The news-vendor problem with drop-shipping and resalable returns

As e-commerce expands, more and more products are offered online to attract internet consumers’ interest. These products are then shipped to consumers’ home by a drop-shipper. Drop-shipping seems to be a good option to sell products in addition to physical stores. Furthermore, both types of products, either sold in store or on Internet can be returned by consumers, with often a higher return ratio for those purchased on Internet. To model these two sales channel and the interactions between them, we consider a News-Vendor (NV) managing both a physical store and an online sale channel that can be fulfilled by a drop-shipping option. We also consider the possibility of reselling products that are returned by consumers during the selling season. The concavity of the expected profit is proven and the optimality condition is obtained. Promising results are obtained from a numerical analysis. In particular, we show that the expected profit can be 14.4% less than the optimal expected profit if the return effect is ignored. Using drop-shipping option can reduce the optimal store inventory by 31.2% and if the NV has no drop-shipping option, the expected profit can be 9% less.     

Optimal manufacturing policy in a reverse logistic system with dependent stochastic returns and limited capacities

The stochastic models of systems with reverse logistics usually assume that the quantity of products returned is independent of sales. This hypothesis is obviously not true and can lead to suboptimal production policies. In this paper a new sales-dependent returns model is described. In this model, the returns depend on the useful life of the products sold and on the probability of an end-of-life product being returned. A Markov decision problem is formulated in order to obtain the optimal manufacturing policy. A numerical example is provided to illustrate the use of the defined model. An approximated Markov decision model is defined where the optimal policy is easily obtained. The optimal policies of the original and the approximated models are compared.     

The use of time series forecasting in zone order picking systems to predict order pickers’ workload

In order to differentiate from competitors in terms of customer service, warehouses accept late orders while providing delivery in a quick and timely way. This trend leads to a reduced time to pick an order. This paper introduces workload forecasting in a warehouse context, in particular a zone picking warehouse. Improved workforce planning can contribute to an effective and efficient order picking process. Most order picking publications treat demand as known in advance. As warehouses accept late orders, the assumption of a constant given demand is questioned in this paper. The objective of this study is to present time series forecasting models that perform well in a zone picking warehouse. A real-life case study demonstrates the value of applying time series forecasting models to forecast the daily number of order lines. The forecast of order lines, along with order pickers’ productivity, can be used by warehouse supervisors to determine the daily required number of order pickers, as well as the allocation of order pickers across warehouse zones. Time series are applied on an aggregated level, as well as on a disaggregated zone level. Both bottom-up and top-down approaches are evaluated in order to find the best-performing forecasting method.     

Pricing decisions for a supply chain with refurbished products

This paper considers a supply chain consisting of a supplier and a retailer where a fixed portion of new products sold will be returned to the retailer and then be repaired and resold as refurbished products at a lower price. Using the utility model, we formulate how consumers will make their choices when facing both new and refurbished products. Then, using the divide-and-conquer method, we derive the supplier and retailer's equilibrium decisions, including the supplier's wholesale price and the retailer's prices for both the new and refurbished products. The main findings include the following. First, refurbished products will be sold in the market only when the refurbishing cost is small. In this situation, as the refurbishing cost increases, most of the negative impact on the retailer will be transferred to the supplier. Second, in the same condition, as the refurbishing cost increases, the wholesale price and retail price of the new product will change in opposite directions. This result contrasts with the traditional pass-through effect. Third, when the repair cost is moderate, the retailer will eventually not sell refurbished products, but its profit can be significantly improved and the double marginalisation effect can be mitigated.     

Chinese and US online consumers’ preferences for content of e-commerce websites: a survey

Content usability of websites is central to the success of e-commerce. In the context of international e-commerce, to serve online consumers from different nations better requires taking into account cultural differences in content preferences. The present study explored how online consumers’ content preferences vary between China and the US with regard to economic standing, cognitive style, cultural dimensions, communication context and infrastructure of e-commerce. This exploration was accomplished by conducting a web-based survey of 68 Chinese and 75 US college students, which examined their preferences for 25 information items when purchasing portable electronic products online. Significant differences in preferences between China and the US were found on 13 of these information items. Implications of these differences in content preferences for e-commerce website design in China and the US are discussed.     

