Order Fulfillment Strategies Research Articles

A Study on E-Commerce Warehousing Dynamics Navigating Order Fulfilment and Returns

The e-commerce over the past decade has experienced remarkable growth, reshaping shopping habits and challenging traditional supply chain methods. This surge in online shopping has compelled e-commerce firms to enhance their warehousing and order fulfilment strategies to meet rising consumer expectations for swift deliveries and hassle-free returns. Effective management of order fulfilment and reverse logistics has become essential for competitiveness in this industry. This study investigates e-commerce warehousing dynamics, emphasizing the optimization of order speed, delivery times, operational costs, and return management. Through industry reports, academic literature, and case studies, we identify best practices in five key areas: warehouse design and automation, demand forecasting, inventory control, order picking and packing processes, transportation strategies, last-mile delivery models, and reverse logistics for returns. Our research underscores the significance of highly automated warehouses equipped with advanced technologies such as robotics, automated storage and retrieval systems (ASRS), automated guided vehicles (AGVs), and intelligent software for material flow management. These innovations empower e-commerce firms to boost throughput, enhance operational flexibility, and adapt to changing demands effectively.

Service Time and Pricing Decisions in Online Retailing with Drop-Shipping and Guaranteed Service Framework

Many online retailers have adopted drop-shipping as their main order fulfillment strategy. Against this backdrop, this paper studies the service time and pricing decisions in an online retailing system in which the single retailer is served by either monopolistic or duopolistic suppliers. The suppliers are dominant in the Stackelberg game. We employ the guaranteed service framework to model the intricate relationship between service time and inventory. The model stipulates that the delivery of online orders must be completed within guaranteed service time. The equilibrium service times and prices are derived for both cases of monopolistic and duopolistic suppliers. In addition, we systematically analyze the impact of operational and market factors on service time, respectively, and rich insights have been obtained. Interestingly, we find that the presence of competition does not necessarily lead to more rapid delivery service. Suppliers in the duopoly market tend to adopt a price-based competitive strategy, i.e., they are better off by lowering price at the expense of longer service time, especially for the new entrant. However, as competition intensifies to some extent, suppliers are recommended to leverage on more responsive service to maintain or expand the customer base.

A prediction-based supply chain recovery strategy under disruption risks

ABSTRACT This paper proposes a prediction-based product change recovery strategy for the SC (supply chain) under long-term disruptions. A real-world case composed of multi-period planning and dynamic customer demand is considered. First, to forecast dynamic customer demand, a data-based demand predictive method with feedback errors is designed. Second, to schedule procurement and production in advance, based on the predicted demand, the selection of the supply portfolio is transformed into a bi-objective mixed integer programming problem incorporating product change. Furthermore, goods allocation and customer order fulfillment strategy is also designed to finish the transportation of goods and delivery of customer orders. To systematically synthesise and address the problems aforementioned, a three-stage heuristic method is further developed. Finally, a case study is presented to substantiate the reliability of the proposed strategy via an actual SC model of Dongsheng Electronics Co., Ltd. Based on the results obtained after one month, the proposed disruption recovery strategy can reduce the unit product cost and improve the service level, which outperforms the original method adopted by Dongsheng. Additionally, sensitivity analysis of unit product change cost is conducted to reveal the effect of different unit product change costs on SC performance.

ANALYSIS INVENTORY FOR SUPPORTING MATERIALS IN NICKEL INDUSTRY USING MATERIAL REQUIREMENT PLANNING METHOD

Alimuddin Tola dan Iwan Vanany
 Email: alimuddintola@gmail.com; vanany@ie.its.ac.id (corresponding author)
 Departement of Industrial and Systems Engineering
 Institut Teknologi Sepuluh Nopember
 Abstract:
 Nickel is one of the resources that is often used by humans with its use increasing from each year. In order to increase nickel production, an integrated and optimum system is needed with carrying out the production and business processes in the one of Indonessian nickel company. To achieve the objectives, system integration between the demand for nickel products and the process of supplying raw materials urgently needed to support nickel processing. Therefore, this study aims to estimate the amount of raw materials and scheduling the availability of raw materials with applying the Material Requirement Planning. Furthermore, to find out the differences in the strategy of ordering raw materials in the system. Order fulfillment strategies (lot sizing) used are level, modified level, and dynamic lot sizing. The level strategy, as the initial strategy of the company, is a strategy that uses inventory as a support with labor made steady and demand is met from inventory. Modified level strategy are formulated to adjust level ordering in dynamic time. The dynamic lot sizing is a strategy of dynamic order quantity and dynamic time order. As for the analysis. The initial level strategy ,that simulate with several equations, shows some overstock and understock condition in the nickel production and material inventory. Its resulted in higher total cost and unfulfill nickel production. The formulation of modified level strategy and dynamic lot sizing can fulfill the material demand with lower total cost.
 
