Modeling defaults of companies in multi-stage supply chain networks

The interest in supply chain networks and their analysis as complex systems is rapidly growing. The physical approach to the topic draws on the concept of heterogenous interacting agents. The interaction among agents is considered as a repeated process of orders and production. The dynamics of production in the supply chain network which we observe is nonlinear due to the random failures in processes of orders and production. We introduce an agent-based model of a supply chain network which represents in more detail the real economic environment in which firms operate. We focus on the influence of local processes on the global economic behavior of the system and study how the proposed modifications change the general properties of the model. We observe collective bankruptcies of firms, which lead to self-emerging network structures. Our results give insight into the dynamics of default processes in supply chain networks, which have important implications both for risk managers and policy makers. Based on the simulations we show that agent-based modeling is a powerful tool for optimization of supply chain networks.     

Streamlining inventory flows with time discounts to improve the profits of a decentralized supply chain

We consider a decentralized supply chain, whereby a supplier sells a product to a group of independent buyers, and develop a strategy for the supplier to offer an all-units price discount or cash rebate for orders that are synchronized with its replenishments. As synchronized orders can be met with inventory directly from receiving to shipping without warehousing, the proposed strategy streamlines system inventory flows to minimize inventory and, hence, the related costs. On the other hand, by increasing the replenishment interval of the supplier, the proposed strategy is able to induce buyers to order in large quantities and hence achieve the objectives of quantity discounts. We show that the proposed strategy can achieve nearly optimal (minimum) system cost, and is much more effective than the existing coordination strategies for decentralized supply chains in the literature.     

An autonomous multi-agent approach to supply chain event management

Organizations have made a significant effort to implement software for planning and scheduling, but disruptive event management is still a problem to be solved. Since a disruptive event can affect the overall performance of the supply chain, SCEM (Supply Chain Event Management) systems presenting different automation levels such as monitoring, alarm and decision support have been proposed. However, the management of disruptive events, taking into account the distributed nature of the supply chain, the members' autonomy and the ability to exert corrective control actions, has been identified as a problem that requires further research. This work presents an agent-based approach for the SCEM problem, which can perform autonomous corrective control actions to minimize the effect of deviations in the plan that is currently being executed. These control actions consist of a distribution of the variation between supply chain members, using the plan's slack in a collaborative way. An innovative feature of this approach is its focus on resources, which are affected by disruptive events in a direct way. Based on this approach, a SCEM system is designed as a net of control points defined on resources connected through supply process orders. Two novel aspects are the distributed collaborative inter-organizational architecture of the SCEM system and a Double Contract Net Protocol. This protocol allows a set of resource:representing agents to interact through an agent, representing a supply process order as a mediator. An application to a case study of the Multi-Agent SCEM system implemented with JADE is provided.     

The role of elasticity in supply chain performance

This paper develops a model that describes the performance of supply chains based on their elasticities of supply and demand. The model can be used to predict a supply chain's ability to respond to supply interruptions, cost increases, and demand shifts, while also quantifying the degree to which it is prone to the bullwhip effect. The bullwhip effect is a behavioral phenomenon by which orders are distorted as they are transmitted through the chain. Four types of supply chains are identified and their distinct operating characters are examined. The impact of rival firms and the impact of a decoupling point on supply chain performance are also examined.     

Cobacabana (control of balance by card-based navigation): A card-based system for job shop control

Existing card-based production control systems such as Kanban are mostly dedicated to repetitive production environments. Cards-based systems for job shop control are lacking, while particularly this industry segment shows a need for simple control systems. This paper aims at filling the gap by presenting a simple card-based system for job shop control, the Cobacabana (control of balance by card-based navigation) system. It is based on the concept of workload control (WLC), which has already proven its value in job shops. Developments towards more robust norms now allow for transforming the WLC concept into a simple card-based system, with loops of cards accompanying orders from release until completion at critical work centers. Cards returning from work centers authorize the planner to release new orders. A card-based display supports the planner with an overview of the shop floor situation, based on non-released cards. An additional loop of cards between sales and planning enables support of the order acceptance and due date promising function. A card-based acceptance display indicates what delivery dates are realistic, considering the current workload situation. Both the scientific roots of the system and practical implementation issues are discussed in this paper.     

