Order Fulfillment Research Articles

Addressing distributional shifts in operations management: The case of order fulfillment in customized production

To meet order fulfillment targets, manufacturers seek to optimize production schedules. Machine learning can support this objective by predicting throughput times on production lines given order specifications. However, this is challenging when manufacturers produce customized products because customization often leads to changes in the probability distribution of operational data—so‐called distributional shifts. Distributional shifts can harm the performance of predictive models when deployed to future customer orders with new specifications. The literature provides limited advice on how such distributional shifts can be addressed in operations management. Here, we propose a data‐driven approach based on adversarial learning, which allows us to account for distributional shifts in manufacturing settings with high degrees of product customization. We empirically validate our proposed approach using real‐world data from a job shop production that supplies large metal components to an oil platform construction yard. Across an extensive series of numerical experiments, we find that our adversarial learning approach outperforms common baselines. Overall, this paper shows how production managers can improve their decision making under distributional shifts.

Analysis of supply chain institutional efficiency performance in potato chips SMEs clusters after Covid-19 pandemic

The pandemic conditions in 2020-2021 resulted in problems for the potato chip micro, small, and medium-enterprise (SMEs) cluster, including an imbalance in sales numbers with the resulting production due to a drastic decline in demand, marketing, and business performance. The first trimester of 2022 shows an increased demand for potato chips. Therefore, efficient performance is needed to support production recovery and business performance by increasing supply chain institutional efficiency. This research aimed to analyze the efficiency performance value and the sub-variables input with the most influence on supplier efficiency performance. This research used the Data Envelopment Analysis (DEA) model CCR-I Dual with input sub-variables (i.e., cash-to-cash-cycle-time, lead time, and flexibility) and output sub-variables (i.e., percentage of conformance quality standards, order fulfilment, and delivery performance). The analysis was carried out on the flow of suppliers to potato chip MSMEs. The results show that 8 decision-making units (DMUs) were inefficient (55.56% and 33.33%), and 1 DMU was in efficient condition (100% green), namely is DMU 6. The results also show that the input sub-variable with the most influence on supplier efficiency performance was the flexibility of sending raw materials followed by cash-to-cash-cycle-time.

Vaccinating Health Care Supply Chains Against Market Failure: The Case of Civica Rx

Summary This article focuses on the value of introducing novel business models into health care to address market failures that are hurting people — delving deeply into learning from real-world examples within the generic drug supply chain and its failure to supply critical medicines reliably at a low cost. Some problems in health care are so complex that traditional private-sector or governmental interventions alone have not been able to solve the problems. In an original response to ongoing generic drug shortages, in 2018, seven U.S. health systems and three philanthropic organizations founded a novel not-for-profit drug manufacturer, Civica Rx, to address the issue. Civica is a new entrant in this supply chain and utilizes a new business model called a health care utility that prioritizes access over profit. The company has been scaled rapidly and now provides more than 75 critical medications that are most at risk for shortages to more than 55 health systems across the United States. This article provides the first empirical evidence of Civica’s effect on security and cost of supply for one of its member health systems by utilizing internal supply chain, pharmacy, and external market data between 2016 and 2022. Results show that Civica was able to improve generic drug access above the wholesaler model. Using data related to 55 Civica orders of 20 distinct products between 2020 and 2022, the authors estimate Civica’s fulfillment of its contractually guaranteed volume at 96% (95% confidence interval [CI] = 92%–100%), whereas data on 302 wholesale orders for the same products over the same period estimate the wholesaler order fulfillment rate at 86% (95% CI = 82%–90%); the difference between these rates is statistically significant (P = 0.03). In addition, through its reserve supply of product, Civica offered a product access benefit of a further 43% above the Civica-guaranteed minimum viable volume floor. Wholesaler prices, at the order level, were estimated to be on average 46% above the Civica price for the same product in the same year (95% CI = 27%–64%, N = 302), with a P value of the difference of less than 0.001. However, through optimizing its wholesaler orders by buying more volume when prices were low from the 62 different non-Civica manufacturers, this closed the actual achieved cost-savings gap between the wholesalers and Civica to 2.7% in aggregate, with Civica still being the lower-cost option.

