Supply Chain Setting Research Articles

Data Synchronization Technology: Standards, Business Values and Implications

The Internet-enabled connectivity has created opportunities for businesses to conduct various forms of collaborative activities. However, the findings of several surveys indicate that the deficiencies in data quality might compromise the potential benefits of joint efforts. Global data synchronization (GDS), the process of timely updating product data to maintain the data consistency among business partners, is viewed as the key to materializing the benefits of ecollaboration in the global supply chain setting. In the paper, we present the need for data synchronization, discuss the evolution of technical standards of data identification schemes, and introduce the Global Data Synchronization Network (GDSN), the platform on which global data synchronization is substantiated. We detail the structure of GDSN and the protocols for the process of GDS. Furthermore, we discuss business and management implications of GDS, different approaches to implementing GDS, and challenges to the implementation of GDS. The emergence of GDS and GDSN presents research opportunities on issues relating to the implementation of GDS, the relationship between GDSN and EPCglobal Network, the impact of GDS on inter-organizational relationships, the network effect of global standards, and evolution of complementary standards. We discuss these research opportunities. In brief, the article covers the history, present status, and future of GDS and GDSN, as well as their potentials, benefits, and implementation issues.

The three dimensions of responsiveness

PurposeThe concept of responsiveness has been widely discussed, yet so far most of this discussion has remained qualitative in nature. The purpose of this paper is to develop a conceptual model identifying the key factors that determine the responsiveness of a supply chain system, which – once quantified – provide a unique profile of each supply chain setting towards the appropriate supply chain strategy.Design/methodology/approachThe paper reviews existing contributions and synthesises these into a conceptual model of responsiveness. The model is applied using three case studies from the automotive and electronics industry. The case research is based on value stream mapping, semi‐structured interviews, and site visits.FindingsThree key findings could be established: first, the concept of responsiveness has a simple logic that aligns itself to a wide range of manufacturing strategies. However, underlying this remit is a complex interaction of an array of key variables, and it was found that previous contributions largely have only addressed a subset of these. Second, these key variables can be grouped into three categories or dimensions of responsiveness – product, process and volume – to provide a holistic understanding of responsiveness and its key determinants. Third, due to the large involved, there cannot be one single “holy grail” concept of how responsiveness can be achieved, neither does one single approach apply to entire sectors.Research limitations/implicationsA great variety of variables needs to be considered in order to provide a balanced view of all three dimensions of responsiveness, thus the case analyses remain at a necessarily high level.Practical implicationsThe paper provides guidelines for management on how to align their supply chain strategy to volume, product and process contingency factors in order to balance responsiveness to customer demand and supply chain efficiency.Originality/valueThe paper aims to elevate a discussion that previously has been held mostly at a conceptual level beyond the qualitative description, and thus addresses a key shortcoming in the current debate.

Supply Chain Collaboration:: Making Sense of the Strategy Continuum

Collaboration in the supply chain has been widely discussed, and a wealth of concepts is at hand. Large-scale projects like the Efficient Consumer Response (ECR) in the fast moving consumer goods sector, for example, or Vendor Managed Inventory (VMI) and Collaborative Planning, Forecasting and Replenishment (CPFR) initiatives more generally provide a rich continuum of strategies for collaborating amongst supply chain partners. While individual successful implementations of the latter have already been reported, there has not yet been the widespread adoption that was originally hoped for. In our research, we looked at implementations across several industries and countries, and our findings show that the slow progress to date may be due to a lack of common understanding of these concepts, and the difficulty of integrating external collaboration with internal production and inventory control. In this paper, we set out to classify collaboration initiatives using a conceptual water-tank analogy, and discuss their dynamic behavior and key characteristics. We draw upon case studies from both successful and less successful implementations to illustrate what companies need to do to fully benefit from their collaborative efforts, given their particular circumstances. We conclude that the effectiveness of supply chain collaboration relies upon two factors: the level to which it integrates internal and external operations, and the level to which the efforts are aligned to the supply chain settings in terms of the geographical dispersion, the demand pattern, and the product characteristics.

Efficient Auction Mechanisms for Supply Chain Procurement

We consider multiunit Vickrey auctions for procurement in supply chain settings. This is the first paper that incorporates transportation costs into auctions in a complex supply network. We first introduce an auction mechanism that makes simultaneous production and transportation decisions so that the total supply chain cost is minimized and induces truth telling from the suppliers. Numerical study shows that considerable supply chain cost savings can be achieved if production and transportation costs are considered simultaneously. However, the buyer's payments in such auctions can be high. We then develop a new Vickrey-type auction that incorporates the buyer's reservation price function into quantity allocation and payment decision. As a result, the buyer has some control over his payments at the expense of introducing uncertainty in the quantity acquired in the auction.

