survival of the fastest: Using sequential pattern analysis to measure efficiency of complex organizational processes

Joseph Johnson, Raju Parakkal, Sherry Bartz, Gang Ren, Mitsunori Ogihara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Measuring the efficiency of complex and dynamic organizational processes is a problem that remains unresolved in the management science literature. We propose a novel sequence transverse velocity measurement of the sequential decision processes from the itemset transition speed of frequent subsequences. Specifically, sequential decision chains of different source sequences under comparison are modeled as time-stamped itemset sequences and their frequent subsequences are extracted using sequential pattern discovery algorithm. The subsequence transverse velocity is represented as the inverse ranking of the traversing time duration of a common subsequence among the source sequences that share this subsequence. The proposed velocity measurement is then combined into a velocity timeline accompanying each source sequence by weighting the velocity of the constituent subsequences according to the statistical and contextual significance of the subsequences. To demonstrate the usage of this velocity measurement and its related computational tools, the paper also includes two empirical studies: one based on real-world business expansion chains and the other based on healthcare delivery systems.

Original languageEnglish (US)
Title of host publicationProceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019
EditorsPanagiotis Papapetrou, Xueqi Cheng, Qing He
PublisherIEEE Computer Society
Pages830-837
Number of pages8
ISBN (Electronic)9781728146034
DOIs
StatePublished - Nov 2019
Event19th IEEE International Conference on Data Mining Workshops, ICDMW 2019 - Beijing, China
Duration: Nov 8 2019Nov 11 2019

Publication series

NameIEEE International Conference on Data Mining Workshops, ICDMW
Volume2019-November
ISSN (Print)2375-9232
ISSN (Electronic)2375-9259

Conference

Conference19th IEEE International Conference on Data Mining Workshops, ICDMW 2019
CountryChina
CityBeijing
Period11/8/1911/11/19

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Keywords

  • Bioinformatics
  • Business expansion
  • Sequence transverse
  • Sequential pattern

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

Cite this

Johnson, J., Parakkal, R., Bartz, S., Ren, G., & Ogihara, M. (2019). Survival of the fastest: Using sequential pattern analysis to measure efficiency of complex organizational processes. In P. Papapetrou, X. Cheng, & Q. He (Eds.), Proceedings - 19th IEEE International Conference on Data Mining Workshops, ICDMW 2019 (pp. 830-837). [8955600] (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 2019-November). IEEE Computer Society. https://doi.org/10.1109/ICDMW.2019.00122