Application of control theoretic principles to manage inventory replenishment in a supply chain

Using uncertain real-time information to update supply chain operational policies creates a need for developing dynamic supply chain management capabilities that increase responsiveness to demand and decrease volatility of the replenishment process (popularly known as the Bullwhip Effect). To this end, we explore the use of control theoretic principles to manage the inventory replenishment process in a supply chain under different forecast situations. We study the use of proportional, proportional-integral and proportional-derivative control schemes to determine the conditions under which specific control actions are beneficial. Analytical models and simulation runs are used to study the trade-off between responsiveness to demand and volatility. Our analysis indicates that using proportional control to manage inventory replenishment is suitable for high forecast error situations. Proportional control along with integral control works well in situations where the forecast bias is relatively higher than the forecast error. Proportional control along with derivative control works best in situations with moderate forecast errors.     

Value of information exchange and synchronization in a multi-tier supply chain

We investigate the value of various information exchange mechanisms in a four-echelon supply chain under a material requirements planning framework. In the absence of any information sharing, each echelon would develop its own forecasts and plan its inventories based on the history of actual demand from its downstream customer (or echelon). Through a simulation study, we compare this policy with policies where each echelon has access to (i) the end-user demand history and (ii) the planned order schedule of the downstream echelon. Among all the demand information exchange mechanisms, planning inventories based on the planned downstream order schedules resulted in the lowest average inventory level for the entire supply chain. However, use of end-user demand history to forecast and plan inventories at all echelons resulted in the lowest total cost. In addition to the information exchange mechanisms, a simple synchronized replenishment system was considered and evaluated in the study. In the synchronized system, the retailer determines a fixed order interval and the upper echelons replenish only at integer multiples of this interval. The study found that synchronized inventory replenishments among the echelons, even without any exchange of demand information, can bring about more benefits and cost reduction than any of the information exchange mechanisms.     

Emerging trends in supply chain architecture

This paper traces significant developments in technology, quality, measurement, and relationships that have led to the study of supply chain networks. The paper introduces five principles of supply chain networks—velocity, variability, vocalize, visualize, and value—that have moved supply chain architecture from an art to a science. Finally, the paper uses each principle to point to an important, emerging trend in supply chain architecture.     

Bullwhip and inventory variance in a closed loop supply chain

A simple dynamic model of a hybrid manufacturing/remanufacturing system is investigated. In particular we study an infinite horizon, continuous time, APIOBPCS (Automatic Pipeline Inventory and Order Based Production Control System) model. We use Åström’s method to quantify variance ratios in the closed loop supply chain. Specifically we highlight the effect of a combined “in-use” and remanufacturing lead-time and the return rate on the inventory variance and bullwhip produced by the ordering policy. Our results clearly show that a larger return rate leads to less bullwhip and less inventory variance in the plant producing new components. Thus returns can be used to absorb demand fluctuations to some extent. Longer remanufacturing and “in-use” lead-times have less impact at reducing inventory variance and bullwhip than shorter lead-times. We find that, within our specified system, that inventory variance and bullwhip is always less in supply chains with returns than supply chains without returns. We conclude by separating out the remanufacturing lead-time from the “in-use” lead-time and investigating its impact on our findings. We find that short remanufacturing lead-times do not qualitatively change our results.     

Impact analysis of customized demand information sharing on supply chain performance

In today's dynamic market environment, rapidly changing customer preferences increase the customization of products and the diversification of demand mix. Companies should understand how the demand mix influences supply chain performance and react properly to fulfil customer satisfaction as to what the customers want. This paper investigated the impact of information sharing of the demand mix on the supply chain performance, under increasing product customization, by changing customer demand pattern and production capacity. The results of simulation analysis demonstrated that a demand mix can be determined that produces the best supply chain performance. A real multi-echelon automotive supply chain was analysed for each of six performance measures and the demand mix information significantly influenced five of them. Demand variation and production capacity also resulted in significant impact on the performance measures.     