 Keyword: Material Requirement Planning, Inventory, Lot sizing, Nickel Industry

Order Fulfillment Decision under Multiwarehouse Collaborative Delivery

Aiming at the high cost of multicategory orders fulfillment under multiwarehouse collaborative distribution, comprehensively considering the fulfillment costs of different orders fulfillment strategies, an order fulfillment strategy selection model is proposed. The first step of the model uses the linear programming algorithm to solve the cost of suborder merge transportation after the order is split. The second step calculates the cost of the current “greedy algorithm” of the e-commerce platform for order split fulfillment. Then, the cost of each strategy is compared and the lowest cost one is chosen. The calculation example analysis shows that the order fulfillment strategy is closely related to the delivery location of the order and the SKU category. When the delivery location is far away and SKU categories are many in the order, the merged transportation strategy of suborders after the order is split will be significantly better than the cost of separate transportation. The multiwarehouse collaborative distribution fulfillment strategy proposed in this paper can provide a decision basis for the e-commerce platform to choose which fulfillment method.

Determinants for order-fulfilment strategies in engineer-to-order companies: Insights from the machinery industry

Recent empirical studies have refined our understanding of engineer-to-order (ETO) situations, supporting the existence of different order-fulfilment strategies based on the degree of customer involvement in the engineering and production activities, which differs depending on the strategic fit with the environment in which the company operates. Despite the importance of this finding, limited attempts have been made to comprehensively understand the determinants for this strategic choice in ETO companies. To overcome this gap, this study aimed to investigate the sources of differentiation between the environments that ETO companies can face and the ways of reacting to strategically fit the order-fulfilment strategy. Therefore, this research analysed the existing literature through a contingency theory lens and performed a multiple case-study research in a specific ETO sector, i.e. the machinery industry. The study identified five different order-fulfilment strategies implemented in the machinery industry to provide different product families to the market. For each strategy, the different environment characteristics were defined, and the performance outcome was measured, explaining the rationale for the positioning of the product families in different strategies. The findings of this study have two main contributions. First, the study contributes to theory by deepening and refining the analysis of contingencies for choosing different order-fulfilment strategies in the ETO context. Second, the study provides practical guidelines to ETO companies that want to adapt their order-fulfilment strategies to the unexpected or planned changes in their environment.

Costs of Alternative Loading and Order Fulfillment Strategies in a Cooperative Cotton Warehouse

Cooperatively owned cotton warehouses have unique inventory management issues. Unlike many other agricultural commodities, cotton is stored and marketed on an identity preserved basis. Unlike other warehouses which are continuously replenished, cotton warehouses are loaded once a year then slowly unloaded as orders for specific bales are received. The warehouse is configured in rows that can only be accessed from a single direction which necessitates moving non-targeted bales to reach a targeted bale. All of those factors create unique issues in simulating warehouse operations. This study conducts applied analysis intended to identify more efficient loading and order fulfillment strategies using the program developed by (Richard 2020). Results suggest the best alternative loading strategy lead to a $499,013.75 per turn of the warehouse (0.85 per bale) reduction in handling costs and the alternative order fulfillment strategy lead to a $34,139.19 per turn (0.06 per bale) reduction in handling costs. Cotton warehouse cooperatives will pass some or all of these savings through to the farmer-owners.