Hybrid Clustering Algorithms with GRASP to Construct an Initial Solution for the MVPPDP

Mobile commerce (m-commerce) contributes to increasing the popularity of electronic commerce (e-commerce), allowing anybody to sell or buy goods using a mobile device or tablet anywhere and at any time. As demand for e-commerce increases tremendously, the pressure on delivery companies increases to organise their transportation plans to achieve profits and customer satisfaction. One important planning problem in this domain is the multi-vehicle profitable pickup and delivery problem (MVPPDP), where a selected set of pickup and delivery customers need to be served within certain allowed trip time. In this paper, we proposed hybrid clustering algorithms with the greedy randomised adaptive search procedure (GRASP) to construct an initial solution for the MVPPDP. Our approaches first cluster the search space in order to reduce its dimensionality, then use GRASP to build routes for each cluster. We compared our results with state-of-the-art construction heuristics that have been used to construct initial solutions to this problem. Experimental results show that our proposed algorithms contribute to achieving excellent performance in terms of both quality of solutions and processing time.     

A model for warehouse layout

This paper describes an approach to determine a layout for the order picking area in warehouses, so that the average travel distance for the order pickers is minimized. We give analytical formulas that can be used to calculate the average length of an order picking route under two different routing policies. The optimal layout can be determined by using these formulas as the objective function in a nonlinear programming model. The optimal number of aisles in an order picking area appears to depend strongly on the required storage space and the pick list size.     

A B2B flexible pricing decision support system for managing the request for quotation process under e-commerce business environment

In the era of digitalisation, e-commerce retail sites have become decisive channels for reaching millions of potential customers worldwide. Digital marketing strategies are formulated by the marketing teams in order to increase the traffic on their e-commerce sites, thereby boosting the sales of the products. With the massive amount of data available from the cloud, which were conventionally made with a high degree of intuition based on decision makers’ knowledge and experience, can now be supported with the application of artificial intelligence techniques. This paper introduces a novel approach in applying the fuzzy association rule mining approach and the fuzzy logic technique, for discovering the factors influencing the pricing decision of products launched in e-commerce retail site, and in formulating flexible, dynamic pricing strategies for each product launched in an e-commerce site. A pricing decision support system for B2B e-commerce retail businesses, namely Smart-Quo, is developed and implemented in a Hong Kong-based B2B e-commerce retail company. A six-month pilot run reveals a significant improvement in terms of the efficiency and effectiveness in making pricing decisions on each product. The case study demonstrates the feasibility and potential benefits of applying artificial intelligence techniques in marketing management in today’s digital age.     

Routing methods for warehouses with multiple cross aisles

This paper considers routing and layout issues for parallel aisle warehouses. In such warehouses order pickers walk or drive along the aisles to pick products from storage. They can change aisles at a number of cross aisles. These cross aisles are usually located at the front and the back of the warehouse, but there can also be one or more cross aisles at positions in between. We describe a number of heuristics to determine order picking routes in a warehouse with two or more cross aisles. To analyse the performance of the heuristics, a branch-and-bound algorithm that generates shortest order picking routes is used. Performance comparisons between heuristics and the branch-and-bound algorithm are given for various warehouse layouts and order sizes. For the majority of the instances with more than two cross aisles, a newly developed heuristic appears to perform better than the existing heuristics. Furthermore, some consequences for layout are discussed. From the results it appears that the addition of cross aisles to the warehouse layout can decrease the handling time of the orders by lowering average travel times. However, adding a large number of cross aisles may increase average travel times because the space occupied by the cross aisles has to be traversed as well.     

The effect of warehouse cross aisles on order picking efficiency

This paper investigates the effects of adding cross aisles to the layout of an order consolidation warehouse, with respect to order picking efficiency. Intuitively, cross aisles provide greater flexibility in the routing of order pickers, thus providing shorter order picking travel distances. However, this effect may be negated when the number of cross aisles becomes excessive, as the cross aisles themselves must be traversed in order to reach the required items. A shortest path pick sequencing model is developed which allows for any number of cross aisles in the warehouse. The optimal routing is computed for a large number of randomly generated picking requests, over a variety of warehouse layout and order picking parameters. The results are used to characterize the optimal number of warehouse cross aisles, as well as the conditions under which cross aisles generate the greatest benefit.     

