A comparative sequence analysis of career paths among knowledge workers in a multinational bank

Paul Squires, Harold G. Kaufman, Julian Togelius, Catalina M. Jaramillo

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

Abstract

This study examined two metrics for measuring the distance between sequences (Euclid and OMSpell) and creating distance matrices combined with two types of clustering methods (AGNES and PAM) to analyze the career path clusters of knowledge workers. A regression tree of covariates and career path clusters was used to predict advancement rates. The results indicated that the metric which focused on subsequences (OMSpell) worked best for both clustering methods. Less time as a knowledge worker was associated with greater advancement. Implications for boundaryless careers and social capital formation are discussed.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
EditorsJian-Yun Nie, Zoran Obradovic, Toyotaro Suzumura, Rumi Ghosh, Raghunath Nambiar, Chonggang Wang, Hui Zang, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Xiaohua Hu, Jeremy Kepner, Alfredo Cuzzocrea, Jian Tang, Masashi Toyoda
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3604-3612
Number of pages9
ISBN (Electronic)9781538627143
DOIs
StatePublished - Jul 1 2017
Event5th IEEE International Conference on Big Data, Big Data 2017 - Boston, United States
Duration: Dec 11 2017Dec 14 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Volume2018-January

Other

Other5th IEEE International Conference on Big Data, Big Data 2017
Country/TerritoryUnited States
CityBoston
Period12/11/1712/14/17

Keywords

  • career paths
  • clustering
  • knowledge worker
  • optimal matching
  • regression tree
  • sequence analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Control and Optimization

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