Adapting transport modes to supply chains classified by the uncertainty supply chain model: A case study at Manaus Industrial Pole
Keywords:Uncertainty Supply Chain Model, Manaus Industrial Pole, Transport
This paper discusses transport modes supporting Uncertainty Supply Chain Model (USCM) in the case of Manaus Industrial Pole (PIM), an industrial cluster in the Brazilian Amazon that hosts six hundred factories with diverse logistics and supply chain managerial strategies. USCM (Lee, 2002; Fisher, 1997)develops a dot matrix classification of the supply chains considering several attributes (e.g., agility, cost, security, responsiveness) and argues that emergent economies industrial clusters, in the effort to keep attractiveness for technological frontier firms, need to adapt supply chain strategies according to USCM attributes. The paper takes a further step, discussing which transport modes are suitable to each supply chain classified at the USCM in PIM´s case. The research´s methods covered the use of PIM´s statistical official database (secondary data), interviews with the main logistical services providers of PIM and phone survey with a sample of firms (primary data). Findings confirm the theoretical argument that different supply chains will demand different transport modes running at the same time in the same industrial cluster (Oliveira, 2009). In the case of PIM, this implies investments on port and airport infrastructure and a strategic focus on air transport mode, due to (1) short life cycle of products, (2) distance from suppliers, (3) quick response to demand and (4) the fact that even PIM´s standard products use, in average, forty per cent of air transport at inbound logistics.
Bowersox, D. J., Closs, D. J., Cooper, M. B. (2002). Supply chain logistics management (Vols. 1 and 2). New York, NY: McGraw-Hill.
Christopher, M. (2000). The Agile Supply Chain: competing in volatile markets. Industrial Marketing Management, 29(1), 37-44. https://doi.org/10.1016/S0019-8501(99)00110-8
Fisher, M. L. (1997). What is the right supply chain for your product? Harvard Business Review. March-April, 1997, 105-116.
Grieger, M. (2003). Electronic Marketplaces: A literature review and a call for supply chain management research. European Journal of Operational Research, 144(2), 280-294. https://doi.org/10.1016/S0377-2217(02)00394-6
Halldorsson, A., Kotzab, H., Mikkola, J. H., Skjøtt-Larsen, T. (2007). Complementary theories to supply chainmanagement. Supply Chain Management: An International Journal, 12(4), 284-296. http://dx.doi.org/10.1108/13598540710759808
Lee, H. (2002). Aligning supply chain strategies with product uncertainties. California Management Review, 44(3),167-179. https://doi.org/10.2307/41166135
Marques, G. C., Pereira, S. C. F., Carona, N. (2008). Proposta de um modelo dinâmico para classificação de cadeias de suprimentos. Anais do XI SIMPOI, Rio de Janeiro.
Oliveira, F. L. (2009). Gestão Estratégica das Cadeias de Suprimento com base no Modelo Logístico de Incerteza: O caso do Polo Industrial de Manaus (PIM). Universidade Federal do Rio de Janeiro (DoctoralThesis).
Bathnagar, R., Sohal, A. S. (2005). Supply chain competitiveness: measuring the impact of location factors, uncertainty and manufacturing practices. Technovation, 25(5), 443-456. http://dx.doi.org/10.1016/j.technovation.2003.09.012
SUFRAMA – Superintendência da Zona Franca de Manaus. (2015) Indicadores de Desempenho do Polo Industrial de Manaus. SUFRAMA, Manaus. Available at: http://www.suframa.gov.br. Last access: January 2016.SUFRAMA – Superintendência da Zona Franca de Manaus. (2015) Perfil das Empresas Incentivadas do Polo Industrial de Manaus.
SUFRAMA, Manaus. Available at: http://www.suframa.gov.br. Last access: January 2016.
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