ВІЗУАЛІЗАЦІЯ ПРОЦЕСІВ ОБРОБКИ ДАНИХ ДЛЯ ІНФОРМАЦІЙНОЇ СИСТЕМИ КОМЕРЦІАЛІЗАЦІЇ ОБ’ЄКТІВ ПРАВА ІНТЕЛЕКТУАЛЬНОЇ ВЛАСНОСТІ

The aim of this article is to visualize the data processing processes for the information system of intellectual property rights commercialization. The article analyses the main legislative and regulatory documents governing the process of intellectual property rights commercialization in the information products and services market in Ukraine. It is also determined that the functioning of this information system will be influenced by external market factors. In particular, the main ones include economic development of the countries where the process of intellectual property rights commercialization takes place, legislation and regulatory framework of the country, financial regulation of the process of intellectual property rights commercialization. Based on these results, the author developed the structure of the data flow diagram of the information system for drafting an intellectual property sale and purchase agreement, taking into account external factors of influence. This data flow diagram includes such processes as determining the terms of the intellectual property contract for an intellectual property object, forming the relevant contract and confirming it. The paper also contains the structure of the data flow diagram for the transfer of product ownership and the intellectual property deposit and payment agreement, taking into account external factors of influence. It includes a description of such processes as the formation of a deposit agreement, order fulfilment control, and payment for the execution of the process of buying and selling an intellectual property object. The proposed visualization of data processing processes for the information system for commercialization of intellectual property rights objects includes a database of laws and regulations of Ukraine and can be expanded for use outside Ukraine. The results of the study are applied and can be used to development an appropriate information system of intellectual property rights commercialization, taking into account the influence of external factors of the market of information products and services.

How to Deploy Robotic Mobile Fulfillment Systems

Many warehouses involved in e-commerce order fulfillment use robotic mobile fulfillment systems. Because demand and variability can be high, scheduling orders, robots, and storage pods in interaction with manual workstations are critical to obtaining high performance. Simultaneously, the scheduling problem is extremely complicated because of interactions between decisions, many of which must be taken timely because of short planning horizons and a constantly changing environment. This paper models all such scheduling decisions in combination to minimize order fulfillment time. We propose two decision methods for the above scheduling problem. The models batch the orders using different batching methods and assign orders and batches to pods and workstations in sequence and robots to jobs. Order picking and stock replenishment operations are included in the models. We conduct numerical experiments based on a real-world case to validate the efficacy and efficiency of the model and algorithm. Instances with 14 workstations, 400 orders, 300 stock-keeping units (SKUs), 160 pods, and 160 robots can be solved to near optimality within four minutes. Our methods can be applied to large instances, for example, using a rolling horizon. Because our model can be solved relatively fast, it can be used to take managerial decisions and obtain executive insights. Our results show that making integrated decisions, even when done heuristically, is more beneficial than sequential, isolated optimization. We also find that positioning pick stations close together along one of the system’s long sides is efficient. The replenishment stations can be grouped along another side. Another finding is that SKU diversity per pod and SKU dispersion over pods have strong and positive impacts on the total completion time of handling order batches. Funding: This work was supported by National Natural Science Foundation of China [72025103, 72361137001, 71831008, 72071173] and the Research Grants Council of the Hong Kong Special Administrative Region, China [HKSAR RGC TRS T32-707/22-N]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/trsc.2022.0265 .

The Impact of Strategic Inventory Management on Logistics Organization’s Performance

This study examines the impact of strategic inventory management on the performance of logistics organizations in Oman. Inventory management plays a crucial role in ensuring efficient operations, reducing costs, and meeting customer demands. The study investigates the strategic inventory management practices adopted by logistics organizations in Oman, including demand forecasting, procurement optimization, and inventory control techniques. It analyses the influence of these practices on key performance indicators such as order fulfillment, on-time delivery, inventory turnover, and customer satisfaction specifically within the context of the Omani logistics industry. The study highlights the significance of a well-designed inventory management strategy in enhancing overall organizational performance by improving resource allocation, minimizing stockouts, and enhancing supply chain responsiveness. The study concludes with practical implications for logistics managers in Oman and suggests avenues for future research in this area specific to the Omani context.

ANALYSIS OF SUPPLY CHAIN MANAGEMENT OF AND PARTNERSHIP PATTERNS IN VEGETABLE ONLINE COMPANY: CASE STUDY AT BEJANA.ID

This study aims to analyze supply chain management of vegetable products, identify supply chain performance based on the estimation of average time and partnership patterns at Bejana.id, Bandar Lampung. The case study method was used to determine the location purposively. Data were collected using questionnaires in December 2022. The sample used purposive sampling, including one person from Bejana.id, six merchant partners, and nine farmer partners. The data analysis method applied for supply chain management and partnership pattern is qualitative, and supply chain management performance is Supply Chain Operation References (SCOR). The results indicated that (1) the Bejana.id supply chain includes farmer and merchant partners, Bejana.id, and B2B (Business to Business) & B2C (Business to Consumers). The flow of products, information, and money are efficient and have not found severe issues, (2) supply chain performance at the supplier partner level is an advantage in standardized products (SP) and parity in perfect order fulfilment (POF), and for the Bejana.id level get the advantage in standardized products (SP), (3) the partnership pattern between Bejana.id and farmer partners is the common trade pattern, and between Bejana.id and merchant partners is the agency pattern. Keywords: e-commerce, partnership, SCOR, supply chain, vegetables

