Continuity, Change & the Product Development Process

MC06.1 Impact of Information Sharing on the Distortion of Demand

• Shanling Li; McGill University, Fac. of Management, 1001 Sherbrooke St. W, Montreal, Quebec, H3A 1G5 , Canada; li@management.mcgill.ca
• Afshin Afshari; McGill University, Fac. of Management, 1001 Sherbrooke St. W, Montreal, Quebec, H3A 1G5 , Canada;

We examine the impact of information sharing in a supply chain model. We propose a sophisticated forecasting technique that updates the demand information over the product life cycles. The demand information may be shared among retailer, manufacturer and supplier. The resulted performance is compared with no information sharing.

MC06.2 Drivers of New Product Development Success: Multivariate Results from PDMA's Best Practices Research

• Abbie Griffin; University of Illinois, 350 Commerce West, Champaign, IL 61820; abbieg@uiuc.edu

We present several multivariate analyses of success drivers in NPD using an extensive data set from 383 US firms. We also present a multi-stage model of NPD factors, analyzed using the same data set. The model and data cover NPD processes, organizations, tools and outcomes.

MC06.3 Discontinuous Change, Disruptive Technologies & the Challenge of Developing New Products

• Susan Walsh Sanderson; National Science Foundation, Innovation & Org. Change Prog., 4201 Wilson Blvd., Arlington, VA 22230; ssanders@nsf.gov

This research looks at the challenge of developing new products in the context of discontinuous change and disruptive new technologies. Studies of firms in the digital photography market help elucidate the elements that lead to success or failure in a dynamic industry.

MC06.4 Setup Strategies in Flexible Manufacturing Environments

• Valerie Tardif; University of Texas, Graduate Program in OR/IE, Dept. of Mech. Eng., Austin, TX 78712-1063; vtardif@mail.utexas.edu
• Wei-Liang Lin; University of Texas, Graduate Program in OR/IE, Dept. of mech. Eng., Austin, TX 78712-1063; wll@csr.utexas.edu

We consider different setup strategies in a flexible PCB assembly line experiencing uncertainty in demand. This is especially important at the beginning of a new product life cycle, when demand volume is low or medium and quite difficult to predict. We present computational results and insights obtained.