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

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
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    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).

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