Success factors in a forming strategic positioning of manufacturing operations within global supply chains

Managing supply chains effectively has become a critical element in enhancing company profitability and has been identified as the new frontier of competitive advantage. An important element of effective supply chain management is the strategic positioning of the company. The strategic positioning process is concerned with the choice of production-centred activities a company carries out internally and those provided externally. Strategic positioning within manufacturing supply chains however is a relatively recent research topic with apparently few articles currently available that explicitly address associated issues directly. Moreover there is no previous research working strategic positioning of manufacturing operations in global context. Therefore the purpose of this paper is to explore strategic positioning within global supply chains. This paper is based on three cases drawn from the cross industry sector manufacturing companies. It describes an exploratory analysis which is aimed at gaining insight into the success factor to form a strategic positioning within global supply chains.

Using min-sum loopy belief propagation for decentralised supply chain formation

Modern business trends such as agile manufacturing and virtual corporations require high levels of flexibility and responsiveness to consumer demand, and require the ability to quickly and efficiently select trading partners. Automated computational techniques for supply chain formation have the potential to provide significant advantages in terms of speed and efficiency over the traditional manual approach to partner selection. Automated supply chain formation is the process of determining the participants within a supply chain and the terms of the exchanges made between these participants. In this thesis we present an automated technique for supply chain formation based upon the min-sum loopy belief propagation algorithm (LBP). LBP is a decentralised and distributed message-passing algorithm which allows participants to share their beliefs about the optimal structure of the supply chain based upon their costs, capabilities and requirements. We propose a novel framework for the application of LBP to the existing state-of-the-art case of the decentralised supply chain formation problem, and extend this framework to allow for application to further novel and established problem cases. Specifically, the contributions made by this thesis are: • A novel framework to allow for the application of LBP to the decentralised supply chain formation scenario investigated using the current state-of-the-art approach. Our experimental analysis indicates that LBP is able to match or outperform this approach for the vast majority of problem instances tested. • A new solution goal for supply chain formation in which economically motivated producers aim to maximise their profits by intelligently altering their profit margins. We propose a rational pricing strategy that allows producers to earn significantly greater profits than a comparable LBP-based profitmaking approach. • An LBP-based framework which allows the algorithm to be used to solve supply chain formation problems in which goods are exchanged in multiple units, a first for a fully decentralised technique. As well as multiple-unit exchanges, we also model in this scenario realistic constraints such as factory capacities and input-to-output ratios. LBP continues to be able to match or outperform an extended version of the existing state-of-the-art approach in this scenario. • Introduction of a dynamic supply chain formation scenario in which participants are able to alter their properties or to enter or leave the process at any time. Our results suggest that LBP is able to deal easily with individual occurences of these alterations and that performance degrades gracefully when they occur in larger numbers.

Decentralised supply chain formation:a belief propagation-based approach

Decentralised supply chain formation involves determining the set of producers within a network able to supply goods to one or more consumers at the lowest cost. This problem is frequently tackled using auctions and negotiations. In this paper we show how it can be cast as an optimisation of a pairwise cost function. Optimising this class of functions is NP-hard but good approximations to the global minimum can be obtained using Loopy Belief Propagation (LBP). Here we detail a LBP-based approach to the supply chain formation problem, involving decentralised message-passing between potential participants. Our approach is evaluated against a well-known double-auction method and an optimal centralised technique, showing several improvements: it obtains better solutions for most networks that admit a competitive equilibrium Competitive equilibrium as defined in [3] is used as a means of classifying results on certain networks to allow for minor inefficiencies in their auction protocol and agent bidding strategies. while also solving problems where no competitive equilibrium exists, for which the double-auction method frequently produces inefficient solutions.

Exploring supply chain related graduate programmes in the UK:a view on their structure, content and approaches

Research in skill requirements needed by supply chain/logistics (SCL) managers has been published since the early nineties, however, research on what is really taught (e.g. curriculum, learning philosophies) by universities is scant. This paper's aim is to fill in this gap by analysing SCL graduate teaching in the UK. Data from 50 SCL MSc programmes were collected from 43 universities. Findings indicate that there seems to be a gap emerging between industry's needs and the content of the programmes being offered. This gap concerns employability, problem based learning, international business and the acquisition of softer interpersonal and problem solving skills.

Decentralized supply chain formation using max-sum loopy belief propagation

Supply chain formation is the process by which a set of producers within a network determine the subset of these producers able to form a chain to supply goods to one or more consumers at the lowest cost. This problem has been tackled in a number of ways, including auctions, negotiations, and argumentation-based approaches. In this paper we show how this problem can be cast as an optimization of a pairwise cost function. Optimizing this class of energy functions is NP-hard but efficient approximations to the global minimum can be obtained using loopy belief propagation (LBP). Here we detail a max-sum LBP-based approach to the supply chain formation problem, involving decentralized message-passing between supply chain participants. Our approach is evaluated against a well-known decentralized double-auction method and an optimal centralized technique, showing several improvements on the auction method: it obtains better solutions for most network instances which allow for competitive equilibrium (Competitive equilibrium in Walsh and Wellman is a set of producer costs which permits a Pareto optimal state in which agents in the allocation receive non-negative surplus and agents not in the allocation would acquire non-positive surplus by participating in the supply chain) while also optimally solving problems where no competitive equilibrium exists, for which the double-auction method frequently produces inefficient solutions. © 2012 Wiley Periodicals, Inc.

