1. OSCM Publications
  2. Volume 2, Issue 1, 2009

Volume 2, Issue 1, 2009

  1. Table of Content
    • OSCM Team
    Full PDF Cite DOI: 10.31387/oscm030014 
    @article{oscm-2009-426,
  title={Table of Content},
  year={2009},
  author={OSCM Team},
  journal={Operations and Supply Chain Management: An International Journal},
  volume={2},
  number={1},
  doi={10.31387/oscm030014}
}
    OSCM Team (2009). Table of Content. Operations and Supply Chain Management: An International Journal, 2(1). https://doi.org/10.31387/oscm030014
  2. Application of Numerical Design Structure Matrix Method in Engineering Projects Management
    • Indra Gunawan
    Abstract Full PDF Cite DOI: 10.31387/oscm030015
    In this paper, ways of improving planning, execution and management of projects using Numerical Design Structure Matrix (NDSM) method are presented to address interdependency of feedback and iteration, which is common in engineering projects management. The NDSM is an alternative approach to traditional project management tools such as Program Evaluation and Review Technique (PERT), Critical Path Method (CPM), and Gantt chart that can only allow the modelling of sequential and parallel processes in projects. As a case study, the model is tested on a set of tasks in a complex petroleum oil field development project, where task sensitivity and information variability attributes are derived. By applying the NDSM method, project duration is optimized and hence total cost of the project is reduced significantly.
    @article{oscm-2009-427,
  title={Application of Numerical Design Structure Matrix Method in Engineering Projects Management},
  year={2009},
  author={Indra Gunawan},
  journal={Operations and Supply Chain Management: An International Journal},
  volume={2},
  number={1},
  pages={1--10},
  doi={10.31387/oscm030015}
}
    Indra Gunawan (2009). Application of Numerical Design Structure Matrix Method in Engineering Projects Management. Operations and Supply Chain Management: An International Journal, 2(1), 1-10. https://doi.org/10.31387/oscm030015
  3. The Influence of Production Management Practices and Systems on Business Performance: From the Perspective of the Push-pull Production Systems
    • Hui-Ming Wee
    • Shu-Yun Peng
    • Ching-Chow Yang
    • Paul KP Wee
    Abstract Full PDF Cite DOI: 10.31387/oscm030020
    This study develops a conceptual model: Customer Output Process Integrated System (COPIS) with hybrid push-pull strategy. We seek to investigate the performance and critical success factors of a Taiwanese enterprise. The COPIS conceptual model provides managerial insights to enterprises to achieve their objectives as well as to improve customer relationship. Through an appropriate process design, the Taiwanese enterprise is able to control critical factors and performance indices to maintain flexibility and robustness. Enterprises should design and plan their process based on the characteristic of the business, the processing design, the flow design and the load leveling system.
    @article{oscm-2009-428,
  title={The Influence of Production Management Practices and Systems on Business Performance: From the Perspective of the Push-pull Production Systems},
  year={2009},
  author={Hui-Ming Wee and Shu-Yun Peng and Ching-Chow Yang and Paul KP Wee},
  journal={Operations and Supply Chain Management: An International Journal},
  volume={2},
  number={1},
  pages={11--23},
  doi={10.31387/oscm030020}
}
    Hui-Ming Wee, Shu-Yun Peng, Ching-Chow Yang, Paul KP Wee (2009). The Influence of Production Management Practices and Systems on Business Performance: From the Perspective of the Push-pull Production Systems. Operations and Supply Chain Management: An International Journal, 2(1), 11-23. https://doi.org/10.31387/oscm030020
  4. An Integrated Forecasting DSS Architecture in Supply Chain Management
    • Tien-You Wang
    • Din-Horng Yeh
    Abstract Full PDF Cite DOI: 10.31387/oscm030120
    In a competing market environment, supply chain management (SCM) has been critical for companies to survive. Demand planning plays an important role in SCM, for it provides accurate demand forecasts which may achieve customer satisfaction by offering benefits such as low inventory level, short lead time, efficient resource allocation, and quick response. To obtain more accurate forecasts, this study presents a web-based DSS architecture and its forecasting core. The forecasting core, named Panel Function, contains three modules: Segmentation Module, Forecasting Module, and Coordination Module. Segmentation Module employs data mining technology to categorize customers with different characteristics into three segments: Loyal Customer Segment, Potential Customer Segment, and Switcher Segment. Based on the three segments, Forecasting Module employs different forecasting and analysis technologies to estimate an integrated forecast: time-series forecasting to capture the loyal customer demand trend, Bayesian inference to estimate the predicted value of switcher purchase quantity, and questionnaire analysis and brand choice models to unearth potential customers. An integration function then synthesizes the results from these three processes to obtain the integrated forecast. Coordination Module then takes this integrated forecast as the base of distribution planning, and provides a minimal system-wide total cost solution for all parties in the supply chain. As a whole, this DSS architecture is anticipated to provide an efficient mechanism for collaborative demand planning, and help create the maximum profit for the supply chain.