Will you stick to a high-quality collecting standard? order fulfillment vs. limited supply in diseconomy-cost-mattered remanufacturing operations

Consider a remanufacturing system consisting of a brand, a new component supplier (Supplier N), and a remanufactured component supplier (Supplier R). The brand priorly purchases remanufactured components and then assembles them into final products, while Supplier R collects the end-of-life products with random residual quality and then produces them to be “as good as new” components at a diseconomy cost based on the residual quality. Supplier R has the option to provide order fulfillment commitment before production (Scenario O), or, do not provide such a commitment, reserving the right to limit the proportion of the orders to save production costs although it may drive the brand to emergently purchase the new components (Scenario L). Specifically, in Scenario L, Supplier R can set a strict residual quality standard which saves the remanufacturing cost and constrains the brand’s order quantity. We reveal that constraining the brand’s order quantity will not be the optimal choice for Supplier R, because the overreliance on the limited-supply threat will distort Supplier R’s wholesale price decision, resulting in significant profit loss. However, the supply chain system can perform better with the quantity constraint, because it concentrates the channel power in the hands of a single decision maker, which enables the decisions made more closely to the first-best level.

Rooting out the root causes of order fulfilment errors: a multiple case study

ABSTRACT While recent technological advancements have enabled improved performance in warehouse operations, companies still struggle with eliminating errors such as incorrect/damaged items or the wrong quantity sent to customers. Such errors result in inefficient resource use, costly returns handling, and customer dissatisfaction. Despite the importance of errors, current knowledge of the underlying causes is limited. This paper addresses the gap by investigating error causes through a relatively new technology – intelligent video analysis (IVA), an additional tool for analysing warehouse operations. A multiple case study involving companies that have implemented IVA in their outbound warehouse operations (i.e. order picking, packing, and sorting) was conducted. This study is the first to investigate implementations of IVA, offering novel empirical insights into error root causes. It shows how many errors reported by customers are actually not made by humans in outbound warehouse operations but are attributable to faulty customer claims, inbound warehouse operation errors, and malfunctioning technology. This study offers interesting insights into the interaction of various technical, organisational, and human factors, thereby contributing to the literature on sociotechnical systems and the human-centric Industry 5.0. Finally, the study outlines a way forward for managers to address and further reduce errors occurring in warehouse operations.

Analisis Penerapan Sistem Informasi Akuntansi Persediaan Studi Kasus Pada CV. Bina Usaha Sejahtera Malang

The rapid development of the industry has made the level of competition even tighter. Companies need to pay attention to several things in the face of competition, one thing that really needs to be considered in the order fulfillment process is the need for an effective and efficient inventory system. The purpose of this research is to find out the implementation of inventory accounting information systems in CV. Prosperous Business Development. The method used by researchers for this research is descriptive qualitative method with primary data and secondary data types. The research results obtained are the Accounting Information System contained in the CV. Bina Usaha Sejahtera is still not optimal, one of the contributing factors is the double duty of the warehouse department.

Analysis of Supply Chain Performance of Banana Chips In Dahlia MSMEs

This study aims to analyze the performance of Banana chips supply chain management in Dahlia MSMEs, Gorontalo City in August-September 2022. This research method is a case study using primary and secondary data types. Data analysis techniques used in this study is the analysis of Supply Chain Operation Reference (SCOR) which then the calculation results will be compared with the data Benchmark. The results showed that of the 4 attributes with 7 assessment indicators only 4 indicators are in the superior category, namely perfect order fulfillment, delivery performance, cash to cash cycle and order fulfillment cycle while the other 3 indicators are volume flexibility, lead time and daily inventory are in the advantage category with the total cost used for Banana chips supply chain process is IDR. 7,560,000 in one production process. The impact for managerial is because the lead time that has not reached a superior position has a strong relationship with volume flexibility where long waiting times will result in the inability of the supply chain to maintain the flexibility of production volume, of course, this will have an impact on daily inventory, because it still have to wait for the schedule for the delivery of raw materials plus the production and marketing process.