The MPS parameterization under lead time uncertainty

The supply planning of assembly systems under lead times uncertainty is studied. The used criteria is the sum of the average holding cost for the components, the average backlogging cost for the finished product, and the setup cost. The decision variables are the planned lead times of components and the periodic ordering quantity. A new generalized Newsboy model gives the optimal solution under the assumption that the lead times of the different types of components follow the same distribution probability, and that the holding costs per period of the ordered quantities are the same.     

Validation of Expert Systems for Innovation Management: Issues, Methodology, and Empirical Assessment

Faced with the complexities of managing new product development, most of us would welcome the support of a computer-based system that captures the knowledge and the reasoning capabilities of experts in our field. Considerable effort has been focused on the design and development of expert systems for applications such as new product management. However, design and development are only two steps on the path to successful implementation of a useful expert system. A rigorous validation process is essential for ensuring that the expert system performs as intended. Using the INNOVATOR expert system as an example, Sundaresan Ram and Sudha Ram propose and test a framework for validating expert systems designed for new product management. The proposed validation framework considers three aspects of the expert system: its knowledge acquisition methodology, its performance, and its utility. Validation of an expert system's knowledge acquisition methodology involves assessment of the knowledge sources used, the criteria for selecting human experts, and the methods used for knowledge acquisition. Using multiple sources improves the likelihood that the expert system will capture the necessary core knowledge. Similarly, selection of the experts who are to supply the knowledge used by the expert system should be based on reliable measures of new product expertise rather than ad hoc measures. The system's performance is evaluated through formal tests of the accuracy and the completeness of the knowledge base, the consistency and the accuracy of the decisions made by the system, and the reasoning process by which the system reaches its decisions. Such tests may involve direct examination of the system by experts, and Turing tests, which compare both the recommendations and the reasoning process of the system with those of selected experts. Both types of tests may involve experts from whom knowledge was acquired during the development of the system as well as experts who were not involved in the design and development of the system. Assessment of an expert system's utility focuses on user perceptions of system performance and utility as well as the design of the user interface. First, end-users must evaluate the relevance of the chosen problem domain. In other words, the validation process must verify that the expert system addresses an important problem that requires decision support tools. Second, the expert system must provide a logical, systematic approach to solving the problem. Finally, the expert system must provide a consistent, intuitive user interface.     

Integrated inventory models with controllable lead time and backorder discount considerations

Many companies use time as a means of differentiating themselves in the marketplace. In many literatures, the controllable lead time is regarded as a decision variable and decomposed into several components, each having a crashing cost function for the respective reduced lead time. When an item is out of stock, the loyal, patient and captive customers will wait until the outstanding orders arrive and are served from them. To compensate for the inconvenience of backordering and to secure orders, the supplier may offer a price discount on the stockout item. In this paper, an integrated inventory system in which shortage is allowed and both lead time and backordering are negotiable is investigated. The lead time crashing cost is represented as a function of reduced lead time and the quantities in the orders. There are two inventory models proposed in the paper, one with normally distributed demand, and another with generally distributed demand.     

Optimal time phasing and periodicity for MRP with POQ policy

This paper deals with component supply planning for assembly systems where several types of components are ordered from external suppliers to produce a single type of finished product. Actual component lead times are often different from those contracted because of random delays. An MRP approach with periodic order quantity (POQ) policy is used for the supply planning of components. Our aim is to find the optimal values of the order periodicity and planned lead times at the offsetting step of the MRP procedure. The goal is to minimise the sum of the average component holding, finished product backlogging and setup costs. Several theoretical properties of the objective function are proven and an efficient optimization algorithm is developed. The proofs of the explicit form and properties of the objective function as well as the development of the optimization algorithm occupy a large portion of this paper. The method developed can be used for the optimization of time phasing and periodicity for such an MRP system under lead time uncertainties.     

Coordinated supply chain scheduling

A mixed integer programming approach is proposed for a long-term, integrated scheduling of material manufacturing, material supply and product assembly in a customer driven supply chain. The supply chain consists of three distinct stages: manufacturer/supplier of product-specific materials (parts), producer where finished products are assembled according to customer orders and a set of customers who generate final demand for the products. The manufacturing stage consists of identical production lines in parallel and the producer stage is a flexible assembly line. The overall problem is how to coordinate manufacturing and supply of parts and assembly of products such that the total supply chain inventory holding cost and the production line start-up and parts shipping costs are minimized. A monolithic approach, where the manufacturing, supply and assembly schedules are determined simultaneously, is compared with a hierarchical approach. Numerical examples modeled after a real-world integrated scheduling in a customer driven supply chain in the electronics industry are presented and some computational results are reported.     