Coordination of a supply chain with loss-averse consumers in service quality

We develop a two-period game model to study the coordination mechanism for a supply chain with loss-averse consumers who are assumed to have dwindling sensitivity to service quality gain relative to loss. We find that all-unit quantity discount coupling with service subsidy rate can coordinate the retailer’s price and service quality decisions together in each period. When consumers become more loss-averse in service quality, the coordinated wholesale price in the first period might increase; whereas that in the second period decreases. With Pareto coordination mechanism, larger loss-aversion might weaken the supplier’s bargaining power. We provide managerial insights on how to adjust the coordinated contract when the consumers’ loss-aversion and reference value of service quality level change.     

Structural-aware simulation analysis of supply chain resilience

Supply chain resilience (SCRES) refers to the ability of a supply chain (SC) to both resist disruptions and recover its operational capability after disruptions. This paper presents a simulation model that includes network structural properties in the analysis of SCRES. This simulation model extends an existing graph model to consider operational behaviours in order to capture disruption-recovery dynamics. Through structural analysis of a supply chain network (SCN), mitigation strategies are designed to build redundancy, while contingency strategies are developed to prioritise recovery of the affected SCN. SCRES indexes are proposed by sampling SC performance measures of disruption for each plant and aggregating the measures based on the criticality of the plants in the SCN. The applicability of this simulation model is demonstrated in a real-world case study of different disruption scenarios. The application of mitigation and contingency strategies is shown to both improve recovery and reduce the total costs associated with disruptions. Through such simulation-based analysis, firms can gain insight into the SCRES of their existing SCNs and identify suitable strategies to improve SCRES by considering recovery time and costs.     

Delphi study on supply chain flexibility

The flexibility literature is dominated by research on manufacturing flexibility. More recently, supply chain flexibility has been recognized as an important flexibility construct for meeting customer demand. An Internet-based Delphi study involving a group of expert practitioners is used to enumerate the characteristics, and the importance of those characteristics, in making a supply chain flexible. Expert opinion is one method for gathering information that can be used to develop a model of supply chain flexibility and provide a framework for future research.     

Integrated inventory models with fuzzy annual demand and fuzzy production rate in a supply chain

The successful implementation of Just-in-time (JIT) production in today's supply chain environment requires a new spirit of cooperation between the buyer and the vendor. An integrated inventory model with such a consideration is based on the total cost optimization under a common stock policy and business formula. However, the supposition of known annual demand in most related literature may not be realistic. This paper proposes the inclusion of fuzzy annual demand and/or the production rate, and then employs the signed distance, a ranking method for fuzzy numbers, to find the estimate of the common total cost in the fuzzy sense, and subsequently derives the corresponding optimal buyer's quantity and the integer number of lots in which the items are delivered from the vendor to the purchaser. Numerical examples are provided to illustrate the results of proposed models.     

Managing demand uncertainty through fuzzy inference in supply chain planning

In this paper, we investigate methods for managing the irregular and uncertain demands involved in supply chain planning. We first build a supply chain planning model based on fuzzy linear programming, which defines demand as a fuzzy parameter. Next, we propose a fuzzy inference approach for converting fuzzy demand into crisp demand. In the proposed fuzzy inference-based approach, judgments of upcoming demand from both internal and external experts are used as input variables to reflect the expected demand irregularity. By adopting fuzzy inference, we can compensate for the limitations of the existing demand treatment approaches, which usually demonstrate poor forecasting performance in cases of irregular demand and thus reduce the accuracy of supply chain planning. To verify the feasibility of the proposed approach, we present an illustrative example of a Korean electronics company.     