A simulation-based genetic algorithm for inventory optimization in a serial supply chain

One of the important aspects of supply chain management is inventory management because the cost of inventories in a supply chain accounts for about 30% of the value of the product. The main focus of this work is to study the performance of a single-product serial supply chain operating with a base-stock policy and to optimize the inventory (i.e. base stock) levels in the supply chain so as to minimize the total supply chain cost (TSCC), comprising holding and shortage costs at all the installations in the supply chain. A genetic algorithm (GA) is proposed to optimize the base-stock levels with the objective of minimizing the sum of holding and shortage costs in the entire supply chain. Simulation is used to evaluate the base-stock levels generated by the GA. The proposed GA is evaluated with the consideration of a variety of supply chain settings in order to test for its robustness of performance across different supply chain scenarios. The effectiveness of the proposed GA (in terms of generating base-stock levels with minimum TSCC) is compared with that of a random search procedure. In addition, optimal base-stock levels are obtained through complete enumeration of the solution space and compared with those yielded by the GA. It is found that the solutions generated by the proposed GA do not significantly differ from the optimal solution obtained through complete enumeration for different supply chain settings, thereby showing the effectiveness of the proposed GA.

How a Base Stock Policy Using "Stale" Forecasts Provides Supply Chain Benefits

Managers often engage in forecast updating with the expectation that forecast updating reduces expected shortage and inventory costs. One undesirable effect of forecast updating is that it may lead to the bullwhip effect, a phenomenon where the variability of demand increases as one moves up the supply chain. The bullwhip effect can be undesirable for the supplier because more volatile orders from the downstream stage can be very costly to the supplier. It can make it more difficult for the supplier to forecast demand, and it can lead to large fluctuations in supplier production levels from period to period. Using "stale" or old forecasts may sound foolish, but their judicious use in a two-stage supply chain can improve fulfillment from the upstream stage to the downstream stage and reduce the fluctuations in production levels. We study a two-stage supply chain where the demand process is nonstationary and both stages use an adaptive base stock policy. We propose a policy that uses old forecasts to set base stock levels at the downstream stage while using current forecasts to communicate upcoming orders from the downstream stage to the upstream stage. We study a decentralized supply chain setting, and we find that our policy can reduce the expected supply chain inventory and shortage costs and significantly reduce the fluctuations in production levels compared to that of using current information. We also study a cooperative supply chain setting and, surprisingly, we find in numerical examples that our proposed policy results in very small increases in the expected systemwide inventory and shortage costs compared to a systemwide optimal policy, while reducing the fluctuations in production levels.

Customized supply chain design: Problems and alternatives for a production company in the food industry. A simulation based analysis

In our paper, we point out that an analysis of a supply chain must be very product- (and company-) specific. For this reason, we suggest an improvement model that helps enhance the performance of a specific supply chain. In this context, we introduce a target system for supply chain evaluation which is necessary to analyze different improvement alternatives. We will show that the ideal robust supply chain setting depends on the demand situation (e.g., smooth, volatile). This model will be illustrated in detail. Hence, the present research studies a product-specific supply chain in the food industry, analyzes the effects of changes carried out and shows how demand uncertainties are dealt with. To measure and analyze the performance effects (e.g., work in process, lead time) of the supply chain configuration alternatives depicted, a simulation environment is developed.

Networking activities in supply networks

The paper traces the origin of the concept of supply networks and focuses on nine different networking activities related to the process of establishing and operating supply networks. These activities are associated with the linking of activities, tying of resources and bonding of actors. Findings from two extensive case studies of supply networks are discussed, focusing on the process of networking in a series of relationships in a set of supply chains constituting each network. The findings reveal some important links between individual activities i.e. specific networking activities that appear to be mutually supportive. Furthermore, positive and negative connections between activities performed in different relationships within each supply network i.e. network effects, are identified.

The Impact of Modular Production on the Dynamics of Supply Chains

The principle of modular production has been applied internally by companies since the 1960's. Innovative companies in various industries are now experimenting with application of the concept in a supply chain setting. Modular production makes it possible to further involve distributors and suppliers in the manufacturing process and create a new tier of suppliers in the automotive industry; that of the “zero‐level supplier”. Expected benefits of the increased integration in the inbound and outbound flow of goods are improved responsiveness to customers and increased efficiency. It can be questioned, however to what extent manufacturers can increase the amount of control over operational activities based on networking, as opposed to control based on ownership, without becoming an empty design and marketing company. This paper assesses the impact of the new model of modular production on the dynamics in supply chains as a whole and the consequences for individual players, based on innovative cases such as that of the SMART car.

How Modular Production can Contribute to Integration in Inbound and Outbound Logistics

ABSTRACT The principle of modular production has been applied internally by companies since the 1960s. Innovative companies in the automotive industry are now experimenting with the application of the concept in a supply chain setting. Modular production makes it possible to further involve both distributors and suppliers in the manufacturing process and create a new tier of suppliers: the “zero-level suppliers”. Expected benefits of the increased (physical) integration in the inbound and the outbound flow of goods are increased responsiveness to customers and preserved efficiency. It can be questioned, however, to what extent OEMs can increase the amount of control over operational activities based on networking, as opposed to control based on ownership, without becoming an “empty” design and marketing company.