Establishing a transport operation focused uncertainty model for the supply chain

Purpose – Much of the recent research on supply chain uncertainty has focused on relationships between manufacturers and suppliers and existing models have therefore been based on this dyadic structure. The aim is to establish a supply chain uncertainty model that explicitly incorporates transport operations and hence the logistics triad; supplier, customer and transport carrier. Design/methodology/approach – This is a literature-based activity that synthesises and extends existing models of supply chain uncertainty. Findings – The paper develops a newmodel to reflect the nature of transport operations. Consequently, it identifies five main categories of uncertainty, namely from the points of view of the supplier, the customer and the carrier, respectively, the control systems used in the supply chain and external factors. The interfaces between the uncertainty categories involving all three parties of the logistics triad are identified, so as to develop a more holistic perspective on supply chain uncertainty and how it can be reduced. Research limitations/implications – This paper is conceptual in nature and empirical research into the area of transport uncertainty will be required to validate its findings. Following this, the model can be used to investigate and evaluate improvements in the economic and/or environmental performance of freight transport within supply chains. Practical implications – The model is intended to provide a framework within which organisations, including logistics providers, can develop a supply chain strategy to mitigate the effects of uncertainty. By categorising uncertainty into the types described, organisations may determine where the greatest uncertainties lie and hence develop a prioritised plan for supply chain re-engineering by initially targeting those uncertainties with the most significant implications for supply chain efficiency. Originality/value – Little research has been undertaken on the impact of uncertainties on transport in the context of collaborative supply chain management. The model rationalises uncertainties into various types taking into account the nature of the logistics triad.

[1]  Chandra Lalwani,et al.  Investigating the impact of demand amplification on freight transport , 2008 .

[2]  Chandra Lalwani,et al.  Analysis of factory gate pricing in the UK grocery supply chain , 2007 .

[3]  Augusto Q. Novais,et al.  An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty , 2007, Eur. J. Oper. Res..

[4]  W. Hoffman Warning bells for 3PLs , 2006 .

[5]  Mohamed Mohamed Naim,et al.  The role of transport flexibility in logistics provision , 2006 .

[6]  Alan C. McKinnon,et al.  LIFE WITHOUT TRUCKS: THE IMPACT OF A TEMPORARY DISRUPTION OF ROAD FREIGHT TRANSPORT ON A NATIONAL ECONOMY , 2006 .

[7]  Kiron Chatterjee,et al.  Planning for an Unpredictable Future: Transport in Great Britain in 2030 , 2006 .

[8]  J. Schulz A hedge against uncertainty , 2006 .

[9]  Dawn M. Russell,et al.  A Disaggregate Analysis of Ocean Carriers' Transit Time Performance , 2006, Transportation Journal.

[10]  R Stratton,et al.  The optimal quantity of quick response manufacturing for an onshore and offshore sourcing model , 2005 .

[11]  T. Litman Efficient vehicles versus efficient transportation. Comparing transportation energy conservation strategies , 2005 .

[12]  R. Eltantawy,et al.  Securing the upstream supply chain: a risk management approach , 2004 .

[13]  Alan C. McKinnon,et al.  Use of a synchronised vehicle audit to determine opportunities for improving transport efficiency in a supply chain , 2004 .

[14]  Michael Tracey,et al.  Transportation Effectiveness and Manufacturing Firm Performance , 2004 .

[15]  Hau L. Lee,et al.  Mitigating supply chain risk through improved confidence , 2004 .

[16]  J. L. Cavinato Supply chain logistics risks: From the back room to the board room , 2004 .

[17]  T.C.E. Cheng,et al.  An empirical study of supply chain performance in transport logistics , 2004 .

[18]  Robert J. Vokurka,et al.  A conceptual model of supply chain flexibility , 2003, Ind. Manag. Data Syst..

[19]  R. Boughton,et al.  ADDRESSING THE ESCALATING COST OF ROAD TRANSPORT , 2003 .

[20]  Glenn Lyons,et al.  Freight and logistics: Number seven in a series of eight reports from the Transport Visions Network , 2003 .