Can Brick-and-Click Stores Yield Returning Online Customers? Assessing In-house Logistics Service Quality (LSQ) of Multi-channel Retailers

This study aims to examine the influence of retail logistics service quality on online customer loyalty in Malaysia. In total, 372 self-administered questionnaires were collected from customers who have ordered products online from ‘brick-and-click’ supermarkets and department stores. The results show that product condition, product availability and delivery durations are significant predictors of customer loyalty. The novelty of this research lies in its strong emphasis on last-mile parcel delivery, which is a crucial aspect of order fulfilment operations, and the first-party home delivery service, which is among the earliest conducted in the region.

Digital twin implementation approach in supply chain processes

Integrating technology and data throughout value chains is critical for achieving efficiency. Smart technologies that enable innovation and continuous improvement are key to long-term success. Modelling and simulation of business processes help to better understand existing systems and optimize processes. However, current approaches to digital transformation tend to focus solely on outcomes rather than the strategic methodology needed for successful implementation, resulting in differing valuations of solutions investments. This paper's significant contribution is introducing a new conceptual implementation method for digital twin technology in supply chain processes. This methodology enables technology and system evaluation at the process study stage, and a stylized business case demonstrates its application in a real-world scenario involving digital twin integration into order fulfilment in a manufacturing factory using Business Process Modelling Notation (BPMN) to simulate "As-Is" and "To-Be" processes.

Sectoral Advanced Planning Systems (APS) Based on Utility Functions

This paper contains the example of sectoral APS systems, for which the problem algorithmic space coincides with the relevant operational environment with great accuracy. The method of scheduling for technological processes with looping is described, based on the simultaneous application of two criteria: the value of relative direct costs and the average utility of order fulfillment. The influence of buffers on the work of shops is considered. The proposed method provides an automatic grouping of the same type of jobs on all machines involved while taking into account the required duration of jobs. A package of application programs has been developed that allows planning for an average number of orders. The result of the program is a set of non-dominant (not improved) options that are offered to the user for making a final decision.

Unleash the power of Emotional Intelligence: Order Fulfillment impact on Sales Performance in the Automobile Industry

The automobile industry is a highly competitive sector that demands effective sales performance to drive revenue and maintain market share. Emotional intelligence, the ability to recognize and manage emotions in oneself and others, plays a crucial role in establishing rapport with customers and understanding their needs. Order fulfillment, the process of delivering products to customers in a timely and accurate manner, is vital for customer satisfaction. This research aims to explore the relationship between emotional intelligence, order fulfillment, and sales performance in the automobile industry. By analyzing these factors, organizations can gain insights into strategies and practices that contribute to enhanced sales performance and customer satisfaction. The findings of this study will provide actionable recommendations for optimizing sales processes and achieving sustainable growth in the highly competitive automobile industry.

Network design with consideration of hours‐of‐service regulation and drop‐and‐swap trailer operations

AbstractThis research, motivated by collaboration with a leading manufacturer and distributor of building products, introduces two distribution network design models considering federally mandated hours of service restrictions on truck drivers and drop‐and‐swap trailer operations. A key feature of the drop‐and‐swap transport mode is the decoupling of linehaul and last‐mile delivery operations, which enables geographic extension of last‐mile delivery routes while complying with hours of service driver regulations and providing next‐day delivery service. The models simultaneously determine the profit‐maximizing size, number, and location of order fulfillment facilities and satellite drop‐and‐swap terminals, and systemwide transportation flows. A case study of the firm's distribution network reveals that the new location models improve profitability by approximately 5% when compared with traditional network design approaches. An experimental study of five marketing and operational characteristics shows when the models are most advantageously applied. Overall, profit improvements range from 2.32% to 10.97% on a set of 288 test problems. The research provides new insights for integrated facility location and transportation strategic design. The potential application of the models in a variety of e‐commerce scenarios is promising.

Marketplace or reseller: the channel strategy analysis for e-commerce platforms considering brand differentiation

PurposeThe paper aims to clarify the effects of brand differentiation on the platform's formulation of channel strategy and help the online platform formulate the optimal channel strategy, which involves selecting a proper selling mode for each brand.Design/methodology/approachThe paper develops a multistage game model consisting of one online platform and two competing manufacturers with differentiated brands and examines the effects of brand differentiation on these three channel members' profits under each candidate channel strategy.FindingsThe results show that the platform prefers to offer the reselling mode for both brands when the brand differentiation is low, and this preference will be enhanced by the decrease in order fulfilment cost. By contrast, when the brand differentiation is high, it will offer the reselling mode for the premium brand but the marketplace service for the economy brand if the order fulfilment cost is not high; or the marketplace mode will be offered to both brands if this cost is high.Research limitations/implicationsThis study assumes that the order fulfilment costs of platform and manufacturer are fixed and symmetric. Therefore, researchers are encouraged to consider asymmetric costs of order fulfilment.Practical implicationsThe paper guides the online platform to formulate the optimal channel strategy for differentiated brands and provides managerial insights for differentiated brands entering online markets.Originality/valueThis paper explores platforms' optimal channel strategy by jointly considering the effects of brand differentiation and investigates the impacts of brand differentiation on the optimal decision making under four candidate options. Moreover, this paper has been extended to examine the case when the manufacturers' production costs cannot be neglected.