考虑臂架弹性的动臂起重机动力学建模及振动分析

动臂起重机负载的振荡会大大降低起重机工作时的防倾翻能力。首先建立动臂起重机的静态模型以便全面了解动臂起重机的系统结构。然后运用AUTOLEV建立了考虑臂架弹性的动臂起重机的一个简单模型及完全多体动力学模型,仿真出动臂起重机各机构运行时弹性臂架输出角度及臂架顶部负载对阶跃输入的响应曲线。从仿真结果可以看出,动臂起重机中车体的运行及臂架的回转和起升都会导致负载的剧烈振荡从而影响整机工作的安全性。详细而全面的负载振动分析为系统的振动控制提供了有力的依据。     

Evaluating order throughput time with variable time window batching

Given increased pressure to provide short delivery times, minimising customer order throughput time is a very important objective in warehousing operations. There are many factors that may affect the performance of an order picking system, such as layout of the warehouse, the storage strategy, the routing policy, the zoning method and the batching policy. In this study, we propose a simple travel time model and analyse the effect of order batching on the expected customer order throughput time with variable time window batching. In addition, we discussed the impact of some parameters on the batch size and the expected customer order throughput time. In the practice of Wuhan Dong Hon Logistics co. Ltd, the storage rack in the warehouse has two levels: the low storage level and the high storage level. These two levels are visited by pickers and forklifts, respectively. The classification improves the performance of order picking. In this study, we build the model based on this practice.     

Enhancing performance in order picking processes by dynamic storage systems

Increasing productivity and reducing labour cost in order picking processes are two major concerns for most warehouse managers. Particularly picker-to-parts order picking methods lead to low productivity as order pickers spend much of their time travelling along the aisles. To enhance order picking process performance, an increasing number of warehouses adopt the concept of dynamic storage where only those products needed for the current order batch are dynamically stored in the pick area, thereby reducing travel time. Other products are stored in a reserve area. We analyse the stability condition for a dynamic storage system with online order arrivals and develop a mathematical model to derive the maximum throughput a DSS can achieve and the minimum number of worker hours needed to obtain this throughput, for order picking systems with a single pick station. We discuss two applications of dynamic storage in order picking systems with multiple pick stations in series. In combination with simulation modelling, we are able to demonstrate that dynamic storage can increase throughput and reduce labour cost significantly.     

Dynamic disassembly planning for remanufacturing of multiple types of products

With the increased need for remanufacturing of end-of-life products, achieving economic efficiency in remanufacturing is urgently needed. The purpose of this study was to devise a cost-minimisation plan for disassembly and remanufacturing of end-of-life products returned by consumers. A returned end-of-life product is disassembled into remanufacturable parts, which are supposed to be used for new products after being remanufactured. Each end-of-life product is disassembled into parts at variable levels and through variable sequences as needed, taking into account not only disassembly but also manufacturing, remanufacturing, and holding inventory of remanufacturable parts. This study proposes a mixed integer linear programming (MILP) model for derivation of the optimal disassembly plan for each returned product, under deterministically known demand and return flows. For the purposes of an illustrative example, the proposed model was applied to the formulation of an optimal disassembly and remanufacturing plan of ‘fuser assembly’ of laser printers. The solution reveals that variable-level disassembly of products saves a significant remanufacturing cost compared with full disassembly.     

Investigating online social media users’ behaviors for social commerce recommendations

Online social media create virtual communities and network platforms that people use to create, share, and exchange opinions, views and experiences. With social networks, social commerce not only relies on commerce, but online social media can also promote the sale of goods or services online. Many online operators have begun to use recommendation systems to analyze customer purchase history and identify individual products that customers may purchase. This enables the company to send product information to consumers to attract their attention. In addition, consumers have a higher purchase rate for recommended products based on consumer data. Based on a survey in Taiwan society, this study uses the questionnaire survey method to collect data on a relational database. This study investigates Taiwan online social media users’ behaviors using data mining methods, including clustering analysis and association rules. Clustering analysis is to investigate possible profiles of users and association rules are to find knowledge patterns and rules of user profiles, online social media usage motivation/preferences and social commerce behavior in order to generate social commerce recommendations in terms of social technology development in the modern society.     