[21]  Scott J. Mason,et al.  INTEGRATING THE WAREHOUSING AND TRANSPORTATION FUNCTIONS OF THE SUPPLY CHAIN , 2003 .

[22]  Diane A. Mollenkopf,et al.  CHEMICAL RAIL TRANSPORT : THE BENEFITS OF RELIABILITY , 2003 .

[23]  Denis Royston Towill,et al.  Simplified material flow holds the key to supply chain integration , 2003 .

[24]  Timon C. Du,et al.  Applying collaborative transportation management models in global third-party logistics , 2003, Int. J. Comput. Integr. Manuf..

[25]  A. Beulens,et al.  Identifying sources of uncertainty to generate supply chain redesign strategies , 2002 .

[26]  Denis Royston Towill,et al.  UNCERTAINTY AND THE SEAMLESS SUPPLY CHAIN , 2002 .

[27]  Michael Coyle,et al.  Effective fuel management in road transport fleets. , 2002 .

[28]  Anu Bask,et al.  Relationships among TPL providers and members of supply chains – a strategic perspective , 2001 .

[29]  Göran Svensson,et al.  A conceptual framework for the analysis of vulnerability in supply chains , 2000 .

[30]  John Dinwoodie,et al.  Congestion and multimodal transport: a survey of cargo transport operators in the Netherlands , 2000 .

[31]  Theodore P. Stank,et al.  A framework for transportation decision making in an integrated supply chain , 2000 .

[32]  Amelia C. Regan,et al.  Impacts of highway congestion on freight operations: perceptions of trucking industry managers , 1999 .

[33]  S. Vickery,et al.  Supply Chain Flexibility: An Empirical Study , 1999 .

[34]  Joseph R. Carter,et al.  Transportation costs and inventory management: Why transportation costs matter , 1996 .

[35]  Massimo Gastaldi,et al.  Environmental protection, economic efficiency and intermodal competition in freight transport , 1996 .

[36]  William J. Baumol,et al.  An Inventory Theoretic Model of Freight Transport Demand , 1970 .

[37]  Lori Tavasszy,et al.  Freight modelling: an overview of international experiences , 2008 .

[38]  Chung-Lun Li,et al.  Managing uncertainty in logistics service supply chain , 2007 .

[39]  M. Naim,et al.  Aligning relationship goals and measures within a logistics triad , 2007 .

[40]  Erhan Kozan,et al.  An assignment model for dynamic load planning of intermodal trains , 2006, Comput. Oper. Res..

[41]  M. M. Naim,et al.  On assessing the sensitivity to uncertainty in distribution network design , 2006 .

[42]  Hens Runhaar,et al.  Public policy intervention in freight transport costs: effects on printed media logistics in the Netherlands , 2005 .

[43]  Chandra Lalwani,et al.  Integrating transportation into the supply chain to improve supply chain performance , 2004 .

[44]  Chandra Lalwani,et al.  Transport in supply chains , 2004 .

[45]  Terry L. Esper,et al.  The value of Collaborative transportation management (CTM): Its relationship to CPFR and information technology , 2003 .

[46]  J. E. Tyworth,et al.  SHIPPER SENSITIVITY TO UNRELIABLE SERVICE IN CARLOAD MARKETS , 2001 .

[47]  Z. K. Weng,et al.  THE DESIGN OF A JIT SUPPLY CHAIN: THE EFFECT OF LEADTIME UNCERTAINTY ON SAFETY STOCK , 1999 .

[48]  Edward A. Morash,et al.  THE ROLE OF TRANSPORTATION CAPABILITIES IN INTERNATIONAL SUPPLY CHAIN MANAGEMENT , 1997 .

[49]  M R Crum,et al.  JUST-IN-TIME MANAGEMENT AND TRANSPORTATION SERVICE PERFORMANCE IN A CROSS-BORDER SETTING , 1997 .

[50]  James A. Narus,et al.  Rethinking Distribution: Adaptive Channels , 1996 .