Modular interconnected processes,fluid partnering,and innovation speed: A loosely coupled systems perspective on B2B service supply chain management

In this paper, we examine whether and how loosely coupled systems in service supply chains influence the speed of innovation in service organizations. Drawing upon the nomological network of loosely coupled systems, we propose a way for supply chains in the business to business (B2B) market context to be conceptualized as loosely coupled systems and explain how the dialectical elements of modularity at the interface of standard process and content interfaces (SPCI) and structured data connectivity (SDC) enable the sharing of high-quality information through fluid partnership in service supply chains to improve innovation speed. Results that are based on a sample of service firms indicate that SPCI and SDC are positively associated with modular interconnected processes, and they, in turn, positively influence the ability to reconfigure supply chain partners (fluid partnership). Fluid partnership enhances information quality, which in turn, influences innovation speed. Implications are discussed for B2B service supply chain efforts in improving innovation speed.     

Accelerating the Process of Engineering Change Orders: Capacity and Congestion Effects

Engineering change orders (ECOs) are important drivers of development costs and lead time. This article analyzes the process of administering engineering change orders in the case of the climate control system development within a large vehicle development project. This administrative process encompasses the emergence of a change (e.g., a problem or a market-driven feature change), its management approval, and final implementation. Despite strong time pressure, this process can take several weeks, several months, and, in extreme cases, even over 1 year. Such a long lead time is especially remarkable as the actual processing time for the change typically does not exceed 2 weeks. Based on our case study, we develop an analytical framework that explains how such an extreme ratio between theoretical processing time and actual lead time is possible. The framework identifies congestion, stemming from scarce capacity coupled with processing variability, as a major lead time contributor. We outline five improvement strategies that an organization can use in order to reduce ECO lead time, namely, flexible capacity, balanced workloads, merged tasks, pooling, and reduced setups and batching. © 1999 Elsevier Science Inc.     

Business processes inter-operation for supply network co-ordination

In a global supply network, the overall improvement of operational efficiency and customer satisfaction can only be achieved through greater co-ordination and collaboration of all the network members. However, full benefits of close co-operation within a global supply network can only be achieved when the business processes of the individual companies can inter-operate. Currently available commercial solutions are inadequate in supporting full network co-ordination in terms of business process changes and technical arrangements. This paper proposes a system that aims to improve the co-ordination of production planning and control activities across the supply network. To achieve this, it is important to develop new business processes and principles for company collaboration and corresponding information systems. This process starts from the identification of business and system requirements, which underlie the general business solutions for network co-ordination, developing the guiding design principles and subsequent process design and system implementation.     

Technology adoption, learning spillovers, and the optimal duration of patent-based monopolies

The paper analyses an often overlooked aspect of the patent system, namely, that a monopoly franchise for production of a new good could lead to a second-best welfare optimum event when there was no future prospect of inventions being induced by the patent. It is shown that a paten may improve economic welfare relative to a regime of competitive supply when there are learning externalities or ‘spillovers’ from experience in the process of production. Comparative statics show that stronger learning effects at low levels of experience tend to strengthen the case for ex post grant of a monopoly franchise.     

Considering stochastic lead times in a manufacturing/remanufacturing system with deterministic demands and returns

In this paper we study a manufacturing/remanufacturing system with stochastic lead times and a constant demand. We base our approach on previous research in which we have developed models to describe an inventory system with stochastic lead times. In this paper, we first adopt this method to manufacturing/remanufacturing situations, where there are essentially two supply sources for replenishing serviceable inventory. We then provide a solution procedure when a cycle ordering policy is used. Secondly, we investigate the possibility to use a dual sourcing ordering policy in which each order is split between a manufacturing and a remanufacturing process. Finally, we compare the two ordering policies and illustrate how the lead-time patterns influence the economic consequences.     

A co-ordination model combining incentive scheme and co-ordination policy for a single-vendor-multi-buyer supply chain

Incentive scheme and co-ordination policy are substantial components for the co-ordination of a decentralized supply chain system, but there is little work combining the two components as a single decision model (Li and Wang, 2007). This paper proposes a model which incorporates both incentive and co-ordination issues into a single co-ordination model for a single-vendor multi-buyer supply chain. In the proposed model, the co-ordination is achieved by synchronizing ordering and production cycles while price discount, which is based on the buyers’ order intervals, is used as the incentive to motivate buyers to participate in the co-ordination. While the vendor is benefited from the co-ordination by synchronized cycles, the proposed price discount scheme can guarantee that a buyer’s total relevant cost of co-ordination will be reduced when compared with independent optimization. More importantly, the proposed price discount scheme does not require any cost information from the buyers.     

