IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v48y2014i3p189-197.html
   My bibliography  Save this article

Economic impact of enhanced forest inventory information and merchandizing yards in the forest product industry supply chain

Author

Listed:
  • Alam, Md Bedarul
  • Shahi, Chander
  • Pulkki, Reino

Abstract

Forest products industry should maximize the value of timber harvested and associated products in order to be competitive in global markets. Enhanced forest inventories and merchandizing yards can help in maximizing value recovery in the forest products supply chain. This study develops an optimization model to analyze the economic impact of enhanced forest inventory information and merchandizing yard operations in the forest products supply chain. The application of the model is demonstrated by using a case study of a hypothetical forest industry in northwestern Ontario, which obtains four log assortment grades from the surrounding eight forest management units. The model analyzes five different scenarios with 0%, 25%, 50%, 75%, and 100% certainty of tree quality in forest inventory information. The results of the study show that with full certainty of tree quality information, it is possible to gain 49% in gross profit in comparison with a scenario with no certainty. The usefulness of enhanced forest inventory and merchandizing yard in the entire supply chain of forest products industry is recognized by maximizing total value of wood fiber (by allocating right log to the right product), reducing fluctuations in raw wood fiber supply, and minimizing inventory carrying costs and lost sales.

Suggested Citation

  • Alam, Md Bedarul & Shahi, Chander & Pulkki, Reino, 2014. "Economic impact of enhanced forest inventory information and merchandizing yards in the forest product industry supply chain," Socio-Economic Planning Sciences, Elsevier, vol. 48(3), pages 189-197.
    • Handle: RePEc:eee:soceps:v:48:y:2014:i:3:p:189-197
    DOI: 10.1016/j.seps.2014.06.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012114000299
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2014.06.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Anton J. Kleywegt & Vijay S. Nori & Martin W. P. Savelsbergh, 2004. "Dynamic Programming Approximations for a Stochastic Inventory Routing Problem," Transportation Science, INFORMS, vol. 38(1), pages 42-70, February.
    2. Chauhan, Satyaveer S. & Frayret, Jean-Marc & LeBel, Luc, 2009. "Multi-commodity supply network planning in the forest supply chain," European Journal of Operational Research, Elsevier, vol. 196(2), pages 688-696, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jagriti Singh & Krishan Kumar Pandey & Anil Kumar & Farheen Naz & Sunil Luthra, 2023. "Drivers, barriers and practices of net zero economy: An exploratory knowledge based supply chain multi-stakeholder perspective framework," Operations Management Research, Springer, vol. 16(3), pages 1059-1090, September.
    2. Riccioli, F. & Fratini, R. & Marone, E. & Fagarazzi, C. & Calderisi, M. & Brunialti, G., 2020. "Indicators of sustainable forest management to evaluate the socio-economic functions of coppice in Tuscany, Italy," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Schmid, Verena & Doerner, Karl F. & Laporte, Gilbert, 2013. "Rich routing problems arising in supply chain management," European Journal of Operational Research, Elsevier, vol. 224(3), pages 435-448.
    2. Hugo P. Simão & Jeff Day & Abraham P. George & Ted Gifford & John Nienow & Warren B. Powell, 2009. "An Approximate Dynamic Programming Algorithm for Large-Scale Fleet Management: A Case Application," Transportation Science, INFORMS, vol. 43(2), pages 178-197, May.
    3. Yossiri Adulyasak & Jean-François Cordeau & Raf Jans, 2015. "Benders Decomposition for Production Routing Under Demand Uncertainty," Operations Research, INFORMS, vol. 63(4), pages 851-867, August.
