You are here: Home / Faculty Research / Supply Chain and Information Systems

Supply Chain and Information Systems

Russell Barton, Professor of Supply Chain and Information Systems, and Jun Shu, Assistant Professor of Supply Chain and Information Systems

Barton and Shu are exploring the application of statistical process control (SPC) to tracking the progress of an item through a supply chain. SPC has long been used to monitor manufacturing processes, but recent developments in RFID now permit items to be tracked in minute detail through a supply chain. Instead of sampling product parameters, SPC can also be used to sample the timeliness of an item's arrival at selected supply chain points and the correctness of a predetermined path. Such SPC applications can give managers an early warning of supply chain problems and a better opportunity to model supply chain dynamics. This research was supported by a grant from the National Science Foundation, and facilitated by significant interaction with the Center for Supply Chain Research members, including VeriSign in particular.

Peter Ebbes, Assistant Professor of Marketing, and Zan Huang, Assistant Professor of Supply Chain and Information Systems

Complex social networks have so many connections and nodes that it is nearly impossible to understand their properties and use them intelligently without asking smart questions about them via successive graph sampling techniques. Companies can use networks intelligently to understand how knowledge about products can spread by word of mouth in a population, about recruiting scarce talent, or making business connections. Sampling techniques (e.g., breadth first search, random walk, and ego networks) can lead to identification of correlations between demographics and network characteristics (e.g., income and degree of connectedness), or identification of market segments based on correlations between influence and connectivity.  Ebbes and Huang have been working on developing new network sampling techniques that managers can use to quickly understand large complex networks. They use a large network database from “Facebook,” but need a highly skilled programmer to develop a program with which to analyze the data and test their methods. They are also interested in other network databases, such as networks of physicians, or business-to-business networks.

Daniel Guide, Associate Professor of Operations and Supply Chain Management

Guide is studying how retailers and manufacturers deal with the substantial number of product returns made by customers. The reasons for returns include mismatch between customer needs and product attributes (often exacerbated by aggressive promotional tactics designed to maximize sales of overstocked products and by poorly trained sales staff), user-unfriendly products, poor product documentation, and defective products. Total supply chain costs and their allocation vary for return of products sold in brick-and-mortar outlets versus over the Internet. Guide is exploring the return policies and practices of retailers and manufacturers, and developing models and tools to align their incentives to reduce product returns and lower costs for all participants across the supply chain.

Terry Harrison, Professor of Supply Chain and Information Systems

Harrison is looking at how firms manage a potential downside consequence of new product introduction and product line extensions, which is the proliferation of SKUs (stock-keeping units). Although introducing new products generally increases revenue, it also can raise costs due to higher inventory, increased complexity, and other factors. This research investigates how firms decide which products to discontinue as new products are added. Harrison plans to survey managers to address this question. His initial inquiries suggest that firms eliminate products on the basis of profitability, volume, number of manufacturing steps, and links to other products. Other firms simply mandate that some products be eliminated as new ones are added. Harrison plans to develop optimization models that link market and supply chain functions and jointly determine the best set of products to eliminate.

Elena Katok, Professor of Supply Chain Management, and Douglas Thomas, Associate Professor of Supply Chain and Information Systems

Many retailers use service level agreements to ensure that their suppliers provide them with a sufficient amount of inventory to maintain high levels of customer service (defined as the proportion of customer orders filled). An example is to reward a supplier for meeting a 95-percent service level over a given review period. Katok and Thomas test the effect of service level agreements for eight versus two demand periods, and for rewards that ranged from zero in the baseline treatment to a high reward condition of 50 times higher than the holding cost for one unit per demand period. Their results show that service level agreements implemented over longer review periods (eight) are more effective than ones implemented over short review periods (two) when tested in the behavioral laboratory with human subjects (both practicing managers and students). The results for size of rewards were that decision-makers overreact to small rewards and under-react to large rewards. Thus, medium-level rewards over longer time horizons may well be more effective than high rewards over shorter time horizon.

Akhil Kumar, Professor of Information Systems

Kumar is exploring techniques that will allow independent but complementary Web services on the Internet to be linked so that customers can use them interactively. For example, airline, hotel, and rental car reservation services are usually developed by different service providers, and a customer has to manually interact with each provider to make the corresponding reservation and any later changes. However, if a customer wanted to combine all three reservations, the processes behind each of these services can be linked with the customer's own internal processes, sometimes via an automated mediator. Kumar is developing techniques to check the feasibility of doing so, and to compose independent Web services, either directly or via mediators, so that business processes of different organizations can interoperate with each other. These composition approaches can also be used to create flexible, inter-organizational processes in the context of supply chains and virtual corporations.

Dawn Russell, Assistant Professor of Supply Chain Management, and Jun Shu, Assistant Professor of Supply Chain and Information Systems

Customers and suppliers can enhance their joint performance significantly by sharing unambiguous and reliable information regarding the status of products in the supply chain, according to Russell and Shu. Achieving this level of data synchronization requires that the parties agree on common terms and language, and that they invest the time and money to reach agreement. To be successful, the parties must address asymmetrical rewards and costs from their collaborative efforts, i.e., a large customer may gain more from this effort than a small supplier. The parties also must learn to trust one another so that they can share information openly enough to assure their mutual gain. Data were collected for this study by talking with suppliers and customers regarding their business priorities, supply chain decision-making processes, and their approaches to managing both formal and informal information exchange.

Susan Xu, Professor of Management Science and Supply Chain Management

Xu’s research focuses on ticket queues in which customers, upon arrival to a service site, are issued a numbered ticket, and the number being served is broadcast on a display panel. Despite the numerous apparent advantages of a ticket queue over a traditional physical queue, it has a drawback that can significantly impede its service performance. In the ticket queue, information on physical queuing is lost, i.e., only the difference between the customer’s ticket number and the number served is observed, but not the actual number of customers ahead of him or her. This information loss often causes an arriving customer to overestimate his/her position in line and abandon the system prematurely because of losing patience with the waiting period. This abandonment is detrimental to both customers and business. Xu's research focuses on developing analytic tools that can accurately estimate the expected waiting time for each customer, based on the difference of the customer’s ticket number and the number being served. Her research shows that by providing this information to customers, management can significantly reduce lost sales and increase customer satisfaction.