An application of cost-effective fuzzy inventory controller to counteract demand fluctuation caused by bullwhip effect

This paper develops a fuzzy inventory model to counteract the demand fluctuation in supply demand networks, which combines fuzzy logic controller with (s,?S) policy based on economic order quantity (EOQ) model. Following a literature review and a discussion of counteractions to the bullwhip effect and the obstruction of general counteraction in supply demand networks, a multi-echelon fuzzy inventory model in supply demand networks is proposed. A simulation model with one- and two-echelon supply demand network is built and tested for (s, S) policy based on the classical EOQ model and the proposed fuzzy inventory model. Based on the simulation, results of the relevance performance are presented and discussed, which show that the proposed multi-echelon fuzzy inventory model provides not only a cost-effective management of inventory (e.g. lower inventory levels and cost) in market uncertainty, but also another effective alternative for counteracting demand fluctuation. In particular, the proposed multi-echelon fuzzy inventory model shows benefit in counteracting demand fluctuation in multi-echelon supply demand networks. Finally, some conclusions and suggestions for further research works are presented.     

Applying genetic algorithms to dampen the impact of price fluctuations in a supply chain

Genetic Algorithms (GAs) have been identified as an innovative and useful approach for dampening the Bullwhip Effect along supply chains. This paper extends previous work by developing an improved supply chain model that incorporates additional cost factors such as ordering cost, item cost, distribution cost and production cost. The revised model is then used to examine one element of the Bullwhip Effect, i.e. price fluctuation strategies. A GA is employed to determine the ordering policy for each member in the model that minimises cost. The research illustrates how the GA performs if a sales promotion is introduced. From the experimental results, it is shown that a GA can help determine an improved ordering policy and reduce the total cost across the supply chain.     

Impact of demand price elasticity on advantages of cooperative advertising in a two-tier supply chain

This paper focuses on pricing and vertical cooperative advertising decisions in a two-tier supply chain. Using a Stackelberg game model where the manufacturer acts as the game leader and the retailer acts as the game follower, we obtain closed-form equilibrium solution and explicitly show how pricing and advertising decisions are made. When market demand decreases exponentially with respect to the retail price and increases with respect to national and local advertising expenditures in an additive way, the manufacturer benefits from providing percentage reimbursement for the retailer’s local advertising expenditure when demand price elasticity is large enough. Whether the manufacturer benefits from cooperative advertising is also closely related to supply chain member’s relative advertising efficiency. In the decision for adopting coop advertising strategy, it is critical for the manufacturer to identify how market demand depends on national and local advertisements. The findings from this research can enhance our understanding of cooperative advertising decisions in a two-tier supply chain with price-dependent demand.     

Pricing decisions of complementary products in a two-level fuzzy supply chain

Pricing decisions of two complementary products in a two-level fuzzy supply chain with two manufacturers and one common retailer are studied in this paper. By considering the two manufacturers and one common retailer’s leader–follower relationship, the two manufacturers’ pricing strategy and the fuzzy uncertainties associated with the manufacturing costs and customer demands of the complementary products, seven pricing games are considered. The corresponding closed-form optimal pricing decisions are obtained in the seven pricing games. Through using numerical studies and sensitivity analysis of parameters’ fuzzy degree, we compare the analytical results of different games and investigate the firms’ optimal decisions facing changing pricing environments. At last, we analyse the effect of the fuzzy degree of key parameters on optimal prices, maximal expected demands and maximal expected profits of different games. Some interesting and valuable managerial insights are established.     

Integrating packaging suppliers into the supply/demand chain

This paper presents the results from qualitative studies done on leading‐edge companies in supply/demand chain management in Sweden. The aim of the study was to create a knowledge base, identify the network integrators and, with reference to previous studies conducted in the packaging industry, analyse the development for packaging suppliers. Copyright © 2005 John Wiley & Sons, Ltd.     

Coordination of a dual-channel supply chain after demand or production cost disruptions

Coordinating a dual-channel supply chain could not only achieve the integrated profit of the supply chain but also alleviate the channel conflict. Although some researches addressed this area, there is scant literature to discuss the coordination issue in the situations of disruption. To fill this void, we utilise a contract with a wholesale price, a direct channel’s price and a lump sum fee to coordinate a dual-channel supply chain under the cases of demand disruptions and production cost disruptions. After deriving the optimal contract for each case, we find that the manufacturer can achieve coordination of the disrupted supply chain by adjusting the parameters of the coordination contract used in a normal environment. We also show that after disruptions, there exists a contract adjustment benefit zone, in which both the manufacturer and the retailer can benefit from the adjustment of coordination contract when demand increases or production cost decreases. A further analysis of the production and distribution strategies in the coordinated dual-channel supply chain after disruptions suggests that the adjustment of the total production and sales of each channel depends heavily on the level of disruptions and the degree of consumers’ loyalty to both channels.     