    4. Bertazzi, Luca & Bosco, Adamo & Laganà, Demetrio, 2015. "Managing stochastic demand in an Inventory Routing Problem with transportation procurement," Omega, Elsevier, vol. 56(C), pages 112-121.
    5. Li, Jing-An & Wu, Yue & Lai, Kin Keung & Liu, Ke, 2008. "Replenishment routing problems between a single supplier and multiple retailers with direct delivery," European Journal of Operational Research, Elsevier, vol. 190(2), pages 412-420, October.
    6. Cárdenas-Barrón, Leopoldo Eduardo & González-Velarde, José Luis & Treviño-Garza, Gerardo & Garza-Nuñez, Dagoberto, 2019. "Heuristic algorithm based on reduce and optimize approach for a selective and periodic inventory routing problem in a waste vegetable oil collection environment," International Journal of Production Economics, Elsevier, vol. 211(C), pages 44-59.
    7. Soumia Ichoua & Michel Gendreau & Jean-Yves Potvin, 2006. "Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching," Transportation Science, INFORMS, vol. 40(2), pages 211-225, May.
    8. Amira Dems & Louis-Martin Rousseau & Jean-Marc Frayret, 2015. "Effects of different cut-to-length harvesting structures on the economic value of a wood procurement planning problem," Annals of Operations Research, Springer, vol. 232(1), pages 65-86, September.
    9. M A Lejeune, 2008. "Preprocessing techniques and column generation algorithms for stochastically efficient demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1239-1252, September.
    10. Miguel A. Lejeune & Andrzej Ruszczyński, 2007. "An Efficient Trajectory Method for Probabilistic Production-Inventory-Distribution Problems," Operations Research, INFORMS, vol. 55(2), pages 378-394, April.
    11. Chih-Kang Lin & Shangyao Yan & Fei-Yen Hsiao, 2021. "Optimal Inventory Level Control and Replenishment Plan for Retailers," Networks and Spatial Economics, Springer, vol. 21(1), pages 57-83, March.
    12. Yugang Yu & Chengbin Chu & Haoxun Chen & Feng Chu, 2012. "Large scale stochastic inventory routing problems with split delivery and service level constraints," Annals of Operations Research, Springer, vol. 197(1), pages 135-158, August.
    13. Sayarshad, Hamid R. & Gao, H. Oliver, 2018. "A non-myopic dynamic inventory routing and pricing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 83-98.
    14. Mirzapour Al-e-hashem, S.M.J. & Rekik, Yacine, 2014. "Multi-product multi-period Inventory Routing Problem with a transshipment option: A green approach," International Journal of Production Economics, Elsevier, vol. 157(C), pages 80-88.
    15. Athanassios Nikolakopoulos & Ioannis Ganas, 2017. "Economic model predictive inventory routing and control," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(3), pages 587-609, September.
    16. Emre Çankaya & Ali Ekici & Okan Örsan Özener, 2019. "Humanitarian relief supplies distribution: an application of inventory routing problem," Annals of Operations Research, Springer, vol. 283(1), pages 119-141, December.
    17. Mirzapour Al-e-hashem, Seyed M.J. & Rekik, Yacine & Mohammadi Hoseinhajlou, Ebrahim, 2019. "A hybrid L-shaped method to solve a bi-objective stochastic transshipment-enabled inventory routing problem," International Journal of Production Economics, Elsevier, vol. 209(C), pages 381-398.
    18. Omid Sanei Bajgiran & Masoumeh Kazemi Zanjani & Mustapha Nourelfath, 2017. "Forest harvesting planning under uncertainty: a cardinality-constrained approach," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1914-1929, April.
    19. Oğuz Solyalı & Jean-François Cordeau & Gilbert Laporte, 2012. "Robust Inventory Routing Under Demand Uncertainty," Transportation Science, INFORMS, vol. 46(3), pages 327-340, August.
    20. Ohlmann, Jeffrey W. & Bean, James C., 2009. "Resource-constrained management of heterogeneous assets with stochastic deterioration," European Journal of Operational Research, Elsevier, vol. 199(1), pages 198-208, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:soceps:v:48:y:2014:i:3:p:189-197. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.