National Chengchi University (TAIWAN)
About this paper:
Appears in: EDULEARN16 Proceedings
Publication year: 2016
Pages: 7363-7370
ISBN: 978-84-608-8860-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2016.0606
Conference name: 8th International Conference on Education and New Learning Technologies
Dates: 4-6 July, 2016
Location: Barcelona, Spain
This research demonstrates a scenario-based simulator we developed for an electronic component distributor to teach its product managers order decision-making. In the high tech industry, an electronic component distributor plays a buffer role for the entire supply chain. It coordinates order quantity and production schedule with its supply chain partners. While an electronic component distributor may face many uncertain situations from upstream and downstream companies, product managers in the company face tremendous challenges in making ordering decisions. A wrong decision may increase stock holding cost or shortage cost. Thus, the purpose of this education tool is to teach product managers how to determine the order quantities in different scenarios.

The simulator we developed is called “Order Decision Support System (ODSS).” We designed four scenarios to help students understand how ODSS simulator works.

The four scenarios are:
(1) abnormal order quantities,
(2) bad credits or poor financial conditions of the customer,
(3) an urgent order, and
(4) an early order.

Students follow scenario information to input parameters at ODSS, including customer name, stock number, expected customer demand, service level, and customer confidence level. ODSS would then suggest optimal order quantity and expected cost. The system allows students to adjust the values of parameters in three different market situations (representing high, medium, and low market uncertainties respectively) and see how the changes of values affect the results.

The ODSS simulator has three features:
1. The ODSS simulator does not take historical data as input, because historical data cannot predict the current situation precisely, particularly with rapid market changes.
2. The ODSS simulator applies probability models to quantify demand uncertainty. Because input parameters are difficult to measure by specific metric, users’ inputs are based on managers’ subjective evaluation (e.g. market situation, customer status).
3. The ODSS simulator is built upon newsvendor model. Newsvendor model is commonly used for managing goods with short life cycles and fast-changing demand such as fashion apparel, seasonal toys, and high-tech consumer electronics (Silver et. al., 1998). Students who use the ODSS simulator should consider opportunity cost with the aid of the newsvendor model. In other words, ODSS allows users to compare the cost or loss of ordering one additional unit with the cost or loss of not ordering one additional unit (Anderson, et al., 2015).

Past literature has found that using scenario-based simulators as learning tools can enhance student’s motivation. Teaching with simulation is applied in many fields, such as electrical engineering training, pilot training, and patient encounters training. Research indicates that students would ask more relevant questions and pay more attention on the course content. It is also suggested that using simulation may avoid real risk or loss while students are not skillful and familiar with uncertain situations. Thus, we expect that via using ODSS in training, junior product managers can learn quickly how to handle orders and make accurate order decisions in abnormal situations.
e-learning, teaching case, simulator, electronic component industry, product management.