Many production processes not only produce desired quality products (high-end products), but also generate yield loss or Not-Quite-Perfect Products (NQPPs) that do not fully meet the quality standards. In practice, a manufacturer may choose to (1) scrap all NQPPs at a cost and carry the high-end products only, or (2) sell some or all NQPPs to a value-conscious low-end market and carry both high-end products and low-end products (NQPPs). This research studies the optimal decision on production yield loss (scrap or sell) and the corresponding pricing and operational strategies under different practical situations. Building upon a standard marketing model for two separated markets, that is, the high-end and the low-end markets, we model the manufacturer's profit maximization problem as a nonlinear programming problem. We characterize the optimal yield-loss decision and the corresponding optimal pricing for each market and production quantity. We also consider the situation that the NQPPs may face competition in the low-end market with products designed and produced specifically for that market. In contrast to the common belief that selling NQPPs to a low-end market can recover some of the cost and hence lead to a higher profit, we show that when the yield rate is small or large enough, selling NQPPs may hurt the manufacturer due to the loss of full control over both markets. This is especially true when competition exists in the low-end market. This research provides practitioners with detailed guidelines on when and how a specific yield loss (product line or marketing) strategy should be adopted. Managerial insights are generated for the optimal yield loss strategies; numerical tests further demonstrate our results.

This paper presents a model for designing a trade credit contract between a supplier and a retailer that would coordinate a supply chain in the presence of investment opportunity for the retailer. Specifically, we study a newsvendor model where the supplier offers a trade credit contract to the retailer who, by delaying the payment, can invest the accounts payable amount and earn returns. We find that when the channel partners have symmetric information about the retailer's investment return, a conditionally concessional trade credit (CTC) contract, which includes a wholesale price, an interest-free period, and a minimum order requirement, can achieve channel coordination. We then extend the model to the information asymmetry setting in which the retailer's investment return is unobservable by the supplier. We show that, although the CTC contract cannot achieve the coordination in this setting, it can effectively improve channel efficiency as well as profitability for individual partners.

The benefits of a consumer return policy have been extensively studied in extent literature. This paper explores the potentially damaging impact of a return policy on the retailer. We develop an analytical framework and examine the economic impact of consumer return among consumers, retailer and supply chain. We distinguish three network-externality (NE) cases: no network externality, fixed network-externality and variable network-externality contingent on return amount to discuss the retailer's selling price, refund and inventory policies. Our analysis derives the optimal policies and shows that they take the form of contingence model in which the policies depend on consumer initial return and NE return. We also examine the influence of the consumer return NE effect on buy-back contracts of the supply chain and show that while the traditional buy-back contract fails to coordinate the supply chain, the NE effect does not render the differentiated buy-back contract less effective. Finally, we extend our study to a heterogeneous consumer case.

This paper studies information sharing in a supply chain where a contract manufacturer (CM) acts as both an upstream partner and a downstream competitor to an original equipment manufacturer (OEM). To better explore the effect of information sharing on a coopetitive supply chain, we consider a sequential game with the OEM as the Stackelberg leader under two different wholesale pricing methods, which is close to the practical situation. Our analysis shows that when the wholesale price is exogenously given, information sharing is beneficial for the OEM but hurts the CM, and a side-payment contract is designed to induce Pareto-optimal information sharing. When the wholesale price is a decision variable, the CM benefits from information sharing while the OEM does not and a discount-based wholesale price contract is designed to induce truthful information sharing. The numerical examples analysis further finds that the OEM benefits from the exogenous wholesale price scenario while the CM benefits from the endogenous wholesale price scenario. The study sheds lights on the decision-making processes for operating and managing the coopetitive supply chain and extends the research scope of information sharing. Our findings also provide some scientific references about information sharing in daily production.

Motivated by Google's technology specifications on Android devices, we consider firms' decisions on production timing in a co-opetitive supply chain comprising a manufacturer and an original equipment manufacturer (OEM), where the manufacturer acts as the OEM's upstream contract manufacturer and downstream competitor. We consider the market acceptance uncertainty of key product designs. If a firm decides to implement ex post production strategy (PS), it can delay the production until the market acceptance uncertainty of its product is resolved. Otherwise, ex-ante production strategy (AS) is implemented. We find that, due to the co-opetition, PS does not always benefit either the manufacturer or the OEM, because the value of delayed production is diminished as the competitor may commit a production quantity earlier under AS. Further, firms' decisions on production timing are dependent on the degree of market acceptance uncertainty of their products and competition intensity. We find that both firms choose PS when uncertainty is high, while only one of them chooses PS when uncertainty is moderate or low. Interestingly, when the competition is intense, the manufacturer tends to choose PS, which can benefit from both the resolved market acceptance uncertainty and OEM's early commitment of production quantity.