    @article{oscm-2009-429,
  title={An Integrated Forecasting DSS Architecture in Supply Chain Management},
  year={2009},
  author={Tien-You Wang and Din-Horng Yeh},
  journal={Operations and Supply Chain Management: An International Journal},
  volume={2},
  number={1},
  pages={24--41},
  doi={10.31387/oscm030120}
}
    Tien-You Wang, Din-Horng Yeh (2009). An Integrated Forecasting DSS Architecture in Supply Chain Management. Operations and Supply Chain Management: An International Journal, 2(1), 24-41. https://doi.org/10.31387/oscm030120
  5. Synthetic Data Generation for Small-Area Demand Forecasting of Freight Flows
    • Paul Metaxatos
    Abstract Full PDF Cite DOI: 10.31387/oscm030121
    Small area statistics have become increasingly critical for the planning and management of intermodal transportation systems. However, for reasons associated with disclosure of confidential information, data is often released on a fairly coarse geography vis-à-vis a much finer geographical level. This has led to extensive research on small area estimation - i.e., estimation at a more detailed geographical level based on data at a coarser level. Most of this work has been single-area-specific or non-flow data. Freight flows, at a minimum, have origin and destination location specificity, which leads to greater complexity. This paper addresses this issue providing a methodology for small-area estimation of freight flows based on the gravity model. Preliminary empirical findings using publicly available data demonstrate the reasonableness of the method as a freight-planning tool.
    @article{oscm-2009-430,
  title={Synthetic Data Generation for Small-Area Demand Forecasting of Freight Flows},
  year={2009},
  author={Paul Metaxatos},
  journal={Operations and Supply Chain Management: An International Journal},
  volume={2},
  number={1},
  pages={42--51},
  doi={10.31387/oscm030121}
}
    Paul Metaxatos (2009). Synthetic Data Generation for Small-Area Demand Forecasting of Freight Flows. Operations and Supply Chain Management: An International Journal, 2(1), 42-51. https://doi.org/10.31387/oscm030121
  6. Time and Form Postponement Competition under Dynamic Behavior of Demand
    • Yohanes Kristianto
    • Petri T. Helo
    Abstract Full PDF Cite DOI: 10.31387/oscm030122
    This paper studies assembly-to-order (form postponement) and make-to-stock (time postponement) duopolistic competition under dynamic price and production strategies for two differentiable products, which share common components at a certain degree of substitution. Both strategies are benchmarked according to the Bertrand and Cournot Stackelberg game. In addition, dynamic game is applied to show the long term effect of both strategic decisions (price and production quantity) on profit and against demand uncertainty. The results show that precommited production is appropriate for high modular products and precommited price for special orders. The final part of the paper concludes the results and outlines future research directions.
    @article{oscm-2009-431,
  title={Time and Form Postponement Competition under Dynamic Behavior of Demand},
  year={2009},
  author={Yohanes Kristianto and Petri T. Helo},
  journal={Operations and Supply Chain Management: An International Journal},
  volume={2},
  number={1},
  pages={52--61},
  doi={10.31387/oscm030122}
}
    Yohanes Kristianto, Petri T. Helo (2009). Time and Form Postponement Competition under Dynamic Behavior of Demand. Operations and Supply Chain Management: An International Journal, 2(1), 52-61. https://doi.org/10.31387/oscm030122
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