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Investigating Service Behavior Variance in Port Logistics from a Process Perspective

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Business Process Management Workshops (BPM 2013)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 171))

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Abstract

This paper presents an approach that explains the synergy between process mining and data mining for the investigation of the service behavior variances in the context of port logistics. The huge variances in service behaviors are identified and regrouped by the trace clustering technique applied to the operational processes. By incorporating domain information, the unsupervised process mining result is considerably improved in both accuracy and comprehensibility. Data mining techniques are then used for investigating the correlations between the variation in services and the contributing factors. The applicability of the proposed approach is demonstrated using an extensive case study carried out at an important Chinese port.

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References

  1. Berry, L.L., Parish, J.T., Cadwallader, S., Shankar, V., Dotzel, T.: Creating new markets through service innovation. MIT Sloan Manag. Rev. 47, 56–63 (2006)

    Google Scholar 

  2. Gallouj, F., Weinstein, O.: Innovation in services. Res. Policy 26, 537–556 (1997)

    Article  Google Scholar 

  3. Grönroos, C.: Service Management and Marketing, vol. 2. Wiley, New York (2001)

    Google Scholar 

  4. Reijers, H.A. (ed.): Design and Control of Workflow Processes. LNCS, vol. 2617. Springer, Heidelberg (2003)

    MATH  Google Scholar 

  5. De Brentani, U.: Success factors in developing new business services. Eur. J. Mark. 25, 33–59 (1991)

    Article  Google Scholar 

  6. Kandampully, J.: Innovation as the core competency of a service organisation: the role of technology, knowledge and networks. Eur. J. Innov. Manag. 5, 18–26 (2002)

    Article  Google Scholar 

  7. Chapman, R.L., Soosay, C., Kandampully, J.: Innovation in logistic services and the new business model: a conceptual framework. Int. J. Phys. Distrib. Logist. Manag. 33, 630–650 (2003)

    Article  Google Scholar 

  8. Siror, J.K., Huanye, S., Dong, W.: Rfid based model for an intelligent port. Comput. Ind. 62, 795–810 (2011)

    Article  Google Scholar 

  9. Roh, H.S., Lalwani, C.S., Naim, M.M.: Modelling a port logistics process using the structured analysis and design technique. Int. J. Logist. Res. Appl. 10(3), 283–302 (2007)

    Article  Google Scholar 

  10. Hult, G.T.M., Ketchen Jr, D.J., Cavusgil, S.T., Calantone, R.J.: Knowledge as a strategic resource in supply chains. J. Oper. Manag. 24, 458–475 (2006)

    Article  Google Scholar 

  11. van der Aalst, W.M., Reijers, H.A., Weijters, A.J., van Dongen, B.F., Alves de medeiros, A., Song, M., Verbeek, H.: Business process mining: an industrial application. Inf. Syst. 32, 713–732 (2007)

    Article  Google Scholar 

  12. De Weerdt, J., De Backer, M., Vanthienen, J., Baesens, B.: A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs. Inf. Syst. 37, 654–676 (2012)

    Article  Google Scholar 

  13. Song, M., Günther, C.W., van der Aalst, W.M.P.: Trace Clustering in Process Mining. In: Ardagna, D., Mecella, M., Yang, J. (eds.) BPM 2008 Workshops. LNBIP, vol. 17, pp. 109–120. Springer, Heidelberg (2009)

    Google Scholar 

  14. Jain, A.K., Murty, M.N., Flynn, P.J.: Data clustering: a review. ACM Comput. Surv. (CSUR) 31, 264–323 (1999)

    Article  Google Scholar 

  15. Goedertier, S., De Weerdt, J., Martens, D., Vanthienen, J., Baesens, B.: Process discovery in event logs: an application in the telecom industry. Appl. Soft Comput. 11, 1697–1710 (2011)

    Article  Google Scholar 

  16. Weijters, A., van der Aalst, W.M., De Medeiros, A.A.: Process mining with the heuristics miner-algorithm. Technische Universiteit Eindhoven, Technical Report WP 166 (2006)

    Google Scholar 

  17. Kotsiantis, S., Zaharakis, I., Pintelas, P.: Supervised machine learning: a review of classification techniques. Front. Artif. Intell. Appl. 160, 3 (2007)

    Google Scholar 

  18. Safavian, S.R., Landgrebe, D.: A survey of decision tree classifier methodology. IEEE Trans. Syst. Man Cybern. 21, 660–674 (1991)

    Article  MathSciNet  Google Scholar 

  19. Hall, M.A., Holmes, G.: Benchmarking attribute selection techniques for discrete class data mining. IEEE Trans. Knowl. Data Eng. 15, 1437–1447 (2003)

    Article  Google Scholar 

  20. Hall, M.A.: Correlation-based feature selection for machine learning, Ph.D. thesis, The University of Waikato (1999)

    Google Scholar 

  21. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, San Fransisco (2005)

    Google Scholar 

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Acknowledgements

This research is supported by the Natural Science Foundation of China under Grant Nos. 71132008.

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Authors and Affiliations

  1. School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China

    Ying Wang, Lei Huang & Yi Guo

  2. Department of Decision Sciences and Information Management, Faculty of Business and Economics, KU Leuven, Naamsestraat 69, 3000, Leuven, Belgium

    Filip Caron & Jan Vanthienen

Authors
  1. Ying Wang
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  2. Filip Caron
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  3. Jan Vanthienen
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  4. Lei Huang
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  5. Yi Guo
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Corresponding author

Correspondence to Ying Wang .

Editor information

Editors and Affiliations

  1. University of Rostock, Rostock, Germany

    Niels Lohmann

  2. Ulsan National Institute of Science and Technology, Ulsan, Korea, Republic of (South Korea)

    Minseok Song

  3. Stockholm University, Stockholm, Sweden

    Petia Wohed

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Wang, Y., Caron, F., Vanthienen, J., Huang, L., Guo, Y. (2014). Investigating Service Behavior Variance in Port Logistics from a Process Perspective. In: Lohmann, N., Song, M., Wohed, P. (eds) Business Process Management Workshops. BPM 2013. Lecture Notes in Business Information Processing, vol 171. Springer, Cham. https://doi.org/10.1007/978-3-319-06257-0_25

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  • DOI: https://doi.org/10.1007/978-3-319-06257-0_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06256-3

  • Online ISBN: 978-3-319-06257-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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