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Implementation of best manufacturing practices using logic models and system dynamics: project design and project assessment views

Author

Listed:
  • Carlos Vallejo

    (Tecnológico de Monterrey)

  • David Romero

    (Tecnológico de Monterrey
    Griffith University)

  • Arturo Molina

    (Tecnológico de Monterrey)

Abstract

In today’s global competitive environment, the need for continuous improvement is a matter of considerable importance within manufacturing enterprises. To this end, project managers, and managers in general, design and assess different projects with the purpose of achieving efficient processes, reducing costs and waste, increasing product and service quality, developing new products and services, enhancing customer relationship management, optimising enterprise resources, and so on. However, it is well-known that managing enterprise resources in order to accomplish effective completion of projects is a complex task to carry out. Furthermore, it has been recognised that the way staff actually understands the purpose of a project, the way they perform different project activities, and how they are able to influence project design and assessment are key factors for influencing the success of a project. This paper presents a systemic methodology to design and assess projects more effectively and efficiently based on program logic models and system dynamics with the aim of facilitating a clear understanding of the needs, purposes, goals, activities and tasks of a project among its stakeholders towards achieving success.

Suggested Citation

  • Carlos Vallejo & David Romero & Arturo Molina, 0. "Implementation of best manufacturing practices using logic models and system dynamics: project design and project assessment views," Information Systems and e-Business Management, Springer, vol. 0, pages 1-41.
    • Handle: RePEc:spr:infsem:v::y::i::d:10.1007_s10257-016-0327-6
    DOI: 10.1007/s10257-016-0327-6
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    References listed on IDEAS

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    1. Michael T. Pich & Christoph H. Loch & Arnoud De Meyer, 2002. "On Uncertainty, Ambiguity, and Complexity in Project Management," Management Science, INFORMS, vol. 48(8), pages 1008-1023, August.
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