Multi‐Modal Order Fulfillment: Concept and Application

Empirical work on order fulfillment strategies suggests that building products to customer order is an important driver of organizational value. Similarly, the experimental literature indicates that customers derive value from customization. The modeling literature provides a more equivocal perspective, suggesting that a combination of build‐to‐forecast and build‐to‐order (BTO) fulfillment modalities may lead to the best system‐wide outcomes. Using an industry studies approach, we build on these theoretical perspectives to examine order fulfillment at a global automotive producer. Interviews with key decision makers and a statistical analysis of 48,534 individual vehicle sales enable the development of four propositions on the organizational and profitability implications of the firm's evolution in order fulfillment strategy. Our analyses indicate that building products to customer order is a source of higher unit profit margin. The BTO process also exposes fault lines and generates opportunities for operational improvement, both in the order‐to‐delivery system and in the broader organization. Build‐to‐order evolves to provide the firm with insight on customers’ willingness to trade delivery lead times against their product attribute preferences. This information allows BTO to incorporate a demand management role, for example, by shifting custom orders to later time periods to accommodate excess demand. These changes lay the groundwork for a multi‐modal order fulfillment strategy that no longer distinguishes between the order source or production modality. This strategy enhances customer responsiveness, while addressing manufacturing capacity management imperatives. Our findings open new avenues for theory building, as well as experimental, empirical and modeling research in order fulfillment.

Evaluation of Order Fulfillment Options in Retail Supply Chains

ABSTRACTRetailers face a major operational challenge in fulfilling online orders while managing their traditional store‐based distribution processes. In this context, the following order fulfillment options available to retailers are considered: store‐facing distribution centers (DCs), dedicated order fulfillment facilities (DTC), retail stores, and direct‐fill by vendors. A framework for the online order fulfillment process is developed to evaluate these options using operational and financial measures collected from a large U.S. retailer. The study presents managerial insights regarding each fulfillment option and identifies operational and cost thresholds where a particular fulfillment option would be preferred. The results show that due to better order fulfillment efficiency, distribution facilities (DC and DTC) out‐perform fulfillment from stores and vendors. However, retailers can leverage their network of stores to overcome the shortfall in store‐based fulfillment costs by focusing on the order delivery process. The analysis presented in this article is useful for practice as it helps retailers identify options that best suit their order fulfillment strategy.

Incorporating Order Crossover Information into Service-Oriented Base Stock Policy Decisions

We investigate the impact of order crossover on a periodic, order-up-to (R,S) inventory system where attaining a target service level is the focus. Order crossover, when orders arrive in a sequence different from that in which they were originally placed, is increasingly likely to occur in modern supply chains. One reason for this is the increasing pressure to focus on service performance, which we refer to as the “Amazon Service Effect”. Many service-oriented changes to order placement and fulfillment strategies will increase the chance of order crossover. While the majority of inventory control studies, including crossover-focused studies, tend to be cost-oriented, in practice many inventory systems are driven by service goals. To explore the use of crossover information in inventory policy decision-making we adopt the “effective lead-time” (ELT) approach (Hayya et al., 2008) to representing order lead-times where order crossover is present. We develop a hybrid discrete-event/continuous simulation model that utilizes a unique structure to provide a detailed representation of a stochastic inventory system and collect precise information about order crossover, effective lead-time, service performance, and related operating characteristics. We first address two crossover related assumptions that have not been directly addressed in the literature. We find that order crossover clearly impacts service-oriented inventory system performance (much as it does cost-oriented systems) and that a protection period of R ELT time units is appropriate for an R,S inventory policy under crossover. We then explore five methods of including ELT information into the process of determining the order-up-to level (S) for a periodic, order-up-to (R,S) inventory policy. We perform a full-factorial simulation study under various conditions of target service level, demand variance, and lead-time variance, for a total of 375 scenarios. We find the method used to include effective lead-time information into the decision significantly impacts service performance. We compare and contrast the different methods, discuss issues such as data requirements and the sources of error, and address the research and managerial implications of our findings.

