Name
Abstract | ||
|---|---|---|
New product forecasting is a challenging area of research, because unlike other forecasting disciplines, where the presence of historical data makes it possible to apply several analysis tools and techniques, new products suffer from scarcity of data to perform conventional analysis. Usually, the data analysis on analogical products is the only solution left and is in practice for so many decades. However, to find a reasonable analogical counterpart for a new product is challenging. In this paper, we propose a methodology based on Fuzzy Analytic Hierarchy process (henceforth Fuzzy AHP) and Technique for Order Preference by Similarity to Ideal Solution (henceforth TOPSIS) to identify an analogical product for a given new product or an innovation. We further demonstrate the applicability of the method by taking a real life example of four consumer durable products in India. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.3233/IFS-141483 | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS |
Keywords | Field | DocType |
Analogy,FAHP,TOPSIS,new product,forecasting | Analysis tools,Scarcity,Ideal solution,Artificial intelligence,TOPSIS,Analogy,Fuzzy ahp,Fuzzy decision,Machine learning,Mathematics,New product development | Journal |
Volume | Issue | ISSN |
28 | 5 | 1064-1246 |
Citations | PageRank | References |
2 | 0.37 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Prateek Pandey | 1 | 2 | 1.05 |
| Shishir Kumar | 2 | 78 | 17.06 |
| Sandeep Shrivastava | 3 | 2 | 0.37 |