A graph-based model to measure structural redundancy for supply chain resilience

Globalisation and lean initiatives increase the vulnerabilities of the supply chains (SC), where disruptions in any plant in a supply chain network (SCN) can propagate throughout the whole SCN. Redundancy is part of the SC re-engineering to improve supply chain resilience (SCRES). This paper presents a conceptual model of an SCN using graph theory, considering the relationships between plants and materials. Based on the model, the structural redundancy of the SCN is measured, which is used to assess SCRES. This assessment approach focuses on the resilience of the SCN against disruptions. Case studies are discussed to illustrate the applicability of this model and show that increasing structural redundancy of the SCN improves SCRES against disruptions.     

Coordinating a supply chain under demand and cost disruptions

In this paper, we investigate the coordination of a supply chain consisting of one manufacturer and n Bertrand competing retailers under disruptions of market demand and production cost. We present a coordination model of a supply chain under normal scenarios. Our findings demonstrate that the coordination scheme designed for the initial production plan should be revised when disruptions of market demand and production cost occur. To resolve this issue, we consider the possible deviation costs caused by disruptions and propose optimal decision models for different disruptions under centralised decision-making. We present an improved revenue-sharing contract model to coordinate the decentralised supply chain under disruptions. The proposed models are then further analysed through numerical examples.     

Reconfigurable supply chain: the X-network

Research on supply chain (SC) digitalization, resilience, sustainability and leagility has remarkably progressed, most of it focused on the individual contributions of these four major frameworks. However, a lack of integration spanning these individual frameworks can be observed. In this conceptual paper, we hypothesize that reconfigurability can be considered such an integral perspective that consolidates the research in SC adaptation to ever changing environments. We theorize a new notion – a Reconfigurable SC or the X-network – that exhibits some crucial design and control characteristics for complex value-adding systems in highly vulnerable environments. We support our argumentation and conceptual viewpoints by a literature analysis along with tertiary studies to review and structure contextual factors of designing the X-networks. We propose respective frameworks and discuss the implementation principles and technologies at the macro and micro levels. Two novel concepts – dynamic SC meta-structures and dynamic autonomous services – are introduced. Distinctively, we go beyond the existing knowledge to predict proactively the future directions in the reconfigurable SCs. Our results can be of value for decision-makers to decipher chances and barriers in contemporary SC transformations.     

Information management strategies and supply chain performance under demand disruptions

The operations management literature presents inadequate comprehensive understanding on information management strategies of mitigating supply chain disruption risks. By using control theory modelling and simulation, this study compares the disruption mitigation effects of three information management strategies. From the aspect of stability, the existing stability boundaries are revised by a new method in a two-echelon case. It shows that supply chains (SC) with popular information management strategies are not evidently more stable than traditional ones. From the aspect of disruption recovery time, an innovative two-echelon swiftest response problem under these information management strategies is formulated and solved. Results show that a collaborative planning, forecasting and replenishment (CPFR) SC with complete SC information performs the best. However, in a later operational risk mitigation test, an information sharing (IS) SC with partial information has the smallest bullwhip effect. From the aspect of demand amplification and frequency response, an innovative frequency–response plot of order amplification is proposed in a time-continuous SC with moving average forecasts. It implies the best frequency response for concurrently mitigating both operational and disruption risks coming from a CPFR SC. But for a certain SC structure there is still a balance between mitigating bullwhip effect and quick response. Moreover, it also implies that anti-bullwhip should exist in a certain condition, as realised in our numerical experiments.