Integrated management of inventory and production systems based on floating decoupling point and real-time information: A simulation based analysis

Globalisation has transformed market conditions reducing lead times and increasing both the degree of product differentiation and price competition. To cope with this issue, new hybrid order fulfilment strategies have emerged which integrate the Make to Stock (MTS) and Build to Order (BTO) strategies, and whose aim is to simultaneously improve opposite objectives, such as the stock level and the lead time. Furthermore, companies face frequent challenges of sharing updated information and avoiding the lack of coordination between the different company subsystems. This work focuses on relatively recent fulfilment strategies based on the Floating Decoupling Point (FDP) which uses real time information to operate. The main objectives of this work are the study of the influence of different sources of real-time information about the available products and select the most suitable configuration of these systems, regarding the inventory control policy and the source of real-time information. The stochastic nature of the process makes simulation an appropriate tool to achieve valuable results. The simulation studies have been carried out following a full factorial Design of Experiments (DoE). Experimental results show that the strategies based on the FDP are very sensitive to the real-time information. These systems achieve the best performance when the inventory control policy uses simultaneously demand forecasting and real-time information of available products corresponding to the Work-In-Process (WIP) and Finished Goods Inventory (FGI). In contrast, system performance deteriorates significantly when real-time information of available products in the WIP has not been taken into account.

Impact of the customer demand on order fulfilment strategies based on floating decoupling point: a simulation analysis

Order Fulfilment Strategies have become more and more popular, thanks to their capability of improving the delivery times and reducing the inventory levels. Among the postponement strategies of Mass Customisation are the Virtual Build-To-Order (VBTO) and i-Virtual Build-To-Order (i-VBTO) systems which are two systems with the ability to serve customers from anywhere in the inventory (Work-in-Process and Finished Goods Inventory) showing an interesting potential of adaptation to the variability of the demand. This study is aimed at testing the suitability of the basis of the i-VBTO system against the VBTO system through the study of the influence of characteristics of demand that are common in real environments. Regarding the contribution of this work, some weaknesses of the VBTO system can be highlighted (e.g. under certain demand conditions it loses the efficiency), and some benefits of the i-VBTO system (e.g. it turns out to be more robust and stable regarding changes in demand than the VBTO system).

Impact of the customer demand on order fulfilment strategies based on floating decoupling point: a simulation analysis

Impact of the customer demand on order fulfilment strategies based on floating decoupling point: a simulation analysis

Impact of Value‐Added Service Features in e‐Retailing Processes: An Econometric Analysis of Web Site Functions

ABSTRACTWe examine the impact of three classes of Web site functions (foundational, customer‐centered, and value‐added) upon e‐retailer performance. Using secondary panel data for 2007–2009 on operating characteristics of over 600 e‐retailers, our econometric analysis finds that only the value‐added service functions are positively associated with changes in e‐retail sales revenues across time. We also observe a decreasing marginal impact of deploying additional value‐added service features. To account for possible alternate explanations, we control for firm‐ and time‐specific fixed effects, merchant types, merchandise categories, and order fulfillment strategies. By further decomposing e‐retail sales revenues into Web site traffic, conversion rate, and average order value, we find that Web site functions affect e‐retail sales revenues mainly through their impact on Web site traffic. Our investigation demonstrates the empirical research usefulness of the Voss conceptual e‐service sand cone model. Our results identify for managers where to focus ongoing e‐retailing system development efforts, yet suggest that focusing too many retailing capabilities on exploratory and experimental value‐added service features may backfire, potentially leading to worsening e‐retailer performance.

Defining value chain architectures: Linking strategic value creation to operational supply chain design

Over the past three decades scholars have developed comprehensive insights into the operational and strategic aspect of designing and managing the supply chain. Reviewing this ample body of knowledge however one cannot help but notice a persistent disunion between the “value chain” view that considers aspects of value creation and appropriation, and the operational “supply chain” view that considers strategies and tools for designing and operating efficient inter-firm networks. Commonly these views do not interact: value creation has the aim of capturing the maximum value-added in financial terms, the supply chain view aims for designing operationally efficient supply chains. In contrast to their treatise within the academic literature, from a practical point of view these two aspects are both necessary (and thus in their own right insufficient) components to a firm's supply chain strategy. In this paper we thus turn to an exploratory case study to identify what such a combined view of the value and supply chain would entail. We refer to this purposeful creation as the “value chain architecture” and propose five fundamental decisions that define the latter: (1) the nature of value provision (driven by the core competence of the firm), (2) the operational footprint decisions for manufacturing, sourcing and distribution, (3) the approach to risk management, (4) the order fulfillment strategy (and implicit in that, the type of product customization), and (5) the buffering strategy. We conclude with an exploration of the application and utility of the “value chain architecture” concept in both academia and practice.