Selection of simulation tools for improving supply chain performance

Simulation is an effective method for improving supply chain performance. However, there is limited advice available to assist practitioners in selecting the most appropriate method for a given problem. Much of the advice that does exist relies on custom and practice rather than a rigorous conceptual or empirical analysis. An analysis of the different modelling techniques applied in the supply chain domain was conducted, and the three main approaches to simulation used were identified; these are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). This research has examined these approaches in two stages. Firstly, a first principles analysis was carried out in order to challenge the received wisdom about their strengths and weaknesses and a series of propositions were developed from this initial analysis. The second stage was to use the case study approach to test these propositions and to provide further empirical evidence to support their comparison. The contributions of this research are both in terms of knowledge and practice. In terms of knowledge, this research is the first holistic cross paradigm comparison of the three main approaches in the supply chain domain. Case studies have involved building ‘back to back’ models of the same supply chain problem using SD and a discrete approach (either DES or ABM). This has led to contributions concerning the limitations of applying SD to operational problem types. SD has also been found to have risks when applied to strategic and policy problems. Discrete methods have been found to have potential for exploring strategic problem types. It has been found that discrete simulation methods can model material and information feedback successfully. Further insights have been gained into the relationship between modelling purpose and modelling approach. In terms of practice, the findings have been summarised in the form of a framework linking modelling purpose, problem characteristics and simulation approach.

Sustainable supplier management in the automotive industry:leading the 3rd revolution through collaboration

The omnipresent global economic crisis has had a particularly dramatic effect on the global automotive industry. It has increased the need for a 3rd revolution and the move towards mass-collaboration between all industrial players that may ultimately lead to a governance model based on partnership-focused collaborative relationships. The first two revolutions were led by the US and Japan respectively, but we propose that this time, the European automotive industry will lead the way in the 3rd revolution. This new book provides an operations and supply chain management perspective while focusing on the issue of sustainable supplier management. © 2010 by Nova Science Publishers, Inc. All Rights Reserved.

Simulation in the supply chain context:matching the simulation tool to the problem

The supply chain can be a source of competitive advantage for the firm. Simulation is an effective tool for investigating supply chain problems. The three main simulation approaches in the supply chain context are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). A sample from the literature suggests that whilst SD and ABM have been used to address strategic and planning problems, DES has mainly been used on planning and operational problems., A review of received wisdom suggests that historically, driven by custom and practice, certain simulation techniques have been focused on certain problem types. A theoretical review of the techniques, however, suggests that the scope of their application should be much wider and that supply chain practitioners could benefit from applying them in this broader way.

Reverse resource exchanges in service supply chains:the case of returnable transport packaging

Purpose: The purpose of this paper is to understand how reverse resource exchanges and resource dependencies are managed in the service supply chain (SSC) of returnable transport packaging (RTP). Design/methodology/approach: A single case study was conducted in the context of automotive logistics focusing on the RTP SSC. Data were collected through 16 interviews, primarily with managers of a logistics service provider (LSP) and document analysis of contractual agreements with key customers of the packaging service. Findings: Resource dependencies among actors in the SSC result from the importance of the RTP for the customer’s production processes, the competition among users for RTP and the negative implications of the temporary unavailability of RTP for customers and the LSP (in terms of service performance). Amongst other things, the LSP is dependent on its customers and third-party users (e.g. the customer’s suppliers) for the timely return of package resources. The role of inter-firm integration and collaboration, formal contracts as well as customers’ power and influence over third-party RTP users are stressed as key mechanisms for managing LSP’s resource dependencies. Research limitations/implications: A resource dependence theory (RDT) lens is used to analyse how reverse resource exchanges and associated resource dependencies in SSCs are managed, thus complementing the existing SSC literature emphasising the bi-directionality of resource flows. The study also extends the recent SSC literature stressing the role of contracting by empirically demonstrating how formal contracts can be mobilised to explicate resource dependencies and to specify, and regulate, reverse exchanges in the SSC. Practical implications: The research suggests that logistics providers can effectively manage their resource dependencies and regulate reverse exchanges in the SSC by deploying contractual governance mechanisms and leveraging their customers’ influence over third-party RTP users. Originality/value: The study is novel in its application of RDT, which enhances our understanding of the management of reverse exchanges and resource dependencies in SSCs.