Interestingness of association rules in data mining: Issues relevant to e-commerce

The ubiquitous low-cost connectivity synonymous with the internet has changed the competitive business environment by dissolving traditional sources of competitive advantage based on size, location and the like. In this level playing field, firms are forced to compete on the basis of knowledge. Data mining tools and techniques provide e-commerce applications with novel and significant knowledge. This knowledge can be leveraged to gain competitive advantage. However, the automated nature of data mining algorithms may result in a glut of patterns — the sheer numbers of which contribute to incomprehensibility. Importance of automated methods that address this immensity problem, particularly with respect to practical application of data mining results, cannot be overstated. We first examine different approaches to address this problem citing their applicability to e-commerce whenever appropriate. We then provide a detailed survey of one important approach, namely interestingness measure, and discuss its relevance in e-commerce applications such as personalization in recommender systems. Study of current literature brings out important issues that reveal many promising avenues for future research. We conclude by reiterating the importance of post-processing methods in data mining for effective and efficient deployment of e-commerce solutions.     

新产品分销下再制造产品直销与分销渠道研究

基于消费者对再制造产品和新产品具有不同接受度,首次研究了制造商通过电子直销渠道销售再制造产品,通过零售商分销渠道销售新产品的渠道模式,构建了再制造产品直销与分销渠道模型,分别求得了两种渠道下制造商与零售商的最优定价策略,并对两种定价策略进行了比较分析.通过数值仿真,分析了消费者对再制造产品接受度对两种销售渠道下的销售价...     

Optimal control of production and remanufacturing in a simple recovery model with linear cost functions

One aspect in reverse logistics concerns returns of used products and recovery for another life cycle. Remanufactured parts can be used for assembly of new products or the entire (upgraded) product can be sold again. Limitations and enormous waste disposal cost, the duty for manufacturers to take back used products from customers, and the fact that returned products can be regarded as a resource for material requirements are reasons for a consideration of product recovery. In this paper, we present an optimal control approach to optimize the production, remanufacturing, and disposal strategy with respect to dynamic demand and returns.     

The value of integrating order picking and vehicle routing decisions in a B2C e-commerce environment

In B2C e-commerce sales, customers expect a fast and low-cost delivery. To be able to fulfil these customer expectations, both warehouse and distribution operations have to be performed in an efficient and effective way. Ideally, these two supply chain functions should be considered simultaneously in an integrated problem since they are interrelated. In this paper, a record-to-record travel algorithm is proposed to solve the integrated order picking-vehicle routing problem (I-OP-VRP). Experiments with both small-size and large-size instances are conducted. Furthermore, the integrated approach is compared with an approach in which both problems are solved sequentially. Results show that integration leads to increased service levels, i.e. it allows to shorten the time between placing an order and receiving the goods. On top, the integrated approach leads to costs savings of on average 1.8%. Thus, integration is indispensable for a fast and cost-efficient delivery of goods.     

A bi-directional path layout for conflict-free routing of AGVs

Automated Guided Vehicles (or AGVs for short) are now widely used in automated material handling systems. Much research has been done on developing path layout and algorithms for the optimal routing and scheduling of AGVs. However, with the drastically increased number of AGVs in some recent applications (e.g. in the order of a hundred in container terminals), algorithms that can achieve a high degree of concurrency of AGV moves are urgently needed. This paper presents a bi-directional path layout and an algorithm for routing AGVs. To route the vehicles without conflicts and to minimize the space requirement of the layout, critical conditions for certain key parameters of the path and vehicle are derived. We further show theoretically that a high degree of concurrency of AGV moves can be achieved, although the routing decision takes only a constant amount of time for each vehicle. The routing efficiency is analysed in terms of the distance traversed and the time requirement for AGVs to complete all pickup and drop-off (or P/D for short) jobs. Results of this study could form a basis for more complicated path layouts and routing algorithms.