Design of inventory pools in spare part support operation systems

The objective of a spare part support operation is to fulfill the part request order with different service contracts in the agreed response time. With this objective to achieve different service targets for multiple service contracts and the considerations of inventory investment, it is not only important to determine the inventory policy but also to design the structure of inventory pools and the order fulfilment strategies. In this research, we focused on two types of inventory pools: multiple inventory pool (MIP) and consolidated inventory pool (CIP). The idea of MIP is to maintain separated inventory pools based on the types of service contract, while CIP solely maintains a single inventory pool regardless of service contract. Our research aims to design the inventory pool analytically and propose reserve strategies to manage the order fulfilment risks in CIP. Mathematical models and simulation experiments would be applied for analysis and evaluation.

"Mass Customization and Profitability: The Roles of Incentives, Inventory, and Option-based Revenue"

Mass customization strategies have been widely heralded as a source of competitive advantage for manufacturing firms. Such customer-driven order fulfillment strategies help generate alignment between manufacturing operations and customer needs, and ultimately translate into higher margins. These margins are attributed, in part, to lower distribution and stock-holding costs as well as fewer sales incentives. However, despite frequent anecdotal and case study evidence for the positive effects of mass customization, empirical support for its financial benefit is limited. We base our study in the automotive industry, and quantify the relative financial impact of a firm's order-fulfillment strategy by exploiting a context that allows us to simultaneously contrast the post-manufacturing cost and revenue implications of building products to order, and building them to forecast. We integrate unit-level production, logistics, sales, and profitability data from a large automotive producer that manufactured vehicles to order as well as to forecast. Our analysis of 48,534 vehicle sales confirms that building products to order leads to reduced sales incentives and post-production inventory holding costs, but also to reduced option-based revenue. On balance, building products to order yields a higher profit margin per unit. Sales incentives, inventory holding costs, and option-based revenue were found to fully mediate between order-fulfillment strategy and unit profitability.

A [formula omitted] inventory model with a drop-shipping option for e-business

Drop shipping is used by online as well as traditional retailers as an order fulfillment strategy. A retailer simply forwards customers’ orders to the manufacturer or a distributor who fills the orders directly to the customers and is paid a predetermined price by the retailer. For the retailer, advantages of drop shipping include lower holding, handling, and shortage costs. Disadvantages include increased per-unit cost, fragmented order delivery when a single customer order involves products from different manufacturers, longer delivery times, and increased order processing cost. In this paper, we develop two ( Q , R ) inventory models that allow a retailer to use the drop-shipping option in case of a shortage during lead-time. In the first model, the units short are backordered whereas in the second model sales are lost. We provide closed-form results for exponential and uniform demand distributions. We perform numerical sensitivity analysis and illustrate the results with numerical examples.

Linking Product Variety to Order-Fulfillment Strategies

Providing a variety of attributes in products is an important way of attracting customers, but it often increases complexity and managerial cost. We drew on two data sets collected in the automotive sector to explore the link between external variety (the variety offered the customer) and internal variety (the variety involved in creating the product). We found that these two dimensions can be independent of each other. External variety is problematic for firms producing to forecast, and handling internal variety is challenging for firms building products to order. The effectiveness of strategies to mitigate variety's negative effects, such as modularity, mutability, late configuration, and option bundling, depends on the order-fulfillment strategy the firm follows.

BUILDING CARS TO CUSTOMER ORDER — WHAT DOES IT MEAN FOR INBOUND LOGISTICS OPERATIONS?

The automotive industry is undergoing a strategic transition. Cost pressure from rising stock levels in the market and increasing incentives needed to sell these vehicles are forcing vehicle manufacturers to rethink their prevalent “stock‐push” approach, building vehicles against a forecast and selling from stock, in favor of a stock‐less “build‐to‐order” order fulfillment strategy. More responsive order fulfillment at the vehicle manufacturer level however will not only require flexible and responsive component supply, but will also have wide ramifications for the logistics operations. Based on three case studies of major inbound logistics operations, this exploratory study assesses their ability to support such a build‐to‐order approach, as well as the potential implications of such transition. The paper concludes with a set of general strategies for how these implications could be mitigated.