Keio University, Graduate School of Media and Governance
MAUI Project
Ph.D. Dissertation

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TITLE SCM Process Design Enabled by Fine Granular Real Space Information

With the recent progress in the ubiquitous computing technologies, it becomes feasible to capture fine granular real space information. However, business process to take advantage of this information and create values has not been established yet.

This research aims to bring a business process design guideline in this situation and processes that follow the guideline, assuming that the fine granular information is captured by networked radio identification technology (RFID) and that the application of the information is supply chain management (SCM).

This research consists of two parts: introduction of a business process design guideline and proposal of three SCM processes. This research defines fine granular information as follows: °»Fine granular information is location and status information of items of which SCM process designers and SCM process operators can utilize individual level, in a real time basis, and with arbitrary locations," and I verify the effectiveness of the assumption by investigating the networked RFID standards and executing a pilot project.

To make most use of the fine granular information, I use the information to solve issues caused by recent demand uncertainty. To solve issues of demand uncertainty, I propose two dynamic processes. The requirements for the business process design guideline are two hold: one is requirements from proposed dynamic processes, and the other is requirements to enable fine granularity management. From this analysis, I conclude that business process to utilize fine granular information needs to have six characteristics: Visibility, Controllability, Manageability, Re-constructiveness, Adaptiveness, and Fairness.

Three SCM processes are proposed. The first process is SCM process in the decentralized inventory management policy, in which decision making regarding forecasting and procurement is transferred to individual stores. By using fine granular information, each store can find and sell items in inventories of different stores. Without fine granular information, this kind of process cannot be executed as a regular process, and, as a result, the store cannot increase procurement amount brought by risk pooling. I show that the process brings higher expected profits to both buyer and supplier if the transshipment cost is lower than the upper bound cost, difference between sales price and salvage price.

The second process is SCM process in the centralized inventory management policy, in which decision making regarding forecasting, procurement, and transshipment is made by headquarter of the retailer. By using fine granular information, the retailer can levels unbalance of inventory and forecasted demand by the continuous transshipment. To evaluate this process, I use a case study method. The company I use is a specialty store retailer that deals with apparel, food, and house hold goods.

By comparing existing business process and proposed process, I show that the proposed process can reduce the procurement amount about 4%. It used to happen that huge amount of items are brought to avoid opportunity loss under the return contract, but, as a result, inventory becomes excess and is returned to the supplier, which lower the profit of both supplier and buyer. This process avoids this inefficient process and increases expected profits of both buyer and supplier.

The third process is SCM process that is combined with the loyalty program. Retailers that deal with short life cycle items usually take conservative procurement decision to avoid excess inventory. To avoid this conservative decision, suppliers offer contracts, such as return or rebate. In such a case, retailers sell items by discount, which incurs additional cost to sell. By using fine granular store floor information, the store can offer discount price based on customers' loyalty status. On the other hand, retailers spend money to strengthen the relationship with their loyal customers anyway. Therefore, by combining these two processes, the retailer virtually lowers the risk of over procurement and avoids opportunity loss. To show the effectiveness of the process, I show that the process can increase expected profit of the retailer, adjust sales price based on the loyalty level, and control the inventory level of the store with a hypothetical scenario.

1. RFID, 2. Fine granularity management, 3. Supply chain management, 4. Business process, 5. Inventory management

CONTACT To obtain the whole paper, please contact;
INABA, Tatsuya (tinaba at

MAUI Proejct
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