Lead users, suppliers, and experts: the exploration and exploitation trade-off in product development

2014 ◽  
Vol 9 (1) ◽  
pp. 6 ◽  
Author(s):  
Christos Tsinopoulos ◽  
N.A. Zu' ◽  
bi M.F. Al Zu' ◽  
N.A. bi
Keyword(s):  
Product Development ◽  
Exploration And Exploitation ◽  
Trade Off ◽  
Lead Users

The Trade-off Between Efficiency and Learning in Interorganizational Relationships for Product Development

2001 ◽  
Vol 47 (4) ◽  
pp. 493-511 ◽  
Author(s):  
Maurizio Sobrero ◽  
Edward B. Roberts
Keyword(s):  
Product Development ◽  
Interorganizational Relationships ◽  
Trade Off

Trade-Off Between Exploration and Exploitation

2021 ◽  
pp. 8213-8214
Author(s):  
Thomas T Hills
Keyword(s):  
Exploration And Exploitation ◽  
Trade Off

scholarly journals Identifying Lead Users for User-Centered Design (UCD) in Sports Product Development

Proceedings ◽  
2018 ◽  
Vol 2 (6) ◽  
pp. 276
Author(s):  
Robert Leen ◽  
Clara Usma ◽  
Kaja Antlej ◽  
Paul K. Collins
Keyword(s):  
Product Development ◽  
User Centered Design ◽  
Lead Users ◽  
User Centered

Placing the choice between exploration and exploitation in context: a study of geography and new product development

2009 ◽  
Vol 3 (3) ◽  
pp. 261-279 ◽  
Author(s):  
Joseph E. Coombs ◽  
David L. Deeds ◽  
R. Duane Ireland
Keyword(s):  
Product Development ◽  
New Product Development ◽  
New Product ◽  
Exploration And Exploitation

Exploration and exploitation alliances in biotechnology: a system of new product development

2004 ◽  
Vol 25 (3) ◽  
pp. 201-221 ◽  
Author(s):  
Frank T. Rothaermel ◽  
David L. Deeds
Keyword(s):  
Product Development ◽  
New Product Development ◽  
New Product ◽  
Exploration And Exploitation

scholarly journals Balancing exploration and exploitation with information and randomization

2020 ◽  
Author(s):  
Robert C Wilson ◽  
Elizabeth Bonawitz ◽  
Vincent Costa ◽  
Becket Ebitz
Keyword(s):  
Exploration And Exploitation ◽  
Trade Off ◽  
Open Questions ◽  
Computational Perspective ◽  
Computational Properties

Explore-exploit decisions require us to trade off the benefits of exploring unknown options to learn more about them, with exploiting known options, for immediate reward. Such decisions are ubiquitous in nature, but from a computational perspective, they are notoriously hard. There is therefore much interest in how humans and animals make these decisions and recently there has been an explosion of research in this area. Here we provide a biased and incomplete snapshot of this field focusing on the major finding that many organisms use two distinct strategies to solve the explore-exploit dilemma: a bias for information (`directed exploration') and the randomization of choice (`random exploration'). We review evidence for the existence of these strategies, their computational properties, their neural implementations, as well as how directed and random exploration vary over the lifespan. We conclude by highlighting open questions in this field that are ripe to both explore and exploit.

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