Put it in the bag: Order fulfillment with a pocket sorter system

AbstractDue to high real estate costs in urban areas, shop floor space is scarce in most brick‐and‐mortar stores. Maneuvering newly arrived merchandise through narrow aisles during shelf replenishment is time‐consuming for the sales staff and impedes customers. Therefore, many retail chains nowadays aim for store‐friendly shipments (SFS). By mirroring the layout of a store in the buildup of its dedicated shipments, the need for a zigzag movement through the store when replenishing shelves can be avoided. On the negative side, however, additional effort arises in the distribution centers. A suitable warehousing system to assemble SFS without excessive effort is a pocket (or pouch or bag) sorter, where each item is put into its separate bag. These bags, filled with items, are automatically transported while hanging from an overhead conveyor and can be sorted into any sequence before being delivered to the workstations that build SFS. This article investigates the assembly of SFS with a pocket sorter and presents scheduling procedures to enhance the efficiency of this process for a given set of store orders. We demonstrate that, despite its notorious complexity, the problem can be solved by simple decision rules with good performance. In a case study, we show that this approach can dramatically reduce the completion times of store orders, resulting in savings of more than 60% of the total working hours compared to a simple real‐world policy. Another 30% of reduction can be obtained by standardized store layouts.

Scenario-Based Optimization of Supply Chain Performance under Demand Uncertainty

This study presents a comprehensive supply chain performance optimization model that addresses the trade-off between supply chain cost and customer service level in the distribution network. The model incorporates both deterministic and scenario-based approaches, allowing for a more realistic representation of supply chain operations. The model is applied to a case company operating in the pharmaceutical supply chain in Ethiopia. The goal is to improve the company’s supply chain performance by optimizing various factors such as establishment costs, handling costs, transportation costs, and demand satisfaction. The study considers both financial measures (supply chain cost) and non-financial measures (customer service level) to evaluate the performance of the supply chain. The results of the study demonstrate the effectiveness of the proposed model in identifying the optimal trade-off between supply chain costs and customer service levels. By comparing the results of the model with the current situation of the case company, it is determined that the company can achieve significant cost reductions of up to 25.26% while still meeting customer demands. The model also takes into account the uncertainty in demand, providing more realistic recommendations for distribution center locations, transportation planning, and order fulfillment. The implications of using this optimization model include the potential for cost savings, improved decision-making, enhanced customer satisfaction, and, ultimately, a more successful supply chain. However, the study has some limitations, including a need for further research on other objectives and considerations, such as environmental impacts and disruptions, which could be addressed in future research directions.

Lead-Time-Constrained Middle-Mile Consolidation Network Design with Fixed Origins and Destinations

Many large e-commerce retailers move sufficient freight volumes to operate private middle-mile consolidation networks for order fulfillment, transporting customer shipments from stocking locations to last-mile delivery partners in consolidated loads to reduce freight costs. We study a middle-mile network design optimization problem with fixed origins and destinations to build load consolidation plans that minimize cost and satisfy customer shipment lead-time constraints. We propose models that extend traditional flat network service network design problems to capture waiting delays between load dispatches and ensure that shipment lead-time requirements are satisfied with a desired probability. We approximate these chance constraints using hyperparameterized linear constraints, resulting in new mixed-integer programs (MIPs) for service network design. To find high-quality solutions to the proposed MIPs, we develop an effective integer-programming-based local search (IPBLS) heuristic that iteratively improves a solution by optimizing over a smartly selected subset of commodities. For the largest problem instances, we propose a two-phase IPBLS heuristic that first utilizes a simplified, restricted MIP that constrains leg waiting delays individually. Computational experiments using data from a large U.S.-based e-commerce partner demonstrate the significant impact of tight lead-time constraints on the structure of the consolidation network designs and their concomitant operating costs. Notably, tighter constraints lead to solutions with increased shipment consolidation and higher dispatch frequencies on selected key transportation lanes. Such solutions trade off higher shipment transit times with significantly reduced shipment waiting times to meet lead-time constraints at lower cost.