Purpose - As traditional supply chains are increasingly becoming intelligent with more objects embedded with sensors and better communication, intelligent decision making and automation capabilities, the new smart supply chain presents unprecedented opportunities for achieving cost reduction and enhancing efficiency improvement. The purpose of this paper is to study and explore the currents status and remaining issues of smart supply chain management. Design/methodology/approach - A literature review is conducted to synthesize the earlier work in this area, and to conceptualize and discuss the smart supply chain characteristics. Further, the authors formulate and investigate five key research topics including information management, IT infrastructure, process automation, advanced analytics, and supply chain integration. Findings - Studies in those aforementioned subject fields are reviewed, categorized, and analyzed based on the review questions defined in the study. It is notable that while the topics of converging atoms with digits are increasingly attracting attention from researchers and practitioners alike, there are many more interesting research questions needing to be addressed. Originality/value - The paper provides original and relevant guidance for supply chain management researchers and practitioners on developing smart supply chains.

This article studies operations sequencing for a multi-stage production inventory system with lead times under predictable (deterministic) yield losses and random demand. We consider various cases with either full or partial release of work-in-process inventories, for either pre-operation or post-operation cost structures, and under either the total discounted or average cost criteria. We derive necessary and sufficient criteria for the optimal sequence of operations in all cases. While the criteria differ in their specific forms, they all lead to the same principal: those operations with (1) lower yields, (2) lower processing costs, (3) longer lead times, and (4) lower inventory holding costs should be placed higher upstream in the system.Copyright (c) 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 144-154, 2014

Cooperative advertising programs are usually provided by manufacturers to stimulate retailers investing more in local advertising to increase the sales of their products or services. While previous literature on cooperative advertising mainly focuses on a "single-manufacturer single-retailer" framework, the decision-making framework with "multiple-manufacturer single-retailer" becomes more realistic because of the increasing power of retailers as well as the increased competition among the manufacturers. In view of this, in this paper we investigate the cooperative advertising program in a "two-manufacturer single-retailer" supply chain in three different scenarios; that is, (i) each channel member makes decisions independently; (ii) the retailer is vertically integrated with one manufacturer; (iii) two manufacturers are horizontally integrated. Utilizing differential game theory, the open-loop equilibrium advertising strategies of each channel member are obtained and compared. Also, we investigate the effects of competitive intensity on the firm's profit in three different scenarios by using the numerical analysis.

"Big data" is an emerging topic and has attracted the attention of many researchers and practitioners in industrial systems engineering and cybernetics. Big data analytics would definitely lead to valuable knowledge for many organizations. Business operations and risk management can be a beneficiary as there are many data collection channels in the related industrial systems (e.g., wireless sensor networks, Internet-based systems, etc.). Big data research, however, is still in its infancy. Its focus is rather unclear and related studies are not well amalgamated. This paper aims to present the challenges and opportunities of big data analytics in this unique application domain. Technological development and advances for industrial-based business systems, reliability and security of industrial systems, and their operational risk management are examined. Important areas for future research are also discussed and revealed.

Multi echelon distribution systems have become more common in recent years. This paper addresses the two echelon open location routing problem (2E-OLRP) which is a variant of the two echelon location routing problem (2E-LRP). This problem seeks to find a minimum-cost set of vehicle routes that do not return to the depot in the first echelon and do not return to satellites in the second echelon due to the presence of individual contractors and third party logistics (3PL) providers. In spite of the large amount of research on LRPs, the 2E-OLRP has received very little attention. Three flow-based mixed-integer linear programs and a hybrid heuristic algorithm are proposed to deal with this problem. Extensive experiments evaluate the effectiveness of these methods.

Owing to the changing fashion trends and a volatile market situation, demand in fashion and textile (FT) industry is unpredictable and could vary and change completely in a short time, which makes it more difficult to coordinate a FT supply chain. A change in product preference due to fashion trends is the main reason why the demand of FT industry shows more variations than other industries. In this paper, we use a well known contract, the all-unit quantity discount policy (AQDP), to coordinate a FT supply chain with certain demand, and we further consider it under the demand variations scenario to investigate whether it can still coordinate the supply chain. In detail, before the selling season, an AQDP is provided by the manufacturer to the retailer, and under which the FT supply chain coordination achieved with a certain demand. During the selling season, demand variation is realized after an abrupt changing of fashion trends, therefore, the manufacturer may need to revise the original AQDP to insure the supply chain is still coordinated. Utilizing the mechanism design theory, we prove that: (i) while the traditional AQDP can coordinate the supply chain when no demand variations, it cannot always coordinate the supply chain after the demand variations; (ii) when the AQDP fails, we can use the proposed capacitated linear pricing policy (CLPP) to achieve a new coordination; (iii) a more dominant decision maker, who can set a higher profit goal, is favorable to stabilization of the supply chain system under demand variations. Numerical examples are proposed also to show our results.