Mechanization in Ghana: Emerging demand,and the search for alternative supply models

Influential studies in the 1980s and early 1990s drew on the Boserup–Ruthenberg theories of farming systems evolution to argue that African countries were not yet ready for widespread agricultural mechanization. Through applying the theories of farming systems evolution and of induced innovation in technical change, this paper shows that demand for certain mechanized farming operations particularly plowing has emerged even among smallholders, suggesting that supply issues may now be the main constraint to successful mechanization. We therefore adopt a supply chain approach to analyze two types of mechanization practices in Ghana, i.e., a recent state-led mechanization program and the private sector-led service hiring market, against an international perspective by drawing on three Asian supply models. We identify two major flaws in existing policies. First, the agricultural mechanization service centers that the government promotes fail to use tractors services with sufficient intensity. Second, direct importation of agricultural machinery by the government inhibits imports of appropriate and affordable machinery. In contrast, the development of mechanized service hiring market in which medium and large scale farmers who are tractor owners provide hiring-out services to small-scale farmers represents a promising model for sustainable mechanization in Ghana. This private sector-led second model is consistent with international experiences.     

Information Use in New Product Development: An Initial Exploratory Empirical Investigation in the Chemical Industry*

In‐depth interviews with product developers and product development software providers in a previous qualitative phase of research uncovered eight general types of information that are used across the new product development process (strategic, project management, financial, market and customer, wants and needs, technical, competitor, and regulatory information) and three general approaches to managing information in the process (project‐centric, functionally oriented, and fully distributed). This paper presents a second phase of research trying to understand the role that managing knowledge and information plays in developing new products and achieving NPD success. This research phase empirically investigates use of the eight types of information across three general phases of the NPD process in the chemical industry using 81 mail survey responses from marketing and new product development professionals. Respondents were asked to indicate the degree to which each of the eight information types was used in each of the following general phases of new product development: the fuzzy front end, development, and testing and launch. The respondents also provided information on new product development success, information management system sophistication, and innovation strategy. This research makes several contributions to new knowledge. First, this research suggests that information management in product development is even more complex than initially posited in Zahay et al. (2004) , with each of the eight types of information identified being used in each of the three phases of development. Unexpectedly, for all but one type of information use is higher in later stages of the NPD process, even though use of several kinds of information early in the project is associated with increased success. Thus, managers may need to encourage teams to start gathering information from outside the firm earlier than is currently the norm. Second, the results suggest that more sophisticated information management systems are indeed associated with increased use of various different types of information, as expected. Third, more sophisticated information management systems are more highly associated with success than less sophisticated information management systems. These results are important, as most new product development information management systems are limited in their ability to handle complex and non‐quantitative information such as customer wants and needs, as well as strategic, competitor, and regulatory information. However, being able to transmit information on these issues is associated with increased firm performance and project success from these data. Thus, firms need to figure out how to improve their ability to manage and use non‐quantitative information more effectively.     

REAL OPTION MODELS FOR MANAGING MANUFACTURING SYSTEM CHANGES IN THE NEW ECONOMY

The manufacturing environment is becoming increasingly dynamic with upsurges in electronic-commerce, supply chain management, forecasting, and procurement and resource planning. It also includes trends toward more process data acquisition and analysis, shorter production runs, and more stringent quality requirements. These drivers lead to an opportunity for companies to collect and use information to identify changes that will affect their manufacturing systems. In conjunction with an industry partner who produces home fashion products, we developed a case-study that highlights four major manufacturing transitions: new product introduction; moving a product from research and development (R&D) to commercialization: new plant location; and starting or restarting production of existing products. These types of changes cross many levels of the operation - including the product level, plant level, and organizational level - and typically present significant operational challenges. We use this case-study to motivate the theoretical and applied research needed to support a real option framework for system changes in manufacturing. The key elements of our framework are to quantify manufacturing changes, develop a real option model for these activities, value the options to identify the best scenarios, and integrate these elements so that we can monitor and manage the overall process. The advantage of this approach is that it allows us to directly incorporate a market driven perspective, tying the manufacturing operations with the organizational economic goals.