Sustainable integrated inventory management policy focuses on reducing the environmental impact of the manufacturing and transport sector. This study develops an integrated single-manufacturer single-buyer inventory model for substitutable deteriorating items considering transport and industry carbon emissions. This article categorizes carbon emissions into two parts: direct and indirect emissions. We also assume two mutually substitutable items, and substitution is considered on the buyer’s side. If one of the items is out of stock, the demand for that item can be partially satisfied by the stock of the other item; else, demand will be lost. The purpose of this study is to minimize the integrated cost of the supply chain with total carbon emissions produced by industry and transport sectors and to determine the optimal number of deliveries, order level and carbon emission quantity. A solution procedure is developed to find the optimal values of the policy. Numerical experiments and sensitivity analyses are presented to demonstrate the proposed model.

This study investigates trade credit and early payment financing in a three-party supply chain consisting of a manufacturer, a capital-constrained distributor, and a retail platform. The manufacturer or the platform provides the financing service to the distributor. Two different leadership structures are investigated, namely, platform and manufacturer leadership Stackelberg game, where the platform or manufacturer first makes the decision, respectively. Under trade credit financing, the manufacturer and the whole supply chain face loss when the commission rate increases. However, under buyer financing, they benefit from the high commission rate. Under platform leadership, the distributor, the manufacturer, and the supply chain perform better with trade credit if and only if the commission rate is small or the production cost is high, while the platform always prefers buyer financing. Under manufacturer leadership, the distributor, manufacturer, and supply chain perform better with trade credit under low production cost and commission rate. The platform prefers trade credit when production cost is in the intermediate range. By further analyzing the case that both financing channels are available and the distributor decides which one to choose, we find that the financing services competition hurts only the platform’s profits. And under certain conditions, trade credit and early payment can achieve the same performance for every supply chain member. These findings enhance our understanding of the supply chain risk allocation efficiency of trade credit and early payment financing under different leadership structures. Neither risk allocation form outperforms the other, and the relative efficiency depends on supply chain characteristics.

In several industrial fields like air transport, energy industry and military domain, maintenance actions are carried out during downtimes in order to maintain the reliability and availability of production system. In such a circumstance, selective maintenance strategy is considered the reliable solution for selecting the faulty components to achieve the next mission without stopping. In this paper, a novel multi-level decision making approach based on data mining techniques is investigated to determine an optimal selective maintenance scheduling. At the first-level, the age acceleration factor and its impact on the component nominal age are used to establish the local failures. This first decision making employed K-means clustering algorithm that exploited the historical maintenance actions. Based on the first-level intervention plan, the remaining-levels identify the stochastic dependence among components by relying upon Apriori association rules algorithm, which allows to discover of the failure occurrence order. In addition, at each decision making level, an optimization model combined to a set of exclusion rules are called to supply the optimal selective maintenance plan within a reasonable time, minimizing the total maintenance cost under a required reliability threshold. To illustrate the robustness of the proposed strategy, numerical examples and a FMS real study case have been solved.

This paper considers a dual channel supply chain, where a manufacturer sells a single product through his/her online channel and a traditional retailer, who provides consumers with pre-sale services. The manufacturer’s online channel may free-ride the retailer’s pre-sale service, which reduces the retailer’s desired effort level, and hence may hurt the manufacturer’s and the overall supply chain performance. Under both Manufacturer- and Retailer-Stackelberg settings, we study how the manufacturer designs a service-cost-sharing (SCS for brevity) contract to enhance the retailer’s service effort level, and how free riding influences two members’ optimal decisions. We design an algorithm for determining the two members’ optimal decisions under each setting. The three main findings are found: (i) In the Manufacturer-Stackelberg setting, the SCS contract can enhance the retailer’s service effort level and eliminate the negative impact incurred by free riding, but can’t in the Retailer-Stackelberg setting. (ii) Under the SCS contract, the smaller the fraction of service cost the retailer is requested to share, the more detrimental to the retailer it will be under certain conditions. That is, the phenomenon called “counter-profit cost-sharing” appears. (iii) Both players like to act as a leader if the price competition between the two channels is not relatively very fierce, otherwise they both like to act as a follower.

Configuration management (CM) is an effective method for data modeling and change management in product development, but the study of how it can be adapted for complex product maintenance, repair and overhaul (MRO) has thus far been superficial. Research propositions are put forward on the basis of a literature review and verified by a case of a high-speed train MRO company. The findings show that CM can be used in MRO data management with adjustments in its functions. First, MRO-CM planning considers both multistage service and single-stage service to keep data consistent and continuous. Second, MRO data integration with the design/production phase should be considered during configuration identification. Third, baselines and change rules are developed for change control. Finally, status accounting and auditing can be repeatedly used in MRO data management. A systematic MRO-CM framework is generated to assist MRO practitioners in understanding the relationships among different MRO-CM functions. This paper contributes to expanding the theory of CM in MRO for complex products and provides an effective method for managing MRO data from systematic engineering insights.

As an important element of the airport ecosystem, airport billboards are playing a crucial role in publicizing the city image and facilitating humanistic airport construction. At the same time, airport billboards have great commercial value and is a popular channel for enterprises to prompt their products and to build their brand image. Currently, most airports in China adopt a simple fixed pricing mechanism for airport billboards. Specifically, for any type of billboard, the advertising price is mainly determined by considering historical prices and the total passenger flow of the entire airport during a whole year. However, this seemingly crude pricing mechanism only considers macro-level data of passenger flow and fails in reflecting the real value of billboards in different locations effectively, since the value of a particular billboard depends not only on its media form, but also on the number of passengers flowing through and whether these passengers are the target customers of the advertising content. Based on big data on airport layout, flight information, and passenger attributes, this paper proposes a time- and location-based value assessment model for airport billboards. Using sample data collected from the Beijing Capital International Airport, the assessment model is adopted to evaluate the value of two real billboards in Terminal T3. Application of this model can reflect the difference in the value of airport billboards located in different spots during various periods. Furthermore, this model provides a solid foundation for airport executives to develop differentiated/dynamic pricing and flexible advertisement scheduling strategies, thereby improving the overall efficiency.